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Diri, B.

Publications and source records attributed to Diri, B..

2 recordsLinked to original sources

Comparative Proteogenomic Analysis of Right-sided Colon Cancer, Left-sided Colon Cancer and Rectal Cancers Reveal Distinct Mutational Profiles.

To understand the molecular differences between right-sided colon cancer (RCC), left-sided colon cancer (LCC) and rectal cancer, we analyzed colorectal tumors at the DNA, RNA, miRNA and protein levels using previously sequenced data from The Cancer Genome Atlas and Memorial Sloan Kettering Cancer Center. Clonal evolution analysis identified the same tumor-initiating events involving APC, KRAS and TP53 genes in RCC, LCC and rectal cancers. However, the individual role-played by each event, their order in tumor dynamics and selection of downstream mutations were distinct in all three anatomical locations, with some similarities noted between LCC and rectal cancer. We found a potentially targetable alteration APC R1450* specific to RCC that has not been previously described. Differential gene expression analysis revealed multiple genes within the homeobox, G-protein coupled receptor binding and transcription regulation families were dysregulated in RCC, LCC, and rectal cancers and may have a pathological role in these cancers. Further, using a novel in silico proteomic analytic tool developed by our research group, we found distinct central or hub proteins with unique interactomes in each location. Protein expression signatures were not necessarily concordant with the tumor profiles obtained at the DNA and RNA levels, underscoring the relevance of post-transcriptional events in defining the biology of these cancers beyond molecular changes at the DNA and/or RNA level. Ultimately, not only tumor location and the respective genomic profile but also protein-protein interactions will need to be taken into account to improve treatment outcomes of colorectal cancers. Further studies that take into account the alterations found in this study may help in developing more tailored, and perhaps more effective, treatment strategies.\n\nAuthor summaryPatients with right-sided colon cancer (RCC) has a worse prognosis compared to left-sided colon cancer (LCC). Recent data has also shown that wild-type RAS metastatic RCCs have poor outcomes when treated with the combination of chemotherapy and anti-EGFR therapy compared to LCC and rectal cancers. Therefore, There is an urgent unmet need to understand the molecular differences between RCC, LCC, and rectal cancers. In this study, we demonstrate clonal evolutionary trajectory and the order of mutations in RCC, LCC, and rectal cancers are distinct with some similarities between LCC and rectal cancers. The order of the mutations that lead to the acquisition of crucial driver alterations may have prognostic and therapeutic implications. We also discovered a novel targetable alteration, APC R1450* to be significantly enriched in early, late and metastatic RCC but not in LCC and rectal cancers. Amazingly, proteomic signatures were discordant with DNA and RNA levels. These distinct differences in DNA, RNA and post-transcriptional events may contribute to their unique clinicopathological features.\n\nConflict of Interest StatementAshiq Masood Advisory board and speaker Bureau Bristol-Myers Squibb and Boehringer Ingelheim\n\nJanakiraman Subramanian Advisory board - Astra Zeneca, Pfizer, Boehringer Ingelheim, Alexion, Paradigm, Bristol-Myers Squibb Speakers Bureau - Astra Zeneca, Boehringer Ingelheim, Lilly Research Support - Biocept and Paradigm\n\nArif Hussain Advisory board - Novartis, Bayer, Astra Zeneca Consultant - Bristol-Myers-Squibb All other authors have no conflict of interest.

genomics

A Scoring System to Evaluate the Impact of SNPs in a Path Related Context to Study Behçet’s Disease Aetiology in Japanese Population

MotivationGenome-wide association study (GWAS) is a powerful method that can provide a list of single nucleotide polymorphisms (SNPs) that are significantly related to the pathogenesis of a disease. Even though in Mendelian diseases strong associations can be found for certain SNPs, in most of the complex diseases only modest associations can be identified from the GWAS. Therefore, the main challenge in such studies is to understand how multiple SNPs that have modest association with the phenotype interact and contribute to its aetiology. This can only be done via pathway based analysis of modestly associated SNPs and the genes that are affected by these changes.\n\nResultsIn this study, we propose DAPath, a Disease Associated Path analyzer tool for discovering signaling paths and the pathways that contain these paths which are subjected to cumulative impact of modestly associated variants. We applied our proposed method on Behcets disease (BD) GWAS dataset from Japanese population. Antigen Processing and Presentation pathway is ranked first with 16 highly affected paths. Th17 cell differentiation, Natural killer cell mediated cytotoxicity, Jak-STAT signaling, and Circadian rhythm pathways are also found to be containing highly affected paths.\n\nAvailabilityThe proposed method is available as a Cytoscape plug-in through https://github.com/ozanozisik/DAPath

bioinformatics