Frameshift mutations of a chromatin-remodeling geneSMARCC2in gastric and colorectal cancers with microsatellite instability

A Subset of Microsatellite Unstable Cancer Genomes Prone to Short Insertions over Deletions Is Associated with Elevated Anticancer Immunity

Deficiencies in DNA mismatch repair (MMRd) leave characteristic footprints of microsatellite instability (MSI) in cancer genomes. We used data from the Cancer Genome Atlas and International Cancer Genome Consortium to conduct a comprehensive analysis of MSI-associated cancers, focusing on indel mutational signatures. We classified MSI-high genomes into two subtypes based on their indel profiles: deletion-dominant (MMRd-del) and insertion-dominant (MMRd-ins). Compared with MMRd-del genomes, MMRd-ins genomes exhibit distinct mutational and transcriptomic features, including a higher prevalence of T>C substitutions and related mutation signatures. Short insertions and deletions in MMRd-ins and MMRd-del genomes target different sets of genes, resulting in distinct indel profiles between the two subtypes. In addition, indels in the MMRd-ins genomes are enriched with subclonal alterations that provide clues about a distinct evolutionary relationship between the MMRd-ins and MMRd-del genomes. Notably, the transcriptome analysis indicated that MMRd-ins cancers upregulate immune-related genes, show a high level of immune cell infiltration, and display an elevated neoantigen burden. The genomic and transcriptomic distinctions between the two types of MMRd genomes highlight the heterogeneity of genetic mechanisms and resulting genomic footprints and transcriptomic changes in cancers, which has potential clinical implications.

Network embedding framework for driver gene discovery by combining functional and structural information

Comprehensive analysis of multiple data sets can identify potential driver genes for various cancers. In recent years, driver gene discovery based on massive mutation data and gene interaction networks has attracted increasing attention, but there is still a need to explore combining functional and structural information of genes in protein interaction networks to identify driver genes. Therefore, we propose a network embedding framework combining functional and structural information to identify driver genes. Firstly, we combine the mutation data and gene interaction networks to construct mutation integration network using network propagation algorithm. Secondly, the struc2vec model is used for extracting gene features from the mutation integration network, which contains both gene's functional and structural information. Finally, machine learning algorithms are utilized to identify the driver genes. Compared with the previous four excellent methods, our method can find gene pairs that are distant from each other through structural similarities and has better performance in identifying driver genes for 12 cancers in the cancer genome atlas. At the same time, we also conduct a comparative analysis of three gene interaction networks, three gene standard sets, and five machine learning algorithms. Our framework provides a new perspective for feature selection to identify novel driver genes.

FBXO28 promotes proliferation, invasion, and metastasis of pancreatic cancer cells through regulation of SMARCC2 ubiquitination

The E3 ligase F-box only protein 28 (FBXO28) belongs to the F-box family of proteins that play a critical role in tumor development. However, the potential function of FBXO28 in pancreatic cancer (PC) and its molecular mechanism remain unclear. In this study, we examined FBXO28 expression in PC and its biological role and explored the mechanism of FBXO28-mediated proliferation, invasion, and metastasis of PC cells. Compared with paracancerous tissues and human normal pancreatic ductal epithelial cells, FBXO28 was highly expressed in PC tissues and cell lines. High expression of FBXO28 was negatively correlated with the survival prognosis of patients with PC. Functional assays indicated that FBXO28 promoted PC cell proliferation, invasion, and metastasis in vitro and in vivo. Furthermore, immunoprecipitation-mass spectrometry was used to identify SMARCC2 as the target of FBXO28; upregulation of SMARCC2 can reverse the effect of overexpression of FBXO28 on promoting the proliferation, invasion, and metastasis of PC cells. Mechanistically, FBXO28 inhibited SMARCC2 expression in post-translation by increasing SMARCC2 ubiquitination and protein degradation. In conclusion, FBXO28 has a potential role in PC, possibly promoting PC progression through SMARCC2 ubiquitination. Thus, FBXO28 might be a potential treatment target in PC.

The SWI/SNF Complex: A Frequently Mutated Chromatin Remodeling Complex in Cancer

The switch/sucrose non-fermenting (SWI/SNF) chromatin remodeling complex is a global regulator of gene expression known to maintain nucleosome-depleted regions at active enhancers and promoters. The mammalian SWI/SNF protein subunits are encoded by 29 genes and 11-15 subunits including an ATPase domain of either SMARCA4 (BRG1) or SMARCA2 (BRM) are assembled into a complex. Based on the distinct subunits, SWI/SNF are grouped into 3 major types (subfamilies): the canonical BRG1/BRM-associated factor (BAF/cBAF), polybromo-associated BAF (PBAF), and non-canonical BAF (GBAF/ncBAF). Pan-cancer genome sequencing studies have shown that nearly 25% of all cancers bear mutations in subunits of the SWI/SNF complex, many of which are loss of function (LOF) mutations, suggesting a tumor suppressor role. Inactivation of SWI/SNF complex subunits causes widespread epigenetic dysfunction, including increased dependence on antagonistic components such as polycomb repressor complexes (PRC1/2) and altered enhancer regulation, likely promoting an oncogenic state leading to cancer. Despite the prevalence of mutations, most SWI/SNF-mutant cancers lack targeted therapeutic strategies. Defining the dependencies created by LOF mutations in SWI/SNF subunits will identify better targets for these cancers.

Two-stage-vote ensemble framework based on integration of mutation data and gene interaction network for uncovering driver genes

Identifying driver genes, exactly from massive genes with mutations, promotes accurate diagnosis and treatment of cancer. In recent years, a lot of works about uncovering driver genes based on integration of mutation data and gene interaction networks is gaining more attention. However, it is in suspense if it is more effective for prioritizing driver genes when integrating various types of mutation information (frequency and functional impact) and gene networks. Hence, we build a two-stage-vote ensemble framework based on somatic mutations and mutual interactions. Specifically, we first represent and combine various kinds of mutation information, which are propagated through networks by an improved iterative framework. The first vote is conducted on iteration results by voting methods, and the second vote is performed to get ensemble results of the first poll for the final driver gene list. Compared with four excellent previous approaches, our method has better performance in identifying driver genes on $33$ types of cancer from The Cancer Genome Atlas. Meanwhile, we also conduct a comparative analysis about two kinds of mutation information, five gene interaction networks and four voting strategies. Our framework offers a new view for data integration and promotes more latent cancer genes to be admitted.

The Emerging Roles of ATP-Dependent Chromatin Remodeling Complexes in Pancreatic Cancer

Pancreatic cancer is an aggressive cancer with low survival rates. Genetic and epigenetic dysregulation has been associated with the initiation and progression of pancreatic tumors. Multiple studies have pointed to the involvement of aberrant chromatin modifications in driving tumor behavior. ATP-dependent chromatin remodeling complexes regulate chromatin structure and have critical roles in stem cell maintenance, development, and cancer. Frequent mutations and chromosomal aberrations in the genes associated with subunits of the ATP-dependent chromatin remodeling complexes have been detected in different cancer types. In this review, we summarize the current literature on the genomic alterations and mechanistic studies of the ATP-dependent chromatin remodeling complexes in pancreatic cancer. Our review is focused on the four main subfamilies: SWItch/sucrose non-fermentable (SWI/SNF), imitation SWI (ISWI), chromodomain-helicase DNA-binding protein (CHD), and INOsitol-requiring mutant 80 (INO80). Finally, we discuss potential novel treatment options that use small molecules to target these complexes.

Identification and Characterization of Tomato SWI3-Like Proteins: Overexpression of SlSWIC Increases the Leaf Size in Transgenic Arabidopsis

As the subunits of the SWI/SNF (mating-type switching (SWI) and sucrose nonfermenting (SNF)) chromatin-remodeling complexes (CRCs), Swi3-like proteins are crucial to chromatin remodeling in yeast and human. Growing evidence indicate that AtSWI3s are also essential for development and response to hormones in Arabidopsis. Nevertheless, the biological functions of Swi3-like proteins in tomato (Solanum lycopersicum) have not been investigated. Here we identified four Swi3-like proteins from tomato, namely SlSWI3A, SlSWI3B, SlSWI3C, and SlSWI3D. Subcellular localization analysis revealed that all SlSWI3s are localized in the nucleus. The expression patterns showed that all SlSWI3s are ubiquitously expressed in all tissues and organs, and SlSWI3A and SlSWI3B can be induced by cold treatment. In addition, we found that SlSWI3B can form homodimers with itself and heterodimers with SlSWI3A and SlSWI3C. SlSWI3B can also interact with SlRIN and SlCHR8, two proteins involved in tomato reproductive development. Overexpression of SlSWI3C increased the leaf size in transgenic Arabidopsis with increased expression of GROWTH REGULATING FACTORs, such as GRF3, GRF5, and GRF6. Taken together, our results indicate that SlSWI3s may play important roles in tomato growth and development.

The BAF complex in development and disease

The ATP-dependent chromatin remodelling complex BAF (= mammalian SWI/SNF complex) is crucial for the regulation of gene expression and differentiation. In the course of evolution from yeast to mammals, the BAF complex evolved an immense complexity with a high number of subunits encoded by gene families. In this way, tissue-specific BAF function and regulation of development begin with the combinatorial assembly of distinct BAF complexes such as esBAF, npBAF and nBAF. Furthermore, whole-genome sequencing reveals the tremendous role BAF complex mutations have in both neurodevelopmental disorders and human malignancies. Therefore, gaining a more elaborate insight into how BAF complex assembly influences its function and which role distinct subunits play, will hopefully give rise to a better understanding of disease pathogenesis and ultimately to new treatments for many human diseases.

BAFfling pathologies: Alterations of BAF complexes in cancer

To activate or repress specific genes, chromatin is constantly modified by chromatin-remodeling complexes. Among these complexes, the SWItch/Sucrose Non-Fermenting (SWI/SNF) complex, also referred to as BRG1-Associated Factor (BAF) complex, moves the nucleosome along chromatin using energy provided by ATP hydrolysis. In mammalian organisms, the SWI/SNF complex is composed of 10-15 subunits, depending on cell type, and a defect in one of these subunits can have dramatic consequences. In this review we will focus on the alterations identified in the SWI/SNF (BAF) complex subunits that lead to cancerous pathologies. While SMARCB1 was the first mutated subunit to be reported in a majority of malignant rhabdoid tumors, the advent of next-generation sequencing allowed the discovery of mutations in various SWI/SNF subunits within a broad spectrum of cancers. In most cases, the mutation leads to a loss of expression or to a truncated subunit unable to perform its function. Even though it is now commonly acknowledged that approximately 20% of all cancers present a mutation in a SWI/SNF subunit, some cancers are associated to a specific alteration of a SWI/SNF subunit, which acts either as tumor suppressor genes or as oncogenes, and therefore constitute diagnostic or prognostic biomarkers. Consistently, therapeutic strategies targeting SWI/SNF subunits or the genes affected downstream have been revealed to treat cancers.

Mammalian SWI/SNF chromatin remodeling complexes and cancer: Mechanistic insights gained from human genomics

Over the past 4 years, nearly 100 exome sequencing studies have revealed the high frequency of mutations in the genes encoding the subunits of ATP-dependent chromatin remodelers in human cancer. Most of these mutations are within the genes encoding subunits of the BAF (Brg/Brahma-associated factors) or mSWI/SNF complex, which is one of two dozen predicted ATP-dependent chromatin remodeling complexes in mammals. Considering BAF complexes as a single entity, the 15 subunits encoded by 29 genes are mutated in >20% of human cancer, across a broad range of tumor types. These observations demonstrate that there is little redundancy in the oncogenic function of BAF complexes with the other remodeling complexes, underscoring their unique roles. Several important conclusions emerge from these genomic data: specific subunits appear to be mutated in specific cancers, highlighting tissue-specific protective roles; mutations can function as tumor suppressors or oncogenes; mutations can be homozygous or, more commonly, heterozygous, implying their dosage-sensitive roles in an unknown yet fundamental process used to suppress the genesis of cancer. These new human genetic findings paired with biochemical studies are challenging old ideas on how chromatin remodeling complexes function, generating new hypotheses with respect to their normal and oncogenic mechanisms and highlighting potential avenues for therapeutic intervention in human cancer.

Genome-wide analysis of alternative transcripts in human breast cancer

Transcript variants play a critical role in diversifying gene expression. Alternative splicing is a major mechanism for generating transcript variants. A number of genes have been implicated in breast cancer pathogenesis with their aberrant expression of alternative transcripts. In this study, we performed genome-wide analyses of transcript variant expression in breast cancer. With RNA-Seq data from 105 patients, we characterized the transcriptome of breast tumors, by pairwise comparison of gene expression in the breast tumor versus matched healthy tissue from each patient. We identified 2839 genes, ~10 % of protein-coding genes in the human genome, that had differential expression of transcript variants between tumors and healthy tissues. The validity of the computational analysis was confirmed by quantitative RT-PCR assessment of transcript variant expression from four top candidate genes. The alternative transcript profiling led to classification of breast cancer into two subgroups and yielded a novel molecular signature that could be prognostic of patients' tumor burden and survival. We uncovered nine splicing factors (FOX2, MBNL1, QKI, PTBP1, ELAVL1, HNRNPC, KHDRBS1, SFRS2, and TIAR) that were involved in aberrant splicing in breast cancer. Network analyses for the coordinative patterns of transcript variant expression identified twelve "hub" genes that differentiated the cancerous and normal transcriptomes. Dysregulated expression of alternative transcripts may reveal novel biomarkers for tumor development. It may also suggest new therapeutic targets, such as the "hub" genes identified through the network analyses of transcript variant expression, or splicing factors implicated in the formation of the tumor transcriptome.

SWI/SNF chromatin remodeling complexes and cancer

The identification of mutations and deletions in the SMARCB1 locus in chromosome band 22q11.2 in pediatric rhabdoid tumors provided the first evidence for the involvement of the SWI/SNF chromatin remodeling complex in cancer. Over the last 15 years, alterations in more than 20 members of the complex have been reported in a variety of human tumors. These include germline mutations and copy number alterations in SMARCB1, SMARCA4, SMARCE1, and PBRM1 that predispose carriers to both benign and malignant neoplasms. Somatic mutations, structural abnormalities, or epigenetic modifications that lead to reduced or aberrant expression of complex members have now been reported in more than 20% of malignancies, including both solid tumors and hematologic disorders in both children and adults. In this review, we will highlight the role of SMARCB1 in cancer as a paradigm for other tumors with alterations in SWI/SNF complex members and demonstrate the broad spectrum of mutations observed in complex members in different tumor types.

SHIFT: server for hidden stops analysis in frame-shifted translation

Background

Frameshift is one of the three classes of recoding. Frame-shifts lead to waste of energy, resources and activity of the biosynthetic machinery. In addition, some peptides synthesized after frame-shifts are probably cytotoxic which serve as plausible cause for innumerable number of diseases and disorders such as muscular dystrophies, lysosomal storage disorders, and cancer. Hidden stop codons occur naturally in coding sequences among all organisms. These codons are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frameshift events. Researchers have identified several consequences of hidden stop codons and their association with myriad disorders. However the wealth of information available is speckled and not effortlessly acquiescent to data-mining. To reduce this gap, this work describes an algorithmic web based tool to study hidden stops in frameshifted translation for all the lineages through respective genetic code systems.

Findings

This paper describes SHIFT, an algorithmic web application tool that provides a user-friendly interface for identifying and analyzing hidden stops in frameshifted translation of genomic sequences for all available genetic code systems. We have calculated the correlation between codon usage frequencies and the plausible contribution of codons towards hidden stops in an off-frame context. Markovian chains of various order have been used to model hidden stops in frameshifted peptides and their evolutionary association with naturally occurring hidden stops. In order to obtain reliable and persuasive estimates for the naturally occurring and predicted hidden stops statistical measures have been implemented.

Conclusions

This paper presented SHIFT, an algorithmic tool that allows user-friendly exploration, analysis, and visualization of hidden stop codons in frameshifted translations. It is expected that this web based tool would serve as a useful complement for analyzing hidden stop codons in all available genetic code systems. SHIFT is freely available for academic and research purpose at http://www.nuccore.org/shift/.