RESUMEN
The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.
Asunto(s)
Neoplasias , Proteogenómica , Humanos , Proteómica , Genómica , Neoplasias/genética , Perfilación de la Expresión GénicaRESUMEN
Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.
Asunto(s)
Neoplasias , Proteogenómica , Humanos , Neoplasias/genética , Oncogenes , Transformación Celular Neoplásica/genética , Variaciones en el Número de Copia de ADNRESUMEN
Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.
Asunto(s)
Neoplasias , Procesamiento Proteico-Postraduccional , Proteómica , Humanos , Acetilación , Histonas/metabolismo , Neoplasias/genética , Neoplasias/metabolismo , Fosforilación , Proteómica/métodosRESUMEN
The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this "proteogenomics" approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy.
Asunto(s)
Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , Carcinogénesis/genética , Carcinogénesis/patología , Terapia Molecular Dirigida , Proteogenómica , Desaminasas APOBEC/metabolismo , Adulto , Anciano , Anciano de 80 o más Años , Neoplasias de la Mama/inmunología , Neoplasias de la Mama/terapia , Estudios de Cohortes , Daño del ADN , Reparación del ADN , Femenino , Humanos , Inmunoterapia , Metabolómica , Persona de Mediana Edad , Mutagénesis/genética , Fosforilación , Inhibidores de Proteínas Quinasas/farmacología , Proteínas Quinasas/metabolismo , Receptor ErbB-2/metabolismo , Proteína de Retinoblastoma/metabolismo , Microambiente Tumoral/inmunologíaRESUMEN
Human cancer cell lines are the workhorse of cancer research. Although cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. Here we use genomic analyses of 106 human cell lines grown in two laboratories to show extensive clonal diversity. Further comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Notably, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single-cell-derived clones demonstrated that continuous instability quickly translates into heterogeneity of the cell line. When the 27 MCF7 strains were tested against 321 anti-cancer compounds, we uncovered considerably different drug responses: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origins and consequences of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.
Asunto(s)
Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/genética , Evolución Molecular , Variación Genética/genética , Inestabilidad Genómica/genética , Transcripción Genética/genética , Neoplasias de la Mama/patología , Proliferación Celular , Forma de la Célula , Células Clonales/citología , Células Clonales/efectos de los fármacos , Células Clonales/metabolismo , Variación Genética/efectos de los fármacos , Inestabilidad Genómica/efectos de los fármacos , Humanos , Células MCF-7 , Reproducibilidad de los ResultadosRESUMEN
Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of ß-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes.
Asunto(s)
Biomarcadores de Tumor/genética , Mapeo Cromosómico/métodos , Estudio de Asociación del Genoma Completo/métodos , Proteínas de Neoplasias/genética , Neoplasias/genética , Polimorfismo de Nucleótido Simple/genética , Resistencia a Antineoplásicos/genética , Genes Relacionados con las Neoplasias/genética , Predisposición Genética a la Enfermedad/genética , Genoma Humano/genética , Humanos , Mutación/genética , Neoplasias/diagnóstico , Transducción de Señal/genéticaRESUMEN
The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
