Mohammed Alshalalfa

The paper identifies molecular signatures in prostate cancer that link inflammatory chemokine expression to metabolic changes and relapse risk.

This study uses CRISPR screens to identify PTGES3 as a novel modulator of AR protein levels and function in prostate cancer, showing its role in therapy resistance.

This study introduces DGS, a method combining denoising autoencoders and transfer learning to predict prostate cancer metastasis using both labelled and unlabelled gene expression data, achieving higher accuracy than existing signatures.