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Biology subjects

Tan, P. H.

Publications and source records attributed to Tan, P. H..

2 recordsLinked to original sources

Effects of breast fibroepithelial tumor associated retinoic acid receptor alpha ligand binding domain mutations on receptor function and retinoid signaling

Point mutations in the ligand binding domain of retinoic acid receptor alpha (RAR) have been implicated in breast fibroepithelial tumors development. However, their role in the tumorigenesis of solid tumors is currently unknown. In this study, using a combination of biochemical and cellular assays, we evaluated the functional consequences of known tumor associated RAR mutations on retinoic acid signaling. All of the clinically associated mutants tested showed diminished transcriptional activities compared to wild type RAR. These mutants also exhibited a dominant negative effect, an activity which has previously been linked to developmental defects and tumor formation in mice. X-ray crystallography showed that mutants remain relatively intact structurally and the loss of transcriptional activity is due to altered co-activator recruitment. In agreement with our biochemical analyses, transcriptomics and cell growth analysis showed that the mutant RAR proteins confer resistance to growth inhibition in the presence of its ligand in phyllodes tumor cells. Although the mutations impair the receptor responses to retinoic acid, certain mutant RAR are partially reactivatable with alternative synthetic agonists. Our data provide insights into the mechanisms by which RAR mutations impact tumorigenesis.

cancer biology↗

Data-driven inference of crosstalk in the tumor microenvironment

Signaling between cancer and nonmalignant (stromal) cells in the tumor microenvironment (TME) is key to tumorigenesis yet challenging to decipher from tumor transcriptomes. Here, we report an unbiased, data-driven approach to deconvolute bulk tumor transcriptomes and predict crosstalk between ligands and receptors on cancer and stromal cells in the TME of 20 solid tumor types. Our approach recovers known transcriptional hallmarks of cancer and stromal cells and is concordant with single-cell and immunohistochemistry data, underlining its robustness. Pan-cancer analysis reveals previously unrecognized features of cancer-stromal crosstalk. We find that autocrine cancer cell cross-talk varied between tissues but often converged on known cancer signaling pathways. In contrast, many stromal cross-talk interactions were highly conserved across tumor types. Interestingly, the immune checkpoint ligand PD-L1 was overexpressed in stromal rather than cancer cells across all tumor types. Moreover, we predicted and experimentally validated aberrant ligand and receptor expression in cancer cells of basal and luminal breast cancer, respectively. Collectively, our findings validate a data-driven method for tumor transcriptome deconvolution and establishes a new resource for hypothesis generation and downstream functional interrogation of the TME in tumorigenesis and disease progression.

cancer biology↗