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Defining relative mutational difficulty to understand cancer formation.

ABSTRACT: Most mutations in human cancer are low-frequency missense mutations, whose functional status remains hard to predict. Here, we show that depending on the type of nucleotide change and the surrounding sequences, the tendency to generate each type of nucleotide mutations varies greatly, even by several hundred folds. Therefore, a cancer-promoting mutation may appear only in a small number of cancer cases, if the underlying nucleotide change is too difficult to generate. We propose a method that integrates both the original mutation counts and their relative mutational difficulty. Using this method, we can accurately predict the functionality of hundreds of low-frequency missense mutations in p53, PTEN, and INK4A. Many loss-of-function p53 mutations with dominant negative effects were identified, and the functional importance of several regions in p53 structure were highlighted by this analysis. Our study not only established relative mutational difficulties for different types of mutations in human cancer, but also showed that by incorporating such a parameter, we can bring new angles to understanding cancer formation.

SUBMITTER: Shan L

PROVIDER: S-EPMC7371891 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Defining relative mutational difficulty to understand cancer formation.

Shan Lin L Yu Jiao J He Zhengjin Z Chen Shishuang S Liu Mingxian M Ding Hongyu H Xu Liang L Zhao Jie J Yang Ailing A Jiang Hai H

Cell discovery 20200721

Most mutations in human cancer are low-frequency missense mutations, whose functional status remains hard to predict. Here, we show that depending on the type of nucleotide change and the surrounding sequences, the tendency to generate each type of nucleotide mutations varies greatly, even by several hundred folds. Therefore, a cancer-promoting mutation may appear only in a small number of cancer cases, if the underlying nucleotide change is too difficult to generate. We propose a method that in ...[more]

PMID: 32704382

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Project description:Macroautophagy/autophagy is a cellular process to recycle damaged cellular components, and its modulation can be exploited for disease treatments. A key autophagy player is the ubiquitin-like protein MAP1LC3B/LC3B. Mutations and changes in MAP1LC3B expression occur in cancer samples. However, the investigation of the effects of these mutations on MAP1LC3B protein structure is still missing. Despite many LC3B structures that have been solved, a comprehensive study, including dynamics, has not yet been undertaken. To address this knowledge gap, we assessed nine physical models for biomolecular simulations for their capabilities to describe the structural ensemble of MAP1LC3B. With the resulting MAP1LC3B structural ensembles, we characterized the impact of 26 missense mutations from pan-cancer studies with different approaches, and we experimentally validated our prediction for six variants using cellular assays. Our findings shed light on damaging or neutral mutations in MAP1LC3B, providing an atlas of its modifications in cancer. In particular, P32Q mutation was found detrimental for protein stability with a propensity to aggregation. In a broader context, our framework can be applied to assess the pathogenicity of protein mutations or to prioritize variants for experimental studies, allowing to comprehensively account for different aspects that mutational events alter in terms of protein structure and function.Abbreviations: ATG: autophagy-related; Cα: alpha carbon; CG: coarse-grained; CHARMM: Chemistry at Harvard macromolecular mechanics; CONAN: contact analysis; FUNDC1: FUN14 domain containing 1; FYCO1: FYVE and coiled-coil domain containing 1; GABARAP: GABA type A receptor-associated protein; GROMACS: Groningen machine for chemical simulations; HP: hydrophobic pocket; LIR: LC3 interacting region; MAP1LC3B/LC3B microtubule associated protein 1 light chain 3 B; MD: molecular dynamics; OPTN: optineurin; OSF: open software foundation; PE: phosphatidylethanolamine, PLEKHM1: pleckstrin homology domain-containing family M 1; PSN: protein structure network; PTM: post-translational modification; SA: structural alphabet; SLiM: short linear motif; SQSTM1/p62: sequestosome 1; WT: wild-type.

Project description:While the adult human heart is primarily composed of cardiomyocytes, fibroblasts, endothelial and smooth muscle cells, the cellular composition during early development remains largely unknown. Reliable identification of fetal cardiac cell types using protein markers is critical to understand cardiac development and delineate the cellular composition of the developing human heart. This is the first study to use immunohistochemistry (IHC), flow cytometry and RT-PCR analyses to investigate the expression and specificity of commonly used cardiac cell markers in the early human fetal heart (8-12 post-conception weeks). The expression of previously reported protein markers for the detection of cardiomyocytes (Myosin Heavy Chain (MHC) and cardiac troponin I (cTnI), fibroblasts (DDR2, THY1, Vimentin), endothelial cells (CD31) and smooth muscle cells (α-SMA) were assessed. Two distinct populations of cTnI positive cells were identified through flow cytometry, with MHC positive cardiomyocytes showing high cTnI expression (cTnIHigh) while MHC negative non-myocytes showed lower cTnI expression (cTnILow). cTnI expression in non-myocytes was further confirmed by IHC and RT-PCR analyses, suggesting troponins are not cardiomyocyte-specific and may play distinct roles in non-muscle cells during early development. Vimentin (VIM) was expressed in cultured ventricular fibroblast populations and flow cytometry revealed VIMHigh and VIMLow cell populations in the fetal heart. MHC positive cardiomyocytes were VIMLow whilst CD31 positive endothelial cells were VIMHigh. Using markers investigated within this study, we characterised fetal human cardiac populations and estimate that 75-80% of fetal cardiac cells are cardiomyocytes and are MHC+/cTnIHigh/VIMLow, whilst non-myocytes comprise 20-25% of total cells and are MHC-/cTnILow/VIMHigh, with CD31+ endothelial cells comprising ~9% of this population. These findings show distinct differences from those reported for adult heart.

Dataset Information

Defining relative mutational difficulty to understand cancer formation.

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Defining relative mutational difficulty to understand cancer formation.

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