Biology subjects

Chen, K. G.

Publications and source records attributed to Chen, K. G..

6 recordsLinked to original sources

bioRxiv2025

Uncovering biological patterns across studies through automated large-scale reanalyses of public transcriptomic data

Large amounts of transcriptomic data have been made available in public repositories. Systematic reanalyses of these data offer the potential to identifying conserved biological patterns or context-specific signatures. However, this is a labour intensive process requiring bioinformatic expertise and a long chain of manual decision making. Use of LLMs and agentic systems holds promise for automating these otherwise time-consuming tasks. Here, we present UORCA (Unified -Omics Reference Corpus of Analyses), a tool to systematically identify and analyse public transcriptomic datasets. UORCA uses an LLM-assisted framework to search for datasets relevant to a research question. These datasets are analysed through a multi-agent system that performs a standardised bioinformatic analyses to identify differentially expressed genes. Results of each analysis are then displayed in an interactive visual interface. We found that UORCA recapitulated findings reported from a manual comparison of datasets, but also found biological signatures that were not initially described. We find that UORCA generates targeted hypotheses relevant for drug design, and facilitates evaluation of experimental results where they differ from past literature. Together, these findings demonstrate how UORCA accelerates biomedical discovery by enabling scientists to extract actionable findings from diverse public datasets.

bioinformatics↗

bioRxiv2024

Metabolic Quadrivalency in RSeT Human Embryonic Stem Cells

One of the most important properties of human embryonic stem cells (hESCs) is related to their pluripotent states. In our recent study, we identified a previously unrecognized pluripotent state induced by RSeT medium. This state makes primed hESCs resistant to conversion to naive pluripotent state. In this study, we have further characterized the metabolic features in these RSeT hESCs, including metabolic gene expression, metabolomic analysis, and various functional assays. The commonly reported metabolic modes include glycolysis or both glycolysis and oxidative phosphorylation (i.e., metabolic bivalency) in pluripotent stem cells. However, besides the presence of metabolic bivalency, RSeT hESCs exhibited a unique metabolome with additional fatty acid oxidation and imbalanced nucleotide metabolism. This metabolic quadrivalency is linked to hESC growth independent of oxygen tension and restricted capacity for naive reprogramming in these cells. Thus, this study provides new insights into pluripotent state transitions and metabolic stress-associated hPSC growth in vitro.

biochemistry↗

bioRxiv2024

Resistance to Naive and Formative Pluripotency Conversion in RSeT Human Embryonic Stem Cells

One of the most important properties of human embryonic stem cells (hESCs) is related to their primed and naive pluripotent states. Our previous meta-analysis indicates the existence of heterogeneous pluripotent states derived from diverse naive protocols. In this study, we have characterized a commercial medium (RSeT)-based pluripotent state under various growth conditions. Notably, RSeT hESCs can circumvent hypoxic growth conditions as required by naive hESCs, in which some RSeT cells (e.g., H1 cells) exhibit much lower single cell plating efficiency, having altered or much retarded cell growth under both normoxia and hypoxia. Evidently, hPSCs lack many transcriptomic hallmarks of naive and formative pluripotency (a phase between naive and primed states). Integrative transcriptome analysis suggests our primed and RSeT hESCs are close to the early stage of post-implantation embryos, similar to the previously reported primary hESCs and early hESC cultures. Moreover, RSeT hESCs did not express naive surface markers such as CD75, SUSD2, and CD130 at a significant level. Biochemically, RSeT hESCs exhibit a differential dependency of FGF2 and co-independency of both Janus kinase (JAK) and TGF{beta} signaling in a cell-line-specific manner. Thus, RSeT hESCs represent a previously unrecognized pluripotent state downstream of formative pluripotency. Our data suggest that human naive pluripotent potentials may be restricted in RSeT medium. Hence, this study provides new insights into pluripotent state transitions in vitro.

cell biology↗

bioRxiv2020

Multivariate Meta-Analysis of Differential Principal Components underlying Human Primed and Naive-like Pluripotent States

The ground or naive pluripotent state of human pluripotent stem cells (hPSCs), which was initially established in mouse embryonic stem cells (mESCs), is an emerging and tentative concept. To verify this important concept in hPSCs, we performed a multivariate meta-analysis of major hPSC datasets via the combined analytic powers of percentile normalization, principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and SC3 consensus clustering. This vigorous bioinformatics approach has significantly improved the predictive values of the current meta-analysis. Accordingly, we were able to reveal various similarities between some naive-like hPSCs (NLPs) and their human and mouse in vitro counterparts. Moreover, we also showed numerous fundamental inconsistencies between diverse naive-like states, which are likely attributed to interlaboratory protocol differences. Collectively, our meta-analysis failed to provide global transcriptomic markers that support a bona fide human naive pluripotent state, rather suggesting the existence of altered pluripotent states under current naive-like growth protocols.

bioinformatics↗

bioRxiv2019

Interlaboratory Data Variability Contributes to the Differential Principal Components of Human Primed and Naïve-like Pluripotent States in Multivariate Meta-Analysis

Currently, genome-wide data analyses have revealed significant differences between various human naive-like pluripotent states derived from different laboratory protocols, confounding the establishment of defining criteria of human naive pluripotency. Thus, it is imperative to understand the concept concerning the ground or naive pluripotent state of pluripotent stem cells, which was initially established in mouse embryonic stem cells (mESCs). Putative human pluripotency has been proposed, largely based on comparing genome-wide transcriptomic signatures of human pluripotent stem cells (hPSCs) with human pre-implantation embryos and mESCs by several research groups. Current bioinformatics approaches, however, have inevitable conceptual biases and technological limitations, including the choices of datasets, analytic methods, and interlaboratory data variability. In this report, we performed a multivariate meta-analysis of major hPSC datasets via the combined analytic powers of percentile normalization, principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and SC3 consensus clustering. This vigorous bioinformatics approach has significantly improved the predictive values of the current meta-analysis. Accordingly, we were able to reveal various fundamental inconsistencies between naive-like hPSCs and their human and mouse in vitro counterparts, which are likely attributed to interlaboratory protocol differences. Moreover, our meta-analysis failed to provide global transcriptomic markers that support the putative in vitro human naive pluripotent state, rather suggesting the existence of altered pluripotent states under current naive-like hPSC growth protocols.

bioinformatics↗

bioRxiv2019

The Genomic Stability at the Coding Regions of the Multidrug Transporter Gene ABCB1: Insights into the Development of Alternative Drug Resistance Mechanisms in Human Leukemia Cells

Despite considerable efforts in reversing clinical multidrug resistance (MDR), targeting the predominant multidrug transporter ABCB1/P-glycoprotein (P-gp) based on small molecule inhibitors has been hindered. This may be due to the emergence of alternative drug resistance mechanisms. However, the non-specific P-gp inhibitor cyclosporine (CsA) showed significant clinical benefits in patients with acute myeloid leukemia (AML), which likely represents the only proof-of-principle clinical trial using several generations of MDR inhibitors. Nevertheless, the mechanisms that underlie this successful MDR modulation by CsA are not elucidated because of the absence of CsA-relevant cellular models. In this study, we report the development of two erythroleukemia variants, RVC and RDC, which were derived by step-wise co-selection of K562/R7 drug-resistant leukemia cells with the etoposide-CsA and doxorubicin-CsA drug combinations, respectively. Interestingly, both RVC and RDC, which retained P-gp expression, showed altered MDR phenotypes that were resistant to cyclosporine modulation. The ABCB1 coding regions were genetically stable even under long-term stringent drug selection. Genomically, ABCB1 is likely the most stable ABC transporter gene when comparing with several ABC superfamily members (such as ABCA1, ABCC1, CFTR, and ABCG2). Our findings suggested that non-P-gp mechanisms were likely responsible for the resistance to CsA modulation in both RVC and RDC cells. Moreover, we found that CsA played a role in undermining the selection of highly drug-resistant cells via induction of low level and unstable drug resistance, thus shedding some light on the benefits of CsA in treating certain types of AML patients.

cancer biology↗