Overexpression and Prognostic Signi cance of PTPN2 Maybe A Novel Immunotherapy Target in Renal Clear Cell Carcinoma


 Immunotherapy has significantly advanced in clear cell renal cell carcinoma (ccRCC). We aimed to find a new immune-related prognostic biomarker and immunotherapeutic target for ccRCC. We analyzed the expression, survival, and related immune gene marker sets data of PTPN2 in patients with ccRCC from TCGA. PTPN2 expression was increased in ccRCC compared to normal tissue. PTPN2 was closely related to T stage (P = 0.008 ), TNM stage (P = 0.017 ) and Grade (P = 0.002 ). Overexpression of PTPN2 predicted a poor survival in ccRCC (P < 0.001). PTPN2 was also related to six types of tumor immune-infiltrating cells, including B cells, CD8 + T cells, CD4 + T cells, Macrophage, Neutrophils, Dendritic cells. PTPN2 was related CTLA-4 (P = 5.645404E-26, r = 0.4339333) and PDCD1 (P = 5.645404E-26, r = 0.4339333). Furthermore, the survival rate in patients with high PTPN2 and CTLA4 was significantly lower than that other three strata (P < 0.0001). GSEA and GO biological analysis was conducted, which was indicated PTPN2 was involved in many immune and inflammatory pathways, including IL-4, IL-12, CD3 T-cell, CD4 T-cell, intestinal inflammation, systemic inflammatory regulation related factors, and so on. Our results implied that PTPN2 was considered as the potential immune therapeutic target and prognostic biomarker in ccRCC.


Introduction
As the most common pathological subtype of renal cell carcinoma (RCC), clear cell renal cell carcinoma (ccRCC) is associated with high morbidity and poor prognosis 1,2 . To date, surgery is also the primary treatment for most ccRCC; radiotherapy and chemotherapy are largely ineffective in the treatment of ccRCC 3 . To improve the survival of ccRCC, many immune checkpoint inhibitors (ICIs) have been approved by the FDA, such as nivolumab and ipilimumab 4 . However, only a few patients with advanced renal cancer have responded to immunotherapy 5 . So the new immunotherapy target may improve the naïve vision of single target-based immunotherapy 6 . PTPN2 was discovered in T-cells, which is also known as T-cell protein tyrosine phosphatases (TCPTP) 7 .
PTPN2 negatively regulated the pro-in ammatory pathways, such as INF-γ induced Janus kinase (JAK)signaling and STAT signaling et al 8 . The importance of PTPN2 in regulating tumorigenicity pathways were also highlighted. The study showed that PTPN2 was negatively associated with activation of AKT in breast cancer 9 . Grohmedann et al. also demonstrated that depletion of PTPN2 in hepatocytes promoted hepatocellular carcinoma (HCC) in mice 10 . PTPN2 may play a tumor-suppressive role in tumors based on the above studies. A fascinating new study published in Nature has reported that PTPN2 deletion markedly increased the response of tumors to immunotherapy by enhancing interferon-γ-mediated effects on antigen presentation and growth suppression 11 . Besides, Wiede et al. reported that PTPN2 could regulate the production of exhausted CD8 positive T cell subsets and control tumor immunity 12 . Due to the role of PTPN2 in tumor immunity, it may become a new target of immunotherapy. Therefore, in this study, we rstly investigated the expression pro ling and prognostic value of PTPN2 in various solid tumors based on TCGA datasets. Then we focused on kidney renal clear cell carcinoma (KIRC) and tried to pinpoint the meaningful nding for future cancer immunotherapy. In this study, ccRCC was used instead of KIRC.

Results
The expression landscape of PTPN2 in pan-cancer TCGA data Integrated analysis was performed on tumor patients in The Cancer Genome Atlas (TCGA) datasets, a comprehensive database containing 11,000 patients samples. The expression pro ling of PTPN2 was visualized by the TIMER platform based on pan-cancer TCGA data, including 31 different tumor types.
Among 31 types of cancer, the result showed that PTPN2 was expressed in all kinds of cancer, but the expression levels were different. The highest expression was Thymoma (THYM), and the lowest was Liver hepatocellular carcinoma (LIHC). The expression level of other types of cancer is between these two types of cancer. Compared to normal tissue, PTPN2 was over-expressed in KIRC, LIHC, Lung squamous

The Prognostic Role Of Ptpn2 In Kirc
When we further investigate the potential clinical role of PTPN2 in KIRC patients, the results showed PTPN2 was closely related to the T stage (P = 0.008 ), TNM stage (P = 0.017 ), and Grade (P = 0.002 ) ( Table 1). Overexpression of PTPN2 predicted poor survival in KIRC based on the TCGA cohort, which was revealed by the Kaplan-Meier method (P < 0.001) ( Fig. 2A). In the multiple Cox analysis, PTPN2, age, and Grade were independent risk factors for OS. The univariate and multivariate analyses are listed in Table 2.
Furthermore, we established a nomogram to predict the probability of OS in KIRC patients (Fig. 2B). In this model, the Grade stage, TNM stage, age, and PTPN2 expressions have important effects on KIRC overall survival prediction.   (Fig. 3).
To further investigate the underlying mechanism of PTPN2 in KIRC, gene co-expression net analyses were performed by Metascape. These co-expression genes were signi cantly enriched in mitotic cell cycle phase transition, centrosome duplication; DNA-dependent DNA replication; DNA repair; regulation of T cell activation (Fig. 4A). GSEA was performed here to identify the biological gene sets or pathways for PTPN2. we found 560 immune-related terms, including GSE29615_CTRL_VS_DAY3_LAIV_IFLU_VACCINE_PBMC_UP; GSE1460_NAIVE_CD4_TCELL_CORD_BLOOD_VS_THYMIC_STROMAL_CELL_DN; GSE12839_CTRL_VS_IL12_TREATED_PBMC_UP; SE21546_UNSTIM_VS_ANTI_CD3_STIM_SAP1A_KO_DP_THYMOCYTES_UP; GSE16385_UNTREATED_VS_12H_ROSIGLITAZONE_IL4_TREATED_MACROPHAGE_DN et al. (Fig. 4B-E).
For gene set enrichment analysis, a series of GO terms related to immune and in ammatory factors were also found, including CD4 T-cell differentiation-related factors, innate and adaptive responses to vaccination, regulating lipid metabolism and in ammatory response in macrophages and dendritic cells and systemic in ammatory regulation related factors.

Ptpn2 And Immune-related Genes
We acquired the immune-related genes from the ImmPort database. Then we identi ed the correlation between PTPN2 and these immune-related genes. The results showed that PTPN2 was related to many immune-related genes. To our greatest interest, CTLA-4 (P = 8.31E-39, r = 0.495) and PDCD1 (P = 1.22E-14, r = 0.306) were included in these related many immune-related genes. Furthermore, when the patients with KIRC were grouped into four strata by the level of PTPN2 and CTLA-4, the survival rate in patients with high PTPN2 and CTLA4 was signi cantly lower than that other three strata (Fig. 5).

Discussion
We performed an integrative analysis focused on the expression of PTPN2 based on TCGA clinical tumor cases and identi ed the over-expression of PTPN2 in KIRC. Next, we found PTPN2 was a prognostic marker in KIRC. Furthermore, the multivariate analysis demonstrated that age, Grade, and PTPN2 were independent prognostic factors in TCGA KIRC dataset. More importantly, using Timer platform analysis, we found PTPN2 correlated with B cell, CD8 + T cell, CD4 + T cell, Macrophage, Neutrophil, and Dendritic cell. Then, CTLA4 was screened from IMMPORT data due to the results of correlation analysis. So, PTPN2 combined with CTLA4 as a model to predict the prognosis of KIRC was constructed; this model could help clinicians predict the disease prognosis and select the suitable treatment for KIRC.
PTPN2 was a protein tyrosine phosphatase family member, which was associated with many key signaling in tumorigenesis 20 . PTPN2 was deleted in 6% of all T cell acute lymphoblastic leukemia 21 , and it was involved in JAK/STAT signaling and tumorigenesis 22 . In chronic myeloid leukemia patients, high PTPN2 expression was associated with poor major molecular response (MMR) 23 . Shilds et al. reported that PTPN2 was de cient in triple-negative primary breast cancer 24 . They also found that loss of PTPN2 in the human breast cancer cell lines could increased cell proliferation 24 . In our study, PTPN2 was overexpressed in KIRC, LIHC, LUSC, STAD, HNSC, ESCA, BLCA, and CHOL based on TIMER pan-cancer analysis. Targeting on PTPN2 may be a novel candidate gene for personalized tumor treatment in these cancer types. The study from Wang et al. also found PTPN2 expression level was increased in glioblastomas and associated with gliomas of the IDH wild-type and mesenchymal subtype 25 . In 2017, PTPN2 was identi ed as a cancer immunotherapy target through CRISPR screening, which was published in Nature 11 . They also found that the increased sensitivity to anti-PD-1 immunotherapy in PTPN2de cient tumors dependent on IFN-γ signaling 11 . These ndings rede ne our understanding of the role of PTPN2 in the tumor.
Immune checkpoint inhibitors have been successfully used in various solid tumors, such as lung cancer 26 and breast cancer 27 . The combination of immunosuppressive agents has a good effect on these types of tumors, such as anti-CTLA-4 combine anti-PD-1 28, 29 . In our study, we not only found PTPN2 was correlated with many immune cells but also screened out CTLA-4, which was associated with PTPN2. Similarly, to sensitize anti-PD-1 immunotherapy, our ndings suggested that if PTPN2 deletion may also sensitize tumors to anti-CTLA-4 immunotherapy

Conclusion
In conclusion, high PTPN2 levels signi cantly correlated with poor survival in ccRCC. PTPN2 is extremely closely associated with many types of TILs and CTLA-4. Our comprehensive bioinformatics analysis' results, PTPN2 may be a potential prognosis biomarker and a novel immunotherapeutic target for KIRC.

Materials And Methods
Expression pro ling of PTPN2 in human cancers The Tumor Immunological Estimation Resource (TIMER) platform (https://cistrome.shiny apps.io/timer/) 13 17,19 . To characterize biologically relevant changes in molecular signaling pathways among two groups, we furthermore calculated the enrichment for each pathway to identify signi cantly enriched concepts. All other parameters were set to default values. A nominal P < 0.01 and FDR <0.25 were used as thresholds for determining the signi cance of the enrichment score (ES).   The correlation between tumor immune-in ltrating cells (TIICs) and PTPN2 expression levels based on TIMER analysis. The Kaplan-Meier analysis comparing overall survival between PTPN2 and CTLA4 expressions