We found epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) is up-regulated in liver cancer cells exposed to sorafenib for a long time using a bioinformatic tool. Here, the mechanism of EFEMP1 in sorafenib resistance of hepatocellular carcinoma (HCC) cells was explored.

Hereditary cancer risk is key to guiding screening and prevention strategies. Cancer risks can vary by individual because of the presence or absence of high- and moderate-risk pathogenic variants (PVs) in cancer-associated genes, in addition to sex, age, and other risk factors. We previously developed Fam3PRO, a flexible multigene, multicancer Mendelian risk prediction model that estimates a patient's risk of carrying a PV in hereditary cancer genes and their future risk of developing several types of cancers. The Fam3PRO R package includes 22 genes with 18 associated cancers, allowing users to build customized submodels from any gene-cancer set. However, the current R package lacks a user interface (UI), limiting its practical use in clinical settings. Therefore, we aim to develop a web-based UI for broader use of the Fam3PRO functionalities.

Acute myeloid leukemia (AML) is a hematopoietic malignancy caused by abnormal proliferation and differentiation of blasts. PRMT5, a methyltransferase that catalyzes symmetric dimethylation of arginine (SDMA) residues, has been implicated in cancer stem cell homeostasis and shown to be a potential therapeutic target in AML. However, given the toxicity of complete PRMT5 inhibition, there is a need to identify effective synergistic therapies. Through a targeted screen of compounds that inhibit key nodes of PRMT5-regulated pathways, we identified a synthetic lethality between inhibition of PRMT5 and LSD1, a lysine demethylase known to affect AML blast differentiation. The two inhibitors broadly reshape the transcriptome of targeted cells and synergize to promote AML differentiation and eventually growth inhibition and apoptosis, in a p53-dependent manner. To leverage this synthetic lethal interaction, we generated new dual compounds to inhibit both enzymes and recapitulated the effects of the drug combination. Our results uncover an unexpected convergence of PRMT5- and LSD1-regulated targets, paving the way for new therapeutic opportunities.

Genome aneuploidy, characterized by copy number variations (CNVs), profoundly alters gene expression in cancer through direct gene dosage effects and indirect compensatory regulatory mechanisms. However, existing differential gene expression (DGE) testing methods do not differentiate between these mechanisms, conflating all expression changes, limiting biological interpretability and obscuring key genes involved in tumor progression. To address this, we developed DeConveil, a computational framework that extends traditional DGE analysis by integrating CNV data. Using a generalized linear model with a negative binomial distribution, DeConveil models RNA-seq expression counts while accounting for copy number gene dosage effects. We proposed a more fine-grained gene decomposition into dosage-sensitive (DSGs), dosage-insensitive (DIGs), and dosage-compensated (DCGs), which explicitly de-couples changes due to CNVs and bona fide changes in transcriptional regulation. Analysis of TCGA datasets from aneuploid solid cancers resulted in notable reclassification of genes, refining and expanding upon the results from conventional methods. Functional enrichment analysis identified distinct biological roles for DSGs, DIGs, and DCGs in tumor progression, immune regulation, and cell adhesion. In a breast cancer case study, DeConveil's CN-aware analysis facilitated the identification of both known and novel prognostic biomarkers, including lncRNAs, linking gene expression signatures to survival outcomes. Utilizing these biomarkers for each gene group significantly improved patient risk stratification, yielding more accurate predictions compared to conventional methods. These results highlight DeConveil's ability to disentangle CNV-driven from regulatory transcriptional changes, enhancing gene classification and biomarker discovery. By improving transcriptomic analysis, DeConveil provides a powerful tool for cancer research, precision oncology, with potential applications in therapeutic target identification.

Breast cancer (BC) is the most commonly diagnosed cancer among women globally, with significant regional variations in its molecular subtypes, clinical presentation, and management. Despite advancements in oncology, limited data exist on the molecular and clinical characteristics of BC in Libya. This study aims to analyze the prevalence of molecular subtypes, clinicopathological features, and treatment patterns among Libyan women with BC at Tobruk Medical Center. This retrospective observational study included BC patients diagnosed between January 2019 and December 2020 at Tobruk Medical Center. Demographic, clinical, pathological, and treatment-related data were extracted from medical records. Molecular subtyping was based on immunohistochemical assessment of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 (HER2), and Ki-67. Statistical analyses were performed using SPSS version 28 (IBM Corp., Armonk). Among 115 patients analyzed, the median age at diagnosis was 46 years. Invasive ductal carcinoma accounted for 89.6% of cases, with grade II tumors being the most common (69.6%). Luminal B was the predominant molecular subtype (67.8%), followed by luminal A (14.8%), HER2-enriched (10.4%), and triple-negative BC (7.0%). Advanced-stage diagnoses (stage III and IV) were observed in 57.4% of cases. Hormone receptor positivity was detected in 82.6%, and HER2 positivity in 25.2% of cases. This study highlights the high prevalence of advanced-stage BC and the predominance of the aggressive luminal B subtype in Libya. Targeted early detection programs and improved treatment access are urgently needed to address these challenges.

This study aims to investigate the effects of long noncoding RNA myocardial infarction-associated transcript (lncRNA MIAT) targeting miR-361-3p on the proliferation, invasion, and apoptosis of hepatocellular carcinoma (HCC) cells. The expression levels of lncRNA MIAT and miR-361-3p were examined in both cancerous and adjacent non-tumorous tissues of HCC patients. Additionally, their expression was analyzed in THLE-2 and MHCC97L cells. MHCC97L cells were transfected to observe changes in relevant mRNA expression and alterations in cell proliferation, invasion, and apoptosis. Compared with adjacent non-tumorous tissues, cancerous tissues exhibited increased levels of lncRNA MIAT mRNA and decreased levels of miR-361-3p (P < .05). Elevated transcription levels of lncRNA MIAT were more prevalent in patients with lymph node metastasis and advanced TNM staging (P < .05). In MHCC97L cells, compared with THLE-2 cells, there was an increase in lncRNA MIAT mRNA and a decrease in miR-361-3p (P < .05). LncRNA MIAT and miR-361-3p were found to have potential binding sites and exhibit target regulation. Cells in the miR-NC group showed no significant changes in all indicators compared with the negative control group (P > .05). Conversely, cells with low expression of lncRNA MIAT and cyclin D1 mRNA and decreased cell proliferation and invasion numbers showed increased expression of miR-361-3p and phosphatase and tensin homolog mRNA and higher apoptosis rates (P < .05). The group with elevated expression levels demonstrated contrasting patterns (P < .05). LncRNA MIAT is upregulated in HCC tissues. Silencing lncRNA MIAT can elevate miR-361-3p levels, inhibiting the proliferation and invasion of MHCC97L cell structures and promoting apoptosis.

Tertiary lymphoid structures (TLSs) are critical components of the tumor microenvironment in HCC. However, the role of TLS-related molecules in predicting HCC outcomes and guiding immunotherapy remains unexplored. This study aimed to develop TLS-related gene signature (TLSRS) to predict prognosis and immunotherapy response in patients with HCC​​​​​​.

Esophageal squamous cell carcinoma (ESCC) is among the most lethal malignancies worldwide, with a five-year survival rate below 20%. Ferroptosis-a regulated form of cell death driven by iron-dependent lipid peroxidation-has emerged as a promising therapeutic strategy, yet its regulation in ESCC remains poorly understood. We investigated the role of tripartite motif-containing 31 (TRIM31), an E3 ubiquitin ligase, in ESCC progression and ferroptosis.

Acute myeloid leukemia (AML) is a lethal and rapidly progressive hematologic malignancy with high rates of relapse and treatment refractoriness. Management of AML is complicated by biological heterogeneity in a disease that is broadly defined by the clonal expansion of myeloblasts that otherwise play an important role in healthy marrow tissues. While subtypes of AML are increasingly defined by druggable driver mutations including FLT3-ITD, IDH1, IDH2, and NPM1, conventional chemotherapy and reduced intensity induction regimens (e.g., azacitidine-venetoclax) remain therapeutic backbones. One area of active development for personalization of AML treatment is the assessment of measurable residual disease (MRD). MRD testing in AML is complicated by uncertainty regarding the physiologic compartment of persistent and relapsing myeloblasts, and by increasing recognition of myeloid driver mutations in some healthy bone marrow states, such as clonal hematopoiesis of indeterminate potential (CHIP). Even in large academic centers, MRD tools are not yet universally available. Standardized workflows for MRD implementation are only beginning to enter consensus and guideline documents. Current understanding of AML biology and state-of-the-art tools for MRD measurement are reviewed here in an effort to promote clinical and laboratory investigator collaboration for the development of reliable tools for improving outcomes in this deadly disease. Clinical trial number: not applicable.

POLE2 exhibits oncogenic properties. This study aimed to clarify its effects and underlying mechanisms in renal cell carcinoma (RCC). Using bioinformatics analyses, we predicted the relationship between POLE2 and autophagy, epithelial-mesenchymal transformation (EMT), and the AKT/mTOR pathway. The expression pattern of POLE2 was further verified in the clinical cohort comprising 94 tumor samples from patients with RCC. Following, we constructed in vivo and in vitro models to further investigate the potential mechanisms of POLE2 using a series of molecular biology approaches. The results showed that GINS1 was the downstream target of POLE2, and its overexpression reversed the inhibitory effects of POLE2 knockdown on RCC proliferation, metastasis, and EMT, while restoring the autophagy suppression. Furthermore, POLE2/GINS1 inhibited AKT/mTOR-mediated autophagy, thereby promoting EMT and lung metastasis of RCC. These findings provide a more comprehensive perspective on the genetic function of POLE2 in RCC progression.

Background/Objectives: To evaluate the immunohistochemical expression of hexokinase-2 (HK2), glutaminase-1 (GLS1), and fatty acid synthase (FASN) and its prognostic significance in diffuse gastric adenocarcinoma. Materials and Methods: Formalin-fixed paraffin-embedded tissue samples from 92 patients with diffuse gastric adenocarcinoma were analyzed. Immunohistochemistry (IHC) was performed to assess the expression of HK2, GLS1 and FASN. Expression levels were evaluated semi-quantitatively based on staining intensity and the percentage of positive cells. Associations between enzyme expression and clinicopathological features were assessed using the Chi-square test. Kaplan-Meier survival analysis was employed to evaluate progression-free survival (PFS) and overall survival (OS) and the log-rank test and Cox proportional hazards models were used for statistical analysis. Results: HK2 and FASN were overexpressed in 20.7% and 22.8% of patients, respectively, and were significantly associated with advanced tumor stage. In contrast, GLS1 expression, found in 30.4% of patients, did not independently correlate with clinicopathological characteristics. Furthermore, HK2 expression and co-expression of HK2/FASN (10.9%) and HK2/GLS1/FASN (8.7%) were associated with progressive disease. In the univariate analysis, stage, HK2 overexpression, and co-expression of HK2/FASN and HK2/GLS1/FASN were associated with shorter survival. However, only stage retained prognostic value in the multivariate analysis. Conclusions: Co-expression of these key metabolic enzymes remains a promising candidate as prognostic markers and therapeutic targets. Concurrent targeting of these metabolic pathways may offer novel therapeutic opportunities for patients with advanced-stage gastric cancer.

Measurable residual disease (MRD) has become a central determinant of prognosis and treatment planning in acute myeloid leukemia (AML). MRD assessment is now aided by a wide range of technologies, including next-generation sequencing, PCR-based assays, multiparameter flow cytometry, and emerging approaches such as liquid biopsy platforms and imaging-based detection. These modalities differ in sensitivity, applicability, and interpretive framework, yet each offers distinct advantages in specific disease contexts. Beyond technical issues, MRD is becoming increasingly integrated into clinical practice. In non-intensive treatment settings, where targeted and low-intensity regimens rely on dynamic disease monitoring to guide ongoing management, MRD is increasingly being used to inform therapeutic decisions. In the peri-transplant setting, MRD status influences conditioning strategies, donor selection, and the use of post-transplant interventions. Despite the growing evidence supporting the clinical relevance of MRD across these scenarios, challenges remain regarding standardization, optimal timing of assessment, and the interpretation of discordant results. This review summarizes the full landscape of MRD detection methods and examines the evolving role of MRD in contemporary AML management, emphasizing current applications and areas requiring further refinement.

Cholangiocarcinoma (CCA) is a highly heterogeneous malignancy in which numerous biomarker candidates have been reported, yet few progress to clinical use. Beyond biological complexity, this low translational yield reflects the lack of systematic criteria for prioritizing biomarkers during the discovery stage. In particular, tumor-derived signals identified in tissue often fail to persist in clinically accessible biofluids, as cross-compartment signal behavior is rarely evaluated explicitly.

Erythroid acute myeloid leukemia (AML) cell line OCI-M2 expresses a particular oncogenic network: IRF6, in concert with ETV2 and HEY1, aberrantly activates NKL homeobox gene NKX2-4, which in turn represses megakaryocytic lineage factor FLI1. Interestingly, in keratinocytes, IRF6 is able to bind glucose which promotes IRF6-dimerization and thus alters its binding site selection. Here, we used OCI-M2 as a model to investigate the role of glucose level and IRF6 in leukemogenesis. Treatment of OCI-M2 with high glucose or 2-deoxy-glucose resulted in the downregulation of IRF6 and NKX2-4, and the upregulation of FLI1, indicating that glucose-mediated dimerization of IRF6 altered its reported autoactivation. The screening of this cell line for genes encoding glycolytic enzymes identified aberrant overexpression of glucose-6-phosphate isomerase (GPI) and phosphofructokinase L (PFKL), which were targeted by genomic amplification and chromothripsis-like alterations, respectively. Furthermore, GPI was activated by NKX2-4 and ETV2, and PFKL by ETV2. Finally, siRNA-mediated downregulation of PFKL resulted in elevated glucose levels, suppressed expression of IRF6 and NKX2-4, and activated FLI1. Thus, we connected an oncogenic regulatory network with deregulated glycolytic enzymes and glucose metabolism, thereby establishing a new in vitro model to develop novel therapeutic avenues in AML subsets.

Oral squamous cell carcinoma (OSCC) is a prevalent form of head and neck cancer that typically develops on the lip or within the oral cavity. Although there have been advances in early detection and treatment, the prognosis for patients, particularly those with advanced-stage disease, remains poor. Liquid biopsy, particularly through the analysis of cell-free DNA (cfDNA) in plasma and urine, has emerged as a promising tool for non-invasive cancer detection and monitoring. This study assessed cfDNA concentration dynamics in plasma and urine samples from 32 OSCC patients, with 5 undergoing genomic characterization by targeted next-generation sequencing (NGS). CfDNA levels were higher in patients compared to healthy controls and showed transient increases following treatment initiation, likely reflecting tumor cell death, followed by a gradual return to baseline. However, cfDNA concentrations were not significantly associated with tumor stage, recurrence, or progression-free survival. Targeted NGS analysis revealed a heterogeneous mutational landscape, identifying 76 variants across tumor tissue and initial cfDNA, with 30.3% shared between both sources. Recurrent hotspot mutations were detected in several important genes, including TP53, PIK3CA, KRAS, APC, and FBXW7. Urine cfDNA also captured several mutations absent from plasma or tissue, supporting its complementary value. These findings demonstrate that cfDNA analysis can dynamically reflect treatment response and capture tumor heterogeneity in OSCC. While informative, cfDNA quantification alone offers limited prognostic reliability, reinforcing the need for a multidimensional approach that includes genomic and clinical evaluation. Overall, this study supports the potential of liquid biopsy as a real-time, non-invasive tool for molecular monitoring and personalized management of OSCC patients.

Chronic exposure to benzo[a]pyrene (BaP), a Group 1 IARC carcinogen, is a major driver of lung carcinogenesis; however, how sustained subcytotoxic exposure reprograms bronchial epithelium toward preneoplastic states remains poorly defined. Here, we subjected BEAS-2B human bronchial epithelial cells to 12 weeks of continuous BaP at environmentally relevant concentrations (0.1 and 1.0 µM) and interrogated the resulting phenotypes using an integrated multi-scale framework encompassing functional toxicology, RT-qPCR, RNA-seq, phospho-kinase/NF-κB arrays, and organotypic air-liquid interface (ALI) cultures. Cells maintained metabolic competence throughout, evidenced by sustained CYP1A1 and CYP1B1 induction at both acute (4 h) and chronic (12-week) timepoints, while accumulating genotoxic stress as demonstrated by dose-dependent nuclear γ-H2AX foci formation and ATM phosphorylation (Ser1981). RNA-seq revealed a dose-dependent transcriptional shift: 0.1 µM BaP yielded 119 differentially expressed genes (DEGs; |log2FC| ≥ 1, FDR < 0.05), whereas 1.0 µM generated 255 DEGs. Downregulated transcripts were enriched for extracellular matrix and cell-adhesion programs (COL14A1, ADAMTS2, CSMD3, CADM3), while upregulated genes encompassed inflammatory, calcium-signaling, and vesicle-trafficking modules (NFATC4, CSF2RA, SYT1, PCLO). Phospho-kinase/NF-κB arrays confirmed a p53/NF-κB signaling nexus, with concurrent activation of MAPK/ERK (Thr202/Tyr204) and PI3K/Akt (Ser473) pathways. Despite persistent genotoxic stress, cells did not acquire anchorage-independent growth and remained non-tumorigenic in vivo. Critically, ALI organotypic cultures derived from BaP-exposed cells exhibited histological dysplasia, nuclear pleomorphism, and disrupted apical-basal polarity. These findings mechanistically link chronic BaP exposure to an initiation-like preneoplastic state and establish a validated 2D/3D multi-omics platform for PAH-driven lung carcinogenesis research.

Triple-negative breast cancer (TNBC) is an aggressive subtype lacking targeted therapies and characterized by pronounced heterogeneity and widespread dysregulation of microRNAs (miRNAs) that influence epithelial-to-mesenchymal transition (EMT) and metastasis. Tumor-derived extracellular vesicles (tEVs) further contribute to TNBC progression by transporting oncogenic cargo that can enhance pro-inflammatory signaling. The synthetic SMRwt peptide has been suggested to modulate oncogenic pathways; however, its effects on EV miRNA composition and inflammatory transcript profiles in TNBC remain unclear. Here, we investigated whether SMRwt alters tEV-associated miRNAs and cytokine transcript signatures relevant to EMT and inflammasome-linked pathways. Extracellular vesicles were isolated from SMR-treated and untreated MDA-MB-231 cells, followed by nanoparticle tracking analysis and small RNA sequencing. SMRwt treatment enriched 11 tumor-suppressive miRNAs (including Let-7a-5p, Let-7b-5p, miR-24-3p, miR-26b-5p, miR-92a-3p, miR-93-5p, and miR-496) previously associated with the regulation of proliferation, EMT, migration, and metastasis. We also observed modest, non-significant decreases (1.01-1.27-fold) in oncogenic miR-1200, miR-374a-5p, and miR-937-3p, which have been implicated in the progression of breast, lung, and bone malignancies. Complementary transcriptomic profiling using the NanoString nCounter Breast Cancer 360 Gene Expression Panel (NanoString Technologies, Inc., Seattle, CA, USA) demonstrated reduced expression of inflammasome-associated cytokines in TNBC cells relative to non-tumorigenic controls, including a log2 fold change of -1.15 for IL 1β (MDA-MB-231 vs. MCF10A). These transcript-level changes suggest potential modulation. Additionally, SMRwt suppresses ASC-mediated caspase-1 activation and reduces IL-1β secretion, thereby inhibiting NLRP3 inflammasome signaling. Therefore, we infer that SMRwt simultaneously restores tumor-suppressive miRNA networks and suppresses inflammasome-driven inflammation, supporting its potential as a dual-target therapeutic strategy for TNBC.

Inflammation is widely viewed as a driver of hepatocellular carcinoma (HCC), yet inflammatory signaling also reshapes hepatic xenobiotic metabolism. Here, we established transgenic (Tg) IKKβΔhep mice (Tg-IKKβΔhep), which combine hepatocyte-specific IKKβ deletion with liver expression of a nuclear, kinase-inactive IKKβ mutant (NLS-IKKβKN). Tg-IKKβΔhep mice developed spontaneous chronic hepatitis and progressive fibrosis but were strikingly resistant to diethylnitrosamine (DEN)-induced hepatocarcinogenesis, with markedly reduced tumor multiplicity and total tumor burden. Despite persistent inflammatory injury, DEN-triggered oxidative DNA damage and p53 activation were markedly attenuated, compatible with reduced tumor initiation. Transcriptomic and biochemical analyses revealed broad repression of xenobiotic-metabolizing cytochrome P450 genes, including the pericentral enzyme CYP2E1, accompanied by reduced CYP2E1 protein abundance. This was associated with impaired HNF4α-PXR-CAR transcriptional output and reduced HNF4α occupancy at target promoters. Acute TNFα or IL-1β exposure recapitulated this repression, in part through reduced PGC-1α expression and decreased RNA polymerase II recruitment to target promoters. In parallel, pericentral xenobiotic metabolism was blunted, a change that could plausibly diminish DEN bioactivation and genotoxic stress. Together, these findings support a "metabolic gatekeeping" model in which chronic inflammation can constrain chemical hepatocarcinogenesis by attenuating carcinogen-metabolizing capacity.

Gastric cancer (GC) remains a major global health burden, with its unfavorable prognosis primarily driven by extensive tumor heterogeneity. Traditional bulk omics, while informative, are inherently limited by the averaging effect of diverse cell populations and fail to capture the critical spatial molecular disparities within the tumor and its microenvironment (TME). Single-cell omics can capture cellular heterogeneity but lack spatial context. Therefore, there is an urgent clinical need for spatial multi-omics to provide a high-definition dissection of GC heterogeneity and to optimize therapeutic efficacy. This review first outlines briefly the evolution of spatial technologies, including transcriptomics, proteomics, metabolomics, genomics and epigenomics, and their transformative applications in GC research. We further explore how these platforms refine molecular classification beyond traditional models, identify next-generation biomarkers, and decode the intricate cellular interactions governing immune evasion and metastasis. Next, we highlight the pivotal role of spatial profiling in unravelling the multidimensional mechanisms of resistance to chemotherapy, targeted therapy and immunotherapy. Finally, we address current technical bottlenecks and discuss prospects for clinical translation.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a 5-year survival rate of 13.3%. First-line treatment relies on two chemotherapy regimens, FOLFIRINOX (FOLFNX) or gemcitabine plus nab-paclitaxel (GEMPAC). However, direct clinical comparisons between these regimens have yielded inconsistent results across survival and toxicity endpoints, and the molecular basis of heterogeneous treatment responses remains poorly defined. To investigate regimen-specific tumor-cell-intrinsic mechanisms, we performed quantitative proteomic profiling of a primary PDAC-derived MIA PaCa-2 cell line following treatment with FOLFNX or GEMPAC. Differentially expressed proteins were analyzed using Gene Ontology, KEGG, and Ingenuity Pathway Analysis to define pathway-level alterations, and findings were contextualized using TCGA transcriptomic data. Proteomic analyses revealed that FOLFNX and GEMPAC engage in distinct cytotoxic programs. FOLFNX predominantly suppressed ribosome biogenesis and mitochondrial translation, consistent with sustained metabolic and biosynthetic stress, whereas GEMPAC preferentially disrupted mitotic cytokinesis and phosphatidylinositol phosphate biosynthesis, consistent with mitotic failure. Integration with TCGA data showed that FOLFNX-altered proteins aligned with favorable prognostic expression signatures, whereas GEMPAC-associated proteins were enriched among adverse profiles, reflecting engagement of distinct tumor-intrinsic programs. Together, these findings provide mechanistic insight into differential chemotherapy responses and establish a foundation for proteomics-based biomarkers to guide personalized chemotherapy selection in PDAC.