Thyroid cancer is the most common malignancy of the endocrine system, encompassing different entities with distinct histological features and clinical behavior. The diagnostic definition, therapeutic approach, and follow-up of thyroid cancers display some controversial aspects that represent unmet medical needs. Liquid biopsy is a non-invasive approach that detects and analyzes biological samples released from the tumor into the bloodstream. With the use of different technologies, tumor cells, free nucleic acids, and extracellular vesicles can be retrieved in the serum of cancer patients and valuable molecular information can be obtained. Recently, a growing body of evidence is accumulating concerning the use of liquid biopsy in thyroid cancer, as it can be exploited to define a patient’s diagnosis, estimate their prognosis, and monitor tumor recurrence or treatment response. Indeed, liquid biopsy can be a valuable tool to overcome the limits of conventional management of thyroid malignancies. In this review, we summarize currently available data about liquid biopsy in differentiated, poorly differentiated/anaplastic, and medullary thyroid cancer, focusing on circulating tumor cells, circulating free nucleic acids, and extracellular vesicles.

Hypereosinophilia (HE) is a heterogeneous condition with a persistent elevated eosinophil count of >350/mm³, which is reported in various (inflammatory, allergic, infectious, or neoplastic) diseases with distinct pathophysiological pathways. HE may be associated with tissue or organ damage and, in this case, the disorder is classified as hypereosinophilic syndrome (HES). Different studies have allowed for the discovery of two major pathogenetic variants known as myeloid or lymphocytic HES. With the advent of molecular genetic analyses, such as T-cell receptor gene rearrangement assays and Next Generation Sequencing, it is possible to better characterize these syndromes and establish which patients will benefit from pharmacological targeted therapy. In this review, we highlight the molecular alterations that are involved in the pathogenesis of eosinophil disorders and revise possible therapeutic approaches, either implemented in clinical practice or currently under investigation in clinical trials.

Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal evolution. In the last few years, functional single-cell omics has improved our understanding of cancer heterogeneity. This approach requires isolation and identification of single cells starting from an entire population. A cell suspension obtained by tumor tissue dissociation or hematological material can be manipulated using different techniques to separate individual cells, employed for single-cell downstream analysis. Single-cell data can then be used to analyze cell–cell diversity, thus mapping evolving cancer biological processes. Despite its unquestionable advantages, single-cell analysis produces massive amounts of data with several potential biases, stemming from cell manipulation and pre-amplification steps. To overcome these limitations, several bioinformatic approaches have been developed and explored. In this work, we provide an overview of this entire process while discussing the most recent advances in the field of functional omics at single-cell resolution.

Germline BRCA1/2 alteration has been linked to an increased risk of hereditary breast and ovarian cancer syndromes. As a result, genetic testing, based on NGS, allows us to identify a high number of variants of uncertain significance (VUS) or conflicting interpretation of pathogenicity (CIP) variants. The identification of CIP/VUS is often considered inconclusive and clinically not actionable for the patients’ and unaffected carriers’ management. In this context, their assessment and classification remain a significant challenge. The aim of the study was to investigate whether the in silico prediction tools (PolyPhen-2, SIFT, Mutation Taster and PROVEAN) could predict the potential clinical impact and significance of BRCA1/2 CIP/VUS alterations, eventually impacting the clinical management of Breast Cancer subjects. In a cohort of 860 BC patients, 10.6% harbored BRCA1 or BRCA2 CIP/VUS alterations, mostly observed in BRCA2 sequences (85%). Among them, forty-two out of fifty-five alterations were predicted as damaging, with at least one in silico that used tools. Prediction agreement of the four tools was achieved in 45.5% of patients. Moreover, the highest consensus was obtained in twelve out of forty-two (28.6%) mutations by considering three out of four in silico algorithms. The use of prediction tools may help to identify variants with a potentially damaging effect. The lack of substantial agreement between the different algorithms suggests that the bioinformatic approaches should be combined with the personal and family history of the cancer patients.

Background: Detection of BCR-ABL1 transcript level via real-time quantitative-polymerase-chain reaction (Q-PCR) is a clinical routine for disease monitoring, assessing Tyrosine Kinase Inhibitor therapy efficacy and predicting long-term response in chronic myeloid leukemia (CML) patients. For valid Q-PCR results, each stage of the laboratory procedures need be optimized, including the cell-counting method that represents a critical step in obtaining g an appropriate amount of RNA and reliable Q-PCR results. Traditionally, manual or automated methods are used for the detection and enumeration of white blood cells (WBCs). Here, we compared the performance of the manual counting measurement to the flow cytometry (FC)-based automatic counting assay employing CytoFLEX platform. Methods: We tested five different types of measurements: one manual hemocytometer-based count and four FC-based automatic cell-counting methods, including absolute, based on beads, based on 7-amino actinomycin D, combining and associating beads and 7AAD. The recovery efficiency for each counting method was established considering the quality and quantity of total RNA isolated and the Q-PCR results in matched samples from 90 adults with CML. Results: Our analyses showed no consistent bias between the different types of measurements, with comparable number of WBCs counted for each type of measurement. Similarly, we observed a 100% concordance in the amount of RNA extracted and in the Q-PCR cycle threshold values for both BCR-ABL1 and ABL1 gene transcripts in matched counted specimens from all the investigated groups. Overall, we show that FC-based automatic absolute cell counting has comparable performance to manual measurements and allows accurate cell counts without the use of expensive beads or the addition of the time-consuming intercalator 7AAD. Conclusions: This automatic method can replace the more laborious manual workflow, especially when high-throughput isolations from blood of CML patients are needed.

Hydroxyurea (HU) cytoreduction is usually administered to patients with chronic myeloid leukemia before starting any tyrosine kinase inhibitors (TKIs) therapy. However, up to date, there is no evidence of any benefit of hydroxyurea pre-treatment. Conversely, evidence has been provided on both the prognostic significance of the quantitative assessment of BCR::ABL1 expression at diagnosis and the individual decline of the BCR::ABL1 slope. In this view, we assumed that any kind of treatment administered before a confirmed diagnosis of chronic myeloid leukemia might change the amount of BCR::ABL1 transcript levels. To this purpose, we evaluated leukocyte counts and BCR::ABL1 quantitative expression either at diagnosis (baseline and no therapy) and on day 7 and day 14 of treatment in a cohort of 45 unselected patients with newly diagnosed chronic myeloid leukemia in the chronic phase. After informed consent, 21 of them received HU cytoreduction for 14 days before starting TKI treatment (HU group), whereas the other 24 patients received frontline TKI therapy without HU pre-treatment (TKI group). Our findings showed that: (i) there is no benefit from HU cytoreduction in patients affected with chronic myeloid leukemia before starting treatment with TKIs; (ii) any kind of therapy administered before a confirmed diagnosis of chronic myeloid leukemia might change the amount of BCR::ABL1 expression levels.