Aug 2026· Journal of Hepatocellular Carcinoma· Vol 13, pp. 1-26· 0 citations· 42 references
Medicine
TL;DR
KIF11 drives HCC progression and predicts immunotherapy response and is a candidate direct resveratrol target and a potential biomarker for patient stratification in immune checkpoint therapy, although further experimental validation is warranted.
Abstract
Objective Hepatocellular carcinoma (HCC) has poor prognosis and variable immunotherapy response. Resveratrol exhibits anti-HCC activity, but its direct targets and association with immunotherapy response are unclear. This study identifies core resveratrol targets in HCC and evaluates their prognostic and predictive value. Methods Resveratrol targets were intersected with TCGA-LIHC differentially expressed genes. A prognostic risk model was built using LASSO-Cox regression. Drug-target binding was assessed by molecular dynamics simulations and qRT-PCR. Single-cell and spatial transcriptomics, cell-cell communication, and a pan-immunotherapy cohort were used to investigate KIF11. An HCC mouse model validated immunomodulatory effects via flow cytometry. Results Thirty-four resveratrol-associated targets were identified, enriched in metabolism pathways. A nine-gene risk model showed robust prognostic performance. Resveratrol stably binds to KIF11’s ATP-binding pocket. KIF11 is overexpressed in malignant hepatocytes and proliferating T cells; KIF11⁺ cells orchestrate VEGF-mediated microenvironment remodeling. High KIF11 expression correlated with poor prognosis but predicted superior survival in the immunotherapy cohort, a phenomenon attributed to the observation that KIF11-high tumors exhibit both enhanced immunogenicity and active immunosuppression. In vivo, resveratrol enhanced CD8⁺ T cell infiltration, proliferation, effector function, and central memory T cells, while reducing Tregs. Conclusion KIF11 drives HCC progression and predicts immunotherapy response. It is a candidate direct resveratrol target and a potential biomarker for patient stratification in immune checkpoint therapy, although further experimental validation is warranted.
This study establishes a novel CSC–associated gene signature for diagnosis and prognosis in HCC and nominates belinostat as a repurposing candidate for targeting stemness‐related pathways, offering a promising strategy for personalized therapy.
Yang Zi, Ying Zhang, Jun Wu et al.· Stem Cells International· 0 citations
Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide and exhibits considerable biological heterogeneity in both molecular and clinical characteristics. The diverse molecular alterations and clinical manifestations of HCC indicate substantial heterogeneity across patient subgroups. This study aimed to identify novel therapeutic targets and predictive biomarkers associated with HCC using an integrative bioinformatics approach. High-throughput genomic datasets were obtained from the UCSC Xena browser to retrieve mRNA HTSeq-count data from the TCGA-HCC cohort. Gene co-expression network (GCN), protein–protein interaction network (PPIN), and enrichment analyses were performed to identify key dysregulated genes and their biological significance. Integrated network analyses identified three dysregulated hub genes, namely CXCR2, TLR2, and TLR4. Genomic alterations in these genes were further evaluated across tumor samples in the TCGA-HCC cohort. Kaplan–Meier (KM) survival analysis demonstrated that lower CXCR2 mRNA expression was significantly associated with poorer overall survival (OS) and recurrence-free survival (RFS). Furthermore, TIMER and UALCAN analyses revealed significant associations between CXCR2 expression and tumor purity, as well as immune cell infiltration levels, including T cells, macrophages, dendritic cells (DCs), and neutrophils. These findings suggest that CXCR2 is significantly associated with the immune microenvironment of HCC and represents a potential prognostic biomarker whose biological role warrants further mechanistic investigation.
S. Almatroodi, Tarique Sarwar, A. Rahmani· International Journal of Mol...· 0 citations
Head and neck squamous cell carcinoma (HNSCC) comprises biologically diverse tumors, and durable responses to immune-checkpoint blockade are achieved by only a subset of patients. There remains a need for markers that connect clinical outcome with malignant-cell phenotypes and tissue-level immune organization.
We integrated The Cancer Genome Atlas HNSCC cohort (TCGA-HNSC), five Gene Expression Omnibus (GEO) validation cohorts, single-cell RNA sequencing, Visium spatial transcriptomics, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)-informed protein-potential inference, pharmacogenomic screening, genetic-risk analysis and experimental validation. A reconstructed 296-pipeline survival modelling framework was used to prioritize prognostic hub genes across validation-cohort-specific analyses.
SIRPG was repeatedly ranked among the top ten selected genes in all five validation cohorts. At single-cell resolution, SIRPG-high tumor cells showed stronger malignant-cell features, immune-inhibitory and metabolic programs, Scissor-positive risk association, CLCA2/P53-related perturbation signals and inferred SIRPG-CD47/signal regulatory protein (SIRP) communication. Spatial analyses placed this axis within an immune-checkpoint-coupled niche, supported by Maxspin/multiview intercellular spatial modelling (MISTy) spatial coupling, communication analysis by optimal transport (COMMOT)-inferred CD47-SIRPG communication and scProTrans-inferred CD47/SIRPG protein-potential overlap. Functionally, SIRPG knockdown reduced HNSCC cell viability and increased apoptosis, whereas re-expression of short hairpin RNA (shRNA)-resistant SIRPG restored the CLCA2-BAX/BCL2 protein response.
Together, these findings identify SIRPG as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.
Jiaqi Tang, Yulun He, Yuqi Wang et al.· Frontiers in Immunology· 0 citations
Background Clear cell renal cell carcinoma (ccRCC) is metabolically primed for ferroptosis, yet the prognostic relevance and mechanistic contribution of ferroptosis-related genes remain incompletely defined. This study aimed to identify ferroptosis-associated biomarkers with prognostic value and to clarify their functional relevance in ccRCC progression. Methods We integrated single-cell RNA sequencing, bulk RNA-seq, spatial transcriptomics, and machine-learning-based feature selection to identify ferroptosis-related prognostic genes in ccRCC. A four-gene risk model and an integrated nomogram were constructed and evaluated in independent cohorts. PANX2 was prioritized for experimental validation using stable knockdown models, RNA sequencing, lipid peroxidation and iron probes, redox assays, Western blot, luciferase reporter assays, xenografts, and an immunocompetent murine renal carcinoma model. Results A four-gene prognostic signature (CA9, PVT1, RRM2, and PANX2) was identified and used to construct a risk model with consistent predictive performance in the training and external validation cohorts. Among these genes, PANX2 was predominantly enriched in epithelial tumor compartments and had not been functionally characterized in ccRCC. PANX2 knockdown inhibited ccRCC cell proliferation, reduced antioxidant capacity, increased intracellular Fe2+ accumulation and lipid peroxidation, and sensitized cells to erastin-induced ferroptotic death. Mechanistically, PANX2 loss was associated with reduced Akt/mTOR pathway activity and diminished SLC7A11 expression; rescue with an Akt activator or SLC7A11 overexpression attenuated ferroptosis-associated phenotypes. In an immunocompetent murine renal carcinoma model, PANX2 knockdown was accompanied by increased infiltration of CD45+ leukocytes, CD3+ T cells, and CD8+ T cells, supporting a potential link between PANX2-dependent ferroptosis resistance and the tumor immune contexture. Conclusions This study identifies PANX2 as a ccRCC-relevant suppressor of ferroptosis and supports the involvement of a PANX2-Akt/mTOR-SLC7A11-associated signaling axis in redox homeostasis and tumor progression. The ferroptosis-related prognostic model and nomogram may support risk stratification, while PANX2 represents a candidate therapeutic vulnerability that warrants further mechanistic and translational validation.
Xing-Lin Li, Yiqi Xiong, Jiyin Wang et al.· Frontiers in Immunology· 0 citations
BACKGROUND
Burkitt lymphoma (BL) is a highly aggressive malignancy with limited effective treatments due to toxicity/resistance. Identifying and prioritizing candidate biomarkers and potential therapeutic targets from complex transcriptomic data, ahead of functional validation, remains a major unmet need.
METHODS
We integrated differential gene expression analysis across BL vs. control cohorts (Gene Expression Omnibus [GEO] datasets GSE43677/GSE12453) with Random Forest machine learning to prioritize candidates. Validated top genes via immunohistochemistry in an independent cohort (n = 10 BL, n = 10 reactive lymphoid hyperplasia [RLH] controls), followed by immune cell infiltration analysis.
RESULTS
This approach identified four candidate genes; only Chromatin Assembly Factor 1 Subunit A (CHAF1A) showed profound protein-level overexpression in BL tumors vs. RLH. In a single-dataset CIBERSORT analysis, CHAF1A expression showed exploratory correlational associations with several immune-cell fractions, most strongly a positive association with M0 macrophages; these in silico associations are hypothesis-generating and do not by themselves establish a mechanistic role in the tumor immune microenvironment.
CONCLUSION
CHAF1A is identified as a candidate biomarker associated with BL that, in exploratory single-dataset analysis, also correlates with immune-cell infiltration; these findings nominate it as a potential therapeutic target that warrants functional validation in future studies.
Colorectal cancer (CRC) is a highly heterogeneous malignancy with substantial variability in clinical outcomes. Although established molecular classification systems have improved CRC stratification, pathway-level subtyping remains underexplored. A framework integrating pathway-based molecular subtype discovery, multi-cohort validation, single-cell projection, and mechanistic target identification is still lacking.
Transcriptomic data from TCGA CRC samples were transformed into pathway activity profiles using gene set variation analysis (GSVA), followed by consensus clustering to define pathway-based molecular subtypes. Nearest template prediction (NTP) was applied across 17 independent cohorts to validate subtype robustness. Three CRC single-cell RNA-seq datasets were integrated and analyzed using the single-cell phenotype-associated subpopulation identifier (scPAS) to map subtype-associated signals at cellular resolution. Multi-cohort Cox regression identified prognostic genes, and LAMP5 was further assessed through clinicopathological correlation, pathway enrichment analyses, and experimental validation
in vitro
and
in vivo
.
Four pathway-based molecular subtypes were identified, among which C4 had the worst prognosis. The subtype classification was reproducible across 17 external cohorts. Single-cell analysis suggested that the aggressive subtype-associated phenotype could be projected onto distinct cell populations. LAMP5 emerged as the most consistent unfavorable prognostic gene across cohorts and was associated with advanced clinicopathological features. Functional analyses linked LAMP5 to TGFβ signaling, epithelial-mesenchymal transition (EMT), angiogenesis, invasion, and metastasis. Experimental results supported the pro-tumorigenic role of LAMP5 in CRC.
This study establishes a pathway-based molecular classification framework for CRC and identifies LAMP5 as a robust prognostic biomarker and candidate therapeutic target associated with the EMT pathway.