Observational Study Analysing the Transcriptome and Mutational Status of Thyroid Carcinomas of Follicular Origin with Different Degrees of Malignancy (TRAMT)

March 12, 2025 updated by: Marco Salvatore, IRCCS SYNLAB SDN

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.

Study Overview

Status

Recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

80

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

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

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Thyroid cancer patients
Patients with thyroid cancer
Control subjects
Subjects with non-cancerous thyroid pathology

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Identification of novel molecular biomarkers associated with the progression and aggressiveness of follicular-derived thyroid carcinomas
Time Frame: 1-36 months
RNA-seq and miRNA-seq on serum samples
1-36 months
Determine genetic alterations hat may contribute to disease progression
Time Frame: 1-36 months
Identification of mutations, copy number variations, and tumor mutation burden)
1-36 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Develop of predictive models for improved risk stratification and prognosis
Time Frame: 12-36 months
Application of machine learning approach to integrate transcriptomic and genomic data
12-36 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

IRCCS SYNLAB SDN

Collaborators

University Federico II of Naples, Department of Clinical and Surgical Medicine

Investigators

  • Principal Investigator: Giovanni Smaldone, Irccs Synlab Sdn

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

March 13, 2023

Primary Completion (Actual)

July 30, 2024

Study Completion (Estimated)

March 31, 2027

Study Registration Dates

First Submitted

March 4, 2025

First Submitted That Met QC Criteria

March 12, 2025

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

March 12, 2025

Last Verified

November 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 3/22

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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