Statistical analysis of pathogenicity of somatic mutations in cancer

Recent large-scale sequencing studies have revealed that cancer genomes contain variable numbers of somatic point mutations distributed across many genes. These somatic mutations most likely include passenger mutations that are not cancer causing and pathogenic driver mutations in cancer genes. Establishing a significant presence of driver mutations in such data sets is of biological interest. Whereas current techniques from phylogeny are applicable to large data sets composed of singly mutated samples, recently exemplified with a p53 mutation database, methods for smaller data sets containing individual samples with multiple mutations need to be developed. By constructing distinct models of both the mutation process and selection pressure upon the cancer samples, exact statistical tests to examine this problem are devised. Tests to examine the significance of selection toward missense, nonsense, and splice site mutations are derived, along with tests assessing variation in selection between functional domains. Maximum-likelihood methods facilitate parameter estimation, including levels of selection pressure and minimum numbers of pathogenic mutations. These methods are illustrated with 25 breast cancers screened across the coding sequences of 518 kinase genes, revealing 90 base substitutions in 71 genes. Significant selection pressure upon truncating mutations was established. Furthermore, an estimated minimum of 29.8 mutations were pathogenic.     

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.     

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.     

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.     

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     

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.     

Haldane's rule and somatic mutations]

Haldane's rule stating that viability and fertility in the heterogametic sex of hybrids are lower than in the homogametic sex is explained on the basis of the assumption that diploidy is aimed at protecting individuals having large body size and large genomes from somatic mutations. The presence of hemizygous sex chromosomes, which are effectively haploid in the heterogametic sex, results in the phenotypic expression of all deleterious somatic mutations arising in them. In the homogametic sex, somatic mutations that affect one out of two identical sex chromosomes are not expressed because the unaffected chromosome functions normally. Thus, the heterogametic sex is more sensitive to the harmful effect of somatic mutations. In hybrids, this difference may be critical. Consequently, when genetic distance between hybridizing species increases, the heterogametic sex of hybrids loses viability and fertility earlier than the homogametic sex, which agrees with Haldane's rule. On the basis of Haldane's rule and data on the small size of natural hybrid zones, restrictions on maximum heterozygosity compatible with viability were established.     

Estimating cell depth from somatic mutations

The depth of a cell of a multicellular organism is the number of cell divisions it underwent since the zygote, and knowing this basic cell property would help address fundamental problems in several areas of biology. At present, the depths of the vast majority of human and mouse cell types are unknown. Here, we show a method for estimating the depth of a cell by analyzing somatic mutations in its microsatellites, and provide to our knowledge for the first time reliable depth estimates for several cells types in mice. According to our estimates, the average depth of oocytes is 29, consistent with previous estimates. The average depth of B cells ranges from 34 to 79, linearly related to the mouse age, suggesting a rate of one cell division per day. In contrast, various types of adult stem cells underwent on average fewer cell divisions, supporting the notion that adult stem cells are relatively quiescent. Our method for depth estimation opens a window for revealing tissue turnover rates in animals, including humans, which has important implications for our knowledge of the body under physiological and pathological conditions.     

Interphase cytogenetics in estimation of genomic mutations in somatic cells

The review considers the current state, possibilities, and perspectives of using interphase cytogenetics in the estimation of genomic mutations in human and animal somatic cells for aims of genetic toxicology and genetic instability analysis. Possible mechanisms underlying action of mutagens causing numeric chromosome aberrations are discussed.     

Biochip detection of KRAS,BRAF, and PIK3CA somatic mutations in colorectal cancer patients

Molecular Biology - Somatic mutations of KRAS, PIK3CA, and BRAF cause insensitivity of colorectal tumors to therapy with anti-EGFR monoclonal antibodies, necessitating a genetic testing prior to...     

Interphase cytogenetics in estimation of genomic mutations in somatic cells

The review considers the current state, possibilities, and perspectives of using interphase cytogenetics in the estimation of genomic mutations in human and animal somatic cells for aims of genetic toxicology and genetic instability analysis. Possible mechanisms underlying action of mutagens causing numeric chromosome aberrations are discussed.Translated from Genetika, Vol. 41, No. 1, 2005, pp. 5–16.Original Russian Text Copyright © 2005 by Timoshevsky, Nazarenko.     

Interactions between somatic mutations and plant development

It is hypothesised that somatic mutations are an important source of genetic variance within long-lived plant individuals, and that shoot ontogeny and sexual reproduction are two processes that decrease the mutation load of the shoot population and the offspring. This paper focuses on the way in which sympodial and monopodial shoot branching may influence intra-plant genetic variation and on the role of physiological integration between plant modules for the phenotypic expression of this variation. I also discuss some possible consequences of the interaction of somatic mutations and shoot ontogeny for the study of seedling recruitment and phenotypic plasticity in plant populations.