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Understanding the heterogeneous molecular landscape of prostate cancer is fundamental to improve treatment of the disease. Here, we aim to provide a broad molecular view of a cross- section of a prostate organ. This study manifests several unique tumor gene expression subtypes, with adjacent stroma, occupying distinct and different anatomical regions. The interplay between multiple molecularly defined tumor gene expression factors and/or Gleason scoring and the corresponding tumor microenvironment was hereby studied in detail. We perform a molecular sub-categorization of the tumor microenvironment throughout the whole prostate, using three different molecular principles; (i) AR staining, since loss of stromal AR is directly proportional to the degree of differentiation (Gleason score), (ii) Masson staining for its role in marking reactive stroma, and (iii) spatial transcriptomics analysis. In particular, we performed a detailed analysis of spatial distribution in histologic sections at the invasive border of a tumor foci contrasting it to the tumor core. Here, we show spatially confined DEPDC1, CHN1 and CRISP3 upregulation at the invasive border with implications of signal transduction pathways such as; PTEN, TGF-beta Receptor Complex, NOTCH4, ERBB2, and VEGF signaling, some of which are druggable. Overall, our results show an unprecedented view of the molecular heterogeneity of a prostate cancer not evident by other means. Here, we reveal patient-specific gene expression hallmarks from low to aggressive cancer within the same cross section of a prostate.

The molecular mechanisms by which potentially lethal castration-resistant prostate cancer emerge in advanced metastatic prostate cancer are still poorly understood. Intratumor heterogeneity is believed to contribute to the fact that a majority of affected men succumb to the disease within a few years. In this study, we will challenge the conventional notion that castration-resistant prostate cancer cells evolve as a consequence of treatment. To examine the temporal aspects of resistance, we analyze tumor heterogeneity in core needle biopsies collected pre-and post-treatment. By doing so, we are able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome- wide data. Our data-driven analysis of transcriptomes identified several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Strikingly, certain minor cell populations present before treatment exhibited gene expression profiles that matched those of resistant tumor cell clusters. Such resistant clusters were confirmed by the localization of the androgen receptor to the nuclei in cancer cells present after treatment. Our data also demonstrate that stromal cells adjacent to resistant tumor factors do not express AR before treatment (or after), which can be used to increase the power in predicting resistant tumors. QC 20200511