Skip to main content

Advertisement

SpringerLink
Log in

Comprehensive transcriptomic analysis of papillary thyroid cancer: potential biomarkers associated with tumor progression

  • Original Article
  • Published:
Journal of Endocrinological Investigation Aims and scope Submit manuscript

Abstract

Purpose

Identification of stage-specific prognostic/predictive biomarkers in papillary thyroid carcinoma (PTC) could lead to its more efficient clinical management. The main objective of this study was to characterize the stage-specific deregulation in genes and miRNA expression in PTC to identify potential prognostic biomarkers.

Methods

495 RNASeq and 499 miRNASeq PTC samples (stage I–IV) as well as, respectively, 56 and 57 normal samples were retrieved from The Cancer Genome Atlas (TCGA). Differential expression analysis was performed using DESeq 2 to identify deregulation of genes and miRNAs between sequential stages. To identify the minority of patients who progress to higher stages, we performed clustering analysis on stage I RNASeq data. An independent PTC RNASeq data set (BioProject accession PRJEB11591) was also used for the validation of the results.

Results

LTF and PLA2R1 were identified as two promising biomarkers down-regulated in a subgroup of stage I (both in TCGA and in the validation data set) and in the majority of stage IV of PTC (in TCGA data set). hsa-miR-205, hsa-miR-509-2, hsa-miR-514-1 and hsa-miR-514-2 were also detected as up-regulated miRNAs in both PTC patients with stage I and stage III. Hierarchical clustering of stage I samples showed substantial heterogeneity in the expression pattern of PTC indicating the necessity of categorizing stage I patients based on the expressional alterations of specific biomarkers.

Conclusion

Stage I PTC patients showed large amount of expressional heterogeneity. Therefore, risk stratification based on the expressional alterations of candidate biomarkers could be an important step toward personalized management of these patients.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Availability of data and material

Data are available at (http://portal.gdc.cancer.gov/).

References

  1. Bray F et al (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J Clin 68(6):394–424

    Google Scholar 

  2. Katoh H et al (2015) Classification and general considerations of thyroid cancer. Ann Clin Pathol 3(1):1045

    Google Scholar 

  3. Agrawal N et al (2014) Integrated genomic characterization of papillary thyroid carcinoma. Cell 159(3):676–690

    PubMed Central  Google Scholar 

  4. Haraldsdottir S, Shah MH (2014) New era for treatment in differentiated thyroid cancer. The Lancet 384(9940):286–288

    Google Scholar 

  5. Liu R et al (2018) Regulation of mutant TERT by BRAF V600E/MAP kinase pathway through FOS/GABP in human cancer. Nat Commun 9(1):579

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Teng H et al (2018) Transcriptomic signature associated with carcinogenesis and aggressiveness of papillary thyroid carcinoma. Theranostics 8(16):4345

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Love M, Anders S, Huber W (2014) Differential analysis of count data–the DESeq2 package. Genome Biol 15(550):10.1186

    Google Scholar 

  8. Chen EY et al (2013) Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinf 14(1):128

    Google Scholar 

  9. Kanehisa M et al (2016) KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res 45(D1):D353–D361

    PubMed  PubMed Central  Google Scholar 

  10. UniProt: the universal protein knowledgebase. (2016) Nucleic Acids Res 45(D1): D158–D169

  11. Seliger C et al (2013) Lactate-modulated induction of THBS-1 activates transforming growth factor (TGF)-beta2 and migration of glioma cells in vitro. PLoS ONE 8(11):e78935

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Amoli MM et al (2010) HLA-DR association in papillary thyroid carcinoma. Dis Markers 28(1):49–53

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Jo YS et al (2008) Significance of the expression of major histocompatibility complex class II antigen, HLA-DR and-DQ, with recurrence of papillary thyroid cancer. Int J Cancer 122(4):785–790

    CAS  PubMed  Google Scholar 

  14. Soini Y, Pääkkö P, Lehto V (1998) Histopathological evaluation of apoptosis in cancer. Am J Pathol 153(4):1041–1053

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Gottfried Y et al (2004) Expression of the pro-apoptotic protein ARTS in astrocytic tumors: Correlation with malignancy grade and survival rate. Cancer Interdiscip Int J Am Cancer Soc 101(11):2614–2621

    CAS  Google Scholar 

  16. Poulios E et al (2018) Identification of a novel, diagnostic microRNA signature in papillary thyroid cancer. J Med Surg Pathol 162–167

  17. Yu S et al (2012) Circulating microRNA profiles as potential biomarkers for diagnosis of papillary thyroid carcinoma. J Clin Endocrinol Metabol 97(6):2084–2092

    CAS  Google Scholar 

  18. Blanco CG, Matute EM, de Leiva Hidalgo A (2012) Molecular biomarkers involved in the tumor dedifferentiation process of thyroid carcinoma of epithelial origin: perspectives. Endocrinol Nutr 59(7):452–458

    Google Scholar 

  19. Acquaviva G et al (2018) Molecular pathology of thyroid tumours of follicular cells: a review of genetic alterations and their clinicopathological relevance. Histopathology 72(1):6–31

    PubMed  Google Scholar 

  20. Liyanarachchi S et al (2016) Genome-wide expression screening discloses long noncoding RNAs involved in thyroid carcinogenesis. J Clin Endocrinol Metabol 101(11):4005–4013

    CAS  Google Scholar 

  21. Brennan K et al (2016) Development of prognostic signatures for intermediate-risk papillary thyroid cancer. BMC Cancer 16(1):736

    PubMed  PubMed Central  Google Scholar 

  22. Menschikowski M et al (2015) Epigenetic control of phospholipase A 2 receptor expression in mammary cancer cells. BMC Cancer 15(1):971

    PubMed  PubMed Central  Google Scholar 

  23. Salazar M et al (2015) Loss of Tribbles pseudokinase-3 promotes Akt-driven tumorigenesis via FOXO inactivation. Cell Death Differ 22(1):131

    CAS  PubMed  Google Scholar 

  24. Lu C et al (2011) Genomic profiling of genes contributing to metastasis in a mouse model of thyroid follicular carcinoma. Am J Cancer Res 1(1):1

    PubMed  Google Scholar 

  25. Rodriguez MCP et al (2012) Methods for diagnosing follicular thyroid cancer. Google Patents

  26. Song J, Yang Z (2018) Case report: whole exome sequencing of circulating cell-free tumor DNA in a follicular thyroid carcinoma patient with lung and bone metastases. J Circ Biomark 7:1849454418763725

    PubMed  PubMed Central  Google Scholar 

  27. Cerutti JM et al (2007) Molecular profiling of matched samples identifies biomarkers of papillary thyroid carcinoma lymph node metastasis. Can Res 67(16):7885–7892

    CAS  Google Scholar 

  28. Qian Z et al (2014) High expression of TNFSF13 in tumor cells and fibroblasts is associated with poor prognosis in non-small cell lung cancer. Am J Clin Pathol 141(2):226–233

    PubMed  Google Scholar 

  29. Huang Y et al (2001) Gene expression in papillary thyroid carcinoma reveals highly consistent profiles. Proc Natl Acad Sci 98(26):15044–15049

    CAS  PubMed  Google Scholar 

  30. Niedźwiecki S et al (2008) Serum levels of interleukin-1 receptor antagonist (IL-1ra) in thyroid cancer patients. Langenbeck’s Archiv Surg 393(3):275–280

    Google Scholar 

  31. Joung KH, Shong M (2012) Epigenetic regulation of RUNX3 in thyroid carcinoma. Korean J Int Med 27(4):391

    CAS  Google Scholar 

  32. dos Reis M et al (2016) Epigenetic alterations in well-differentiated thyroid cancer. J Clin Epigenet 1:1

    Google Scholar 

  33. Moarii M et al (2015) Changes in correlation between promoter methylation and gene expression in cancer. BMC Genom 16(1):873

    Google Scholar 

  34. Saiselet M et al (2016) miRNA expression and function in thyroid carcinomas: a comparative and critical analysis and a model for other cancers. Oncotarget 7(32):52475

    PubMed  PubMed Central  Google Scholar 

  35. Mancikova V et al (2015) MicroRNA deep-sequencing reveals master regulators of follicular and papillary thyroid tumors. Mod Pathol 28(6):748

    CAS  PubMed  Google Scholar 

  36. Zhang P et al (2018) Association of miR-1247-5p expression with clinicopathological parameters and prognosis in breast cancer. Int J Exp Pathol 99(4):199–205

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Fang T et al (2018) Tumor-derived exosomal miR-1247-3p induces cancer-associated fibroblast activation to foster lung metastasis of liver cancer. Nat Commun 9(1):191

    PubMed  PubMed Central  Google Scholar 

  38. He J, Wang H (2019) HspA1B is a prognostic biomarker and correlated with immune infiltrates in different subtypes of breast cancers. bioRxiv 1–31. https://doi.org/10.1101/725861

  39. Peng JX, Liang SY, Li L (2019) sFRP1 exerts effects on gastric cancer cells through GSK3β/Rac1-mediated restraint of TGFβ/Smad3 signaling. Oncol Rep 41(1):224–234

    CAS  PubMed  Google Scholar 

  40. Fadda G (2012) Application of liquid-based cytology to fine-needle aspiration biopsies of the thyroid gland. Front Endocrinol 3:57

    Google Scholar 

  41. Del Pino M et al (2015) mRNA biomarker detection in liquid-based cytology: a new approach in the prevention of cervical cancer. Mod Pathol 28(2):312

    PubMed  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the supports provided by Iran University of Medical Sciences (Grant number 33444).

Funding

Financial support was provided by Iran University of Medical Sciences (Grant number 33444).

Author information

Authors and Affiliations

  1. Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran

    N. Hosseinkhan, M. Honardoost & M. E. Khamseh

  2. Biomedical Sciences Research Institute, Ulster University, Coleraine, Northern Ireland

    K. Blighe & C. B. T. Moore

Authors
  1. N. Hosseinkhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Honardoost
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. Blighe
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C. B. T. Moore
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. E. Khamseh
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M. K designed and supervised the project. N. H performed the data analyses and wrote the manuscript. K. B, M. K and M. H commented on the manuscript. T. M reviewed the paper.

Corresponding author

Correspondence to M. E. Khamseh.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethics approval and consent to participate

Ethical approval for this study was obtained from The Committee for Ethics in Research Involving Human Subjects, Iran University of Medical Sciences (Ethical code—IR.IUMS.REC.1397.203).

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

List of up and down-regulated genes in different clusters of stage I (XLS 36 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hosseinkhan, N., Honardoost, M., Blighe, K. et al. Comprehensive transcriptomic analysis of papillary thyroid cancer: potential biomarkers associated with tumor progression. J Endocrinol Invest 43, 911–923 (2020). https://doi.org/10.1007/s40618-019-01175-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40618-019-01175-7

Keywords

Search

Navigation