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PubMed2026

Estrogen Receptor, GATA-3, TTF-1, and KRAS in Endometrial Carcinoma of No Specific Molecular Profile: Prognostic or Diagnostic Markers?

Endometrial carcinoma with no specific molecular profile (NSMP) is a clinicopathologically heterogeneous group of diseases with an overall intermediate prognosis. Prognostic refinement is needed for better personalized treatment. The updated European Society of Gynecological Oncology-European Society for Radiotherapy and Oncology-European Society of Pathology guidelines for endometrial carcinoma stratify NSMP according to histotype and estrogen receptor (ER) status. ER (with other ancillary markers) also helps differentiate histotypes of endometrial carcinoma. This study describes clinicopathological characteristics of ER-positive and -negative-NSMP endometrial carcinoma. Furthermore, we investigate the prognostic and diagnostic significance of ER, GATA3, TTF1, and KRAS in a large and relatively unselected NSMP carcinoma cohort. POLE sequencing results and immunohistochemistry for p53, mismatch repair proteins, and ER were available for 930 samples of endometrial carcinoma. Within NSMP cases (n = 377), 22 samples presented ER staining in <1% of the carcinoma cells, 5 cases in 1% to 9%, and 350 cases in ≥10%. ER expression ≥10% predicted an excellent outcome (comparable with POLE-mutated cases) in univariable analysis, where ER negativity (<10%) was associated with a poor outcome (comparable with p53 abnormal cases). Most ER-positive NSMP cases were low-grade endometrioid carcinomas, whereas most ER-negative NSMP cases were nonendometrioid or high-grade endometrioid carcinomas. In addition to high-risk histotype, ER negativity was associated with various other clinicopathological risk factors. In multivariable analysis adjusting for histotype and other risk factors, ER did not independently predict disease progression (P = .814). No disease-related deaths were observed in the rare (n = 3) patients with ER-negative-low-grade endometrioid carcinoma. GATA3/TTF1 positivity and KRAS mutation were discovered not only in mesonephric-like carcinoma but also in endometrioid carcinoma. No prognostic relevance was found for these markers. In conclusion, the different prognosis of ER-positive vs ER-negative-NSMP endometrial carcinoma is not attributable to ER status itself but rather to its strong correlation with histotype and other clinicopathological risk factors. Limited specificity of GATA3, TTF1, and KRAS warrants caution in their use as diagnostic markers of mesonephric-like carcinoma.

Humans↗

PubMed2026

Personalizing endometrial cancer care beyond histology: clinical applications and limits of molecular classification.

Endometrial cancer is a biologically heterogeneous disease whose management has been reshaped by molecular classification. This review summarizes the current evidence supporting the integration of molecular subgroups into prognostic assessment and treatment personalization across stages of disease. The Cancer Genome Atlas classification and its clinically applicable surrogates identify four major molecular categories: POLE-mutated, mismatch repair-deficient, p53-abnormal, and no specific molecular profile tumors. These groups differ substantially in biology, prognosis, treatment sensitivity, and areas of unmet need. POLE-mutated tumors have an excellent prognosis and represent the clearest candidates for adjuvant treatment de-escalation, particularly in early-stage disease. Mismatch repair-deficient tumors show intermediate prognosis but strong sensitivity to immune checkpoint inhibition, which has transformed the management of advanced and recurrent disease and is now being tested in earlier settings. p53-abnormal tumors represent the highest-risk subgroup, requiring multimodal treatment and offering opportunities for biomarker-driven strategies including HER2-directed therapy and DNA damage repair targeting. No specific molecular profile tumors remain the most heterogeneous category, increasingly refined by estrogen receptor status, grade, L1 cell adhesion molecule overexpression, and other biomarkers. Mismatch repair-proficient advanced/recurrent disease should be interpreted as a composite clinical trial population rather than a molecular class. Molecular classification should be integrated with traditional clinicopathologic factors, emerging biomarkers, and local implementation strategies to support equitable, biologically informed treatment selection in endometrial cancer.

Humans↗

PubMed2026

Integrated expression profiling of trophoblast cell-surface antigen 2 (TROP2), folate receptor alpha (FRα), and human epidermal growth factor receptor 2 (HER2) in endometrial Cancer across molecular classes, genomic alterations, and histologic subtypes.

OBJECTIVE: Antibody-drug conjugates (ADCs) are expanding treatment options in endometrial carcinoma, but the distribution of actionable surface targets across histologic, molecular, and genomic subgroups remains incompletely defined. METHODS: This single-institution retrospective tissue microarray (TMA) study included 312 endometrial carcinomas: 158 endometrioid and 154 serous tumors. Trophoblast cell-surface antigen 2 (TROP2) was quantified by histochemical score (H-score); human epidermal growth factor receptor 2 (HER2) was assessed using endometrial carcinoma-specific and gastric/DESTINY-PanTumor02 criteria; and folate receptor alpha (FRα) positivity was defined as ≥75% viable tumor cells with ≥2+ membranous staining. Molecular class was assigned using a hierarchical DNA polymerase epsilon (POLE)-mutant, microsatellite instability/mismatch repair-deficient (MSI/MMRd), p53-abnormal, and no specific molecular profile (NSMP) classifier. Tumor mutational burden (TMB) and recurrent genomic alterations were analyzed in relation to biomarker expression. RESULTS: TROP2 was broadly expressed, with median H-scores of 280 in endometrioid and 200 in serous carcinomas. HER2 gastric-score 2+/3+ expression and FRα positivity were enriched in serous versus endometrioid carcinoma (22.5% vs 8.9% and 20.1% vs 4.4%), restricted to FIGO grade 3 tumors, and concentrated in p53-abnormal disease. FRα positivity was absent in POLE-mutant and MSI/MMRd tumors. HER2 2+/3+ expression correlated with erb-b2 receptor tyrosine kinase 2 (ERBB2) alterations, whereas FRα-positive tumors were enriched for TP53 alterations and showed lower frequencies of ARID1A and PTEN alterations. Triple-negative TROP2/HER2/FRα tumors were uncommon (6/308, 1.9%). CONCLUSIONS: TROP2 is broadly expressed in endometrial carcinoma, whereas HER2 and FRα define a more restricted high-grade, serous/serous-like, p53-abnormal compartment, supporting biomarker-informed ADC development.

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↗

PubMed2024

Transcriptomic pathology of neocortical microcircuit cell types across psychiatric disorders.

Psychiatric disorders such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are characterized by altered cognition and mood, brain functions that depend on information processing by cortical microcircuits. We hypothesized that psychiatric disorders would display cell type-specific transcriptional alterations in neuronal subpopulations that make up cortical microcircuits: excitatory pyramidal (PYR) neurons and vasoactive intestinal peptide- (VIP), somatostatin- (SST), and parvalbumin- (PVALB) expressing inhibitory interneurons. Using laser capture microdissection followed by RNA sequencing (LCM-seq), we performed cell type-specific molecular profiling of subgenual anterior cingulate cortex, a region implicated in mood and cognitive control. We sequenced libraries from 130 whole cells pooled per neuronal subtype (VIP, SST, PVALB, superficial and deep PYR) in 76 subjects from the University of Pittsburgh Brain Tissue Donation Program, evenly split between MDD, BD and SCZ subjects and healthy controls (totaling 380 bulk transcriptomes from ~50,000 neurons). We identified hundreds of differentially expressed (DE) genes and biological pathways across disorders and neuronal subtypes, with the vast majority in interneurons, particularly PVALB. While DE genes were unique to each cell type, there was a partial overlap across disorders for genes involved in the formation and maintenance of neuronal circuits. We observed coordinated alterations in biological pathways between select pairs of microcircuit cell types, also partially shared across disorders. Finally, DE genes coincided with known risk variants from psychiatric genome-wide association studies, suggesting cell type-specific convergence between genetic and transcriptomic risk for psychiatric disorders. Our study suggests transdiagnostic cortical microcircuit pathology in SCZ, BD, and MDD and sets the stage for larger-scale studies investigating how cell circuit-based changes contribute to shared psychiatric risk.

Humans↗

PubMed2025

TCGA molecular subtypes in endometriosis-associated ovarian cancer: a systematic review and meta-analysis.

BACKGROUND: Endometriosis-associated ovarian cancer (EAOC) mainly includes endometrioid ovarian cancer (ENOC) and clear cell ovarian cancer (CCOC). The Cancer Genome Atlas (TCGA) revealed four molecular subtypes of endometrial cancer (EC) in 2013, which have been proven pivotal in the diagnostic, prognostic and therapeutic domains of EC. Existing evidence indicates that EC and EAOC molecular analysis have similar significance. This review aims to investigate the distribution, staging and prognostic characteristics of molecular subtypes in EAOC. METHODS: PubMed, Embase and Web of Science were systematically searched from January 2013 to December 2023 using predefined keywords. Patient characteristics, including stage and prognostic characteristics, were extracted from the selected studies. Data analysis was carried out using Stata 14MP. RESULTS: A total of 6 studies involving 1,133 patients with ENOC and 4 studies comprising 377 patients with CCOC were included. ENOC had a higher frequency of the POLE mutation (POLEmut) subtype (odds ratio (OR) = 2.29, 95% CI: 1.03-5.11, p = 0.043) and the mismatch repair deficient (MMRd) subtype (OR = 3.54, 95% CI: 2.05-6.11, p = 0.000) than CCOC; ENOC had a lower frequency of the no specific molecular profile (NSMP) subtype (OR = 0.55, 95% CI: 0.41-0.73, p = 0.000) and the p53 abnormal (p53abn) subtype (OR = 0.97, 95% CI: 0.67-1.42, p = 0.893). The hazard ratios (HR) of the p53abn subtype in ENOC were disease-free survival (DFS) (HR = 3.25, 95% CI: 1.46-7.21, p = 0.004) and progression-free survival (PFS) (HR = 4.11, 95% CI: 2.86-5.92, p = 0.000). The DFS of the p53abn subtype in CCOC was calculated (HR = 5.52, 95% CI: 3.43-8.90, p = 0.000). CONCLUSION: The TCGA subtypes of EC may exhibit similarities in prognosis between ENOC and CCOC.

Humans↗

PubMed2025

Comparative genomic analysis of key oncogenic pathways in hepatocellular carcinoma among diverse populations.

BACKGROUND/OBJECTIVES: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with significant racial and ethnic disparities in incidence, tumor biology, and clinical outcomes. Hispanic/Latino (H/L) patients tend to be diagnosed at younger ages and more advanced stages than Non-Hispanic White (NHW) patients, yet the molecular mechanisms underlying these disparities remain poorly understood. Key oncogenic pathways, including RTK/RAS, TGF-Beta, WNT, PI3K, and TP53, play pivotal roles in tumor progression, treatment resistance, and response to targeted therapies. However, ethnicity-specific alterations within these pathways remain largely unexplored. This study aims to compare pathway-specific mutations in HCC between H/L and NHW patients, assess tumor mutation burden, and identify ethnicity-associated oncogenic drivers using publicly available datasets. Findings from this analysis may inform precision medicine strategies for improving early detection and targeted therapies in underrepresented populations. METHODS: We conducted a bioinformatics analysis using publicly available HCC datasets to assess mutation frequencies in RTK/RAS, TGF-Beta, WNT, PI3K, and TP53 pathway genes. The study included 547 patients, consisting of 69 H/L patients and 478 NHW patients. Patients were stratified by ethnicity (H/L vs. NHW) to evaluate differences in mutation prevalence. Chi-squared tests were used to compare mutation frequencies, while Kaplan-Meier survival analysis assessed overall survival differences associated with pathway-specific alterations in both populations. RESULTS: Significant differences were observed in the RTK/RAS pathway related genes, particularly in FGFR4 mutations, which were more prevalent in H/L patients compared to NHW patients (4.3% vs. 0.6%, p = 0.02). Additionally, IGF1R mutations exhibited borderline significance (7.2% vs. 2.9%, p = 0.07). In the PI3K pathway, INPP4B alterations were more frequent in H/L patients than in NHW patients (4.3% vs. 1%, p = 0.06), while in the TGF-Beta pathway, TGFBR2 mutations were more common in H/L patients (2.9% vs. 0.4%, p = 0.07), suggesting potential ethnicity-specific variations. Survival analysis revealed no significant differences in overall survival between H/L and NHW patients, indicating that molecular alterations alone may not fully explain survival disparities and suggesting a role for additional factors such as immune response, environmental exposures, or access to targeted therapies. CONCLUSIONS: This study provides one of the first ethnicity-focused analyses of key oncogenic pathway alterations in HCC, revealing distinct molecular differences between H/L and NHW patients. The findings suggest that RTK/RAS (FGFR4, IGF1R), PI3K (INPP4B), and TGF-Beta (TGFBR2) pathway alterations may play a distinct role in HCC among H/L patients, while their prognostic significance in NHW patients remains unclear. These insights emphasize the importance of incorporating ethnicity-specific molecular profiling into precision medicine approaches to improve early detection, targeted therapies, and clinical outcomes in HCC, particularly for underrepresented populations.

PI3K pathway↗

PubMed2026

A chromosome-level genome assembly and developmental transcriptome profiling reveal stage-specific remodeling of the molecular chaperone system in Helicoverpa armigera.

Helicoverpa armigera is one of the most destructive lepidopteran pests worldwide owing to its remarkable polyphagy, long-distance migration, and rapid adaptation to insecticides. Here, we present a chromosome-level genome assembly of H. armigera generated from a field-collected individual in southwestern China, providing a valuable resource for future population genomic and pangenome studies. Developmental transcriptome analyses of first-instar larvae, fifth-instar larvae, and adults identified 6817, 3519, and 5518 differentially expressed genes, respectively, including 797 shared among all developmental transitions. Functional enrichment and co-expression network analyses revealed extensive transcriptional reprogramming, characterized by coordinated regulation of glycolysis, the tricarboxylic acid (TCA) cycle, and fatty acid β-oxidation, indicating dynamic metabolic remodeling during development. Genome-wide analysis identified 77 heat shock protein (HSP) genes belonging to six subfamilies. These genes were unevenly distributed across chromosomes, with HSP20 members exhibiting extensive tandem duplication. Expression profiling revealed pronounced stage specificity, suggesting progressive remodeling of molecular chaperone networks during development. Early larvae primarily relied on HSP40/HSP60/HSP70 and HSP10/HSP60 chaperone systems; fifth-instar larvae exhibited HSP20-centered proteostasis; and adults predominantly expressed HSP40 together with multiple HSP70 members, accompanied by enrichment of stress response and metamorphosis-related functions. This study provides new insights into developmental transcriptional regulation, metabolic remodeling, and stage-specific specialization of molecular chaperone networks in H. armigera, establishing a foundation for future studies of stress adaptation, population genomic variation, and developmental mechanisms.

Cotton bollworm↗

PubMed2026

Genome-Wide Single-Nucleotide Polymorphism (SNP)-based Profiling of Loss of Heterozygosity Reveals Distinct Molecular Subgroup-Specific Patterns in Gastrointestinal Stromal Tumors (GIST).

PURPOSE: Gastrointestinal stromal tumors (GIST) are molecularly heterogeneous neoplasms defined by mutually exclusive driver alterations (KIT, PDGFRA, SDH, BRAF, RAS, and NF1). However, driver mutations alone do not fully explain their biological and clinical variability. Chromosomal imbalances and loss of heterozygosity (LOH) may represent an additional layer of tumor characterization. We developed a single-nucleotide polymorphism (SNP)-based next-generation sequencing panel enabling genome-wide LOH assessment from formalin-fixed paraffin-embedded tissue. MATERIALS AND METHODS: Forty-nine GIST cases molecularly classified using targeted next-generation sequencing (KIT n = 19, PDGFRA n = 9, SDH-deficient n = 8, NF1 n = 7, quadruple wild-type n = 6) were analyzed. LOH was inferred from variant allele frequency patterns across 1826 genome-wide SNPs. RESULTS: Chromosome 14 was the most commonly affected (63%), followed by chromosomes 22 (45%), 15 (41%), 21 (27%), and 13 (20%). Loss of chromosome arm 1p occurred in 43% of tumors. Distinct subgroup-specific patterns emerged: KIT-mutant GIST exhibited the highest degree of genomic instability, whereas both SDH-deficient tumors and PDGFRA-mutant GIST displayed minimal chromosomal instability. NF1-mutant tumors showed recurrent single-arm chromosome 17 LOH. Quadruple wild-type GISTs were heterogeneous, including 1 case with extensive chromosomal instability. CONCLUSIONS: Genome-wide SNP-based LOH profiling reveals distinct, subgroup-specific patterns of chromosomal imbalance in GIST and may serve as a feasible complementary approach to driver mutation analysis for refined molecular characterization and potential future clinical utility.

Humans↗

PubMed2025

NOODAI: a webserver for network-oriented multi-omics data analysis and integration pipeline.

SUMMARY: Omics profiling has proven of great use for unbiased and comprehensive identification of key features that define biological phenotypes and underlie medical conditions. While each omics profile assists characterization of specific molecular components relevant for the studied phenotype, their joint evaluation can offer deeper insights into the overall mechanistic functioning of biological systems. Here, we introduce an approach where, starting from representative traits (e.g. differentially expressed elements) obtained for each omics profile, we construct and analyze joint interaction networks. The resulting networks rely on the existing knowledge of confident interactions among biological entities. We use these maps to identify and describe central elements, which connect multiple entities characteristic of the studied phenotypes and we leverage MONET network decomposition tool in order to highlight functionally connected network modules. In order to enable broad usage of this approach, we developed the NOODAI software platform, which enables integrative omics analysis through a user-friendly interface. The analysis outcomes are presented both as raw output tables as well as informative summary plots and written reports. Since the MONET tool enables the use of algorithms with strong performance in identifying disease-relevant modules, NOODAI software platform can be of a high value for analyzing clinical multi-omics datasets. AVAILABILITY AND IMPLEMENTATION: NOODAI is freely accessible at https://omics-oracle.com. Source code is available under GPL3 at: https://github.com/TotuTiberiu/NOODAI with the DOI: 10.5281/zenodo.17203984.

Software↗

PubMed2026

Early Cardiomyopathy in Prediabetic NDPK-B-Deficient Mice Is Associated with Remodeling of the Mitochondrial O-GlcNAc Proteome.

Diabetic cardiomyopathy (DCM) is characterized by myocardial remodeling that may already be evident during prediabetes, yet the molecular alterations accompanying these early changes remain poorly understood. The present study examined mouse models of Nucleoside diphosphate kinase B (NDPK-B)-deficient prediabetes and streptozotocin-induced diabetes using O-GlcNAc-associated proteomic profiling to define stage-specific molecular alterations during the progression from prediabetic to diabetic cardiomyopathy. Both models exhibited increased left ventricular extracellular matrix deposition and impaired diastolic function, together with activation of the hexosamine biosynthesis pathway. Profiling of O-GlcNAc-associated proteins uncovered extensive remodeling of the mitochondrial proteome already at the prediabetic stage, with respiratory complex I among the most prominently altered targets, alongside changes in substrate metabolism and inflammatory signaling. In overt DCM, the putative O-GlcNAc proteomic profile was associated with a shift toward wider lipid-dependent metabolic reprogramming and remodeling of mitochondrial proteins. These findings identify early remodeling of the mitochondrial O-GlcNAc-associated proteome as a molecular signature of prediabetic cardiomyopathy and highlight respiratory complex I proteins as candidate targets for future mechanistic investigations.

Animals↗

PubMed2026

COVID-19 multi-omics reveal organ-specific responses and biomarkers.

OBJECTIVE: Post-COVID-19 syndrome is characterised by persistent immune dysfunction and multi-organ sequelae. This study aimed to characterise the systemic blood molecular landscape induced by SARS-CoV-2 infection and identify prognostic markers linked to skeletal muscle mass loss, a key driver of poor outcomes. METHODS: We enrolled 30 healthy controls and 307 COVID-19 patients, collecting 422 plasma samples for integrated proteomic and metabolomic profiling to investigate organ-specific molecular alterations in COVID-19. RESULTS: We comprehensively mapped the molecular landscape of COVID-19, encompassing immune, tissue-specific, and metabolic perturbations, and delineated their interactions. Focusing on organ-damage-related molecular patterns associated with disease progression and mortality, we found that skeletal muscle mass loss contributed to poor clinical outcomes of COVID-19 (p < 0.0001). Dysregulated arginine metabolism emerged as a key metabolic signature in fatal COVID-19 cases, with GLUL, GOT1, and citrulline showing significant correlation with skeletal muscle mass loss. Longitudinal analyses further revealed that reduced citrulline levels underlie the poor outcome of COVID-19 patients with muscle mass loss. These findings were robustly supported through multiple approaches: Mendelian randomization confirmed causal relationships between citrulline depletion, sarcopenia/fat-free mass loss, and COVID-19 mortality (p < 0.05), transcriptomic analyses of SARS-CoV-2-infected golden hamsters (GSE231910) provided additional support in enrichment of arginine biosynthesis (FDR < 0.05), and in vitro experiments further demonstrated that citrulline depletion promotes pro-inflammatory M1 macrophage polarisation — a key immunological feature of critical COVID-19. Leveraging these insights, we developed a skeletal muscle loss-specific prognostic prediction model for COVID-19 using GLUL, GOT1, and citrulline. This model effectively stratified patients into high- and low-risk groups (p = 0.035). CONCLUSION: Our study advances the understanding of COVID-19-induced organ pathophysiology and provides a foundation for developing targeted therapeutic strategies for post-COVID sequelae.

COVID-19↗

PubMed2026

Integrative Multiomics and Drug Sensitivity Profiling Reveal Potential Biomarkers and Therapeutic Strategies in Pediatric Solid Tumors.

UNLABELLED: Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. Moreover, survival rates are particularly low for some pediatric tumors-such as high-risk group 3 medulloblastomas, osteosarcomas, Ewing sarcomas, high-risk neuroblastomas, and high-grade gliomas-and dismal for patients with relapsed malignancies. A functional drug response profiling platform for pediatric solid and brain tumors has been established within the INFORM program to identify patient-specific vulnerabilities and biomarkers and to unravel molecular mechanisms associated with drug response profiles for clinical translation. In this study, we performed a multiomics analysis using drug sensitivity profiles, as well as genomic and transcriptomic data, of 81 pediatric solid tumor samples. The integrative analysis suggested two multiomics signatures associated with drug sensitivity. One signature distinguished neuroblastoma samples with sensitivity to navitoclax, a BCL2 family inhibitor. A second signature was specific to a subset of Wilms tumors harboring the SIX1 (Q177R) hotspot mutation that displayed high expression of MGAM, PTPN14, STAT4, and KDM2B and high sensitivity to MEK inhibitors. A patient-specific causal interaction network analysis suggested possible molecular interactions between MEK inhibitors and the SIX1 mutation in Wilms tumor samples. In conclusion, the integration of drug sensitivity profiling and multiomics data revealed potential biomarkers that may be associated with drug sensitivity in pediatric solid tumors. Patient-specific causal interaction network analysis further elucidated the interaction between inhibitors and signature biomarkers, providing insights that may inform clinical translation. SIGNIFICANCE: The combination of multiomics analysis and drug sensitivity profiling identified two signatures related to drug sensitivity in pediatric solid tumors, contributing to the advancement of functional precision medicine and personalized treatment strategies. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI .

Humans↗

PubMed2025

Analysis of genomic traits of oral and laryngeal cancer: A comparative study.

Oral and laryngeal cancers exhibit overlapping clinical features but distinct genomic profiles. In a study of 60 Head and neck squamous cell carcinomas(HNSCC) cases (30 OSCC, 30 LSCC), NGS revealed TP53 mutations in 70% of oral squamous cell carcinoma (OSCC) and 83% of laryngeal squamous cell carcinoma (LSCC). CDKN2A alterations were more common in OSCC (40%) than LSCC (20%), while PIK3CA mutations were higher in LSCC (30%). NOTCH1 mutations were more frequent in OSCC (27%) than LSCC (10%). Pathway analysis showed disruptions in p53 and PI3K-Akt, with stronger enrichment in LSCC (ES: 3.42). The results suggest site-specific tumor biology influencing therapeutic targets. Molecular profiling is crucial for precision treatment in head and neck cancers.

Oral cancer↗

PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗

PubMed2025

Global lncRNA expression profiles in medulloblastoma reveal crucial lncRNA-oncogene interactions in Sonic hedgehog and Group 4.

BACKGROUND: Advances in multi-omic studies have improved medulloblastoma (MB) characterization, yet novel molecular biomarkers are needed to refine tumor biology and therapeutic strategies. Current profiling mainly targets the protein-coding genome, while the potential of noncoding regions remains unexplored. This study aims to identify long noncoding RNAs (lncRNAs), emerging as crucial regulators in MB, as potential key biomarkers specific to molecular group, enhancing understanding of MB's genomic landscape. METHODS: RNA-seq data from 54 Spanish MB patients (C1) and 207 public samples (C2) were analyzed to profile lncRNAs. Expression and Weighted Gene Coexpression Network (WGCNA) analyses were performed to identify lncRNA-oncogene interactions. Group-specific interactions were examined to infer their role in MB pathogenesis and highlight potential lncRNA involvement in disease mechanisms. RESULTS: LncRNA expression profiles identified 4 clusters corresponding to the MB molecular groups, confirming their potential as biomarkers. Expression and WGCNA analyses revealed group-specific lncRNAs for Sonic hedgehog (SHH), Group 3 (Gr3), and Group 4 (Gr4) MB. Lnc-SMARCA2 was exclusively upregulated in SHH MB, and associated with ATOH1 and PDLIM3, key cilium regulators of this group's cell of origin. In Gr4 MB, MGC32805 and LOC107986446 were upregulated and linked to SNCAIP, potentially influencing PRDM6 activation via enhancer hijacking. Additionally, a 5-lncRNA signature linked to phototransduction was exclusive to Gr3, offering insights into its lineage switch and molecular regulation. CONCLUSIONS: Lnc-SMARCA2 and, MGC32805 and LOC107986446, are exclusively deregulated in SHH and Gr4 MB, respectively, and directly associated with group-specific MB oncogenes, representing promising novel biomarkers and therapeutic targets in MB.

cancer biomarkers↗

PubMed2024

Multi-organ gene expression analysis and network modeling reveal regulatory control cascades during the development of hypertension in female spontaneously hypertensive rat.

Hypertension is a multifactorial disease with stage-specific gene expression changes occurring in multiple organs over time. The temporal sequence and the extent of gene regulatory network changes occurring across organs during the development of hypertension remain unresolved. In this study, female spontaneously hypertensive (SHR) and normotensive Wistar Kyoto (WKY) rats were used to analyze expression patterns of 96 genes spanning inflammatory, metabolic, sympathetic, fibrotic, and renin-angiotensin (RAS) pathways in five organs, at five time points from the onset to established hypertension. We analyzed this multi-dimensional dataset containing ~15,000 data points and developed a data-driven dynamic network model that accounts for gene regulatory influences within and across visceral organs and multiple brainstem autonomic control regions. We integrated the data from female SHR and WKY with published multiorgan gene expression data from male SHR and WKY. In female SHR, catecholaminergic processes in the adrenal gland showed the earliest gene expression changes prior to inflammation-related gene expression changes in the kidney and liver. Hypertension pathogenesis in male SHR instead manifested early as catecholaminergic gene expression changes in brainstem and kidney, followed by an upregulation of inflammation-related genes in liver. RAS-related gene expression from the kidney-liver-lung axis was downregulated and intra-adrenal RAS was upregulated in female SHR, whereas the opposite pattern of gene regulation was observed in male SHR. We identified disease-specific and sex-specific differences in regulatory interactions within and across organs. The inferred multi-organ network model suggests a diminished influence of central autonomic neural circuits over multi-organ gene expression changes in female SHR. Our results point to the gene regulatory influence of the adrenal gland on spleen in female SHR, as compared to brainstem influence on kidney in male SHR. Our integrated molecular profiling and network modeling identified a stage-specific, sex-dependent, multi-organ cascade of gene regulation during the development of hypertension.

Animals↗

PubMed2026

FGF19 as a site-specific candidate biomarker in colorectal neuroendocrine carcinomas.

PURPOSE: Gastrointestinal neuroendocrine carcinomas (GI-NECs) are aggressive tumors with marked site-specific heterogeneity, yet molecular markers for colorectal origin are lacking. This study characterized genomic and protein expression profiles to identify origin-specific biomarkers. METHODS: Nineteen GI-NECs (7 esophageal, 6 gastric, 6 colorectal) were analyzed by targeted next-generation sequencing (NGS) of 425 genes and immunohistochemistry (IHC). Genetic variations across primary sites were compared, and associations between FGF19 expression, clinicopathological features, microsatellite (MS) status, and tumor mutational burden (TMB) were assessed. FGF19 transcriptional expression was further examined in The Cancer Genome Atlas (TCGA) colorectal cohort using the UALCAN platform. RESULTS: A total of 163 genomic alterations were identified. FGF19 was the only gene showing site-specific alterations, being exclusively mutated or amplified in colorectal NECs (50%, 95% CI: 11.8-88.2%) with significantly elevated protein expression (83.3%, 95% CI: 35.9-99.6%) compared with other sites. A microsatellite instability-high (MSI-H) subgroup (10.5%, 95% CI: 1.3-33.1%) exhibited markedly higher TMB. TCGA data confirmed upregulated FGF19 in colorectal tumors but showed no survival association, consistent with the prognostic neutrality in our cohort. CONCLUSIONS: FGF19 may act as a site-specific candidate biomarker for colorectal NECs, with 83.3% protein positivity and exclusive site-specific alterations in 50% of cases. Detection of MSI-H suggests that mismatch repair (MMR) testing may be considered in selected patients with suggestive clinical or family histories to inform immunotherapy decisions.

FGF19↗