HotSpotter: efficient visualization of driver mutations

HotSPOT: A Computational Tool to Design Targeted Sequencing Panels to Assess Early Photocarcinogenesis

Mutations found in skin are acquired in specific patterns, clustering around mutation-prone genomic locations. The most mutation-prone genomic areas, mutation hotspots, first induce the growth of small cell clones in healthy skin. Mutations accumulate over time, and clones with driver mutations may give rise to skin cancer. Early mutation accumulation is a crucial first step in photocarcinogenesis. Therefore, a sufficient understanding of the process may help predict disease onset and identify avenues for skin cancer prevention. Early epidermal mutation profiles are typically established using high-depth targeted next-generation sequencing. However, there is currently a lack of tools for designing custom panels to capture mutation-enriched genomic regions efficiently. To address this issue, we created a computational algorithm that implements a pseudo-exhaustive approach to identify the best genomic areas to target. We benchmarked the current algorithm in three independent mutation datasets of human epidermal samples. Compared to the sequencing panel designs originally used in these publications, the mutation capture efficacy (number of mutations/base pairs sequenced) of our designed panel improved 9.6-12.1-fold. Mutation burden in the chronically sun-exposed and intermittently sun-exposed normal epidermis was measured within genomic regions identified by hotSPOT based on cutaneous squamous cell carcinoma (cSCC) mutation patterns. We found a significant increase in mutation capture efficacy and mutation burden in cSCC hotspots in chronically sun-exposed vs. intermittently sun-exposed epidermis (p < 0.0001). Our results show that our hotSPOT web application provides a publicly available resource for researchers to design custom panels, enabling efficient detection of somatic mutations in clinically normal tissues and other similar targeted sequencing studies. Moreover, hotSPOT also enables the comparison of mutation burden between normal tissues and cancer.

The Arabidopsis gene co-expression network

Identifying genes that interact to confer a biological function to an organism is one of the main goals of functional genomics. High-throughput technologies for assessment and quantification of genome-wide gene expression patterns have enabled systems-level analyses to infer pathways or networks of genes involved in different functions under many different conditions. Here, we leveraged the publicly available, information-rich RNA-Seq datasets of the model plant Arabidopsis thaliana to construct a gene co-expression network, which was partitioned into clusters or modules that harbor genes correlated by expression. Gene ontology and pathway enrichment analyses were performed to assess functional terms and pathways that were enriched within the different gene modules. By interrogating the co-expression network for genes in different modules that associate with a gene of interest, diverse functional roles of the gene can be deciphered. By mapping genes differentially expressing under a certain condition in Arabidopsis onto the co-expression network, we demonstrate the ability of the network to uncover novel genes that are likely transcriptionally active but prone to be missed by standard statistical approaches due to their falling outside of the confidence zone of detection. To our knowledge, this is the first A. thaliana co-expression network constructed using the entire mRNA-Seq datasets (>20,000) available at the NCBI SRA database. The developed network can serve as a useful resource for the Arabidopsis research community to interrogate specific genes of interest within the network, retrieve the respective interactomes, decipher gene modules that are transcriptionally altered under certain condition or stage, and gain understanding of gene functions.

Predicting Novel Therapies and Targets: Regulation of Notch3 by the Bromodomain Protein BRD4

Systematic approaches for accurate repurposing of targeted therapies are needed. We developed and aimed to biologically validate our therapy predicting tool (TPT) for the repurposing of targeted therapies for specific tumor types by testing the role of Bromodomain and Extra-Terminal motif inhibitors (BETi) in inhibiting BRD4 function and downregulating Notch3 signaling in ovarian cancer.Utilizing established ovarian cancer preclinical models, we carried out in vitro and in vivo studies with clinically relevant BETis to determine their therapeutic effect and impact on Notch3 signaling.Treatment with BETis or siRNA-mediated BRD4 knockdown resulted in decreased cell viability, reduced cell proliferation, and increased cell apoptosis in vitro. In vivo studies with orthotopic mouse models demonstrated that treatment with BETi decreased tumor growth. In addition, knockdown of BRD4 with doxycycline-inducible shRNA increased survival up to 50% (P < 0.001). Treatment with either BETis or BRD4 siRNA decreased Notch3 expression both in vitro and in vivo BRD4 inhibition also decreased the expression of NOTCH3 targets, including HES1 Chromatin immunoprecipitation revealed that BRD4 was present at the NOTCH3 promoter.Our findings provide biological validation for the TPT by demonstrating that BETis can be an effective therapeutic agent for ovarian cancer by downregulating Notch3 expression.The TPT could rapidly identify candidate drugs for ovarian or other cancers along with novel companion biomarkers.

Clinicopathological features and clinical outcomes associated with TP53 and BRAFNon-V600 mutations in cutaneous melanoma patients

BACKGROUND

BRAFV600 , NRAS, TP53, and BRAFNon-V600 are among the most common mutations detected in non-acral cutaneous melanoma patients. Although several studies have identified clinical and pathological features associated with BRAFV600 and NRAS mutations, limited data are available regarding the correlates and significance of TP53 and BRAFNon-V600 mutations.

METHODS

This study analyzed the patient demographics, primary tumor features, and clinical outcomes of a large cohort of non-acral cutaneous melanoma patients who had undergone clinically indicated molecular testing (n = 926).

RESULTS

The prevalence of BRAFV600 , NRAS, TP53, and BRAFNon-V600 mutations was 43%, 21%, 19%, and 7%, respectively. The presence of a TP53 mutation was associated with older age (P = .019), a head and neck primary tumor site (P = .0001), and longer overall survival (OS) from the diagnosis of stage IV disease in univariate (P = .039) and multivariate analyses (P = .015). BRAFNon-V600 mutations were associated with older age (P = .005) but not with primary tumor features or OS from stage IV. Neither TP53 nor BRAFNon-V600 mutations correlated significantly with OS with frontline ipilimumab treatment, and the TP53 status was not significantly associated with outcomes with frontline BRAF inhibitor therapy. Eleven patients with BRAFNon-V600 mutations were treated with a BRAF inhibitor. Three patients were not evaluable for a response because of treatment cessation for toxicities; the remaining patients had disease progression as the best response to therapy.

CONCLUSIONS

These results add to the understanding of the clinical features associated with TP53 and BRAFNon-V600 mutations in advanced cutaneous melanoma patients, and they support the rationale for evaluating the prognostic significance of TP53 in other cohorts of melanoma patients. Cancer 2017;123:1372-1381. © 2016 American Cancer Society.

Reprogramming strategies for the establishment of novel human cancer models

Cancer comprises heterogeneous cells, ranging from highly proliferative immature precursors to more differentiated cell lineages. The emergence of the "cancer stem cell" (CSC) hypothesis that they are the cells responsible for resistance, metastasis and secondary tumor appearance identifies these populations as novel obligatory targets for the treatment of cancer. CSCs, like their normal tissue-specific stem cell counterparts, are multipotent, partially differentiated, self-sustaining, yet transformed cells. To date, most studies on CSC biology have relied on the use of murine models and primary human material. In spite of much progress, the use of primary material presents several limitations that limit our understanding of the mechanisms underlying CSC formation, the similarities between normal stem cells and CSCs and ultimately, the possibility for developing targeted therapies. Recently, different strategies for controlling cell fate have been applied to the modeling of human cancer initiation and for the generation of human CSC models. Here we will summarize recent developments in the establishment and application of reprogramming strategies for the modeling of human cancer initiation and CSC formation.

Exploring preferred amino acid mutations in cancer genes: Applications to identify potential drug targets

Somatic mutations developed with missense, silent, insertions and deletions have varying effects on the resulting protein and are one of the important reasons for cancer development. In this study, we have systematically analysed the effect of these mutations at protein level in 41 different cancer types from COSMIC database on different perspectives: (i) Preference of residues at the mutant positions, (ii) probability of substitutions, (iii) influence of neighbouring residues in driver and passenger mutations, (iv) distribution of driver and passenger mutations around hotspot site in five typical genes and (v) distribution of silent and missense substitutions. We observed that R→H substitution is dominant in drivers followed by R→Q and R→C whereas E→K has the highest preference in passenger mutations. A set of 17 mutations including R→Y, W→A and V→R are specific to driver mutations and 31 preferred substitutions are observed only in passenger mutations. These frequencies of driver mutations vary across different cancer types and are selective to specific tissues. Further, driver missense mutations are mainly surrounded with silent driver mutations whereas the passenger missense mutations are surrounded with silent passenger mutations. This study reveals the variation of mutations at protein level in different cancer types and their preferences in cancer genes and provides new insights for understanding cancer mutations and drug development.

Analysis of mTOR Gene Aberrations in Melanoma Patients and Evaluation of Their Sensitivity to PI3K-AKT-mTOR Pathway Inhibitors

PURPOSE

mTOR is a validated target in cancer. It remains to be determined whether melanoma patients bearing mTOR mutation could be selected for treatment with PI3K-AKT-mTOR pathway inhibitors.

EXPERIMENTAL DESIGN

A total of 412 melanoma samples were included. Gene aberrations in all exons of mTOR were detected by Sanger sequencing and confirmed by using Agilent's SureSelect Target Enrichment System. HEK293T cells stably expressing mTOR mutants were constructed by using transcription activator-like effector nucleases technique. Function of mTOR mutants and in vitro sensitivity of gain-of-function mTOR mutations to PI3K-AKT-mTOR pathway inhibitors were analyzed.

RESULTS

The overall incidence of somatic nonsynonymous mutations of mTOR was 10.4% (43/412). mTOR nonsynonymous mutations were relatively more frequent in acral (11.0%) and mucosal (14.3%) melanomas than in chronic sun-induced damage (CSD; 6.7%) and non-CSD (3.4%) melanomas. Of the 43 cases with mTOR mutations, 41 different mutations were detected, affecting 25 different exons. The median survival time for melanoma patients with mTOR nonsynonymous mutation was significantly shorter than that for patients without mTOR nonsynonymous mutation (P = 0.028). Transient expression of mTOR mutants in HEK293T cells strongly activated the mTOR-p70S6K pathway. In HEK293T cells with stable expression of H1968Y or P2213S mTOR mutants, LY294002 and AZD5363 showed higher potency than temsirolimus or BYL719 in inhibiting the PI3K-AKT-mTOR pathway and cell proliferation.

CONCLUSIONS

mTOR nonsynonymous mutations are frequent in melanoma patients. mTOR nonsynonymous mutation may predict a worse prognosis of melanoma. Clinical trials with PI3K-AKT-mTOR pathway inhibitors may be beneficial for melanoma patients with specific mTOR mutations.