Clear cell renal cell carcinoma (ccRCC) exhibits a paradoxical fructose metabolism signature characterized by upregulation of the fructose transporter GLUT5 alongside downregulation of the catabolic enzymes (ketohexokinase, aldolase B, and triokinase), a pattern associated with poor prognosis. Functionally, unlike the pro-survival effect of fructose under glucose deprivation, in the presence of glucose, fructose co-treatment suppresses ccRCC cell proliferation, and induces profound mitochondrial dysfunction, including impaired oxidative phosphorylation, loss of membrane potential, excessive mitochondrial superoxide production, reduced mtDNA copy number, and downregulation of mitochondria-encoded electron transport chain subunits (notably ND2 and ND4 of complex I). Mechanistically, co-treatment with glucose and fructose creates a metabolic trap resulting in fructose-1-phosphate accumulation and ATP depletion. This energy crisis drives profound depletion of purine and pyrimidine nucleotide pools, which selectively triggers the PERK-eIF2S1-ATF4-CHOP axis of the integrated stress response, thereby mediating mitochondrial impairment and ultimately sensitizing ccRCC cells to intrinsic apoptosis via BID cleavage and caspase-3 activation under nutrient stress. Pharmacological treatment with the chemical chaperone 4-phenylbutyric acid (4-PBA) or nucleoside supplementation reverses mitochondrial dysfunction and fructose-induced cytotoxicity. The tumor-suppressive effect of fructose is validated in patient-derived organoids and xenograft mouse models, where fructose administration significantly attenuates tumor growth via ER stress. These findings reveal fructose-driven nucleotide depletion and PERK-dependent ER stress leading to mitochondrial dysfunction, which underlies the tumor-suppressive toxicity of fructose and exposes a targetable metabolic vulnerability in ccRCC.

Gene fusions have moved from ancillary molecular findings to defining events for an expanding group of neoplasms, with consequences for tumor classification, diagnostic certainty, and, in selected settings, targeted therapy. Yet the practical problem facing pathologists is not simply whether fusion testing is available, but when morphology should trigger it, which assay should be selected, and when conventional testing should be bypassed in favor of RNA-based sequencing. This structured narrative review synthesizes established morphologic, immunohistochemical, and molecular principles into a cross-cutting, tumor-type-agnostic, pathology-centered decision framework. We first summarize morphologic red flags that raise the pre-test probability of a fusion-driven neoplasm, including monomorphic spindle-cell, primitive round-cell, epithelioid/clear-cell, and secretory or salivary-like patterns, as well as unusual age-site combinations and morphology-immunophenotype discordance. We then position immunohistochemistry (IHC) as a triage layer rather than a molecular surrogate in all cases, emphasizing marker specificity, clone- and platform-dependent performance, and the distinction between screening and near-diagnostic surrogate markers. The relative roles of fluorescence in situ hybridization (FISH), reverse-transcription polymerase chain reaction (RT-PCR), DNA-based next-generation sequencing (NGS), targeted RNA-based NGS (RNA-NGS), and whole-transcriptome approaches are compared from a diagnostic decision-making perspective. Particular attention is given to the potential role of direct-to-RNA testing in tissue-limited or fusion-diverse cases, pre-analytical limitations of formalin-fixed paraffin-embedded (FFPE) material, and the interpretation of discordant, novel, or multiple fusion calls. Finally, we propose an expert-derived, hypothesis-generating closed-loop escalation framework in which molecular data resolve morphologic questions rather than replace morphologic reasoning. The framework has not been prospectively validated; its decision thresholds and potential effects on diagnostic yield, tissue use, cost, and time to diagnosis require formal evaluation.

Oral squamous cell carcinoma (OSCC) continues to be associated with a poor prognosis despite recent advances in surgical and adjuvant treatment. Although a variety of experimental models are available, no widely accepted or practical framework has combined cell lines, patient-derived organoids, and in vivo transplantation models in translational OSCC research. This review summarizes the main preclinical models used in OSCC research and discusses how they can be used together in a stepwise manner for drug development. A narrative review of the literature was conducted focusing on OSCC research cell lines, organoids, and transplantation smodels, as well as studies that have applied artificial intelligence (AI) and multi-omics analyses. Cell lines are useful for reproducible mechanistic studies and initial drug screening. Organoids better preserve tumour heterogeneity and allow patient-specific testing. Orthotopic transplantation models reproduce local invasion, metastatic spread, and interactions with the tumour microenvironment. When data from these platforms are analysed together and, where appropriate, supported by AI-based imaging and molecular profiling, their translational relevance may be enhanced. Combining cell lines, organoids, and in vivo models in a planned, stepwise approach provides a practical framework for OSCC research. This approach may help bridge the gap between experimental studies and clinical practice, particularly in oral and maxillofacial surgery.

Mutual information (MI)-based approaches have increasingly been applied to cancer genomics; however, their use for genome-wide prognostic biomarker discovery remains relatively underexplored. The present article summarizes the conceptual workflow of Mutual Information-based Prognostic Omics Gene (MI-POG) based on previously published applications in breast cancer, lower-grade glioma, and other cancer datasets. The framework consists of clinical endpoint discretization, genome-wide MI-based screening, candidate ranking, and downstream validation using conventional survival-analysis approaches. Previous MI-POG applications identified solute carrier family 20 member 1 (SLC20A1) as a prognostic biomarker in hormone receptor-positive breast cancer. Elevated SLC20A1 expression was associated with unfavorable survival outcomes and was independently validated in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. Methodological analyses demonstrated how survival endpoints can be integrated into an information-theoretic framework through fixed-time outcome discretization, enabling model-independent assessment of molecular-clinical dependencies. Applications across multiple cancer datasets suggested the potential applicability of the framework across biologically distinct tumor types, although further validation will be required to establish its robustness and generalizability. In conclusion, MI-POG can be formalized as an information-theoretic framework for genome-wide identification of prognostic biomarkers by quantifying molecular-clinical dependencies using mutual information. Representative applications from previously published studies suggest that MI-POG may complement conventional survival-analysis approaches and provide a useful strategy for biomarker discovery, although additional benchmarking and prospective validation will be required.

Endoplasmic reticulum resident protein 44 (ERP44), a protein disulfide isomerase family member, has been implicated in tumor biology, but its role in lower-grade glioma (LGG) remains unclear. This study investigated the prognostic significance and biological function of ERP44 in LGG, focusing on proliferation and temozolomide (TMZ) resistance.

ERP44 expression, clinicopathological associations, and prognostic value were analyzed using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) datasets. Time-dependent receiver operating characteristic (ROC) curves, Cox regression, and a prognostic nomogram were constructed. Differential expression, Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) enrichment, immune infiltration, and drug sensitivity analyses were performed. Functional validation was conducted in SW1088 and SW1783 cells using shRNA-mediated ERP44 knockdown, followed by RT-qPCR, western blotting, CCK-8, colony formation, and TMZ IC₅₀ assays. Subcutaneous xenograft models with or without TMZ treatment were used for in vivo validation.

ERP44 was markedly upregulated in LGG and associated with higher WHO grade, IDH wildtype status, 1p/19q non-codeletion, and poor survival in TCGA and CGGA cohorts. ERP44 showed strong prognostic performance and improved risk stratification in a multivariable nomogram. Enrichment analyses linked high ERP44 expression to immune/inflammatory pathways and reduced neuronal functional signatures. ERP44 positively correlated with immune infiltration, proliferation/stemness markers, and predicted TMZ resistance, while its knockdown inhibited proliferation and colony formation, reduced TMZ IC₅₀, suppressed xenograft growth, enhanced TMZ efficacy, and decreased Ki67 positivity.

ERP44 is a prognostic biomarker that promotes LGG proliferation and TMZ resistance, suggesting its potential as a therapeutic target.

Lung adenocarcinoma (LUAD) exhibits substantial molecular heterogeneity and variable clinical outcomes, highlighting the need for biomarkers that reflect core tumor biological processes. Centrosome-associated proteins regulate mitotic fidelity and genome stability, yet their roles in LUAD remain incompletely defined. In this study, we systematically characterized mitotic spindle organizing protein 1 (MOZART1; MZT1) and related family members in LUAD.

We performed integrated analyses combining bulk transcriptomic datasets, survival modeling, gene set enrichment, immune deconvolution, machine-learning based prognostic modeling, and single-cell RNA sequencing. Expression patterns and clinical associations of MZT family genes were evaluated across pan-cancer and LUAD cohorts.

MZT family genes were consistently upregulated in tumor tissues, with MZT1 showing the most robust expression pattern. Elevated MZT1 expression was significantly associated with reduced overall survival. Functional analyses revealed coordinated activation of proliferative and genome maintenance pathways, including G₂/M checkpoint regulation, E2F and MYC signaling, and DNA repair. A multivariable analysis indicated that the prognostic association of MZT1 was reduced after adjusting for canonical proliferation markers, suggesting partial overlap with established proliferation signals. The LASSO-based Cox model demonstrated stable time-dependent predictive performance at 1-, 3-, and 5-year survival. Immune analyses indicated associations between MZT1 expression and tumor microenvironmental features. Single-cell analysis showed that MZT1 expression was predominantly enriched in malignant epithelial cells and associated with proliferative cellular states. Protein-level validation supported concordance with transcriptomic findings.

MZT1 is a proliferation-associated marker that integrates clinical risk, transcriptional programs, cellular heterogeneity, and predictive modeling in LUAD, providing a potential framework for biomarker development and risk stratification.

Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide. Although immunotherapy has improved outcomes for a subset of patients, its limited efficacy in many cases highlights the need for a more comprehensive understanding of the CRC immune microenvironment. This study aimed to characterize the molecular landscape of the CRC immune microenvironment using an integrated multi-omics approach and to identify candidate regulatory molecules associated with immune remodelling.

We integrated structural variation, DNA methylation, chromatin accessibility, proteomic, and phosphoproteomic data generated from an in-house CRC cohort with transcriptomic data from The Cancer Genome Atlas (TCGA). Analyses focused on 1,539 immune-related genes (IRGs) associated with CD4⁺ T cells, B cells, and natural killer (NK) cells. Multi-layered genomic and proteomic analyses were performed to identify altered immune-related pathways, hub genes, candidate transcription factors, and upstream kinases.

Higher infiltration of CD4⁺ T cells, B cells, and NK cells was associated with CRC. IRGs exhibited widespread alterations across genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic levels. IL10, LEP, ITGAM, and EGFR emerged as candidate hub genes. EGFR phosphorylation at S991 and T693 was significantly decreased in CRC. STAT2 and HSF1 were identified as candidate upstream transcription factors, while CDK2 emerged as a candidate upstream kinase associated with immune infiltration and immune checkpoint expression.

This study provides a systematic multi-omics characterization of immune microenvironment remodelling in CRC and identifies candidate molecular regulators that may serve as potential targets for future immunotherapy research.

In breast cancer, knowledge of the associations between clinicopathologic characteristics, genetic changes, and subtype-specific patterns is expanding. This study investigated how pathological and clinical variables affect the actionability of Next Generation Sequencing (NGS)-based tumor molecular data.

227 breast cancer patients referred to Genekor's laboratory for tumor molecular profile analysis were included in the study. Pathology records were used to assess critical clinicopathological features, including HER2, ER, PR, Ki67, grade, metastatic site, and age. A 1021-gene NGS-based multigene panel was utilized to assess tumor biology alongside tumor mutational burden (TMB) and microsatellite instability (MSI).

Comprehensive genomic profiling revealed that 95.6% of the patients harbored at least one oncogenic or likely oncogenic alteration, highlighting the high diagnostic yield of NGS-based testing. Distinct subtype-specific patterns were observed: HR+/HER2- tumors were enriched for PIK3CA and ESR1 gene alterations, whereas triple-negative breast cancer (TNBC) was dominated by TP53 alterations. Clinically actionable alterations were most common in HR+/HER2- tumors (~60% on-label), whereas TNBC more often harbored off-label or trial-associated targets. The inclusion of tumor-agnostic biomarkers (TMB/MSI) increased on-label actionability up to 64.5% in HR+/HER2- tumors, primarily driven by TMB-high cases. Median TMB values were low, and age was the only independent predictor. Furthermore, the presence of actionable alterations was significantly higher in metastatic tumors, and TP53 alterations were associated with aggressive tumor characteristics.

Comprehensive NGS-based genomic profiling identifies clinically actionable alterations in over half of breast cancer patients, with substantial variability across molecular subtypes. The HR+/HER2- subtype demonstrates the highest prevalence of on-label actionable biomarkers. These findings support the routine implementation of comprehensive genomic profiling, especially in metastatic HER2-negative breast cancer, to guide precision oncology strategies and enable enrollment in biomarker-driven clinical trials.

The incidence of cancer is increasing across all age groups including children. This disease and its costly treatment affect not only the patient but their entire family-especially parents as primary caregivers-leading to psychological distress, physical exhaustion and financial strain. Social support serves as a vital protective factor for parents facing their child's cancer diagnosis. As a complex, context-dependent phenomenon emerging from social interactions, its process requires exploration within diverse cultural settings. Thus, this study aims to explain the process of social support for parents of children with cancer in the sociocultural context of Iran.

This protocol outlines a qualitative study using grounded theory design. Data will be collected via semi-structured interviews. Parents of children with cancer will initially be selected through purposive sampling. Subsequent participants will be recruited via theoretical sampling to fully develop emerging concepts and theory dimensions. Sampling will continue until conceptual and theoretical saturation is achieved. Data analysis will follow Corbin and Strauss's (2015) constant comparative method, using MAXQDA V.2022 software.

Ethical approval was obtained under the code IR.UMSU.REC.1403.129. Written informed consent will be obtained from all participants before data collection. Study findings will be shared through presentations at national conferences, publication in peer-reviewed journals and dissemination of results to participating centres and interested participants.

Approximately 30% of all cancers have mutations in the KRAS proto-oncogene, GTPase (KRAS), and approximately 88% of pancreatic cancer tumors have mutations in KRAS. Recently, a novel KRAS inhibitor, daraxonrasib, with activity against both wild-type and mutant KRAS, has been developed and has shown efficacy in a phase III clinical trial of recurrent pancreatic-cancer patients, but with significant side-effects. In the present report, we determined whether daraxonrasib is synergistic with recombinant methioninase (rMETase) on pancreatic cancer cells that have the KRAS G12D mutation, compared to normal fibroblasts.

Cell viability was measured with the WST-8 reagent. The half-maximal inhibitory concentrations (IC₅₀) of rMETase and daraxonrasib were determined on PANC-1 human pancreatic cancer cells and Hs-27 human normal fibroblasts in vitro. The viability of PANC-1 and Hs-27 cells treated with rMETase alone, DXR alone, or a combination of rMETase and daraxonrasib was determined at their respective IC₅₀ values.

The IC₅₀ values of daraxonrasib were 10.5 μM for PANC-1 and 8.4 μM for Hs-27. The IC₅₀ values of rMETase were 0.47 U/ml for PANC-1 and 0.42 U/ml for Hs-27. Daraxonrasib alone and rMETase alone showed significantly higher cytotoxicity towards PANC-1 cancer cells than Hs-27 fibroblasts. The combination of daraxonrasib and rMETase demonstrated selective synergistic cytotoxicity toward PANC-1 cells compared to normal Hs-27 fibroblasts (p<0.05).

The present results suggest that the combination of daraxonrasib and rMETase has clinical potential for lowering the effective dose of daraxonrasib, thereby reducing daraxonrasib-associated side-effects, as well as increasing its efficacy.