Andrew Dhawan

This study shows that platelet PAR4 signaling, interacting with estrogen receptor beta, drives glioblastoma progression and immune suppression, with sex-specific effects on survival and TME dynamics.

This study shows that Cx43 promotes glioblastoma cancer stem cell survival and self-renewal via a WNK1-c-MYC signaling pathway.

This paper identifies cooperative microRNA regulatory modules in breast cancer subtypes using multiomic data and finds the miR-29 family as a conserved regulator of EMT and collagen remodeling.

The paper shows that homologous recombination (HR) promotes mitotic death, which suppresses the innate immune response by preventing immunogenic cell death.

This study identifies miR-644a as a tumor cell-intrinsic mediator of sex bias in glioblastoma, showing it is more highly expressed in females and its target genes are linked to poorer survival.

This paper identifies therapeutic miRNA cocktails for Ewing Sarcoma using a network science-based approach to prioritize miRNA targets and combinations.

The paper identifies a switch from DICER-dependent to Argonaute-mediated miRNA biogenesis in cancer, showing that non-canonical processing of oncogenic miRNAs promotes cancer progression.

RadiationGeneSigDB curates gene expression signatures for oxic and hypoxic radiation responses and demonstrates their utility in identifying hypoxia-regulated microRNAs across cancer types.

The paper shows how non-coding RNA acting as miRNA sponges can generate oscillatory dynamics in a transcriptional feedback network, with implications for understanding RNA species roles in biological processes.

The paper investigates miRNA regulation across 15 cancer types, finding complex interactions between miRNA expression and cancer hallmarks, with specific emphasis on the oncomiR-1 cluster and repression of tumour suppressor genes.

This paper introduces sigQC, an R package that standardizes gene signature quality control, demonstrating its application in evaluating signatures on cancer gene expression data.

The paper challenges the classic U-shape model of resistance by proposing alternative population-level models for ruxolitinib resistance in CMML and explores the role of oxygen and cytokine signaling in resistance dynamics.

This study shows that resistance to ALK inhibitors in lung cancer is unstable and dynamic, with collateral sensitivity to other drugs offering new treatment options.