Enhancing antitumor immunity and achieving tumor eradication with IL11RA mRNA immunotherapy.

Current methods for delivering genes to target tumors face significant challenges, including off-target effects and immune responses against delivery vectors. In this study, we developed a novel approach using messenger RNA (mRNA) to encode IL11RA for local immunotherapy, aiming to harness the immune system to combat tumors. Our research uncovered a compelling correlation between IL11RA expression and CD8 + T cell levels across multiple tumor types, with elevated IL11RA expression correlating with improved overall survival. Examination of the Pan-Cancer Atlas dataset showed a significant reduction in IL11RA expression in various cancer types compared to normal tissue, raising questions about its potential role in tumorigenesis. To achieve efficient in vivo expression of IL11RA, we synthesized two mRNA sequences mimicking the wild-type protein. These mRNA sequences were formulated and capped to ensure effective delivery, resulting in robust expression within tumor sites. Our investigation into IL11RA mRNA therapy demonstrated its effectiveness in controlling tumor growth when administered both intratumorally and intravenously in mouse models. Additionally, IL11RA mRNA treatment significantly stimulated the expansion of CD8 + T cells within tumors, draining lymph nodes, and the spleen. Transcriptome analysis revealed distinct transcriptional patterns associated with T cell functions. Using multiple deconvolution algorithms, we found substantial infiltration of CD8 + T cells following IL11RA mRNA treatment, highlighting its immunomodulatory effects within the tumor microenvironment. In conclusion, IL11RA mRNA therapy presents a promising strategy for tumor regression with potential immunomodulatory effects and clinical implications for improved survival outcomes.

Identifying the Crucial Biomarker of MASH-Related HCC.

OBJECTIVES: This study aimed to explore the key oncogenic factor of metabolicassociated steatohepatitis (MASH) to hepatocellular carcinoma (HCC). METHODS: We utilized four differential GEO datasets (GSE164760, GSE139602, GSE197112, and GSE49541) to identify the key oncogenic factor for MASH-related HCC. The differential genes were analyzed using the GEO2R algorithm online. The GEPIA online website was used to explore the expression of selected four genes (SPP1, GNMT, CLDN11, and THBS2). The genetic alterations in genes were estimated by the cBioPortal website. The Kaplan-Meier Plotter online database was applied to explore the prognostic value of SPP1. Univariate and multivariate Cox analyses were carried out to further confirm the prognostic value of SPP1. The GO and KEGG enrichment analysis exported associated pathways with SPP1 expression. The positively or negatively related immune cells and immune checkpoint expressions were identified through Pearson correlation analysis. The lipogenesis-associated proteins were detected using western blotting and fluorescence. The high-fat diet (HFD) mouse model was constructed, and liver samples were collected. RESULTS: SPP1, GNMT, CLDN11, and THBS2 were determined in the transformation process of MASH to liver fibrosis. SPP1 and GNMT were upregulated in the HCC tumor tissue. SPP1, in particular, had the potential to be the prognostic factor through Cox analysis. Remarkably, SPP1 was highly expressed in HCC compared to normal tissues in three independent datasets (GSE121248, GSE14520, and GSE45267). SPP1 is mainly involved in the amplification and deep deletion mutations. SPP1 was found to be strongly correlated with ANXA2 expression, and ANXA2 was also highly expressed in HCC with significant prognostic performance. Moreover, SPP1 was found to participate in the carcinogenic mechanism and correlate with immune cells and immune checkpoint expression. SPP1 knockdown suppressed the SREBP1 and FASN expressions and increased the SIRT1 expression in vitro. Moreover, the HFD model validated the upregulation of SPP1 in the fatty liver in vivo. CONCLUSION: SPP1 may be the key oncogenic factor for the transformation of MASH to HCC, and it could be a potential immunotherapeutic target in HCC.

Prediction of severe hypertriglyceridemia-associated acute pancreatitis using a nomogram based on CT findings and blood biomarkers.

Hypertriglyceridemia is a common cause of acute pancreatitis (AP). Fatty liver, a manifestation of metabolic syndrome, is related to the severity of AP. The present study aimed to construct an accurate predictive model for severe AP (SAP) by combining the fatty liver infiltration on a computerized tomography (CT) scan with a series of blood biomarkers in patients with hypertriglyceridemia-associated AP (HTG-AP). A total of 213 patients diagnosed with HTG-AP were included in the present retrospective study. Clinical information and imageological findings were retrospectively analyzed. The model was constructed from independent risk factors using univariate analysis, the least absolute shrinkage and selection operator method. Subsequently, the data from the training group of 111 patients with HTG-AP was analyzed using logistic regression analysis. The efficacy of the model was verified using an external validation group of 102 patients through the receiver operating characteristic curve (ROC). Independent predictors, including serum calcium, C-reactive protein, lactate dehydrogenase and liver-to-spleen CT attenuation ratio (L/S ratio), were incorporated into the nomogram model for SAP in HTG-AP. The model achieved a sensitivity of 91.3% and a specificity of 88.6% in the training group. Compared with the Ranson model, the established nomogram model exhibited a better discriminative ability in the training group [area under the curve (AUC): 0.957] and external validation group (AUC: 0.930), as well as better calibration and clinical benefits. The present study demonstrates that the constructed nomogram based on CT findings and blood biomarkers is useful for the accurate prediction of SAP in HTG-AP.

Unlocking hepatocellular carcinoma aggression: STAMBPL1-mediated TRAF2 deubiquitination activates WNT/PI3K/NF-kb signaling pathway.

STAM Binding Protein Like 1 (STAMBPL1), functions as a deubiquitinase (DUB) and plays a significant role in various types of cancers. However, its effect as a DUB participating in the HCC tumorigenesis and progression still unknown. In the study, the upregulation and strong prognosis value of STAMBPL1 were identified in HCC patients. Functionally, STAMBPL1 significantly promoted HCC cells proliferation and metastasis, and it interacts with TRAF2 and stabilize it via the deubiquitination at the K63 residue. The TRAF2 upregulation stabilized by STAMBPL1 overexpression transfers of P65 protein into the nucleus and activates the WNT/PI3K/ NF-kb signaling pathway. The 251-436 sites of STAMBPL1 particularly interact with the 294-496 sites of TRAF2, thereby exerting the function of DUB and removing the ubiquitin molecules attached to TRAF2. Our research unveiled a new function of STAMBPL1 in mediating TRAF2 deubiquitination and stabilization, thereby activating the WNT/PI3K/NF-kb signaling pathway, suggesting its potential as a novel biomarker and therapeutic target for HCC.

The Biological Function of POLA2 in Hepatocellular Carcinoma.

INTRODUCTION: The role and prognostic value of POLA2 in liver cancer were comprehensively analyzed through TCGA, GEO, and ICGC databases, and the role of POLA2 in liver cancer cells and the regulatory mechanism involved were further verified through cell experiments. Hepatocellular carcinoma (HCC) is the most prevalent malignancy with high morbidity and mortality. Consequently, it is critical to identify robust and reliable predictive biomarkers and therapeutic targets for HCC patients. POLA2 is involved in the regulation of various tumors, but the specific role of POLA2 in HCC has not been reported. The regulatory role and prognostic value of POLA2 in HCC were determined by bioinformatics techniques and cell experiments. METHOD: The specific role and prognostic value of POLA2 in HCC were comprehensively analyzed by combining the expression data of POLA2 in TCGA, GEO, and ICGC databases and clinical data. In clinical samples, the expression of POLA2 in liver cancer was verified by QPCR. Further, the regulatory role of POLA2 in HCC was explored through cell experiments such as CCK-8, clonal formation experiment, EDU cell proliferation experiment, and flow cytometry. In terms of mechanism exploration, western blot was used to verify the specific regulatory mechanism that POLA2 participated in. Finally, the relationship between POLA2 and immune invasion of HCC was analyzed by using the TIMER database. RESULT: A POLA2 expression and prognosis analysis of HCC patients was conducted using the TCGA, GEO, and ICGC databases. We hypothesized that POLA2 might be one of the key factors contributing to the HCC progression. According to a combined analysis of TCGA, ICGC, and GEO databases, POLA2 was highly expressed in HCC. This was further confirmed in clinical samples using the qPCR. POLA2 knockdown was also performed in vitro on HCC cell lines to study the changes in their biological behavior. We confirmed that POLA2 was associated with HCC proliferation by CCK-8, Colony Formation, and EDU assay. We verified the POLA2's involvement in cell cycle regulation using flow techniques. The relationship between POLA2 and PI3K/AKT/mTOR pathway was explored using Western Blotting experiments regarding its mechanism. Further analysis revealed that the POLA2 expression was significantly associated with HCC immune infiltration. CONCLUSION: Our study demonstrated POLA2's importance in HCC development and progression and its potential role as a biomarker for disease progression on multiple levels. POLA2 has an important role in regulating the cell cycle and cell proliferation. By interfering with the cell cycle and proliferation, HCC cell growth is inhibited. Furthermore, POLA2 expression was significantly associated with immune infiltration. POLA2 may play a role in HCC immunotherapy based on its correlation with several immune cell types' genetic markers. The findings of this study are expected to lead to new anticancer strategies for HCC.

Long noncoding RNA MyD88 functions as a promising diagnostic biomarker in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most frequent malignancies. Alpha-fetoprotein (AFP) has some limitations in diagnosing early HCC. Recently, long noncoding RNAs (lncRNAs) showed great potential as tumor diagnostic biomarkers, and lnc-MyD88 was previously identified as a carcinogen in HCC. Here, we explored its diagnostic value as a plasma biomarker. Materials and methods: Quantitative real-time PCR was adopted to detect lnc-MyD88 expression in plasma samples of 98 HCC patients, 52 liver cirrhosis (LC) patients, and 105 healthy people. The correlation between lnc-MyD88 and clinicopathological factors was analyzed through chi-square test. The receiver operating characteristic (ROC) curve was used to analyze the sensitivity, specificity, Youden index, and area under the curve (AUC) of lnc-MyD88 and AFP alone and in combination for the diagnosis of HCC. The relationship between MyD88 and immune infiltration was analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm. Results: Lnc-MyD88 was highly expressed in plasma samples of HCC and hepatitis B virus (HBV)-associated HCC patients. Lnc-MyD88 had better diagnostic value than AFP in HCC patients using healthy people or LC patients as control (healthy people, AUC: 0.776 vs. 0.725; LC patients, AUC: 0.753 vs. 0.727). The multivariate analysis showed that lnc-MyD88 had great diagnostic value for distinguishing HCC from LC and healthy people. Lnc-MyD88 had no correlation with AFP. Lnc-MyD88 and AFP were independent diagnostic factors for HBV-associated HCC. The AUC, sensitivity, and Youden index of the combined diagnosis of lnc-MyD88 and AFP combined were higher than those of lnc-MyD88 and AFP alone. The ROC curve of lnc-MyD88 for the diagnosis of AFP-negative HCC was plotted with a sensitivity of 80.95%, a specificity of 79.59%, and an AUC value of 0.812 using healthy people as control. The ROC curve also presented its great diagnostic value using LC patients as control (sensitivity: 76.19%, specificity: 69.05%, AUC value: 0.769). Lnc-MyD88 expression was correlated with microvascular invasion in HBV-associated HCC patients. MyD88 was positively correlated with infiltrating immune cells and immune-related genes. Conclusion: The high expression of plasma lnc-MyD88 in HCC is distinct and could be utilized as a promising diagnostic biomarker. Lnc-MyD88 had great diagnostic value for HBV-associated HCC and AFP-negative HCC, and it had higher efficacy in combination with AFP.

ARHGAP21 Is Involved in the Carcinogenic Mechanism of Cholangiocarcinoma: A Study Based on Bioinformatic Analyses and Experimental Validation.

Background and Objectives: Rho GTPase-activating protein (RhoGAP) is a negative regulatory element of Rho GTPases and participates in tumorigenesis. Rho GTPase-activating protein 21 (ARHGAP21) is one of the RhoGAPs and its role in cholangiocarcinoma (CCA) has never been disclosed in any publications. Materials and Methods: The bioinformatics public datasets were utilized to investigate the expression patterns and mutations of ARHGAP21 as well as its prognostic significance in CCA. The biological functions of ARHGAP21 in CCA cells (RBE and Hccc9810 cell) were evaluated by scratch assay, cell counting kit-8 assay (CCK8) assay, and transwell migration assay. In addition, the underlying mechanism of ARHGAP21 involved in CCA was investigated by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and the most significant signaling pathway was identified through gene set enrichment analysis (GSEA) and the Western blot method. The ssGSEA algorithm was further used to explore the immune-related mechanism of ARHGAP21 in CCA. Results: The ARHGAP21 expression in CCA tissue was higher than it was in normal tissue, and missense mutation was the main alteration of ARHGAP21 in CCA. Moreover, the expression of ARHGAP21 had obvious differences in patients with different clinical characteristics and it had great prognostic significance. Based on cell experiments, we further observed that the proliferation ability and migration ability of the ARHGAP21-knockdown group was reduced in CCA cells. Several pathological signaling pathways correlated with proliferation and migration were determined by GO and KEGG analysis. Furthermore, the PI3K/Akt signaling pathway was the most significant one. GSEA analysis further verified that ARHGAP21 was highly enriched in PI3K/Akt signaling pathway, and the results of Western blot suggested that the phosphorylated PI3K and Akt were decreased in the ARHGAP21-knockdown group. The drug susceptibility of the PI3K/Akt signaling pathway targeted drugs were positively correlated with ARHGAP21 expression. Moreover, we also discovered that ARHGAP21 was correlated with neutrophil, pDC, and mast cell infiltration as well as immune-related genes in CCA. Conclusions: ARHGAP21 could promote the proliferation and migration of CCA cells by activating the PI3K/Akt signaling pathway, and ARHGAP21 may participate in the immune modulating function of the tumor microenvironment.

PI3K/AKT/mTOR Pathway-Associated Genes Reveal a Putative Prognostic Signature Correlated with Immune Infiltration in Hepatocellular Carcinoma.

Background: The dysregulated PI3K/AKT/mTOR pathway acts as the main regulator of tumorigenesis in hepatocellular carcinoma (HCC). Aim: Here, we identify the prognostic significance of PI3K/AKT/mTOR pathway-associated genes (PAGs) as well as their putative signature based on PAGs in an HCC patient's cohort. Methods: The transcriptomic data and clinical feature sets were queried to extract the putative prognostic signature. Results: We identified nine PAGs with different expressions. GO and KEGG indicated that these differentially expressed genes were associated with various carcinogenic pathways. Based on the signature-computed median risk score, we categorized the patients into groups of low risk and high risk. The survival time for the low-risk group is longer than that of the high-risk group in Kaplan-Meier (KM) curves. The prognostic value of risk score (ROC = 0.736) of receiver operating characteristic (ROC) curves performed better in comparison to that of other clinicopathological features. In both the GEO database and ICGC database, these outcomes were verified. The predictions of the overall survival rates in HCC patients of 1 year, 3 years, and 5 years can be obtained separately from the nomogram. The risk score was associated with the immune infiltrations of CD8 T cells, activated CD4 memory T cells, and follicular helper T cells, and the expression of immune checkpoints (PD-1, TIGIT, TIM-3, BTLA, LAG-3, and CTLA4) was positively relevant to the risk score. The sensitivity to several chemotherapeutic drugs can also be revealed by the signature. CDK1, PITX2, PRKAA2, and SFN were all upregulated in the tumor tissue of clinical samples. Conclusion: A putative and differential dataset-validated prognostic signature on the basis of integrated bioinformatic analysis was established in our study, providing the immunotherapeutic targets as well as the personalized treatment in HCC with neoteric insight.

The biological behavior of tRNA-derived fragment tRF-Leu-AAG in pancreatic cancer cells.

Pancreatic cancer (PC) is a life-threatening cancer with increasing incidence in developed countries. Reports indicate that tRNA-derived fragments (tRFs) are possible therapeutic targets and biomarkers for cancer treatment. Nonetheless, the effect of tRF-Leu-AAG on PC is unclear. This study aims to explore the role of tRF-Leu-AAG and upstream frameshift mutant 1 (UPF1) in the development of PC and its potential underlying mechanisms. High-throughput second-generation sequencing techniques were used to detect the expression of tRFs in cancerous and adjacent normal tissues from PC patients. The role of tRF-Leu-AAG proliferation in PC cells was investigated via the Cell Counting Kit-8 (CCK8) assay. The effect of tRF-Leu-AAG on the invasion and migration ability of PC cells was also determined by the transwell assay. Thereafter, the downstream target genes of tRF-Leu-AAG were comprehensively predicted using bioinformatics analysis databases. We also used the Dual-Luciferase Reporter assay to assess the nexus between tRF-Leu-AAG and UPF1. Eventually, Western Blot was used to validate the expression of UPF1 in PC cells. A total of 33 tRF expressions significantly varied from PC patients. RT-qPCR confirmed that the expression of tRF-Leu-AAG was observably up-regulated in PC cells as compared to the control cells. Importantly, knockdown of tRF-Leu-AAG observably inhibited cell proliferation, migration, and invasion. Furthermore, according to the predicted frameshift database results, the UPF1 acted as downstream target genes for tRF-Leu-AAG and significantly down-regulated UPF1 expression.

DOK5 as a Prognostic Biomarker of Gastric Cancer Immunoinvasion: A Bioinformatics Analysis.

BACKGROUND: Docking protein 5 (DOK5) is a member of the docking protein group of membrane proteins and is an adapter protein involved in signal transduction. Nevertheless, the role of DOK5 expression in the prognosis of gastric cancer (GC) remains unclear. METHODS: In this study, clinical prognostic parameters and survival data related to DOK5, in patients with GC, were analyzed using bioinformatics analysis comprising Oncomine and TIMER, UALCAN database, Kaplan-Meier plotter, GEPIA, GSEA, DAVID, and cBioPortal websites. RESULTS: In our study, GC contained various DOK5 expressions, which forecasted poor survival outcomes. Moreover, our research showed that high DOK5 could predict high-level infiltration of several GC immune cells, as evidenced by M1, TAM, M2, B cell, and T cell failure. Hence, DOK5 might become a new gastric cancer biomarker and therapeutic target. In the following analysis, in order to explore the prognostic value of DOK5 in GC, more clinical trials are needed to validate our results. CONCLUSIONS: Through multiple database verifications, DOK5 was found to be part of the pathogenic genes for GC. Thus, it can change the formation and progression of tumors by acting on human immunity.

Identification of CDC20 as an immune infiltration-correlated prognostic biomarker in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. E3 ubiquitin-protein ligases play essential roles in HCC, such as regulating progression, migration, and metastasis. We aimed to explore a hub E3 ubiquitin-protein ligase gene and verify its association with prognosis and immune cell infiltration in HCC. Cell division cycle 20 (CDC20) was identified as a hub E3 ubiquitin-protein ligase in HCC by determining the intersecting genes in a protein-protein interaction (PPI) network of differentially expressed genes (DEGs) using HCC data from the International Cancer Genome Consortium (ICGC) and the gene list of 919 E3 ubiquitin-protein ligases. DEGs and their correlations with clinicopathological features were explored in The Cancer Genome Atlas (TCGA), ICGC, and Gene Expression Omnibus (GEO) databases via the Wilcoxon signed-rank test. The prognostic value of CDC20 was illustrated by Kaplan-Meier (K-M) curves and Cox regression analyses. Subsequently, the correlation between CDC20 and immune infiltration was demonstrated via the Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA). CDC20 expression was significantly higher in HCC than in normal tissues (all P < 0.05). High CDC20 expression predicted a poor prognosis and might be an independent risk factor in HCC (P < 0.05). Additionally, CDC20 was correlated with the immune infiltration of CD8 + T cells, T cells (general), monocytes, and exhausted T cells. This study reveals the potential prognostic value of CDC20 in HCC and demonstrates that CDC20 may be an immune-associated therapeutic target in HCC because of its correlation with immune infiltration.

CDCA3 Is a Novel Prognostic Biomarker Associated with Immune Infiltration in Hepatocellular Carcinoma.

Cell division cycle-associated protein-3 (CDCA3) contributes to the regulation of the cell cycle. CDCA3 plays an important role in the carcinogenesis of various cancers; however, the association between CDCA3 expression, prognosis of patients, and immune infiltration in the tumor microenvironment is still unknown. Here, we demonstrated that CDCA3 was differentially expressed between the tumor tissues and corresponding normal tissues using in silico analysis in the ONCOMINE and Tumor Immune Estimation Resource (TIMER) databases. We analyzed the relationship between the expression of CDCA3 and prognosis of patients with hepatocellular carcinoma (HCC) using the Kaplan-Meier plotter database and Gene Expression Profiling Interactive Analysis (GEPIA). Furthermore, we determined the prognostic value of CDCA3 expression using univariate and multivariate analyses. We observed that CDCA3 expression closely correlated with immune infiltration and gene markers of infiltrating immune cells in the TIMER database. CDCA3 was highly expressed in the tumor tissues than in the adjacent normal tissues in various cancers, including HCC. Increased expression of CDCA3 was accompanied by poorer overall survival (OS), relapse-free survival (RFS), progression-free survival (PFS), and disease-specific survival (DSS). The correlation between CDCA3 expression and OS and disease-free survival (DFS) was also studied using GEPIA. CDCA3 expression was associated with the levels of immune cell infiltration and was positively correlated with tumor purity. Moreover, CDCA3 expression was associated with gene markers such as PD-1, CTLA4, LAG3, and TIM-3 from exhausted T cells, CD3D, CD3E, and CD2 from T cells, and TGFB1 and CCR8 located on the surface of Tregs. Thus, we demonstrated that CDCA3 may be a potential target and biomarker for the management and diagnosis of HCC.