Effective cancer biomarkers will contribute to the development of tumor precision medicine. Researches on the role of SPP1 in tumorigenesis and development have been extensively carried out in a variety of malignant tumors, and made a lot of progress. However, due to the limited types of cancers currently studied and the lack of sufficient studied populations, whether SPP1 can be a suitable cancer predictor is still a tricky problem. As immunotherapy becomes popular in cancer treatment, identifying SPP1's anomalous changes in the pathological process of cancer will not only help to understand the mechanism of cancer lesions, but also be of great help for individualized treatment. TCGA contains 33 types of cancer, covering multiple data such as genome, transcriptome, epigenetics, proteome, etc., which can help cancer researches and improve the technology of cancer prevention, diagnosis and treatment. Therefore, based on the TCGA database, we use pan-cancer analysis methods to reveal the functional significance of SPP1 in cancer.
Identifying abnormal genetic expression in tumor is very important for individualized treatment, as it pointedly improves clinical outcomes (10). Our differential analysis suggests that SPP1 expression is up-regulated in most tumors, and high expression is associated with poor prognosis and can be used as a risk prognostic factor. It is worth noting that SPP1 is down-regulated in some other tumors. Studies have found that SPP1 in colorectal cells can negatively regulate T cell activation by binding to CD44 and promoting cancer progression (11). However, some studies have also proved that the overexpression of SPP1 and the down-regulation of CD44 can inhibit the pathological process of colon cancer (12, 13). This suggests that SPP1 has multiple effects on tumors and may function in multiple ways. The results of GSEA analysis also support this view.
Survival analysis is an important method for clinical evaluation of tumor diagnosis, treatment effect and prognosis. Our study showed that the relationship between SPP1 and cancer survival rate showed different K-M analysis results. In most tumors, up-regulated SPP1 is related to adverse prognoses, such as CESC, GBM, HNSC, LGG, LIHC, PAAD, SKCM, SARC, LUSC, LUAD, GBM, COAD, etc., with higher expression and lower survival. However, high expression levels in UVM show a better prognosis. It suggests that SPP1 has dual effects of promoting tumor and anti-tumor. This may be attributed to different subtypes (SPP1a, SPP1b, SPP1c) in different tissue locations, different molecular functions, and different signal transduction pathways activated to function (13–15). In addition, mining the potential pathways of SPP1 through GSEA is expected to provide a basis for future researches.
Our study found that SPP1 is also related to the clinical stage of the tumor. It is worth noting that the expression levels of COAD, ESCA, and READ in Stage I SPP1 are significantly different from those of Stage I, Stage II and Stage III. Moreover, most tumors have different levels of expression of SPP1 in different stages. These results indicate that SPP1 is expected to become an early diagnostic biomarker for cancer, and can even be used as an indicator for predicting the process stage of a specific tumor and assessing the degree of deterioration.
TME refers to the cellular environment in which tumors exist, including blood vessels, immune cells, fibroblasts, other cells, signal molecules and extracellular matrix (16). Our study proved the immune correlation between SPP1 and tumors through the CIBERSORT analysis of immune cell infiltration content and correlation analysis. In TME, eosinophils can influence local immunity in the disease process, and there is growing evidence that they can exert anticancer effects through multiple pathways. Cytokine signaling and epigenetic signaling in the microenvironment, among others, induce neutrophils to polarize into anti-tumor N1 tumor-associated neutrophils and pro-tumor growth N2 tumor-associated neutrophils. Tumor
cell-associated macrophages (TAM) and M2 type macrophages can promote the occurrence and development of tumors. Zhang Yan et al. found that SPP1 is highly expressed in TAM in human lung adenocarcinoma, and tumor cells can induce M2 type macrophages through SPP1 overexpression, and participate in tumor progression (4). This study further verified that SPP1 is closely related to neutrophils, eosinophils and M2 macrophages, and it is speculated that it can promote immune cells (neutrophils, eosinophils, M2 macrophages) to infiltrate tumors pathological process.
The mechanism by which cancer evades immunity is the target of immunotherapy. Gene co-expression analysis found that SPP1 can participate in tumor immunity through interactions with immune-related genes (CD86, HAVCR2, LAIR1, NRP1, LGALS9, etc.). In addition, it has been reported that SPP1 is related to the drug resistance of breast cancer and lung adenocarcinoma immunotherapy. The above can further infer that SPP1 may be a predictive target of immune resistance, but this requires more in-depth researches to be confirmed.
Gene mutations are one of the main causes of tumors (17). TMB refers to the number of somatic mutations in the tumor genome after germline mutations have been removed. The more neoantigens a tumor produces, the easier it is to be recognized by the immune system, and the better the immunotherapy effect (18). MSI verifies the defect of DNA mismatch repair. The higher the number, the more somatic mutations, the more neoantigens produced, and the better the efficacy of immunotherapy (19). Both TMB and MSI are important predictors of immunotherapy. In this study, we found that SPP1 correlated with TMB in ACC, THYM, STAD, SRAC, PRAD, OV, LGG, KIRC, DLBC and COAD; SPP1 correlated with MSI in SARC, LUSC, LUAD, GBM and COAD. SPP1 may be used as an indicator of the efficacy of a variety of tumor immunotherapy.
In summary, our study shows that SPP1 is an effective prognostic biomarker in some cancer types. Its expression is immune-related, which may provide a basis for developing new targets for cancer diagnosis, treatment and prognostic assessment. However, there are still some limitations in our study. Due to the wide range of cancer types studied, the findings lack adequate support from actual clinical evidence and need sufficient time to be validated.