Using the data from the TCGA, CCLE, and GTEx databases, the MEX3A gene across different tumors was comprehensively analyzed, focusing on molecular characteristics such as gene expression, mutations, and MSI. CCLE data indicated pronounced MEX3A expression in lung tissues, with significant expression also observed in breast and ovarian tissues. This aligns with existing research findings. For instance, Shi, XBA et al. demonstrated MEX3A's role in promoting breast cancer by modulating PIK3CA [4], while Zhang, PP et al. suggested that MEX3A affects ovarian cancer cell functions by influencing immune infiltration in the tumor microenvironment [18]. Additionally, Liang, JH et al. identified MEX3A as a prognostic marker and therapeutic target for LUAD, attributing its impact to the downregulation of LAMA2 expression [10].
Analysis of MEX3A expression and prognosis in 33 tumor types from the TCGA database revealed differential expression between cancerous and normal tissues across various cancers, with prevalent overexpression in most tumor types except KICH, where MEX3A expression is reduced compared to normal tissues. At present, the relationship between MEX3A and KICH is underexplored, leaving the mechanisms underlying this observation unclear and presenting a potential area for future research.
Prognostic analyses revealed that elevated MEX3A expression correlates with poorer outcomes in ACC, KICH, LIHC, MESO, PCPG, SARC, THCA, and UCEC. Conversely, in LAML, higher MEX3A levels were associated with a more favorable prognosis, suggesting a potential antitumor effect of MEX3A. Yang, DQ et al. reported that MEX3A upregulation in liver cancer significantly correlates with poor survival, highlighting its role as an independent prognostic marker for liver cancer [5]. Furthermore, MEX3A expression is linked to OS in ACC, KICH, LAML, LIHC, MESO, PCPG, SARC, THCA, and UCEC, indicating its predictive potential across these cancers.
This study focused on the relationship between MEX3A expression, immune cell infiltration, and tumor immunity. Data on six types of immune infiltrating cells across 33 cancers from the TIMER database were analyzed to assess the correlation with MEX3A expression. Notably, in LUAD, SARC, and THCA, a significant correlation was observed between MEX3A expression and immune infiltration, aligning with OS-related findings. Specifically, MEX3A expression inversely correlated with monocyte and M1 macrophage infiltration in SARC but positively with M0 macrophages, plasma B cells, and naive B cells. Similar patterns were observed in THCA, LUAD, and SARC, underscoring MEX3A's role in modulating tumor immunity in these cancers. Given the growing importance of identifying immune biomarkers, this study's insights into the relationship between MEX3A expression and immune cells may inform targeted immunotherapy strategies, particularly as tumor-infiltrating lymphocytes (tumor-associated macrophages, TAMs) and tumor-infiltrating neutrophils (TINs) influence chemotherapy and immunotherapy outcomes [19].
Immune checkpoint inhibitors (ICIs) have emerged as a novel and promising approach in cancer therapy, targeting the regulatory pathways of T cells to modulate immune cell functions. Immune checkpoints play a crucial role in regulating the balance between stimulatory and inhibitory pathways of the immune system [20]. In the context of cancer, immune checkpoint signaling facilitates immune escape, contributing to tumor progression and invasiveness. Currently, the most effective ICIs are monoclonal antibodies that target the programmed death-1 (PD-1) receptor or its ligand PD-L1 [21]. Despite their potential, clinical responses to ICIs targeting PD-L1 or CTLA-4 are limited to a subset of patients [22], underscoring the need for research into new inhibitory checkpoints and their ligands to enhance the scope of checkpoint inhibition therapy.
This study examined the association between MEX3A expression and approximately 40 common immune checkpoints. In KICH, SARC, and UCEC, MEX3A expression correlated with immune checkpoints VSIR, CD86, and TNFRSF14D. Additionally, KICH and SARC showed a strong correlation with the immune checkpoint TNFRSF25. Across 25 cancer types, MEX3A expression was positively associated with CD276, with similar findings observed in BRCA and LUAD. Conversely, MEX3A expression was inversely related to VSIR in these tumors. Further investigation into the relationship between MEX3A expression and novel immune checkpoints may yield insights for developing new immunotherapeutic strategies and establishing potential therapeutic targets.
The effectiveness of immune checkpoint blockade therapy is often determined by the immunogenicity of the tumor, with tumors showing low immunogenicity due to sparse T-cell infiltration showing limited responses to such therapies [23]. Normally, immune checkpoint molecules down-regulate activation signals from costimulatory molecules, a mechanism critical for maintaining tolerance and preventing autoimmunity. However, cancer cells use this pathway to suppress T-cell activation and function, facilitating immune evasion and promoting tumor progression [24].
Tumor neoantigens, novel antigens arising from mutations within tumor cell genes, represent a class of abnormal proteins not found in normal cells, primarily generated through point mutations, deletions, and gene fusions. Vaccines can be designed based on tumor cell mutations, leveraging the immunogenic potential of these neoantigens offering a therapeutic strategy [25]. Analysis of neoantigen counts across various tumor samples revealed a positive correlation between MEX3A expression and the production of neoantigens in LUAD, LUSC, BRCA, BLCA, PRAD, and LGG, with LUAD showing the strongest correlation (R = 0.261). Conversely, in UCEC, a negative correlation exists between MEX3A expression and neoantigen count, aligning with poorer OS outcomes in cases of elevated MEX3A expression. This inverse relationship suggests that higher MEX3A levels may reduce neoantigen production, complicating the development of neoantigen-based vaccines and immunotherapy for UCEC.
TMB is considered a reliable biomarker for predicting the outcome of immunotherapy [26]. TMB quantifies the total count of somatic mutations within a specified region of the tumor genome. The predictive value of TMB for immunotherapy efficacy is attributed to the generation of neoantigens from somatic mutations. These neoantigens, processed into short peptides and presented by major histocompatibility complex (MHC) molecules on cancer cell surfaces, trigger an immune-mediated attack. To evade this, tumors often weaken the activity of proteins acting as immune checkpoints, thereby suppressing the immune response [27]. ICIs can revive the immune system by blocking these proteins, increasing the immune recognition of cancer cells. As neoantigens arise from mutations, a higher mutation count (reflected by elevated TMB) increases the likelihood of T-cell recognition and cancer cell elimination. Previous research has demonstrated a correlation between high TMB and improved outcomes from immunotherapy in cancer patients [28], validating TMB as a reliable biomarker for immunotherapy prognosis. Furthermore, MSI—variations in microsatellite length due to insertions or deletions, resulting in the emergence of new microsatellite alleles —has been shown to influence chemosensitivity and patient prognosis in certain cancers [29]. Our analysis revealed a positive correlation between MEX3A expression and TMB in THYM, BRCA, KICH, LAML, LUAD, and PRAD. Similarly, MEX3A expression positively correlates with MSI in BRCA and LUAD. These findings suggest that MEX3A expression may influence tumor mutational profiles, offering potential for its use in tumor screening, immunotherapy selection, and therapeutic efficacy and prognosis assessment in future studies.
The MMR system is a crucial intracellular mechanism that corrects replication errors in DNA. Dysfunction in key MMR genes leads to uncorrected DNA replication errors, resulting in an increased rate of somatic mutations [30]. Analysis of the association between mutations in five MMR genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) and MEX3A expression in BRCA and LUAD revealed distinct patterns. In BRCA, MEX3A expression was positively correlated with four DNA repair genes (MSH2, MSH6, PMS2, and EPCAM) but negatively with MLH1. Conversely, in LUAD, MEX3A expression positively correlated with all five DNA repair genes. These observations suggest a potential role for MEX3A in the pathogenesis of BRCA and LUAD, highlighting its role as a molecular target for diagnosing or treating these cancers or specific subtypes.
Oncogenic signaling pathways, which regulate cell growth, apoptosis, and cell cycle progression, are frequently altered in cancer, marked by varied activation frequencies and complex inter-pathway crosstalk [31]. Key pathways, such as the RTK-RAS pathway, are commonly changed across different cancer types, while others may be specific to certain malignancies [32]. Prior studies have identified MEX3A as a tumor promoter and potential prognostic marker in LUAD and breast cancer through its regulation of the PI3K/AKT signaling pathway [10; 33]. Our findings corroborate these results, showing statistically significant associations between MEX3A expression and the PI3K/AKT signaling pathway (P = 0.0452, FDR = 0.12).
Jiang H et al. reported that the hMEX3A gene primarily influences the G1/M phase of cell division, suggesting its involvement in cell transformation. They also reported that MEX3A expression is significantly upregulated in human gastric cancer, with levels more than 1.5 times higher than in adjacent non-tumorous tissues [34]. This observation underscores the potential of MEX3A as a biomarker for the early detection of gastric cancer and as a therapeutic target. Furthermore, functional assays, including transwell chamber and wound healing assays, demonstrated that the knockdown of the hMEX3A gene significantly affects the metastatic abilities of cancer cells, implicating MEX3A in cancer progression and metastasis [35].
Using microarray comparative genomic hybridization technology, MEX3A overexpression was identified in nephroblastoma. Pereira B [16] further elucidated MEX3A's role in disrupting intestinal differentiation and cell polarization by modulating CDX2 levels in gastric and rectal cells. This action interferes with the cell cycle process, suggesting a potential oncogenic function of MEX3A. Additionally, it has been reported that MEX3A facilitates glioma tumorigenesis through its involvement in ubiquitination processes [36].
In summary, MEX3A gene expression correlates with immune cell proliferation, neoantigen production, TMB, and MMRs in BRCA and LUAD. This suggests a pivotal role for MEX3A in future tumor screening, immunotherapy strategies, and therapeutic outcomes and prognosis assessment. Additionally, exploring checkpoint proteins such as CD276 and VSIR may represent a significant advancement in oncological research. In the context of osteosarcoma, significant correlations were observed between MEX3A expression and immune cell proliferation, neoantigen production, and TMB, indicating that regulating MEX3A expression could potentially prevent osteosarcoma development and improve its prognosis.
Furthermore, MEX3A gene expression is linked to disease progression and earlier tumor recurrence in some patients, underscoring the importance of enhanced care and monitoring for individuals with elevated MEX3A expression. Identifying high-risk patients, formulating personalized treatment plans, and strengthening the care and follow-up of these patients potentially improve their prognosis.
Recent advances underscore the reliability of genetic markers over traditional TNM staging and histopathological diagnosis in predicting tumor outcomes [37]. Confirmatory analyses validated the significant overexpression of the MEX3A gene in BLCA, GBM, KICH, OV, PAAD, and LIHC, reinforcing the significance of MEX3A as a biomarker in these malignancies.
Even though we integrated information across multiple databases about the role of MEX3A in pan-cancer, this study still had limitations. (1) Since the OS core data in the GEO database are of different properties, different intervention methods, and different types of OS cores, the OS core data are not available in the GEO database. In this study, we were not able to analyse multiple GEO databases together, and only a single dataset was analysed, but the dataset GSE was not analysed. (2) The microarray and sequencing data about MEX3A were collected by analyzing tumor tissue information, the immune cell marker analysis could have introduced systematic bias. (3) This study only conducted a bioinformatics analysis concerning the role of MEX3A in pancancer across different databases, and in vivo and in vitro experiment verification and further mechanism research is also needed.