PO.BCS01.01 · 生物信息与计算
COSMIC: Advancing the cancer genomics knowledgebase of somatic mutations
作者与单位
摘要 Abstract
COSMIC (Catalogue Of Somatic Mutations in Cancer) has evolved from an initial catalogue to the world's most comprehensive knowledgebase of somatic variants in cancer, built upon a foundation of continuous, expert curation. COSMIC currently aggregates over 29 million unique somatic variants carefully curated from 1.5 million samples, establishing an essential resource for studying the cancer genome. This rich dataset is the result of extensive, dedicated work, drawing on insights from more than 30,000 scientific publications and major studies.
COSMIC is structured into a suite of specialized modules that collectively transform raw genomic variants into biologically and clinically meaningful insight. These include the Cancer Gene Census (CGC), which systematically classifies causal cancer genes; the Cancer Mutation Census (CMC), which distinguishes driver from passenger mutations through computational and evidence-based annotation; Mutational Signatures, which captures genome-wide mutagenic processes; COSMIC 3D, which contextualizes variants within protein structures; and the Actionability and Resistance resources, which map genomic alterations to therapeutic response and resistance mechanisms. Together, these modules provide a framework essential for interpreting somatic variant landscapes in precision oncology.
We highlight ongoing research on the next iteration of the Cancer Mutation Census (CMC v2), designed to enhance COSMIC's ability to extract biologically meaningful signals from large-scale somatic datasets. CMC v2 applies refined background models to identify mutation hotspots at the amino acid level across cancer genes in a pan-cancer context, focusing on positions exhibiting statistically significant enrichment of somatic variants. This approach isolates non-random, spatially coherent clusters of mutations that represent strong candidates for driver activity. Although currently under development, these analyses demonstrate the potential of CMC v2 to provide higher-resolution insights into cancer gene dysregulation and support more nuanced interpretation of tumor evolution.
The development of CMC v2 marks a key step in COSMIC's evolution toward more data-driven, biologically grounded interpretation of cancer variants. By integrating statistical modeling with expert insight, CMC v2 refines our capacity to distinguish meaningful mutational patterns from background noise across diverse tumor contexts. These advances exemplify COSMIC's ongoing commitment to translating large-scale genomics into actionable biological knowledge. As the knowledgebase continues to expand and engage with the global cancer research community, COSMIC remains an indispensable foundation for understanding cancer gene function, refining biomarker discovery, and supporting precision oncology.
利益披露 Disclosure
M. Madhumita, None..
M. Ahmed, None..
J. Argasinska, None..
D. Armstrong, None..
N. B. Dhir, None..
D. Carvalho-Silva, None..
L. Chadelle, None..
P. Dao, None..
S. Duke, None..
G. Fasanella, None..
M. Fouzan, None..
A. Gnanasambandam, None..
A. G. Neogi, None..
S. Haller, None..
B. Harsha, None..
B. Hetenyi, None..
L. Hodges, None..
S. Jupe, None..
R. Lyne, None..
T. Maurel, None..
K. McLaren, None..
T. Mutimer, None..
S. Nair, None..
H. Najgebauer, None..
H. Pedro, None..
S. Poole, None..
A. Sangrador-Vegas, None..
Z. Sheard, None..
M. Singh Chawla, None..
M. Starkey, None..
R. Steele, None..
S. Ward, None..
E. Wiedemann, None..
J. Wilding, None..
S. Yit Yong, None..
J. Teague, None.