Identification of Potential Predictive Transcript Isoform-Biomarkers for the Early Diagnosis of Breast Cancer Using Bioinformatics Tools Bioinformatics tools in early diagnosis of BC

Hulya Gundesli (1), Medi Kori (2), Cihan Ergul (3)
(1) Gulhane Faculty of Medicine, University of Health Sciences, Department of Medical Biology, Ankara, Turkey, Turkey,
(2) Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey; Faculty of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, Turkey,
(3) Gulhane Faculty of Medicine, University of Health Sciences, Department of Medical Biology, Ankara, Turkey, Turkey

Abstract

Background: Several studies have demonstrated that the expression status of isoforms is more informative as a biomarker than overall gene expression. This study aimed to determine highly but significantly expressed transcript isoforms and evaluate their prognostic and diagnostic impact in breast invasive carcinoma (BRCA) stage I patients.


Methods: The differentially expressed genes and their transcript isoforms in BRCA stage I were determined using the Cancer Differentially Expressed Isoform and gene (Cancer DEIso) platform based on The Cancer Genome Atlas (TCGA) data. The prognostic and diagnostic impact of significantly upregulated top 10 genes and their transcripts were revealed using the Cancer DEIso tool, the Kaplan-Meier (KM) method, and the Receiver Operating Characteristic Curve (ROC) approach, respectively. Isoform-level protein-protein interactions (PPI) were constructed using the Domain Interaction Graph Guided ExploreR (DIGGER) database. ConsensusPathDB was used to perform pathway enrichment analysis based on the constructed interactions.


Results: This study revealed that NM_024037, NM_001143782, and NM_021619 transcript isoforms have significant diagnostic ability with AUC values 93.2%, 77.1% and 75.3%, respectively to distinguish stage I BRCA patients from normal. KM-plot analysis showed that these three isoforms have no prognostic significance in stage I patients, but their upregulation was correlated with decreased survival in BRCA patients regardless of stage. Isoform-based pathway enrichment analyses indicated that these three isoforms involved in chromatin organization, senescense, DNA damage and several signalling pathways which promotes cancer when there is misregulation. .


Conclusion: NM_024037, NM_001143782, and NM_021619 transcript isoforms are potential biomarkers for detecting early-stage BRCA. Thus, it is essential to find out how these three isoforms contribute to the development of breast carcinogenesis and evolve a new approach for capturing breast tumors at an earlier stage of the clinical landscape.

Full text article

Generated from XML file

References

De Miglio MR and Mello-Thoms C. Editorial: Reviews in breast cancer. Front. Oncol. 2023; 13:1161583. doi: 10.3389/fonc.2023.1161583.

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; 71:209–49. doi: 10.3322/CAAC.21660.

GLOBOCAN Cancer Tomorrow Prediction Tool. https://gco.iarc.fr/tomorrow/en/dataviz/tables?cancers=20&years=2050&types=0. Accessed on March 30, 2024.

Mangone L, Marinelli F, Bisceglia I, Braghiroli MB, Damato A and Pinto C. Five-year relative survival by stage of breast and colon cancers in northern Italy. Front Oncol. 2022; 12:982461. doi: 10.3389/fonc.2022.982461.

Orrantia-Borunda E, Anchondo-Nuñez P, Acuña-Aguilar LE, Gómez-Valles FO, Ramírez-Valdespino CA. Subtypes of Breast Cancer. In: Mayrovitz HN. editor. Breast Cancer. Brisbane (AU): Exon Publications. Online first 22 Jun 2022. Doi: https://doi.org/10.36255/exon-publications-breast-cancer-subtypes.

Neves Rebello Alves, L., Dummer Meira D, Poppe Merigueti L, Correia Casotti M, do Prado Ventorim D, Ferreira Figueiredo Almeida J, Pereira de Sousa V, Cindra Sant’Ana M, Gonçalves Coutinho da Cruz R, Santos Louro L, et al. Biomarkers in Breast Cancer: An Old Story with a New End. Genes. 2023; 14: 1364. https://doi.org/10.3390/genes14071364.

Nair MG, Somashekaraiah VM, Ramamurthy V, Prabhu JS, Sridhar TS. miRNAs: Critical mediators of breast cancer metastatic programming. Exp. Cell Res. 2021; 401: 112518. doi: 10.1016/j.yexcr.2021.112518.

Uhl B, Mittmann LA, Dominik J, Hennel R, Smiljanov B, Haring F, Schaubächer JB, Braun C, Padovan L, Pick R, et al. uPA-PAI-1 heteromerization promotes breast cancer progression by attracting tumorigenic neutrophils. EMBO Mol. Med. 2021; 13: e13110. doi: 10.15252/emmm.202013110.

Tu X, Qin B, Zhang Y, Zhang C, Kahila M, Nowsheen S, Yin P, Yuan J, Pei H, Li H, et al. PD-L1 (B7-H1) Competes with the RNA Exosome to Regulate the DNA Damage Response and Can Be Targeted to Sensitize to Radiation or Chemotherapy. Mol Cell. 2019; 74: 1215–26. doi: 10.1016/j.molcel.2019.04.005.

Zhang R, Yang Y, Dong W, Lin M, He J, Zhang X, Tian T, Yang Y, Chen K, Lei QY, et al. D-mannose facilitates immunotherapy and radiotherapy of triple-negative breast cancer via degradation of PD-L1. Proc Natl Acad Sci USA. 2022; 119: e2114851119. doi: 10.1073/pnas.2114851119.

Klouch KZ, Stern MH, Trabelsi-Grati O, Kiavue N, Cabel L, Silveira AB, Hego C, Rampanou A, Popova T, Bataillon G, et al. Microsatellite instability detection in breast cancer using drop-off droplet digital PCR. Oncogene. 2022; 41: 5289–97. doi: 10.1038/s41388-022-02504-6.

Trincado JL, Sebestyén E, Pagés A, Eyras E. The prognostic potential of alternative transcript isoforms across human tumors, Genome Med. 2016; 8: 85. https://doi.org/10.1186/s13073-016-0339-3.

Pal S, Bi Y, MacYszyn L, Showe LC, O'Rourke DM, Davuluri RV. Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypes, Nucleic Acids Res. 2014; 201442: 1–11. https://doi.org/10.1093/ nar/gku121.

Zhang Z, Pal S, Bi Y, Tchou J, Davuluri RV. Isoform level expression profiles provide better cancer signatures than gene level expression profiles, Genome Med. 2013; 5, 33. https://doi.org/10.1186/gm437.

Safikhani Z, Thu KL, Silvester J, Smirnov P, Lupien M, Mak TW, et al. Gene isoforms as expression-based biomarkers predictive of drug response in vitro. Nat Commun. 2017; 160937. https://doi.org/10.1101/160937.

Avery-Kiejda, KA, Morten B, Wong-Brown MW, Mathe A, Scott RJ. The relative mRNA expression of p53 isoforms in breast cancer is associated with clinical features and outcome. Carcinogenesis. 2014; 35, 586–96. doi: 10.1093/carcin/bgt411.

Safikhani Z, Smirnov P, Thu KL, Silvester J, El-Hachem N, et al. Gene isoforms as expression-based biomarkers predictive of drug response in vitro. Nat Commun. 2017; 24,8(1), 1126. doi: 10.1038/s41467-017-01153-8.

Lin T, Qiu Y, Peng W, Peng L. Heat Shock Protein 90 Family Isoforms as Prognostic Biomarkers and Their Correlations with Immune Infiltration in Breast Cancer. Biomed Res Int. 2020: 2020:2148253. doi: 10.1155/2020/2148253.

Erdem M, Ozgul I, Dioken DN, Gurcuoglu I, Guntekin-Ergun S, Cetin-Atalay R, et al. Identification of an mRNA isoform switch for HNRNPA1 in breast cancers. Sci Rep. 2021; 11:24444. https://doi.org/10.1038/s41598-021-04007-y.

Tzu-Hsien Y, Yu-Hsuan C, Sheng-Cian S, Po-Heng L, Ya-Chiao Y, Kai-Chi T et al. Cancer DEIso: An integrative analysis platform for investigating differentially expressed gene-level and isoform-level human cancer markers. Comput Struct Biotechnol J. 2021; 19, 5149-59. doi: 10.1016/j.csbj.2021.09.005.

Tomczak K, Czerwin´ska P, Wiznerowicz M. The Cancer Genome Atlas (TCGA): An immeasurable source of knowledge. Contemp Oncol (Pozn). 2015; 19(1A), A68–A77. doi: 10.5114/wo.2014.47136

Mandrekar JN. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010; 5(9), 1315–16. doi: 10.1097/JTO.0b013e3181ec173d.

Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, et al. Orchestrating highthroughput genomic analysis with Bioconductor. Nat Methods. 2015; 12(2), 115–121. doi: 10.1038/nmeth.3252.

Louadi Z, Yuan K, Gress A, Tsoy O, Kalinina OV, Baumbach J, et al. DIGGER: exploring the functional role of alternative splicing in protein interactions. Nucleic Acids Research. 2021; 49, 309–18. doi: 10.1093/nar/gkaa768.

Kamburov A, Stelzl U, Lehrach H, Herwing R. The ConsensusPathDB interaction database: 2013 update. Nucleic Acids Res. 2013; 41, 793–800. doi: 10.1093/nar/gks1055.

Zhang Z, Pal S, Yingtao B, Tchou J, Davuluri RV. Isoform level expression profiles provide better cancer signatures than gene level expression profiles. Genome Med. 2013; 5(4), 33. doi: 10.1186/gm437.

Mei J, Liu Y, Xu R, Hao L, Qin A, Chu C, Zhu Y, Liu X. Characterization of the expression and prognostic value of 14-3-3 isoforms in breast cancer. Aging (Albany NY). 2020; 12(19), 19597-19617. doi: 10.18632/aging.103919.

Gundesli H, Kori M, Arga KY. The Versatility of Plectin in Cancer: A Pan-Cancer Analysis on Potential Diagnostic and Prognostic Impacts of Plectin Isoforms. OMICS, 2023; 27(6):281-296. doi: 10.1089/omi.2023.0053.

Yang L, Gilbertsen A, Jacobson B, Pham J, Fujioka N, Henke CA, et al. SFPQ and Its Isoform as Potential Biomarker for Non-Small-Cell Lung Cancer. Int J Mol Sci. 2023; 24(15), 12500. doi: 10.3390/ijms241512500.

Lieu AS, Cheng TS, Chou CH, Wu CH, Hsu CY, Huang CYF, et al. Functional characterization of AIBp, a novel Aurora-a binding protein in centrosome structure and spindle formation. Int J Oncol. 2010; 37(2), 429–436. doi: 10.3892/ijo_0000069.

Lou J, Chen H, Han J, He H, Huen MSY, Feng XH et al. AUNIP/C1orf135 directs DNA double-strand breaks towards the homologous recombination repair pathway. Nat Commun. 2017; 8(1), 985. doi: 10.1038/s41467-017-01151-w.

Yang Z, Liang X, Fu Y, Liu Y, Zheng L, Liu F, et al. Identification of AUNIP as a candidate diagnostic and prognostic biomarker for oral squamous cell carcinoma. EBioMedicine. 2019; 47, 44-57. doi: 10.1016/j.ebiom.2019.08.013.

Ma C, Kang W, Yu L, Yang Z and Ding T. AUNIP expression is correlated with immune infiltration and is a candidate diagnostic and prognostic biomarker for hepatocellular carcinoma and lung adenocarcinoma. Front. Oncol. 2020; 10, 590006. doi: 10.3389/fonc.2020.590006.

Qu Y, Lu J, Mei W, Jia Y, Bian C, Ding Y et al. Prognostic biomarkers of pancreatic cancer identified based on a competing endogenous RNA regulatory network. Transl Cancer Res. 2022; 11(11), 4019-36. doi: 10.21037/tcr-22-709.

Harding MW, Galat A, Uehling DE, Schreiber SL. A Receptor for the Immunosuppressant FK506 Is a Cis-Trans Peptidyl-Prolyl Isomerase. Nature, 1989; 341, 758–60. doi: 10.1038/341758a0.

Solassol J, Mange A, Maudelonde T. FKBP Family Proteins as Promising New Biomarkers for Cancer. Curr Opin Pharmacol. 2011; 11, 320–25. doi: 10.1016/j.coph.2011.03.012.

Ge Y, Xu A, Zhang M, Xiong H, Fang L, Zhang X, et al. FK506 Binding Protein 10 Is Overexpressed and Promotes Renal Cell Carcinoma. Urol Int. 2017; 98, 169–76. doi: 10.1159/000448338.

Wang T, He X, Liu X, Liu Y, Zhang W, Huang Q, Liu W, Xiong L, Tan R, Wang H and Zeng H. Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway. Front. Physiol. 2017; 8:1010. doi: 10.3389/fphys.2017.01010.

Qiu L, Liu H, Wang S, Dai XH, Shang JW, Lian XL, et al. FKBP11 promotes cell proliferation and tumorigenesis via p53-related pathways in oral squamous cell carcinoma. Biochem. Biophys. Res. Commun. 2021; 25, 559, 183-90. doi: 10.1016/j.bbrc.2021.04.096.

Sun Z, Qin X, Fang J, Tang Y and Fan Y. Multi-Omics Analysis of the Expression and Prognosis for FKBP Gene Family in Renal Cancer. Front. Oncol. 2021; 11, 697534. doi: 10.3389/fonc.2021.697534.

Wang CC, Shen WJ, Anuraga G, Hsieh YH, Khoa Ta HD, Xuan DTM, et al. Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma. J. Pers. Med. 2023; 13, 49. https://doi.org/10.3390/jpm13010049.

Zeng D, Li J, Yuan X, Cai F, Yu B, Liu L, et al. FKBP11 improves the malignant property of osteosarcoma cells and acts as a prognostic factor of osteosarcoma. Aging (Albany NY). 2023; 15(7), 2450-59. doi: 10.18632/aging.204523.

Casamassimi A, Rienzo M, Di Zazzo E, Sorrentino A, Fiore D, Proto MC, et al. Multifaceted Role of PRDM Proteins in Human Cancer. Int. J. Mol. Sci. 2020; 21, 2648. doi: 10.3390/ijms21072648.

Rienzo M, Di Zazzo E, Casamassimi A, Gazzerro P, Perini G, Bifulco M, Abbondanza C. PRDM12 in Health and Diseases. Int. J. Mol. Sci. 2021; 22, 12030. https://doi.org/10.3390/ijms222112030.

Huang S, Shao G, Liu L. The PR Domain of the Rb-binding Zinc Finger Protein RIZ1 Is a Protein Binding Interface and Is Related to the SET Domain Functioning in Chromatin-mediated Gene Expression. J. Biol. Chem. 1998; 273, 15933–15939. doi: 10.3390/ijms19103250.

Sorrentino A, Federico A, Rienzo M, Gazzerro P, Bifulco M, Ciccodicola A, et al. PR/SET Domain Family and Cancer: Novel Insights from the Cancer Genome Atlas. Int. J. Mol. Sci. 2018; 19, 3250. doi: 10.3390/ijms19103250.

Reid AG, Nacheva EP. A potential role for PRDM12 in the pathogenesis of chronic myeloid leukaemia with derivative chromosome 9 deletion. Leukemia. 2003; 18, 178–80. doi: 10.1038/sj.leu.2403162.

Huet S, Dulucq S, Chauveau A, Ménard A, Chomel JC, Maisonneuve H, et al. Molecular characterization and follow-up of five CML patients with new BCR-ABL1 fusion transcripts. Genes Chromosom. Cancer. 2015; 54, 595–605. doi: 10.1002/gcc.22263.

Kuo CY, Moi SH, Hou MF, Luo CW, Pan MR. Chromatin Remodeling Enzyme Cluster Predicts Prognosis and Clinical Benefit of Therapeutic Strategy in Breast Cancer. Int. J. Mol. Sci. 2023; 24, 5583. https://doi.org/10.3390/ijms24065583.

Zhang L, Qu J, Qi Y, Duan Y, Huang YW, Zhou Z, et al. EZH2 engages TGFβ signaling to promote breast cancer bone metastasis via integrin β1-FAK activation. Nat. Commun. 2022; 13(1), 2543. doi: 10.1038/s41467-022-30105-0.

Zhao Y, Hu Z, Li J, Hu T. EZH2 Exacerbates Breast Cancer by Methylating and Activating STAT3 Directly. J. Cancer. 2021; 12(17), 5220-30. doi: 10.7150/jca.50675. eCollection 2021.

Authors

Hulya Gundesli
hulya.gundesli@sbu.edu.tr (Primary Contact)
Medi Kori
Cihan Ergul
1.
Gundesli H, Kori M, Ergul C. Identification of Potential Predictive Transcript Isoform-Biomarkers for the Early Diagnosis of Breast Cancer Using Bioinformatics Tools: Bioinformatics tools in early diagnosis of BC. Arch Breast Cancer [Internet]. 2024 Oct. 25 [cited 2024 Nov. 14];11(4). Available from: https://archbreastcancer.com/index.php/abc/article/view/950

Article Details