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PubMed2025

Stochastic epigenetic mutation profiles as biomarkers of clinical activity in juvenile idiopathic arthritis: a multi-omic machine learning approach for gene prioritization.

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a rare autoimmune disease arising from a complex interplay between genetic and environmental factors. Epigenetic modifications such as DNA methylation (DNAm) have been described as potential mediators in gene-environment interactions, contributing to immune system dysregulation. Emerging evidence suggests that DNAm profiles also predict therapeutic responses in autoimmune diseases. This study aims to identify epigenetic biomarkers and epigenetic-driven gene expression changes associated with JIA clinical activity. METHODS: We reanalyzed a publicly available dataset of 44 JIA patients, with whole-genome DNAm and gene expression from CD4 + T cells measured at two points: at anti-TNF therapy withdrawal (T0) and eight months later (Tend). At Tend, 30 patients maintained inactive disease (ID) while 14 did not (NO ID). We investigated differences between ID and NO ID patients in the epigenetic mutation load and various epigenetic clocks through linear regression models, and prioritized genomic regions with significantly higher number of epimutations in NO ID patients through machine learning. RESULTS: We found a higher mutation load in NO ID than ID patients, both at T0 and at Tend, with the differences at Tend reaching statistical significance (p = 0.02). In contrast, we found no evidence of association between epigenetic clocks and JIA clinical activity. Using a multi-omic approach, we identified a List of candidate epigenetically-driven differentially expressed genes, 80 up-regulated and 77 down-regulated, in NO ID patients. Finally, comparing our candidate gene list with the Connectivity Map database, we identified new candidate potential therapeutic targets. Key findings were validated in independent datasets: DNAm profiles from CD4 + T cells (56 JIA patients, 57 controls) and transcriptomic data from PBMCs of JIA patients with active or inactive disease, confirming dysregulation of pathways such as TNF-α signaling via NF-kB and TGF-β signaling among others. CONCLUSIONS: We described a significant association of epigenetic mutations with JIA clinical activity, indicating that epigenetic changes might precede clinical symptoms and may serve as biomarkers for early disease monitoring. Further, our results shed light on biomolecular mechanisms of JIA, supporting the development of more effective treatments.

Humans↗

PubMed2025

A comparative genomic analysis of left- and right-sided colon cancer using real-world data from the AACR project GENIE BPC dataset.

Left- and Right-sided colon cancers (LCC and RCC) are increasingly recognized as distinct clinicopathological and molecular subtypes with divergent prognoses and therapeutic responses. Leveraging a large, multi-institutional cohort from the AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) Biopharma Collaborative (BPC) (n = 750; LCC: 363 vs. RCC: 387), we conducted a comprehensive analysis of mutational profiles, tumor mutation burden (TMB), and survival outcomes. Our findings revealed a markedly higher TMB in RCC compared to LCC (6.65 ± 11.3 vs. 3.17 ± 4.35; adjusted P = 3.12×10-32), suggesting greater genomic instability in RCC. After applying functional annotation filters (PolyPhen > 0.85, SIFT < 0.05), RCC tumors were significantly enriched for mutations in BRAF (23.1% vs. 6.7%), KMT2D (8.6% vs. 3.2%), and SMAD4 (13.1% vs. 7.3%), while TP53 mutations predominated in LCC (40.6% vs. 31.8%). Multivariate Cox regression analysis identified RCC as an independent predictor of poorer overall survival (OS) relative to LCC (HR: 1.30, 95% CI: 1.02-1.66, P = 0.033). Notably, KRAS mutations were associated with significantly worse OS in LCC (HR: 1.68, 95% CI: 1.06-2.70, P = 0.027), while BRAF mutations predicted adverse outcomes in RCC (HR: 1.58, 95% CI: 1.05-2.37, P = 0.028). These results underscore the prognostic value of tumor sidedness and specific genetic alterations in colon adenocarcinoma. Our study highlights the need for sidedness-specific molecular profiling to inform precision oncology strategies in colon cancer management.

BRAF↗

PubMed2026

Lipid Metabolism-related lncRNA Model Identifies AC026412.3 as a Driver of Fatty Acid β-oxidation in Hepatocellular Carcinoma.

BACKGROUND AND AIMS: Dysregulated lipid metabolism contributes to hepatocellular carcinoma (HCC) progression, but the prognostic value and mechanistic roles of lipid metabolism-related long noncoding RNAs (LRLs) remain insufficiently characterized. This study aimed to construct and validate an LRL-based prognostic model and to investigate the biological function and metabolic mechanism of AC026412.3 in HCC. METHODS: Transcriptomic and clinical data from the The Cancer Genome Atlas Liver Hepatocellular Carcinoma cohort were analyzed to identify LRLs based on their correlation with curated lipid metabolism genes. Differential expression, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses were performed to construct a prognostic signature, which was evaluated using Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses. Functional enrichment analyses Gene Ontology [GO], Kyoto Encyclopedia of Genes and Genomes [KEGG] and gene set enrichment analysis [GSEA], mutation profiling, tumor mutational burden, immune infiltration estimation, and consensus clustering were applied to characterize associated features. A key LRL was identified through integrated bioinformatic screening and prioritization. Its biological role was assessed by quantitative reverse transcription polymerase chain reactionq (RT-PCR), western blotting, BODIPY staining, colony formation, Transwell assays, and xenograft models. RNA sequencing followed by pathway enrichment analysis was conducted to explore underlying mechanisms. RESULTS: A three-LRL signature (AL031985.3, NRAV, and AC026412.3) stratified HCC patients into distinct risk groups with significantly different survival outcomes and demonstrated independent prognostic value. AC026412.3 was markedly upregulated in HCC and associated with poor prognosis. Functional assays demonstrated that AC026412.3 promoted proliferation, invasion, and tumor growth while reducing lipid accumulation. Mechanistically, AC026412.3 upregulated solute carrier family 22 member 5 (SLC22A5), enhanced fatty acid β-oxidation, and increased adenosine triphosphate (ATP) production, thereby driving metabolic reprogramming. CONCLUSIONS: This study establishes a robust LRL-based prognostic model and identifies AC026412.3 as a key regulator of lipid metabolic reprogramming via the SLC22A5-fatty acid β-oxidation axis, highlighting its potential as a biomarker and therapeutic target in HCC.

HCC↗

PubMed2026

Associations of TILs and genomic alterations in HER2+ early breast cancer.

This study investigated the associations between tumor-infiltrating lymphocytes (TILs), genomic features, and prognosis in HER2+ early breast cancer (EBC) patients receiving adjuvant trastuzumab. We retrospectively analyzed 864 HER2+ EBC patients from Shanghai Ruijin Hospital (2009-2017). The optimal threshold of TILs for predicting disease-free survival (DFS) and overall survival (OS) was explored. Whole-exome sequencing (WES) on 261 tumors assessed the mutational profiles, tumor mutational burden (TMB), and copy number alteration (CNA). Associations between these genomic features, TIL levels, and prognosis were further evaluated. TILs showed a right-skewed distribution (median: 15%, IQR: 1-30%), and higher TIL levels were significantly associated with hormone receptor negativity and high histologic grade (P < 0.001). A 15% TIL threshold optimally predicted prognosis, with low-TIL (≤15%, 63.0%) patients showing inferior DFS (HR: 1.63, P = 0.009) and OS (HR: 2.12, P = 0.037). WES identified frequent mutations in TP53 (62.8%), PIK3CA (34.5%), and BRCA2 (9.6%). A higher TIL density was observed in TP53-wild-type, low-TMB or low-CNA tumors (P < 0.05). PIK3CA mutations conferred a significant DFS advantage. Integrating TIL level with PIK3CA or BRCA2 mutational status yielded distinct DFS trajectories (log-rank P = 0.023 and 0.040, respectively); patients with both high TIL levels and either PIK3CA or BRCA2 mutations had the most favorable outcomes. Stromal TILs at a 15% cutoff provide robust prognostic information in trastuzumab-treated HER2+ EBC. Integrating TIL levels with PIK3CA or BRCA2 mutational status enables refined risk stratification, offering a practical framework for personalized treatment decisions.

Humans↗

PubMed2026

RCoxNet: A Deep Learning Framework Integrating Random Walk with Restart, Mutation, and Clinical Data for Cancer Survival Prediction.

Accurate survival prediction in cancer remains challenging due to the sparsity of somatic mutation profiles and the failure of existing models to capture higher-order gene-gene dependencies. Network diffusion methods such as Random Walk with Restart (RWR) can propagate mutation signals across protein-protein interaction (PPI) networks to address sparsity, yet their integration within a deep learning Cox survival framework has not been comprehensively benchmarked across multiple cancer cohorts. We present RCoxNet, a deep learning framework that maps somatic mutation profiles onto a ConsensusPathDB-derived PPI network via RWR, selects prognostic genes by log-rank filtering, and processes network-informed mutation scores through three fully connected hidden layers feeding into a Cox proportional hazards output. RCoxNet was evaluated on The Cancer Genome Atlas (TCGA) cohorts for four cancer types (breast invasive carcinoma [BRCA], lung adenocarcinoma [LUNG], glioblastoma multiforme [GBM], and ovarian serous cystadenocarcinoma [OV]) using 20 independent random splits. The model achieved mean C-index values of 0.807 ± 0.044 (BRCA), 0.750 ± 0.039 (LUNG), 0.704 ± 0.041 (GBM), and 0.668 ± 0.036 (OV), consistently outperforming DeepSurv, Cox-nnet, SurvivalNet, Cox Elastic-Net (Cox-EN), and DeepHit, with statistically significant gains over Cox-EN, Cox-nnet, SurvivalNet, and DeepHit across the majority of cohorts. RCoxNet demonstrates that embedding sparse mutation profiles into a PPI network context substantially improves cancer survival prediction and yields biologically interpretable prognostic features relevant to precision oncology.

cancer survival prediction↗

PubMed2026

Clinical and genetic features of Ph-negative myeloproliferative neoplasms with dual-driver gene positivity.

OBJECTIVES: To investigate the clinical laboratory characteristics and gene mutation features of dual-driver gene positivity in patients with Philadelphia chromosome-negative myeloproliferative neoplasm (Ph-negative MPN). METHODS: We conducted a retrospective analysis of clinical data and genetic test results from 203 newly diagnosed patients with Ph-negative MPN. Of these, 194 had single-driver gene positivity and 9 had dual-driver gene positivity. High-throughput sequencing was used to detect mutations in JAK2, CALR, and MPL. Clinical characteristics and gene mutation profiles were compared between the two patient groups. RESULTS: The incidence of dual-driver gene positivity was 4.4% (9/203), with the most common combinations being JAK2 with CALR (4 patients) and JAK2 with MPL (4 patients). Compared with the single-driver group, the dual-driver group had a significantly higher risk of bleeding [4.1% (8/194) vs. 33.3% (3/9), P = 0.008] and a higher proportion of uncommon mutations [3.6% (7/194) vs. 33.3% (3/9), P = 0.006]. No statistically significant differences were observed between the two groups regarding age, thrombosis incidence, splenomegaly, or routine blood test indicators. During follow-up, 1 patient in the dual-driver group died from cerebrovascular disease. No leukaemia transformation or disease-related deaths occurred among the remaining patients. DISCUSSION: The increased bleeding risk in dual-driver patients may be related to a higher proportion of CALR mutations, elevated platelet counts, and higher variant allele frequencies, though these findings require validation in larger cohorts due to the small sample size. The higher prevalence of uncommon mutations suggests a more complex mutational landscape in this subgroup. CONCLUSION: Patients with Ph-negative MPN and dual-driver gene positivity may have a higher risk of bleeding and a more complex gene mutation profile.

Humans↗

PubMed2025

EV DNA from pancreatic cancer patient-derived cells harbors molecular, coding, non-coding signatures and mutational hotspots.

DNA packaged into cancer cell-derived EV is not well appreciated. Here, we uncovered signatures of EV DNA secreted by pancreatic cancer cells. The cancer cells and non-cancer counterparts exhibit distinct low vs. high molecular weight (LMW vs. HMW) EV DNA fragments distribution, respectively. Genome sequencing and Single Nucleotide Variants analysis revealed that 95% of reads and 94% of SNVs map to noncoding regions of the genome. Given that ~1% of the human genome represents coding regions, the 5% mapping rate to coding regions suggests a non-random enrichment of certain coding regions and mutations. The LMW DNA fragments not only set cancer cells apart, but also harbor cancer specific enrichment of unique coding regions, the top nine being FAM135B, COL22A1, TSNARE1, KCNK9, ZFAT, JRK, MROH5, GSDMD, and MIR3667HG. Additionally, the cancer cells' LMW DNA fragments exhibit dense centromeric mapping more strikingly on chromosomes 3, 7, 9, 10, 11, 13, 17, and 20. Mutational profiling turned up close to 200 mutations specific for the cancer cells. Altogether, our analyses suggest that centromeric regions might hold clues to EV DNA content from pancreatic cancer, the molecular, mutational signatures thereof, and rationalizes the need for a new approach to DNA biomarker research.

Humans↗

PubMed2026

FANCI promotes esophageal squamous cell carcinoma progression and cell cycle regulation and interacts with FANCD2.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is an aggressive malignancy with poor clinical outcomes, and reliable molecular biomarkers and therapeutic targets remain limited. Fanconi anemia group I protein (FANCI) is a core component of the Fanconi anemia (FA) pathway, but its expression pattern, clinical significance, and functional role in ESCC have not been comprehensively defined. This study aimed to investigate FANCI expression and prognostic value in ESCC, assess its effects on malignant cellular phenotypes and tumor growth, and explore its potential mechanistic relationship with Fanconi anemia group D2 protein (FANCD2) and cell-cycle regulation. METHODS: Multi-cohort analyses were performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, together with ESCC single-cell RNA sequencing (RNA-seq) data. FANCI functions were assessed by bidirectional gain- and loss-of-function experiments in vitro (proliferation, colony formation, migration, invasion, apoptosis, and cell-cycle assays) and by xenograft models in vivo. Mechanistic studies included protein-protein interaction (PPI) analyses, co-immunoprecipitation (Co-IP), and immunofluorescence (IF) colocalization. RESULTS: FANCI was consistently upregulated in ESCC across bulk transcriptomic datasets and was further supported by quantitative polymerase chain reaction (qPCR), Western blotting, and immunohistochemistry (IHC). FANCI discriminated ESCC from normal tissues in TCGA-ESCC and was independently validated in GSE53624 [area under the curve (AUC) =0.940 and 0.975, respectively]. FANCI was associated with poorer overall survival (OS) and shorter disease-free interval (DFI), and these findings were validated in an independent GEO cohort. Functionally, FANCI promoted ESCC cell proliferation, migration, and invasion, while inhibiting apoptosis; FANCI knockdown suppressed tumor growth in vivo and induced G2/M cell-cycle arrest. Mechanistically, FANCI physically interacted with FANCD2, colocalized with FANCD2 in the nucleus, and was associated with altered FANCD2 protein abundance, consistent with cell-cycle and DNA repair-related programs. Single-cell analysis indicated that FANCI was enriched in epithelial cells and associated with higher activity of malignant functional programs. In TCGA-ESCC, FANCI-high tumors showed distinct mutation profiles, a trend toward increased tumor mutation burden (TMB), and altered immune-associated signatures. CONCLUSIONS: FANCI is upregulated in ESCC and is associated with diagnostic and prognostic value. It promotes malignant phenotypes and tumor growth, potentially through a FANCI-FANCD2-linked cell-cycle/DNA repair program, supporting FANCI as a candidate biomarker and therapeutic target in ESCC.

Esophageal squamous cell carcinoma (ESCC)↗

PubMed2026

Triple primary synchronous liver cancer in one patient: the first case report and origin speculation through bioinformatics.

INTRODUCTION: A diagnosis of multiple primary liver tumors is extremely rare. Preoperative diagnosis based on imaging findings is difficult. Moreover, the clinical benefits of treatment strategies for multiple liver cancers remain unclear. Here, we report a case of three synchronous primary liver tumors with three distinct pathological types-hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangiocarcinoma (cHCC‑CCA)-in a single patient. Bioinformatics analysis supported at least two clonal origins, with cHCC‑CCA and ICC sharing a common lineage based on identical HBV integration sites. CASE PRESENTATION: A 63-year-old female with a history of hepatitis B for several years presented with three lesions in hepatic segment VIII. Multiphase magnetic resonance imaging with gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid revealed a diagnosis of multiple lesions, namely, cHCC‑CCA, with multiple intrahepatic metastases. The AFP level was normal, while the CA 19 - 9 level was mildly elevated (normal range ≤ 30.00 U/ml). Hepatectomy was performed, and postoperative assessment confirmed that the large lesion was cHCC‑CCA. However, the small lesions close to the large lesion were HCC and ICC. Gene testing revealed distinct mutational profiles among the three tumors. Similar gene mutations were detected in cHCC‑CCA and ICC. We also found that gene fragments of hepatitis B virus-C (HBV-C) were inserted into the genomes of ICC and cHCC‑CCA rather than that of HCC. The genomic integration site of HBV-C in cHCC‑CCA and ICC was the same. CONCLUSION: We report an extremely rare case of three synchronous primary liver tumors with three distinct pathological types (HCC, ICC, and cHCC‑CCA) in a single patient. Bioinformatics analysis supported at least two clonal origins, with cHCC‑CCA and ICC sharing a common lineage based on identical HBV integration sites. Hepatectomy represents a potential radical strategy for the treatment of multiple PLCs.

Humans↗

PubMed2026

Case Report: Immune-driven clonal selection underlying lineage switch from B-Precursor acute lymphoblastic leukemia to acute myeloid leukemia following inotuzumab ozogamicin.

Lineage switch (LS), defined as a change in leukemic lineage during the disease course, is a rare but clinically significant event in acute leukemia and is typically associated with poor prognosis. Although LS has been increasingly reported following targeted immunotherapies, the clonal mechanisms underlying this phenomenon remain incompletely understood, particularly in cases without KMT2A rearrangement. We report a case of LS from B-precursor acute lymphoblastic leukemia (BCP-ALL) to acute myeloid leukemia (AML) following treatment with the CD22-targeted antibody-drug conjugate inotuzumab ozogamicin. To elucidate the clonal architecture underlying LS, targeted next-generation sequencing was performed on bone marrow samples obtained at multiple time points throughout the disease course. Genomic analysis demonstrated that the lymphoid and myeloid disease phases shared ancestral genetic alterations but displayed distinct mutational profiles. At the time of LS, TP53 and SMC1A mutations newly emerged, whereas only a subset of mutations detected at ALL relapse was retained. These findings suggest that the AML phase most likely resulted from the selective expansion of a genetically distinct subclone derived from a common progenitor, rather than the direct transdifferentiation of the dominant ALL clone, consistent with immunotherapy-driven clonal selection. Longitudinal genomic profiling revealed stepwise clonal evolution during disease progression, supporting a model of immunotherapy-driven clonal selection leading to LS. This case provides molecular evidence suggesting that immune-targeted therapy can promote expansion of minor pre-existing subclones with alternative lineage potential within a common progenitor even in non-KMT2A-rearranged leukemia. Our findings highlight the importance of comprehensive genomic monitoring during immunotherapy to identify therapy-resistant subclones and better understand mechanisms of lineage plasticity in acute leukemia.

Humans↗

PubMed2025

Clinicopathologic and Molecular Analysis of Colorectal Carcinomas With Spectrum of Neuroendocrine Carcinoma Components.

The genetics of colorectal carcinoma (CRC) with neuroendocrine differentiation remain poorly understood; recent studies focusing on pure neuroendocrine carcinomas (NECs) demonstrated mutation profiles closely resembling colorectal adenocarcinomas (ACAs) with more frequent BRAF mutations and Rb/p16 pathway dysregulation. However, pathogenesis of mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs) and ACAs with minor NEC component (AMiNECs) remains controversial. We aimed to define the behavior and molecular underpinnings of these tumors in comparison with conventional ACAs. In total, 20 NECs, 10 MiNENs, and 8 AMiNECs were compared with 100 controls with ACAs. Well-differentiated neuroendocrine tumors of any grade were excluded. CRCs with NEC components presented at a slightly earlier age (mean, 59 vs 65 years; P = .24) in a similar sex distribution (male:female, 1:1.11 vs 1.04:1; P = .97). The majority of cases arose either from a precursor adenoma (42%) or in the setting of inflammatory bowel disease (18%), whereas 5 of 10 cases (50%) originating from the rectum were human papillomavirus driven. Despite similarity in tumor size and depth of invasion among all groups, CRCs with NEC components showed more frequent lymph node and distant metastases (P < .001 each), leading to more advanced disease stage (stage III/IV; P < .001) and worse 5-year survival outcomes (35.4% for NECs, 30% for MiNENs, and 41.6% for AMiNECs vs 85.1% for ACAs; P < .001), compared with ACAs. Next-generation sequencing revealed more frequent BRAF (40% vs 3%; P < .001) and BRCA1 alterations (15% vs 1%; P = .001) in NECs compared with ACAs. Genomic alterations in RB1 were exclusively found in NECs (10%) and MiNENs (20%). In conclusion, the presence of any NEC component (from AMiNEC to pure NEC) in CRC carries a dismal prognosis. Yet, these tumors are more likely to harbor potentially targetable mutations such as BRAF p.V600E and alterations in BRCA1/2, which are of therapeutic value.

Humans↗

PubMed2024

Predictive modeling of gene mutations for the survival outcomes of epithelial ovarian cancer patients.

Epithelial ovarian cancer (EOC) has a low overall survival rate, largely due to frequent recurrence and acquiring resistance to platinum-based chemotherapy. EOC with homologous recombination (HR) deficiency has increased sensitivity to platinum-based chemotherapy because platinum-induced DNA damage cannot be repaired. Mutations in genes involved in the HR pathway are thought to be strongly correlated with favorable response to treatment. Patients with these mutations have better prognosis and an improved survival rate. On the other hand, mutations in non-HR genes in EOC are associated with increased chemoresistance and poorer prognosis. For this reason, accurate predictions in response to treatment and overall survival remain challenging. Thus, analyses of 360 EOC cases on NCI's The Cancer Genome Atlas (TCGA) program were conducted to identify novel gene mutation signatures that were strongly correlated with overall survival. We found that a considerable portion of EOC cases exhibited multiple and overlapping mutations in a panel of 31 genes. Using logistical regression modeling on mutational profiles and patient survival data from TCGA, we determined whether specific sets of deleterious gene mutations in EOC patients had impacts on patient survival. Our results showed that six genes that were strongly correlated with an increased survival time are BRCA1, NBN, BRIP1, RAD50, PTEN, and PMS2. In addition, our analysis shows that six genes that were strongly correlated with a decreased survival time are FANCE, FOXM1, KRAS, FANCD2, TTN, and CSMD3. Furthermore, Kaplan-Meier survival analysis of 360 patients stratified by these positive and negative gene mutation signatures corroborated that our regression model outperformed the conventional HR genes-based classification and prediction of survival outcomes. Collectively, our findings suggest that EOC exhibits unique mutation signatures beyond HR gene mutations. Our approach can identify a novel panel of gene mutations that helps improve the prediction of treatment outcomes and overall survival for EOC patients.

Humans↗

PubMed2026

Genomic determinants of fluoroquinolone resistance in Escherichia coli in Nigeria: dominance of QRDR mutations and limited contribution of PMQR in a cross-sectional study.

BACKGROUND: Fluoroquinolone-resistant Escherichia coli is a major global clinical threat, particularly in low- and middle-income countries like Nigeria. However, the full genomic landscape, including the relative contributions of chromosomal mutations, plasmid-mediated resistance, and the role of high-risk clones, remains poorly characterized in this setting. This study aimed to define the genomic mechanisms, clonal distribution, and genotype-phenotype relationships of fluoroquinolone resistance in clinical E. coli isolates from Nigeria. METHODS: A cross-sectional study of 107 clinical E. coli isolates was conducted. Phenotypic susceptibility to ciprofloxacin and nalidixic acid was determined using VITEK 2 and broth microdilution. Whole-genome sequencing was performed, and analysis included detection of quinolone resistance determining region (QRDR) mutations (gyrA, parC, parE) and plasmid-mediated quinolone resistance (PMQR) genes, multilocus sequence typing (MLST), and phylogenetic analysis. Statistical associations were evaluated using chi-squared tests or Fisher's exact tests. RESULTS: Ciprofloxacin non-susceptibility was high at 86.0%. Resistance was primarily driven by a conserved chromosomal mutation profile; the combination of gyrA S83L, gyrA D87N, and parC S80I was present in 85 isolates and was associated with ciprofloxacin non-susceptibility in all affected isolates in this cohort. Isolates with only gyrA mutations were resistant to nalidixic acid but susceptible to ciprofloxacin, consistent with a stepwise resistance pathway. In this cohort, the triple QRDR signature (gyrA S83L + gyrA D87N/Y + parC S80I) was a perfect positive predictor of ciprofloxacin non-susceptibility (85/85; 100%). The ST131 lineage dominated, accounting for 21.5% of isolates and universally carrying the complete triple QRDR profile; notably, no ST131 isolate carried a PMQR determinant. Plasmid-mediated quinolone resistance (PMQR) genes were detected in 15.0% of isolates but were not independently associated with ciprofloxacin non-susceptibility in this cohort in the absence of concomitant QRDR mutations. Efflux pump genes were ubiquitous and non-predictive. Notably, six isolates, all from urine, were non-susceptible (R/I) despite lacking all known QRDR and PMQR determinants, pointing to uncharacterized mechanisms. In a multivariable logistic regression model that included ST131 status, PMQR carriage, and parE mutation status, ST131 was associated with ciprofloxacin non-susceptibility (adjusted OR 5.96, 95% CI 1.21-29.4, p = 0.028), whereas PMQR carriage was not (adjusted OR 0.94, 95% CI 0.18-4.85, p = 0.94). The triple QRDR signature was not included in this model because it perfectly predicted ciprofloxacin non-susceptibility in this cohort. Resistance patterns varied by clinical source, with the highest burden in bloodstream and wound infections. This stepwise hierarchy from first-step gyrA mutations to the classic triple QRDR profile is summarised in the graphical abstract, Fig. 1. CONCLUSIONS: Fluoroquinolone resistance in Nigerian clinical E. coli is predominantly driven by chromosomal QRDR mutations within successful clones like ST131. PMQR genes and efflux pumps appeared to play a supplementary role rather than being independent drivers of ciprofloxacin resistance in this cohort. These data support prioritising key QRDR mutations in genomic reporting and local stewardship decisions, while the QRDR-negative resistant urine isolates require further investigation.

Escherichia coli↗

PubMed2025

Construction and accuracy assessment of an efferocytosis-related prognostic model for ovarian cancer: A diagnostic accuracy study.

The study aimed to investigate the prognostic significance of efferocytosis-related genes in ovarian cancer (OC) with regard to cancer development, progression, invasion, and metastasis. OC cohorts were assembled from bioinformatics repositories. Utilizing consensus clustering analysis, distinct clusters were delineated based on the intersection of OC-related genes and efferocytosis-related genes. A prognostic signature specific to efferocytosis in OC was developed using data from The Cancer Genome Atlas, validated against the gene expression omnibus database, and subjected to independent prognostic analysis. Subsequently, a nomogram model was formulated. Moreover, investigations encompassed the immune microenvironment, immunotherapy, mutation profiling, drug sensitivity assessments, drug prediction models, and molecular docking analyses. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays were employed to ascertain the mRNA expression levels of key genes. Five key genes, FCGBP, BTN3A3, WDR91, SLC25A45, and BTNL3, were identified as significantly associated with OC. Both datasets and qRT-PCR demonstrated elevated expression levels of FCGBP and WDR91 in OC. Notably, AFLATOXIN B1 exhibited strong binding affinity to SLC25A45, ciclopirox to BTN3A3, and irinotecan to WDR91. The risk score, age, and stage were identified as independent prognostic factors, with the nomogram displaying efficacy in predicting OC patient survival. Variations in the immune cell infiltration profiles, including naive B cells, and expression levels of 6 immune checkpoint genes, such as CTLA4, were notable. High tumor mutation burden scores were associated with improved survival outcomes. Additionally, significant differences in the IC50 values of 123 anticancer drugs were observed between the 2 risk groups. This findings of this study highlight the efficacy of the efferocytosis-associated risk model in predicting the survival outcomes of OC patients, thus providing a novel reference for prognostic prediction in OC patients.

Humans↗

PubMed2026

Characteristics of p53 and Smad4 immunohistochemistry in pancreatic ductal adenocarcinoma and validation by next-generation sequencing.

BACKGROUND: Mutations in four major driver genes -KRAS, CDKN2A, TP53, and SMAD4- are central to the pathogenesis of pancreatic ductal adenocarcinoma (PDAC) and critically inform diagnosis, therapeutic decision-making, and prognostic assessment. Although next-generation sequencing (NGS) is widely regarded as the gold standard for detecting these mutations, its clinical application is often limited by suboptimal analytical efficiency and substantial economic cost. Among these genes, immunohistochemical (IHC) staining for the proteins encoded by TP53 and SMAD4 has been extensively adopted in routine pathology practice. However, standardized IHC pattern classification schemes and rigorous validation of their predictive accuracy for underlying genomic alterations remain lacking in PDAC. METHODS: We retrospectively enrolled 63 PDAC patients and systematically characterized the typical IHC expression patterns of p53 and Smad4. Targeted NGS was subsequently performed on all available tumor specimens, and the resulting mutational profiles were correlated with corresponding IHC findings. Diagnostic performance including sensitivity, specificity and accuracy of p53 IHC for predicting TP53 mutations and of Smad4 IHC for predicting SMAD4 mutations was rigorously evaluated. RESULTS: Among the four canonical driver genes, co-occurring double- or triple-gene mutations were prevalent; within TP53 and SMAD4, missense mutations constituted the most frequent variant type. Using NGS as the reference standard, we validated the diagnostic utility of a three-tiered p53 IHC classification system, particularly in fine-needle biopsy (FNB) specimens. Furthermore, we proposed a novel, refined Smad4 IHC pattern classification that incorporates an "intermediate" category, thereby expanding upon conventional binary interpretation. This new scheme achieved markedly improved mutation prediction accuracy (0.76) compared with traditional approaches (0.57). CONCLUSION: Our study highlights the complementary diagnostic value of p53 and Smad4 IHC relative to molecular testing in PDAC, especially when tissue is limited, as commonly encountered in FNB specimens. The newly established Smad4 IHC classification system, which integrates an intermediate expression category into the conventional two-tier framework, demonstrates superior clinical utility and enhances predictive accuracy for SMAD4 genomic alterations.

Humans↗

PubMed2025

SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection.

SUMMARY: SISTEM is a software package and mathematical framework for simulating tumor evolution and cell migrations at single-cell resolution. Unlike existing frameworks which simulate cancer cell populations under the neutral coalescent or using simple birth-death models, SISTEM simulates tumor populations under somatic clonal selection using an agent-based framework. SISTEM can generate mutation profiles, read counts, and DNA sequencing reads along with ground truth cell lineages and migration graphs under a number of easily customizable mutation and selection models. For improved realism, SISTEM allows for cell fitness to be driven by genomic events of various scales including single nucleotide variants, segmental gains and losses, whole-chromosomal and chromosome-arm aberrations, and whole-genome duplications. SISTEM also includes numerous migration models to simulate metastatic cancers, facilitating the exploration and evaluation of diverse migration patterns. AVAILABILITY AND IMPLEMENTATION: SISTEM is written in Python and is freely available open-source under GNU GPLv3 from: https://github.com/samsonweiner/sistem.

Software↗

PubMed2026

Establishment of Stable Immortalized Human Choroidal Melanocytes for Ocular Research.

PURPOSE: The short lifespan of primary normal choroidal melanocytes (NCMs) in vitro represents a major barrier to mechanistic, functional, and translational studies of choroid biology and uveal melanoma (UM). This study aimed to establish and characterize immortalized human NCM lines that retain melanocytic function, maintain a non-cancerous profile, and are amenable to gene editing. METHODS: NCMs from four donors were immortalized by lentiviral transduction of cyclin-dependent kinase 4 (CDK4R24C), cyclin D1, and human telomerase reverse transcriptase (hTERT), establishing NCM-K4DT lines. Their morphology, melanocytic marker expression, proliferation, and functional properties (melanin synthesis and tyrosinase activity) were evaluated. Genomic stability was assessed by targeted mutation profiling, karyotyping, and copy number variation (CNV) analysis. The tumorigenicity was tested in immunodeficient mice. Plasmid-based CRISPR/Cas9 editing was performed to determine their suitability for gene editing. RESULTS: NCM-K4DT lines retained dendritic-shaped morphology, pigmentation, and expression of PMEL, TYRP1, Melan-A, and SOX10. Cells exhibited enhanced proliferative capacity with preserved cell cycle regulation. Melanin production and tyrosinase activity were comparable to primary NCMs. Genomic profiling confirmed the absence of UM-associated driver mutations and chromosomal abnormalities. In vivo growth assays demonstrated that NCM-K4DT lines did not form tumors within the 3-month observation period. Notably, NCM-K4DT cells were efficiently edited by CRISPR/Cas9. CONCLUSIONS: NCM-K4DT lines represent stable, non-cancerous, and genetically tractable models for studying choroidal melanocyte biology, modeling UM-associated mechanisms, and advancing therapeutic development in ocular research.

Humans↗

PubMed2025

Genomic and Transcriptomic Landscape of Epstein-Barr Virus-Positive Inflammatory Follicular Dendritic Cell Sarcoma: A Multicenter Study.

Epstein-Barr virus (EBV)-positive inflammatory follicular dendritic cell sarcoma (EBV+ IFDCS) is a rare indolent malignant neoplasm, which occurs almost exclusively in the liver or spleen and may arise from a common EBV-infected mesenchymal cell that differentiates along the follicular or fibroblastic dendritic cell pathway. Despite its rarity, it presents a pressing need for an improved understanding of its genetic underpinnings and potential treatment strategies for recurrent or disseminated cases. To address this, we conducted comprehensive whole-exome sequencing and transcriptome sequencing (mRNA-seq) analyses on 31 and 6 cases of EBV+ IFDCS, respectively, collected from multiple centers in China. We also compared the genetic features of EBV+ IFDCS with those of other EBV-associated malignancies. Our analyses revealed a relatively high somatic mutation rate and widespread copy number variations affecting the major histocompatibility complex-I/II in EBV+ IFDCS. Integrated mutational profiling identified key signaling pathways involved in epigenetic regulation, NF-κB signaling, RTK/RAS/PI(3)K, and the Hippo pathway. Furthermore, we identified several frequently altered genes that could serve as potential therapeutic targets in EBV+ IFDCS. Transcriptomic analysis unveiled significant upregulation of pathways related to virus infection, immune responses, and multiple immune checkpoint genes in EBV+ IFDCS. Comparative analysis demonstrated clear genetic distinctions between EBV+ IFDCS and other EBV-associated tumors. In conclusion, our study provides comprehensive insights into the unique genomic and transcriptomic landscape of EBV+ IFDCS. We have identified multiple genetic alterations that likely contribute to the development and progression of this malignancy. Our results suggest that targeted therapy and immune checkpoint inhibitors may hold promise as potential therapeutic approaches for patients with recurrent or disseminated EBV+ IFDCS.

Humans↗