scholarly journals A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes

2016 ◽  
Vol 23 (4) ◽  
pp. 681-691 ◽  
Author(s):  
Feixiong Cheng ◽  
Junfei Zhao ◽  
Michaela Fooksa ◽  
Zhongming Zhao
Keyword(s):  
Drug Repositioning ◽  
Human Cancer ◽  
Cancer Therapeutics ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Underlying Assumption ◽  
Cancer Genomes ◽  
Cancer Types ◽  
Druggable Targets ◽  
Integrative Network

Abstract Objective Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics. Methods We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network. Results We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1). Conclusions In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics.

scholarly journals Pan-cancer analyses of human nuclear receptors reveal transcriptome diversity and prognostic value across cancer types

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Toshima Z. Parris
Keyword(s):  
Human Cancer ◽  
The Cancer Genome Atlas ◽  
Transcriptional Networks ◽  
Cancer Type ◽  
Sequencing Data ◽  
Pairwise Correlation ◽  
Organ Systems ◽  
Cancer Types ◽  
Disease Stratification ◽  
Pan Cancer

AbstractThe human nuclear receptor (NR) superfamily comprises 48 ligand-dependent transcription factors that play regulatory roles in physiology and pathophysiology. In cancer, NRs have long served as predictors of disease stratification, treatment response, and clinical outcome. The Cancer Genome Atlas (TCGA) Pan-Cancer project provides a wealth of genetic data for a large number of human cancer types. Here, we examined NR transcriptional activity in 8,526 patient samples from 33 TCGA ‘Pan-Cancer’ diseases and 11 ‘Pan-Cancer’ organ systems using RNA sequencing data. The web-based Kaplan-Meier (KM) plotter tool was then used to evaluate the prognostic potential of NR gene expression in 21/33 cancer types. Although, most NRs were significantly underexpressed in cancer, NR expression (moderate to high expression levels) was predominantly restricted (46%) to specific tissues, particularly cancers representing gynecologic, urologic, and gastrointestinal ‘Pan-Cancer’ organ systems. Intriguingly, a relationship emerged between recurrent positive pairwise correlation of Class IV NRs in most cancers. NR expression was also revealed to play a profound effect on patient overall survival rates, with ≥5 prognostic NRs identified per cancer type. Taken together, these findings highlighted the complexity of NR transcriptional networks in cancer and identified novel therapeutic targets for specific cancer types.

scholarly journals Cellular Fitness Phenotypes of Cancer Target Genes from Oncobiology to Cancer Therapeutics

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 433
Author(s):  
Bijesh George ◽  
P. Mukundan Pillai ◽  
Aswathy Mary Paul ◽  
Revikumar Amjesh ◽  
Kim Leitzel ◽  
...  
Keyword(s):  
Drug Targets ◽  
Target Genes ◽  
Human Cancer ◽  
Cancer Therapeutics ◽  
Survival Duration ◽  
Cancer Drug ◽  
Targeted Therapeutics ◽  
Cellular Targets ◽  
Human Cancer Cells ◽  
Cancer Types

To define the growing significance of cellular targets and/or effectors of cancer drugs, we examined the fitness dependency of cellular targets and effectors of cancer drug targets across human cancer cells from 19 cancer types. We observed that the deletion of 35 out of 47 cellular effectors and/or targets of oncology drugs did not result in the expected loss of cell fitness in appropriate cancer types for which drugs targeting or utilizing these molecules for their actions were approved. Additionally, our analysis recognized 43 cellular molecules as fitness genes in several cancer types in which these drugs were not approved, and thus, providing clues for repurposing certain approved oncology drugs in such cancer types. For example, we found a widespread upregulation and fitness dependency of several components of the mevalonate and purine biosynthesis pathways (currently targeted by bisphosphonates, statins, and pemetrexed in certain cancers) and an association between the overexpression of these molecules and reduction in the overall survival duration of patients with breast and other hard-to-treat cancers, for which such drugs are not approved. In brief, the present analysis raised cautions about off-target and undesirable effects of certain oncology drugs in a subset of cancers where the intended cellular effectors of drug might not be good fitness genes and that this study offers a potential rationale for repurposing certain approved oncology drugs for targeted therapeutics in additional cancer types.

Exome-Wide Pan-Cancer Analysis of Germline Variants in 8,719 Individuals Finds Little Evidence of Rare Variant Associations

2021 ◽  
pp. 1-10
Author(s):  
Zoe Guan ◽  
Ronglai Shen ◽  
Colin B. Begg
Keyword(s):  
Rare Variant ◽  
Rare Variants ◽  
Association Studies ◽  
The Cancer Genome Atlas ◽  
Considerable Proportion ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Risk Variants ◽  
Cancer Types ◽  
Pan Cancer

<b><i>Background:</i></b> Many cancer types show considerable heritability, and extensive research has been done to identify germline susceptibility variants. Linkage studies have discovered many rare high-risk variants, and genome-wide association studies (GWAS) have discovered many common low-risk variants. However, it is believed that a considerable proportion of the heritability of cancer remains unexplained by known susceptibility variants. The “rare variant hypothesis” proposes that much of the missing heritability lies in rare variants that cannot reliably be detected by linkage analysis or GWAS. Until recently, high sequencing costs have precluded extensive surveys of rare variants, but technological advances have now made it possible to analyze rare variants on a much greater scale. <b><i>Objectives:</i></b> In this study, we investigated associations between rare variants and 14 cancer types. <b><i>Methods:</i></b> We ran association tests using whole-exome sequencing data from The Cancer Genome Atlas (TCGA) and validated the findings using data from the Pan-Cancer Analysis of Whole Genomes Consortium (PCAWG). <b><i>Results:</i></b> We identified four significant associations in TCGA, only one of which was replicated in PCAWG (BRCA1 and ovarian cancer). <b><i>Conclusions:</i></b> Our results provide little evidence in favor of the rare variant hypothesis. Much larger sample sizes may be needed to detect undiscovered rare cancer variants.

scholarly journals Landscape of Microsatellite Instability Across 39 Cancer Types

2017 ◽  
pp. 1-15 ◽  
Author(s):  
Russell Bonneville ◽  
Melanie A. Krook ◽  
Esko A. Kautto ◽  
Jharna Miya ◽  
Michele R. Wing ◽  
...  
Keyword(s):  
Microsatellite Instability ◽  
Mismatch Repair ◽  
Human Cancer ◽  
The Cancer Genome Atlas ◽  
Repair System ◽  
Multiple Cancer ◽  
External Data ◽  
Mismatch Repair System ◽  
Cancer Types ◽  
Genomic Microsatellites

Purpose Microsatellite instability (MSI) is a pattern of hypermutation that occurs at genomic microsatellites and is caused by defects in the mismatch repair system. Mismatch repair deficiency that leads to MSI has been well described in several types of human cancer, most frequently in colorectal, endometrial, and gastric adenocarcinomas. MSI is known to be both predictive and prognostic, especially in colorectal cancer; however, current clinical guidelines only recommend MSI testing for colorectal and endometrial cancers. Therefore, less is known about the prevalence and extent of MSI among other types of cancer. Methods Using our recently published MSI-calling software, MANTIS, we analyzed whole-exome data from 11,139 tumor-normal pairs from The Cancer Genome Atlas and Therapeutically Applicable Research to Generate Effective Treatments projects and external data sources across 39 cancer types. Within a subset of these cancer types, we assessed mutation burden, mutational signatures, and somatic variants associated with MSI. Results We identified MSI in 3.8% of all cancers assessed—present in 27 of tumor types—most notably adrenocortical carcinoma (ACC), cervical cancer (CESC), and mesothelioma, in which MSI has not yet been well described. In addition, MSI-high ACC and CESC tumors were observed to have a higher average mutational burden than microsatellite-stable ACC and CESC tumors. Conclusion We provide evidence of as-yet-unappreciated MSI in several types of cancer. These findings support an expanded role for clinical MSI testing across multiple cancer types as patients with MSI-positive tumors are predicted to benefit from novel immunotherapies in clinical trials.

scholarly journals Cellular Fitness Phenotypes of Cancer Target Genes in Cancer Therapeutics

2019 ◽  
Author(s):  
Bijesh George ◽  
P. Mukundan Pillai ◽  
Aswathy Mary Paul ◽  
Kim Leitzel ◽  
Suhail M. Ali ◽  
...  
Keyword(s):  
Drug Targets ◽  
Target Genes ◽  
Human Cancer ◽  
Cancer Therapeutics ◽  
Survival Duration ◽  
Cancer Drug ◽  
Cellular Targets ◽  
Human Cancer Cells ◽  
Cancer Types ◽  
Approved Drugs

AbstractTo define the growing significance of cellular targets of targeted cancer drugs, we examined the fitness dependency of cancer drug targets across human cancer cells in a CRISPR-Cas9 fitness screening dataset wherein cellular genes were selectively knocked out before assaying for their fitness dependency in cancer cell lines representing 19 cancer types. We observed that the deletion of 35 out of 47 fitness targets of oncology drugs did not result in the expected loss of cell fitness in appropriate cancer types for which drugs targeting these molecules were approved. This raised the possibility of undesirable off-target effects of these drugs in such cancers. Additionally, our analysis recognized 43 drug targets which were fitness genes observed in several cancer types as candidate targets for repurposing approved oncology drugs in cancer types in which these drugs were not approved. For example, we found the widespread upregulation and fitness dependency of the components of the mevalonate and purine biosynthesis pathways (currently targeted by bisphosphonates, statins, and pemetrexed in certain cancers) and an association between the overexpression of these targets and reduction in the overall survival duration of patients with breast and other hard-to-treat cancers, for which these drugs are not approved. In brief, the present analysis raised cautions about off-target and undesirable effects of certain oncology drugs in a subset of cancers where the intended drug targets are not fitness genes. The study also offers a rationale for repurposing approved oncology drugs for cancer types that have significant fitness dependency on cellular targets of such approved drugs.

scholarly journals Identifying and characterizing lincRNA genomic clusters reveals its cooperative functions in human cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hanxiao Zhou ◽  
Yue Gao ◽  
Xin Li ◽  
Shipeng Shang ◽  
Peng Wang ◽  
...  
Keyword(s):  
Human Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Pathophysiological Mechanism ◽  
Multiple Cancer ◽  
Cancer Types ◽  
Genomic Clusters

Abstract Background Emerging evidence has revealed that some long intergenic non-coding RNAs (lincRNAs) are likely to form clusters on the same chromosome, and lincRNA genomic clusters might play critical roles in the pathophysiological mechanism. However, the comprehensive investigation of lincRNA clustering is rarely studied, particularly the characterization of their functional significance across different cancer types. Methods In this study, we firstly constructed a computational method basing a sliding window approach for systematically identifying lincRNA genomic clusters. We then dissected these lincRNA genomic clusters to identify common characteristics in cooperative expression, conservation among divergent species, targeted miRNAs, and CNV frequency. Next, we performed comprehensive analyses in differentially-expressed patterns and overall survival outcomes for patients from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) across multiple cancer types. Finally, we explored the underlying mechanisms of lincRNA genomic clusters by functional enrichment analysis, pathway analysis, and drug-target interaction. Results We identified lincRNA genomic clusters according to the algorithm. Clustering lincRNAs tended to be co-expressed, highly conserved, targeted by more miRNAs, and with similar deletion and duplication frequency, suggesting that lincRNA genomic clusters may exert their effects by acting in combination. We further systematically explored conserved and cancer-specific lincRNA genomic clusters, indicating they were involved in some important mechanisms of disease occurrence through diverse approaches. Furthermore, lincRNA genomic clusters can serve as biomarkers with potential clinical significance and involve in specific pathological processes in the development of cancer. Moreover, a lincRNA genomic cluster named Cluster127 in DLK1-DIO3 imprinted locus was discovered, which contained MEG3, MEG8, MEG9, MIR381HG, LINC02285, AL132709.5, and AL132709.1. Further analysis indicated that Cluster127 may have the potential for predicting prognosis in cancer and could play their roles by participating in the regulation of PI3K-AKT signaling pathway. Conclusions Clarification of the lincRNA genomic clusters specific roles in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types.

scholarly journals Epigenetic silencing of lncRNA MORT in 16 TCGA cancer types

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 211 ◽  
Author(s):  
Lukas Vrba ◽  
Bernard W. Futscher
Keyword(s):  
Dna Methylation ◽  
Mammary Epithelial Cells ◽  
Human Cancer ◽  
Large Fraction ◽  
Cell Types ◽  
Mammary Epithelial ◽  
The Cancer Genome Atlas ◽  
Human Mammary Epithelial ◽  
Cancer Types

We have previously described a hominid-specific long non-coding RNA, MORT (also known as ZNF667-AS1, Gene ID: 100128252), which is expressed in all normal cell types, but epigenetically silenced during cancer-associated immortalization of human mammary epithelial cells.  Initial analysis of The Cancer Genome Atlas (TCGA) showed that 15 of 17 cancer types, which represent the 10 most common cancers in women and men, display DNA methylation associated MORT silencing in a large fraction of their tumors.  In this study we analyzed MORT expression and DNA methylation state in the remaining 16 TCGA cancer types not previously reported.  Seven of the 16 cancer types showed DNA methylation linked MORT silencing in a large fraction of their tumors.  These are carcinomas (cervical cancer, and cancers of esophagus, stomach, and bile duct), and the non-epithelial tumors mesothelioma, sarcoma, and uterine carcinosarcoma.  Together with the findings from our previous report, MORT expression is silenced by aberrant DNA methylation in 22 of 33 of TCGA cancer types.  These 22 cancers include most carcinoma types, blood derived cancers and sarcomas.  In conclusion, results suggest that the MORT gene is one of the most common epigenetic aberrations seen in human cancer.  Coupled with the timing of MORT gene silencing during in vitro epithelial cell immortalization and its occurrence early in the temporal arc of human carcinogenesis, this provides strong circumstantial evidence for a tumor suppressor role for MORT.

scholarly journals My personal mutanome: a computational genomic medicine platform for searching network perturbing alleles linking genotype to phenotype

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yadi Zhou ◽  
Junfei Zhao ◽  
Jiansong Fang ◽  
William Martin ◽  
Lang Li ◽  
...  
Keyword(s):  
Posttranslational Modifications ◽  
Genomic Medicine ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Protein Binding Sites ◽  
Functional Sites ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Protein Posttranslational Modifications

AbstractMassive genome sequencing data have inspired new challenges in personalized treatments and facilitated oncological drug discovery. We present a comprehensive database, My Personal Mutanome (MPM), for accelerating the development of precision cancer medicine protocols. MPM contains 490,245 mutations from over 10,800 tumor exomes across 33 cancer types in The Cancer Genome Atlas mapped to 94,563 structure-resolved/predicted protein-protein interaction interfaces (“edgetic”) and 311,022 functional sites (“nodetic”), including ligand-protein binding sites and 8 types of protein posttranslational modifications. In total, 8884 survival results and 1,271,132 drug responses are obtained for these mapped interactions. MPM is available at https://mutanome.lerner.ccf.org.

scholarly journals Single-cell analysis of a tumor-derived exosome signature correlates with prognosis and immunotherapy response

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jiani Wu ◽  
Dongqiang Zeng ◽  
Shimeng Zhi ◽  
Zilan Ye ◽  
Wenjun Qiu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Single Cell ◽  
Immune Modulation ◽  
Expression Profiles ◽  
Predictive Biomarkers ◽  
Disease Diagnosis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Cancer Types

Abstract Background Tumor-derived exosomes (TEXs) are involved in tumor progression and the immune modulation process and mediate intercellular communication in the tumor microenvironment. Although exosomes are considered promising liquid biomarkers for disease diagnosis, it is difficult to discriminate TEXs and to develop TEX-based predictive biomarkers. Methods In this study, the gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) database, IMvigor210 cohorts, and six independent Gene Expression Omnibus datasets. A TEXs-associated signature named TEXscore was established to predict overall survival in multiple cancer types and in patients undergoing immune checkpoint blockade therapies. Results Based on exosome-associated genes, we first constructed a tumor-derived exosome signature named TEXscore using a principal component analysis algorithm. In single-cell RNA-sequencing data analysis, ascending TEXscore was associated with disease progression and poor clinical outcomes. In the TCGA Pan-Cancer cohort, TEXscore was elevated in tumor samples rather than in normal tissues, thereby serving as a reliable biomarker to distinguish cancer from non-cancer sources. Moreover, high TEXscore was associated with shorter overall survival across 12 cancer types. TEXscore showed great potential in predicting immunotherapy response in melanoma, urothelial cancer, and renal cancer. The immunosuppressive microenvironment characterized by macrophages, cancer-associated fibroblasts, and myeloid-derived suppressor cells was associated with high TEXscore in the TCGA and immunotherapy cohorts. Besides, TEXscore-associated miRNAs and gene mutations were also identified. Further experimental research will facilitate the extending of TEXscore in tumor-associated exosomes. Conclusions TEXscore capturing tumor-derived exosome features might be a robust biomarker for prognosis and treatment responses in independent cohorts.

scholarly journals Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

2018 ◽  
Author(s):  
Isidro Cortés-Ciriano ◽  
June-Koo Lee ◽  
Ruibin Xi ◽  
Dhawal Jain ◽  
Youngsook L. Jung ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Human Cancer ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
End Joining ◽  
Cancer Types ◽  
Non Homologous End Joining

SummaryChromothripsis is a newly discovered mutational phenomenon involving massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in cancer suggest that chromothripsis may be far more common than initially inferred from low resolution DNA copy number data. Here, we analyze the patterns of chromothripsis across 2,658 tumors spanning 39 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of >50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy number states, a considerable fraction of the events involves multiple chromosomes as well as additional structural alterations. In addition to non-homologous end-joining, we detect signatures of replicative processes and templated insertions. Chromothripsis contributes to oncogene amplification as well as to inactivation of genes such as mismatch-repair related genes. These findings show that chromothripsis is a major process driving genome evolution in human cancer.

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