Poly(ADP-ribose) polymerase inhibitors (PARPis) have demonstrated remarkable efficacy in tumors carrying BRCA1/2 pathogenic variants (PVs) through the mechanism of synthetic lethality. PVs in other homologous recombination (HR) genes may also impair homologous recombination repair and confer sensitivity to PARPis; however, their predictive value remains uncertain and appears to vary according to the affected gene and tumor type. We review and critically discuss the current evidence regarding the predictive value of non-BRCA HR gene pathogenic variants as biomarkers of PARPi sensitivity across ovarian, breast, prostate, and pancreatic cancers. A narrative review was conducted between October 2023 and December 2025, first identifying pivotal clinical trials of PARP inhibitors across ovarian, breast, prostate, and pancreatic cancers, followed by a targeted search of PubMed, Embase, Web of Science, and Google Scholar for relevant preclinical and clinical studies. Seventeen clinical studies and multiple preclinical reports were analyzed regarding genomic frequency, HRD association, and treatment response. Preclinical studies consistently demonstrated increased PARPi sensitivity in models with alterations in several non-BRCA HR genes. Clinical evidence, however, was heterogeneous. PALB2 demonstrated the strongest and most consistent association with PARPi benefit across tumor types, while RAD51C and RAD51D also showed clinically meaningful activity, particularly in ovarian cancer. In contrast, evidence supporting PARPi sensitivity in tumors harboring ATM, CHEK2, CDK12, and several other HR gene alterations remained limited or inconsistent. Differences in gene function, biallelic inactivation, variant type, and current limitations of HRD companion diagnostic assays likely contribute to the observed variability in clinical response. Non-BRCA HR gene alterations represent promising predictive biomarkers for PARPi therapy but should not be considered a homogeneous group. Future biomarker-driven studies integrating comprehensive genomic profiling and functional assessment of homologous recombination deficiency are needed to refine patient selection and optimize the clinical application of PARPis beyond BRCA1/2-associated cancers.

WWOX and HIF1A are linked to hypoxia-driven metabolic and immune modulation in cancer. We examined whether the WWOX/HIF1A expression ratio acts as a context-dependent molecular integrator across breast cancer (BRCA) subtypes and ovarian carcinoma (OV). We analyzsed TCGA RNA-seq and clinical data from BRCA (n = 390) and OV (n = 228), using neoplasm cancer status as a proxy for disease-free survival (DFS). Patients were stratified by subtype-specific WWOX/HIF1A ratio cutpoints for exploratory Kaplan--Meier analyses, and the ratio was also modelled as a standardizsed continuous covariate in Cox regression. Transcriptomic, pathway, immune-cell and hormone-related profiles were examined in relation to ratio status, with all multivariable and cutpoint-based findings treated as hypothesis-generating. The WWOX/HIF1A ratio does not act as a uniform or strongly predictive prognostic marker but instead delineates distinct biological states whose association with DFS is modest, context-dependent and statistically fragile in TCGA. Higher ratios are linked to more favourable DFS only in basal-like and HER2-enriched BRCA, together with oxidative phosphorylation, ribosomal and reduced ADAM10-linked Notch and monocyte/macrophage signatures. In luminal A BRCA and OV, lower ratios are linked to relatively favourable DFS and coincide with cytokine/JAK-STAT signalling, cytotoxic immune signatures and coordinated metabolic-endocrine programmes, whereas luminal B shows mixed immune and metabolic patterns. In this TCGA-based analysis, the WWOX/HIF1A ratio functions as a context-dependent molecular index of hypoxia, immune and hormone-related states rather than a strong, generalisable DFS predictor. The observed subtype-specific survival trends (high-ratio favourability in basal/HER2, low-ratio favourability in luminal A,B and OV) are non-significant and exploratory, and all ratio-based survival patterns require confirmation in independent cohorts and functional studies.

Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer and remains a major global health burden. Comprehensive characterization of tumor microenvironment (TME) heterogeneity is critical for understanding tumor progression and clinical outcomes in NSCLC. In this study, we identified 34 transcriptionally defined cell states and 6 multicellular ecotypes using the EcoTyper framework, thereby systematically delineating the TME landscape of NSCLC. These cell states and ecotypes were further validated across 11 independent bulk transcriptomic cohorts, one single-cell RNA sequencing cohort, and one spatial transcriptomics cohort, demonstrating strong reproducibility and robustness. Prognostic analyses revealed that several cell states and ecotypes were significantly associated with patient survival outcomes in NSCLC. Transcriptional regulatory analysis further identified SP8, MAZ, and FOS as potential regulators involved in shaping NSCLC ecotypes. Collectively, this study provides a comprehensive atlas of TME-associated cell states and ecotypes in NSCLC, offering new insights into tumor heterogeneity and potential opportunities for personalized prognostic assessment and therapeutic intervention.

Cervical carcinoma is predominantly driven by high-risk human papillomavirus (HPV) infection, in which functional inactivation of p53 occurs mainly through viral oncoproteins rather than mutations in the TP53 gene. This raises questions concerning the prognostic relevance of TP53 gene status and p53 protein levels in this tumor type. This study aimed to systematically evaluate the prognostic significance of TP53 mutation status, p53 protein abundance, and selected downstream p53-regulated proteins in cervical carcinoma, with particular focus on tumors carrying wild-type TP53. Clinical and proteomic data from 162 cervical carcinoma patients were retrieved from The Cancer Genome Atlas (TCGA). Protein levels (p53, BAX, p21/CDKN1A, and TIGAR) were assessed using reverse-phase protein array (RPPA) data. Survival analyses were performed using Kaplan-Meier estimates with log-rank testing after stratification into quartile-based expression groups. The vast majority of tumors (~93%) harbored wild-type TP53, and the TP53 mutation status showed no association with patient survival. In tumors with wild-type TP53, p53 protein levels did not significantly correlate with overall survival, indicating a limited prognostic value. In contrast, elevated levels of the pro-apoptotic protein BAX showed a clear tendency to be associated with poorer overall and progression-free survival, suggesting BAX as a potential prognostic marker in this specific molecular context. The expression of p21/CDKN1A showed no prognostic relevance, while high TIGAR levels displayed a slight trend toward poorer survival, although without reaching statistical significance. In summary, in HPV-driven cervical carcinoma, neither the TP53 mutation status nor the p53 protein abundance reliably predict patient outcome. Instead, selected downstream effectors of p53 signaling-particularly BAX-may provide more informative prognostic insights in tumors retaining wild-type TP53. These findings highlight the importance of assessing functional outputs of p53 signaling rather than the p53 status alone in this disease context.

Polyploid giant cancer cells (PGCCs) are increasingly recognized as major drivers of therapy resistance and tumor relapse, yet the conserved molecular programs underlying their persistence remain incompletely defined. To identify genes consistently deregulated across eight independent datasets, we performed an integrative transcriptomic analysis of PGCCs derived from prostate, ovarian, and breast cancers. By focusing on consistently up- or down-regulated genes that were expressed in at least five datasets and showed a concordant direction of expression across more than 70% of datasets and met a significance threshold of adjusted p < 0.05, we defined the core regulatory architecture stabilizing the PGCC state under therapeutic stress. Our analysis reveals that PGCCs exhibit a paradoxical ranscriptomic signature consistent with cytolytic activity alongside reduced immune detection. These cells activated pro-inflammatory cytokine and chemokine signaling while simultaneously engaging immune-evasion mechanisms, including PD-L1-associated and virus-like escape programs. Concurrently, PGCCs displayed transcriptional features characteristic of immune-privileged cellular states, including embryonic development, reproductive programs, senescence-associated survival, apoptosis resistance, and deep dormancy marked by coordinated suppression of major housekeeping processes. Notably, PGCCs also activated neuronal differentiation and neurodegeneration-associated pathways, including axon guidance, neurogenesis, and calcium signaling. This neuron-like, calcium-dependent stress adaptation program may further enhance immune privilege and long-term survival capacity. We propose that PGCCs represent an immune-adaptive polyploid survival state in which inflammatory and ontogenetic pathways are repurposed to support immune evasion and tumor persistence. By identifying actionable vulnerabilities within calcium signaling, neuronal mimicry, and checkpoint-associated pathways, this study provides a framework for therapeutic strategies aimed at dismantling the PGCC reservoir and preventing tumor relapse.

Triple-negative breast cancer (TNBC) lacking androgen receptor (AR) expression defines quadruple-negative breast cancer (QNBC), which is characterized by younger age at diagnosis, high Ki-67 index, and high genomic instability, however a comprehensive description of the genomic characteristics remains poorly defined. A total of 54 TNBC cases were categorized as TNBC with 100% AR expression (TNBC AR-100%) or QNBC, TNBC with 0% AR expression (TNBC AR-0%). Clinical, molecular, and genomic parameters, specifically pathogenic/likely pathogenic (P/LP) variants in homologous recombination repair (HRR) and cancer-related pathways were measured and analyzed. The QNBC cohort exhibited a high homologous recombination deficiency (HRD) score and a greater overall incidence of copy number variants (CNVs). QNBC harbored a higher mutation rate in TP53 and MYC signaling pathway than TNBC AR-100% tumors. P/LP variants corresponding to the HRR, PI3K/AKT, and RTK/RAS pathways were exclusively identified in QNBC. These results suggest that, at both molecular and genomic levels, the two groups are distinct, holding QNBC tumors more aggressive characteristics, genomic instability, and particular impairments in HRR and cancer-related pathways. In terms of actionability, these differences could potentially be leveraged through different combinations of therapies.

Lynch syndrome (LS) is the most common hereditary colorectal cancer (CRC) syndrome, caused by germline pathogenic or likely pathogenic variants (PV/LPV) in mismatch repair (MMR) genes. Data on the spectrum of LS-associated variants in Slavic populations, including Serbia, remain limited. Given the high burden of CRC and endometrial cancer and the limited implementation of hereditary CRC screening, characterizing the spectrum of germline variants in clinically selected high-risk individuals is important for improving genetic testing strategies, risk assessment, and clinical management. Between 2018 and 2025, 176 individuals underwent germline testing for hereditary CRC syndrome based on the Amsterdam/Bethesda criteria, validated LS risk prediction models, and/or family history (FH). Next-generation sequencing (NGS) was performed using the Illumina TruSight Hereditary Cancer Panel, and variants were classified according to American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP) guidelines. PV/LPVs in MMR genes were identified in 27/176 (15.3%) and were associated with positive FH of LS-related tumors (p = 0.0001). Most PV/LPVs were identified in MLH1 (10.2%), followed by MSH2 (4.0%) and MSH6 (1.1%), with no PV/LPVs identified in PMS2. Additionally, no pathogenic sequence-level EPCAM variants detectable by the applied panel-based NGS approach were identified. Recurrent MLH1 variants were observed in multiple families, and two previously unreported MLH1 variants were identified. This first systematic analysis of a clinically selected high-risk Serbian cohort provides novel data on the spectrum of LS-associated variants in this referral population, demonstrates the predominance of MLH1 variants, and supports broader implementation of genetic testing, tumor screening, and genetic counseling.

The leading-edge (LE) of hepatocellular carcinoma (HCC) is a critical region driving malignant progression and is closely associated with high patient mortality and marked intratumoral heterogeneity. Multi-omics integration identified elevated expression of SPARC and IGFBP7 in the LE region, which was associated with stromal remodeling-related transcriptional programs and an immune-depleted microenvironment. Cell-cell communication and pathway analyses further suggested potential links between LE-associated stromal states and pro-invasive signaling programs. Furthermore, we developed SpaPred, which demonstrated favorable performance in inferring the spatiotemporal heterogeneity of HCC at the spatial resolution. This model overcomes the limitations of existing algorithms in analyzing the composition of tissue spatial structures. Finally, integration of in silico trajectory-perturbation and pharmacogenomic drug-response analyses prioritized Oxaliplatin, Belinostat, and Temsirolimus as candidate compounds associated with LE-related transcriptional programs. These drug predictions are computational and require experimental validation. Collectively, SpaPred provides a hypothesis-generating framework for investigating spatial heterogeneity and candidate therapeutic vulnerabilities in HCC.

Field cancerization describes molecular alterations occurring in histologically normal tissues surrounding tumors that may contribute to cancer initiation and progression. In prostate cancer (PCa), the molecular characteristics of peritumoral tissue (PTT) remain incompletely understood. Because microRNAs (miRNAs) play key roles in gene regulation, tumor progression, and microenvironmental remodeling, we investigated miRNA expression patterns and regulatory networks across benign tissue (BT), PTT, and tumor tissue (TT). Small RNA sequencing was performed on matched formalin-fixed paraffin-embedded samples from 40 patients with PCa. Differential expression analysis was conducted using DESeq2, adjusting for age and Gleason grade, while functional enrichment analysis and weighted gene co-expression network analysis (WGCNA) were used to identify dysregulated pathways and conserved miRNA modules. PTT exhibited a molecular profile intermediate between BT and TT, consistent with a field cancerization effect. Compared with BT, 102 miRNAs were differentially expressed in TT and 57 in PTT, with 39 miRNAs (68% of the PTT-associated miRNAs) overlapping the tumor signature. Shared dysregulated pathways included PI3K-Akt, p53, and HIF-1 signaling; whereas, PTT showed additional enrichment in pathways related to epigenetic regulation (Polycomb Repressive Complex) and cellular stress responses (mitophagy, protein processing in ER) exclusively through up-regulated miRNAs; no pathways were uniquely enriched from down-regulated miRNAs in PTT. WGCNA identified conserved miRNA modules enriched for members of the let-7, miR-200, miR-103/107, and miR-106a~363 families, which have established roles in epithelial-mesenchymal transition, tumor progression, and microenvironmental remodeling. Collectively, these findings demonstrate that histologically benign peritumoral tissues harbor tumor-associated miRNA programs and regulatory networks that closely resemble those observed in prostate tumors, providing molecular evidence of field cancerization in PCa and identifying potential miRNA-mediated mechanisms relevant to disease progression and biomarker development.

Prostate adenocarcinoma is characterized by substantial inter-patient heterogeneity, limiting the clinical reliability of conventional diagnostic tools, including prostate-specific antigen testing. This limitation underscores the need for robust molecular biomarkers that may complement conventional diagnostic tools, highlighting the urgent need for biomarkers capable of enhancing diagnostic accuracy and enabling more precise risk stratification. In the present study, transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed using an integrative bioinformatics and machine learning pipeline., The proposed workflow was designed as a stepwise and reproducible biomarker prioritization framework in which differential expression analysis, functional enrichment, protein-protein interaction (PPI) based network interpretation, graph-convolutional feature selection, and hybrid ensemble machine learning were sequentially integrated. Differential gene expression analysis was combined with pathway enrichment (Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome), protein-protein interaction network construction, and graph-convolutional feature selection. Multiple machine learning algorithms, including Random Forest, Gradient Boosting Machine, Support Vector Classifier, Artificial Neural Network, and AdaBoost, were systematically evaluated. A hybrid ensemble model integrating Gradient Boosting Machine and Random Forest (GBM+RF) was subsequently developed. Model performance was assessed using accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic (ROC) and externally validated using the independent GSE14206 dataset. The analysis revealed a coordinated molecular pattern characterized by dysregulated cell cycle activity and enhanced interferon-mediated immune signaling. Protein-protein interaction analysis identified STAT1 and PLK1 as highly connected network hub genes within immune-related and cell-cycle-associated modules. Among the evaluated models, the hybrid GBM+RF framework achieved the highest predictive performance on the TCGA dataset, with AUC: 0.9526; Accuracy: 97.49%. External validation using the GSE14206 dataset confirmed the robustness of this model (AUC: 0.9156; Accuracy: 91.53%). These findings support a broader multi-gene candidate signature in prostate adenocarcinoma, in which machine learning prioritized genes such as XAF1, APP, RPA3, IFIH1, UBE2D2, RSAD2, KIF2C, and PLK1, while STAT1 and PLK1 provided complementary network-level biological relevance. The proposed framework provides a robust and transferable strategy for biomarker discovery and precision oncology.

Thymic epithelial tumors (TETs), comprising thymomas and thymic carcinomas, are rare, biologically heterogeneous thoracic malignancies with limited therapeutic advances since platinum-based regimens were adopted decades ago. Recent genomic and immunophenotypic profiling has uncovered recurrent genomic alterations and high programmed death-ligand 1 (PD-L1) expression, particularly in thymic carcinoma, yet few targeted or immunotherapies have achieved regulatory approval. This mini-review synthesizes current knowledge on TET heterogeneity and the genomic landscape, evaluates the clinical evidence supporting targeted agents and immune checkpoint inhibitors, and examines emerging biomarkers, including circulating tumor DNA. We also address practical barriers to precision oncology in TETs: challenges of next-generation sequencing implementation and cost in resource-limited settings; scarcity of large, biomarker-driven trials; and safety concerns unique to TETs (immune-related toxicity). Finally, we discuss the translational hurdles for antibody-drug conjugates and cellular therapies, limited validated cell surface targets, antigen heterogeneity, and preclinical model gaps and outline strategic paths forward to enable rational, safe, and equitable precision therapeutics for TET patients.

Multiple myeloma (MM) remains an incurable hematological malignancy in which tumor-intrinsic immune evasion limits the efficacy of immunotherapy. Here, we identify the RNA editing enzyme ADAR1 as a key regulator of innate immune suppression in MM. Integrative analyses of bulk and single-cell transcriptomic datasets, together with clinical validation, demonstrated that ADAR1 is upregulated in malignant plasma cells and is associated with adverse clinical outcomes and reduced CD8+ T-cell infiltration. Mechanistically, ADAR1 knockdown increased the association of endogenous dsRNA with melanoma differentiation-associated protein 5 (MDA5), restoring type I interferon (IFN) signaling, enhancing IFNα production and STAT1 activation, and promoting CD8+ T-cell proliferation and cytotoxic function. These effects were largely abolished by MDA5 depletion, establishing a functional ADAR1-MDA5 signaling axis in MM. In vivo, treatment with 8-azaadenosine significantly potentiated the antitumor efficacy of PD-1 blockade, resulting in reduced tumor growth, increased tumor cell apoptosis, elevated IFNα expression, and enhanced CD8+ T-cell infiltration. Together, our findings demonstrate that ADAR1-mediated RNA editing enables immune evasion by restricting MDA5-dependent sensing of endogenous dsRNA and highlight the ADAR1-MDA5-type I interferon axis as a promising therapeutic target for improving immunotherapy in multiple myeloma.

Butyrophilin-like 9 (BTNL9), a member of the immunoglobulin superfamily containing a bZIP-like domain, has a poorly defined role in cancer. Here, we identify BTNL9 as a non-canonical transcriptional regulator and investigate its function in non-small cell lung cancer (NSCLC). Coiled-coil prediction, native PAGE, and co-immunoprecipitation demonstrated BTNL9 homodimerization via its bZIP-like region, while subcellular fractionation and immunofluorescence confirmed its presence in both the nucleus and cytoplasm. Chromatin immunoprecipitation sequencing (ChIP-seq) analysis identified 9709 BTNL9-associated genomic regions, including sites proximal to transcription start sites, with enrichment of a cytosine-rich motif. Whether chromatin association reflects direct DNA binding or indirect co-regulatory interaction remains to be experimentally confirmed. Integrated transcriptomic and protein analyses revealed that BTNL9 overexpression represses genes involved in cell cycle progression and DNA replication while activating a subset of p53-associated pathways. Consistently, functional assays showed that increased BTNL9 expression induces cell cycle arrest, suppresses proliferation and clonogenicity, and inhibits tumor growth in xenograft models. In addition, cytotoxicity assays demonstrated enhanced sensitivity to bortezomib, with context-dependent effects on etoposide response. Analysis of public clinical datasets further showed that low BTNL9 expression is associated with advanced tumor stage, reduced remission rates, and poorer survival outcomes in NSCLC. These findings identify BTNL9 as a non-canonical tumor-suppressive transcriptional regulator with potential biomarker relevance in NSCLC.

Human alkyladenine DNA glycosylase (AAG) initiates base excision repair of various alkylated and deaminated purines. Single nucleotide polymorphisms (SNPs) in the AAG gene occur frequently in populations and tumors, but the functional impact of most variants remains unknown. Previously, we identified three SNPs-P94L, V158M, and E293K-which have been predicted to have a high deleterious potential. This study aimed to characterize their biochemical properties and structural consequences. Using a combination of biochemical assays and molecular dynamics simulations, we assessed the thermal stability, DNA binding affinity, and catalytic activity of these mutants on two structurally distinct substrates: 1, N6-ethenoadenosine (εA) and hypoxanthine (Hx). All three mutants exhibited reduced melting temperatures, indicating pronounced destabilization. Despite this, their DNA-binding affinities remained close to WT AAG. Strikingly, the mutants displayed differential loss of catalytic activity: P94L was inactive against both εA and Hx; V158M retained activity against εA but lost activity against Hx; and E293K was active against Hx but inactive against εA. MD simulations revealed that P94L alters the flexible R138-T143 loop, V158M narrows the active site cleft, and E293K disrupts a C-terminal salt bridge while increasing DNA engagement by the positively charged tail. These findings demonstrate that non-active-site SNPs can qualitatively reprogram the substrate specificity of AAG. These variants could be considered as potential functional biomarkers for cancer risk and response to alkylating chemotherapy.

Cancer cells are able to survive under conditions of high endoplasmic reticulum (ER) stress by activating the adaptive unfolded protein response (UPR), which is closely linked with autophagy. On the other hand, excessive and prolonged ER stress leads to apoptosis. However, the relationships between different UPR branches and apoptosis or autophagy vary in cancer cells of different origins and depend on the extent and nature of the stress signal. This study was designed to establish the role of ER stress sensors protein kinase RNA-like endoplasmic reticulum kinase (PERK) and inositol-requiring enzyme 1 (IRE1α) in apoptosis or autophagy signaling in T-lymphoblastic leukemia MOLT-3 cells via the RNA interference method. The cells were transfected with small interfering RNAs (si-PERK, si-IRE1α, or si-Cont) for 6 h and further cultured under normal conditions for 72 h to provide an insight into chronic effects of the gene silencing. The expression of apoptosis and autophagy effectors at the mRNA and protein levels was compared using RT-PCR and Western blot assays, respectively. Transfection of the cells with PERK siRNA led to a significant decrease in PERK protein and gene expression, and decreased phosphorylation of its downstream effector eukaryotic initiation factor 2α (eIF2α). PERK silencing was accompanied by activation of apoptosis-related genes and proteins-BCL2-associated X (Bax), caspase-3, C/EBP homologous protein (CHOP), while the levels of autophagy markers (Unc-51 like autophagy activating kinase 1 (ULK1), Beclin-1, and microtubule-associated proteins 1A/1B light chain 3 (LC3A/B)) remained stable. In contrast, treatment of the cells with si-IRE1α reduced the content of IRE1α, X-box-binding protein 1 (sXBP1), and glucose-regulated protein 78 (GRP78) proteins, but increased ERN1 gene expression. IRE1α RNA interference did not affect the levels of the pro-apoptotic marker Bax, but suppressed caspase-3, CHOP, c-Jun N-terminal kinase (JNK), and autophagy signaling molecules (ULK1, Beclin-1, LC3A/B) at both the transcriptional and translational levels. These results indicate that the PERK pathway is an important contributor to the survival of MOLT-3 cells under basal ER stress, while PERK depletion compromises the resistance of cells to UPR-mediated apoptosis. The IRE1α UPR branch is directly linked with autophagy-dependent signaling, although IRE1α knockdown exerted a more complicated influence on the cells, probably via activation of multiple pro-death and compensatory pro-survival regulatory mechanisms.

This Special Issue, "Advancements in Cancer Biomarkers", focuses on recent developments in cancer biomarker research, providing an updated perspective on the rapidly evolving field of molecular oncology [...].

Syntaphilin (SNPH), initially considered a neuron-specific protein, has recently been found to be widely expressed across various cancers. Mechanistically, SNPH inhibits mitochondrial transport to the cortical cytoskeleton, thereby suppressing cancer cell migration and metastasis. Although SNPH is known to participate in the metastatic progression of multiple malignancies, its precise underlying mechanism remains obscure. In this study, we investigated the role of SNPH in the epithelial-mesenchymal transition (EMT) and invasiveness of gastric cancer cells. Knockdown of SNPH in SNU-638 gastric cancer cells significantly enhanced their migratory and invasive capacities by approximately 1.4-fold and 2.5-fold, respectively. This knockdown concurrently increased focal adhesion kinase (FAK) phosphorylation, upregulated the EMT marker vimentin, and increased the expression of key EMT-related transcription factors, including Snail, Slug, and Twist. Furthermore, SNPH depletion induced the phosphorylation of nuclear factor kappa B (NF-κB), a transcription factor regulating matrix metalloproteinase-9 (MMP-9), which subsequently upregulated MMP-9 mRNA expression. This cascade promotes extracellular matrix degradation, thereby increasing metastatic potential. Notably, these phenotypic and molecular changes were completely reversed upon SNPH overexpression in SNU-638 cells. Taken together, our results demonstrate that SNPH deficiency enhances the migration and metastatic potential of gastric cancer cells by driving EMT and invasion via the FAK/NF-κB/MMP-9 signaling pathway. Consequently, we propose that SNPH represents a novel biomarker and a promising therapeutic target for mitigating gastric cancer metastasis.

Intratumor heterogeneity (ITH) of premalignant colorectal lesions is an important area of research for understanding the diverse biological behavior of colorectal cancer (CRC). Accurate assessment of ITH depends substantially on the sampling strategy used. We present a novel methodological approach termed whole tumor heterogeneity topography (WTHT) and compare it with three previously described sampling strategies: whole tumor homogenization, macrodissection of selected tumor regions, and multisampling. A cohort of 184 advanced precancerous colorectal lesions was processed into paraffin blocks, and the entire tumor mass was systematically divided into equally sized samples (~10 mm3). DNA was isolated from each sample separately and analyzed for hotspot mutations in APC, KRAS, BRAF, PIK3CA, and TP53. ITH was quantified using mutation variance and a newly introduced Heterogeneity Grade (HG). Results obtained by WTHT were statistically and graphically compared with three other modeled sampling strategies. Significant differences were observed among the analyzed sampling approaches. Macrodissection showed the greatest deviation from WTHT, indicating substantial sampling bias, whereas multisampling produced the closest results. WTHT enabled precise quantification and spatial mapping of mutational clones across the entire lesion. WTHT combined with HG provides a robust and reproducible framework for comprehensive assessment of ITH in colorectal adenomas.

Glioblastoma (GBM) exhibits marked sex differences in incidence, outcome, and molecular regulation, yet the mechanisms underlying these disparities remain poorly defined. ZEB1 is a neurodevelopmental transcription factor implicated in GBM progression and cellular plasticity, but its prognostic and functional relevance may differ by sex. Here, we analyzed TCGA-GBM transcriptomic and clinical data to assess the relationship between ZEB1 expression, patient sex, and survival and to identify sex-specific transcriptional programs associated with ZEB1. Patients were stratified by ZEB1 expression and sex, followed by differential expression analysis, functional enrichment, and survival modeling. High ZEB1 expression was associated with improved overall survival in female patients but not in male patients. Sex-stratified transcriptomic analysis revealed distinct ZEB1-associated gene expression signatures, with enrichment of chromatin-modifying and demethylase-related pathways among male-female comparisons. Candidate Y-linked epigenetic regulators, including KDM5D and UTY, were differentially expressed in ZEB1-high male tumors. qPCR validation in male and female patient-derived GBM cell lines supported sex-dependent regulation of these candidates and showed that KDM5D and UTY expression was reduced following ZEB1 knockdown in male cells. Together, these findings identify a sex-dependent prognostic role for ZEB1 in GBM and suggest that ZEB1 interacts with sex-chromosome-linked epigenetic regulators to shape tumor transcriptional states.

Resistance to apoptosis, metabolic plasticity, and redox adaptation are major contributors to cancer progression and treatment failure. Ferroptosis and cuproptosis have therefore emerged as metal-dependent forms of regulated cell-death programs with potential relevance for tumours that survive conventional therapy. Ferroptosis is driven by iron-dependent phospholipid peroxidation when glutathione peroxidase 4 (GPX4)-dependent and parallel antioxidant systems fail, whereas cuproptosis depends on mitochondrial copper engagement of lipoylated tricarboxylic-acid-cycle proteins, lipoylated-protein aggregation, iron-sulfur protein destabilization, and proteotoxic stress. This review integrates the molecular basis, genetic architecture, long non-coding RNA (lncRNA)-mediated regulation, mechanistic crosstalk, and therapeutic implications of ferroptosis and cuproptosis in cancer. It emphasizes a critical evidence hierarchy: expression association, computational signature construction, metal accumulation, reactive oxygen species (ROS) generation, or reduced viability should not be interpreted as pathway dependency without pathway-defining biochemical endpoints and rescue experiments. The most credible translational opportunities will depend on functional stratification, tumour-selective delivery, and pharmacodynamic confirmation that distinguishes pathway-defined ferroptosis or cuproptosis from nonspecific metal-induced and oxidative cytotoxicity.