Pseudogene HSPA7 is a Poor Prognostic Biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) and Correlated With Immune Inltrates Chunjin Ding Nantong University Aliated Hospital: Aliated Hospital of Nantong University Rundong He Nanjing Medical University Jinghan Zhang Nanjing Medical University Aliated Nanjing Children's Hospital: Children's Hospital of Nanjing Medical University Zhan Dong Nanjing Medical University Aliated Nanjing Children's Hospital: Children's Hospital of Nanjing Medical University Jun Wu ( [email protected] ) Nanjing Medical University https://orcid.org/0000-0001-6353-3013 Primary research Keywords: Kidney Renal Clear Cell Carcinoma (KIRC), HSPA7, immune, prognostic biomarker, tumor Posted Date: May 18th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-518429/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published at Cancer Cell International on August 19th, 2021. See the published version at https://doi.org/10.1186/s12935-021-02141-1. Page 1/21 Abstract Background: Pseudogenes played important roles in tumorigenesis, while there are nearly no reports about the expression and roles of HSPA7 in the cancer. Methods: Firstly,we used Logistic regression,the KS test, the GEPIA database, UALCAN database and qRT- PCR to analyze the level of HSPA7 expressed in KIRC,then we used the Cox regression and the Kaplan- Meier curve to analyze the overall survival(OS) of KIRC patients with different Clinico-pathological parameters. Thirdly, we used the multivariate Cox analysis of inuencing factors to compare the correlation between the HSPA7 expression level and the clinical parameters. Finally, we used multi-GSEA analysis and the Tumor Immunoassay Resource (TIMER) database to explore the functional role of HSPA7 in KIRC. Results: The HSPA7 is highly expressed in KIRC tumor tissues, and its expression is related to clinico- pathological features and survival in KIRCpatints.GSEA analysis displayed the high expression of HSPA7 in KIRC were related to several tumor-related and immune-related pathways. With the TIMER database analysis we showed that HSPA7 levels were correlated with the CD4+ T cells, neutrophils and Dendritic Cell. Conclusions: Our study showed that HSPA7 is very important in the tumor progression and may act as a poor prognostic biomarker for KIRC tumor by modulating immune inltrating cells. Introduction The morbidity of renal cell carcinoma (RCC) is about 4.2% of all newly-appeared cancer cases, which make RCC become one of the most frequent malignances worldwide. According to a recent survey, there were about 73,820 new cases of RCC and 14,770 deaths occurred in United States in 2019[1]. Kidney Renal Clear Cell Carcinoma (KIRC) is the most common kidney cancer subtype [2]. At present, the primary treatment of KIRC is surgery,while 30% of the patients who underwent surgery still experience metastasis[3], and the currently used drugs are not effective and have relatively great side effects. Early identication and diagnosis of KIRC patients can help with more precise clinical treatment. Therefore,it is urgent to discover new and reliable markers to predict the prognosis of patients. Pseudogenes are non-coding genes lacking of protein-coding ability, and were once labeled as junk genes. However, there is growing evidence that pseudogenes can inuence the regulatory mechanisms of many human cancers. [4]. And Pseudogene expression were treated as a novel marker and used in a variety of cancer types to stratify patients subtypes [5]and is therefore should taken into account in cancer survival prognostic factors.The HSPA7 (HSP70B) gene discovered in 1985 and encoded near the highly homologous HSPA6 (HSP70B') on chromosome 1, although mRNA can be expressed after thermal stimulation, it cannot transcribe a functional protein[6]. Numerous investigations have shown that HSPA6 plays an important role in multiple human cancers, including esophageal cancer[7, 8], glioma[9], lung cancer[10], hepatocellular carcinoma[11] and leukemia[12].However, little has been reported about the Page 2/21 expression and role of HSPA7 in cancer. Our study showed that high expression of HSPA7 can indicate the poor prognosis of KIRC. Our study examined the expression and prognostic value of HSPA7 in KIRC patients in the Cancer Genome Atlas (TCGA) and validated them in multiple independent cohorts. Moreover, GSEA[13] and Tumor Immunoassay Resource (TIMER) database[14] were used to assay the potential mechanisms of HSPA7 in KIRC. Our results implied that the functional role of HSPA7 in KIRC may through regulating immune cell inltration. Methods 2.1.Data Mining and Data Collection The KIRC data of TCGA consists of 72 normal tissues and 539 tumor samples,was acquired from the TCGA data portal (https://tcga-data.nci.nih.gov/tcga/). Clinical data pertaining to patients’ age, gender, survival, grade, stage, and recurred/progressed outcome were also acquired from the data portal. The dataset including mRNA expression counts and survival data with clinical information. The samples with missing expression data were excluded from the study.The dataset contains survival data with clinical information and mRNA expression counts. The samples with missing expression data were excluded from our study. 2.2.Data Analysis The R-3.6.2 project was used to analysis the acquired data.Firstly, we used the Logistic regression and the KS test to analyze the relation between the HSPA7 gene expression and Clinico-pathological features. Then we used the Cox regression and the Kaplan-Meier curve to analyze the overall survival of KIRC patients with different Clinico-pathological parameters from TCGA data. Finally, we used the multivariate Cox analysis of inuencing factors to compare the correlation between the HSPA7 expression level and the clinical parameters,such as age, gender grade, stage, T classication, N classication, and M classication, related to survival. The Cutoff Finder.2 was used to determine the cut-off value of HSPA7 expression. 2.3.Gene Set Enrichment Analysis (GSEA) Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori dened set of genes shows statistically signicant between two biological expression states[13]. In our study, an ordered list of genes based on the pathways related to the HSPA7 expression level were generated by the GSEA,and then the signicant differences between the high and low-level expression groups of HSPA7 were annotated. The multi-GSEA results and signaling pathway enrichment analysis of phenotypes and were ranked by normalized enrichment score (NES) and the nominal p-value. 2.4. Analysis of TIMER database Page 3/21 The TIMER (https://cistrome.shinyapps.io/timer/) database is designed for analysing immune cell inltrates in multiple cancers. This database can estimate tumour immune inltration by macrophages, dendritic cells, CD4/CD8+ T cells, neutrophils , and B cells [15].We used the TIMER database to assess the HSPA7 different expression levels in particular tumours, and then we explored the correlation between HSPA7 expression level and the degree of inltration in particular immune cell subsets. We further explored the differences in patient survival as a function of gene expression or immune cell inltration by Kaplan-Meier curve analyses 2.5. Analysis of GEPIA and UALCAN database The GEPIA (http://gepia.cancer-pku.cn/index.html) databse and UALCAN (http://ualcan.path.uab.edu) databse can explored the association of mRNA expression level with overall survival(OS). We uesd these two database to explore the correlation between the HSPA7 expression and patient overall survival in KIRC. 2.6.RNA Extraction and qRT-PCR Analysiy RNA extraction and qRT-PCR were performed as the product manual described(Cat# R312-01, Cat# Q131- 02, Vazyme,China).The primers used in this study are purchased from Generay (Shanghai, China) and listed as follows. HSPA7-R: CATCCCCAAGGTGCAGAAGT HSPA7-F: ACCATCCTCTCCACCTCCTC GAPDH-R: GGGAGCCAAAAGGGTCAT GAPDH-F: GAGTCCTTCCACGATACCAA Results 3.1.Characteristics of the of the Patients 537 patients’ clinical data were acquired from TCGA, including the age, gender, Histological grade, TNM classication of KIRC(Table 1). 3.2.High HSPA7 mRNA Expression in KIRC First, we assessed the differences in HSPA7 expression between KIRC tumor tissues and adjacent tissues via differential expression scatter plots and paired difference analyses. We nd that the expression level of HSPA7 was signicantlly higher in KIRC tumor tissues (p=6.183e-35) and in paired cancer tissues(p=3.311e-18) compared with adjacent tissues(Figure 1A and 1B). Then, the expression level of HSPA7 in KIRC tumor tissues and adjacent tissues were veried by GEPIA[16] (Figures 1C) database, UALCAN database(Figures 1D)[17] and qRT-PCR analysis(Figures 1E) . Page 4/21 3.3. Correlation Between HSPA7 Expression level and Clinico-pathological featuresin KIRC tumors As the Table 2 shown the expression of HSPA7 was highly statistically signicantly correlated with clinical stage (p = 0.044) and distant metastasis (positive vs. negative, p = 0.049) . 3.4.Correlation Between KIRC patients Survival and HSPA7 Expression To evaluate the effect of HSPA7 expression on KIRC patients survival, the log-rank test and Kaplan-Meier survival analysis were used to estimate the correlation between HSPA7 expression and KIRC patients prognosis. The patients with high HSPA7 expression level displayed relatively poor survival (p=1.176e−04; Figure 2A). The clinical subgroup analysis implied that the patients in Histological grade (G1–2 vs. G3–4) , clinical stage(Stage I vs Stage IV), M classication and T classication (the T1–2 vs. T3–4) with HSPA7 expression also had signicantly poor overall survival(OS) (Figure 2B-E) , whereas not in the N classication (Figures 2F). We performed the univariate analysis with the variables and listed in the Table 3. We also performed Multivariate analysis with the Cox proportional hazards model and the results implied that the expression of HSPA7 (HR =1.304605, p =0.005187) is a potential prognostic factor for KIRC patients (Table 4).