Radical cystectomy (RC), preceded by platinum-based neoadjuvant chemotherapy (NAC), is recommended for eligible patients with muscle-invasive bladder cancer (MIBC). Although NAC improves survival, many patients do not respond; in non-responders, it may delay surgery and cause toxicity. Predictive biomarkers to guide NAC remain lacking. Here, high-throughput transcriptomics, immunohistochemistry, and cell transfection experiments were applied to identify biomarkers of cisplatin-based NAC response. Two transcriptome analyses of transurethral resection of bladder tumor (TUR-BT) samples from NAC-naïve patients were conducted, followed by feature selection using Stable Iterative Variable Selection (SIVS). Protein validation was performed by immunohistochemistry on tissue microarrays, and functional validation of a candidate long non-coding RNA was assessed by in vitro overexpression in bladder cancer cells. SIVS identified a gene panel distinguishing chemoresistant from chemosensitive patients (AUROC >0.8). The three leading protein-coding genes (PYGM, FOXQ1, LGALS7B) were validated immunohistochemically but lacked sufficient predictive performance at the protein level. The long non-coding RNA DIO3OS showed only a slight, non-significant reduction in cisplatin sensitivity upon overexpression in 5637 cells. These findings underscore the complexity of predicting NAC response in MIBC and suggest that multi-gene RNA/DNA-based panels may offer more robust patient stratification than single biomarkers.

Background:Risk stratification for prostate cancer (PCa) progression or aggressiveness is often based on clinicopathologic features, some of which may be influenced by genetic factors. We developed a novel, germline polygenic risk score (PRSagg) to predict likelihood of developing aggressive PCa. Methods:PRSagg was developed using data from 38,688 patients with PCa (case-only analysis) from the Million Veteran Program (MVP) through a genome-wide search for variants associated with PCa grade group at diagnosis. We tested associations of PRSagg with grade group using the entire MVP dataset using the .632 bootstrap method. In an MVP cohort with localized PCa that was initially monitored without treatment, we tested PRSagg for association with unfavorable outcomes (subsequent development of grade group 4-5, metastasis, and/or biochemical recurrence after definitive treatment). We performed external validation in data from patients in the PRACTICAL Consortium (n=45,214) and from participants in the ProtecT randomized trial who underwent active monitoring (n=316). Odds ratios (ORs) were calculated per standard deviation (SD) increase with 95% confidence intervals, while adjusting for age, genetic ancestry, a previously developed polygenic score for risk of PCa (PHS601), and a polygenic score for benign elevated prostate-specific antigen (PRSPSA). For the outcome of metastasis, we additionally adjusted for PSA at diagnosis. Results:In the MVP training dataset, PRSagg (172 variants) was associated with higher grade group at diagnosis (OR = 1.53 [1.51-1.56]) and with increased risk of unfavorable outcomes during monitoring (OR = 1.13 [1.09-1.18]). These findings were confirmed in the external datasets. PRSagg was associated with greater odds of higher grade group at diagnosis (OR = 1.09 [1.061.11]). Among ProtecT participants undergoing active monitoring, PRSagg was associated with higher risk of metastasis (OR = 2.15 [1.02-3.88]). Among MVP participants with high polygenic risk of developing any PCa, the risk of aggressive disease was highest in men with high PRSagg and low genetic risk of PSA elevation. Conclusions:Among men who develop PCa, a weighted sum of common germline variants (PRSagg) is independently associated with PCa aggressiveness. These findings may inform future study of germline influence on tumor evolution and risk-stratified intensity of active surveillance.

Precision healthcare aims to tailor disease prevention and early detection to individual risk. Prostate cancer screening may benefit from genomics-informed approaches. We developed and validated the P-CARE model, a prostate cancer risk prediction tool combining a polygenic score, family history and genetic ancestry, using data from over 585,000 male participants in the Million Veteran Program. The model was externally validated in diverse cohorts and implemented via a blended genome–exome assay for clinical use. Here we show that the P-CARE model identifies clinically meaningful gradients of prostate cancer risk among men, with higher scores associated with increased risk of any, metastatic and fatal prostate cancer. The model is now being used in a clinical trial of precision prostate cancer screening. This work demonstrates the potential for genomics-enabled health systems to improve prostate cancer screening and prevention in men. ClinicalTrials.gov registration: NCT05926102 . Vassy, Dornisch and colleagues developed a genomics-based prostate cancer risk model to support a randomized clinical trial of precision screening in a national healthcare system.

Abstract Background Prostate cancer (PCa) is heterogeneous, making risk stratification essential for clinical care. Although polygenic risk scores (PRSs) with main effects of single-nucleotide polymorphisms (SNPs) can help identify individuals at high risk before biological and clinical onset, a PRS for predicting PCa aggressiveness remains underdeveloped. The KLK3 , which encodes prostate-specific antigen (PSA), is linked to PCa aggressiveness. Recent findings on KLK3 SNP-SNP interactions show promise for predicting PCa aggressiveness. The objective of this study is to develop a PRS (PRS-KLK3int) by examining KLK3 SNP-SNP interaction pairs. Methods The PRS-KLK3int was developed based on a discovery set (10,836 PCa patients) and two validation sets with 14,348 and 16,584 patients of European ancestry. A total of 3145 SNP pairs and two published PRSs were evaluated. Results This study developed a PRS-KLK3int with 284 SNPs, combining an existing PRS with 270 SNPs and 12 SNP-SNP interaction pairs with 15 SNPs (one overlapped). All these 12 pairs were involved with at least one SNP from KLK3 . The PRS-KLK3int outperformed two existing PRSs in predicting PCa aggressiveness (p-values: 3.5×10 −18 , 9×10 −14 , and 1.7×10 −20 for the three sets). It effectively distinguished high-risk from low-risk groups across all datasets. The top 1% high-risk group had a higher prevalence of PCa aggressiveness than the middle 50% group (45.5% vs. 25.9%, OR = 2.38, p = 2.2×10 −5 ) in the discovery set, and similar results were observed in validation sets (OR = 2.56, p = 4.3×10 −6 ; OR = 2.07, p = 2.1×10 −5 ). Conclusions These findings support PRS-KLK3int as a valuable tool for PCa severity stratification, especially in identifying extremely high-risk PCa patients.

Better tools to predict the likelihood of a recurrence of prostate cancer (PC) after a radical prostatectomy are needed and would provide more personalized therapies for the patients early enough to efficiently control the disease burden. In this study, the transcriptome profiles from matched malignant and adjacent benign prostate tissue were compared in 41 patients to facilitate the identification of novel markers for PC aggressiveness. Hierarchical clustering separated benign and malignant tissues and identified expected transcriptional changes associated with carcinogenesis. Reproducibility-optimized statistical testing (ROTS) identified 45 genes whose expression change between malignant and benign prostate tissue from the same patient differed in patients with and without biochemical recurrence (FDR < 0.05). The results indicated two interconnected regulatory pathways underlying the pathogenesis: one centered on the NR4A, FOS, and EGR family transcription factors, and another centered on IL6. Expression of these 45 transcripts was also found to differ between more aggressive Luminal B-type PC and Luminal A- and Basal-type PC. A machine learning method (SIVS) was then used to further define five transcripts (BPIFB2, NR4A2, NR4A3, C11orf96, DUSP5) whose individualized malignant-to-benign expression difference within a patient was most strongly associated with an increased risk of relapse. Of these, BPIFB2 and NR4A2 were responsive to antiandrogen treatment in VCaP xenografts in castrated mice in a direction concordant with the malignant-to-benign expression ratio associated with reduced risk of BCR, and were also co-expressed in the PC epithelium. In summary, this study identified novel tumor-expressed markers whose expression changes during malignancy are associated with PC aggressiveness.

Abstract Background and aims Clopidogrel is a prodrug activated mainly by the polymorphic CYP2C19 enzyme. Because clopidogrel resistance is common and clinical recommendations for pharmacogenetic testing remain uncertain, we examined pharmacogenetic profiles of patients treated with clopidogrel and their associations with platelet function and subsequent thromboses or bleedings. Methods Patients who started clopidogrel during a hospital admission were identified from Turku University Hospital data pool. Genomic data from the FinnGen project were linked with demographic and clinical information. A subset—mostly acute ischemic stroke patients—had platelet function testing using the MPADP assay (Roche). Clinically relevant outcomes were captured as emergency procedures for acute bleedings or thromboses (including thrombectomies and thrombolysis) occurring 7–365 days after clopidogrel initiation. Pharmacogenetic results did not guide treatment. Patients were grouped by CYP2C19 phenotype and by MPADP response category (increased/normal/decreased) using manufacturer cut-offs. Analyses used chi-square testing and correlation methods (Kendall’s tau-b, Spearman’s rho) as appropriate. Results Among 62,015 patients with genomic data, 3,751 received clopidogrel with complete follow-up. There were 112 acute thromboses (3%) and 27 acute bleedings (0.7%), with no significant associations between CYP2C19 phenotype and either outcome. Platelet function results were available for 433 patients. Platelet response showed a weak, non-significant trend toward better response with higher CYP2C19 metabolic phenotypes. Non-response remained high: more than one-third of rapid and ultrarapid metabolizers were non-responders (Figure). Conclusions In this cohort, CYP2C19 phenotype was not significantly associated with thromboses, bleedings, or platelet function. Randomized trials of pharmacogenetically guided selection of clopidogrel versus alternative antiplatelets are needed. Conflict of interest Jori Ruuskanen: Scientific consultancy fees (AstraZeneca, Amgen), travel expenses reimbursement (UCB Pharma), employed and equity interest (Medbase, Turku, Finland). Juuso Blomster: Employed and equity interest in Precordior Oy, honoraria from Novo Nordisk and Roche Diagnostics. Pauli Ylikotila: Speaker fee (AstraZeneca). Niina Kannisto, Lila Kallio, Päivi Helmiö, Aleksi Tornio, Johanna Schleutker: Nothing to disclose. Figure 1 - belongs to Conclusions

Prostate cancer (PrCa) is highly prevalent in the Western world. Currently, however, there are many unmet needs in PrCa care, for example in distinguishing between clinically significant and indolent cases in early phases of the disease. ANO7 is a prostate-specific gene associated with PrCa risk and prognosis, but its exact function in the prostate remains unclear. This study investigates the role of ANO7 in benign prostatic epithelium using spatial transcriptomics by examining differences between ANO7-expressing and non-expressing epithelial regions and their corresponding stromal compartments. A total of 18,676 protein-coding genes were assessed from prostatectomy samples collected from patients with localised prostate cancer. In the collected sample cohort, ANO7 exhibited a distinct, heterogeneous, on-off epithelial expression pattern, enabling an in-depth analysis of ANO7-dependent processes. ANO7-positive epithelium was predominantly enriched with luminal epithelial cells and a specific NK cell subtype, CD56bright. In contrast, ANO7-negative regions were characterised by enrichment of club cells, inflammation, and features of proliferative inflammatory atrophy. Gene-set enrichment analysis revealed that ANO7 expression is associated with androgen receptor (AR) signalling and lipid metabolism. A detailed analysis of differentially expressed genes identified an ANO7- signature, which consisted of genes co-expressed with ANO7 in luminal cells, that demonstrated high consistency in bulk RNA-sequencing (RNA-seq) data. The ANO7-signature was enriched for AR-regulated genes, which highlighted lipid metabolism processes, particularly arachidonic acid metabolism, as a key metabolic feature of the ANO7-positive epithelium. Furthermore, the ANO7-signature demonstrated clinical significance in low-grade PrCa, correlating with a better response to therapy. In summary, these results highlight the potential role of ANO7 in regulating lipid metabolism associated with androgen signalling in benign luminal cells and low-grade cancer, reinforcing the hypothesis that ANO7 functions as a tumour suppressor. © 2025 The Pathological Society of Great Britain and Ireland.

BACKGROUND:Prostate cancer (PrCa) is a significant health concern, ranking as the second most common cancer in males globally. Genetic factors contribute substantially to PrCa risk, with up to 57% of the risk being attributed to genetic determinants. A major challenge in managing PrCa is the early identification of aggressive cases for targeted treatment, while avoiding unnecessary interventions in slow-progressing cases. Therefore, there is a critical need for genetic biomarkers that can distinguish between aggressive and non-aggressive PrCa cases. Previous research, including our own, has shown that germline variants in ANO7 are associated with aggressive PrCa. However, the function of ANO7 in the prostate remains unknown. METHODS:We performed RNA-sequencing (RNA-seq) on RWPE1 cells engineered to express ANO7 protein, alongside the analysis of a single-cell RNA-sequencing (scRNA-seq) dataset and RNA-seq from prostate tissues. Differential gene expression analysis and gene set enrichment analysis (GSEA) were conducted to identify key pathways. Additionally, we assessed oxidative phosphorylation (OXPHOS), glycolysis, and targeted metabolomics. Image analysis of mitochondrial morphology and lipidomics were also performed to provide further insight into the functional role of ANO7 in prostate cells. RESULTS:ANO7 expression resulted in the downregulation of metabolic pathways, particularly genes associated with the MYC pathway and oxidative phosphorylation (OXPHOS) in both prostate tissue and ANO7-expressing cells. Measurements of OXPHOS and glycolysis in the ANO7-expressing cells revealed a metabolic shift towards glycolysis. Targeted metabolomics showed reduced levels of the amino acid aspartate, indicating disrupted mitochondrial function in the ANO7-expressing cells. Image analysis demonstrated altered mitochondrial morphology in these cells. Additionally, ANO7 downregulated genes involved in fatty acid metabolism and induced changes in lipid composition of the cells, characterized by longer acyl chain lengths and increased unsaturation, suggesting a role for ANO7 in regulating lipid metabolism in the prostate. CONCLUSIONS:This study provides new insights into the function of ANO7 in prostate cells, highlighting its involvement in metabolic pathways, particularly OXPHOS and lipid metabolism. The findings suggest that ANO7 may act as a key regulator of cellular lipid metabolism and mitochondrial function in the prostate, shedding light on a previously unknown aspect of ANO7's biology.

The coagulation cascade is thought to contribute to cancer progression. Although in vitro studies suggest that anticoagulants, such as warfarin, might reduce cancer progression, epidemiological data indicate that warfarin users may have a higher risk of cancer mortality. However, single nucleotide polymorphisms (SNPs) that influence warfarin dosing might affect this association. We investigated the risk associations between warfarin use and prostate cancer (PCa) survival, considering the SNP genotypes of CYP2C9 and VKORC1, which are known to impact both warfarin pharmacokinetics and pharmacodynamics, resulting in lower warfarin dose requirement. We genotyped 2,246 Finnish men with PCa from two different cohorts for SNPs rs1057910, rs1799853, and rs9923231. Genotyping was done using a custom Illumina iSelect genotyping array (iCOGs). Using Cox regression models, we calculated hazard ratios (HRs) and 95% confidence intervals (CI) for the risk of overall death, cancer deaths overall, and PCa-specific death after PCa diagnosis based on SNP genotypes. Data on warfarin purchases was obtained from a national registry. Our findings revealed that the SNPs did not alter the risk of cancer or PCa death in either cohort, nor did they modify the risk among warfarin users. However, overall mortality was higher among warfarin users compared to non-users, particularly in carriers of all three SNPs. Even though the increased mortality is likely due to confounding by indication, warfarin use may increase overall mortality especially in men with lower warfarin dose requirements due to SNP carrier status. However, we need further studies with larger populations to confirm these findings.

The advent of high-throughput sequencing technologies has revolutionized the field of genomic sciences by cutting down the cost and time associated with standard sequencing methods. This advancement has not only provided the research community with an abundance of data but has also presented the challenge of analyzing it. The paramount challenge in analyzing the copious amount of data is in using the optimal resources in terms of available tools. To address this research gap, we propose "Kuura-An automated workflow for analyzing WES and WGS data", which is optimized for both whole exome and whole genome sequencing data. This workflow is based on the nextflow pipeline scripting language and uses docker to manage and deploy the workflow. The workflow consists of four analysis stages-quality control, mapping to reference genome & quality score recalibration, variant calling & variant recalibration and variant consensus & annotation. An important feature of the DNA-seq workflow is that it uses the combination of multiple variant callers (GATK Haplotypecaller, DeepVariant, VarScan2, Freebayes and Strelka2), generating a list of high-confidence variants in a consensus call file. The workflow is flexible as it integrates the fragmented tools and can be easily extended by adding or updating tools or amending the parameters list. The use of a single parameters file enhances reproducibility of the results. The ease of deployment and usage of the workflow further increases computational reproducibility providing researchers with a standardized tool for the variant calling step in different projects. The source code, instructions for installation and use of the tool are publicly available at our github repository https://github.com/dhanaprakashj/kuura_pipeline.

Background: As healthcare moves from a one-size-fits-all approach towards precision care, individual risk prediction is an important step in disease prevention and early detection. Biobank-linked healthcare systems can generate knowledge about genomic risk and test the impact of implementing that knowledge in care. Risk-stratified prostate cancer screening is one clinical application that might benefit from such an approach. Methods: We developed a clinical translation pipeline for genomics-informed prostate cancer screening in a national healthcare system. We used data from 585,418 male participants of the Veterans Affairs (VA) Million Veteran Program (MVP), among whom 101,920 self-identify as Black/African-American, to develop and validate the Prostate CAncer integrated Risk Evaluation (P-CARE) model, a prostate cancer risk prediction model based on a polygenic score, family history, and genetic principal components. The model was externally validated in data from 18,457 PRACTICAL Consortium participants. A novel blended genome-exome (BGE) platform was used to develop a clinical laboratory assay for both the P-CARE model and rare variants in prostate cancer-associated genes, including additional validation in 74,331 samples from the All of Us Research Program. Results: In overall and ancestry-stratified analyses, the polygenic score of 601 variants was associated with any, metastatic, and fatal prostate cancer in MVP and PRACTICAL. Values of the P-CARE model at ≥80th percentile in the multiancestry cohort overall were associated with hazard ratios (HR) of 2.75 (95% CI 2.66-2.84), 2.78 (95% CI 2.54-2.99), and 2.59 (95% CI 2.22-2.97) for any, metastatic, and fatal prostate cancer in MVP, respectively, compared to the median. When high- and low-risk groups were defined as P-CARE HR>1.5 and HR<0.75 for metastatic prostate cancer, the 220,062 (37.6%) high-risk vs.146,826 (25.1%) low-risk participants in MVP had a 47.9% vs. 14.1%, 9.3% vs. 2.0%, and 3.6% vs. 0.8% cumulative cause-specific incidence of any, metastatic, and fatal prostate cancer by age 90, respectively. The clinical assay and reports are now being implemented in a clinical trial of precision prostate cancer screening in the VA healthcare system (Clinicaltrials.gov [NCT05926102][1]). Conclusions: A model consisting of a polygenic score, family history, and genetic principal components describes a clinically important gradient of prostate cancer risk in a diverse patient population and demonstrates the potential of learning health systems to implement and evaluate precision health care approaches. ### Competing Interest Statement N.L. has received speaking honoraria from Illumina Inc and is an advisory board member for FYR Diagnostics and Everygene. N.L has received research collaborative funding (for work unrelated to this publication) from Illumina Inc and PacBio Inc. JAL, KML, and CTC report grants from Alnylam Pharmaceuticals, Inc., Astellas Pharma, Inc., AstraZeneca Pharmaceuticals LP, Biodesix, Inc, Celgene Corporation, Cerner Enviza, GSK PLC, IQVIA Inc., Janssen Pharmaceuticals, Inc., Novartis International AG, Parexel International Corporation through the University of Utah or Western Institute for Veteran Research outside the submitted work. ASK reports fundings (for work unrelated to this publication) from Janssen, Pfizer, Profound, Bristol Myers Squibb, and Merck. SLD reports grants from AstraZeneca Pharmaceuticals, Biodesix, Myriad Genetic Laboratories, Parexel, Moderna, GlaxoSmithKline, Cerner Enviza, Janssen Research & Development, Celgene, Novartis Pharmaceuticals, IQVIA, Astellas Pharma, and Alnylam Pharmaceuticals. RAE reports speaking honoraria from GU-ASCO, Janssen, University of Chicago, and Dana Farber Cancer Institute, educational honorarium from Bayer and Ipsen, being a member of external expert committee to Astra Zeneca UK and Member of Active Surveillance Movember Committee and is a member of the SAB of Our Future Health; additionally undertakes private practice as a sole trader at The Royal Marsden NHS Foundation Trust and 90 Sloane Street SW1X 9PQ and 280 Kings Road SW3 4NX, London, UK. LAM reports research funding from Astra Zeneca to Harvard University; she holds equity in Convergent Therapeutics. TMS reports honoraria from Varian Medical Systems, WebMD, GE Healthcare, and Janssen; he has an equity interest in CorTechs Labs, Inc. and serves on its Scientific Advisory Board; he receives research funding from GE Healthcare through the University of California San Diego. These companies might potentially benefit from the research results. The terms of this arrangement have been reviewed and approved by the University of California San Diego in accordance with its conflict-of-interest policies. The other authors have no disclosures. ### Funding Statement This work was funded by the Million Veteran Program MVP022 award #I01CX001727 (PI: RLH) and MVP084 award #I01CX002635 (PI: JLV). See Supplement for additional funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Veterans Affairs Central Institutional Review Board approved this study (IRBNet 1735869 and 1735136). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes It is not possible for the authors to directly share the individual-level data that were obtained from the Million Veteran Program (MVP) due to constraints stipulated in the informed consent. Anyone wishing to gain access to this data should inquire directly to MVP at MVPLOI@va.gov. The data generated from our analyses are included in the manuscript. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT05926102&atom=%2Fmedrxiv%2Fearly%2F2024%2F11%2F04%2F2024.11.03.24316516.atom

Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility in men. The non-synonymous KLK3 single nucleotide polymorphism (SNP), rs17632542 (c.536T>C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity mediates prostate cancer pathogenesis. The 'Thr' PSA variant leads to small subcutaneous tumours, supporting reduced prostate cancer risk. However, 'Thr' PSA also displays higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterisation of this PSA variant demonstrates markedly reduced proteolytic activity that correlates with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele have reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes. The PSA (KLK3) genetic variant rs17632542 is associated with reduced prostate cancer risk and lower serum PSA levels, although the underlying reasons are unclear. Here, the authors show that this PSA variant reduced proteolytic activity and leads to smaller tumours, but also increases invasion and bone metastasis, indicating its dual risk association depending on tumour context; the variant is associated with both lower risk and poor clinical outcomes.

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP–SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP–SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP–SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a hub SNP with a significant main effect and a large minor allele frequency (MAF) tended to have a higher false-positive rate. In addition, peripheral null SNPs in a cluster with a small MAF tended to enhance false positivity. We also demonstrated that using the modified significance criterion based on the 3 p-value rules and the bootstrap approach (3pRule + bootstrap) can reduce false positivity and maintain high true positivity. In addition, our results also showed that a pair without a significant main effect tends to have weak or no interaction. This study identified the cluster effect and suggested using the 3pRule + bootstrap approach to enhance SNP–SNP interaction detection accuracy.

Background: Breast cancer is the most common malignancy, with a mean age of onset of approximately 60 years. Only a minority of breast cancer patients present with an early onset at or before 40 years of age. An exceptionally young age at diagnosis hints at a possible genetic etiology. Currently, known pathogenic genetic variants only partially explain the disease burden of younger patients. Thus, new knowledge is warranted regarding additional risk variants. In this study, we analyzed DNA repair genes to identify additional variants to shed light on the etiology of early-onset breast cancer. Methods: Germline whole-exome sequencing was conducted in a cohort of 63 patients diagnosed with breast cancer at or before 40 years of age (median 33, mean 33.02, range 23–40 years) with no known pathogenic variants in BRCA genes. After filtering, all detected rare variants were sorted by pathogenicity prediction scores (CADD score and REVEL) to identify the most damaging genetic changes. The remaining variants were then validated by comparison to a validation cohort of 121 breast cancer patients with no preselected age at cancer diagnosis (mean 51.4 years, range 28–80 years). Analysis of novel exonic variants was based on protein structure modeling. Results: Five novel, deleterious variants in the genes WRN, RNF8, TOP3A, ERCC2, and TREX2 were found in addition to a splice acceptor variant in RNF4 and two frameshift variants in EXO1 and POLE genes, respectively. There were also multiple previously reported putative risk variants in other DNA repair genes. Conclusions: Taken together, whole-exome sequencing yielded 72 deleterious variants, including 8 novel variants that may play a pivotal role in the development of early-onset breast cancer. Although more studies are warranted, we demonstrate that young breast cancer patients tend to carry multiple deleterious variants in one or more DNA repair genes.

Abstract Prostate cancer (PCa), the most common male cancer worldwide, causes about 10% of cancer related deaths in Europe. It has a wide spectrum of clinical behavior that ranges from decades of indolence to rapid metastatic progression and lethality. However, the molecular mechanisms involved in aggressive PCa progression are still poorly understood. In PCa the expression of anoctamin 7 (ANO7) has been shown to diminish as the cancer progresses. We have previously linked single-nucleotide polymorphisms in the ANO7 gene to the risk of aggressive prostate cancer and shown that in homozygous carriers of rs77559646, the variant leads to a total loss of ANO7 protein. ANO7 is a prostate-specific gene and is highly expressed in the luminal cells of the human prostate. ANO7 belongs to a family of calcium-activated chloride channels and select members of the anoctamin family have phospholipid scramblase activity. To uncover the cellular functions of ANO7 has proven challenging because ANO7 is not expressed in commercially available cell lines. To study the cellular functions of ANO7, we have generated stable prostate cell lines overexpressing ANO7 using lentiviral transduction. To gain information into what pathways ANO7 is affecting, we performed RNA-sequencing and gene set enrichment analysis. Interestingly, we found enrichment and downregulation of mitochondrial genes participating in oxidative phosphorylation in ANO7 cells. We assessed the mitochondrial function by measuring the oxidative phosphorylation capability of the cells and showed that the basal and maximal respiratory capacity of ANO7 overexpressing cells is indeed reduced. We also analyzed which of the three major mitochondrial fuels (glucose, glutamine and fatty acids) are not used as efficiently for oxidative phosphorylation in ANO7 overexpressing cells. The result proves that ANO7 cells are not utilizing glucose as effectively as control cells. Furthermore, the glycolysis stress assay showed that glycolytic capacity is increased in ANO7 overexpressing cells. In addition, a targeted metabolite screening revealed that aspartate is decreased in ANO7 cells, which again points towards perturbed mitochondrial function as aspartate is produced from a tricarboxylic acid cycle intermediate. By inhibiting the uptake of extracellular aspartate, we measured slower proliferation of ANO7 expressing cells, while inhibiting aspartate had no effect on control cells. Interestingly, preliminary results also suggest ANO7's involvement in regulation of phospholipid acyl chain length and saturation, offering insights into altered signaling observed in ANO7 cells. Taken together, this study shows for the first time that ANO7 rewires prostate mitochondrial functions and thus cellular metabolism, which could explain why it is beneficial for cancer cells to lose ANO7 expression. Citation Format: Christoffer Löf, Nasrin Sultana, Neha Goel, Gudrun Wahlström, Johanna Schleutker. The role of aggressive prostate cancer risk gene ANO7 in prostate metabolism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7056.

Introduction: Intracellular cholesterol metabolism plays an important role in prostate cancer progression and emergence of treatment resistance. However, it remains unclear whether serum cholesterol and lipoproteins are associated with prostate cancer outcomes. Studies on serum cholesterol and cancer are often confounded by lifestyle factors such as diet and obesity. A possible solution is to use instrumental variables, such as SNPs predicting serum cholesterol. According to the Mendelian randomization theory, germline SNP distribution is unaffected by confounding variables such as diet and lifestyle factors. Objective: To estimate whether SNPs that predict serum cholesterol and lipoproteins also predict mortality among a cohort of men with prostate cancer. Methods: Our study cohort consisted of 3,241 men diagnosed with prostate cancer between 1996-2015, using data collected by the Finnish Randomized Study of Screening for Prostate Cancer. Blood samples were genotyped by PRACTICAL consortium. A UCSC genome browser was utilized for selecting 85 SNPs in lipid metabolism-associated genes. Dates and causes of deaths between 1996-2015 were obtained from the Statistics Finland's statistics on causes of death. Information on serum cholesterol and lipoprotein measurements were obtained from a regional laboratory database.Scores predicting serum cholesterol, LDL, HDL and triglyceride level by SNP genotype were created using linear regression and lasso regression. Risk of prostate cancer death and overall mortality by level of the SNP risk score were evaluated with multivariable-adjusted Cox regression. Follow-up started at prostate cancer diagnosis and continued until death, emigration or common closing date of Dec 31, 2015.Results: SNP score predicting total cholesterol stratified prostate cancer patients both for disease-specific (HR 1.27, 95% CI 0.49-3.28 for highest tertile vs. lowest) and overall survival (HR 1.43, 95% CI 0.94-2.20, p for trend = 0.077), albeit statistical significance was not reached. Similar survival differences were observed for SNP score predicting triglyceride level, but not for scores predicting LDL or HDL.Conclusions: SNPs predicting serum cholesterol and triglycerides are likely prognostic factors for survival of prostate cancer patients. This suggest serum cholesterol and lipoproteins areimportant in prostate cancer progression. Total cholesterol SNP scoreProstate-cancer specific survival Overall survival Citation Format: Sebastian Boele, Aino Siltari, Paavo Raittinen, Johanna Schleutker, Kimmo Taari, Kirsi Talala, Teuvo Tammela, Anssi Auvinen, Teemu J. Murtola. Single nucleotide polymorphisms that predict serum cholesterol as a prostate cancer prognostic factor - a Mendelian randomization study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6486.

Supplementary Table 1. Prostate cancer risk estimates for 2169 putative miRSNPs.

Supplementary Table 1. Clinical characteristics of Finnish prostate cancer patients Supplementary Table 2. Tumour Stage Group (TSG) definitions Supplementary Table 3. Follow-up characteristics used in survival analyses of Finnish prostate cancer patients Supplementary Table 4. Primer sequences used in quantitative RT-PCR reactions Supplementary Table 5. Assessment of PrCa risk due to the combination of HOXB13 T and CIP2A T in dual carriers relative to the risk in non-carriers Supplementary Table 6 Time-to-PrCa event of HOXB13 rs138213197 and CIP2A rs2278911 Supplementary Table 7 Association of HOXB13 G84E and CIP2A R229Q carrier status and clinical features of prostate cancer subgroups Supplementary Table 8. Association of HOXB13 and CIP2A carrier status and combined modality stage of prostate cancer patients according to ERSPC Supplementary Table 9. P-values for Figure1, Figure 2 and Supplementary figure 2. Supplementary figure 1. Higher mRNA expression pattern of HOXB13-CIP2A correlated with increased risk of prostate cancer biochemical recurrence. Supplementary figure 2. Effects of HOXB13 G84E and CIP2A R229Q variants on prostate cell migration. Supplementary figure 3. ChIP-qPCR in VCaP cell line Supplementary figure 4. Overexpression of HOXB13 G84E and CIP2A R229Q variants promotes cell proliferation.

PDF file - 39K, The first column indicates the predicted class for the amino acid denoted by the letters B (buried) and E (exposed). Second Column shows the amino acid while in third column the amino acid position is indicated. Fourth column shows the predicted value of relative solvent accessibility (RSA). Fifth column shows the z-fit score of for the RSA prediction which represents the reliability of the RSA prediction.

Prostate cancer (PCa), the most common male cancer worldwide, causes about 10% of cancer related deaths in Europe. It has a wide spectrum of clinical behavior that ranges from decades of indolence to rapid metastatic progression and lethality. However, the molecular mechanisms involved in aggressive PCa progression are still poorly understood. We have previously linked single-nucleotide polymorphisms in the anoctamin 7 (ANO7) gene to the risk of aggressive prostate cancer and shown that carriers of a rs77559646 variant have improved treatment response to docetaxel. The expression of ANO7 is lost when prostate cancer progresses and is completely lacking in prostate cancer metastases. ANO7 is a prostate specific gene and is highly expressed in the luminal cells of the human prostate. ANO7 belongs to a family of calcium-activated chloride channels and select members of the anoctamin family have phospholipid scramblase activity. Whether ANO7 has any of these capabilities is unclear. To uncover the cellular functions of ANO7 has proven challenging because the expression of ANO7 at protein level is either minimal or nonexistent in all commercially available cell lines. To overcome this and to study the cellular functions of ANO7, we have generated stable prostate cell lines overexpressing ANO7 using lentiviral transduction. The characterization of the RWPE-1 cells overexpressing ANO7 showed that the viability and proliferation was increased both in 2D and 3D. To gain information into what pathways ANO7 is affecting, we performed RNA-sequencing and pathway analysis. Interestingly, we found enrichment of mitochondrial genes participating in oxidative phosphorylation in cells overexpressing ANO7. The genes expressed from the mitochondrial genome were upregulated and the nuclear genes encoding for proteins involved in mitochondrial functions were mostly downregulated. This suggests that the mitochondrial metabolism has changed. We assessed the mitochondrial function by measuring the oxidative phosphorylation capability of the cells and showed that the maximal respiratory capacity of ANO7 overexpressing cells is indeed reduced compared to control cells. We also analyzed which of the three major mitochondrial fuels (glucose, glutamine and fatty acids) are not used as efficiently for oxidative phosphorylation in ANO7 overexpressing cells. The result proves that ANO7 cells are not utilizing glucose as effectively as control cells as there were no differences in maximal respiratory capacity when we treated the cells with the UK5099 inhibitor, which inhibits pyruvate import to mitochondria. Furthermore, preliminary results from the glycolysis stress assay indicates that glycolysis is increased in ANO7 overexpressing cells. In addition, electron microscopy study suggests that ANO7 overexpressing cells have less cristae compared to control. This study shows for the first time that ANO7 rewires prostate mitochondrial functions and thus cellular metabolism. Citation Format: Nasrin Sultana, Christoffer Lof, Neha Goel, Johanna Schleutker. Unraveling the role of ANO7 in prostate cancer metabolism [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A020.