Clinical trial NCT06878534: Observational Study Analysing the Transcriptome and Mutational Status of Thyroid Carcinomas of Follicular Origin with Different Degrees of Malignancy
Official title: Observational Study Analysing the Transcriptome and Mutational Status of Thyroid Carcinomas of Follicular Origin with Different Degrees of Malignancy
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Thyroid Cancer
Keywords: Thyroid Cancer, miRNA, non coding RNA
Lead sponsor: IRCCS SYNLAB SDN
Sponsor class: OTHER
Collaborators: name: University Federico II of Naples, Department of Clinical and Surgical Medicine
First posted: 2025-03-17
Enrollment: 80
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population consists of patients with thyroid carcinoma originating from the follicular thyroid cell at varying degrees of malignancy. For such a retrospective population, considering the study's primary objective of identifying potential tissue biomarkers of pathology, an a posteriori power analysis was performed, considering a paired statistical design of the case-control type, where the control group is afferent to the healthy counterpart of the tissues available in the archives of the same thyroid carcinoma patients.

For the subgroup analyses associated with the different degrees of invasiveness/aggressiveness, the statistical power associated with the possible clinical stratifications will be assessed before proceeding with the statistical analyses

Brief summary: Thyroid cancer (TC) is the most common endocrine malignancy, with well-differentiated thyroid carcinomas (DTCs)-papillary (PTC) and follicular (FTC)-comprising the majority of cases. While DTCs generally have favorable prognoses, a subset progresses to poorly differentiated or anaplastic thyroid carcinoma (ATC), which is highly aggressive. Tumor classification is based on histopathology, invasiveness, and molecular characteristics, with new entities like thyroid tumors of uncertain malignant potential (TT-UMP) and non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) refining diagnostic criteria.

Current standard treatments include surgical resection, radioactive iodine therapy, and thyroid hormone replacement. However, some patients develop radioiodine-refractory disease with an increased risk of recurrence and progression. Molecular alterations in the MAPK and PI3K pathways play critical roles in thyroid tumorigenesis, influencing therapeutic response and prognosis. Identifying novel biomarkers for early detection and risk stratification is crucial. Emerging evidence highlights the role of microRNAs (miRNAs) in thyroid cancer progression, functioning as oncogenes or tumor suppressors.

This retrospective case-control study aims to identify novel molecular markers linked to thyroid cancer aggressiveness. Archived formalin-fixed paraffin-embedded (FFPE) tissue and blood samples will be analyzed from patients with varying degrees of PTC and FTC invasiveness. Control samples will be histologically normal thyroid tissue from the same patients.

Next Generation Sequencing (NGS), including RNA-seq and miRNA-seq, will be employed to detect differentially expressed RNA molecules. Validation will be performed using Real-Time PCR in an independent cohort. High-throughput genomic sequencing (Illumina TruSight Oncology 500) will assess mutations, copy number variations, and tumor mutation burden to correlate genetic alterations with malignancy. Variants will be prioritized based on frequency differences in tumor vs. non-tumor populations and functional relevance.

The study will enroll patients with follicular cell-derived thyroid carcinoma. A power analysis indicates that 80 subjects provide \>80% statistical power for biomarker identification. Descriptive statistics, parametric/non-parametric tests, and machine learning approaches will analyze transcriptomic and genomic data. Receiver operating characteristic (ROC) curves will assess diagnostic biomarker accuracy, while logistic regression will model associations between molecular alterations and disease severity.

This study aims to uncover molecular mechanisms driving thyroid cancer progression and identify biomarkers for improved risk stratification, early diagnosis, and potential therapeutic targeting. Findings may enhance personalized treatment approaches in thyroid oncology.


Eligibility criteria: Inclusion Criteria:

* Patients of either sex aged \> 18 years with thyroid cancer of follicular origin.

Exclusion Criteria:

* Patients who do not fit the inclusion criteria.

Primary outcomes:
measure: Identification of novel molecular biomarkers associated with the progression and aggressiveness of follicular-derived thyroid carcinomas
timeFrame: 1-36 months
measure: Determine genetic alterations hat may contribute to disease progression
timeFrame: 1-36 months
Secondary outcomes:
measure: Develop of predictive models for improved risk stratification and prognosis
timeFrame: 12-36 months
Other outcomes:
Locations:
city: Naples
country: Italy
facility: Irccs Synlab Sdn
Study officials:
affiliation: IRCCS SYNLAB SDN
name: Giovanni Smaldone
role: PRINCIPAL_INVESTIGATOR
References:
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citation: Rossi ED, Locantore P, Bruno C, Dell'Aquila M, Tralongo P, Curatolo M, Revelli L, Raffaelli M, Larocca LM, Pantanowitz L, Pontecorvi A. Molecular Characterization of Thyroid Follicular Lesions in the Era of "Next-Generation" Techniques. Front Endocrinol (Lausanne). 2022 May 12;13:834456. doi: 10.3389/fendo.2022.834456. eCollection 2022.
citation: Xu B, Fuchs T, Dogan S, Landa I, Katabi N, Fagin JA, Tuttle RM, Sherman E, Gill AJ, Ghossein R. Dissecting Anaplastic Thyroid Carcinoma: A Comprehensive Clinical, Histologic, Immunophenotypic, and Molecular Study of 360 Cases. Thyroid. 2020 Oct;30(10):1505-1517. doi: 10.1089/thy.2020.0086. Epub 2020 May 8.
citation: Macerola E, Poma AM, Vignali P, Basolo A, Ugolini C, Torregrossa L, Santini F, Basolo F. Molecular Genetics of Follicular-Derived Thyroid Cancer. Cancers (Basel). 2021 Mar 7;13(5):1139. doi: 10.3390/cancers13051139.
citation: Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022 Jan;72(1):7-33. doi: 10.3322/caac.21708. Epub 2022 Jan 12.