scholarly journals Network-aware mutation clustering of cancer

2018 ◽  
Author(s):  
Swetansu Pattnaik ◽  
Catherine Vacher ◽  
Hong Ching Lee ◽  
Warren Kaplan ◽  
David M. Thomas ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Cancer Biology ◽  
Difficult Problem ◽  
The Cancer Genome Atlas ◽  
Precision Oncology ◽  
Protein Protein Interactions ◽  
Dna Mutation ◽  
Mutation Profile ◽  
Cancer Genome Atlas ◽  
Protein Modules

AbstractThe grouping of cancers across tissue boundaries is central to precision oncology, but remains a difficult problem. Here we present EPICC (Experimental Protein Interaction Clustering of Cancer), a novel technique to cluster cancer patients based on DNA mutation profile, that leverages knowledge of protein-protein interactions to reduce noise and amplify biological signal. We applied EPICC to data from The Cancer Genome Atlas (TCGA), and both recapitulated known cancer clusterings, and identified new cross-tissue cancer groups that may indicate novel cancer molecular subtypes. Investigation of EPICC clusters revealed new protein modules which were recurrently mutated across cancers, and indicate new avenues for research into cancer biology. EPICC leveraged the Vodafone DreamLab citizen science platform, and we provide our results as a resource for researchers to investigate the role of protein modules in cancer.

scholarly journals Small-molecule binding sites to explore protein–protein interactions in the cancer proteome

2016 ◽  
Vol 12 (10) ◽  
pp. 3067-3087 ◽  
Author(s):  
David Xu ◽  
Shadia I. Jalal ◽  
George W. Sledge ◽  
Samy O. Meroueh
Keyword(s):  
Small Molecule ◽  
Protein Interactions ◽  
Binding Sites ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Mrna Levels ◽  
Protein Protein Interactions ◽  
Poor Survival ◽  
Cancer Genome Atlas ◽  
Genome Atlas

The Cancer Genome Atlas (TCGA) offers an unprecedented opportunity to identify small-molecule binding sites on proteins with overexpressed mRNA levels that correlate with poor survival.

Mutational oncogenic signatures on structurally resolved protein interacting interfaces

2015 ◽  
Author(s):  
Luz Garcia-Alonso ◽  
Joaquin Dopazo
Keyword(s):  
Cancer Patients ◽  
Protein Interactions ◽  
Three Dimensional ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interactions ◽  
Cancer Occurrence ◽  
Domain Interactions ◽  
Cancer Mutations ◽  
Cancer Genome Atlas

The importance of the context of interactions in the proteins mutated in cancer is long known. However, our knowledge on how mutations affecting to protein-protein interactions (PPIs) are related to cancer occurrence and progression is still poor. Here, we extracted the missense somatic mutations from 5920 cancer patients of 33 different cancer types, taken from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), and mapped them onto a structurally resolved interactome, which integrates three-dimensional atomic-level models of domain-domain interactions with experimentally determined PPIs, involving a total of 7580 unique interacting domains that participate in 13160 interactions connecting 4996 proteins. We observed that somatic nonsynonymous mutations tend to concentrate in ordered regions of the affected proteins and, within these, they have a clear preference for the interacting interfaces. Also, we have identified more than 250 interacting interfaces candidate to drive cancer. Examples demonstrate how mutations in the interacting interfaces are strongly associated with patient survival time, while similar mutations in other areas of the same proteins lack this association. Our results suggest that the perturbation caused by cancer mutations in protein interactions is an important factor in explaining the heterogeneity between cancer patients.

scholarly journals Systematic Discovery of the Functional Impact of Somatic Genome Alterations in Individual Tumors through Tumor-specific Causal Inference

2018 ◽  
Author(s):  
Chunhui Cai ◽  
Gregory F. Cooper ◽  
Kevin N. Lu ◽  
Xiaojun Ma ◽  
Shuping Xu ◽  
...  
Keyword(s):  
Causal Inference ◽  
Cancer Biology ◽  
The Cancer Genome Atlas ◽  
Precision Oncology ◽  
Causal Relationships ◽  
Functional Impact ◽  
Disease Mechanisms ◽  
Cancer Genome Atlas ◽  
Somatic Genome ◽  
Molecular Phenotypes

AbstractWe report a tumor-specific causal inference (TCI) framework, which discovers causative somatic genome alterations (SGAs) through inferring causal relationships between SGAs and molecular phenotypes (e.g., transcriptomic, proteomic, or metabolomic changes) within an individual tumor. We applied the TCI algorithm to tumors from The Cancer Genome Atlas (TCGA) and identified those SGAs that causally regulate the differentially expressed genes (DEGs) within each tumor. Overall, TCI identified 634 SGAs that cause cancer-related DEGs in a significant number of tumors, including most of the previously known drivers and many novel candidate cancer drivers. The inferred causal relationships are statistically robust and biologically sensible, and multiple lines of experimental evidence support the predicted functional impact of both well-known and novel candidate drivers. By identifying major candidate drivers and revealing their functional impact in a tumor, TCI shed light on disease mechanisms of each tumor, providing useful information for advancing cancer biology and precision oncology.Significance statementsCancer is mainly caused by SGAs. Precision oncology involves identifying and targeting tumor-specific aberrations resulting from causative SGAs. TCI is a novel computational framework for discovering the causative SGAs and their impact on oncogenic processes, thus revealing tumor-specific disease mechanisms. This information can be used to guide precision oncology.

scholarly journals Integrated Dissection of lncRNA-Perturbated Triplets Reveals Novel Prognostic Signatures Across Cancer Types

2020 ◽  
Vol 21 (17) ◽  
pp. 6087
Author(s):  
Yunzhen Wei ◽  
Limeng Zhou ◽  
Yingzhang Huang ◽  
Dianjing Guo
Keyword(s):  
Cancer Biology ◽  
Noncoding Rna ◽  
The Cancer Genome Atlas ◽  
Dynamic Changes ◽  
Computational Framework ◽  
Potential Biomarker ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tcga Dataset ◽  
Pan Cancer

Long noncoding RNA (lncRNA)/microRNA(miRNA)/mRNA triplets contribute to cancer biology. However, identifying significative triplets remains a major challenge for cancer research. The dynamic changes among factors of the triplets have been less understood. Here, by integrating target information and expression datasets, we proposed a novel computational framework to identify the triplets termed as “lncRNA-perturbated triplets”. We applied the framework to five cancer datasets in The Cancer Genome Atlas (TCGA) project and identified 109 triplets. We showed that the paired miRNAs and mRNAs were widely perturbated by lncRNAs in different cancer types. LncRNA perturbators and lncRNA-perturbated mRNAs showed significantly higher evolutionary conservation than other lncRNAs and mRNAs. Importantly, the lncRNA-perturbated triplets exhibited high cancer specificity. The pan-cancer perturbator OIP5-AS1 had higher expression level than that of the cancer-specific perturbators. These lncRNA perturbators were significantly enriched in known cancer-related pathways. Furthermore, among the 25 lncRNA in the 109 triplets, lncRNA SNHG7 was identified as a stable potential biomarker in lung adenocarcinoma (LUAD) by combining the TCGA dataset and two independent GEO datasets. Results from cell transfection also indicated that overexpression of lncRNA SNHG7 and TUG1 enhanced the expression of the corresponding mRNA PNMA2 and CDC7 in LUAD. Our study provides a systematic dissection of lncRNA-perturbated triplets and facilitates our understanding of the molecular roles of lncRNAs in cancers.

scholarly journals Identification of novel alternative splicing isoform biomarkers and their association with overall survival in colorectal cancer

2019 ◽  
Author(s):  
Hongtao Jia ◽  
Aili Wang ◽  
Haifeng Lian ◽  
Yuanyuan Shen ◽  
Qian Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Alternative Splicing ◽  
Cancer Biology ◽  
The Cancer Genome Atlas ◽  
Normal Tissues ◽  
Eukaryotic Gene ◽  
Cancer Genome Atlas ◽  
Alternative Splicing Events ◽  
Therapeutic Tools

Abstract Alternative splicing is an important mechanism of regulating eukaryotic gene expression. Understanding the most common alternative splicing events in colorectal cancer (CRC) will help developing diagnostic, prognostic or therapeutic tools in CRC. Publicly available RNA-seq data of 31 pairs of CRC and normal tissues and 18 pairs of metastatic and normal tissues were used to identify alternative splicing events using PSI and DEXSeq methods. The highly significant splicing events were used to search a database of The Cancer Genome Atlas (TCGA). We identified alternative splicing events in 10 genes marking the signature of CRC (more inclusion of CLK1-E4, COL6A3-E6, CD44v8-10, alternative first exon regulation of ARHGEF9, CHEK1, HKDC1 and HNF4A) or metastasis (decrease of SERPINA1-E1a, CALD-E5b, E6 and FBLN2-E9). Except for CHEK1, all other 9 splicing events were confirmed by TCGA data with 382 CRC tumors and 52 normal controls. Two splicing events (COL6A3 and HKDC1) were found to be significantly associated with patient overall survival. The alternative splicing signatures of the 10 genes are highly consistent with previous reports and/or relevant to cancer biology. The significant association of higher expression of the COL6A3 E5-E6 junction and HKDC1 E1-E2 with better overall survival was firstly reported. This study might be of significant value in the future biomarker, prognosis marker and therapeutics development of CRC.

Genomic profiling of circulating tumor DNA (ctDNA) from patients (pts) with pancreatic ductal adenocarcinoma (PDA).

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 4128-4128
Author(s):  
Nathan Bahary ◽  
Jie He ◽  
Mark Bailey ◽  
Shan Zhong ◽  
Gerald Li ◽  
...  
Keyword(s):  
Cancer Biology ◽  
Clinical Care ◽  
Circulating Tumor Dna ◽  
The Cancer Genome Atlas ◽  
Ductal Adenocarcinoma ◽  
Genomic Profiling ◽  
Tissue Samples ◽  
Comprehensive Genomic Profiling ◽  
Cancer Genome Atlas ◽  
Genomic Characterization

4128 Background: PDA is a lethal and increasingly common malignancy and tissue samples for genomic characterization may be limited. As PDA has a high and consistent frequency of KRAS, p53 and CDKN2A mutations it serves as a robust indication to test the utility of ctDNA in accurately characterizing genomic alterations (GA). A prior study suggested significant differences between ctDNA and tissue base profiling but assays were not conducted on the same platform (PMID27833075). We undertook this study to see whether ctDNA could recapitulate the known genomic hallmarks of tumor based profiling. Methods: Hybrid-capture based genomic profiling of 62 genes (FoundationACT) was performed on ctDNA from 78 pts with advanced PDA with samples received in the course of clinical care. The fraction of ctDNA in the blood was estimated using the maximum somatic allele frequency (MSAF) for each sample. Frequencies of alterations in these common drivers were then compared to those seen in tumors of pts who underwent comprehensive genomic profiling (CGP) tissue testing performed on the same core platform, FoundationOne, and The Cancer Genome Atlas (TCGA). Results: Pt characteristics: Median age 65 (range, 47-88); Female (33) /Male (45). FoundationACT results show that 53/78 (68%) cases had MSAF >0 (56%-78%%, 95% CI). ≥1 GA was reported in 81% of the cases with evidence of ctDNA in the blood. The most common GA detected by FoundationACT (based on cases with evidence of ctDNA in blood) vs FoundationOne were in KRAS (59% vs 89%, p< 0.0001), TP53 (69% vs.74%, p=0.19), and CDKN2A (14% vs.45%). Other detected clinically relevant GA detected by FoundationACT included: BRCA1, ERBB2, NF1, PIK3CA. Conclusions: This study demonstrates significant differences between the established driver oncogenic alterations for PDA, as assessed by ct DNA and tissue based genomic profiling which are unlikely to be explained by differences in assay, but rather novel cancer biology. At present use of ctDNA genomic profiling in PDA should not routinely replace tissue based genomic characterization. [Table: see text]

scholarly journals Deciphering biological evolution exploiting the topology of Protein Locality Graph

2021 ◽  
Author(s):  
Barnali Das ◽  
Pralay Mitra
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Biological Networks ◽  
Biological Evolution ◽  
Interaction Network ◽  
Computational Time ◽  
Protein Protein Interactions ◽  
Power Graph ◽  
New Evidence ◽  
Protein Modules

The conventional sequence comparison-based evolutionary studies ignore other evolutionary constraints like interaction among proteins, functions of proteins and genes etc. A lot of speculations exist in literature regarding the presence of species divergence at the level of the Protein Interaction Networks. Additionally, it has been conjectured that the intra-module connections stay conserved whereas the inter-module connections change during evolution. The most important components of the biological networks are the functional modules which are more conserved among the evolutionary closer species. Here, we demonstrate an alternative method to decipher biological evolution by exploiting the topology of a spatially localized Protein Interaction Network called Protein Locality Graph (PLG). Our lossless graph compression from PLG to a power graph called Protein Cluster Interaction Network (PCIN) results in a 90% size reduction and aids in improving computational time. Further, we exploit the topology of PCIN and demonstrate our capability of deriving the correct species tree by focusing on the cross-talk between the protein modules exclusively. Our results provide new evidence that traces of evolution are not only present at the level of the Protein-Protein Interactions, but are also very much present at the level of the inter-module interactions.

scholarly journals Protein–protein interactions and protein modules in the control of neurotransmitter release

1999 ◽  
Vol 354 (1381) ◽  
pp. 243-257 ◽  
Author(s):  
Fabio Benfenati ◽  
Franco Onofri ◽  
Silvia Giovedí
Keyword(s):  
Synaptic Vesicle ◽  
Protein Interactions ◽  
Neurotransmitter Release ◽  
Synaptic Vesicles ◽  
Physiological Role ◽  
Presynaptic Membrane ◽  
Protein Protein Interactions ◽  
Sequence Of Events ◽  
Reserve Pool ◽  
Protein Modules

Information transfer among neurons is operated by neurotransmitters stored in synaptic vesicles and released to the extracellular space by an efficient process of regulated exocytosis. Synaptic vesicles are organized into two distinct functional pools, a large reserve pool in which vesicles are restrained by the actin–based cytoskeleton, and a quantitatively smaller releasable pool in which vesicles approach the presynaptic membrane and eventually fuse with it on stimulation. Both synaptic vesicle trafficking and neurotransmitter release depend on a precise sequence of events that include release from the reserve pool, targeting to the active zone, docking, priming, fusion and endocytotic retrieval of synaptic vesicles. These steps are mediated by a series of specific interactions among cytoskeletal, synaptic vesicle, presynaptic membrane and cytosolic proteins that, by acting in concert, promote the spatial and temporal regulation of the exocytotic machinery. The majority of these interactions are mediated by specific protein modules and domains that are found in many proteins and are involved in numerous intracellular processes. In this paper, the possible physiological role of these multiple protein–protein interactions is analysed, with ensuing updating and clarification of the present molecular model of the process of neurotransmitter release.

scholarly journals Phenotype and target-based chemical biology investigations in cancers

2018 ◽  
Vol 6 (6) ◽  
pp. 1111-1127 ◽  
Author(s):  
Guo-Qiang Chen ◽  
Ying Xu ◽  
Shao-Ming Shen ◽  
Jian Zhang
Keyword(s):  
Protein Interactions ◽  
Cancer Biology ◽  
Chemical Biology ◽  
Molecular Mechanisms ◽  
Target Identification ◽  
Expression System ◽  
Protein Protein Interactions ◽  
Anticancer Compounds ◽  
Protein Protein Interaction ◽  
Mechanisms Of Carcinogenesis

Abstract Chemical biology has been attracting a lot of attention because of the key roles of chemical methods and techniques in helping to decipher and manipulate biological systems. Although chemical biology encompasses a broad field, this review will focus on chemical biology aimed at using exogenous chemical probes to interrogate, modify and manipulate biological processes, at the cellular and organismal levels, in a highly controlled and dynamic manner. In this area, many advances have been achieved for cancer biology and therapeutics, from target identification and validation based on active anticancer compounds (forward approaches) to discoveries of anticancer molecules based on some important targets including protein-protein interaction (reverse approaches). Herein we attempt to summarize some recent progresses mainly from China through applying chemical biology approaches to explore molecular mechanisms of carcinogenesis. Additionally, we also outline several new strategies for chemistry to probe cellular activities such as proximity-dependent labeling methods for identifying protein-protein interactions, genetically encoded sensors, and light activating or repressing gene expression system.

scholarly journals Identification of novel alternative splicing isoform biomarkers and their association with overall survival in colorectal cancer

2019 ◽  
Author(s):  
Haifeng Lian ◽  
Aili Wang ◽  
Yuanyuan Shen ◽  
Qian Wang ◽  
Zhenru Zhou ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Alternative Splicing ◽  
Cancer Biology ◽  
The Cancer Genome Atlas ◽  
Normal Tissues ◽  
Eukaryotic Gene ◽  
Cancer Genome Atlas ◽  
Alternative Splicing Events ◽  
Therapeutic Tools

Abstract Alternative splicing is an important mechanism of regulating eukaryotic gene expression. Understanding the most common alternative splicing events in colorectal cancer (CRC) will help developing diagnostic, prognostic or therapeutic tools in CRC. Publicly available RNA-seq data of 31 pairs of CRC and normal tissues and 18 pairs of metastatic and normal tissues were used to identify alternative splicing events using PSI and DEXSeq methods. The highly significant splicing events were used to search a database of The Cancer Genome Atlas (TCGA). We identified alternative splicing events in 10 genes marking the signature of CRC (more inclusion of CLK1-E4, COL6A3-E6, CD44v8-10, alternative first exon regulation of ARHGEF9, CHEK1, HKDC1 and HNF4A) or metastasis (decrease of SERPINA1-E1a, CALD-E5b, E6 and FBLN2-E9). Except for CHEK1, all other 9 splicing events were confirmed by TCGA data with 382 CRC tumors and 52 normal controls. Two splicing events (COL6A3 and HKDC1) were found to be significantly associated with patient overall survival. The alternative splicing signatures of the 10 genes are highly consistent with previous reports and/or relevant to cancer biology. The significant association of higher expression of the COL6A3 E5-E6 junction and HKDC1 E1-E2 with better overall survival was firstly reported. This study might be of significant value in the future biomarker, prognosis marker and therapeutics development of CRC.

Sign in / Sign up

Export Citation Format

Share Document