Abstract
Background and objectivesTranscriptomic landscape of prostate cancer (PCa) shows multidimensional variability, potentially arising from the cell-of-origin, reflected in serum markers, and most importantly related to drug sensitivities. For example, Aggressive Variant Prostate Cancer (AVPC) presents low PSA per tumor burden, and characterized by de novo resistance to androgen receptor signaling inhibitors (ARIs). Understanding PCa transcriptomic complexity can provide biological insight and therapeutic guidance. However, unsupervised clustering analysis is hindered by potential confounding factors such as stromal contamination and stress-related material degradation.Materials and methodsTo focus on prostate epithelial cell-relevant heterogeneity, we defined 1,629 genes expressed by prostate epithelial cells by analyzing publicly available bulk and single- cell RNA sequencing data. Consensus clustering and CIBERSORT deconvolution were used for class discovery and proportion estimate analysis. The Cancer Genome Atlas Prostate Adenocarcinoma dataset served as a training set. The resulting clusters were analyzed in association with clinical, pathologic, and genomic characteristics and impact on survival. Serum markers PSA and PAP was analyzed to predict response to docetaxel chemotherapy in metastatic setting.ResultsWe identified two luminal subtypes and two aggressive variant subtypes of PCa: luminal A (Adipogenic/AR-active/PSA-high) (30.0%); luminal S (Secretory/PAP-high) (26.0%); AVPC-I (Immune-infiltrative) (14.7%), AVPC-M (Myc-active) (4.2%), and mixed (25.0%). AVPC-I and AVPC-M subtypes predicted to be resistant to ARI and have low PSA per tumor burden. Luminal A and AVPC-M predicted to be resistant to docetaxel and have high PSA/PAP Ratio. Metastatic PCa patients with high PSA/PAP ratio (>20) had significantly shorter progression-free survival than those with low ratio (≤20) following docetaxel chemotherapy.ConclusionWe propose four prostate adenocarcinoma subtypes with distinct transcriptomic, genomic, and pathologic characteristics. PSA/PAP ratio in advanced cancer may aid in determining which patients would benefit from maximized androgen receptor inhibition or early use of antimicrotubule agents.
Highlights
Previous attempts to subtype prostate cancer (PCa) by transcriptomic variability, including ETS transcription-factor– based classifications and luminal/basal lineage models [1,2,3], was not able to provide additional clinical information beyond known risk factors [4]
Luminal A and Aggressive Variant Prostate Cancer (AVPC)-M predicted to be resistant to docetaxel and have high prostate specific antigen (PSA)/prostate-specific acid phosphatase (PAP) Ratio
PSA/PAP ratio in advanced cancer may aid in determining which patients would benefit from maximized androgen receptor inhibition or early use of antimicrotubule agents
Summary
Previous attempts to subtype PCa by transcriptomic variability, including ETS transcription-factor– based classifications and luminal/basal lineage models [1,2,3], was not able to provide additional clinical information beyond known risk factors [4]. Whole-transcriptome analysis of tumor tissue is susceptible to those potential confounding factors when attempting to identify subtypes based on the tumor cell intrinsic heterogeneity. Transcriptomic landscape of prostate cancer (PCa) shows multidimensional variability, potentially arising from the cell-of-origin, reflected in serum markers, and most importantly related to drug sensitivities. Aggressive Variant Prostate Cancer (AVPC) presents low PSA per tumor burden, and characterized by de novo resistance to androgen receptor signaling inhibitors (ARIs). Unsupervised clustering analysis is hindered by potential confounding factors such as stromal contamination and stress-related material degradation. Serum markers PSA and PAP was analyzed to predict response to docetaxel chemotherapy in metastatic setting
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
