Gnanapragasam, V. J. | Search bioRxiv

bioRxiv2026

Novel Methylation Markers in a Prostate Cancer Cohort are Associated with Disease Development and Relapse

Prostate cancer remains one of the most common cancers among men globally. While significant strides have been made in diagnosis and treatment, understanding the complex genetic and epigenetic underpinnings of the disease remains crucial for guiding intervention and developing more personalized and effective therapies. The importance of DNA methylation in prostate cancer has been known for some time, but important facets of the modulation of the epigenome during carcinogenesis remain obscure, partly because the bulk of cancer methylation data have been produced using microarray technologies. Here we utilise the TruSeq methyl capture method (EPICseq) to profile the, previously defined, UK Prostate ICGC cohort of well-annotated primary prostate cancers. To this we add methylation sequencing of benign tissue from the same men. These data allow us to identify differentially methylated regions distinguishing cancerous and non-cancerous prostate tissue, while identifying numerous genes whose methylation profiles can perform that task as well as distinguishing between classes of prostate cancer. We describe a describe a methylation-based control mechanism for prostate-cancer-associated SNPs, and show that this seems a likely mechanism of action for a SNP near the MMP7 gene. We describe three novel molecular signatures that arise from different aspects of the biology of prostate cancer revealed by sequencing. Each is shown to be an independent classifier of cancers into groups with different expected times to relapse. These consist of patterns in driver gene methylation, strand-specific methylation, and signal arising in mitochondrial reads. We show that these signatures, combined with existing molecular tools, provide a powerful predictor of time to recurrence. By substantially enhancing understanding of prostate cancer risk, detection, and prognosis, we pave the way for the development of clinical practices that will benefit patients and improve outcomes.

cancer biology↗

bioRxiv2020

Cellular mRNA signals in human kidney tumors

The cellular transcriptome may provide clues into the differentiation state and origin of human cancer, as tumor cells may retain patterns of gene expression similar to the cell they derive from. Here, we studied the differentiation state and cellular origin of human kidney tumors, by assessing mRNA signals in 1,300 childhood and adult renal tumors, spanning seven different tumor types. Using single cell mRNA reference maps of normal tissues generated by the Human Cell Atlas project, we measured the abundance of reference "cellular signals" in each tumor. Quantifying global differentiation states, we found that, irrespective of tumor type, childhood tumors exhibited fetal cellular signals, thus replacing the long-held presumption of "fetalness" with a precise, quantitative readout of immaturity. By contrast, in adult cancers our assessment refuted the suggestion of dedifferentiation towards a fetal state in the overwhelming majority of cases, with the exception of lethal variants of clear cell renal cell carcinoma. Examining the specific cellular phenotype of each tumor type revealed an intimate connection between the different mesenchymal populations of the developing kidney and childhood renal tumors, whereas adult tumors mostly represented specific mature tubular cell types. RNA signals of each tumor type were remarkably uniform and specific, indicating a possible therapeutic and diagnostic utility. We demonstrated this utility with a case study of a cryptic renal tumor. Whilst not classifiable by clinical pathological work-up, mRNA signals revealed the diagnosis. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer.

cancer biology↗