https://orcid.org/0000-0002-9492-1083
Figures
Abstract
α1C-tubulin (TUBA1C) is a member of the α-tubulin family and has served as a potential biomarker in a variety of cancers in many studies. In this study, the gene expression profile of TUBA1C in The Cancer Genome Atlas (TCGA) was extracted for analysis, and the prognostic value of TUBA1C in breast cancer was comprehensively evaluated. The Wilcoxon signed-rank test, Kruskal-Wallis test, and logistic regression analysis were performed to confirm the correlations between TUBA1C expression and the clinical characteristics of breast cancer patients. The effect of TUBA1C expression on the survival of breast cancer patients was assessed by Kaplan-Meier curve, Cox regression analysis, and the Kaplan-Meier plotter (an online database). The TCGA data set was used for the Gene Set Enrichment Analysis (GSEA). The results confirmed that high TUBA1C expression in breast cancer was closely correlated with survival time, survival status, and tumor size. In addition, elevated TUBA1C expression can predict poor overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS). Univariate and multivariate analyses (Cox regression analyses) confirmed that TUBA1C was an independent prognostic factor for the OS of breast cancer patients. The GSEA identified that the high TUBA1C expression phenotype was differentially enriched in cell cycle, basal transcription factor, P53 signaling pathway, pathways in cancer, TOLL-like receptor signaling pathway, and NOD-like receptor signaling pathway. In summary, high messenger RNA (mRNA) expression of TUBA1C is an independent risk factor for poor prognosis of breast cancer.
Citation: Zhao Y, Wang W, Li J, Du J, Xie Q, Wang M, et al. (2023) Elevated expression of TUBA1C in breast cancer predicts poor prognosis. PLoS ONE 18(11): e0263710. https://doi.org/10.1371/journal.pone.0263710
Editor: Suhwan Chang, University of Ulsan College of Medicine, REPUBLIC OF KOREA
Received: March 15, 2021; Accepted: May 15, 2022; Published: November 30, 2023
Copyright: © 2023 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: We have performed the upload of the minimum dataset according to the PLOS ONE journal's request for our manuscript, which we uploaded at the following website address: https://datadryad.org/stash/share/vxLw66WOaURhhfMojF44xMguUP9YtgY_eBGDtXZu3fw.
Funding: this work was supported by grants from the Key Research & Development and Transformation Project of Qinghai Province for 2018 (2018-SF-113).
Competing interests: The authors have declared that no competing interests exist.
Background
Breast cancer is a common malignancy in women worldwide, as new breast cancer cases account for 11.67% of all new cancer cases each year, and of these, breast cancer mortality accounts for 6.69% of all cancer deaths [1]. Therefore, breast cancer seriously threatens the lives and health of women. In recent years, with continuous advancements in medical technology, considerable progress has been made in the early diagnosis and treatment of breast cancer, which has led to some improvements in prognosis. Unfortunately, many patients still cannot be diagnosed early and are at risk for recurrence and metastasis due to a lack of more sensitive and specific prognostic indicators [2]. The existing pathological staging and molecular subtypes of breast cancer do not provide an accurate patient prognosis, and more prognostic markers are needed to reflect the diversity of tumor subtypes, improve patient risk stratification, and adjust individualized treatment strategies.
As an important component of the cytoskeleton, microtubules, which are composed of tubulin, have a plus-end and a minus-end, each of which has a different function [3,4]. At present, seven tubulin subtypes have been confirmed, each of which also has a distinct function [5]. Microtubules can participate in cell proliferation, intracellular transport of substances, and signal transduction by means of polymerization and depolymerization, and thus, they maintain normal cell morphology [6]. Microtubules also play an important role in cell division and chromosome segregation. Intracellular microtubules are primarily reticulate or in bundles and interact with other proteins in these two forms to participate in the formation of many important structures, including cell spindles, flagella, and cilia, whereas α-tubulin is one of the main subtypes that forms microtubule structures [7,8]. Recently, substantial evidence has indicated that α1C-tubulin (TUBA1C), which is a component of microtubules, is closely related to the occurrence and development of a variety of cancers [9–12]. For example, abnormally elevated TUBA1C expression in pancreatic cancer cells is associated with the prognosis of pancreatic cancer patients [10]. Although the exact mechanisms of TUBA1C in disease are still unclear, existing research suggests that TUBA1C may be a powerful potential prognostic marker of cancer progression and metastasis.
Observation of the gene expression profile suggests that TUBA1C might play an important role in breast cancer [13,14]. However, the correlations between abnormally elevated TUBA1C expression and breast cancer prognosis as well as other clinical factors of breast cancer have not been clearly elucidated. In this study, sequencing data, clinical information, and follow-up data for patients were extracted from The Cancer Genome Atlas (TCGA) to evaluate the differential expression of TUBA1C between breast cancer patients and healthy individuals, after which a pairwise comparison was performed. In addition, after patients were divided into TUBA1C high and low expression groups, the correlations between different TUBA1C expression levels and overall survival (OS), recurrence-free survival (RFS), distant metastasis-free survival (DMFS), post progression survival (PPS), and other clinical characteristics of breast cancer patients were analyzed, and gene set enrichment analysis (GSEA) was used to further explore the biological pathways regulated by TUBA1C. The results demonstrated that TUBA1C is a potential prognostic biomarker of breast cancer.
Methods
2.1 Ethical statement
This study was approved by the Ethics Committee of Qinghai University Affiliated Hospital. All experimental data were derived from public databases, thus ensuring that informed consent was obtained for all data used in the study.
2.2 RNA sequencing (RNA-seq) gene data for patients and bioinformatics analysis
The gene expression data in this study and the corresponding clinical patient data were obtained from the TCGA database(TCGA, http//gdc.cancer.gov/) [15]. After exclusion of incomplete data, the RNA-seq gene expression data and the corresponding clinical data for 1085 breast cancer patients were collected. The differential expression, correlation analysis of clinical characteristics, univariate Cox analysis, multivariate Cox analysis, and logistic regression analysis were performed using R software (version 4.0.3).
2.3 Gene Expression Profiling Interactive Analysis (GEPIA) dataset
GEPIA (http://gepia.cancer-pku.cn/) is a new advanced interactive web server for analyzing RNA-seq gene expression data, including data from 9736 tumor samples and 8587 normal samples [16]. The included samples are all from the TCGA database and the Genotype Tissue Expression (GTEx) project. GEPIA has a variety of analytical functions, such as online analysis of differential expression between tumor and normal tissues, survival analysis, analysis based on different cancers or pathological stages, and the ability to search for similar genes. In addition, we used the limma packages, beeswarm packages in R language to further analyse the differential expression of the TUBA1C gene in breast cancer and normal breast tissue.
2.4 Kaplan-Meier plotter
The Kaplan-Meier plotter (http://kmplot.com/analysis/) is a prognosis-related online analysis tool, which was used to analyze the prognostic value of the TUBA1C gene in breast cancer tissues [17]. To analyze the prognostic indicators, i.e., OS, PPS, RFS, and DMFS, of breast cancer patients, breast cancer tissues were divided into high expression and low expression groups according to the median expression of TUBA1C messenger RNA (mRNA) and were evaluated using the Kaplan-Meier plotter. A p value < 0.05 indicated statistical significance.
2.5 GSEA
GSEA is an analysis tool for whole-genome expression microarray data that can construct a molecular signature database based on information about gene location, function, and biological significance [18]. Hybridization data of the expression profiles of a set of genes in two biological states were analyzed to determine statistical significance. In this study, raw data were processed in batches using GSEA to analyze the signaling pathways involved in the TUBA1C high expression group and the TUBA1C low expression group. TUBA1C expression was identified using phenotypic markers. The nominal p value and normalized enrichment score (NES) were used to sort the enriched pathways, with 1000 sorts per analysis.
2.6 Statistical analysis
The correlations between TUBA1C expression and OS, PPS, DMFS, and RFS were determined using the Kaplan-Meier plotter, and other statistical analyses were completed using R software (version 4.0.3). The Wilcoxon signed-rank test, Kruskal-Wallis test, and logistic regression analysis were performed to analyze the correlations between TUBA1C expression and the clinical characteristics of patients in the TCGA database. The median expression of TUBA1C mRNA was used to divide patients into the high and low expression groups. Univariate Cox analysis was used to analyze potential prognostic factors. Multivariate Cox analysis was performed to verify the correlations between TUBA1C expression and clinicopathological features as well as survival. P < 0.05 was considered statistically significant.
Results
3.1 Characteristics of the study population
The analysis process of this study is shown in Fig 1. The clinical data for 1085 breast cancer patients were downloaded from the TCGA database and included patient age, survival status, clinical stage, tumor size, lymph node status, and the presence or absence of distant organ metastasis (Table 1).
3.2 TUBA1C expression is significantly increased in breast cancer
By downloading RNA-seq data from the TCGA database, differences in TUBA1C expression between breast cancer and normal breast tissues were statistically analyzed. The results showed that compared with normal breast tissue, TUBA1C expression was significantly increased in breast cancer tissues (P = 2.558e-51) (Fig 2B). In addition, pairwise difference analysis was performed on cancer and paracancerous tissues from the same sample taken from the TCGA database, and the results showed that TUBA1C expression in cancer tissues was significantly higher than that in paracancerous tissues (P = 1.446e-05) (Fig 2C). To further verify the analysis results, the changes in TUBA1C expression in different cancers were analyzed online through the GEPIA server, and it was found that TUBA1C expression was elevated in multiple cancer tissues including breast cancer (Fig 2A).
A. Expression pattern of TUBA1C in 33 types of tumor tissues and paired paracancerous tissues. B. Differences in TUBA1C expression between breast cancer tissues and normal breast tissues. C. Pairwise difference analysis of TUBA1C in breast cancer tissues and paired paracancerous tissues. Data were obtained from the GEPIA and TCGA databases.
3.3 Correlation analysis of TUBA1C and the clinical characteristics of breast cancer patients
The TCGA data included 1085 breast cancer samples with information on TUBA1C expression. The correlation analysis between TUBA1C expression and the clinical characteristics of these samples showed that high TUBA1C expression was correlated with survival time (P = 0.032), survival status (P = 0.043), and tumor size (P = 0.005) (Fig 3B, 3C and 3F). The logistic regression analysis found that TUBA1C was significantly correlated with the survival status and survival time of patients (P < 0.05) (Table 2). These results suggested that patients with high TUBA1C expression had a poor overall survival rate.
A. Age. B. Vital status. C. Survival time. D-E. Stage. F. T classification. G. N classification. H. M classification.
3.4 High TUBA1C expression is an independent risk factor for OS of breast cancer patients
The Kaplan-Meier curve showed that the OS of breast cancer patients with high TUBA1C expression was lower than that of patients with low TUBA1C expression (P < 0.05) (S1 Fig). To further validate this result, the correlations between different expression levels of TUBA1C and the OS, PPS, RFS, and DMFS of breast cancer patients were analyzed using the Kaplan-Meier Plotter (an online database). The results showed that compared with patients with low TUBA1C expression, patients with high TUBA1C expression had a worse OS (P = 0.0088), RFS (P = 4.3e-07), and DMFS (P = 2.2e-05), and a significantly higher PPS (P = 0.0024) (Fig 4A–4D). In addition, univariate and multivariate Cox analyses also showed that high TUBA1C expression was an independent risk factor for OS in breast cancer patients (hazard ratio [HR] = 1.5430, 95% confidence interval [CI]: 1.1927–1.9962, P = 0.0010) (Tables 3 and 4).
(A-D) Correlation analysis between the different expression levels of TUBA1C and OS, PPS, RFS, and DMFS of breast cancer patients.
3.5 TUBA1C-correlated signaling pathways by GSEA
To determine the signaling pathways that were differentially activated by TUBA1C in breast cancer, GSEA was performed between datasets with low and high TUBA1C expression. GSEA determined significant differences (FDR < 0.25, NOM p < 0.05) in enrichment in the molecular signatures database (MSigDB) (c2.cp.kegg.v6.2.symbols.gmt). Based on the NES, the most significantly enriched signaling pathways are listed in Table 5 and Fig 5A–5F. The GSEA showed that the high TUBA1C expression phenotype was differentially enriched in cell cycle, basal transcription factors, P53 signaling pathway, pathways in cancer, TOLL-like receptor signaling pathway, and NOD-like receptor signaling pathway.
The results of GSEA showed that (A) cell cycle, (B) pathways in cancer, (C) P53 signaling pathway, (D) basal transcription factor, (E) TOLL-like receptor signaling pathway and (F) NOD-like receptor signaling pathway in breast cancer with high expression of TUBA1C were differentially enriched.
Discussion
Many previous studies have confirmed that TUBA1C can play a role in the occurrence and development of a variety of tumors. Related research reports confirm that TUBA1C can promote liver cancer cell proliferation and invasion and can be used as a prognostic indicator in liver cancer [12]. Mugahed Abdullah Hasan Albahde et al. reported that high TUBA1C expression could affect the cell cycle of pancreatic cancer cells and promote the occurrence and progression of pancreatic cancer [10]. In addition, TUBA1C can also negatively regulate miR-143-3p to promote the proliferation of lung cancer cells and reduce cancer cell apoptosis [11]. However, few studies on TUBA1C in breast cancer have been published. Although other studies have included TUBA1C in the screening of differentially expressed genes in breast cancer, the focus of these studies was not TUBA1C, and thus, the correlation between TUBA1C and the prognosis of breast cancer patients has not been thoroughly studied [19]. In this study, the expression and potential prognostic value of TUBA1C in breast cancer were investigated.
In this study, analysis of high-throughput RNA-seq data from the TCGA database confirmed that TUBA1C expression in breast cancer tissues was significantly higher than that in normal tissues, and the pairwise difference analysis between cancer and paired paracancerous tissues also showed that in cancer tissues, TUBA1C expression was significantly higher than that in paired paracancerous tissues. According to previous research, high TUBA1C expression can promote cell proliferation, which may lead to the poor prognosis of breast cancer patients. In addition, the abnormally high TUBA1C expression in breast cancer tissues was closely related to survival status, survival time, and tumor size. Compared with the low expression group, patients with high TUBA1C expression had worse OS and were more prone to disease recurrence; moreover, DMFS was also significantly lower. Univariate and multivariate Cox analyses also showed that high TUBA1C expression was an independent risk factor for OS in breast cancer patients.
To further investigate the function of TUBA1C in breast cancer, the pathways related to TUBA1C were analyzed by GSEA. The results showed that the high TUBA1C expression phenotype was differentially enriched in cell cycle, basal transcription factor, P53 signaling pathway, pathways in cancer, TOLL-like receptor signaling pathway, and NOD-like receptor signaling pathway. The correlations between TUBA1C and the TOLL-like receptor signaling pathway and the NOD-like receptor signaling pathway in breast cancer were first reported in this study, but the specific regulatory mechanisms remain to be further elucidated.
Analysis of the HPA database showed that the upregulation of TUBA1C expression in lung cancer, liver cancer, pancreatic cancer, and breast cancer tissues exhibited the same trend. Studies targeting lung cancer, liver cancer, and pancreatic cancer have all confirmed that TUBA1C promotes tumorigenesis and progression and is a potential prognostic biomarker for liver cancer and pancreatic cancer.
In summary, a comprehensive bioinformatics analysis using the TCGA database was performed, and the results showed that TUBA1C is a potential biomarker that predicts a poor prognosis in breast cancer. However, the study design had some limitations, and additional prospective studies and experiments are still needed to reveal the biological function of TUBA1C in breast cancer.
Supporting information
S1 Fig. Correlation analysis between the different expression levels of TUBA1C and OS.
The data were processed using R software (version 4.0.3).
https://doi.org/10.1371/journal.pone.0263710.s001
(TIF)
Acknowledgments
The authors express our sincerely acknowledgment to Mr. Zhang Chengwu who provided assistance in study design.
References
- 1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021. pmid:33538338.
- 2. Jafari SH, Saadatpour Z, Salmaninejad A, Momeni F, Mokhtari M, Nahand JS, et al. Breast cancer diagnosis: Imaging techniques and biochemical markers. J Cell Physiol. 2018; 233:5200–13. pmid:29219189.
- 3. Kaur R, Kaur G, Gill RK, Soni R, Bariwal J. Recent developments in tubulin polymerization inhibitors: An overview. Eur J Med Chem. 2014; 87:89–124. pmid:25240869.
- 4. Zahnleiter D, Hauer NN, Kessler K, Uebe S, Sugano Y, Neuhauss SC, et al. MAP4-dependent regulation of microtubule formation affects centrosome, cilia, and Golgi architecture as a central mechanism in growth regulation. Hum Mutat. 2015; 36:87–97. pmid:25323976.
- 5. Matov A, Applegate K, Kumar P, Thoma C, Krek W, Danuser G, et al. Analysis of microtubule dynamic instability using a plus-end growth marker. Nat Methods. 2010; 7:761–8. pmid:20729842.
- 6. Grimaldi AD, Zanic M, Kaverina I. Encoding the microtubule structure: Allosteric interactions between the microtubule +TIP complex master regulators and TOG-domain proteins. Cell Cycle. 2015; 14:1375–8. pmid:25895033.
- 7. Verdier-Pinard P, Wang F, Burd B, Angeletti RH, Horwitz SB, Orr GA. Direct analysis of tubulin expression in cancer cell lines by electrospray ionization mass spectrometry. Biochemistry. 2003; 42:12019–27. pmid:14556633.
- 8. Hall JL, Cowan NJ. Structural features and restricted expression of a human alpha-tubulin gene. Nucleic Acids Res. 1985; 13:207–23. pmid:3839072.
- 9. Fortner RT, Damms-Machado A, Kaaks R. Systematic review: Tumor-associated antigen autoantibodies and ovarian cancer early detection. Gynecol Oncol. 2017; 147:465–80. pmid:28800944.
- 10. Albahde M, Zhang P, Zhang Q, Li G, Wang W. Upregulated Expression of TUBA1C Predicts Poor Prognosis and Promotes Oncogenesis in Pancreatic Ductal Adenocarcinoma via Regulating the Cell Cycle. Front Oncol. 2020; 10:49. pmid:32117719.
- 11. Yang J, Jia Y, Wang B, Yang S, Du K, Luo Y, et al. Circular RNA TUBA1C accelerates the progression of non-small-cell lung cancer by sponging miR-143-3p. Cell Signal. 2020; 74:109693. pmid:32599139.
- 12. Wang J, Chen W, Wei W, Lou J. Oncogene TUBA1C promotes migration and proliferation in hepatocellular carcinoma and predicts a poor prognosis. Oncotarget. 2017; 8:96215–24. pmid:29221200.
- 13. Nami B, Wang Z. Genetics and Expression Profile of the Tubulin Gene Superfamily in Breast Cancer Subtypes and Its Relation to Taxane Resistance. Cancers (Basel). 2018; 10. pmid:30126203.
- 14. Ramos J, Yoo C, Felty Q, Gong Z, Liuzzi JP, Poppiti R, et al. Sensitivity to differential NRF1 gene signatures contributes to breast cancer disparities. J Cancer Res Clin Oncol. 2020; 146:2777–815. pmid:32705365.
- 15. Tomczak K, Czerwińska P, Wiznerowicz M. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemp Oncol (Pozn). 2015; 19:A68–77. pmid:25691825.
- 16. Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017; 45:W98–98W102. pmid:28407145.
- 17. Győrffy B, Surowiak P, Budczies J, Lánczky A. Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer. PLoS One. 2013; 8:e82241. pmid:24367507.
- 18. Damian D, Gorfine M. Statistical concerns about the GSEA procedure. Nat Genet. 2004; 36:663; author reply 663. pmid:15226741.
- 19. Wang C, Li CY, Cai JH, Sheu PC, Tsai J, Wu MY, et al. Identification of Prognostic Candidate Genes in Breast Cancer by Integrated Bioinformatic Analysis. J Clin Med. 2019; 8. pmid:31382519.