Prioritization of driver mutations in pancreatic cancer using cancer-specific high-throughput annotation of somatic mutations (CHASM)

Oncolytic Tanapoxvirus Variants Expressing mIL-2 and mCCL-2 Regress Human Pancreatic Cancer Xenografts in Nude Mice

Pancreatic ductal adenocarcinoma (PDAC) is the fifth leading cause of cancer-related death and presents the lowest 5-year survival rate of any form of cancer in the US. Only 20% of PDAC patients are suitable for surgical resection and adjuvant chemotherapy, which remains the only curative treatment. Chemotherapeutic and gene therapy treatments are associated with adverse effects and lack specificity/efficacy. In this study, we assess the oncolytic potential of immuno-oncolytic tanapoxvirus (TPV) recombinants expressing mouse monocyte chemoattractant protein (mMCP-1 or mCCL2) and mouse interleukin (mIL)-2 in human pancreatic BxPc-3 cells using immunocompromised and CD-3+ T-cell-reconstituted mice. Intratumoral treatment with TPV/∆66R/mCCL2 and TPV/∆66R/mIL-2 resulted in a regression in BxPc-3 xenograft volume compared to control in immunocompromised mice; mCCL-2 expressing TPV OV resulted in a significant difference from control at p < 0.05. Histological analysis of immunocompromised mice treated with TPV/∆66R/mCCL2 or TPV/∆66R/mIL-2 demonstrated multiple biomarkers indicative of increased severity of chronic, active inflammation compared to controls. In conclusion, TPV recombinants expressing mCCL2 and mIL-2 demonstrated a therapeutic effect via regression in BxPc-3 tumor xenografts. Considering the enhanced oncolytic potency of TPV recombinants demonstrated against PDAC in this study, further investigation as an alternative or combination treatment option for human PDAC may be warranted.

Cilia and Cancer: From Molecular Genetics to Therapeutic Strategies

Cilia are microtubule-based organelles that project from the cell surface with motility or sensory functions. Primary cilia work as antennae to sense and transduce extracellular signals. Cilia critically control proliferation by mediating cell-extrinsic signals and by regulating cell cycle entry. Recent studies have shown that primary cilia and their associated proteins also function in autophagy and genome stability, which are important players in oncogenesis. Abnormal functions of primary cilia may contribute to oncogenesis. Indeed, defective cilia can either promote or suppress cancers, depending on the cancer-initiating mutation, and the presence or absence of primary cilia is associated with specific cancer types. Together, these findings suggest that primary cilia play important, but distinct roles in different cancer types, opening up a completely new avenue of research to understand the biology and treatment of cancers. In this review, we discuss the roles of primary cilia in promoting or inhibiting oncogenesis based on the known or predicted functions of cilia and cilia-associated proteins in several key processes and related clinical implications.

Computational Methods Summarizing Mutational Patterns in Cancer: Promise and Limitations for Clinical Applications

Since the rise of next-generation sequencing technologies, the catalogue of mutations in cancer has been continuously expanding. To address the complexity of the cancer-genomic landscape and extract meaningful insights, numerous computational approaches have been developed over the last two decades. In this review, we survey the current leading computational methods to derive intricate mutational patterns in the context of clinical relevance. We begin with mutation signatures, explaining first how mutation signatures were developed and then examining the utility of studies using mutation signatures to correlate environmental effects on the cancer genome. Next, we examine current clinical research that employs mutation signatures and discuss the potential use cases and challenges of mutation signatures in clinical decision-making. We then examine computational studies developing tools to investigate complex patterns of mutations beyond the context of mutational signatures. We survey methods to identify cancer-driver genes, from single-driver studies to pathway and network analyses. In addition, we review methods inferring complex combinations of mutations for clinical tasks and using mutations integrated with multi-omics data to better predict cancer phenotypes. We examine the use of these tools for either discovery or prediction, including prediction of tumor origin, treatment outcomes, prognosis, and cancer typing. We further discuss the main limitations preventing widespread clinical integration of computational tools for the diagnosis and treatment of cancer. We end by proposing solutions to address these challenges using recent advances in machine learning.

Identification and validation of a metabolism-related gene signature for the prognosis of colorectal cancer: a multicenter cohort study

OBJECTIVE

Cell metabolism plays a vital role in the proliferation, metastasis and sensitivity to chemotherapy drugs of colorectal cancer. The purpose of this multicenter cohort study is to investigate the potential genes indicating clinical outcomes in colorectal cancer patients.

METHODS

We analyzed gene expression profiles of colorectal cancer to identify differentially expressed genes then used these differentially expressed genes to construct prognostic signature based on the least absolute shrink-age and selection operator Cox regression model. In addition, the multi-gene signature was validated in independent datasets including our multicenter cohort. Finally, nomograms were set up to evaluate the prognosis of colorectal cancer patients.

RESULTS

Seventeen metabolism-related genes were determined in the least absolute shrink-age and selection operator model to construct signature, with area under receiver operating characteristic curve for relapse-free survival, 0.741, 0.755 and 0.732 at 1, 3 and 5 year, respectively. External validation datasets, GSE14333, GSE37892, GSE17538 and the Cancer Genome Atlas cohorts, were analyzed and stratified, indicating that the metabolism-related signature was reliable in discriminating high- and low-risk colorectal cancer patients. Area under receiver operating characteristic curves for relapse-free survival in our multicenter validation cohort were 0.801, 0.819 and 0.857 at 1, 3 and 5 year, respectively. Nomograms incorporating the genetic biomarkers and clinical pathological features were set up, which yielded good discrimination and calibration in the prediction of prognosis for colorectal cancer patients.

CONCLUSION

An original metabolism-related signature was developed as a predictive model for the prognosis of colorectal cancer patients. A nomogram based on the signature was advantageous to facilitate personalized counselling and treatment of colorectal cancer patients.

Enhancing Cancer Driver Gene Prediction by Protein-Protein Interaction Network

With the advances in gene sequencing technologies, millions of somatic mutations have been reported in the past decades, but mining cancer driver genes with oncogenic mutations from these data remains a critical and challenging area of research. In this study, we proposed a network-based classification method for identifying cancer driver genes with merging the multi-biological information. In this method, we construct a cancer specific genetic network from the human protein-protein interactome (PPI) to mine the network structure attributes, and combine biological information such as mutation frequency and differential expression of genes to achieve accurate prediction of cancer driver genes. Across seven different cancer types, the proposed algorithm always achieves high prediction accuracy, which is superior to the existing advanced methods. In the analysis of the predicted results, about 40 percent of the top 10 candidate genes overlap with the Cancer Gene Census database. Interestingly, the feature comparison indicates that the network based features are still more important than the biological features, including the mutation frequency and genetic differential expression. Further analyses also show that the integration of network structure attributes and biological information is valuable for predicting new cancer driver genes.

Comprehensive Analysis of Expression and Prognostic Value of MS4As in Glioma

Glioma is the most common malignancy of the nervous system with high mortality rates. The MS4A family members have been reported as potential prognostic biomarkers in several cancers; however, the relationship between the MS4A family and glioma has not been clearly confirmed. In our study, we explored the prognostic value of MS4As as well as their potential pro-cancer mechanisms of glioma. Using bioinformatics analysis methods based on the data from public databases, we found that the expression of MS4A4A, MS4A4E, MS4A6A, MS4A7, TMEM176A, and TMEM176B was significantly overexpressed in glioma tissues compared with that of normal tissues. The Kaplan–Meier method and Cox proportional hazards models revealed that high levels of MS4As can be associated with a poorer prognosis; TMEM176A, TMEM176B, age, WHO grade, and IDH status were identified as independent prognostic factors. Enrichment analysis predicted that MS4As were related to tumor-related pathways and immune response, which might regulate the process of MS4As promoting tumorigenesis. Additionally, we analyzed the correlations of MS4A expression with immune cells and immune inhibitory molecules. Finally, data from the cell culture suggested that knockdown of the TMEM176B gene contributes to the decreased proliferation and migration of glioma cells. In conclusion, MS4A4A, MS4A4E, MS4A6A, MS4A7, TMEM176A, and TMEM176B may act as potential diagnostic or prognostic biomarkers in glioma and play a role in forming the immune microenvironment in gliomas.

Overarching roles of diacylglycerol signaling in cancer development and antitumor immunity

Diacylglycerol (DAG) is a lipid second messenger that is generated in response to extracellular stimuli and channels intracellular signals that affect mammalian cell proliferation, survival, and motility. DAG exerts a myriad of biological functions through protein kinase C (PKC) and other effectors, such as protein kinase D (PKD) isozymes and small GTPase-regulating proteins (such as RasGRPs). Imbalances in the fine-tuned homeostasis between DAG generation by phospholipase C (PLC) enzymes and termination by DAG kinases (DGKs), as well as dysregulation in the activity or abundance of DAG effectors, have been widely associated with tumor initiation, progression, and metastasis. DAG is also a key orchestrator of T cell function and thus plays a major role in tumor immunosurveillance. In addition, DAG pathways shape the tumor ecosystem by arbitrating the complex, dynamic interaction between cancer cells and the immune landscape, hence representing powerful modifiers of immune checkpoint and adoptive T cell-directed immunotherapy. Exploiting the wide spectrum of DAG signals from an integrated perspective could underscore meaningful advances in targeted cancer therapy.

Bioinformatics analysis of the prognostic value of NEK8 and its effects on immune cell infiltration in glioma

Glioma is the most common malignancy of the nervous system with high rates of recurrence and mortality, even after surgery. The 5‐year survival rate is only about 5%. NEK8 is involved in multiple biological processes in a variety of cancers; however, its role in glioma is still not clear. In the current study, we evaluated the prognostic value of NEK8, as well as its role in the pathogenesis of glioma. Using a bioinformatics approach and RNA‐seq data from public databases, we found that NEK8 expression is elevated in glioma tissues; we further verified this result by RT‐PCR, Western blotting and immunochemistry using clinical samples. Functional enrichment analyses of genes with correlated expression indicated that elevated NEK8 expression is associated with increased immune cell infiltration in glioma and may affect the tumour microenvironment via the regulation of DNA damage/repair. Survival analyses revealed that high levels of NEK8 are associated with a poorer prognosis; higher WHO grade, IDH status, 1p/19q codeletion, age and NEK8 were identified as an independent prognostic factor. These findings support the crucial role of NEK8 in the progression of glioma via effects on immune cell infiltration and suggest that it is a new prognostic biomarker.

Demographic History and Genomic Response to Environmental Changes in a Rapid Radiation of Wild Rats

For organisms to survive and prosper in a harsh environment, particularly under rapid climate change, poses tremendous challenges. Recent studies have highlighted the continued loss of megafauna in terrestrial ecosystems and the subsequent surge of small mammals, such as rodents, bats, lagomorphs, and insectivores. However, the ecological partitioning of these animals will likely lead to large variation in their responses to environmental change. In the present study, we investigated the evolutionary history and genetic adaptations of white-bellied rats (Niviventer Marshall, 1976), which are widespread in the natural terrestrial ecosystems in Asia but also known as important zoonotic pathogen vectors and transmitters. The southeastern Qinghai-Tibet Plateau was inferred as the origin center of this genus, with parallel diversification in temperate and tropical niches. Demographic history analyses from mitochondrial and nuclear sequences of Niviventer demonstrated population size increases and range expansion for species in Southeast Asia, and habitat generalists elsewhere. Unexpectedly, population increases were seen in N. eha, which inhabits the highest elevation among Niviventer species. Genome scans of nuclear exons revealed that among the congeneric species, N. eha has the largest number of positively selected genes. Protein functions of these genes are mainly related to olfaction, taste, and tumor suppression. Extensive genetic modification presents a major strategy in response to global changes in these alpine species.

Integrative Pan-Cancer Analysis Reveals Decreased Melatonergic Gene Expression in Carcinogenesis and RORA as a Prognostic Marker for Hepatocellular Carcinoma

Background

Melatonin has been shown to play a protective role in the development and progression of cancer. However, the relationship between alterations in the melatonergic microenvironment and cancer development has remained unclear.

Methods

We performed a comprehensive investigation on 12 melatonergic genes and their relevance to cancer occurrence, progression and survival by integrating multi-omics data from microarray analysis and RNA sequencing across 11 cancer types. Specifically, the 12 melatonergic genes that we investigated, which reflect the melatonergic microenvironment, included three membrane receptor genes, three nuclear receptor genes, two intracellular receptor genes, one synthetic gene, and three metabolic genes.

Results

Widely coherent underexpression of nuclear receptor genes, intracellular receptor genes, and metabolic genes was observed in cancerous samples from multiple cancer types compared to that in normal samples. Furthermore, genomic and/or epigenetic alterations partially contributed to these abnormal expression patterns in cancerous samples. Moreover, the majority of melatonergic genes had significant prognostic effects in predicting overall survival. Nevertheless, few corresponding alterations in expression were observed during cancer progression, and alterations in expression patterns varied greatly across cancer types. However, the association of melatonergic genes with one specific cancer type, hepatocellular carcinoma, identified RORA as a tumor suppressor and a prognostic marker for patients with hepatocellular carcinoma.

Conclusions

Overall, our study revealed decreased melatonergic gene expression in various cancers, which may help to better elucidate the relationship between melatonin and cancer development. Taken together, our findings highlight the potential prognostic significance of melatonergic genes in various cancers.

Subcellular Localization Relevance and Cancer-Associated Mechanisms of Diacylglycerol Kinases

An increasing number of reports suggests a significant involvement of the phosphoinositide (PI) cycle in cancer development and progression. Diacylglycerol kinases (DGKs) are very active in the PI cycle. They are a family of ten members that convert diacylglycerol (DAG) into phosphatidic acid (PA), two-second messengers with versatile cellular functions. Notably, some DGK isoforms, such as DGKα, have been reported to possess promising therapeutic potential in cancer therapy. However, further studies are needed in order to better comprehend their involvement in cancer. In this review, we highlight that DGKs are an essential component of the PI cycle that localize within several subcellular compartments, including the nucleus and plasma membrane, together with their PI substrates and that they are involved in mediating major cancer cell mechanisms such as growth and metastasis. DGKs control cancer cell survival, proliferation, and angiogenesis by regulating Akt/mTOR and MAPK/ERK pathways. In addition, some DGKs control cancer cell migration by regulating the activities of the Rho GTPases Rac1 and RhoA.

Specificity of Acyl Chain Composition of Phosphatidylinositols

Phosphatidylinositol (PI) lipids have a predominance of a single molecular species present through the organism. In healthy mammals this molecular species is 1-stearoyl-2-arachidonoyl (18:0/20:4) PI. Although the importance of PI lipids for cell physiology has long been appreciated, less is known about the biological role of enriching PI lipids with 18:0/20:4 acyl chains. In conditions with dysfunctional lipid metabolism, the predominance of 18:0/20:4 acyl chains is lost. Recently, molecular mechanisms underpinning the enrichment or alteration of these acyl chains in PI lipids have begun to emerge. In the majority of the cases a common feature is the presence of enzymes bearing substrate acyl chain specificity. However, in cancer cells, it has been shown that one (not the only) of the mechanisms responsible for the loss in this acyl chain enrichment is mutation on the transcription factor p53 gene, which is one of the most highly mutated genes in cancers. There is a compelling need for a global picture of the specificity of the acyl chain composition of PIs. This can be possible once high-resolution spatio-temporal information is gathered in a cellular context; which can ultimately lead to potential novel targets to combat conditions with altered PI acyl chain profiles.

Role of PI3K/AKT pathway in cancer: the framework of malignant behavior

Given that the PI3K/AKT pathway has manifested its compelling influence on multiple cellular process, we further review the roles of hyperactivation of PI3K/AKT pathway in various human cancers. We state the abnormalities of PI3K/AKT pathway in different cancers, which are closely related with tumorigenesis, proliferation, growth, apoptosis, invasion, metastasis, epithelial-mesenchymal transition, stem-like phenotype, immune microenvironment and drug resistance of cancer cells. In addition, we investigated the current clinical trials of inhibitors against PI3K/AKT pathway in cancers and found that the clinical efficacy of these inhibitors as monotherapy has so far been limited despite of the promising preclinical activity, which means combinations of targeted therapy may achieve better efficacies in cancers. In short, we hope to feature PI3K/AKT pathway in cancers to the clinic and bring the new promising to patients for targeted therapies.

The Landscape of Atypical and Eukaryotic Protein Kinases

Kinases are attractive anticancer targets due to their central role in the growth, survival, and therapy resistance of tumor cells. This review explores the two primary kinase classes, the eukaryotic protein kinases (ePKs) and the atypical protein kinases (aPKs), and provides a structure-centered comparison of their sequences, structures, hydrophobic spines, mutation and SNP hotspots, and inhibitor interaction patterns. Despite the limited sequence similarity between these two classes, atypical kinases commonly share the archetypical kinase fold but lack conserved eukaryotic kinase motifs and possess altered hydrophobic spines. Furthermore, atypical kinase inhibitors explore only a limited number of binding modes both inside and outside the orthosteric binding site. The distribution of genetic variations in both classes shows multiple ways they can interfere with kinase inhibitor binding. This multilayered review provides a research framework bridging the eukaryotic and atypical kinase classes.

3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in "patches" which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways that are revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between the groups and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the possible therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine.

Multi-Omics Characterization of the Spontaneous Mesenchymal-Epithelial Transition in the PMC42 Breast Cancer Cell Lines

Epithelial-mesenchymal plasticity (EMP), encompassing epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET), are considered critical events for cancer metastasis. We investigated chromosomal heterogeneity and chromosomal instability (CIN) profiles of two sister PMC42 breast cancer (BC) cell lines to assess the relationship between their karyotypes and EMP phenotypic plasticity. Karyotyping by GTG banding and exome sequencing were aligned with SWATH quantitative proteomics and existing RNA-sequencing data from the two PMC42 cell lines; the mesenchymal, parental PMC42-ET cell line and the spontaneously epithelially shifted PMC42-LA daughter cell line. These morphologically distinct PMC42 cell lines were also compared with five other BC cell lines (MDA-MB-231, SUM-159, T47D, MCF-7 and MDA-MB-468) for their expression of EMP and cell surface markers, and stemness and metabolic profiles. The findings suggest that the epithelially shifted cell line has a significantly altered ploidy of chromosomes 3 and 13, which is reflected in their transcriptomic and proteomic expression profiles. Loss of the TGFβR2 gene from chromosome 3 in the epithelial daughter cell line inhibits its EMT induction by TGF-β stimulus. Thus, integrative 'omics' characterization established that the PMC42 system is a relevant MET model and provides insights into the regulation of phenotypic plasticity in breast cancer.

Integrative genomic analysis of mouse and human hepatocellular carcinoma

Cancer genomics has enabled the exhaustive molecular characterization of tumors and exposed hepatocellular carcinoma (HCC) as among the most complex cancers. This complexity is paralleled by dozens of mouse models that generate histologically similar tumors but have not been systematically validated at the molecular level. Accurate models of the molecular pathogenesis of HCC are essential for biomedical progress; therefore we compared genomic and transcriptomic profiles of four separate mouse models [MUP transgenic, TAK1-knockout, carcinogen-driven diethylnitrosamine (DEN), and Stelic Animal Model (STAM)] with those of 987 HCC patients with distinct etiologies. These four models differed substantially in their mutational load, mutational signatures, affected genes and pathways, and transcriptomes. STAM tumors were most molecularly similar to human HCC, with frequent mutations in Ctnnb1, similar pathway alterations, and high transcriptomic similarity to high-grade, proliferative human tumors with poor prognosis. In contrast, TAK1 tumors better reflected the mutational signature of human HCC and were transcriptionally similar to low-grade human tumors. DEN tumors were least similar to human disease and almost universally carried the Braf V637E mutation, which is rarely found in human HCC. Immune analysis revealed that strain-specific MHC-I genotype can influence the molecular makeup of murine tumors. Thus, different mouse models of HCC recapitulate distinct aspects of HCC biology, and their use should be adapted to specific questions based on the molecular features provided here.

Cytidine monophosphate N-acetylneuraminic acid synthetase enhances invasion of human triple-negative breast cancer cells

Background

Cancer cells have altered bioenergetics, which contributes to their ability to proliferate, survive in unusual microenvironments, and invade other tissues. Changes in glucose metabolism can have pleomorphic effects on tumor cells.

Methods

To investigate potential mechanisms responsible for the increased malignancy associated with altered glucose metabolism, we used an unbiased nuclear magnetic resonance spectroscopy screening method to identify glucose metabolites differentially produced in a highly malignant human triple-negative breast cancer (TNBC) cell line (BPLER) and a less malignant isogenic TNBC cell line (HMLER).

Results

N-acetylneuraminic acid (Neu5Ac), the predominant sialic acid derivative in mammalian cells, which forms the terminal sugar on mucinous cell surface glycoproteins, was the major glucose metabolite that differed. Neu5Ac was ~7-fold more abundant in BPLER than HMLER. Loss of Neu5Ac by enzymatic removal or siRNA knockdown of cytidine monophosphate N-acetylneuraminic acid synthetase (CMAS), which activates cellular sialic acids for glycoprotein conjugation, had no significant effect on cell proliferation, but decreased the ability of BPLER to invade through a basement membrane. Conversely, overexpressing CMAS in HMLER increased invasivity. TNBCs in The Cancer Genome Atlas also had significantly more CMAS copy number variations and higher mRNA expression than non-TNBC, which have a better prognosis. CMAS knockdown in BPLER ex vivo blocked xenograft formation in mice.

Conclusion

Neu5Ac is selectively highly enriched in aggressive TNBC, and CMAS, the enzyme required for sialylation, may play an important role in TNBC tumor formation and invasivity.

Pentose conversions support the tumorigenesis of pancreatic cancer distant metastases

Pancreatic ductal adenocarcinoma (PDAC) adopts several unique metabolic strategies to support primary tumor growth. Whether additional metabolic strategies are adopted to support metastatic tumorigenesis is less clear. This could be particularly relevant for distant metastasis, which often follows a rapidly progressive clinical course. Here we report that PDAC distant metastases evolve a unique series of metabolic reactions to maintain activation of the anabolic glucose enzyme phosphogluconate dehydrogenase (PGD). PGD catalytic activity was recurrently elevated across distant metastases, and modulating PGD activity levels dictated tumorigenic capacity. Metabolomics data raised the possibility that distant metastases evolved a core pentose conversion pathway (PCP) that converted glucose-derived metabolites into PGD substrate, thereby hyperactivating the enzyme. Consistent with this, each individual metabolite in the PCP stimulated PGD catalysis in distant metastases, and knockdown of each individual PCP enzyme selectively impaired tumorigenesis. We propose that the PCP manufactures PGD substrate outside of the rate-limiting oxidative pentose phosphate pathway (oxPPP). This enables PGD-dependent tumorigenesis by providing adequate substrate to fuel high catalytic activity, and raises the possibility that PDAC distant metastases adopt their own unique metabolic strategies to support tumor growth.

Whole-exome sequencing identified mutational profiles of high-grade colon adenomas

Although gene-to-gene analyses identified genetic alterations such as APC, KRAS and TP53 mutations in colon adenomas, it is largely unknown whether there are any others in them. Mutational profiling of high-grade colon adenoma (HGCA) that just precedes colon carcinoma might identify not only novel adenoma-specific genes but also critical genes for its progression to carcinoma. For this, we performed whole-exome sequencing (WES) of 12 HGCAs and identified 11 non-hypermutated and one hypermutated (POLE-mutated) cases. We identified 22 genes including APC, KRAS, TP53, GNAS, NRAS, SMAD4, ARID2, and PIK3CA with non-silent mutations in the cancer Census Genes. Bi-allelic and mono-allelic APC alterations were found in nine and one HGCAs, respectively, while the other two harbored wild-type APC. Five HGCAs harbored either mono-allelic (four HGCAs) or bi-allelic (one HGCA) SMAD4 mutation or 18q loss that had been known as early carcinoma-specific changes. We identified MTOR, ACVR1B, GNAQ, ATM, CNOT1, EP300, ARID2, RET and MAP2K4 mutations for the first time in colon adenomas. Our WES data is largely matched with the earlier 'adenoma-carcinoma model' (APC, KRAS, NRAS and GNAS mutations), but there are newly identified SMAD4, MTOR, ACVR1B, GNAQ, ATM, CNOT1, EP300, ARID2, RET and MAP2K4 mutations in this study. Our findings provide resource for understanding colon premalignant lesions and for identifying genomic clues for differential diagnosis and therapy options for colon adenomas and carcinomas.

Mutational burdens and evolutionary ages of thyroid follicular adenoma are comparable to those of follicular carcinoma

Follicular thyroid adenoma (FTA) precedes follicular thyroid carcinoma (FTC) by definition with a favorable prognosis compared to FTC. However, the genetic mechanism of FTA to FTC progression remains unknown. For this, it is required to disclose FTA and FTC genomes in mutational and evolutionary perspectives. We performed whole-exome sequencing and copy number profiling of 14 FTAs and 13 FTCs, which exhibited previously-known gene mutations (NRAS, HRAS, BRAF, TSHR and EIF1AX) and copy number alterations (CNAs) (22q loss and 1q gain) in follicular tumors. In addition, we found eleven potential cancer-related genes with mutations (EZH1, SPOP, NF1, TCF12, IGF2BP3, KMT2C, CNOT1, BRIP1, KDM5C, STAG2 and MAP4K3) that have not been reported in thyroid follicular tumors. Of note, FTA genomes showed comparable levels of mutations to FTC in terms of the number, sequence composition and functional consequences (potential driver mutations) of mutations. Analyses of evolutionary ages using somatic mutations as molecular clocks further identified that FTA genomes were as old as FTC genomes. Whole-transcriptome sequencing did not find any gene fusions with potential significance. Our data indicate that FTA genomes may be as old as FTC genomes, thus suggesting that follicular thyroid tumor genomes during the transition from FTA to FTC may stand stable at genomic levels in contrast to the discernable changes at pathologic and clinical levels. Also, the data suggest a possibility that the mutational profiles obtained from early biopsies may be useful for the molecular diagnosis and therapeutics of follicular tumor patients.

Targeted sequencing-based analyses of candidate gene variants in ulcerative colitis-associated colorectal neoplasia

BACKGROUND

Long-standing ulcerative colitis (UC) leading to colorectal cancer (CRC) is one of the most serious and life-threatening consequences acknowledged globally. Ulcerative colitis-associated colorectal carcinogenesis showed distinct molecular alterations when compared with sporadic colorectal carcinoma.

METHODS

Targeted sequencing of 409 genes in tissue samples of 18 long-standing UC subjects at high risk of colorectal carcinoma (UCHR) was performed to identify somatic driver mutations, which may be involved in the molecular changes during the transformation of non-dysplastic mucosa to high-grade dysplasia. Findings from the study are also compared with previously published genome wide and exome sequencing data in inflammatory bowel disease-associated and sporadic colorectal carcinoma.

RESULTS

Next-generation sequencing analysis identified 1107 mutations in 275 genes in UCHR subjects. In addition to TP53 (17%) and KRAS (22%) mutations, recurrent mutations in APC (33%), ACVR2A (61%), ARID1A (44%), RAF1 (39%) and MTOR (61%) were observed in UCHR subjects. In addition, APC, FGFR3, FGFR2 and PIK3CA driver mutations were identified in UCHR subjects. Recurrent mutations in ARID1A (44%), SMARCA4 (17%), MLL2 (44%), MLL3 (67%), SETD2 (17%) and TET2 (50%) genes involved in histone modification and chromatin remodelling were identified in UCHR subjects.

CONCLUSIONS

Our study identifies new oncogenic driver mutations which may be involved in the transition of non-dysplastic cells to dysplastic phenotype in the subjects with long-standing UC with high risk of progression into colorectal neoplasia.

PLMET: A Novel Pseudolikelihood-Based EM Test for Homogeneity in Generalilzed Exponential Tilt Mixture Models

Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model, to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the differences in higher order moments (e.g. mean and variance) between subjects in cancer and normal groups. A pairwise pseudolikelihood is constructed to eliminate the unknown nuisance function. To circumvent boundary and non-identifiability problems as in parametric mixture models, we modify the pseudolikelihood by adding a penalty function. In addition, the test with simple asymptotic distribution has computational advantages compared with permutation-based test for high-dimensional genetic or epigenetic data. We propose a pseudolikelihood based expectation-maximization test, and show the proposed test follows a simple chi-squared limiting distribution. Simulation studies show that the proposed test controls Type I errors well and has better power compared to several current tests. In particular, the proposed test outperforms the commonly used tests under all simulation settings considered, especially when there are variance differences between two groups. The proposed test is applied to a real data set to identify differentially methylated sites between ovarian cancer subjects and normal subjects.

Modulated DISP3/PTCHD2 expression influences neural stem cell fate decisions

Neural stem cells (NSCs) are defined by their dual ability to self-renew through mitotic cell division or differentiate into the varied neural cell types of the CNS. DISP3/PTCHD2 is a sterol-sensing domain-containing protein, highly expressed in neural tissues, whose expression is regulated by thyroid hormone. In the present study, we used a mouse NSC line to investigate what effect DISP3 may have on the self-renewal and/or differentiation potential of the cells. We demonstrated that NSC differentiation triggered significant reduction in DISP3 expression in the resulting astrocytes, neurons and oligodendrocytes. Moreover, when DISP3 expression was disrupted, the NSC "stemness" was suppressed, leading to a larger population of cells undergoing spontaneous neuronal differentiation. Conversely, overexpression of DISP3 resulted in increased NSC proliferation. When NSCs were cultured under differentiation conditions, we observed that the lack of DISP3 augmented the number of NSCs differentiating into each of the neural cell lineages and that neuronal morphology was altered. In contrast, DISP3 overexpression resulted in impaired cell differentiation. Taken together, our findings imply that DISP3 may help dictate the NSC cell fate to either undergo self-renewal or switch to the terminal differentiation cell program.

Diacylglycerol kinases in cancer

Diacylglycerol kinases (DGK) are a family of enzymes that catalyze the transformation of diacylglycerol into phosphatidic acid. In T lymphocytes, DGKα and ζ limit the activation of the PLCγ/Ras/ERK axis, providing a critical checkpoint to inhibit T cell responses. Upregulation of these isoforms limits Ras activation, leading to hypo-responsive, anergic states similar to those caused by tumors. Recent studies have identified DGKα upregulation in tumor lymphocyte infiltrates, and cells from DGKα and ζ deficient mice show enhanced antitumor activity, suggesting that limitation of DAG based signals by DGK is used by tumors to evade immune attack. DGKα expression is low or even absent in other healthy cells like melanocytes, hepatocytes or neurons. Expression of this isoform, nevertheless is upregulated in melanoma, hepatocarcinoma and glioblastoma where DGKα contributes to the acquisition of tumor metastatic traits. A model thus emerges where tumor milieu fosters DGKα expression in tumors as well as in tumor infiltrating lymphocytes with opposite consequences. Here we review the mechanisms and targets that facilitate tumor "addiction" to DGKα, and discuss its relevance in the more advanced forms of cancer for tumor immune evasion. A better knowledge of this function offers a new perspective in the search of novel approaches to prevent inhibition of immune attack in cancer. Part of the failure in clinical progress may be attributed to the complexity of the tumor/T lymphocyte interaction. As they develop, tumors use a number of mechanisms to drive endogenous, tumor reactive T cells to a general state of hyporesponsiveness or anergy. A better knowledge of the molecular mechanisms that tumors use to trigger T cell anergic states will greatly help in the advance of immunotherapy research.

iCAGES: integrated CAncer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes

Cancer results from the acquisition of somatic driver mutations. Several computational tools can predict driver genes from population-scale genomic data, but tools for analyzing personal cancer genomes are underdeveloped. Here we developed iCAGES, a novel statistical framework that infers driver variants by integrating contributions from coding, non-coding, and structural variants, identifies driver genes by combining genomic information and prior biological knowledge, then generates prioritized drug treatment. Analysis on The Cancer Genome Atlas (TCGA) data showed that iCAGES predicts whether patients respond to drug treatment (P = 0.006 by Fisher's exact test) and long-term survival (P = 0.003 from Cox regression). iCAGES is available at http://icages.wglab.org .

A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Whole Exome Sequencing (WES) is the application of the next-generation technology to determine the variations in the exome and is becoming a standard approach in studying genetic variants in diseases. Understanding the exomes of individuals at single base resolution allows the identification of actionable mutations for disease treatment and management. WES technologies have shifted the bottleneck in experimental data production to computationally intensive informatics-based data analysis. Novel computational tools and methods have been developed to analyze and interpret WES data. Here, we review some of the current tools that are being used to analyze WES data. These tools range from the alignment of raw sequencing reads all the way to linking variants to actionable therapeutics. Strengths and weaknesses of each tool are discussed for the purpose of helping researchers make more informative decisions on selecting the best tools to analyze their WES data.

NEK8 regulates DNA damage-induced RAD51 foci formation and replication fork protection

Proteins essential for homologous recombination play a pivotal role in the repair of DNA double strand breaks, DNA inter-strand crosslinks and replication fork stability. Defects in homologous recombination also play a critical role in the development of cancer and the sensitivity of these cancers to chemotherapy. RAD51, an essential factor for homologous recombination and replication fork protection, accumulates and forms immunocytochemically detectable nuclear foci at sites of DNA damage. To identify kinases that may regulate RAD51 localization to sites of DNA damage, we performed a human kinome siRNA library screen, using DNA damage-induced RAD51 foci formation as readout. We found that NEK8, a NIMA family kinase member, is required for efficient DNA damage-induced RAD51 foci formation. Interestingly, knockout of Nek8 in murine embryonic fibroblasts led to cellular sensitivity to the replication inhibitor, hydroxyurea, and inhibition of the ATR kinase. Furthermore, NEK8 was required for proper replication fork protection following replication stall with hydroxyurea. Loading of RAD51 to chromatin was decreased in NEK8-depleted cells and Nek8-knockout cells. Single-molecule DNA fiber analyses revealed that nascent DNA tracts were degraded in the absence of NEK8 following treatment with hydroxyurea. Consistent with this, Nek8-knockout cells showed increased chromosome breaks following treatment with hydroxyurea. Thus, NEK8 plays a critical role in replication fork stability through its regulation of the DNA repair and replication fork protection protein RAD51.

Genomic landscape of endometrial stromal sarcoma of uterus

Although recurrent gene fusions such as JAZF1-JJAZ1 are considered driver events for endometrial stromal sarcoma (ESS) development, other genomic alterations remain largely unknown. In this study, we performed whole-exome sequencing, transcriptome sequencing and copy number profiling for five ESSs (three low-grade ESS (LG-ESS) and two undifferentiated uterine sarcomas (UUSs)). All three LG-ESSs exhibited either one of JAZF1-SUZ12, JAZF1-PHF1 and MEAF6-PHF1 fusions, whereas the two UUSs did not. All ESSs except one LG-ESS exhibited copy number alterations (CNAs), many of which encompassed cancer-related genes. In UUSs, five CNAs encompassing cancer-related genes (EZR, CDH1, RB1, TP53 and PRKAR1A) accompanied their expressional changes, suggesting that they might stimulate UUS development. We found 81 non-silent mutations (35 from LG-ESSs and 46 from UUSs) that included 15 putative cancer genes catalogued in cancer-related databases, including PPARG and IRF4 mutations. However, they were non-recurrent and did not include any well-known mutations, indicating that point mutations may not be a major driver for ESS development. Our data show that gene fusions and CNAs are the principal drivers for LG-ESS and USS, respectively, but both may require additional genomic alterations including point mutations. These differences may explain the different biologic behaviors between LG-ESS and UUS. Our findings suggest that ESS development requires point mutations and CNAs as well as the gene fusions.

Protein-structure-guided discovery of functional mutations across 19 cancer types

Local concentrations of mutations are well known in human cancers. However, their three-dimensional spatial relationships in the encoded protein have yet to be systematically explored. We developed a computational tool, HotSpot3D, to identify such spatial hotspots (clusters) and to interpret the potential function of variants within them. We applied HotSpot3D to >4,400 TCGA tumors across 19 cancer types, discovering >6,000 intra- and intermolecular clusters, some of which showed tumor and/or tissue specificity. In addition, we identified 369 rare mutations in genes including TP53, PTEN, VHL, EGFR, and FBXW7 and 99 medium-recurrence mutations in genes such as RUNX1, MTOR, CA3, PI3, and PTPN11, all mapping within clusters having potential functional implications. As a proof of concept, we validated our predictions in EGFR using high-throughput phosphorylation data and cell-line-based experimental evaluation. Finally, mutation-drug cluster and network analysis predicted over 800 promising candidates for druggable mutations, raising new possibilities for designing personalized treatments for patients carrying specific mutations.

STK33 potentiates the malignancy of hypopharyngeal squamous carcinoma: Possible relation to calcium

BACKGROUND

The present study aims to further explore the role of STK33 in hypopharyngeal squamous cell carcinoma (HSCC), with special attention given to the possible relationship between STK33 alteration and calcium.

METHODS

An in vivo experiment and microarray analysis were performed to investigate the impact of STK33 knockdown (STK33-RNAi) on the biological behaviors and the gene profile alterations of a HSCC cell line (Fadu). Cell viability and morphological change of Fadu cells in response to Ionomycin were measured by MTT assay and acridine orange staining. The concentration of intracellular calcium ([Ca(2+)]i) was detected by laser scanning confocal microscope with fluo-3/AM. The mRNA and protein expressions of relevant genes were examined by real-time PCR and Western blot.

RESULTS

STK33-RNAi retarded the Fadu cell proliferation and the metastasis in nude mice and led to up- and down-regulation of the expressions of abundance of genes, especially, the downregulation of the CAPN1 gene. Ionomycin increased the [Ca(2+)]i and decreased the survival rates of Fadu cells in a time-dependent manner. Moreover, Ionomycin resulted in the elevation of CAPN1 mRNA expression in normal Fadu cells and, conversely, had almost no effect on CAPN1 expression in STK33-RNAi cells.

CONCLUSIONS

Findings from this work further validate that STK33 is a potential oncogene and plays an important role in tumorigenesis of HSCC via regulation of numerous genes. In addition, there exists the reciprocal influence between STK33 and [Ca(2+)]i in Fadu cells.

COMMD7 functions as molecular target in pancreatic ductal adenocarcinoma

Our previous studies provided evidence that COMMD7 was associated with tumor progression in human solid cancer. Herein, we aimed to investigate its expression pattern, clinical significance, and biological function in pancreatic ductal adenocarcinoma (PDAC). We found that high COMMD7 expression was specifically detected in PDAC tissues and PDAC cell lines. In addition, COMMD7 overexpression positively correlated with histological differentiation and tumor node metastasis (TNM) stage. Patients with high COMMD7 expression had significantly poorer overall survival, and high COMMD7 expression was an independent predictor of poor prognosis. To further explore the regulatory mechanism of COMMD7, we used stable short hairpin RNA (shRNA)-mediated knockdown and divided the work into in vitro and in vivo experiments. In vitro, the anti-proliferation effects of COMMD7 inhibition were observed under long-time stress conditions, which correlated with cyclin D1 and Bcl-2 downregulation and Bax upregulation. We found that under short-time stress conditions, decreased COMMD7 expression also inhibited PDAC cell invasion in vitro which decreased the secretion of matrix metalloproteinase 2 (MMP-2). Moreover, extracellular signal-regulated kinase1/2 (ERK1/2) was identified as a direct target of COMMD7. The inhibition of ERK1/2 activity under short- or long-time stress conditions using specific inhibitors in COMMD7 inhibition cells all exhibited a strong tumorigenic role. In vivo, COMMD7 was sufficient to impair tumor growth. Our results suggest that COMMD7 plays an important role in the late progression of PDAC and is a potential novel target. © 2016 Wiley Periodicals, Inc.

Progression of naive intraepithelial neoplasia genome to aggressive squamous cell carcinoma genome of uterine cervix

Although cervical intraepithelial neoplasia (CIN) is considered a neoplasia, its genomic alterations remain unknown. For this, we performed whole-exome sequencing and copy number profiling of three CINs, a microinvasive carcinoma (MIC) and four cervical squamous cell carcinomas (CSCC). Both total mutation and driver mutation numbers of the CINs were significantly fewer than those of the MIC/CSCCs (P = 0.036 and P = 0.018, respectively). Importantly, PIK3CA was altered in all MIC/CSCCs by either mutation or amplification, but not in CINs. The CINs harbored significantly lower numbers of copy number alterations (CNAs) than the MIC/CSCCs as well (P = 0.036). Pathway analysis predicted that the MIC/CSCCs were enriched with cancer-related signalings such as cell adhesion, mTOR signaling pathway and cell migration that were depleted in the CINs. The mutation-based estimation of evolutionary ages identified that CIN genomes were younger than MIC/CSCC genomes. The data indicate that CIN genomes harbor unfixed mutations in addition to human papilloma virus infection but require additional driver hits such as PIK3CA, TP53, STK11 and MAPK1 mutations for CSCC progression. Taken together, our data may explain the long latency from CIN to CSCC progression and provide useful information for molecular diagnosis of CIN and CSCC.

Concurrent Mutations in ATM and Genes Associated with Common γ Chain Signaling in Peripheral T Cell Lymphoma

Peripheral T cell lymphoma (PTCL) is a heterogeneous malignancy with poor response to current therapeutic strategies and incompletely characterized genetics. We conducted whole exome sequencing of matched PTCL and non-malignant samples from 12 patients, spanning 8 subtypes, to identify potential oncogenic mutations in PTCL. Analysis of the mutations identified using computational algorithms, CHASM, PolyPhen2, PROVEAN, and MutationAssessor to predict the impact of these mutations on protein function and PTCL tumorigenesis, revealed 104 somatic mutations that were selected as high impact by all four algorithms. Our analysis identified recurrent somatic missense or nonsense mutations in 70 genes, 9 of which contained mutations predicted significant by all 4 algorithms: ATM, RUNX1T1, WDR17, NTRK3, TP53, TRMT12, CACNA2D1, INTS8, and KCNH8. We observed somatic mutations in ATM (ataxia telangiectasia-mutated) in 5 out of the 12 samples and mutations in the common gamma chain (γc) signaling pathway (JAK3, IL2RG, STAT5B) in 3 samples, all of which also harbored mutations in ATM. Our findings contribute insights into the genetics of PTCL and suggest a relationship between γc signaling and ATM in T cell malignancy.

The serine/threonine kinase 33 is present and expressed in palaeognath birds but has become a unitary pseudogene in neognaths about 100 million years ago

Background

Serine/threonine kinase 33 (STK33) has been shown to be conserved across all major vertebrate classes including reptiles, mammals, amphibians and fish, suggesting its importance within vertebrates. It has been shown to phosphorylate vimentin and might play a role in spermatogenesis and organ ontogenesis. In this study we analyzed the genomic locus and expression of stk33 in the class Aves, using a combination of large scale next generation sequencing data analysis and traditional PCR.

Results

Within the subclass Palaeognathae we analyzed the white-throated tinamou (Tinamus guttatus), the African ostrich (Struthio camelus) and the emu (Dromaius novaehollandiae). For the African ostrich we were able to generate a 62,778 bp long genomic contig and an mRNA sequence that encodes a protein showing highly significant similarity to STK33 proteins from other vertebrates. The emu has been shown to encode and transcribe a functional STK33 as well. For the white-throated tinamou we were able to identify 13 exons by sequence comparison encoding a protein similar to STK33 as well.

In contrast, in all 28 neognath birds analyzed, we could not find evidence for the existence of a functional copy of stk33 or its expression. In the genomes of these 28 bird species, we found only remnants of the stk33 locus carrying several large genomic deletions, leading to the loss of multiple exons. The remaining exons have acquired various indels and premature stop codons.

Conclusions

We were able to elucidate and describe the genomic structure and the transcription of a functional stk33 gene within the subclass Palaeognathae, but we could only find degenerate remnants of stk33 in all neognath birds analyzed. This led us to the conclusion that stk33 became a unitary pseudogene in the evolutionary history of the class Aves at the paleognath-neognath branch point during the late cretaceous period about 100 million years ago. We hypothesize that the pseudogenization of stk33 might have become fixed in neognaths due to either genetic redundancy or a non-orthologous gene displacement and present potential candidate genes for such an incident.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1769-9) contains supplementary material, which is available to authorized users.

Diacylglycerol kinase α promotes 3D cancer cell growth and limits drug sensitivity through functional interaction with Src

Diacylglycerol kinase (DGK)α converts diacylglycerol to phosphatidic acid. This lipid kinase sustains survival, migration and invasion of tumor cells, with no effect over untransformed cells, suggesting its potential as a cancer-specific target. Nonetheless the mechanisms that underlie DGKα specific contribution to cancer survival have not been elucidated. Using three-dimensional (3D) colon and breast cancer cell cultures, we demonstrate that DGKα upregulation is part of the transcriptional program that results in Src activation in these culture conditions. Pharmacological or genetic DGKα silencing impaired tumor growth in vivo confirming its function in malignant transformation. DGKα-mediated Src regulation contributed to limit the effect of Src inhibitors, and its transcriptional upregulation in response to PI3K/Akt inhibitors resulted in reduced toxicity. Src oncogenic properties and contribution to pharmacological resistance have been linked to its overactivation in cancer. DGKα participation in this central node helps to explain why its pharmacological inhibition or siRNA-mediated targeting specifically alters tumor viability with no effect on untransformed cells. Our results identify DGKα-mediated stabilization of Src activation as an important mechanism in tumor growth, and suggest that targeting this enzyme, alone or in combination with other inhibitors in wide clinical use, could constitute a treatment strategy for aggressive forms of cancer.

Genetics of familial melanoma: 20 years after CDKN2A

Twenty years ago, the first familial melanoma susceptibility gene, CDKN2A, was identified. Two years later, another high-penetrance gene, CDK4, was found to be responsible for melanoma development in some families. Progress in identifying new familial melanoma genes was subsequently slow; however, with the advent of next-generation sequencing, a small number of new high-penetrance genes have recently been uncovered. This approach has identified the lineage-specific oncogene MITF as a susceptibility gene both in melanoma families and in the general population, as well as the discovery of telomere maintenance as a key pathway underlying melanoma predisposition. Given these rapid recent advances, this approach seems likely to continue to pay dividends. Here, we review the currently known familial melanoma genes, providing evidence that most additionally confer risk to other cancers, indicating that they are likely general tumour suppressor genes or oncogenes, which has significant implications for surveillance and screening.

The Emerging Genetic Basis and Its Clinical Implication in Pancreatic Cancer

<b><i>Background:</i></b> Pancreatic cancer is one of the most devastating diseases without early detection, effective screening biomarkers and therapeutic treatments. In the past decades, genetic studies have indicated various genes related to this malignancy. <b><i>Summary:</i></b> Genetic alterations have been involved in the initiation, progression and invasion of pancreatic cancer, which might indicate promising targets for early screening, diagnosis and future intervention. Here we will review genetic changes in pancreatic cancer and analyze their correlations with several common precursors and familial syndromes. <b><i>Key Message:</i></b> Genetic analysis for pancreatic cancer or its precursors might help us to characterize patients into subtype individuals in the future and have significant implications for individualized treatments. <b><i>Practical Implications:</i></b> At present, pancreatic cancer is regarded as a disease with a wide range of genetic alterations, including germline and somatic mutations. Some genetic alterations such as <i>KRAS</i>, <i>p16</i>^{<i>CDKN2A</i>}, <i>TP53</i> and <i>SMAD4</i> were specifically correlated with different types of histological precursors of pancreatic cancer and some familial syndromes highly related to pancreatic cancer. Moreover, genetic changes also predict drug sensitivity and implicate novel therapeutic targets.

Deciphering oncogenic drivers: from single genes to integrated pathways

Technological advances in next-generation sequencing have uncovered a wide spectrum of aberrations in cancer genomes. The extreme diversity in cancer mutations necessitates computational approaches to differentiate between the 'drivers' with vital function in cancer progression and those nonfunctional 'passengers'. Although individual driver mutations are routinely identified, mutational profiles of different tumors are highly heterogeneous. There is growing consensus that pathways rather than single genes are the primary target of mutations. Here we review extant bioinformatics approaches to identifying oncogenic drivers at different mutational levels, highlighting the strategies for discovering driver pathways and networks from cancer mutation data. These approaches will help reduce the mutation complexity, thus providing a simplified picture of cancer.

Targeting p110gamma in gastrointestinal cancers: attack on multiple fronts

Phosphoinositide 3-kinases (PI3Ks) regulate several cellular functions that are critical for cancer progression and development, including cell survival, proliferation and migration. Three classes of PI3Ks exist with the class I PI3K encompassing four isoforms of the catalytic subunit known as p110α, p110β, p110γ, and p110δ. Although for many years attention has been mainly focused on p110α recent evidence supports the conclusion that p110β, p110γ, and p110δ can also have a role in cancer. Amongst these, accumulating evidence now indicates that p110γ is involved in several cellular processes associated with cancer and indeed this specific isoform has emerged as a novel important player in cancer progression. Studies from our laboratory have identified a specific overexpression of p110γ in human pancreatic ductal adenocarcinoma (PDAC) and in hepatocellular carcinoma (HCC) tissues compared to their normal counterparts. Our data have further established that selective inhibition of p110γ is able to block PDAC and HCC cell proliferation, strongly suggesting that pharmacological inhibition of this enzyme can directly affect growth of these tumors. Furthermore, increasing evidence suggests that p110γ plays also a key role in the interactions between cancer cells and tumor microenvironment and in particular in tumor-associated immune response. It has also been reported that p110γ can regulate invasion of myeloid cells into tumors and tumor angiogenesis. Finally p110γ has also been directly involved in regulation of cancer cell migration. Taken together these data indicate that p110γ plays multiple roles in regulation of several processes that are critical for tumor progression and metastasis. This review will discuss the role of p110γ in gastrointestinal tumor development and progression and how targeting this enzyme might represent a way to target very aggressive tumors such as pancreatic and liver cancer on multiple fronts.

Somatic aberrations of mismatch repair genes as a cause of microsatellite-unstable cancers

Lynch syndrome (LS) is caused by germline mutations in mismatch repair (MMR) genes, resulting in microsatellite-unstable tumours. Approximately 35% of suspected LS (sLS) patients test negative for germline MMR gene mutations, hampering conclusive LS diagnosis. The aim of this study was to investigate somatic MMR gene aberrations in microsatellite-unstable colorectal and endometrial cancers of sLS patients negative for germline MMR gene mutations. Suspected LS cases were selected from a retrospective Clinical Genetics Department diagnostic cohort and from a prospective multicentre population-based study on LS in The Netherlands. In total, microsatellite-unstable tumours of 40 sLS patients (male/female 20/20, median age 57 years) were screened for somatic MMR gene mutations by next-generation sequencing. In addition, loss of heterozygosity (LOH) of the affected MMR genes in these tumours as well as in 68 LS-associated tumours and 27 microsatellite-unstable tumours with MLH1 promoter hypermethylation was studied. Of the sLS cases, 5/40 (13%) tumours had two pathogenic somatic mutations and 16/40 (40%) tumours had a (likely) pathogenic mutation and LOH. Overall, LOH of the affected MMR gene locus was observed in 24/39 (62%) tumours with informative LOH markers. Of the LS cases and the tumours with MLH1 promoter hypermethylation, 39/61 (64%) and 2/21 (10%) tumours, respectively, demonstrated LOH. Half of microsatellite-unstable tumours of sLS patients without germline MMR gene mutations had two (likely) deleterious somatic MMR gene aberrations, indicating their sporadic origin. Therefore, we advocate adding somatic mutation and LOH analysis of the MMR genes to the molecular diagnostic workflow of LS.

Functional annotation of putative regulatory elements at cancer susceptibility Loci

Most cancer-associated genetic variants identified from genome-wide association studies (GWAS) do not obviously change protein structure, leading to the hypothesis that the associations are attributable to regulatory polymorphisms. Translating genetic associations into mechanistic insights can be facilitated by knowledge of the causal regulatory variant (or variants) responsible for the statistical signal. Experimental validation of candidate functional variants is onerous, making bioinformatic approaches necessary to prioritize candidates for laboratory analysis. Thus, a systematic approach for recognizing functional (and, therefore, likely causal) variants in noncoding regions is an important step toward interpreting cancer risk loci. This review provides a detailed introduction to current regulatory variant annotations, followed by an overview of how to leverage these resources to prioritize candidate functional polymorphisms in regulatory regions.

The genomic landscape of nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) has extremely skewed ethnic and geographic distributions, is poorly understood at the genetic level and is in need of effective therapeutic approaches. Here we determined the mutational landscape of 128 cases with NPC using whole-exome and targeted deep sequencing, as well as SNP array analysis. These approaches revealed a distinct mutational signature and nine significantly mutated genes, many of which have not been implicated previously in NPC. Notably, integrated analysis showed enrichment of genetic lesions affecting several important cellular processes and pathways, including chromatin modification, ERBB-PI3K signaling and autophagy machinery. Further functional studies suggested the biological relevance of these lesions to the NPC malignant phenotype. In addition, we uncovered a number of new druggable candidates because of their genomic alterations. Together our study provides a molecular basis for a comprehensive understanding of, and exploring new therapies for, NPC.

High risk of tobacco-related cancers in CDKN2A mutation-positive melanoma families

BACKGROUND

Germline mutations in the tumour suppressor gene CDKN2A occur in 5-20% of familial melanoma cases. A single founder mutation, p.Arg112dup, accounts for the majority of CDKN2A mutations in Swedish carriers. In a national program, carriers of p.Arg112dup mutation have been identified. The aim of this study was to assess cancer risks in p.Arg112dup carriers and their first degree relatives (FDRs) and second degree relatives (SDRs).

METHODS

In this prospective cohort study, cancer diagnoses in carriers (n=120), non-carriers (n=111), carriers' FDRs (n=275) and SDRs (n=321) and controls (n=3976) were obtained from the Swedish Cancer Registry. Relative risks (RRs) for cancers were calculated (number of cancers/person years). Two-sided 95% CIs were calculated for all RRs.

RESULTS

In carriers prospective RR for non-melanoma cancers was 5.0 (95% CI 3.7 to 7.3), for pancreatic cancer 43.8 (95% CI 13.8 to 139.0), for cancers in upper digestive tissues 17.1 (95% CI 6.3 to 46.5), and in respiratory tissues 15.6 (5.4 to 46.0). In FDRs and SDRs RRs were significantly elevated for cancers in pancreas, respiratory and upper digestive tissues. In ever-smoking carriers compared with never-smoking carriers, the odds ratio (OR) of cancers in pancreas, respiratory or upper digestive tissues was 9.3 (95% CI 1.9 to 44.7).

CONCLUSIONS

CDKN2A p.Arg112dup mutation carriers from melanoma-prone families and their FDRs and SDRs have elevated risk for pancreatic, lung, head and neck and gastro-oesophageal carcinomas. These cancers were mainly seen in ever-smoking carriers. Germline CDKN2A mutations may confer an increased sensitivity to carcinogens in tobacco smoke. CDKN2A mutation carriers should be counselled to abstain from smoking.

A graph theoretic approach to utilizing protein structure to identify non-random somatic mutations

Background

It is well known that the development of cancer is caused by the accumulation of somatic mutations within the genome. For oncogenes specifically, current research suggests that there is a small set of "driver" mutations that are primarily responsible for tumorigenesis. Further, due to recent pharmacological successes in treating these driver mutations and their resulting tumors, a variety of approaches have been developed to identify potential driver mutations using methods such as machine learning and mutational clustering. We propose a novel methodology that increases our power to identify mutational clusters by taking into account protein tertiary structure via a graph theoretical approach.

Results

We have designed and implemented GraphPAC (Graph Protein Amino acid Clustering) to identify mutational clustering while considering protein spatial structure. Using GraphPAC, we are able to detect novel clusters in proteins that are known to exhibit mutation clustering as well as identify clusters in proteins without evidence of prior clustering based on current methods. Specifically, by utilizing the spatial information available in the Protein Data Bank (PDB) along with the mutational data in the Catalogue of Somatic Mutations in Cancer (COSMIC), GraphPAC identifies new mutational clusters in well known oncogenes such as EGFR and KRAS. Further, by utilizing graph theory to account for the tertiary structure, GraphPAC discovers clusters in DPP4, NRP1 and other proteins not identified by existing methods. The R package is available at: http://bioconductor.org/packages/release/bioc/html/GraphPAC.html.

Conclusion

GraphPAC provides an alternative to iPAC and an extension to current methodology when identifying potential activating driver mutations by utilizing a graph theoretic approach when considering protein tertiary structure.

Predicting the functional consequences of somatic missense mutations found in tumors

Cancer-specific High-throughput Annotation of Somatic Mutations (CHASM) is a computational method that uses supervised machine learning to prioritize somatic missense mutations detected in tumor sequencing studies. Missense mutations are a key mechanism by which important cellular behaviors, such as cell growth, proliferation, and survival, are disrupted in cancer. However, only a fraction of the missense mutations observed in tumor genomes are expected to be cancer causing. Distinguishing tumorigenic "driver" mutations from their neutral "passenger" counterparts is currently a pressing problem in cancer research.CHASM trains a Random Forest classifier on driver mutations from the COSMIC databases and uses background nucleotide substitution rates observed in tumor sequencing data to model tumor type-specific passenger mutations. Each missense mutation is represented by quantitative features that fall into five major categories: physiochemical properties of amino acid residues; scores derived from multiple sequence alignments of protein or DNA; region-based amino acid sequence composition; predicted properties of local protein structure; and annotations from the UniProt feature tables. Both a software package and a Web server implementation of CHASM are available to facilitate high-throughput prioritization of somatic missense mutations from large, multi-tumor exome sequencing studies. After ranking candidate driver mutations with CHASM, the vector of features describing each mutation can be used to suggest possible mechanism by which mutations alter protein activity in tumorigenesis. This chapter details the application of both implementations of CHASM to tumor sequencing data.

Functional modules analysis based on coexpression network in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most common epithelial, exocrine pancreatic malignancy, accounting for more than 80 % of the malignant neoplasms of the pancreas. Although the molecular basis of pancreatic cancer is now better understood than ever before, there remains a long distance from being completely understood. In this study, we identified the differentially expressed genes (DEGs) in PDAC tissue compared with normal tissue and constructed a co-expression network by computing the pairwise correlation coefficient between the DEGs. We applied a statistical approach of MCODE to cluster genes in the coexpression network. Ten functional modules were identified in this network. Our results strongly suggest that dysregulations of immune response, homeostasis and cell adhesion may significantly contribute to the development and progression of PDAC. Results from this study will provide the groundwork for the understanding of PDAC. Future studies are needed to confirm some of the possible interactions suggested by this study.

microRNA-18b is upregulated in breast cancer and modulates genes involved in cell migration

microRNAs are small non-coding RNAs of ~22 nucleotides that function at post-transcriptional level as negative regulators of gene expression. Aberrant expression of microRNAs could promote uncontrolled proliferation, migration and invasion of human cancer cells. In this study, we analyzed the expression of microRNA-18b (miR-18b) in breast cancer cell lines and in a set of clinical specimens. Our results showed that miR-18b was upregulated in four out of five breast cancer cell lines and also in breast tumors. In order to identify potential gene targets, we carried out transcriptional profiling of MDA-MB-231 breast cancer cells that ectopically expressed miR-18b. Our results showed that 263 genes were significantly modulated in miR-18b-deficient cells (fold change >1.5; P≤0.05). We found that knock-down of miR-18b induced the upregulation of 55 olfactory receptor (OR) genes and nine genes (NLRP7, KLK3, OLFM3, POSTN, MAGED4B, KIR3DL3, CRX, SEMG1 and CEACAM5) with key roles in cell migration and metastasis. Consistently, we found that ectopic inhibition of miR-18b suppressed the migration of two breast cancer cell models in vitro. In conclusion, we have uncovered genes directly or indirectly modulated by miR-18b which may represent potential therapeutic targets in breast cancer. Our data also pointed out a role of miR-18b in migration of breast cancer cells.

Integrated analysis of recurrent properties of cancer genes to identify novel drivers

The heterogeneity of cancer genomes in terms of acquired mutations complicates the identification of genes whose modification may exert a driver role in tumorigenesis. In this study, we present a novel method that integrates expression profiles, mutation effects, and systemic properties of mutated genes to identify novel cancer drivers. We applied our method to ovarian cancer samples and were able to identify putative drivers in the majority of carcinomas without mutations in known cancer genes, thus suggesting that it can be used as a complementary approach to find rare driver mutations that cannot be detected using frequency-based approaches.

Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities

Recent advances in high-throughput biotechnologies have led to the rapid growing research interest in reverse engineering of biomolecular systems (REBMS). 'Data-driven' approaches, i.e. data mining, can be used to extract patterns from large volumes of biochemical data at molecular-level resolution while 'design-driven' approaches, i.e. systems modeling, can be used to simulate emergent system properties. Consequently, both data- and design-driven approaches applied to -omic data may lead to novel insights in reverse engineering biological systems that could not be expected before using low-throughput platforms. However, there exist several challenges in this fast growing field of reverse engineering biomolecular systems: (i) to integrate heterogeneous biochemical data for data mining, (ii) to combine top-down and bottom-up approaches for systems modeling and (iii) to validate system models experimentally. In addition to reviewing progress made by the community and opportunities encountered in addressing these challenges, we explore the emerging field of synthetic biology, which is an exciting approach to validate and analyze theoretical system models directly through experimental synthesis, i.e. analysis-by-synthesis. The ultimate goal is to address the present and future challenges in reverse engineering biomolecular systems (REBMS) using integrated workflow of data mining, systems modeling and synthetic biology.