Indian Journal of Pathology and Microbiology
Home About us Instructions Submission Subscribe Advertise Contact e-Alerts Ahead Of Print Login 
Users Online: 9843
Print this page  Email this page Bookmark this page Small font sizeDefault font sizeIncrease font size

  Table of Contents    
Year : 2012  |  Volume : 55  |  Issue : 2  |  Page : 158-162
Discriminating thyroid cancers from benign lesions based on differential expression of a limited set of miRNA using paraffin embedded tissues

1 Department of Pathology, Unit VI, Christian Medical College, Vellore, Tamil Nadu, India
2 Department of Biostatistics, Unit VI, Christian Medical College, Vellore, Tamil Nadu, India
3 Department of Surgery, Unit VI, Christian Medical College, Vellore, Tamil Nadu, India

Click here for correspondence address and email

Date of Web Publication3-Jul-2012


Background : Micro-RNAs (miRNAs) are expressed in a tissue-specific manner and are known to demonstrate differential expression even among the various subtypes of a given tumor. This differential expression has been harnessed successfully in the development of diagnostic assays for various malignant tumors. These assays have been found to be relevant and of value as additional diagnostic tools even among thyroid tumors, particularly with regard to thyroid carcinomas of follicular morphology. Materials and Methods : A limited set of miRNA have been assessed as part of this study in an effort to use minimal number of miRNA markers (miR-187, miR-221, miR-222, and miR-224) to differentiate the benign from the malignant thyroid tumors using miRNA derived from paraffin embedded material. Results : While miR-221 and miR-222 were found to provide good accuracy as individual markers (86% and 84%), a combination of the two provided slightly better accuracy (91%). Both miR-221 and 222 were able to significantly differentiate malignant tumors from the benign samples (P< 0.001) individually and as a combination of markers. However, inclusion of miR-187 and miR-224 in the panel did not provide any additional benefit. Conclusion : While a combination of miR-221 and 222 when used in a diagnostic panel could provide fairly good accuracy additional markers may need to be investigated to augment their diagnostic utility.

Keywords: Diagnostic markers, miR-221, miR-222, miRNA, thyroid tumors

How to cite this article:
Pai R, Nehru G A, Samuel P, Selvan B, Kumar R, Jacob PM, Nair A. Discriminating thyroid cancers from benign lesions based on differential expression of a limited set of miRNA using paraffin embedded tissues. Indian J Pathol Microbiol 2012;55:158-62

How to cite this URL:
Pai R, Nehru G A, Samuel P, Selvan B, Kumar R, Jacob PM, Nair A. Discriminating thyroid cancers from benign lesions based on differential expression of a limited set of miRNA using paraffin embedded tissues. Indian J Pathol Microbiol [serial online] 2012 [cited 2022 Aug 11];55:158-62. Available from: https://www.ijpmonline.org/text.asp?2012/55/2/158/97845

   Introduction Top

Thyroid carcinomas encompass a heterogeneous group of neoplasms with distinct clinical and pathological features, constituting ~98% of all thyroid malignancies. [1],[2] Most thyroid carcinomas originate from the thyroid follicular cells and can be subdivided as well differentiated papillary carcinoma (PC) and follicular carcinoma (FC), where both could progress to poorly differentiated carcinoma (PDC) or lose differentiation to become anaplastic carcinoma (AC). The current standard to distinguish benign from malignant tumors and classify thyroid carcinomas into their consequential subtypes is largely based on histological examination. [1,3] However, histological classification of these tumors can be challenging particularly among some follicular patterned tumors when follicular adenomas that are benign, need to be distinguished from FC. Therefore, there is considerable emphasis on developing additional diagnostic tests that could help overcome this dilemma. In this context, micro-RNA (miRNA) profiling has been found to be very promising and the utility of several miRNA in improving diagnostic accuracy has been validated. [4],[5],[6]

Micro-RNAs (miRNA) are small non-protein coding RNAs involved in crucial biological processes including cellular differentiation, development, apoptosis, and proliferation. [7],[8] There is growing evidence that the "miRNA signature" is different in cancer and normal cells and that expression is tissue-specific making them important tools with diagnostic and prognostic relevance. Further, miRNA remain intact and well preserved even in formalin fixed paraffin embedded (FFPE) material making it possible to characterize them from routine histopathological samples. Studies have successfully demonstrated the usefulness of these markers in discriminating poorly differentiated and undifferentiated tumors in terms of tissue of origin. [9],[10],[11] Interestingly, several promising miRNA markers have been identified for thyroid carcinomas by different investigators with some overlapping suggestions. [12],[13],[14],[15] The most comprehensive panel characterized thus far, has included as many as seven markers (miR-187, miR-221, miR-222, miR-146b, miR-155, miR-224, and miR-197) to detect thyroid cancers in surgical and preoperative samples. [12] While these results are encouraging, performing seven assays routinely in smaller laboratories with limited resources particularly in developing country settings may be difficult. We therefore undertook a small pilot study at our center, to determine if the expression patterns of a limited set of miRNA viz., miR-187, miR-221, miR-222, and miR-224 would be adequate to accurately discriminate thyroid carcinoma from non-malignant specimens. These markers were chosen from a set of ten most up-regulated miRNA, among the various thyroid tumors tested by Nikiforova et al. [4]

   Materials and Methods Top

Thyroid Tissue Samples

Thirty eight formalin fixed paraffin embedded (FFPE) thyroidectomy samples (9 classical papillary thyroid carcinomas [PTC]; 8 follicular variant of PTC, 2 follicular thyroid carcinomas [FTC], 11 follicular adenomas [FA], 2 poorly differentiated thyroid carcinomas [PDC], 1 anaplastic thyroid carcinoma [ATC], 5 normal thyroid tissues) included in the study were obtained from the archives of the pathology department. All thyroidectomy samples included were obtained during the period 2007-08. The H&E slides of these cases were reviewed and their diagnosis confirmed using standard histological criteria for diagnosis. [3] Tumor was manually removed from unstained sections from representative blocks and transferred to microcentrifuge tubes for extraction of RNA.

RNA Extraction

RNA was extracted using the RecoverAll TM Total nucleic acid isolation kit (Ambion Inc, USA).

Briefly, the FFPE material obtained from the unstained sections were deparaffinized with xylene and digested with proteinase for 3 hours at 50°C, followed by several buffer washes, DNase treatment and final elution. RNA elute was quantitated using the NanoDrop (NanoDrop technologies, USA) and the 260/280 ratio determined. Further, 10 ng of total RNA was reverse transcribed with the Taqman microRNA reverse transcription kit (Applied Biosystems, USA), using miRNA sequence-specific primers for RNU-44, miR-187, miR-221, miR-222, and miR-224 in a 15 μl reaction volume, taking care to incubate reaction mixes for 5 minutes on ice before cycling for reverse transcription.

Quantitative Real-time PCR

Each sample was amplified with specific primers and probes (Applied Biosystems, USA) to determine miRNA expression of miR-187 (hsa-miR-187) and miR-221 (hsa-miR-221), miR-222 (hsa-miR-222) and miR-224 (hsa-miR-224). The reaction was performed in a 20 μl volume using 1X TaqMan mastermix (Applied Biosystems, USA) and 1 μl of cDNA. Amplification was performed using the universal thermal cycling conditions (50°C for 2 min, 95°C for 10 min, 95°C for 15 sec, 60°C for 1 min) on the 7500 real-time PCR system (Applied Biosystems, USA) for 40 cycles. Small nucleolar RNA, RNU-44, was used as an endogenous control and was amplified for all samples using the same thermal cycling parameters. Three samples were assayed three times to ensure reproducibility of the assay. miRNA expression levels were interpreted in terms of fold-change by the 2-ΔΔCT method. [16] The data was analyzed as the fold change in the miRNA expression of the tumor sample relative to the normal thyroid tissues after normalization to RNU-44.

Statistical Analysis

As a first step, the diagnostic value of each marker was determined by calculating the sensitivity, specificity, and accuracy. Accuracy was defined as (true positives + true negatives)/total sample size. The Receiver Operating Characteristic (ROC) Curve was plotted for each marker and the area under the ROC curve (area under the curve [AUC]) calculated. The area under the ROC curve is a common index of diagnostic accuracy, with a larger AUC indicating better ability of test at discriminating the two groups (malignant/benign tumors). [17] As a second step, multiple logistic regression analyses were performed to identify the best combination of two, three, and four markers that could discriminate the two groups. The coefficients from each of the regression analyses were used to construct a risk score. The risk score defines the probability of disease, given the data on multiple markers. This score, was grouped into two categories [>0.5 (malignant)/≤0.5 (benign)] and diagnostic accuracy measures were calculated.

   Results Top

All 38 samples included provided good quality of miRNA (A260/280, 1.7-2.11) except for one follicular variant of papillary carcinoma, which was excluded from analysis. Further, all samples tested for RNU-44 expression were clustered with Ct values of <2 cycles of each other.

Expression Pattern of miRNA Tested

The expression pattern of miR-187, miR-221, miR-222, and miR-224 was evaluated by the real-time method and the mean Ct values for the five normal thyroid samples was used as a baseline to deduce the expression of all other samples, after normalization with RNU-44. miR-221 and miR-222 were able to significantly (P < 0.001) discriminate the malignant samples (PTC, follicular variants of PTC, FTC, ADC, and PDC) from the non-malignant neoplasms (FA), both with a two-fold and a more stringent three-fold higher cut-off. Further, each marker was analyzed individually, for its sensitivity, specificity, and accuracy [Table 1], and miR-221 was found to provide higher accuracy (88%) than the other markers assessed. The AUC was also highest (0.86) for miR-221, indicating its diagnostic utility [Figure 1]. miR-222, interestingly matched the specificity provided by miR-221, though it had slightly lower sensitivity and accuracy. In fact, miR-222 appeared to accurately classify 6/7 follicular variant of PTC than, miR-221, and miR-187 (4/7 respectively). Interestingly, miR-187 expression was ~9 fold higher for the lone sample of ATC included for characterization. Further, one out of the nine FA samples included in the study showed a uniformly high expression (>3 fold) across all four markers characterized. miR-224 was the least discriminatory with much lower accuracy than all the other markers tested but was able to classify the PTCs accurately.
Figure 1: Receiver operator curve analysis of area under curve for four miRNA markers analyzed

Click here to view
Table 1: Diagnostic value of each individual miRNA marker in differentiating malignant tumors and benign samples

Click here to view

Combination of miRNA Markers

Since the primary objective of this study was to identify the least number of markers that could provide good accuracy, multiple logistic regression analysis was performed using the risk scores that were calculated. [Table 2] lists the combinations of markers that provided an accuracy of 90% or higher. Interestingly, a combination of all the four markers characterized showed the same levels of accuracy, sensitivity, specificity, and AUC as that of just two markers miR-221 and miR-222. Three marker combinations of miR-221, 222, 224 and miR-221, 222, 187 also provided similar results.
Table 2: Diagnostic value of a combination of markers* for differentiating malignant tumors and benign samples using logistic regression analyses

Click here to view

   Discussion Top

Ever since their initial discovery in C.elegans, miRNA have become one of the most characterized molecules. The fact that they are expressed in a tissue specific manner and that they are well preserved in formalin fixed paraffin embedded (FFPE) material has made it possible to analyze miRNA targets for molecular diagnosis or in the prognostication of various malignant tumors. [18],[19],[20],[21] miRNA expression based methods have also overcome some of the drawbacks associated with mRNA expression, including the fact that the latter method is less reliable using FFPE material and may require a large number of target genes to be analyzed to allow sufficient discrimination. [15],[22] It is now well established that miRNA expression profiles vary between tumor subtypes and that this differential expression could have diagnostic implications. [4],[22] A large body of literature now exists on the miRNA expression profile in various malignant tumors including among the heterogeneous group of thyroid tumors, [4],[14],[15] which is also a focus of this study.

Thirty eight FFPE thyroid tumors tissues (including 5 normal thyroid tissue) were characterized as part of this study. This was done to determine the feasibility of testing a limited number of miRNA markers to accurately differentiate the malignant samples from the non-malignant neoplasms, since a smaller number of markers would certainly lend the testing system for more routine analysis in resource limited settings. The four miRNA markers included in the analysis were chosen from the ten most upregulated miRNA markers among the various subtypes of thyroid tumors, as previously reported. [4] miR-187, miR-221, and miR-222 were included since they were up-regulated several folds among the PTCs, FTCs, PDCs and among the ATCs characterized in a earlier study, [4] while their expression was relatively low among the FA, except for a slightly higher expression of miR-221 among the oncocytic FAs. miR-224 was also included for analysis in this study since it is known to be a pan-PTC marker and PTCs are the predominant malignant thyroid tumors reported from our center.

All samples except one yielded good quality miRNA in the study. Similar results have been reported previously among studies that characterized malignant thyroid tumors using FFPE. [14],[15] This is particularly important in developing country setting since most laboratories may not have access to fresh tissues and/or facilities for storage of such tissues. The feasibility of performing miRNA expression based analysis on routinely archived samples therefore has important implications in such settings.

Each marker analyzed in the study was assessed individually for its sensitivity, specificity, accuracy, and the AUC was established after plotting the ROC. miR-221 provided maximum accuracy (88%) and the best AUC (0.86) among the markers when analyzed individually, though this was slightly lower compared to the accuracy provided by a single marker (95%) in another study, the only difference between the two studies being that the latter was done on fresh tissues and on fine needle aspirate (FNA) material. Further, miR-222 closely followed miR-221 in sensitivity, specificity, and accuracy indicating that the expression of these two markers is closely coordinated. [4],[14],[15] since they are probably encoded by a single polycistron being clustered on the same chromosome. [5] However, more interesting was the fact that miR-222 was able to classify the follicular variants of PTC much more accurately (86%) than miR-187 or miR-221 (57% in both markers). Chen et al, have suggested that since the expression of both miR-221 and 222 are nearly similar, it might be adequate to include one of the two in a diagnostic panel. [15] This may not be beneficial especially if miR-222 is able to identify the FVPTC more accurately as seen in our study. However, these results need to be validated on a larger number of samples of FVPTC before a conclusive argument can be made.

Most follicular adenomas included in the study were accurately distinguished from malignant tumors by at least two of the four markers i.e., miR-221 and 222. However, one case of follicular adenoma showed high expression (>3 fold) among all the four markers tested. Histopathological slides for the case were reviewed again by two pathologists not involved in the study, and there was concurrence that morphologically there were no features suggestive of malignancy. However, the patient was not available for further follow-up. Though this up-regulation of all the four markers in an otherwise phenotypically benign sample is difficult to explain, it may be prudent to have a more vigilant clinical follow-up of such cases.

The only ATC reported from our center for the period 2008-2009 and was included for analysis in this study. This sample showed a nine-fold increase in miR-187. Though this is a significant increase, a larger number of samples of ATC will have to be evaluated against this marker to deduce its precise diagnostic utility. Very few ATCs have been analyzed as part of other studies where miRNA have been investigated as diagnostic markers. [4],[14],[15] Nikiforova et al. reported up-regulation of miR-187 among the ATCs tested and also included it among the panel of miRNA markers to distinguish benign and malignant thyroid tumors. But Visone et al,[23] have extensively characterized miRNA profile among ATCs and have suggested yet another set of miRNA markers with a >3 fold down-regulation. While the inclusion of such select markers may lead to accurate detection, it may not be practical to include additional miRNA targets for routine screening of ATCs, especially since the number of ATCs reported tend to be small in most centers.

Finally, the most important objective of this study was to establish if a combination of markers analyzed in this study could provide adequate discrimination between the malignant tumor and the benign groups. Multiple logistic regression was performed and the risk score was calculated. It was interesting to note that a combination of miR-221 and 222 was able to provide the same level of accuracy (91%) as when coupled with either miR-187 or miR-224 or if all four markers were to be used. This then raises questions on the utility of miR-187 and or miR-224 in a diagnostic panel. While miR-187 may be useful in identifying cases of PTC (sometimes even with a five-fold increase) and may also prove useful with cases of ATC, its utility was especially limited in terms of discriminating FVPTCs and PDC. Similarly, miR-224 was useful only in identifying PTCs. Therefore, these markers may be of limited utility in diagnostic settings and may need to be replaced with other markers that may aid the testing system in achieving higher levels of accuracy.

This pilot study has some limitations especially in terms of assessing a relatively small number of samples pertaining to each subtype of thyroid tumor and also because these numbers may not be adequate to arrive at conclusions that could lead to change in practice. Nonetheless, these results will still be of value in developing country setting where it may not be feasible to use a large number of markers and will be especially useful for laboratories that are considering the incorporation of miRNA expression based differentiation of thyroid neoplasms among fine needle aspiration derived cytology specimens.

   References Top

1.Eszlinger M, Krohn K, Hauptmann S, Dralle H, Giordano TJ, Paschke R. Perspectives for improved and more accurate classification of thyroid epithelial tumors. J Clin Endocrinol Metab 2008;93:3286-94.  Back to cited text no. 1
2.Hundahl SA, Cady B, Cunningham MP, Mazzaferri E, McKee RF, Rosai J, et al. Initial results from a prospective cohort study of 5583 cases of thyroid carcinoma treated in the United States during 1996. U.S. and German Thyroid Cancer Study Group. An American College of Surgeons Commission on Cancer Patient Care Evaluation study. Cancer 2000;8:202-17.  Back to cited text no. 2
3.DeLellis RA, Lloyd RV, Heitz PU, Eng C. World Health Organization classification of tumours: pathology and genetics of tumours of endocrine organs. Lyon, France: IARC Press; 2004.  Back to cited text no. 3
4.Nikiforova MN, Tseng GC, Steward D, Diorio D, Nikiforov YE. MicroRNA expression profiling of thyroid tumors: biological significance and diagnostic utility. J Clin Endocrinol Metab 2008;93:1600-8.  Back to cited text no. 4
5.Pallante P, Visone R, Ferracin M, Ferraro A, Berlingieri MT, Troncone G, et al. MicroRNA deregulation in human thyroid papillary carcinomas. Endocr Relat Cancer 2006;13:497-508.  Back to cited text no. 5
6.Aherne ST, Smyth PC, Flavin RJ, Russell SM, Denning KM, Li JH, et al. Geographical mapping of a multifocal thyroid tumour using genetic alteration analysis & miRNA profiling. Mol Cancer 2008;7:89.  Back to cited text no. 6
7.Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer 2006;6:857-66.  Back to cited text no. 7
8.Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004;116:281-97.  Back to cited text no. 8
9.Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, et al. MicroRNA expression profiles classify human cancers. Nature 2005;435:834-8.  Back to cited text no. 9
10.Volinia S, Calin GA, Liu CG, Ambs S, Cimmino A, Petrocca F, et al. MicroRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A 2006;103:2257-61.  Back to cited text no. 10
11.He H, Jazdzewski K, Li W, Liyanarachchi S, Nagy R, Volinia S, et al. The role of microRNA genes in papillary thyroid carcinoma. Proc Natl Acad Sci U S A 2005;102:19075-80.  Back to cited text no. 11
12.Nikiforova MN, Chiosea SI, Nikiforov YE. MicroRNA expression profiles in thyroid tumors. Endocr Pathol 2009;20:85-91.  Back to cited text no. 12
13.Nikiforova MN, Nikiforov YE. Molecular genetics of thyroid cancer: implications for diagnosis, treatment and prognosis. Expert Rev Mol Diagn 2008;8:83-95.  Back to cited text no. 13
14.Tetzlaff MT, Liu A, Xu X, Master SR, Baldwin DA, Tobias JW, et al. Differential expression of miRNAs in papillary thyroid carcinoma compared to multinodular goiter using formalin fixed paraffin embedded tissues. Endocr Pathol 2007;18:163-73.  Back to cited text no. 14
15.Chen YT, Kitabayashi N, Zhou XH, Fahey TJ 3rd, Scognamiglio T. MicroRNA analysis as a potential diagnostic tool for papillary thyroid carcinoma. Mod Pathol 2008;21:1139-46.  Back to cited text no. 15
16.Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001;25:402-8.  Back to cited text no. 16
17.Bewick V, Cheek L, Ball J. Statistics review 14: Logistic regression. Critical Care 2005;9:112-8.  Back to cited text no. 17
18.Heneghan HM, Miller N, Kelly R, Newell J, Kerin MJ. Systemic miR-195 differentiates breast cancer from other malignancies and is a potential marker for detecting noninvasive and early disease. Oncologist 2010;15:673-82.  Back to cited text no. 18
19.Barshack I, Lithwick-Yanai G, Afek A, Rosenblatt K, Tabian-Keissar H, Zepeniuk M, et al. MicroRNA expression differentiates between primary lung tumors and metastases to the lung. Pathol Res Pract 2010;206:578-84.  Back to cited text no. 19
20.Du J, Schageman JJ, Irnov, Girard L, Hammond SM, Minna JD, et al. A MicroRNA expression distinguishes SCLC and NSCLC lung tumor cells and suggests a possible pathological relationship between SCLCs and NSCLCs. J Exp Clin Cancer Res 2010;29:75.  Back to cited text no. 20
21.Fridman E, Dotan Z, Barshack I, David BM, Dov A, Tabak S, et al. Accurate Molecular Classification of Renal Tumors Using MicroRNA Expression. J Mol Diagn 2010;12:687-96.  Back to cited text no. 21
22.Menon MP, Khan A. Micro-RNAs in thyroid neoplasms: molecular, diagnostic and therapeutic implications. J Clin Pathol 2009;62:978-85.  Back to cited text no. 22
23.Visone R, Pallante P, Vecchione A, Cirombella R, Ferracin M, Ferraro A, et al. Specific microRNAs are downregulated in human thyroid anaplastic carcinomas. Oncogene 2007;26:7590-5.  Back to cited text no. 23

Correspondence Address:
Rekha Pai
Molecular Pathology Laboratory, Department of Pathology, Christian Medical College, Vellore- 632 004
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0377-4929.97845

Rights and Permissions


  [Figure 1]

  [Table 1], [Table 2]

This article has been cited by
1 Biomarker Value of miR-221 and miR-222 as Potential Substrates in the Differential Diagnosis of Papillary Thyroid Cancer Based on Data Synthesis and Bioinformatics Approach
Shang Cai, Jiayan Ma, Yong Wang, Yuxing Cai, Liwei Xie, Xiangying Chen, Yingying Yang, Qiliang Peng
Frontiers in Endocrinology. 2022; 12
[Pubmed] | [DOI]
2 MicroRNA-224 inhibition prevents progression of cervical carcinoma by targeting PTX3
Li-Mei Yu,Wei-Wei Wang,Rong Qi,Tian-Gang Leng,Xiao-Lu Zhang
Journal of Cellular Biochemistry. 2018; 119(12): 10278
[Pubmed] | [DOI]
3 MiRNA-221/222 in thyroid cancer: A meta-analysis
Ling Liang,Xucai Zheng,Mingjun Hu,Yanjie Cui,Qi Zhong,Shengying Wang,Fen Huang
Clinica Chimica Acta. 2018; 484: 284
[Pubmed] | [DOI]
4 Expression and role of oncogenic miRNA-224 in esophageal squamous cell carcinoma
Xiaoyan He,Zhimei Zhang,Ming Li,Shuo Li,Lihua Ren,Hong Zhu,Bin Xiao,Ruihua Shi
BMC Cancer. 2015; 15(1)
[Pubmed] | [DOI]
5 Plasma miR-221/222 Family as Novel Descriptive and Prognostic Biomarkers for Glioma
Rui Zhang,Bo Pang,Tao Xin,Hua Guo,Yi Xing,Shangchen Xu,Bin Feng,Bin Liu,Qi Pang
Molecular Neurobiology. 2015;
[Pubmed] | [DOI]
6 Upregulation of microRNA-224 confers a poor prognosis in glioma patients
S. Lu,S. Wang,S. Geng,S. Ma,Z. Liang,B. Jiao
Clinical and Translational Oncology. 2013; 15(7): 569
[Pubmed] | [DOI]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Email Alert *
    Add to My List *
* Registration required (free)  

    Materials and Me...
    Article Figures
    Article Tables

 Article Access Statistics
    PDF Downloaded258    
    Comments [Add]    
    Cited by others 6    

Recommend this journal