Long noncoding RNAs in prostate cancer: overview and clinical implications.

Prostate cancer is the second most common cause of cancer mortality among men in the United States. While many prostate cancers are indolent, an important subset of patients experiences disease recurrence after conventional therapy and progresses to castration-resistant prostate cancer (CRPC), which is currently incurable. Thus, there is a critical need to identify biomarkers that will distinguish indolent from aggressive disease, as well as novel therapeutic targets for the prevention or treatment of CRPC. In recent years, long noncoding RNAs (lncRNAs) have emerged as an important class of biological molecules. LncRNAs are polyadenylated RNA species that share many similarities with protein-coding genes despite the fact that they are noncoding (not translated into proteins). They are usually transcribed by RNA polymerase II and exhibit the same epigenetic signatures as protein-coding genes. LncRNAs have also been implicated in the development and progression of variety of cancers, including prostate cancer. While a large number of lncRNAs exhibit tissue- and cancer-specific expression, their utility as diagnostic and prognostic biomarkers is just starting to be explored. In this review, we highlight recent findings on the functional role and molecular mechanisms of lncRNAs in the progression of prostate cancer and evaluate their use as potential biomarkers and therapeutic targets

Genomic biomarkers in prostate cancer.

Prostate cancer is the most common non-cutaneous cancer among men in the United States. In the last decade there has been a rapid expansion in the field of biomarker assays for diagnosis, prognosis, and treatment prediction in prostate cancer. The evidence base for these assays is rapidly evolving. With several commercial assays available at each stage of the disease, deciding which genomic assays are appropriate for which patients can be nuanced for physicians. In an effort to help guide these decisions in clinical practice, we aim to give an update on the current status of the biomarker field of prostate cancer

Molecular Genetics of Prostate Cancer and Role of Genomic Testing.

Prostate cancer (PCa) is characterized by profound genomic heterogeneity. Recent advances in personalized treatment entail an increasing need of genomic profiling. For localized PCa, gene expression assays can support clinical decisions regarding active surveillance and adjuvant treatment. In metastatic PCa, homologous recombination deficiency, microsatellite instability-high (MSI-H), and CDK12 deficiency constitute main actionable alterations. Alterations in DNA repair genes confer variable sensitivities to poly(ADP-ribose)polymerase inhibitors, and the use of genomic instability assays as predictive biomarker is still incipient. MSI can be assessed by immunohistochemistry To date there is a lack of consensus as to testing standards

Chromatin to Clinic: The Molecular Rationale for PARP1 Inhibitor Function.

Poly(ADP-ribose) polymerase 1 (PARP1) inhibitors were recently shown to have potential clinical impact in a number of disease settings, particularly as related to cancer therapy, treatment for cardiovascular dysfunction, and suppression of inflammation. The molecular basis for PARP1 inhibitor function is complex, and appears to depend on the dual roles of PARP1 in DNA damage repair and transcriptional regulation. Here, the mechanisms by which PARP-1 inhibitors elicit clinical response are discussed, and strategies for translating the preclinical elucidation of PARP-1 function into advances in disease management are reviewed

A Comprehensive Analysis of CXCL12 Isoforms in Breast Cancer1,2

AbstractCXCL12-CXCR4-CXCR7 signaling promotes tumor growth and metastasis in breast cancer. Alternative splicing of CXCL12 produces isoforms with distinct structural and biochemical properties, but little is known about isoform-specific differences in breast cancer subtypes and patient outcomes. We investigated global expression profiles of the six CXCL12 isoforms, CXCR4, and CXCR7 in The Cancer Genome Atlas breast cancer cohort using next-generation RNA sequencing in 948 breast cancer and benign samples and seven breast cancer cell lines. We compared expression levels with several clinical parameters, as well as metastasis, recurrence, and overall survival (OS). CXCL12-α, -β, and -γ are highly co-expressed, with low expression correlating with more aggressive subtypes, higher stage disease, and worse clinical outcomes. CXCL12-δ did not correlate with other isoforms but was prognostic for OS and showed the same trend for metastasis and recurrence-free survival. Effects of CXCL12-δ remained independently prognostic when taking into account expression of CXCL12, CXCR4, and CXCR7. These results were also reflected when comparing CXCL12-α, -β, and -γ in breast cancer cell lines. We summarized expression of all CXCL12 isoforms in an important chemokine signaling pathway in breast cancer in a large clinical cohort and common breast cancer cell lines, establishing differences among isoforms in multiple clinical, pathologic, and molecular subgroups. We identified for the first time the clinical importance of a previously unstudied isoform, CXCL12-δ

The role of the maximum involvement of biopsy core in predicting outcome for patients treated with dose-escalated radiation therapy for prostate cancer

Abstract Purpose To evaluate the influence of the maximum involvement of biopsy core (MIBC) on outcome for prostate cancer patients treated with dose-escalated external beam radiotherapy (EBRT). Methods and materials The outcomes of 590 men with localized prostate cancer treated with EBRT (≥75 Gy) at a single institution were retrospectively analyzed. The influence of MIBC on freedom from biochemical failure (FFBF), freedom from metastasis (FFM), cause-specific survival (CSS), and overall survival (OS) was compared to other surrogates for biopsy tumor volume, including the percentage of positive biopsy cores (PPC) and the total percentage of cancer volume (PCV). Results MIBC correlated with PSA, T-stage, Gleason score, NCCN risk group, PPC, PCV, and treatment related factors. On univariate analysis, MIBC was prognostic for all endpoints except OS; with greatest impact in those with Gleason scores of 8–10. However, on multivariate analysis, MIBC was only prognostic for FFBF (hazard ratio [HR] 1.9, p = 0.008), but not for FFM (p = 0.19), CSS (p = 0.16), and OS (p = 0.99). Conclusions In patients undergoing dose-escalated EBRT, MIBC had the greatest influence in those with Gleason scores of 8–10 but provided no additional prognostic data as compared to PPC and PCV, which remain the preferable prognostic variables in this patient population.http://deepblue.lib.umich.edu/bitstream/2027.42/112858/1/13014_2012_Article_631.pd

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies

Predictors of multidomain decline in health‐related quality of life after stereotactic body radiation therapy (SBRT) for prostate cancer

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136687/1/cncr30519_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136687/2/cncr30519.pd

Disease Ontology: a backbone for disease semantic integration

The Disease Ontology (DO) database (http://disease-ontology.org) represents a comprehensive knowledge base of 8043 inherited, developmental and acquired human diseases (DO version 3, revision 2510). The DO web browser has been designed for speed, efficiency and robustness through the use of a graph database. Full-text contextual searching functionality using Lucene allows the querying of name, synonym, definition, DOID and cross-reference (xrefs) with complex Boolean search strings. The DO semantically integrates disease and medical vocabularies through extensive cross mapping and integration of MeSH, ICD, NCI's thesaurus, SNOMED CT and OMIM disease-specific terms and identifiers. The DO is utilized for disease annotation by major biomedical databases (e.g. Array Express, NIF, IEDB), as a standard representation of human disease in biomedical ontologies (e.g. IDO, Cell line ontology, NIFSTD ontology, Experimental Factor Ontology, Influenza Ontology), and as an ontological cross mappings resource between DO, MeSH and OMIM (e.g. GeneWiki). The DO project (http://diseaseontology.sf.net) has been incorporated into open source tools (e.g. Gene Answers, FunDO) to connect gene and disease biomedical data through the lens of human disease. The next iteration of the DO web browser will integrate DO's extended relations and logical definition representation along with these biomedical resource cross-mappings