An alternative approach in endocrine pathology research: MALDI-IMS in papillary thyroid carcinoma

Spatially Resolved Molecular Characterization of Noninvasive Follicular Thyroid Neoplasms with Papillary-like Nuclear Features (NIFTPs) Identifies a Distinct Proteomic Signature Associated with RAS-Mutant Lesions

Follicular-patterned thyroid neoplasms comprise a diverse group of lesions that pose significant challenges in terms of differential diagnosis based solely on morphologic and genetic features. Thus, the identification of easily testable biomarkers complementing microscopic and genetic analyses is a highly anticipated advancement that could improve diagnostic accuracy, particularly for noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTPs). These tumors exhibit considerable morphological and molecular heterogeneity, which may complicate their distinction from structurally similar neoplasms, especially when genetic analyses reveal shared genomic alterations (e.g., RAS mutations). Here, we integrated next-generation sequencing (NGS) with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to perform a proteogenomic analysis on 85 NIFTPs (n = 30 RAS-mutant [RAS-mut] and n = 55 RAS-wild type [RAS-wt]), with the aim to detect putative biomarkers of RAS-mut lesions. Through this combined approach, we identified four proteins that were significantly underexpressed in RAS-mut as compared to RAS-wt NIFTPs. These proteins could serve as readily accessible markers in morphologically borderline cases showing RAS mutations. Additionally, our findings may provide insights into the distinct pathogenic pathways through which RAS-mut and RAS-wt NIFTPs arise, highlighting the pivotal role of constitutive RAS-mitogen-activated protein kinase (MAPK) pathway activation in the development and progression of RAS-mut tumors.

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.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Cytological Cytospin Preparation for the Spatial Proteomics Analysis of Thyroid Nodules Using MALDI-MSI

The application of innovative spatial omics approaches in the context of cytological specimens may open new frontiers for their diagnostic assessment. In particular, spatial proteomics using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) represents one of the most promising avenues, owing to its capability to map the distribution of hundreds of proteins within a complex cytological background in a multiplexed and relatively high-throughput manner. This approach may be particularly beneficial in the heterogeneous context of thyroid tumors where certain cells may not present clear-cut malignant morphology upon fine-needle aspiration biopsy, highlighting the necessity for additional molecular tools which are able to improve their diagnostic performance.This chapter aims to provide a detailed overview of a cytospin-based preparation workflow that has been optimized to facilitate the reliable spatial proteomics analysis of cytological thyroid specimens using MALDI-MSI, indicating the key aspects which should be considered when handling such samples.

Ex vivo thyroid fine needle aspirations as an alternative for MALDI-MSI proteomic investigation: intra-patient comparison

Fine needle aspiration (FNA) is the reference standard for the diagnosis of thyroid nodules. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been successfully used to discriminate the proteomic profiles of benign and malignant thyroid FNAs within the scope of providing support to pathologists for the classification of morphologically borderline cases. However, real FNAs provide a limited amount of material due to sample collection restrictions. Ex vivo FNAs could represent a valuable alternative, increasing sample size and the power of statistical conclusions. In this study, we compared the real and ex vivo MALDI-MSI proteomic profiles, extracted from thyrocyte containing regions of interest, of 13 patients in order to verify their similarity. Statistical analysis demonstrated the mass spectra similarity of the proteomic profiles by performing intra-patient comparison, using statistical similarity systems. In conclusion, these results show that post-surgical FNAs represent a possible alternative source of material for MALDI-MSI proteomic investigations in instances where pre-surgical samples are unavailable or the number of cells is scarce.

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.

Molecular testing in diagnosis of indeterminate thyroid cytology: Trends and drivers

Fine needle aspiration (FNA), the cornerstone of diagnosis in thyroid swellings, fails to render a definitive diagnosis in about 20% to 30% of cases that are reported as indeterminate on cytology. Since the clinical management in thyroid rests on the risk of malignancy (ROM) in a given nodule, this distinction between "benign" and "possibly malignant" assumes paramount clinical importance. Over the last two decades, tremendous progress has been achieved in our understanding of the molecular basis of thyroid pathologies leading to identification of several genetic alterations that could potentially be exploited for diagnostic, prognostic and therapeutic purposes. An array of molecular tests has hit the markets aiming to predict the ROM in thyroid nodules. A deeper understanding of the strengths and limitations of these tests is imperative to be able to judiciously choose the right molecular test in a given case for maximum clinical benefit. This narrative review provides an overview of current status of molecular testing in the evaluation of thyroid nodules encompassing the current status and applications of these tests in diagnostic, prognostic and therapeutic areas along with a brief insight into the future developments in this field.

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.

The management of haemoglobin interference for the MALDI-MSI proteomics analysis of thyroid fine needle aspiration biopsies

MALDI-MSI represents an ideal tool to explore the spatial distribution of proteins directly in situ, integrating molecular and cytomorphological information, enabling the discovery of potential diagnostic markers in thyroid cytopathology. However, red cells present in the fine needle aspiration biopsy (FNAB) specimens caused ion suppression of other proteins during the MALDI-MSI analysis due to large amount of haemoglobin. Aim of this study was to set up a sample preparation workflow able to manage this haemoglobin interference. Three protocols were compared using ex vivo cytological samples collected from fresh thyroid nodules of 9 patients who underwent thyroidectomy: (A) conventional air-dried smears, (B) cytological smears immediately fixed in ethanol, and (C) ThinPrep liquid-based preparation. Protocols C and A were also evaluated using real FNABs. Results show that protocol C markedly decreased the amount of haemoglobin, with respect to protocols A and B. Protein profiles obtained with protocols A and B were characterised by high inter-patient variability, probably related to the abundance of the haemoglobin, whereas similar spectra were observed for protocol C, where haemoglobin contents were lower. Our findings suggest protocol C as the sample preparation method for MALDI-MSI analysis. Graphical abstract.

Feasibility Study for the MALDI-MSI Analysis of Thyroid Fine Needle Aspiration Biopsies: Evaluating the Morphological and Proteomic Stability Over Time

PURPOSE

MALDI-MS imaging (MALDI-MSI) is an emerging technology that enables the spatial distribution of biomolecules within tissue to be combined with the traditional morphological information familiar to clinicians. Thus, for diagnostic or prognostic purposes, along with predicting response to therapeutic treatment, it is important to properly collect and handle biological specimens in order to avoid degradation or the formation of artifacts in the morphological structure and proteomic profile.

EXPERIMENTAL DESIGN

In this work, the morphological and proteomic stability of thyroid fine needle aspiration biopsies in PreservCyt (up to 14 days) and CytoLyt (up to 7 days) solutions at 4 °C has been verified, by MALDI-MSI analysis. Moreover, a new measure has been introduced in order to assess the similarity of the obtained MALDI-MSI spectra, by equally taking into account the number of signals (fit and retrofit), and their intensities (Spearman's correlation and spectra overlap).

RESULTS

Results show no degradation of the cellular morphology and a good stability of the samples up to 14 days in PreservCyt solution.

CONCLUSIONS AND CLINICAL RELEVANCE

Moreover, this protocol can be easily implemented in pathological units, allowing simple sample collection and shipment to be used not only for the proteomic MALDI-MSI analysis of thyroid FNABs but also for other biological liquid based specimens.

Discerning the Primary Carcinoma in Malignant Peritoneal and Pleural Effusions Using Imaging Mass Spectrometry-A Feasibility Study

PURPOSE

Malignant effusions challenge diagnostic accuracy due to cytomorphologic overlaps between various malignant primaries. Workup of this material to establish a correct diagnosis is time consuming and limited by the sparsity of material. In order to circumvent these drawbacks, the use of MALDI imaging MS (IMS) as a diagnostic platform has been explored.

EXPERIMENTAL DESIGN

Cytology cell blocks from malignant effusions (serous ovarian carcinoma and several non-ovarian carcinomas including gastric adenocarcinoma) containing at least 30% neoplastic cells are selected for generation of cytology microarrays (CMA). CMA sections are transferred to conductive glass slides, subjected to on-tissue tryptic digestion, and matrix application for MALDI-IMS analysis.

RESULTS

Supervised classification analysis identifies serous ovarian carcinomas as the source of malignant effusions with a sensitivity of 85.7% when compared to samples from all other included primary sites. When compared to gastric adenocarcinoma, serous ovarian carcinoma samples can be delineated with a sensitivity of 97.3%.

CONCLUSION AND CLINICAL RELEVANCE

These preliminary results highlight that MALDI-IMS allows subtyping of malignant effusions to identify the precise origin of neoplastic cells. While achieving similar results compared to classical approaches such as immunocytology, more material is conserved that will be available for further tests.

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.

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.

MALDI-MSI Analysis of Cytological Smears: The Study of Thyroid Cancer

Fine needle aspiration (FNA) biopsies are the current gold-standard for the preoperative evaluation of thyroid nodules. However, a significant number of them (15-30%) are unable to be affirmatively diagnosed and are given an "indeterminate for malignancy" final report, meaning that the malignant nature of the thyroid nodule remains unknown and the recommended therapeutic approach is total thyroidectomy. Furthermore, cytomorphological evaluation of biopsies taken post-surgery indicates that approximately 80% of nodules within this group of patients are in fact benign, and the total thyroidectomy unwarranted. Therefore, the identification of new possible diagnostic targets that can assist in the preoperative diagnosis of thyroid tumors and reduce the number of unnecessary thyroidectomies is imperative.Matrix-Assisted Laser Desorption/Ionization (MALDI)-Mass Spectrometry Imaging (MSI) has the ability to provide very precise and localized information regarding protein expression in cytological specimens. This enables the detection of cell subpopulations based on their different protein profiles, even within regions that are indistinguishable at the microscopic level, and the feasibility of this approach to investigate FNA specimens has already been highlighted in a number of studies. Here, an overview about the sample preparation procedure for the MALDI-MSI analysis of ex vivo FNA biopsies is provided, highlighting how molecular imaging can be combined with traditional histology to generate protein signatures of the different thyroid lesions, and, ultimately, build classification models that can be potentially used to classify benign and malignant thyroid nodules from a molecular standpoint.

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.

A Support Vector Machine Classification of Thyroid Bioptic Specimens Using MALDI-MSI Data

Biomarkers able to characterise and predict multifactorial diseases are still one of the most important targets for all the “omics” investigations. In this context, Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry Imaging (MALDI-MSI) has gained considerable attention in recent years, but it also led to a huge amount of complex data to be elaborated and interpreted. For this reason, computational and machine learning procedures for biomarker discovery are important tools to consider, both to reduce data dimension and to provide predictive markers for specific diseases. For instance, the availability of protein and genetic markers to support thyroid lesion diagnoses would impact deeply on society due to the high presence of undetermined reports (THY3) that are generally treated as malignant patients. In this paper we show how an accurate classification of thyroid bioptic specimens can be obtained through the application of a state-of-the-art machine learning approach (i.e., Support Vector Machines) on MALDI-MSI data, together with a particular wrapper feature selection algorithm (i.e., recursive feature elimination). The model is able to provide an accurate discriminatory capability using only 20 out of 144 features, resulting in an increase of the model performances, reliability, and computational efficiency. Finally, tissue areas rather than average proteomic profiles are classified, highlighting potential discriminating areas of clinical interest.

Solid cell nests of the thyroid gland: morphological, immunohistochemical and genetic features

AIMS

The correct identification of solid cell nests (SCNs) is an important issue in thyroid pathology because of the spectrum of differential diagnoses of this type of lesion.

METHODS AND RESULTS

Ten cases of 295 consecutive thyroidectomies showed the presence of SCNs at histological examination. The identification of the exact SCN type required the distinction of the cystic and solid pattern; SCNs were usually composed of a mixture of main cells (MCs) and C-cells (CCs). The immunohistochemical calcitonin stain identified CCs easily, both inside SCNs and dispersed in islets at the periphery. For the characterization of MCs, we added the utility of p40 to p63. The use of thyroid transcription factor-1 (TTF-1) helped in their identification, as MCs did not react with this marker; the combination of TTF-1 and p40 or p63 IHC stains was useful for the characterization of cystic SCNs of both types 3 and 4. The negativity of mouse monoclonal mesothelioma antibody (HMBE-1) and a very low proliferative index (MIB-1) supported the diagnosis. [Correction added on 23 November 2015, after online publication: MIB-1 was incorrectly defined, the expanded form was deleted.] We discourage the use of galectin-3 (Gal-3) and cytokeratin-19 (CK-19), as they have an important overlap with papillary thyroid carcinoma. The complete absence of any B-Raf proto-oncogene, serine/threonine kinase (BRAF) mutations is an additional fundamental finding.

CONCLUSIONS

We reviewed the most relevant morphological and immunohistochemical features of SCNs and have provided a genetic analysis of the BRAF gene because of its expanding use in thyroid pathology.

A MALDI-Mass Spectrometry Imaging method applicable to different formalin-fixed paraffin-embedded human tissues

The paper shows a new method for the application of Matrix Assisted Laser Desorption/Ionisation (MALDI) Mass Spectrometry Imaging (MSI) technology on formalin-fixed paraffin-embedded (FFPE) tissue samples.

FISH molecular testing in cytological preparations from solid tumors

Many of the exciting new developments in solid tumor molecular cytogenetics impact classical and molecular pathology. Fluorescence in situ hybridization to identify specific DNA target sequences in nuclei of non-dividing cells in solid neoplasms has contributed to the integration of molecular cytogenetics into cytology in spite of the remarkable promiscuity of cancer genes. Indeed, although it is a low-throughput assay, fluorescence in situ hybridization enables the direct disclosure and localization of genetic markers in single nuclei. Gene fusions are among the most prominent genetic alterations in cancer, providing markers that may be determinant in needle biopsies that are negative or suspicious for malignancy, and may contribute to the correct classification of the tumors. In view of the expanding use of fluorescence in situ hybridization in cytology, future challenges include automated sample evaluation and the specification of common criteria for interpreting and reporting results.

Optimizing detection of RET and PPARg rearrangements in thyroid neoplastic cells using a home-brew tetracolor probe

BACKGROUND

Fluorescence in situ hybridization (FISH) to identify specific DNA target sequences in the nuclei of nondividing cells of numerous solid neoplasms has contributed to the introduction of molecular cytogenetics as a useful adjunct to cytology, leading recently to the "marriage" of the 2 disciplines. Numerous cancer molecular markers can now be investigated using different technical approaches, at both the gene and expression levels, in biopsies of various suspected cancers, including differentiated thyroid carcinoma. The limited amount of bioptic material is often insufficient to carry out multiple tests, and optimizing handling of the biopsy is desirable.

METHODS

We have developed a home-brew tetracolor break-apart probe able to simultaneously identify the 2 most common genetic alterations in differentiated thyroid carcinoma: RET/PTC variants in papillary thyroid carcinoma and PAX8/PPARg fusion and variants in follicular thyroid carcinoma.

RESULTS

The probe had 100% specificity, 99.5% sensitivity, and ≥ 3% cutoff. The probe was tested on RET/PTC and PAX8/PPARg RT-PCR positive controls, and feasibility was assessed in 368 thyroid nodule fine-needle aspirations (FNA). In the latter analysis, 24 FNAs had split RET signal, and 9 had split PPARg signal. FISH analysis of available surgically removed nodules confirmed the sensitivity of FISH in detecting abnormal clones and oligoclones.

CONCLUSIONS

The home-brew tetracolor probe showed high feasibility, optimizing the use of the biological material in relation to the available molecular tests and maximizing the FISH experimental and slide-scoring times. This probe may be considered an alternative to RT-PCR when recovery and quality of RNA amplification from FNA are insufficient.