An Individualized Immune Prognostic Index is a Superior Predictor of Survival of Hepatocellular Carcinoma

Identification of VEGFs-related gene signature for predicting microangiogenesis and hepatocellular carcinoma prognosis

Microangiogenesis is an important prognostic factor in various cancers, including hepatocellular carcinoma (HCC). The Vascular Endothelial Growth Factor (VEGF) has been shown to contribute to tumor angiogenesis. Recently, several studies have investigated the regulation of VEGF production by a single gene, with few researchers exploring all genes that affect VEGF production. In this study, we comprehensively analyzed all genes affecting VEGF production in HCC and developed a risk model and gene-based risk score based on VEGF production. Moreover, the model's predictive capacity on prognosis of HCCs was verified using training and validation datasets. The developed model showed good prediction of the overall survival rate. Patients with a higher risk score experienced poor outcomes compared to those with a lower risk score. Furthermore, we identified the immunological causes of the poor prognosis of patients with high-risk scores comparing with those with low-risk scores.

Stroma-associated FSTL3 is a factor of calcium channel-derived tumor fibrosis

Hepatocellular carcinoma (HCC) is the most widespread histological form of primary liver cancer, and it faces great diagnostic and therapeutic difficulties owing to its tumor diversity. Herein, we aim to establish a unique prognostic molecular subtype (MST) and based on this to find potential therapeutic targets to develop new immunotherapeutic strategies. Using calcium channel molecules expression-based consensus clustering, we screened 371 HCC patients from The Cancer Genome Atlas to screen for possible MSTs. We distinguished core differential gene modules between varying MSTs, and Tumor Immune Dysfunction and Exclusion scores were employed for the reliable assessment of HCC patient immunotherapeutic response rate. Immunohistochemistry and Immunofluorescence staining were used for validation of predicted immunotherapy outcomes and underlying biological mechanisms, respectively. We identified two MSTs with different clinical characteristics and prognoses. Based on the significant differences between the two MSTs, we further identified Follistatin-like 3 (FSTL3) as a potential indicator of immunotherapy resistance and validated this result in our own cohort. Finally, we found that FSTL3 is predominantly expressed in HCC stromal components and that it is a factor in enhancing fibroblast-M2 macrophage signaling crosstalk, the function of which is relevant to the pathogenesis of HCC. The presence of two MSTs associated with the calcium channel phenotype in HCC patients may provide promising directions for overcoming immunotherapy resistance in HCC, and the promotion of FSTL3 expressed in stromal components for HCC hyperfibrosis may be responsible for the poor response rate to immunotherapy in Cluster 2 (C2) patients.

Analysis of m6A modulator-mediated methylation modification patterns and the tumor microenvironment in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer. In the development and progression of LUAD, epigenetic aberration plays a crucial role. However, the function of RNA N6-methyladenosine (m⁶A) modifications in the LUAD progression is unknown. The m6A regulator modification patterns in 955 LUAD samples were analyzed comprehensively. Patterns were systematically correlated with the tumor microenvironment (TME) cell-infiltration characteristics. Using principal component analysis algorithms, the m6Ascore was generated to quantify m⁶A modification patterns in individual tumors. Then, their values for predicting prognoses and therapeutic response in LUAD patients were assessed. Three distinct m⁶A modification patterns in LUAD were identified. Among them, the prognosis of m6Acluster C was the best, while the prognosis of m⁶Acluster A was the worst. Interestingly, the characterization of TME cell infiltration and biological behavior differed among the three patterns. To evaluate m⁶A modification patterns within individual tumors, an m⁶Ascore signature was constructed. The results showed that the high m⁶Ascore group was associated with a better prognosis; tumor somatic mutations and tumor microenvironment differed significantly between the high- and low- m⁶Ascore groups. Furthermore, in the cohort with anti-CTLA-4 treatment alone, patients with a high m⁶Ascore had higher ICI scores, which indicated significant therapeutic advantage and clinical benefits.

Identification of NAD+ Metabolism-Derived Gene Signatures in Ovarian Cancer Prognosis and Immunotherapy

Background: Nicotinamide adenine dinucleotide (NAD⁺) has emerged as a critical regulator of cell signaling and survival pathways, affecting tumor initiation and progression. In this study it was investigated whether circulating NAD⁺ metabolism-related genes (NMRGs) could be used to predict immunotherapy response in ovarian cancer (OC) patients.

Method: In this study, NMRGs were comprehensively examined in OC patients, three distinct NMRGs subtypes were identified through unsupervised clustering, and an NAD⁺-related prognostic model was generated based on LASSO Cox regression analysis and generated a risk score (RS). ROC curves and an independent validation cohort were used to assess the model’s accuracy. A GSEA enrichment analysis was performed to investigate possible functional pathways. Furthermore, the role of RS in the tumor microenvironment, immunotherapy, and chemotherapy was also investigated.

Result: We found three different subgroups based on NMRGs expression patterns. Twelve genes were selected by LASSO regression to create a prognostic risk signature. High-RS was founded to be linked to a worse prognosis. In Ovarian Cancer Patients, RS is an independent prognostic marker. Immune infiltrating cells were considerably overexpressed in the low-RS group, as immune-related functional pathways were significantly enriched. Furthermore, immunotherapy prediction reveal that patients with low-RS are more sensitive to immunotherapy.

Conclusion: For a patient with OC, NMRGs are promising biomarkers. Our prognostic signature has potential predictive value for OC prognosis and immunotherapy response. The results of this study may help improve our understanding of NMRG in OCs.

Gene expression-based immune infiltration analyses of renal cancer and their associations with survival outcome

BACKGROUND

Renal cancer is a common malignant tumor with an increasing incidence rate.

METHODS

In this study, based on the gene expression profiles, we analyzed the compositions of tumor-infiltrating immune cells (TIICs) in renal cancer and paracancerous samples using CIBERSORT. The proportions of 22 TIICs subsets in 122 paired renal carcinoma and paracancerous samples, and 224 Wilms tumor (WT) samples varied between intragroup and intergroup.

RESULTS

After analyzed the difference of TIICs composition between renal cancer and paired paracancerous samples, we found that M0 macrophages and CD8 T cells were significantly elevated, while naive B cells were significantly decreased in renal cancer samples compared with paracancerous samples. Survival analysis showed that high overall TIICs proportion, the low proportion of resting mast cells and the high proportion of activated memory CD4 T cells were associated with poor prognosis of renal cancer patients. In addition, 3 clusters were identified by hierarchical clustering analysis, and they presented a distinct prognosis. Cluster 1 had superior survival outcomes, while cluster 2 had an inferior survival outcome.

CONCLUSIONS

Our study indicated that overall TIICs proportion, certain TIICs subset proportion, including resting mast cells and activated memory CD4 T cells, and distinct cluster patterns were associated with the prognosis of renal cancer, which was significant for the clinical surveillance and treatment of renal cancer.

Gene expression-based immune infiltration analyses of liver cancer and their associations with survival outcomes

INTRODUCTION

Liver cancer is one of the most lethal malignancies, presenting inferior survival outcomes once diagnosed. Current therapeutic approaches mainly target the tumor cells or vasculature, but rarely take the immune factors into consideration.

METHODS

In our study, the compositions of tumor-infiltrating immune cells (TIICs) in liver cancer and paracancer samples were analyzed based on the gene expression profiles by CIBERSORT. After calculating the proportions of 22 TIICs subtypes in 51 paired cancer and paracancer samples, we found their proportions varied between intragroup and intergroup. Compared with the paracancer tissues, the relative proportions of macrophages M0 and resting mast cells in liver cancer samples were significantly elevated, while that of M2 macrophages were reduced.

RESULTS

Univariate Cox regression analysis with the 22 TIICs subtypes as continuous variables showed increased B cells memory and resting NK cells were significantly associated with poor survival outcome. Besides, hierarchical clustering analysis based on the proportions of 22 TIICs subtypes identified 3 clusters, which exhibited distinct prognosis. Among them, cluster 1 had superior survival outcomes, while cluster 3 had inferior survival outcomes.

CONCLUSIONS

Collectively, our research suggested certain TIICs subpopulations proportions, as well as cluster patterns were associated with the prognosis of liver cancer, which provided potential therapeutic targets for liver cancer.