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In primary prostate cancer, the common multifocality and heterogeneity are major obstacles in finding robust prognostic tissue biomarkers. The long noncoding RNA SCHLAP1 has been suggested, but its prognostic value has not been investigated in the context of tumor heterogeneity. In the present study, expression of SCHLAP1 was investigated using real-time RT-PCR in a multisampled series of 778 tissue samples from radical prostatectomies of 164 prostate cancer patients (median follow-up time 7.4 y). The prognostic value of SCHLAP1 was evaluated with biochemical recurrence as endpoint. In total, 29% of patients were classified as having high expression of SCHLAP1 in at least one malignant sample. Among these, inter- and intrafocal heterogeneity was detected in 72% and 56%, respectively. High expression of SCHLAP1 was shown to be a predictor of biochemical recurrence in both uni- and multivariable cox regression analyses (P < 0.001 and P = 0.02). High expression of SCHLAP1 was also significantly associated with adverse clinicopathological characteristics, including grade group, high pT stage, invasive cribriform growth/intraductal carcinoma of the prostate, and reactive stroma. In conclusion, high expression of SCHLAP1 in at least one malignant sample is a robust prognostic biomarker in primary prostate cancer. For the first time, high SCHLAP1 expression has been associated with the aggressive histopathologic feature reactive stroma. The expression of SCHLAP1 is highly heterogeneous, and analysis of multiple samples is therefore crucial in determination of the SCHLAP1 status of a patient., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Prostate cancer is a highly heterogeneous disease and typically multiple distinct cancer foci are present at primary diagnosis. Molecular classification of prostate cancer can potentially aid the precision of diagnosis and treatment. A promising genomic classifier was published by The Cancer Genome Atlas (TCGA), successfully classifying 74% of primary prostate cancers into seven groups based on one cancer sample per patient. Here, we explore the clinical usefulness of this classification by testing the classifier's performance in a multifocal context. We analyzed 106 cancer samples from 85 distinct cancer foci within 39 patients. By somatic mutation data from whole-exome sequencing and targeted qualitative and quantitative gene expression assays, 31% of the patients were uniquely classified into one of the seven TCGA classes. Further, different samples from the same focus had conflicting classification in 12% of the foci. In conclusion, the level of both intra- and interfocal heterogeneity is extensive and must be taken into consideration in the development of clinically useful molecular classification of primary prostate cancer.

Background: Most primary prostate cancers are multifocal with individual tumors harboring different aggressiveness; however, the genomic heterogeneity among these tumors is poorly understood., Objective: To better understand the biological basis for clinical variability among different lesions, we sought to comprehensively characterize the heterogeneity of somatic gene mutations in multifocal prostate cancer., Design, Setting, and Participants: High-coverage whole-exome sequencing of 153 frozen tissue samples, taken from two to three distinct tumor foci and one non-cancerous area from each of 41 patients, covering a total of 89 tumor foci., Outcome Measurements and Statistical Analysis: State-of-the-art bioinformatics tools for mutation calling and copy number determination from whole-exome sequencing data., Results and Limitations: We found a very high degree of interfocal heterogeneity among tumors, that is, 76% of pairwise-compared tumor foci from the same prostatectomy specimen had no point mutations in common and DNA copy number changes were rarely shared across cancer foci. The few point mutations shared across tumor foci were seldom in cancer-critical genes., Conclusions: In this first large genomic heterogeneity study of primary prostate cancer, we observe that different tumor foci within the same patient are genetically distinct, only rarely sharing any somatic gene mutations, including those in cancer driver genes. This heterogeneity affects how genomics-based management of prostate cancer can be implemented, as information from all tumor foci is necessary to draw valid conclusions about the cancer's genomic alterations., Patient Summary: Most primary prostate cancers consist of multiple tumors within the same organ, but little is known about their relationships. We have compared the sets of gene mutations among such tumors and found that they only exceptionally have any in common. This will influence treatment decisions in the future as each tumor's mutations will render it unique and have to be considered to gain the best treatment results., (Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.)