Collision tumors revealed by prospectively assessing subtype-defining molecular alterations in 904 individual prostate cancer foci

Prostate cancer: Molecular aspects, consequences, and opportunities of the multifocal nature

Prostate cancer is unique compared to other major cancers due to the presence of multiple primary malignant foci in the majority of patients at the time of diagnosis. Each malignant focus has distinct somatic mutations and gene expression patterns, which represents a challenge for the development of prognostic tests for localized prostate cancer. Additionally, the molecular heterogeneity of advanced prostate cancer has important implications for management, particularly for patients with metastatic and locally recurrent cancer. Studies have shown that prostate cancers with mutations in DNA damage response genes are more sensitive to drugs inhibiting the poly ADP-ribose polymerase (PARP) enzyme. However, testing for such mutations should consider both spatial and temporal heterogeneity. Here, we summarize studies where multiregional genomics and transcriptomics analyses have been performed for primary prostate cancer. We further discuss the vast interfocal heterogeneity and how prognostic biomarkers and a molecular definition of the index tumor should be developed. The concept of focal treatments in prostate cancer has been evolving as a demand from patients and clinicians and is one example where there is a need for defining an index tumor. Here, biomarkers must have proven value for individual malignant foci. The potential discovery and implementation of biomarkers that are agnostic to heterogeneity are also explored as an alternative to multisample testing. Thus, deciding upon whole-organ treatment, such as radical prostatectomy, should depend on information from biomarkers which are informative for the whole organ.

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.

Clonal relationships of adjacent Gleason pattern 3 and Gleason pattern 5 lesions in Gleason Scores 3+5=8 and 5+3=8

Genomic studies have demonstrated a high level of intra-tumoral heterogeneity in prostate cancer. There is strong evidence suggesting that individual tumor foci can arise as genetically distinct, clonally independent lesions. However, recent studies have also demonstrated that adjacent Gleason pattern (GP) 3 and GP4 lesions can originate from the same clone but follow divergent genetic and morphologic evolution. The clonal relationship of adjacent GP3 and GP5 lesions has thus far not been investigated. Here we analyzed a cohort of 14 cases-11 biopsy and 3 radical prostatectomy specimens-with a Gleason score of 3 + 5 = 8 or 5 + 3 = 8 present in the same biopsy or in a single dominant tumor nodule at radical prostatectomy. Clonal and subclonal relationships between GP3 and GP5 lesions were assessed using genetically validated immunohistochemical assays for ERG, PTEN, and P53. 9/14 (64%) cases showed ERG reactivity in both GP3 and GP5 lesions. Only 1/14 (7%) cases showed a discordant pattern with ERG staining present only in GP3. PTEN expression was lost in 2/14 (14%) cases with perfect concordance between GP5 and GP3. P53 nuclear reactivity was present in 1/14 (7%) case in both GP5 and GP3. This study provides first evidence that the majority of adjacent GP3 and GP5 lesions share driver alterations and are clonally related. In addition, we observed a lower-than-expected rate of PTEN loss in GP5 in the context of Gleason score 3 + 5 = 8 or 5 + 3 = 8 tumors.

Characterization of Immune-Based Molecular Subtypes and Prognostic Model in Prostate Adenocarcinoma

Prostate adenocarcinoma (PRAD), also named prostate cancer, the most common visceral malignancy, is diagnosed in male individuals. Herein, in order to obtain immune-based subtypes, we performed an integrative analysis to characterize molecular subtypes based on immune-related genes, and further discuss the potential features and differences between identified subtypes. Simultaneously, we also construct an immune-based risk model to assess cancer prognosis. Our findings showed that the two subtypes, C1 and C2, could be characterized, and the two subtypes showed different characteristics that could clearly describe the heterogeneity of immune microenvironments. The C2 subtype presented a better survival rate than that in the C1 subtype. Further, we constructed an immune-based prognostic model based on four screened abnormally expressed genes, and they were selected as predictors of the robust prognostic model (AUC = 0.968). Our studies provide reference for characterization of molecular subtypes and immunotherapeutic agents against prostate cancer, and the developed robust and useful immune-based prognostic model can contribute to cancer prognosis and provide reference for the individualized treatment plan and health resource utilization. These findings further promote the development and application of precision medicine in prostate cancer.

In situ expression of ERG protein in the context of tumor heterogeneity identifies prostate cancer patients with inferior prognosis

Prognostic biomarkers for prostate cancer are needed to improve prediction of disease course and guide treatment decisions. However, biomarker development is complicated by the common multifocality and heterogeneity of the disease. We aimed to determine the prognostic value of candidate biomarkers transcriptional regulator ERG and related ETS family genes, while considering tumor heterogeneity. In a multisampled, prospective, and treatment‐naïve radical prostatectomy cohort from one tertiary center (2010–2012, median follow‐up 8.1 years), we analyzed ERG protein (480 patients; 2047 tissue cores), and RNA of several ETS genes in a subcohort (165 patients; 778 fresh‐frozen tissue samples). Intra‐ and interfocal heterogeneity was identified in 29% and 33% (ERG protein) and 39% and 27% (ETS RNA) of patients, respectively. ERG protein and ETS RNA was identified exclusively in a nonindex tumor in 31% and 32% of patients, respectively. ERG protein demonstrated independent prognostic value in predicting biochemical (P = 0.04) and clinical recurrence (P = 0.004) and appeared to have greatest prognostic value for patients with Grade Groups 4–5. In conclusion, when heterogeneity is considered, ERG protein is a robust prognostic biomarker for prostate cancer.