Concordance between somatic copy number loss and down-regulated expression: A pan-cancer study of cancer predisposition genes

Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer

In this review, we provide a general overview of the current panorama of mining strategies for multi-omics data to investigate lncRNAs with an actual or potential role as biological markers in cancer. Several multi-omics studies focusing on lncRNAs have been performed in the past with varying scopes. Nevertheless, many questions remain regarding the pragmatic application of different molecular technologies and bioinformatics algorithms for mining multi-omics data. Here, we attempt to address some of the less discussed aspects of the practical applications using different study designs for incorporating bioinformatics and statistical analyses of multi-omics data. Finally, we discuss the potential improvements and new paradigms aimed at unraveling the role and utility of lncRNAs in cancer and their potential use as molecular markers for cancer diagnosis and outcome prediction.

Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel

BACKGROUND

The rapid adoption of next-generation sequencing in clinical oncology has enabled detection of molecular biomarkers which are shared between multiple tumour types. Intra-tumour heterogeneity is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the tumour-related copy number variants (CNVs), as key regulators of cancer origination, development, and progression, across various types of cancers are poorly understood.

METHODS

We performed pan-cancer CNV analysis of cancer-related genes in 15 types of cancers including 1438 cancerous patients by next-generation sequencing using a commercially available pan-cancer panel (Onco PanScan™). Downstream bioinformatics analysis was performed in order to detect CNVs, cluster analysis of the found CNVs, and comparison of the frequency of gained CNVs between different types of cancers. LASSO analysis was used for identification of the most important CNVs.

RESULTS

We also identified 523 CNVs among which 16 CNVs were common while 22 CNVs were caner-specific CNVs. Meanwhile, FAM58A was most commonly found in all studied cancers in this study and significant differences were found in FAM58A between female and male patients (p = .001). Common CNVs, such as FOXA1, NFKBIA, HEY1, MECOM, CHD7, AGO2, were mutated in 6.79%, 8.45%, 7.51%, 6.43%, 7.59%, 8.16% of tumours, while most of these mutations have proven roles in positive regulation of transcription from RNA polymerase II promoter. 11 features including sex, DIS3, EPHB1, ERBB2, FLT1, HCK, KEAP1, MYD88, PARP3, TBX3, and TOP2A were found as the key features for classification of cancers using CNVs.

CONCLUSION

The 16 common CNVs between cancers can be used to identify the target of pan-cancer drug design and targeted therapies. Additionally, 22 caner-specific CNVs can be used as unique diagnostic markers for each cancer type.

circExp database: an online transcriptome platform for human circRNA expressions in cancers

Circular RNA (circRNA) is a highly stable, single-stranded, closed-loop RNA that works as RNA or as a protein decoy to regulate gene expression. In humans, thousands of circRNA transcriptional products precisely express in specific developmental stages, tissues and cell types. Due to their stability and specificity, circRNAs are ideal biomarkers for cancer diagnosis and prognosis. To provide an integrated and standardized circRNA expression profile for human cancers, we performed extensive data curation across 11 technical platforms, collecting 48 expression profile data sets for 18 cancer types and amassing 860 751 expression records. We also identified 189 193 differential expression signatures that are significantly different between normal and cancer samples. All the pre-calculated expression analysis results are organized into 132 plain text files for bulk download. Our online interface, circExp, provides data browsing and search functions. For each data set, a dynamic expression heatmap provides a profile overview. Based on the processed data, we found that 52 circRNAs were consistently and differentially expressed in 20 or more processed analyses. By mapping those circRNAs to their parent protein-coding genes, we found that they may have profoundly affected the survival of 10 797 patients in the The Cancer Genome Atlas pan-cancer data set. In sum, we developed circExp and demonstrated that it is useful to identify circRNAs that have potential diagnostic and prognostic significance for a variety of cancer types. In this online and reusable database, found at http://soft.bioinfo-minzhao.org/circexp, we have provided pre-calculated expression data about circRNAs and their parental genes, as well as data browsing and searching functions. Database URL: http://soft.bioinfominzhao.org/circexp/.

Easy One-Step Amplification and Labeling Procedure for Copy Number Variation Detection

BACKGROUND

The specific characteristics of copy number variations (CNVs) require specific methods of detection and characterization. We developed the Easy One-Step Amplification and Labeling procedure for CNV detection (EOSAL-CNV), a new method based on proportional amplification and labeling of amplicons in 1 PCR.

METHODS

We used tailed primers for specific amplification and a pair of labeling probes (only 1 labeled) for amplification and labeling of all amplicons in just 1 reaction. Products were loaded directly onto a capillary DNA sequencer for fragment sizing and quantification. Data obtained could be analyzed by Microsoft Excel spreadsheet or EOSAL-CNV analysis software. We developed the protocol using the LDLR (low density lipoprotein receptor) gene including 23 samples with 8 different CNVs. After optimizing the protocol, it was used for genes in the following multiplexes: BRCA1 (BRCA1 DNA repair associated), BRCA2 (BRCA2 DNA repair associated), CHEK2 (checkpoint kinase 2), MLH1 (mutL homolog 1) plus MSH6 (mutS homolog 6), MSH2 (mutS homolog 2) plus EPCAM (epithelial cell adhesion molecule) and chromosome 17 (especially the TP53 [tumor protein 53] gene). We compared our procedure with multiplex ligation-dependent probe amplification (MLPA).

RESULTS

The simple procedure for CNV detection required 150 min, with <10 min of handwork. After analyzing >240 samples, EOSAL-CNV excluded the presence of CNVs in all controls, and in all cases, results were identical using MLPA and EOSAL-CNV. Analysis of the 17p region in tumor samples showed 100% similarity between fluorescent in situ hybridization and EOSAL-CNV.

CONCLUSIONS

EOSAL-CNV allowed reliable, fast, easy detection and characterization of CNVs. It provides an alternative to targeted analysis methods such as MLPA.

Integrated genetic and epigenetic analysis of cancer-related genes in non-ampullary duodenal adenomas and intramucosal adenocarcinomas

The molecular and clinical characteristics of non‐ampullary duodenal adenomas and intramucosal adenocarcinomas are not fully understood because they are rare. To clarify these characteristics, we performed genetic and epigenetic analysis of cancer‐related genes in these lesions. One hundred and seven non‐ampullary duodenal adenomas and intramucosal adenocarcinomas, including 100 small intestinal‐type tumors (90 adenomas and 10 intramucosal adenocarcinomas) and 7 gastric‐type tumors (2 pyloric gland adenomas and 5 intramucosal adenocarcinomas), were investigated. Using bisulfite pyrosequencing, we assessed the methylation status of CpG island methylator phenotype (CIMP) markers and MLH1. Then using next‐generation sequencing, we performed targeted exome sequence analysis within 75 cancer‐related genes in 102 lesions. There were significant differences in the clinicopathological and molecular variables between small intestinal‐ and gastric‐type tumors, which suggests the presence of at least two separate carcinogenic pathways in non‐ampullary duodenal adenocarcinomas. The prevalence of CIMP‐positive lesions was higher in intramucosal adenocarcinomas than in adenomas. Thus, concurrent hypermethylation of multiple CpG islands is likely associated with development of non‐ampullary duodenal intramucosal adenocarcinomas. Mutation analysis showed that APC was the most frequently mutated gene in these lesions (56/102; 55%), followed by KRAS (13/102; 13%), LRP1B (10/102; 10%), GNAS (8/102; 8%), ERBB3 (7/102; 7%), and RNF43 (6/102; 6%). Additionally, the high prevalence of diffuse or focal nuclear β‐catenin accumulation (87/102; 85%) as well as mutations of WNT pathway components (60/102; 59%) indicates the importance of WNT signaling to the initiation of duodenal adenomas. The higher than previously reported frequency of APC gene mutations in small bowel adenocarcinomas as well as the difference in the APC mutation distributions between small intestinal‐type adenomas and intramucosal adenocarcinomas may indicate that the adenoma–carcinoma sequence has only limited involvement in duodenal carcinogenesis. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Significance of gene mutations in the Wnt signaling pathway in traditional serrated adenomas of the colon and rectum

Recent studies have shown that colorectal serrated lesions, which include sessile serrated adenomas (SSAs) and traditional serrated adenomas (TSAs), are precursors of colorectal cancer. However, the molecular mechanisms underlying the carcinogenesis, particularly in TSAs, remain largely uncharacterized. To clarify their molecular and clinicopathological characteristics, we performed mutation and methylation analyses of cancer-associated genes in 78 serrated lesions, including TSAs, SSAs and microvesicular hyperplastic polyps. Target exon sequence analysis was performed with 39 genes, including genes known to be frequently mutated in colorectal cancers and/or serrated lesions. We also used bisulfite pyrosequencing to assess the methylation status of various cancer-associated genes and marker genes of the CpG island methylator phenotype (CIMP). The prevalence of mutations in genes associated with Wnt signaling was significantly higher in TSAs than SSAs (65% vs. 28%, p < 0.01). Among those, RNF43 mutations were observed in 38% of TSAs and 17% of SSAs. In immunohistochemical studies of 39 serrated lesions, the prevalence of abnormal nuclear β-catenin accumulation was significantly higher in TSAs (57%) than SSAs (8%) (P = 0.01). SMOC1 methylation was detected in 54% of TSAs but in no SSAs (p < 0.01). Additionally, SMOC1 methylation was more prevalent among TSAs with KRAS mutation (82%) than with BRAF mutation (38%, p = 0.03). Lesions with CIMP-high or RNF43 mutations were detected only in TSAs with BRAF mutation, suggesting two distinct carcinogenic pathways in TSAs. Mutations in genes associated with Wnt signaling play a greater role in the carcinogenesis of TSAs than SSAs.

Clinically Actionable Insights into Initial and Matched Recurrent Glioblastomas to Inform Novel Treatment Approaches

Glioblastoma is the most common primary adult brain tumour, and despite optimal treatment, the median survival is 12–15 months. Patients with matched recurrent glioblastomas were investigated to try to find actionable mutations. Tumours were profiled using a validated DNA-based gene panel. Copy number variations (CNVs) and single nucleotide variants (SNVs) were examined, and potentially pathogenic variants and clinically actionable mutations were identified. The results revealed that glioblastomas were IDH-wildtype (IDH^WT; n = 38) and IDH-mutant (IDH^MUT; n = 3). SNVs in TSC2, MSH6, TP53, CREBBP, and IDH1 were variants of unknown significance (VUS) that were predicted to be pathogenic in both subtypes. IDH^WT tumours had SNVs that impacted RTK/Ras/PI(3)K, p53, WNT, SHH, NOTCH, Rb, and G-protein pathways. Many tumours had BRCA1/2 (18%) variants, including confirmed somatic mutations in haemangioblastoma. IDH^WT recurrent tumours had fewer pathways impacted (RTK/Ras/PI(3)K, p53, WNT, and G-protein) and CNV gains (BRCA2, GNAS, and EGFR) and losses (TERT and SMARCA4). IDH^MUT tumours had SNVs that impacted RTK/Ras/PI(3)K, p53, and WNT pathways. VUS in KLK1 was possibly pathogenic in IDH^MUT. Recurrent tumours also had fewer pathways (p53, WNT, and G-protein) impacted by genetic alterations. Public datasets (TCGA and GDC) confirmed the clinical significance of findings in both subtypes. Overall in this cohort, potentially actionable variation was most often identified in EGFR, PTEN, BRCA1/2, and ATM. This study underlines the need for detailed molecular profiling to identify individual GBM patients who may be eligible for novel treatment approaches. This information is also crucial for patient recruitment to clinical trials.

Integrative analysis of rare copy number variants and gene expression data in alopecia areata implicates an aetiological role for autophagy

Alopecia areata (AA) is a highly prevalent autoimmune disease that attacks the hair follicle and leads to hair loss that can range from small patches to complete loss of scalp and body hair. Our previous linkage and genome-wide association studies (GWAS) generated strong evidence for aetiological contributions from inherited genetic variants at different population frequencies, including both rare mutations and common polymorphisms. Additionally, we conducted gene expression (GE) studies on scalp biopsies of 96 patients and controls to establish signatures of active disease. In this study, we performed an integrative analysis on these two datasets to test the hypothesis that rare CNVs in patients with AA could be leveraged to identify drivers of disease in our AA GE signatures. We analysed copy number variants (CNVs) in a case-control cohort of 673 patients with AA and 16 311 controls independent of the case-control cohort of 96 research participants used in our GE study. Using an integrative computational analysis, we identified 14 genes whose expression levels were altered by CNVs in a consistent direction of effect, corresponding to gene expression changes in lesional skin of patients. Four of these genes were affected by CNVs in three or more unrelated patients with AA, including ATG4B and SMARCA2, which are involved in autophagy and chromatin remodelling, respectively. Our findings identified new classes of genes with potential contributions to AA pathogenesis.

eQTL analysis from co-localization of 2739 GWAS loci detects associated genes across 14 human cancers

Genetic variants can predict other "linked" diseases because alterations in one or more genes in vivo may affect relevant phenotype properties. Our study systematically explored the pan-cancer common gene and cancer type-specific genes based on GWAS loci and TCGA data of multiple cancers. It was found that there were 17 SNPs were significantly associated with the expression of 18 genes. Associations between the 18 cis-regulatory genes and the pathologic stage of each cancer showed that MYL2 and PTGFR in HNSC, 4 genes (F8, SATB2, G6PD and UGT1A6) in KIRP, 3 genes (CHMP4C, MAP3K1 and MECP2) in LUAD were all strongly associated with cancer stage levels. Additionally, the survival association analysis showed that SATB2 was correlated with HNSC survival, and MPP1 was strongly associated with the survival of SARC. This study will shed light on the biological pathways involved in cancer-genetic associations, and has the potential to be applied to the predictions of the risk of cancers developing in healthy individuals.

A pan-cancer study of copy number gain and up-regulation in human oncogenes

AIM

There has been limited research on CNVs in oncogenes and we conducted a systematic pan-cancer analysis of CNVs and their gene expression changes. The aim of the present study was to provide an insight into the relationships between gene expression and oncogenesis.

MAIN METHODS

We collected all the oncogenes from ONGene database and overlapped with CNVs TCGA tumour samples from Catalogue of Somatic Mutations in Cancer database. We further conducted an integrative analysis of CNV with gene expression using the data from the matched TCGA tumour samples.

KEY FINDINGS

From our analysis, we found 637 oncogenes associated with CNVs in 5900 tumour samples. There were 204 oncogenes with frequent copy number of gain (CNG). These 204 oncogenes were enriched in cancer-related pathways including the MAPK cascade and Ras GTPases signalling pathways. By using corresponding tumour samples data to perform integrative analyses of CNVs and gene expression changes, we identified 95 oncogenes with consistent CNG occurrence and up-regulation in the tumour samples, which may represent the recurrent driving force for oncogenesis. Surprisingly, eight oncogenes shown concordant CNG and gene up-regulation in at least 250 tumour samples: INTS8 (355), ECT2 (326), LSM1 (310), DDHD2 (298), COPS5 (286), EIF3E (281), TPD52 (258) and ERBB2 (254).

SIGNIFICANCE

As the first report about abundant CNGs on oncogene and concordant change of gene expression, our results may be valuable for the design of CNV-based cancer diagnostic strategy.

Identification of novel prognosis-related genes associated with cancer using integrative network analysis

Prognosis identifies the seriousness and the chances of survival of a cancer patient. However, it remains a challenge to identify the key cancer genes in prognostic studies. In this study, we collected 2064 genes that were related to prognostic studies by using gene expression measurements curated from published literatures. Among them, 1820 genes were associated with copy number variations (CNVs). The further functional enrichment on 889 genes with frequent copy number gains (CNGs) revealed that these genes were significantly associated with cancer pathways including regulation of cell cycle, cell differentiation and mitogen-activated protein kinase (MAPK) cascade. We further conducted integrative analyses of CNV and their target genes expression using the data from matched tumour samples of The Cancer Genome Atlas (TCGA). Ultimately, 95 key prognosis-related genes were extracted, with concordant CNG events and increased up-regulation in at least 300 tumour samples. These genes, and the number of samples in which they were found, included: ACTL6A (399), ATP6V1C1 (425), EBAG9 (412), FADD (308), MTDH (377), and SENP5 (304). This study provides the first observation of CNV in prognosis-related genes across pan-cancer. The systematic concordance between CNG and up-regulation of gene expression in these novel prognosis-related genes may indicate their prognostic significance.