Page 54 - Hormel Report 2021

Rendong Yang, Ph.D.
“Identifying specific subtypes of prostate cancer and the distinct pattern of mutations associat- ed with them will enhance development of precise diagnostic tools that detect specific genetic aberrations, allowing doctors to reliably predict a patient’s outcome and prescribe per-
sonalized treatment.”
Rendong Yang
54 | THE HORMEL INSTITUTE // UNIVERSITY OF MINNESOTA Computational Cancer Genomics
SECTION LEADER / ASSISTANT PROFESSOR
Developing novel algorithms for indel detection. Our most recent work has been in the development of clinical genomic
variant detection pipelines for our customized on- cology gene panels in the University of Minnesota Molecular Diagnostic Lab. Briefly, we developed
a new algorithm named ScanIndel to accurately detect insertion and deletion (indel) mutations in human genome from next generation sequenc- ing data. In particular, ScanIndel reliably detects medium-size and large indels. With this method, indels contribute to pathogenesis of constitution- al and somatic diseases can be identified quickly and accurately which is important for targeted therapy or patient prognosis.
Detecting gene rearrangement, splicing and epigenetic regulator of AR in prostate cancer. We developed an integrated pipeline to detect structural rearrangements in the AR gene, which encodes the androgen receptor. Through this work, we identified diverse genomic-dependent and genomic-independent AR splicing variants
expressed in prostate cancer. Additionally, our early work focuses on prostate cancer epigenomic studies by analyzing the ChIP-seq data of AR and BRD4 in prostate cancer VCaP cell line. Our study revealed the crosstalk between AR and BRD4 signaling in prostate cancer progression.
Developing algorithms for detecting cancer biomarkers. We have been developing EgoNet algorithm by integrating gene expression micro- array data and protein interaction networks to identify network modules that can distinguishing different breast cancer subtypes.
Detecting novel indels from prostate cancer genome
We developed transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid- sized insertions and large deletions based on the linear alignments of split reads from DNA-seq