Role of SERCA3 in the Prognosis and Immune Function in Pan-Cancer

The sarcoendoplasmic reticulum calcium adenosine triphosphatase (ATPase) 3 (SERCA3), a member of the SERCA protein family, is located at the endoplasmic reticulum. Its main function is to pump Ca2+ into the endoplasmic reticulum and is involved in maintaining intracellular calcium homeostasis and signal transduction, which are very important factors impacting cancer development and progression. However, the specific role of SERCA3 in cancer remains unclear. Our study, for the first time, comprehensively analyzed the SERCA3 expression profile in multiple cancers and its prognostic value in different cancers using bioinformatics. Furthermore, TCGA database was applied to evaluate the certain correlation of SERCA3 expression with immune modulator genes, immune checkpoints, immune cell infiltration, TMB, and MSI. The results revealed that in many cancers, SERCA3 expression was markedly decreased, which was related to poor prognosis. Additionally, we noticed that SERCA3 expression was correlated with TNM classification and WHO cancer stages in some cancer types. The Pearson correlation analysis showed that SERCA3 expression was closely associated with chemokines, chemokine receptors, MHC, immune activation genes, and immunosuppressive genes. In most cancer types, SERCA3 expression was also associated with immune checkpoints, including PDCD1 and CTLA-4. Further analysis suggested that SERCA3 was significantly correlated with CD8+ T cells, and regulatory T cells. Additionally, pan-cancer analysis confirmed that SERCA3 expression was related to TMB and MSI. In conclusion, these results offer a new insight into the functions and effects of SERCA3 in pan-cancer, and further provide some basis for considering SERCA3 as a potential cancer treatment target and biomarker.


Introduction
Cancer, a major cause of death worldwide, imposed a heavy burden on society [1][2][3][4]. Cancer incidence and mortality are exceptionally high. Global cancer cases increased by 19 million in 2020, and nearly 10 million deaths due to cancer were recorded. Furthermore, America cancer cases expected to rise by 1.9 million, and new cancer deaths are expected to reach 60,936 by 2022 [3,5]. Te rapid development of cancer immunotherapy in recent years has improved the prognosis of some cancer patients; however, immune checkpoint inhibitors have not achieved satisfactory results in most cancer cases [6][7][8]. Tis may be attributed to the susceptibility of cancer to mutations and drug resistance, which signifcantly limit cancer screening and treatment [9,10]. Terefore, identifying new therapeutic targets or biomarkers is important for the early screening and successful treatment of cancer.
Te sarcoendoplasmic reticulum calcium adenosine triphosphatase (ATPase) 3 (SERCA3) enzyme belongs to the SERCA protein family and is found in the endoplasmic reticulum. It pumps calcium ions (Ca 2+ ) from the cytoplasm into the endoplasmic reticulum, which is the main calcium-storing organelle. In most cells, it is mainly involved in maintaining homeostasis of endoplasmic reticulum Ca 2+ and the intracellular Ca 2+ concentration [11][12][13]. Being the second messenger of intracellular signal transduction, Ca 2+ is an important regulator of cellular signaling activities, and intracellular Ca 2+ disorders can afect gene expression, proliferation, diferentiation, and cell death [14][15][16]. Cumulative evidence suggests that Ca 2+ signal transduction is crucial for cancer development. Te growth, proliferation, invasion, death, and drug resistance of cancer cells are regulated by Ca 2+ [17][18][19][20]. It has been reported that abnormal changes in amplitude of cytoplasmic free Ca 2+ concentration and duration of Ca 2+ elevation may promote breast cancer cell proliferation and invasion [17,21]. Te same phenomenon was confrmed in endometrial and colorectal cancers [22,23].
Intracellular calcium homeostasis is a crucial factor that afects the occurrence and development of cancers. SERCA3 is one of the most important calcium modulators involved in maintaining intracellular calcium homeostasis by modulating the entry of cytoplasmic calcium into the endoplasmic reticulum. However, no pan-cancer study of SERCA3 has been reported, and the role of SERCA3 in pan-cancer remains unknown. Our study elucidated the SERCA3 expression profle and examined correlations between SERCA3 expression and cancer prognosis; moreover, the correlation between SERCA3, tumor-node-metastasis (TNM) classifcation, and World Health Organization (WHO) cancer stages was also detected. Te relationship between SERCA3 with immune modulator pathways, immune checkpoints, and immune cell infltration levels was analyzed. Finally, we examined the correlation of SERCA3 expression with cancer mutation burden (TMB) and microsatellite instability (MSI). We provided a study of SERCA3 in pan-cancer, focusing on the role of SERCA3 in cancer immune functions and the potential mechanisms of cancer immunotherapy.

SERCA3 Expression in Human Pan-Cancer. Te Cancer
Genome Atlas (TCGA) pan-cancer database (PANCAN, N � 10535, G � 60499, year: updated in 2022) was downloaded from the UCSC Cancer Genome Browser (https:// xenabrowser.net/), from which SERCA3 expression data for each cancer type were extracted [24,25]. Furthermore, we screened data from the Primary Tumor (year: updated in 2022) and Solid Tissue Normal (year: updated in 2022) databases to compare SERCA3 expression between diferent cancer types. Te fnal cancer expression data were obtained after eliminating cancer types from less than three sample. All expression data were standardized by log2 conversion. SERCA3 expression in diferent cancers was calculated using R software (version 3.6.4) [24]. Additionally, we used the Human Protein Atlas (HPA) database to investigate SERCA3 expression in normal and cancer tissues in humans.

Association of SERCA3 Expression with TNM Classifcation and WHO Cancer Stages.
We selected SERCA3 expression data from TCGA-LAML (year: updated in 2022) and Primary Tumor databases. Te fnal cancer expression data were obtained after eliminating cancer types from less than three sample. Using R software to correlate SERCA3 expression with TNM classifcation and WHO cancer stages in various types of cancer. All expression data were standardized via log2 conversion.

Prognostic Analysis.
In addition to extraction of data from TCGA-LAML, TCGA-SKCM (year: updated in 2022), and Primary Tumor databases, prognostic data for TCGA within 1 month of follow-up were also obtained from a previously published TCGA prognosis study [26], and pancancer data were obtained after eliminating the cancer types with less than 10 samples. Applying hazard ratios (HR) and 95% confdence intervals (CI) to assess overall survival (OS).

Relationship between SERCA3 Expression and Immune
Modulator Pathways and Immune Checkpoints. Te SERCA3 expression data and data on fve immune modulator pathways, including chemokines, chemokine receptors, major histocompatibility complex (MHC), immune activation genes, and immunosuppressive genes, were extracted from TCGA. Further, we excavated TCGA-LAML and Primary Tumor data and plotted the Spearman correlation analysis heat map of SERCA3 expression and fve immune modulator pathways.
Moreover, we extracted expression data on two immune checkpoints, including 24 immune checkpoint inhibitors and 36 immune checkpoint stimulators, from a previous study [27]. We screened the cancer samples as follows: TCGA-LAML and Primary Tumor. All expression data were standardized by log2 conversion. Te Pearson correlation between SERCA3 level and two immune checkpoint pathways was calculated.

SERCA3 Expression and Immune Cell Infltration.
Mapping the obtained SERCA3 expression data of each cancer type to Gene Symbol, using CIBERSORT [28,29] in R software IOBR (version 0.99.9) [30]. Immune cell infltration levels of each cancer type were assessed, the corr.test function of the R software psych (version 2.1.6) was used to calculate the Spearman correlation coefcient.

Association of SERCA3 Expression with TMB and MSI.
SERCA3 expression and TMB data were extracted from TCGA and Primary Tumor. Downloaded TCGA level 4 simple nucleotide variation data processed by MuTect2 software from GDC [31]. TMB for each cancer type was estimated using the "maftools" R package (version 2.8.05). Subsequently, SERCA3 expression and TMB data were integrated. Te fnal cancer expression data were obtained after eliminating cancer types from less than three sample. All expression data were standardized via log2 conversion.
Spearman's correlation between SERCA3 expression and TMB was then compared.
Subsequently, we obtained the MSI score of each cancer type from a previous study [32], and the MSI score and SERCA3 expression data were integrated; less than three samples of cancer types were eliminated, and the fnal cancer expression data was acquired. All expression data were standardized via log2 conversion. Spearman correlation between SERCA3 expression and MSI was then compared.

Statistical
Analysis. Diferential expression of SERCA3 in various cancer types was evaluated using Student's t-test. Kruskal-Wallis test and Mann-Whitney U-test were used to calculate the relationship of SERCA3 expression with TNM classifcation and WHO cancer stages. HR and p-values for overall survival were assessed using the log-rank test. Spearman correlation and Pearson's correlation were applied to detect the correlation between SERCA3 expression and immunity. All analyses were performed using R software (IOBR, psych, and maftools). p ≤ 0.05 was considered a statistically signifcant diference.

Prognostic Analysis of SERCA3 Expression.
Te relevance between the expression of SERCA3 and the OS in cancer patients was evaluated. SERCA3 is a protective factor in most cancers, HR and 95%CI for cancers were PAAD (0.

Relationship between SERCA3 Expression and Immune
Modulator Pathways and Immune Checkpoints. Based on TCGA database, we analyzed the connection between SERCA3 expression and the fve immune modulator pathways. Te heat map revealed that SERCA3 expression was closely correlated with the level of chemokines and chemokine receptors, such as CCL5, CCL17, CCL22, CCR4, and Immunotherapy is increasingly becoming an important means of cancer treatment, the application of immune checkpoint inhibitors has improved the prognosis of some cancer patients [33,34]. Terefore, we collected the expression data of 60 common immune checkpoints [27], using Pearson's correlation analyzed the relationship between SERCA3 expression and immune checkpoints. Our results suggested that in most types of cancer, SERCA3 expression was distinctly related to immune checkpoints, such as TLR4, ICOS, CTLA-4, PDCD1, and CD27 ( Figure 6).

Immune Cell Infltration
Analysis. Te abundances of 22 immune cells were calculated using CIBERSORT, the relationship between SERCA3 expression and immune cell infltration levels in diferent cancer types was analyzed. We noticed that the abundance of many immune cells was correlated with SERCA3 expression. SERCA3 expression was positively connected with CD8 + T cells, regulatory T (Treg) cells, M1 macrophages, and naïve B cells, while negatively correlated with M0 macrophages, M2 macrophages, and eosinophils ( Figure 7).

Association of SERCA3 Expression with TMB and MSI.
TMB and MSI afect the sensitivity of immunotherapy and prognosis. Te current study analyzed whether there is a correlation between SERCA3 expression and TMB and MSI in various cancers. From the analysis results it seems that SERCA3 expression was positively correlated with TMB in some cancers. A p-value for these cancers were UCEC
Analysis of the results of the TCGA database revealed that the expression of SERCA3 was correlated with the chemokine receptors CCR4, which plays a signifcant role in immune regulation and is regarded as a potential therapeutic target in bronchial asthma. CCR4 is also highly expressed in adult T-cell leukemia/lymphoma (ATLL) and cutaneous Tcell lymphoma (CTCLs) [37]. Li et al. showed that overexpression of CCR4 mediates the chemotactic response of breast cancer cells to CCL17 and accelerates the growth and metastasis of breast cancer [38]. Our results found a correlation between the level of SERCA3 and immune-activating and immunosuppressive genes, including PDCD1 (PD-1), CTLA-4, TIGIT, and ICOS. By analyzing the correlation between SERCA3 expression and immune checkpoints we found that SERCA3 expression was related to immune checkpoints, including CTLA-4, PDCD1, and ICOS in most types of cancer. PDCD1 and CTLA-4 antibodies, which are immune checkpoint inhibitors, have been approved for the treatment of cancers including non-small cell lung cancer (NSCLC) and melanoma, and have improved the prognosis of patients with these cancers [39,40]. Tese results proved that SERCA3 might partially afect immune checkpoints.
Te tumor microenvironment (TME) is pivotal in regulating cancer progression and can predict treatment outcomes [41][42][43]. Te composition of the TME is complex and includes vascular vessels, immune infltrates, fbroblasts, and the extracellular matrix [44][45][46]. Te immune cells, an important part of the TME, show an apparent impact on cancer development [46,47]. Investigating the association of SERCA3 expression and levels of immune cell, we detected   Type  HLA-DOB   HLA-DOA  HLA-DPA1  HLA-DPB1  HLA-DQA1   HLA-DQA2  HLA-DQB1  HLA-E   HLA-B  HLA-F  HLA-A  HLA-C   TAP1  TAP2  TAPBP  R2M   HLA-DRA  HLA-DRB1  HLA-G   HLA-DMA  HLA-DMB   THYM  LAML  AC  PAAD  LUAD  BRCA  STAD  UCEC  SARC  ESCA  COAD  COADREAD  PRAD  UC  REA  STES  BLCA  CESC  DLB  PCPG  THCA  TGCT  GBMLGG  LGG  GBM  OV  KIRC  KIRP  CHOL  MESO  HNSC  LUSC  LIHC  UVM  KIPAN  KICH  SKCM   (c)   Type  C10orf54  TNFRSF8  KLRK1   LTA  TNFRSF17   TNFRSF13B   TNFSF13B  KLRC1   TNFRSF13C   TMIGD2   CXCR4   CD40LG   CD27   CD70  IL6   CD48   ICOS   CD28   ENTPD1  TMEM173  TNFRSF14   TNF8F4   TNFSF13  TNFSF14   TNFSF15   TNFSF18  MICB   NT5E  HHLA2  BTNL2   CXCL12   CD86   IL2RA   CD80   TNFSF9  ICOSLG  IL6R   TNFRSF9  RAETIE  PVR  ULBP1  CD276   TNFRSF25   TNFRSF18 CD40 TNFRSF4  that SERCA3 expression was positively associated with M1 macrophages and CD8 + T cells levels, whereas it showed a negative correlation with the levels of M0 and M2 macrophages. Cytotoxic CD8 + T cells are the main immune cells against pathogens and neoplastic cells. Te cancer immunotherapy partially strengthens CD8+ T cell activity leading to the reduced escape of cancer cells from the immune system and then establishing durable and efcient anti-tumor immunity [48,49]. SERCA3 may play a protective role in most cancers by increasing T cell infltration. Previous research reported that an increased M2/M1 macrophage ratio promotes cancer progression [50]. SERCA3 expression was positively correlation with M1 macrophage levels while negatively correlation with M2 macrophage levels, further providing a basis for the protective role of SERCA3 in most cancer types. Tese results suggest that SERCA3 may interfere with the prognosis of various cancers by regulating the expression of multiple immune cells. Finally, we assessed the correlation among SERCA3 expression, TMB, and MSI. Te more somatic mutations in tumors, the newer antigens that may form, and TMB can be used to evaluate the number of new tumor antigen loads [51]. MSI is an indicator of DNA mismatch repair (MMR) defects. TMB and MSI were used as biomarkers to predict the efcacy of immune checkpoint blockade (ICB) [52,53]. By pan-cancer analysis we found that SERCA3 expression correlated with TMB and MSI, providing evidence for SERCA3 as a potential predictor of ICB therapy.
However, our study had some limitations. First, it was based on bioinformatics and diferent databases; methods of generating data may have impacted the results. Second, TCGA database lacks data on immunotherapy; hence, we cannot further analyze the indications for immunotherapy. Overall, our study systematically analyzed the association of SERCA3 expression with prognosis, immune modulator genes, immune checkpoints, immune cell infltration, TMB, and MSI, which can provide information to further understand the role of SERCA3 in cancers and its relationship with the immune responses. It also provides a basis for considering SERCA3 as a potential cancer treatment target and biomarker. A potential challenge in the future will involve the development of new therapeutic methods related to the specifc targeting of SERCA3 to limit the development and progression of cancer.

Conclusions
Tis research revealed that SERCA3 expression was significantly decreased in most types of cancer, cancer patients with reduced SERCA3 expression tend to have a poor prognosis. Moreover, we analyzed the correlation of SERCA3 expression with immune regulatory gene expression, immune checkpoints, immune cell infltration, TMB, and MSI. We speculated that SERCA3 might afect cancer progression by regulating the TME, especially immune cells. Tese results provide new ideas for the function and role of SERCA3 in pan-cancer and provide a theoretical basis for considering SERCA3 as a potential cancer treatment target and biomarker.

Disclosure
Jiajia Li and Xionghui Li are co-frst authors.

Conflicts of Interest
Te authors declare no commercial or fnancial conficts of interest related to this study.