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Prognostic Biomarker TUBA1C Is Correlated to Immune Cell Infiltration

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Prognostic Biomarker TUBA1C Is Correlated to Immune Cell Infiltration Bian et al. Cancer Cell Int (2021) 21:144 https://doi.org/10.1186/s12935-021-01849-4 Cancer Cell International PRIMARY RESEARCH Open Access Prognostic biomarker TUBA1C is correlated to immune cell infltration in the tumor microenvironment of lung adenocarcinoma Tingting Bian1† , Miaosen Zheng1,2†, Daishan Jiang3, Jian Liu4, Hui Sun1, Xiaoli Li1, Lei Liu1, Jianguo Zhang1* and Yifei Liu1,2* Abstract Background: TUBA1C is a microtubule component that is involved in a variety of cancers. Our main objective was to investigate TUBA1C expression, its prognostic value, its potential biological functions, and its impact on the immune system of patients with lung adenocarcinoma (LUAD). Methods: The Cancer Genome Atlas (TCGA), Gene Expression Profling Interactive Analysis (GEPIA) and Immunohis- tochemistry Analysis were used to analyze TUBA1C expression, its clinicopathology, overall survival (OS), and disease- free survival (DFS) in LUAD patients. We also determined the correlation between TUBA1C and tumor-infltrating immune cells (TIICs) by using CIBERSORT and GEPIA databases. To determine the expression of TUBA1C in LUAD, we analyzed a collection of immune infltration levels and cumulative survival of LUAD tissues in TIMER database. By using UALCAN, STRING, and GeneMANIA databases, we investigated the protein-coding genes related to TUBA1C and its co-expression genes in LUAD tissues. Gene set enrichment analysis (GSEA) was performed by using the TCGA dataset. Results: The mRNA and the protein expression of TUBA1C were found to be up-regulated in LUAD tissues. The uni- variate analysis indicated that an increased expression of TUBA1C was signifcantly correlated to the following param- eters: age, stage, and lymph node metastasis. An over-expression of TUBA1C was associated with a poor prognosis of LUAD. In TIMER and CIBERSORT databases, we found that TUBA1C is correlated with 13 types of TIICs: activated B cell, activated CD4 T cell, central memory CD4 T cell, efector memory CD8 T cell, eosinophils, immature B cell, gamma- delta T cell, immature dendritic cell, mast cell, memory B cell, natural killer T cell, regulatory T cell, and type 2T helper cell. By performing GSEA, we found that TUBA1C is closely correlated to cell cycle, p53 signaling pathway, glycolysis, and gluconeogenesis. Conclusions: Our fndings indicate that TUBA1C is associated with TIICs in tumor microenvironment. Therefore, it serves as a novel prognostic biomarker and a target for future treatment methods of LUAD. Keywords: TUBA1C, Lung adenocarcinoma, Tumor-infltrating immune cells, Prognosis, Diagnosis Background Te morbidity and mortality of lung cancer has been the highest among all types of cancers, so it is the most common form of malignancy worldwide [1]. Lung ade- *Correspondence: [email protected]; [email protected] nocarcinoma (LUAD) is a major pathological subtype †Tingting Bian and Miaosen Zheng contributed equally to this work 1 Department of Pathology, Afliated Hospital of Nantong University, of non-small cell lung cancer (NSCLC), which approxi- Nantong, Jiangsu, China mately accounts for 40% of lung cancer cases [2]. Surgery, Full list of author information is available at the end of the article chemotherapy, radiotherapy, and targeted therapy are the © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Bian et al. Cancer Cell Int (2021) 21:144 Page 2 of 13 conventional methods of treating patients with NSCLC; pathologists. Te follow up was 60 months. All experi- however, the prognosis of these patients has been unsat- ments involving patient specimens were approved by the isfactory till date [3]. Since the past decade, immune Ethics Committee of the Afliated Hospital of Nantong checkpoint inhibitors (ICIS) have been used to treat University, China. patients with NSCLC, and they have modifed the treat- ment pattern of this refractory disease [4]. Tumor-infl- GEPIA analysis trating immune cells (TIICs) have impacted the immune Gene Expression Profling Interactive Analysis (http:// system and tackled abnormal biological behaviors in a gepia .cance r-pku.cn/index .html) is an online database complex way, so they play a key role in eliciting the body’s developed by scientists of Peking University, China [14]. response to immunotherapy [5]. To determine the expression of TUBA1C in LUAD tis- Microtubule is an important component of the eukary- sues, we performed GEPIA and constructed boxplot, otic cytoskeleton. Moreover, it is one of the most func- pathological stage plot, and survival curves, such as over- tional proteins, which play an important role in dynamic all survival (OS) curve and disease-free survival (DFS) polymerization and depolymerization through cell rep- curve. Meanwhile, the relationship between TUBA1C lication and division [6]. Microtubules are uniformly and immune infltrating cells was analyzed by GEPIA. assembled from highly conserved α/β-tubulin heter- Te Spearman method was used to determine the corre- odimers [7]. Recently, several studies have reported that lation coefcient of the relationship. α-tubulin is involved in the occurrence of a variety of tumors, such as lung cancer, breast cancer and prostatic Immunohistochemistry analysis cancer [8–10]. In addition, α-tubulin is also associated An immunohistochemistry (IHC) assay was conducted with the development of astrocytoma and chemothera- as previously described [15]. Briefy, the LUAD sam- peutic resistance of liver cancer [11]. Moreover, TUBA1C ples were deparafnized and rehydrated. Te primary is a subtype of α-tubulin, and its overexpression is associ- antibody was that against TUBA1C (1:100 dilution; ated with the poor prognosis of hepatocellular carcinoma ab222849; abcam). Te positive expression of TUBA1C (HCC) and pancreatic ductal adenocarcinoma [12, 13]. was localized in cytoplasm. Te scoring criteria for IHC However, no previous study has elucidated how the over- staining were based on the intensity of the stain and expression of TUBA1C afects LUAD patients. the percentage of immunoreactive cells, as previously In this study, IHC and Gene Expression Profling Inter- described [15]. active Analysis (GEPIA) were performed to elucidate the correlation between TUBA1C and LUAD. Furthermore, TIMER analysis we used the computational algorithms CIBERSORT and In this experiment, we used TIMER (https ://cistr ome. TIMER to explore the relationship between TUBA1C shiny apps.io/timer /) algorithm to comprehensively elu- and TIICs in LUAD patients. In addition, STRING soft- cidate the correlation between diferent types of tumors ware, GeneMANIA Analysis, and Gene Set Enrichment and TIICs [16]. Moreover, we performed a series of anal- Analysis (GSEA) were used to further study the function yses to determine the expression of TUBA1C in diferent and mechanism of TUBA1C in LUAD patients. Te fnd- types of cancer and to comprehend its correlation with ings proved that TUBA1C played an important role in the abundance of TIICs. Tese TIICs were further classi- the development of LUAD. Furthermore, we elucidated fed as follows: B cells, CD4+ T cells, CD8+ T cells, mac- the potential relationship between TUBA1C and tumor- rophages, neutrophils, and dendritic cells. By using the immune interaction. TIMER algorithm, we performed a correlation analysis between TUBA1C, its related genes, and the markers of Materials and methods immune cells [17]. Te expression of TUBA1C gene was Data acquisition plotted on the x-axis, and the expression of its related Te TCGA database (https ://porta l.gdc.cance r.gov/) marker genes was plotted on the y-axis. was used to obtain the data of TUBA1C expression in LUAD tissues and normal tissues. A total of 535 tumor CIBERSORT analysis tissues (Additional fle 1) and 59 normal tissues were Te computational method of CIBERSORT [18] (http:// included in the data analysis. Meanwhile, 390 LUAD ciber sort.stanf ord.edu/) is a deconvolution algorithm tissues and 60 normal tissues were treated from the based on gene expression, and it is used to evaluate the Afliated Hospital of Nantong University in China. All changes of a group of genes relative to all other genes in patients were treated by surgical resection between a sample. Based on the expression of TUBA1C, we clas- 2012 and 2013. All clinical data on the patients were sifed 497 samples into high and low expression groups. carefully recorded after the diagnosis of LUAD by two Using CIBERSORT algorithm, we measured the immune Bian et al. Cancer Cell Int (2021) 21:144 Page 3 of 13 responses of 28 TIICs and evaluated the relationship biological functions of TUBA1C. A false discovery rate between these TIICs and the expression of TUBA1C in (FDR) < 0.050 and a nominal P < 0.050 were considered to LUAD tissues. Our main goal was to determine the cor- be statistically signifcant. relation between these TIICs. Statistical analysis UALCAN analysis All statistical analyses were performed by using R lan- Te University of Alabama Cancer Database (UALCAN) guage (version 3.5.3). Kaplan–Meier univariate analysis (http://ualca n.path.uab.edu/index .html) is a visual portal was used to determine the efect of TUBA1C expression of the Cancer Genome Atlas (TCGA) database [19].
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