Oncogenic Role of THOR, a Conserved Cancer/Testis Long Non-coding RNA.

Large-scale transcriptome sequencing efforts have vastly expanded the catalog of long non-coding RNAs (lncRNAs) with varying evolutionary conservation, lineage expression, and cancer specificity. Here, we functionally characterize a novel ultraconserved lncRNA, THOR (ENSG00000226856), which exhibits expression exclusively in testis and a broad range of human cancers. THOR knockdown and overexpression in multiple cell lines and animal models alters cell or tumor growth supporting an oncogenic role. We discovered a conserved interaction of THOR with IGF2BP1 and show that THOR contributes to the mRNA stabilization activities of IGF2BP1. Notably, transgenic THOR knockout produced fertilization defects in zebrafish and also conferred a resistance to melanoma onset. Likewise, ectopic expression of human THOR in zebrafish accelerated the onset of melanoma. THOR represents a novel class of functionally important cancer/testis lncRNAs whose structure and function have undergone positive evolutionary selection.

The role of the histone H3 variant CENPA in prostate cancer.

Overexpression of centromeric proteins has been identified in a number of human malignancies, but the functional and mechanistic contributions of these proteins to disease progression have not been characterized. The centromeric histone H3 variant centromere protein A (CENPA) is an epigenetic mark that determines centromere identity. Here, using an array of approaches, including RNA-sequencing and ChIP-sequencing analyses, immunohistochemistry-based tissue microarrays, and various cell biology assays, we demonstrate that CENPA is highly overexpressed in prostate cancer in both tissue and cell lines and that the level of CENPA expression correlates with the disease stage in a large cohort of patients. Gain-of-function and loss-of-function experiments confirmed that CENPA promotes prostate cancer cell line growth. The results from the integrated sequencing experiments suggested a previously unidentified function of CENPA as a transcriptional regulator that modulates expression of critical proliferation, cell-cycle, and centromere/kinetochore genes. Taken together, our findings show that CENPA overexpression is crucial to prostate cancer growth.

Use of the MyProstateScore Test to Rule Out Clinically Significant Cancer: Validation of a Straightforward Clinical Testing Approach.

PURPOSE: The MyProstateScore test was validated for improved detection of clinically significant (grade group ≥2) prostate cancer relative to prostate specific antigen based risk calculators. We sought to validate an optimal MyProstateScore threshold for clinical use in ruling out grade group ≥2 cancer in men referred for biopsy. MATERIALS AND METHODS: Biopsy naïve men provided post-digital rectal examination urine prior to biopsy. MyProstateScore was calculated using the validated, locked multivariable model including only serum prostate specific antigen, urinary prostate cancer antigen 3 and urinary TMPRSS2:ERG. The MyProstateScore threshold approximating 95% sensitivity for grade group ≥2 cancer was identified in a training cohort, and performance was measured in 2 external validation cohorts. We assessed the 1) overall biopsy referral population and 2) population meeting guideline based testing criteria (ie, prostate specific antigen 3-10, or <3 with suspicious digital rectal examination). RESULTS: Validation cohorts were prospectively enrolled from academic (977 patients, median prostate specific antigen 4.5, IQR 3.1-6.0) and community (548, median prostate specific antigen 4.9, IQR 3.7-6.8) settings. In the overall validation population (1,525 patients), 338 men (22%) had grade group ≥2 cancer on biopsy. The MyProstateScore threshold of 10 provided 97% sensitivity and 98% negative predictive value for grade group ≥2 cancer. MyProstateScore testing would have prevented 387 unnecessary biopsies (33%), while missing only 10 grade group ≥2 cancers (3.0%). In 1,242 patients meeting guideline based criteria, MyProstateScore ≤10 provided 96% sensitivity and 97% negative predictive value, and would have prevented 32% of unnecessary biopsies, missing 3.7% of grade group ≥2 cancers. CONCLUSIONS: In a large, clinically pertinent biopsy referral population, MyProstateScore ≤10 provided exceptional sensitivity and negative predictive value for ruling out grade group ≥2 cancer. This straightforward secondary testing approach would reduce the use of more costly and invasive procedures after screening with prostate specific antigen.

TACO produces robust multisample transcriptome assemblies from RNA-seq.

Accurate transcript structure and abundance inference from RNA sequencing (RNA-seq) data is foundational for molecular discovery. Here we present TACO, a computational method to reconstruct a consensus transcriptome from multiple RNA-seq data sets. TACO employs novel change-point detection to demarcate transcript start and end sites, leading to improved reconstruction accuracy compared with other tools in its class. The tool is available at http://tacorna.github.io and can be readily incorporated into RNA-seq analysis workflows.

Coordinating Tissue Regeneration Through Transforming Growth Factor-ß Activated Kinase 1 Inactivation and Reactivation.

Aberrant wound healing presents as inappropriate or insufficient tissue formation. Using a model of musculoskeletal injury, we demonstrate that loss of transforming growth factor-ß activated kinase 1 (TAK1) signaling reduces inappropriate tissue formation (heterotopic ossification) through reduced cellular differentiation. Upon identifying increased proliferation with loss of TAK1 signaling, we considered a regenerative approach to address insufficient tissue production through coordinated inactivation of TAK1 to promote cellular proliferation, followed by reactivation to elicit differentiation and extracellular matrix production. Although the current regenerative medicine paradigm is centered on the effects of drug treatment ("drug on"), the impact of drug withdrawal ("drug off") implicit in these regimens is unknown. Because current TAK1 inhibitors are unable to phenocopy genetic Tak1 loss, we introduce the dual-inducible COmbinational Sequential Inversion ENgineering (COSIEN) mouse model. The COSIEN mouse model, which allows us to study the response to targeted drug treatment ("drug on") and subsequent withdrawal ("drug off") through genetic modification, was used here to inactivate and reactivate Tak1 with the purpose of augmenting tissue regeneration in a calvarial defect model. Our study reveals the importance of both the "drug on" (Cre-mediated inactivation) and "drug off" (Flp-mediated reactivation) states during regenerative therapy using a mouse model with broad utility to study targeted therapies for disease. Stem Cells 2019;37:766-778.

MechRNA: prediction of lncRNA mechanisms from RNA-RNA and RNA-protein interactions.

Motivation: Long non-coding RNAs (lncRNAs) are defined as transcripts longer than 200 nt that do not get translated into proteins. Often these transcripts are processed (spliced, capped and polyadenylated) and some are known to have important biological functions. However, most lncRNAs have unknown or poorly understood functions. Nevertheless, because of their potential role in cancer, lncRNAs are receiving a lot of attention, and the need for computational tools to predict their possible mechanisms of action is more than ever. Fundamentally, most of the known lncRNA mechanisms involve RNA-RNA and/or RNA-protein interactions. Through accurate predictions of each kind of interaction and integration of these predictions, it is possible to elucidate potential mechanisms for a given lncRNA. Results: Here, we introduce MechRNA, a pipeline for corroborating RNA-RNA interaction prediction and protein binding prediction for identifying possible lncRNA mechanisms involving specific targets or on a transcriptome-wide scale. The first stage uses a version of IntaRNA2 with added functionality for efficient prediction of RNA-RNA interactions with very long input sequences, allowing for large-scale analysis of lncRNA interactions with little or no loss of optimality. The second stage integrates protein binding information pre-computed by GraphProt, for both the lncRNA and the target. The final stage involves inferring the most likely mechanism for each lncRNA/target pair. This is achieved by generating candidate mechanisms from the predicted interactions, the relative locations of these interactions and correlation data, followed by selection of the most likely mechanistic explanation using a combined P-value. We applied MechRNA on a number of recently identified cancer-related lncRNAs (PCAT1, PCAT29 and ARLnc1) and also on two well-studied lncRNAs (PCA3 and 7SL). This led to the identification of hundreds of high confidence potential targets for each lncRNA and corresponding mechanisms. These predictions include the known competitive mechanism of 7SL with HuR for binding on the tumor suppressor TP53, as well as mechanisms expanding what is known about PCAT1 and ARLn1 and their targets BRCA2 and AR, respectively. For PCAT1-BRCA2, the mechanism involves competitive binding with HuR, which we confirmed using HuR immunoprecipitation assays. Availability and implementation: MechRNA is available for download at https://bitbucket.org/compbio/mechrna. Supplementary information: Supplementary data are available at Bioinformatics online.

Strategic Targeting of Multiple BMP Receptors Prevents Trauma-Induced Heterotopic Ossification.

Trauma-induced heterotopic ossification (tHO) is a condition of pathologic wound healing, defined by the progressive formation of ectopic bone in soft tissue following severe burns or trauma. Because previous studies have shown that genetic variants of HO, such as fibrodysplasia ossificans progressiva (FOP), are caused by hyperactivating mutations of the type I bone morphogenetic protein receptor (T1-BMPR) ACVR1/ALK2, studies evaluating therapies for HO have been directed primarily toward drugs for this specific receptor. However, patients with tHO do not carry known T1-BMPR mutations. Here we show that, although BMP signaling is required for tHO, no single T1-BMPR (ACVR1/ALK2, BMPR1a/ALK3, or BMPR1b/ALK6) alone is necessary for this disease, suggesting that these receptors have functional redundancy in the setting of tHO. By utilizing two different classes of BMP signaling inhibitors, we developed a translational approach to treatment, integrating treatment choice with existing diagnostic options. Our treatment paradigm balances either immediate therapy with reduced risk for adverse effects (Alk3-Fc) or delayed therapy with improved patient selection but greater risk for adverse effects (LDN-212854).

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer.

Importance: Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater). Objective: To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers. Design, Setting, and Participants: RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023. Exposure: Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy. Main Outcomes and Measures: Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily. Results: Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater. Conclusions and Relevance: In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

Association of MyProstateScore (MPS) with prostate cancer grade in the radical prostatectomy specimen.

BACKGROUND: To evaluate the association between urinary MyProstateScore (MPS) and pathologic grade group (GG) at surgery in men diagnosed with GG1 prostate cancer (PCa) on biopsy. METHODS: Using an institutional biospecimen protocol, we identified men with GG1 PCa on biopsy and PSA ≤10 ng/ml who underwent radical prostatectomy (RP) at the University of Michigan. MPS was retrospectively calculated using prospectively collected, post-DRE urine samples. The primary outcome was upgrading on RP pathology, defined as GG ≥ 2. The associations of MPS, PSA, and PSA density (PSAD) with upgrading were assessed on univariable logistic regression, and the predictive accuracy of each marker was estimated by the area under the receiver operating characteristic curve (AUC). RESULTS: There were 52 men with urinary specimens available that met study criteria, based on biopsy Gleason Grade and specimen collection. At RP, 17 men (33%) had GG1 cancer and 35 (67%) had GG ≥ 2 cancer. Preoperative MPS was significantly higher in patients with GG ≥ 2 cancer at surgery (median 37.8 [IQR, 22.2-52.4]) as compared to GG1 (19.3 [IQR, 9.2-29.4]; P = 0.001). On univariable logistic regression, increasing MPS values were significantly associated with upgrading (odds ratio 1.07 per one-unit MPS increase, 95% confidence interval 1.02-1.12, P = 0.004), while PSA and PSAD were not significantly associated with upgrading. Similarly, the discriminative ability of the MPS model (AUC 0.78) for upgrading at RP was higher compared to models based on PSA (AUC 0.52) and PSAD (AUC 0.62). CONCLUSIONS: In men diagnosed with GG1 PCa who underwent surgery, MPS was significantly associated with RP cancer grade. In this limited cohort of men, these findings suggest that MPS could help identify patients with undetected high-grade cancer. Additional studies are needed to better characterize this association.