Ostroverkhova, D., Przytycka, T. M. & Panchenko, A. R. Cancer driver mutations: predictions and reality. Trends Mol. Med. 29, 554–566 (2023).

Article  CAS  PubMed  Google Scholar 

Kustatscher, G. et al. Understudied proteins: opportunities and challenges for functional proteomics. Nat. Methods 19, 774–779 (2022).

Article  CAS  PubMed  Google Scholar 

Dinstag, G. & Shamir, R. PRODIGY: personalized prioritization of driver genes. Bioinformatics 36, 1831–1839 (2020).

Article  CAS  PubMed  Google Scholar 

Leiserson, M. D. M. et al. Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat. Genet. 47, 106–114 (2015).

Article  CAS  PubMed  Google Scholar 

Sharan, R., Ulitsky, I. & Shamir, R. Network-based prediction of protein function. Mol. Syst. Biol. 3, 88 (2007).

Article  PubMed  PubMed Central  Google Scholar 

Kim, M. et al. A protein interaction landscape of breast cancer. Science 374, eabf3066 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Swaney, D. L. et al. A protein network map of head and neck cancer reveals PIK3CA mutant drug sensitivity. Science 374, eabf2911 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Quackenbush, J. Microarrays—guilt by association. Science 302, 240–241 (2003).

Article  CAS  PubMed  Google Scholar 

Yanai, I. et al. Similar gene expression profiles do not imply similar tissue functions. Trends Genet. 22, 132–138 (2006).

Article  CAS  PubMed  Google Scholar 

Wang, J. et al. Proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Mol. Cell. Proteomics 16, 121–134 (2017).

Article  CAS  PubMed  Google Scholar 

Ribeiro, D. M., Ziyani, C. & Delaneau, O. Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis. Commun. Biol. 5, 876 (2022).

Article  Google Scholar 

Kustatscher, G. et al. Co-regulation map of the human proteome enables identification of protein functions. Nat. Biotechnol. 37, 1361–1371 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wu, L. et al. Variation and genetic control of protein abundance in humans. Nature 499, 79–82 (2013).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lapek, J. D. Jr et al. Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities. Nat. Biotechnol. 35, 983–989 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li, Y. et al. Proteogenomic data and resources for pan-cancer analysis. Cancer Cell 41, 1397–1406 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhu, H. et al. Proteomics of adjacent-to-tumor samples uncovers clinically relevant biological events in hepatocellular carcinoma. Natl Sci. Rev. 10, nwad167 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Obayashi, T. & Kinoshita, K. Rank of correlation coefficient as a comparable measure for biological significance of gene coexpression. DNA Res. 16, 249–260 (2009).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Huttlin, E. L. et al. Dual proteome-scale networks reveal cell-specific remodeling of the human interactome. Cell 184, 3022–3040 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Luck, K. et al. A reference map of the human binary protein interactome. Nature 580, 402–408 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Oughtred, R. et al. The BioGRID database: a comprehensive biomedical resource of curated protein, genetic, and chemical interactions. Protein Sci. 30, 187–200 (2021).

Article  CAS  PubMed  Google Scholar 

Szklarczyk, D. et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 49, D605–D612 (2021).

Article  CAS  PubMed  Google Scholar 

Tsitsiridis, G. et al. CORUM: the comprehensive resource of mammalian protein complexes—2022. Nucleic Acids Res. 51, D539–D545 (2023).

Article  CAS  PubMed  Google Scholar 

Shi, Z., Derow, C. K. & Zhang, B. Co-expression module analysis reveals biological processes, genomic gain, and regulatory mechanisms associated with breast cancer progression. BMC Syst. Biol. 4, 74 (2010).

Article  PubMed  PubMed Central  Google Scholar 

Barabási, A.-L. & Oltvai, Z. N. Network biology: understanding the cell’s functional organization. Nat. Rev. Genet. 5, 101–113 (2004).

Article  PubMed  Google Scholar 

Shi, Z., Wang, J. & Zhang, B. NetGestalt: integrating multidimensional omics data over biological networks. Nat. Methods 10, 597–598 (2013).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Knijnenburg, T. A., Bismeijer, T., Wessels, L. F. A. & Shmulevich, I. A multilevel pan-cancer map links gene mutations to cancer hallmarks. Chin. J. Cancer 34, 439–449 (2015).

Article  CAS  PubMed  Google Scholar 

Chen, Y., Verbeek, F. J. & Wolstencroft, K. Establishing a consensus for the hallmarks of cancer based on gene ontology and pathway annotations. BMC Bioinformatics 22, 178 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Chen, X. & Cubillos-Ruiz, J. R. Endoplasmic reticulum stress signals in the tumour and its microenvironment. Nat. Rev. Cancer 21, 71–88 (2021).

Article  CAS  PubMed  Google Scholar 

Vasaikar, S. et al. Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities. Cell 177, 1035–1049 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang, B. et al. Proteogenomic characterization of human colon and rectal cancer. Nature 513, 382–387 (2014).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Giacinti, C. & Giordano, A. RB and cell cycle progression. Oncogene 25, 5220–5227 (2006).

Article  CAS  PubMed