JUN mediates the senescence associated secretory phenotype and immune cell recruitment to prevent prostate cancer progression.

BACKGROUND: Prostate cancer develops through malignant transformation of the prostate epithelium in a stepwise, mutation-driven process. Although activator protein-1 transcription factors such as JUN have been implicated as potential oncogenic drivers, the molecular programs contributing to prostate cancer progression are not fully understood. METHODS: We analyzed JUN expression in clinical prostate cancer samples across different stages and investigated its functional role in a Pten-deficient mouse model. We performed histopathological examinations, transcriptomic analyses and explored the senescence-associated secretory phenotype in the tumor microenvironment. RESULTS: Elevated JUN levels characterized early-stage prostate cancer and predicted improved survival in human and murine samples. Immune-phenotyping of Pten-deficient prostates revealed high accumulation of tumor-infiltrating leukocytes, particularly innate immune cells, neutrophils and macrophages as well as high levels of STAT3 activation and IL-1ß production. Jun depletion in a Pten-deficient background prevented immune cell attraction which was accompanied by significant reduction of active STAT3 and IL-1ß and accelerated prostate tumor growth. Comparative transcriptome profiling of prostate epithelial cells revealed a senescence-associated gene signature, upregulation of pro-inflammatory processes involved in immune cell attraction and of chemokines such as IL-1ß, TNF-α, CCL3 and CCL8 in Pten-deficient prostates. Strikingly, JUN depletion reversed both the senescence-associated secretory phenotype and senescence-associated immune cell infiltration but had no impact on cell cycle arrest. As a result, JUN depletion in Pten-deficient prostates interfered with the senescence-associated immune clearance and accelerated tumor growth. CONCLUSIONS: Our results suggest that JUN acts as tumor-suppressor and decelerates the progression of prostate cancer by transcriptional regulation of senescence- and inflammation-associated genes. This study opens avenues for novel treatment strategies that could impede disease progression and improve patient outcomes.

STAT3/LKB1 controls metastatic prostate cancer by regulating mTORC1/CREB pathway.

Prostate cancer (PCa) is a common and fatal type of cancer in men. Metastatic PCa (mPCa) is a major factor contributing to its lethality, although the mechanisms remain poorly understood. PTEN is one of the most frequently deleted genes in mPCa. Here we show a frequent genomic co-deletion of PTEN and STAT3 in liquid biopsies of patients with mPCa. Loss of Stat3 in a Pten-null mouse prostate model leads to a reduction of LKB1/pAMPK with simultaneous activation of mTOR/CREB, resulting in metastatic disease. However, constitutive activation of Stat3 led to high LKB1/pAMPK levels and suppressed mTORC1/CREB pathway, preventing mPCa development. Metformin, one of the most widely prescribed therapeutics against type 2 diabetes, inhibits mTORC1 in liver and requires LKB1 to mediate glucose homeostasis. We find that metformin treatment of STAT3/AR-expressing PCa xenografts resulted in significantly reduced tumor growth accompanied by diminished mTORC1/CREB, AR and PSA levels. PCa xenografts with deletion of STAT3/AR nearly completely abrogated mTORC1/CREB inhibition mediated by metformin. Moreover, metformin treatment of PCa patients with high Gleason grade and type 2 diabetes resulted in undetectable mTORC1 levels and upregulated STAT3 expression. Furthermore, PCa patients with high CREB expression have worse clinical outcomes and a significantly increased risk of PCa relapse and metastatic recurrence. In summary, we have shown that STAT3 controls mPCa via LKB1/pAMPK/mTORC1/CREB signaling, which we have identified as a promising novel downstream target for the treatment of lethal mPCa.

A tissue miRNA expression pattern is associated with disease aggressiveness of localized prostate cancer.

BACKGROUND: Prostate cancer (PCa) is a heterogeneous malignancy with high variability in clinical course. Insufficient stratification according to the aggressiveness at the time of diagnosis causes unnecessary or delayed treatment. Current stratification systems are not effective enough because they are based on clinical, surgical or biochemical parameters, but do not take into account molecular factors driving PCa cancerogenesis. MicroRNAs (miRNAs) are important players in molecular pathogenesis of PCa and could serve as valuable biomarkers for the assessment of disease aggressiveness and its prognosis. METHODS: In the study, in total, 280 PCa patients were enrolled. The miRNA expression profiles were analyzed in FFPE PCa tissue using the miRCURY LNA miRNA PCR System. The expression levels of candidate miRNAs were further verified by two-level validation using the RT-qPCR method and evaluated in relation to PCa stratification reflecting the disease aggressiveness. RESULTS: MiRNA profiling revealed 172 miRNAs dysregulated between aggressive (ISUP 3-5) and indolent PCa (ISUP 1) (p < 0.05). In the training and validation cohort, miR-15b-5p and miR-106b-5p were confirmed to be significantly upregulated in tissue of aggressive PCa when their level was associated with disease aggressiveness. Furthermore, we established a prognostic score combining the level of miR-15b-5p and miR-106b-5p with serum PSA level, which discriminated indolent PCa from an aggressive form with even higher analytical parameters (AUC being 0.9338 in the training set and 0.8014 in the validation set, respectively). The score was also associated with 5-year biochemical progression-free survival (bPFS) of PCa patients. CONCLUSIONS: We identified a miRNA expression pattern associated with disease aggressiveness in prostate cancer patients. These miRNAs may be of biological interest as the focus can be also set on their specific role within the molecular pathology and the molecular mechanism that underlies the aggressivity of prostate cancer.

Radiogenomic markers enable risk stratification and inference of mutational pathway states in head and neck cancer.

PURPOSE: Head and neck squamous cell carcinomas (HNSCCs) are a molecularly, histologically, and clinically heterogeneous set of tumors originating from the mucosal epithelium of the oral cavity, pharynx, and larynx. This heterogeneous nature of HNSCC is one of the main contributing factors to the lack of prognostic markers for personalized treatment. The aim of this study was to develop and identify multi-omics markers capable of improved risk stratification in this highly heterogeneous patient population. METHODS: In this retrospective study, we approached this issue by establishing radiogenomics markers to identify high-risk individuals in a cohort of 127 HNSCC patients. Hybrid in vivo imaging and whole-exome sequencing were employed to identify quantitative imaging markers as well as genetic markers on pathway-level prognostic in HNSCC. We investigated the deductibility of the prognostic genetic markers using anatomical and metabolic imaging using positron emission tomography combined with computed tomography. Moreover, we used statistical and machine learning modeling to investigate whether a multi-omics approach can be used to derive prognostic markers for HNSCC. RESULTS: Radiogenomic analysis revealed a significant influence of genetic pathway alterations on imaging markers. A highly prognostic radiogenomic marker based on cellular senescence was identified. Furthermore, the radiogenomic biomarkers designed in this study vastly outperformed the prognostic value of markers derived from genetics and imaging alone. CONCLUSION: Using the identified markers, a clinically meaningful stratification of patients is possible, guiding the identification of high-risk patients and potentially aiding in the development of effective targeted therapies.

KMT2C methyltransferase domain regulated INK4A expression suppresses prostate cancer metastasis.

BACKGROUND: Frequent truncation mutations of the histone lysine N-methyltransferase KMT2C have been detected by whole exome sequencing studies in various cancers, including malignancies of the prostate. However, the biological consequences of these alterations in prostate cancer have not yet been elucidated. METHODS: To investigate the functional effects of these mutations, we deleted the C-terminal catalytic core motif of Kmt2c specifically in mouse prostate epithelium. We analysed the effect of Kmt2c SET domain deletion in a Pten-deficient PCa mouse model in vivo and of truncation mutations of KMT2C in a large number of prostate cancer patients. RESULTS: We show here for the first time that impaired KMT2C methyltransferase activity drives proliferation and PIN formation and, when combined with loss of the tumour suppressor PTEN, triggers loss of senescence, metastatic dissemination and dramatically reduces life expectancy. In Kmt2c-mutated tumours we show enrichment of proliferative MYC gene signatures and loss of expression of the cell cycle repressor p16INK4A. In addition, we observe a striking reduction in disease-free survival of patients with KMT2C-mutated prostate cancer. CONCLUSIONS: We identified truncating events of KMT2C as drivers of proliferation and PIN formation. Loss of PTEN and KMT2C in prostate cancer results in loss of senescence, metastatic dissemination and reduced life expectancy. Our data demonstrate the prognostic significance of KMT2C mutation status in prostate cancer patients. Inhibition of the MYC signalling axis may be a viable treatment option for patients with KMT2C truncations and therefore poor prognosis.

Linked by Ancestral Bonds: Multiple Whole-Genome Duplications and Reticulate Evolution in a Brassicaceae Tribe.

Pervasive hybridization and whole-genome duplications (WGDs) influenced genome evolution in several eukaryotic lineages. Although frequent and recurrent hybridizations may result in reticulate phylogenies, the evolutionary events underlying these reticulations, including detailed structure of the ancestral diploid and polyploid genomes, were only rarely reconstructed. Here, we elucidate the complex genomic history of a monophyletic clade from the mustard family (Brassicaceae), showing contentious relationships to the early-diverging clades of this model plant family. Genome evolution in the crucifer tribe Biscutelleae (∼60 species, 5 genera) was dominated by pervasive hybridizations and subsequent genome duplications. Diversification of an ancestral diploid genome into several divergent but crossable genomes was followed by hybridizations between these genomes. Whereas a single genus (Megadenia) remained diploid, the four remaining genera originated by allopolyploidy (Biscutella, Lunaria, Ricotia) or autopolyploidy (Heldreichia). The contentious relationships among the Biscutelleae genera, and between the tribe and other early diverged crucifer lineages, are best explained by close genomic relatedness among the recurrently hybridizing ancestral genomes. By using complementary cytogenomics and phylogenomics approaches, we demonstrate that the origin of a monophyletic plant clade can be more complex than a parsimonious assumption of a single WGD spurring postpolyploid cladogenesis. Instead, recurrent hybridization among the same and/or closely related parental genomes may phylogenetically interlink diploid and polyploid genomes despite the incidence of multiple independent WGDs. Our results provide new insights into evolution of early-diverging Brassicaceae lineages and elucidate challenges in resolving the contentious relationships within and between land plant lineages with pervasive hybridization and WGDs.

LncRNA PVT1 is increased in renal cell carcinoma and affects viability and migration in vitro.

BACKGROUND: Renal cell carcinoma is difficult to diagnose and unpredictable in disease course and severity. There are no specific biomarkers for diagnosis and prognosis estimation feasible in clinical practice. Long non-coding RNAs (lncRNAs) have emerged as potent regulators of gene expression in recent years. Aside from their cellular role, their expression patterns could be used as a biomarker of ongoing pathology. METHODS: In this work, we used next-generation sequencing for global lncRNA expression profiling in tumor and non-tumor tissue of RCC patients. The four candidate lncRNAs have been further validated on an independent cohort. PVT1, as the most promising lncRNA, has also been studied using functional in vitro tests. RESULTS: Next-generation sequencing showed significant dysregulation of 1163 lncRNAs; among them top 20 dysregulated lncRNAs were AC061975.7, AC124017.1, AP000696.1, AC148477.4, LINC02437, GATA3-AS, LINC01762, LINC01230, LINC01271, LINC01187, LINC00472, AC007849.1, LINC00982, LINC01543, AL031710.1, and AC019197.1 as down-regulated lncRNAs; and SLC16A1-AS1, PVT1, LINC0887, and LUCAT1 as up-regulated lncRNAs. We observed statistically significant dysregulation of PVT1, LUCAT1, and LINC00982. Moreover, we studied the effect of artificial PVT1 decrease in renal cell line 786-0 and observed an effect on cell viability and migration. CONCLUSION: Our results show not only the diagnostic but also the therapeutic potential of PVT1 in renal cell carcinoma.

Identification of Plasmatic MicroRNA-206 as New Predictor of Early Recurrence of Atrial Fibrillation After Catheter Ablation Using Next-generation Sequencing.

BACKGROUND: Catheter ablation (CA) of atrial fibrillation (AF) is indicated in patients with recurrent and symptomatic AF episodes. Despite the strict inclusion/exclusion criteria, AF recurrence after CA remains high. Identification of a novel biomarker that would predict AF recurrence would help to stratify the patients. The aim of the study was to seek novel biomarkers among the plasmatic microRNAs (miRNAs, miRs). METHODS: A prospective monocentric study was conducted. A total of 49 consecutive AF patients indicated for CA were included. Blood sampling was performed prior to CA. RNA was isolated from plasma using commercial kits. In the exploration phase, small RNA sequencing was performed in ten AF patients (five with and five without AF recurrence) using Illumina instrument. In the validation phase, levels of selected miRNAs were determined using quantitative reverse transcription polymerase chain reaction (qRT-PCR) in all participants. RESULTS: Altogether, 22 miRNAs were identified as altered between the groups by next-generation sequencing (using the DESeq2 algorithm). Using qRT-PCR, levels of the five most altered miRNAs (miR-190b/206/326/505-5p/1296-5p) were verified in the whole cohort. Plasma levels of hsa-miR-206 were significantly higher in patients with early (within 6 months) AF recurrence and showed an increase of risk recurrence,2.65 times by every increase in its level by 1 unit in the binary logistic regression. CONCLUSION: We have identified a set of 22 plasmatic miRNAs that differ between the patients with and without AF recurrence after CA and confirmed hsa-miR-206 as a novel miRNA associated with early AF recurrence. Results shall be verified in a larger independent cohort.

A novel assessment of whole-mount Gleason grading in prostate cancer to identify candidates for radical prostatectomy: a machine learning-based multiomics study.

Purpose: This study aims to assess whole-mount Gleason grading (GG) in prostate cancer (PCa) accurately using a multiomics machine learning (ML) model and to compare its performance with biopsy-proven GG (bxGG) assessment. Materials and Methods: A total of 146 patients with PCa recruited in a pilot study of a prospective clinical trial (NCT02659527) were retrospectively included in the side study, all of whom underwent 68Ga-PSMA-11 integrated positron emission tomography (PET) / magnetic resonance (MR) before radical prostatectomy (RP) between May 2014 and April 2020. To establish a multiomics ML model, we quantified PET radiomics features, pathway-level genomics features from whole exome sequencing, and pathomics features derived from immunohistochemical staining of 11 biomarkers. Based on the multiomics dataset, five ML models were established and validated using 100-fold Monte Carlo cross-validation. Results: Among five ML models, the random forest (RF) model performed best in terms of the area under the curve (AUC). Compared to bxGG assessment alone, the RF model was superior in terms of AUC (0.87 vs 0.75), specificity (0.72 vs 0.61), positive predictive value (0.79 vs 0.75), and accuracy (0.78 vs 0.77) and showed slightly decreased sensitivity (0.83 vs 0.89) and negative predictive value (0.80 vs 0.81). Among the feature categories, bxGG was identified as the most important feature, followed by pathomics, clinical, radiomics and genomics features. The three important individual features were bxGG, PSA staining and one intensity-related radiomics feature. Conclusion: The findings demonstrate a superior assessment of the developed multiomics-based ML model in whole-mount GG compared to the current clinical baseline of bxGG. This enables personalized patient management by identifying high-risk PCa patients for RP.

Investigation of long non-coding RNAs in extracellular vesicles from low-volume blood serum specimens of colorectal cancer patients.

Colorectal cancer (CRC) is the second most prevalent cancer type worldwide, which highlights the urgent need for non-invasive biomarkers for its early detection and improved prognosis. We aimed to investigate the patterns of long non-coding RNAs (lncRNAs) in small extracellular vesicles (sEVs) collected from low-volume blood serum specimens of CRC patients, focusing on their potential as diagnostic biomarkers. Our research comprised two phases: an initial exploratory phase involving RNA sequencing of sEVs from 76 CRC patients and 29 healthy controls, and a subsequent validation phase with a larger cohort of 159 CRC patients and 138 healthy controls. Techniques such as dynamic light scattering, transmission electron microscopy, and Western blotting were utilized for sEV characterization. Optimized protocol for sEV purification, RNA isolation and preamplification was applied to successfully sequence the RNA content of sEVs and validate the results by RT-qPCR. We successfully isolated sEVs from blood serum and prepared sequencing libraries from a low amount of RNA. High-throughput sequencing identified differential levels of 460 transcripts between CRC patients and healthy controls, including mRNAs, lncRNAs, and pseudogenes, with approximately 20% being lncRNAs, highlighting several tumor-specific lncRNAs that have not been associated with CRC development and progression. The validation phase confirmed the upregulation of three lncRNAs (NALT1, AL096828, and LINC01637) in blood serum of CRC patients. This study not only identified lncRNA profiles in a population of sEVs from low-volume blood serum specimens of CRC patients but also highlights the value of innovative techniques in biomolecular research, particularly for the detection and analysis of low-abundance biomolecules in clinical samples. The identification of specific lncRNAs associated with CRC provides a foundation for future research into their functional roles in cancer development and potential clinical applications.