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Journal articles on the topic 'Multiomic integration'

Author: Grafiati

Published: 16 November 2024

Last updated: 31 July 2025

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1

Ugidos, Manuel, Sonia Tarazona, José M. Prats-Montalbán, Alberto Ferrer, and Ana Conesa. "MultiBaC: A strategy to remove batch effects between different omic data types." Statistical Methods in Medical Research 29, no. 10 (2020): 2851–64. http://dx.doi.org/10.1177/0962280220907365.

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Diversity of omic technologies has expanded in the last years together with the number of omic data integration strategies. However, multiomic data generation is costly, and many research groups cannot afford research projects where many different omic techniques are generated, at least at the same time. As most researchers share their data in public repositories, different omic datasets of the same biological system obtained at different labs can be combined to construct a multiomic study. However, data obtained at different labs or moments in time are typically subjected to batch effects tha

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Blutt, Sarah E., Cristian Coarfa, Josef Neu, and Mohan Pammi. "Multiomic Investigations into Lung Health and Disease." Microorganisms 11, no. 8 (2023): 2116. http://dx.doi.org/10.3390/microorganisms11082116.

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Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics inv

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Ramos, Marcel, Ludwig Geistlinger, Sehyun Oh, et al. "Multiomic Integration of Public Oncology Databases in Bioconductor." JCO Clinical Cancer Informatics, no. 4 (October 2020): 958–71. http://dx.doi.org/10.1200/cci.19.00119.

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PURPOSE Investigations of the molecular basis for the development, progression, and treatment of cancer increasingly use complementary genomic assays to gather multiomic data, but management and analysis of such data remain complex. The cBioPortal for cancer genomics currently provides multiomic data from > 260 public studies, including The Cancer Genome Atlas (TCGA) data sets, but integration of different data types remains challenging and error prone for computational methods and tools using these resources. Recent advances in data infrastructure within the Bioconductor project enable a n

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Hatami, Elham, Hye-Won Song, Hongduan Huang, et al. "Integration of single-cell transcriptomic and chromatin accessibility on heterogenicity of human peripheral blood mononuclear cells utilizing microwell-based single-cell partitioning technology." Journal of Immunology 212, no. 1_Supplement (2024): 1508_5137. http://dx.doi.org/10.4049/jimmunol.212.supp.1508.5137.

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Abstract Single-cell RNA sequencing (scRNA-Seq) deepens our understanding of cellular development and heterogeneity. However, limitations exist in unraveling cell states and gene regulatory programs. Chromatin state profiles assess gene expression potential and offer insights into transcriptional regulation. Integrated with gene expression data, chromatin accessibility region (CAR) profiles establish fundamental gene regulatory logic for cell fate. ATAC-seq (Assay for Transposase-Accessible Chromatin using Sequencing) is a highly potent approach for profiling genome-wide CARs. To investigate t

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Antequera-González, Borja, Neus Martínez-Micaelo, Carlos Sureda-Barbosa, et al. "Specific Multiomic Profiling in Aortic Stenosis in Bicuspid Aortic Valve Disease." Biomedicines 12, no. 2 (2024): 380. http://dx.doi.org/10.3390/biomedicines12020380.

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Introduction and purpose: Bicuspid aortic valve (BAV) disease is associated with faster aortic valve degeneration and a high incidence of aortic stenosis (AS). In this study, we aimed to identify differences in the pathophysiology of AS between BAV and tricuspid aortic valve (TAV) patients in a multiomics study integrating metabolomics and transcriptomics as well as clinical data. Methods: Eighteen patients underwent aortic valve replacement due to severe aortic stenosis: 8 of them had a TAV, while 10 of them had a BAV. RNA sequencing (RNA-seq) and proton nuclear magnetic resonance spectroscop

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Silberberg, Gilad, Clare Killick-Cole, Yaron Mosesson, et al. "Abstract 854: A pharmaco-pheno-multiomic integration analysis of pancreatic cancer: A highly predictive biomarker model of biomarkers of Gemcitabine/Abraxane sensitivity and resistance." Cancer Research 83, no. 7_Supplement (2023): 854. http://dx.doi.org/10.1158/1538-7445.am2023-854.

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Abstract The overall survival of patients diagnosed with Pancreatic Cancer remains low. Initial responses to current therapeutic interventions are below 50%, leading to a high mortality rate shortly after diagnosis. To date, only a companion diagnostic, non-specific for pancreatic cancer, has been approved for this indication. A better understanding of the tumor cell biology and resistance mechanisms may shed light onto novel therapeutic targets that improve long-term outcome and improved patient stratification. In this study, we performed an exhaustive analysis to identify predictive biomarke

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Reem, El Kabbout, Abi Sleimen Antonella, Boucherat Olivier, Bonnet Sebastien, Provencher Steeve, and Potus Francois. "Multiomics Integration for Identifying Treatment Targets, Drug Development, and Diagnostic Designs in PAH." Advances in Pulmonary Hypertension 23, no. 2 (2025): 33–42. https://doi.org/10.21693/1933-088x-23.2.33.

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Unraveling the complexities of pulmonary arterial hypertension (PAH) is challenging due to its multifaceted nature, encompassing molecular, cellular, tissue, and organ-level alterations. The advent of omics technologies, including genomics, epigenomics, transcriptomics, metabolomics, and proteomics, has generated a vast array of public and nonpublic datasets from both humans and model organisms, opening new avenues for understanding PAH. However, the insights provided by individual omics datasets into the molecular mechanisms of PAH are inherently limited. In response, efforts are increasing

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Culley, Christopher, Supreeta Vijayakumar, Guido Zampieri, and Claudio Angione. "A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth." Proceedings of the National Academy of Sciences 117, no. 31 (2020): 18869–79. http://dx.doi.org/10.1073/pnas.2002959117.

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Metabolic modeling and machine learning are key components in the emerging next generation of systems and synthetic biology tools, targeting the genotype–phenotype–environment relationship. Rather than being used in isolation, it is becoming clear that their value is maximized when they are combined. However, the potential of integrating these two frameworks for omic data augmentation and integration is largely unexplored. We propose, rigorously assess, and compare machine-learning–based data integration techniques, combining gene expression profiles with computationally generated metabolic fl

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Pratapa, Aditya, Lydia Hernandez, Bassem Ben Cheikh, Niyati Jhaveri, and Arutha Kulasinghe. "Abstract 5503: Ultrahigh-plex spatial phenotyping of head and neck cancer tissue uncovers multiomic signatures of immunotherapy response." Cancer Research 84, no. 6_Supplement (2024): 5503. http://dx.doi.org/10.1158/1538-7445.am2024-5503.

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Abstract Background Targeted immune checkpoint inhibitors (ICI) with anti-PD-1/PD-L1 therapy offer durable treatment of mucosal head and neck squamous cell cancer (HNSCC), in both human papillomavirus-positive (HPV+) and negative (HPV-) patients. However, currently available biomarker signatures for targeted ICI therapies have limited predictive value. Our recent ultrahigh-plex profiling of HNSCC tissue with 100+ cancer hallmarks of tumor and immunobiology uncovered distinct spatial domains that serve as defining factors for clinical response and resistance. Methods Our unbiased analysis of wh

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Jamal, Sabri, Michael J. Wilson, Jean Teyssandier, et al. "Abstract 6296: Unlocking scalable and efficient multiomic analysis of 5- and 6-base genomes." Cancer Research 85, no. 8_Supplement_1 (2025): 6296. https://doi.org/10.1158/1538-7445.am2025-6296.

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We present a computational toolkit to analyze 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) Cytosine modifications at scale and describe its performance on a liquid biopsy dataset. Methylation data has diverse applications in cancer, including early-stage diagnosis through liquid biopsy, classification to guide treatment pathways, and prognosis. However, analyzing methylation data poses significant challenges. Many existing tools are difficult to use and struggle to scale as sample sizes grow. This lack of scalability makes standard tasks, such as identifying differentially methyla

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Signorelli, Mirko, Roula Tsonaka, Annemieke Aartsma-Rus, and Pietro Spitali. "Multiomic characterization of disease progression in mice lacking dystrophin." PLOS ONE 18, no. 3 (2023): e0283869. http://dx.doi.org/10.1371/journal.pone.0283869.

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Duchenne muscular dystrophy (DMD) is caused by genetic mutations leading to lack of dystrophin in skeletal muscle. A better understanding of how objective biomarkers for DMD vary across subjects and over time is needed to model disease progression and response to therapy more effectively, both in pre-clinical and clinical research. We present an in-depth characterization of disease progression in 3 murine models of DMD by multiomic analysis of longitudinal trajectories between 6 and 30 weeks of age. Integration of RNA-seq, mass spectrometry-based metabolomic and lipidomic data obtained in musc

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Silberberg, Gilad, Bandana Vishwakarama, Brandon Walling, et al. "Abstract 3907: A pheno-multiomic integration analysis of primary samples of acute myeloid leukemia reveals biomarkers of cytarabine resistance." Cancer Research 82, no. 12_Supplement (2022): 3907. http://dx.doi.org/10.1158/1538-7445.am2022-3907.

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Abstract The overall survival of patients diagnosed with Acute Myeloid Leukemia (AML) remains low. While initial responses to therapy are favorable, the duration of response is short and overcoming therapeutic resistance has proven difficult. A better understanding of the tumor cell biology and resistance mechanisms may shed light onto novel therapeutic targets that improve long-term outcome. In this study, we performed an exhaustive analysis to include deep tumor phenotyping, drug sensitivity profiling and comprehensive omic characterization. These datasets were included in integrative pharma

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Baldan-Martin, M., M. Azkargorta, A. M. Aransay, et al. "DOP08 A novel multiomic approach to unravel the mechanisms of action of biologics and tofacitinib in Inflammatory Bowel Disease." Journal of Crohn's and Colitis 18, Supplement_1 (2024): i85—i87. http://dx.doi.org/10.1093/ecco-jcc/jjad212.0048.

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Abstract Background Inflammatory bowel diseases (IBD), which includes Crohn´s disease (CD) and ulcerative colitis (UC), are complex and heterogeneous diseases characterized by a multifactorial etiology. IBD prevalence is increasing worldwide. The availability of diverse treatments with different mechanisms of action have revolutionized the ability to achieve clinical remission and endoscopic healing. The aim of this study was to achieve a deeper understanding of the mechanism of action and response to different IBD treatments using a multiomic approach. Methods We analysed the metabolome of se

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Guerrero-Sánchez, Víctor M., Cristina López-Hidalgo, María-Dolores Rey, María Ángeles Castillejo, Jesús V. Jorrín-Novo, and Mónica Escandón. "Multiomic Data Integration in the Analysis of Drought-Responsive Mechanisms in Quercus ilex Seedlings." Plants 11, no. 22 (2022): 3067. http://dx.doi.org/10.3390/plants11223067.

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The integrated analysis of different omic layers can provide new knowledge not provided by their individual analysis. This approach is also necessary to validate data and reveal post-transcriptional and post-translational mechanisms of gene expression regulation. In this work, we validated the possibility of applying this approach to non-model species such as Quercus ilex. Transcriptomics, proteomics, and metabolomics from Q. ilex seedlings subjected to drought-like conditions under the typical summer conditions in southern Spain were integrated using a non-targeted approach. Two integrative a

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Mokhtari, Amazigh, El Chérif Ibrahim, Arnaud Gloaguen, et al. "Using multiomic integration to improve blood biomarkers of major depressive disorder: a case-control study." eBioMedicine 113 (March 2025): 105569. https://doi.org/10.1016/j.ebiom.2025.105569.

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Liu, Hailong, Tao Jiang, and Xiaoguang Qiu. "Spatiotemporal multiomic landscape of human medulloblastoma at single cell resolution." Journal of Clinical Oncology 40, no. 16_suppl (2022): 2069. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.2069.

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2069 Background: Medulloblastoma is the most common malignant childhood tumor type with distinct molecular subgroups. While advances in the comprehensive treatment have been made, the mortality in the high-risk group is still very high, driven by an incomplete understanding of cellular diversity. Methods: We use single-nucleus RNA expression, chromatin accessibility and spatial transcriptomic profiling to generate an integrative multi-omic map in 40 human medulloblastomas spanning all molecular subgroups and human postnatal cerebella, which is supplemented by the bulk whole genome and RNA sequ

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Louca, Stilianos, Alyse K. Hawley, Sergei Katsev, et al. "Integrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone." Proceedings of the National Academy of Sciences 113, no. 40 (2016): E5925—E5933. http://dx.doi.org/10.1073/pnas.1602897113.

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Microorganisms are the most abundant lifeform on Earth, mediating global fluxes of matter and energy. Over the past decade, high-throughput molecular techniques generating multiomic sequence information (DNA, mRNA, and protein) have transformed our perception of this microcosmos, conceptually linking microorganisms at the individual, population, and community levels to a wide range of ecosystem functions and services. Here, we develop a biogeochemical model that describes metabolic coupling along the redox gradient in Saanich Inlet—a seasonally anoxic fjord with biogeochemistry analogous to ox

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Hu, Xiaohui, Masaya Ono, Nyam-Osor Chimge, et al. "Differential Kat3 Usage Orchestrates the Integration of Cellular Metabolism with Differentiation." Cancers 13, no. 23 (2021): 5884. http://dx.doi.org/10.3390/cancers13235884.

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The integration of cellular status with metabolism is critically important and the coupling of energy production and cellular function is highly evolutionarily conserved. This has been demonstrated in stem cell biology, organismal, cellular and tissue differentiation and in immune cell biology. However, a molecular mechanism delineating how cells coordinate and couple metabolism with transcription as they navigate quiescence, growth, proliferation, differentiation and migration remains in its infancy. The extreme N-termini of the Kat3 coactivator family members, CBP and p300, by far the least

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Wanchai, Visanu, Hongwei Xu, Cody Ashby, et al. "Single Nuclei Multiomic Profiling of Transcriptional and Chromatin Accessibility of Tumor Cells Underlines Extensive Cis-Regulatory Interaction during Multiple Myeloma Progression." Blood 144, Supplement 1 (2024): 1885. https://doi.org/10.1182/blood-2024-205344.

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Introduction Multiple myeloma (MM) is a complex hematological disease with high heterogeneity resulting from abnormal proliferation of plasma cells in bone marrow. The progression of the disease from Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), to MM involves multiple drivers and, moderately, by dynamic interactions of cis-regulatory elements in premalignant/malignant cells. Using single-nuclei multiome technology, the same-cell readouts of nucleus RNA sequencing (snRNA-seq) and Assay for Transposase-Accessible Chromatin sequencing (snATAC-seq)

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Angione, Claudio. "Human Systems Biology and Metabolic Modelling: A Review—From Disease Metabolism to Precision Medicine." BioMed Research International 2019 (June 9, 2019): 1–16. http://dx.doi.org/10.1155/2019/8304260.

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In cell and molecular biology, metabolism is the only system that can be fully simulated at genome scale. Metabolic systems biology offers powerful abstraction tools to simulate all known metabolic reactions in a cell, therefore providing a snapshot that is close to its observable phenotype. In this review, we cover the 15 years of human metabolic modelling. We show that, although the past five years have not experienced large improvements in the size of the gene and metabolite sets in human metabolic models, their accuracy is rapidly increasing. We also describe how condition-, tissue-, and p

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Zawistowski, Jon, Isai Salas-Gonzalez, Tia Tate, et al. "Abstract 6929: Inter- and intratumoral PIK3CA subclonal diversity in breast cancer contextualized by single-cell multiomics." Cancer Research 84, no. 6_Supplement (2024): 6929. http://dx.doi.org/10.1158/1538-7445.am2024-6929.

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Abstract Rare clonotypes within pre-cancerous tissues can drive progression to cancer. However, the evolution of rare clonotypes in tumors or normal tissue cannot be defined in the absence of single-cell resolution. At this single-cell level, multiomic interrogation across the Central Dogma of Biology provides enhanced power to reconstruct such evolutionary trajectories, defining the mutational profile, cell identify, and receptor expression within each subpopulation. Leveraging a multiomic approach, we aimed to define how different mutations in the same oncogenic driver observed in the same t

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Clark, Jeremy, Rachel Hurst, Mark Simon Winterbone, et al. "Urine Biomarkers for Prostate Cancer Diagnosis and Progression." Société Internationale d’Urologie Journal 2, no. 3 (2021): 159–70. http://dx.doi.org/10.48083/sawc9585.

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Prostate cancer (PCa) can be highly heterogeneous and multifocal, and accurate assessment of the volume, grade, and stage of PCa in situ is not a simple task. Urine has been investigated as a source of PCa biomarkers for over 70 years, and there is now strong evidence that analysis of urine could provide more accurate diagnosis and a better risk stratification that could aid clinical decisions regarding disease surveillance and treatment. Urine diagnostics is a developing area, moving towards multiomic biomarker integration for improved diagnostic performance. Urine tests developed by strong c

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Heck, Ashley, Hiromi Sato, Christine Kang, et al. "Abstract 1880: Advancing spatial discovery multiomics: Integration of a novel 1,000+ plex discovery proteome atlas with an 18,000+ plex whole transcriptome atlas for same-slide investigation of multiple cancer pathologies." Cancer Research 85, no. 8_Supplement_1 (2025): 1880. https://doi.org/10.1158/1538-7445.am2025-1880.

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Abstract Spatial multiomics at high plex represents a transformative approach to understanding complex biological systems. Whereas high plex spatial transcriptomics have transformed tissue analyses, spatial proteomics have been limited by low plex and lacking coverage of major biological pathways. Proteins, which represent the functional units of cellular response and activity, are essential for studying the heterogeneity of cancer and immune pathology. Furthermore, cellular responses to intrinsic and extrinsic stimuli are often driven by post-translational modifications of proteins. Enabling

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Azulay, A., Y. Aharoni Frutkoff, Y. Shimhlash, et al. "P1224 Predicting response to nutritional therapy in newly diagnosed children with Crohn’s Disease (CD) using multi-omics approach." Journal of Crohn's and Colitis 18, Supplement_1 (2024): i2172. http://dx.doi.org/10.1093/ecco-jcc/jjad212.1354.

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Abstract Background Background. One third of children with Crohn's disease (CD) will fail treatment with exclusive enteral nutrition (EEN) but predictors of response have been hitherto lacking. In this prospective cohort study, we aimed to use multiomic data to predict EEN response in treatment-naïve children with CD. Methods Methods. Children commenced on EEN at CD onset were followed through 8 weeks. Stool was collected for microbiome and metabolomics, and serum for metabolomics. Disease indices and clinical data were recorded. Targeted quantitative metabolomics approach was applied to analy

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Frétin, Marie, Amaury Gérard, Anne Ferlay, et al. "Integration of Multiomic Data to Characterize the Influence of Milk Fat Composition on Cantal-Type Cheese Microbiota." Microorganisms 10, no. 2 (2022): 334. http://dx.doi.org/10.3390/microorganisms10020334.

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A previous study identified differences in rind aspects between Cantal-type cheeses manufactured from the same skimmed milk, supplemented with cream derived either from pasture-raised cows (P) or from cows fed with maize silage (M). Using an integrated analysis of multiomic data, the present study aimed at investigating potential correlations between cream origin and metagenomic, lipidomic and volatolomic profiles of these Cantal cheeses. Fungal and bacterial communities of cheese cores and rinds were characterized using DNA metabarcoding at different ripening times. Lipidome and volatolome we

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Winders, Dafne Alves, Riley Graham, Xiangying Mao, et al. "Abstract 4411: Enhancing scalability and consistency in clinical multiomics via an optimized fixed cell ATAC-seq method." Cancer Research 84, no. 6_Supplement (2024): 4411. http://dx.doi.org/10.1158/1538-7445.am2024-4411.

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Abstract ATAC-seq has an emerging role in decoding mechanisms of gene regulation, offering valuable insights into pathology and treatment response in disease models. However, clinical adoption of ATAC-seq methods has been limited by logistical hurdles, including time-sensitive processing of fresh samples and compromised viability of cryopreserved cells. These constraints, compounded by changes in open chromatin regions (OCRs) following cryopreservation, introduce unintended bias and pose significant obstacles for the translational impact of ATAC-seq experiments. Here, we introduce an optimiz

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Li, Yiping, Brock C. Christensen, and Lucas A. Salas. "Abstract 5018: Multiomic integration of DNA methylation, DNA hydroxymethylation, and gene expression in clear cell renal cell carcinoma." Cancer Research 85, no. 8_Supplement_1 (2025): 5018. https://doi.org/10.1158/1538-7445.am2025-5018.

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Abstract Background: DNA methylation (5-methylcytosine -5mC) and DNA hydroxymethylation (5-hydroxymethylcytosine -5hmC) are critical epigenetic modifications for understanding gene expression in clear cell renal cell carcinoma (ccRCC). While 5mC and 5hmC modifications may influence promoter and enhancer regions differently, their distinct roles in gene regulation remain unclear. Integrating RNA sequencing (RNA-seq) data with 5mC and 5hmC analyses enables a multiomic understanding of gene regulation, revealing critical changes associated with ccRCC progression. This study integrates 5mC, 5hmC,

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Murphy, Charlie, Kate Thompson, Lubna Nousheen, Divya Rao, and Todd E. Druley. "A Multiomic, Single-Cell Measurable Residual Disease (scMRD) Assay for Phasing DNA Mutations and Surface Immunophenotypes." Blood 142, Supplement 1 (2023): 6055. http://dx.doi.org/10.1182/blood-2023-189360.

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The small population of cancerous cells that remain following treatment, known as measurable residual disease (MRD), is the major cause of relapse in acute myeloid leukemia (AML). Usually, these refractory cells have gained additional resistance mutations or changed their surface immunophenotypes in ways that preclude detection and phasing by current gold standard flow cytometry or bulk next-generation sequencing assays. For this reason, a multiomic single-cell MRD (scMRD) assay could offer a more comprehensive indicator of relapse and the potential for faster response. Here, we present a new

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Lysenkova Wiklander, Mariya, Gustav Arvidsson, Ignas Bunikis, et al. "A multiomic characterization of the leukemia cell line REH using short- and long-read sequencing." Life Science Alliance 7, no. 8 (2024): e202302481. http://dx.doi.org/10.26508/lsa.202302481.

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The B-cell acute lymphoblastic leukemia (ALL) cell line REH, with the t(12;21)ETV6::RUNX1translocation, is known to have a complex karyotype defined by a series of large-scale chromosomal rearrangements. Taken from a 15-yr-old at relapse, the cell line offers a practical model for the study of pediatric B-ALL. In recent years, short- and long-read DNA and RNA sequencing have emerged as a complement to karyotyping techniques in the resolution of structural variants in an oncological context. Here, we explore the integration of long-read PacBio and Oxford Nanopore whole-genome sequencing, IsoSeq

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Blandford, Emily, Jennifer Delegard, Andrew Hardigan, Aditya Mohan, Simon Gregory, and Anoop Patel. "EPCO-42. SINGLE-CELL MULTIOMIC ANALYSIS OF BRAIN METASTASES ACROSS MULTIPLE PRIMARY TUMOR TYPES." Neuro-Oncology 26, Supplement_8 (2024): viii11. http://dx.doi.org/10.1093/neuonc/noae165.0041.

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Abstract Brain metastases are the most common form of intracranial tumor in adults, however the prognosis remains dismal due to lack of effective treatments and limited understanding of the underlying physiology allowing them to thrive in the foreign cell type environment of the brain. Here we characterized the transcriptomic and epigenomic landscape of 35 human brain metastases obtained from surgical resection using combined scRNA-seq and ATAC-seq spanning the most prevalent primary tumor types including lung adenocarcinoma (n=16), melanoma (n=14), breast (n=10), and renal cell carcinoma (n=6

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Thompson, Kathryn, Benjamin Geller, Lubna Nousheen, et al. "A Multiomic, Single-Cell Measurable Residual Disease (scMRD) Assay for Simultaneous Assessment of DNA Mutations and Surface Immunophenotypes in Acute Myeloid Leukemia." Blood 144, Supplement 1 (2024): 6168. https://doi.org/10.1182/blood-2024-204025.

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The small population of cancerous cells that remain following treatment, known as measurable residual disease (MRD), is the major cause of relapse in acute myeloid leukemia (AML). Usually, these refractory cells have gained additional resistance mutations or changed their surface immunophenotypes in ways that preclude detection and phasing by current gold standard flow cytometry or bulk next-generation sequencing assays. For this reason, a multiomic single-cell MRD (scMRD) assay could offer a more comprehensive indicator of relapse and the potential for faster response. Here, we present a new

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Gao, Quanxin, Hao Huang, Peimin Liu, et al. "Integration of Gut Microbiota with Transcriptomic and Metabolomic Profiling Reveals Growth Differences in Male Giant River Prawns (Macrobrachium rosenbergii)." Animals 14, no. 17 (2024): 2539. http://dx.doi.org/10.3390/ani14172539.

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The giant freshwater prawn (GFP; Macrobrachium rosenbergii), a tropical species cultured worldwide, has high market demand and economic value. Male GFP growth varies considerably; however, the mechanisms underlying these growth differences remain unclear. In this study, we collected gut and hemolymphatic samples of large (ML), medium (MM), and small (MS) male GFPs and used the 16S rRNA sequencing and liquid chromatography–mass spectrometry-based metabolomic methods to explore gut microbiota and metabolites associated with GFP growth. The dominant bacteria were Firmicutes and Proteobacteria; hi

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Graham, Zachary A., Jacob A. Siedlik, Carlos A. Toro, Lauren Harlow, and Christopher P. Cardozo. "Boldine Alters Serum Lipidomic Signatures after Acute Spinal Cord Transection in Male Mice." International Journal of Environmental Research and Public Health 20, no. 16 (2023): 6591. http://dx.doi.org/10.3390/ijerph20166591.

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Traumatic spinal cord injury (SCI) results in wide-ranging cellular and systemic dysfunction in the acute and chronic time frames after the injury. Chronic SCI has well-described secondary medical consequences while acute SCI has unique metabolic challenges as a result of physical trauma, in-patient recovery and other post-operative outcomes. Here, we used high resolution mass spectrometry approaches to describe the circulating lipidomic and metabolomic signatures using blood serum from mice 7 d after a complete SCI. Additionally, we probed whether the aporphine alkaloid, boldine, was able to

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Rubinstein, Samuel M., and Jeremy L. Warner. "CancerLinQ: Origins, Implementation, and Future Directions." JCO Clinical Cancer Informatics, no. 2 (December 2018): 1–7. http://dx.doi.org/10.1200/cci.17.00060.

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Rapid-learning health systems have been proposed as a potential solution to the problem of quality in medicine, by leveraging data generated from electronic health systems in near-real time to improve quality and reduce cost. Given the complex, dynamic nature of cancer care, a rapid-learning health system offers large potential benefits to oncology practice. In this article, we review the rationale for developing a rapid-learning health system for oncology and describe the sequence of events that led to the development of ASCO’s CancerLinQ (Cancer Learning Intelligence Network for Quality) ini

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Abdurahiman, S., J. Sabino, S. Verstockt, et al. "P0030 Multiomic Analysis Reveals Three Distinct subtypes within Perianal Crohn’s Disease, Independent of Concomitant Proctitis." Journal of Crohn's and Colitis 19, Supplement_1 (2025): i373—i375. https://doi.org/10.1093/ecco-jcc/jjae190.0204.

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Abstract Background Perianal fistulisation (pCD) affects ~20% of Crohn’s disease (CD) patients and often requires combined medical and surgical management. Despite significant progress in management of luminal CD, pCD continues to pose a major unmet need, emphasizing the importance of understanding the molecular and environmental drivers and to discover new therapeutic targets. Methods Paired biopsies from the fistula tract and rectal orifice of 81 pCD patients underwent 16S rRNA and RNA sequencing, generating multiomic profiles for both tissues. We applied Multiomics Factor Analysis (MOFA), t

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O’Hara, Eóin, Megan Dubois, Gabriel O. Ribeiro, and Robert J. Gruninger. "PSIX-18 Multiomic analysis to identify host and microbiome contributions to digestibility in beef cattle." Journal of Animal Science 102, Supplement_3 (2024): 734–35. http://dx.doi.org/10.1093/jas/skae234.827.

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Abstract This study evaluated beef heifers selected for high (efficient) or low (inefficient) digestible fiber intake (DFI). Initial analysis showed that high DFI animals had reduced methane production versus low-DFI under a high forage diet. Using the same cohort of animals maintained on a further 4 diets of varying forage:concentrate ratios, we employed multi-kingdom amplicon sequencing and metagenome shotgun sequencing of rumen digesta and feces alongside RNA sequencing of rumen epimural samples to evaluate the compositional and functional interplay between different microbial groups, and t

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Harris, Alexandra R., Huaitian Liu, Brittany Jenkins-Lord, et al. "Abstract C044: Investigation of breast tumor biology and microenvironment in women of African descent using a single cell multiomic approach." Cancer Epidemiology, Biomarkers & Prevention 32, no. 12_Supplement (2023): C044. http://dx.doi.org/10.1158/1538-7755.disp23-c044.

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Abstract Women of African descent are at an increased risk of developing and dying from aggressive subtypes of breast cancer. A connection between aggressive disease and Western Sub-Saharan African ancestry has been postulated, but it remains largely unknown to what extent breast cancer in Africa is reminiscent of breast cancer in U.S. African American (AA) women who experience disproportionately high mortality rates. We performed ATAC- and RNA-sequencing on 9 human triple-negative breast cancer cell lines of U.S. origin and discovered that African ancestry influences the chromatin landscape,

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Karasarides, Maria, Alexandria P. Cogdill, Paul B. Robbins, et al. "Hallmarks of Resistance to Immune-Checkpoint Inhibitors." Cancer Immunology Research 10, no. 4 (2022): 372–83. http://dx.doi.org/10.1158/2326-6066.cir-20-0586.

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Abstract Immune-checkpoint inhibitors (ICI), although revolutionary in improving long-term survival outcomes, are mostly effective in patients with immune-responsive tumors. Most patients with cancer either do not respond to ICIs at all or experience disease progression after an initial period of response. Treatment resistance to ICIs remains a major challenge and defines the biggest unmet medical need in oncology worldwide. In a collaborative workshop, thought leaders from academic, biopharma, and nonprofit sectors convened to outline a resistance framework to support and guide future immune-

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Godbole, Shweta, Hannah Voss, Simon Schlumbohm, et al. "MDB-19. MULTIOMIC PROFILING OF MEDULLOBLASTOMA REVEALS SUBTYPE-SPECIFIC TARGETABLE ALTERATIONS AT THE PROTEOME AND N-GLYCAN LEVEL." Neuro-Oncology 25, Supplement_1 (2023): i66. http://dx.doi.org/10.1093/neuonc/noad073.252.

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Abstract Medulloblastomas (MBs) are malignant pediatric brain tumors which are clinically and histologically very heterogeneous. Epigenomic and transcriptomic analyses have advanced the understanding of these tumors and four main molecular subgroups – which themselves comprise several subtypes- have been defined: WNT-activated MB, Sonic hedgehog (SHH)-activated MB, Group3 and Group4 MB. Despite tremendous advances in classification and stratification, the pathogenesis of subtypes is still poorly understood and there is still a lack of targeted therapies. In contrast to nucleic acids, proteins

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Irineu, Luiz Eduardo Souza da Silva, Cleiton de Paula Soares, Tatiane Sanches Soares, et al. "Multiomic Approaches Reveal Hormonal Modulation and Nitrogen Uptake and Assimilation in the Initial Growth of Maize Inoculated with Herbaspirillum seropedicae." Plants 12, no. 1 (2022): 48. http://dx.doi.org/10.3390/plants12010048.

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Herbaspirillum seropedicae is an endophytic bacterium that can fix nitrogen and synthesize phytohormones, which can lead to a plant growth-promoting effect when used as a microbial inoculant. Studies focused on mechanisms of action are crucial for a better understanding of the bacteria-plant interaction and optimization of plant growth-promoting response. This work aims to understand the underlined mechanisms responsible for the early stimulatory growth effects of H. seropedicae inoculation in maize. To perform these studies, we combined transcriptomic and proteomic approaches with physiologic

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Dadey, Rebekah E., Ruxuan Li, Jake Griner, et al. "Multiomics identifies tumor-intrinsic SREBP1 driving immune exclusion in hepatocellular carcinoma." Journal for ImmunoTherapy of Cancer 13, no. 6 (2025): e011537. https://doi.org/10.1136/jitc-2025-011537.

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Immune checkpoint inhibitors (ICI) have improved patient outcomes in hepatocellular carcinoma (HCC); however, most patients do not experience durable benefit. The non-T cell-inflamed tumor microenvironment, characterized by limited CD8+T-cell infiltration, reduced dendritic cell function, and low interferon-γ-associated gene expression, is associated with a lower likelihood of response to ICI. To nominate new therapeutic targets for overcoming ICI resistance in HCC, we conducted a large-scale multiomic analysis on 900+human specimens (RNA sequencing (RNA-seq), proteomics) and 31 tumor single-c

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Maamari, Dimitri J., Roukoz Abou-Karam, and Akl C. Fahed. "Polygenic Risk Scores in Human Disease." Clinical Chemistry 71, no. 1 (2025): 69–76. https://doi.org/10.1093/clinchem/hvae190.

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Abstract Background Polygenic risk scores (PRS) are measures of genetic susceptibility to human health traits. With the advent of large data repositories combining genetic data and phenotypic information, PRS are providing valuable insights into the genetic architecture of complex diseases and are transforming the landscape of precision medicine. Content PRS have emerged as tools with clinical utility in human disease. Herein, details on how to develop PRS are provided, followed by 5 areas in which they can be used to improve human health: (a) augmenting risk prediction, (b) refining diagnosis

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Gagler, Dylan C., Hussein Ghamlouch, Di Zhang, et al. "A Multiomic Analysis of Waldenstrom's Macroglobulinemia Identifies Three Subtypes of Disease Based on Impaired Plasma Cell Differentiation." Blood 144, Supplement 1 (2024): 857. https://doi.org/10.1182/blood-2024-210654.

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Introduction Waldenstrom's macroglobulinemia (WM) is a lymphoplasmacytic lymphoma which recent DNA methylation studies have shown to exhibit multiple phenotypes. To enhance disease classification and explore the features and potential mechanisms underlying these subtypes, we performed a single-cell (sc) multiomic analysis on a series of MYD88 mutated WM cases, complemented by bulk RNA-seq and whole genome sequencing (WGS). Methods Single-cell multiomic analysis was performed on flow sorted CD19+/CD3- mature B-cells from 13 MYD88-mutated WM patients and was analyzed alongside reference B-cell p

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Das, Souvik, Suparna Mazumder, Neyaz Alam, et al. "Precision Oncology in the Era of Genomics and Artificial Intelligence." Journal of Current Oncological Trends 1, no. 1 (2024): 22–30. https://doi.org/10.4103/jcot.jcot_3_23.

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Abstract Cancer patient care classically represents proper diagnosis, designing appropriate therapeutics and clinical management protocols. Concept of precision medicine emerged in conjuncture to personalized medicine when subpopulations reasonably differ in disease risks, prognosis, and treatment response due to interpersonal differences in disease biology. Precision oncology aims to tailor medical decisions and interventions to optimize clinical guidance on survival benefits or quality of life for each patient by utilizing person’s characteristics such as clinicopathology, mutational load, b

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Bulusu, Krishna C., Jake Cohen-Setton, Ioannis Kagiampakis, et al. "Abstract 3531: PRESSNET: Patient stratification and biomarker discovery using multi-modal knowledge graph framework." Cancer Research 84, no. 6_Supplement (2024): 3531. http://dx.doi.org/10.1158/1538-7445.am2024-3531.

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Abstract Background: Multiomics data is critical to obtain a near comprehensive picture of disease progression and drug response. In addition, the generation of response and survival biomarkers, and the segmentation of patients into subtypes with distinct, actionable ‘omic signatures and survival trajectories, is vital for personalised medicine research and successful trial design. However, as the volume and diversity of data increases, so too does the challenge of effective multiomic data integration. Knowledge graphs (KGs) can capture heterogeneous data and relationships between entities in

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Harris, Alexandra R., Huaitian Liu, Brittany Jenkins-Lord, et al. "Abstract 6108: Investigation of breast tumor biology and microenvironment in women of African descent using a single cell multiomic approach." Cancer Research 84, no. 6_Supplement (2024): 6108. http://dx.doi.org/10.1158/1538-7445.am2024-6108.

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Abstract Women of African descent are at an increased risk of developing and dying from aggressive subtypes of breast cancer. A connection between aggressive disease and Western Sub-Saharan African ancestry has been postulated, but it remains largely unknown to what extent breast cancer in Africa is reminiscent of breast cancer in U.S. African American (AA) women who experience disproportionately high mortality rates. We performed ATAC- and RNA-sequencing on 9 human triple-negative breast cancer cell lines of U.S. origin and discovered that African ancestry influences the chromatin landscape,

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Ashuach, Tal, Mariano I. Gabitto, Rohan V. Koodli, Giuseppe-Antonio Saldi, Michael I. Jordan, and Nir Yosef. "MultiVI: deep generative model for the integration of multimodal data." Nature Methods, June 29, 2023. http://dx.doi.org/10.1038/s41592-023-01909-9.

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AbstractJointly profiling the transcriptome, chromatin accessibility and other molecular properties of single cells offers a powerful way to study cellular diversity. Here we present MultiVI, a probabilistic model to analyze such multiomic data and leverage it to enhance single-modality datasets. MultiVI creates a joint representation that allows an analysis of all modalities included in the multiomic input data, even for cells for which one or more modalities are missing. It is available at scvi-tools.org.

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Smith, Jennifer R., Marek A. Tutaj, Jyothi Thota, et al. "Standardized pipelines support and facilitate integration of diverse datasets at the Rat Genome Database." Database 2025 (2025). https://doi.org/10.1093/database/baae132.

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Abstract The Rat Genome Database (RGD) is a multispecies knowledgebase which integrates genetic, multiomic, phenotypic, and disease data across 10 mammalian species. To support cross-species, multiomics studies and to enhance and expand on data manually extracted from the biomedical literature by the RGD team of expert curators, RGD imports and integrates data from multiple sources. These include major databases and a substantial number of domain-specific resources, as well as direct submissions by individual researchers. The incorporation of these diverse datatypes is handled by a growing lis

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Licht, Philipp. "Multiomic Data Integration Reveals Microbial Drivers of Aetiopathogenesis in Mycosis Fungoides." September 19, 2023. https://doi.org/10.5281/zenodo.8359552.

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WANG, Ruohan, Jianping WANG, and Shuaicheng Li. "Probabilistic tensor decomposition extracts better latent embeddings from single-cell multiomic data." May 2, 2023. https://doi.org/10.5281/zenodo.7886413.

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These are source codes, example data, and example usage of SCOIT (https://github.com/deepomicslab/SCOIT).  SCOIT is an implementation of a probabilistic tensor decomposition framework for single-cell multiomic data integration. SCOIT accepts the input of datasets from multiple omics, with missing values allowed. The example data contains the eight single-cell multiomic datasets (sc-GEM, SNARE-seq_adult_mouse, SNARE-seq_neonatal_mouse, sci-CAR, PEA-STA, CITE-seq, SCoPE2, scNMT-seq), which are used in the manuscript. The example usage contains codes to analyse the eight datasets with SCOIT.

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