scispace - formally typeset
R

Rehan Akbani

Researcher at University of Texas MD Anderson Cancer Center

Publications -  134
Citations -  106557

Rehan Akbani is an academic researcher from University of Texas MD Anderson Cancer Center. The author has contributed to research in topics: Gene & Cancer. The author has an hindex of 65, co-authored 124 publications receiving 84443 citations. Previous affiliations of Rehan Akbani include University of Texas at San Antonio & National Institutes of Health.

Papers
More filters

Integrated genomic characterization of endometrial carcinoma

Gad Getz, +271 more
Abstract: We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.
Proceedings ArticleDOI

A Hybrid Trust Management System for automated fine-grained access control

TL;DR: A new Hybrid Trust Management System (HTMS) that combines Role Based Trust Management (RBTM) with Reputation Systems (RS) and shows that HTMS performs very close to the ideal if it can accurately estimate the proportion of malicious nodes in the network.
Proceedings ArticleDOI

Abstract 3382: A pan-cancer analysis reveals high frequency genetic alterations in mediators of signaling by the TGF-β superfamily

TL;DR: The data suggest that TGF-β superfamily indices when combined with specific genes, such as HMGA2 and TERT , may represent strong prognostic markers, and targets in some cancer types such as HCC.