PathwayMapper: a collaborative visual web editor for cancer pathways and genomic data

Exploring Molecular Genetic Alterations and RAF Fusions in Melanoma: A Belvarafenib Expanded Access Program in Patients with RAS/RAF-Mutant Melanoma

BACKGROUND

Melanoma incidence is on the rise in East Asia, yet studies of the molecular landscape are lacking in this population. We examined patients with melanoma who underwent next-generation sequencing (NGS) at a single tertiary center in South Korea, focusing on patients harboring NRAS or RAF alterations who received belvarafenib, a pan-RAF dimer inhibitor, through the Expanded Access Program (EAP).

PATIENTS AND METHODS

Data were collected from 192 patients with melanoma who underwent NGS between November 2017 and May 2023. Variant call format data were obtained and annotated. Patients in the EAP received 450 mg twice daily doses of belvarafenib.

RESULTS

Alterations in the RAS/RTK pathway were the most prevalent, with BRAF and NRAS alteration rates of 22.4% and 17.7%, respectively. NGS enabled additional detection of fusion mutations, including 6 BRAF and 1 RAF1 fusion. Sixteen patients with NRAS or RAF alterations received belvarafenib through the EAP, and disease control was observed in 50%, with 2 patients demonstrating remarkable responses.

CONCLUSIONS

Our study highlights the value of NGS in detecting BRAF, NRAS mutations and RAF fusions, expanding possibilities for targeted therapies in malignant melanoma. Belvarafenib showed clinical benefit in patients harboring these alterations. Ongoing trials will provide further insights into the safety and efficacy of belvarafenib.

Hsp Inhibitor is Affective Against Adenocarcinomic Human Alveolar Basal Epithelial Cells Through Modulating ERK/MAPK Signaling Pathway

The extracellular signal-regulated kinase (ERK) - mitogen-activated protein kinase (MAPK) pathway regulates cell proliferation, differentiation, and apoptosis. Heat Shock Protein 90 (HSP90) is required to activate proto-oncogenic protein kinases and promotes tumor growth through anti-apoptotic effects on A549-non-small cell lung cancer (NSCLC). Therefore, deregulation of the ERK-MAPK pathway and abnormal expression of HSP90 are reasonably frequent events in NSCLC. In this study, novel perimidine-pyrazole compounds employed to block ERK-MAPK deregulation through inhibiting HSP dependent cancer cell survival mechanisms. A set of perimidine-pyrazole derivatives effects was monitored on NSCLC cell line. Array experiments performed to understand the effect of the compounds on signaling pathways and results were analyzed by gene enrichment analysis. Further, senescence and apoptosis experiments were performed to support the enrichment results along with in silico methods to determine perimidine-pyrazole/HSP interactions. Treatment of NSCLC cells with perimidine-pyrazole derivatives displayed cancer-inhibitory, pro-senescent and pro-apoptotic effects on NSCLC cells through ERK/MAPK pathway and these compounds are promising templates for designing anticancer drugs.

Lidocaine induces apoptosis in head and neck squamous cell carcinoma through activation of bitter taste receptor T2R14

Head and neck squamous cell carcinomas (HNSCCs) have high mortality and significant treatment-related morbidity. It is vital to discover effective, minimally invasive therapies that improve survival and quality of life. Bitter taste receptors (T2Rs) are expressed in HNSCCs, and T2R activation can induce apoptosis. Lidocaine is a local anesthetic that also activates bitter taste receptor 14 (T2R14). Lidocaine has some anti-cancer effects, but the mechanisms are unclear. Here, we find that lidocaine causes intracellular Ca2+ mobilization through activation of T2R14 in HNSCC cells. T2R14 activation with lidocaine depolarizes mitochondria, inhibits proliferation, and induces apoptosis. Concomitant with mitochondrial Ca2+ influx, ROS production causes T2R14-dependent accumulation of poly-ubiquitinated proteins, suggesting that proteasome inhibition contributes to T2R14-induced apoptosis. Lidocaine may have therapeutic potential in HNSCCs as a topical gel or intratumor injection. In addition, we find that HPV-associated (HPV+) HNSCCs are associated with increased TAS2R14 expression. Lidocaine treatment may benefit these patients, warranting future clinical studies.

Network-based prediction approach for cancer-specific driver missense mutations using a graph neural network

BACKGROUND

In cancer genomic medicine, finding driver mutations involved in cancer development and tumor growth is crucial. Machine-learning methods to predict driver missense mutations have been developed because variants are frequently detected by genomic sequencing. However, even though the abnormalities in molecular networks are associated with cancer, many of these methods focus on individual variants and do not consider molecular networks. Here we propose a new network-based method, Net-DMPred, to predict driver missense mutations considering molecular networks. Net-DMPred consists of the graph part and the prediction part. In the graph part, molecular networks are learned by a graph neural network (GNN). The prediction part learns whether variants are driver variants using features of individual variants combined with the graph features learned in the graph part.

RESULTS

Net-DMPred, which considers molecular networks, performed better than conventional methods. Furthermore, the prediction performance differed by the molecular network structure used in learning, suggesting that it is important to consider not only the local network related to cancer but also the large-scale network in living organisms.

CONCLUSIONS

We propose a network-based machine learning method, Net-DMPred, for predicting cancer driver missense mutations. Our method enables us to consider the entire graph architecture representing the molecular network because it uses GNN. Net-DMPred is expected to detect driver mutations from a lot of missense mutations that are not known to be associated with cancer.

Precise microdissection of gastric mixed adeno-neuroendocrine carcinoma dissects its genomic landscape and evolutionary clonal origins

Gastric mixed adenoneuroendocrine carcinoma (MANEC) is a clinically aggressive and heterogeneous tumor composed of adenocarcinoma (ACA) and neuroendocrine carcinoma (NEC). The genomic properties and evolutionary clonal origins of MANEC remain unclear. We conduct whole-exome and multiregional sequencing on 101 samples from 33 patients to elucidate their evolutionary paths. We identify four significantly mutated genes, TP53, RB1, APC, and CTNNB1. MANEC resembles chromosomal instability stomach adenocarcinoma in that whole-genome doubling in MANEC is predominant and occurs earlier than most copy-number losses. All tumors are of monoclonal origin, and NEC components show more aggressive genomic properties than their ACA counterparts. The phylogenetic trees show two tumor divergence patterns, including sequential and parallel divergence. Furthermore, ACA-to-NEC rather than NEC-to-ACA transition is confirmed by immunohistochemistry on 6 biomarkers in ACA- and NEC-dominant regions. These results provide insights into the clonal origin and tumor differentiation of MANEC.

Synchronous endometrial and ovarian cancer: A case report

BACKGROUND

Synchronous endometrial and ovarian cancer (SEOC) is a rare genital tract tumor. Precise diagnosis is crucial for the disease management since prognosis and overall survival differ substantially between metastatic endometrial cancer (EC) or OC. In this review we present 2 cases of women who were diagnosed with SEOC, and discuss the clinical characteristic of SEOC, diagnostic and molecular profiling issues. Next generation sequencing of 10 gene panel was performed on cancerous tissue and uterine lavage samples.

CASE SUMMARY

In our report patients with SEOC had endometroid type histology with early stage and low-grade histology for both EC and OC. They underwent surgical treatment and staging. Next-generation sequencing of 10 gene-panel identified CTNNB1, PIK3CA, and PTEN gene mutations in ovarian tissue in one case, while none of these genes were mutated in other case. Literature review in support to our data suggest a good prognosis for SEOC diagnosed at early stage.

CONCLUSION

Accurate diagnosis of SEOC is essential for disease management and gene mutation analysis can be helpful as a complementary diagnostic and prognostic tool.

Integrated genomic analyses of hepatocellular carcinoma

BACKGROUND

Genomic alterations play important roles in the development of cancer. We explored the impact of protein-coding genes and transcriptomic changes on clinical and molecular alterations in Taiwanese hepatocellular carcinoma (HCC) patients.

METHODS

We analyzed 147 whole-exome sequencing and 100 RNA sequencing datasets of HCC and compared them with The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma cohort and develop a panel of 81 apoptosis-related genes for molecular classification.

RESULTS

TERT (50%), TP53 (25%), CTNNB1 (14%), ARID1A (12%), and KMT2C (11%) were the most common genetic alterations of cancer-related genes. ALDH2 and KMT2C mutated at much higher frequencies in our cohort than in TCGA, whereas CTNNB1 was found only in 14% of our Taiwanese patients. A high germline mutation rate of ALDH2 in the APOBEC mutational signature and herb drug-related aristolochic acid-associated signature was also observed. Groups A and B of HCC were identified when we used apoptosis-related genes for molecular classification. The latter group, which had poorer survival outcomes, had significantly more aDC, CD4+ Tem, macrophages M2, NKT, plasma cells, and Th1 cells, and less CD4+ memory T cells, CD8+ Tcm, cDC, iDC, and Th2 cells, as well as more inter-chromosome fusion genes. Metatranscriptomic analysis revealed 54 cases of HBV infection. Moreover, we found that the main target gene of HBV integration is ALB.

CONCLUSIONS

Unique genomic alterations were observed in our Taiwanese HCC patients. Molecular classification using apoptosis-related genes could lead to new therapeutic approaches for HCC.

Translating desktop success to the web in the cytoscape project

Cytoscape is an open-source bioinformatics environment for the analysis, integration, visualization, and query of biological networks. In this perspective piece, we describe our project to bring the Cytoscape desktop application to the web while explaining our strategy in ways relevant to others in the bioinformatics community. We examine opportunities and challenges in developing bioinformatics software that spans both the desktop and web, and we describe our ongoing efforts to build a Cytoscape web application, highlighting the principles that guide our development.

Drug Repurposing Applications to Overcome Male Predominance via Targeting G2/M Checkpoint in Human Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is strongly characterized by a male predominance with higher mortality rates and worse responses to treatment in males versus females. Despite the role of sex hormones, other causes that may contribute to sex bias in ESCC remain largely unknown, especially as age increases and the hormone difference begins to diminish between sexes. In this study, we analyzed genomics, transcriptomics, and epigenomics from 663 ESCC patients and found that G2/M checkpoint pathway-related sex bias and age bias were significantly present in multi-omics data. In accordance with gene expression patterns across sexes, ten compounds were identified by applying drug repurposing from three drug sensitivity databases: The Connective Map (CMap), Genomics of Drug Sensitivity in Cancer (GDSC), and The Cancer Therapeutic Response Portal (CTRP). MK1775 and decitabine showed better efficacy in two male ESCC cell lines in vitro and in vivo. The drugs' relevance to the transition between G2 and M was especially evident in male cell lines. In our study, we first validated the sex bias of the G2/M checkpoint pathway in ESCC and then determined that G2/M targets may be included in combination therapy for male patients to improve the efficacy of ESCC treatment.

Computational methods and translational applications for targeted next-generation sequencing platforms

During the past decade, next-generation sequencing (NGS) technologies have become widely adopted in cancer research and clinical care. Common applications within the clinical setting include patient stratification into relevant molecular subtypes, identification of biomarkers of response and resistance to targeted and systemic therapies, assessment of heritable cancer risk based on known pathogenic variants, and longitudinal monitoring of treatment response. The need for efficient downstream processing and reliable interpretation of sequencing data has led to the development of novel algorithms and computational pipelines, as well as structured knowledge bases that link genomic alterations to currently available drugs and ongoing clinical trials. Cancer centers around the world use different types of targeted solid-tissue and blood based NGS assays to analyze the genomic and transcriptomic profile of patients as part of their routine clinical care. Recently, cross-institutional collaborations have led to the creation of large pooled datasets that can offer valuable insights into the genomics of rare cancers.

Tumor Suppressive Effects of GAS5 in Cancer Cells

In recent years, long non-coding RNAs (lncRNAs) have been shown to play important regulatory roles in cellular processes. Growth arrests specific transcript 5 (GAS5) is a lncRNA that is highly expressed during the cell cycle arrest phase but is downregulated in actively growing cells. Growth arrests specific transcript 5 was discovered to be downregulated in several cancers, primarily solid tumors, and it is known as a tumor suppressor gene that regulates cell proliferation, invasion, migration, and apoptosis via multiple molecular mechanisms. Furthermore, GAS5 polymorphism was found to affect GAS5 expression and functionality in a cell-specific manner. This review article focuses on GAS5’s tumor-suppressive effects in regulating oncogenic signaling pathways, cell cycle, apoptosis, tumor-associated genes, and treatment-resistant cells. We also discussed genetic polymorphisms of GAS5 and their association with cancer susceptibility.

Comprehensive Analysis of Subtype-Specific Molecular Characteristics of Colon Cancer: Specific Genes, Driver Genes, Signaling Pathways, and Immunotherapy Responses

Colon cancer is a complex, heterogeneous disease. The Colorectal Cancer Subtyping Consortium reported a novel classification system for colon cancer in 2015 to better understand its heterogeneity. This molecular classification system divided colon cancer into four distinct consensus molecular subtypes (CMS 1, 2, 3, and 4). However, the characteristics of different colon cancer molecular subtypes have not been fully elucidated. This study comprehensively analyzed the molecular characteristics of varying colon cancer subtypes using multiple databases and algorithms, including The Cancer Genome Atlas (TCGA) database, DriverDBv3 database, CIBERSORT, and MCP-counter algorithms. We analyzed the alterations in the subtype-specific genes of different colon cancer subtypes, such as the RNA levels and DNA alterations, and showed that specific subtype-specific genes significantly affected prognosis. We also explored the changes in colon cancer driver genes and representative genes of 10 signaling pathways in different subtypes. We identified genes that were altered in specific subtypes. We further detected the infiltration of 22 immune cell types in four colon cancer subtypes and the infiltration level of primary immune cells among these subtypes. Additionally, we explored changes in immune checkpoint genes (ICGs) and immunotherapy responses among different colon cancer subtypes. This study may provide clues for the molecular mechanism of tumorigenesis and progression in colon cancer. It also offers potential biomarkers and targets for the clinical diagnosis and treatment of different colon cancer subtypes.

Association between Altered Oncogenic Signaling Pathways and Overall Survival of Patients with Metastatic Colorectal Cancer

Systemic characterization of genomic alterations into signaling pathways helps to understand the molecular pathogenies of colorectal cancer; however, their clinical implications remain unclear. Here, 128 patients with metastatic colorectal cancer (mCRC) receiving targeted next generation sequencing were retrospectively enrolled to analyze the impact of altered oncogenic pathways on clinical outcome. The datasets from Memorial Sloan Kettering Cancer Center were used for validation. In 123 patients with non-MSI-high tumor, the most common mutated gene was TP53 (84.6%), followed by APC (78.0%), KRAS (49.6%), and SMAD4 (22.8%). When mutated genes were allocated into signaling pathways defined as The Cancer Genome Atlas Pan-Cancer Analysis Project, alterations of cell cycle, Wnt, p53, RTK-RAS, PI3K, TGF-β, Notch, and Myc pathways were identified in 88%, 87%, 85%, 75%, 28%, 26%, 17%, and 10% of mCRC tissues, respectively. The survival analyses revealed that Myc and TGF-β pathway alterations were associated with a shorter overall survival (OS) (hazard ratio [HR]: 2.412; 95% confidence interval [CI]: 1.139–5.109; p = 0.018 and HR: 2.754; 95% CI: 1.044–7.265; p = 0.033, respectively). The negative prognostic impact of altered TGF-β pathway was maintained in patients receiving an anti-EGFR antibody. The OS of patients with mCRC carrying MYC and BRAF mutation was shorter than those with either MYC or BRAF mutation (HR: 4.981, 95% CI: 0.296–83.92; p = 0.02). These findings have clinical implications, such as prognosis prediction, treatment guidance, and molecular-targeted therapy development.

PPARγ Targets-Derived Diagnostic and Prognostic Index for Papillary Thyroid Cancer

Simple Summary

Through targeted next-generation sequencing of thyroid cancer-related genes in monozygotic twins with papillary thyroid cancer (PTC), we identified common variants of the gene encoding peroxisome proliferator activated receptor gamma (PPARG). Notably, the expression levels of PPARγ target genes were frequently deregulated in PTC compared to benign tissues and were closely associated with disease-specific survival (DSS) outcomes in a TCGA-PTC cohort. Machine learning-powered personalized scoring index comprising 10 PPARγ targets, termed as PPARGi, achieved a near-perfect accuracy in distinguishing cancers from benign tissues, and further identified a small subpopulation of patients at high-risk across different profiling platforms.

Abstract

In most cases, papillary thyroid cancer (PTC) is highly curable and associated with an excellent prognosis. Yet, there are several clinicopathological features that lead to a poor prognosis, underscoring the need for a better genomic strategy to refine prognostication and patient management. We hypothesized that PPARγ targets could be potential markers for better diagnosis and prognosis due to the variants found in PPARG in three pairs of monozygotic twins with PTC. Here, we developed a 10-gene personalized prognostic index, designated PPARGi, based on gene expression of 10 PPARγ targets. Through scRNA-seq data analysis of PTC tissues derived from patients, we found that PPARGi genes were predominantly expressed in macrophages and epithelial cells. Machine learning algorithms showed a near-perfect performance of PPARGi in deciding the presence of the disease and in selecting a small subset of patients with poor disease-specific survival in TCGA-THCA and newly developed merged microarray data (MMD) consisting exclusively of thyroid cancers and normal tissues.

Targeted Therapy of Papillary Thyroid Cancer: A Comprehensive Genomic Analysis

Background

A limited number of targeted therapy options exist for papillary thyroid cancer (PTC) to date. Based on genetic alterations reported by the "The Cancer Genome Atlas (TCGA)", we explored whether PTC shows alterations that may be targetable by drugs approved by the FDA for other solid cancers.

Methods

Databases of the National Cancer Institute and MyCancerGenome were screened to identify FDA-approved drugs for targeted therapy. Target genes were identified using Drugbank. Genetic alterations were classified into conferring drug sensitivity or resistance using MyCancerGenome, CiViC, TARGET, and OncoKB. Genomic data for PTC were extracted from TCGA and mined for alterations predicting drug response.

Results

A total of 129 FDA-approved drugs with 128 targetable genes were identified. One hundred ninety-six (70%) of 282 classic, 21 (25%) of 84 follicular, and all 30 tall-cell variant PTCs harbored druggable alterations: 259 occurred in 29, 39 in 19, and 31 in 2 targetable genes, respectively. The BRAF V600 mutation was seen in 68% of classic, 16% of follicular variant, and 93% of tall-cell variant PTCs. The RET gene fusion was seen in 8% of classic PTCs, NTRK1 and 3 gene fusions in 3%, and other alterations in <2% of classic variant PTCs. Ninety-nine of 128 (77%) FDA-approved targetable genes did not show any genetic alteration in PTC. Beside selective and non-selective BRAF-inhibitors, no other FDA-approved drug showed any frequent predicted drug sensitivity (<10%).

Conclusion

Treatment strategies need to focus on resistance mechanisms to BRAF inhibition and on genetic alteration-independent alternatives rather than on current targeted drugs.

Proteogenomic analysis of pancreatic cancer subtypes

Pancreatic cancer remains a significant public health problem with an ever-rising incidence of disease. Cancers of the pancreas are characterised by various molecular aberrations, including changes in the proteomics and genomics landscape of the tumour cells. Therefore, there is a need to identify the proteomic landscape of pancreatic cancer and the specific genomic and molecular alterations associated with disease subtypes. Here, we carry out an integrative bioinformatics analysis of The Cancer Genome Atlas dataset, including proteomics and whole-exome sequencing data collected from pancreatic cancer patients. We apply unsupervised clustering on the proteomics dataset to reveal the two distinct subtypes of pancreatic cancer. Using functional and pathway analysis based on the proteomics data, we demonstrate the different molecular processes and signalling aberrations of the pancreatic cancer subtypes. In addition, we explore the clinical characteristics of these subtypes to show differences in disease outcome. Using datasets of mutations and copy number alterations, we show that various signalling pathways previously associated with pancreatic cancer are altered among both subtypes of pancreatic tumours, including the Wnt pathway, Notch pathway and PI3K-mTOR pathways. Altogether, we reveal the proteogenomic landscape of pancreatic cancer subtypes and the altered molecular processes that can be leveraged to devise more effective treatments.

The prevalence of HLA-I LOH in Chinese pan-cancer patients and genomic features of patients harboring HLA-I LOH

HLA-I LOH may facilitate immune evasion. However, large population studies on the prevalence of HLA-I LOH across different cancer types and in relation to mutational profiles are lacking, in particular, in the Chinese population. In this study, analysis was performed in 1504 advanced pan-cancer patients and 134 early-stage non-small-cell lung cancer patients using a 1021-gene panel. The consistency between the 1021-gene panel and whole-exome sequencing was evaluated in 45 samples, where concordant results were obtained in 95.6% (43/45) of the samples. Analytical results revealed that the prevalence of HLA-I LOH in tumor tissue presents considerable differences across cancer types. HLA-I LOH was relevant to genomic instability, reflected in higher tumor mutation burden level. HLA-I LOH occurs more frequently in MSS samples than in MSI-H samples. The alteration frequencies of p53 pathway, RTK/RAS pathway, Notch pathway, Hippo pathway, and Nrf2 pathway in HLA-I LOH group were significantly higher than that in HLA-I stable group (p < .0001, p < .0001, p = .032, p = .013, p = .003, respectively). In DNA damage response pathways, alterations in the checkpoint factor pathway and Fanconi anemia pathway are enriched in HLA-I LOH group (p < .0001, p = .023, respectively). Besides, HLA-I LOH was accompanied by higher mutation rates of several tumor suppressors, including TP53 and LRP1B. These results may shed light on follow-up tumor immunology research.

Uncovering the Subtype-Specific Molecular Characteristics of Breast Cancer by Multiomics Analysis of Prognosis-Associated Genes, Driver Genes, Signaling Pathways, and Immune Activity

Breast cancer is a heterogeneous malignant disease with different prognoses and has been divided into four molecular subtypes. It is believed that molecular events occurring in breast stem/progenitor cells contribute to the carcinogenesis and development of different breast cancer subtypes. However, these subtype-specific molecular characteristics are largely unknown. In this study, we employed 1217 breast cancer samples from The Cancer Genome Atlas (TCGA) database for a multiomics analysis of the molecular characteristics of different breast cancer subtypes based on PAM50 algorithms. We detected the expression changes of subtype-specific genes and revealed that the expression of particular subtype-specific genes significantly affected prognosis. We also investigated the mutations and copy number variations (CNVs) of breast cancer driver genes and the representative genes of ten signaling pathways in different subtypes and revealed several subtype-specifically altered genes. Moreover, we detected the infiltration of various immune cells in different subtypes of breast cancer and showed that the infiltration levels of major immune cell types are different among these subtypes. Additionally, we investigated the factors affecting the immune infiltration level and the immune cytolytic activity in different breast cancer subtypes, namely, the mutation burden, genome instability and cancer-associated fibroblast (CAF) infiltration. This study may shed light on the molecular events contributing to carcinogenesis and development and provide potential markers and targets for the clinical diagnosis and treatment of different breast cancer subtypes.

MEScan: a powerful statistical framework for genome-scale mutual exclusivity analysis of cancer mutations

MOTIVATION

Cancer somatic driver mutations associated with genes within a pathway often show a mutually exclusive pattern across a cohort of patients. This mutually exclusive mutational signal has been frequently used to distinguish driver from passenger mutations and to investigate relationships among driver mutations. Current methods for de novo discovery of mutually exclusive mutational patterns are limited because the heterogeneity in background mutation rate can confound mutational patterns, and the presence of highly mutated genes can lead to spurious patterns. In addition, most methods only focus on a limited number of pre-selected genes and are unable to perform genome-wide analysis due to computational inefficiency.

RESULTS

We introduce a statistical framework, MEScan, for accurate and efficient mutual exclusivity analysis at the genomic scale. Our framework contains a fast and powerful statistical test for mutual exclusivity with adjustment of the background mutation rate and impact of highly mutated genes, and a multi-step procedure for genome-wide screening with the control of false discovery rate. We demonstrate that MEScan more accurately identifies mutually exclusive gene sets than existing methods and is at least two orders of magnitude faster than most methods. By applying MEScan to data from four different cancer types and pan-cancer, we have identified several biologically meaningful mutually exclusive gene sets.

AVAILABILITY AND IMPLEMENTATION

MEScan is available as an R package at https://github.com/MarkeyBBSRF/MEScan.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In vivo genome-wide CRISPR screen reveals breast cancer vulnerabilities and synergistic mTOR/Hippo targeted combination therapy

Triple negative breast cancer (TNBC) patients exhibit poor survival outcomes and lack effective targeted therapies. Using unbiased in vivo genome-wide CRISPR screening, we interrogated cancer vulnerabilities in TNBC and identified an interplay between oncogenic and tumor suppressor pathways. This study reveals tumor regulatory functions for essential components of the mTOR and Hippo pathways in TNBC. Using in vitro drug matrix synergy models and in vivo patient-derived xenografts, we further establish the therapeutic relevance of our findings and show that pharmacological inhibition of mTORC1/2 and oncoprotein YAP efficiently reduces tumorigenesis in TNBC. At the molecular level, we find that while verteporfin-induced YAP inhibition leads to apoptosis, torin1-mediated mTORC1/2 inhibition promotes macropinocytosis. Torin1-induced macropinocytosis further facilitates verteporfin uptake, thereby greatly enhancing its pro-apoptotic effects in cancer cells. Overall, our study underscores the power and robustness of in vivo CRISPR genome-wide screens in identifying clinically relevant and innovative therapeutic modalities in cancer.

Triple negative breast cancer (TNBC) lack effective therapies. Here, through an in vivo genome-wide CRISPR screen in TNBCs, the authors identify tumorigenic functions for components of the mTORC1/2 complex and of the YAP/Hippo pathway, and demonstrate that pharmacological inhibition of mTOR and YAP reduces tumour growth in vivo.

Control Analysis of Protein-Protein Interaction Network Reveals Potential Regulatory Targets for MYCN

BACKGROUND

MYCN is an oncogenic transcription factor of the MYC family and plays an important role in the formation of tissues and organs during development before birth. Due to the difficulty in drugging MYCN directly, revealing the molecules in MYCN regulatory networks will help to identify effective therapeutic targets.

METHODS

We utilized network controllability theory, a recent developed powerful tool, to identify the potential drug target around MYCN based on Protein-Protein interaction network of MYCN. First, we constructed a Protein-Protein interaction network of MYCN based on public databases. Second, network control analysis was applied on network to identify driver genes and indispensable genes of the MYCN regulatory network. Finally, we developed a novel integrated approach to identify potential drug targets for regulating the function of the MYCN regulatory network.

RESULTS

We constructed an MYCN regulatory network that has 79 genes and 129 interactions. Based on network controllability theory, we analyzed driver genes which capable to fully control the network. We found 10 indispensable genes whose alternation will significantly change the regulatory pathways of the MYCN network. We evaluated the stability and correlation analysis of these genes and found EGFR may be the potential drug target which closely associated with MYCN.

CONCLUSION

Together, our findings indicate that EGFR plays an important role in the regulatory network and pathways of MYCN and therefore may represent an attractive therapeutic target for cancer treatment.

The genetic landscape of metaplastic breast cancers and uterine carcinosarcomas

Metaplastic breast carcinoma (MBC) and uterine carcinosarcoma (UCS) are rare aggressive cancers, characterized by an admixture of adenocarcinoma and areas displaying mesenchymal/sarcomatoid differentiation. We sought to define whether MBCs and UCSs harbor similar patterns of genetic alterations, and whether the different histologic components of MBCs and UCSs are clonally related. Whole-exome sequencing (WES) data from MBCs (n = 35) and UCSs (n = 57, The Cancer Genome Atlas) were reanalyzed to define somatic genetic alterations, altered signaling pathways, mutational signatures, and genomic features of homologous recombination DNA repair deficiency (HRD). In addition, the carcinomatous and sarcomatous components of an additional cohort of MBCs (n = 11) and UCSs (n = 6) were microdissected separately and subjected to WES, and their clonal relatedness was assessed. MBCs and UCSs harbored recurrent genetic alterations affecting TP53, PIK3CA, and PTEN, similar patterns of gene copy number alterations, and an enrichment in alterations affecting the epithelial-to-mesenchymal transition (EMT)-related Wnt and Notch signaling pathways. Differences were observed, however, including a significantly higher prevalence of FAT3 and FAT1 somatic mutations in MBCs compared to UCSs, and conversely, UCSs significantly more frequently harbored somatic mutations affecting FBXW7 and PPP2R1A as well as HER2 amplification than MBCs. Genomic features of HRD and biallelic alterations affecting bona fide HRD-related genes were found to be more prevalent in MBCs than in UCSs. The distinct histologic components of MBCs and UCSs were clonally related in all cases, with the sarcoma component likely stemming from a minor subclone of the carcinoma component in the samples with interpretable chronology of clonal evolution. Despite the similar histologic features and pathways affected by genetic alterations, UCSs differ from MBCs on the basis of FBXW7 and PPP2R1A mutations, HER2 amplification, and lack of HRD, supporting the notion that these entities are more than mere phenocopies of the same tumor type in different anatomical sites.

Statistical Methods in Experimental Pathology: A Review and Primer

Correct use of statistical methods is important to ensure the reliability and value of the published experimental pathology literature. Considering increasing interest in the quality of statistical reporting in pathology, the statistical methods used in 10 recent issues of the American Journal of Pathology were reviewed. The statistical tests performed in the articles were summarized, with attention to their implications for contemporary pathology research and practice. Among the 195 articles identified, 93% reported using one or more statistical tests. Retrospective statistical review of the articles revealed several key findings. First, tests for normality were infrequently reported, and parametric hypothesis tests were overutilized. Second, studies reporting multisample hypothesis tests (eg, analysis of variance) infrequently performed post hoc tests to explore differences between study groups. Third, correlation, regression, and survival analysis techniques were underutilized. On the basis of these findings, a primer on relevant statistical concepts and tests is presented, including issues related to optimal study design, descriptive and comparative statistics, and regression, correlation, survival, and genetic data analysis.

Genomic and transcriptomic landscape of conjunctival melanoma

Conjunctival melanoma (CJM) is a rare but potentially lethal and highly-recurrent cancer of the eye. Similar to cutaneous melanoma (CM), it originates from melanocytes. Unlike CM, however, CJM is relatively poorly characterized from a genomic point of view. To fill this knowledge gap and gain insight into the genomic nature of CJM, we performed whole-exome (WES) or whole-genome sequencing (WGS) of tumor-normal tissue pairs in 14 affected individuals, as well as RNA sequencing in a subset of 11 tumor tissues. Our results show that, similarly to CM, CJM is also characterized by a very high mutation load, composed of approximately 500 somatic mutations in exonic regions. This, as well as the presence of a UV light-induced mutational signature, are clear signs of the role of sunlight in CJM tumorigenesis. In addition, the genomic classification of CM proposed by TCGA seems to be well-applicable to CJM, with the presence of four typical subclasses defined on the basis of the most frequently mutated genes: BRAF, NF1, RAS, and triple wild-type. In line with these results, transcriptomic analyses revealed similarities with CM as well, namely the presence of a transcriptomic subtype enriched for immune genes and a subtype enriched for genes associated with keratins and epithelial functions. Finally, in seven tumors we detected somatic mutations in ACSS3, a possible new candidate oncogene. Transfected conjunctival melanoma cells overexpressing mutant ACSS3 showed higher proliferative activity, supporting the direct involvement of this gene in the tumorigenesis of CJM. Altogether, our results provide the first unbiased and complete genomic and transcriptomic classification of CJM.

Conjunctival melanoma is an extremely rare form of cancer of the eye that arises from melanocytes–the cells producing the protective pigment melanin–in the outmost layer of the eye: the conjunctiva. This tissue, similarly to the skin, can also be exposed to UV light radiation from the sun. We investigated the genetic background of this rare form of cancer in samples from fourteen patients, by global DNA and RNA sequencing. Our results showed that conjunctival melanoma is genetically very similar to cutaneous melanoma. More precisely, in tumor DNA we detected signs of damage caused by UV light, as well as mutations in the genes BRAF, NF1 and NRAS/HRAS, previously described to be involved in cutaneous melanoma. Analysis of tumor gene expression also revealed similarities between these two types of cancer, some of which could be used as prognostic factors or as indicators of a patients’ response to therapy. In addition, we identified frequent somatic mutations in ACSS3, a gene not yet associated with either conjunctival or cutaneous melanoma, which represents a potential key player in oncogenesis of conjunctival melanoma.

Loss of Jag1 cooperates with oncogenic Kras to induce pancreatic cystic neoplasms

Notch signaling exerts both oncogenic and tumor-suppressive functions in the pancreas. In this study, deletion of Jag1 in conjunction with oncogenic Kras ^G12D expression in the mouse pancreas induced rapid development of acinar-to-ductal metaplasia and early stage pancreatic intraepithelial neoplasm; however, culminating in cystic neoplasms rather than ductal adenocarcinoma. Most cystic lesions in these mice were reminiscent of serous cystic neoplasm, and the rest resembled intraductal papillary mucinous neoplasm. Jag1 expression was lost or decreased in cystic lesions but retained in adenocarcinoma in these mice, so was the expression of Sox9. In pancreatic cancer patients, JAG1 expression is higher in cancerous tissue, and high JAG1 is associated with poor overall survival. Expression of SOX9 is correlated with JAG1, and high SOX9 is also associated with poor survival. Mechanistically, Jag1 regulates expression of Lkb1, a tumor suppressor involved in the development of pancreatic cystic neoplasm. Collectively, Jag1 can act as a tumor suppressor in the pancreas by delaying precursor lesions, whereas loss of Jag1 promoted a phenotypic switch from malignant carcinoma to benign cystic lesions.

Genetic and epigenetic landscape of IDH-wildtype glioblastomas with FGFR3-TACC3 fusions

A subset of glioblastomas (GBMs) harbors potentially druggable oncogenic FGFR3-TACC3 (F3T3) fusions. However, their associated molecular and clinical features are poorly understood. Here we analyze the frequency of F3T3-fusion positivity, its associated genetic and methylation profiles, and its impact on survival in 906 IDH-wildtype GBM patients. We establish an F3T3 prevalence of 4.1% and delineate its associations with cancer signaling pathway alterations. F3T3-positive GBMs had lower tumor mutational and copy-number alteration burdens than F3T3-wildtype GBMs. Although F3T3 fusions were predominantly mutually exclusive with other oncogenic RTK pathway alterations, they did rarely co-occur with EGFR amplification. They were less likely to harbor TP53 alterations. By methylation profiling, they were more likely to be assigned the mesenchymal or RTK II subclass. Despite being older at diagnosis and having similar frequencies of MGMT promoter hypermethylation, patients with F3T3-positive GBMs lived about 8 months longer than those with F3T3-wildtype tumors. While consistent with IDH-wildtype GBM, F3T3-positive GBMs exhibit distinct biological features, underscoring the importance of pursuing molecular studies prior to clinical trial enrollment and targeted treatment.

A phase 2 trial of buparlisib in patients with platinum-resistant metastatic urothelial carcinoma

BACKGROUND

The phosphatidyl 3-inositol kinase (PI3K)/Akt/mechanistic target of rapamycin (mTOR) pathway frequently is activated in patients with urothelial carcinoma (UC). In the current study, the authors performed a phase 2 study evaluating the efficacy of the pan-isoform class I PI3K inhibitor buparlisib in patients with platinum-refractory metastatic UC.

METHODS

Two cohorts were recruited: an initial genetically unselected cohort and a subsequent expansion cohort of patients with PI3K/Akt/mTOR pathway-altered tumors. The primary endpoint was the 2-month progression-free survival rate. A rate of ≥80% was considered promising using a Simon 2-stage minimax design. Secondary endpoints included safety and correlation of markers of PI3K pathway activation with outcome.

RESULTS

Six of 13 evaluable patients within the initial cohort demonstrated stable disease and 1 demonstrated a partial response, which was below the cutoff of 9 patients required to proceed to stage 2. Three of the patients with stable disease and the patient with a partial response harbored somatic TSC1 alterations. Four patients subsequently were recruited onto an expansion cohort: 3 patients with TSC1 alterations and 1 patient with a PIK3CA-activating mutation. No patient achieved disease control at 8 weeks and accrual was halted. Of the 19 patients evaluable for toxicity, 17 demonstrated treatment-related toxicities, 2 of whom had to discontinue therapy.

CONCLUSIONS

Buparlisib was found to demonstrate modest activity in patients with metastatic UC whose tumors harbored TSC1 loss of function alterations; however, this was not a robust predictor of response to buparlisib. The pattern of genetic coalterations likely influences drug sensitivity. Given the modest clinical activity and substantial toxicity of buparlisib, future trials of PI3K inhibitors in patients with UC should focus on isoform-selective PI3K inhibitors in genomically selected patients.

LAY SUMMARY

The phosphatidyl 3-inositol kinase (PI3K)/Akt/mechanistic target of rapamycin (mTOR) signaling pathway frequently is upregulated in patients with metastatic urothelial carcinoma (UC). This trial explored buparlisib, an inhibitor of the pathway, in patients with heavily pretreated metastatic UC. Although the drug was found to have modest efficacy, with 6 patients experiencing stable disease and 1 patient achieving a partial response at 8 weeks on therapy, significant side effects also were observed. Patients with specific genetic alterations responded to treatment. Further studies of PI3K pathway inhibition are warranted using newer agents that have superior toxicity profiles and are more selective inhibitors of the pathway.

Drug Vulnerabilities and Disease Prognosis Linked to the Stem Cell-Like Gene Expression Program Triggered by the RHO GTPase Activator VAV2 in Hyperplastic Keratinocytes and Head and Neck Cancer

Simple Summary

Head and neck squamous cell carcinoma are epithelial tumors with a very poor prognosis. They are also in high need of new targeted and immune-based therapeutics to limit tumor recurrence and improve long-term survival. The poor prognosis of patients with head and neck tumors is usually associated with histological features associated with poor differentiation and high proliferative activity found in their tumor biopsies. Therefore, it is of paramount importance to identify vulnerabilities associated with such pathobiological programs. In this work, the authors utilize a stem cell-like program linked to the deregulated activity of VAV2, a protein frequently overexpressed in this type of tumors, to identify new therapeutic targets that can discriminate tumors from healthy cells. The authors also show that this gene expression program can be used to stratify patients according to long-term prognosis.

Abstract

We have recently shown that VAV2, a guanosine nucleotide exchange factor that catalyzes the stimulation step of RHO GTPases, is involved in a stem cell-like (SCL) regenerative proliferation program that is important for the development and subsequent maintenance of the tumorigenesis of both cutaneous (cSCC) and head and neck squamous cell carcinomas (hnSCC). In line with this, we have observed that the levels of the VAV2 mRNA and VAV2-regulated gene signatures are associated with poor prognosis in the case of human papillomavirus-negative hnSCC patients. These results suggest that the SCL program elicited by VAV2 in those cells can harbor therapeutically actionable downstream targets. We have addressed this issue using a combination of both in silico and wet-lab approaches. Here, we show that the VAV2-regulated SCL program does harbor a number of cell cycle- and signaling-related kinases that are essential for the viability of undifferentiated keratinocytes and hnSCC patient-derived cells endowed with high levels of VAV2 activity. Our results also show that the VAV2-regulated SCL gene signature is associated with poor hnSCC patient prognosis. Collectively, these data underscore the critical role of this VAV2-regulated SCL program for the viability of both preneoplastic and fully transformed keratinocytes.

The genomic landscape of Mongolian hepatocellular carcinoma

Mongolia has the highest incidence of hepatocellular carcinoma (HCC) in the world, but its causative factors and underlying tumor biology remain unknown. Here, we describe molecular characteristics of HCC from 76 Mongolian patients by whole-exome and transcriptome sequencing. We present a comprehensive analysis of mutational signatures, driver genes, and molecular subtypes of Mongolian HCC compared to 373 HCC patients of different races and ethnicities and diverse etiologies. Mongolian HCC consists of prognostic molecular subtypes similar to those found in patients from other areas of Asia, Europe, and North America, as well as other unique subtypes, suggesting the presence of distinct etiologies linked to Mongolian patients. In addition to common driver mutations (TP53, CTNNB1) frequently found in pan-cancer analysis, Mongolian HCC exhibits unique drivers (most notably GTF2IRD2B, PNRC2, and SPTA1), the latter of which is associated with hepatitis D viral infection. These results suggest the existence of new molecular mechanisms at play in Mongolian hepatocarcinogenesis.

Identification of New Therapeutic Targets for Gastric Cancer With Bioinformatics

We aimed to identify new targets affecting gastric cancer (GC) prognosis. Six target genes were identified from hub genes based on their relationship with important factors affecting tumor progression, like immune infiltration, purity, tumor mutation burden (TMB), and tumor microenvironment (TME) score. The effect of target genes' somatic mutations and copy number alteration (CNA) was examined to determine their effect on GC prognosis. Six target genes (FBN1, FN1, HGF, MMP9, THBS1, and VCAN) were identified. Reduced expression of each target gene, except MMP9, indicated better prognosis and lower grade in GC. FBN1, THBS1, and VCAN showed lower expression in stage I GC. Non-silencing mutations of the six genes played a role in significantly higher TMB and TME scores. THBS1 mutation was associated with earlier stage GC, and VCAN mutation was associated with lower grade GC. However, patients with target gene CNA displayed higher tumor purity. MMP9, THBS1, and VCAN CNA was associated with lower grade GC, while FBN1 CNA reflected earlier T stage. Additionally, the target genes may affect GC prognosis by influencing multiple oncogenic signaling pathways. FBN1, FN1, HGF, MMP9, THBS1, and VCAN may be new GC prognostic targets by affecting tumor purity, TMB, TME score, and multiple oncogenic signaling pathways.

RAS/MAPK Pathway Driver Alterations Are Significantly Associated With Oncogenic KIT Mutations in Germ-cell Tumors

OBJECTIVE

To report the mutational profile and clinical outcomes of a cohort of patients with KIT-mutant seminomas and nonseminomatous germ-cell tumors (SGCT/NSGCTs).

PATIENTS AND METHODS

Retrospective cohort study of all patients with KIT-mutant GCTs sequenced at Memorial Sloan Kettering between March 2014 and March 2020. Tumors were assessed with MSK-IMPACT, a DNA next-generation sequencing assay for targeted sequencing of up to 468 key cancer genes.

RESULTS

Among 568 patients with GCTs, 8.1% had somatic KIT mutations, including 28 seminomas and 18 mixed/NSGCTs. Exons 17 (67.3%), 11 (22.4%), and 13 (6.1%) were most commonly affected. KIT-mutant cases were enriched for oncogenic RAS/MAPK pathway alterations compared to KIT-wildtype cases (34.8% vs 19.2%, P = .02). Among KIT-mutant cases, concurrent mutations were noted in KRAS (21.7%), RRAS2 (11.8%), CBL (6.5%), NRAS (4.3%), MAP2K1 (2.2%), and RAC1 (2.2%). Mutations in KRAS, RRAS2, and NRAS were mutually exclusive. In all, 73.9% of patients developed metastases and 95.7% received chemotherapy. No patients received KIT-directed tyrosine kinase inhibitors (TKIs). Classification as a NSGCT rather than a SGCT was associated with an increased risk of death (hazard ratio 9.1, 95% confidence interval 1.1-78.4, P = .04) while the presence of a concurrent RAS/MAPK pathway alteration was not (hazard ratio 0.8, 95% confidence interval 0.1-4.3, P = .76).

CONCLUSION

Mitogenic driver alterations can co-occur with activating KIT mutations, which may explain the lack of efficacy of KIT-directed TKIs in prior trials. Novel KIT-directed TKIs that target exon 17 mutations may benefit chemotherapy-refractory patients with KIT-mutant GCTs without RAS/MAPK alterations. Dual MEK/KIT inhibitor therapy in KIT-mutant GCTs with concurrent RAS/MAPK alterations could also be a plausible therapeutic strategy.

Genomic and Transcriptomic Characterization of Sporadic Medullary Thyroid Carcinoma

Background: Sporadic medullary thyroid carcinoma (MTC) is a relatively uncommon neuroendocrine malignancy and the molecular tumorigenesis of its sporadic type (sMTC) is only partially understood. In this study, we performed a study focusing on the genomic and transcriptomic characterization of sMTC. Methods: Twenty-nine sMTC patients were included. Whole-exome sequencing (WES) was carried out in 18 patients, including both tumor samples and matched noncancerous tissues. Whole transcriptome sequencing (RNA-Seq) was performed in all 29 tumors. WES, RNA-Seq, and copy number alteration (CNA) data were analyzed. A Cell Counting Kit-8 (CCK-8) assay was used to evaluate cell proliferation. Results: Among the somatic mutations, RET was the only recurrently cancer-related mutated gene (5/18, 27.8%). In the germline, FAT1 and FAT4, two members of the FAT gene family, were identified as the two most common mutated genes. CNA analysis found that FAT1 and FAT4, both located on chromosome 4q, were also two of the genes most commonly affected by somatic chromosomal deletions (4/18, 22.2%). Using TT and MZ-CRC-1 cell lines, the CCK-8 assay showed that FAT1 and FAT4 knockdown could promote MTC cell proliferation. Based on the gene expression profile, patients were clustered into two molecular subtypes: the mesenchymal-like subtype is characterized by epithelial-mesenchymal transition, while the proliferative-like subtype is associated with enrichment of cell cycle pathways. Most events of structural recurrence (80%) occurred in the proliferative-like subtype. Conclusion: In addition to RET, these findings demonstrate that FAT1/FAT4 genomic alterations appear to be frequent in sMTC. Two molecular subtypes of sMTC with distinct biological behavior could be identified. However, these results need to be validated by larger samples and more comprehensive experiments in the future, especially for the frequency and function of FAT1/FAT4 germline variants.

A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data

The Cancer Genome Atlas (TCGA) is a publicly funded project that aims to catalog and discover major cancer-causing genomic alterations with the goal of creating a comprehensive ‘atlas’ of cancer genomic profiles. The availability of this genome-wide information provides an unprecedented opportunity to expand our knowledge of tumourigenesis. Computational analytics and mining are frequently used as effective tools for exploring this byzantine series of biological and biomedical data. However, some of the more advanced computational tools are often difficult to understand or use, thereby limiting their application by scientists who do not have a strong computational background. Hence, it is of great importance to build user-friendly interfaces that allow both computational scientists and life scientists without a computational background to gain greater biological and medical insights. To that end, this survey was designed to systematically present available Web-based tools and facilitate the use TCGA data for cancer research.

Integrative network modeling reveals mechanisms underlying T cell exhaustion

Failure to clear antigens causes CD8⁺ T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8⁺ T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier pro-memory/proliferative (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that drug-induced interference with EZH2 function increases the proportion of pro-memory/proliferative cells in the early days post-activation.

Pathway Commons 2019 Update: integration, analysis and exploration of pathway data

Pathway Commons (https://www.pathwaycommons.org) is an integrated resource of publicly available information about biological pathways including biochemical reactions, assembly of biomolecular complexes, transport and catalysis events and physical interactions involving proteins, DNA, RNA, and small molecules (e.g. metabolites and drug compounds). Data is collected from multiple providers in standard formats, including the Biological Pathway Exchange (BioPAX) language and the Proteomics Standards Initiative Molecular Interactions format, and then integrated. Pathway Commons provides biologists with (i) tools to search this comprehensive resource, (ii) a download site offering integrated bulk sets of pathway data (e.g. tables of interactions and gene sets), (iii) reusable software libraries for working with pathway information in several programming languages (Java, R, Python and Javascript) and (iv) a web service for programmatically querying the entire dataset. Visualization of pathways is supported using the Systems Biological Graphical Notation (SBGN). Pathway Commons currently contains data from 22 databases with 4794 detailed human biochemical processes (i.e. pathways) and ∼2.3 million interactions. To enhance the usability of this large resource for end-users, we develop and maintain interactive web applications and training materials that enable pathway exploration and advanced analysis.

ZDOG: zooming in on dominating genes with mutations in cancer pathways

Background

Inference of cancer-causing genes and their biological functions are crucial but challenging due to the heterogeneity of somatic mutations. The heterogeneity of somatic mutations reveals that only a handful of oncogenes mutate frequently and a number of cancer-causing genes mutate rarely.

Results

We develop a Cytoscape app, named ZDOG, for visualization of the extent to which mutated genes may affect cancer pathways using the dominating tree model. The dominator tree model allows us to examine conveniently the positional importance of a gene in cancer signalling pathways. This tool facilitates the identification of mutated “master” regulators even with low mutation frequency in deregulated signalling pathways.

Conclusions

We have presented a model for facilitating the examination of the extent to which mutation in a gene may affect downstream components in a signalling pathway through its positional information. The model is implemented in a user-friendly Cytoscape app which will be freely available upon publication.

Availability

Together with a user manual, the ZDOG app is freely available at GitHub (https://github.com/rudi2013/ZDOG). It is also available in the Cytoscape app store (http://apps.cytoscape.org/apps/ZDOG) and users can easily install it using the Cytoscape App Manager.

Molecular characterization of lung adenocarcinoma from Korean patients using next generation sequencing

The treatment of Lung adenocarcinoma (LUAD) could benefit from the incorporation of precision medicine. This study was to identify cancer-related genetic alterations by next generation sequencing (NGS) in resected LUAD samples from Korean patients and to determine their associations with clinical features. A total of 201 tumors and their matched peripheral blood samples were analyzed using targeted sequencing via the Illumina HiSeq 2500 platform of 242 genes with a median depth of coverage greater than 500X. One hundred ninety-two tumors were amenable to data analysis. EGFR was the most frequently mutated gene, occurring in 106 (55%) patients, followed by TP53 (n = 67, 35%) and KRAS (n = 11, 6%). EGFR mutations were strongly increased in patients that were female and never-smokers. Smokers had a significantly higher tumor mutational burden (TMB) than never-smokers (average 4.84 non-synonymous mutations/megabase [mt/Mb] vs. 2.84 mt/Mb, p = 0.019). Somatic mutations of APC, CTNNB1, and AMER1 in the WNT signaling pathway were highly associated with shortened disease-free survival (DFS) compared to others (median DFS of 89 vs. 27 months, p = 0.018). Patients with low TMB, annotated as less than 2 mt/Mb, had longer DFS than those with high TMB (p = 0.041). A higher frequency of EGFR mutations and a lower of KRAS mutations were observed in Korean LUAD patients. Profiles of 242 genes mapped in this study were compared with whole exome sequencing genetic profiles generated in The Cancer Genome Atlas Lung Adenocarcinoma. NGS-based diagnostics can provide clinically relevant information such as mutations or TMB from readily available formalin-fixed paraffin-embedded tissue.

A comprehensive overview of oncogenic pathways in human cancer

Alterations of biological pathways can lead to oncogenesis. An overview of these oncogenic pathways would be highly valuable for researchers to reveal the pathogenic mechanism and develop novel therapeutic approaches for cancers. Here, we reviewed approximately 8500 literatures and documented experimentally validated cancer-pathway associations as benchmarking data set. This data resource includes 4709 manually curated relationships between 1557 paths and 49 cancers with 2427 upstream regulators in 7 species. Based on this resource, we first summarized the cancer-pathway associations and revealed some commonly deregulated pathways across tumor types. Then, we systematically analyzed these oncogenic pathways by integrating TCGA pan-cancer data sets. Multi-omics analysis showed oncogenic pathways may play different roles across tumor types under different omics contexts. We also charted the survival relevance landscape of oncogenic pathways in 26 tumor types, identified dominant omics features and found survival relevance for oncogenic pathways varied in tumor types and omics levels. Moreover, we predicted upstream regulators and constructed a hierarchical network model to understand the pathogenic mechanism of human cancers underlying oncogenic pathway context. Finally, we developed `CPAD’ (freely available at http://bio-bigdata.hrbmu.edu.cn/CPAD/), an online resource for exploring oncogenic pathways in human cancers, that integrated manually curated cancer-pathway associations, TCGA pan-cancer multi-omics data sets, drug–target data, drug sensitivity and multi-omics data for cancer cell lines. In summary, our study provides a comprehensive characterization of oncogenic pathways and also presents a valuable resource for investigating the pathogenesis of human cancer.

Integrative landscape of dysregulated signaling pathways of clinically distinct pancreatic cancer subtypes

Despite modern therapeutic advances, the survival prospects of pancreatic cancer patients have remained poor. Besides being highly metastatic, pancreatic cancer is challenging to treat because it is caused by a heterogeneous array of somatic mutations that impact a variety of signaling pathways and cellular regulatory systems. Here we use publicly available transcriptomic, copy number alteration and mutation profiling datasets from pancreatic cancer patients together with data on disease outcomes to show that the three major pancreatic cancer subtypes each display distinctive aberrations in cell signaling and metabolic pathways. Importantly, patients afflicted with these different pancreatic cancer subtypes also exhibit distinctive survival profiles. Within these patients, we find that dysregulation of the phosphoinositide 3-kinase and mitogen-activated protein kinase pathways, and p53 mediated disruptions of cell cycle processes are apparently drivers of disease. Further, we identify for the first time the molecular perturbations of signalling networks that are likely the primary causes of oncogenesis in each of the three pancreatic cancer subtypes.

Oncogenic Signaling Pathways in The Cancer Genome Atlas

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFβ signaling, p53 and β-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy.

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these "hidden responders" may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders.