Cytolytic Activity of Effector T-lymphocytes Against Hepatocellular Carcinoma is Improved by Dendritic Cells Pulsed with Pooled Tumor Antigens

Anoikis-related lncRNA signature predicts prognosis and is associated with immune infiltration in hepatocellular carcinoma

Anoikis is a programmed cell death process triggered when cells are dislodged from the extracellular matrix. Numerous long noncoding RNAs (lncRNAs) have been identified as significant factors associated with anoikis resistance in various tumor types, including glioma, breast cancer, and bladder cancer. However, the relationship between lncRNAs and the prognosis of hepatocellular carcinoma (HCC) has received limited research attention. Further research is needed to investigate this potential link and understand the role of lncRNAs in the progression of HCC. We developed a prognostic signature based on the differential expression of lncRNAs implicated in anoikis in HCC. A co-expression network of anoikis-related mRNAs and lncRNAs was established using data obtained from The Cancer Genome Atlas (TCGA) for HCC. Cox regression analyses were conducted to formulate an anoikis-related lncRNA signature (ARlncSig) in a training cohort, which was subsequently validated in both a testing cohort and a combined dataset comprising the two cohorts. Receiver operating characteristic curves, nomograms, and decision curve analyses based on the ARlncSig score and clinical characteristics demonstrated robust predictive ability. Moreover, gene set enrichment analysis revealed significant enrichment of several immune processes in the high-risk group compared to the low-risk group. Furthermore, significant differences were observed in immune cell subpopulations, expression of immune checkpoint genes, and response to chemotherapy and immunotherapy between the high- and low-risk groups. Lastly, we validated the expression levels of the five lncRNAs included in the signature using quantitative real-time PCR. In conclusion, our ARlncSig model holds substantial predictive value regarding the prognosis of HCC patients and has the potential to provide clinical guidance for individualized immunotherapy. In this study, we obtained 36 genes associated with anoikis from the Gene Ontology and Gene Set Enrichment Analysis databases. We also identified 22 differentially expressed lncRNAs that were correlated with these genes using data from TCGA. Using Cox regression analyses, we developed an ARlncSig in a training cohort, which was then validated in both a testing cohort and a combined cohort comprising data from both cohorts. Additionally, we collected eight pairs of liver cancer tissues and adjacent tissues from the Affiliated Tumor Hospital of Nantong University for further analysis. The aim of this study was to investigate the potential of ARlncSig as a biomarker for liver cancer prognosis. The study developed a risk stratification system called ARlncSig, which uses five lncRNAs to categorize liver cancer patients into low- and high-risk groups. Patients in the high-risk group exhibited significantly lower overall survival rates compared to those in the low-risk group. The model's predictive performance was supported by various analyses including the receiver operating characteristic curve, nomogram calibration, clinical correlation analysis, and clinical decision curve. Additionally, differential analysis of immune function, immune checkpoint, response to chemotherapy, and immune cell subpopulations revealed significant differences between the high- and low-risk groups. Finally, quantitative real-time PCR validated the expression levels of the five lncRNAs. In conclusion, the ARlncSig model demonstrates critical predictive value in the prognosis of HCC patients and may provide clinical guidance for personalized immunotherapy.

Machine learning-based disulfidptosis-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity in hepatocellular carcinoma

Disulfidptosis a new cell death mode, which can cause the death of Hepatocellular Carcinoma (HCC) cells. However, the significance of disulfidptosis-related Long non-coding RNAs (DRLs) in the prognosis and immunotherapy of HCC remains unclear. Based on The Cancer Genome Atlas (TCGA) database, we used Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression model to construct DRL Prognostic Signature (DRLPS)-based risk scores and performed Gene Expression Omnibus outside validation. Survival analysis was performed and a nomogram was constructed. Moreover, we performed functional enrichment annotation, immune infiltration and drug sensitivity analyses. Five DRLs (AL590705.3, AC072054.1, AC069307.1, AC107959.3 and ZNF232-AS1) were identified to construct prognostic signature. DRLPS-based risk scores exhibited better predictive efficacy of survival than conventional clinical features. The nomogram showed high congruence between the predicted survival and observed survival. Gene set were mainly enriched in cell proliferation, differentiation and growth function related pathways. Immune cell infiltration in the low-risk group was significantly higher than that in the high-risk group. Additionally, the high-risk group exhibited higher sensitivity to Afatinib, Fulvestrant, Gefitinib, Osimertinib, Sapitinib, and Taselisib. In conclusion, our study highlighted the potential utility of the constructed DRLPS in the prognosis prediction of HCC patients, which demonstrated promising clinical application value.

Lymph node and tumor-associated PD-L1+ macrophages antagonize dendritic cell vaccines by suppressing CD8+ T cells

Current immunotherapies provide limited benefits against T cell-depleted tumors, calling for therapeutic innovation. Using multi-omics integration of cancer patient data, we predict a type I interferon (IFN) responseHIGH state of dendritic cell (DC) vaccines, with efficacious clinical impact. However, preclinical DC vaccines recapitulating this state by combining immunogenic cancer cell death with induction of type I IFN responses fail to regress mouse tumors lacking T cell infiltrates. Here, in lymph nodes (LNs), instead of activating CD4+/CD8+ T cells, DCs stimulate immunosuppressive programmed death-ligand 1-positive (PD-L1+) LN-associated macrophages (LAMs). Moreover, DC vaccines also stimulate PD-L1+ tumor-associated macrophages (TAMs). This creates two anatomically distinct niches of PD-L1+ macrophages that suppress CD8+ T cells. Accordingly, a combination of PD-L1 blockade with DC vaccines achieves significant tumor regression by depleting PD-L1+ macrophages, suppressing myeloid inflammation, and de-inhibiting effector/stem-like memory T cells. Importantly, clinical DC vaccines also potentiate T cell-suppressive PD-L1+ TAMs in glioblastoma patients. We propose that a multimodal immunotherapy and vaccination regimen is mandatory to overcome T cell-depleted tumors.

Boron Derivatives Inhibit the Proliferation of Breast Cancer Cells and Affect Tumor-Specific T Cell Activity In Vitro by Distinct Mechanisms

Breast cancer is the most frequently diagnosed cancer among women worldwide. Despite the initial clinical response obtained with the widely used conventional chemotherapy, an improved prognosis for breast cancer patients has been missing in the clinic because of the high toxicity to normal cells, induction of drug resistance, and the potential immunosuppressive effects of these agents. Therefore, we aimed to investigate the potential anti-carcinogenic effect of some boron derivatives (sodium pentaborate pentahydrate (SPP) and sodium perborate tetrahydrate (SPT)), which showed a promising effect on some types of cancers in the literature, on breast cancer cell lines, as well as immuno-oncological side effects on tumor-specific T cell activity. These findings suggest that both SPP and SPT suppressed proliferation and induced apoptosis in MCF7 and MDA-MB-231 cancer cell lines through downregulation of the monopolar spindle-one-binder (MOB1) protein. On the other hand, these molecules increased the expression of PD-L1 protein through their effect on the phosphorylation level of Yes-associated protein (Phospho-YAP (Ser127). In addition, they reduced the concentrations of pro-inflammatory cytokines such as IFN-γ and cytolytic effector cytokines such as sFasL, perforin, granzyme A, Granzyme B, and granulysin and increased the expression of PD-1 surface protein in activated T cells. In conclusion, SPP, SPT, and their combination could have growth inhibitory (antiproliferative) effects and could be a potential treatment for breast cancer. However, their stimulatory effects on the PD-1/PD-L1 signaling pathway and their effects on cytokines could ultimately account for the observed repression of the charging of specifically activated effector T cells against breast cancer cells.

Innovative molecular subtypes of multiple signaling pathways in colon cancer and validation of FMOD as a prognostic-related marker

PURPOSE

Colon cancer is highly heterogeneous in terms of the immune and stromal microenvironment, genomic integrity, and oncogenic properties; therefore, molecular subtypes of the four characteristic dimensions are expected to provide novel clues for immunotherapy of colon cancer.

METHODS

According to the enrichment of four dimensions, we performed consensus cluster analysis and identified three robust molecular subtypes for colon cancer, namely immune enriched, immune deficiency, and stroma enriched. We characterized and validated the immune infiltration, gene mutations, copy number variants, methylation, protein expression, and clinical features in different datasets. Finally, we developed an 8-gene risk prognostic model and proposed the innovative RiskScore. In addition, a nomogram model was constructed combining clinical characteristics and RiskScore to validate its excellent clinical predictive power.

RESULTS

Combining clinical patient tissue samples and histochemical microarray data, we found that high FMOD expression in tumor epithelial cells was associated with poorer patient prognosis, but FMOD expression in the mesenchyme was not associated with prognosis. In pan-cancer, RiskScore, a prognostic model constructed based on characteristic pathway scores, was a poor prognostic factor for malignancy and was negatively associated with immunotherapy response.

CONCLUSION

The identification of molecular subtypes could provide innovative ideas for immunotherapy of colon cancer.

Dendritic-Cell-Vaccine-Based Immunotherapy for Hepatocellular Carcinoma: Clinical Trials and Recent Preclinical Studies

Although many surgical and nonsurgical therapeutic options have been well-established, hepatocellular carcinoma (HCC) remains the third most common cause of cancer-related death worldwide. Therefore, the discovery of novel potential therapeutic strategies is still urgently required for improving survival and prognosis of HCC patients. As the most potent antigen-presenting cells in the human immune system, dendritic cells (DCs) play an important role in activating not only innate but also adaptive immune responses to specifically destroy tumor cells. As a result, DC-based vaccines, which are prepared by different tumor-antigen-pulsing strategies or maturation-stimulating reagents, either alone or in combination with various anticancer therapies and/or immune effector cells, have been developed as a promising personalized cancer immunotherapy. This review provides a comprehensive summary of the evidence from clinical trials evaluating the safety, feasibility, and efficacy of DC-based vaccines in treating HCC patients and highlights the data from recent preclinical studies regarding the development of promising strategies for optimizing the efficacy of DC-vaccine-based immunotherapy for HCC.

Identification of HLA-A2 restricted epitopes of glypican-3 and induction of CTL responses in HLA-A2 transgenic mice

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality, but lacks effective treatments. Carcinoembryonic antigen glypican-3 (GPC3) is a tumor-associated antigen overexpressed in HCC but rarely expressed in healthy individuals and thus is one of the most promising therapeutic targets. T cell epitope-based vaccines may bring light to HCC patients, especially to the patients at a late stage. However, few epitopes from GPC3 were identified to date, which limited the application of GPC3-derived epitopes in immunotherapy and T cell function detection. In this study, a total of 25 HLA-A0201 restricted GPC3 epitopes were in silico predicted and selected as candidate epitopes. Then, HLA-A0201⁺/GPC3⁺ HCC patients' PBMCs were collected and co-stimulated with the candidate epitope peptides in ex vivo IFN-γ Elispot assay, by which five epitopes were identified as real-world epitopes. Their capacity to elicit specific CD8⁺ T cells activation and proliferation was further confirmed by in vitro co-cultures of patients' PBMCs with peptide, in vitro co-cultures of healthy donors' PBLs with DCs and peptide, T2 cell binding assay as well as HLA-A2 molecule stability assay. Moreover, the in vivo immunogenicity of the five validated epitopes was confirmed by peptides cocktail/poly(I:C) vaccination in HLA-A0201/DR1 transgenic mice. Robust epitope-specific CD8⁺ T cell responses and cytotoxicity targeting HepG2 cells were observed as detected by IFN-γ Elispot, intracellular IFN-γ staining and cytolysis assay. This study provided novel GPC3 CTL epitopes for the development of T cell epitope vaccines and evaluation of GPC3 specific T cell responses.

Atypical immunometabolism and metabolic reprogramming in liver cancer: Deciphering the role of gut microbiome

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality worldwide. Much recent research has delved into understanding the underlying molecular mechanisms of HCC pathogenesis, which has revealed to be heterogenous and complex. Two major hallmarks of HCC include: (i) a hijacked immunometabolism and (ii) a reprogramming in metabolic processes. We posit that the gut microbiota is a third component in an entanglement triangle contributing to HCC progression. Besides metagenomic studies highlighting the diagnostic potential in the gut microbiota profile, recent research is pinpointing the gut microbiota as an instigator, not just a mere bystander, in HCC. In this chapter, we discuss mechanistic insights on atypical immunometabolism and metabolic reprogramming in HCC, including the examination of tumor-associated macrophages and neutrophils, tumor-infiltrating lymphocytes (e.g., T-cell exhaustion, regulatory T-cells, natural killer T-cells), the Warburg effect, rewiring of the tricarboxylic acid cycle, and glutamine addiction. We further discuss the potential involvement of the gut microbiota in these characteristics of hepatocarcinogenesis. An immediate highlight is that microbiota metabolites (e.g., short chain fatty acids, secondary bile acids) can impair anti-tumor responses, which aggravates HCC. Lastly, we describe the rising 'new era' of immunotherapies (e.g., immune checkpoint inhibitors, adoptive T-cell transfer) and discuss for the potential incorporation of gut microbiota targeted therapeutics (e.g., probiotics, fecal microbiota transplantation) to alleviate HCC. Altogether, this chapter invigorates for continuous research to decipher the role of gut microbiome in HCC from its influence on immunometabolism and metabolic reprogramming.