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Results for “Immune correlation”

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PubMed2024

Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis.

BACKGROUND: Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD. METHODS: The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis. RESULTS: In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD. CONCLUSIONS: Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.

Bipolar Disorder↗

PubMed2026

Investigation of Fatty Acid Metabolism-Associated Molecular CPOX and the Underlying Mechanism in Follicular Lymphoma.

Dysregulated lipid metabolism is a key driver of follicular lymphoma (FL). This study aimed to explore the lipid metabolism-related genes (LMRGs) and clarify the underlying roles and mechanisms in FL. Bioinformatics methods, including differential analysis, WGCNA, machine learning, and Mendelian randomization, were utilized to select the LMRGs in FL. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the function of the key LMRG. Receiver operator characteristic (ROC) was used to evaluate the diagnostic value of the key gene CPOX. A pan-cancer analysis investigated CPOX's expression level and immune correlations. In vitro experiments using FL cell lines (WSU-FSCCL, DOHH2) validated CPOX expression, and CPOX knockdown in DOHH2 cells was used to assess its impact on viability, migration, invasion, and fatty acid metabolism. CPOX was confirmed to be a risk factor, significantly overexpressed in FL, and exhibited effective diagnostic ability in FL (AUC = 0.731). Functional analysis linked CPOX to mitochondrial function, oxidative phosphorylation, and heme metabolic process. Pan-cancer indicated the dysregulated CPOX across multiple cancers and closely correlation with immune characteristics. Experimentally, CPOX was higher in the more invasive DOHH2 cells; and CPOX knockdown suppressed FL progression and reduced lipid droplet formation, triglyceride, total cholesterol, and free fatty acid levels. In conclusion, this study fills the gap in understanding the significance of lipid metabolism-related molecules in FL, and innovatively proposes that CPOX is a risk factor for FL. Knockdown of CPOX inhibits the FL progression, which is regulated by fatty acid metabolism.

Lymphoma, Follicular↗

PubMed2026

The prognostic value and molecular mechanisms of Porphyromonas gingivalis infection-associated differentially expressed genes in oral squamous cell carcinoma.

BACKGROUND: Increasing evidence suggests that Porphyromonas gingivalis (Pg) is associated with oral squamous cell carcinoma (OSCC) development and progression. This study aimed to identify Pg-associated genes with prognostic relevance in OSCC through integrated bioinformatics analysis. METHODS: OSCC-related differentially expressed genes (DEGs) were identified from the The Cancer Genome Atlas (TCGA)-OSCC cohort and intersected with Pg supernatant-associated DEGs from GSE192887. Raw count data were analyzed with DESeq2, whereas transcripts per million (TPM)-transformed expression values were used for downstream visualization and model construction. Weighted gene co-expression network analysis (WGCNA), univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariable Cox modeling were used to develop a seven-gene prognostic signature, which was externally evaluated in GSE41613. Additional analyses examined treatment-associated expression changes in the seven model genes, pairwise correlations among the model genes, and correlations between Pg supernatant-associated differentially expressed gene (PgSDEG)-derived module eigengenes and immune-cell fractions. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed in eight paired OSCC and adjacent non-tumor tissues and in supplemented-brain heart infusion (BHI) vehicle-control and Pg culture-supernatant-treated HOK, HSC-3, and CAL-27 cells. RESULTS: A prognostic signature comprising CXCL8, GAST, HBQ1, PADI3, STC1, TEX19, and TMEM92 was established. The signature showed limited-to-moderate discrimination in the TCGA training cohort, with 1-, 3-, and 5-year areas under the curve (AUCs) of 0.68, 0.69, and 0.69, respectively, and limited discrimination in the GSE41613 external cohort (AUCs: 0.66, 0.67, and 0.61). Kaplan-Meier analysis showed poorer survival in the high-risk group in both cohorts. The GSE192887 analysis showed significant treatment-associated expression changes in all seven genes after Pg culture-supernatant exposure. In paired tissues, CXCL8 and TMEM92 were significantly higher in OSCC tissues, whereas STC1 was not significant after Holm correction. In CAL-27 cells, CXCL8, STC1, and TMEM92 increased significantly after culture-supernatant treatment, whereas the corresponding comparisons were not significant in HOK or HSC-3 cells after adjustment. CONCLUSIONS: This study developed a seven-gene Pg-associated prognostic signature for OSCC and provided complementary transcriptomic, immune-correlation, tissue, and cell-based evidence that placed the signature in biological context. The model showed limited-to-moderate discrimination and is not ready for clinical use. The enrichment, gene-correlation, and immune-correlation findings are hypothesis-generating rather than mechanistic evidence. Further independent validation and dedicated functional studies are required.

Oral squamous cell carcinoma (OSCC)↗

PubMed2026

RECQL correlates with immune infiltration and serves as a prognostic biomarker and therapeutic predictor in gastric cancer.

BACKGROUND: RecQ-like helicase (RECQL), a member of the RecQ-like DNA helicase family, plays a crucial role in maintaining genomic stability. However, its relevance in gastric cancer (GC) has not been fully investigated. This study aimed to explore the clinical significance, biological functions, and potential role of RECQL in the tumor immune microenvironment of GC through comprehensive bioinformatics analyses and in vitro experiments. METHODS: Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and least absolute shrinkage and selection operator (LASSO) regression were performed using public datasets [The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD), GSE150290] to identify key genes associated with GC progression. Subsequently, key pathways were identified through functional enrichment analysis, while immune infiltration and spatial transcriptomic analyses were conducted to characterize RECQL expression and its association with the tumor immune microenvironment. Finally, the effects of RECQL knockdown on the biological function of GC cells were assessed through Cell Counting Kit-8 (CCK-8), colony formation, scratch, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays. RESULTS: RECQL was significantly upregulated in GC tissues and correlated with advanced clinical stage and poor prognosis. Gene set enrichment analysis (GSEA) revealed a strong association between high RECQL expression and DNA repair pathway. Immune infiltration analysis indicated significant enrichment of M2 macrophages in the high-RECQL group, along with upregulation of immune checkpoint molecules including PDCD1, CTLA4, and CD274. Spatial transcriptomics further demonstrated co-localization of RECQL with myeloid cell-enriched regions in tumor parenchymal areas. Furthermore, in vitro experimental results indicated that RECQL was highly expressed in GC cell lines, and its knockdown effectively inhibited the viability, proliferation, and migration capabilities of HGC-27 cells, while enhancing their apoptosis. CONCLUSIONS: RECQL serves as a promising biomarker and potential therapeutic target in GC.

DNA repair↗

PubMed2024

Exploring correlations between immune cell phenotypes and the risk of epilepsy: A bidirectional Mendelian randomization study.

BACKGROUND: Neuroinflammation plays an important pathophysiological role in epilepsy; however, the precise connection between immune cells and epilepsy remains unclear. This study used Mendelian randomization (MR) to analyze the causal relationship between 731 immune cell traits and epilepsy. METHODS: Based on data from a genome-wide association study (GWAS), a bidirectional two-sample MR analysis was conducted to investigate the potential influence of immune cell phenotypes on epilepsy. Five MR methods were used to analyze the results, with the inverse variance weighted (IVW) method as the primary method, and the results were corrected using the false discovery rate (FDR) method. Sensitivity analyses were performed to test for heterogeneity and horizontal pleiotropy. RESULTS: After correction for FDR, four immune traits remained significantly associated with epilepsy risk: CD25 expression on memory (OR = 1.04, 95 % CI = 1.02 ∼ 1.06,P = 2.55 × 10-4), IgD+CD38dim (OR = 1.05, 95 % CI = 1.02 ∼ 1.08, P = 4.73 × 10-4), CD24+CD27+ (OR = 1.04, 95 % CI = 1.02 ∼ 1.06, P = 4.82 × 10-4), and IgD-CD38dim (OR = 1.04, 95 % CI = 1.02 ∼ 1.06, P = 1.04 × 10-3) B cells. The risk of generalized epilepsy was significantly associated with two immune cell traits, whereas that of focal epilepsy was significantly associated with seven immune cell traits. Furthermore, immune cell phenotypes are not affected by genetically predicted epilepsy. CONCLUSION: This MR study affirms the causal connection between circulating immune cells and epilepsy, offering guidance for further understanding of the immune mechanisms that underlie epilepsy and the discovery of novel targets for therapy.

Humans↗

PubMed2025

Cholesterol Metabolism-related Characteristics Predict Therapeutic Response and Survival in Esophageal Cancer.

INTRODUCTION: Cholesterol homeostasis has been identified as an essential downstream pathway of mutations in TP53. Esophageal cancer is one of the most prevalent malignancies exhibiting the mutation. OBJECTIVES: To explore the significance of cholesterol metabolism-related characteristics in tumor phenotype and treatment outcomes of esophageal cancer. METHODS: We established a cholesterol metabolism-related gene set (CMGs) and performed Lasso-Cox analysis to identify prognostic signatures. Nomogram-based risk scores and clinical stages afterwards were constructed and evaluated. We simultaneously identified two metabolic subtypes based on the distinct features of the CMGs. We annotated the functional and pathway characteristics of differentially expressed genes between the clusters and compared the differences in clinical and immune characteristics. Finally, we assessed the prognostic value of signatures in the GSE53625 and two clinical cohorts using whole-exon sequencing and multiplex immunofluorescence. RESULTS: Our study identified five cholesterol prognosis-related genes (CRGs) that demonstrated superior prognostic efficacy in the training set compared to clinical staging, validated in independent public databases and two clinical cohorts. According to the different expression patterns of the signatures, patients were divided into two subtypes. The C1 group demonstrated poorer overall survival, response to immunotherapy, and downregulation of the p53 pathway. In the immune correlation analysis, we found that the risk score based on 5-signature model was significantly positively correlated with the abundance of suppressive immune cells and the immune checkpoints. Finally, we explored the impact of expression and genomic polymorphism of the signatures on the prognosis at the pan-cancer level. CONCLUSIONS: Our findings underscore the distinct expression patterns of CRGs in esophageal cancer. These signatures are efficient to serve as prognostic indicators and assess the effectiveness of immunotherapy. They may also represent promising targets in other TP53 mutant malignancies.

Humans↗

PubMed2026

Immortal genome assumption significantly underestimates replication and death rates of Mycobacterium tuberculosis in mice and monkeys.

Immune correlates of protection against infection with Mycobacterium tuberculosis (Mtb) or against tuberculosis (TB) remain poorly defined. The ratio of colony forming units (CFUs) to chromosomal equivalents (CEQs), Z = CFUs/CEQs, recovered either from the whole lung (mice) or individual lesions (monkeys or rabbits) of Mtb-infected animals has been used as a metric for how effectively Mtb is killed in vivo. However, the contribution of bacterial killing to changes in the CFU/CEQ ratio during an infection has not been rigorously investigated. We developed alternative mathematical models to study the dynamics of CFUs, CEQs, and their ratio during an Mtb infection. We find that the ratioalone cannot be used to infer the death rate of bacteria, unless the dynamics of CEQs and CFUs are entirely uncoupled, which is biologically unreasonable and inconsistent with the view that CEQs reflect an accumulated burden of both viable and non-viable bacteria. Importantly, we estimate a decay rate of 3.6%/day (a half life of about 20 days) of Mtb H37Rv CEQs in B6 mice that is similar to 4%/day, previously found for Mtb Erdman in cynomolgus macaques. While the estimated Mtb DNA decay rate seems small, we found that estimated rates of Mtb replication and death/killing are still extremely sensitive even to slow decay of Mtb DNA, in part, because Mtb replication and death rates are also small especially during chronic phases of infection. By applying our models to data on Mtb dynamics during the first 3 weeks of infection in macaques, we provide evidence of substantial killing of Mtb bacteria, prior to arrival of adaptive immunity to the site of infection, challenging the previously established notion of non-dying bacteria in the absence of T cell immunity and granuloma formation. We also propose experiments that will allow more accurately to measure the rate of Mtb DNA loss, helping more rigorously quantify impact of immunity on within-host Mtb dynamics.

Mycobacterium tuberculosis↗

PubMed2026

Papillary Thyroid Carcinoma with Terminal Immune Exhaustion Phenotype Correlates with Increased Risk of Lymph Node Metastasis: An Exploratory Study Combining Flow Cytometry and TCGA.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, with lymph node metastasis (LNM) being a key predictor of recurrence and poor prognosis. Preoperative detection of LNM remains challenging due to the limitations of imaging modalities, leading to inadequate surgical resection in 20-30% of patients. While immune checkpoint molecules have been implicated in PTC progression, the heterogeneity of CD8+ T cell exhaustion subsets and their specific association with LNM remain poorly defined. In this study, we aimed to perform an exploratory characterization of the distinct immune landscape of PTC prone to LNM, with a focus on terminal immune exhaustion, in order to generate hypotheses for improved risk stratification and therapeutic strategies. METHODS: Fresh PTC tissues from 40 patients (22 LNM-positive and 18 LNM-negative) were analyzed via flow cytometry (FCM) to quantify immune cell subsets, inflammatory cytokines, and chemokines. Immunohistochemistry (IHC) validated CD45+ immune cell infiltration. Transcriptomic and clinical data from 448 PTC patients in The Cancer Genome Atlas (TCGA-PTC) cohort were used for bioinformatic analysis consistent with the observed phenotype, including Gene Set Variation Analysis (GSVA) of terminal exhaustion gene signatures. RESULTS: LNM-positive PTC exhibited a unique inflammatory milieu with significantly elevated IL-6, IL-1ra, CCL5, and IL-9 levels (all p < 0.05) in tumor interstitial fluid. FCM analysis revealed that LNM-positive PTC had increased infiltration of total CD45+ immune cells, CD3+ T cells, and CD3+CD8+ T cells (all p < 0.05). Critically, terminally exhausted PD-1hiTIM-3+ CD8+ T cells were significantly enriched in LNM-positive PTC (p = 0.022) and positively correlated with extrathyroidal extension (p = 0.044). Additionally, LNM risk was associated with increased CD4+ regulatory T (Treg) cell frequency (p = 0.023) and elevated CTLA-4 expression on CD4+ T cells (p = 0.047). In TCGA-PTC validation, the terminal exhaustion gene signature was predominantly enriched in LNM-positive (p < 0.0001) and advanced-stage PTC (p < 0.001) and strongly correlated with BRAF mutation (predominantly V600E) (p < 0.0001)-the most common oncogenic driver in aggressive PTC. CONCLUSIONS: Our findings suggest a terminal immune exhaustion phenotype (characterized by PD-1hiTIM-3+ CD8+ T cells and Treg enrichment) as a potential key feature associated with LNM-prone PTC. This phenotype shows consistency across clinical samples and TCGA datasets, linking BRAF mutation (predominantly V600E) to immune suppression and metastatic potential. These insights provide a novel exploratory immune-based biomarker for LNM risk stratification and support the potential of combining anti-PD-1/TIM-3 therapy with BRAF inhibitors for high-risk PTC, which should be confirmed in future studies.

lymph node metastasis↗

PubMed2024

ZEB family is a prognostic biomarker and correlates with anoikis and immune infiltration in kidney renal clear cell carcinoma.

BACKGROUND: Zinc finger E-box binding homEeobox 1 (ZEB1) and ZEB2 are two anoikis-related transcription factors. The mRNA expressions of these two genes are significantly increased in kidney renal clear cell carcinoma (KIRC), which are associated with poor survival. Meanwhile, the mechanisms and clinical significance of ZEB1 and ZEB2 upregulation in KIRC remain unknown. METHODS: Through the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, expression profiles, prognostic value and receiver operating characteristic curves (ROCs) of ZEB1 and ZEB2 were evaluated. The correlations of ZEB1 and ZEB2 with anoikis were further assessed in TCGA-KIRC database. Next, miRTarBase, miRDB, and TargetScan were used to predict microRNAs targeting ZEB1 and ZEB2, and TCGA-KIRC database was utilized to discern differences in microRNAs and establish the association between microRNAs and ZEBs. TCGA, TIMER, TISIDB, and TISCH were used to analyze tumor immune infiltration. RESULTS: It was found that ZEB1 and ZEB2 expression were related with histologic grade in KIRC patient. Kaplan-Meier survival analyses showed that KIRC patients with low ZEB1 or ZEB2 levels had a significantly lower survival rate. Meanwhile, ZEB1 and ZEB2 are closely related to anoikis and are regulated by microRNAs. We constructed a risk model using univariate Cox and LASSO regression analyses to identify two microRNAs (hsa-miR-130b-3p and hsa-miR-138-5p). Furthermore, ZEB1 and ZEB2 regulate immune cell invasion in KIRC tumor microenvironments. CONCLUSIONS: Anoikis, cytotoxic immune cell infiltration, and patient survival outcomes were correlated with ZEB1 and ZEB2 mRNA upregulation in KIRC. ZEB1 and ZEB2 are regulated by microRNAs.

Humans↗

PubMed2025

Anoikis classification of lung squamous cell carcinoma reveals correlation with clinical prognosis and immune characteristics.

BACKGROUND: Anoikis is a new mode of cell death that has been shown to correlate significantly with tumors. However, the clinical prognostic significance of anoikis in lung squamous cell carcinoma (LUSC) remains poorly studied. METHODS: The differentially expressed ARGs and candidate genes were selected by the differential analysis to construct a predictive model. Independent prognostic gene was determined by Cox and LASSO analysis and we used the HCC95 and NCI H520 cell line to verify the gene function. We used the data from TCGA, GEO, GeneCards, and Harmonizome databases to analyze the immune microenvironment, functional enrichment, and drug sensitivity analysis. RESULTS: We identified 717 differentially expressed and selected 3 ARGs (FADD, SNAI1, and BAG4) to construct a predictive model. We found that SNAI1 is an independent prognostic gene and confirmed that knocking out the SNAI1 inhibited the HCC95/NCI H520 cell proliferation. We used single-sample gene-set enrichment analysis (ssGSEA) to evaluate the immune infiltration based on the 3 ARG expression levels. We constructed a risk score and provided a visual representation of the prophetic implications of the ARGs-based signature through a nomogram. We found 15 susceptible drugs in the high-risk group and 15 sensitive drugs in the low-risk group by the drug sensitivity analysis. CONCLUSION: We used ARGs to construct a prognosis model for LUSC that can accurately predict the prognosis of LUSC patients. ARGs, especially SNAI1, play an essential role in developing LUSC. These findings could provide individualized treatment plans and new research ideas for LUSC patients.

Humans↗

PubMed2026

Increased IL4I1 expression predicts poor survival and modulates the immune microenvironment in acute myeloid leukemia.

BACKGROUND: The immunometabolic enzyme Interleukin-4-induced-1 (IL4I1) is implicated in cancer pathogenesis, yet its specific function and clinical relevance in acute myeloid leukemia (AML) remain unclear. METHODS: Comparative analysis of IL4I1 mRNA levels between AML patients and normal controls was performed using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The Kaplan–Meier survival analysis was conducted to evaluate the prognostic value of IL4I1. Functional insights were derived from analyses of differentially expressed genes (DEGs), Gene Set Enrichment Analysis (GSEA), and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Immune infiltration was evaluated using the ssGSEA, ESTIMATE, quanTIseq and single-cell RNA sequencing (scRNA-seq) analysis. Finally, in vitro and in vivo functional experiments were perfromed to explore the impact of IL4I1 on AML progression and immunoregulation. RESULTS: IL4I1 expression was significantly elevated in AML compared to normal controls (p = 0.0004) and associated with poorer overall survival (p = 0.003). Bioinformatic analysis revealed that IL4I1 was linked to immune-related pathways—including humoral immune response, leukocyte interactions, and chemokine signaling—and to cellular amino acid metabolism. Its expression correlated with immune cell infiltration and checkpoint molecule expression. Experimentally, IL4I1 promoted leukemia cell proliferation in vitro and in vivo (p < 0.05). Furthermore, silencing IL4I1 suppressed M2 macrophage polarization and reduced secretion of inflammatory factors (p < 0.05). CONCLUSIONS: IL4I1 may serve as a potential biomarker for poor prognosis and an attractive target for immune-based therapeutic interventions in AML.

Humans↗

PubMed2025

Higher Expression of HPV16 Derived E7_LI Transcript Observed in Men With HIV and Recurrent Anal Cancer.

Squamous cell carcinoma of the anus (SCCA) or anal cancer (AC) is an understudied cancer with a high occurrence rate in people with HIV (PWH), especially men having sex with men (MSM). Furthermore, AC recurs in approximately one-fourth of patients who undergo standard care with chemoradiation therapy (CRT). Using bulk RNA sequencing data of AC obtained from 12 patients with non-recurrent (NR, N = 9) or recurrent (R, N = 3) cancer, we previously showed upregulated expression of key immune genes in the NR compared to the R group. Although the main causative agent of AC is high-risk human papillomavirus (HPV), association of host and viral RNA transcript expression contributing to AC recurrence has not been extensively studied. The objective of the current study was to determine whether enrichment of specific HPV genotypes and/or HPV gene expression patterns differentiate the two groups and if any specific viral (HPV) and host (human) immune mediators correlate with each other. Using bulk RNA sequencing data and VIRTUS 2, we detected viral RNA reads mapping to seven high-risk and six low-risk HPV types, of which the high-risk HPV16 observed in 83% (10/12) AC tumors (7/9 NR and 3/3 R). Rate of all HPV genomes trended toward a decrease in NR AC isolates and correlation between HPV types was more commonly observed in low-risk ones. Analysis of HPV 16 gene expression profile showed a significantly lower positivity rate for a polycistronic transcript encoding for E7^L1 in the NR group (1/9, NR vs. 3/3, R, p < 0.05). An unbiased correlation analysis of HPV-human transcript expression showed a direct correlation between HPV transcripts and human genes involved in cell growth. The data also identified human transcripts showing an inverse correlation with HPV gene expression. These included genes involved in negative regulation of growth, proliferation, and immune response. Taken together, these data indicate that concurrent analyses of viral and host factors in the same tumor can identify potential new therapeutic targets to ameliorate cancer recurrence post-treatment.

Humans↗

PubMed2025

The correlation of DPM1 overexpression with immune infiltration and poor prognosis in hepatocellular carcinoma.

BACKGROUND: The DPM1 gene, crucial for glycosylation processes, has shown abnormal expression in various cancers, raising interest in its potential oncogenic role and as a biomarker in hepatocellular carcinoma (HCC). METHODS: Transcriptomic data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. DPM1 expression levels were compared between HCC tissues and adjacent normal tissues. Clinical correlations were assessed using statistical analyses, including survival analysis and multivariate Cox regression. Immune microenvironment profiling was conducted to evaluate associations between DPM1 expression and immune cell infiltration patterns. RESULTS: Elevated DPM1 levels were associated with advanced tumor stages (P < 0.001), higher pathologic T stage (P < 0.001), increased histologic grade (P < 0.001), tumor positivity (P < 0.001), tissue inflammation (P < 0.001), and elevated alpha-fetoprotein levels (AFP > 400 ng/mL, P < 0.05). Multivariate Cox regression analysis identified DPM1 as an independent prognostic factor for reduced overall survival (HR = 1.990, 95% CI 1.390-2.848). Immunological analysis revealed that DPM1 expression was positively correlated with T helper cells (R = 0.268, P < 0.001) and Th2 cells (R = 0.295, P < 0.001), and negatively correlated with plasmacytoid dendritic cells (R=-0.291, P < 0.001) and cytotoxic cells (R=-0.284, P < 0.001). CONCLUSIONS: DPM1 serves as a promising prognostic biomarker in HCC, with its expression correlating with unfavorable clinical outcomes and immune landscape alterations. Future studies should further validate DPM1's impact on ferroptosis and immune evasion in HCC, and explore its potential as a therapeutic target.

DPM1↗

PubMed2026

Identification and evaluation of glutamine-related gene characteristics based on multi-omics to predict the prognosis of patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC), a prevalent malignancy of the gastrointestinal tract, ranks among the leading causes of cancer-related morbidity and mortality. Its clinical course is marked by high fatality and poor prognosis. Elucidating the mechanisms underlying CRC initiation and recurrence is therefore critical for identifying novel therapeutic targets. METHODS: This study incorporated two datasets, TCGA-CRC and GSE17537. A total of 84 glutamine metabolism-related genes (GMRGs) were identified, and differential expression analysis was conducted using the TCGA-CRC dataset. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to determine gene modules most strongly associated with GMRG scores. Single-cell RNA sequencing (scRNA-seq) was utilized to characterize key cellular clusters and to identify differentially expressed genes (DEGs) between high and low glutamine metabolism (GM) groups. Overlapping GMRGs were visualized using the ggVennDiagram package in R. A CRC risk prediction model was developed through Cox proportional hazards and LASSO regression analyses, with performance evaluated by ROC curves. Cell type enrichment across 64 immune and stromal populations was assessed via xCell, and intergroup differences were tested using the Wilcoxon rank-sum test. TIDE scores were used to estimate immunotherapy responsiveness, while oncoPredict facilitated drug sensitivity profiling. PCOLCE2 expression in CRC was validated by RT-qPCR and Western blotting. Its functional role was examined through CCK-8 assays, invasion and migration tests, flow cytometry, and glutamate quantification. RESULTS: ScRNA-seq analysis identified two key cell populations and 437 DEGs associated with GM status. WGCNA pinpointed the MEgreen module as most significantly correlated with GMRG scores, encompassing 1075 genes. Integration of DEGs, module genes, and GM-related DEGs yielded 60 candidate genes for downstream analysis. A GMRG-based prognostic model comprising six genes (SRPX, CXCL1, GPX3, PCOLCE2, CLU, SEMA3E) demonstrated strong predictive performance. Prognostic gene expression correlated with immune and stromal infiltration patterns, as indicated by Spearman correlation analysis. The high-risk group exhibited diminished predicted response to immunotherapy (TIDE scores). Drug sensitivity analysis identified four compounds—Dasatinib-51, WH-4-023-56, TWS-119-366, and LDN-193189-478—with elevated efficacy in high-risk CRC cases. PCOLCE2 expression was significantly reduced in CRC tissues. Functional assays revealed that PCOLCE2 knockdown did not substantially affect cell proliferation but significantly impaired invasion and migration in CRC cells, increased apoptosis, and suppressed both glutamine uptake and glutamate production—highlighting its oncogenic role. CONCLUSION: Six GMRGs—SRPX, CXCL1, GPX3, PCOLCE2, CLU, and SEMA3E—were identified as key components of a robust prognostic model for CRC. These findings offer valuable insights into CRC pathogenesis and potential therapeutic strategies. Notably, this study provides the first evidence implicating PCOLCE2 as a tumor-promoting factor in CRC.

Glutamine↗

PubMed2026

Interindividual variability in immune response to AAV ocular gene delivery across species impedes immunomonitoring.

Adeno-associated viruses (AAVs) have been used in gene therapy, especially for inherited retinal diseases. Despite their effectiveness in gene transduction, immune responses to the AAV capsid and transgene products have been reported, which can compromise both the efficacy and the safety of AAV-mediated therapies. The eye is regarded as an immune-privileged organ where immune activity is constitutively suppressed. Here, we highlight that immunomonitoring in an ocular gene transfer reveals variable immune responses, whatever the species (human clinical trial, nonhuman primates, mice), the site of injection, the cassette, and the dose. We further explored factors contributing to this variability, investigating the potential correlation among immune parameters in a controlled experimental setting. In a syngeneic murine model after a subretinal injection of AAV, our results highlight an interindividual variability of immune parameters, emphasizing the importance of considering inherent variability among individuals when designing personalized therapies.

Animals↗

PubMed2026

Integrated Pan-Cancer, Single-Cell, and Spatial Transcriptomic Analyses Identify ZDHHC12 as a Biomarker Associated with Macrophage Infiltration and the Immune Landscape in Glioma.

BACKGROUND: The tumor immune microenvironment (TME) critically influences cancer progression and therapeutic response. However, the pan-cancer expression landscape, prognostic relevance, and spatial distribution of ZDHHC12 remain incompletely characterized. This study investigated the prognostic value of ZDHHC12 and its associations with immune microenvironmental features and drug sensitivity. METHODS: Data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets were used to evaluate ZDHHC12 expression and prognosis across cancer types. Immune infiltration analyses, single-cell RNA sequencing, and spatial transcriptomics were integrated to characterize the associations of ZDHHC12 with the cancer immunity cycle and the spatial architecture of glioma. Drug sensitivity and immunotherapy-related metrics were assessed using pharmacogenomic databases and computational prediction models. RESULTS: ZDHHC12 was aberrantly expressed across multiple tumors and was associated with patient prognosis. Its expression was broadly correlated with immune cell recruitment- and activation-related signatures. In glioma, single-cell and spatial transcriptomic analyses showed enrichment of ZDHHC12 in monocyte/macrophage populations and spatial co-localization with BAK1, CD68, and CD163. ZDHHC12 expression was also associated with predicted drug sensitivity and immunotherapy-related metrics. CONCLUSION: ZDHHC12 may serve as a candidate pan-cancer prognostic biomarker. In glioma, its expression is associated with macrophage-enriched and immunosuppressive microenvironmental features. Functional studies are required to establish causality and determine its therapeutic relevance.

GBM↗

PubMed2026

Pan-cancer analysis identifies GPRIN1 as a prognostic biomarker and promoter of cell proliferation in pancreatic cancer.

BACKGROUND: G protein-regulated inducer of neurite outgrowth 1 (GPRIN1), an emerging modulator of GPCR signaling, has been implicated in oncogenesis. However, its comprehensive role across human cancers, particularly in reshaping the tumor microenvironment (TME), remains poorly characterized. We aimed to elucidate the pan-cancer significance of GPRIN1 in TME modulation and its therapeutic implications. METHODS: We analyzed multi-omics data from TCGA and other public databases, performing a systematic analysis of GPRIN1 regarding expression, prognosis, immune infiltration, and genomic instability across 33 cancer types. To validate these bioinformatic findings, we performed lentiviral shRNA-mediated knockdown in pancreatic (PANC-1) and hepatic (HepG2) cancer cells to assess proliferation and migration. Crucially, the clinical relevance of GPRIN1 was further validated in an independent cohort of pancreatic cancer patients (N = 17) using immunohistochemistry (IHC). RESULTS: The analysis identified a lineage-dependent expression pattern. Epithelial tumors exhibited upregulation, whereas glioblastoma samples displayed downregulation. GPRIN1 expression consistently correlated with immune subtypes and CD8+ T cell abundance. In vitro assays demonstrated that GPRIN1 depletion significantly inhibited cell proliferation and migration (P < 0.0001). In the clinical validation cohort, multivariate Cox regression analysis identified high GPRIN1 protein levels as an independent predictor of post-operative recurrence. These patients also showed a trend toward extended overall survival. CONCLUSIONS: These findings define GPRIN1 as a context-dependent regulator of the TME. By integrating computational and experimental data, this study supports GPRIN1 as a potential biomarker for risk assessment in pancreatic cancer.

Humans↗

PubMed2026

ERP44 Is Associated With Poor Prognosis and Promotes Proliferation and Temozolomide Resistance in Lower-grade Glioma.

BACKGROUND/AIM: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: ERP44 is a prognostic biomarker that promotes LGG proliferation and TMZ resistance, suggesting its potential as a therapeutic target.

Humans↗