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Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations.

ABSTRACT: Cancer sequencing studies have primarily identified cancer driver genes by the accumulation of protein-altering mutations. An improved method would be annotation independent, sensitive to unknown distributions of functions within proteins and inclusive of noncoding drivers. We employed density-based clustering methods in 21 tumor types to detect variably sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and noncoding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼ 15% of specific tumor types. SMRs demonstrate spatial clustering of alterations in molecular domains and at interfaces, often with associated changes in signaling. Mutation frequencies in SMRs demonstrate that distinct protein regions are differentially mutated across tumor types, as exemplified by a linker region of PIK3CA in which biophysical simulations suggest that mutations affect regulatory interactions. The functional diversity of SMRs underscores both the varied mechanisms of oncogenic misregulation and the advantage of functionally agnostic driver identification.

SUBMITTER: Araya CL

PROVIDER: S-EPMC4731297 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations.

Araya Carlos L CL Cenik Can C Reuter Jason A JA Kiss Gert G Pande Vijay S VS Snyder Michael P MP Greenleaf William J WJ

Nature genetics 20151221 2

Cancer sequencing studies have primarily identified cancer driver genes by the accumulation of protein-altering mutations. An improved method would be annotation independent, sensitive to unknown distributions of functions within proteins and inclusive of noncoding drivers. We employed density-based clustering methods in 21 tumor types to detect variably sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and noncoding elements, including tra ...[more]

PMID: 26691984

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Project description:BackgroundCurrently developed molecular markers can predict the effectiveness of cancer immunotherapy and screen beneficiaries to some extent, but they are not stable enough. Therefore, there is an urgent need for discovering novel biomarkers. At the same time, sex factor plays a vital role in the response to immunotherapy, so it is particularly important to identify sex-related molecular indicators.MethodsWe integrated a pan-cancer cohort consisting of 2348 cancer patients who received immune checkpoint inhibitors and targeted sequencing. Using somatic mutation profiles, we identified mutational signatures, molecular subtypes, and frequently mutated genes, and analyzed their relationships with immunotherapeutic outcomes. We also explored sex disparities of determined biomarkers in response to treatments.ResultsWe found that male patients exhibited better immunotherapy outcomes and higher tumor mutational burden. A total of seven mutational signatures were identified, among which signatures 1 and 3 were associated with worse immunotherapy outcomes, while signatures 2 and 6 correlated with better outcomes. Gender-based analysis revealed that mutational signature 1 continued to show a worse immunotherapy outcome in female patients, whereas signature 6 demonstrated a better outcome in male patients. Based on mutational activities, we identified four potential molecular subtypes with gender differences and relevance to treatment outcomes. PI3K-AKT, RAS signaling pathways, and 68 significantly mutated genes were identified to be associated with immunotherapy outcomes, with nine genes (i.e., ATM, ATRX, DOT1L, EP300, EPHB1, NOTCH1, PBRM1, RBM10, and SETD2) exhibiting gender differences. Finally, we discovered co-mutated gene pairs and TP53 p.R282W mutations related to treatment outcomes, highlighting their gender-specific differences.ConclusionThis study identified several molecular biomarkers related to cancer immunotherapy outcomes in terms of mutational signatures, molecular subtypes, and mutated genes, and explored their gender-relatedness in order to provide clues and basis for clinical treatment efficacy evaluation and patient selection.

Project description:Brain function relies on communication via neuronal synapses. Neurons build and diversify synaptic contacts using different protein combinations that define the specificity, function and plasticity potential of synapses. More than a thousand proteins have been globally identified in both pre- and postsynaptic compartments, providing substantial potential for synaptic diversity. While there is ample evidence of diverse synaptic structures, states or functional properties, the diversity of the underlying individual synaptic proteomes remains largely unexplored. Here we used 7 different Cre-driver mouse lines crossed with a floxed mouse line in which the presynaptic terminals were fluorescently labeled (SypTOM) to identify the proteomes that underlie synaptic diversity. We combined microdissection of 5 different brain regions with fluorescent-activated synaptosome sorting to isolate and analyze using quantitative mass spectrometry 18 types of synapses and their underlying synaptic proteomes. We discovered ~1’800 unique synapse type-enriched proteins and allocated thousands of proteins to different types of synapses. We identify commonly shared synaptic protein modules and highlight the hotspots for proteome specialization. A protein-protein correlation network classifies proteins into modules and their association with synaptic traits reveals synaptic protein communities that correlate with either neurotransmitter glutamate or GABA. Finally, we reveal specializations and commonalities of the striatal dopaminergic proteome and outline the proteome diversity of synapses formed by parvalbumin, somatostatin and vasoactive intestinal peptide-expressing cortical interneuron subtypes, highlighting proteome signatures that relate to their functional properties. This study opens the door for molecular systems-biology analysis of synapses and provides a framework to integrate proteomic information for synapse subtypes of interest with cellular or circuit-level experiments.

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Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations.

Publications

Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations.

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