Biology subjects

Chia, B. K. H.

Publications and source records attributed to Chia, B. K. H..

2 recordsLinked to original sources

bioRxiv2018

Whole-Genome Genomics Correlates of Response To Anti-PD1 Therapy in Relapsed/Refractory Natural Killer/T Cell Lymphoma

AbstractThis study aims to identify recurrent genetic alterations in relapsed or refractory (RR) natural-killer/T-cell lymphoma (NKTL) patients who have achieved complete response (CR) with programmed cell death 1 (PD-1) blockade therapy. Seven of the eleven patients treated with pembrolizumab achieved CR while the remaining four had progressive disease (PD). Using whole genome sequencing (WGS), we found recurrent clonal structural rearrangements (SR) of the PD-L1 gene in four of the seven (57%) CR patients pretreated tumors. These PD-L1 SRs consist of inter-chromosomal translocations, tandem duplication and micro-inversion that disrupted the suppressive function of PD-L1 3UTR. Interestingly, recurrent JAK3-activating (p.A573V) mutations were also validated in two CR patients tumors that did not harbor the PD-L1 SR. Importantly, these mutations were absent in the four PD cases. With immunohistochemistry (IHC), PD-L1 positivity could not discriminate patients who archived CR (range: 6%-100%) from patients who had PD (range: 35%-90%). PD-1 blockade with pembrolizumab is a potent strategy for RR NKTL patients and genomic screening could potentially accompany PD-L1 IHC positivity to better select patients for anti-PD-1 therapy.

genomics↗

bioRxiv2017

Critical Assessment of Metagenome Interpretation - a benchmark of computational metagenomics software

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.

bioinformatics↗