The DOI matches its Crossref record; 150 of the 153 references it cites were found in a registry or an index.
Proteogenomic and metabolomic characterization of human glioblastoma
Open accessAbstract
Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“High-throughput genomic, epigenomic, and transcriptomic profiling of glioblastoma cells revealed three main subtypes harboring distinct molecular and phenotypic landscapes that affect response to the therapy and clinical outcome: mesenchymal, proneural, and classical subtypes.96,97,98,99,100”
From MiR-128-3p – a gray eminence of the human central nervous system (2024) · cites this paper as [100]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Scikit-learn: Machine Learning in Python
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., et al. (2012) · arXiv · doi:10.48550/arxiv.1201.0490 · Cited by 71,016
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
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
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
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
Self-citationRSEM: 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
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., et al. (2019) · Journal of Open Source Software · doi:10.21105/joss.01686 · Cited by 22,138
Radiotherapy Plus Concomitant and Adjuvant Temozolomide for Glioblastoma
Stupp, R., Mason, W. P., van den Bent, M. J., Weller, M., Fisher, B., Taphoorn, M. J. B., Belanger, K., Brandes, A. A., Marosi, C., Bogdahn, U., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa043330 · Cited by 21,807
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
Self-citationThe 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary
Louis, D. N., Perry, A., Reifenberger, G., von Deimling, A., Figarella‐Branger, D., Cavenee, W. K., Ohgaki, H., Wiestler, O. D., Kleihues, P., & Ellison, D. W. (2016) · Acta Neuropathologica · doi:10.1007/s00401-016-1545-1 · Cited by 15,703
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
Self-citationIntegrating single-cell transcriptomic data across different conditions, technologies, and species
Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018) · Nature Biotechnology · doi:10.1038/nbt.4096 · Cited by 13,174
Ostrom, Q. T., Gittleman, H. R., Farah, P., Ondracek, A., Chen, Y., Wolinsky, Y., Stroup, N. E., Kruchko, C., & Barnholtz‐Sloan, J. S. (2013) · Neuro-Oncology · doi:10.1093/neuonc/not151 · Cited by 12,063
Self-citationComplex heatmaps reveal patterns and correlations in multidimensional genomic data
Gu, Z., Eils, R., & Schlesner, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw313 · Cited by 10,037
The mutational constraint spectrum quantified from variation in 141,456 humans
Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., et al. (2020) · Nature · doi:10.1038/s41586-020-2308-7 · Cited by 9,434
Self-citationA map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Self-citationComprehensive genomic characterization defines human glioblastoma genes and core pathways
The Cancer Genome Atlas Research Network (2008) · Nature · doi:10.1038/nature07385 · Cited by 7,735
Verhaak, R. G. W., Hoadley, K. A., Purdom, E., Wang, V., Qi, Y., Wilkerson, M. D., Miller, C. R., Ding, L., Golub, T., Mesirov, J. P., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2009.12.020 · Cited by 7,575
Self-citationO'Leary, N. A., Wright, M. W., Brister, J. R., Ciufo, S., Haddad, D., McVeigh, R., Rajput, B., Robbertse, B., Smith-White, B., Ako-Adjei, D., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1189 · Cited by 6,357
IDH1 and IDH2 Mutations in Gliomas
Yan, H., Parsons, D. W., Jin, G., McLendon, R., Rasheed, B. A., Yuan, W., Kos, I., Batinic-Haberle, I., Jones, S., Riggins, G. J., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0808710 · Cited by 5,847
Self-citationConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking
Wilkerson, M. D., & Hayes, D. N. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq170 · Cited by 5,645
The Reactome pathway Knowledgebase
Fabregat, A., Sidiropoulos, K., Garapati, P., Gillespie, M., Hausmann, K., Haw, R., Jassal, B., Jupe, S., Korninger, F., McKay, S., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1351 · Cited by 5,605
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
Self-citationSensitive detection of somatic point mutations in impure and heterogeneous cancer samples
Cibulskis, K., Lawrence, M. S., Carter, S. L., Sivachenko, A., Jaffe, D. B., Sougnez, C. L., Gabriel, S., Meyerson, M. M., Lander, E. S., & Getz, G. A. (2013) · Nature Biotechnology · doi:10.1038/nbt.2514 · Cited by 4,965
Self-citationVarScan 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 4,954
Self-citationDetermining cell type abundance and expression from bulk tissues with digital cytometry
Newman, A. M., Steen, C. B., Liu, C. L., Gentles, A. J., Chaudhuri, A. A., Scherer, F., Khodadoust, M. S., Esfahani, M. S., Luca, B. A., Steiner, D. F., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0114-2 · Cited by 4,586
Hafemeister, C., & Satija, R. (2019) · Genome Biology · doi:10.1186/s13059-019-1874-1 · Cited by 4,479
xCell: digitally portraying the tissue cellular heterogeneity landscape
Aran, D., Hu, Z., & Butte, A. J. (2017) · Genome Biology · doi:10.1186/s13059-017-1349-1 · Cited by 4,397
ACSL4 dictates ferroptosis sensitivity by shaping cellular lipid composition
Doll, S., Proneth, B., Tyurina, Y. Y., Panzilius, E., Kobayashi, S., Ingold, I., Irmler, M., Beckers, J., Aichler, M., Walch, A., et al. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2239 · Cited by 4,293
TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data
Colaprico, A., Silva, T. C., Olsen, C., Garofano, L., Cava, C., Garolini, D., Sabedot, T. S., Malta, T. M., Pagnotta, S. M., Castiglioni, I., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1507 · Cited by 4,205
Self-citationSystematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1
Barbie, D. A., Tamayo, P., Boehm, J. S., Kim, S. Y., Moody, S. E., Dunn, I. F., Schinzel, A. C., Sandy, P., Meylan, E., Scholl, C., et al. (2009) · Nature · doi:10.1038/nature08460 · Cited by 3,922
Pluskal, T., Castillo, S., Villar‐Briones, A., & Orešič, M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-395 · Cited by 3,852
Orchestrating high-throughput genomic analysis with Bioconductor
Huber, W. K., Carey, V. J., Gentleman, R. C., Anders, S., Carlson, M. R. J., Carvalho, B. S., Bravo, H. C., Davis, S. R., Gatto, L., Girke, T., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3252 · Cited by 3,614
Mermel, C. H., Schumacher, S. E., Hill, B., Meyerson, M. M., Beroukhim, R., & Getz, G. A. (2011) · Genome biology · doi:10.1186/gb-2011-12-4-r41 · Cited by 3,520
Self-citationA Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles
Subramanian, A., Narayan, R., Corsello, S. M., Peck, D. D., Natoli, T. E., Lu, X., Gould, J., Davis, J. F., Tubelli, A. A., Asiedu, J. K., et al. (2017) · Cell · doi:10.1016/j.cell.2017.10.049 · Cited by 3,515
DNA methylation-based classification of central nervous system tumours
Capper, D., Jones, D., Sill, M., Hovestadt, V., Schrimpf, D., Sturm, D., Koelsche, C., Sahm, F., Chávez, L., Reuß, D., et al. (2018) · Nature · doi:10.1038/nature26000 · Cited by 3,114
Self-citationOxidized arachidonic and adrenic PEs navigate cells to ferroptosis
Kagan, V. E., Mao, G., Qu, F., Angeli, J. P. F., Doll, S., Croix, C. S., Dar, H. H., Liu, B., Tyurin, V. A., Ritov, V. B., et al. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2238 · Cited by 3,029
GENCODE reference annotation for the human and mouse genomes
Frankish, A., Diekhans, M., Ferreira, A.-M., Johnson, R., Jungreis, I., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J. C., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky955 · Cited by 3,006
The Reactome Pathway Knowledgebase
Fabregat, A., Jupe, S., Matthews, L. R., Sidiropoulos, K., Gillespie, M. E., Garapati, P. V., Haw, R., Jassal, B., Korninger, F., May, B., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1132 · Cited by 2,862
Snakemake—a scalable bioinformatics workflow engine
Köster, J., & Rahmann, S. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts480 · Cited by 2,780
Ostrom, Q. T., Cioffi, G., Gittleman, H. R., Patil, N. T., Waite, K. A., Kruchko, C., & Barnholtz‐Sloan, J. S. (2019) · Neuro-Oncology · doi:10.1093/neuonc/noz150 · Cited by 2,660
Self-citationStupp, R., Taillibert, S., Kanner, A., Read, W., Steinberg, D. M., Lhermitte, B., Toms, S., Idbaih, A., Ahluwalia, M. S., Fink, K., et al. (2017) · JAMA · doi:10.1001/jama.2017.18718 · Cited by 2,644
Self-citationDELLY: structural variant discovery by integrated paired-end and split-read analysis
Rausch, T., Zichner, T., Schlattl, A., Stütz, A. M., Beneš, V., & Korbel, J. O. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts378 · Cited by 2,438
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 2,307
Self-citationComprehensive Characterization of Cancer Driver Genes and Mutations
Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.060 · Cited by 2,256
Self-citation(2015) · doi:10.1093/bioinformatics/btv710 · Cited by 2,234
Self-citationMetagenes and molecular pattern discovery using matrix factorization
Brunet, J.-P., Tamayo, P., Golub, T. R., & Mesirov, J. P. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308531101 · Cited by 2,183
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
Malta, T. M., Sokolov, A., Gentles, A. J., Burzykowski, T., Poisson, L., Weinstein, J. N., Kamińska, B., Huelsken, J., Omberg, L., Gevaert, O., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.034 · Cited by 2,180
Self-citationWang, Q., Hu, B., Hu, X., Kim, H., Squatrito, M., Scarpace, L. M., deCarvalho, A. C., Lyu, S., Li, P., Li, Y., et al. (2017) · Cancer Cell · doi:10.1016/j.ccell.2017.06.003 · Cited by 2,039
Self-citationYe, K., Schulz, M. H., Long, Q., Apweiler, R., & Ning, Z. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp394 · Cited by 2,029
Lipid peroxidation in cell death
Gaschler, M. M., & Stockwell, B. R. (2017) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2016.10.086 · Cited by 1,853
Sturm, D., Witt, H., Hovestadt, V., Khuong-Quang, D.-A., Jones, D. T. W., Konermann, C., Pfaff, E., Tönjes, M., Sill, M., Bender, S., et al. (2012) · Cancer Cell · doi:10.1016/j.ccr.2012.08.024 · Cited by 1,828
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
Self-citationBioconda: sustainable and comprehensive software distribution for the life sciences
Grüning, B., Dale, R., Sjödin, A., Chapman, B., Rowe, J., Tomkins-Tinch, C. H., Valieris, R., Caprez, A., Batut, B., Haudgaard, M., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0046-7 · Cited by 1,673
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
Self-citationBeausoleil, S. A., Villén, J., Gerber, S. A., Rush, J., & Gygi, S. P. (2006) · Nature Biotechnology · doi:10.1038/nbt1240 · Cited by 1,577
A flexible R package for nonnegative matrix factorization
Gaujoux, R., & Seoighe, C. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-367 · Cited by 1,516
Kind, T., Wohlgemuth, G., Lee, D. Y., Lü, Y., Palazoglu, M., Shahbaz, S., & Fiehn, O. (2009) · Analytical Chemistry · doi:10.1021/ac9019522 · Cited by 1,486
Current state of immunotherapy for glioblastoma
Lim, M. K., Xia, Y., Bettegowda, C., & Weller, M. (2018) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-018-0003-5 · Cited by 1,396
Killela, P. J., Reitman, Z. J., Jiao, Y., Bettegowda, C., Agrawal, N., Diaz, L. A., Friedman, A. H., Friedman, H., Gallia, G. L., Giovanella, B. C., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1303607110 · Cited by 1,368
Self-citationCORUM: the comprehensive resource of mammalian protein complexes—2009
Ruepp, A., Wägele, B., Lechner, M., Brauner, B., Dunger-Kaltenbach, I., Fobo, G., Frishman, G., Montrone, C., & Mewes, H. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp914 · Cited by 1,299
Functions and mechanisms of non-histone protein acetylation
Narita, T., Weinert, B. T., & Choudhary, C. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0081-3 · Cited by 1,232
Short-Course Radiation plus Temozolomide in Elderly Patients with Glioblastoma
Perry, J., Laperrière, N., O'Callaghan, C. J., Brandes, A. A., Menten, J. J., Phillips, C., Fay, M. F., Nishikawa, R., Cairncross, J. G., Roa, W., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1611977 · Cited by 1,179
CIRI: an efficient and unbiased algorithm for de novo circular RNA identification
Gao, Y., Wang, J., & Zhao, F. (2015) · Genome biology · doi:10.1186/s13059-014-0571-3 · Cited by 1,115
Self-citationMS-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
Histone acetylation: a switch between repressive and permissive chromatin
Eberharter, A., & Becker, P. B. (2002) · EMBO Reports · doi:10.1093/embo-reports/kvf053 · Cited by 944
Brat, D. J., Aldape, K., Colman, H., Holland, E. C., Louis, D. N., Jenkins, R. B., Kleinschmidt-DeMasters, B. K., Perry, A., Reifenberger, G., Stupp, R., et al. (2018) · Acta Neuropathologica · doi:10.1007/s00401-018-1913-0 · Cited by 904
DGIdb 3.0: a redesign and expansion of the drug–gene interaction database
Cotto, K. C., Wagner, A. H., Feng, Y.-Y., Kiwala, S., Coffman, A. C., Spies, G., Wollam, A., Spies, N. C., Griffith, O. L., & Griffith, M. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1143 · Cited by 877
Kim, H., & Park, H. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm134 · Cited by 865
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
Self-citationZhou, W., Laird, P. W., & Shen, H. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw967 · Cited by 742
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
Self-citationSurvival in glioblastoma: a review on the impact of treatment modalities
López, P. D. D., & Corrales-García, E. M. (2016) · Clinical & Translational Oncology · doi:10.1007/s12094-016-1497-x · Cited by 693
OmniPath: guidelines and gateway for literature-curated signaling pathway resources
Türei, D., Korcsmáros, T., & Sáez-Rodríguez, J. (2016) · Nature Methods · doi:10.1038/nmeth.4077 · Cited by 687
Fisher, S., Barry, A. J., Abreu, J., Minie, B., Nolan, J., Delorey, T. M., Young, G., Fennell, T. J., Allen, A., Ambrogio, L., et al. (2011) · Genome biology · doi:10.1186/gb-2011-12-1-r1 · Cited by 676
Self-citationHaas, B. J., Dobin, A., Li, B., Stransky, N., Pochet, N., & Regev, A. (2019) · Genome biology · doi:10.1186/s13059-019-1842-9 · Cited by 646
Li, S., Shen, D., Shao, J., Crowder, R. J., Liu, W., Prat, A., He, X., Liu, S., Hoog, J., Lu, C., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.08.022 · Cited by 637
Self-citationStupp, R., Taillibert, S., Kanner, A. A., Read, W. L., Steinberg, D. M., Lhermitte, B., Toms, S. A., Idbaïh, A., Ahluwalia, M. S., Fink, K., et al. (2017) · Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) · doi:10.5167/uzh-143757 · Cited by 630
Self-citationDriver Fusions and Their Implications in the Development and Treatment of Human Cancers
Gao, Q., Liang, W.-W., Foltz, S. M., Mutharasu, G., Jayasinghe, R. G., Cao, S., Liao, W., Reynolds, S. M., Wyczalkowski, M. A., Yao, L., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.050 · Cited by 608
Self-citationButowski, N. A., Colman, H., de Groot, J., Omuro, A. M. P., Nayak, L., Wen, P. Y., Cloughesy, T. F., Marimuthu, A., Haidar, S., Perry, A., et al. (2015) · Neuro-Oncology · doi:10.1093/neuonc/nov245 · Cited by 593
Role for Akt3/Protein Kinase Bγ in Attainment of Normal Brain Size
Easton, R., Cho, H., Roovers, K., Shineman, D. W., Mizrahi, M., Forman, M. S., Lee, V. M. ‐., Szabolcs, M. J., de Jong, R., Oltersdorf, T., et al. (2005) · Molecular and Cellular Biology · doi:10.1128/mcb.25.5.1869-1878.2005 · Cited by 551
Yan, H., Killela, P. J., Reitman, Z. J., Jiao, Y., Bettegowda, C., Agrawal, N., Diaz, L. A., Friedman, A. H., Friedman, H. S., Gallia, G. L., et al. (2014) · Neuro-Oncology · doi:10.1093/neuonc/nou206.18 · Cited by 531
Self-citationProteogenomic 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
Self-citationImmune Microenvironment in Glioblastoma Subtypes
Chen, Z., & Hambardzumyan, D. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01004 · Cited by 449
Hiller, K., Hangebrauk, J., Jäger, C., Spura, J., Schreiber, K., & Schomburg, D. (2009) · Analytical Chemistry · doi:10.1021/ac802689c · Cited by 443
DAnTE: a statistical tool for quantitative analysis of -omics data
Polpitiya, A. D., Qian, W., Jaitly, N., Petyuk, V., Adkins, J., Camp, D., Anderson, G., & Smith, R. D. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn217 · Cited by 431
Self-citationKeenan, A. B., Jenkins, S. L., Jagodnik, K. M., Koplev, S., He, E., Torre, D., Wang, Z., Dohlman, A. B., Silverstein, M. C., Lachmann, A., et al. (2018) · Cell Systems · doi:10.1016/j.cels.2017.11.001 · Cited by 423
Self-citationKim, S., Gupta, N., & Pevzner, P. A. (2008) · Journal of Proteome Research · doi:10.1021/pr8001244 · Cited by 412
TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach
Zecha, J., Satpathy, S., Kanashova, T., Avanessian, S. C., Kane, M. H., Clauser, K. R., Mertins, P., Carr, S. A., & Küster, B. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir119.001385 · Cited by 400
Self-citationThe Double Bromodomain Proteins Brd2 and Brd3 Couple Histone Acetylation to Transcription
LeRoy, G., Rickards, B., & Flint, S. J. (2008) · Molecular Cell · doi:10.1016/j.molcel.2008.01.018 · Cited by 397
Social network architecture of human immune cells unveiled by quantitative proteomics
Rieckmann, J. C., Geiger, R., Hornburg, D., Wolf, T., Kveler, K., Jarrossay, D., Sallusto, F., Shen-Orr, S. S., Lanzavecchia, A., Mann, M., et al. (2017) · Nature Immunology · doi:10.1038/ni.3693 · Cited by 385
The landscape of the mesenchymal signature in brain tumours
Behnan, J., Finocchiaro, G., & Hanna, G. (2019) · Brain · doi:10.1093/brain/awz044 · Cited by 357
Bady, P., Sciuscio, D., Diserens, A., Bloch, J., van den Bent, M. J., Marosi, C., Dietrich, P.-Y., Weller, M., Mariani, L., Heppner, F. L., et al. (2012) · Acta Neuropathologica · doi:10.1007/s00401-012-1016-2 · Cited by 351
KinomeXplorer: an integrated platform for kinome biology studies
Horn, H., Schoof, E. M., Kim, J., Robin, X., Miller, M. L., Diella, F., Palma, A., Cesareni, G., Jensen, L. J., & Linding, R. (2014) · Nature Methods · doi:10.1038/nmeth.2968 · Cited by 338
Arg1 expression defines immunosuppressive subsets of tumor-associated macrophages
Arlauckas, S. P., Garren, S. B., Garris, C., Köhler, R. H., Oh, J., Pittet, M. J., & Weissleder, R. (2018) · Theranostics · doi:10.7150/thno.26888 · Cited by 337
TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages
Silva, T. C., Colaprico, A., Olsen, C., D’Angelo, F., Bontempi, G., Ceccarelli, M., & Noushmehr, H. (2016) · F1000Research · doi:10.12688/f1000research.8923.1 · Cited by 303
Self-citationCurrent State of Immunotherapy for Treatment of Glioblastoma
McGranahan, T. M., Therkelsen, K. E., Ahmad, S., & Nagpal, S. (2019) · Current Treatment Options in Oncology · doi:10.1007/s11864-019-0619-4 · Cited by 287
Nassiri, F., Mamatjan, Y., Suppiah, S., Badhiwala, J. H., Mansouri, S., Karimi, S., Saarela, O., Poisson, L., Gepfner‐Tuma, I., Schittenhelm, J., et al. (2019) · Neuro-Oncology · doi:10.1093/neuonc/noz061 · Cited by 267
SIGNOR: a database of causal relationships between biological entities
Perfetto, L., Briganti, L., Calderone, A., Perpetuini, A. C., Iannuccelli, M., Langone, F., Licata, L., Marinkovic, M., Mattioni, A., Pavlidou, T., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1048 · Cited by 235
Nakayasu, E. S., Nicora, C., Sims, A. M., Burnum-Johnson, K., Kim, Y., Kyle, J. E., Matzke, M. M., Shukla, A. K., Chu, R., Schepmoes, A., et al. (2016) · mSystems · doi:10.1128/msystems.00043-16 · Cited by 235
Self-citationDiscovering chimeric transcripts in paired-end RNA-seq data by using EricScript
Benelli, M., Pescucci, C., Marseglia, G., Severgnini, M., Torricelli, F., & Magi, A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts617 · Cited by 231
Estimating telomere length from whole genome sequence data
Ding, Z., Mangino, M., Aviv, A., Spector, T. D., & Durbin, R. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku181 · Cited by 224
A Novel Role for Gab1 and SHP2 in Epidermal Growth Factor-induced Ras Activation
Montagner, A., Yart, A., Dance, M., Perret, B., Salles, J., & Raynal, P. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m410012200 · Cited by 210
Recurrent chimeric fusion RNAs in non-cancer tissues and cells
Babiceanu, M., Qin, F., Xie, Z., Jia, Y., Lopez, K., Janus, N., Facemire, L., Kumar, S., Pang, Y., Qi, Y., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw032 · Cited by 208
The Two Faces of Tumor-Associated Macrophages and Their Clinical Significance in Colorectal Cancer
Pinto, M. L., Rios, E., Durães, C., Ribeiro, R. J. T., Machado, J. C., Mantovani, A., Barbosa, M. A., Carneiro, F., & Oliveira, M. J. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.01875 · Cited by 208
SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 update
Licata, L., Surdo, P. L., Iannuccelli, M., Palma, A., Micarelli, E., Perfetto, L., Peluso, D., Calderone, A., Castagnoli, L., & Cesareni, G. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz949 · Cited by 206
Monroe, M. E., Shaw, J. L., Daly, D. S., Adkins, J., & Smith, R. D. (2008) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2008.02.006 · Cited by 202
Self-citationLarge-scale profiling of microRNAs for The Cancer Genome Atlas
Chu, A., Robertson, G., Brooks, D., Mungall, A. J. J., Birol, İ., Coope, R., Ma, Y. P., Jones, S. J. M., & Marra, M. A. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv808 · Cited by 171
Plasminogen Activator Inhibitor-1 Promotes the Recruitment and Polarization of Macrophages in Cancer
Kubala, M. H., Punj, V., Placencio-Hickok, V., Hua, F., Fernández, G. E., Sposto, R., & DeClerck, Y. A. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.10.082 · Cited by 166
LINCS Data Portal 2.0: next generation access point for perturbation-response signatures
Stathias, V., Turner, J., Koleti, A., Vidovic, D., Cooper, D., Fazel-Najafabadi, M., Pilarczyk, M., Terryn, R., Chung, C., Umeano, A., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkz1023 · Cited by 161
Self-citationLouis, D. N., Aldape, K. D., Brat, D. J., Capper, D., Ellison, D. W., Hawkins, C. E., Paulus, W., Perry, A., Reifenberger, G., Figarella-Branger, D. F., et al. (2016) · Acta Neuropathologica · doi:10.1007/s00401-016-1646-x · Cited by 155
Connecting omics signatures and revealing biological mechanisms with iLINCS
Pilarczyk, M., Fazel‐Najafabadi, M., Kouril, M., Shamsaei, B., Vasiliauskas, J., Niu, W., Mahi, N. A., Zhang, L., Clark, N. A., Ren, Y., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32205-3 · Cited by 154
Self-citationXi, R., Lee, S., Xia, Y., Kim, T., & Park, P. J. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw491 · Cited by 140
SUMO1 modification stabilizes CDK6 protein and drives the cell cycle and glioblastoma progression
Bellail, A. C., Olson, J. J., & Hao, C. (2014) · Nature Communications · doi:10.1038/ncomms5234 · Cited by 132
INTEGRATE: gene fusion discovery using whole genome and transcriptome dataPreprint
Zhang, J., White, N. M. A., Schmidt, H. K., Fulton, R. S., Tomlinson, C., Warren, W. C., Wilson, R. K., & Maher, C. A. (2015) · Genome Research · doi:10.1101/gr.186114.114 · Cited by 128
Salomonis, N., Dexheimer, P. J., Omberg, L., Schroll, R., Bush, S., Huo, J. S., Schriml, L. M., Sui, S. H., Keddache, M. A., Mayhew, C. N., et al. (2016) · Stem Cell Reports · doi:10.1016/j.stemcr.2016.05.006 · Cited by 125
An EGFR-ERK-SOX9 Signaling Cascade Links Urothelial Development and Regeneration to Cancer
Ling, S., Chang, X., Schultz, L., Lee, T. K. M., Chaux, A., Marchionni, L., Netto, G. J., Sidransky, D., & Berman, D. M. (2011) · Cancer Research · doi:10.1158/0008-5472.can-10-3072 · Cited by 121
LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data
Kyle, J. E., Crowell, K. L., Casey, C., Fujimoto, G. M., Kim, S., Dautel, S. E., Smith, R. D., Payne, S., & Metz, T. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx046 · Cited by 113
Self-citationPoulin, B., Sekiya, F., & Rhee, S. G. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0409590102 · Cited by 108
Improved quality control processing of peptide-centric LC-MS proteomics data
Matzke, M. M., Waters, K. M., Metz, T. O., Jacobs, J. M., Sims, A. C., Baric, R. S., Pounds, J. G., & Webb-Robertson, B.-J. M. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr479 · Cited by 107
Voena, C., Conte, C., Ambrogio, C., Erba, E. B., Boccalatte, F. E., Mohammed, S., Jensen, O. N., Palestro, G., Inghirami, G., & Chiarle, R. (2007) · Cancer Research · doi:10.1158/0008-5472.can-06-4350 · Cited by 103
Interpreting pathways to discover cancer driver genes with Moonlight
Colaprico, A., Olsen, C., Bailey, M. H., Odom, G., Terkelsen, T., Silva, T. C., Olsen, A. V., Cantini, L., Zinovyev, A. Y., Barillot, E., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-13803-0 · Cited by 101
Self-citationONE-CLASS DETECTION OF CELL STATES IN TUMOR SUBTYPES
Sokolov, A., Paull, E., & Stuart, J. M. (2015) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814749411_0037 · Cited by 94
Karimi, S., Zuccato, J., Mamatjan, Y., Mansouri, S., Suppiah, S., Nassiri, F., Diamandis, P., Muñoz, D. G., Aldape, K., & Zadeh, G. M. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0766-2 · Cited by 94
Liu, L., Shi, Y., Shi, J. Y., Wang, H., Sheng, Y., Jiang, Q., Chen, H., Li, X., & Dong, J. (2019) · Cell Death and Disease · doi:10.1038/s41419-019-1698-7 · Cited by 91
Self-citationLitichevskiy, L., Peckner, R., Abelin, J. G., Asiedu, J. K., Creech, A. L., Davis, J. F., Davison, D., Dunning, C. M., Egertson, J. D., Egri, S. B., et al. (2018) · Cell Systems · doi:10.1016/j.cels.2018.03.012 · Cited by 85
Self-citationCausal Interactions from Proteomic Profiles: Molecular Data Meets Pathway Knowledge
Babur, Ö., Luna, A., Korkut, A., Durupınar, F., Siper, M. C., Doğrusöz, U., Jácome, A. S. V., Peckner, R., Christianson, K. E., Jaffe, J. D., et al. (2020) · Patterns · doi:10.1016/j.patter.2021.100257 · Cited by 85
Self-citationDaily, K., Ho Sui, S. J., Schriml, L. M., Dexheimer, P. J., Salomonis, N., Schroll, R., Bush, S., Keddache, M., Mayhew, C., Lotia, S., et al. (2017) · Scientific Data · doi:10.1038/sdata.2017.30 · Cited by 81
Self-citationHe, H., Conrad, C. A., Nilsson, C. L., Ji, Y., Schaub, T. M., Marshall, A. G., & Emmett, M. R. (2007) · Analytical Chemistry · doi:10.1021/ac071413m · Cited by 74
Kunze, K., Spieker, T., Gamerdinger, U., Nau, K., Berger, J., Dreyer, T., Sindermann, J. R., Hoffmeier, A., Gattenlöhner, S., & Bräuninger, A. (2014) · Cancer Research · doi:10.1158/0008-5472.can-14-1162 · Cited by 74
The human DEPhOsphorylation database DEPOD: a 2015 update
Duan, G., Li, X., & Köhn, M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1009 · Cited by 71
Quantifying circular RNA expression from RNA-seq data using model-based framework
Li, M., Xie, X., Zhou, J., Sheng, M., Yin, X., Ko, E.-A., Zhou, T., & Gu, W. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx129 · Cited by 64
Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts
Tabb, D. L., Wang, X., Carr, S. A., Clauser, K. R., Mertins, P., Chambers, M., Holman, J. D., Wang, J., Zhang, B., Zimmerman, L. J., et al. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00859 · Cited by 54
Self-citationCorrecting systematic bias and instrument measurement drift with mzRefinery
Gibbons, B. C., Chambers, M., Monroe, M. E., Tabb, D. L., & Payne, S. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv437 · Cited by 52
Self-citationIRF8 is a transcriptional determinant for microglial motility
Masuda, T., Nishimoto, N., Tomiyama, D., Matsuda, T., Tozaki‐Saitoh, H., Tamura, T., Kohsaka, S., Tsuda, M., & Inoue, K. (2014) · Purinergic Signalling · doi:10.1007/s11302-014-9413-8 · Cited by 51
Modulation of β-Catenin Phosphorylation/Degradation by Cyclin-dependent Kinase 2
Park, C. S., Kim, S. I., Lee, M. S., Youn, C.-Y., Kim, D. J., Jho, E., & Song, W. K. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m314208200 · Cited by 47
MODMatcher: Multi-Omics Data Matcher for Integrative Genomic Analysis
Yoo, S., Huang, T., Campbell, J. D., Lee, E., Tu, Z., Geraci, M. W., Powell, C. A., Schadt, E. E., Spira, A. E., & Zhu, J. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003790 · Cited by 36
Self-citationWebb‐Robertson, B., Kim, Y., Zink, E., Hallaian, K., Zhang, Q., Madupu, R., Waters, K. M., & Metz, T. (2014) · Metabolomics · doi:10.1007/s11306-014-0642-1 · Cited by 32
Self-citationSong, 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
Self-citationRole of histone deacetylase 2 and its posttranslational modifications in cardiac hypertrophy
Eom, G. H., & Kook, H. Y. (2015) · BMB Reports · doi:10.5483/bmbrep.2015.48.3.242 · Cited by 29
Database of evidence for precision oncology portal
Sun, S. Q., Mashl, R. J., Sengupta, S., Scott, A. D., Wang, W., Batra, P., Wang, L.-B., Wyczalkowski, M. A., & Ding, L. J. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty531 · Cited by 27
Self-citationBhagat, U., & Das, U. N. (2015) · Archives of Medical Science · doi:10.5114/aoms.2015.53302 · Cited by 22
Gu, X., Hua, Z., Dong, Y., Zhan, Y., Zhang, X., Tian, W., Liu, Z., Thiele, C. J., & Li, Z. (2017) · Scientific Reports · doi:10.1038/srep42062 · Cited by 17
Webb‐Robertson, B., Matzke, M. M., Metz, T., McDermott, J., Walker, H., Rodland, K., Pounds, J. G., & Waters, K. M. (2013) · BioTechniques · doi:10.2144/000113978 · Cited by 16
Self-citationBlackSheep: 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
Self-citationInterpreting pathways to discover cancer driver genes with Moonlight
Colaprico, A., Olsen, C., Bailey, M. H., Odom, G., Terkelsen, T., Silva, T. C., Olsen, A. V., Cantini, L., Zinovyev, A. Y., Barillot, E., et al. (2020) · doi:10.7490/f1000research.1118074.1 · Cited by 9
Self-citation
Research works printed but not linked: 1
- Pilarczyk, 2019, Connecting Omics Signatures of Diseases, Drugs, and Mechanisms of Actions with iLINCS, BioRxiv, 826271
Cited by
Sorted by citations
Gu, Z. (2022) · iMeta · doi:10.1002/imt2.43 · Cited by 1,943
Small molecule metabolites: discovery of biomarkers and therapeutic targets
Qiu, S., Cai, Y., Yao, H., Lin, C., Xie, Y., Tang, S., & Zhang, A. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01399-3 · Cited by 993
Microglia: Immune and non-immune functions
Borst, K., Dumas, A. A., & Prinz, M. (2021) · Immunity · doi:10.1016/j.immuni.2021.09.014 · Cited by 804
Proteogenomic characterization of pancreatic ductal adenocarcinoma
Cao, L., Huang, C., Cui Zhou, D., Hu, Y., Lih, T. M., Savage, S. R., Krug, K., Clark, D. J., Schnaubelt, M., Chen, L., et al. (2021) · Cell · doi:10.1016/j.cell.2021.08.023 · Cited by 578
Self-citationZhong, Q., Xiao, X., Qiu, Y., Xu, Z., Chen, C., Chong, B., Zhao, X., Hai, S., Li, S., An, Z., et al. (2023) · MedComm · doi:10.1002/mco2.261 · Cited by 442
Metadata
- Authors
- Wang, L.-B., Karpova, A., Gritsenko, M. A., Kyle, J. E., Cao, S., Li, Y., Rykunov, D., Colaprico, A., Rothstein, J. H., Hong, R., Stathias, V., Cornwell, M., Petralia, F., Wu, Y., Reva, B., Krug, K., Pugliese, P., Kawaler, E., Olsen, L. K., Liang, W.-W., Song, X., Dou, Y., Wendl, M. C., Caravan, W., Liu, W., Cui Zhou, D., Ji, J., Tsai, C.-F., Petyuk, V. A., Moon, J., Ma, W., Chu, R. K., Weitz, K. K., Moore, R. J., Monroe, M. E., Zhao, R., Yang, X., Yoo, S., Krek, A., Demopoulos, A., Zhu, H., Wyczalkowski, M. A., McMichael, J. F., Henderson, B. L., Lindgren, C. M., Boekweg, H., Lu, S., Baral, J., Yao, L., Stratton, K. G., Bramer, L. M., Zink, E., Couvillion, S. P., Bloodsworth, K. J., Satpathy, S., Sieh, W., Boca, S. M., Schürer, S., Chen, F., Wiznerowicz, M., Ketchum, K. A., Boja, E. S., Kinsinger, C. R., Robles, A. I., Hiltke, T., Thiagarajan, M., Nesvizhskii, A. I., Zhang, B., Mani, D. R., Ceccarelli, M., Chen, X. S., Cottingham, S. L., Li, Q. K., Kim, A. H., Fenyö, D., Ruggles, K. V., Rodriguez, H., Mesri, M., Payne, S. H., Resnick, A. C., Wang, P., Smith, R. D., Iavarone, A., Chheda, M. G., Barnholtz-Sloan, J. S., Rodland, K. D., Liu, T., Ding, L., Agarwal, A., Amin, M., An, E., Anderson, M. L., Andrews, D. W., Bauer, T., Birger, C., Birrer, M. J., Blumenberg, L., Bocik, W. E., Borate, U., Borucki, M., Burke, M. C., Cai, S., Calinawan, A. P., Carr, S. A., Cerda, S., Chan, D. W., Charamut, A., Chen, L. S., Chesla, D., Chinnaiyan, A. M., Chowdhury, S., Cieślik, M. P., Clark, D. J., Culpepper, H., Czernicki, T., D'Angelo, F., Day, J., De Young, S., Demir, E., Dhanasekaran, S. M., Dhir, R., Domagalski, M. J., Druker, B., Duffy, E., Dyer, M., Edwards, N. J., Edwards, R., Elburn, K., Ellis, M. J., Eschbacher, J., Francis, A., Gabriel, S., Gabrovski, N., Garofano, L., Getz, G., Gillette, M. A., Godwin, A. K., Golbin, D., Hanhan, Z., Hannick, L. I., Hariharan, P., Hindenach, B., Hoadley, K. A., Hostetter, G., Huang, C., Jaehnig, E., Jewell, S. D., Ji, N., Jones, C. D., Karz, A., Kaspera, W., Kim, L., Kothadia, R. B., Kumar-Sinha, C., Lei, J., Leprevost, F. D., Li, K., Liao, Y., Lilly, J., Liu, H., Lubínski, J., Madan, R., Maggio, W., Malc, E., Malovannaya, A., Mareedu, S., Markey, S. P., Marrero-Oliveras, A., Martinez, N., Maunganidze, N., McDermott, J. E., McGarvey, P. B., McGee, J., Mieczkowski, P., Migliozzi, S., Modugno, F., Montgomery, R., Newton, C. J., Omenn, G. S., Ozbek, U., Paklina, O. V., Paulovich, A. G., Perou, A. M., Pico, A. R., Piehowski, P. D., Placantonakis, D. G., Polonskaya, L., Potapova, O., Pruetz, B., Qi, L., Ramkissoon, S., Resnick, A., Richey, S., Riggins, G., Robinson, K., Roche, N., Rohrer, D. C., Rood, B. R., Rossell, L., Savage, S. R., Schadt, E. E., Shi, Y., Shi, Z., Shutack, Y., Singh, S., Skelly, T., Sokoll, L. J., Stawicki, J., Stein, S. E., Suh, J., Szopa, W., Tabor, D., Tan, D., Tansil, D., Thangudu, R. R., Tognon, C., Traer, E., Tsang, S., Tyner, J., Um, K. S., Valley, D. R., Vasaikar, S., Vatanian, N., Velvulou, U., Vernon, M., Wan, W., Wang, J., Webster, A., Wen, B., Whiteaker, J. R., Wilson, G. D., Zakhartsev, Y., Zelt, R., Zhang, H., Zhang, L., Zhang, Z., Zhao, G., & Zhu, J.
- Affiliations
- Washington University in St. Louis (US)
- Pacific Northwest National Laboratory (US)
- Icahn School of Medicine at Mount Sinai (US)
- University of Miami (US)
- NYU Langone Health (US)
- New York University (US)
- Broad Institute (US)
- University of Sannio (IT)
- Brigham Young University (US)
- Tisch Cancer Institute (US)
- Baylor College of Medicine (US)
- Poznan University of Medical Sciences (PL)
- Northwell Health (US)
- Georgetown University Medical Center (US)
- Enterprise Science and Computing (United States) (US)
- National Cancer Institute (US)
- Frederick National Laboratory for Cancer Research (US)
- University of Michigan (US)
- Biogem (IT)
- Spectrum Health (US)
- Johns Hopkins University (US)
- Columbia University Irving Medical Center (US)
- University Hospitals of Cleveland (US)
- Corresponding author
- Rodland, Karin D.
- Liu, Tao
- Ding, Li
- ORCID
- Wang, Liang-Bo
- Karpova, Alla
- Kyle, Jennifer E.
- Cao, Song
- Li, Yize
- Rykunov, Dmitry
- Colaprico, Antonio
- Rothstein, Joseph H.
- Hong, Runyu
- Stathias, Vasileios
- Cornwell, MacIntosh
- Petralia, Francesca
- Wu, Yige
- Reva, Boris
- Krug, Karsten
- Pugliese, Pietro
- Kawaler, Emily
- Liang, Wen-Wei
- Song, Xiaoyu
- Dou, Yongchao
- Wendl, Michael C.
- Caravan, Wagma
- Liu, Wenke
- Ji, Jiayi
- Tsai, Chia-Feng
- Petyuk, Vladislav A.
- Moon, Jamie
- Ma, Weiping
- Chu, Rosalie K.
- Weitz, Karl K.
- Moore, Ronald J.
- Monroe, Matthew E.
- Zhao, Rui
- Yang, Xiaolu
- Yoo, Seungyeul
- Krek, Azra
- Wyczalkowski, Matthew A.
- McMichael, Joshua F.
- Henderson, Brittany L.
- Lindgren, Caleb M.
- Lu, Shuangjia
- Stratton, Kelly G.
- Bramer, Lisa M.
- Zink, Erika
- Couvillion, Sneha P.
- Bloodsworth, Kent J.
- Satpathy, Shankha
- Sieh, Weiva
- Boca, Simina M.
- Schürer, Stephan
- Chen, Feng
- Wiznerowicz, Maciej
- Ketchum, Karen A.
- Boja, Emily S.
- Kinsinger, Christopher R.
- Robles, Ana I.
- Hiltke, Tara
- Thiagarajan, Mathangi
- Nesvizhskii, Alexey I.
- Zhang, Bing
- Mani, D.R.
- Ceccarelli, Michele
- Li, Qing Kay
- Kim, Albert H.
- Fenyö, David
- Ruggles, Kelly V.
- Rodriguez, Henry
- Mesri, Mehdi
- Wang, Pei
- Smith, Richard D.
- Iavarone, Antonio
- Chheda, Milan G.
- Rodland, Karin D.
- Liu, Tao
- Ding, Li
- Agarwal, Anupriya
- Amin, Mitual
- An, Eunkyung
- Anderson, Matthew L.
- Andrews, David W.
- Birrer, Michael J.
- Blumenberg, Lili
- Bocik, William E.
- Borate, Uma
- Burke, Meghan C.
- Cai, Shuang
- Calinawan, Anna P.
- Carr, Steven A.
- Chan, Daniel W.
- Chen, Lin S.
- Chinnaiyan, Arul M.
- Chowdhury, Shrabanti
- Clark, David J.
- Czernicki, Tomasz
- Demir, Emek
- Dhanasekaran, Saravana Mohan
- Dhir, Rajiv
- Domagalski, Marcin J.
- Druker, Brian
- Duffy, Elizabeth
- Dyer, Maureen
- Edwards, Nathan J.
- Edwards, Robert
- Ellis, Matthew J.
- Eschbacher, Jennifer
- Francis, Alicia
- Gabriel, Stacey
- Garofano, Luciano
- Getz, Gad
- Gillette, Michael A.
- Godwin, Andrew K.
- Golbin, Denis
- Hannick, Linda I.
- Hoadley, Katherine A.
- Hostetter, Galen
- Huang, Chen
- Jaehnig, Eric
- Jewell, Scott D.
- Ji, Nan
- Jones, Corbin D.
- Karz, Alcida
- Kaspera, Wojciech
- Kothadia, Ramani B.
- Lei, Jonathan
- Leprevost, Felipe D.
- Li, Kai
- Liao, Yuxing
- Lilly, Jena
- Liu, Hongwei
- Madan, Rashna
- Malc, Ewa
- Malovannaya, Anna
- Martinez, Nina
- McGarvey, Peter B.
- Mieczkowski, Piotr
- Migliozzi, Simona
- Modugno, Francesmary
- Omenn, Gilbert S.
- Paklina, Oxana V.
- Paulovich, Amanda G.
- Pico, Alexander R.
- Piehowski, Paul D.
- Placantonakis, Dimitris G.
- Potapova, Olga
- Riggins, Gregory
- Rohrer, Daniel C.
- Rood, Brian R.
- Savage, Sara R.
- Schadt, Eric E.
- Shi, Yan
- Shi, Zhiao
- Sokoll, Lori J.
- Stawicki, Jakub
- Stein, Stephen E.
- Suh, James
- Szopa, Wojciech
- Thangudu, Ratna R.
- Tognon, Cristina
- Traer, Elie
- Tyner, Jeffrey
- Vasaikar, Suhas
- Wan, Weiqing
- Wen, Bo
- Whiteaker, Jeffrey R.
- Wilson, George D.
- Zhang, Hui
- Zhang, Zhen
- Zhao, Grace
- Zhu, Jun
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 39
- Issue
- 4
- Pages
- 509-528.e20
- ISSN
- 1535-6108 (ISSN-L)
- PMC
- PMC8044053
- OpenAlex
- W3126609356
- Cited by
- 661
- References
- 153
- Citations by year
- 2026: 103 · 2025: 124 · 2024: 127 · 2023: 140 · 2022: 123 · 2021: 43
- FWCI
- 62.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cancer Cell (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- National Institutes of Health
- U.S. Department of Energy (DE-AC05-76RL01830)
- National Human Genome Research Institute (R01HG009711, R01NS107833)
- National Cancer Institute (U01CA214125, U24CA210954, U24CA210955, U24CA210967, U24CA210972, U24CA210979, U24CA210985, U24CA210986, U24CA210993)
- Orbus Therapeutics
- Topics
- Health Sciences › Medicine › Oncology › Glioma Diagnosis and Treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Keywords
- glioblastoma, proteogenomics, metabolomics, post-translational modification, protein phosphorylation, PTPN11, phospholipase C-gamma1, EGFR, TP53, RB1, tumor immune subtypes, single-cell RNA sequencing, histone acetylation, CREB-binding protein, EP300, lipid metabolism, IDH mutation, molecular subtypes, patient stratification
- MeSH terms
- Proteogenomics, Brain Neoplasms, Glioblastoma, Humans, Mutation, Phosphorylation, Computational Biology, Proteomics, Phospholipase C gamma, Protein Tyrosine Phosphatase, Non-Receptor Type 11, Metabolomics
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review