Statistical method on nonrandom clustering with application to somatic mutations in cancer

Background  

Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention.     

Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers

Large‐scale cancer genome sequencing has uncovered thousands of gene mutations, but distinguishing tumor driver genes from functionally neutral passenger mutations is a major challenge. We analyzed 800 cancer genomes of eight types to find single‐nucleotide variants (SNVs) that precisely target phosphorylation machinery, important in cancer development and drug targeting. Assuming that cancer‐related biological systems involve unexpectedly frequent mutations, we used novel algorithms to identify genes with significant phosphorylation‐associated SNVs (pSNVs), phospho‐mutated pathways, kinase networks, drug targets, and clinically correlated signaling modules. We highlight increased survival of patients with TP53 pSNVs, hierarchically organized cancer kinase modules, a novel pSNV in EGFR, and an immune‐related network of pSNVs that correlates with prolonged survival in ovarian cancer. Our findings include multiple actionable cancer gene candidates (FLNB, GRM1, POU2F1), protein complexes (HCF1, ASF1), and kinases (PRKCZ). This study demonstrates new ways of interpreting cancer genomes and presents new leads for cancer research.     

A comprehensive catalogue of somatic mutations in cancer genomes

This Hot Topics contribution considers two recently published papers that demonstrate the utility of advanced DNA sequencing technologies for identifying classes of mutations other than base substitutions. Data are presented from genome analyses of immortalized cell lines derived from a malignant melanoma and a small cell carcinoma of the lung. Among other observations the studies suggest the operation of novel DNA repair mechanisms or modes.     

Uncovering the profile of somatic mtDNA mutations in Chinese colorectal cancer patients

In the past decade, a high incidence of somatic mitochondrial DNA (mtDNA) mutations has been observed, mostly based on a fraction of the molecule, in various cancerous tissues; nevertheless, some of them were queried due to problems in data quality. Obviously, without a comprehensive understanding of mtDNA mutational profile in the cancerous tissue of a specific patient, it is unlikely to disclose the genuine relationship between somatic mtDNA mutations and tumorigenesis. To achieve this objective, the most straightforward way is to directly compare the whole mtDNA genome variation among three tissues (namely, cancerous tissue, para-cancerous tissue, and distant normal tissue) from the same patient. Considering the fact that most of the previous studies on the role of mtDNA in colorectal tumor focused merely on the D-loop or partial segment of the molecule, in the current study we have collected three tissues (cancerous, para-cancerous and normal tissues) respectively recruited from 20 patients with colorectal tumor and completely sequenced the mitochondrial genome of each tissue. Our results reveal a relatively lower incidence of somatic mutations in these patients; intriguingly, all somatic mutations are in heteroplasmic status. Surprisingly, the observed somatic mutations are not restricted to cancer tissues, for the para-cancer tissues and distant normal tissues also harbor somatic mtDNA mutations with a lower frequency than cancerous tissues but higher than that observed in the general population. Our results suggest that somatic mtDNA mutations in cancerous tissues could not be simply explained as a consequence of tumorigenesis; meanwhile, the somatic mtDNA mutations in normal tissues might reflect an altered physiological environment in cancer patients.     

Evidence of somatic mutations in osteoarthritis

We examined, cytogenetically and by in situ hybridization (ISH) techniques, the synovia, osteophytes, and articular cartilage from 32 patients with pronounced osteoarthritis (OA), a prevalent form of arthropathy characterized by progressive reduction of articular cartilage, and synovial samples from 17 control patients. In short-term cultures, clonal chromosome aberrations, in particular the gain of chromosomes 7 (+7) and 5 (+5), were found to be strongly associated with OA. These aberrations were found in almost 90% of the cultures from synovia and osteophytes, whereas only 1/11 synovial samples from joints unequivocally unaffected by OA had cells with +5 or +7. The in vivo nature of trisomy 7 was demonstrated by ISH on uncultured cells, and serial passaging showed that cells with +7 had a proliferative advantage in vitro. Thus, the combined data indicate that cells with somatic mutations appear early and may be influential in the disease process leading to OA. Received: 7 June 1996 / Revised: 9 August 1996     

E-cadherin destabilization accounts for the pathogenicity of missense mutations in hereditary diffuse gastric cancer

E-cadherin is critical for the maintenance of tissue architecture due to its role in cell-cell adhesion. E-cadherin mutations are the genetic cause of Hereditary Diffuse Gastric Cancer (HDGC) and missense mutations represent a clinical burden, due to the uncertainty of their pathogenic role. In vitro and in vivo, most mutations lead to loss-of-function, although the causal factor is unknown for the majority. We hypothesized that destabilization could account for the pathogenicity of E-cadherin missense mutations in HDGC, and tested our hypothesis using in silico and in vitro tools. FoldX algorithm was used to calculate the impact of each mutation in E-cadherin native-state stability, and the analysis was complemented with evolutionary conservation, by SIFT. Interestingly, HDGC patients harbouring germline E-cadherin destabilizing mutants present a younger age at diagnosis or death, suggesting that the loss of native-state stability of E-cadherin accounts for the disease phenotype. To elucidate the biological relevance of E-cadherin destabilization in HDGC, we investigated a group of newly identified HDGC-associated mutations (E185V, S232C and L583R), of which L583R is predicted to be destabilizing. We show that this mutation is not functional in vitro, exhibits shorter half-life and is unable to mature, due to premature proteasome-dependent degradation, a phenotype reverted by stabilization with the artificial mutation L583I (structurally tolerated). Herein we report E-cadherin structural models suitable to predict the impact of the majority of cancer-associated missense mutations and we show that E-cadherin destabilization leads to loss-of-function in vitro and increased pathogenicity in vivo.     

Statistical analysis of disease-causing and neutral mutations in human membrane proteins

Mutations in transmembrane proteins (TMPs) have diverse effects on their structure and functions, which may lead to various diseases. In this present study, we have investigated variations in human membrane proteins and found that negatively charged to positively charged/polar and nonpolar to nonpolar changes are dominant in disease-causing and neutral mutations, respectively. Further, we analyzed the top 10 preferred mutations in 14 different disease classes and found that each class has at least two Arg mutations. Moreover, in cardiovascular diseases and congenital disorders of metabolism, Cys mutations occur more frequently in single-pass proteins, whereas Arg and nonpolar residues are more frequently substituted in multi-pass membrane proteins. The immune system diseases are enriched in C → R and C → Y mutations in inside and outside regions. On the other hand, in the membrane region, E → K and R → Q mutations are prevalent. The comparison of mutations in topologically similar regions of globular and membrane proteins showed that Ser and Thr mutations cause deleterious effects in membrane regions, whereas Cys and charged residues, Asp and Arg are prevalent in the buried regions of globular proteins. Our comprehensive analysis of disease-associated mutations in transmembrane proteins will be useful for developing prediction tools.     

Identification of high-confidence somatic mutations in whole genome sequence of formalin-fixed breast cancer specimens

The utilization of archived, formalin-fixed paraffin-embedded (FFPE) tumor samples for massive parallel sequencing has been challenging due to DNA damage and contamination with normal stroma. Here, we perform whole genome sequencing of DNA isolated from two triple-negative breast cancer tumors archived for >11 years as 5 μm FFPE sections and matched germline DNA. The tumor samples show differing amounts of FFPE damaged DNA sequencing reads revealed as relatively high alignment mismatch rates enriched for C · G > T · A substitutions compared to germline samples. This increase in mismatch rate is observable with as few as one million reads, allowing for an upfront evaluation of the sample integrity before whole genome sequencing. By applying innovative quality filters incorporating global nucleotide mismatch rates and local mismatch rates, we present a method to identify high-confidence somatic mutations even in the presence of FFPE induced DNA damage. This results in a breast cancer mutational profile consistent with previous studies and revealing potentially important functional mutations. Our study demonstrates the feasibility of performing genome-wide deep sequencing analysis of FFPE archived tumors of limited sample size such as residual cancer after treatment or metastatic biopsies.     

High throughput interrogation of somatic mutations in high grade serous cancer of the ovary

Background

Epithelial ovarian cancer is the most lethal of all gynecologic malignancies, and high grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer. The objective of this study was to determine the frequency and types of point somatic mutations in HGSC using a mutation detection protocol called OncoMap that employs mass spectrometric-based genotyping technology.

Methodology/Principal Findings

The Center for Cancer Genome Discovery (CCGD) Program at the Dana-Farber Cancer Institute (DFCI) has adapted a high-throughput genotyping platform to determine the mutation status of a large panel of known cancer genes. The mutation detection protocol, termed OncoMap has been expanded to detect more than 1000 mutations in 112 oncogenes in formalin-fixed paraffin-embedded (FFPE) tissue samples. We performed OncoMap on a set of 203 FFPE advanced staged HGSC specimens. We isolated genomic DNA from these samples, and after a battery of quality assurance tests, ran each of these samples on the OncoMap v3 platform. 56% (113/203) tumor samples harbored candidate mutations. Sixty-five samples had single mutations (32%) while the remaining samples had ≥2 mutations (24%). 196 candidate mutation calls were made in 50 genes. The most common somatic oncogene mutations were found in EGFR, KRAS, PDGRFα, KIT, and PIK3CA. Other mutations found in additional genes were found at lower frequencies (<3%).

Conclusions/Significance

Sequenom analysis using OncoMap on DNA extracted from FFPE ovarian cancer samples is feasible and leads to the detection of potentially druggable mutations. Screening HGSC for somatic mutations in oncogenes may lead to additional therapies for this patient population.     

Casein kinase I epsilon somatic mutations found in breast cancer cause overgrowth in Drosophila

We are using a candidate gene approach to identify genes contributing to cancer through somatic mutation. Somatic mutations were found in breast cancer samples in the human casein kinase I epsilon (CKIepsilon) gene, a homolog of the Drosophila gene dco in which certain point mutations lead to imaginal disc overgrowth. We therefore created fly genotypes in which the dco gene carried point mutations homologous to those discovered in CKIepsilon, and tested them in vivo. The results show that the most frequent mutation discovered in breast cancer, L39Q, causes a striking overgrowth phenotype in flies. Further experiments show that this mutation affects the newly recognized Fat/Warts signaling pathway, which controls organ size and shape in both flies and mammals. Another mutation, S101R, modifies the mutant phenotype so that the affected tissue disintegrates, mimicking more aggressive forms of breast cancer. Our results thus strongly support the conclusion that CKIepsilon mutations play important roles in breast carcinogenesis.     

On somatic mutations and tissue fields in cancer: additional observations challenge the SMT

Editor's suggested further reading in BioEssays: Fields and field cancerization: The preneoplastic origins of cancer Abstract