Pan-Cancer Analysis of Immune Cell Infiltration Identifies a Prognostic Immune-Cell Characteristic Score (ICCS) in Lung Adenocarcinoma

Abstract

Background: The tumor microenvironment (TME) consists of heterogeneous cell populations, including malignant cells and nonmalignant cells that support tumor proliferation, invasion, and metastasis through extensive cross talk. The intra-tumor immune landscape is a critical factor influencing patient survival and response to immunotherapy. Methods: Gene expression data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Immune cell infiltration was determined by single-sample Gene Set Enrichment Analysis (ssGSEA) depending on the integrated immune gene sets from published studies. Univariate analysis was used to determine the prognostic value of the infiltrated immune cells. Least absolute shrinkage and selection operator (LASSO) regression was performed to screen for the most survival-relevant immune cells. An immune-cell characteristic score (ICCS) model was constructed by using multivariate Cox regression analysis. Results: The immune cell infiltration patterns across 32 cancer types were identified, and patients in the high immune cell infiltration cluster had worse overall survival (OS) but better progression-free interval (PFI) compared to the low immune cell infiltration cluster. However, immune cell infiltration showed inconsistent prognostic value depending on the cancer type. High immune cell infiltration (High CI) indicated a worse prognosis in brain lower grade glioma (LGG), glioblastoma multiforme (GBM), and uveal melanoma (UVM), and favorable prognosis in adrenocortical carcinoma (ACC), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), sarcoma (SARC), and skin cutaneous melanoma (SKCM). LUAD prognosis was significantly influenced by the infiltration of 13 immune cell types, with high infiltration of all but Type 2 T helper (Th2) cells correlating with a favorable prognosis. The ICCS model based on six most survival-relevant immune cell populations was generated that classified patients into low- and high-ICCS groups with good and poor prognoses, respectively. The multivariate and stratified analyses further revealed that the ICCS was an independent prognostic factor for LUAD. Conclusions: The infiltration of immune cells in 32 cancer types was quantified, and considerable heterogeneity was observed in the prognostic relevance of these cells in different cancer types. An ICCS model was constructed for LUAD with competent prognostic performance, which can further deepen our understanding of the TME of LUAD and can have implications for immunotherapy.

Identification of a Five-Autophagy-Related-lncRNA Signature as a Novel Prognostic Biomarker for Hepatocellular Carcinoma

“…The immune cell infiltration status was acquired based on quanTIseq, a method to quantify the fractions of 10 immune cell types from bulk RNA-sequencing data (Finotello et al, 2019 ), by using the single-sample gene set enrichment approach (Zuo et al, 2020 ) to the transcriptomes of HCC.…”

Development of A Vitamin-Related Gene Signature to Predict the Immune Characteristics and Prognosis of Glioma

“…At the same time, it also suggested that the vitamin-related risk signature can directly predict the local immune status of glioma, highlighting its strong predictive ability. It has been shown that higher immune cells in ltration indicates a worse outcome in both LGG and GBM (36). This further con rmed the accuracy and reliability of the vitamin-related risk signature in predicting the local immune response of the glioma microenvironment and the prognosis of glioma patients.…”

ITGA3 Is a Reliable Biomarker and Putative Therapeutic Target for Glioma

“…Figure 3F show the relationship between the enrichment of these six types of immune cells and the expression level of ITGA3 in TCGA, CGGA, and GSE16011 datasets. It had been con rmed that high immune cell in ltration resulted in a more unfavorable prognosis in glioma (27). These results indicated that ITGA3 reduced the purity of glioma by promoting the enrichment of immune cells in the glioma microenvironment, thereby affecting the prognosis of glioma.…”