Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine.

BACKGROUND: Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question. METHODS: We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones. RESULTS: In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis' potential impact on therapy selection appears positive in these pilot cases. CONCLUSIONS: PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

Combined Longitudinal Clinical and Autopsy Phenomic Assessment in Lethal Metastatic Prostate Cancer: Recommendations for Advancing Precision Medicine.

BACKGROUND: Systematic identification of data essential for outcome prediction in metastatic prostate cancer (mPC) would accelerate development of precision oncology. OBJECTIVE: To identify novel phenotypes and features associated with mPC outcome, and to identify biomarker and data requirements to be tested in future precision oncology trials. DESIGN SETTING AND PARTICIPANTS: We analyzed deep longitudinal clinical, neuroendocrine expression, and autopsy data of 33 men who died from mPC between 1995 and 2004 (PELICAN33), and related findings to mPC biomarkers reported in the literature. INTERVENTION: Thirty-three men prospectively consented to participate in an integrated clinical-molecular rapid autopsy study of mPC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Data exploration with correction for multiple testing and survival analysis from the time of diagnosis to time to death and time to first occurrence of severe pain as outcomes were carried out. The effect of seven complications on the modeled probability of dying within 2 yr after presenting with the complication was evaluated using logistic regression. RESULTS AND LIMITATIONS: Feature exploration revealed novel phenotypes related to mPC outcome. Four complications (pleural effusion, severe anemia, severe or controlled pain, and bone fracture) predict the likelihood of death within 2 yr. Men with Gleason grade group 5 cancers developed severe pain sooner than those with lower-grade tumors. Surprisingly, neuroendocrine (NE) differentiation was frequently observed in the setting of high serum prostate-specific antigen (PSA) levels (≥30 ng/ml). In 4/33 patients, no controlled (requiring analgesics) or severe pain was detected, and strikingly, 14/15 metastatic sites studied in these men did not express NE markers, suggesting an inverse relationship between NE differentiation and pain in mPC. Intracranial subdural metastasis is common (36%) and is usually clinically undetected. Categorization of "skeletal-related events" complications used in recent studies likely obscures the understanding of spinal cord compression and fracture. Early death from prostate cancer was identified in a subgroup of men with a low longitudinal PSA bandwidth. Cachexia is common (body mass index <0.89 in 24/31 patients) but limited to the last year of life. Biomarker review identified 30 categories of mPC biomarkers in need of winnowing in future trials. All findings require validation in larger cohorts, preferably alongside data from this study. CONCLUSIONS: The study identified novel outcome subgroups for future validation and provides "vision for mPC precision oncology 2020-2050" draft recommendations for future data collection and biomarker studies. PATIENT SUMMARY: To better understand variation in metastatic prostate cancer behavior, we assembled and analyzed longitudinal clinical and autopsy records in 33 men. We identified novel outcomes, phenotypes, and aspects of disease burden to be tested and refined in future trials.