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Human serum and other body fluids are rich resources for the identification of novel biomarkers, which can be measured in routine clinical diagnosis. microRNAs are small non-coding RNA molecules, which have an important function in regulating RNA stability and gene expression. The deregulation of microRNAs has been linked to cancer development and tumor progression. Recently, it has been reported that serum and other body fluids contain sufficiently stable microRNA signatures. Thus, the profiles of circulating microRNAs have been explored in a variety of studies aiming at the identification of novel non-invasive biomarkers. In this review, we discuss recent findings indicating that circulating microRNAs are useful as non-invasive biomarkers for different tumor types. Additionally, we summarize the knowledge about the mechanism of microRNA release and the putative functional roles of circulating microRNAs. Although several challenges remain to be addressed, circulating microRNAs have the potential to be useful for the diagnosis and prognosis of cancer diseases.

Introduction Artificial intelligence (AI) is increasingly used in healthcare. AI-based chatbots can act as automated conversational agents, capable of promoting health and providing education at any time. The objective of this study was to develop and evaluate a user-friendly medical chatbot (prostate cancer communication assistant (PROSCA)) for provisioning patient information about early detection of prostate cancer (PC). Methods The chatbot was developed to provide information on prostate diseases, diagnostic tests for PC detection, stages, and treatment options. Ten men aged 49 to 81 years with suspicion of PC were enrolled in this study. Nine of ten patients used the chatbot during the evaluation period and filled out the questionnaires on usage and usability, perceived benefits, and potential for improvement. Results The chatbot was straightforward to use, with 78% of users not needing any assistance during usage. In total, 89% of the chatbot users in the study experienced a clear to moderate increase in knowledge about PC through the chatbot. All study participants who tested the chatbot would like to re-use a medical chatbot in the future and support the use of chatbots in the clinical routine. Conclusions Through the introduction of the chatbot PROSCA, we created and evaluated an innovative evidence-based health information tool in the field of PC, allowing targeted support for doctor–patient communication and offering great potential in raising awareness, patient education, and support. Our study revealed that a medical chatbot in the field of early PC detection is readily accepted and benefits patients as an additional informative tool.

Aggressive prostate cancer (PC) represents a significant health concern. Conventional screening methods, primarily based on prostate-specific antigen (PSA) levels, lack specificity, leading to an urgent need for more accurate diagnostic tools. This study investigates whether integrating clinical and routine blood laboratory parameters can improve the early non-invasive prediction of aggressive PC. In a pilot study of 578 patients with suspicion of PC, 28 laboratory values alongside data on family history, diet, and lifestyle were analyzed. A logistic regression classifier was developed, with model performance evaluated using repeated k-fold cross-validation on the complete dataset (n = 282). Participants were categorized into healthy, moderate PC (ISUP 1–2), and aggressive PC (ISUP 3–5). Significant associations were found between PC aggressiveness and lower levels of androstenedione, dehydroepiandrosterone-sulfate (DHEA-S) and free PSA%, as well as higher levels of sex hormone binding globulin (SHBG). The integration of these serum markers with clinical parameters into a new multi-stage risk classifier significantly improved the predictive accuracy for aggressive PC, outperforming PSA-only methods. The integration of DHEA-S, androstenedione, and SHBG as widely available and cost-effective novel blood biomarkers offers a more targeted, non-invasive prediction of aggressive PC. This approach could reduce reliance on invasive prostate biopsies and expensive magnetic resonance imaging.

The serine protease hepsin is frequently overexpressed in human prostate cancer (PCa) and is associated with matrix degradation and PCa progression in mice. Curiously, low expression of hepsin is associated with poor survival in different cancer types, and transgenic overexpression of hepsin leads to loss of viability in various cancer cell lines. Here, by comparing isogenic transfectants of the PCa cell line PC-3 providing inducible overexpression of wild-type hepsin (HPN) vs. the protease-deficient mutant HPN S353A , we were able to attribute hepsin-mediated tumor-adverse effects to its excess proteolytic activity. A stem-like expression signature of surface markers and adhesion molecules, Notch intracellular domain release, and increased pericellular protease activity were associated with low expression levels of wild-type hepsin, but were partially lost in response to overexpression. Instead, overexpression of wild-type hepsin, but not of HPN S353A , induced relocalization of the protein to the cytoplasm, and increased autophagic flux in vitro as well as LC3B punctae frequency in tumor xenografts. Confocal microscopy revealed colocalization of wild-type hepsin with both LC3B punctae as well as with the autophagy cargo receptor p62/SQSTM1. Overexpression of wild type, but not protease-deficient hepsin induced expression and nuclear presence of CHOP, indicating activation of the unfolded protein response and ER-associated protein degradation (ERAD). Whereas inhibitors of ER stress and secretory protein trafficking slightly increased viability, combined inhibition of the ubiquitin-proteasome degradation pathway (by bortezomib) with either ER stress (by salubrinal) or autophagy (by bafilomycin A1) revealed a significant decrease of viability during overexpression of wild-type hepsin in PC-3 cells. Our results demonstrate that a precise control of Hepsin proteolytic activity is critical for PCa cell fate and suggest, that the interference with ERAD could be a promising therapeutic option, leading to induction of proteotoxicity in hepsin-overexpressing tumors.

Background Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings. Methods Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity. Results We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance. Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations. Conclusions The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - in the long term - result in a more reliable prediction of individual cancer therapies.

Loss of cell cycle control is a prerequisite for cancer onset and progression. In prostate cancer, increased activity of cell cycle genes has been associated with prognostic parameters such as biochemical relapse and survival. The identification of novel oncogenic and druggable targets in patient subgroups with poor prognosis may help to develop targeted therapy approaches. We analyzed prostate cancer and corresponding benign tissues ( n  = 98) using microarrays. The comparison of high- and low-grade tumors (Gleason score ≥ 4 + 3 vs. ≤ 3 + 4) revealed 144 differentially expressed genes ( p  < 0.05). Out of these, 15 genes were involved in the cell cycle process. The gene maternal embryonic leucine zipper kinase ( MELK ) was identified to be highly correlated with cell cycle genes like UBE2C , TOP2A , CCNB2 , and AURKB . Increased MELK gene expression in high-risk prostate cancer was validated by qPCR in an independent patient cohort ( p  < 0.005, n  = 79). Immunohistochemistry analysis using a tissue microarray ( n  = 94) revealed increased MELK protein expression in prostate cancer tissues of high Gleason scores. RNAi-based inhibition of MELK in PC3 and LNCaP cells suggested putative function in chromatin modification, embryonic development and cell migration. The concerted inhibition of MELK and other cell cycle targets by the antibiotic siomycin A strongly impaired cell viability of prostate cancer cells, and may point to a novel therapy approach for a subset of high-risk prostate cancer patients.

Pathogenesis and factors for determining progression of alcoholic and non-alcoholic steatosis to steatohepatitis with risk of further progression to liver cirrhosis and cancer are poorly understood. In the present study, we aimed to identify potential molecular signatures for discrimination of steatohepatitis from steatosis. Global microarray gene expression analysis was applied to unravel differentially expressed genes between steatohepatitis compared to steatosis and control samples. For functional annotation as well as the identification of disease-relevant biological processes of the differentially expressed genes the gene ontology (GO) database was used. Selected candidate genes (n = 46) were validated in 87 human liver samples from two sample cohorts by quantitative real-time PCR (qRT-PCR). The GO analysis revealed that genes down-regulated in steatohepatitis were mainly involved in metabolic processes. Genes up-regulated in steatohepatitis samples were associated with cancer progression and proliferation. In surgical liver resection samples, 39 genes and in percutaneous liver biopsies, 30 genes were significantly up-regulated in steatohepatitis. Furthermore, immunohistochemical investigation of human liver tissue revealed a significant increase of AKR1B10 protein expression in steatohepatitis. The development of steatohepatitis is characterized by distinct molecular changes. The most striking examples in this respect were KRT23 and AKR1B10, which we found to be highly differentially expressed in steatohepatitis compared to steatosis and normal liver. We propose that KRT23 and AKR1B10 may serve as future potential biomarkers for steatohepatitis as well as markers for progression to HCC.

The current classification of human lung adenocarcinoma defines five different histological growth patterns within the group of conventional invasive adenocarcinomas. The five growth patterns are characterised by their typical architecture, but also by variable tumor biological behaviour. The aim of this study was to identify specific gene signatures of the five adenocarcinoma growth patterns defined by the joint IASLC/ATS/ERS working group. Total RNA from microdissected adenocarcinoma tissue samples of ten lepidic, ten acinar, ten solid, nine papillary, and nine micropapillary tumor portions was isolated and prepared for gene expression analysis. Differential expression of genes was determined using the R package \"LIMMA\". The overall significance of each signature was assessed via global test. Gene ontology statistics were analysed using GOstat. For immunohistochemical validation, tissue specimens from 20 tumors with solid and 20 tumors with lepidic growth pattern were used. Microarray analyses between the growth patterns resulted in numerous differentially expressed genes between the solid architecture and other patterns. The comparison of transcriptomic activity in the solid and lepidic patterns revealed 705 up- and 110 downregulated non-redundant genes. The pattern-specific protein expression of Inositol-1,4,5-trisphosphate-kinase-A (ITPKA) and angiogenin by immunohistochemistry confirmed the RNA levels. The strongest differences in protein expression between the two patterns were shown for ITPKA (p = 0.02) and angiogenin (p = 0.113). In this study growth pattern-specific gene signatures in pulmonary adenocarcinoma were identified and distinct transcriptomic differences between lung adenocarcinoma growth patterns were defined. The study provides valuable new information about pulmonary adenocarcinoma and allows a better assessment of the five adenocarcinoma subgroups.

Circulating cell-free DNA (cfDNA) released from cancerous tissues has been found to harbor tumor-associated alterations and to represent the molecular composition of the tumor. Recent advances in technologies, especially in next-generation sequencing, enable the analysis of low amounts of cfDNA from body fluids. We analyzed the exomes of tumor tissue and matched serum samples to investigate the molecular representation of the tumor exome in cfDNA. To this end, we implemented a workflow for sequencing of cfDNA from low serum volumes (200 μl) and performed whole-exome sequencing (WES) of serum and matched tumor tissue samples from six non-small cell lung cancer (NSCLC) patients and two control sera. Exomes, including untranslated regions (UTRs) of cfDNA were sequenced with an average coverage of 68.5x. Enrichment efficiency, target coverage, and sequencing depth of cfDNA reads were comparable to those from matched tissues. Discovered variants were compared between serum and tissue as well as to the COSMIC database of known mutations. Although not all tissue variants could be confirmed in the matched serum, up to 57% of the tumor variants were reflected in matched cfDNA with mutations in PIK3CA, ALK, and PTEN as well as variants at COSMIC annotated sites in all six patients analyzed. Moreover, cfDNA revealed a mutation in MTOR, which was not detected in the matched tissue, potentially from an untested region of the heterogeneous primary tumor or from a distant metastatic clone. WES of cfDNA may provide additional complementary molecular information about clinically relevant mutations and the clonal heterogeneity of the tumors.

Background Outcomes under anti-PD-(L)1 therapy have been variable in advanced non-small cell lung cancer (NSCLC) without reliable predictive biomarkers so far. Targeted next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) has demonstrated potential clinical utility to support clinical decisions, but requires prior tumor genetic profiling for proper interpretation, and wide adoption remains limited due to high costs. Methods Tumor-agnostic low-coverage ctDNA whole genome sequencing (lcWGS) was used to longitudinally track genome-wide copy number variations (CNVs) and fragmentation features in advanced NSCLC patients ( n  = 118 samples from 49 patients) and healthy controls ( n  = 57). Tumor PD-L1 expression was available for comparison. Findings Fragmentation features and CNVs were complementary indicators, whose combination significantly increased ctDNA detection compared to single-marker assessments (+ 20.3% compared to CNV analysis alone). Baseline fragment length alterations, but not CNVs, were significantly associated with subsequent progression-free survival (PFS; hazard ratio [HR] = 4.10, p  = 6.58e-05) and could improve PFS predictions based on tumor PD-L1 expression alone (HR = 2.70, p  = 0.019). Residual CNVs or aberrant fragmentation of ctDNA under ongoing therapy could stratify patients according to the subsequent response duration (median 5.8 vs. 47.0 months, p  = 1.13e-06). The integrative analysis of ctDNA fragment characteristics at baseline, tumor PD-L1 expression, and residual ctDNA under ongoing treatment constituted the strongest independent predictor of PFS ( p  = 6.25e-05) and overall survival ( p  = 1.3e-03) in multivariable analyses along with other clinicopathologic variables. Interpretation This study demonstrates the feasibility and potential clinical utility of lcWGS for the tumor-agnostic stratification and monitoring of advanced NSCLC under PD-(L)1 blockade based on CNV and fragmentomic profiling.