Search Results (1,027)

Background/Objectives: Genetic testing (GT) is essential for precision therapy in prostate cancer (PC). Implementation in routine outpatient cancer care remains heterogeneous. We assessed real-world data on GT practices among German Outpatient Urologists (GOUs) to identify strategies for improvement. Methods: A nationwide, multi-center survey was conducted among GOUs in Germany (02–06/2025), assessing demographics, qualifications, and GT behavior. Cochran-Armitage test for trend and Fisher’s exact test were used to assess associations; odds ratios with 95% confidence intervals were estimated using binary logistic regression. Results: In total, 117 GOUs participated, all practiced in outpatient settings. GT differed by disease stage: in localized prostate cancer, 6.0% reported ordering somatic testing (SoT) and 8.5% germline testing (GeT), compared to 67.5% and 42.7%, respectively, in metastatic disease. Overall, 29.1% reported not ordering GT of any kind. Ordering SoT for metastatic disease was significantly lower among senior physicians compared to early- and mid-career physicians (43% vs. 78% and 74%; OR 0.46 per career stage, 95% CI 0.27–0.79, p = 0.004). GeT did not differ significantly by experience (OR 0.90 per career stage, 95% CI 0.56–1.46, p = 0.67). Neither gender (OR 0.74, 95% CI 0.31–1.74), nor having a qualification in urological cancer-specific genetic counseling (26.5% of respondents; OR 0.81, 95% CI 0.33–1.98) was significantly associated with testing. BRCA1 and BRCA2 were recognized by 96.6% of respondents. Knowledge of other PC-associated genes was much lower. Conclusions: Despite guideline recommendations, GT, particularly GeT, remains underutilized in PC care in Germany. Senior physicians tested significantly less, and gene knowledge beyond BRCA1/2 was limited. Full article

While ovarian cancer screening is not recommended in the general population, attention has shifted to screening women with elevated hereditary risks. Although germline BRCA 1/2 pathogenic variants account for 40% of inherited ovarian cancer risk and family history (FH) remains important, known germline variants alone do not fully explain familial ovarian cancer risk. Whole-exome sequencing (WES) was performed on blood samples taken from 231 individuals, including 39 patients with high-grade serous ovarian cancer (HGSOC) and 192 healthy controls (HCs) stratified by FH. We analyzed pathogenic or likely pathogenic (P/LP) germline variants in cancer-related genes and assessed their association with family cancer history. Additionally, we performed somatic variant comparisons using 1:4 propensity score matching and analyzed clonal hematopoiesis of indeterminate potential (CHIP)-related somatic variants. P/LP germline variants were detected in 56.4% of HGSOC patients, 49.4% of controls with FH, and 33.3% without. The HGSOC group and controls with FH exhibited similar P/LP germline mutation patterns in ovarian cancer-related genes. From CHIP analysis, somatic CHIP mutations were detected in 6.3% of the HGSOC group and 8.5% in HCs. Our findings demonstrate genomic overlap between ovarian cancer patients and FH-positive individuals. Therefore, germline variant screening could be considered to facilitate early diagnosis. Full article

Vitamin D is a fat-soluble secosteroid essential for skeletal development and calcium homeostasis, but it also exerts pleiotropic effects on numerous biological processes via its active metabolites. Vitamin D metabolites act as steroid hormones that regulate cell-cycle progression, proliferation, differentiation, apoptosis, immune responses, and multiple intracellular signaling pathways. Moreover, they modulate the expression of genes involved in carcinogenesis. As circulating vitamin D levels are influenced by diet, fortified foods, and supplementation, they represent a potentially modifiable factor. Whether vitamin D status affects cancer risk or disease progression in carriers of pathogenic BRCA1 variants remains unclear and continues to be actively investigated. Clarifying this relationship could have significant clinical implications for risk stratification and prevention in this high-risk population. This narrative review summarizes current evidence from epidemiological, clinical, and molecular studies examining the role of vitamin D in BRCA1 pathogenic variant carriers. It also highlights key limitations in the existing literature and identifies critical directions for future research, emphasizing the need for well-designed prospective studies in representative cohorts. Full article

Background/Objectives: Breast cancer (BC) is the most frequently diagnosed malignancy among women worldwide, yet tumor genomic data from Latin American and admixed populations remain limited. This gap affects the interpretation of cancer-associated variants and may limit the representation of these populations in genomic research. This study aimed to characterize the genomic landscape of breast tumors from Ecuadorian women and contextualize variant interpretation through genetic ancestry analysis. Methods: Breast tissue samples from 23 Ecuadorian mestizo women with suspected malignancy were analyzed. After histopathological confirmation, 21 breast tumors were included in the final cohort. Targeted next-generation sequencing was performed using a 94-gene cancer panel. Variants were annotated and classified according to clinical significance. Because matched normal DNA was unavailable, variant allele frequency was used as an exploratory approach to infer putative somatic, putative germline, indeterminate, or putative homozygous germline profiles. Putative germline and indeterminate variants were interpreted using ACMG/AMP criteria, whereas putative somatic variants were evaluated using the AMP/ASCO/CAP framework. Genetic ancestry was inferred using ancestry-informative insertion/deletion markers. Results: Seventy-two unique variants across 40 genes were identified, including 14 pathogenic, 10 likely pathogenic, and 48 variants of uncertain significance. Pathogenic and likely pathogenic alterations were detected in clinically relevant genes, including TP53, BRCA2, PTEN, CDH1, RAD51C, MSH6, NF1, CYLD, and SDHB. Variants of uncertain significance represented 66.7% of all detected variants and affected several cancer-associated and DNA repair genes. The cohort showed a trihybrid ancestry profile, with predominant Native American ancestry, followed by European and African contributions. Conclusions: This study expands BC genomic data from an underrepresented Ecuadorian cohort and highlights the coexistence of clinically relevant alterations with a high burden of variants of uncertain significance. The findings underscore the limitations of tumor-only sequencing and current variant interpretation frameworks in admixed populations. Larger studies integrating matched normal DNA, ancestry-informed analyses, functional validation, and broader sequencing strategies could help improve variant interpretation in Latin American populations. Full article

Background: The therapeutic landscape of metastatic prostate cancer has rapidly evolved with the integration of biomarker-driven strategies, particularly targeting homologous recombination repair (HRR) alterations. Poly(ADP-ribose) polymerase inhibitors (PARPi) have demonstrated clinically meaningful benefit, especially in Breast Cancer genes 1/2-altered tumors, through synthetic lethality. However, the expansion of PARPi across multiple Treatment settings has introduced substantial complexity in patient selection, Treatment sequencing, and biomarker interpretation. This review aims to move beyond a descriptive synthesis of clinical trials and provide a clinically applicable, decision-oriented framework for the use of PARP inhibitors in metastatic prostate cancer. Methods: We conducted a narrative review of pivotal phase II and III trials published between 2020 and 2026 evaluating PARPi as monotherapy or in combination strategies. Evidence was critically analyzed with a focus on biomarker relevance, Treatment positioning, and real-world applicability. Evidence Synthesis: PARPi consistently improve radiographic progression-free survival, with the most robust and clinically meaningful benefit observed in BRCA-altered disease. In contrast, non-BRCA HRR alterations demonstrate heterogeneous and often limited predictive value, highlighting the limitations of a binary biomarker approach. Combination strategies in first-line metastatic castration-resistant prostate cancer (mCRPC) have expanded therapeutic options but raise important concerns regarding toxicity, overTreatment, and unclear benefit in biomarker-unselected populations. In parallel, variability in molecular testing strategies and access continues to limit real-world implementation. Conclusions: PARP inhibitors represent a cornerstone of precision oncology in metastatic prostate cancer, but their optimal use requires a refined, biomarker-informed approach. In this context, we propose a pragmatic 2026 clinical decision framework integrating molecular characteristics, prior Treatment exposure, and clinical factors. This approach aims to bridge the gap between clinical trial evidence, guideline recommendations, and real-world practice. Full article

Genomic sequencing can reveal potentially life-threatening clinically actionable secondary findings in healthy individuals. Little is known about the spectrum and frequency of secondary findings in healthy people in Russia. Here, we analyzed whole-genome sequences of 42,826 healthy volunteers from urban populations across Russia, focusing on known pathogenic and likely pathogenic variants of 81 genes associated with treatable or preventable monogenic diseases listed in the American College of Medical Genetics and Genomics’ Secondary Findings recommendations (ACMG SF v3.2). Based on the ClinVar 20250421 version, secondary findings were detected in 1186 (2.76%) participants. Cancer phenotypes were the most common category of secondary findings present in 565 (1.32%) participants, followed by cardiovascular phenotypes (454 individuals, 1.05%). Genes harboring the most frequent variants were BRCA1 (151 variants), BRCA2 (100), RYR1 (93), and LDLR (71). In addition, we found 238 potential loss-of-function variants in dominant ACMG SF v3.2 list genes in 280 (0.65%) participants, which, if confirmed by orthogonal methods, could increase the frequency of secondary findings to 3.41%. A study of such depth and scale was performed for the first time in the Russian population. Full article

Skeletal muscle differentiation relies on transient DNA strand breaks (DSBs), yet excessive DNA damage remains harmful to myogenic progression. The RNA-binding protein Zfp36l1 is expressed in skeletal muscle and contributes to muscle regeneration; nevertheless, its role in preserving genome stability during myogenic differentiation has not been defined. Here, we investigated the role and mechanism of Zfp36l1 in regulating DNA damage using C2C12 myoblast cells, combining loss- and gain-of-function assays, RNA-seq, and rescue experiments. The results revealed that Zfp36l1 expression is strongly induced during early myogenic differentiation, coinciding with the onset of physiological DSBs. Functional assays revealed that silencing Zfp36l1 aggravates DSB accumulation, reinforces G0/G1 cell cycle arrest, and promotes apoptosis, whereas Zfp36l1 overexpression attenuates these abnormalities. Transcriptomic profiling shows that Zfp36l1 knockdown impairs homologous recombination (HR)-mediated DNA repair by downregulating core repair factors, including Rad51 and Brca1. Gene set enrichment analysis further confirms significant suppression of the HR-dependent DSB repair pathway. Mechanistically, Zfp36l1 regulates HR repair by suppressing p21 expression, thereby relieving inhibition of E2F1-mediated Rad51 transcription. Co-silencing p21 restores Rad51 expression and reduces DNA damage in Zfp36l1-knockdown cells. Collectively, these findings identify Zfp36l1 as an essential safeguard of genome stability during myogenic differentiation by balancing DNA damage levels through the p21-E2F1-Rad51 signaling axis, and provide new insights into the regulatory basis of muscle development and genomic instability-associated muscle diseases. Full article

Background: Pathogenic germline BRCA1 and BRCA2 variants cause most hereditary breast and ovarian cancers. Widespread genetic testing has revealed thousands of variants with unknown effects on disease risk, known as variants of uncertain significance (VUS). BRCA VUS, the majority of which are missense, complicate genetic test interpretation and clinical decision-making. This study aimed to evaluate BRCA1 VUS pathogenicity with enhanced accuracy through computational, functional and structural methods. Methods: We characterized the structural distribution of BRCA1 variants. In silico tools scored known consequence variants within a specific region of BRCA1. The Molecular Feature Selection Tool (MolecularFeaST; Renwick Lab at Queen’s University; Kingston, ON, Canada) performed feature selection of the most discriminative tools. MATLAB (MATLAB R2024a; Mathworks; Natick, MA, USA) Classification Learner Application trained supervised machine learning models using combinations of the most accurate tools; the best model assigned pathogenicity prediction scores to VUS. Select VUS were functionally assessed through phosphopeptide binding pull-down assays and structurally analyzed on PyMOL (v2.4.1; Schrödinger Inc.; New York, NY, USA). Results: The RING and BRCT domains were identified as hotspots for missense pathogenic variants and VUS; BRCT was selected as the focus of the computational classifier. Nine in silico tools (CADD hg19, MetaRNN, ClinPred, VEST4, BayesDel AD, EVE, Eigen PC, gMVP and PolyPhen2) defined the BRCT-specific missense variant classifier. Twenty-two VUS (R1699P, F1704S, W1837L, W1712G, F1734S, V1804A, I1674V, V1804L, V1804I, I1807V, T1675S, I1764L, N1774I, E1698K, Q1848K, P1749S, A1669T, N1774H, L1839V, T1658I, L1705I, V1654L) demonstrated varying phosphopeptide binding ability and protein levels relative to the wildtype. Computational structural modeling contextualized VUS phosphopeptide interactions and structural implications. Conclusions: We provide in silico and functional evidence for the classification of BRCA1 BRCT VUS and highlight the utility of domain-specific computational approaches for characterizing missense variants in multi-domain genes. Full article

Background: Homologous recombination deficiency (HRD) is emerging as a clinically relevant biomarker across diverse tumor types, in addition to ovarian cancer. In this study, we evaluated the genomic instability score (GIS) across multiple tumor types using the TruSight Oncology 500 HRD assay, which incorporates the Myriad Genetics GIS algorithm, a widely used reference standard for HRD assessment. Methods: A total of 162 tumor samples (17 ovarian cancers and 145 non-ovarian tumors) underwent next-generation sequencing using the TruSight Oncology 500 HRD assay. Results: A total of 14 tumors were classified as GIS-High, defined as a GIS score ≥42, representing 8.6% of all cases. Among ovarian cancers, 7 out of 17 cases (41.2%) met the GIS-High threshold. Among non-ovarian tumors, seven GIS-High tumors were identified, accounting for 4.8% of cases (7/145). GIS-High cases occurred in breast (n = 4), lung (n = 2), and hepatobiliary tract (n = 1) cancers. GIS scores showed significant associations with BRCA1/2 and TP53 mutational status. In contrast, alterations in HRD-related genes other than BRCA1/2 did not show significant associations with GIS score. Conclusions: GIS-High tumors were identified in a small subset of non-ovarian cancers. These findings support further investigation of GIS as an exploratory biomarker of HRD-like genomic scarring beyond ovarian cancer, but its predictive and therapeutic relevance in non-ovarian tumors requires additional validation. Full article

Background: Given the challenges in early detection and diagnosis, understanding the molecular underpinnings of endometrioid ovarian cancer (EOC) is crucial for improving patient outcomes. This multi-level study provides a new perspective on EOC, focusing on the expression of ARID1a (BAF250a) and RIF1. Methods: This study evaluates patient cohorts with EOC through semi-quantitative immunohistochemical staining of BAF250a (protein encoded by ARID1a) and RIF1 proteins alongside mutations that influence the gene expression of ARID1a and RIF1. Besides survival analyses, platinum- and taxane-based treatment responsiveness with regard to ARID1a and RIF1 expression has been analyzed using an online available database. Results: Histological and immunohistochemical analysis of clinical samples revealed a significant reciprocal alteration in protein expression, characterized by a marked reduction in the tumor suppressor BAF250a (p < 0.0001) and a concomitant elevation of RIF1 (p < 0.0001) in EOC compared to controls. Tumors harboring mutations in BRCA1 exhibited significantly (p = 2.82 × 10⁻⁴) lower ARID1a expression levels compared with corresponding wild-type tumors, whereas LAMB3-mutant tumors showed a significant (p = 5.16 × 10⁻³) upregulation of RIF1 mRNA expression. Conclusions: In conclusion, our study offers a new perspective, emphasizing that EOC is a distinct clinical and molecular entity. We demonstrated the expression patterns of ARID1a/BAF250a and RIF1 in EOC, establishing their potential relevance in the context of tumor biology and malignant transformation. Full article

Background: Triple-negative breast cancer (TNBC) remains a clinical challenge due to its aggressive nature and the frequent emergence of therapeutic resistance. While the role of protein-coding genes in DNA repair is well-documented, the regulatory contributions of the non-coding genome, specifically long intergenic non-coding RNAs (lincRNAs), remain largely undefined. Objectives: In this study, we characterize the biological significance of LincRNA-BC7, a novel transcript identified within the breast cancer field effect. Methods: Through a combined in silico and in vitro approach, we investigated the transcriptional dynamics of the LincRNA-BC7/miR-663a/BRCA1 axis in response to the PARP inhibitor, Olaparib. Results: Our results demonstrate that Olaparib induces selective cytotoxicity in BRCA1-deficient MDA-MB-231 cells while sparing non-cancerous HEK293 cells, a response accompanied by a significant downregulation of LincRNA-BC7 and a reciprocal upregulation of BRCA1. Bioinformatics analysis through BLASTN, miRBase, and KEGG revealed that LincRNA-BC7 contains highly complementary binding sites for miR-663a, suggesting it functions as a competing endogenous RNA (ceRNA) or “molecular sponge.” Conclusions: By sequestering miR-663a, LincRNA-BC7 appears to modulate the expression of critical signaling nodes within the PI3K-AKT and TP53 pathways, thereby influencing cellular sensitivity to DNA-damaging agents. These findings suggest that LincRNA-BC7 is a key determinant of the aggressive TNBC phenotype and the response to PARP inhibition. Our study establishes the LincRNA-BC7/miR-663a axis as a novel biomarker for precision risk stratification and a promising therapeutic target to enhance treatment outcomes in BRCA1-associated breast cancers. Full article

Background: Breast cancer (BRCA) is a common malignant tumor that seriously threatens women’s health. Studies have shown that histone modifications (HMs) play a vital role in the occurrence and development of BRCA. This study aims to explore the distribution patterns of HMs in the mammary epithelial cell line (HMEC) and breast cancer cell line (MCF-7), and their potential associations with gene expression, patient prognosis, and drug efficacy. Methods: First, the distribution of histone modification (HM) signals in HMEC and MCF-7 cell lines was analyzed. Multiple algorithms were then used to predict the effects of different HMs and their modified regions on gene expression in the two cell lines. Based on four key regions identified from this analysis, 268 HM-related immune-related genes (H_IRGs) were screened, followed by functional enrichment and pathway analysis. Subsequently, Cox and LASSO regression analyses were performed on the H_IRGs to construct a risk scoring model. Results: The random forest algorithm showed the best predictive performance (AUC = 0.92) and identified three key HMs (H3K4me2, H3K27me3, and H3K36me3) and four key regions that strongly influenced gene expression. A risk scoring model was constructed from 11 key IRGs (BCL2A1, PSME2, STC2, ESRRG, CRISP3, IL13RA1, LCN1, EED, CLEC10A, SLURP1, and FGF12). This model effectively predicted patients’ survival in both the training and validation cohorts. Conclusions: In summary, our research results provide a theoretical basis for the occurrence and development of BRCA, and the 11 key IRGs discovered are expected to become potential biomarkers for BRCA prognostic assessment and treatment response prediction. Full article

Cancer is a complex and evolutionary disease, with the development of different types of cancers leading to various different defective gene mutations. Synthetic lethality is a genetic-level precision medical strategy. Currently, treating BRCA (BReast CAncer)-mutated breast or ovarian cancer cells with a chemical inhibitor (Poly(ADP-ribose) polymerase, PARPi) is a typical synthetic lethal application in clinical practice. However, PARPi therapy has been found to cause off-target effects and therapy-induced immune escape driven by PD-L1 upregulation, allowing for cancer cells to escape attack from the immune response. To overcome these challenges, we developed a core–shell structure comprising a hydrophobic core of quercetin (Q)-mediated PARP inhibition and iron oxide nanoparticles (IONPs), enveloped by a hydrophilic fucoidan (Fu) shell to encapsulate short hairpin RNA targeting Programmed Death Ligand 1 (shPD-L1) for efficient gene transfection (shPD-L1@QIO@Fu). Structurally, the incorporation of quercetin into the intermediate hydrophobic layer enables modulate of the PARP effect, while the inner aqueous core with shPD-L1 gene silencing can inhibit the expression of PD-L1 protein. In this study, we proved that shPD-L1@QIO@Fu demonstrated a dual therapeutic mechanism against BRCA-mutant cancer cells by inducing extensive DNA double-strand breaks and promoting apoptosis. Furthermore, the combined action of quercetin-mediated DNA damage and shPD-L1-driven PD-L1 suppression led to a significant reduction in PD-L1 mRNA to approximately 5% at 72 h and decreased surface PD-L1 below baseline by 96 h. This effectively suppresses PARPi-induced PD-L1 upregulation and enhances antitumor immunity. These findings demonstrate the therapeutic efficacy of shPD-L1@QIO@Fu nanomedicine, providing a promising foundation for advanced co-delivery strategies to synergize PARP inhibition mediated synthetic lethality with immune checkpoint blockade in next-generation precision medicine. Full article

Background/Objectives: Integrating multi-omics data for cancer prognosis remains a challenging problem in bioinformatics because molecular profiles are high-dimensional, heterogeneous, and structured by incomplete biological relationships. Pathway databases provide biologically meaningful prior knowledge for modeling gene-level associations, but the sparsity and local incompleteness of pathway-derived networks often limit the performance of graph-based survival models. This study aimed to develop a pathway-guided framework for improving multi-omics survival prediction and identifying biologically relevant prognostic signals. Methods: We proposed PANA-Surv, a pathway-guided adaptive neighborhood augmentation framework for multi-omics cancer survival analysis. In this framework, KEGG pathways were used to construct gene graphs, and gene-level multi-omics profiles were encoded as node features. A conditional variational autoencoder module (PANA-VAE) was designed to enhance local representations through neighborhood reconstruction and adaptive weighting. The augmented features were then integrated into a graph convolutional survival model optimized with the Cox partial likelihood. Results: PANA-Surv was evaluated on 10 cancer cohorts from The Cancer Genome Atlas (TCGA). The proposed method achieved the highest mean concordance index (C-index) among all compared models and significantly outperformed Cox-EN, DeepSurv, GraphSurv, and LAGProg (all p < 0.01). Ablation analyses showed that both neighborhood reconstruction and adaptive weighting contributed to the observed performance gains, and KEGG-guided graph construction was more effective than alternative graph construction strategies. In a breast cancer (BRCA) case study, PANA-Surv identified 18 prognostic genes, including 12 genes supported by previous studies and 6 potentially novel candidates. Conclusions: These findings indicate that the integration of pathway prior knowledge with adaptive local feature enhancement can improve multi-omics survival modeling and support the identification of biologically relevant prognostic signals associated with cancer outcomes. Full article

Metastatic pancreatic ductal adenocarcinoma (PDAC) is typically treated with fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) or gemcitabine plus nab-paclitaxel (GnP), but the choice between regimens remains largely empirical. This narrative review summarizes biomarkers with potential to inform first-line selection in metastatic PDAC, emphasizing genomic and transcriptomic correlates of differential benefit. Recent head-to-head trials, particularly Pancreatic Adenocarcinoma Signature Stratification for Treatment (PASS-01) and GENERATE (Japan Clinical Oncology Group [JCOG] 1611), indicate that modified FOLFIRINOX (mFOLFIRINOX) is not uniformly superior to GnP, strengthening the rationale for biomarker-guided selection. The strongest evidence favoring platinum-based/FOLFIRINOX strategies involves homologous recombination repair deficiency (HRD), especially alterations in germline breast cancer gene 1/2 (BRCA1/2) or partner and localizer of BRCA2 (PALB2), as well as broader genomic scar signatures. Transcriptomic subtype and GATA-binding protein 6 (GATA6) expression are promising but remain unsettled because retrospective data favor classical/GATA6-high disease for FOLFIRINOX, whereas PASS-01 suggested better outcomes with GnP in classical tumors. Candidate biomarkers favoring GnP include high human equilibrative nucleoside transporter 1 (hENT1), low class III β-tubulin (TUBB3) expression, and exploratory phosphatidylinositol 3-kinase (PI3K)/KIT/NOTCH pathway mutation signals. Comprehensive molecular profiling also identifies actionable alterations that may redirect patients to targeted therapy or clinical trials rather than standard chemotherapy alone. Importantly, no biomarker has yet been prospectively validated in a biomarker-stratified randomized trial with regimen selection as the primary endpoint; all biomarker-regimen associations described in this review should therefore be considered hypothesis-generating rather than practice-defining. Nevertheless, the convergence of genomic, transcriptomic, and organoid-based approaches makes biologically informed first-line selection increasingly feasible in metastatic PDAC. Full article