Articles de revues : « AML, Biomarker, Prognose »

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Núñez, Kelley G., Tyler Sandow, Daniel Fort, Jai Patel, Mina Hibino, Ian Carmody, Ari J. Cohen et Paul Thevenot. « Baseline Alpha-Fetoprotein, Alpha-Fetoprotein-L3, and Des-Gamma-Carboxy Prothrombin Biomarker Status in Bridge to Liver Transplant Outcomes for Hepatocellular Carcinoma ». Cancers 13, n^o 19 (23 septembre 2021) : 4765. http://dx.doi.org/10.3390/cancers13194765.

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The biomarkers α-fetoprotein (AFP), Lens culinaris agglutinin-reactive AFP fraction (AFP-L3), and des-γ-carboxy prothrombin (DCP) have emerging implications in hepatocellular carcinoma (HCC) surveillance, overall prognosis, and post-surgical recurrence risk. This retrospective study investigated treatment and bridge to liver transplant (LT) prognosis associated with AFP, AFP-L3%, and DCP biomarker profiles prior to liver-directed therapy (LDT). In a 140-patient cohort, each biomarker was associated with HCC progression risk using the established thresholds of AFP > 20 ng/mL, AFP-L3 > 15%, and DCP > 7.5 ng/mL. Over 60% of the cohort expressed at least one biomarker at baseline. Although most biomarker-positive patients expressed the clinical standard AFP (57/87), only 32% were positive for AFP alone. Biomarker accumulation increased HCC progression risk but was not associated with demographic factors or preserved liver function. Biomarker triple negative patients had smaller index HCC (p = 0.003), decreased multifocal burden (p = 0.010), and a higher objective response rate (ORR, 62% compared to 46%, p = 0.011). Expressing all three biomarkers at baseline was associated with dismal first-line ORR (12%) with a median time to progression (TTP) of only 181 days post-LDT. Patients with triple negative status for the HCC biomarkers AFP, AFP-L3%, and DCP have the highest first-line ORR with < 5% HCC progression 1-year post-LDT. Biomarker profiling can establish baseline prognosis for identifying optimal bridge to LT and downstaging to LT candidates with triple negative biomarker status and providing an ideal post-LDT target as a compliment to radiographic response.

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Zhu, Rui, Xin Yang, Wenna Guo, Xin-Jian Xu et Liucun Zhu. « An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma ». PeerJ 7 (22 octobre 2019) : e7836. http://dx.doi.org/10.7717/peerj.7836.

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Background Bladder cancer is one of the most common cancers, and its histopathological type is mainly bladder urothelial carcinoma, accounting for about 90%. The prognostic biomarkers of bladder cancer are classified into clinical features biomarkers and molecular biomarkers. Nevertheless, due to the existence of individual specificity, patients with similar pathological characteristics still have great differences in the risk of disease recurrence. Therefore, it is often inaccurate to predict the survival status of patients based on clinical characteristic biomarkers, and a prognostic molecular biomarker that can grade the risk of bladder cancer patients is needed. Methods A total of three bladder urothelial carcinoma datasets were used in this study from the Cancer Genome Atlas database and Gene Expression Omnibus database. In order to avoid overfitting, all samples were randomly divided into one training set and three validation sets, which were used to construct and test the prognostic biomarker model of bladder urothelial carcinoma. Univariate and multivariate Cox regression were used to screen candidate mRNAs and construct prognostic biomarkers model. Kaplan–Meier survival analysis and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model. Results A prognostic biomarker model of bladder urothelial carcinoma combining with eight mRNA was constructed. Kaplan–Meier analyses indicated that a significant difference in the survival time of patients between the high-risk and the low-risk group. The area under the ROC curve were 0.632 (95% confidence interval (CI) [0.541–0.723]), 0.693 (95% CI [0.601–0.784]) and 0.686 (95% CI [0.540–0.831]) when the model was used to predict the patient’s survival time in three validation datasets. The model showed high accuracy and applicability.

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Liss, Franziska, Miriam Frech, Ying Wang, Gavin Giel, Sabrina Fischer, Clara Simon, Lisa Marie Weber et al. « IRF8 Is an AML-Specific Susceptibility Factor That Regulates Signaling Pathways and Proliferation of AML Cells ». Cancers 13, n^o 4 (12 février 2021) : 764. http://dx.doi.org/10.3390/cancers13040764.

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Personalized treatment of acute myeloid leukemia (AML) that target individual aberrations strongly improved the survival of AML patients. However, AML is still one of the most lethal cancer diseases of the 21st century, demonstrating the need to find novel drug targets and to explore alternative treatment strategies. Upon investigation of public perturbation data, we identified the transcription factor IRF8 as a novel AML-specific susceptibility gene in humans. IRF8 is upregulated in a subset of AML cells and its deletion leads to impaired proliferation in those cells. Consistently, high IRF8 expression is associated with poorer patients’ prognoses. Combining gene expression changes upon IRF8 deletion and the genome-wide localization of IRF8 in the AML cell line MV4-11, we demonstrate that IRF8 directly regulates key signaling molecules, such as the kinases SRC and FAK, the transcription factors RUNX1 and IRF5, and the cell cycle regulator Cyclin D1. IRF8 loss impairs AML-driving signaling pathways, including the WNT, Chemokine, and VEGF signaling pathways. Additionally, many members of the focal adhesion pathway showed reduced expression, providing a putative link between high IRF8 expression and poor prognosis. Thus, this study suggests that IRF8 could serve as a biomarker and potential molecular target in a subset of human AMLs.

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Bartels, Claudia, Anna Kögel, Mark Schweda, Jens Wiltfang, Michael Pentzek, Silke Schicktanz et Anja Schneider. « Use of Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease Risk in Mild Cognitive Impairment and Subjective Cognitive Decline in Routine Clinical Care in Germany ». Journal of Alzheimer's Disease 78, n^o 3 (24 novembre 2020) : 1137–48. http://dx.doi.org/10.3233/jad-200794.

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Background: The National Institute of Aging and Alzheimer’s Association’s diagnostic recommendations for preclinical Alzheimer’s disease (AD) and mild cognitive impairment (MCI) define AD by pathological processes which can be detected by biomarkers. These criteria were established as part of a research framework intended for research purposes but progressively enter the clinical practice. Objective: We investigated the availability, frequency of use, interpretation, and therapeutic implications of biomarkers for the etiologic diagnosis and prognosis in MCI and subjective cognitive decline (SCD) in routine clinical care. Methods: We conducted a cross-sectional questionnaire survey among 215 expert dementia centers (hospitals and memory clinics) in Germany. Results: From the 98 centers (45.6% of contacted centers) included, two-thirds reported use of the cerebrospinal fluid (CSF) biomarkers Aβ42, tau, and phospho-tau in the diagnostic workup of MCI and one third in SCD. CSF biomarker analysis was more often employed by neurological (MCI 84%; SCD 42%) compared to psychiatric institutions (MCI 61%; SCD 33%; p≤0.001). Although dementia experts disagreed on the risk of progression associated with different CSF biomarker constellations, CSF biomarker results guided therapeutic decisions: ∼40% of responders reported to initiate cholinesterase inhibitor therapy in MCI and 18% in SCD (p = 0.006), given that all CSF biomarkers were in the pathological range. Conclusion: Considering the vast heterogeneity among dementia expert centers in use of CSF biomarker analysis, interpretation of results, and therapeutic consequences, a standardization of biomarker-based diagnosis practice in pre-dementia stages is needed.

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Odubanjo, Anthony A., Rohini Kalisetti, Robert Adrah, Adeniyi Ajenifuja, Blessey Joseph et Mohammed Zaman. « Severe Myopericarditis in Diabetic Ketoacidosis—All Troponin are Not Myocardial Infarction ». Clinical Medicine Insights : Case Reports 11 (1 janvier 2018) : 117954761876335. http://dx.doi.org/10.1177/1179547618763356.

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Uncontrolled diabetes and acute coronary syndrome share a complex dynamic that results in significant ambiguity when interpreting biomarker elevations in this setting. This is concerning because myocardial infarction has been shown to be the most common cause of death in the first 24 hours of admission for uncontrolled diabetes. Literature shows that elevation in cardiac biomarkers in patients with uncontrolled diabetes could be from viral myopericarditis, although a clear clinical significance is still lacking.1 It is, however, clear that elevation in cardiac biomarkers portends a poor long-term prognosis in patients with uncontrolled diabetes mellitus. We present a rare case of myopericarditis in a middle-aged patient with uncontrolled diabetes. The patient had elevated troponin I level reaching a peak of 7.3 ng/mL with associated ST elevations on electrocardiography. Coronary angiogram was subsequently done revealing clean coronaries. To our knowledge, this is the first description of myopericarditis in uncontrolled diabetes without a known cause.

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Yang, Mingjun, Boni Song, Juxiang Liu, Zhitong Bing, Yonggang Wang et Linmiao Yu. « Gene signature for prognosis in comparison of pancreatic cancer patients with diabetes and non-diabetes ». PeerJ 8 (11 novembre 2020) : e10297. http://dx.doi.org/10.7717/peerj.10297.

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Background Pancreatic cancer (PC) has much weaker prognosis, which can be divided into diabetes and non-diabetes. PC patients with diabetes mellitus will have more opportunities for physical examination due to diabetes, while pancreatic cancer patients without diabetes tend to have higher risk. Identification of prognostic markers for diabetic and non-diabetic pancreatic cancer can improve the prognosis of patients with both types of pancreatic cancer. Methods Both types of PC patients perform differently at the clinical and molecular levels. The Cancer Genome Atlas (TCGA) is employed in this study. The gene expression of the PC with diabetes and non-diabetes is used for predicting their prognosis by LASSO (Least Absolute Shrinkage and Selection Operator) Cox regression. Furthermore, the results are validated by exchanging gene biomarker with each other and verified by the independent Gene Expression Omnibus (GEO) and the International Cancer Genome Consortium (ICGC). The prognostic index (PI) is generated by a combination of genetic biomarkers that are used to rank the patient’s risk ratio. Survival analysis is applied to test significant difference between high-risk group and low-risk group. Results An integrated gene prognostic biomarker consisted by 14 low-risk genes and six high-risk genes in PC with non-diabetes. Meanwhile, and another integrated gene prognostic biomarker consisted by five low-risk genes and three high-risk genes in PC with diabetes. Therefore, the prognostic value of gene biomarker in PC with non-diabetes and diabetes are all greater than clinical traits (HR = 1.102, P-value < 0.0001; HR = 1.212, P-value < 0.0001). Gene signature in PC with non-diabetes was validated in two independent datasets. Conclusions The conclusion of this study indicated that the prognostic value of genetic biomarkers in PCs with non-diabetes and diabetes. The gene signature was validated in two independent databases. Therefore, this study is expected to provide a novel gene biomarker for predicting prognosis of PC with non-diabetes and diabetes and improving clinical decision.

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Christensen, Ib Jarle, Gunilla Høyer-Hansen, Tine Thurison, Barry Dowell, Julia S. Johansen, Rikke Henriksen, Kristoffer Staal Rohrberg, Nils Brunner et Hans J. Nielsen. « The prognostic value of seven soluble proteins measured in plasma or serum from patients with colorectal cancer in TNM stages I-III. » Journal of Clinical Oncology 30, n^o 30_suppl (20 octobre 2012) : 35. http://dx.doi.org/10.1200/jco.2012.30.30_suppl.35.

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35 Background: In colorectal cancer (CRC) several independent blood-borne biomarkers have been proposed as prognostic and/or predictive markers. However only CEA is at present recommended as a serological CRC biomarker. We have identified 6 other biomarkers and the aim of this study is to see if a combination of markers improves the prognostic and/or predictive value. Methods: Two-hundred and twenty-eight patients with CRC have been included in this study, all with TNM stages I-III. Overall survival (OS) was chosen as the primary endpoint with 93 events and the minimum follow-up was 47 months. Seven biomarkers measured in plasma or serum were analysed: CEA, TIMP-1, the 3 soluble uPAR forms suPAR(I-III), suPAR(I-III)+(II-III) and uPAR(I), PAI-1 and YKL-40. Multivariable analyses of OS were done using regression analysis and results presented by 3 and 5 year OS rates with area under the receiver operating characteristic curve (AUC). All biomarker levels were analysed on the log scale (base 2). Results: High levels of each of the included biomarker were significantly associated in a multivariable analysis (adjusted for age, gender, TNM stage, tumor localization, adjuvant chemotherapy,interaction between adjuvant therapy and biomarker) to poor prognosis in patients not receiving adjuvant chemotherapy. The results are shown for those patients (see Table). The uPAR forms were the only biomarkers significantly associated to OS in patients receiving adjuvant chemotherapy. Combining the markers resulted in an enhanced prediction of 3 and 5 year OS. For TNM stage II patients not receiving adjuvant therapy, the AUC was 0.765 for 3 year OS and 0.745 for 5 year OS. The corresponding AUC’s for TNM stage III were 0.859 and 0.861. Conclusions: The presented combination of blood biomarkers are shown to predict OS with higher precision than any single marker for patients not receiving adjuvant chemotherapy and may provide useful information for use in the management of patients with CRC. [Table: see text]

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Melichar, Bohuslav, Denisa Vitásková, Marie Bartoušková, Lenka Javorská, Lenka Kujovská Krčmová, Eliška Pešková, Radomír Hyšpler, Dagmar Solichová, Klára Hrůzová et Hana Študentová. « Comparison of performance of composite biomarkers of inflammatory response in determining the prognosis of breast cancer patients ». Pteridines 28, n^o 3-4 (20 décembre 2017) : 213–20. http://dx.doi.org/10.1515/pterid-2017-0005.

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AbstractIn the present study, we determined complex indices of inflammatory activity and compared the performance of these indices as prognostic biomarkers in a cohort of breast cancer patients. All proposed composite biomarkers could be evaluated in 418 out of 474 patients in the cohort with complete data on peripheral blood cell count, urinary neopterin, albumin and C-reactive protein. Neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, systemic inflammatory index, Glasgow prognostic index, modified Glasgow prognostic index, prognostic nutritional index and C-reactive protein/albumin ratio were calculated and further complex indices were proposed. Although a number of the investigated indices were significantly associated with survival in the univariate analysis, only age and stage, but none of the laboratory biomarkers or composite biomarkers, were significant predictors of survival in the whole group in the multivariate analysis. In patients evaluated before the start of the treatment, age, stage and urinary neopterin were significant predictors of survival. These results underscore the importance of neopterin as a prognostic biomarker in breast cancer.

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Crabb, S. J., C. D. Bajdik, C. H. Speers, D. G. Huntsman et K. A. Gelmon. « Can we identify a group of breast cancer patients with a good prognosis despite four or more positive (4+) axillary nodes using a tissue microarray (TMA) ? » Journal of Clinical Oncology 25, n^o 18_suppl (20 juin 2007) : 10582. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.10582.

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10582 Background: Although breast cancer with 4+ axillary lymph nodes generally carries a poor prognosis, we hypothesized that a good prognostic subgroup of such patients would be identifiable by immunohistochemical (IHC) biomarkers. Methods: Patients with primary breast cancer with 4+ axillary nodes and no metastatic disease at diagnosis were identified from a large clinically annotated TMA of formalin-fixed paraffin-embedded archival breast cancers and analyzed for eight IHC based biomarkers: estrogen receptor, HER2, carbonic anhydrase IX, EGFR, CK 5/6, progesterone receptor, p53 and Ki67. Expression of each biomarker was scored 0 or 1 to indicate good or bad prognosis based on univariate analysis of relapse free survival (RFS). Patients were banded as having a total score of 0 (i.e. each biomarker predicted a good outcome), 1–4 or 5–8. Kaplan Meier and Cox regression analysis of RFS outcomes was performed. 10 year RFS for each band was compared to the mean of predicted outcomes based on the prognostic tool Adjuvant! ( www.adjuvantonline.com ). Results: 313 eligible patients were identified and complete data were available for 228. The subset of 228 was similar to the larger group of 313 with respect to RFS and conventional prognostic factors. 10 year RFS for the 228 patients was 39.5% (standard error, SE 3.4%). The subgroup of 37 (16%) scoring zero for all 8 biomarkers had a mean 10 year RFS of 77.6% (SE 7.0). Mean 10 year RFS for the bands scoring 1–4 (154 patients, 68%) and 5–8 (37 patients, 16%) were 34.9% (SE 4.1) and 19.0% (SE 6.9) respectively. Mean 10 year RFS predictions by Adjuvant! were 35.9% (SE 2.6), 34.5% (SE 1.2) and 34.3% (SE 2.3) respectively. In multivariate analysis with conventional prognostic factors, the banded biomarker score retained statistical significance for predicting RFS (p=0.0007) along with estrogen receptor status (p=0.03) and tumour size (p=0.01). Conclusions: This TMA biomarker panel identified a breast cancer subgroup with good prognosis despite extensive axillary node involvement. Long term outcome was markedly better than that predicted by conventional prognostic factors. If validated, treatment decisions and clinical trial stratification might be modified using this new score. No significant financial relationships to disclose.

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Rammos, Aidonis, Aris Bechlioulis, Petros Kalogeras, Evanthia E. Tripoliti, Yorgos Goletsis, Anna Kalivi, Effrosyni Blathra et al. « Salivary Biomarkers for Diagnosis and Therapy Monitoring in Patients with Heart Failure. A Systematic Review ». Diagnostics 11, n^o 5 (2 mai 2021) : 824. http://dx.doi.org/10.3390/diagnostics11050824.

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The aim of this study was to perform a systematic review on the potential value of saliva biomarkers in the diagnosis, management and prognosis of heart failure (HF). The correlation between saliva and plasma values of these biomarkers was also studied. PubMed was searched to collect relevant literature, i.e., case-control, cross-sectional studies that either compared the values of salivary biomarkers among healthy subjects and HF patients, or investigated their role in risk stratification and prognosis in HF patients. No randomized control trials were included. The search ended on 31st of December 2020. A total of 15 studies met the inclusion criteria. 18 salivary biomarkers were analyzed and the levels of all biomarkers studied were found to be higher in HF patients compared to controls, except for amylase, sodium, and chloride that had smaller saliva concentrations in HF patients. Natriuretic peptides are the most commonly used plasma biomarkers in the management of HF. Their saliva levels show promising results, although the correlation of saliva to plasma values is weakened in higher plasma values. In most of the publications, differences in biomarker levels between HF patients and controls were found to be statistically significant. Due to the small number of patients included, larger studies need to be conducted in order to facilitate the use of saliva biomarkers in clinical practice.

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Yang, Xiangchou, Rongxin Yao et Hong Wang. « Update of ALDH as a Potential Biomarker and Therapeutic Target for AML ». BioMed Research International 2018 (2018) : 1–5. http://dx.doi.org/10.1155/2018/9192104.

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Studies employing mouse transplantation have illustrated the role of aldehyde dehydrogenase (ALDH) defining hematopoietic stem cells (HSCs) and leukemia stem cells (LSCs). Besides being a molecular marker, ALDH mediates drug resistance in AML, which induces poor prognosis of the patients. In AML patients, either CD34+ALDHbrpopulation or CD34+CD38−ALDHintpopulation was found to denote LSCs and minimal residual disease (MRD). A bunch of reagents targeting ALDH directly or indirectly have been evaluated. ATRA, disulfiram, and dimethyl ampal thiolester (DIMATE) are all shown to be potential candidates to open new perspective for AML treatment. However, inconsistent results have been shown for markers of LSCs, which makes it even more difficult to differentiate LSCs and HSCs. In this review, we elevated the role of ALDH to be a potential marker to define and distinguish HSCs and LSCs and its importance in prognosis and target therapy in AML patients. In addition to immunophenotypical markers, ALDH is also functionally active in defining and distinguishing HSCs and LSCs and offers intracellular protections against cytotoxic drugs. Targeting ALDH may be a potential strategy to improve AML treatment. Additional studies concerning specific targeting ALDH and mechanisms of its roles in LSCs are warranted.

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Chen, Yuxiao, Rui Zhu, Min Chen, Wenna Guo, Xin Yang, Xin-Jian Xu et Liucun Zhu. « Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma ». Journal of Oncology 2020 (15 mai 2020) : 1–11. http://dx.doi.org/10.1155/2020/8106212.

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Soft tissue sarcomas (STS) are a highly aggressive and heterogeneous group of malignant mesenchymal tumors. The prognosis of patients with advanced or metastatic STS remains poor, and the main therapy of STS patients combines primary surgery, radiotherapy, and chemotherapy. Aberrant DNA methylation shows close association with the pathogenesis and tumor progression. Therefore, DNA methylation biomarkers might have the potential in accurately predicting the survival of STS patients. In order to identify a prognostic biomarker based on DNA methylation sites, a comprehensive analysis of the DNA methylation profile of STS patients in the Cancer Genome Atlas (TCGA) database was performed. All samples were randomly divided into training and testing datasets. Cox proportional hazards regression analysis was performed to identify a prognostic biomarker that contains three DNA methylation sites. The Kaplan–Meier analysis demonstrated that the 3-DNA methylation biomarker discriminated patients into high-risk and low-risk groups, both in the training and in the testing datasets, and the area under the receiver operating characteristic curve values (AUCs) were 0.844 (P<0.001, 95% CI: 0.740–0.948) and 0.710 (P=0.002, 95% CI: 0.595–0.823), respectively. Besides, this biomarker presented superior prognostic performance in STS patients with different age, sex, tissue of origin, therapy, and histologic subtypes. Compared with other prognostic biomarkers, this biomarker tended to be a more precise prognostic factor in STS patients. Moreover, methylation sites in this biomarker might provide a new way for clinicians to make decisions regarding the intervention and assess the effectiveness of an individual therapeutic strategy.

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Lo Presti, Caroline, Florence Fauvelle, Marie-Christine Jacob, Julie Mondet et Pascal Mossuz. « The metabolic reprogramming in acute myeloid leukemia patients depends on their genotype and is a prognostic marker ». Blood Advances 5, n^o 1 (6 janvier 2021) : 156–66. http://dx.doi.org/10.1182/bloodadvances.2020002981.

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Abstract Leukemic cells display some alterations in metabolic pathways, which play a role in leukemogenesis and in patients’ prognosis. To evaluate the characteristics and the impact of this metabolic reprogramming, we explore the bone marrow samples from 54 de novo acute myeloid leukemia (AML) patients, using an untargeted metabolomics approach based on proton high-resolution magic angle spinning-nuclear magnetic resonance. The spectra obtained were subjected to multivariate statistical analysis to find specific metabolome alterations and biomarkers correlated to clinical features. We found that patients display a large diversity of metabolic profiles, according to the different AML cytologic subtypes and molecular statuses. The link between metabolism and molecular status was particularly strong for the oncometabolite 2-hydroxyglutarate (2-HG), whose intracellular production is directly linked to the presence of isocitrate dehydrogenase mutations. Moreover, patients’ prognosis was strongly impacted by several metabolites, such as 2-HG that appeared as a good prognostic biomarker in our cohort. Conversely, deregulations in phospholipid metabolism had a negative impact on prognosis through 2 main metabolites (phosphocholine and phosphoethanolamine), which could be potential aggressiveness biomarkers. Finally, we highlighted an overexpression of glutathione and alanine in chemoresistant patients. Overall, our results demonstrate that different metabolic pathways could be activated in leukemic cells according to their phenotype and maturation levels. This confirms that metabolic reprogramming strongly influences prognosis of patients and underscores a particular role of certain metabolites and associated pathways in AML prognosis, suggesting common mechanisms developed by leukemic cells to maintain their aggressiveness even after well-conducted induction chemotherapy.

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Lo Presti, Caroline, Florence Fauvelle, Marie-Christine Jacob, Julie Mondet et Pascal Mossuz. « The metabolic reprogramming in acute myeloid leukemia patients depends on their genotype and is a prognostic marker ». Blood Advances 5, n^o 1 (6 janvier 2021) : 156–66. http://dx.doi.org/10.1182/bloodadvances.2020002981.

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Abstract Leukemic cells display some alterations in metabolic pathways, which play a role in leukemogenesis and in patients’ prognosis. To evaluate the characteristics and the impact of this metabolic reprogramming, we explore the bone marrow samples from 54 de novo acute myeloid leukemia (AML) patients, using an untargeted metabolomics approach based on proton high-resolution magic angle spinning-nuclear magnetic resonance. The spectra obtained were subjected to multivariate statistical analysis to find specific metabolome alterations and biomarkers correlated to clinical features. We found that patients display a large diversity of metabolic profiles, according to the different AML cytologic subtypes and molecular statuses. The link between metabolism and molecular status was particularly strong for the oncometabolite 2-hydroxyglutarate (2-HG), whose intracellular production is directly linked to the presence of isocitrate dehydrogenase mutations. Moreover, patients’ prognosis was strongly impacted by several metabolites, such as 2-HG that appeared as a good prognostic biomarker in our cohort. Conversely, deregulations in phospholipid metabolism had a negative impact on prognosis through 2 main metabolites (phosphocholine and phosphoethanolamine), which could be potential aggressiveness biomarkers. Finally, we highlighted an overexpression of glutathione and alanine in chemoresistant patients. Overall, our results demonstrate that different metabolic pathways could be activated in leukemic cells according to their phenotype and maturation levels. This confirms that metabolic reprogramming strongly influences prognosis of patients and underscores a particular role of certain metabolites and associated pathways in AML prognosis, suggesting common mechanisms developed by leukemic cells to maintain their aggressiveness even after well-conducted induction chemotherapy.

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Shivarov, Velizar, Ralitza Gueorguieva, Angel Stoimenov et Ramon Tiu. « DNMT3A mutation is a poor prognosis biomarker in AML : Results of a meta-analysis of 4500 AML patients ». Leukemia Research 37, n^o 11 (novembre 2013) : 1445–50. http://dx.doi.org/10.1016/j.leukres.2013.07.032.

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Nikas, Jason B., Walter C. Low et Paul A. Burgio. « Prognosis of Treatment Response (Pathological Complete Response) in Breast Cancer ». Biomarker Insights 7 (janvier 2012) : BMI.S9387. http://dx.doi.org/10.4137/bmi.s9387.

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Pertaining to the female population in the USA, breast cancer is the leading cancer in terms of annual incidence rate and, in terms of mortality, the second most lethal cancer. There are currently no biomarkers available that can predict which breast cancer patients will respond to chemotherapy with both sensitivity and specificity > 80%, as mandated by the latest FDA requirements. In this study, we have developed a prognostic biomarker model (complex mathematical function) that–-based on global gene expression analysis of tumor tissue collected during biopsy and prior to the commencement of chemotherapy–-can identify with a high accuracy those patients with breast cancer (clinical stages I–III) who will respond to the paclitaxel-fluorouracil-doxorubicin-cyclophosphamide chemotherapy and will experience pathological complete response (Responders), as well as those breast cancer patients (clinical stages I–III) who will not do so (Non-Responders). Most importantly, both the application and the accuracy of our breast cancer prognostic biomarker model are independent of the status of the hormone receptors ER, PR, and HER2, as well as of the ethnicity and age of the subjects. We developed our prognostic biomarker model with 50 subjects [10 responders (R) and 40 non-responders (NR)], and we validated it with 43 unknown (new and different) subjects [10 responders (R) and 33 non-responders (NR)]. All 93 subjects were recruited at five different clinical centers around the world. The overall sensitivity and specificity of our prognostic biomarker model were 90.0% and 91.8%, respectively. The nine most significant genes identified, which comprise the input variables to the mathematical function, are involved in regulation of transcription; cell proliferation, invasion, and migration; oncogenesis; suppression of immune response; and drug resistance and cancer recurrence.

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Kujawski, Michelle R., Margaret Prechel, He Zhu, Jeanine Walenga, Debra Hoppensteadt, Josephine Cunanan, Cafer Adiguzel et Jawed Fareed. « A Unique Biomarker Is Associated with the Prevalence of Functional Heparin Induced Thrombocytopenia (HIT) Associated Antibodies : Results from Proteomic (ProteinChip Array) Profiling of ELISA Positive HIT Plasma Samples. » Blood 110, n^o 11 (16 novembre 2007) : 3205. http://dx.doi.org/10.1182/blood.v110.11.3205.3205.

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Abstract Heparin induced thrombocytopenia (HIT) represents a complex immunopathologic syndrome resulting in the activation of coagulation, inflammatory and cellular processes, which contribute to the overall pathogenesis. Protease mediated transformation of endogenous proteins resulting in the generation of certain mediators and specific cleavage products may be used to understand the pathogenesis of this syndrome. It was hypothesized that unique biomarkers may be generated in patients who develop HIT antibodies upon exposure to heparins. The identification of unique biomarkers and their prevalence in heparin exposed patients may provide an additional parameter in the prognosis of this syndrome. To profile the proteomic biomarkers in serum, specimens were selected from archived sera that had been referred to Loyola University Medical Center for the quantitation of HIT antibodies and 14C Serotonin Release Assay (SRA). All of these specimens were positive in the GTI PF4 Enhanced ELISA for the presence of anti-heparin platelet factor 4 antibodies with a broad range of antibody titers absorbance range (0.4 – 2.5). Eleven of these specimens were positive in the SRA. All of these samples were proteomic profiled utilizing a ProteinChip Array method using a Gold (AU) Chip in the molecular weight range of 0 – 150 kDa. The normal sera samples (n = 40) were also analyzed simultaneously in a crossover fashion along with the patients’ specimens. Surface enhanced laser desorption/ionization (SELDI) technique utilizing Ciphergen PBS II (Fremont, CA) was used for mass profiling. Proteomic profiling is widely used to identify unique biomarkers in various hemotologic disorders. Although electrophoretic methods identify biomarkers at molecular weights ≥ 25 kDa, the SELDI technique provides a complete spectrum in the lower molecular weight range. The ProteinChip Software for mass profiling was used to analyze the data. Proteins such as albumin were used as control proteins throughout the study. Of the 54 HIT samples profiled, 36 showed a unique biomarker peak at 11.9 kDa (67%) whereas none of the normal sera (n = 40) showed this peak. All of the SRA positive samples also showed the 11.9 kDa biomarker peak. Several biomarker peaks in the range of 5 – 10 kDa were present in the HIT positive sera suggesting increased proteolysis. While no other unique biomarkers were obvious in the HIT samples, the relative proportion of some of the biomarker peaks in the range of 15 – 20 kDa were differentiable in the HIT group. These studies demonstrate that HIT patients’ sera exhibit a unique biomarker profile, which is distinguishable from normal serum samples. Combined usage of the ProteinChip Array analysis of the HIT patients’ sera with other diagnostic methods may further enhance the diagnostic process for this syndrome. Additional molecular characterization of these biomarkers will also help in the understanding of the pathogenesis of HIT with particular reference to the protease activation processes.

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Vlasakova, Katerina, Sean P. Troth, Frank D. Sistare et Warren E. Glaab. « Evaluation of 10 Urinary Biomarkers for Renal Safety With 5 Nephrotoxicants in Nonhuman Primates ». Toxicologic Pathology 48, n^o 5 (juillet 2020) : 633–48. http://dx.doi.org/10.1177/0192623320932159.

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To date, there has been very little published data evaluating the performance of novel urinary kidney biomarkers in nonhuman primates (NHPs). To assess the biomarker performance and characterize the corresponding histomorphologic patterns of tubular renal injury in the NHP, several studies were conducted using mechanistically diverse nephrotoxicants including cefpirome, cisplatin, naproxen, cyclosporine, and a combination of gentamicin with everninomicin. An evaluation of 10 urinary biomarkers (albumin, clusterin, cystatin C, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin, liver-type fatty acid-binding protein, N-acetyl-β-D-glucosaminidase, osteopontin, retinol binding protein 4 and total protein) was performed on urine collected from these studies. Each of these 5 treatments resulted in kidney proximal tubule injury of various severities. Histomorphologic features observed following treatment were generally consistent with analogous drug-induced changes in humans described in the literature. Most of the analyzed biomarkers were able to detect the injury earlier and with greater sensitivity than blood urea nitrogen and serum creatinine. Across all studies, KIM-1 and clusterin showed the highest overall performance. Differences in the patterns of biomarker responsiveness were noted among certain studies that may be informing tubular injury severity and recovery potential, underlying histopathologic processes, and prognosis. These findings demonstrate the utility of urinary kidney translational safety biomarkers in NHPs and provide additional supporting evidence for translating these biomarkers for use in clinical trial settings to further ensure patient safety.

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Santos, Ana Rita, Pedro Freitas, Jorge Ferreira, Afonso Oliveira, Mariana Gonçalves, Daniel Faria, João Bicho Augusto et al. « Risk stratification in normotensive acute pulmonary embolism patients : focus on the intermediate–high risk subgroup ». European Heart Journal : Acute Cardiovascular Care 9, n^o 4 (24 avril 2019) : 279–85. http://dx.doi.org/10.1177/2048872619846506.

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Background: Patients with acute pulmonary embolism are at intermediate–high risk in the presence of imaging signs of right ventricular dysfunction plus one or more elevated cardiac biomarker. We hypothesised that intermediate–high risk patients with two elevated cardiac biomarkers and imaging signs of right ventricular dysfunction have a worse prognosis than those with one cardiac biomarker and imaging signs of right ventricular dysfunction. Methods: We analysed the cumulative presence of cardiac biomarkers and imaging signs of right ventricular dysfunction in 525 patients with intermediate risk pulmonary embolism (intermediate-high risk = 237) presenting at the emergency department in two centres. Studied endpoints were composites of all-cause mortality and/or rescue thrombolysis at 30 days (primary endpoint; n=58) and pulmonary embolism-related mortality and/or rescue thrombolysis at 30 days (secondary endpoint; n=40). Results: Patients who experienced the primary endpoint showed a higher proportion of elevated troponin (47% vs. 76%, P<0.001), elevated N-terminal pro-brain natriuretic peptide (67% vs. 93%, P<0.001) and imaging signs of right ventricular dysfunction (47% vs. 80%, P<0.001). Multivariate analysis revealed N-terminal pro-brain natriuretic peptide (hazard ratio (HR) 3.6, 95% confidence interval (CI) 1.3–10.3; P=0.015) and imaging signs of right ventricular dysfunction (HR 2.8, 95% CI 1.5–5.2; P=0.001) as independent predictors of events. In the intermediate–high risk group, patients with two cardiac biomarkers performed worse than those with one cardiac biomarker (HR 3.3, 95% CI 1.8–6.2; P=0.003). Conclusions: Risk stratification in normotensive pulmonary embolism should consider the cumulative presence of cardiac biomarkers and imaging signs of right ventricular dysfunction, especially in the intermediate–high risk subgroup.

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Duda, Dan G., Simona O. Dima, Dana Cucu, Andrei Sorop, Sebastian Klein, Marek Ancukiewicz, Shuji Kitahara et al. « Potential Circulating Biomarkers of Recurrence after Hepatic Resection or Liver Transplantation in Hepatocellular Carcinoma Patients ». Cancers 12, n^o 5 (18 mai 2020) : 1275. http://dx.doi.org/10.3390/cancers12051275.

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Background: Improving surgical outcomes in hepatocellular carcinoma (HCC) patients would greatly benefit from biomarkers. Angiogenesis and inflammation are hallmarks of HCC progression and therapeutic targets. Methods: We retrospectively evaluated preoperative clinical variables and circulating (plasma) biomarkers of angiogenesis and inflammation in a cohort of HCC patients who underwent liver resection (LR) or transplantation (LT). Biomarker correlation with outcomes—freedom of liver recurrence (FLR), disease-free survival (DFS) and overall survival (OS)—was tested using univariate and multivariate Cox regression analyses. Results: Survival outcomes associated with sVEGFR1, VEGF and VEGF-C in LT patients and with IL-10 in LR patients. Moreover, in LT patients within Milan criteria, higher plasma VEGF and sVEGFR1 were associated with worse outcomes, while in those outside Milan criteria lower plasma VEGF-C associated with better outcomes. Multivariate analysis indicated that adding plasma VEGF or VEGF-C to a predictive model including Milan criteria and AFP improved prediction of DFS and OS (all p < 0.05). Conclusion: Survival outcomes after LR or LT differentially associated with angiogenic and inflammatory biomarkers. High plasma VEGF correlated with poorer prognosis within Milan criteria while low plasma VEGF-C associated with better prognosis outside Milan criteria. These candidate biomarkers should be further validated to improve patient stratification.

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Castro-Sesquen, Yagahira E., Santosh L. Saraf, Victor R. Gordeuk, Sergei Nekhai et Marina Jerebtsova. « Use of Multiple Urinary Biomarkers for Early Detection of Chronic Kidney Disease in Sickle Cell Anemia Patients ». Blood 136, Supplement 1 (5 novembre 2020) : 30. http://dx.doi.org/10.1182/blood-2020-139500.

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BACKGROUND : More than 60% of sickle cell anemia (SCA) adults develop chronic kidney disease (CKD). Identification of early stages of CKD in SCA patients at high risk of complications could lead to personalized treatment and better prognosis. Recently we identified several urinary biomarkers that can differentiate CKD stage 1 in SCA patients. These biomarkers reflect pathophysiology of SCA, including iron homeostasis (ceruloplasmin, transferrin, hemoglobin, and ferritin); inflammation (orosomucoid); and glomerular hyperfiltration (hepatocyte growth factor like). HYPOTHESIS: We hypothesized that combination of novel urinary biomarkers might improve the accuracy of early detection of CKD. METHODS : We evaluated spot urine samples of 54 patients with SCA in a steady state from the University of Illinois at Chicago. Patients were classified by the stage of chronic kidney disease (CKD) based on the National Kidney Foundation, Kidney Disease Outcomes Quality Initiatives guidelines. Three groups of CKD stages were compared: Stage 0 (without CKD, n=23), stage 1 (early stage of CKD, n=19), and stages 2 to 5 (moderate to severe CKD, n=12). Urine levels of ceruloplasmin (CP), transferrin (TrF), hemoglobin (Hgb), ferritin (FrT), orosomucoid (ORM), and hepatocyte growth factor like (HGFL) were measured by ELISA and normalized to urinary creatinine (CRE) concentrations. Differences in sensitivity and specificity of biomarker combinations were compared using the McNemar's Test against the simple model, which uses urine Hgb only, and the complete model, with all the biomarkers together. A test for the equality of the Area Under the Curve (AUC) compared to the simple and complete models was done using the algorithm suggested by DeLong, DeLong, and Clarke-Pearson (1988). RESULTS: We tested the ability of each biomarker to distinguish SCA patients without CKD and with CKD stage 1. Receiver operating characteristic (ROC) curves were constructed to determine appropriate cutoffs for each biomarker. Cutoffs that provided the highest Youden Indexes were used. Three biomarkers (Hgb, CP, and ORM) had a sensitivity of 100%; however, specificity was lower than 80% (range: 65.2%-72.7%). Other biomarkers (Frt, Trf, and HGFL) had sensitivities lower than 80%, suggesting that individually these biomarkers are not accurate for early detection of CKD. We compared different combinations to the single biomarker model (Hgb only or model 0) and a complete combination of six biomarkers (model 1) (Table 1). The complete combination significantly improved specificity (from 69.6 to 82.6%) and increased AUC (from 0.86 to 0.96) compared to the single biomarker model. All combinations significantly increased the specificity (from 69.6% to 78.3-82.7%) compared to the single biomarker model. Combinations of four to five biomarkers (models 1-6) significantly increased specificity and AUC values than model 0. Combination of Hgb + CP+ ORM + Frt produced similar specificity and AUC values compared to complete model. CONCLUSION: These results demonstrate that the use of multiple biomarkers can improve the accuracy in the detection of kidney pathology in SCD patients, which has essential value for clinicians and researchers of clinical trials to target high-risk individuals for early treatment and preventive care. LIMITATION: Small cohort of patients from one center. Disclosures Saraf: Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other: Advisory Boards, Speakers Bureau; Novartis, Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pfizer, Global Blood Therapeutics, Novartis: Research Funding. Gordeuk:Imara: Research Funding; Novartis: Consultancy; Ironwood: Research Funding; CSL Behring: Consultancy, Research Funding; Global Blood Therapeutics: Consultancy, Research Funding.

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Pogosova-Agadjanyan, Era L., Soheil Meshinchi, Hana Lee, Brent L. Wood et Derek L. Stirewalt. « Expression Differences of Prognostic Biomarkers in Mononuclear Cells (MNCs) and Malignant Blasts of Acute Myeloid Leukemia (AML) Patients ». Blood 118, n^o 21 (18 novembre 2011) : 1468. http://dx.doi.org/10.1182/blood.v118.21.1468.1468.

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Abstract Abstract 1468 INTRODUCTION. Many molecular biomarkers have proven to be useful for guiding therapy for AML patients, yet remain inadequate for accurately predicting clinical outcomes. Possible explanations may be that certain biomarkers are more informative for restricted subpopulations of AML patients, or that the results of biomarkers must be interpreted in combination. Another explanation may be that there are methodological limitations in the assays. Most AML biomarkers are currently examined in MNCs, which include non-leukemic cells (lymphocytes, monocytes, and erythroblasts) and leukemic blasts. In addition, cells within the AML blast population display a wide spectrum of differentiation stages. To evaluate the potential impact of the non-leukemic cells in AML samples on the expression of prognostic transcriptional biomarkers, we examined enriched populations of cells from diagnostic AML samples. METHODS. Cryopreserved bone marrow (BM) and peripheral blood (PB) MNCs were obtained from 12 AML patients from the Leukemia Repository at the FHCRC. The cells were thawed and an aliquot was saved for future studies. Remaining cells were sorted for viable AML blasts using a combination of fluorochrome-conjugated antibodies (CD45, CD34, CD38, HLA-DR, and/or CD117) and DAPI. Additional sorts further differentiated the AML blasts into more or less mature (N=4 patients). RNA was extracted using Qiagen AllPrep RNA/DNA kit and reverse transcribed using AMV RT (Invitrogen). Expression of 22 potential prognostic biomarkers was evaluated using commercially available assays (Applied Biosystems) on ABI HT 7900 Fast Real-time PCR system. Fold differences in expression were computed by the comparative CT method, using GUSB to correct for RNA integrity and a pool of RNA from 10 PB from normal donors as a calibrator. RESULTS. Analyses showed marked differences between expression in the unsorted MNCs and AML blasts. Transcript expression was generally the same or more pronounced in AML blasts than in MNCs (e.g., BAALC, Figure 1A). In addition, any transcript differences identified in two populations generally diminished and were less dramatic in AML samples with high blast percentages. However, this was not the case for all samples and/or biomarkers. For example, CEBPA showed similar expression levels in MNCs and AML blasts. Attempts to adjust the signal in MNCs by blast percentages typically did not yield similar transcriptional levels for many samples. Similarly, the expression of examined prognostic biomarkers in subpopulations of AML blasts (mature vs. immature) showed a degree of heterogeneity among the patients. For some biomarkers, the immature population displayed a more pronounced fold difference in expression (e.g. BAALC, Figure1B), while for others, the expression was very similar in examined populations of most patients (e.g. CCNA1). CONCLUSION. As expected, the potential prognostic biomarkers demonstrated variable differences in expression in MNCs and enriched AML blasts, and these differences were even found to occur between the more and less differentiated AML blasts for the same patient. These differences may be of prognostic and predictive significance and may potentially impact the predictive ability of the biomarker. We are expanding these studies to include additional samples and determine if enriching for AML blasts, or even subpopulations within the blasts, may provide a more accurate assessment of prognosis. Disclosures: No relevant conflicts of interest to declare.

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Edwards, Katie L., Michele A. Miller, Jessica Siegal-Willott et Janine L. Brown. « Serum Health Biomarkers in African and Asian Elephants : Value Ranges and Clinical Values Indicative of the Immune Response ». Animals 10, n^o 10 (27 septembre 2020) : 1756. http://dx.doi.org/10.3390/ani10101756.

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Serum biomarkers indicative of inflammation and disease can provide useful information regarding host immune processes, responses to treatment and prognosis. The aims of this study were to assess the use of commercially available anti-equine reagents for the quantification of cytokines (tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), interleukins (IL) 2, 6, and 10) in African (Loxodonta africana, n = 125) and Asian (Elephas maximus, n = 104) elephants, and alongside previously validated anti-human reagents for acute-phase proteins (serum amyloid A and haptoglobin), calculate species-specific biomarker value ranges. In addition, we used opportunistically collected samples to investigate the concentrations of each biomarker during identified clinical cases of illness or injury, as a first step to understanding what biomarkers may be useful to managing elephant health. Immune biomarkers were each elevated above the calculated species-specific value ranges in at least one clinical case, but due to variability in both clinical and non-clinical samples, only serum amyloid A was significantly higher in clinical compared to non-clinical paired samples, with tendencies for higher TNF-α and IL-10. We also detected increased secretion of serum amyloid A and all five cytokines following routine vaccination of a single Asian elephant, indicating that these biomarkers can be beneficial for studying normal immune processes as well as pathology. This study indicates that assays developed with commercial reagents can be used to quantify health biomarkers in wildlife species and identifies several that warrant further investigation to elucidate immune responses to various pathologies.

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Karapetis, Christos Stelios, Heshan Liu, Michael Sorich, Jack Fiskum, Axel Grothey, Eric Van Cutsem, Tim Maughan et al. « Treatment effects (TEs) of EGFR monoclonal antibodies (mAbs) in metastatic colorectal cancer (mCRC) patients (pts) with KRAS, NRAS, and BRAF mutation (MT) status : Individual patient data (IPD) meta-analysis of randomized trials from the ARCAD database. » Journal of Clinical Oncology 38, n^o 15_suppl (20 mai 2020) : 4090. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.4090.

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4090 Background: EGFR mAbs have become incorporated into clinical practice for the management of mCRC over the last decade. KRAS and NRAS mutations are used as predictive biomarkers and BRAF V600E mutations are associated with an adverse prognosis. The observed TE within biomarker subpopulations has varied between studies. Methods: IPD from randomized trials with head-to-head comparison between EGFR mAb versus no EGFR mAb (chemotherapy alone or BSC) in mCRC, across all lines of therapy (first, second and later), were pooled. Biomarker subpopulations are defined in the table. Overall survival (OS) and progression-free survival (PFS) were compared between groups by Cox model, stratified by studies and adjusted by age, gender, and performance status. TEs were estimated by adjusted hazard ratio (HRadj) and 95% confidence interval (CI). Within each biomarker subgroup, EGFR mAb efficacy was explored according to multiple exploratory factors, including line of therapy, type of backbone chemo, gender, sidedness and site of metastasis. Interaction tests were performed. P-values < 0.01 were considered statistically significant to account for multiple comparisons. Results: 5729 pts from 8 studies with data available for ≥ 1 biomarker were analysed. PFS benefits (median 9.2 mos in EGFR mAbs, 8.0 mos in no EGFR mAbs) were confirmed in triple-WT pts, but not for OS (refer to table). No OS/PFS benefits were observed for pts with any of the MT tumors. Exploratory analyses showed a potential detrimental TE of EGFR mAbs in KRAS MT mCRC with liver metastasis (OS: HRadj 1.22, p = .003, pinteraction .0056; PFS: HRadj 1.24, p = .0009, pinteraction .0008). These results were confirmed within the subgroup of pts with all 3 biomarkers available. Conclusions: This is the largest IPD analysis to explore the predictive value of RAS/BRAF biomarkers in mCRC. Our findings demonstrate that there is no evidence of efficacy of EGFR mAbs in KRAS, BRAF and/or NRAS MT mCRC. EGFR mAbs might have a detrimental effect in KRAS MT mCRC with liver metastases. [Table: see text]

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Lee, Bernett T. K., Chun Meng Song, Boon Huat Yeo, Cheuk Wang Chung, Ying Leong Chan, Teng Ting Lim, Yen Bing Chua et al. « Gastric Cancer (Biomarkers) Knowledgebase (GCBKB) : A Curated and Fully Integrated Knowledgebase of Putative Biomarkers Related to Gastric Cancer ». Biomarker Insights 1 (janvier 2006) : 117727190600100. http://dx.doi.org/10.1177/117727190600100005.

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The Gastric Cancer (Biomarkers) Knowledgebase (GCBKB) ( http://biomarkers.bii.a-star.edu.sg/background/gastricCancerBiomarkersKb.php ) is a curated and fully integrated knowledgebase that provides data relating to putative biomarkers that may be used in the diagnosis and prognosis of gastric cancer. It is freely available to all users. The data contained in the knowledgebase was derived from a large literature source and the putative biomarkers therein have been annotated with data from the public domain. The knowledgebase is maintained by a curation team who update the data from a defined source. As well as mining data from the literature, the knowledgebase will also be populated with unpublished experimental data from investigators working in the gastric cancer biomarker discovery field. Users can perform searches to identify potential markers defined by experiment type, tissue type and disease state. Search results may be saved, manipulated and retrieved at a later date. As far as the authors are aware this is the first open access database dedicated to the discovery and investigation of gastric cancer biomarkers.

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Hajiaghamemar, Marzieh, Todd Kilbaugh, Kristy B. Arbogast, Christina L. Master et Susan S. Margulies. « Using Serum Amino Acids to Predict Traumatic Brain Injury : A Systematic Approach to Utilize Multiple Biomarkers ». International Journal of Molecular Sciences 21, n^o 5 (5 mars 2020) : 1786. http://dx.doi.org/10.3390/ijms21051786.

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Traumatic brain injury (TBI) can cause biochemical and metabolomic alterations in the brain tissue and serum. These alterations can be used for diagnosis and prognosis of TBI. Here, the serum concentrations of seventeen amino acids (AA) were studied for their potential utility as biomarkers of TBI. Twenty-five female, 4-week-old piglets received diffuse (n = 13) or focal (n = 12) TBI. Blood samples were obtained both pre-injury and at either 24-h or 4-days post-TBI. To find a robust panel of biomarkers, the results of focal and diffuse TBIs were combined and multivariate logistic regression analysis, coupled with the best subset selection technique and repeated k-fold cross-validation method, was used to perform a thorough search of all possible subsets of AAs. The combination of serum glycine, taurine, and ornithine was optimal for TBI diagnosis, with 80% sensitivity and 86% overall prediction rate, and showed excellent TBI diagnostic performance, with 100% sensitivity and 78% overall prediction rate, on a separate validation dataset including four uninjured and five injured animals. We found that combinations of biomarkers outperformed any single biomarker. We propose this 3-AA serum biomarker panel to diagnose mild-to-moderate focal/diffuse TBI. The systematic approaches implemented herein can be used for combining parameters from various TBI assessments to develop/evaluate optimal multi-factorial diagnostic/prognostic TBI metrics.

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Bivona, Giulia, Luisa Agnello et Marcello Ciaccio. « Biomarkers for Prognosis and Treatment Response in COVID-19 Patients ». Annals of Laboratory Medicine 41, n^o 6 (1 novembre 2021) : 540–48. http://dx.doi.org/10.3343/alm.2021.41.6.540.

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Luo, Jiaxin, Lin Wu, Dinghui Liu, Zhaojun Xiong, Linli Wang, Xiaoxian Qian et Xiaoqiang Sun. « Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data ». Mathematical Biosciences and Engineering 18, n^o 6 (2021) : 7774–89. http://dx.doi.org/10.3934/mbe.2021386.

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<abstract> <p>Cardiovascular and cerebrovascular diseases are leading causes of death worldwide, accounting for more than 40% of all deaths in China. Acute myocardial infarction (AMI) is a common cardiovascular disease and traditionally divided into ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI), which are known with different prognoses and treatment strategies. However, key regulatory genes and pathways involved in AMI that may be used as potential biomarker for prognosis are unknown. In this study, we employed both bulk and single-cell RNA-seq to construct gene regulatory networks and cell-cell communication networks. We first constructed weighted gene co-expression networks for differential expressed genes between STEMI and NSTEMI patients based on whole-blood RNA-seq transcriptomics. Network topological attributes (e.g., node degree, betweenness) were analyzed to identify key genes involved in different functional network modules. Furthermore, we used single-cell RNA-seq data to construct multilayer signaling network to infer regulatory mechanisms of the above key genes. PLAUR (receptor for urokinase plasminogen activator) was found to play a vital role in transducing inter-cellular signals from endothelial cells and fibroblast cells to intra-cellular pathways of myocardial cells, leading to gene expression involved in cellular response to hypoxia. Our study sheds lights on identifying molecular biomarkers for diagnosis and prognosis of AMI, and provides candidate key regulatory genes for further experimental validation.</p> </abstract>

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Chen, Yiping, Yanjuan Lin, Haoruo Zhang, Yanchun Peng, Sailan Li et Xizhen Huang. « Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection ». BioMed Research International 2020 (21 avril 2020) : 1–7. http://dx.doi.org/10.1155/2020/1057496.

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Markers of prothrombotic state and inflammation are associated with the prognosis of patients with acute type A aortic dissection (AAAD). However, it is unclear that the relationship between these biomarkers and their combined impact on risk stratification. The present study evaluated the prognostic value of platelet counts, lymphocyte to neutrophil ratio (LNR), and lymphocyte to monocyte ratio (LMR), alone and in combination. A retrospective analysis of clinical data of 744 AAAD patients was conducted to identify whether these biomarkers were related to the 30-day mortality risk. A Kaplan-Meier analysis and log-rank test were used to compare survival between groups. A Cox hazard regression multivariable analysis was performed for 30-day mortality. Individual biomarker (platelet count, LNR, or LMR) was unable to predict 30-day mortality. However, combinations of all three biomarkers provided additive predictive value over either marker alone, the receiver operating characteristic (ROC) model had a prediction probability of 0.739 when platelet counts, LNR, and LMR were included. Cox hazard regression multivariable analysis showed that combinations of all three biomarkers were the strongest predictor of 30-day mortality (p<0.021). Combined with these three easily measurable biomarkers at admission, they could help identify AAAD patients with a high risk of 30-day mortality.

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Branco, João Paulo, Joana Santos Costa, João Sargento-Freitas, Sandra Oliveira, Bruno Mendes, Jorge Laíns et João Pinheiro. « Neuroimagem e Biomarcadores no Prognóstico Funcional de Doentes com Acidente Vascular Cerebral ». Acta Médica Portuguesa 29, n^o 11 (30 novembre 2016) : 749. http://dx.doi.org/10.20344/amp.7411.

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Introduction: Stroke remains one of the leading causes of morbidity and mortality around the world and it is associated with an important long-term functional disability. Some neuroimaging resources and certain peripheral blood or cerebrospinal fluid proteins can give important information about etiology, therapeutic approach, follow-up and functional prognosis in acute ischemic stroke patients. However, among the scientific community, there is currently more interest in the stroke vital prognosis over the functional prognosis. Predicting the functional prognosis during acute phase would allow more objective rehabilitation programs and better management of the available resources. The aim of this work is to review the potential role of acute phase neuroimaging and blood biomarkers as functional recovery predictors after ischemic stroke.Material and Methods: Review of the literature published between 2005 and 2015, in English, using the terms “ischemic stroke”, “neuroimaging” e “blood biomarkers”.Results: We included nine studies, based on abstract reading.Discussion: Computerized tomography, transcranial doppler ultrasound and diffuse magnetic resonance imaging show potential predictive value, based on the blood flow study and the evaluation of stroke’s volume and localization, especially when combined with the National Institutes of Health Stroke Scale. Several biomarkers have been studied as diagnostic, risk stratification and prognostic tools, namely the S100 calcium binding protein B, C-reactive protein, matrix metalloproteinases and cerebral natriuretic peptide.Conclusion: Although some biomarkers and neuroimaging techniques have potential predictive value, none of the studies were able to support its use, alone or in association, as a clinically useful functionality predictor model. All the evaluated markers were considered insufficient to predict functional prognosis at three months, when applied in the first hours after stroke. Additional studies are necessary to identify reliable predictive markers for functional prognosis after ischemic stroke.

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Zhang, Jingyu, Colin McCulloch, Yunxia Sui, Sean Dinn, Qing Li, Alberto Santamaria-Pang, Christopher J. Sevinsky et al. « Characterization of glioblastoma (GBM) vasculature and protein expression of surrounding tumor cells on single FFPE sections with a multicycle multiplexed in situ immunofluorescent staining technology. » Journal of Clinical Oncology 31, n^o 15_suppl (20 mai 2013) : 2097. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.2097.

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2097 Background: GBM is the most common brain tumor in humans and has a dismal prognosis. Although antiangiogenic therapy (bevacizumab) is an option for GBM, there is still unmet need to understand tumor pathophysiology and predictive biomarkers. We built a tissue based multiplexed immunofluorescent assays and developed algorithms to identify and quantify tumor vasculature, that enabled quantification, visualization, and colocalization of multiple protein in surrounding tumor cells at single cell and subcellular levels. This assay provides unique opportunity to explore tumor heterogeneity of tissue morphology and their relationships to vasculature, and is a novel tool for biomarker and treatment discovery. Methods: Tissue micro arrays (TMAs) were constructed from 141 GBM patients. Fluorescent dye labeled antibodies against 18 biomarkers were sequentially applied on single sections of these TMAs. Metrics were built to identify vessels, quantify distance of tumor cells to vessels, and analyze expression profiles of biomarkers, including signaling molecules in EGFR, PI3K/AKT, TGF-beta pathways, and hypoxia marker Glut1, in proximity to blood vessels. Results: CD31 was successfully used to identify blood vessels in GMB. Vessel segmentation and quantification were performed on all of the images. Biomarker profiling in the context of blood vessels demonstrated different patterns in close proximity to vessels, with some biomarkers showing increased levels (e.g. SMA, EGFR, pS6), some showing decreased levels (e.g. p4EBP), and others remain the same (FOXO3a, S6). Quantification of biomarkers showed heterogeneous expression within the same sample and across the cohort. In addition, co-localization of the above markers was visualized and demonstrated on single cell and subcellular levels. Conclusions: We were able to use a novel fluorescent multiplexing technology (MultiOmyx) to study GBM biology. This technology allowed the simultaneous analyses of multiple biomarkers of GBM, and provides new insights on the relationship of markers to each other, tumor heterogeneity and angiogenesis.

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Cuadrado, MJ, MA Aguirre, N. Barbarroja, MA Khamashta et Ch Lopez-Pedrera. « Proteomics in antiphospholipid syndrome : a review ». Lupus 19, n^o 4 (30 mars 2010) : 385–88. http://dx.doi.org/10.1177/0961203309360986.

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The presence of antiphospholipid antibodies (aPL) has been closely related to the development of thrombosis and complications in pregnancy. However, not all patients with aPL will develop those clinical features. The exact pathogenic mechanisms leading to thrombosis and/or pregnancy morbidity are poorly understood. Currently, biomarkers which enable one to predict the prognosis of patients with positive aPL are not readily available. Current advances in genomics and proteomics provide the opportunity to discover novel biomarkers based on changes in concentration levels or post-translational modifications of proteins and peptides. These techniques are now being applied in various areas of medicine with very promising results. This review covers recent studies that have used this approach for a better understanding of the pathogenic mechanisms involved in the development of thrombosis in patients with antiphospholipid syndrome (APS). Although, there are very few qualified biomarkers that have arisen as a result of efforts in proteomics, it is expected that these techniques will deliver biomarkers that might ultimately identify different subgroups of APS patients with various prognoses that might have implications with respect to management and prognosis. Lupus (2010) 19, 385—388.

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Jakhar, Shailja, Alexis A. Bitzer, Loreen R. Stromberg et Harshini Mukundan. « Pediatric Tuberculosis : The Impact of “Omics” on Diagnostics Development ». International Journal of Molecular Sciences 21, n^o 19 (23 septembre 2020) : 6979. http://dx.doi.org/10.3390/ijms21196979.

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Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the “omics” approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.

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Santiloni Cury, Sarah, Diogo de Moraes, Paula Paccielli Freire, Grasieli de Oliveira, Douglas Venâncio Pereira Marques, Geysson Javier Fernandez, Maeli Dal-Pai-Silva et al. « Tumor Transcriptome Reveals High Expression of IL-8 in Non-Small Cell Lung Cancer Patients with Low Pectoralis Muscle Area and Reduced Survival ». Cancers 11, n^o 9 (26 août 2019) : 1251. http://dx.doi.org/10.3390/cancers11091251.

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Cachexia is a syndrome characterized by an ongoing loss of skeletal muscle mass associated with poor patient prognosis in non-small cell lung cancer (NSCLC). However, prognostic cachexia biomarkers in NSCLC are unknown. Here, we analyzed computed tomography (CT) images and tumor transcriptome data to identify potentially secreted cachexia biomarkers (PSCB) in NSCLC patients with low-muscularity. We integrated radiomics features (pectoralis muscle, sternum, and tenth thoracic (T10) vertebra) from CT of 89 NSCLC patients, which allowed us to identify an index for screening muscularity. Next, a tumor transcriptomic-based secretome analysis from these patients (discovery set) was evaluated to identify potential cachexia biomarkers in patients with low-muscularity. The prognostic value of these biomarkers for predicting recurrence and survival outcome was confirmed using expression data from eight lung cancer datasets (validation set). Finally, C2C12 myoblasts differentiated into myotubes were used to evaluate the ability of the selected biomarker, interleukin (IL)-8, in inducing muscle cell atrophy. We identified 75 over-expressed transcripts in patients with low-muscularity, which included IL-6, CSF3, and IL-8. Also, we identified NCAM1, CNTN1, SCG2, CADM1, IL-8, NPTX1, and APOD as PSCB in the tumor secretome. These PSCB were capable of distinguishing worse and better prognosis (recurrence and survival) in NSCLC patients. IL-8 was confirmed as a predictor of worse prognosis in all validation sets. In vitro assays revealed that IL-8 promoted C2C12 myotube atrophy. Tumors from low-muscularity patients presented a set of upregulated genes encoding for secreted proteins, including pro-inflammatory cytokines that predict worse overall survival in NSCLC. Among these upregulated genes, IL-8 expression in NSCLC tissues was associated with worse prognosis, and the recombinant IL-8 was capable of triggering atrophy in C2C12 myotubes.

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Iafolla, Marco Adelmo James, Sarah Louise Picardo, Kyaw Lwin Aung et Aaron Richard Hansen. « Systematic review and REMARK scoring of renal cell carcinoma (RCC) prognostic circulating biomarker manuscripts. » Journal of Clinical Oncology 37, n^o 7_suppl (1 mars 2019) : 569. http://dx.doi.org/10.1200/jco.2019.37.7_suppl.569.

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569 Background: No validated biomarkers exist to help guide prognosis of RCC patients. This study seeks to determine the current state of published prognostic RCC biomarker manuscripts and evaluate their quality using the REMARK criteria. Methods: The phrase “(renal cell carcinoma OR renal cancer OR kidney cancer OR kidney carcinoma) AND circulating AND (biomarkers OR cell free DNA OR tumor DNA OR methylated cell free DNA OR methylated tumor DNA)” was searched in Embase, Medline and PubMed during March 2018. One author (MI) selected all relevant manuscripts from the search results, and two authors (MI and SP) independently scored all relevant manuscripts using the REMARK guidelines (maximum 20 points comprised of 20 items subdivided into 48 criteria). Results: The search identified 525 publications: 73 were valid, 436 were rejected, and 26 were uncertain of their relevance. Amongst the valid publications, 33 were manuscripts of primary research (remainder: 26 review papers, 14 abstracts): manuscripts evaluating ≥ 2 biomarkers (n = 8) and novel biomarkers not published elsewhere (n = 7) comprised the majority. The median REMARK score was 10.6 (range 6.4-14.2). All manuscripts stated their marker, study objectives and method of case selection. The lowest scoring criteria were lack of: description of time between storage of blood/serum and marker assay (n = 2); flow or study profile diagram (n = 2); blinding of the person making the marker assessment to clinical outcomes (n = 3); and pre-specified hypotheses (n = 3). In total, only 8 studies reported a hazard or odds ratio. Using Pearson’s correlation, there was no association with either year of publication (median 2014; range 2004-2018; r2 = 0.14; p = 0.44) or impact factor (median 5.168; range 1.2-26.303; r2 = 0.24; p = 0.17) with REMARK score. Conclusions: Despite several published manuscripts on RCC prognostic biomarkers, most poorly adhere to the REMARK guidelines; this may be the cause for the paucity of a validated RCC biomarker to help supplement or supplant current clinical prognostic criteria. Better designed studies and appropriate reporting of methods, results and interpretation are required to address this urgent unmet need.

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Kaissis, Georgios A., Friederike Jungmann, Sebastian Ziegelmayer, Fabian K. Lohöfer, Felix N. Harder, Anna Melissa Schlitter, Alexander Muckenhuber et al. « Multiparametric Modelling of Survival in Pancreatic Ductal Adenocarcinoma Using Clinical, Histomorphological, Genetic and Image-Derived Parameters ». Journal of Clinical Medicine 9, n^o 5 (25 avril 2020) : 1250. http://dx.doi.org/10.3390/jcm9051250.

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Rationale: Pancreatic ductal adenocarcinoma (PDAC) remains a tumor entity of exceptionally poor prognosis, and several biomarkers are under current investigation for the prediction of patient prognosis. Many studies focus on promoting newly developed imaging biomarkers without a rigorous comparison to other established parameters. To assess the true value and leverage the potential of all efforts in this field, a multi-parametric evaluation of the available biomarkers for PDAC survival prediction is warranted. Here we present a multiparametric analysis to assess the predictive value of established parameters and the added contribution of newly developed imaging features such as biomarkers for overall PDAC patient survival. Methods: 103 patients with resectable PDAC were retrospectively enrolled. Clinical and histopathological data (age, sex, chemotherapy regimens, tumor size, lymph node status, grading and resection status), morpho-molecular and genetic data (tumor morphology, molecular subtype, tp53, kras, smad4 and p16 genetics), image-derived features and the combination of all parameters were tested for their prognostic strength based on the concordance index (CI) of multivariate Cox proportional hazards survival modelling after unsupervised machine learning preprocessing. Results: The average CIs of the out-of-sample data were: 0.63 for the clinical and histopathological features, 0.53 for the morpho-molecular and genetic features, 0.65 for the imaging features and 0.65 for the combined model including all parameters. Conclusions: Imaging-derived features represent an independent survival predictor in PDAC and enable the multiparametric, machine learning-assisted modelling of postoperative overall survival with a high performance compared to clinical and morpho-molecular/genetic parameters. We propose that future studies systematically include imaging-derived features to benchmark their additive value when evaluating biomarker-based model performance.

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Blangy-Letheule, Angélique, Antoine Persello, Bertrand Rozec, Michel De Waard et Benjamin Lauzier. « New Approaches to Identify Sepsis Biomarkers : The Importance of Model and Sample Source for Mass Spectrometry ». Oxidative Medicine and Cellular Longevity 2020 (24 décembre 2020) : 1–10. http://dx.doi.org/10.1155/2020/6681073.

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Septic shock is a systemic inflammatory response syndrome associated with circulatory failure leading to organ failure with a 40% mortality rate. Early diagnosis and prognosis of septic shock are necessary for specific and timely treatment. However, no predictive biomarker is available. In recent years, improvements in proteomics-based mass spectrometry have improved the detection of such biomarkers. This approach can be performed on different samples such as tissue or biological fluids. Working directly from human samples is complicated owing to interindividual variability. Indeed, patients are admitted at different stages of disease development and with signs of varying severity from one patient to another. All of these elements interfere with the identification of early, sensitive, and specific septic shock biomarkers. For these reasons, animal models of sepsis, although imperfect, are used to control the kinetics of the development of the pathology and to standardise experimentation, facilitating the identification of potential biomarkers. These elements underline the importance of the choice of animal model used and the sample to be studied during preclinical studies. The aim of this review is to discuss the relevance of different approaches to enable the identification of biomarkers that could indirectly be relevant to the clinical setting.

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Selvarajah, Senthooran, Ola H. Negm, Mohamed R. Hamed, Carolyn Tubby, Ian Todd, Patrick J. Tighe, Tim Harrison et Lucy C. Fairclough. « Development and Validation of Protein Microarray Technology for Simultaneous Inflammatory Mediator Detection in Human Sera ». Mediators of Inflammation 2014 (2014) : 1–12. http://dx.doi.org/10.1155/2014/820304.

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Biomarkers, including cytokines, can help in the diagnosis, prognosis, and prediction of treatment response across a wide range of disease settings. Consequently, the recent emergence of protein microarray technology, which is able to quantify a range of inflammatory mediators in a large number of samples simultaneously, has become highly desirable. However, the cost of commercial systems remains somewhat prohibitive. Here we show the development, validation, and implementation of an in-house microarray platform which enables the simultaneous quantitative analysis of multiple protein biomarkers. The accuracy and precision of the in-house microarray system were investigated according to the Food and Drug Administration (FDA) guidelines for pharmacokinetic assay validation. The assay fell within these limits for all but the very low-abundant cytokines, such as interleukin- (IL-) 10. Additionally, there were no significant differences between cytokine detection using our microarray system and the “gold standard” ELISA format. Crucially, future biomarker detection need not be limited to the 16 cytokines shown here but could be expanded as required. In conclusion, we detail a bespoke protein microarray system, utilizing well-validated ELISA reagents, that allows accurate, precise, and reproducible multiplexed biomarker quantification, comparable with commercial ELISA, and allowing customization beyond that of similar commercial microarrays.

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Sun, Changling, Xiaolin Xuan, Zhi Zhou, Yuan Yuan et Fei Xue. « A Preliminary Report on the Investigation of Prestin as a Biomarker for Idiopathic Sudden Sensorineural Hearing Loss ». Ear, Nose & ; Throat Journal 99, n^o 8 (30 mai 2019) : 528–31. http://dx.doi.org/10.1177/0145561319849949.

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To date, no specific biomarkers for idiopathic sudden sensorineural hearing loss (ISSHL) have been used. The aim of this study is to investigate whether prestin, the motor protein of cochlear outer hair cells, could be used as a biomarker candidate for the diagnosis and prognosis judgement of ISSHL. Blood samples of 14 ISSHL patients and 28 control patients without history of hearing loss were collected. Plasma prestin concentration was measured using Human Prestin (SLC26A5) ELISA Kit. The results showed that prestin was detectable in the plasma of all patients and the concentration of prestin was significantly higher in ISSHL patients with about half being above the average range of control patients. Moreover, in treatment responsive group, 6 of 10 patients had decreased prestin levels after treatment compared to those of before treatment, while the prestin levels of all the 4 patients in treatment unresponsive group increased in varying degrees. Our promising preliminary results suggest that prestin has the potential to serve as a biomarker to assist diagnosis and judge response to pharmacological treatments.

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Singh, Shikha Satendra. « Characterization of a novel regulator of AKT/mTOR signaling in gastric cancer. » Journal of Clinical Oncology 34, n^o 4_suppl (1 février 2016) : 68. http://dx.doi.org/10.1200/jco.2016.34.4_suppl.68.

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68 Background: Gastric cancer (GC) is a leading cause of cancer-related death with poor prognosis and “one-size fits all approach”. Dysregulation of PI3K/Akt/mTOR pathway is a common event in GC with PIK3CAmutations reported to correlate with poor prognosis. With prognosis far from satisfactory, we aimed to identify novel surrogate biomarkers. We hypothesize the role of DP103, a DEAD-box RNA helicase, as a novel surrogate biomarker for GC by regulating the PI3K/Akt/mTOR pathway. Additionally, we shed light on high DP103 GC cells responding to Akt/mTOR dual inhibitor treatment, indicating its potential role as a surrogate biomarker for GC treatment. Methods: Tissue microarray data from GC cohorts were used in correlation analysis between DP103 and PIK3CA expression. Effect of DP103 knockdown was assessed on functions downstream of PI3K/Akt/mTOR pathway including apoptosis, autophagy and cell invasion. Next, DP103 depletion studies were done and PI3K/Akt/mTOR pathway proteins were assessed. Further, immunoprecipitation studies assessed for DP103 interacting partners from PI3K/Akt/mTOR pathway in GC. Results: Herein, we provide clinical evidence of DP103 upregulation in GC patients’ tissues compared to normal gastric tissues. Additionally, we showed a positive correlation between DP103 and PIK3CA expression in GC patients’. DP103 knockdown resulted in decrease in cell invasion and an increase in apoptosis and autophagy. Further, decrease in phosphorylation of PI3K/Akt/mTOR pathway proteins was observed with DP103 depletion. Mechanistically, we discovered a novel physical interaction between DP103 and PI3K in GC. Conclusions: Here we summarized, current understanding of DP103 regulating PI3K/Akt/mTOR pathway in GC and discuss potential use as a new surrogate biomarker for better clinical application.

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Marazzi, Monica Gioia, Filippo Randelli, Marco Brioschi, Lorenzo Drago, Carlo Luca Romanò, Giuseppe Banfi, Luca Massaccesi et al. « Presepsin : A potential biomarker of PJI ? A comparative analysis with known and new infection biomarkers ». International Journal of Immunopathology and Pharmacology 31 (18 décembre 2017) : 039463201774935. http://dx.doi.org/10.1177/0394632017749356.

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There is still no “gold standard” for the diagnosis and prognosis of post-operative periprosthetic joint infection (PJI). Among serum biomarkers, an emerging molecule is presepsin, the soluble fraction of CD14, recently described in other settings as a powerful diagnostic tool to detect sepsis at different degrees of severity. The aim of this study was to investigate the diagnostic and prognostic value of presepsin in PJI. A total of 30 patients with PJI and 30 patients without PJI were enrolled. Presepsin, C-reactive protein (CRP), serum interleukin (IL)-6, triggering receptor expressed on myeloid cells 1 (TREM-1), CCL2, matrix metalloproteinase 9 (MMP-9), CD163, osteopontin (OPN), and toll-like receptor 2 (TLR2) were measured at different times after surgery. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were analyzed for each biomarker. Presepsin showed greater diagnostic value than CRP and IL-6; CD163, TREM-1, and MMP-9 had very low diagnostic potential. Presepsin, OPN, CCL2, suPAR, and TLR2 all decreased significantly with increasing time of recovery after surgery in PJI patients. Presepsin can be considered a useful tool for the diagnosis and clinical monitoring of PJI and can be backed by a panel of new inflammatory markers involved in monocyte-/macrophage-mediated inflammatory responses, such as OPN, CCL2, TLR2, and suPAR.

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Ma, Xiaoling. « MicroRNA-181a-3p as a diagnostic and prognostic biomarker for acute myeloid leukemia ». Mediterranean Journal of Hematology and Infectious Diseases 12, n^o 1 (26 février 2020) : e2020012. http://dx.doi.org/10.4084/mjhid.2020.012.

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Background: Micro (mi)RNAs play an important role in the pathogenesis and development of acute myeloid leukemia (AML), and their abnormal expression may be sufficient to predict the prognosis and outcomes in AML patients. We evaluated the clinical diagnostic value of miRNA-181a-3p in predicting prognosis and outcomes in patients with AML. Methods: A total of 119 newly diagnosed adult patients with AML and 60 healthy controls were recruited. Blood specimens were obtained from all AML patients at diagnosis, and 10 blood specimens were obtained on day 28 after induction chemotherapy. The controls also provided blood samples. MiR-181a-3p expression was quantified by PCR, and relative miRNA expression was determined using the comparative Ct method. Results: Compared with healthy controls, the expression of miRNA-181a-3p was significantly increased in patients with AML. MiR-181a-3p expression could be used to discriminate AML patients from controls, with up-regulated expression correlating with favorable prognosis. Moreover, miRNA-181a-3p expression was significantly decreased in patients who achieved a complete response after induction chemotherapy. The multivariate Cox analysis highlighted the prognostic value of miR-181a-3p for patients with AML. Conclusions: MiR-181a-3p may be clinically useful as a disease marker for AML, and enhanced the prediction of patient outcomes to chemotherapy.

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Chen, Michelle, Antoninus Soosaipillai, Douglas D. Fraser et Eleftherios P. Diamandis. « Discovery of novel plasma biomarker ratios to discriminate traumatic brain injury ». F1000Research 8 (27 septembre 2019) : 1695. http://dx.doi.org/10.12688/f1000research.20445.1.

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Background: Traumatic brain injury (TBI) is a major cause of death and disability. Despite increased awareness, reliable biomarkers are urgently needed to aid in all forms of traumatic brain injury diagnosis and prognosis. Methods: Here, we aim to assess the diagnostic utility of known and novel TBI biomarkers in a pilot patient cohort of severe TBI (sTBI) patients and healthy controls. We analyzed concentrations of S100 calcium binding protein B (S100B), neuron specific enolase (NSE), human kallikrein 6 (hK6) and prostaglandin D2 synthase (PGDS) using ELISA immunoassays. Results: Plasma levels of hK6 and PGDS were significantly lower in sTBI compared with controls, while S100B and NSE were significantly higher. Furthermore, we show that ratios of NSE and S100B with hK6 and PGDS may be able to determine the presence of sTBI better than single markers alone. Conclusions: The findings presented here represent a starting point for future validation, where biomarker ratios can be tested in independent TBI cohorts.

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Mitra, Anirban Pradip, Jose E. Castelao, Debra Hawes, Denice D. Tsao-Wei, Xuejuan Jiang, Shan Rong Shi, Lillian L. Young et al. « Defining a nine-biomarker panel for predicting bladder cancer outcome in combination with smoking intensity : A report from the Los Angeles Cancer Surveillance Program. » Journal of Clinical Oncology 30, n^o 15_suppl (20 mai 2012) : 4575. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.4575.

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4575 Background: Urothelial carcinoma of the bladder (UCB) is a disease of alterations in several cellular pathways. Routine molecular profiling studies do not account for smoking, a well established risk factor for UCB, and its influence on outcome. This study assessed the prognostic potential of a multi-pathway protein panel across all UCB stages in a population-based cohort after accounting for clinicopathologic factors and smoking history. Methods: 212 UCB patients from the LA CSP, part of the NCI/SEER cancer registry, were included. "Smoking intensity" analyzed biologic and molecular impact of smoking by combining smoking status, duration of smoking and number of cigarettes smoked daily into a composite covariate. Tumors were profiled for Bax, caspase-3, Apaf-1, Bcl-2, p53, p21, COX2, VEGF and E-cadherin alterations by IHC. Univariate analyses and multivariable modeling examined associations with outcome. Results: Median follow up was 13.2 years. Age, pathologic stage, adjuvant therapy (all p< 0.001) and surgical modality (p = 0.05) were associated with survival. Increasing smoking intensity was associated with worse outcome (P < 0.001). Apaf-1 (p = 0.005), E-cadherin (p = 0.014) and p53 (p = 0.032) were univariately prognostic; E-cadherin remained prognostic after multivariate analysis (p = 0.04). Combined alterations in all 9 biomarkers were prognostic by univariate (p < 0.001) and multivariate (p = 0.006) analysis. A multivariate model that included all 9 biomarkers and smoking intensity was more accurate in predicting prognosis than models comprising of standard clinicopathologic covariates without (p < 0.001) or with (p = 0.018) smoking intensity. Conclusions: The study confirms detrimental effects of smoking on UCB prognosis. Apaf-1, E-cadherin and p53 individually predicted UCB survival. Increasing number of biomarker alterations was significantly associated with worsening survival, although markers contained in the panel were not necessarily prognostic individually. Predictive value of the nine-biomarker panel with smoking intensity was significantly higher than that of routine clinicopathologic parameters alone.

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Eusebi, Paolo, Oskar Hansson, Silvia Paciotti, Massimiliano Orso, Davide Chiasserini, Paolo Calabresi, Kaj Blennow et Lucilla Parnetti. « Cerebrospinal fluid biomarkers for the diagnosis and prognosis of Parkinson’s disease : protocol for a systematic review and individual participant data meta-analysis ». BMJ Open 7, n^o 11 (novembre 2017) : e018177. http://dx.doi.org/10.1136/bmjopen-2017-018177.

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IntroductionIdiopathic Parkinson’s disease (PD) is a progressive neurodegenerative disorder related to α-synuclein misfolding and aggregation. For this reason, it belongs to the family of ‘synucleinopathies’, which also includes some other neurological diseases. Although imaging and ancillary investigations may be helpful in the diagnostic workup, the diagnosis of PD mostly relies on the clinician’s expertise. Furthermore, there is a need today for markers that can track the disease progression in PD that might improve the evaluation of novel disease-modifying therapies. The cerebrospinal fluid (CSF) has been widely investigated with the purpose of finding useful diagnostic and prognostic biomarkers for PD.Methods and analysisThis systematic review protocol has been developed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses Protocol 2015 statement and was registered on the PROSPERO international prospective register of systematic reviews. An international collaboration will be established. We will search the Cochrane Library, Web of Science, Medline and Embase from inception, using appropriate search strategies. Individual participant data from all included studies will be merged into a single database. We will include any study assessing the diagnostic and prognostic role of CSF biomarkers in PD. To evaluate the risk of bias and applicability of primary diagnostic accuracy studies, we will use Quality Assessment of Diagnostic Accuracy Studies-2 and Quality in Prognostic Studies. We will use standard meta-analytic procedures. We will first explore the utility of each CSF biomarker in turn. For each biomarker, we will assess its diagnostic and prognostic utility by means of receiver operating characteristic analysis and regression models. We will then move towards a multivariate approach considering different panels of biomarkers.Ethics and disseminationOur study will not include confidential data, and no intervention will be involved, so ethical approval is not required. The results of the study will be reported in international peer-reviewed journals.

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Steuber, Thomas, Andrew J. Vickers, Angel M. Serio, Ville Vaisanen, Alexander Haese, Kim Pettersson, James A. Eastham, Peter T. Scardino, Hartwig Huland et Hans Lilja. « Comparison of Free and Total Forms of Serum Human Kallikrein 2 and Prostate-Specific Antigen for Prediction of Locally Advanced and Recurrent Prostate Cancer ». Clinical Chemistry 53, n^o 2 (1 février 2007) : 233–40. http://dx.doi.org/10.1373/clinchem.2006.074963.

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Abstract Background: We evaluated the association of total and free forms of serum human kallikrein 2 (hK2) and prostate-specific antigen (PSA) with prostate cancers of unfavorable prognosis. Methods: We retrospectively measured total PSA (tPSA), free PSA (fPSA), and total hK2 (thK2) in preoperative serum samples from 867 men [and assessed free hK2 (fhK2) measured in 577 of these men] treated with radical prostatectomy for clinically localized prostate cancer. Associations between biomarker concentrations and extracapsular extension, seminal vesicle invasion, and biochemical recurrence (BCR) were evaluated. A subset of patients with PSA ≤10 μg/L, the group most commonly seen in clinical practice in the US, was analyzed. Results: thK2 was the strongest predictor of extracapsular extension and seminal vesicle invasion (areas under the ROC curve [AUC], 0.662 and 0.719, respectively), followed by tPSA (AUC, 0.654 and 0.663). All biomarkers were significant predictors of BCR. hK2 forms, but not PSA forms, remained highly significant for predicting BCR in the low-PSA group. Combining tPSA, fPSA, and thK2 in a multivariable model improved prediction compared with any biomarker used individually (AUC, 0.711, 0.755, and 0.752 for this combination predicting extracapsular extension, seminal vesicle invasion, and BCR, respectively; P <0.001 for all). Conclusions: Increased concentrations of hK2 in the blood are significantly associated with unfavorable features of prostate cancer, and thK2 is predictive of locally advanced and recurrent cancer in patients with PSA ≤10 μg/L. Independent of tPSA and fPSA, hK2 predicts unfavorable prognosis.

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Gjerum, Le, Birgitte Bo Andersen, Marie Bruun, Anja Hviid Simonsen, Otto Mølby Henriksen, Ian Law, Steen Gregers Hasselbalch et Kristian Steen Frederiksen. « Comparison of the clinical impact of 2-[18F]FDG-PET and cerebrospinal fluid biomarkers in patients suspected of Alzheimer’s disease ». PLOS ONE 16, n^o 3 (12 mars 2021) : e0248413. http://dx.doi.org/10.1371/journal.pone.0248413.

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Background The two biomarkers 2-[18F]FDG-PET and cerebrospinal fluid biomarkers are both recommended to support the diagnosis of Alzheimer’s disease. However, there is a lack of knowledge for the comparison of the two biomarkers in a routine clinical setting. Objective The aim was to compare the clinical impact of 2-[18F]FDG-PET and cerebrospinal fluid biomarkers on diagnosis, prognosis, and patient management in patients suspected of Alzheimer’s disease. Methods Eighty-one patients clinically suspected of Alzheimer’s disease were retrospectively included from the Copenhagen Memory Clinic. As part of the clinical work-up all patients had a standard diagnostic program examination including MRI and ancillary investigations with 2-[18F]FDG-PET and cerebrospinal fluid biomarkers. An incremental study design was used to evaluate the clinical impact of the biomarkers. First, the diagnostic evaluation was based on the standard diagnostic program, then the diagnostic evaluation was revised after addition of either cerebrospinal fluid biomarkers or 2-[18F]FDG-PET. At each diagnostic evaluation, two blinded dementia specialists made a consensus decision on diagnosis, prediction of disease course, and change in patient management. Confidence in the decision was measured on a visual analogue scale (0–100). After 6 months, the diagnostic evaluation was performed with addition of the other biomarker. A clinical follow-up after 12 months was used as reference for diagnosis and disease course. Results The two biomarkers had a similar clinical value across all diagnosis when added individually to the standard diagnostic program. However, for the correctly diagnosed patient with Alzheimer’s disease cerebrospinal fluid biomarkers had a significantly higher impact on diagnostic confidence (mean scores±SD: 88±11 vs. 82±11, p = 0.046) and a significant reduction in the need for ancillary investigations (23 vs. 18 patients, p = 0.049) compared to 2-[18F]FDG-PET. Conclusion The two biomarkers had similar clinical impact on diagnosis, but cerebrospinal fluid biomarkers had a more significant value in corroborating the diagnosis of Alzheimer’s disease compared to 2-[18F]FDG-PET.

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Zolotovskaia, Marianna, Victor Tkachev, Maxim Sorokin, Andrew Garazha, Ella Kim, Sven Rainer Kantelhardt, Sven-Ernö Bikar et al. « Algorithmically Deduced FREM2 Molecular Pathway Is a Potent Grade and Survival Biomarker of Human Gliomas ». Cancers 13, n^o 16 (16 août 2021) : 4117. http://dx.doi.org/10.3390/cancers13164117.

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Gliomas are the most common malignant brain tumors with high mortality rates. Recently we showed that the FREM2 gene has a role in glioblastoma progression. Here we reconstructed the FREM2 molecular pathway using the human interactome model. We assessed the biomarker capacity of FREM2 expression and its pathway as the overall survival (OS) and progression-free survival (PFS) biomarkers. To this end, we used three literature and one experimental RNA sequencing datasets collectively covering 566 glioblastomas (GBM) and 1097 low-grade gliomas (LGG). The activation level of deduced FREM2 pathway showed strong biomarker characteristics and significantly outperformed the FREM2 expression level itself. For all relevant datasets, it could robustly discriminate GBM and LGG (p < 1.63 × 10−13, AUC > 0.74). High FREM2 pathway activation level was associated with poor OS in LGG (p < 0.001), and low PFS in LGG (p < 0.001) and GBM (p < 0.05). FREM2 pathway activation level was poor prognosis biomarker for OS (p < 0.05) and PFS (p < 0.05) in LGG with IDH mutation, for PFS in LGG with wild type IDH (p < 0.001) and mutant IDH with 1p/19q codeletion(p < 0.05), in GBM with unmethylated MGMT (p < 0.05), and in GBM with wild type IDH (p < 0.05). Thus, we conclude that the activation level of the FREM2 pathway is a potent new-generation diagnostic and prognostic biomarker for multiple molecular subtypes of GBM and LGG.

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Brankovic, Milos, K. Martijn Akkerhuis, Henk Mouthaan, Jasper J. Brugts, Olivier C. Manintveld, Jan van Ramshorst, Tjeerd Germans, Victor Umans, Eric Boersma et Isabella Kardys. « Cardiometabolic Biomarkers and Their Temporal Patterns Predict Poor Outcome in Chronic Heart Failure (Bio-SHiFT Study) ». Journal of Clinical Endocrinology & ; Metabolism 103, n^o 11 (2 août 2018) : 3954–64. http://dx.doi.org/10.1210/jc.2018-01241.

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Abstract Purpose Multiple hormonal and metabolic alterations occur in chronic heart failure (CHF), but their proper monitoring during clinically silent progression of CHF remains challenging. Hence, our objective was to explore whether temporal patterns of six emerging cardiometabolic biomarkers predict future adverse clinical events in stable patients with CHF. Methods In 263 patients with CHF, we determined the risk of a composite end point of heart failure hospitalization, cardiac death, left ventricular assist device implantation, and heart transplantation in relation to serially assessed blood biomarker levels and slopes (i.e., rate of biomarker change per year). During 2.2 years of follow-up, we repeatedly measured IGF binding proteins 1, 2, and 7 (IGFBP-1, IGFBP-2, IGFBP-7), adipose fatty acid binding protein 4 (FABP-4), resistin, and chemerin (567 samples in total). Results Serially measured IGFBP-1, IGFBP-2, IGFBP-7, and FABP-4 levels predicted the end point [univariable hazard ratio (95% CI) per 1-SD increase: 3.34 (2.43 to 4.87), 2.86 (2.10 to 3.92), 2.45 (1.91 to 3.13), and 2.46 (1.88 to 3.24), respectively]. Independently of the biomarkers’ levels, their slopes were also strong clinical predictors [per 0.1-SD increase: 1.20 (1.11 to 1.31), 1.27 (1.14 to 1.45), 1.23 (1.11 to 1.37), and 1.27 (1.12 to 1.48)]. All associations persisted after multivariable adjustment for patient baseline characteristics, baseline N-terminal pro-hormone brain natriuretic peptide and cardiac troponin T, and pharmacological treatment during follow-up. Main Conclusions The temporal patterns of IGFBP-1, IGFBP-2, IGFBP-7, and adipose FABP-4 predict adverse clinical outcomes during outpatient follow-up of patients with CHF and may be clinically relevant as they could help detect more aggressive CHF forms and assess patient prognosis, as well as ultimately aid in designing more effective biomarker-guided therapy.

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Gui, Huiming, Yutong Song, Yongsheng Yin, Hanzhang Wang, Ronald Rodriguez et Zhiping Wang. « Prognostic value of preoperative inflammation-based predictors in patients with bladder carcinoma after radical cystectomy ». Open Medicine 16, n^o 1 (1 janvier 2021) : 816–25. http://dx.doi.org/10.1515/med-2021-0277.

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Abstract Aims Emerging evidence has related inflammation-based biomarkers to numerous carcinomas, including bladder carcinoma (BC). However, the role of inflammatory biomarkers in the prognosis of BC remains inconclusive. This study aimed to compare preoperative plasma fibrinogen (PF) and other inflammatory biomarkers such as the platelet–lymphocyte ratio (PLR), neutrophil–lymphocyte ratio (NLR), lymphocyte–monocyte ratio (LMR), C-reactive protein (CRP) level, and serum albumin level to predict the prognosis of patients with BC. Methods This article focused on a retrospective analysis of 175 patients with newly diagnosed BC who were admitted to our hospital from March 2005 to March 2016. Of these BC patients, 136 had undergone radical cystectomy (RC). Results According to multivariate analysis, high PF level was an independent predictor of overall survival (OS) in 136 BC patients receiving RC (HR = 3.759; P = 0.011), but not for all 175 BC patients. Combining the NLR and PF values showed higher predictive accuracy for OS than NLR or PF alone (P < 0.05). Additionally, for 136 BC patients who had undergone RC, a close relationship was found between high PF levels (≥3.39 g/L) and lymph node metastasis (P = 0.011) and clinical T stage (P = 0.015). Furthermore, PF was a superior prognostic factor compared with the LMR, PLR, CRP, and albumin values in 136 BC patients who had undergone RC (P < 0.001). Conclusions The preoperative PF level may be a prognostic biomarker; and when combined with the NLR, it can improve the predictive ability of the survival of BC patients, particularly of BC patients who underwent RC.

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