Low immune index correlates with favorable prognosis but with reduced benefit from chemotherapy in gallbladder cancer

Research progress on prognostic factors of gallbladder carcinoma

BACKGROUND

Gallbladder carcinoma is the most common malignant tumor of the biliary system, and has a poor overall prognosis. Poor prognosis in patients with gallbladder carcinoma is associated with the aggressive nature of the tumor, subtle clinical symptoms, ineffective adjuvant treatment, and lack of reliable biomarkers.

PURPOSE

Therefore, evaluating the prognostic factors of patients with gallbladder carcinoma can help improve diagnostic and treatment methods, allowing for tailored therapies that could benefit patient survival.

METHODS

This article systematically reviews the factors affecting the prognosis of gallbladder carcinoma, with the aim of evaluating prognostic risk in patients.

CONCLUSION

A comprehensive and in-depth understanding of prognostic indicators affecting patient survival is helpful for assessing patient survival risk and formulating personalized treatment plans.

The prognostic value of Forkhead box P3 regulatory T cells in biliary tract cancer: A systematic review and meta-analysis

BACKGROUND

This study aimed to explore the value of tumor-infiltrating Forkhead box P3(FoxP3+) regulatory T cells (Tregs) in evaluating the prognosis of biliary tract cancer.

METHODS

Four electronic databases were searched using 2 computers: PubMed, Embase, Web of Science, and Cochrane Library. The vocabulary and syntax were adapted according to the database. Two researchers independently selected the studies, collected information, and assessed the risk of bias. The Meta-analysis was performed using STATA 17.0, and HR and its corresponding 95% CI were used to evaluate the correlation between FoxP3+ Tregs and the overall survival of patients with biliary tract cancer. In addition, the quality of the included studies was evaluated.

RESULTS

Ten articles were included in this study. The results of the meta-analysis showed that patients with high FoxP3+ Tregs infiltration had worse overall survival (OS) (HR = 1.34,95% CI 1.16 to 1.71; P < .001). Subgroup analysis of gallbladder carcinoma and cholangiocarcinoma showed that the high infiltration of FoxP3+ Tregs was significantly correlated with the OS of the former (HR = 1.55,95% CI 1.11 to 2.00; P < .001), but not with the OS of the latter (HR = 1.00,95% CI 0.62 to 1.38; P > .05).

CONCLUSIONS

Our meta-analysis reveals that high infiltration of FoxP3 + Tregs is significantly associated with reduced overall survival in gallbladder carcinoma, endorsing their use as a prognostic biomarker for this subtype. In contrast, no significant prognostic correlation was identified for FoxP3+ Tregs in cholangiocarcinoma, indicating the need for subtype-specific evaluation of their prognostic relevance in biliary tract cancers.

Multi-clinical index classifier combined with AI algorithm model to predict the prognosis of gallbladder cancer

Objectives

It is significant to develop effective prognostic strategies and techniques for improving the survival rate of gallbladder carcinoma (GBC). We aim to develop the prediction model from multi-clinical indicators combined artificial intelligence (AI) algorithm for the prognosis of GBC.

Methods

A total of 122 patients with GBC from January 2015 to December 2019 were collected in this study. Based on the analysis of correlation, relative risk, receiver operator characteristic curve, and importance by AI algorithm analysis between clinical factors and recurrence and survival, the two multi-index classifiers (MIC1 and MIC2) were obtained. The two classifiers combined eight AI algorithms to model the recurrence and survival. The two models with the highest area under the curve (AUC) were selected to test the performance of prognosis prediction in the testing dataset.

Results

The MIC1 has ten indicators, and the MIC2 has nine indicators. The combination of the MIC1 classifier and the "avNNet" model can predict recurrence with an AUC of 0.944. The MIC2 classifier and "glmet" model combination can predict survival with an AUC of 0.882. The Kaplan-Meier analysis shows that MIC1 and MIC2 indicators can effectively predict the median survival of DFS and OS, and there is no statistically significant difference in the prediction results of the indicators (MIC1: χ² = 6.849, P = 0.653; MIC2: χ² = 9.14, P = 0.519).

Conclusions

The MIC1 and MIC2 combined with avNNet and mda models have high sensitivity and specificity in predicting the prognosis of GBC.

Identification of INSRR as an immune-related gene in the tumor microenvironment of glioblastoma by integrated bioinformatics analysis

Gliomas are the most common malignant tumors in the central nervous system. The tumor microenvironment (TME) plays a crucial role in tumor proliferation, invasion, angiogenesis, and immune escape. However, little is known about TME in gliomas. The purpose of this study was to explore the biomarkers associated with TME in glioblastoma (GBM) to predict immunotherapy effectiveness and prognosis in patients. Based on RNA-seq transcriptome data and clinical features of 1222 samples (113 normal samples and 1109 tumor samples) in The Cancer Genome Atlas (TCGA) database, the ImmuneScore, StromalScore, and ESTIMATEScore were calculated by ESTIMATE algorithm. The differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were determined in the TCGA GBM cohort. Furthermore, gene set enrichment analysis (GSEA) was used to investigate the enrichment pathways of INSRR genes with abnormal expression. The proportion of tumor-infiltrating immune cells (TIICs) was evaluated by CIBERSORT. Frequent mutations of TP53, EGFR, and PTEN occurred in high and low immune scores. The cross-analysis of DEGs and DMGs revealed that INSRR was an immune-related biomarker in the TCGA GBM cohort. According to GSEA, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway with INSRR abnormal expression were IgA-produced intestinal immune network and Alzheimer's disease, oxidative phosphorylation, and Parkinson's disease, respectively. Additionally, INSRR expression was correlated with dendritic cells activated, dendritic cells resting, T cells CD8, and T cell gamma delta. INSRR is associated with the immune microenvironment in GBM and is used as a biomarker to predict immune invasion.

[CD40LG is a novel immune- and stroma-related prognostic biomarker in the tumor microenvironment of invasive breast cancer]

OBJECTIVE

To identify tumor microenvironment (TME)- related genes associated with the occurrence of invasive breast cancer as potential prognostic biomarkers and therapeutic targets.

METHODS

RNA transcriptome data and clinically relevant data were retrieved from TCGA database, and the StromalScore and ImmuneScore were calculated using the ESTIMATE algorithm. The differentially expressed genes (DEGs) were screened by taking the intersection. A protein- protein interaction network was established, and univariate COX regression analysis was used to identify the core genes among the DEGs. A core gene was selected for GSEA and CIBERSORT analysis to determine the function of the core gene and the proportion of tumor-infiltrating immune cells, respectively. Western blotting and qRT-PCR were performed to verify the expression level of CD40LG in breast cancer cell lines and clinical specimens.

RESULTS

A total of 1222 samples (124 normal and 1098 tumor samples) were extracted from TCGA for analysis, from which 487 DEGs were identified. These genes were mainly enriched in immune-related pathways, and crossover analysis identified 11 key genes (CD40LG, ITK, CD5, CD3E, SPN, IL7R, CD48, CCL19, CD2, CD52, and CD2711) associated with breast cancer TME status. CD40LG was selected as the core gene, whose high expression was found to be associated with a longer overall survival of breast cancer patients (P=0.002), and its expression level differed significantly with TNM stage and tumor size (P < 0.05). GSEA and CIBERSORT analyses indicated that CD40LG expression level was associated with immune activity in the TME. Western blotting and qRT-PCR showed that the protein and mRNA expression of CD40LG were significantly lower in breast cancer cells and cancer tissues than in normal breast cells and adjacent tissues.

CONCLUSIONS

The high expression of CD40LG in TME is positively correlated with the survival of patients with invasive breast cancer, suggesting its value as a potential new biomarker for predicting prognosis of the patients.

Pancancer Analysis of Revealed TDO2 as a Biomarker of Prognosis and Immunotherapy

Background

Tryptophan 2,3-dioxygenase (TDO) encoded by TDO2, a rate-limiting enzyme in the kynurenine pathway, catabolizes tryptophan to kynurenine, evades immune surveillance, and promotes tumor growth. Although accumulating evidence suggests a crucial role of TDO2 during tumor formation and development, systematic evaluation of TDO2 across human cancers has rarely been reported.

Methods

To shed more light on the role of TDO2 in human cancer, we explored the expression profiles of TDO2 and identified its prognostic value in pancancer analysis through TCGA, CCLE, and GTEx databases. We further utilized TCGA data to evaluate the association between TDO2 and tumor immunological features, such as mismatch repair (MMR), tumor immune infiltration, immune checkpoint-related genes, tumor mutational burden (TMB), microsatellite instability (MSI), and DNA methyltransferase (DNMT).

Results

TDO2 exhibited different expression levels in various cancer cell lines. Frequently, TDO2 was detected to be highly expressed in the majority of cancers. In addition, high TDO2 expression was correlated with an unfavorable prognosis for patients in KIRP, LGG, TGCT, and UVM. Moreover, high TDO2 expression level positively correlated with higher immune infiltration, especially dendritic cells. Additionally, there is a close relationship between TDO2 and immune checkpoint-related gene markers, such as LAIR1, CD276, NRP1, CD80, and CD86. Finally, correlation analysis has demonstrated a high-correlation between TDO2 and TMB, MSI, MMR, and DNMT of multiple cancer types.

Conclusion

Therefore, our results suggest that TDO2 can function as a potential prognostic biomarker due to its role in tumor immunity regulation.

Mast Cells in Immune-Mediated Cholangitis and Cholangiocarcinoma

Cholestasis, which is impaired bile flow from the liver into the intestine, can be caused by cholangitis and/or bile duct obstruction. Cholangitis can arise from bacterial infections and cholelithiasis, however, immune-mediated cholangitis in primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) is characterized by a strong immune response targeting the biliary epithelial cells (BECs). Persistent biliary inflammation further represents a risk for biliary neoplasia, cholangiocarcinoma (CCA) by driving chronic cellular stress in the BECs. Currently, immune-mediated cholangitis is considered a Th1-Th17-dominant disease, however, the presence of Th2-related mast cells (MCs) in tissue samples from PBC, PSC and CCA patients has been described, showing that these MCs are active players in these diseases. Here, we reviewed and discussed experimental and clinical data supporting a pro-fibrotic role for MCs in immune-mediated cholangitis as well as their participation in supporting tumor growth acting as angiogenesis promoters. Thus, although MCs have classically been identified as downstream effectors of Th2 responses in allergies and parasitic infections, evidence suggests that these MCs are relevant players in biliary inflammation and neoplasia. The availability of strategies to prevent MCs’ activation represents a therapeutic opportunity in biliary diseases.

Integrating Machine Learning and Tumor Immune Signature to Predict Oncologic Outcomes in Resected Biliary Tract Cancer

BACKGROUND

Improved methods are needed to predict outcomes in biliary tract cancers (BTCs). We aimed to build an immune-related signature and establish holistic models using machine learning.

METHODS

Samples were from 305 BTC patients treated with curative-intent resection, divided into derivation and validation cohorts in a two-to-one ratio. Spatial resolution of T cell infiltration and PD-1/PD-L1 expression was assessed by immunohistochemistry. An immune signature was constructed using classification and regression tree. Machine learning was applied to develop prediction models for disease-specific survival (DSS) and recurrence-free survival (RFS).

RESULTS

The immune signature composed of CD3+, CD8+, and PD-1+ cell densities and PD-L1 expression within tumor epithelium significantly stratified patients into three clusters, with median DSS varying from 11.7 to 80.8 months and median RFS varying from 6.2 to 62.0 months. Gradient boosting machines (GBM) outperformed rival machine-learning algorithms and selected the same 11 covariates for DSS and RFS prediction: immune signature, tumor site, age, bilirubin, albumin, carcinoembryonic antigen, cancer antigen 19-9, tumor size, tumor differentiation, resection margin, and nodal metastasis. The clinical-immune GBM models accurately predicted DSS and RFS, with respective concordance index of 0.776-0.816 and 0.741-0.781. GBM models showed significantly improved performance compared with tumor-node-metastasis staging system.

CONCLUSIONS

The immune signature promises to stratify prognosis and allocate treatment in resected BTC. The clinical-immune GBM models accurately predict recurrence and death from BTC following surgery.

Diversity and intratumoral heterogeneity in human gallbladder cancer progression revealed by single-cell RNA sequencing

BACKGROUND

Gallbladder cancer (GC) is a malignant disease characterized with highly cellular heterogeneity and poor prognosis. Determining the intratumoral heterogeneity and microenvironment (TME) can provide novel therapeutic strategies for GC.

METHODS

We performed the single-cell RNA sequencing on the primary and lymph node metastatic gallbladder tumors and the adjacent normal tissues of five patients. The transcriptomic atlas and ligand-receptor-based intercellular communication networks of the single cells were characterized.

RESULTS

The transcriptomic landscape of 24,887 single cells was obtained and characterized as 10 cellular clusters, including epithelial, neuroendocrine tumor cells, T&NK cells, B cells, RGS5+ fibroblasts, POSTN+ fibroblasts, PDGFRA+ fibroblasts, endothelial, myeloid cells, and mast cells. Different types of GC harbored distinct epithelial tumor subpopulations, and squamous cell carcinoma could be differentiated from adenocarcinoma cells. Abundant immune cells infiltrated into adenocarcinoma and squamous cell carcinoma, rather than neuroendocrine neoplasms, which showed significant enrichment of stromal cells. CD4+/FOXP3+ T-reg and CD4+/CXCL13+ T helper cells with higher exhausting biomarkers, as well as a dynamic lineage transition of tumor-associated macrophages from CCL20hi /CD163lo , CCL20lo /CD163hi to APOE+, were identified in GC tissues, suggesting the immunosuppressive and tumor-promoting status of immune cells in TME. Two distinct endothelial cells (KDR+ and ACKR1+), which were involved in angiogenesis and lymphangiogenesis, showed remarkable ligand-receptor interactions with primary GC cells and macrophages in gallbladder tumors.

CONCLUSIONS

This study reveals a widespread reprogramming across multiple cell populations in GC progression, dissects the cellular heterogeneity and interactions in gallbladder TME, and provides potential therapeutic targets for GC.

Prognostic Nomograms to Predict Survival of Patients with Resectable Gallbladder Cancer: A Surveillance, Epidemiology, and End Results (SEER)-Based Analysis

Background

Gallbladder adenocarcinoma (GBAC) is globally acknowledged as one of the most common malignancies among all gastrointestinal cancers. Despite prognosis of GBAC patients remains poor, patients with early-stage disease can be observed with long-term survival.

Material/Methods

In this study, 2556 patients with pathological GBAC between 2010 and 2015 were derived from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic nomograms containing all independent prognostic factors for predicting overall survival (OS) and cancer-specific survival (CSS) were constructed to achieve superior prognostic discriminatory ability.

Results

Based on the AJCC 7^th TNM staging system, we found the TNM substaging was not accurate enough to predict the survival and stratify the risk. Based on the results of univariate and multivariate analyses, a more precise prognostic nomogram was constructed containing all significant independent prognostic factors (age, grade, TNM stage, bone metastasis, and chemotherapy) for OS, while age, grade, TNM stage, bone metastasis and radiotherapy significant independent prognostic factors for CSS. The C-index of the constructed nomogram for predicting OS and CSS was 0.740 and 0.737 higher than that of TNM staging alone (0.667 for OS and 0.689 for CSS), respectively. In addition, the calibration curves and decision curve analysis further showed its robust power in survival prediction.

Conclusions

The constructed nomograms showed better discrimination abilities to predict OS and CSS rates at 1, 3, and 5 years. In the future, these constructed models for this disease will assist in risk stratification to guide GBAC treatment.

The immunological characteristics of gallbladder carcinoma and advances in immunotherapy practices

Gallbladder carcinoma (GBC) is one of the most common malignant tumors in the biliary system, ranking sixth among gastrointestinal malignancies. In addition, the incidence of GBC has recently increased in China. GBC metastasizes early and invades adjacent organs such as the liver, making patients with GBC ineligible for radical surgery and giving them a poor prognosis. What is more, GBC is more inclined to develop chemo-resistance, which requires new strategies for clinical intervention. Cancer immunotherapy has made great advances over the past few years, with improved clinical efficacy against multiple malignancies, including GBC. This review summarizes the immunological characteristics of GBC as well as current advances in immunotherapies for GBC in order to provide new insights into future treatment and prevention of GBC.

Prediction Efficacy for Clinical Outcome of Prognostic Nutritional Index in Patients with Resectable Biliary Tract Cancer Depends on Sex and Obstructive Jaundice Status

BACKGROUND

The Prognostic Nutritional Index (PNI), a marker of nutritional status and systemic inflammation, is a proven prognostic biomarker in some cancers. The predictive value of PNI in biliary tract cancer (BTC) has not been established.

OBJECTIVE

The aim of this study was to determine the relationship between the PNI and outcomes of resectable BTC.

METHODS

In total, 430 patients with stage I-III resectable BTC [gallbladder cancer (GBC), n = 212; cholangiocarcinoma (CHO), n = 218] who had attended Fudan University Zhongshan Hospital were enrolled. The relationship between the PNI and clinical outcomes was evaluated both in the whole cohort and in selected subgroups.

RESULTS

Eligible patients were classified into PNI-low (PNI < 45) and PNI-high (PNI ≥ 45) groups. The PNI-low group had significantly worse overall survival (OS) in both the whole cohort (p = 0.002) and in the GBC subgroup (p = 0.001), but had similar OS as the PNI-high group in the CHO subgroup (p = 0.328). Multivariate analysis revealed that low PNI is an independent risk factor for worse survival in GBC (hazard ratio 1.623, 95% confidence interval 1.063-2.480, p = 0.026). PNI was found to predict clinical outcome in women (p < 0.001) and patients without obstructive jaundice (p = 0.017) with GBC, but was not a prognostic factor in any subgroup with CHO. The estimated area under the time-dependent receiver operating characteristic curve was significantly greater when TNM stage was combined with PNI in women with GBC.

CONCLUSIONS

PNI is an independent predictor of OS in GBC, but not in CHO. It has no prognostic value in men with GBC or patients with obstructive jaundice.

Low immune index correlates with favorable prognosis but with reduced benefit from chemotherapy in gallbladder cancer

Use of immune index is a new potential approach for cancer classification and prediction. To investigate the status and clinical effect of immune index in gallbladder cancer (GBC), 238 GBC patients from Zhongshan Hospital affiliated to Fudan University were involved in the present study, including 113 patients in a training set and 125 patients in a validation set. Five immune cells (macrophages, neutrophils, regulatory T cells, cytotoxic T cells and mast cells) were selected based on a literature review and the immune index for each patient was calculated using the LASSO regression. A low immune index (<1) was defined as immunotype A and a high immune index (≥1) was defined as immunotype B. The 5-year overall survival rate for immunotype A was higher than that for immunotype B in the training set and the validation set (70.0% vs 37.0%, P < 0.001; 68.9% vs 47.5%, P = 0.002; respectively). Moreover, the immune index showed higher prediction efficiency compared with all the single immune cells which we selected. When combined with the immune index, the areas under the curve (AUC) of the TNM staging system in both sets were elevated from 0.677 to 0.787 and from 0.631 to 0.694, respectively. Interestingly, gemcitabine-based chemotherapy only benefits stage II patients of immunotype B and stage III patients of both immunotype A and immunotype B (P = 0.015, P = 0.030, P = 0.011, respectively) but does not work in stage II patients of immunotype A (P = .307). Taken together, the immune index could effectively predict prognosis and the benefits of gemcitabine-based chemotherapy and might improve on the TNM staging system.