Search Results (324)

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a rising incidence and a poor prognosis that largely reflects late-stage diagnosis. Although most cases are sporadic, approximately 5–10% of PCs occur in the context of inherited cancer susceptibility, including hereditary pancreatic cancer (HPC) syndromes and familial pancreatic cancer (FPC). Germline pathogenic variants in genes involved in DNA damage repair, cell-cycle regulation, and genomic stability—such as BRCA1, BRCA2, PALB2, ATM, CDKN2A, STK11, mismatch repair genes, and TP53—contribute to PC risk and may influence disease biology. This review provides an overview of the genetic landscape of hereditary and FPC, focusing on established cancer predisposition syndromes and emerging susceptibility genes. Current evidence regarding the prevalence, penetrance, and clinical relevance of germline pathogenic variants (PGVs) is summarized, together with the challenges associated with identifying individuals at increased risk. Contemporary recommendations for germline genetic testing, including the use of multigene panel approaches and limitations in real-world implementation, are also discussed. In addition, surveillance strategies for PDAC in high-risk individuals (HRI) are reviewed, and the available data on the outcomes and limitations of surveillance programs are examined. Finally, the therapeutic implications of inherited alterations, particularly in DNA repair-deficient PC, are outlined with reference to genotype-informed systemic treatment approaches. Full article

Cancer predisposition syndromes (CPSs) account for 8.5–18% of all childhood cancer cases. Most of them are inherited in an autosomal dominant pattern; consequently, there is a 50% risk of transmission to offspring. Early detection of CPSs is crucial for choosing patient treatment strategies and for counseling in the family. This study enrolled 886 pediatric patients with hematologic and solid neoplasms from prospective and retrospective cohorts (2018–2025). Clinical exome or multigene panel sequencing was used to analyze blood DNA. Overall, 186 pathogenic/likely pathogenic (PLP) variants in cancer-associated genes were identified in 176/886 (20%) of patients, and the most frequently mutated were the NF1 (n = 35) and TP53 (n = 18) genes. Among the 186 PLP variants, 126/886 (14.2%) were causative for pediatric neoplasms, while 56/886 (6.3%) were heterozygous mutations associated with adult-onset CPSs affecting DNA repair. The highest total mutation rate was revealed in retinoblastoma (80%), peripheral nerve sheath tumors (60%), and pheochromocytoma/paraganglioma (47%), while the lowest rate was found in hematologic malignancies (4.6%) and neuroblastoma (12%). The wide range and high frequency of deleterious variants in pediatric patients, especially in those with solid tumors, highlights the importance of multigene panel sequencing for the accurate determination of CPSs. Full article

Background: Germline multigene testing is increasingly integrated into breast cancer care, but the ability of current eligibility frameworks to identify pathogenic variant carriers remains uncertain in real-world cohorts. Methods: This retrospective observational study included 556 patients with histologically confirmed breast cancer who underwent germline multigene testing at a single oncology center. Testing eligibility was retrospectively assessed according to NCCN criteria, ESMO-based recommendations, and the ASBrS universal-testing recommendations. Family history up to third-degree relatives and surgical data were evaluated. Results: Pathogenic variants were identified in 137 patients (24.6%), while variants of uncertain significance were reported in 310 patients (55.8%). NCCN criteria were fulfilled by 135 of 137 patients with pathogenic variants (98.5%), indicating high sensitivity but limited discriminatory capacity, as eligibility was also frequent among patients without pathogenic variants. ESMO-based criteria were met by 94 mutation-positive patients (68.6%) and were significantly associated with pathogenic variant status (p < 0.001; OR = 3.08, 95% CI: 2.05–4.65). Notably, 42.3% of pathogenic-variant-positive patients reported no family history of malignancy. Prophylactic surgery was documented in only 16.8% of patients with pathogenic variants. Conclusions: NCCN criteria captured nearly all mutation-positive patients; ESMO-based criteria were more selective. The findings support broader access to germline testing before surgery. Full article

Rice tiller number is a key determinant of panicle number and yield, yet its genetic architecture is highly influenced by environmental variation. Identifying loci showing reproducible effects across multiple growing seasons at the same experimental site is important for improving the reliability of GWAS-based locus prioritization for breeding. In this study, 240 rice accessions from the Rice3K panel were evaluated for tiller number over three growing seasons (2021–2023) in Sanya, Hainan Province, representing the South China rice-growing region. Genome-wide association analyses using GLM and MLM, combined with BLUEs, identified reproducible genetic signals. Several previously reported tillering-related genes, such as NAL1, BON3, ANT1, MRG702, D27, WTG1, and VPE2, were detected across different analyses. Among them, NAL1 and ANT1 represented the most consistently associated loci across three growing seasons and statistical models. Gene-based association analysis identified the promoter variants Chr4:31203262 (C/T) in NAL1 and Chr7:7310528 (G/A) in ANT1 as the lead polymorphisms, with the favorable C and G alleles associated with increased tiller number, respectively. In addition, nine putative candidate loci showing suggestive associations across three growing seasons were identified as putative candidate breeding resources. These results highlight the importance of integrating multi-year phenotyping with GWAS to prioritize loci showing reproducible associations across three growing seasons and provide valuable candidate genetic resources for future molecular improvement of rice adapted to the South China rice-growing region. Full article

Salinity stress affects not only the survival and productivity of halophytic plants, but also the composition, structure and processability of their biomass. In Salicornia spp., salt-induced regulation of ion transport, osmotic adjustment, reactive oxygen species signaling, antioxidant defense, and cell wall remodeling can directly influence residual salinity, water retention, texture, extractability, drying behavior, and oxidative stability of plant biomass. However, most existing transcriptomic studies of Salicornia and related halophytes have focused mainly on salt tolerance mechanisms, whereas the connection between stress-regulated molecular networks and processing-related biomass traits remains insufficiently systematized. This review addresses this gap by proposing a mechanistic framework that links salinity perception, ROS-mediated signaling, ABA and MAPK pathways, antioxidant gene families, transcription factor networks and processing-oriented quality traits. Special attention is given to enzymatic antioxidant systems, including SOD, CAT, APX, POD and components of the ascorbate-glutathione cycle, as well as to non-enzymatic defense mechanisms involving ascorbate, glutathione, phenolic compounds, carotenoids, proline and glycine betaine. The review also discusses the regulatory roles of WRKY, DREB/CBF, NAC, bZIP and MYB transcription factor families as molecular control points connecting salinity stress responses with downstream metabolic and structural traits. Network-based approaches, including WGCNA, pathway signatures and transcript panels, are considered more informative than single-gene markers for predicting complex quality traits in Salicornia biomass. In addition, recent genomic and computational strategies, including CRISPR/Cas-mediated functional validation, GWAS, genomic selection, multi-omics integration and AI-assisted modeling, are discussed as emerging tools for candidate-gene prioritization and predictive assessment of stress-dependent biomass quality. Overall, this review shifts the interpretation of Salicornia transcriptomics from a descriptive salt-tolerance model toward a mechanistic and application-oriented framework for improving halophytic raw materials for food, feed and bioprocessing applications. Full article

Low-density SNP panels are widely used to reduce genotyping costs in genomic selection (GS) in aquaculture, but sparse marker density can constrain prediction accuracy, particularly in species with rapid linkage disequilibrium decay. In this study, we evaluated a locally enriched multi-SNP (mSNP) strategy derived from a conventional 1K SNP panel in a family-based breeding population of Pacific white shrimp (Penaeus vannamei). Targeted sequencing was used to recover multiple nearby variants surrounding each marker locus, and conventional SNP and mSNP panels were compared for genomic features, imputation performance, and genomic prediction accuracy for body weight. The mSNP panel exhibited higher polymorphism and broader gene-region coverage than the corresponding SNP panel. The original mSNP panel improved prediction accuracy by 11.6% over the original 1K SNP panel. This advantage was maintained or slightly improved when mSNPs were restricted to on-target variants within ±300 bp of the target markers. A locus-matched comparison further showed that enriched mSNPs consistently outperformed conventional SNPs derived from the same target loci, with a 12.0% improvement at the full 961-locus panel. Although imputation improved the 1K SNP panel, the original mSNP panel already outperformed the imputed SNP panel and reached 0.509 after imputation. These findings demonstrate that locally enriched mSNP markers provide an effective and practical strategy for improving low-density GS in aquaculture species with rapid LD decay. Full article

Background/Objectives: Reliable biomarkers for longitudinal surveillance of neuroendocrine tumors (NETs) remain an unmet clinical need. Chromogranin A (CgA), the most widely used circulating biomarker, is limited by low sensitivity, substantial biologic variability, and poor concordance with radiologic progression. NETest2.0^® is a blood-based multigene transcriptomic liquid biopsy designed to dynamically assess NET biologic activity. This study compared serial NETest2.0^® measurements with CgA for monitoring disease progression in a real-world registry cohort. Methods: Patients with histologically confirmed NETs enrolled in the RegisterNET program (NCT02270567) who had paired blood samples and contemporaneous clinical assessment were included. NETest2.0^® scores were derived from quantitative RT-PCR analysis of a 51-gene transcript panel and expressed on a 0–100 scale. Serum CgA levels were measured using standard clinical immunoassays. Imaging-based disease assessment was performed using CT, MRI, and/or ⁶⁸Ga-somatostatin receptor PET/CT with RECIST 1.1 criteria applied where appropriate. Longitudinal percentage changes (Δ) between sequential measurements were evaluated using predefined NETest2.0^® thresholds and compared with the conventional CgA threshold (>50%). NETest2.0 Δ thresholds of >0% and >5% were evaluated a priori: >0% as a high-sensitivity threshold capturing any upward transcriptomic drift, and >5% as a more conservative threshold intended to reduce minor biological or analytical fluctuation. Receiver operating characteristic (ROC) analysis, operating characteristics, multivariable analysis (MVA), and logistic regression analysis (LRA) were performed. Results: A total of 191 patients were analyzed. Exploratory ROC analysis demonstrated superior discrimination for progression using serial NETest2.0^® changes compared with changes in CgA (AUC: 0.893 vs. 0.538; p < 0.0001). In the primary surveillance analysis, NETest2.0^® thresholds of >0% and >5% achieved AUCs of 0.860 (95% CI: 0.803–0.906) and 0.822 (95% CI: 0.760–0.873), respectively, both significantly superior to CgA (AUC: 0.553, 95% CI: 0.480–0.625; both p < 0.0001). NETest2.0^® >0% demonstrated the highest sensitivity (86.4%), whereas NETest2.0^® >5% achieved the optimal balance of sensitivity (70.5%), specificity (93.9%), and overall accuracy (88.5%). In multivariable and logistic regression analyses, changes in NETest2.0^® were the strongest independent predictor of progression (all p < 0.0001; odds ratios: 52.99–61.26), whereas CgA did not significantly contribute to progression prediction. Conclusions: Serial NETest2.0^® assessment significantly outperformed CgA for monitoring NET disease activity and progression. These findings support the integration of NETest2.0^® into molecularly informed surveillance strategies to complement imaging and improve longitudinal monitoring of patients with NETs. Full article

Background/Objectives: Advanced hormone receptor-positive (HR+), epidermal growth factor 2-negative (HER2−) breast carcinoma (BC) patients receive frontline therapy with cyclin-dependent tyrosine kinase 4/6 inhibitors + endocrine therapy (ET). At progression, the best management includes mutational analysis for ESR-1, allowing second-line therapy with elacestrant. The aim of this study was to evaluate the efficacy and safety of elacestrant in an Italian real-world setting. Methods: A multicenter, observational study with a mixed retrospective and prospective design was conducted in 13 medical oncology units across Italy. The study population included adult patients with HR+/HER2− locally advanced or metastatic breast cancer with an activating ESR1 mutation documented by liquid biopsy and progressing after at least one line of endocrine therapy containing a CDK4/6 inhibitor. Mutational analysis of plasma was performed using next-generation sequencing with a multigene panel that included ESR1, PIK3CA, AKT, and PTEN. The sample size was calculated according to the two-stage Simon design. Toxicity was classified according to CTCAE version 5.0 criteria. Survival analyses were conducted using the Kaplan–Meier method. Results: At the time of analysis, 39 evaluable patients were enrolled, all female and Caucasian, with a median age of 67 years (range 41–89). The efficacy analysis documented an overall ORR of 28% and a disease control rate of 56%. The median duration of response was 6+ months (95% CL: 3.5–10.6 m). Median overall survival was not reached with a median follow-up of 10 months. The toxicity profile was overall favorable: grade ≥2 asthenia was the most frequent adverse event (23%), followed by gastrointestinal toxicity, which was generally mild. No treatment-related toxicity was reported in 64% of patients. Dose reductions were necessary in 15% of cases, while permanent treatment discontinuation due to toxicity occurred in only 4%. Conclusions: The results of this Italian multicenter observational study confirm the efficacy and tolerability of elacestrant in HR+/HER2− metastatic breast cancer with ESR1 mutation, in a real-world context consistent with the data from the pivotal EMERALD study and with real-world data present in the literature. Full article

Cytohesin-4 (CYTH4), an ARF guanine nucleotide exchange factor, remains unknown in RCC pathogenesis. We report that CYTH4 was dramatically upregulated in clear cell renal cell carcinoma (ccRCC) and following ccRCC progression. CYTH4 was strongly associated with ccRCC’s immune-suppressive features and stratified ccRCC poor outcome. From CYTH4’s network/NW, a multigene panel, SigCYTH4NW, was derived. In retrospective studies, (1) SigCYTH4NW effectively predicted ccRCC’s inferior prognosis, was strongly associated with the well-validated poor risk ccB signature in four independent ccRCC cohorts (n = 1132), was significantly upregulated in ccB compared to ccA (favorable risk) tumors, was robustly correlated with an immune checkpoint signature (SigIC), and was predominantly expressed in tumor-associated macrophages, and (2) SigCYTH4NW effectively predicted poor prognosis and correlated with SigIC across 21 other cancer types. CYTH4 was expressed at low levels in 786-0 ccRCC cells; its stable expression promoted 786-0 cell proliferation in vitro and xenograft formation in vivo. CYTH4 bound PPP1R9B, which maintains pRb’s hypophosphorylation. 786-0 CYTH4 cells displayed intensive pRb hyperphosphorylation, suggesting that CYTH4 enhances cell proliferation partially by pRb inhibition. Gene expression profiling by RNA-seq revealed a 786-0 CYTH4 network that was relevant to primary ccRCC, particularly in the aspect of immune evasion. Collectively, this study supports CYTH4’s promoting ccRCC. Full article

The present study evaluated the stability of candidate reference genes during adipogenic differentiation of 3T3-L1 cells cultured on different extracellular matrices. The aim was to investigate the effects of matrix composition and differentiation stage on the expression of candidate housekeeping genes and to compare validation strategies in dynamic in vitro models. Eleven candidate reference genes (18S, Actb, B2m, Gapdh, Hmbs, Hprt, Nono, Ppia, Rplp0, Tbp, and Ywhaz) were analyzed by RT-qPCR in 3T3-L1 cells cultured on TC, collagen, gelatin, and Matrigel at Days 7 and 14 of differentiation. Gene stability was assessed using geNorm, NormFinder, RefFinder, comparative ΔCt, BestKeeper, generalized linear model (GLM), linear mixed model (LMM), and correlation analyses with the adipogenic markers Pparg and Fasn. The results demonstrated that the expression of most housekeeping genes was influenced by matrix composition, differentiation stage, or their interaction. Actb and 18S exhibited the strongest condition-dependent variability and pronounced matrix sensitivity. Gapdh and Hprt showed significant correlations with both Pparg and Fasn, while Hmbs correlated with Fasn, suggesting that these reference genes may not be fully independent of adipogenic status. Ppia demonstrated markedly contrasting rankings across analytical approaches, highlighting limitations of single-method stability assessment. The findings confirm that universal housekeeping genes are unlikely to exist across different matrix conditions and differentiation stages. The results highlight the need for multi-level validation strategies and experimentally validated normalization panels to minimize normalization bias and avoid misleading RT-qPCR expression profiles. Functional validation identified B2m and Rplp0 as the most suitable two-gene normalization panel for the experimental model evaluated, whereas Tbp remained a strong complementary reference gene candidate. Full article

Background: Cancer predisposition syndromes (CPS) are increasingly recognized in pediatric oncology. In many cases, malignancy in children represents one manifestation of a broader genetic syndrome, often accompanied by dysmorphic features or other distinctive clinical findings. Methods: Clinical documentation and genetic test reports of pediatric patients evaluated over a six-year period (2020–2025) at a genetic counseling unit in a tertiary university hospital in Varna, Bulgaria, were retrospectively reviewed. Referral patterns, clinical characteristics, and genetic findings in children assessed for suspected CPS were analyzed. Results: In total, 430 children underwent genetic testing during the study period; among them, 42 fulfilled the criteria for CPS and were subsequently included in the analysis. Patients were categorized into three groups: those with malignancy (21.4%), those with high-risk hematologic/immune features without malignancy (9.5%), and those referred based on phenotypic features alone (69.0%). Most referrals originated outside oncology services, primarily from general pediatric clinics and outpatient settings, highlighting the importance of non-oncologists in early CPS recognition. Multisystem phenotypic features were common, with 69.0% of patients exhibiting involvement of two or more clinical domains. Genetic testing, predominantly using multigene panels and exome sequencing, identified clinically relevant variants in established CPS genes, most frequently in autosomal dominant conditions within this diagnosis-confirmed cohort. The most common diagnostic categories included NF1 spectrum disorders and RASopathies. Conclusions: These findings emphasize that CPS identification often relies on recognition of non-oncologic features rather than malignancy alone. Genetic counseling plays a central role in diagnosis, risk assessment, and cascade testing. Strengthening awareness among general pediatricians and improving access to genetic services are critical for optimizing early detection and prevention strategies. Full article

Understanding germline genetic variation is essential for improving human cancer care. Cancer predisposition genetic testing has become a part of the landscape of healthcare. Clinical guidelines have been established to identify individuals with monogenic risk, support variant classification, and guide enhanced cancer surveillance and prevention strategies. However, genetic mechanisms, cancer syndromes, genetic testing, patient education, and high-risk cancer management are often addressed in separate professional domains leading to limited cross-disciplinary understanding and confusion. A review tailored to a broad spectrum of clinicians is necessary to synthesize information, connect key concepts, and clearly define the principles and reasoning underlying recommended practice. Advanced genetic technology identified numerous genes and countless pathogenic variants contributing to a wide range of cancer predispositions. Rapid and accurate next-generation sequencing has enabled the routine use of multi-gene panel testing to stratify cancer risk. In precision cancer therapies, tumor genomic profiling frequently uncovers not only somatic alterations but also germline mutations, revealing additional cancer risk for the patients and their biological relatives. Beyond monogenic risks, the cumulative effect of numerous common polygenic factors can also significantly influence cancer susceptibility. Despite major advances in integrating germline genetic information into cancer care, substantial challenges remain in variant interpretation, precise risk stratification, and implementing personalized screening and prevention strategies. Using several cancer predisposition syndromes as examples, such as breast and ovarian cancer syndrome, Lynch syndrome, and Li-Fraumeni syndrome, the review provides a high-level overview of key concepts, the evolution of knowledge and technology, and the rationale underlying the current clinical management strategies. Full article

Inherited retinal diseases (IRDs) are a major cause of visual impairment worldwide, marked by extensive genetic and phenotypic heterogeneity. Recent estimates from the U.S. suggest a prevalence of nearly 1 in 1000 individuals, reflecting both disease burden and improved diagnostic recognition. This review traces the shift from linkage analysis and Sanger sequencing to high-throughput next-generation sequencing, including panel-based, whole-exome, and whole-genome sequencing. Phenotype-driven testing strategies and standardized variant interpretation frameworks, such as the American College of Medical Genetics and Genomics guidelines, have substantially increased diagnostic yield. Copy number and structural variant detection, transcriptomics, and functional assays further help address unresolved cases. Nonetheless, barriers remain regarding cost, access, and the interpretation of variants of uncertain significance. Molecular confirmation has become essential for access to novel gene-directed therapies, exemplified by voretigene neparvovec for biallelic RPE65 variants, and is often a prerequisite for clinical trial participation. The growing role of genetic testing highlights the need for multidisciplinary evaluation and standardized outcome measures. Emerging tools, including artificial intelligence-assisted variant prioritization, image-to-genotype modeling, and multi-omics analyses, bridge molecular diagnoses with clinical phenotypes, accelerating the transition to targeted therapies. Continued progress will depend on increased access, standardized analytical regulations, and the integration of emerging technologies into routine clinical care. Full article

With colorectal cancer (CRC) accounting for over 1.9 million new cases and 930,000 deaths globally in 2020, there is a critical need for innovative indicators to forecast disease advancement and therapeutic outcomes. The gut microbiome has emerged as a fertile area for discovering such diagnostic and prognostic signals. This narrative review collected current evidence on intestinal microorganisms and their metabolic products as candidate markers for CRC control. Intestinal communities influence malignancy through diverse mechanisms, including metabolic shifts, immune modulation, inflammation, proliferation/apoptosis regulation, genotoxicity, and mucosal barrier disruption. Pathogenic species, such as Fusobacterium nucleatum and enterotoxigenic Bacteroides fragilis, facilitate tumorigenesis via FadA-mediated signaling and Th17/IL-17 responses. In contrast, beneficial taxa like Faecalibacterium prausnitzii and Akkermansia muciniphila provide protective effects through short chain fatty acid production. Macrophage phenotype physiological equilibrium is altered and inflammatory status fluctuates under the former. Metabolically, hydrogen sulfide damages mitochondrial DNA and secondary bile acids stimulate cellular proliferation. While 16S rRNA sequencing and shotgun metagenomics are established detection strategies, innovative platforms like organoids and gene arrays remain in the exploratory stage. Clinical data indicates that F. nucleatum aligns with advanced tumor stage, and its combined detection with colibactin-producing E. coli achieves high sensitivity for early-stage screening. Additionally, A. muciniphila levels can anticipate the efficacy of PD-1 blockade immunotherapy. Microbiota-derived tools represent a transformative direction in oncology. Future research must focus on standardizing protocols and validating multi-marker panels to enhance clinical translation. Full article

Soybean (Glycine max [L.] Merr.) seed hardness is a critical physical trait that dictates processing efficiency and end-product quality, yet the underlying genetic and metabolic regulatory networks remain poorly elucidated. To systematically decipher the mechanisms governing this complex quantitative trait, a multi-omics approach integrating a genome-wide association study (GWAS), transcriptomics, and metabolomics was conducted on a panel of 162 soybean germplasm accessions from Northeast China. Four significant quantitative trait nucleotides (QTNs) on chromosomes 15 and 19 were identified by GWAS. Subsequent RNA-seq and liquid chromatography–mass spectrometry (LC-MS) analyses comparing extreme phenotypes identified 573 differentially expressed genes (DEGs) and 784 differentially accumulated metabolites (DAMs). Joint multi-omics analysis revealed 14 consistently enriched pathways, highlighting the crucial role of secondary metabolite biosynthesis. Notably, Glyma.19G030500, which encodes an isoflavone malonyltransferase, was identified as the primary hub gene. These findings offer valuable genomic targets for the marker-assisted breeding of soybean varieties with optimized processing qualities. Full article