Identification and validation of ZAP70 as a potential biomarker associated with T cell infiltration in lung adenocarcinoma

Introduction

Lung cancer is responsible for 1.796 million deaths worldwide, as reported in the Global Cancer Statistics 2020 (1). Non-small cell lung cancer (NSCLC) constitutes over 85% of all lung cancer cases (2). The most common subtypes are lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) (3,4). In the era of precision medicine, immunotherapy has emerged as a potentially revolutionary treatment for malignancies, including NSCLC. Therefore, the identification of more druggable molecular targets is of paramount importance to optimize combination therapy strategies and enhance cancer management.

Zeta-chain-associated protein kinase 70 kDa (ZAP70) plays a pivotal role in the activation of T cell receptors (TCRs) (5). Without the recruitment of ZAP-70, the differentiation of T cells is restricted (6). However, individuals with the absence of ZAP-70 recruitment exhibit impaired functionality in peripheral CD4⁺ T cells due to abnormal TCR signaling. In the context of cancer, ZAP70 expression is notably absent and associated with cancer development. The up-regulation of ZAP70 distinctly suppresses the invasion of laryngeal cancer cells (7). The expression of ZAP70 contributes to the anti-tumor activity of infiltrating T cells, while its inactivation in infiltrating T cells inhibits T cell activation and the anti-tumor immune response (8). Nonetheless, the clinical significance of ZAP70, particularly regarding prognosis and tumor immune infiltration in LUAD, remains unclear.

Thus, we first evaluated ZAP70 expression in lung cancer, clinicopathological features, and immune infiltration by public databases. We further evaluated its independent prognostic value through Kaplan-Meier (K-M) survival and subgroup analyses. Pathway enrichment analyses were performed to explore mechanisms potentially linked to ZAP70. Finally, we validated ZAP70 expression in a real-world patient cohort to clarify its prognostic and therapeutic relevance in lung cancer. We present this article in accordance with the REMARK reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2667/rc).

Methods

Public database

Clinical and bulk RNA data for LUAD were obtained from The Cancer Genome Atlas (TCGA), complemented by two Gene Expression Omnibus (GEO) cohorts (GSE75037, GSE116959) and a single-cell dataset (GSE139555). All raw files were processed using a unified pipeline that included background correction, normalization, and expression summarization. Microarray probe IDs were re-annotated to official gene symbols according to the respective platform files. Differentially expressed genes (DEGs): |log₂ fold change (FC)| >2, P<0.05. All datasets were retrieved on May 1, 2025. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

ZAP70 expression profiling

ZAP70 expression profiles were systematically analyzed across multiple platforms. messenger RNA (mRNA) expression was evaluated using the Gene Expression Profiling Interactive Analysis (GEPIA), TCGA, and GEO datasets, while protein levels were assessed through Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (HPA). Furthermore, pan-cancer expression patterns and immune infiltration correlations were characterized using the Tumor Immune Estimation Resource (TIMER)/TIMER2 (9) and HPA resources. All database queries were performed on June 22, 2025.

Survival analysis

Survival data of ZAP70 from lung cancer patient cohorts were analyzed via the K-M plotter tool (accessed June 22, 2025), focusing on differences across clinical subpopulations. For survival analysis in the GEPIA database, patients were stratified into high- and low-expression groups based on the median ZAP70 expression level across all investigated cancer types. This grouping strategy was applied consistently across all analyzed cancer types, with the top 50% of patients categorized as the ‘High’ group and the bottom 50% as the ‘Low’ group according to the GEPIA database. For survival analysis in the GEPIA database, patients were stratified into high- and low-expression groups based on the median ZAP70 expression level across all investigated cancer types.

Single-cell analysis

Single-cell transcriptomic analyses were conducted using lung cancer datasets (NSCLC_GSE131907, NSCLC_GSE139555, NSCLC_GSE148071) obtained from the Tumor Immune Single-cell Hub (TISCH) database. Additional NSCLC datasets (NSCLC_GSE140819, NSCLC_GSE139555, NSCLC_GSE131907) were retrieved from the scTIME Portal.

Quantitative real-time polymerase chain reaction (qRT-PCR)

Seven lung cancer tissue specimens were obtained from Hunan Provincial People’s Hospital, comprising samples from 4 male and 3 female patients. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Hunan Provincial People’s Hospital (No. LY-2023-16). The informed written consent from all participants or next of kin was obtained.

RNA extraction was performed using Trizol reagent in combination with RNase-free grinding beads placed in EP tubes, and the samples were subsequently lysed through ultrasonic treatment. Complementary DNA (cDNA) synthesis and qRT-PCR assays were carried out using the Takara kit (Table 1).

Western blot

Lung cancer samples were homogenized in RIPA lysis solution supplemented with protease inhibitors (Applygen, Beijing, China). Total proteins were fractionated (Servicebio, Wuhan, China) and electroblotted onto PVDF (Millipore, Burlington, MA, USA). The PVDF were then exposed overnight at 4 ℃ to rabbit anti-ZAP70 antibody (1:1,000; 12313S, Cell Signaling Technology, Danvers, MA, USA) and rabbit anti-β-actin antibody (1:5,000; 66009-1-Ig, Proteintech, Wuhan, China). Following extensive rinsing, goat anti-rabbit IgG (1:5,000; ab6721, Abcam, Cambridge, UK) was applied for 2 h.

Statistical analysis

SPSS version 22.0 with unpaired t-tests was used for analysis. Data are expressed as mean ± standard deviation (SD). Statistical significance: P<0.05 (*), P<0.01 (**), P<0.001 (***), and P<0.0001 (****).

Results

Analysis of the expression of ZAP70 in cancers

We first analyzed ZAP70 expression across multiple cancer types. In normal samples, ZAP70 showed high expression in the spleen, small intestine, lung, colon, and liver (Figure 1A). Pan-cancer analysis revealed significantly reduced ZAP70 mRNA expression in COAD, LUSC, SKCM, and THCA compared with normal tissues, while ZAP70 was upregulated in HNSC, KIRC, KIRP, LIHC, PRAD, and STAD (Figure 1B, the sample sizes of cancer patients and NC from TIMER2 see Table S1). Protein expression data from the CPTAC portal further showed elevated ZAP70 levels in clear cell RCC, UCEC, PAAD, HNSC, and glioblastoma, but reduced levels in breast, colon, ovarian, lung, and liver cancers (Figure 1C). We further validated the expression profile of ZAP70 by incorporating data from the GEPIA database. This additional analysis confirms that ZAP70 is significantly downregulated in both LUAD and LUSC compared to normal lung tissues (Figure S1). These findings highlight the heterogeneous expression of ZAP70 across different tumor types. Collectively, these results demonstrate substantial alterations in ZAP70 expression at both the mRNA and protein levels across multiple cancers.

Figure 1 Expression profile of ZAP70 in normal tissue and cancer tissue. (A) ZAP70 expression in normal tissues. (B) Comparison of the mRNA levels of ZAP70 expression between cancer patients and NC from TIMER2. (C) The assessment of ZAP70 protein expression levels through the CPTAC Data Portal. Blue: normal control; red: cancer patients. *, P<0.05; **, P<0.01; ***, P<0.001. CPTAC, Clinical Proteomic Tumor Analysis Consortium; NC, normal control; nTPM, normalized transcripts per million; TPM, transcripts per million; ZAP70, zeta-chain-associated protein kinase 70 kDa.

The prognostic value of ZAP70 in pan-cancer analysis

In order to assess the prognostic significance of ZAP70 in different cancers, we conducted a comprehensive evaluation of its expression via the GEPIA database (Figure 2). Our findings revealed that low ZAP70 expression in SKCM, LUAD, HNSC, and LIHC was correlated with unfavorable prognosis, while high ZAP70 expression in KIRC was also associated with poor prognostic outcomes.

Figure 2 Kaplan-Meier survival analysis showing the association between ZAP70 expression and patient outcomes across cancers, based on GEPIA database data. GEPIA, Gene Expression Profiling Interactive Analysis; HR, hazard ratio; TPM, transcripts per million; ZAP70, zeta-chain-associated protein kinase 70 kDa.

ZAP70 mRNA expression and immune infiltration in pan-cancer

To assess the link between ZAP70 expression and immune infiltration, the TIMER2 resource was analyzed. Elevated ZAP70 levels were closely associated with increased infiltration of diverse immune cells across the majority of tumor categories (Figure 3).

Figure 3 Correlation between ZAP70 mRNA expression and immune infiltration in pan-cancer. NK, natural killer; ZAP70, zeta-chain-associated protein kinase 70 kDa.

Prognostic and diagnostic roles of ZAP70 in lung cancer

To identify the most promising candidate for further mechanistic investigation, we performed a systematic screening based on ‘expression consistency’ and ‘clinical relevance’ across multiple omics levels (Table 2). While ZAP70 exhibited diverse expression patterns across various malignancies, LUAD emerged as the primary focus due to its high degree of cross-omic alignment. To evaluate its diagnostic and prognostic potential, we examined ZAP70 expression in relation to clinicopathological characteristics (Figure 4A, the specific sample size in Table S2). Low ZAP70 expression was significantly associated with T2 classification, stage IV disease, and M1 metastasis. K-M analysis showed that patients with lower ZAP70 expression had markedly worse outcomes (Figure 4B).

Figure 4 Clinical significance of ZAP70 in LUAD. (A) Association between ZAP70 expression and clinical phenotypes in LUAD. (B) Kaplan Meier survival analysis illustrating the relationship of ZAP70 expression with OS, FP, and PPS. *, P<0.05; **, P<0.01; ****, P<0.0001. CI, confidence interval; FP, first progression; FPKM, fragments per kilobase of transcript per million mapped reads; HR, hazard ratio; LUAD, lung adenocarcinoma; M, metastasis; N, node; OS, overall survival; PPS, post-progression survival; T, tumor; ZAP70, zeta-chain-associated protein kinase 70 kDa.

ZAP70 expression dynamics revealed by single-cell analysis

Using single-cell datasets from the TISCH, we mapped ZAP70 expression across immune cell populations in lung cancer (Figure 5A). Analysis of NSCLC datasets from the scTIME Portal further showed pronounced ZAP70 enrichment in cycling T cells (Figure 5B,5C). These findings suggest that ZAP70 may play an important role in immune cell regulation and could influence responses to immunotherapy.

Figure 5 Single-cell profiling of ZAP70 expression in LUAD. (A) ZAP70 expression patterns at single-cell resolution derived from the scRNA-seq TISCH database. (B,C) Characteristics of ZAP70 expression in T-cell subsets. (B) X-axis: UMAP_1; Y-axis: UMAP_2. DC, dendritic cell; LUAD, lung adenocarcinoma; NK, natural killer; NSCLC, non-small cell lung cancer; nTPM, normalized transcripts per million; TISCH, Tumor Immune Single-cell Hub; TPM, transcripts per million; ZAP70, zeta-chain-associated protein kinase 70 kDa.

We then examined ZAP70 expression across T cell subsets in LUAD (Figure 6A). Consistent with database analyses, ZAP70 was primarily expressed in T cells (Figure 6B,6C). T cells were isolated and further subdivided (Figure 6D) into CD4⁺ naïve, effector, regulatory T cell (Treg), exhausted, memory, activated, and γδ T cells, as well as CD8⁺ naïve, effector memory, memory, effector, GZMK⁺ effector, KLRC1⁺ effector, cytotoxic, exhausted, proliferating (MKI67⁺), and γδ T cells. Compared with adjacent normal tissue, LUAD tissue showed reduced proportions of Tregs and effector T cells, but increased memory T, and CD8⁺ cytotoxic T cells (Figure 6E). Notably, the proportion of cells with lower ZAP70 expression was markedly increased in LUAD samples (Figure 6F,6G).

Figure 6 Single-cell transcriptomic mapping of ZAP70 expression in LUAD. (A) UMAP of major immune cell populations in LUAD. (B) Feature plot showing ZAP70 expression across cells. (C) Violin plots of ZAP70 and lineage markers in mast cells, myeloid cells, T cells, and B cells. (D) UMAP of T cell subclusters and their composition in LN and LT. (E) Proportions of individual T cell subsets in LN and LT. (F) Sample-wise proportions of ZAP70^hi and ZAP70^low T cells in LN and LT. (G) Comparison of ZAP70^hi and ZAP70^low T cell fractions between LN and LT. LN, normal lung; LT, LUAD tissue; LUAD, lung adenocarcinoma; UMAP, Uniform Manifold Approximation and Projection; ZAP70, zeta-chain-associated protein kinase 70 kDa.

Functional analysis of ZAP70 in LUAD

We explored the biological significance of ZAP70 in patients from the TCGA LUAD cohort (n=253) to identify key DEGs for functional enrichment. Gene Ontology (GO) analysis (Figure 7A) indicated that ZAP70-related genes are enriched in mitotic nuclear division, chromosome segregation and sister chromatid partitioning. Disease Ontology analysis (Figure 7B) further linked ZAP70 to multiple cancer-related processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis (Figure 7C) implicated ZAP70 in cell cycle regulation and motor protein related pathways. Consistently, GSEA (Figure 7D) comparing high- versus low-expression groups showed that high ZAP70 expression is associated with enrichment of DNA replication, p53 signaling, proteasome function, and other cell cycle related pathways.

Figure 7 Functional enrichment of DEGs in LUAD stratified by ZAP70 expression levels. (A) GO enrichment analysis of DEGs between high- and low-ZAP70 groups. (B) Disease Ontology (DO) enrichment highlighting infectious and immune-related diseases associated with ZAP70-related DEGs. (C) KEGG pathway enrichment of DEGs. (D) GSEA plots of immune-related pathways enriched in the high-ZAP70 expression group. BP, biological process; CC, cellular component; DEGs, differentially expressed genes; DO, Disease Ontology; GO, Gene Ontology; GSEA, Gene Set Enrichment Analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; LUAD, lung adenocarcinoma; MF, molecular function; ZAP70, zeta-chain-associated protein kinase 70 kDa.

Experimental validation of ZAP70 expression

To experimentally validate the expression pattern of ZAP70, we analyzed seven paired LUAD tumors and matched adjacent tissues from a real-world cohort (the detailed clinical information for these 7 patients in Table S3). ZAP70 mRNA and protein levels were quantified by qRT-PCR and Western blotting, respectively (Figure 8). Consistent with our bioinformatic findings, ZAP70 expression was reduced, with a more pronounced decrease in patients with advanced disease. These results suggest that therapeutic strategies aimed at enhancing ZAP70 activity may benefit patients with low ZAP70 expression.

Figure 8 Validation of ZAP70 expression in seven paired LUAD and adjacent tissues. (A,B) Western blot analysis of ZAP70 protein. n=5. (C) Relative ZAP70 mRNA expression measured by qRT-PCR. (D) Association between ZAP70 expression and clinical characteristics. N, adjacent tissues, n=7; T, LUAD tissues, n=7. *, P<0.05; **, P<0.01. LUAD, lung adenocarcinoma; N, node; qRT-PCR, quantitative real-time polymerase chain reaction; T, tumor; ZAP70, zeta-chain-associated protein kinase 70 kDa.

Discussion

This study conducted a pan-cancer analysis of ZAP70 and assessed its prognostic value in LUAD using bioinformatics approaches. ZAP70 mRNA and protein levels were broadly reduced across multiple tumor types, with particularly marked decreases in SKCM and LUAD. Low ZAP70 expression was associated with poor prognosis in SKCM, LUAD, HNSC, and LIHC, and negatively correlated with pathological stage in LUAD. Functional enrichment and single-cell transcriptomic analyses indicated that ZAP70 is primarily expressed in T cells and influences T-cell infiltration in LUAD. Independent datasets further confirmed reduced ZAP70 expression in lung cancer. Collectively, these findings support low ZAP70 expression as a prognostic marker associated with adverse outcomes in lung cancer.

ZAP70, a protein tyrosine kinase for T cell activation and differentiation, exhibits predominant expression in T cells (10). It mediates T cell activation through tyrosine phosphorylation, which enhances its kinase activity and triggers downstream signaling cascades. ZAP70 expression has been linked to disease progression, particularly in chronic lymphocytic leukemia, where it serves as a prognostic marker. In addition, increased ZAP70 expression has been reported to suppress laryngeal cancer cell invasion while promoting migration and invasion in prostate cancer cells. However, its specific biological role remains largely undefined.

In this study, we observed reduced ZAP70 expression in LUAD. To clarify its relevance in T cells, we performed single-cell analysis and found that ZAP70 is predominantly expressed in T cells, with expression closely associated with CD4⁺ and CD8⁺ subsets. Recent studies indicate that ZAP70 supports the anti-tumor activity of tumor-infiltrating T cells, whereas ZAP70 inactivation in CD8⁺ T cells attenuates their activation and impairs anti-tumor immunity (7). Conversely, immunomodulatory drugs (IMiDs) can activate ZAP70, thereby enhancing the cytotoxicity of T and natural killer (NK) cells in multiple myeloma (8). By promoting ZAP70 phosphorylation, these agents boost T-cell activation. Collectively, these suggest that reduced ZAP70 expression may limit tumor-infiltrating T cells and weaken anti-tumor immunity in LUAD.

There are several limitations in this study. First, although our computational analyses implicate ZAP70 in LUAD, its precise molecular mechanisms remain to be defined and require validation in vitro and in vivo. Second, despite the promising prognostic value observed, prospective studies with larger cohorts are needed.

Conclusions

Our findings suggest that ZAP70 reflects the immune microenvironment of LUAD and may serve as both a potential therapeutic target and a prognostic biomarker in lung cancer, thereby providing a basis for future clinical translation.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2667/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2667/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2667/prf

Funding: This work was supported by the Hunan Provincial Health Commission (No. 202204013116).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2667/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Hunan Provincial People’s Hospital (No. LY-2023-16). The informed written consent from all participants or next of kin was obtained.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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