Peptidomics Unveils Distinct Acetylation Patterns of Histone and Annexin A1 in Differentiated Thyroid Cancer

Thyroid cancer is a common malignancy of the endocrine system. Nodules are routinely evaluated for malignancy risk by fine needle aspiration biopsy (FNAB), and in cases such as follicular lesions, differential diagnosis between benign and malignant nodules is highly uncertain. Therefore, the discovery of new biomarkers for this disease could be helpful in improving diagnostic accuracy. Thyroid nodule biopsies were subjected to a precipitation step with both the insoluble and supernatant fractions subjected to proteome and peptidome profiling. Proteomic analysis identified annexin A1 as a potential biomarker of thyroid cancer malignancy, with its levels increased in malignant samples. Also upregulated were the acetylated peptides of annexin A1, revealed by the peptidome analysis of the supernatant fraction. In addition, supernatant peptidomic analysis revealed a number of acetylated histone peptides that were significantly elevated in the malignant group, suggesting higher gene transcription activity in malignant tissue. Two of these peptides were found to be robust malignancy predictors, with an area under the receiver operating a characteristic curve (ROC AUC) above 0.95. Thus, this combination of proteomics and peptidomics analyses improved the detection of malignant lesions and also provided new evidence linking thyroid cancer development to heightened transcription activity. This study demonstrates the importance of peptidomic profiling in complementing traditional proteomics approaches.

Proteomics Reveals mRNA Regulation and the Action of Annexins in Thyroid Cancer

Differentiated thyroid cancer is the most common malignancy of the endocrine system. Although most thyroid nodules are benign, given the high incidence of thyroid nodules in the population, it is important to understand the differences between benign and malignant thyroid cancer and the molecular alterations associated with malignancy to improve detection and signal potential diagnostic, prognostic, and therapeutic targets. Proteomics analysis of benign and malignant human thyroid tissue largely revealed changes indicating modifications in RNA regulation, a common cancer characteristic. In addition, changes in the immune system and cell membrane/endocytic processes were also suggested to be involved. Annexin A1 was considered a potential malignancy biomarker and, similarly to other annexins, it was found to increase in the malignant group. Furthermore, a bioinformatics approach points to the transcription factor Sp1 as being potentially involved in most of the alterations seen in the malignant thyroid nodules.

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

INTRODUCTION

Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions.

AREAS COVERED

This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions.

EXPERT COMMENTARY

Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

The Complex Cyto-Molecular Landscape of Thyroid Nodules in Pediatrics

Thyroid fine-needle aspiration (FNA) is a commonly used diagnostic cytological procedure in pediatric patients for the evaluation of thyroid nodules, triaging them for the detection of thyroid cancer. In recent years, greater attention has been paid to thyroid FNA in this setting, including the use of updated ultrasound score algorithms to improve accuracy and yield, especially considering the theoretically higher risk of malignancy of these lesions compared with the adult population, as well as to minimize patient discomfort. Moreover, molecular genetic testing for thyroid disease is an expanding field of research that could aid in distinguishing benign from cancerous nodules and assist in determining their clinical management. Finally, artificial intelligence tools can help in this task by performing a comprehensive analysis of all the obtained data. These advancements have led to greater reliance on FNA as a first-line diagnostic tool for pediatric thyroid disease. This review article provides an overview of these recent developments and their impact on the diagnosis and management of thyroid nodules in children.

Alteration of Serum Proteome in Levo-Thyroxine-Euthyroid Thyroidectomized Patients

The monotherapy with levo-thyroxine (LT4) is the treatment of choice for patients with hypothyroidism after thyroidectomy. However, many athyreotic LT4-treated patients with thyroid hormones in the physiological range experience hypothyroid-like symptoms, showing post-operative, statistically significant lower FT3 levels with respect to that before total thyroidectomy. Since we hypothesized that the lower plasmatic FT3 levels observed in this subgroup could be associated with tissue hypothyroidism, here we compared, by a preliminary proteomic analysis, eight sera of patients with reduced post-surgical FT3 to eight sera from patients with FT3 levels similar to pre-surgery levels, and six healthy controls. Proteomic analysis highlights a different serum protein profile among the considered conditions. By enrichment analysis, differential proteins are involved in coagulation processes (PLMN-1.61, -1.98 in reduced vs. stable FT3, p < 0.02; A1AT fragmentation), complement system activation (CFAH + 1.83, CFAB + 1.5, C1Qb + 1.6, C1S + 7.79 in reduced vs. stable FT3, p < 0.01) and in lipoprotein particles remodeling (APOAI fragmentation; APOAIV + 2.13, p < 0.003), potentially leading to a pro-inflammatory response. This study suggests that LT4 replacement therapy might restore biochemical euthyroid conditions in thyroidectomized patients, but in some cases without re-establishing body tissue euthyroidism. Since our results, this condition is reflected by the serum protein profile.

A Novel Nanoproteomic Approach for the Identification of Molecular Targets Associated with Thyroid Tumors

A thyroid nodule is the most common presentation of thyroid cancer; thus, it is extremely important to differentiate benign from malignant nodules. Within malignant lesions, classification of a thyroid tumor is the primary step in the assessment of the prognosis and selection of treatment. Currently, fine-needle aspiration biopsy (FNAB) is the preoperative test most commonly used for the initial thyroid nodule diagnosis. However, due to some limitations of FNAB, different high-throughput “omics” approaches have emerged that could further support diagnosis based on histopathological patterns. In the present work, formalin-fixed paraffin-embedded (FFPE) tissue specimens from normal (non-neoplastic) thyroid (normal controls (NCs)), benign tumors (follicular thyroid adenomas (FTAs)), and some common types of well-differentiated thyroid carcinoma (follicular thyroid carcinomas (FTCs), conventional or classical papillary thyroid carcinomas (CV-PTCs), and the follicular variant of papillary thyroid carcinomas (FV-PTCs)) were analyzed. For the first time, FFPE thyroid samples were deparaffinized using an easy, fast, and non-toxic method. Protein extracts from thyroid tissue samples were analyzed using a nanoparticle-assisted proteomics approach combined with shotgun LC-MS/MS. The differentially regulated proteins found to be specific for the FTA, FTC, CV-PTC, and FV-PTC subtypes were analyzed with the bioinformatic tools STRING and PANTHER showing a profile of proteins implicated in the thyroid cancer metabolic reprogramming, cancer progression, and metastasis. These proteins represent a new source of potential molecular targets related to thyroid tumors.

Classification of Thyroid Tumors Based on Mass Spectrometry Imaging of Tissue Microarrays; a Single-Pixel Approach

The primary diagnosis of thyroid tumors based on histopathological patterns can be ambiguous in some cases, so proper classification of thyroid diseases might be improved if molecular biomarkers support cytological and histological assessment. In this work, tissue microarrays representative for major types of thyroid malignancies—papillary thyroid cancer (classical and follicular variant), follicular thyroid cancer, anaplastic thyroid cancer, and medullary thyroid cancer—and benign thyroid follicular adenoma and normal thyroid were analyzed by mass spectrometry imaging (MSI), and then different computation approaches were implemented to test the suitability of the registered profiles of tryptic peptides for tumor classification. Molecular similarity among all seven types of thyroid specimens was estimated, and multicomponent classifiers were built for sample classification using individual MSI spectra that corresponded to small clusters of cells. Moreover, MSI components showing the most significant differences in abundance between the compared types of tissues detected and their putative identity were established by annotation with fragments of proteins identified by liquid chromatography-tandem mass spectrometry in corresponding tissue lysates. In general, high accuracy of sample classification was associated with low inter-tissue similarity index and a high number of components with significant differences in abundance between the tissues. Particularly, high molecular similarity was noted between three types of tumors with follicular morphology (adenoma, follicular cancer, and follicular variant of papillary cancer), whose differentiation represented the major classification problem in our dataset. However, low level of the intra-tissue heterogeneity increased the accuracy of classification despite high inter-tissue similarity (which was exemplified by normal thyroid and benign adenoma). We compared classifiers based on all detected MSI components (n = 1536) and the subset of the most abundant components (n = 147). Despite relatively higher contribution of components with significantly different abundance and lower overall inter-tissue similarity in the latter case, the precision of classification was generally higher using all MSI components. Moreover, the classification model based on individual spectra (a single-pixel approach) outperformed the model based on mean spectra of tissue cores. Our result confirmed the high feasibility of MSI-based approaches to multi-class detection of cancer types and proved the good performance of sample classification based on individual spectra (molecular image pixels) that overcame problems related to small amounts of heterogeneous material, which limit the applicability of classical proteomics.

Diagnosis of papillary thyroid carcinoma by 1H NMR spectroscopy-based metabolomic analysis of whole blood

The incidence rate of thyroid carcinoma, especially papillary thyroid carcinoma (PTC), has increased significantly over time. As a primary pathway for metastasis, the lymphatic system is an important prognostic factor for PTC patients. Although the metabolic changes in PTC patients have been investigated in extensive studies, few studies focused on the whole blood metabolic profiling of PTC patients. In this study, we investigated the ¹H NMR-based metabolic profiles of whole blood samples that were obtained from healthy individuals and PTC patients, with or without lymph node metastasis. The estimation of the predictive potential of metabolites was evaluated using multivariate statistical analyses, which revealed that the whole blood carries information that is sufficient for distinguishing between PTC patients and healthy individuals. However, PTC patients were not well classified as positive or negative according to the lymph nodes. We did not find a metabolite that could discriminate the presence of lymph node metastasis. Further studies with larger sample sizes are needed to elucidate significant metabolites to indicate the presence of lymph node metastasis in patients with PTC.

Molecular trait of follicular-patterned thyroid neoplasms defined by MALDI-imaging

In the field of thyroid neoplasms, the most interesting recent change regards the introduction of a new terminology for follicular-patterned thyroid tumors, named Noninvasive Thyroid Neoplasm with Papillary-like Nuclear Features (NIFTP). This pre-malignant tumor is considered to be the putative precursor of invasive carcinoma. However, given that several issues are still unresolved, the application of ancillary tools, based on omics-techniques, may improve the clinical management of these challenging cases. The present paper highlights the proteomic profiles of a series of NIFTPs submitted to Fine Needle Aspirations (FNAs) and analysed by MALDI-imaging in order to confirm the heterogeneous phenotype of nodules included in the present NIFTP terminology and to underline the necessity of more accurate biomarkers that can be used for their characterization. Ethical and economic implications in terms of healthcare costs, operative risks, morbidity, as well as the potential need for lifelong hormone replacement therapy, seem to be significant reasons to approach the characterization of NIFTPs using alternative tools such as MALDI-MSI.

The Potential of Metabolomics in the Diagnosis of Thyroid Cancer

Thyroid cancer is the most common endocrine system malignancy. However, there is still a lack of reliable and specific markers for the detection and staging of this disease. Fine needle aspiration biopsy is the current gold standard for diagnosis of thyroid cancer, but drawbacks to this technique include indeterminate results or an inability to discriminate different carcinomas, thereby requiring additional surgical procedures to obtain a final diagnosis. It is, therefore, necessary to seek more reliable markers to complement and improve current methods. "Omics" approaches have gained much attention in the last decade in the field of biomarker discovery for diagnostic and prognostic characterisation of various pathophysiological conditions. Metabolomics, in particular, has the potential to identify molecular markers of thyroid cancer and identify novel metabolic profiles of the disease, which can, in turn, help in the classification of pathological conditions and lead to a more personalised therapy, assisting in the diagnosis and in the prediction of cancer behaviour. This review considers the current results in thyroid cancer biomarker research with a focus on metabolomics.

Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome

Recent advances in high-throughput molecular and multi-omics technologies have improved our understanding of the molecular changes associated with thyroid cancer initiation and progression. The translation into clinical use based on molecular profiling of thyroid tumors has allowed a significant improvement in patient risk stratification and in the identification of targeted therapies, and thereby better personalized disease management and outcome. This review compiles the following: (1) the major molecular alterations of the genome, epigenome, transcriptome, proteome, and metabolome found in all subtypes of thyroid cancer, thus demonstrating the complexity of these tumors and (2) the great translational potential of multi-omics studies to improve patient outcome.

MALDI-MSI as a Complementary Diagnostic Tool in Cytopathology: A Pilot Study for the Characterization of Thyroid Nodules

The present study applies for the first time as Matrix-Assisted Laser Desorption/Ionization (MALDI) Mass Spectrometry Imaging (MSI) on real thyroid Fine Needle Aspirations (FNAs) to test its possible complementary role in routine cytology in the diagnosis of thyroid nodules. The primary aim is to evaluate the potential employment of MALDI-MSI in cytopathology, using challenging samples such as needle washes. Firstly, we designed a statistical model based on the analysis of Regions of Interest (ROIs), according to the morphological triage performed by the pathologist. Successively, the capability of the model to predict the classification of the FNAs was validated in a different group of patients on ROI and pixel-by-pixel approach. Results are very promising and highlight the possibility to introduce MALDI-MSI as a complementary tool for the diagnostic characterization of thyroid nodules.

High Spatial Resolution MALDI-MS Imaging in the Study of Membranous Nephropathy

PURPOSE

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technology has advanced rapidly during recent years with the development of instruments equipped with low-diameter lasers that are suitable for high spatial resolution imaging. This may provide significant advantages in certain fields of molecular pathology where more specific protein fingerprints of individual cell types are required, such as renal pathology.

EXPERIMENTAL DESIGN

Here MALDI-MSI analysis of a cohort of membranous nephropathy (MN) patients is performed among which patients either responded favorably (R; n = 6), or unfavorably (NR; n = 4), to immunosuppressive treatment (Ponticelli Regimen), employing a 10 µm laser spot diameter.

RESULTS

Specific tryptic peptide profiles of the different cellular regions within the glomerulus can be generated, similarly for the epithelial cells belonging to the proximal and distal tubules. Conversely, specific glomerular and sub-glomerular profiles cannot be obtained while using the pixel size performed in previous studies (50 µm). Furthermore, two proteins are highlighted, sonic hedgehog and α-smooth muscle actin, whose signal intensity and spatial localization within the sub-glomerular and tubulointerstitial compartments differ between treatment responders and non-responders.

CONCLUSIONS AND CLINICAL RELEVANCE

The present study exemplifies the advantage of using high spatial resolution MALDI-MSI for the study of MN and highlights that such findings have the potential to provide complementary support in the routine prognostic assessment of MN patients.

Proteomic Analysis of Zn Depletion/Repletion in the Hormone-Secreting Thyroid Follicular Cell Line FRTL-5

Zinc deficiency predisposes to a wide spectrum of chronic diseases. The human Zn proteome was predicted to represent about 10% of the total human proteome, reflecting the broad array of metabolic functions in which this micronutrient is known to participate. In the thyroid, Zn was reported to regulate cellular homeostasis, with a yet elusive mechanism. The Fischer Rat Thyroid Cell Line FRTL-5 cell model, derived from a Fischer rat thyroid and displaying a follicular cell phenotype, was used to investigate a possible causal relationship between intracellular Zn levels and thyroid function. A proteomic approach was applied to compare proteins expressed in Zn deficiency, obtained by treating cells with the Zn-specific chelator N,N,N′,N′-tetrakis (2-pyridylmethyl) ethylene-diamine (TPEN), with Zn repleted cells. Quantitative proteomic analysis of whole cell protein extracts was performed using stable isotope dimethyl labelling coupled to nano-ultra performance liquid chromatography-mass spectrometry (UPLC-MS). TPEN treatment led to almost undetectable intracellular Zn, while decreasing thyroglobulin secretion. Subsequent addition of ZnSO₄ fully reversed these phenotypes. Comparative proteomic analysis of Zn depleted/repleted cells identified 108 proteins modulated by either treatment. Biological process enrichment analysis identified functions involved in calcium release and the regulation of translation as the most strongly regulated processes in Zn depleted cells.

Update on: proteome analysis in thyroid pathology - part II: overview of technical and clinical enhancement of proteomic investigation of the thyroid lesions

INTRODUCTION

An accurate diagnostic classification of thyroid lesions remains an important clinical aspect that needs to be addressed in order to avoid 'diagnostic' thyroidectomies. Among the several 'omics' techniques, proteomics is playing a pivotal role in the search for diagnostic markers. In recent years, different approaches have been used, taking advantage of the technical improvements related to mass spectrometry that have occurred. Areas covered: The review provides an update of the recent findings in diagnostic classification, in genetic definition and in the investigation of thyroid lesions based on different proteomics approaches and on different type of specimens: cytological, surgical and biofluid samples. A brief section will discuss how these findings can be integrated with those obtained by metabolomics investigations. Expert commentary: Among the several proteomics approaches able to deepen our knowledge of the molecular alterations of the different thyroid lesions, MALDI-MSI is strongly emerging above all. In fact, MS-imaging has also been demonstrated to be capable of distinguishing thyroid lesions, based on their different molecular signatures, using cytological specimens. The possibility to use the material obtained by the fine needle aspiration makes MALDI-MSI a highly promising technology that could be implemented into the clinical and pathological units.

Proteomics study of serum exosomes from papillary thyroid cancer patients

Lymph node metastasis (LNM) in papillary thyroid cancer (PTC) is related to increased risk of recurrence and poor prognosis. Tumour exosomes have been shown to be associated with metastasis of cancer cells. Therefore, we aim to identify the characteristics and biological functions of serum exosomes in lymph node metastases of PTC. We compared proteome profiles of serum-purified exosomes (SPEs) from PTC patients with LNM, PTC patients without LNM, and healthy donors, using a combination of liquid chromatography-tandem mass spectroscopy analyses and tandem mass tag label quantitation analysis. We identified 1569 proteins by two or more unique peptides. Compared with the SPEs of PTC patients without LNM, we found 697 differentially expressed proteins in the SPEs of PTC patients with LNM. Our results revealed overexpression of specific proteins with well-established links to cancer cell metastasis, such as SRC, TLN1, ITGB2 and CAPNS1. Consistent with mass spectrum results, we performed Western blot to detect the expression of these proteins in individual sample. Biological pathway analyses showed that integrin signalling was aberrantly activated in the SPEs of PTC patients with LNM compared to those without LNM. Our study reveals that SPEs of PTC patients with lymph node metastases promote BHT101 thyroid cancer cell invasiveness, but have no apparent influence on cell migration. In the serum exosomes of PTC patients with LNM, integrin-associated proteins are obviously upregulated. These proteomic findings will contribute to elucidation of the pathophysiological functions of tumour-derived exosomes.

Proteome profiles of different types of thyroid cancers

Proteomics profiling of tissue specimens representative for major types of thyroid cancers: papillary (classical and follicular variant), follicular, anaplastic and medullary, as well as benign follicular adenoma, was performed using shotgun LC-MS/MS approaches. A combination of Orbitrap and MALDI-TOF approach allowed to identify protein products of 3700 unique genes and revealed large differences between medullary, anaplastic and epithelium-derived differentiated cancers (papillary and follicular). Proteins characteristic for medullary and anaplastic cancers included factors associated with neuroendocrine functions and factors typically associated with advanced malignancies, respectively. Proteomes of different types of epithelium-derived differentiated cancers and follicular adenoma were compared using multi-enzyme LC-MS/MS approach, which revealed products of 4800 unique genes. A comparable overall similarity of follicular cancers to both variants of papillary cancers was found. Moreover, follicular adenoma showed higher overall similarity to follicular cancer than to either variant of papillary cancer. Proteins discriminating differentiated thyroid neoplasms included factors associated with lipid and hormone metabolism, regulation of gene expression and maintenance of DNA structure. Importantly, proteome data matched several features of transcriptome and metabolome profiles of thyroid cancers contributing to systems biology of this malignancy.

Decreased apolipoprotein A4 and increased complement component 3 as potential markers for papillary thyroid carcinoma: A proteomic study

BACKGROUND:

Thyroid carcinomas have comprised the fastest rising incidence of cancer in the past decade. Currently, the diagnosis of thyroid tumors is performed by the fine-needle aspiration biopsy (FNAB) method, which still holds some challenges and limitations, mostly in discriminating malignant and benign lesions. Therefore, the development of molecular markers to distinguish between these lesion types are in progress.

METHODS:

A 2D-PAGE separation of proteins was performed followed by tandem mass spectrometry with the aim of discovering potential serum protein markers for papillary thyroid carcinoma and multinodular goiter. Protein-protein interaction network analysis revealed the most important pathways involved in the progression of papillary thyroid cancer. The enzyme-linked immunosorbent assay method was used to confirm a part of the results.

RESULTS:

The significantly altered proteins included C3, C4A, GC, HP, TTR, APOA4, APOH, ORM2, KRT10, AHSG, IGKV3-20, and IGKC. We also confirmed that increased complement component 3 and decreased apolipoprotein A4 occurred in papillary thyroid cancer. Network investigations demonstrated that complement activation cascades and PPAR signaling might play a role in the pathogenesis of thyroid cancer.

CONCLUSION:

The results demonstrated that serum proteomics could serve as a viable method for proposing novel potential markers for thyroid tumors. Surely, further research must be performed in larger cohorts to validate the results.

Molecular signatures of medullary thyroid carcinoma by matrix-assisted laser desorption/ionisation mass spectrometry imaging

The main aim of the study was to assess the feasibility of matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in the pathological investigation of Medullary Thyroid Carcinoma (MTC). Formalin-fixed paraffin-embedded (FFPE) samples from seven MTC patients were analysed by MALDI-MSI in order to detect proteomic alterations within tumour lesions and to define the molecular profiles of specific findings, such as amyloid deposition and C cell hyperplasia (CCH). nLC-ESI MS/MS was employed for the identification of amyloid components and to select alternative proteomic markers of MTC pathogenesis. Results highlighted the potential of MALDI-MSI to confirm the classic immunohistochemical methods employed for the diagnosis of MTC, with good sensitivity and specificity. Intratumoural amyloid components were also detected and identified, and were characterised by calcitonin, apolipoprotein E, apolipoprotein IV, and vitronectin. The tryptic peptide profiles representative of MTC and CCH were distinctly different, with four alternative markers for MTC being detected; K1C18, and three histones (H2A, H3C, and H4). Finally, a further 115 proteins were identified through the nLC-ESI-MS/MS analysis alone, with moesin, veriscan, and lumican being selected due to their potential involvement in MTC pathogenesis. This approach represents a complimentary strategy that could be employed to detect new proteomic markers of MTC. STATEMENT OF SIGNIFICANCE: Medullary thyroid carcinoma (MTC) is a rare endocrine malignancy that originates from the parafollicular C-cells of the thyroid. The diagnosis is typically established using a combination of fine-needle aspiration biopsy (FNAB) of a suspicious nodule along with the demonstrable elevation of serum biomarkers, such as calcitonin and carcinoembryonic antigen (CEA). Unfortunately, this combination is often associated with a high degree of false-positive results and this can lead to misdiagnosis and avoidable total thyroidectomy. The current study presents the potential role of MALDI-MSI in the search for new proteomic markers of MTC with diagnostic and prognostic significance. MALDI-MSI was capable of detecting the classic immunohistochemical markers employed for the diagnosis of MTC, with good sensitivity and specificity. Furthermore, the complementary combination of MALDI-MSI and nLC-ESI-MS/MS analysis, using a single tissue section, enabled further potential markers to be identified and their spatial localisation visualised within tumoural regions. Such findings could be a valuable starting point for further studies focused on confirming the data presented here using thyroid FNABs, with the final objective being to provide complimentary assistance for the detection of MTC during the pre-operative phase.

Identification of CHEK1, SLC26A4, c-KIT, TPO and TG as new biomarkers for human follicular thyroid carcinoma

The search for preoperative biomarkers for thyroid malignancies, in particular for follicular thyroid carcinoma (FTC) diagnostics, is of utmost clinical importance. We thus aimed at screening for potential biomarker candidates for FTC. To evaluate dynamic alterations in molecular patterns as a function of thyroid malignancy progression, a comparative analysis was conducted in clinically distinct subgroups of FTC and poorly differentiated thyroid carcinoma (PDTC) nodules. NanoString analysis of FFPE samples was performed in 22 follicular adenomas, 56 FTC and 25 PDTC nodules, including oncocytic and non-oncocytic subgroups. The expression levels of CHEK1, c-KIT, SLC26A4, TG and TPO were significantly altered in all types of thyroid carcinomas. Based on collective changes of these biomarkers which correlating among each other, a predictive score has been established, allowing for discrimination between benign and FTC samples with high sensitivity and specificity. Additional transcripts related to thyroid function, cell cycle, circadian clock, and apoptosis regulation were altered in the more aggressive oncocytic subgroups only, with expression levels correlating with disease progression. Distinct molecular patterns were observed for oncocytic and non-oncocytic FTCs and PDTCs. A predictive score correlation coefficient based on collective alterations of identified here biomarkers might help to improve the preoperative diagnosis of FTC nodules.

Molecular Signature of Indeterminate Thyroid Lesions: Current Methods to Improve Fine Needle Aspiration Cytology (FNAC) Diagnosis

Fine needle aspiration cytology (FNAC) represents the gold standard for determining the nature of thyroid nodules. It is a reliable method with good sensitivity and specificity. However, indeterminate lesions remain a diagnostic challenge and researchers have contributed molecular markers to search for in cytological material to refine FNAC diagnosis and avoid unnecessary surgeries. Nowadays, several "home-made" methods as well as commercial tests are available to investigate the molecular signature of an aspirate. Moreover, other markers (i.e., microRNA, and circulating tumor cells) have been proposed to discriminate benign from malignant thyroid lesions. Here, we review the literature and provide data from our laboratory on mutational analysis of FNAC material and circulating microRNA expression obtained in the last 6 years.

Clinical applications of MALDI imaging technologies in cancer and neurodegenerative diseases

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) enables localization of analytes of interest along with histology. More specifically, MALDI-IMS identifies the distributions of proteins, peptides, small molecules, lipids, and drugs and their metabolites in tissues, with high spatial resolution. This unique capacity to directly analyze tissue samples without the need for lengthy sample preparation reduces technical variability and renders MALDI-IMS ideal for the identification of potential diagnostic and prognostic biomarkers and disease gradation. MALDI-IMS has evolved rapidly over the last decade and has been successfully used in both medical and basic research by scientists worldwide. In this review, we explore the clinical applications of MALDI-IMS, focusing on the major cancer types and neurodegenerative diseases. In particular, we re-emphasize the diagnostic potential of IMS and the challenges that must be confronted when conducting MALDI-IMS in clinical settings. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Proteomic profiles of thyroid tumors by mass spectrometry-imaging on tissue microarrays

The current study proposes the successful use of a mass spectrometry-imaging technology that explores the composition of biomolecules and their spatial distribution directly on-tissue to differentially classify benign and malignant cases, as well as different histotypes. To identify new specific markers, we investigated with this technology a wide histological Tissue Microarray (TMA)-based thyroid lesion series. Results showed specific protein signatures for malignant and benign specimens and allowed to build clusters comprising several proteins with discriminant capabilities. Among them, FINC, ACTB1, LMNA, HSP7C and KAD1 were identified by LC-ESI-MS/MS and found up-expressed in malignant lesions. These findings represent the opening of further investigations for their translation into clinical practice, e.g. for setting up new immunohistochemical stainings, and for a better understanding of thyroid lesions. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

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.

Proteomics in thyroid cytopathology: Relevance of MALDI-imaging in distinguishing malignant from benign lesions

Several proteomic strategies are used extensively for the purpose of biomarker discovery and in order to obtain insights into the molecular aspects of cancers, using either body fluids or tissue as samples. Among them, MALDI-imaging can be applied to cytological thyroid specimens to investigate the molecular signatures of different pathological conditions and highlight differences in the proteome that are of relevance for diagnostic and pathogenetic research. In this study, 26 ex-vivo fine needle aspirations from benign thyroid nodules (n = 13) and papillary thyroid carcinomas (n = 13) were analyzed by MALDI-imaging. Based on the specific protein signatures capable of distinguishing the aforementioned patients, MALDI-imaging was able to correctly assign, in blind, the specimens from ten additional FNABs to a malignant or benign class, as later confirmed by the morphological classification. Moreover, some proteins presented a progressive overexpression in malignant phenotypes when compared with Hashimoto's thyroiditis and hyperplastic/follicular adenoma. This data not only suggests that a MALDI-imaging based approach can be a valuable tool in the diagnosis of thyroid lesions but also in the detection of proteins that have a possible role in the promotion of tumorigenic activity.