A Systems Approach to Prostate Cancer Classification—Response (2017)

We are gratified to learn that Thysell and colleagues investigated the PCS1–3 classification system (1, 2) in an independent prostate cancer cohort. The analysis of prostate cancer metastases from their cohort (3, 4) showed clear separation of the tumor samples into three categories, consistent with our own findings. However, their recent correspondence identified the PCS2 subtype as predominating (77%) in bone metastases (2). This appears to disagree with our conclusion (1) that the PCS1 subtype is the most aggressive. We note here that Thysell and colleagues subtyped their dataset using only the first two principal components (PC) from the 428 subtype-enriched gene set described by us (1); however, our method to define the categories employs a random forest algorithm for application of this gene set (1). The Thysell and colleagues' approach, which was not described in our study, only accounts for 23.9% of the variance in the gene set in their dataset (Fig. 1A). A comparison of the discrepancy in clustering is shown for three cohorts (Fig. 1B–D). To visualize the differences of the clustering output between Thysell and colleagues' approach and our method, we generated two dendrograms based on the first two PCs from the 428 subtype-enriched gene set or ones from the random forest classifier probability of the PCS1–3 categories. In Fig. 1B–D, the PCS assignment for both dendrograms was performed using a naïve Bayes classifier based on the 14-pathway activation scheme that we used to define the PCS categories in our study (1). Application of our method to the Thysell and colleagues' dataset shows that the PCS2 subtype is least frequently represented in bone metastases, in comparison with PCS1 and PCS3 (Fig. 1E). Although our study (1) did not address the question of PCS1–3 assignments in bone metastases specifically, these findings are consistent with our conclusion that PCS2 occurs less frequently in metastatic prostate cancer. The high representation of PCS3 (a notable feature therein is relatively suppressed AR activity) in bone metastases is an interesting new finding. In the Thysell and colleagues' dataset (2–4), PCS1 bone metastases exhibited high activation of AR-variant and low activation of AR pathways, consistent with the results from PCS1 metastases in the You and colleagues' (1) and PCF-SU2C cohorts (Fig. 1F; ref. 5). We interrogated the samples from different organs in the You and colleagues' (1) and PCF-SU2C (5) cohorts to determine whether any of the PCS categories are associated with a tendency to colonize specific organ sites. Metastases were most frequently assigned to PCS1 and PCS3, with no PCS2 present in liver metastases in both cohorts (Fig. 2A and B). Our results suggest that PCS1 and PCS3 are the most common subtypes in metastases to bone and liver. Further validation of the PCS1–3 classification system using well-defined clinical information, such as treatment history, may reveal therapy-driven alterations in the PCS categories and their associated patterns of pathway activation.See the original Letter to the Editor, p. 7131No potential conflicts of interest were disclosed.