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A novel four‐gene signature predicts immunotherapy response of patients with different cancers

Abstract Background Immune checkpoint blockade (ICB) therapy has demonstrated favorable clinical efficacy, particularly for advanced or difficult‐to‐treat cancer types. However, this therapy is ineffective for many patients displaying lack of immune response or resistance to ICB. This study aimed to establish a novel four‐gene signature (CD8A, CD8B, TCF7, and LEF1) to provide a prognostic immunotherapy biomarker for different cancers. Methods Transcriptome profiles and clinical data were obtained from The Cancer Genome Atlas database. Multivariate Cox regression analysis was used to establish a four‐gene signature. The R package estimate was used to obtain the immune score for every patient. Results Risk scores of the novel four‐gene signature could effectively divided all patients into high‐ and low‐risk groups, with distinct outcomes. The immune score calculated via the estimate package demonstrated that the four‐gene signature was significantly associated with the immune infiltration level. Furthermore, the four‐gene signature could predict the response to atezolizumab immunotherapy in patients with metastatic urothelial cancer. Conclusions The novel four‐gene signature developed in this study is a good prognostic biomarker, as it could identify many kinds of patients with cancer who are likely to respond to and benefit from immunotherapy.

hepatocellular carcinoma (LIHC), 12,13 thyroid carcinoma (THCA), 14 adrenocortical carcinoma (ACC), and uveal melanoma (UVM). 15 A small percentage of patients receiving anti-CTLA-4/B7 or anti-PD1/ PD-L1 therapy experienced prolonged survival. Thus, the combination of anti-CTLA-4/B7 with anti-PD1/PD-L1 therapy may have promising clinical efficacy. 16 To apply immunotherapy to many types of cancers, it is pivotal to predict the immune responses and clinical outcomes of patients with metastatic cancer prior to treatment, and to enhance the response to immunotherapy of recalcitrant patients, whose cancer cells may be more resistant to ICB agents.
Previous studies have reported that PD-L1 expression in tumor cells can be used to predict clinical responses to ICB therapy. 5,17,18 However, some patients with PD-L1-negative melanoma can also derive durable clinical benefits from PD-1 blockade. 19 Notably, T cells play a crucial role in immune defense against cancer. [20][21][22][23] In particular, the level of tumor-infiltrating CD8 + T lymphocytes is often a predictor of patient survival and response to immunotherapy, [24][25][26][27][28][29][30][31] and both anti-CTLA-4 and anti-PD-1 treatments can induce CD8 + T-cell expansion. However, not all CD8 + T-cell subsets exhibit this behavior. 32 Some memory CD8 + T cells in human lymph nodes are highly similar to a subset of mouse CD8 + T cells, identified in chronic infection models, that respond to checkpoint blockade immunotherapy.
These cells exhibit a distinct transcriptional signature, including the expression of lymphoid enhancer binding factor 1 (LEF1) and T-cellspecific transcription factor 7 (TCF7). 33 TCF7 and LEF1 are historically known as effector transcription factors acting downstream of the WNT signaling pathway, and are essential for early T-cell development. 34,35 A group of CD8 + T cells displaying hallmarks of exhausted cells and central memory cells was identified; notably, TCF7 expression was required for the generation of this CD8 + T-cell subset, which exhibited a proliferative burst after PD1 blockade. 34,36,37 The "progenitor" or "stem-like" exhausted cells were a subset of exhausted CD8 + tumor-infiltrating lymphocytes that persisted long term and retained polyfunctionality. Moreover, melanoma patients displaying a higher percentage of progenitor exhausted cells experienced more durable response to checkpoint blockade therapy. 38 Stem-like CD8 + T cells in human tumors have been confirmed to be stem-like CD8 + T cells expressing TCF7, which divide into terminally differentiated cells that express effector molecules. Additionally, initiation of effector differentiation is critical for the infiltration of many T cells into the tumor. 39 TCF7 and LEF1, belonging to the high-mobility group (HMG) family owing to their conserved HMG DNA-binding domains, are wellknown stem cell-associated transcription factors that are usually expressed in CD8 + T cells, 40,41 and play critical roles in establishing CD8 + T-cell identity through their intrinsic histone deacetylase activity. 42,43 These proteins also play vital roles in the regulation of CD8 + T-cell function and differentiation.
The CD8 antigen, acting as a co-receptor of T lymphocytes, is composed of the isoforms CD8 alpha chain and CD8 beta chain, which are encoded by CD8A and CD8B, respectively. Granzyme A (GZMA) and granzyme B (GZMB) are T cell-and natural killer cell-specific serine proteases, which may function as common components necessary for the lysis of target cells by cytotoxic T lymphocytes (CTLs) and natural killer cells. Perforin 1 (PRF1) forms membrane pores that allow the release of granzymes and the subsequent cytolysis of target cells. Previous studies have shown that the average expression levels of CD8A, CD8B, GZMA, GZMB, and PRF1 can be used to estimate CTL levels in a tumor. 44 Therefore, CD8A, CD8B, TCF7, and LEF1 expression may reveal the presence of stem-like CD8 + T cells and may be thus used as a reliable immunotherapy biomarker to predict ICB outcomes. In the current study, we established an immune-  (Table S1). Data from patients with metastatic urothelial cancer (mUC) treated with atezolizumab (an anti-PD-L1 agent) were obtained from the R package IMvigor210CoreBiologies (version 1.0.0). 45

| Statistical analysis
All statistical and bioinformatics analyses were performed in R (version 4.0.1).

| Identification of Differentially Expressed Genes (DEGs)
Differential expression analysis for the four genes CD8A, CD8B, TCF7, and LEF1 between tumor and normal tissues was performed using edge R (version 3.30.3).

| Functional and pathway enrichment analyses
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the R package clusterProfiler (version 3.16.0) to investigate the functional and pathway enrichment associated to the four genes CD8A, CD8B, TCF7, and LEF1. The terms were sorted by their p value.

| Cox proportional hazards regression model and risk score
The four-gene signature (CD8A, CD8B, TCF7, and LEF1) was created as a prognostic model that was used to calculate the risk score of each patient based on multivariable Cox regression analysis. The mean risk score value was used as a threshold, according to which the patients were divided into high-and low-risk groups.
The C-index was used to evaluate the validation of the four-gene signature prognostic model. Time-dependent receiver operating characteristic (ROC) curves were used to assess the sensitivity and specificity of the four-gene signature. Multivariate Cox regression analysis was performed using the R package survival (version 3.2-3).

| Survival curve analysis
Survival results were expressed as Kaplan-Meier (KM) curves, and statistical significance was assessed using the log-rank test. Receiver operating characteristic (ROC) curve analysis was performed using the R package survival ROC (version 1.0.3). Statistical significance was set at p < 0.05.

| Immune infiltration analysis
Immune scores, which represent the immune infiltration levels of patients, were calculated with the R package estimate (version 1.0.13) 46 based on the TCGA RNA-seq database.

| Prognosis prediction for BRCA
To assess the predictive ability of the four-gene signature (CD8A,

TA B L E 1 Univariable and multivariable
Cox regression analyses for BRCA outcomes, it is necessary to further examine the predictive value of the four-gene signature to predict survival outcomes for cancer patients in different age groups or at different tumor stages. Two age groups of patients with BRCA were selected in this study: an older group (age >60 years) and a younger group (age ≤60 years).
KM curves and log-rank test suggested that the four-gene signature might be more suitable for predicting survival outcomes in the older group than in the younger group. In fact, the ROC for the 3-year OS in the older group was 0.625, whereas the ROC for the 5-year OS in the younger group was 0.706 ( Figure 3A,B).

Considering the different stages of BRCA from the American Joint
Committee on Cancer (AJCC), the four-gene signature was used to predict the survival outcomes of patients with cancer at different stages, namely stages 1, 2, 3, and 4. KM curves and logrank tests indicated that the four-gene signature might be more robust for patients with BRCA at stages 2, 3, and 4 than for those F I G U R E 4 Overall survival analysis and ROC curves for patients with various cancers. The KM curves of the four-gene signature (CD8A, CD8B, TCF7, and LEF1) showed that the risk score could be effectively used to divide patients into high-and low-risk groups with distinct outcomes.

| Prognostic prediction for other cancers
To  showed that the four-gene signature has predictive value for different ages, stage events, or sexes, and thus could serve as an independent prognostic factor in these patients (Table 3 and Table 4; Figure S1, Figure S2, Figure S3 and Figure S4). However, the fourgene signature exhibited poor predictive value for different ages,

TA B L E 6
Log-rank test analyses for KIRC, KIRP, THCA, and READ stage events, and sexes in patients with KIRC, KIRP, THCA, and READ, and thus could not serve as an independent prognostic factor for these cancer types (Table 5 and Table 6). Owing to the small sample size of patients with ACC or UVM, neither univariate nor multivariate Cox regression analyses were performed in this study.   primary immunodeficiency, melanogenesis, hematopoietic cell lineage, arrhythmogenic right ventricular cardiomyopathy, adherent junction, acute myeloid leukemia, antigen processing, and presentation ( Figure 6B).

| The four-gene signature as an immuneassociated prognostic signature for cancers
To investigate the immune-related risk stratification of the fourgene signature, the immune score, which represents the immune infiltration level, was obtained using the R package estimate. When comparing high-to low-risk groups of cancer patients, the fourgene signature was found to be significantly associated with the immune infiltration level in patients with 10 types of cancer (Figure 7).
For example, in patients with mUC, the KM survival curves and log-rank test revealed significant differences in survival outcomes ( Figure 8A, B). Moreover, immune infiltration levels differed significantly between the high-and low-risk groups in patients with mUC (p < 0.0001. Figure 8C). The four-gene signature score was lower in the complete response subgroups (CRs) than in the stable disease subgroups (SDs, p = 0.0475) or partial disease subgroups (PDs, p = 0.0017) ( Figure 8D). The four-gene signature was positively associated with complete response to atezolizumab treatment, an anti-PD-L1 immunotherapy ( Figure 8E. p = 0.0054). Collectively, our results suggest that the four-gene signature can be used to predict the efficacy of immunotherapy and identify patients that could benefit from immunotherapy.

| DISCUSS ION
In many cancers, the presence of tumor-infiltrating CD8 + T lymphocytes can be used to predict patient survival and response to immunotherapy. [24][25][26][27][28][29][30][31] The presence of tumor-infiltrating lymphocytes, particularly CD8 + T cells, is a positive prognostic marker in multiple solid tumors, but these cells fail to effectively eliminate cancer cells. This is because not all CD8 + T-cell subsets expand following ICB. 32 Stem-like CD8 + T cells, a subpopulation of CD8 + T cells that can express effector molecules, play critical roles in maintaining CD8 + T-cell responses in human cancers. 47 In fact, the proliferative burst derives almost exclusively from these "stem-like" CD8 + T cells after ICB. Moreover, melanoma patients with a higher percentage of progenitor exhausted cells benefit from a more durable response to ICB therapy. 34,[36][37][38][39] In the current study, based on the transcriptomic profiles from the TCGA database, a multi-  Importantly, TCF7 and LEF1 play critical roles in the establishment of CD8 + T-cell identity, as they are directly involved in genetic and epigenetic regulation resulting in an appropriate gene expression pattern for CD8 + T cells. Such regulatory functions mainly depend on their intrinsic histone deacetylase activity. 43 Therefore,

ACK N OWLED G EM ENT
We thank Dr. Xiaodong Zheng from the Institute of Dermatology at Anhui Medical University for data analysis.
This work was supported by Anhui Natural Science Foundation (1808085MH259) and National Nature Science Foundation of China (81772909).

CO N FLI C T O F I NTE R E S T
The authors declare that they have no competing interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.