Integrative multi-omics approaches in cancer research: from biological networks to clinical subtypes

PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer

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WGCNA: an R package for weighted correlation network analysis

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STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

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Comprehensive Integration of Single-Cell Data

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Evaluation of Factors Related to Late Recurrence - Later than 10 Years after the Initial Treatment - in Primary Breast Cancer

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Comprehensive molecular portraits of human breast tumours

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Comprehensive molecular characterization of human colon and rectal cancer

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Integrated genomic analyses of ovarian carcinoma

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Comprehensive molecular characterization of gastric adenocarcinoma

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The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups

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Integrated genomic characterization of endometrial carcinoma

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Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia

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Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples

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Comprehensive molecular characterization of clear cell renal cell carcinoma

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A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes

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Patterns of somatic mutation in human cancer genomes

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Similarity network fusion for aggregating data types on a genomic scale

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Integrated genomic characterization of pancreatic ductal adenocarcinoma

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Comparing protein abundance and mRNA expression levels on a genomic scale

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Proteogenomics connects somatic mutations to signalling in breast cancer

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Integrative single-cell analysis

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Metabolite profiling identifies a key role for glycine in rapid cancer cell proliferation

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Genomic and transcriptional aberrations linked to breast cancer pathophysiologies

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The transcriptional network for mesenchymal transformation of brain tumours

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Intertumoral Heterogeneity within Medulloblastoma Subgroups

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Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer

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From genomics to proteomics

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Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE

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Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine

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Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis

Shen, R., Olshen, A. B., & Ladanyi, M. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp543 · Cited by 849 · see citing works

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

Gillette, M. A., Satpathy, S., Cao, S., Dhanasekaran, S. M., Vasaikar, S. V., Krug, K., Petralia, F., Li, Y., Liang, W.-W., Reva, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.013 · Cited by 820 · see citing works

An Interactive Resource to Identify Cancer Genetic and Lineage Dependencies Targeted by Small Molecules

Basu, A. B., Bodycombe, N. E., Cheah, J. H., Price, E. V., Liu, K., Schaefer, G. I., Ebright, R. Y., Stewart, M. L., Ito, D., Wang, S. Y., et al. (2013) · Cell · doi:10.1016/j.cell.2013.08.003 · Cited by 820 · see citing works

Accumulation of driver and passenger mutations during tumor progression

Božić, I., Tibor Antal, A., Ohtsuki, H., Carter, H. K., Kim, D., Chen, S., Karchin, R., Kinzler, K. W., Vogelstein, B., & Nowak, M. A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1010978107 · Cited by 790 · see citing works

Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM

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An Extensive MicroRNA-Mediated Network of RNA-RNA Interactions Regulates Established Oncogenic Pathways in Glioblastoma

Sumazin, P., Yang, X., Chiu, H., Chung, W., Iyer, A. P., Llobet‐Navàs, D., Rajbhandari, P., Bansal, M., Guarnieri, P., Silva, J., et al. (2011) · Cell · doi:10.1016/j.cell.2011.09.041 · Cited by 692 · see citing works

The mTORC1 Pathway Stimulates Glutamine Metabolism and Cell Proliferation by Repressing SIRT4

Csibi, A., Fendt, S.-M., Li, C., Poulogiannis, G., Choo, A. Y., Chapski, D. J., Jeong, S. M., Dempsey, J. M., Parkhitko, A., Morrison, T., et al. (2013) · Cell · doi:10.1016/j.cell.2013.04.023 · Cited by 586 · see citing works

Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis

Shen, R., Olshen, A. B., & Ladanyi, M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp659 · Cited by 566 · see citing works

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

Lai, Z., Tsugawa, H., Wohlgemuth, G., Mehta, S. S., Mueller, M. R., Zheng, Y., Ogiwara, A., Meissen, J. K., Showalter, M. R., Takeuchi, K., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4512 · Cited by 564 · see citing works

Extensions of Sparse Canonical Correlation Analysis with Applications to Genomic Data

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Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

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Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy

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Genotyping and Genomic Profiling of Non–Small-Cell Lung Cancer: Implications for Current and Future Therapies

Li, T., Kung, H., Mack, P. C., & Gandara, D. R. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.45.3753 · Cited by 515 · see citing works

FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry

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A module of negative feedback regulators defines growth factor signaling

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Pattern discovery and cancer gene identification in integrated cancer genomic data

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Synthetic lethal screen identification of chemosensitizer loci in cancer cells

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Synthetic lethality as an engine for cancer drug target discovery

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Proteogenomics of Non-smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression

Chen, Y.-J., Roumeliotis, T. I., Chang, Y.-H., Chen, C.-T., Han, C.-L., Lin, M.-H., Chen, H.-W., Chang, G.-C., Chang, Y.-L., Wu, C.-T., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.012 · Cited by 382 · see citing works

Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine

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A review on mass spectrometry-based quantitative proteomics: Targeted and data independent acquisition

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Target discovery

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Bayesian consensus clustering

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A non-negative matrix factorization method for detecting modules in heterogeneous omics multi-modal data

Yang, Z., & Michailidis, G. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btv544 · Cited by 295 · see citing works

Proteogenomic Characterization of Human Early-Onset Gastric Cancer

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NEMO: cancer subtyping by integration of partial multi-omic data

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Quantitative proteomics: challenges and opportunities in basic and applied research

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SALMON: survival analysis learning with multi-omics neural networks on breast cancer

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A dream of single-cell proteomics

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A Technical Assessment of the Utility of Reverse Phase Protein Arrays for the Study of the Functional Proteome in Non-microdissected Human Breast Cancers

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Quantifying the Role of Angiogenesis in Malignant Progression of Gliomas: In Silico Modeling Integrates Imaging and Histology

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Interplay of transcriptomics and proteomics

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Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification

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Bayesian correlated clustering to integrate multiple datasets

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Identification of Optimal Drug Combinations Targeting Cellular Networks: Integrating Phospho-Proteomics and Computational Network Analysis

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An omics perspective on drug target discovery platforms

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Defining principles of combination drug mechanisms of action

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Validating cancer drug targets

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Model‐driven multi‐omic data analysis elucidates metabolic immunomodulators of macrophage activation

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PINSPlus: a tool for tumor subtype discovery in integrated genomic data

Nguyen, H., Shrestha, S., Drăghici, S., & Nguyen, T. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty1049 · Cited by 140 · see citing works

Identification of Druggable Cancer Driver Genes Amplified across TCGA Datasets

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Integrated genomic analyses of ovarian carcinoma

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The glucose‐deprivation network counteracts lapatinib‐induced toxicity in resistant ErbB2‐positive breast cancer cells

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iOmicsPASS: network-based integration of multiomics data for predictive subnetwork discovery

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Integrative genomics identifies a convergent molecular subtype that links epigenomic with transcriptomic differences in autism

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Multiview learning for understanding functional multiomics

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Bayesian Inference of Signaling Network Topology in a Cancer Cell Line

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Patient-specific data fusion defines prognostic cancer subtypes

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Evaluation of integrative clustering methods for the analysis of multi-omics data

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Combined experimental and computational analysis of DNA damage signaling reveals context‐dependent roles for Erk in apoptosis and G1/S arrest after genotoxic stress

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Mechanistic patient-specific predictive correlation of tumor drug response with microenvironment and perfusion measurements

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Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

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Understanding resistance to targeted cancer drugs through loss of function genetic screens

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Systems Biology: Confronting the Complexity of Cancer

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Mapping Cellular Coordinates through Advances in Spatial Transcriptomics Technology.

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MONET: Multi-omic module discovery by omic selection

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Mechanisms of Macromolecular Interactions Mediated by Protein Intrinsic Disorder

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Multiomics profiling of paired primary and recurrent glioblastoma patient tissues

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Single-Cell Toolkits Opening a New Era for Cell Engineering

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Inferences of Individual Drug Response-Related Long Non-coding RNAs Based on Integrating Multi-omics Data in Breast Cancer

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Advancements and challenges in triple-negative breast cancer: a comprehensive review of therapeutic and diagnostic strategies

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Multi-OMICS approaches in cancer biology: New era in cancer therapy

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