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Comprehensive Biological Information Analysis of PTEN Gene in Pan-Cancer

Background: PTEN is a multifunctional tumor suppressor gene mutating at high frequency in a variety of cancers. However, its expression in pan-cancer, correlated genes, survival prognosis, and regulatory pathways are not completely described. Here, we aimed to conduct a comprehensive analysis from the above perspectives in order to provide reference for clinical application. Methods: we studied the expression levels in cancers by using data from TCGA and GTEx database. Obtain expression box plot from UALCAN database. Perform mutation analysis on the cBioportal website. Obtain correlation genes on the GEPIA website. Construct protein network and perform KEGG and GO enrichment analysis on the STRING database. Perform prognostic analysis on the Kaplan-Meier Plotter website. We also performed transcription factor prediction on the PROMO database and performed RNA-RNA association and RNA-protein interaction on the RNAup Web server and RPISeq. The gene 3D structure, protein sequence and conserved domain were obtained in NCBI respectively. Results: PTEN was underexpressed in all cancers we studied. It was closely related to the clinical stage of tumors, suggesting PTEN may involved in cancer development and progression. The mutations of PTEN were present in a variety of cancers, most of which were truncation mutations and missense mutations. Among cancers (KIRC, LUAD, THYM, UCEC, Gastric Cancer, Liver Cancer, Lung Cancer, Breast Cancer), patients with low expression of PTEN had a shorter OS time and poorer OS prognosis. The low expression of PTEN can cause the deterioration of RFS in certain cancers (TGCT, UCEC, LIHC, LUAD, THCA), suggesting that the expression of PTEN was related to the clinical prognosis. Our study identied genes correlated with PTEN and performed GO enrichment analysis on 100 PTEN-related genes obtained from the GEPIA website. Conclusions: The understanding of PTEN gene and the in-depth exploration of its related regulatory pathways may provide insight for the discovery of tumor-specic biomarkers and clinical potential therapeutic targets.


Introduction
PTEN (Phosphoatase and Tensin Homolog) is a classical tumor suppressor gene located on chromosome 10 in region 10q23. Encoding 403 amino acids, it is a multifunctional protein that is often absent in tumors (1)(2)(3). Loss of heterozygosity often occurs in this area in various types of cancers (4).
The protein encoded by this gene is phosphatidylinositol-3,4,5-trisphosphate 3-phosphatase. It contains a catalytic domain and a tensin like domain which is similar to the bispeci c protein tyrosine phosphatase.
PTEN acts as a classical tumor suppressor and is primarily involved in the homeostasis maintenance of the phosphatilinositol 3 kinase (PI3K)/Akt cascade. In most human cancers, the function of PTEN is typically lost through somatic mutation, gene silence or epigenetic mechanisms. Tumor-associated mutations may occur in all PTEN domains, suggesting that each different protein region may be pathologically involved in the development and progression of cancer. Thus, partial loss of PTEN function is su cient to promote the growth of some human malignancies (5). Studies have shown that somatic cells without PTEN are present in a variety of tumor diseases, including melanoma, glioblastoma, colon and endometrial cancers(6, 7). Studies have also shown that low expression of PTEN often leads to a worse prognosis in cancer (bladder cancer(8), gastric cancer (9), prostate cancer(10), epithelioid malignant peritoneal mesothelioma (11), etc).
In this study, we used data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) to assess PTEN expression levels in 17 different cancers, and evaluated PTEN expression in different histological subtypes, molecular subtypes, patient status and individual pathological cancer stage. The clinical correlation with patient prognosis was also assessed. In addition, in order to further analyze the role of PTEN in the occurrence and development of diseases, our study constructed a 3D structure diagram of PTEN (Fig. 1A), and identi ed a variety of genes in the protein regulatory network of PTEN. This will provide information and direction for subsequent clinical and basic researches. with matched TCGA normal tissue and GTEx data (Fig. 1B). Then, we assessed the expression of PTEN in normal tissue by using RNA-sequencing data available from GTEx data. In particicular, we compared expression levels of PTEN between tumors with respect to normal matches, and GTEx data. We found that in terms of its expression in normal tissues, PTEN showed lower levels in these 17 cancers, and the differences between these cancers and normal samples were shown in boxplot form in Supplementary Figure S1.
Next, we evaluated PTEN expression levels with respect to tumor molecular and histological subtypes of tumors, tumor grades, and other patient conditions based on data obtained from UALCAN.
In urologic cancer, we found that the expression of the histological subtypes of BLCA was decreased in both papilloma and non-papilloma compared with normal people (Table 1 and Data S1 Panel 1A).
Regarding its molecular subtypes, the PTEN expression level in neuronal, basal squanous, luminal and luminal_papillary decreased signi cantly compared to normal (Table 1 and Data S1 panel 1B). While luminal and luminal_papillary decreased most signi cantly, followed by neuronal and basal squamous. In KIRP tumors, the expression of PTEN was signi cantly decreased in both Type1 PRCC and Type2 PRCC (Table 1 and Data S1 panel 1D), and the decrease was more signi cant in Type2 PRCC. In PRAD tumors, the expression of PTEN was decreased in Gleason score 9, Gleason score 6, Gleason score 7 and Gleason score 8. In their molecular subtypes, the expression of PTEN was also decreased signi cantly in ERG fusion, ETV1 fusion, FOXA1 mutation and SPOP mutation (Table 1 and Data S1 Panel 1E). Compared to normal tissue in BRCA tumors, the expression of PTEN was lower in all different molecular subtypes, including triple negative breast cancer (TNBC), HER2-ampli cation and luminal subtype. (Table  1 and Data S1 Panel 2D). In terms of TNBC type in BRCA, the statistically signi cant changes were seen in TNBC-mesenchymal (TNBC-M), followed by TNbC-UNS, TNBC-immunomodulatory (TNBC-IM), TNbCbasal like2 (BL2) and TNBC-basal like1(BL1). (Table 1 and Data S1 Panel 2A). PTEN expression level was decreased in pre-menopausal, peri-menopausal, and post-menopausal patients having BRCA compared with normal. However, only the difference between pre-menopausal and post-menopausal was statistically signi cant (Table 1 and Data S1 Panel 2C). In addition, the expression of PTEN in BRCA was low in all histologic subtypes, most notably in invasive lobular carcinoma (ILC) and invasive ductal carcinoma (IDC) ( Table 1 and Data S1 Panel 2B). The expression of amplied MYC proto-oncogene (MYC), cyclin D1 (CnD1) and ERB-B2 receptor tyrosine kinase 2 (ERBB2) in metastatic breast cancer compared to conditions without ampli cation indicated no signi cand correlation with PTEN expression (Table 1 and Data S1 panel 2E).
About digestive system tumors, COAD tumor showed increased PTEN levels in adenocarcinoma and mucinous-adenocarcinoma (Table 1 and Data S1 panel 3A). In PAAD tumor, the reduction of PTEN expression level was statistically signi cant in non-drinkers and daily drinkers (Table 1 and Data S1 panel 3E). In addition, compared with normal people, in patients with acute pancreatitis, their PTEN level decreased more signi cantly than patients with acute pancreatitis, but the comparison between them and patients without pancreatitis was not statistically signi cant (Table 1 and Data S1 panel 3C). The reduction of PTEN in patients with diabetes was also more signi cant than that in normal patients (Table  1 and Data S1 Panel 3B). In terms of tumor grade, PTEN reduction was more signi cant in Grade 2 and Grade 3 than in normal subjects (Table 1 and Data S1 Panel 3D).
Regarding the expression of PTEN in LUSC tumors, we found that for LUSC patients based on smoking habits, the PTEN expression of all cancer types was decreased compared with normal people, and was more signi cant in smoker, reformed smoker1 and reformed smoker2 (Table 1 and Data S1 Panel 4A). The reduction of PTEN was more obvious in LUSC NOS in terms of the histological subtypes of LUSC, followed by Lusc Mixed, Lusc SolidPatternPredominant and LUSC papillary (Table 1 and Data S1 panel 4B).
For THYM tumor, the expression level of PTEN in THYM Type A, THYM Type B2|B3, THYM Type C, THYM Type AB and THYM Type B3 was all signi cantly reduced (Table 1 and Data S1 panel 5A). In THCA tumor, the decrease of PTEN expression was most obvious in THCA Classical based on the histological subtype of THCA, followed by THCA tall and THCA follicular (Table 1 and Data S1 panel 5B). For UCEC tumors, the expression level of PTEN decreased in UCEC endometrioid, UCEC serous and UCEC Mixed serous and endometrioid, which was statistically signi cant. Among them, the most signi cantly decrease was occurred in UCEC endometrioid. Based on the menopausal stage of UCEC patients, the expression of PTEN was signi cantly decreased in pre-menopausal, peri-menopausal and post-menopausal patients, which was most signi cant in post-menopausal patients, followed by peri-menopausal and premenopausal patients. However, there was no signi cant difference in the expression level of PTEN among pre-menopausal, peri-menopausal and post-menopausal patients.
Next, we investigated PTEN expression based on patients' pathological stage in TCGA cancer types. We found that the expression level of PTEN in BRCA, COAD, KICH, KIRP, LUAD, LUSC, THCA and UCEC was signi cantly lower at the early stage (Fig. 1C, p < 0.05), suggesting that PTEN may be involved in the onset of cancers. In addition, compared with the early stage, the expression level of PTEN in BLCA and TGCT was lower at advanced cancer, suggesting that PTEN may play a role in cancer progression and cancer invasion (Fig. 1C, cancer without and/or small numbers of normal matches (when there is only one sample in each stage) were excluded from this analysis).

Genetic variation analysis of PTEN
We observed the genetic alteration condition of PTEN in different tumors of TCGA. As shown in Fig. 2A, Endometrial cancer (in which mutation is the main change type) showed the highest mutation frequency (> 60%). The frequency of PTEN changes in prostate cancer was about 20% and deep deletion was the main type of PTEN changes. It is worth noting that in these cancers, there are almost no Fusion and Multiple Alterations among the types of PTEN gene alterations. Figure 2B shows the type, location and the number of cases of PTEN gene change. In the 1203 group of mutation cases (including samples of single patient with double mutations), we found that the truncation mutation of PTEN was the main type of genetic changes(563 cases), followed by missense mutation (516 cases) while the number of cases with inframe mutation and fusion mutation was relatively small. In addition, the R130q /G/*/L/P/ QFS *4 mutation in DSPc domain can induce the development of a variety of cancers (uterine cancers account for the vast majority).

Role of PTEN low expression in cancer prognosis
In the Kaplan-Meier Plotter database, we compared the OS time between tumor patients with high PTEN expression level and tumor patients with low PTEN expression level, and the data showed that patients with low PTEN expression levels had a shorter OS time and worse prognosis compared with patients having high PTEN expression levels in the following cancers: KIRC, LUAD, Gastric Cancer, Liver Cancer, Lung Cancer, Breast Cancer, THYM and UCEC (Fig. 3A).
About RFS time, compared with the high PTEN expression level of the following tumor patients, the low expression level of PTEN in these tumor patients can lead to a worse prognosis (Fig. 3B). These tumors are: Liver Cancer, TGCT, UCEC, LIHC, LUAD and THCA.
In summary, the data proved that in the tumors mentioned above, lower-expressed PTEN level can lead to a worse clinical consequense.

Correlation between gene expression of PTEN and other genes in cancer
Our research showed that the expression of PTEN has a moderate to strong positive correlation with these genes in 17 cancers (Supplementary Table S1, which provides all information on coe cient correlations and p-value, using different colors to distinguish correlations as follows: Strong positive correlation in green; medium positive correlation in black; weak positive correlation in red; very weak correlation in violet and almost no correlation is indicated in light blue). As seen in Supplementary Table  S1 and Table 2. Among 12 or more cancers, the following genes have a strong positive correlation with PTEN expression (R between 0.5 and 1, p-value < 0.05): phosphatase and tensin homolog pseudogene 1 (PTENP1), ATPase family AAA domain containing 1 (ATAD1), wings apart-like homolog (WAPAL), tankyrase 2 (TNKS2), membrane-associated ring nger 5 (MARCH5), coiled-coil serine rich protein 2 (CCSER2), component of inhibitor of nuclear factor kappa B kinase complex (CHUK) and eukaryotic translation initiation factor 3 subunit A (EIF3A). In addition, the following genes showed a strong positive correlation with PTEN among 10 to 12 cancer types: hypoxia inducible factor 1 subunit alpha inhibitor (HIF1AN), survival motor neuron domain containing 1 (SMNDC), chromosome 10 open reading frame (C10orf12), Sp3 transcription factor (SP3), chondroitin sulfate N-acetylgalactosaminyltransferase 2 (CSGALNACT2), structural maintenance of chromosomes 3 (SMC3), NOC3 like DNA replication regulator (NOC3L), family with sequence similarity 35 member A (FAM35A), STE20 like kinase (SLK) and golgi brefeldin A resistant guanine nucleotide exchange factor 1 (GBF1). In addition, some genes showed strong positive associations with PTEN in several cancers among 17 studied cancers as indicated in the Table S1 and Table 2. For the UCEC cancer mentioned in Table S1 (shown in light blue) and Table 2   In addition, we searched for genes with protein products that have transcription factor binding sites in the PTEN promoter region. Intersection analysis of these genes and the PTEN-related genes obtained from the GEPIA database is performed by using Venn diagram, which led to the discovery of YY1 transcription factor (YY1), and we found that among the 17 cancers we studied, YY1 has a strong positive correlation with DLBC, KIRP, THCA, THYM, ACC, KICH and BRCA (ranked from high to low).
It can be seen from Table S1 that the genes most closely correlated to PTEN are phosphatase and tensin homolog pseudogene 1 (PTENP1), tankyrase 2 (TNKS2), membrane-associated ring nger 5 (MARCH5), ATPase family AAA domain containing 1 (ATAD1), wings apart-like homolog (WAPAL), coiled-coil serine rich protein 2 (CCSER2), component of inhibitor of nuclear factor kappa B kinase complex (CHUK) and eukaryotic translation initiation factor 3 subunit A (EIF3A). It is worth noting that PTENP1 has a strong positive correlation with PTEN in all 17 cancers. In UCEC tumor, we observed that TNKS2, MARCH5, ATAD1 and CHUK all had a weak positive correlation with PTEN (0.2 < R < 0.4). Besides, WAPAL, CCSER2 and EIF3A had a very weak correlation with PTEN (0.1 < R < 0.2). In addition, we found that MARCH5, CHUK and EIF3A all had a weak correlation in LUSC tumor. In UCS tumor, WAPAL and CHUK had a weak correlation with EIF3A. In THYM tumor, ATAD1 had a weak correlation (Table S1 and Table 2). The above data was shown in Table 2. Notably, among the genes positively correlated with PTEN, some genes can be considered as targets for several types of cancers. Such as: The lncRNA of phosphatase and tensin homolog pseudogene 1 (PTENP1) can inhibit the progression of cervical cancer by inhibiting mir-106b (12). In addition, studies have pointed out that the overexpression of lncRNA PTENP1 has been observed in vitro to successfully inhibit the proliferation and metastasis of glioma cells (13). In gastric cancer, PTENP1 can inhibit the progression of gastric cancer by regulating the expression of PTEN protein (14). In bladder cancer (15), breast cancer(16) and clear-cell renal cell carcinoma (17), PTENP1 also has a tumor suppressor effect. cAMP responsive element binding protein 1 (CREB1) can be used as a potential target for the treatment of hepatocellular carcinoma(18), colorectal cancer (19), gastric cancer (20) and bladder cancer (21). Polybromo 1 (PBRM1) has clinical application value in kidney cancer (22), breast cancer(23) and cholangiocarcinoma (24). Heterogeneous nuclear ribonucleoprotein K (HNRNPK) can be used as a potential therapeutic target for gastric cancer (25). F-box and WD repeat domain containing 2 (FBXW2) can be used as a tumor suppressor in lung cancer to inhibit the growth of cancer cells(26). Mutations in APC regulator of WNT signaling pathway (APC) can promote the occurrence and development of colorectal cancer (27) and bladder cancer(28). The genes mentioned above show obvious low expression in some cancers, have abnormal expression in different pathological cancer stages and poor OS prognosis is occurred in several cancers. (Table 3 and Supplementary Data S2). Table 3 Statistically signi cant down-expression of different proposed target genes in most common cancers.

Genes
Cancers

PTEN Protein Network
We analyzed some genes, including genes that have strongly positive correlation with PTEN, genes that are closely related to PTEN and positively correlated with PTEN found in the STRING database (Analysis using Venn diagram, Fig. 4A) ( Table 2 and Supplementary Table S1), and genes which have protein products that have transcription factor binding sites on the promoter regions of PTEN. Data from the STRING database showed that these proteins are in the same protein network (Fig. 4B (Table 4 and Supplementary Table S2). All the pathways that PTEN is mainly involved in were indicated in red (Supplementary Table S2). The protein (YY1) with transcription factor binding site in the promoter region of PTEN also participated in the PTEN protein network. As shown in Supplementary Table S2, this protein was also involved in most pathways with the participation of PTEN (Supplementary Table S2). In addition, we used the RNAup webserver to analyze the RNA-RNA interaction and RNA-protein interaction between YY1 and PTEN ( Fig. 4C and Fig.  4D).

Analysis of PTEN Structural Features
We analyzed the basic structure of PTEN (NM_000314.8 for mRNA and NP_000305.3 for protein) (Fig.   5A), and we analyzed the conserved domains of PTEN among different species. As shown in Fig. 5B, PTEN has conserved protein structures in different species (eg. H.sapiens, P.troglodytes, M.mulatta, C.lupus, etc) and all of these contain the PTEN_C2 domain (Fig. 5B).

Discussion
PTEN acts as a dual-speci c protein phosphatase dephosphorylating tyrosine, serine and threonine in proteins, and it can also act as a lipid phosphatase, which is essential for its tumor suppressor effect.
Therefore, the occurrence of PTEN mutations and the abnormally low expression of PTEN may lead to uncontrolled cell proliferation, which may be one of the main characteristics of cancer.
Our study rstly conducted a comprehensive analysis of the expression of PTEN in a variety of tumors.
Our results showed that PTEN was down-regulated in all 17 different cancers studied, which is in agreement with earlier reports about PTEN showing decreased somatic expression of PTEN in various tumor types. In fact, low expression of PTEN has been reported in gastric cancer (29), prostate cancer(30), liver cancer(31), colorectal cancer(32), etc. This was also con rmed in our data. For example, a study by Monica Prasad Hayes et al showed that PTEN mutations often occur in endometrioid carcinoma (33), and our study also showed that PTEN expression is signi cantly absent in UCEC Endometrioid tissue subtype (Table 1). More importantly, our research showed that the low expression of PTEN was a common feature in the 17 human cancers analyzed in this study, which indicated that it is a tumor suppressor gene. Moreover, the current study revealed the signi cant PTEN low-expression across the histological and molecular subtypes of different tumors mentioned in the results and possible associations between PTEN expression and different patient conditions. For example, smoking and drinking habits in LUSC and PAAD. In addition, the expression of PTEN, based on the pathological stage of the patient, indicated that the low expression of PTEN may be related to tumor occurrence, progression and invasion. Also, we found that PTEN mutations existed in a variety of cancers, most of which are truncation mutations and missense mutations.
We showed that patients with low PTEN expression had a shorter overall survival time and poorer prognosis. Moreover, the low expression level of PTEN also lead to poor prognosis of relapse free survival in many cancers, thus con rming that low expression of PTEN can lead to poor clinical prognosis of many tumors. For example, a report by J P Fan et al showed that lower levels of PTEN can lead to worse prognosis of gastric cancer, and our data also con rmed this point (Fig. 3A).
Our research had identi ed some genes related to the PTEN protein network, these genes were involved in activated Rho/ROCK1 signaling pathway can worsen breast cancer(38). Among the genes involved in the cell cycle, the RAD21 protein complex composed of genes such as SMC and SMC1A participates in the aggregation of sister chromatids (39). Similarly, STAG1/STAG2 is also part of the adhesion protein complex, which participates in the adhesion of sister chromatids (40). Among the genes involved in apoptosis, the overexpression of CHUK can promote the proliferation of Mantle cell lymphoma cells and inhibit its apoptosis pathway (41). MAPK8 can inhibit tumor cell apoptosis through the MAPK signaling pathway (42). Among the genes involved in oocyte meiosis, SMC3 can enhance chromosome cohesion to ensure accurate chromosome separation (43). Among the genes involved in the AMPK signaling pathway, CREB1 can upregulate GLUT3 to enhance the e cacy of colorectal cancer therapy (44). Our data emphasizes that the PTEN network is one of the main protein networks involved in cancer, and further research on it in tumors may provide inspiration for new treatment strategies for cancer.
We analyzed the gene transcription factor YY1 which was co-expressed by PTEN. It has a binding site in the PTEN promoter region and can affect the expression of PTEN to regulate tumor development. This is consistent with previous studies (45). In addition, we also analyzed the RNA interaction and RNA-protein interaction between YY1 and PTEN, indicating that YY1 and PTEN were closely related ( Fig. 4C and Fig. 4D).
In addition, we searched for several PTEN-correlated genes (PTENP1, CREB1, PBRM1, HNRNPK, FBXW2, APC) that may be closely related to cancer treatment. Moreover, their expression levels in some tumors were signi cantly reduced, and these low-expressed genes had a worse OS prognosis (Table 3), which indicated that they may be potential targets for cancer treatment.
Finally, we analyzed the structural characteristics of PTEN and the structural diagrams of PTEN protein in different species, from which we obtained the conserved domains of PTEN in different species. Moreover, the conserved protein structures of PTEN in different species all contain the PTEN_C2 domain (Fig. 5).

Conclusions
All in all, the current research showed that PTEN can be regarded as a tumor marker and research on its related pathways can help discover common therapeutic targets for cancer. However, further functional studies are needed to clarify the relevant role of PTEN in cancer.

Methods
In the current research, our research was conducted by using different bioinformatics tools and databases, including GEPIA (46)