Junfeng Xia

BRAF L597 mutations in melanoma are associated with sensitivity to MEK inhibitors

UNLABELLED Kinase inhibitors are accepted treatment for metastatic melanomas that harbor specific driver mutations in BRAF or KIT, but only 40% to 50% of cases are positive. To uncover other potential targetable mutations, we conducted whole-genome sequencing of a highly aggressive BRAF (V600) and KIT (W557, V559, L576, K642, and D816) wild-type melanoma. Surprisingly, we found a somatic BRAF(L597R) mutation in exon 15. Analysis of BRAF exon 15 in 49 tumors negative for BRAF(V600) mutations as well as driver mutations in KIT, NRAS, GNAQ, and GNA11, showed that two (4%) harbored L597 mutations and another two involved BRAF D594 and K601 mutations. In vitro signaling induced by L597R/S/Q mutants was suppressed by mitogen-activated protein (MAP)/extracellular signal-regulated kinase (ERK) kinase (MEK) inhibition. A patient with BRAF(L597S) mutant metastatic melanoma responded significantly to treatment with the MEK inhibitor, TAK-733. Collectively, these data show clinical significance to BRAF(L597) mutations in melanoma. SIGNIFICANCE This study shows that cells harboring BRAF(L597R) mutants are sensitive to MEK inhibitor treatment, providing a rationale for routine screening and therapy of BRAF(L597R)-mutant melanoma.

Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives

Gene fusions are important genomic events in human cancer because their fusion gene products can drive the development of cancer and thus are potential prognostic tools or therapeutic targets in anti-cancer treatment. Major advancements have been made in computational approaches for fusion gene discovery over the past 3 years due to improvements and widespread applications of high-throughput next generation sequencing (NGS) technologies. To identify fusions from NGS data, existing methods typically leverage the strengths of both sequencing technologies and computational strategies. In this article, we review the NGS and computational features of existing methods for fusion gene detection and suggest directions for future development.

A Meta-analysis of Somatic Mutations from Next Generation Sequencing of 241 Melanomas: A Road Map for the Study of Genes with Potential Clinical Relevance

Next generation sequencing (NGS) has been used to characterize the overall genomic landscape of melanomas. Here, we systematically examined mutations from recently published melanoma NGS data involving 241 paired tumor-normal samples to identify potentially clinically relevant mutations. Melanomas were characterized according to an in-house clinical assay that identifies well-known specific recurrent mutations in five driver genes: BRAF (affecting V600), NRAS (G12, G13, and Q61), KIT (W557, V559, L576, K642, and D816), GNAQ (Q209), and GNA11 (Q209). Tumors with none of these mutations are termed “pan negative.” We then mined the driver mutation-positive and pan-negative melanoma NGS data for mutations in 632 cancer genes that could influence existing or emerging targeted therapies. First, we uncovered several genes whose mutations were more likely associated with BRAF- or NRAS-driven melanomas, including TP53 and COL1A1 with BRAF, and PPP6C, KALRN, PIK3R4, TRPM6, GUCY2C, and PRKAA2 with NRAS. Second, we found that the 69 “pan-negative” melanoma genomes harbored alternate infrequent mutations in the five known driver genes along with many mutations in genes encoding guanine nucleotide binding protein α-subunits. Third, we identified 12 significantly mutated genes in “pan-negative” samples (ALK, STK31, DGKI, RAC1, EPHA4, ADAMTS18, EPHA7, ERBB4, TAF1L, NF1, SYK, and KDR), including five genes (RAC1, ADAMTS18, EPHA7, TAF1L, and NF1) with a recurrent mutation in at least two “pan-negative” tumor samples. This meta-analysis provides a road map for the study of additional potentially actionable genes in both driver mutation-positive and pan-negative melanomas. Mol Cancer Ther; 13(7); 1918–28. ©2014 AACR.

Investigating the relationship of DNA methylation with mutation rate and allele frequency in the human genome

BackgroundDNA methylation, which mainly occurs at CpG dinucleotides, is a dynamic epigenetic regulation mechanism in most eukaryotic genomes. It is already known that methylated CpG dinucleotides can lead to a high rate of C to T mutation at these sites. However, less is known about whether and how the methylation level causes a different mutation rate, especially at the single-base resolution.ResultsIn this study, we used genome-wide single-base resolution methylation data to perform a comprehensive analysis of the mutation rate of methylated cytosines from human embryonic stem cell. Through the analysis of the density of single nucleotide polymorphisms, we first confirmed that the mutation rate in methylated CpG sites is greater than that in unmethylated CpG sites. Then, we showed that among methylated CpG sites, the mutation rate is markedly increased in low-intermediately (20-40% methylation level) to intermediately methylated CpG sites (40-60% methylation level) of the human genome. This mutation pattern was observed regardless of DNA strand direction and the sequence coverage over the site on which the methylation level was calculated. Moreover, this highly non-random mutation pattern was found more apparent in intergenic and intronic regions than in promoter regions and CpG islands. Our investigation suggested this pattern appears primarily in autosomes rather than sex chromosomes. Further analysis based on human-chimpanzee divergence confirmed these observations. Finally, we observed a significant correlation between the methylation level and cytosine allele frequency.ConclusionsOur results showed a high mutation rate in low-intermediately to intermediately methylated CpG sites at different scales, from the categorized genomic region, whole chromosome, to the whole genome level, thereby providing the first supporting evidence of mutation rate variation at human methylated CpG sites using the genome-wide sing-base resolution methylation data.

NGS Catalog: A Database of Next Generation Sequencing Studies in Humans

Next generation sequencing (NGS) technologies have been rapidly applied in biomedical and biological research since its advent only a few years ago, and they are expected to advance at an unprecedented pace in the following years. To provide the research community with a comprehensive NGS resource, we have developed the database Next Generation Sequencing Catalog (NGS Catalog, http://bioinfo.mc.vanderbilt.edu/NGS/index.html), a continually updated database that collects, curates and manages available human NGS data obtained from published literature. NGS Catalog deposits publication information of NGS studies and their mutation characteristics (SNVs, small insertions/deletions, copy number variations, and structural variants), as well as mutated genes and gene fusions detected by NGS. Other functions include user data upload, NGS general analysis pipelines, and NGS software. NGS Catalog is particularly useful for investigators who are new to NGS but would like to take advantage of these powerful technologies for their own research. Finally, based on the data deposited in NGS Catalog, we summarized features and findings from whole exome sequencing, whole genome sequencing, and transcriptome sequencing studies for human diseases or traits.

Next-generation sequencing of paired tyrosine kinase inhibitor-sensitive and -resistant EGFR mutant lung cancer cell lines identifies spectrum of DNA changes associated with drug resistance

Somatic mutations in kinase genes are associated with sensitivity of solid tumors to kinase inhibitors, but patients with metastatic cancer eventually develop disease progression. In EGFR mutant lung cancer, modeling of acquired resistance (AR) with drug-sensitive cell lines has identified clinically relevant EGFR tyrosine kinase inhibitor (TKI) resistance mechanisms such as the second-site mutation, EGFR T790M, amplification of the gene encoding an alternative kinase, MET, and epithelial-mesenchymal transition (EMT). The full spectrum of DNA changes associated with AR remains unknown. We used next-generation sequencing to characterize mutational changes associated with four populations of EGFR mutant drug-sensitive and five matched drug-resistant cell lines. Comparing resistant cells with parental counterparts, 18-91 coding SNVs/indels were predicted to be acquired and 1-27 were lost; few SNVs/indels were shared across resistant lines. Comparison of two related parental lines revealed no unique coding SNVs/indels, suggesting that changes in the resistant lines were due to drug selection. Surprisingly, we observed more CNV changes across all resistant lines, and the line with EMT displayed significantly higher levels of CNV changes than the other lines with AR. These results demonstrate a framework for studying the evolution of AR and provide the first genome-wide spectrum of mutations associated with the development of cellular drug resistance in an oncogene-addicted cancer. Collectively, the data suggest that CNV changes may play a larger role than previously appreciated in the acquisition of drug resistance and highlight that resistance may be heterogeneous in the context of different tumor cell backgrounds.

MET Exon 14 Skipping in Non-Small Cell Lung Cancer

BACKGROUND Non-small cell lung cancers (NSCLCs) harboring specific genetic alterations can be highly sensitive to targeted therapies. MATERIALS AND METHODS We performed a targeted rearrangement assay on 54 NSCLCs across all stages that were from patients who were never smokers and did not have driver mutations. Because MET exon 14 skipping was the most frequent alteration found, we surveyed the results for MET exon 14 skipping at Massachusetts General Hospital (MGH) since the inclusion of this alteration into our current molecular profiling panel. RESULTS In a cohort of 54 never-smokers with lung cancers that were wild-type for known driver mutations, MET exon 14 skipping was the most frequently recurring alteration, occurring in 10 cancers (19%). Clinical testing at MGH via our next-generation sequencing (NGS) and NGS-rearrangement panels showed an additional 16 cases of MET exon 14 skipping, for an overall estimated frequency of 5.6%. A clinical case of a patient with MET exon 14 skipping treated with the MET inhibitor crizotinib is also described. CONCLUSION MET exon 14 skipping is a targetable gene alteration found in NSCLC. Patients with these alterations may respond well to MET inhibition. IMPLICATIONS FOR PRACTICE MET exon 14 skipping occurs with an approximately 5% frequency in NSCLC and is seen in both squamous and adenocarcinoma histology. Patients whose cancers have MET exon 14 skipping can respond well to MET inhibitors. Molecular testing for MET exon 14 skipping should be performed on all lung cancers because this is a targetable alteration.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer.

Inconsistency and features of single nucleotide variants detected in whole exome sequencing versus transcriptome sequencing: A case study in lung cancer.

Whole exome sequencing (WES) and RNA sequencing (RNA-Seq) are two main platforms used for next-generation sequencing (NGS). While WES is primarily for DNA variant discovery and RNA-Seq is mainly for measurement of gene expression, both can be used for detection of genetic variants, especially single nucleotide variants (SNVs). How consistently variants can be detected from WES and RNA-Seq has not been systematically evaluated. In this study, we examined the technical and biological inconsistencies in SNV detection using WES and RNA-Seq data from 27 pairs of tumor and matched normal samples. We analyzed SNVs in three categories: WES unique - those only detected in WES, RNA-Seq unique - those only detected in RNA-Seq, and shared - those detected in both. We found a small overlap (average ∼14%) between the SNVs called in WES and RNA-Seq. The WES unique SNVs were mainly due to low coverage, low expression, or their location on the non-transcribed strand in RNA-Seq data, while the RNA-Seq unique SNVs were primarily due to their location out of the WES-capture boundary regions (accounting ∼71%), as well as low coverage of the regions, low coverage of the mutant alleles or RNA-editing. The shared SNVs had high locus-specific coverage in both WES and RNA-Seq and high gene expression levels. Additionally, WES unique and RNA-Seq unique SNVs showed different nucleotide substitution patterns, e.g., ∼55% of RNA-Seq unique variants were A:T→G:C, a hallmark of RNA editing. This study provides an important evaluation on the inconsistencies of somatic SNVs called in WES and RNA-Seq data.

Virus interactions with human signal transduction pathways

Viruses depend on their hosts at every stage of their life cycles and must therefore communicate with them via Protein-Protein Interactions (PPIs). To investigate the mechanisms of communication by different viruses, we overlay reported pairwise human-virus PPIs on human signalling pathways. Of 671 pathways obtained from NCI and Reactome databases, 355 are potentially targeted by at least one virus. The majority of pathways are linked to more than one virus. We find evidence supporting the hypothesis that viruses often interact with different proteins depending on the targeted pathway. Pathway analysis indicates overrepresentation of some pathways targeted by viruses. The merged network of the most statistically significant pathways shows several centrally located proteins, which are also hub proteins. Generally, hub proteins are targeted more frequently by viruses. Numerous proteins in virus-targeted pathways are known drug targets, suggesting that these might be exploited as potential new approaches to treatments against multiple viruses.