Biology subjects

Gan, D.

Publications and source records attributed to Gan, D..

4 recordsLinked to original sources

bioRxiv2023

Overcome Prostate Cancer Resistance to Immune Checkpoint Therapy with Ketogenic Diet-Induced Epigenetic Reprogramming

Advanced prostate cancer (PCa) is overwhelmingly resistant to immune checkpoint blockade (ICB) therapy, representing a formidable clinical challenge. In this study, we developed a syngeneic murine PCa model with acquired ICB resistance. Using this model, synergistic efficacy was achieved by combining anti-PD1 and anti-CTLA4 antibodies with histone deacetylase inhibitor (HDACi) vorinostat, a cyclic ketogenic diet (CKD), or supplementation of ketone body {beta}-hydroxybutyrate (BHB, endogenous HDACi) via 1,3-butanediol-admixed food. CKD and BHB supplementation delayed PCa tumors as monotherapy, and both BHB and adaptive immunity are required for the anti-tumor activity of CKD. Single-cell transcriptomic and proteomic profiling revealed that the HDACi and ketogenesis-enhanced ICB therapy involves cancer-cell-intrinsic (upregulated MHC class I molecules) and extrinsic mechanisms (CD8+ T cell chemoattraction, M1/M2 macrophage rebalancing, monocyte differentiation toward antigen presenting cells, and diminished neutrophils). Overall, these findings underscore the potential of using HDACi and optimized KD to enhance ICB therapy for PCa.

cancer biology↗

bioRxiv2022

The Graphical R2D2 Estimator for the Precision Matrices

Biological networks are important for the analysis of human diseases, which summarize the regulatory interactions and other relationships between different molecules. Understanding and constructing networks for molecules, such as DNA, RNA and proteins, can help elucidate the mechanisms of complex biological systems. The Gaussian Graphical Models (GGMs) are popular tools for the estimation of biological networks. Nonetheless, reconstructing GGMs from high-dimensional datasets is still challenging. Current methods cannot handle the sparsity and high-dimensionality issues arising from datasets very well. Here we developed a new GGM, called the GR2D2 (Graphical R2-induced Dirichlet Decomposition) model, based on the R2D2 priors for linear models. Besides, we provided a data-augmented block Gibbs sampler algorithm. The R code is available at https://github.com/RavenGan/GR2D2. The GR2D2 estimator shows superior performance in estimating the precision matrices compared to existing techniques in various simulation settings. When the true precision matrix is sparse and of high dimension, the GR2D2 provides the estimates with smallest information divergence from the underlying truth. We also compare the GR2D2 estimator to the graphical horseshoe estimator in five cancer RNA-seq gene expression datasets grouped by three cancer types. Our results show that GR2D2 successfully identifies common cancer pathways and cancer-specific pathways for each dataset.

bioinformatics↗

bioRxiv2021

Evolutionary Analysis of Transcriptional Regulation Mediated by Cdx2 in Rodents

Differences in gene expression, which can arise from divergence in cis-regulatory elements or alterations in transcription factors binding specificity, are one of the most important causes of phenotypic diversity during evolution. By protein sequence analysis, we observed high sequence conservation in the DNA binding domain (DBD) of the transcription factor Cdx2 across many vertebrates, whereas three amino acid changes were exclusively found in mouse Cdx2 (mCdx2), suggesting potential positive selection in the mouse lineage. Multi-omics analyses were then carried out to investigate the effects of these changes. Surprisingly, there were no significant functional differences between mCdx2 and its rat homologue (rCdx2), and none of the three amino acid changes had any impact on its function. Finally, we used rat-mouse allodiploid embryonic stem cells (RMES) to study the cis effects of Cdx2-mediated gene regulation between the two rodents. Interestingly, whereas Cdx2 binding is largely divergent between mouse and rat, the transcriptional effect induced by Cdx2 is conserved to a much larger extent. Author summaryOur study 1) represented a first systematic analysis of species-specific adaptation in DNA binding pattern of transcription factor. Although the mouse-specific amino acid changes did not manifest functional impact in our system, several explanations may account for it (See Discussion part for the detail); 2) represented a first study of cis-regulation between two reproductively isolated species by using a novel allodiploid system; 3) demonstrated a higher conservation of transcriptional output than that of DNA binding, suggesting the evolvability/plasticity of the latter; 4) finally provided a rich data resource for Cdx2 mediated regulation, including gene expression, chromatin accessibility and DNA binding etc.

evolutionary biology↗

bioRxiv2020

CIGAR-seq, a CRISPR/Cas-based method for unbiased screening of novel mRNA modification regulators

Cellular RNA is decorated with over 170 types of chemical modifications. Many modifications in mRNA, including m6A and m5C, have been associated with critical cellular functions under physiological and/or pathological conditions. To understand the biological functions of these modifications, it is vital to identify the regulators that modulate the modification rate. However, a high-throughput method for unbiased screening of these regulators is so far lacking. Here, we report such a method combining pooled CRISPR screen and reporters with RNA modification readout, termed CRISPR integrated gRNA and reporter sequencing (CIGAR-seq). Using CIGAR-seq, we discovered NSUN6 as a novel mRNA m5C methyltransferase. Subsequent mRNA bisulfite sequencing in HAP1 cells without or with NSUN6 and/or NSUN2 knockout showed that NSUN6 and NSUN2 worked on non-overlapping subsets of mRNA m5C sites, and together contributed to almost all the m5C modification in mRNA. Finally, using m1A as an example, we demonstrated that CIGAR-seq can be easily adapted for identifying regulators of other mRNA modification.

molecular biology↗