Novel KRAS Gene Mutations in Sporadic Colorectal Cancer

Introduction

In this article, we report 7 novel KRAS gene mutations discovered while retrospectively studying the prevalence and pattern of KRAS mutations in cancerous tissue obtained from 56 Saudi sporadic colorectal cancer patients from the Eastern Province.

Methods

Genomic DNA was extracted from formalin-fixed, paraffin-embedded cancerous and noncancerous colorectal tissues. Successful and specific PCR products were then bi-directionally sequenced to detect exon 4 mutations while Mutector II Detection Kits were used for identifying mutations in codons 12, 13 and 61. The functional impact of the novel mutations was assessed using bioinformatics tools and molecular modeling.

Results

KRAS gene mutations were detected in the cancer tissue of 24 cases (42.85%). Of these, 11 had exon 4 mutations (19.64%). They harbored 8 different mutations all of which except two altered the KRAS protein amino acid sequence and all except one were novel as revealed by COSMIC database. The detected novel mutations were found to be somatic. One mutation is predicted to be benign. The remaining mutations are predicted to cause substantial changes in the protein structure. Of these, the Q150X nonsense mutation is the second truncating mutation to be reported in colorectal cancer in the literature.

Conclusions

Our discovery of novel exon 4 KRAS mutations that are, so far, unique to Saudi colorectal cancer patients may be attributed to environmental factors and/or racial/ethnic variations due to genetic differences. Alternatively, it may be related to paucity of clinical studies on mutations other than those in codons 12, 13, 61 and 146. Further KRAS testing on a large number of patients of various ethnicities, particularly beyond the most common hotspot alleles in exons 2 and 3 is needed to assess the prevalence and explore the exact prognostic and predictive significance of the discovered novel mutations as well as their possible role in colorectal carcinogenesis.     

An Integrated Approach to Uncover Driver Genes in Breast Cancer Methylation Genomes

Background

Cancer cells typically exhibit large-scale aberrant methylation of gene promoters. Some of the genes with promoter methylation alterations play “driver” roles in tumorigenesis, whereas others are only “passengers”.

Results

Based on the assumption that promoter methylation alteration of a driver gene may lead to expression alternation of a set of genes associated with cancer pathways, we developed a computational framework for integrating promoter methylation and gene expression data to identify driver methylation aberrations of cancer. Applying this approach to breast cancer data, we identified many novel cancer driver genes and found that some of the identified driver genes were subtype-specific for basal-like, luminal-A and HER2+ subtypes of breast cancer.

Conclusion

The proposed framework proved effective in identifying cancer driver genes from genome-wide gene methylation and expression data of cancer. These results may provide new molecular targets for potential targeted and selective epigenetic therapy.     

An Integrative -omics Approach to Identify Functional Sub-Networks in Human Colorectal Cancer

Emerging evidence indicates that gene products implicated in human cancers often cluster together in “hot spots” in protein-protein interaction (PPI) networks. Additionally, small sub-networks within PPI networks that demonstrate synergistic differential expression with respect to tumorigenic phenotypes were recently shown to be more accurate classifiers of disease progression when compared to single targets identified by traditional approaches. However, many of these studies rely exclusively on mRNA expression data, a useful but limited measure of cellular activity. Proteomic profiling experiments provide information at the post-translational level, yet they generally screen only a limited fraction of the proteome. Here, we demonstrate that integration of these complementary data sources with a “proteomics-first” approach can enhance the discovery of candidate sub-networks in cancer that are well-suited for mechanistic validation in disease. We propose that small changes in the mRNA expression of multiple genes in the neighborhood of a protein-hub can be synergistically associated with significant changes in the activity of that protein and its network neighbors. Further, we hypothesize that proteomic targets with significant fold change between phenotype and control may be used to “seed” a search for small PPI sub-networks that are functionally associated with these targets. To test this hypothesis, we select proteomic targets having significant expression changes in human colorectal cancer (CRC) from two independent 2-D gel-based screens. Then, we use random walk based models of network crosstalk and develop novel reference models to identify sub-networks that are statistically significant in terms of their functional association with these proteomic targets. Subsequently, using an information-theoretic measure, we evaluate synergistic changes in the activity of identified sub-networks based on genome-wide screens of mRNA expression in CRC. Cross-classification experiments to predict disease class show excellent performance using only a few sub-networks, underwriting the strength of the proposed approach in discovering relevant and reproducible sub-networks.     

Procedure for Identifying Nonsense Mutations

A method has been devised for the rapid identification of nonsense mutations (UAG, UAA, UGA codons) in Salmonella. The mutations to be tested are reverted, and the revertants are replica-printed onto lactose plates spread with lawns of tester strains. These tester strains contain F' lac episomes with nonsense mutations in the episomal Z gene. The revertants are infected with the episome from the tester strain lawn. Because S. typhimurium is unable to ferment lactose, only those revertants which have nonsense suppressors are able to grow on lactose. If colonies appear on the lactose plate, it may be concluded that the original strain carries a nonsense mutation, since nonsense suppressors suppress the mutant phenotype.     

Drug Resistance Missense Mutations in Cancer Are Subject to Evolutionary Constraints

Several tumour types are sensitive to deactivation of just one or very few genes that are constantly active in the cancer cells, a phenomenon that is termed ‘oncogene addiction’. Drugs that target the products of those oncogenes can yield a temporary relief, and even complete remission. Unfortunately, many patients receiving oncogene-targeted therapies relapse on treatment. This often happens due to somatic mutations in the oncogene (‘resistance mutations’). ‘Compound mutations’, which in the context of cancer drug resistance are defined as two or more mutations of the drug target in the same clone may lead to enhanced resistance against the most selective inhibitors. Here, it is shown that the vast majority of the resistance mutations occurring in cancer patients treated with tyrosin kinase inhibitors aimed at three different proteins follow an evolutionary pathway. Using bioinformatic analysis tools, it is found that the drug-resistance mutations in the tyrosine kinase domains of Abl1, ALK and exons 20 and 21 of EGFR favour transformations to residues that can be identified in similar positions in evolutionary related proteins. The results demonstrate that evolutionary pressure shapes the mutational landscape in the case of drug-resistance somatic mutations. The constraints on the mutational landscape suggest that it may be possible to counter single drug-resistance point mutations. The observation of relatively many resistance mutations in Abl1, but not in the other genes, is explained by the fact that mutations in Abl1 tend to be biochemically conservative, whereas mutations in EGFR and ALK tend to be radical. Analysis of Abl1 compound mutations suggests that such mutations are more prevalent than hitherto reported and may be more difficult to counter. This supports the notion that such mutations may provide an escape route for targeted cancer drug resistance.     

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.     

Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks

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高分辨率熔解曲线分析法检测结直肠癌KRAS基因突变

目的:采用高分辨率熔解曲线分析法检测结直肠癌中KRAS基因突变,探讨其用于临床检测的可行性。方法:首先用高分辨率熔解曲线分析法检测64例结直肠癌患者KRAS基因第2外显子的突变情况,再用直接测序法对结果进行验证。结果:通过高分辨率熔解曲线分析法检测,发现有23例KRAS基因突变(35.9%),经直接测序法验证,证实所有患者的突变情况与高分辨率熔解曲线法的结果完全一致;共检测出6种KRAS突变类型,G12D(GGT>GAT)的突变率最高(47.8%),G12D、G12V和G13D等3种常见突变型占总突变数的78.3%。结论:与直接测序法相比,应用高分辨率熔解曲线分析法检测KRAS基因突变具有操作简单快捷、结果准确、成本低的优点,适合应用于临床检测。     

An S-Curve-Based Approach of Identifying Biological Sequences

The main idea of S-curve diagram is to assign different angle values (from 0° to 180°) to different nucleotide acid residues or to different protein amino acids, and then according to cos α _j and sin α _j , the values are accumulated to construct an S-curve diagram, which is in strict one-to-one correspondence with the biological sequence. In addition, the S-curve diagram proves to be without the degeneracy phenomenon, so that both the degeneracy problem represented by diagrams and the problem of visualization for biological sequence data are solved. Meanwhile, a new approach to differentiate the similarity of biological sequences—the degree of similarity—is put forward on the basis of the S-curve diagram. To put it in detail, the least square approach is first adopted to obtain a straight line equation according to the S-curve diagram, then according to the distance formula of the point to the straight line, the average ratio of square sum for the distance between the S-curve and the straight line is calculated, and finally, the similarity of the biological sequences is presented by the new standard—the degree of similarity. As is shown by the experimental results, the S-curve diagram can better represent biological sequences (such as protein’s) within Cartesian coordinate system, and the mutation point of biological sequence. Thus, it turns out that the new standard—the degree of similarity is of obviously great advantage.     

Distinct Clinicopathological Patterns of Mismatch Repair Status in Colorectal Cancer Stratified by KRAS Mutations

In sporadic colorectal cancer (CRC), the BRAF^V600E mutation is associated with deficient mismatch repair (MMR) status and inversely associated with to KRAS mutations. In contrast to deficient MMR (dMMR) CRC, data on the presence of KRAS oncogenic mutations in proficient MMR (pMMR) CRC and their relationship with tumor progression are scarce. We therefore examined the MMR status in combination with KRAS mutations in 913 Chinese patients and correlated the findings obtained with clinical and pathological features. The MMR status was determined based on detection of MLH1, MSH2, MSH6 and PMS2 expression. KRAS mutation and dMMR status were detected in 36.9% and 7.5% of cases, respectively. Four subtypes were determined by MMR and KRAS mutation status: KRAS (+)/pMMR (34.0%), KRAS (+)/dMMR (2.9%), KRAS (-)/pMMR (58.5%) and KRAS (-)/dMMR (4.6%). A higher percentage of pMMR tumors with KRAS mutation were most likely to be female (49.0%), proximal located (45.5%), a mucinous histology (38.4%), and to have increased lymph node metastasis (60.3%), compared with pMMR tumors without BRAF^V600E and KRAS mutations (36.0%, 29.3%, 29.4% and 50.7%, respectively; all P < 0.01). To the contrary, compared with those with KRAS(-)/dMMR tumors, patients with KRAS(+)/dMMR tumors demonstrated no statistically significant differences in gender, tumor location, pT depth of invasion, lymph node metastasis, pTNM stage, and histologic grade. This study revealed that specific epidemiologic and clinicopathologic characteristics are associated with MMR status stratified by KRAS mutation. Knowledge of MMR and KRAS mutation status may enhance molecular pathologic staging of CRC patients and metastatic progression in CRC can be estimated based on the combination of these biomarkers.     

Identification of Candidate Driver Genes in Common Focal Chromosomal Aberrations of Microsatellite Stable Colorectal Cancer

Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide. Chromosomal instability (CIN) is a major driving force of microsatellite stable (MSS) sporadic CRC. CIN tumours are characterised by a large number of somatic chromosomal copy number aberrations (SCNA) that frequently affect oncogenes and tumour suppressor genes. The main aim of this work was to identify novel candidate CRC driver genes affected by recurrent and focal SCNA. High resolution genome-wide comparative genome hybridisation (CGH) arrays were used to compare tumour and normal DNA for 53 sporadic CRC cases. Context corrected common aberration (COCA) analysis and custom algorithms identified 64 deletions and 32 gains of focal minimal common regions (FMCR) at high frequency (>10%). Comparison of these FMCR with published genomic profiles from CRC revealed common overlap (42.2% of deletions and 34.4% of copy gains). Pathway analysis showed that apoptosis and p53 signalling pathways were commonly affected by deleted FMCR, and MAPK and potassium channel pathways by gains of FMCR. Candidate tumour suppressor genes in deleted FMCR included RASSF3, IFNAR1, IFNAR2 and NFKBIA and candidate oncogenes in gained FMCR included PRDM16, TNS1, RPA3 and KCNMA1. In conclusion, this study confirms some previously identified aberrations in MSS CRC and provides in silico evidence for some novel candidate driver genes.     

Prevalence of Pathological Germline Mutations of hMLH1 and hMSH2 Genes in Colorectal Cancer

The prevalence of pathological germline mutations in colorectal cancer has been widely studied, as germline mutations in the DNA mismatch repair genes hMLH1 and hMSH2 confer a high risk of colorectal cancer. However, because the sample size and population of previous studies are very different from each other, the conclusions still remain controversial. In this paper, Databases such as PubMed were applied to search for related papers. The data were imported into Comprehensive Meta-Analysis V2, which was used to estimate the weighted prevalence of hMLH1 and hMSH2 pathological mutations and compare the differences of prevalence among different family histories, ethnicities and related factors. This study collected and utilized data from 102 papers. In the Amsterdam-criteria positive group, the prevalence of pathological germline mutations of the hMLH1 and hMSH2 genes was 28.55% (95%CI 26.04%–31.19%) and 19.41% (95%CI 15.88%–23.51%), respectively, and the prevalence of germline mutations in hMLH1/hMSH2 was 15.44%/10.02%, 20.43%/13.26% and 15.43%/11.70% in Asian, American multiethnic and European/Australian populations, respectively. Substitution mutations accounted for the largest proportion of germline mutations (hMLH1: 52.34%, hMSH2: 43.25%). The total prevalence of mutations of hMLH1 and hMSH2 in Amsterdam-criteria positive, Amsterdam-criteria negative and sporadic colorectal cancers was around 45%, 25% and 15%, respectively, and there were no obvious differences in the prevalence of germline mutations among different ethnicities.