Cancer proteogenomics: current impact and future prospects
Open accessAbstract
Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.
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Recent advances in proteomics through the maturation of several MS techniques have enabled the introduction of proteogenomic approaches that can integrate genomic data with proteomics and information on post-translational modifications.
“Recent advances in proteomics through the maturation of several MS techniques have enabled the introduction of proteogenomic approaches that can integrate genomic data with proteomics and information on post-translational modifications [89].”
From Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer (2024) · cites this paper as [89]
The Abstract (page unavailable) describes LC-MS/MS-based proteomics measuring proteins and post-translational modifications and relating them to genomic changes; Computational methods and tools describes linking genomic and proteomic data. The cited passages do not establish the more specific historical claim that maturation of several MS techniques enabled the introduction of proteogenomic approaches. (LLM, conf=0.83)
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Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
Self-citationSTAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458 · see citing works
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895 · see citing works
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179 · see citing works
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849 · see citing works
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556 · see citing works
The NIST Definition of Cloud Computing
Mell, P., & Grance, T. (2011) · doi:10.6028/nist.sp.800-145 · Cited by 15,338 · see citing works
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855 · see citing works
Slamon, D. J., Leyland-Jones, B., Shak, S., Fuchs, H., Paton, V., Bajamonde, A., Fleming, T., Eiermann, W., Wolter, J., Pegram, M., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200103153441101 · Cited by 11,500 · see citing works
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,216 · see citing works
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658 · see citing works
The Perseus computational platform for comprehensive analysis of (prote)omics data
Tyanova, S., Temu, T., Sinitcyn, P. G., Carlson, A., Hein, M. Y., Geiger, T., Mann, M., & Cox, J. (2016) · Nature Methods · doi:10.1038/nmeth.3901 · Cited by 7,977 · see citing works
Van der Auwera, G. A., Carneiro, M. O., Hartl, C., Poplin, R., del Angel, G., Levy‐Moonshine, A., Jordan, T., Shakir, K., Roazen, D., Thibault, J., et al. (2013) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1110s43 · Cited by 6,687 · see citing works
Comprehensive molecular characterization of gastric adenocarcinoma
The Cancer Genome Atlas Research Network (2014) · Nature · doi:10.1038/nature13480 · Cited by 6,498 · see citing works
Comprehensive molecular profiling of lung adenocarcinoma
The Cancer Genome Atlas Research Network (2014) · Nature · doi:10.1038/nature13385 · Cited by 5,732 · see citing works
The Somatic Genomic Landscape of Glioblastoma
Brennan, C. W., Verhaak, R. G. W., McKenna, A., Campos, B., Noushmehr, H., Salama, S. R., Zheng, S., Chakravarty, D., Sanborn, J. Z., Berman, S. H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.09.034 · Cited by 5,016 · see citing works
VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencingPreprint
Koboldt, D. C., Zhang, Q., Larson, D. E., Shen, D., McLellan, M. D., Lin, L., Miller, C. A., Mardis, E. R., Ding, L., & Wilson, R. K. (2012) · Genome Research · doi:10.1101/gr.129684.111 · Cited by 4,822 · see citing works
Self-citationSkyline: an open source document editor for creating and analyzing targeted proteomics experiments
MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G. L., Frewen, B., Kern, R., Tabb, D. L., Liebler, D. C., & MacCoss, M. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq054 · Cited by 4,697 · see citing works
The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
Tyanova, S., Temu, T., & Cox, J. (2016) · Nature Protocols · doi:10.1038/nprot.2016.136 · Cited by 4,691 · see citing works
Coming of age: ten years of next-generation sequencing technologies
Goodwin, S., McPherson, J. D., & McCombie, W. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.49 · Cited by 4,352 · see citing works
Five-Year Follow-up of Patients Receiving Imatinib for Chronic Myeloid Leukemia
Druker, B. J., Guilhot, F., O’Brien, S. G., Gathmann, I., Kantarjian, H. M., Gattermann, N., Deininger, M. W., Silver, R. T., Goldman, J. M., Stone, R. M., et al. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa062867 · Cited by 3,474 · see citing works
WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs
Liao, Y., Wang, J., Jaehnig, E. J., Shi, Z., & Zhang, B. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz401 · Cited by 3,144 · see citing works
Self-citationCoudray, N., Ocampo, P. S., Sakellaropoulos, T., Narula, N., Snuderl, M., Fenyö, D., Moreira, A. L., Razavian, N., & Tsirigos, A. (2018) · Nature Medicine · doi:10.1038/s41591-018-0177-5 · Cited by 2,930 · see citing works
RSeQC: quality control of RNA-seq experiments
Wang, L., Wang, S., & Li, W. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts356 · Cited by 2,813 · see citing works
A survey of best practices for RNA-seq data analysis
Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Szcześniak, M. W., Gaffney, D. J., Elo, L. L., Zhang, X., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0881-8 · Cited by 2,794 · see citing works
Improved Overall Survival in Melanoma with Combined Dabrafenib and Trametinib
Robert, C., Karaszewska, B., Schachter, J., Rutkowski, P. L., Mackiewicz, A. A., Stroyakovskiy, D., Lichinitser, M., Dummer, R., Grange, F., Mortier, L., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1412690 · Cited by 2,698 · see citing works
MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry–based proteomics
Kong, A. T., Leprevost, F. D. V., Avtonomov, D. M., Mellacheruvu, D., & Nesvizhskii, A. I. (2017) · Nature Methods · doi:10.1038/nmeth.4256 · Cited by 2,344 · see citing works
Mass-spectrometric exploration of proteome structure and function
Aebersold, R., & Mann, M. (2016) · Nature · doi:10.1038/nature19949 · Cited by 2,334 · see citing works
LinkedOmics: analyzing multi-omics data within and across 32 cancer types
Vasaikar, S. V., Straub, P., Wang, J., & Zhang, B. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1090 · Cited by 2,324 · see citing works
Self-citationSingle-pot, solid-phase-enhanced sample preparation for proteomics experiments
Hughes, C. S., Moggridge, S., Müller, T., Sorensen, P. H. B., Morin, G. B., & Krijgsveld, J. (2018) · Nature Protocols · doi:10.1038/s41596-018-0082-x · Cited by 1,938 · see citing works
Seiwert, T. Y., Burtness, B., Mehra, R., Weiss, J., Berger, R., Eder, J. P., Heath, K., McClanahan, T., Lunceford, J., Gause, C., et al. (2016) · The Lancet Oncology · doi:10.1016/s1470-2045(16)30066-3 · Cited by 1,745 · see citing works
Toward a Shared Vision for Cancer Genomic Data
Grossman, R. L., Heath, A. P., Ferretti, V., Varmus, H. E., Lowy, D. R., Kibbe, W. A., & Staudt, L. M. (2016) · New England Journal of Medicine · doi:10.1056/nejmp1607591 · Cited by 1,680 · see citing works
Proteogenomics connects somatic mutations to signalling in breast cancer
CPTAC, N., Mertins, P., Mani, D. R., Ruggles, K. V., Gillette, M. A., Clauser, K. R., Wang, P., Wang, X., Qiao, J. W., Cao, S., et al. (2016) · Nature · doi:10.1038/nature18003 · Cited by 1,676 · see citing works
Self-citationStrelka2: fast and accurate calling of germline and somatic variants
Kim, S., Scheffler, K., Halpern, A. L., Bekritsky, M. A., Noh, E., Källberg, M., Chen, X., Kim, Y., Beyter, D., Krusche, P., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0051-x · Cited by 1,643 · see citing works
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells
Ramsköld, D., Luo, S., Wang, Y.-C., Li, R., Deng, Q., Faridani, O. R., Daniels, G. A., Khrebtukova, I., Loring, J. F., Laurent, L. C., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2282 · Cited by 1,609 · see citing works
Systematic and Quantitative Assessment of the Ubiquitin-Modified Proteome
Kim, W., Bennett, E. J., Huttlin, E. L., Guo, A., Li, J., Possemato, A. P., Sowa, M. E., Rad, R., Rush, A. J., Comb, M. J., et al. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.08.025 · Cited by 1,582 · see citing works
Proteogenomic characterization of human colon and rectal cancer
CPTAC, T. N., Zhang, B., Wang, J., Wang, X., Zhu, J., Liu, Q., Shi, Z., Chambers, M. C., Zimmerman, L. J., Shaddox, K. F., et al. (2014) · Nature · doi:10.1038/nature13438 · Cited by 1,462 · see citing works
Self-citationmRNAs, proteins and the emerging principles of gene expression control
Buccitelli, C., & Selbach, M. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0258-4 · Cited by 1,243 · see citing works
CEL-seq: single-cell RNA-seq by multiplexed linear amplification
Hashimshony, T., Wagner, F., Sher, N., & Yanai, I. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.08.003 · Cited by 1,231 · see citing works
The Third Revolution in Sequencing Technology
van Dijk, E., Jaszczyszyn, Y., Naquin, D., & Thermes, C. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.05.008 · Cited by 1,186 · see citing works
Wang, J., Vasaikar, S. V., Shi, Z., Greer, M., & Zhang, B. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx356 · Cited by 1,161 · see citing works
Self-citationThe whole-genome landscape of medulloblastoma subtypes
Northcott, P. A., Buchhalter, I., Morrissy, A. S., Hovestadt, V., Weischenfeldt, J., Ehrenberger, T., Gröbner, S., Segura-Wang, M., Zichner, T., Rudneva, V. A., et al. (2017) · Nature · doi:10.1038/nature22973 · Cited by 1,112 · see citing works
MS-GF+ makes progress towards a universal database search tool for proteomics
Kim, S., & Pevzner, P. A. (2014) · Nature Communications · doi:10.1038/ncomms6277 · Cited by 1,098 · see citing works
Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma
Gao, Q., Zhu, H., Dong, L., Shi, W., Chen, R., Song, Z., Huang, C., Li, J., Dong, X., Zhou, Y., et al. (2019) · Cell · doi:10.1016/j.cell.2019.08.052 · Cited by 1,096 · see citing works
Self-citationWang, K., Yuen, S. T., Xu, J., Lee, S. P., Yan, H. H. N., Shi, S. T., Siu, H. C., Deng, S., Chu, K. M., Law, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.2983 · Cited by 1,045 · see citing works
Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer
Zhang, H., Liu, T., Zhang, Z., Payne, S. H., Zhang, B., McDermott, J. E., Zhou, J.-Y., Petyuk, V. A., Chen, L., Ray, D., et al. (2016) · Cell · doi:10.1016/j.cell.2016.05.069 · Cited by 1,029 · see citing works
Self-citationOverview of Next‐Generation Sequencing Technologies
Slatko, B. E., Gardner, A. F., & Ausubel, F. M. (2018) · Current Protocols in Molecular Biology · doi:10.1002/cpmb.59 · Cited by 968 · see citing works
Wagner, S., Beli, P., Weinert, B. T., Nielsen, M. L., Cox, J., Mann, M., & Choudhary, C. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.013284 · Cited by 889 · see citing works
WikiPathways: connecting communities
Martens, M., Ammar, A., Riutta, A., Waagmeester, A., Slenter, D., Hanspers, K., Miller, R. A., Digles, D., Lopes, É. N., Ehrhart, F., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1024 · Cited by 847 · 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
Self-citationHigh-throughput sequencing of the transcriptome and chromatin accessibility in the same cell
Chen, S., Lake, B. B., & Zhang, K. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0290-0 · Cited by 810 · see citing works
Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present
Bantscheff, M., Lemeer, S., Savitski, M. M., & Kuster, B. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-6203-4 · Cited by 801 · see citing works
Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities
Vasaikar, S., Huang, C., Wang, X., Petyuk, V. A., Savage, S. R., Wen, B., Dou, Y., Zhang, Y., Shi, Z., Arshad, O. A., et al. (2019) · Cell · doi:10.1016/j.cell.2019.03.030 · Cited by 799 · see citing works
Self-citationProteogenomics: concepts, applications and computational strategies
Nesvizhskii, A. I. (2014) · Nature Methods · doi:10.1038/nmeth.3144 · Cited by 763 · see citing works
Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma
Clark, D. J., Dhanasekaran, S. M., Petralia, F., Pan, J., Song, X., Hu, Y., da Veiga Leprevost, F., Reva, B., Lih, T.-S. M., Chang, H.-Y., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.007 · Cited by 730 · see citing works
Self-citationProteogenomic and metabolomic characterization of human glioblastoma
Wang, L.-B., Karpova, A., Gritsenko, M. A., Kyle, J. E., Cao, S., Li, Y., Rykunov, D., Colaprico, A., Rothstein, J. H., Hong, R., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.01.006 · Cited by 661 · see citing works
Self-citationPerseus: A Bioinformatics Platform for Integrative Analysis of Proteomics Data in Cancer Research
Tyanova, S., & Cox, J. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7493-1_7 · Cited by 643 · see citing works
Integrated proteomic analysis of post-translational modifications by serial enrichment
Mertins, P., Qiao, J., Patel, J., Udeshi, N. D., Clauser, K. R., Mani, D. R., Burgess, M. W., Gillette, M. A., Jaffe, J. D., & Carr, S. A. (2013) · Nature Methods · doi:10.1038/nmeth.2518 · Cited by 619 · see citing works
Self-citationPhilosopher: a versatile toolkit for shotgun proteomics data analysis
Leprevost, F. D. V., Haynes, S. E., Avtonomov, D. M., Chang, H.-Y., Shanmugam, A. K., Mellacheruvu, D., Kong, A. T., & Nesvizhskii, A. I. (2020) · Nature Methods · doi:10.1038/s41592-020-0912-y · Cited by 618 · see citing works
Integrative Proteomic Characterization of Human Lung Adenocarcinoma
Xu, J., Zhang, C., Wang, X., Zhai, L., Ma, Y., Mao, Y., Qian, K., Sun, C., Liu, Z., Jiang, S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.043 · Cited by 612 · see citing works
A survey of tools for variant analysis of next-generation genome sequencing data
Pabinger, S., Dander, A., Fischer, M., Snajder, R., Sperk, M., Efremova, M., Krabichler, B., Speicher, M. R., Zschocke, J., & Trajanoski, Z. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs086 · Cited by 595 · see citing works
Rozenblatt–Rosen, O., Regev, A., Oberdoerffer, P., Nawy, T., Hupalowska, A., Rood, J., Ashenberg, O., Cerami, E. G., Coffey, R. J., Demir, E., et al. (2020) · Cell · doi:10.1016/j.cell.2020.03.053 · Cited by 557 · see citing works
Self-citationProteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy
Krug, K., Jaehnig, E. J., Satpathy, S., Blumenberg, L. M., Karpova, A. Y., Anurag, M., Miles, G., Mertins, P., Geffen, Y., Tang, L. C., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.036 · Cited by 533 · see citing works
Self-citationYu, F., Haynes, S. E., & Nesvizhskii, A. I. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100077 · Cited by 514 · see citing works
Addressing Accuracy and Precision Issues in iTRAQ Quantitation
Karp, N. A., Huber, W. K., Sadowski, P. G., Charles, P. D., Hester, S. V., & Lilley, K. S. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900628-mcp200 · Cited by 497 · see citing works
iTRAQ Underestimation in Simple and Complex Mixtures: “The Good, the Bad and the Ugly”
Ow, S. Y., Salim, M., Noirel, J., Evans, C. A., Rehman, I., & Wright, P. C. (2009) · Journal of Proteome Research · doi:10.1021/pr900634c · Cited by 490 · see citing works
Resensitization to Crizotinib by the Lorlatinib ALK Resistance Mutation L1198F
Shaw, A. T., Friboulet, L., Leshchiner, I., Gainor, J. F., Bergqvist, S., Brooun, A., Burke, B. J., Deng, Y., Liu, W., Dardaei, L., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1508887 · Cited by 487 · see citing works
Proteogenomic Characterization of Endometrial Carcinoma
Dou, Y., Kawaler, E. A., Cui Zhou, D., Gritsenko, M. A., Huang, C., Blumenberg, L., Karpova, A., Petyuk, V. A., Savage, S. R., Satpathy, S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.01.026 · Cited by 485 · see citing works
Self-citationMertins, P., Tang, L. C., Krug, K., Clark, D. J., Gritsenko, M., Chen, L., Clauser, K. R., Clauss, T. R., Shah, P., Gillette, M. A., et al. (2018) · Nature Protocols · doi:10.1038/s41596-018-0006-9 · Cited by 482 · see citing works
Self-citationSasagawa, Y., Nikaido, I., Hayashi, T., Danno, H., Uno, K. D., Imai, T., & Ueda, H. R. (2013) · Genome Biology · doi:10.1186/gb-2013-14-4-r31 · Cited by 455 · see citing works
Li, J., Vranken, J. G. V., Vaites, L. P., Schweppe, D. K., Huttlin, E. L., Etienne, C. L., Nandhikonda, P., Viner, R., Robitaille, A. M., Thompson, A. H., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0781-4 · Cited by 431 · see citing works
Tian, C., Clauser, K. R., Öhlund, D., Rickelt, S., Huang, Y., Gupta, M. R., Mani, D. R., Carr, S. A., Tuveson, D. A., & Hynes, R. O. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1908626116 · Cited by 415 · see citing works
Self-citationGan, C. S., Chong, P. K., Pham, T. K., & Wright, P. C. (2007) · Journal of Proteome Research · doi:10.1021/pr060474i · Cited by 404 · see citing works
Mertins, P., Yang, F., Liu, T., Mani, D. R., Petyuk, V., Gillette, M. A., Clauser, K. R., Qiao, J., Gritsenko, M. A., Moore, R., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.036392 · Cited by 395 · see citing works
Self-citationChen, 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
Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant
Yu, F., Haynes, S. E., Teo, G. C., Avtonomov, D. M., Polasky, D. A., & Nesvizhskii, A. I. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir120.002048 · Cited by 377 · see citing works
A proteogenomic portrait of lung squamous cell carcinoma
Satpathy, S., Krug, K., Beltran, P. M. J., Savage, S. R., Petralia, F., Kumar‐Sinha, C., Dou, Y., Reva, B. A., Kane, M. H., Avanessian, S. C., et al. (2021) · Cell · doi:10.1016/j.cell.2021.07.016 · Cited by 377 · see citing works
Self-citationSingle-cell Proteomics: Progress and Prospects
Kelly, R. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r120.002234 · Cited by 360 · see citing works
Huang, C. L., Chen, L., Savage, S. R., Eguez, R. V., Dou, Y., Li, Y., Leprevost, F. D. V., Jaehnig, E. J., Lei, J. T., Wen, B., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2020.12.007 · Cited by 354 · see citing works
Self-citationUdeshi, N. D., Svinkina, T., Mertins, P., Kuhn, E. W., Mani, D. R., Qiao, J., & Carr, S. A. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o112.027094 · Cited by 335 · see citing works
Self-citationA Curated Resource for Phosphosite-specific Signature Analysis
Krug, K., Mertins, P., Zhang, B., Hornbeck, P. V., Raju, R., Ahmad, R., Szucs, M. J., Mundt, F., Forestier, D., Jané‐Valbuena, J., et al. (2018) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir118.000943 · Cited by 329 · see citing works
Self-citationIntegrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer
Petralia, F., Tignor, N., Reva, B., Koptyra, M., Chowdhury, S., Rykunov, D., Krek, A., Ma, W., Zhu, Y., Ji, J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.044 · Cited by 317 · see citing works
Self-citationIntegrated Omics of Metastatic Colorectal Cancer
Li, C., Sun, Y.-D., Yu, G.-Y., Cui, J.-R., Lou, Z., Zhang, H., Huang, Y., Bai, C.-G., Deng, L.-L., Liu, P., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.08.002 · Cited by 297 · see citing works
Proteogenomic Characterization of Human Early-Onset Gastric Cancer
Mun, D.-G., Bhin, J., Kim, S., Kim, H., Jung, J. H., Jung, Y., Jang, Y. E., Park, J. M., Kim, H., Jung, Y., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2018.12.003 · Cited by 294 · see citing works
Mutational Signature of Aristolochic Acid Exposure as Revealed by Whole-Exome Sequencing
Hoang, M. L., Chen, C., Sidorenko, V. S., He, J., Dickman, K. G., Yun, B. H., Moriya, M., Niknafs, N., Douville, C. B., Karchin, R., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3006200 · Cited by 285 · see citing works
Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
Chen, C., Hou, J., Tanner, J. J., & Cheng, J. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21082873 · Cited by 280 · see citing works
Comprehensive Single-Shot Proteomics with FAIMS on a Hybrid Orbitrap Mass Spectrometer
Hebert, A. S., Prasad, S., Belford, M. W., Bailey, D. J., McAlister, G. C., Abbatiello, S. E., Huguet, R., Wouters, E. R., Dunyach, J., Brademan, D. R., et al. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b02233 · Cited by 280 · see citing works
Measuring and Managing Ratio Compression for Accurate iTRAQ/TMT Quantification
Savitski, M. M., Mathieson, T., Zinn, N., Sweetman, G. M. A., Doce, C., Becher, I., Pachl, F., Küster, B., & Bantscheff, M. (2013) · Journal of Proteome Research · doi:10.1021/pr400098r · Cited by 278 · see citing works
Cetuximab: An epidermal growth factor receptor chimeric human-murine monoclonal antibody
Harding, J., & Burtness, B. A. (2005) · Drugs of today · doi:10.1358/dot.2005.41.2.882662 · Cited by 262 · see citing works
Multiplexed and data‐independent tandem mass spectrometry for global proteome profiling
Chapman, J. D., Goodlett, D. R., & Masselon, C. (2013) · Mass Spectrometry Reviews · doi:10.1002/mas.21400 · Cited by 258 · see citing works
Systematic comparison and assessment of RNA-seq procedures for gene expression quantitative analysis
Corchete, L. A., Rojas, E. A., Alonso‐López, D., Rivas, J. D. L., Gutierrez, N. C., & Burguillo, F. J. (2020) · Scientific Reports · doi:10.1038/s41598-020-76881-x · Cited by 250 · see citing works
ALK inhibitors in non-small cell lung cancer: crizotinib and beyond.
Awad, M. M., & Shaw, A. T. (2014) · PubMed · Cited by 244 · see citing works
The Proteogenomic Landscape of Curable Prostate Cancer
Sinha, A., Huang, V., Livingstone, J. M., Wang, J., Fox, N. S., Kurganovs, N. J., Ignatchenko, V., Fritsch, K., Donmez, N., Heisler, L. E., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.02.005 · Cited by 241 · see citing works
Robust and Sensitive iTRAQ Quantification on an LTQ Orbitrap Mass Spectrometer
Bantscheff, M., Böesche, M., Eberhard, D., Mathieson, T., Sweetman, G. M. A., & Küster, B. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800029-mcp200 · Cited by 235 · see citing works
Breast cancer quantitative proteome and proteogenomic landscape
Johansson, H. J., Socciarelli, F., Vacanti, N. M., Haugen, M. H., Zhu, Y., Siavelis, I., Fernandez-Woodbridge, A., Aure, M. R. R., Sennblad, B., Vesterlund, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09018-y · Cited by 230 · see citing works
Schweppe, D. K., Prasad, S., Belford, M. W., Navarrete-Perea, J., Bailey, D. J., Huguet, R., Jedrychowski, M. P., Rad, R., McAlister, G., Abbatiello, S. E., et al. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b05399 · Cited by 229 · see citing works
The diverse and expanding role of mass spectrometry in structural and molecular biology
Lössl, P., van de Waterbeemd, M., & Heck, A. J. (2016) · The EMBO Journal · doi:10.15252/embj.201694818 · Cited by 222 · see citing works
Panorama: A Targeted Proteomics Knowledge Base
Sharma, V., Eckels, J., Taylor, G. K., Shulman, N., Stergachis, A. B., Joyner, S., Yan, P., Whiteaker, J. R., Halusa, G. N., Schilling, B., et al. (2014) · Journal of Proteome Research · doi:10.1021/pr5006636 · Cited by 213 · see citing works
Self-citationClinical potential of mass spectrometry-based proteogenomics
Zhang, B., Whiteaker, J. R., Hoofnagle, A. N., Baird, G. S., Rodland, K. D., & Paulovich, A. G. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-018-0135-7 · Cited by 210 · see citing works
Self-citationArcher, T. C., Ehrenberger, T., Mundt, F. O., Gold, M. P., Krug, K., Mah, C. K., Mahoney, E. L., Daniel, C. J., LeNail, A., Ramamoorthy, D., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.08.004 · Cited by 198 · see citing works
Self-citationiTRAQ Labeling is Superior to mTRAQ for Quantitative Global Proteomics and Phosphoproteomics
Mertins, P., Udeshi, N. D., Clauser, K. R., Mani, D. R., Patel, J., Ong, S., Jaffe, J. D., & Carr, S. A. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.014423 · Cited by 190 · see citing works
Self-citationThompson, A., Wölmer, N., Koncarevic, S., Selzer, S., Böhm, G., Legner, H., Schmid, P., Kienle, S., Penning, P., Höhle, C., et al. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b04474 · Cited by 186 · see citing works
The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment
Rodriguez, H., Zenklusen, J. C., Staudt, L. M., Doroshow, J. H., & Lowy, D. R. (2021) · Cell · doi:10.1016/j.cell.2021.02.055 · Cited by 186 · see citing works
Svinkina, T., Gu, H., Silva, J. C., Mertins, P., Qiao, J., Fereshetian, S., Jaffe, J. D., Kuhn, E. W., Udeshi, N. D., & Carr, S. A. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o114.047555 · Cited by 179 · see citing works
Self-citationWu, P., Heins, Z., Muller, J., Katsnelson, L., de Bruijn, I., Abeshouse, A. A., Schultz, N. D., Fenyö, D., & Gao, J. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir119.001673 · Cited by 177 · see citing works
Latonen, L., Afyounian, E., Jylhä, A., Nättinen, J. E., Aapola, U., Annala, M., Kivinummi, K. K., Tammela, T. L. J., Beuerman, R. W., Uusitalo, H. M. T., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03573-6 · Cited by 172 · see citing works
Single-cell protein analysis by mass spectrometry
Slavov, N. (2021) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2020.04.018 · Cited by 164 · see citing works
Hu, P., Fabyanic, E., Kwon, D. Y., Tang, S., Zhou, Z., & Wu, H. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.11.017 · Cited by 162 · see citing works
Wang, X., & Zhang, B. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt543 · Cited by 162 · see citing works
Self-citationCoscia, F., Lengyel, E. R., Duraiswamy, J., Ashcroft, B., Bassani‐Sternberg, M., Wierer, M., Johnson, A., Wroblewski, K., MONTAG, A. G., Yamada, S. D., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.065 · Cited by 162 · see citing works
Elevated NSD3 histone methylation activity drives squamous cell lung cancer
Yuan, G., Flores, N. M., Hausmann, S., Lofgren, S., Kharchenko, V., Angulo‐Ibáñez, M., Sengupta, D., Lu, X., Czaban, I., Azhibek, D. M., et al. (2021) · Nature · doi:10.1038/s41586-020-03170-y · Cited by 158 · see citing works
Tsai, C., Zhao, R., Williams, S., Moore, R. J., Schultz, K., Chrisler, W., Paša‐Tolić, L., Rodland, K., Smith, R. D., Shi, T., et al. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra119.001857 · Cited by 156 · see citing works
Rudnick, P. A., Markey, S. P., Roth, J. S., Mirokhin, Y. A., Yan, X., Tchekhovskoi, D. V., Edwards, N. J., Thangudu, R. R., Ketchum, K. A., Kinsinger, C. R., et al. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b01091 · Cited by 154 · see citing works
Wen, B., Zeng, W., Liao, Y., Shi, Z., Savage, S. R., Jiang, W., & Zhang, B. (2020) · PROTEOMICS · doi:10.1002/pmic.201900335 · Cited by 152 · see citing works
Self-citationMethods, Tools and Current Perspectives in Proteogenomics
Ruggles, K. V., Krug, K., Wang, X., Clauser, K. R., Wang, J., Payne, S., Fenyö, D., Zhang, B., & Mani, D. R. (2017) · Molecular & Cellular Proteomics · doi:10.1074/mcp.mr117.000024 · Cited by 148 · see citing works
Self-citationGeiszler, D., Kong, A. T., Avtonomov, D. M., Yu, F., Leprevost, F. D. V., & Nesvizhskii, A. I. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir120.002216 · Cited by 147 · see citing works
Erickson, B. K., Mintseris, J., Schweppe, D. K., Navarrete-Perea, J., Erickson, A. R., Nusinow, D. P., Paulo, J. A., & Gygi, S. P. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00899 · Cited by 146 · see citing works
Proteogenomic integration reveals therapeutic targets in breast cancer xenografts
Huang, K., Li, S., Mertins, P., Cao, S., Gunawardena, H. P., Ruggles, K. V., Mani, D. R., Clauser, K. R., Tanioka, M., Usary, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14864 · Cited by 146 · see citing works
Self-citationForget, A., Martignetti, L., Puget, S., Calzone, L., Brabetz, S., Picard, D. J., Montagud, A., Liva, S., Sta, A., Dingli, F., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.08.002 · Cited by 144 · see citing works
Hu, Y., Pan, J., Shah, P., Ao, M., Thomas, S. N., Liu, Y., Chen, L., Schnaubelt, M., Clark, D. J., Rodriguez, H., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108276 · Cited by 142 · see citing works
Self-citation(2013) · Nature Methods · doi:10.1038/nmeth.2801 · Cited by 137 · see citing works
Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis
Wen, B., Li, K., Zhang, Y., & Zhang, B. (2020) · Nature Communications · doi:10.1038/s41467-020-15456-w · Cited by 137 · see citing works
Self-citationProteogenomic landscape of squamous cell lung cancer
Stewart, P. A., Welsh, E. A., Slebos, R. J. C., Fang, B., Izumi, V., Chambers, M., Zhang, G., Cen, L., Pettersson, F. H., Zhang, Y., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11452-x · Cited by 122 · see citing works
Pan, J., Hu, Y., Sun, S., Chen, L., Schnaubelt, M., Clark, D. J., Ao, M., Zhang, Z., Chan, D. W., Qian, J. X., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19976-3 · Cited by 122 · see citing works
Overview of Peptide and Protein Analysis by Mass Spectrometry
Zhang, G., Annan, R. S., Carr, S. A., & Neubert, T. A. (2010) · Current Protocols in Protein Science · doi:10.1002/0471140864.ps1601s62 · Cited by 119 · see citing works
Self-citationRuggles, K. V., Tang, Z., Wang, X., Grover, H., Askenazi, M., Teubl, J., Cao, S., McLellan, M. D., Clauser, K. R., Tabb, D. L., et al. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m115.056226 · Cited by 116 · see citing works
Self-citationMicroscaled proteogenomic methods for precision oncology
Satpathy, S., Jaehnig, E. J., Krug, K., Kim, B., Saltzman, A. B., Chan, D. W., Holloway, K. R., Anurag, M., Huang, C. L., Singh, P., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14381-2 · Cited by 113 · see citing works
Self-citationRapid and deep-scale ubiquitylation profiling for biology and translational research
Udeshi, N. D., Mani, D. R., Satpathy, S., Fereshetian, S., Gasser, J. A., Svinkina, T., Olive, M. E., Ebert, B. L., Mertins, P., & Carr, S. A. (2020) · Nature Communications · doi:10.1038/s41467-019-14175-1 · Cited by 112 · see citing works
Self-citationOSBREAC, Aure, M. R. R., Vitelli, V., Jernström, S., Kumar, S., Krohn, M., Due, E. U., Haukaas, T. H., Leivonen, S., Vollan, H. K. M., et al. (2017) · Breast Cancer Research · doi:10.1186/s13058-017-0812-y · Cited by 103 · see citing works
McDermott, J. E., Arshad, O. A., Petyuk, V. A., Fu, Y., Gritsenko, M. A., Clauss, T. R., Moore, R. J., Schepmoes, A. A., Zhao, R., Monroe, M. E., et al. (2020) · Cell Reports Medicine · doi:10.1016/j.xcrm.2020.100004 · Cited by 97 · see citing works
Self-citationYang, M., Vesterlund, M., Siavelis, I., Moura‐Castro, L. H., Castor, A., Fioretos, T., Jafari, R., Lilljebjörn, H., Odom, D. T., Olsson, L., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09469-3 · Cited by 97 · see citing works
Roper, N., Gao, S., Maity, T. K., Banday, A. R., Zhang, X., Venugopalan, A. K., Cultraro, C. M., Patidar, R., Sindiri, S., Brown, A., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2019.02.028 · Cited by 97 · see citing works
PepQuery enables fast, accurate, and convenient proteomic validation of novel genomic alterationsPreprint
Wen, B., Wang, X., & Zhang, B. (2019) · Genome Research · doi:10.1101/gr.235028.118 · Cited by 97 · see citing works
Self-citationFinding driver mutations in cancer: Elucidating the role of background mutational processes
Brown, A., Li, M., Goncearenco, A., & Panchenko, A. R. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006981 · Cited by 90 · see citing works
Proteogenomics from a bioinformatics angle: A growing field
Menschaert, G., & Fenyö, D. (2015) · Mass Spectrometry Reviews · doi:10.1002/mas.21483 · Cited by 85 · see citing works
Austen, M., Cerni, C., Lüscher‐Firzlaff, J., & Lüscher, B. (1998) · Oncogene · doi:10.1038/sj.onc.1201968 · Cited by 81 · see citing works
Flores‐Morales, A., Bergmann, T., Lavallee, C., Batth, T. S., Lin, D., Lerdrup, M., Friis, S., Bartels, A., Kristensen, G., Krzyzanowska, A., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-0729 · Cited by 81 · see citing works
Spatially resolved analysis of FFPE tissue proteomes by quantitative mass spectrometry
Buczak, K., Kirkpatrick, J. M., Truckenmueller, F., Santinha, D., Ferreira, L., Roessler, S., Singer, S., Beck, M., & Ori, A. (2020) · Nature Protocols · doi:10.1038/s41596-020-0356-y · Cited by 78 · see citing works
Proteogenomics of glioblastoma associates molecular patterns with survival
Arad, G., Ofek, P., Yeini, E., Mardamshina, M., Danilevsky, A., Shomron, N., Grossman, R., Satchi‐Fainaro, R., & Geiger, T. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108787 · Cited by 74 · see citing works
Single-Cell RNA Sequencing and Its Combination with Protein and DNA Analyses
Choi, J. R., Yong, K. W., Choi, J. Y., & Cowie, A. C. (2020) · Cells · doi:10.3390/cells9051130 · Cited by 65 · see citing works
NetGestalt: integrating multidimensional omics data over biological networks
Shi, Z., Wang, J., & Zhang, B. (2013) · Nature Methods · doi:10.1038/nmeth.2517 · Cited by 64 · see citing works
Self-citationEzzoukhry, Z., Henriet, E., Cordelières, F. P., Dupuy, J., Maître, M., Gay, N., Di-Tommaso, S., Mercier, L., Goetz, J. G., Peter, M., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04461-9 · Cited by 64 · see citing works
scATAC-pro: a comprehensive workbench for single-cell chromatin accessibility sequencing data
Yu, W., Uzun, Y., Zhu, Q., Chen, C., & Tan, K. (2020) · Genome biology · doi:10.1186/s13059-020-02008-0 · Cited by 60 · see citing works
Rudolph, J. D., de Graauw, M., van de Water, B., Geiger, T., & Sharan, R. (2016) · Cell Systems · doi:10.1016/j.cels.2016.11.005 · Cited by 60 · see citing works
HYPERsol: High-Quality Data from Archival FFPE Tissue for Clinical Proteomics
Marchione, D. M., Ilieva, I., Devins, K. M., Sharpe, D., Pappin, D., Garcia, B. A., Wilson, J. P., & Wojcik, J. B. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00686 · Cited by 60 · see citing works
Mundt, F. O., Rajput, S., Li, S., Ruggles, K. V., Mooradian, A. D., Mertins, P., Gillette, M. A., Krug, K., Guo, Z., Hoog, J., et al. (2018) · Cancer Research · doi:10.1158/0008-5472.can-17-1990 · Cited by 56 · see citing works
Self-citationGroßerueschkamp, F., Bracht, T., Diehl, H. C., Küpper, C., Ahrens, M., Kallenbach‐Thieltges, A., Axel Mosig, A., Eisenacher, M., Marcus, K., Behrens, T., et al. (2017) · Scientific Reports · doi:10.1038/srep44829 · Cited by 54 · see citing works
Proteomic analysis of Medulloblastoma reveals functional biology with translational potential
Rivero-Hinojosa, S., Lau, L. S., Stampar, M., Staal, J. A., Zhang, H., Gordish‐Dressman, H., Northcott, P. A., Pfister, S. M., Taylor, M. D., Brown, K. J., et al. (2018) · Acta Neuropathologica Communications · doi:10.1186/s40478-018-0548-7 · Cited by 52 · see citing works
DreamAI: algorithm for the imputation of proteomics dataPreprint
Ma, W., Kim, S., Chowdhury, S., Li, Z., Yang, M., Yoo, S., Petralia, F., Jacobsen, J. R., Li, J. J., Ge, X., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.21.214205 · Cited by 51 · see citing works
Comparing the performance of selected variant callers using synthetic data and genome segmentation
Bian, X., Zhu, B., Wang, M., Hu, Y., Chen, Q., Nguyen, C. D., Hicks, B. D., & Meerzaman, D. M. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2440-7 · Cited by 49 · see citing works
Residual tissue repositories as a resource for population-based cancer proteomic studies
Piehowski, P., Petyuk, V., Sontag, R. L., Gritsenko, M. A., Weitz, K., Fillmore, T., Moon, J., Makhlouf, H. R., Chuaqui, R. F., Boja, E. S., et al. (2018) · Clinical Proteomics · doi:10.1186/s12014-018-9202-4 · Cited by 49 · see citing works
Single-cell ATAC-seq signal extraction and enhancement with SCATE
Ji, Z., Zhou, W., Hou, W., & Ji, H. (2020) · Genome biology · doi:10.1186/s13059-020-02075-3 · Cited by 47 · see citing works
Birger, C., Hanna, M., Salinas, E. A., Neff, J., Saksena, G., Livitz, D. G., Rosebrock, D., Stewart, C., Leshchiner, I., Baumann, A., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/209494 · Cited by 45 · see citing works
Simplified and Unified Access to Cancer Proteogenomic Data
Lindgren, C. M., Adams, D. W., Kimball, B., Boekweg, H., Tayler, S., Pugh, S. L., & Payne, S. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00919 · Cited by 40 · see citing works
Mass spectrometry at the interface of proteomics and genomics
Krug, K., Nahnsen, S., & Maček, B. (2010) · Molecular BioSystems · doi:10.1039/c0mb00168f · Cited by 39 · see citing works
Self-citationHiroshima, Y., Kasajima, R., Kimura, Y., Komura, D., Ishikawa, S., Ichikawa, Y., Bouvet, M., Yamamoto, N., Oshima, T., Morinaga, S., et al. (2019) · Cancer Letters · doi:10.1016/j.canlet.2019.10.031 · Cited by 34 · see citing works
The protein landscape of chronic lymphocytic leukemia
Meier‐Abt, F., Lu, J., Cannizzaro, E., Pohly, M. F., Kummer, S., Pfammatter, S., Kunz, L., Collins, B. C., Nadeu, F., Lee, K.-S., et al. (2021) · Blood · doi:10.1182/blood.2020009741 · Cited by 34 · see citing works
Song, X., Ji, J., Gleason, K. J., Yang, F., Martignetti, J. A., Chen, L., & Wang, P. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra118.001220 · Cited by 32 · see citing works
The human melanoma proteome atlas—Defining the molecular pathology
Betancourt, L. H., Gil, J., Kim, Y., Doma, V., Çakır, U., Sánchez, A., Murillo, J. R., Kuras, M., Plá, I., Sugihara, Y., et al. (2021) · Clinical and Translational Medicine · doi:10.1002/ctm2.473 · Cited by 30 · see citing works
A Pilot Characterization of Human Lung NSCLC by Protein Pathway Activation Mapping
Zupa, A., Improta, G., Silvestri, A., Pin, E., Deng, J., Aieta, M., Musto, P., Nitti, D., Mammano, E., Liotta, L. A., et al. (2012) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e3182725fc7 · Cited by 30 · see citing works
Petralia, F., Wang, L., Peng, J., Yan, A., Zhu, J., & Wang, P. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty280 · Cited by 29 · see citing works
Spatially interacting phosphorylation sites and mutations in cancer
Huang, K., Scott, A. D., Zhou, D. C., Wang, L.-B., Weerasinghe, A., Elmas, A., Liu, R., Wu, Y., Wendl, M. C., Wyczalkowski, M. A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22481-w · Cited by 23 · see citing works
Self-citationYang, F., Bai, B., Liang, Y., Ren, Y., Liu, Y., Zhou, F., Lou, X., Zi, J., Hou, G., Chen, F., et al. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100068 · Cited by 19 · see citing works
Proteogenomic Landscape of Squamous Cell Lung Cancer
Stewart, P. A., Slebos, R. J. C., Welsh, E. A., Cen, L., Zhang, Y., Chen, Z., Cheng, C., Pettersson, F. H., Berglund, A., Zhang, G., et al. (2017) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2017.06.037 · Cited by 18 · see citing works
Whole-Exome Enrichment with the Illumina TruSeq Exome Enrichment PlatformPreprint
Chen, R., Im, H., & Snyder, M. (2015) · Cold Spring Harbor Protocols · doi:10.1101/pdb.prot084863 · Cited by 17 · see citing works
PANOPLY: a cloud-based platform for automated and reproducible proteogenomic data analysis
Mani, D. R., Maynard, M., Kothadia, R. B., Krug, K., Christianson, K. E., Heiman, D. I., Clauser, K. R., Birger, C., Getz, G. A., & Carr, S. A. (2021) · Nature Methods · doi:10.1038/s41592-021-01176-6 · Cited by 16 · see citing works
Self-citationPathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment
Staunton, L., Tonry, C. L., Lis, R. T., Espina, V. A., Liotta, L. A., Inzitari, R., Bowden, M., Fabre, A., O’Leary, J. J., Finn, S. P., et al. (2017) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-16-0358 · Cited by 16 · see citing works
A comprehensive quality control workflow for paired tumor-normal NGS experiments
Schroeder, C., Hilke, F. J., Loeffler, M. W., Bitzer, M., Lenz, F., & Sturm, M. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx032 · Cited by 16 · see citing works
BlackSheep: A Bioconductor and Bioconda Package for Differential Extreme Value Analysis
Blumenberg, L. M., Kawaler, E. A., Cornwell, M., Smith, S. A., Ruggles, K. V., & Fenyö, D. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00190 · Cited by 15 · see citing works
Bateman, N. W., Tarney, C. M., Abulez, T. S., Soltis, A. R., Zhou, M., Conrads, K. A., Litzi, T. A., Oliver, J., Hood, B. L., Driggers, P. H., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-88585-x · Cited by 15 · see citing works
BayesDeBulk: A Flexible Bayesian Algorithm for the Deconvolution of Bulk Tumor DataPreprint
Petralia, F., Krek, A., Calinawan, A. P., Charytonowicz, D., Sebra, R., Feng, S., Gosline, S. J. C., Pugliese, P., Paulovich, A. G., Kennedy, J. J., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.25.449763 · Cited by 13 · see citing works
Interferon-induced transmembrane protein 3 (IFITM3) limits lethality of SARS-CoV-2 in micePreprint
Zani, A., Kenney, A. D., Kawahara, J., Eddy, A. C., Wang, X.-L., Mahesh, K. C., Lu, M., Hemann, E. A., Lǐ, J., Peeples, M. E., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.12.22.473914 · Cited by 9 · see citing works
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Cited by
Sorted by citations
The present and future of the Cancer Dependency Map
Arafeh, R., Shibue, T., Dempster, J. M., Hahn, W. C., & Vazquez, F. (2025) · Nature Reviews Cancer · doi:10.1038/s41568-024-00763-x · Cited by 454 · see citing works
Multi-Omics Profiling for Health
Babu, M., & Snyder, M. P. (2023) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100561 · Cited by 419 · see citing works
Mass-spectrometry-based proteomics: from single cells to clinical applications
Guo, T., Steen, J. A. J., & Mann, M. (2025) · Nature · doi:10.1038/s41586-025-08584-0 · Cited by 351 · see citing works
Proteogenomic data and resources for pan-cancer analysis
Li, Y., Dou, Y., Leprevost, F. D. V., Geffen, Y., Calinawan, A. P., Aguet, F., Akiyama, Y., Anand, S. K., Birger, C., Cao, S., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.06.009 · Cited by 260 · see citing works
Self-citationPharmacogenomics: Driving Personalized Medicine
Sadée, W., Wang, D., Hartmann, K., & Toland, A. E. (2023) · Pharmacological Reviews · doi:10.1124/pharmrev.122.000810 · Cited by 251 · see citing works
Geffen, Y., Anand, S. K., Akiyama, Y., Yaron, T. M., Song, Y., Johnson, J. L., Govindan, A., Babur, Ö., Li, Y., Huntsman, E. M., et al. (2023) · Cell · doi:10.1016/j.cell.2023.07.013 · Cited by 211 · see citing works
Self-citationPan-cancer proteogenomics expands the landscape of therapeutic targets
Savage, S. R., Yi, X., Lei, J. T., Wen, B., Zhao, H., Liao, Y., Jaehnig, E. J., Somes, L. K., Shafer, P. W., Lee, T. D., et al. (2024) · Cell · doi:10.1016/j.cell.2024.05.039 · Cited by 136 · see citing works
Self-citationAdvancing CAR T cell therapy through the use of multidimensional omics data
Yang, J., Chen, Y., Jing, Y., Green, M. R., & Han, L. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00729-2 · Cited by 128 · see citing works
Advances in Integrated Multi-omics Analysis for Drug-Target Identification
Du, P., Fan, R., Zhang, N., Wu, C., & Zhang, Y. (2024) · Biomolecules · doi:10.3390/biom14060692 · Cited by 97 · see citing works
Precision cancer medicine: Concepts, current practice, and future developments
Edsjö, A., Holmquist, L., Geoerger, B., Nowak, F., Gomon, G., Alix‐Panabières, C., Staaf, J., Ploeger, C., Lassen, U., Tourneau, C. L., et al. (2023) · Journal of Internal Medicine · doi:10.1111/joim.13709 · Cited by 87 · see citing works
Matsuoka, T., & Yashiro, M. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25115880 · Cited by 83 · see citing works
“Recent advances in proteomics through the maturation of several MS techniques have enabled the introduction of proteogenomic approaches that can integrate genomic data with proteomics and information on post-translational modifications [89].”
BackgroundHong, H., Chen, X., Wang, H., Gu, X., Yuan, Y., & Zhang, Z. (2023) · PROTEOMICS · doi:10.1002/pmic.202200432 · Cited by 79 · see citing works
Clinical applications of mass spectrometry‐based proteomics in cancer: Where are we?
Boys, E. L., Liu, J., Robinson, P. J., & Reddel, R. R. (2022) · PROTEOMICS · doi:10.1002/pmic.202200238 · Cited by 65 · see citing works
Abelin, J. G., Bergstrom, E. J., Rivera, K. D., Taylor, H. B., Klaeger, S., Xu, C., Verzani, E. K., White, C. J., Woldemichael, H. B., Virshup, M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37547-0 · Cited by 61 · see citing works
Self-citationFerdosi, S., Stukalov, A., Hasan, M., Tangeysh, B., Brown, T. R., Wang, T., Elgierari, E. M., Zhao, X., Huang, Y., Alavi, A., et al. (2022) · Advanced Materials · doi:10.1002/adma.202206008 · Cited by 61 · see citing works
A proteogenomics data-driven knowledge base of human cancer
Liao, Y., Savage, S. R., Dou, Y., Shi, Z., Yi, X., Jiang, W., Lei, J. T., & Zhang, B. (2023) · Cell Systems · doi:10.1016/j.cels.2023.07.007 · Cited by 57 · see citing works
Self-citationKnol, J. C., Lyu, M., Böttger, F., Monteiro, M. N., Pham, T. V., Rolfs, F., Vallés‐Martí, A., Schelfhorst, T., Haas, R. R. D. G., Bijnsdorp, I. V., et al. (2025) · Cancer Cell · doi:10.1016/j.ccell.2025.05.003 · Cited by 59 · see citing works
Qiu, X., Wang, A., Wang, J., Zhang, Z., & Tao, L. (2025) · Cell Death Discovery · doi:10.1038/s41420-025-02670-y · Cited by 56 · see citing works
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Eloff, K., Kalogeropoulos, K., Mabona, A., Morell, O., Catzel, R., Rivera‐de‐Torre, E., Jespersen, J. B., Williams, W., van Beljouw, S. P. B., Skwark, M. J., et al. (2025) · Nature Machine Intelligence · doi:10.1038/s42256-025-01019-5 · Cited by 47 · see citing works
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Aggarwal, S., Raj, A., Kumar, D., Dash, D., & Yadav, A. K. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac163 · Cited by 42 · see citing works
Diversifying the concept of model organisms in the age of -omics
Bertile, F., Matallana‐Surget, S., Tholey, A., Cristóbal, S., & Armengaud, J. (2023) · Communications Biology · doi:10.1038/s42003-023-05458-x · Cited by 41 · see citing works
Zhang, B., & Bassani-Sternberg, M. (2023) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2023-007073 · Cited by 44 · see citing works
Self-citationProteomics: An In‐Depth Review on Recent Technical Advances and Their Applications in Biomedicine
Liang, J., Tian, J., Zhang, H., Li, H., & Chen, L. (2025) · Medicinal Research Reviews · doi:10.1002/med.22098 · Cited by 41 · see citing works
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Weaver, C., Satter, K. B., Richardson, K. P., Tran, L. K. H., Tran, P. M. H., & Purohit, S. B. (2022) · Biomedicines · doi:10.3390/biomedicines10112953 · Cited by 42 · see citing works
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Creighton, C. J. (2023) · The Cancer Journal · doi:10.1097/ppo.0000000000000638 · Cited by 35 · see citing works
Ramberger, E., Sapozhnikova, V., Ng, Y. L. D., Dolnik, A., Ziehm, M., Popp, O., Sträng, E., Kull, M., Grünschläger, F., Krüger, J., et al. (2024) · Nature Cancer · doi:10.1038/s43018-024-00784-3 · Cited by 35 · see citing works
Gong, T., Guo, S., Liu, F.-H., Huo, Y.-L., Zhang, M., Shi, Y., Zhou, H., Xu, P., Wang, X., Xu, H.-L., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43282-3 · Cited by 33 · see citing works
Song, Y., Das, D., Zhang, Y., Chen, M., Fernie, A. R., Zhu, F., & Han, J. (2023) · Trends in biotechnology · doi:10.1016/j.tibtech.2023.05.010 · Cited by 34 · see citing works
Targeting the Molecular and Immunologic Features of Leiomyosarcoma
Cope, B. M., Traweek, R. S., Lazcano, R., Keung, E. Z.-Y., Lazar, A. J., Roland, C. L., & Nassif, E. F. (2023) · Cancers · doi:10.3390/cancers15072099 · Cited by 31 · see citing works
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Cai, Z., Poulos, R. C., Aref, A., Robinson, P. J., Reddel, R. R., & Zhong, Q. (2024) · Cancer Research Communications · doi:10.1158/2767-9764.crc-24-0285 · Cited by 36 · see citing works
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Arad, G., & Geiger, T. (2023) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100587 · Cited by 34 · see citing works
Groeneveld, C. S., Sánchez‐Quiles, V., Dufour, F., Shi, M., Dingli, F., Nicolle, R., Chapeaublanc, E., Poullet, P., Jeffery, D., Krucker, C., et al. (2023) · European Urology · doi:10.1016/j.eururo.2023.05.037 · Cited by 29 · see citing works
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Joshi, S. K., Piehowski, P., Liu, T., Gosline, S. J. C., McDermott, J., Druker, B. J., Traer, E. A., Tyner, J. W., Agarwal, A., Tognon, C. E., et al. (2023) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-022723-113921 · Cited by 31 · see citing works
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Sun, B., Liu, Z., Liu, J., Zhao, S., Wang, L., & Wang, F. (2022) · PROTEOMICS · doi:10.1002/pmic.202200132 · Cited by 26 · see citing works
Clinical proteomics towards multiomics in cancer
Creighton, C. J. (2022) · Mass Spectrometry Reviews · doi:10.1002/mas.21827 · Cited by 26 · see citing works
The 2023 Report on the Proteome from the HUPO Human Proteome Project
Omenn, G. S., Lane, L., Overall, C. M., Lindskog, C., Pineau, C., Packer, N. H., Cristea, I. M., Weintraub, S. T., Orchard, S. E., Roehrl, M. H. A., et al. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00591 · Cited by 26 · see citing works
Frontiers in mass spectrometry–based clinical proteomics for cancer diagnosis and treatment
Haga, Y., Minegishi, Y., & Ueda, K. (2023) · Cancer Science · doi:10.1111/cas.15731 · Cited by 24 · see citing works
Eloff, K., Kalogeropoulos, K., Morell, O., Mabona, A., Jespersen, J. B., Williams, W., van Beljouw, S. P. B., Skwark, M. J., Laustsen, A. H., Brouns, S. J. J., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.30.555055 · Cited by 24 · see citing works
Current development of molecular classifications of gastric cancer based on omics (Review)
Ma, Y., Jiang, Z., Pan, L., Zhou, Y., Xia, R., Liu, Z., & Li, Y. (2024) · International Journal of Oncology · doi:10.3892/ijo.2024.5677 · Cited by 24 · see citing works
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Zhang, W., Chen, S., Bai, Z., Gan, M., Chen, M., Zhang, Y., Liu, S., & Liu, D. (2024) · International Journal of Nanomedicine · doi:10.2147/ijn.s481901 · Cited by 25 · see citing works
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Huang, P., Gao, W., Fu, C., & Tian, R. (2023) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100575 · Cited by 23 · see citing works
Omics-based molecular classifications empowering in precision oncology
Zhou, Z., Lin, T., Chen, S., Zhang, G., Xu, Y., Zou, H., Zhou, A., Zhang, Y., Weng, S., Han, X., et al. (2024) · Cellular Oncology · doi:10.1007/s13402-023-00912-8 · Cited by 23 · see citing works
RNA methylation and cellular response to oxidative stress-promoting anticancer agents
Ponzetti, M., Rucci, N., & Falone, S. (2023) · Cell Cycle · doi:10.1080/15384101.2023.2165632 · Cited by 22 · see citing works
Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics
Park, J., Yu, F., Fulcher, J. M., Williams, S., Engbrecht, K. M., Moore, R. J., Clair, G., Petyuk, V., Nesvizhskii, A. I., & Zhu, Y. (2023) · Analytical Chemistry · doi:10.1021/acs.analchem.2c03739 · Cited by 20 · see citing works
Zhang, R., Hu, M. X., Chen, H., Wang, X., Xia, Z., Liu, Y., Wang, R., Xia, X., Yang, S., Du, D., et al. (2023) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100532 · Cited by 19 · see citing works
Wang, J., Yu, W., D’Anna, R. K., Przybyła, A., Wilson, M., Sung, M. S., Bullen, J., Hurt, E. M., D’Angelo, G., Sidders, B. S., et al. (2023) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100626 · Cited by 17 · see citing works
Translational Aspects of Epithelioid Sarcoma: Current Consensus
Grünewald, T. G. P., Postel-Vinay, S. C., Nakayama, R. T., Berlow, N., Bolzicco, A., Cerullo, V., Dermawan, J. K. T. K., Frezza, A. M., Italiano, A., Jin, J. X., et al. (2023) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-23-2174 · Cited by 19 · see citing works
Rocca, A., Crinò, L., Braga, L., Salton, F., Ruaro, B., Confalonieri, M., Generali, D., & Confalonieri, P. (2025) · British Journal of Cancer · doi:10.1038/s41416-025-03139-6 · Cited by 22 · see citing works
Multi-omics approach to identifying isoform variants as therapeutic targets in cancer patients
Shaw, T. I., Zhao, B., Li, Y., Wang, H., Wang, L., Manley, B. J., Stewart, P. A., & Karolak, A. M. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.1051487 · Cited by 16 · see citing works
Liu, Y., Li, X., Chen, S., Zhu, C., Shi, Y., Dang, S., Zhang, W., & Li, W. (2024) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1277508 · Cited by 17 · see citing works
Zhu, X., Shijing, Y. O. U., Du, X., Song, K., Lv, T., Zhao, H., & Yao, Q. (2023) · BMC Medical Genomics · doi:10.1186/s12920-023-01435-9 · Cited by 16 · see citing works
Phenotyping Tumor Heterogeneity through Proteogenomics: Study Models and Challenges
Piana, D., Iavarone, F., Paolis, E. D., Daniele, G., Parisella, F., Minucci, A., Greco, V., & Urbani, A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25168830 · Cited by 16 · see citing works
Wang, S. E., Viallon, V., Lee, M. A., Dimou, N. L., Hamilton, F., Biessy, C., O’Mara, T. A., Kyrgiou, M., Crosbie, E. J., Truong, T., et al. (2024) · EBioMedicine · doi:10.1016/j.ebiom.2024.105341 · Cited by 16 · see citing works
Exploring the landscape of post-translational modification in drug discovery
Cao, Y., Yu, T., Zhu, Z., Zhang, Y., Sun, S., Li, N., Gu, C., & Yang, Y. (2024) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2024.108749 · Cited by 15 · see citing works
Li, M., Wang, L., Hu, Y., Liu, Y., Xu, S., Peng, K., Li, C., Huang, H., Fang, L., Li, L., et al. (2025) · Analytica Chimica Acta · doi:10.1016/j.aca.2025.343796 · Cited by 15 · see citing works
Modulating autophagy to treat diseases: A revisited review on in silico methods
Wu, L., Jin, W., Yu, H., & Liu, B. (2023) · Journal of Advanced Research · doi:10.1016/j.jare.2023.05.002 · Cited by 15 · see citing works
Clinical Proteomics: A Promise Becoming Reality
Gillette, M. A., Jiménez, C. R., & Carr, S. A. (2024) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100688 · Cited by 15 · see citing works
Self-citationProteogenomics offers a novel avenue in neoantigen identification for cancer immunotherapy
Ren, Y., Yue, Y., Li, X., Weng, S., Xu, H., Liu, L., Cheng, Q., Luo, P., Zhang, T., Liu, Z., et al. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.113147 · Cited by 16 · see citing works
Li, W., Sun, J. P., Sun, R., Wei, Y., Zheng, J., Zhu, Y., & Guo, T. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.4c04421 · Cited by 15 · see citing works
RNA N6‐methyladenosine modifications and potential targeted therapeutic strategies in kidney disease
Ni, W., Lu, H., Ma, N., Hou, B., Zeng, J., Zhou, H., Shao, W., & Meng, X. (2022) · British Journal of Pharmacology · doi:10.1111/bph.15968 · Cited by 15 · see citing works
Complex Interplay between DNA Damage and Autophagy in Disease and Therapy
Singh, A. D., Ravendranathan, N., Frisbee, J. C., & Singh, K. K. (2024) · Biomolecules · doi:10.3390/biom14080922 · Cited by 14 · see citing works
Guo, J. R., Lv, Y., Wang, S., Peng, Z., Xie, Y., Wang, Y., Jiang, H., Li, X., Wang, M., Hu, M., et al. (2022) · Oncogene · doi:10.1038/s41388-022-02494-5 · Cited by 14 · see citing works
Wu, X., Lin, X., Ma, X., Huang, H., Zhang, D., Liu, Y., Cheng, R., Song, J. T., Zhang, L., Tan, Y., et al. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.5c01296 · Cited by 13 · see citing works
The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens
Oreper, D., Klaeger, S., Jhunjhunwala, S., & Delamarre, L. (2023) · Seminars in Immunology · doi:10.1016/j.smim.2023.101758 · Cited by 13 · see citing works
Unraveling the Post-Translational Modifications and therapeutical approach in NSCLC pathogenesis
Gulhane, P., & Singh, S. (2023) · Translational Oncology · doi:10.1016/j.tranon.2023.101673 · Cited by 12 · see citing works
The Regulation of m6A Modification in Glioblastoma: Functional Mechanisms and Therapeutic Approaches
Deacon, S., Walker, L., Radhi, M., & Smith, S. J. (2023) · Cancers · doi:10.3390/cancers15133307 · Cited by 13 · see citing works
Pomella, S., Melaiu, O., Cifaldi, L., Bei, R., GARGARI, M., Campanella, V., & Barillari, G. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25168929 · Cited by 14 · see citing works
Liu, Y., Yang, Z., Pu, J. J., Zhong, J., Khoo, U., Su, Y., & Zhang, G. (2025) · Clinical and Translational Medicine · doi:10.1002/ctm2.70261 · Cited by 12 · see citing works
Li, Q., Xie, D., Yao, L., Qiu, H., You, P., Deng, J., Li, C., Zhan, W., Weng, M., Wu, S., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.944378 · Cited by 13 · see citing works
Mao, P., Shen, Y., Xu, X., & Zhong, J. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.864473 · Cited by 10 · see citing works
Pan-cancer analysis of SLC2A family genes as prognostic biomarkers and therapeutic targets
Liu, Y., Li, X., Yang, J., Chen, S., Zhu, C., Shi, Y., Dang, S., Zhang, W., & Li, W. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e29655 · Cited by 11 · see citing works
Expanding individualized therapeutic options via genoproteomics
Zhan, D., Zheng, N., Zhao, B., Cheng, F., Tang, Q., Liu, X., Wang, J., Wang, Y., Liu, H., Li, X.-L., et al. (2023) · Cancer Letters · doi:10.1016/j.canlet.2023.216123 · Cited by 11 · see citing works
Functional Genomics and Network Biology
Joshi, A., Kumar, A., & Kaushik, V. (2024) · Springer eBooks · doi:10.1007/978-981-99-8401-5_3 · Cited by 10 · see citing works
Galaz-Montoya, J. G. (2024) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2024.1390858 · Cited by 9 · see citing works
Proteogenomics in Cancer: Then and Now
Wang, X., Xu, Y., & Lau, A. T. Y. (2023) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00196 · Cited by 9 · see citing works
Wang, Q., Zhou, L., Qin, G., Tan, C., Zhou, Y.-C., & Yao, S. (2023) · World Journal of Gastroenterology · doi:10.3748/wjg.v29.i37.5313 · Cited by 9 · see citing works
Raj-Kumar, P.-K., Lin, X., Liu, T., Sturtz, L. A., Gritsenko, M., Petyuk, V., Sagendorf, T. J., Deyarmin, B., Liu, J., Praveen-Kumar, A., et al. (2024) · Breast Cancer Research · doi:10.1186/s13058-024-01835-4 · Cited by 8 · see citing works
Stimuli-responsive smart nanomaterials for theranostics of urological cancers
Xu, Y., Moradialvand, M., Sala, F. D., Zare, E. N., Hushmandi, K., Rahimmanesh, I., Borzacchiello, A., Iravani, S., Zare, I., Shin, J., et al. (2025) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2025.216745 · Cited by 8 · see citing works
Peng, L., Zhang, Z., Du, W., Jiang, Z., & Duan, W. (2024) · Journal of Proteomics · doi:10.1016/j.jprot.2024.105260 · Cited by 7 · see citing works
Fan, M., Hu, J., Xu, X., Chen, J., Zhang, W., Zheng, X., Pan, J., Xu, W., & Feng, S. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e38182 · Cited by 7 · see citing works
Li, Q. K., Lih, T. M., Clark, D. J., Chen, L., Schnaubelt, M., & Zhang, H. (2025) · Nature Protocols · doi:10.1038/s41596-024-01113-9 · Cited by 7 · see citing works
Harnessing technologies to unravel gastric cancer heterogeneity
Wang, Y., Jin, R. U., Xu, J., Lin, D., Sun, Z.-Y. J., Xu, Y., Li, Q. K., & Zhang, H. (2025) · Trends in cancer · doi:10.1016/j.trecan.2025.04.011 · Cited by 8 · see citing works
Comprehensive Insights Into the Role of TRPM4 in Pan-Cancer Progression and Immune Regulation
Chang, W., Gao, W., Luo, B., Chen, Y., & Wen, Z. (2025) · ImmunoTargets and Therapy · doi:10.2147/itt.s542176 · Cited by 7 · see citing works
Mouse Stromal Cells Confound Proteomic Characterization and Quantification of Xenograft Models
Shi, Z., Mao, B., Chen, X., Hao, P., & Guo, S. (2023) · Cancer Research Communications · doi:10.1158/2767-9764.crc-22-0431 · Cited by 7 · see citing works
Schmid, K., Sehring, J., Németh, A., Harter, P. N., Weber, K. J., Vengadeswaran, A., Storf, H., Seidemann, C., Karki, K., Fischer, P., et al. (2023) · Brain Pathology · doi:10.1111/bpa.13228 · Cited by 7 · see citing works
Liu, Y., Shi, Q., Su, Y., Chen, Z., & He, X. (2024) · Cancer Medicine · doi:10.1002/cam4.70157 · Cited by 7 · see citing works
Using proteomics for stratification and risk prediction in patients with solid tumors
Werner, T., Fahrner, M., & Schilling, O. (2023) · Die Pathologie · doi:10.1007/s00292-023-01261-x · Cited by 7 · see citing works
Gutiérrez‐González, A., del Hierro, I., & Cariaga-Martínez, A. E. (2024) · Biology · doi:10.3390/biology13110923 · Cited by 7 · see citing works
Du, Y., Xu, K., Zhang, S., Chen, M., Liu, Z., & Xie, L. (2025) · Genes · doi:10.3390/genes16070821 · Cited by 6 · see citing works
The Role of Artificial Intelligence in Early Cancer Detection: A Primer on Artificial Intelligence
Thaker, N. G., Dicker, A. P., Loaiza‐Bonilla, A., Manda, S., Frank, S. J., Orio, P. F., & Doria, C. (2024) · AI in Precision Oncology · doi:10.1089/aipo.2024.0003 · Cited by 6 · see citing works
Zhou, Z., Lu, Y., Gu, Z., Sun, Q., Fang, W., Yan, W., Ku, X., Liang, Z. T., & Hu, G. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106665 · Cited by 6 · see citing works
Mass Spectrometry Proteomics: A Key to Faster Drug Discovery
Tagliazucchi, L., & Costi, M. P. (2025) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5c01986 · Cited by 7 · see citing works
Oncoproteomic profiling of AML: moving beyond genomics
Joshi, S. K., Tognon, C. E., Druker, B. J., & Rodland, K. (2022) · Expert Review of Proteomics · doi:10.1080/14789450.2023.2176757 · Cited by 5 · see citing works
Arolt, C., Hoffmann, F. S., Nachtsheim, L., Mayer, M., Guntinas‐Lichius, O., Buettner, R., von Eggeling, F., Klußmann, J. P., Hillmer, A. M., Quaas, A., et al. (2023) · The Journal of Pathology · doi:10.1002/path.6071 · Cited by 5 · see citing works
Pan, L., Rong, P., Liu, D., Qin, P., Zeng, X., & Peng, S. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10386066 · Cited by 5 · see citing works
Recent advances in biosensors for analysis of DNA/RNA methylation
Ma, Z.-S., Hu, Y., Wang, L., Li, M., Li, C., Li, L., Huang, H., Fang, L., Wang, X., Liu, H., et al. (2024) · Sensing and Bio-Sensing Research · doi:10.1016/j.sbsr.2024.100690 · Cited by 5 · see citing works
Long, H., Zhou, J., Zhou, C., Xie, S., Wang, J., Tan, M., & Xu, J. (2025) · Biomedicines · doi:10.3390/biomedicines13010152 · Cited by 5 · see citing works
Xu, N., Gao, Z., Wu, D., Chen, H., Zhang, Z., Zhang, L., Wang, Y., Lu, X., Xu, Y., Liu, X., et al. (2025) · Clinical and Translational Medicine · doi:10.1002/ctm2.70189 · Cited by 5 · see citing works
Polymerase Chain Reaction Chips for Biomarker Discovery and Validation in Drug Development
Vo, D.-K., & Trinh, K. T. L. (2025) · Micromachines · doi:10.3390/mi16030243 · Cited by 5 · see citing works
A Proteomics Outlook on the Molecular Effectors of CAR-T Cell Therapy in Cancer Management
Teibo, J. O., Picanço‐Castro, V., de Souza, L. E. B., & Faça, V. M. (2025) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00930 · Cited by 5 · see citing works
- Authors
- Mani, D. R., Krug, K., Zhang, B., Satpathy, S., Clauser, K. R., Ding, L., Ellis, M., Gillette, M. A., & Carr, S. A.
- Affiliations
- Broad Institute (US)
- Baylor College of Medicine (US)
- Washington University in St. Louis (US)
- Corresponding author
- Mani, D. R.
- Carr, Steven A.
- ORCID
- Venue
- Nature Reviews Cancer
- Published
- 2022-03-02
- Volume
- 22
- Issue
- 5
- Pages
- 298-313
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- PMC
- PMC12404316
- OpenAlex
- W4214929667
- Cited by
- 229
- References
- 173
- Citations by year
- 2026: 47 · 2025: 56 · 2024: 51 · 2023: 59 · 2022: 16
- FWCI
- 5.32
- Type
- journal article
- Language
- en
- Open access
- green
- pmc.ncbi.nlm.nih.gov
- Locations
- Nature reviews. Cancer (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- Funders
- National Human Genome Research Institute (R01HG009711)
- National Cancer Institute (U24CA210972, P50CA186784, U24CA210954, U24CA210986, U01CA214125, U2CCA233303, U24CA211006, U24CA160034, U24CA210979, U54CA224083)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Prostate Cancer Treatment and Research
- Keywords
- somatic mutations, copy number variation, post-translational modification, targeted therapy resistance, mass spectrometry-based proteomics, cancer immunotherapy, translational oncology
- MeSH terms
- Proteogenomics, Humans, Neoplasms, Genomics, Proteomics, DNA Copy Number Variations
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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