TERT expression is associated with metastasis from thin primaries, exhausted CD4+ T cells in melanoma and with DNA repair across cancer entities.

Telomerase reverse transcriptase (TERT) promoter mutations occur frequently in cancer, have been associated with increased TERT expression and cell proliferation, and could potentially influence therapeutic regimens for melanoma. As the role of TERT expression in malignant melanoma and the non-canonical functions of TERT remain understudied, we aimed to extend the current knowledge on the impact of TERT promoter mutations and expression alterations in tumor progression by analyzing several highly annotated melanoma cohorts. Using multivariate models, we found no consistent association for TERT promoter mutations or TERT expression with the survival rate in melanoma cohorts under immune checkpoint inhibition. However, the presence of CD4+ T cells increased with TERT expression and correlated with the expression of exhaustion markers. While the frequency of promoter mutations did not change with Breslow thickness, TERT expression was increased in metastases arising from thinner primaries. As single-cell RNA-sequencing (RNA-seq) showed that TERT expression was associated with genes involved in cell migration and dynamics of the extracellular matrix, this suggests a role of TERT during invasion and metastasis. Co-regulated genes found in several bulk tumors and single-cell RNA-seq cohorts also indicated non-canonical functions of TERT related to mitochondrial DNA stability and nuclear DNA repair. This pattern was also evident in glioblastoma and across other entities. Hence, our study adds to the role of TERT expression in cancer metastasis and potentially also immune resistance.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer.

BACKGROUND: Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression. METHODS: We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan-Meier estimator, log-rank test, and Cox regression. RESULTS: Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05). CONCLUSIONS: Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

Database for queries of melanoma cohorts with molecular and clinical data.

Large genome-scale studies are deposited in various public sequence repositories. However, their access and analysis can be non-trivial to infrequent users. Here, we present a new database connecting whole transcriptomes with clinical data for straight-forward access and analysis of patient-specific samples. Users can perform association tests of survival and gene expression across different cohorts, identify cell-type expressions, or correlate the presence of immune cells. In summary, we present a new data hub for bench scientists to perform replication and discovery studies.

ProstaTrend-A Multivariable Prognostic RNA Expression Score for Aggressive Prostate Cancer.

BACKGROUND: Prostate cancer (PCa) is the most prevalent solid cancer among men in Western Countries. The clinical behavior of localized PCa is highly variable. Some cancers are aggressive leading to death, while others can even be monitored safely. Hence, there is a high clinical need for precise biomarkers for identification of aggressive disease in addition to established clinical parameters. OBJECTIVE: To develop an RNA expression-based score for the prediction of PCa prognosis that facilitates clinical decision making. DESIGN, SETTING, AND PARTICIPANTS: We assessed 233 tissue specimens of PCa patients with long-term follow-up data from fresh-frozen radical prostatectomies (RPs), from formalin-fixed and paraffin-embedded RP specimens and biopsies by transcriptome-wide next-generation sequencing and customized expression microarrays. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We applied Cox proportional hazard models to the cohorts from different platforms and specimen types. Evidence from these models was combined by fixed-effect meta-analysis to identify genes predictive of the time to death of disease (DoD). Genes were combined by a weighted median approach into a prognostic score called ProstaTrend and transferred for the prediction of biochemical recurrence (BCR) after RP in an independent cohort of The Cancer Genome Atlas (TCGA). RESULTS AND LIMITATIONS: ProstaTrend comprising ∼1400 genes was significantly associated with DoD in the training cohort of PCa patients treated by RP (leave-one-out cross-validation, Cox regression: p=2e-09) and with BCR in the TCGA validation cohort (Cox regression: p=3e-06). The prognostic impact persisted after multivariable Cox regression analysis adjusting for Gleason grading group (GG) ≥3 and resection status (p=0.001; DoD, training cohort) and for GG≥3, pathological stage ≥T3, and resection state (p=0.037; BCR, validation cohort). CONCLUSIONS: ProstaTrend is a transcriptome-based score that predicts DoD and BCR in cohorts of PCa patients treated with RP. PATIENT SUMMARY: ProstaTrend provides molecular patient risk stratification after radical prostatectomy.

The Role of lncRNAs TAPIR-1 and -2 as Diagnostic Markers and Potential Therapeutic Targets in Prostate Cancer.

In search of new biomarkers suitable for the diagnosis and treatment of prostate cancer, genome-wide transcriptome sequencing was carried out with tissue specimens from 40 prostate cancer (PCa) and 8 benign prostate hyperplasia patients. We identified two intergenic long non-coding transcripts, located in close genomic proximity, which are highly expressed in PCa. Microarray studies on a larger cohort comprising 155 patients showed a profound diagnostic potential of these transcripts (AUC~0.94), which we designated as tumor associated prostate cancer increased lncRNA (TAPIR-1 and -2). To test their therapeutic potential, knockdown experiments with siRNA were carried out. The knockdown caused an increase in the p53/TP53 tumor suppressor protein level followed by downregulation of a large number of cell cycle- and DNA-damage repair key regulators. Furthermore, in radiation therapy resistant tumor cells, the knockdown leads to a renewed sensitization of these cells to radiation treatment. Accordingly, in a preclinical PCa xenograft model in mice, the systemic application of nanoparticles loaded with siRNA targeting TAPIR-1 significantly reduced tumor growth. These findings point to a crucial role of TAPIR-1 and -2 in PCa.

Master and servant: LINC00152 - a STAT3-induced long noncoding RNA regulates STAT3 in a positive feedback in human multiple myeloma.

BACKGROUND: The survival of INA-6 human multiple myeloma cells is strictly dependent upon the Interleukin-6-activated transcription factor STAT3. Although transcriptional analyses have revealed many genes regulated by STAT3, to date no protein-coding STAT3 target gene is known to mediate survival in INA-6 cells. Therefore, the aim here was to identify and analyze non-protein-coding STAT3 target genes. In addition to the oncogenic microRNA-21, we previously described five long noncoding RNAs (lncRNAs) induced by STAT3, named STAiRs. Here, we focus on STAT3-induced RNA 18 (STAiR18), an mRNA-like, long ncRNA that is duplicated in the human lineage. One STAiR18 locus is annotated as the already well described LINC00152/CYTOR, however, the other harbors the MIR4435-2HG gene and is, up to now, barely described. METHODS: CAPTURE-RNA-sequencing was used to analyze STAiR18 transcript architecture. To identify the STAiR18 and STAT3 phenotype, siRNA-based knockdowns were performed and microarrays were applied to identify their target genes. RNA-binding partners of STAiR18 were determined by Chromatin-Isolation-by-RNA-Purification (ChIRP) and subsequent sequencing. STAT3 expression in dependence of STAiR18 was investigated by immunoblots, chromatin- and RNA-immunoprecipitations. RESULTS: As identified by CAPTURE-RNA sequencing, a complex splice pattern originates from both STAiR18 loci, generating different transcripts. Knockdown of the most abundant STAiR18 isoforms dramatically decreased INA-6 cell vitality, suggesting a functional role in myeloma cells. Additionally, STAiR18 and STAT3 knockdowns yielded overlapping changes of transcription patterns in INA-6 cells, suggesting a close functional interplay between the two factors. Moreover, Chromatin isolation by RNA purification (ChIRP), followed by genome-wide RNA sequencing showed that STAiR18 associates specifically with the STAT3 primary transcript. Furthermore, the knockdown of STAiR18 reduced STAT3 levels on both the RNA and protein levels, suggesting a positive feedback between both molecules. Furthermore, STAiR18 knockdown changes the histone methylation status of the STAT3 locus, which explains the positive feedback and indicates that STAiR18 is an epigenetic modulator. CONCLUSION: Hence, STAiR18 is an important regulator of myeloma cell survival and is strongly associated with the oncogenic function of STAT3. The close functional interplay between STAT3 and STAiR18 suggests a novel principle of regulatory interactions between long ncRNAs and signaling pathways.

Deep sequencing and automated histochemistry of human tissue slice cultures improve their usability as preclinical model for cancer research.

Cancer research requires models closely resembling the tumor in the patient. Human tissue cultures can overcome interspecies limitations of animal models or the loss of tissue architecture in in vitro models. However, analysis of tissue slices is often limited to histology. Here, we demonstrate that slices are also suitable for whole transcriptome sequencing and present a method for automated histochemistry of whole slices. Tumor and peritumoral tissue from a patient with glioblastoma was processed to slice cultures, which were treated with standard therapy including temozolomide and X-irradiation. Then, RNA sequencing and automated histochemistry were performed. RNA sequencing was successfully accomplished with a sequencing depth of 243 to 368 x 106 reads per sample. Comparing tumor and peritumoral tissue, we identified 1888 genes significantly downregulated and 2382 genes upregulated in tumor. Treatment significantly downregulated 2017 genes, whereas 1399 genes were upregulated. Pathway analysis revealed changes in the expression profile of treated glioblastoma tissue pointing towards downregulated proliferation. This was confirmed by automated analysis of whole tissue slices stained for Ki67. In conclusion, we demonstrate that RNA sequencing of tissue slices is possible and that histochemical analysis of whole tissue slices can be automated which increases the usability of this preclinical model.

uap: reproducible and robust HTS data analysis.

BACKGROUND: A lack of reproducibility has been repeatedly criticized in computational research. High throughput sequencing (HTS) data analysis is a complex multi-step process. For most of the steps a range of bioinformatic tools is available and for most tools manifold parameters need to be set. Due to this complexity, HTS data analysis is particularly prone to reproducibility and consistency issues. We have defined four criteria that in our opinion ensure a minimal degree of reproducible research for HTS data analysis. A series of workflow management systems is available for assisting complex multi-step data analyses. However, to the best of our knowledge, none of the currently available work flow management systems satisfies all four criteria for reproducible HTS analysis. RESULTS: Here we present uap, a workflow management system dedicated to robust, consistent, and reproducible HTS data analysis. uap is optimized for the application to omics data, but can be easily extended to other complex analyses. It is available under the GNU GPL v3 license at https://github.com/yigbt/uap. CONCLUSIONS: uap is a freely available tool that enables researchers to easily adhere to reproducible research principles for HTS data analyses.

Extracellular vesicle-associated miRNAs in ovarian cancer - design of an integrated NGS-based workflow for the identification of blood-based biomarkers for platinum-resistance.

Background Extracellular vesicle (EV)-associated microRNAs (miRNAs) have been suggested as promising biomarkers for blood-based cancer diagnosis. However, one of the major limitations for the use of EVs with diagnostic purpose is the lack of standardized EV-profiling techniques. In this regard, the objective of our study was to design an integrated next-generation sequencing (NGS)-based workflow for analyzing the signature of EV-associated miRNA in the plasma of platinum-resistant ovarian cancer patients. Methods For EV-extraction, different enrichment methods were compared (ExoQuick vs. exoRNeasy). NGS was performed with the Illumina platform. Results We established an integrated NGS-based workflow, including EV-enrichment with the ExoQuick system, which resulted in an optimal RNA-yield and consistent small RNA libraries. We applied this workflow in a pilot cohort of clinically documented platinum-sensitive (n=15) vs. platinum-resistant (n=15) ovarian cancer patients, resulting in a panel of mature EV-associated miRNAs (including ovarian cancer associated miR-181a, miR-1908, miR-21, miR-486 and miR-223), which were differentially abundant in the plasma of platinum-resistant patients. Conclusions This is the first study, analyzing the profile of EV-associated miRNAs in platinum-resistant ovarian cancer patients. We provide rationale to further validate these miRNA candidates in an independent set of patients, in order to characterize their biomarker potential as predictors for platinum-resistance.

A mutation in Orai1 causes immune deficiency by abrogating CRAC channel function.

Antigen stimulation of immune cells triggers Ca2+ entry through Ca2+ release-activated Ca2+ (CRAC) channels, promoting the immune response to pathogens by activating the transcription factor NFAT. We have previously shown that cells from patients with one form of hereditary severe combined immune deficiency (SCID) syndrome are defective in store-operated Ca2+ entry and CRAC channel function. Here we identify the genetic defect in these patients, using a combination of two unbiased genome-wide approaches: a modified linkage analysis with single-nucleotide polymorphism arrays, and a Drosophila RNA interference screen designed to identify regulators of store-operated Ca2+ entry and NFAT nuclear import. Both approaches converged on a novel protein that we call Orai1, which contains four putative transmembrane segments. The SCID patients are homozygous for a single missense mutation in ORAI1, and expression of wild-type Orai1 in SCID T cells restores store-operated Ca2+ influx and the CRAC current (I(CRAC)). We propose that Orai1 is an essential component or regulator of the CRAC channel complex.