Pan-cancer proteogenomics connects oncogenic drivers to functional states
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved..
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.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:186 |
|---|---|
| Enthalten in: |
Cell - 186(2023), 18 vom: 31. Aug., Seite 3921-3944.e25 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Yize [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 04.09.2023 Date Revised 30.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.cell.2023.07.014 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a CPTAC | |
| 650 | 4 | |a cancer hallmark | |
| 650 | 4 | |a oncogenic driver | |
| 650 | 4 | |a pan-cancer | |
| 650 | 4 | |a phosphoproteomics | |
| 650 | 4 | |a protein complex | |
| 650 | 4 | |a proteogenomics | |
| 650 | 4 | |a proteomics | |
| 650 | 4 | |a therapeutic target | |
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