Somatic Variations in Cervical Cancers in Indian Patients

There are very few reports that describe the mutational landscape of cervical cancer, one of the leading cancers in Indian women. The aim of the present study was to investigate the somatic mutations that occur in cervical cancer. Whole exome sequencing of 10 treatment naïve tumour biopsies with matched blood samples, from a cohort of Indian patients with locally advanced disease, was performed. The data revealed missense mutations across 1282 genes, out of 1831 genes harbouring somatic mutations. These missense mutations (nonsynonymous + stop-gained) when compared with pre-existing mutations in the COSMIC database showed that 272 mutations in 250 genes were already reported although from cancers other than cervical cancer. More than 1000 novel somatic variations were obtained in matched tumour samples. Pathways / genes that are frequently mutated in various other cancers were found to be mutated in cervical cancers. A significant enrichment of somatic mutations in the MAPK pathway was observed, some of which could be potentially targetable. This is the first report of whole exome sequencing of well annotated cervical cancer samples from Indian women and helps identify trends in mutation profiles that are found in an Indian cohort of cervical cancer.     

A Bayesian ensemble approach with a disease gene network predicts damaging effects of missense variants of human cancers

Large-scale sequencing of cancer genomes has revealed many novel mutations and inter-tumoral heterogeneity. Therefore, prioritizing variants according to their potential deleterious effects has become essential. We constructed a disease gene network and proposed a Bayesian ensemble approach that integrates diverse sources to predict the functional effects of missense variants. We analyzed 23,336 missense disease mutations and 36,232 neutral polymorphisms of 12,039 human proteins. The results showed successful improvement of prediction accuracy in both sensitivity and specificity, and we demonstrated the utility of the method by applying it to somatic mutations obtained from colorectal and breast cancer cell lines. The candidate genes with predicted deleterious mutations as well as known cancer genes were significantly enriched in many KEGG pathways related to carcinogenesis, supporting genetic homogeneity of cancer at the pathway level. The breast cancer-specific network increased the prediction accuracy for breast cancer mutations. This study provides a ranked list of deleterious mutations and candidate cancer genes and suggests that mutations affecting cancer may occur in important pathways and should be interpreted on the phenotype-related network or pathway. A disease gene network may be of value in predicting functional effects of novel disease-specific mutations.     

Multigene Panel Sequencing Reveals Cancer-Specific and Common Somatic Mutations in Colorectal Cancer Patients: An Egyptian Experience

This study aims at identifying common pathogenic somatic mutations at different stages of colorectal carcinogenesis in Egyptian patients. Our cohort included colonoscopic biopsies collected from 120 patients: 20 biopsies from patients with inflammatory bowel disease, 38 from colonic polyp patients, and 62 from patients with colorectal cancer. On top of this, the cohort included 20 biopsies from patients with non-specific mild to moderated colitis. Targeted DNA sequencing using a customized gene panel of 96 colorectal related genes running on the Ion Torrent NGS technology was used to process the samples. Our results revealed that 69% of all cases harbored at least one somatic mutation. Fifty-seven genes were found to carry 232 somatic non-synonymous variants. The most frequently pathogenic somatic mutations were localized in TP53, APC, KRAS, and PIK3CA. In total, 16 somatic mutations were detected in the CRC group and in either the IBD or CP group. In addition, our data showed that 51% of total somatic variants were CRC-specific variants. The average number of CRC-specific variants per sample is 2.4. The top genes carrying CRC-specific mutations are APC, TP53, PIK3CA, FBXW7, ATM, and SMAD4. It seems obvious that TP53 and APC genes were the most affected genes with somatic mutations in all groups. Of interest, 85% and 28% of the APC and TP53 deleterious somatic mutations were located in Exon 14 and Exon 3, respectively. Besides, 37% and 28% of the total somatic mutations identified in APC and TP53 were CRC-specific variants, respectively. Moreover, we identified that, in 29 somatic mutations in 21 genes, their association with CRC patients was unprecedented. Ten detected variants were likely to be novel: six in PIK3CA and four variants in FBXW7. The detected P53, Wnt/βcatenin, Angiogenesis, EGFR, TGF-β and Interleukin signaling pathways were the most altered pathways in 22%, 16%, 12%, 10%, 9% and 9% of the CRC patients, respectively. These results would contribute to a better understanding of the colorectal cancer and in introducing personalized therapies for Egyptian CRC patients.     

Detection of somatic mutations by high-resolution DNA melting (HRM) analysis in multiple cancers

Identification of somatic mutations in cancer is a major goal for understanding and monitoring the events related to cancer initiation and progression. High resolution melting (HRM) curve analysis represents a fast, post-PCR high-throughput method for scanning somatic sequence alterations in target genes. The aim of this study was to assess the sensitivity and specificity of HRM analysis for tumor mutation screening in a range of tumor samples, which included 216 frozen pediatric small rounded blue-cell tumors as well as 180 paraffin-embedded tumors from breast, endometrial and ovarian cancers (60 of each). HRM analysis was performed in exons of the following candidate genes known to harbor established commonly observed mutations: PIK3CA, ERBB2, KRAS, TP53, EGFR, BRAF, GATA3, and FGFR3. Bi-directional sequencing analysis was used to determine the accuracy of the HRM analysis. For the 39 mutations observed in frozen samples, the sensitivity and specificity of HRM analysis were 97% and 87%, respectively. There were 67 mutation/variants in the paraffin-embedded samples, and the sensitivity and specificity for the HRM analysis were 88% and 80%, respectively. Paraffin-embedded samples require higher quantity of purified DNA for high performance. In summary, HRM analysis is a promising moderate-throughput screening test for mutations among known candidate genomic regions. Although the overall accuracy appears to be better in frozen specimens, somatic alterations were detected in DNA extracted from paraffin-embedded samples.     

Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility

Background  

Germline polymorphisms can influence gene expression networks in normal mammalian tissues and can affect disease susceptibility. We and others have shown that analysis of this genetic architecture can identify single genes and whole pathways that influence complex traits, including inflammation and cancer susceptibility. Whether germline variants affect gene expression in tumors that have undergone somatic alterations, and the extent to which these variants influence tumor progression, is unknown.     

Strategies to target energy metabolism in consensus molecular subtype 3 along with Kirsten rat sarcoma viral oncogene homolog mutations for colorectal cancer therapy

Alterations in cellular energy metabolism play a critical role in colorectal cancer (CRC), which has been identified as the definition of consensus molecular subtypes (CMSs), and CMS3 tumors exhibit energy metabolism signatures along with Kirsten rat sarcoma viral oncogene homolog (KRAS)-activating mutations. This review summarizes the relationship between CMS3 tumors associated with mutated KRAS and energy metabolism in CRC, especially for the dysregulated energy metabolism that affects tumor cell proliferation, invasion, and migration. Furthermore, this review concentrates on the role of metabolic genes and factors and signaling pathways, which coupled with a primary energy source connected with the CMS3 associated with mutated KRAS, induce metabolic alterations. The strategies to target energy metabolism for the metabolic alterations in mutated KRAS CRC are also introduced. In conclusion, dysregulated energy metabolism has a close relationship with mutated KRAS in CMS3 tumors. Therefore, selective inhibitors or agents against metabolic targets or KRAS signaling may be clinically useful for CMS3 tumor treatment through a personalized approach for patients with cancer.     

Associating somatic mutation with clinical outcomes through kernel regression and optimal transport

Somatic mutations in cancer patients are inherently sparse and potentially high dimensional. Cancer patients may share the same set of deregulated biological processes perturbed by different sets of somatically mutated genes. Therefore, when assessing the associations between somatic mutations and clinical outcomes, gene-by-gene analysis is often under-powered because it does not capture the complex disease mechanisms shared across cancer patients. Rather than testing genes one by one, an intuitive approach is to aggregate somatic mutation data of multiple genes to assess their joint association with clinical outcomes. The challenge is how to aggregate such information. Building on the optimal transport method, we propose a principled approach to estimate the similarity of somatic mutation profiles of multiple genes between tumor samples, while accounting for gene–gene similarities defined by gene annotations or empirical mutational patterns. Using such similarities, we can assess the associations between somatic mutations and clinical outcomes by kernel regression. We have applied our method to analyze somatic mutation data of 17 cancer types and identified at least five cancer types, where somatic mutations are associated with overall survival, progression-free interval, or cytolytic activity.     

Association of Single Nucleotide Polymorphisms in Wnt Signaling Pathway Genes with Breast Cancer in Saudi Patients

Breast cancer is a complex heterogeneous disease involving genetic and epigenetic alterations in genes encoding proteins that are components of various signaling pathways. Candidate gene approach have identified association of genetic variants in the Wnt signaling pathway genes and increased susceptibility to several diseases including breast cancer. Due to the rarity of somatic mutations in key genes of Wnt pathway, we investigated the association of genetic variants in these genes with predisposition to breast cancers. We performed a case-control study to identify risk variants by examining 15 SNPs located in 8 genes associated with Wnt signaling. Genotypic analysis of individual locus showed statistically significant association of five SNPs located in β-catenin, AXIN2, DKK3, SFRP3 and TCF7L2 with breast cancers. Increased risk was observed only with the SNP in β-catenin while the other four SNPs conferred protection against breast cancers. Majority of these associations persisted after stratification of the cases based on estrogen receptor status and age of on-set of breast cancer. The rs7775 SNP in exon 6 of SFRP3 gene that codes for either arginine or glycine exhibited very strong association with breast cancer, even after Bonferroni''s correction. Apart from these five variants, rs3923086 in AXIN2 and rs3763511 in DKK4 that did not show any association in the overall population were significantly associated with early on-set and estrogen receptor negative breast cancers, respectively. This is the first study to utilize pathway based approach to identify association of risk variants in the Wnt signaling pathway genes with breast cancers. Confirmation of our findings in larger populations of different ethnicities would provide evidence for the role of Wnt pathway as well as screening markers for early detection of breast carcinomas.     

Convergence of mutation and epigenetic alterations identifies common genes in cancer that predict for poor prognosis

Background

The identification and characterization of tumor suppressor genes has enhanced our understanding of the biology of cancer and enabled the development of new diagnostic and therapeutic modalities. Whereas in past decades, a handful of tumor suppressors have been slowly identified using techniques such as linkage analysis, large-scale sequencing of the cancer genome has enabled the rapid identification of a large number of genes that are mutated in cancer. However, determining which of these many genes play key roles in cancer development has proven challenging. Specifically, recent sequencing of human breast and colon cancers has revealed a large number of somatic gene mutations, but virtually all are heterozygous, occur at low frequency, and are tumor-type specific. We hypothesize that key tumor suppressor genes in cancer may be subject to mutation or hypermethylation.

Methods and Findings

Here, we show that combined genetic and epigenetic analysis of these genes reveals many with a higher putative tumor suppressor status than would otherwise be appreciated. At least 36 of the 189 genes newly recognized to be mutated are targets of promoter CpG island hypermethylation, often in both colon and breast cancer cell lines. Analyses of primary tumors show that 18 of these genes are hypermethylated strictly in primary cancers and often with an incidence that is much higher than for the mutations and which is not restricted to a single tumor-type. In the identical breast cancer cell lines in which the mutations were identified, hypermethylation is usually, but not always, mutually exclusive from genetic changes for a given tumor, and there is a high incidence of concomitant loss of expression. Sixteen out of 18 (89%) of these genes map to loci deleted in human cancers. Lastly, and most importantly, the reduced expression of a subset of these genes strongly correlates with poor clinical outcome.

Conclusions

Using an unbiased genome-wide approach, our analysis has enabled the discovery of a number of clinically significant genes targeted by multiple modes of inactivation in breast and colon cancer. Importantly, we demonstrate that a subset of these genes predict strongly for poor clinical outcome. Our data define a set of genes that are targeted by both genetic and epigenetic events, predict for clinical prognosis, and are likely fundamentally important for cancer initiation or progression.     

Guanine Holes Are Prominent Targets for Mutation in Cancer and Inherited Disease

Single base substitutions constitute the most frequent type of human gene mutation and are a leading cause of cancer and inherited disease. These alterations occur non-randomly in DNA, being strongly influenced by the local nucleotide sequence context. However, the molecular mechanisms underlying such sequence context-dependent mutagenesis are not fully understood. Using bioinformatics, computational and molecular modeling analyses, we have determined the frequencies of mutation at G•C bp in the context of all 64 5′-NGNN-3′ motifs that contain the mutation at the second position. Twenty-four datasets were employed, comprising >530,000 somatic single base substitutions from 21 cancer genomes, >77,000 germline single-base substitutions causing or associated with human inherited disease and 16.7 million benign germline single-nucleotide variants. In several cancer types, the number of mutated motifs correlated both with the free energies of base stacking and the energies required for abstracting an electron from the target guanines (ionization potentials). Similar correlations were also evident for the pathological missense and nonsense germline mutations, but only when the target guanines were located on the non-transcribed DNA strand. Likewise, pathogenic splicing mutations predominantly affected positions in which a purine was located on the non-transcribed DNA strand. Novel candidate driver mutations and tissue-specific mutational patterns were also identified in the cancer datasets. We conclude that electron transfer reactions within the DNA molecule contribute to sequence context-dependent mutagenesis, involving both somatic driver and passenger mutations in cancer, as well as germline alterations causing or associated with inherited disease.     

Toward the precision breast cancer survival prediction utilizing combined whole genome-wide expression and somatic mutation analysis

Background

Breast cancer is the most common type of invasive cancer in woman. It accounts for approximately 18% of all cancer deaths worldwide. It is well known that somatic mutation plays an essential role in cancer development. Hence, we propose that a prognostic prediction model that integrates somatic mutations with gene expression can improve survival prediction for cancer patients and also be able to reveal the genetic mutations associated with survival.

Method

Differential expression analysis was used to identify breast cancer related genes. Genetic algorithm (GA) and univariate Cox regression analysis were applied to filter out survival related genes. DAVID was used for enrichment analysis on somatic mutated gene set. The performance of survival predictors were assessed by Cox regression model and concordance index(C-index).

Results

We investigated the genome-wide gene expression profile and somatic mutations of 1091 breast invasive carcinoma cases from The Cancer Genome Atlas (TCGA). We identified 118 genes with high hazard ratios as breast cancer survival risk gene candidates (log rank p?<? 0.0001 and c-index?=?0.636). Multiple breast cancer survival related genes were found in this gene set, including FOXR2, FOXD1, MTNR1B and SDC1. Further genetic algorithm (GA) revealed an optimal gene set consisted of 88 genes with higher c-index (log rank p?<? 0.0001 and c-index?=?0.656). We validated this gene set on an independent breast cancer data set and achieved a similar performance (log rank p?<? 0.0001 and c-index?=?0.614). Moreover, we revealed 25 functional annotations, 15 gene ontology terms and 14 pathways that were significantly enriched in the genes that showed distinct mutation patterns in the different survival risk groups. These functional gene sets were used as new features for the survival prediction model. In particular, our results suggested that the Fanconi anemia pathway had an important role in breast cancer prognosis.

Conclusions

Our study indicated that the expression levels of the gene signatures remain the effective indicators for breast cancer survival prediction. Combining the gene expression information with other types of features derived from somatic mutations can further improve the performance of survival prediction. The pathways that were associated with survival risk suggested by our study can be further investigated for improving cancer patient survival.

     

Making sense out of missense mutations: Mechanistic dissection of Notch receptors through structure-function studies in Drosophila

Notch signaling is involved in the development of almost all organ systems and is required post-developmentally to modulate tissue homeostasis. Rare variants in Notch signaling pathway genes are found in patients with rare Mendelian disorders, while unique or recurrent somatic mutations in a similar set of genes are identified in cancer. The human genome contains four genes that encode Notch receptors, NOTCH1-4, all of which are linked to genetic diseases and cancer. Although some mutations have been classified as clear loss- or gain-of-function alleles based on cellular or rodent based assay systems, the functional consequence of many variants/mutations in human Notch receptors remain unknown. In this review, I will first provide an overview of the domain structure of Notch receptors and discuss how each module is known to regulate Notch signaling activity in vivo using the Drosophila Notch receptor as an example. Next, I will introduce some interesting mutant alleles that have been isolated in the fly Notch gene over the past > 100 years of research and discuss how studies of these mutations have facilitated the understanding of Notch biology. By identifying unique alleles of the fly Notch gene through forward genetic screens, mapping their molecular lesions and characterizing their phenotypes in depth, one can begin to unravel new mechanistic insights into how different domains of Notch fine-tune signaling output. Such information can be useful in deciphering the functional consequences of rare variants/mutations in human Notch receptors, which in turn can influence disease management and therapy.     

Mutations in components of antiviral or microbial defense as a basis for breast cancer

In-depth functional analyses of thousands of breast cancer gene mutations reveals vastly different sets of mutated genes in each of 21 different breast cancer genomes. Despite differences in which genes are mutated, innate immunity pathways and metabolic reactions supporting them are always damaged. These functions depend on many different genes. Mutations may be rare individually but each set of mutations affects some aspect of pathogen recognition and defense, especially those involving viruses. Some mutations cause a dysregulated immune response, which can also increase cancer risks. The frequency of an individual mutation may be less important than its effect on function. This work demonstrates that acquired immune deficiencies and immune dysregulation in cancer can occur because of mutations. Abnormal immune responses represent a hidden variable in breast cancer–viral association studies. Compensating for these abnormalities may open many new opportunities for cancer prevention and therapy.     

Whole Genome Sequencing of Newly Established Pancreatic Cancer Lines Identifies Novel Somatic Mutation (c.2587G>A) in Axon Guidance Receptor Plexin A1 as Enhancer of Proliferation and Invasion

The genetic profile of human pancreatic cancers harbors considerable heterogeneity, which suggests a possible explanation for the pronounced inefficacy of single therapies in this disease. This observation has led to a belief that custom therapies based on individual tumor profiles are necessary to more effectively treat pancreatic cancer. It has recently been discovered that axon guidance genes are affected by somatic structural variants in up to 25% of human pancreatic cancers. Thus far, however, some of these mutations have only been correlated to survival probability and no function has been assigned to these observed axon guidance gene mutations in pancreatic cancer. In this study we established three novel pancreatic cancer cell lines and performed whole genome sequencing to discover novel mutations in axon guidance genes that may contribute to the cancer phenotype of these cells. We discovered, among other novel somatic variants in axon guidance pathway genes, a novel mutation in the PLXNA1 receptor (c.2587G>A) in newly established cell line SB.06 that mediates oncogenic cues of increased invasion and proliferation in SB.06 cells and increased invasion in 293T cells upon stimulation with the receptor’s natural ligand semaphorin 3A compared to wild type PLXNA1 cells. Mutant PLXNA1 signaling was associated with increased Rho-GTPase and p42/p44 MAPK signaling activity and cytoskeletal expansion, but not changes in E-cadherin, vimentin, or metalloproteinase 9 expression levels. Pharmacologic inhibition of the Rho-GTPase family member CDC42 selectively abrogated PLXNA1 c.2587G>A-mediated increased invasion. These findings provide in-vitro confirmation that somatic mutations in axon guidance genes can provide oncogenic gain-of-function signals and may contribute to pancreatic cancer progression.     

Breast cancer in the personal genomics era

Breast cancer is a heterogeneous disease with a complex etiology that develops from different cellular lineages, progresses along multiple molecular pathways, and demonstrates wide variability in response to treatment. The "standard of care" approach to breast cancer treatment in which all patients receive similar interventions is rapidly being replaced by personalized medicine, based on molecular characteristics of individual patients. Both inherited and somatic genomic variation is providing useful information for customizing treatment regimens for breast cancer to maximize efficacy and minimize adverse side effects. In this article, we review (1) hereditary breast cancer and current use of inherited susceptibility genes in patient management; (2) the potential of newly-identified breast cancer-susceptibility variants for improving risk assessment; (3) advantages and disadvantages of direct-to-consumer testing; (4) molecular characterization of sporadic breast cancer through immunohistochemistry and gene expression profiling and opportunities for personalized prognostics; and (5) pharmacogenomic influences on the effectiveness of current breast cancer treatments. Molecular genomics has the potential to revolutionize clinical practice and improve the lives of women with breast cancer.     

Modulation of Mutational Landscape in HER2-Positive Breast Cancer after Neoadjuvant Chemotherapy

IntroductionIn early-stage HER2 positive breast cancer (BC) patients, tumor response to neoadjuvant chemotherapy (NACT) predict survival outcomes. Patients achieving less than pathological complete response (pCR) have a worse prognosis, however, this group is heterogeneous. Nowadays limited data on predictive/prognostic biomarkers in patients with residual cancer disease are available.MethodsUsing next-generation sequencing technology, we evaluated a panel of 21 cancer genes in a group of HER2 positive BC patients with residual disease after NACT. A control group of patients who achieved the pCR was selected too. The BC mutational profile was analyzed on both the tumor diagnostic biopsy and matched residual disease.ResultsOverall, the detection rate of mutations was 79% in the No-pCR group versus 90% in the pCR cohort and 98% in the residual BC. The most mutated genes were TP53 and PIK3CA. No correlations between single gene mutations and survival outcomes were found. In no-pCR cohort, 52% of patients had different mutational profile after NACT, 69% of them had an increased in the number of mutated genes. Mutational profile changes from diagnostic biopsy to residual BC were a negative prognostic factor in term of relapse free survival: recurrence probability in different gene profile sub-group was 42% vs 0% in the same profile one (P = .019).ConclusionsTreatment selective pressure on tumor cells due to NACT changed the gene mutational profile in more than half of BC patient with residual tumor disease. Treatment-induced gene mutations significantly increase the risk of relapse. Profiling primary and residual BC is a major step in order to further personalized adjuvant treatment strategy.     

High Mutability of the Tumor Suppressor Genes RASSF1 and RBSP3 (CTDSPL) in Cancer

Background

Many different genetic alterations are observed in cancer cells. Individual cancer genes display point mutations such as base changes, insertions and deletions that initiate and promote cancer growth and spread. Somatic hypermutation is a powerful mechanism for generation of different mutations. It was shown previously that somatic hypermutability of proto-oncogenes can induce development of lymphomas.

Methodology/Principal Findings

We found an exceptionally high incidence of single-base mutations in the tumor suppressor genes RASSF1 and RBSP3 (CTDSPL) both located in 3p21.3 regions, LUCA and AP20 respectively. These regions contain clusters of tumor suppressor genes involved in multiple cancer types such as lung, kidney, breast, cervical, head and neck, nasopharyngeal, prostate and other carcinomas. Altogether in 144 sequenced RASSF1A clones (exons 1–2), 129 mutations were detected (mutation frequency, MF = 0.23 per 100 bp) and in 98 clones of exons 3–5 we found 146 mutations (MF = 0.29). In 85 sequenced RBSP3 clones, 89 mutations were found (MF = 0.10). The mutations were not cytidine-specific, as would be expected from alterations generated by AID/APOBEC family enzymes, and appeared de novo during cell proliferation. They diminished the ability of corresponding transgenes to suppress cell and tumor growth implying a loss of function. These high levels of somatic mutations were found both in cancer biopsies and cancer cell lines.

Conclusions/Significance

This is the first report of high frequencies of somatic mutations in RASSF1 and RBSP3 in different cancers suggesting it may underlay the mutator phenotype of cancer. Somatic hypermutations in tumor suppressor genes involved in major human malignancies offer a novel insight in cancer development, progression and spread.     

Genomic profile analysis of diffuse-type gastric cancers

Background

Stomach cancer is the third deadliest among all cancers worldwide. Although incidence of the intestinal-type gastric cancer has decreased, the incidence of diffuse-type is still increasing and its progression is notoriously aggressive. There is insufficient information on genome variations of diffuse-type gastric cancer because its cells are usually mixed with normal cells, and this low cellularity has made it difficult to analyze the genome.

Results

We analyze whole genomes and corresponding exomes of diffuse-type gastric cancer, using matched tumor and normal samples from 14 diffuse-type and five intestinal-type gastric cancer patients. Somatic variations found in the diffuse-type gastric cancer are compared to those of the intestinal-type and to previously reported variants. We determine the average exonic somatic mutation rate of the two types. We find associated candidate driver genes, and identify seven novel somatic mutations in CDH1, which is a well-known gastric cancer-associated gene. Three-dimensional structure analysis of the mutated E-cadherin protein suggests that these new somatic mutations could cause significant functional perturbations of critical calcium-binding sites in the EC1-2 junction. Chromosomal instability analysis shows that the MDM2 gene is amplified. After thorough structural analysis, a novel fusion gene TSC2-RNF216 is identified, which may simultaneously disrupt tumor-suppressive pathways and activate tumorigenesis.

Conclusions

We report the genomic profile of diffuse-type gastric cancers including new somatic variations, a novel fusion gene, and amplification and deletion of certain chromosomal regions that contain oncogenes and tumor suppressors.