Biomarker panel diagnosis of thyroid cancer: a critical review

Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics

Blood analysis is one of the foundations of clinical diagnostics. In recent years, the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. To demonstrate the method's full potential, we used an isotope-labeled synthetic peptide mix of 782 peptides, derived from 579 plasma proteins, spiked into blood plasma samples with a prm-PASEF measurement allowing the quantification of 565 plasma proteins by targeted proteomics. As a less time-consuming alternative to the prm-PASEF method, we describe guided data independent acquisition (dia)-PASEF (g-dia-PASEF) and compare its application to prm-PASEF for measuring blood plasma. To demonstrate both methods' performance in clinical samples, 20 patient plasma samples from a colorectal cancer (CRC) cohort were analyzed. The analysis identified 14 differentially regulated proteins between the CRC patient and control individual plasma samples. This shows the technique's potential for the rapid and unbiased screening of blood proteins, abolishing the need for the preselection of potential biomarker proteins.

Diagnostic and prognostic value of Stanniocalcin 1 expression in papillary thyroid cancer

PURPOSE

To evaluate the potential role of immunohistochemical changes in stanniocalcin 1 (STC1) and stanniocalcin 2 (STC2) expressions in papillary thyroid cancer (PTC) tissues in the disease's diagnosis and to investigate their relationship with classical clinicopathological prognostic factors.

METHODS

The study included 100 patients with PTC. Normal thyroid tissue adjacent to the tumor was taken as the control group. Clinicopathological prognostic features at the time of diagnosis of patients were recorded. STC1 and STC2 expressions of tumor tissue and adjacent normal tissue were determined immunohistochemically.

RESULTS

The sensitivity of STC1 in the diagnosis of PTC was 93%, the specificity was 94%, positive predictive value (PPV) 93.9%, and negative predictive value (NPV) 93.1%. It was determined that the STC1 staining score in tumor tissue was positively correlated with the disease TNM stage score (r = 0.259, p = 0.009) and the increase in STC1 staining score were independent risk factors that increased the risk of lymph node metastasis (R² = 0.398, p < 0.001). While 21% of the tumor tissues were stained with STC2, none of the normal thyroid tissues adjacent to the tumor tissue showed any staining with STC2. No correlation was found between STC2 immunohistochemical staining of tumor tissue and clinicopathological risk factors for the disease.

CONCLUSION

Increased STC1 expression in thyroid lesions may be helpful in diagnosing PTC. In addition, since increased STC1 expression in PTC tissues is associated with the risk of lymph node metastasis, it may be an efficient marker for predicting the prognosis of the disease.

Machine learning reveals salivary glycopatterns as potential biomarkers for the diagnosis and prognosis of papillary thyroid cancer

The diagnosis of thyroid cancer, especially papillary thyroid cancer (PTC), is increasing rapidly worldwide. In this study, we aimed to study the glycosylation of salivary proteins associated with PTC and assess the likelihood that salivary glycopatterns may be a potential biomarker of PTC diagnosis. Firstly, 22 benign thyroid nodule (BTN) samples, 27 PTC samples, and 30 healthy volunteers (HV) samples were collected to probe the difference of salivary glycopatterns associated with PTC using lectin microarrays. Then, five machine learning models including K-Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) were established to distinguish HV, BTN and PTC based on the changes of salivary glycopatterns. As a result, SVM had the best diagnostic effect with an accuracy rate of 92 % in testing set. Besides, lectin microarrays were used to explore the differences in salivary glycopatterns of 26 paired salivary samples of PTC patients before and after operation in order to probe into salivary glycopatterns as potential biomarkers for prognosis of PTC patients. The results showed that the levels of salivary glycopatterns recognized by 6 different lectins in patients after the operation almost convergenced with HVs. This study could help to screen and assess patients with PTC and their prognosis based on precise changes of salivary glycopatterns.

Identifying the Signatures and Rules of Circulating Extracellular MicroRNA for Distinguishing Cancer Subtypes

Cancer is one of the most threatening diseases to humans. It can invade multiple significant organs, including lung, liver, stomach, pancreas, and even brain. The identification of cancer biomarkers is one of the most significant components of cancer studies as the foundation of clinical cancer diagnosis and related drug development. During the large-scale screening for cancer prevention and early diagnosis, obtaining cancer-related tissues is impossible. Thus, the identification of cancer-associated circulating biomarkers from liquid biopsy targeting has been proposed and has become the most important direction for research on clinical cancer diagnosis. Here, we analyzed pan-cancer extracellular microRNA profiles by using multiple machine-learning models. The extracellular microRNA profiles on 11 cancer types and non-cancer were first analyzed by Boruta to extract important microRNAs. Selected microRNAs were then evaluated by the Max-Relevance and Min-Redundancy feature selection method, resulting in a feature list, which were fed into the incremental feature selection method to identify candidate circulating extracellular microRNA for cancer recognition and classification. A series of quantitative classification rules was also established for such cancer classification, thereby providing a solid research foundation for further biomarker exploration and functional analyses of tumorigenesis at the level of circulating extracellular microRNA.

Quantitative Analysis of Galectin-3 Expression in Benign and Malignant Thyroid Nodules

In this study, galectin-3 was analyzed as a potential marker for preoperative detection of malignant thyroid lesions. Galectin-3 expression was analyzed by quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) in preoperative thyroid fine-needle aspirates from 245 patients with thyroid nodules. Out of 245 samples, 238 were adequate for analysis by RT-PCR. Galectin-3 was positive in 34 (89.5%) of 38 papillary carcinomas, 3 (89.5%) of 4 follicular carcinomas, 17 (53.1%) of 32 follicular adenomas, 2 (33.3%) of 6 Hurthle cell adenoma, 11 (28.2%) of 39 Hashimoto thyroiditis, and 69 (57.9%) of 119 nodular goiter samples. Galectin-3 showed specificity of 49.5%, sensitivity of 88.1%, positive predictive value of 27.2%, and negative predictive value of 95.1% as a marker for detection of malignant thyroid nodules. Owing to the relatively low positive predictive value due to the relatively high false positive rate, the clinical value of galectin-3 analyzed by quantitative real-time RT-PCR as a marker for preoperative detection of malignant thyroid lesions is limited.

Galectin-3 and HBME-1 Expression on Agarose Cell Blocks from Fine-needle aspirates of Follicular Cell-derived Thyroid Tumors

Aim:

To test the expression of galectin-3 (gal-3) and Hector Battifora mesothelial antigen-1 (HBME-1) on agarose cell blocks (CBs) of fine-needle aspirates aiming to determine their diagnostic value in thyroid follicle cell-derived tumors.

Materials and Methods:

Forty patients with thyroid nodule were enrolled. Fine-needle aspiration biopsy was done and processed to produce smears and CBs. Immune staining was done on CBs using antibodies to gal-3 and HBME-1. Diagnostic value of tests was determined in comparison to pathology.

Results:

Current study included 17 papillary thyroid carcinoma (PTC), 15 follicular adenoma, and 8 follicular thyroid carcinoma (FTC). In PTC diagnosis, co-expression of gal-3/HBME-1 had a sensitivity of 94.1%, specificity of 73.3%, positive predictive value (PPV) of 80%, negative predictive value (NPV) 91.7%, and accuracy of 84.4%. In FTC diagnosis, combined gal-3/HBME-1 expression had a sensitivity of 75%, specificity of 78.6%, PPV of 50%, NPV of 91.7%, and accuracy of 77.8%. Co-expression of gal-3/HBME-1 raised the sensitivity of detection of differentiated thyroid carcinomas from 40% with cytomorphology to 92% and accuracy from 62.5% to 85%.

Conclusion:

The combined immunocytochemical expression of gal-3 and HBME-1 utilizing fine-needle aspirates can improve the sensitivity of detection and diagnostic accuracy of differentiated follicular cell-derived thyroid carcinomas.

Galectin-3: The Impact on the Clinical Management of Patients with Thyroid Nodules and Future Perspectives

Galectins (S-type lectins) are an evolutionarily-conserved family of lectin molecules, which can be expressed intracellularly and in the extracellular matrix, as well. Galectins bind β-galactose-containing glycoconjugates and are functionally active in converting glycan-related information into cell biological programs. Altered glycosylation notably occurring in cancer cells and expression of specific galectins provide, indeed, a fashionable mechanism of molecular interactions able to regulate several tumor relevant functions, among which are cell adhesion and migration, cell differentiation, gene transcription and RNA splicing, cell cycle and apoptosis. Furthermore, several galectin molecules also play a role in regulating the immune response. These functions are strongly dependent on the cell context, in which specific galectins and related glyco-ligands are expressed. Thyroid cancer likely represents the paradigmatic tumor model in which experimental studies on galectins' glycobiology, in particular on galectin-3 expression and function, contributed greatly to the improvement of cancer diagnosis. The discovery of a restricted expression of galectin-3 in well-differentiated thyroid carcinomas (WDTC), compared to normal and benign thyroid conditions, contributed also to promoting preclinical studies aimed at exploring new strategies for imaging thyroid cancer in vivo based on galectin-3 immuno-targeting. Results derived from these recent experimental studies promise a further improvement of both thyroid cancer diagnosis and therapy in the near future. In this review, the biological role of galectin-3 expression in thyroid cancer, the validation and translation to a clinical setting of a galectin-3 test method for the preoperative characterization of thyroid nodules and a galectin-3-based immuno-positron emission tomography (immuno-PET) imaging of thyroid cancer in vivo are presented and discussed.

ProNGF is a potential diagnostic biomarker for thyroid cancer

The precursor for nerve growth factor (proNGF) is expressed in some cancers but its clinicopathological significance is unclear. The present study aimed to define the clinicopathological significance of proNGF in thyroid cancer. ProNGF expression was analysed by immunohistochemistry in two cohorts of cancer versus benign tumors (adenoma) and normal thyroid tissues. In the first cohort (40 thyroid cancers, 40 thyroid adenomas and 80 normal thyroid tissues), proNGF was found overexpressed in cancers compared to adenomas and normal samples (p<0.0001). The area under the receiver-operating characteristic (ROC) curve was 0.84 (95% CI 0.75-0.93, p<0.0001) for cancers versus adenomas, and 0.99 (95% CI 0.98-1.00, p<0.0001) for cancers versus normal tissues. ProNGF overexpression was confirmed in a second cohort (127 cancers of various histological types and 55 normal thyroid tissues) and using a different antibody (p<0.0001). ProNGF staining intensity was highest in papillary carcinomas compared to other histological types (p<0.0001) and there was no significant association with age, gender, tumor size, stage and lymph node status. In conclusion, proNGF is increased in thyroid cancer and should be considered as a new potential diagnostic biomarker.

Molecular profiles of thyroid cancer subtypes: Classification based on features of tissue revealed by mass spectrometry imaging

Determination of the specific type of thyroid cancer is crucial for the prognosis and selection of treatment of this malignancy. However, in some cases appropriate classification is not possible based on histopathological features only, and it might be supported by molecular biomarkers. Here we aimed to characterize molecular profiles of different thyroid malignancies using mass spectrometry imaging (MSI) which enables the direct annotation of molecular features with morphological pictures of an analyzed tissue. Fifteen formalin-fixed paraffin-embedded tissue specimens corresponding to five major types of thyroid cancer were analyzed by MALDI-MSI after in-situ trypsin digestion, and the possibility of classification based on the results of unsupervised segmentation of MALDI images was tested. Novel method of semi-supervised detection of the cancer region of interest (ROI) was implemented. We found strong separation of medullary cancer from malignancies derived from thyroid epithelium, and separation of anaplastic cancer from differentiated cancers. Reliable classification of medullary and anaplastic cancers using an approach based on automated detection of cancer ROI was validated with independent samples. Moreover, extraction of spectra from tumor areas allowed the detection of molecular components that differentiated follicular cancer and two variants of papillary cancer (classical and follicular). We concluded that MALDI-MSI approach is a promising strategy in the search for biomarkers supporting classification of thyroid malignant tumors. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Galectin-3 and HBME-1 improve the accuracy of core biopsy in indeterminate thyroid nodules

Core needle biopsy (CNB) has been recently described as an accurate second-line test in thyroid inconclusive cytology (FNA). Here we retrospectively investigated the potential improvement given by Galectin-3, Cytokeratin-19, and HBME-1 on the accuracy of CNB in thyroid nodules with prior indeterminate FNA report. The study included 74 nodules. At CNB diagnosis, 15 were cancers, 40 were benign, and 19 had uncertain/non-diagnostic CNB report. The above immunohistochemical (IHC) panel was analyzed in all cases. After surgery, 19 malignant and 55 benign lesions were found. All 15 cancers and all 40 benign nodules diagnosed at CNB were confirmed at final histology. Regarding the uncertain CNB group, 4 (21 %) were malignant and 15 (79 %) benign. When we considered all the series, the most accurate IHC combination was Galectin-3 plus HBME-1, while HBME-1 was the most sensitive marker in those nodules with uncertain CNB report. The combination of CNB plus IHC could indentify 19/19 cancers and 53/55 benign lesions. Sensitivity and specificity of CNB increased from 79 to 100 % and from 73 to 96 %, respectively, by adding IHC. CNB can diagnose the majority of thyroid nodules with previous indeterminate FNA cytology, while the accuracy of CNB is increased by adding Galectin-3, Cytokeratin-19, and HBME-1 panel. We suggest to adopt CNB as a second-line approach to indeterminate thyroid FNA, and apply IHC in those lesions with uncertain/non-diagnostic CNB report. This approach should improve the pre-surgical diagnosis of patients. These results should be confirmed in larger prospective series.

Unveiling a novel biomarker panel for diagnosis and classification of well-differentiated thyroid carcinomas

Thyroid cancer is the most common human endocrine malignancy with increasing global incidence. Papillary thyroid carcinomas (PTC) and follicular thyroid carcinomas (FTC) are well-differentiated thyroid cancers (WDTC) accounting for 95% of all thyroid cancer cases, with survival rates of almost 100% when diagnosed early. Since PTC and FTC have different modes of metastasis, they require different treatment strategies. Standard diagnosis by fine needle aspiration with cytopathological examination can be inaccurate in approximately 10-30% of all cases and difficult to definitively classify as WDTC. Currently, there is no single or panel of biomarkers available for thyroid cancer diagnosis and classification. This study identified novel biomarkers for thyroid cancer diagnosis and classification using proteomics, which may be translated into a biomarker panel for clinical application. Two-dimensional SDS-PAGE and mass spectrometry were used to identify potential biomarkers in papillary and follicular thyroid carcinoma cell lines, and the biomarkers were validated in five PTC and five FTC tissues, with their adjacent normal tissues from Thai patients. Eight biomarkers could distinguish PTC from normal tissues, namely enolase 1, triose phosphate isomerase, cathepsin D, annexin A2, cofilin 1, proliferating cell nuclear antigen (PCNA), copine 1 and heat shock protein 27 kDa (HSP27). These biomarkers can also discriminate FTC from normal tissues, except for annexin A2. On the contrary, annexin A2, cofilin 1, PCNA and HSP27 can be used to classify the types of WDTC. These findings have potential for use as a novel multi-marker panel for more accurate diagnosis and classification to better guide physicians on thyroid cancer treatment. Moreover, our results suggest the involvement of proteins in cell growth and proliferation, and the p53 pathway in the carcinogenesis of WDTC, which may lead to targeted therapy for thyroid cancer.

Application of metabolomics in thyroid cancer research

Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput "omics" techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

Immunohistochemical Diagnosis of Thyroid Tumors

Recent insight into the molecular mechanisms of thyroid carcinogenesis has led to studies involving newly directed antibodies. With the introduction of new molecular targeted therapies, these antibodies may represent useful predictors of therapeutic response in tumors unresponsive to radioiodine or insensitive to conventional antitumor therapies. These markers complement the development of markers that are able to discern benign from malignant entities, including hyalinizing trabecular tumors, oncocytic neoplasms, and follicular variant of papillary thyroid carcinoma. The use of antibodies directed to proteins generated by mutated genes may represent a cost-effective method for diagnosing and managing patients affected by thyroid tumors.

Thyroid cytology

This article covers, in a comprehensive way, thyroid cytopathology. The Bethesda System for Reporting Thyroid Cytology is reviewed, with emphasis on the atypical and indeterminate diagnostic categories. Immunohistochemistry stains and molecular tests panels applicable to cytology specimens are described.

Preoperative diagnosis of thyroid nodules using the Bethesda System for Reporting Thyroid Cytopathology: a comprehensive review and meta-analysis

Fine-needle aspiration biopsy (FNAB) is the test of choice for the evaluation of nodules, arriving at a cancer diagnosis, and guiding surgical management. This review and meta-analysis aims to objectively evaluate the Bethesda System for Reporting Thyroid Cytopathology (BSRTC) based upon literature reports of histopathological outcomes following cytopathological diagnoses. Thirteen studies were reviewed and the risk of malignancy (ROM) for each of the BSRTC diagnostic categories were calculated as: Non-diagnostic 11-26%, Benign 4-9%, AUS/FLUS 19-38%, FN/SFN 27-40%, SFM 50-79%, and Malignant 98-100%. In typical clinical utilization, the sensitivity and specificity of thyroid FNAB diagnosis using the BSRTC were 96% and 46%, respectively. The BSRTC represents an important advance in standardizing thyroid FNAB cytopathological reporting. Close attention should be paid to the observation that the AUS-FLUS and FN-SFN DCs have overlapping ROMs, and the potential clinical implications of this finding on patient management.

Molecular diagnosis for indeterminate thyroid nodules on fine needle aspiration: advances and limitations

Indeterminate thyroid lesions are diagnosed in up to 30% of fine needle aspirations. These nodules harbor malignancy in more than 25% of cases, and hemithyroidectomy or total thyroidectomy has therefore been advocated in order to achieve definitive diagnosis. Recently, many molecular markers have been investigated in an attempt to increase diagnostic accuracy of indeterminate fine needle aspiration cytology and thereby avoid unnecessary complications and costs associated with thyroid surgery. Somatic mutation testing, mRNA gene expression platforms, protein immunocytochemistry and miRNA panels have improved the diagnostic accuracy of indeterminate thyroid nodules, and although no test is perfectly accurate, in the authors' opinion, these methods will most certainly become an important part of the diagnostic tools for clinicians and cytopathologists in the future.

Whole-transcriptome profiling of thyroid nodules identifies expression-based signatures for accurate thyroid cancer diagnosis

PURPOSE

Due to the limitations of fine-needle aspiration biopsy (FNAB) cytopathology, many individuals who present with thyroid nodules eventually undergo thyroid surgery to diagnose thyroid cancer. The objective of this study was to use whole-transcriptome profiling to develop and validate a genomic classifier that significantly improves the accuracy of preoperative thyroid cancer diagnosis.

MATERIALS AND METHODS

Nucleic acids were extracted and amplified for microarray expression analysis on the Affymetrix Human Exon 1.0 ST GeneChips from 1-mm-diameter formalin-fixed and paraffin-embedded thyroid tumor tissue cores. A training group of 60 thyroidectomy specimens (30 cancers and 30 benign lesions) were used to assess differential expression and for subsequent generation of a genomic classifier. The classifier was validated in a blinded fashion on a group of 31 formalin-fixed and paraffin-embedded thyroid FNAB specimens.

RESULTS

Expression profiles of the 57 thyroidectomy training and 31 FNAB validation specimens that passed a series of quality control steps were analyzed. A genomic classifier composed of 249 markers that corresponded to 154 genes, had an overall validated accuracy of 90.0% in the 31 patient FNAB specimens and had positive and negative predictive values of 100% and 85.7%, respectively. The majority of the identified markers that made up the classifier represented non-protein-encoding RNAs.

CONCLUSIONS

Whole-transcriptome profiling of thyroid nodule surgical specimens allowed for the development of a genomic classifier that improved the accuracy of preoperative thyroid cancer FNAB diagnosis.

Diagnostic use of molecular markers in the evaluation of thyroid nodules

OBJECTIVE

To describe the molecular markers thus far evaluated for use in the care of patients with clinically relevant thyroid nodules.

METHODS

We review the currently available molecular tests that have been applied to patients with thyroid nodules.

RESULTS

In the United States, approximately 450 000 diagnostic fine-needle aspirates will be performed on patients with thyroid nodules this year in an effort to identify thyroid cancer. Unfortunately, this test is imprecise and, at times, inaccurate. Because of this, novel diagnostic testing modalities have been pursued, the most promising of which involve molecular analysis of thyroid tissue. Immunohistochemical staining, analysis for mutations and gene rearrangements, and microarray analysis have all been investigated with regard to their performance characteristics in targeted patient populations.

CONCLUSIONS

Molecular tests to evaluate thyroid nodules demonstrate variable performance characteristics. Further evaluation of available and emerging molecular tests will necessarily rely on prospective real-world test validation in the clinical setting.

The quest for diagnostic molecular markers for thyroid nodules with indeterminate or suspicious cytology

Thyroid nodules are very common and fine needle aspiration (FNA) is a very sensitive means of diagnosis. However, its limitations include the fact that the cytology reports are often indeterminate or suspicious only. The quest for adjunctive measures to improve its specificity has been ongoing for decades, but significant results have remained elusive. The potential use of diagnostic molecular markers appears to be the most promising area of research at this time.

The new molecular markers DDIT3, STT3A, ARG2 and FAM129A are not useful in diagnosing thyroid follicular tumors

Preoperative characterization of thyroid follicular lesions is challenging. Fine-needle aspiration specimens cannot differentiate follicular carcinomas from benign follicular neoplasias. Recently, promising markers have been detected using modern molecular techniques. We conducted a retrospective study to confirm the usefulness of immunohistochemical staining for the protein markers, DDIT3, STT3A (ITM1), ARG2 and FAM129A (C1orf24) in separating benign and malignant thyroid follicular lesions. Formalin-fixed, paraffin-embedded thyroid tissue from 30 in-house cases (15 follicular carcinomas and 15 follicular adenomas), as well as 8 follicular carcinomas and 21 follicular adenomas on tissue microarray slides were stained immunohistochemically for DDIT3, STT3A, ARG2 and FAM129A expression. Control tissue consisted of thyroid parenchyma adjacent to the tumors and 11 separate cases of normal thyroid parenchyma. All in-house cases of follicular adenomas, follicular carcinomas and adjacent normal thyroid tissue showed positive immunostaining with anti-DDIT3 and anti-STT3A. Anti-ARG2 and anti-FAM129A polyclonal antibodies showed positive staining in 20 and 60% of in-house follicular adenomas, and 40 and 87% of in-house follicular carcinomas, respectively. Monoclonal anti-FAM129A demonstrated positive staining in 13 and 33% of in-house follicular adenomas and follicular carcinomas, respectively. Polyclonal anti-DDIT3, -STT3A and -FAM129A antibodies showed positive staining in all tissue microarray slides of follicular carcinoma and in 76, 85 and 81% of the follicular adenomas, respectively. Monoclonal anti-STT3A stained 81% of the follicular adenoma cores. Anti-ARG2 stained positive in 13% of follicular carcinomas and 10% of follicular adenomas on the tissue microarray slides. In conclusion, DDIT3, STT3A, ARG2 and FAM129A immunohistochemistry does not appear to be useful in the diagnosis of thyroid follicular neoplasias, as they do not reliably distinguish follicular thyroid carcinoma from follicular thyroid adenoma.

Follicular thyroid neoplasms can be classified as low- and high-risk according to HBME-1 and Galectin-3 expression on liquid-based fine-needle cytology

DESIGN

Fine-needle aspiration biopsy (FNAB) is the most reliable diagnostic tool in the diagnosis of thyroid nodules. A cytologic diagnosis of follicular neoplasm with atypical cells of undetermined significance (FN/AUS) implies that the selection of patients between surgery and follow-up is difficult. In this setting immunocytochemical stainings might be helpful. The efficacy of a panel made up of HBME-1 and Galectin-3 antibodies is evaluated in cases processed by liquid-based cytology (LBC).

METHODS

Out of 7091 thyroid FNAB processed by LBC method, 120 cases undergoing surgery successively were selected. These cases were classified as benign lesion (BL, eight cases), FN, including the ACUS category of the Bethesda classification (FN/AUS, 50 cases), suspicious for malignancy (SM, 59 cases), and malignant neoplasm (MN, three cases). Immunostains for HBME-1 and Galectin-3 were carried out on the LBC slides.

RESULTS

All MN and BL were histologically confirmed. FN/AUS and SM showed a malignancy risk of 24 and 72.9% respectively. The complete immunocytochemical panel was positive in 83.3% of the cases resulting in malignancy and negative in 87.5% of cases resulting in benign histology. Among the FN/AUS, the complete positive immunocytochemical panel was detected in 76.9% of cases resulting as malignant and the complete negative immunocytochemical panel was observed in 96.8% of cases resulting as benign at histology.

CONCLUSIONS

The expression of HBME-1 and Galectin-3 in cases classified as FN/AUS on LBC-processed FNABs can effectively distinguish lesions, which need immediate surgery (high risk or FNH or Thy 3h) from those which can be followed-up (low risk or FNL or Thy 3l).

Conditioned media from cell lines: a complementary model to clinical specimens for the discovery of disease-specific biomarkers

In the strictest sense, the cell secretome (conditioned media) refers to the collection of proteins that contain a signal peptide and are processed via the endoplasmic reticulum and Golgi apparatus through the classical secretion pathway. More generally, the secretome also encompasses proteins shed from the cell surface and intracellular proteins released through non-classical secretion pathway or exosomes. These secreted proteins include numerous enzymes, growth factors, cytokines and hormones or other soluble mediators. They are fundamental in the processes of cell growth, differentiation, invasion and angiogenesis by regulating cell-to-cell and cell-to-extracellular matrix interactions. The main aim of this review is to provide a synopsis of findings from the analysis of the secretome taking diabetes, cancer and neurodegenerative diseases as examples. We will also discuss the preparation of conditioned media and on the main proteomic-based methodological approaches that have been developed for the study of secreted/shed proteins.

The Immunocytochemistry Is a Valuable Tool in the Diagnosis of Papillary Thyroid Cancer in FNA's Using Liquid-Based Cytology

Introduction. Papillary thyroid carcinoma (PTC) is the most common malignancy of the thyroid. An accurate cytological diagnosis is based on distinctive cytological features in combination with immunocytochemistry. Methods. A number of 83 fine needle aspirations, positive for papillary thyroid cancer (44 from thyroid nodules and 39 from cervical lymph nodes), were studied using Thin Layer Cytology. A panel of the immunomarkers Cytokeratin-19, Galectin-3, HBME1, CD-44, CD-56, and E-Cadherin was performed. Results. Positive expression of CK-19 was observed in 77 cases (92.7%), of Galectin-3 in 74 cases (89.1%), of HBME1 in 65 (78.3%), and of CD-44 in 72 cases (86.7%). Loss of expression of CD-56 was observed in 80 cases (96.4%) and of E-cadherin in 78 (93.9%). Conclusions. Our data suggest that Thin Layer Cytology increases the diagnostic accuracy in papillary carcinoma and seems to be a promising technique for further investigation of thyroid lesions permitting the possibility to use archive material. Positive immunoexpression of CK-19, Galectin-3, HBME-1, and CD-44 improves the diagnostic accuracy of papillary thyroid cancer. Furthermore, loss of E-cadherin and of CD-56 expression is a feature of malignancy.

Galectins as cancer biomarkers

Galectins are a group of proteins that bind β-galactosides through evolutionarily conserved sequence elements of the carbohydrate recognition domain (CRD). Proteins similar to galectins can be found in very primitive animals such as sponges. Each galectin has an individual carbohydrate binding preference and can be found in cytoplasm as well as in the nucleus. They also can be secreted through non-classical pathways and function extracellularly. Experimental and clinical data demonstrate a correlation between galectin expression and tumor progression and metastasis, and therefore, galectins have the potential to serve as reliable tumor markers. In this review, we describe the expression and role of galectins in different cancers and their clinical applications for diagnostic use.

Diagnostic utility of galectin-3 in thyroid cancer

Galectin-3 (Gal-3), which has received significant recent attention for its utility as a diagnostic marker for thyroid cancer, represents the most well-studied molecular candidate for thyroid cancer diagnosis. Gal-3 is a protein that binds to beta-galactosidase residues on cell surface glycoproteins and has also been identified in the cytoplasmic and nuclear compartment. This marker has been implicated in regulation of normal cellular proliferation and apoptosis, as well as malignant transformation and the metastasis of cancer cells. We here present a mechanistic review of Gal-3 and its role in cancer development and progression. Gal-3 expression studies in thyroid tissue and cytologic tumor specimens and their methodological considerations are also discussed in this article. Despite great variance in their methodology, the majority of immunohistochemical studies found that Gal-3 was differentially expressed in thyroid carcinoma compared with benign and normal thyroid specimens, suggesting that Gal-3 is a good diagnostic marker for thyroid cancer. Recent studies have also demonstrated improved methodological reliability. On the other hand, Gal-3 genomic expression studies have shown inconsistent results for diagnostic utility and are not recommended. Overall, the development of Gal-3 as a diagnostic marker for thyroid cancer represents a promising avenue for future study, and its clinical application could significantly reduce the number of diagnostic thyroid operations performed for cases of indeterminant fine needle aspiration biopsy cytology, and thus positively impact the current management of thyroid nodular disease.

Glioma pathophysiology: insights emerging from proteomics

Proteomics is increasingly employed in both neurological and oncological research to provide insight into the molecular basis of disease but rarely has a coherent, novel pathophysiological insight emerged. Gliomas account for >50% of adult primary intracranial tumors, with malignant gliomas (anaplastic astrocytomas and glioblastoma multiforme) being the most common. In glioma, the application of proteomic technology has identified altered protein expression but without consistency of these alterations or their biological significance being established. A systematic review of multiple independent proteomic analyses of glioma has demonstrated alterations of 99 different proteins. Importantly 10 of the 99 proteins found differentially expressed in glioma [PHB, Hsp20, serum albumin, epidermal growth factor receptor (EGFR), EA-15, RhoGDI, APOA1, GFAP, HSP70, PDIA3] were identified in multiple publications. An assessment of protein-protein interactions between these proteins compiled using novel web-based technology, revealed a robust and cohesive network for glioblastoma. The protein network discovered (containing TP53 and RB1 at its core) compliments recent findings in genomic studies of malignant glioma. The novel perspective provided by network analysis indicates that the potential of this technology to explore crucial aspects of glioma pathophysiology can now be realized but only if the conceptual and technical limitations highlighted in this review are addressed.