Popularized: Discovered Gene Patterns Can Predict Prostate Cancer Treatment Response - Beyond the Abstract

Perhaps the most significant clinical challenge today is deciding which type of treatment will work best for different prostate cancer patient groups. In the study "Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse" led by Dr. Alfonso Urbanucci from Oslo University Hospital and Professor Matti Nykter from Tampere University, the researchers found that specific patterns in gene expression and DNA organization can predict patient response to treatment.

The study utilized a combination of prostate cancer resistance models to Xtandi (enzalutamide) and advanced technology to analyze genes and DNA organization at the single-cell level. This revealed pre-existing subsets of cells that were treatment-resistant and showed stem cell-like and regenerative gene expression patterns. The researchers' results suggest that the presence of such patterns in cancer tissue may predict the risk of recurrence and disease development. Such information can help tailor treatment for different subgroups of prostate cancer patients.


Significance: We used models of resistance to approved androgen receptor-targeted therapies for prostate cancer to identify subpopulations of treatment-persistent and pre-existing cells. We established that chromatin structure reconfigurations led to alterations in gene expression and drove alternative tumor adaptations and treatment escape. Motivated by the need for pre-treatment biomarkers in prostate cancer, we identified molecular predictors of therapy response based on the presence of treatment-persistent and pre-existing cells.

Summary: We show that subpopulations of treatment-persistent cells with stem-like and regenerative properties foster alternative trajectories of enzalutamide resistance in prostate cancer. Alternative transcriptional patterns of resistance are induced by divergent chromatin reprogramming. Transcriptional enrichment of signals from these treatment-persistent cells stratifies patient outcomes in both early-stage treatment-naive and treatment-exposed tumors.


  1. Identification of prostate cancer cells with gene expression patterns of regenerative potential that persist and exist prior to enzalutamide treatment.
  2. Profiling of chromatin and transcriptional features from subpopulations of treatment-challenged prostate cancer cells.
  3. Identification of gene signatures associated with stem-like and regenerative potential.
  4. Stratification of prostate cancer patients from “bulk” RNA sequencing data based on identified stemness- and regeneration-related gene signatures.

Caption: Single-cell level regenerative (PROSGenesis) and stem-like (Persist) gene patterns identified in prostate specimens

Written by: Alfonso Urbanucci, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway

The study is supported by the Norwegian Cancer Society (Kreftforeningen) and was published in the journal Nature Communications on September 6th, 2021 

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