Relevant bibliographies by topics / Cancer grading

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cancer grading'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Cancer grading"

1

Epstein, Jonathan I. "Prostate Cancer Grading." American Journal of Surgical Pathology 40, no. 1 (2016): 137. http://dx.doi.org/10.1097/pas.0000000000000563.

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Thomas, Marie S. "GRADING CANCER HANDOUTS." AJN, American Journal of Nursing 90, no. 11 (1990): 27. http://dx.doi.org/10.1097/00000446-199011000-00020.

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Herrera, Guillermo A., Elba A. Turbat-Herrera, and David G. Bostwick. "Prostate Cancer Grading." Pathology Case Reviews 19, no. 3 (2014): 108–17. http://dx.doi.org/10.1097/pcr.0000000000000033.

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Thomas, Marie S. "Grading Cancer Handouts." American Journal of Nursing 90, no. 11 (1990): 27. http://dx.doi.org/10.2307/3464068.

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Koshrawipour, Tanja, Ingo Stricker, Andrea Tannapfel, Lars Steinstraesser, Stefan Langer, and Andrej Ring. "Risk factors leading to grading changes within 300 low-grade soft tissue sarcomas." Journal of Clinical Oncology 30, no. 15_suppl (2012): 10059. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.10059.

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10059 Background: Soft tissue sarcomas (STS) are rare, mesenchymal derived tumors. Based on malignancy, three grades are distinguished with G1 equaling low grade, G2 intermediate grade and G3 high grade, respectively. Studies have shown that some G1 tumors which underwent complete surgical resection reoccurred as lesions with a grading shift from G1 to higher malignancy. This grading change is referred to as up grading. Patients with grading changes were thoroughly examined in our study. Our aim was to find possible risk factors for up gradings, such as age, localization of tumor and tumor type. Methods: This retrospective case control study evaluated 333 Patients, who, between 1996 to 2011 were treated for G1 STS at Bergmannsheil Bochum, university clinic. These patients received complete initial surgical resection. Among our 333 patients, 9.9% (n=33) developed up gradings of their STS. These were then reviewed more closely in the aim of finding possible risk factors. We did not exclude any patients from our data or deliberately pick any grading changers and regard our collective as randomly sampled. The processed data includes age, gender, tumor type, tumor localization, occurrence of recidive and grading change. Results: Patients with up gradings were found to have a higher mean age of 4, 5 years than reference collective. The tumor type has a strong, statistically significant effect on grading change as patients with fibrosarcomas have a threefold risk of developing up gradings when compared to patients with other G1 STS. Conclusions: Our results indicate that age and tumor type play the key role in the development of up gradings in low malignant STS .Patients aged 60 and above diagnosed with fibrosarcomas are at a 3 times higher risk of developing a grading change as opposed to patients younger than 60 with other low grade STS than fibrosarcoma. We discussed the significance of these risk factors and argued whether, in addition to wide tumor resection, a short term postoperative radiotherapy should be applied for these patients to improve therapeutical outcome.
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Shah, Rajal B. "Current Perspectives on the Gleason Grading of Prostate Cancer." Archives of Pathology & Laboratory Medicine 133, no. 11 (2009): 1810–16. http://dx.doi.org/10.5858/133.11.1810.

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Abstract Context.—Since its description in 1966 by Donald Gleason, the Gleason grading has remained a cornerstone in the diagnosis and management of prostate cancer. With widespread use of the prostate specific antigen screening, the diagnosis and management patterns of prostate cancers have dramatically changed. In addition, better understanding of the morphologic spectrum of prostate cancer and its subsequent outcome have prompted the refinement of the grading criteria and reporting practices applicable to contemporary practice management. Objective.—To present contemporary perspectives and approaches to the Gleason grading of prostate cancer. Data Sources.—Personal practice experience, review of medical literature, and excerpts from the 2005 International Society of Urological Pathology Consensus Statement on Gleason Grading of Prostate Cancer. Conclusions.—This review addresses the trend in contemporary practice toward a grading shift, with rare utilization of Gleason patterns 1 and 2, and discusses the refinement of histologic criteria for Gleason patterns 3 and 4; approaches to Gleason grading in the setting of unusual variant morphologies of prostate cancer; significance of higher tertiary pattern 5; and practice recommendations for reporting in the setting of extended multiple core biopsies and multifocal prostate cancers in radical prostatectomy. Finally, the impact of consensus recommendations in current practice, its limitations and pitfalls, are also addressed.
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Zeller, John L. "Grading of Prostate Cancer." JAMA 298, no. 13 (2007): 1596. http://dx.doi.org/10.1001/jama.298.13.1596.

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Sotiriou, C., Wirapati, S. Loi, et al. "Is genomic grading killing histological grading?" European Journal of Cancer Supplements 4, no. 2 (2006): 177. http://dx.doi.org/10.1016/s1359-6349(06)80452-0.

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Elston, E. W., and I. O. Ellis. "Method for grading breast cancer." Journal of Clinical Pathology 46, no. 2 (1993): 189–90. http://dx.doi.org/10.1136/jcp.46.2.189-b.

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Coard, Kathleen C., and Vincent L. Freeman. "Gleason Grading of Prostate Cancer." American Journal of Clinical Pathology 122, no. 3 (2004): 373–76. http://dx.doi.org/10.1309/mhcy35fj296cllc8.

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Dissertations / Theses on the topic "Cancer grading"

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Khan, Adnan M. "Algorithms for breast cancer grading in digital histopathology images." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/66024/.

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Histological analysis of tissue biopsies by an expert pathologist is considered gold standard for diagnosing many cancers, including breast cancer. Nottingham grading system, which is the most widely used criteria for histological grading of breast tissues, consists of three components: mitotic count, nuclear atypia and tubular formation. In routine histological analysis, pathologists perform grading of breast cancer tissues by manually examining each tissue specimen against the three components, which is a laborious and subjective process and thus can suffer from low inter-observer agreement. With the advent of digital whole-slide scanning platforms, automatic image analysis algorithms can be used as a partial solution for these issues. The main goal of this dissertation is to develop frameworks that can aid towards building an automated or semi-automated breast cancer grading system. We present novel frameworks for detection of mitotic cells and nuclear atypia scoring in breast cancer histopathology images. Both of these frameworks can play a fundamental role in developing a computer-assisted breast cancer grading system. Moreover, the proposed image analysis frameworks can be adapted to grading and analysis of cancers of several other tissues such as lung and ovarian cancers. In order to deal with one of the fundamental problems in histological image analysis applications, we first present a stain normalisation algorithm that minimises the staining inconsistency in histological images. The algorithm utilises a novel image-specific colour descriptor which summarises the colour contents of a histological image. Stain normalisation algorithm is used in the remainder of the thesis as a preprocessing step. We present a mitotic cell detection framework mimicking a pathologist’s approach, whereby we first perform tumour segmentation to restrict our search for mitotic cells to tumour regions only, followed by candidate detection and evaluation in a statistical machine learning framework. We also employ a discriminative dictionary learning paradigm to learn the visual appearance of mitotic cells, that models colour, texture, and shape in a composite manner. Finally, we present a nuclear atypia scoring framework based on a novel image descriptor which summarises the texture heterogeneity, inherent in histological images in a compact manner. Classification is performed using a geodesic k-nearest neighbour classifier which explicitly exploits the structure of Riemannian manifold of the descriptor and achieves significant performance boost as compared to Euclidean counterpart.
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Hillergren, Pierre. "Towards non-invasive Gleason grading of prostate cancer using diffusion weighted MRI." Thesis, Umeå universitet, Institutionen för fysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172808.

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Prostate cancer is one of the most common cancer diagnosis in men. This project aimed to help in characterization and treatment planning of prostate cancer by producing a Gleason grading probability based on apparent diffusion coefficient (ADC). In a study, from which this project received the patient data, the patients were first imaged using magnetic resonance imaging (MRI) in a 3T positron emission tomography MRI (PET/MRI) scanner. The prostates were surgically removed and placed in a patient specific mold. While inside the mold, the prostates were imaged using the same scanner, producing ex-vivo images of the prostates. Lastly the prostates were cut in histopathology slices and Gleason graded by a pathologist. To get correlation between ADC and Gleason grade all images needed to be correctly related to each other. This was done by three image registrations, which was the main part of this project. The histopathology slices were first registered to the ex-vivo images of the prostate, and then to the in-vivo T2-weighted images. The in-vivo T2w images were matched to images depicting the diffusion of water in the prostates, known as ADC-maps. The ADC-values were collected and matched to their possible Gleason grade. Information from 149 images were used, which came from 22 different patients. 3D pixels, known as voxels, with a corresponding Gleason grade annotation measured a lower average ADC-value. These voxels also showed more variation with a larger standard deviation. Furthermore, these voxels measured a larger range of ADC-values compared to voxels without a corresponding Gleason grade, but the probability of a Gleason grade was mainly seen for ADC-values below 1200 mm2/s. Filtering the ADC-map before collecting the information showed less spread in measurements, and larger total probability of Gleason grade annotation for lower ADC-values. To test the validity of the result a movement of the Gleason grade map was used to simulate registration errors. No large impact was observed for small movements but more obvious change for large. The results indicate this method as promising in predicting regions with a probability for Gleason grade of 3 or 4, however it was less accurate in separating the two. Gleason 5 showed very low probability, mainly as a result of the low sample size since only two patients had such tumors. Further research with better optimized filtering is recommended in the future.
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Chaudry, Qaiser Mahmood. "Improving cancer subtype diagnosis and grading using clinical decision support system based on computer-aided tissue image analysis." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47745.

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This research focuses towards the development of a clinical decision support system (CDSS) based on cellular and tissue image analysis and classification system that improves consistency and facilitates the clinical decision making process. In a typical cancer examination, pathologists make diagnosis by manually reading morphological features in patient biopsy images, in which cancer biomarkers are highlighted by using different staining techniques. This process is subjected to pathologist's training and experience, especially when the same cancer has several subtypes (i.e. benign tumor subtype vs. malignant subtype) and the same cancer tissue biopsy contains heterogeneous morphologies in different locations. The variability in pathologist's manual reading may result in varying cancer diagnosis and treatment. This Ph.D. research aims to reduce the subjectivity and variation existing in traditional histo-pathological reading of patient tissue biopsy slides through Computer-Aided Diagnosis (CAD). Using the CAD, quantitative molecular profiling of cancer biomarkers of stained biopsy images are obtained by extracting and analyzing texture and cellular structure features. In addition, cancer sub-type classification and a semi-automatic grade scoring (i.e. clinical decision making) for improved consistency over a large number of cancer subtype images can be performed. The CAD tools do have their own limitations and in certain cases the clinicians, however, prefer systems which are flexible and take into account their individuality when necessary by providing some control rather than fully automated system. Therefore, to be able to introduce CDSS in health care, we need to understand users' perspectives and preferences on the new information technology. This forms as the basis for this research where we target to present the quantitative information acquired through the image analysis, annotate the images and provide suitable visualization which can facilitate the process of decision making in a clinical setting.
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Tutac, Adina Eunice. "[Formal representation and reasoning for microscopic medical image-based prognosis] : [application to breast cancer grading]." Besançon, 2010. http://www.theses.fr/2010BESA2025.

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Cette thèse aborde l'aide du pronostic basée sur l'image et les ontologies médicales, en utilisant la représentation des connaissances et le raisonnement pour les très grandes images microscopiques. Une application médicale particulière dans laquelle une assistance de type pronostic est nécessaire est la graduation du cancer du sein. Même si cela est considéré comme un outil d'évaluation essentiel dans la pratique de pathologie moderne les principaux problèmes posés par la procédure manuelle de pronostic sont: la nécessité des connaissances, attention et temps. D'autre part, le manque de reprédentation sémantique formelle standardisée pour aider l'indexation et la classification de la terminologie, ainsi que l'utilisation d'un mécanisme d'inférence pour assister le graduation représentent des problématiques clé du domaine. Dans ce sens, cette étude propose une représentation formelle qualitative pour la graduation du cancer du sein ainsi qu'une ontologie d'application Brest cancer Grading Ontology (BCGO) pour décrire les connaissances d'une manière cohérente. Une autre question que nous adressons en proposant l'ontologie, est le fossé sémantique entre les concepts sémantiques de haut niveau et les caractéristiques de l'image de bas niveau. En plus, nous proposonsun soutien de théorie spatiale pour la représentation des relations spatiales entre les concepts spécifiques à la graduation du cancer du sein. L'ontologie BCGO est intégré dans une plateforme microscopique cognitive virtuelle MICO, pour l'exploitation visuelle, l'indexation et l'extration sémantique des l'images microscopiques<br>This thesis addresses ontology-driven prognosis assistance using knowledge representation and reasoning for very large microscopic medical images. One particular medical application in which prognosis assistance is needed is the breast cancer grading. Althrough this is considered the key assessment tool in prognosis of modern pathology pratice, the main problems of the manual procedure are: time constraint, the need of knowledge and attention. More over, the lack of formal standardized semantic representation for the indexing and classification of terminology and the lack of an inference mechanism to assist the grading are key issues of the domain. To this end, we propose a qualitativ ontological representation of breast cancer grading, an application ontology entlited Breast Cancer Grading Ontology (BCGO) based on OWL-DL and SWRL formalisms. Using this approach, the thesis also tackles the semantic gap between the high-level semantic concepts and the low-level image features. Additionally, we propose a spatial theory support for the representation of the spatial relations between the spatial concepts of the breast cancer grading. This ontology is integrated into a cognitive microscope framework MICO, guiding the image exploration, semantic indexing and retrieval of the microscopic images
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KONDO, TATSUHEI, HIDEO KAMEI, and KEISUKE TERABE. "Histopathological Study on the Prognosis of pT2 Gastric Cancer." Nagoya University School of Medicine, 1986. http://hdl.handle.net/2237/17488.

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Naqvi, Shabbar. "Modelling FTIR spectral sata with Type-I and Type-II fuzzy sets for breast cancer grading." Thesis, University of Nottingham, 2014. http://eprints.nottingham.ac.uk/14321/.

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Breast cancer is one of the most frequently occurring cancers amongst women throughout the world. After the diagnosis of the disease, monitoring its progression is important in predicting the chances of long term survival of patients. The Nottingham Prognostic Index (NPI) is one of the most common indices used to categorise the patients into different groups depending upon the severity of the disease. One of the key factors of this index is cancer grade which is determined by pathologists who examine cell samples under a microscope. This manual method has a higher chance of false classification and may lead to incorrect treatment of patients. There is a need to develop automated methods that employ advanced computational methods to help pathologists in making a decision regarding the classification of breast cancer grade. Fourier transform infra-red spectroscopy (FTIR) is one of the relatively new techniques that has been used for diagnosis of various cancer types with advanced computational methods in the literature. In this thesis we examine the use of advanced fuzzy methods with the FTIR spectral data sets to develop a model prototype that can help clinicians with breast cancer grading. Initial work is focussed on using the commonly used clustering algorithms k-means and fuzzy c-means with principal component analysis on different cancer spectral data sets to explore the complexities within them. After that, a novel model based on Type-II fuzzy logic is developed for use on a complex breast cancer FTIR spectral data set that can help clinicians classify breast cancer grades. The data set used for the purpose consists of multiple cases of each grade. We consider two types of uncertainty, one within the spectra of a single case of a grade (intra -case) and other when comparing it with other cases of same grade (inter-case). Features have been extracted in terms of interval data from various peaks and troughs. The interval data from the features has been used to create Type-I fuzzy sets for each case. After that the Type-I fuzzy sets are combined to create zSlices based General Type-II fuzzy sets for each feature for each grade. The created benchmark fuzzy sets are then used as prototypes for classification of unseen spectral data. Type-I fuzzy sets are created for unseen spectral data and then compared against the benchmark prototype Type-II fuzzy sets for each grade using a similarity measure. The best match based on the calculated similarity scores is assigned as the resultant grade. The novel model is tested on an independent spectral data set of oral cancer patients. Results indicate that the model was able to successfully construct prototype fuzzy sets for the data set, and provide in-depth information regarding the complexities of the data set as well as helping in classification of the data.
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Jiménez, Garay Gabriel Alexandro. "Deep Learning for Semantic Segmentation versus Classification in Computational Pathology: Application to mitosis analysis in Breast Cancer grading." Master's thesis, Pontificia Universidad Católica del Perú, 2019. http://hdl.handle.net/20.500.12404/13969.

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Existing computational pathology approaches did not allow, yet, the emergence of effective/efficient computer-aided tools used as a second opinion for pathologists in the daily practice. Focusing on the case of computer-based qualification for breast cancer diagnosis, the present article proposes two deep learning architectures to efficiently and effectively detect and classify mitosis in a histopathological tissue sample. The first method consisted of two parts, entailing a preprocessing of the digital histological image and a free-handcrafted-feature Convolutional Neural Network (CNN) used for binary classification. Results show that the methodology proposed can achieve 95% accuracy in testing with an F1-score of 94.35%, which is higher than the results from the literature using classical image processing techniques and also higher than the approaches using handcrafted features combined with CNNs. The second approach was an end-to-end methodology using semantic segmentation. Results showed that this algorithm can achieve an accuracy higher than 95% in testing and an average Dice index of 0.6 which is higher than the results from the literature using CNNs (0.9 F1-score). Additionally, due to the semantic properties of the deep learning approach, an end-to-end deep learning framework is viable to perform both tasks: detection and classification of mitosis. The results showed the potential of deep learning in the analysis of Whole Slide Images (WSI) and its integration to computer-aided systems. The extension of this work to whole slide images is also addressed in the last two chapters; as well as, some computational key points that are useful when constructing a computer-aided-system inspired by the described technology.<br>Trabajo de investigación
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Tay, ChiangHau. "Algorithms for Tissue Image Analysis using Multifractal Techniques." Thesis, University of Canterbury. Computer Science and Software Engineering, 2012. http://hdl.handle.net/10092/7268.

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Histopathological classification and grading of biopsy specimens play an important role in early cancer detection and prognosis. Nottingham Grading System (NGS) is one of the standard grading procedures used in breast cancer assessment, where three parameters, Mitotic Count (MC), Nuclear Pleomorphism (NP), and Tubule Formation (TF) are used for prognostic information. The grading takes into account the deviations in cellular structures and appearance between tumour and normal cells, using measures such as density, size, colour, and regularity. Cell structures in tissue images are also known to exhibit multifractal characteristics. This research focused on the multifractal properties of several graded biopsy specimens and analysed the dependency and variation of the fractal parameters with respect to the scores pre-assigned by pathologists. The effectiveness of using multifractal techniques on breast cancer grading was measured with a set of quantitative evaluations for MC, NP, and TF criteria. The developed method for MC scoring has obtained 82.87% true positive rate on detecting mitotic cells. Furthermore, the overall positive classification rates for NP and TF analysis were 67.38% and 71.82%, respectively, while obtaining 30.26% of false classification rate for NP analysis and 27.17% for TF analysis. The results have shown that multifractal formalism is a feasible and novel method that could be used for automatic grading of biopsy sections.
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ALFARANO, GABRIELE. "INTERFERON REGULATORY FACTOR 1 (IRF1) LINKS IMMUNOLOGICAL AND METABOLIC TRAITS TO HISTOLOGICAL GRADE IN PANCREATIC CANCER." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/607574.

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Pancreatic Ductal Adenocarcinoma (PDAC) is the most frequent neoplasia of the exocrine pancreas with a 5-years overall survival of less than 5% . Poor response to treatments can be attributed, at least in part, to the pervasive heterogeneity of this type of cancer, whose histological differentiation grade ranges from a well differentiated to a poorly differentiated phenotype . My lab previously dissected the transcriptional and epigenetic networks underlying PDAC grading. By using cell line models mimicking different PDAC grades, transcriptional data highlighted an interferon-related signature as peculiar of low-grade PDACs. This project aims at investigating the links between this interferon-related signature and the epithelial phenotype of well-differentiated PDACs. The role of Interferon Regulatory Factor 1 (IRF1), a transcription factor critical for the interferon response, in PDAC differentiation will be investigated. By combining a loss-of-function strategy and RNA-seq this work aimed at defining the targets and the effects of IRF1 differential expression in the mentioned cell line model. Model reliability will also be confirmed via immunohistochemistry on tumour microarrays. The immunological and metabolic phenotypes regulated by IRF1 in well differentiated PDACs will further be analysed by the use of xenografts and cell culture based assays. It will be shown that IRF1 regulates multiple interferon related genes involved in antigen processing and presentation; its deletion affects stromal composition in xenografts. IRF1 deficient cells also rewire their metabolic networks, with changes in lipid composition and metabolite usage. Overall, we found that the transcription factor IRF1 pleiotropically controls a variety of phenotypical traits of low grade PDACs: from antigen processing and presentation pathways, to metabolism, which IRF1 deficiency rewired towards an increased respiratory and lipogenic profile.
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MILAN, MARTA. "INVOLVEMENT OF THE TRANSCRIPTION FACTOR MYRF IN SIGNALING FROM THE ENDOPLASMIC RETICULUM TO THE NUCLEUS IN PANCREATIC CANCER." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/607575.

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Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer death worldwide. One reason for the poor prognosis is the high intra-tumor heterogeneity, with the coexistence of well- and poorly-differentiated cells in virtually all tumor cases. Thus, a better characterization of the circuitries regulating PDAC cell differentiation is required. We found that MYRF, a poorly characterized transcription factor, is selectively expressed in well-differentiated PDAC cell lines. MYRF is synthetized as an endoplasmic reticulum (ER) membrane protein and self-cleaves after trimerization, releasing the N-terminal trimer that translocates into the nucleus and regulates transcription. We generated MYRF-KO PDAC cells and combined transcriptomic profiles and analyses of MYRF genomic occupancy to study its function. We retrieved the MYRF DNA binding motif from our ChIP-sequencing data and demonstrated that MYRF capability to bind this sequence and activate transcription is strictly dependent on its trimerization. MYRF deletion resulted in the downregulation of cell replication-related genes and upregulation of ER stress-related genes. Consistently, MYRF loss resulted in an altered ER morphology and function, probably as a result of the overexpression of membrane and secreted proteins with complex folding, such as cysteine rich and highly glycosylated proteins. Additionally, we found that MYRF creates a feed-forward loop with the transcription factors FOS and FOSB. In doing so, MYRF directly regulates the expression of these two transcription factors that in turn cooperate to generate the MYRF transcriptional outcome. In conclusion, this work points to a role for MYRF as a key player in the communication between ER and nucleus, working as a sensor of proper ER function. MYRF appears to license cells for DNA replication and concomitantly to serve as a guardian against ER overload in highly secretory cancer cells.
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Books on the topic "Cancer grading"

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Damjanov, Ivan, and Fang Fan, eds. Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6.

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Damjanov, Ivan, and Fang Fan, eds. Cancer Grading Manual. Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-33751-7.

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Amin, Mahul B. Gleason grading of prostate cancer: A contemporary approach. Lippincott Williams & Wilkins, 2002.

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Brennan, Liam. Nucleolar organiser regions as a basis of cervical cancer grading. The Author], 1990.

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The Gleason grading system: A complete guide for pathologists and clinicians. Wolters Kluwer/Lippincott Williams & Wilkins Health, 2013.

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Mouriquand, Jacqueline. Diagnosis of non-palpable breast lesions: Ultrasonographically controlled fine-needle aspiration : diagnostic and prognostic implications of cytologic grading, morphometry, DNA cytometry, immunocytochemistry, and color doppler. Karger, 1993.

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Mouriquand, Jacqueline. Diagnosis of non-palpable breast lesions: Ultrasonographically controlled fine-needle aspirations : diagnostic and prognostic implications of cytologic grading, morphometry, DNA cytometry, immunocytochemistry, and color doppler. Karger, 1993.

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Damjanov, Ivan, and Fang Fan. Cancer Grading Manual. Springer, 2016.

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Damjanov, Ivan, and Fang Fan. Cancer Grading Manual. Springer, 2013.

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(Editor), Ivan Damjanov, and Fang Fan (Editor), eds. Cancer Grading Manual. Springer, 2006.

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Book chapters on the topic "Cancer grading"

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Furihata, Mutsuo, and Tamotsu Takeuchi. "Gleason Grading." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-27841-9_2415-2.

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Furihata, Mutsuo, and Tamotsu Takeuchi. "Gleason Grading." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-46875-3_2415.

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Furihata, Mutsuo, and Tamotsu Takeuchi. "Gleason Grading." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-16483-5_2415.

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Damjanov, Ivan. "History and General Aspects of Tumor Grading." In Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6_1.

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Prat, Jaime, and Ivan Damjanov. "Tumors of the Female Genital Organs." In Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6_10.

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Fan, Fang. "Tumors of the Breast." In Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6_11.

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Weiss, Lawrence M., and Karen L. Chang. "Lymphoid and Hematopoietic Systems." In Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6_12.

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Gatalica, Zoran, John F. Fetsch, Markku Miettinen, and Ivan Damjanov. "Tumors of the Soft Tissue and Bone." In Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6_13.

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Fraga, Garth R. "Tumors of the Skin." In Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6_14.

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Ma, Muchou Joe. "Tumors of the Central Nervous System." In Cancer Grading Manual. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34516-6_15.

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Conference papers on the topic "Cancer grading"

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Dalle, Jean-Romain, Wee Kheng Leow, Daniel Racoceanu, Adina Eunice Tutac, and Thomas C. Putti. "Automatic breast cancer grading of histopathological images." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4649847.

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Sengar, Namita, Neeraj Mishra, Malay Kishore Dutta, Jiri Prinosil, and Radim Burget. "Grading of colorectal cancer using histology images." In 2016 39th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2016. http://dx.doi.org/10.1109/tsp.2016.7760936.

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Mohsin, Muhammad, Arslan Shaukat, Usman Akram, and Muhammad Kaab Zarrar. "Automatic Prostate Cancer Grading Using Deep Architectures." In 2021 IEEE/ACS 18th International Conference on Computer Systems and Applications (AICCSA). IEEE, 2021. http://dx.doi.org/10.1109/aiccsa53542.2021.9686869.

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Vuong, Thi Le Trinh, Daigeun Lee, Jin Tae Kwak, and Kyungeun Kim. "Multi-task Deep Learning for Colon Cancer Grading." In 2020 International Conference on Electronics, Information, and Communication (ICEIC). IEEE, 2020. http://dx.doi.org/10.1109/iceic49074.2020.9051305.

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Camalan, Seda, Muhammad Khalid Khan Niazi, Mahesh Devarasetty, Shay Soker, and Metin N. Gurcan. "Bladder cancer organoid image analysis: textured-based grading." In Digital and Computational Pathology, edited by John E. Tomaszewski and Aaron D. Ward. SPIE, 2021. http://dx.doi.org/10.1117/12.2582208.

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Tutac, A. E., V. I. Cretu, and D. Racoceanu. "Spatial representation and reasoning in breast cancer grading ontology." In 2010 International Joint Conference on Computational Cybernetics and Technical Informatics. IEEE, 2010. http://dx.doi.org/10.1109/icccyb.2010.5491320.

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Greenblatt, Aaron, Clara Mosquera-Lopez, and Sos Agaian. "Quaternion Neural Networks Applied to Prostate Cancer Gleason Grading." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.199.

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Yu, Xiaotian, Zunlei Feng, Xiuming Zhang, Yuexuan Wang, and Thomas Li. "Space and Level Cooperation Framework for Pathological Cancer Grading." In 2022 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2022. http://dx.doi.org/10.1109/vcip56404.2022.10008824.

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Li, Zhenfeng, Yuchun Li, Yu Zhang, et al. "Gleason Grading of Prostate Cancer Based on Improved AlexNet." In 2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT). IEEE, 2021. http://dx.doi.org/10.1109/acait53529.2021.9731223.

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Bhattacharyya, Riddhasree, Paromita Roy, Sugata Banerji, and Sushmita Mitra. "Efficient grading of prostate cancer WSI with deep learning." In Digital and Computational Pathology, edited by John E. Tomaszewski and Aaron D. Ward. SPIE, 2024. http://dx.doi.org/10.1117/12.3006835.

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Reports on the topic "Cancer grading"

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Charatsi, Dimitra, Polyxeni Vanakara, Michail Nikolaou, et al. Vaginal Dilator Use to Promote Sexual Wellbeing After Radiotherapy in Gynaecological Cancer Survivors: A Prospective Observational Study. Science Repository, 2021. http://dx.doi.org/10.31487/j.ijcst.2021.03.01.sup.

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Background: Since continuing advances in radiotherapy technology broaden the role of radiotherapy in the treatment of gynaecologic malignancies, the use of vaginal dilators has been introduced in order to mitigate the risk of vaginal stenosis. The main aims of this study were to investigate the vaginal dilator use efficacy in the treatment of radiation-induced vaginal stenosis and the vaginal dilator effect on sexual quality of life. Methods: We studied fifty-three patients with endometrial or cervical cancer. The participants were treated with radical or adjuvant external beam radiotherapy and/or brachytherapy. They were routinely examined at four time points post-radiotherapy when also they were asked to fill in a validated sexual function-vaginal changes questionnaire. A p-value less than 0.05 was considered statistically significant. Results: The vaginal stenosis grading score was decreased and the size of the vaginal dilator comfortably insertable was gradually increased throughout the year of vaginal dilator use while radiation-induced vaginal and sexual symptoms were improved throughout the year of VD use. All patients with initial grade 3 showed vaginal stenosis of grade 2 after 12 months of vaginal dilator use and 65.8% of the patients with grade 2 initial vaginal stenosis demonstrated final vaginal stenosis grade 1 while 77.8% of the participants with initial 1st size of vaginal dilators reached the 3rd vaginal dilator size after 12 months. Starting time of dilator therapy &lt;= 3 months after the end of radiotherapy was associated with a significant decrease in vaginal stenosis. Additionally, there was an overall upward trend regarding patients’ satisfaction with their sexual life. Conclusion: Endometrial and cervical cancer survivors should be encouraged to use vaginal dilators for the treatment of vaginal stenosis and sexual rehabilitation after radiotherapy.
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Bancalari, Antonella, Samuel Berlinski, Giancarlo Buitrago, María Fernanda García, Dolores de la Mata, and Marcos Vera-Hernández. Health Inequalities in Latin American and the Caribbean: Child, Adolescent, Reproductive, Metabolic Syndrome and Mental Health. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005208.

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Health constitutes a fundamental aspect of our well-being. It is also a key factor in determining our contribution to market and non-market output. Health inequality refers to the unequal realization of health outcomes between different groups in the population. Systematic disparities in health outcomes and in access to health resources not only undermine basic principles of fairness and social justice but also contributes towards perpetuating poverty and disadvantage. In this chapter, we start by presenting evidence on how the burden of disease in Latin America and the Caribbean (LAC) has changed during the last 30 years. Consistent with the fall in fertility and population aging, the region has shifted from a burden of disease dominated by maternal, neonatal, and communicable disease in the 1990s to one dominated by cardiovascular disease, cancers, diabetes, and increasingly by mental health disorders. The poorest in the region are burdened by worst access to maternal care and higher levels of infant mortality and stunting. Despite being knowledgeable about contraceptive methods, young women in Latin America and the Caribbean have very high levels of teenage pregnancy with a steep socio-economic gradient. Noncommunicable diseases also affect the poor disproportionately in many countries. Finally, mental health is a growing source of lost days of healthy living among women and the poor. Overall, our results highlight that despite the epidemiological transition which is underway, socio-economic health disparities in the LAC region are still more important on early childhood and teenagerhood than in adulthood, at least as it pertains to the outcomes analyzed in this chapter. At the same time, we show that while socio-economic inequalities in child health are smaller in the richest countries, the contrary happens with inequalities in some adult outcomes.
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Cooper, Christopher, Jacob McDonald, and Eric Starkey. Wadeable stream habitat monitoring at Congaree National Park: 2018 baseline report. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2286621.

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The Southeast Coast Network (SECN) Wadeable Stream Habitat Monitoring Protocol collects data to give park resource managers insight into the status of and trends in stream and near-channel habitat conditions (McDonald et al. 2018a). Wadeable stream monitoring is currently implemented at the five SECN inland parks with wadeable streams. These parks include Horseshoe Bend National Military Park (HOBE), Kennesaw Mountain National Battlefield Park (KEMO), Ocmulgee Mounds National Historical Park (OCMU), Chattahoochee River National Recreation Area (CHAT), and Congaree National Park (CONG). Streams at Congaree National Park chosen for monitoring were specifically targeted for management interest (e.g., upstream development and land use change, visitor use of streams as canoe trails, and potential social walking trail erosion) or to provide a context for similar-sized stream(s) within the park or network (McDonald and Starkey 2018a). The objectives of the SECN wadeable stream habitat monitoring protocol are to: Determine status of upstream watershed characteristics (basin morphology) and trends in land cover that may affect stream habitat, Determine the status of and trends in benthic and near-channel habitat in selected wadeable stream reaches (e.g., bed sediment, geomorphic channel units, and large woody debris), Determine the status of and trends in cross-sectional morphology, longitudinal gradient, and sinuosity of selected wadeable stream reaches. Between June 11 and 14, 2018, data were collected at Congaree National Park to characterize the in-stream and near-channel habitat within stream reaches on Cedar Creek (CONG001, CONG002, and CONG003) and McKenzie Creek (CONG004). These data, along with the analysis of remotely sensed geographic information system (GIS) data, are presented in this report to describe and compare the watershed-, reach-, and transect-scale characteristics of these four stream reaches to each other and to selected similar-sized stream reaches at Ocmulgee Mounds National Historical Park, Kennesaw Mountain National Battlefield Park, and Chattahoochee National Recreation Area. Surveyed stream reaches at Congaree NP were compared to those previously surveyed in other parks in order to provide regional context and aid in interpretation of results. edar Creek’s watershed (CONG001, CONG002, and CONG003) drains nearly 200 square kilometers (77.22 square miles [mi2]) of the Congaree River Valley Terrace complex and upper Coastal Plain to the north of the park (Shelley 2007a, 2007b). Cedar Creek’s watershed has low slope and is covered mainly by forests and grasslands. Cedar Creek is designated an “Outstanding Resource Water” by the state of South Carolina (S.C. Code Regs. 61–68 [2014] and S.C. Code Regs. 61–69 [2012]) from the boundary of the park downstream to Wise Lake. Cedar Creek ‘upstream’ (CONG001) is located just downstream (south) of the park’s Bannister Bridge canoe landing, which is located off Old Bluff Road and south of the confluence with Meyers Creek. Cedar Creek ‘middle’ and Cedar Creek ‘downstream’ (CONG002 and CONG003, respectively) are located downstream of Cedar Creek ‘upstream’ where Cedar Creek flows into the relatively flat backswamp of the Congaree River flood plain. Based on the geomorphic and land cover characteristics of the watershed, monitored reaches on Cedar Creek are likely to flood often and drain slowly. Flooding is more likely at Cedar Creek ‘middle’ and Cedar Creek ‘downstream’ than at Cedar Creek ‘upstream.’ This is due to the higher (relative to CONG001) connectivity between the channels of the lower reaches and their out-of-channel areas. Based on bed sediment characteristics, the heterogeneity of geomorphic channel units (GCUs) within each reach, and the abundance of large woody debris (LWD), in-stream habitat within each of the surveyed reaches on Cedar Creek (CONG001–003) was classified as ‘fair to good.’ Although, there is extensive evidence of animal activity...
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