Interfocal heterogeneity challenges the clinical usefulness of molecular classification of primary prostate cancer.

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.

Multifocal Primary Prostate Cancer Exhibits High Degree of Genomic Heterogeneity.

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.

Novel transcription-induced fusion RNAs in prostate cancer.

Prostate cancer is a clinically and pathologically heterogeneous disease with a broad spectrum of molecular abnormalities in the genome and transcriptome. One key feature is the involvement of chromosomal rearrangements creating fusion genes. Recent RNA-sequencing technology has uncovered that fusions which are not caused by chromosomal rearrangements, but rather meditated at transcription level, are common in both healthy and diseased cells. Such fusion transcripts have been proven highly associated with prostate cancer development and progression. To discover novel fusion transcripts, we analyzed RNA sequencing data from 44 primary prostate tumors and matched benign tissues from The Cancer Genome Atlas. Twenty-one high-confident candidates were significantly enriched in malignant vs. benign samples. Thirteen of the candidates have not previously been described in prostate cancer, and among them, five long intergenic non-coding RNAs are involved as fusion partners. Their expressions were validated in 50 additional prostate tumor samples and seven prostate cancer cell lines. For four fusion transcripts, we found a positive correlation between their expression and the expression of the 3' partner gene. Among these, differential exon usage and qRT-PCR analyses in particular support that SLC45A3-ELK4 is mediated by an RNA polymerase read-through mechanism.