Few studies have analyzed the prevalence of TERT amplification in thyroid cancer, showing discrepancies in various topics. The impact on tumor recurrence and patient survival in papillary thyroid carcinoma (PTC) remains unknown. Thirteen cancer cell lines and 215 tumor samples from 91 patients, who underwent surgery for PTC (41), poorly differentiated thyroid carcinoma (PDC = 15), or anaplastic thyroid carcinoma (ATC = 35), were analyzed. Clonality, spread with tumor dedifferentiation or metastatic PTC cells, and coexistence with TERTp , BRAF , RAS , and PIK3CA mutations were also investigated. TERT amplification was found in 17%, 20%, and 17% of the PTC, PDC, and ATC, respectively. It was more frequent in follicular variant PTC and PTC with distant metastases (86%, P = 0.0448). The cell lines HTh74, SW1736, and T242 had amplification. In PTC, TERT amplification was a subclonal event. The increase in TERT copy number spread in all cases with metastatic PTC cells. In 67% of the PDC and 100% of the ATC, TERT activation segregated with tumor dedifferentiation. TERT amplification correlated with TERTp mutations in PTC ( P = 0.0313) and PIK3CA mutations in ATC ( P = 0.0272). TERT amplification significantly correlated with vascular invasion ( P = 0.03637), distant metastases at diagnosis and/or follow-up ( P = 0.04482), metachronous distant metastases ( P = 0.03131), death patient status ( P = 0.000829), stage at diagnosis ( P = 0.01995), and stage III/IV at last follow-up ( P = 0.01552). TERT amplification associated independently with tumor-related recurrence and death. Our study shows that PTC can be stratified into clinically prognostic relevant categories based on the presence or not of TERT amplification in the cells.

Thyroid cancer prevalence has increased in the last few decades. Whereas the majority of well-differentiated histotypes have effective therapeutic options, the most advanced cases lacked successful treatment until recent years. Genomic alterations have emerged as targets for new anti-cancer drugs. This molecular knowledge is gradually being translated into sophisticated approaches for the stratification, management, and therapies of patients with thyroid carcinomas. The genomic characterisation of tumours in clinical assistance serves as a tool for enhancing the prognostic assessment of patients with thyroid cancer and predicting their responses to the agents. The MAPK pathway is the most predominantly activated molecular route in this cancer. Several drugs have been developed to inhibit this pathway at different levels. However, the acquired resistance that emerges is the main problem in their use. Other strategies targeting not only driver mutations but also those that confer aggressive behaviour on tumours can be potential targetable options. Due to the new therapies, patients with the most aggressive histotypes have improved survival rates. Adverse events, although manageable, have a high prevalence among the current therapies. Selective inhibitors, immunotherapies, and the combination of both will play a pivotal role in the treatment and the improvements in overall survival in thyroid cancer patients.

RET gene is a driver of thyroid cancer (TC) tumorigenesis. The incidence of TC has increased worldwide in the last few decades, both in medullary and follicular‐derived subtypes. Several drugs, including multikinase and selective inhibitors, have been explored. Selpercatinib and pralsetinib are selective RET inhibitors that have shown clear clinical benefits for patients in the LIBRETTO and ARROW trials, respectively. Currently, their development and application in clinical practice are ongoing. However, its efficacy in different RET pathogenic variants has not yet been well established. Although selpercatinib and pralsetinib achieved a high ORR, no data are available regarding the differences in tumor responses of both TC groups according to RET pathogenic variants. Clinical trials and literature have analyzed the efficacy of selective RET inhibitors with a special interest in the most common variants. A review of LIBRETTO and ARROW trials was made regarding the change in tumor size depending on the pathogenic variants. M918T pathogenic variant resulted in a higher complete response rate. Patients who underwent fusion had the highest ORR (objective response rate). MKi‐treated patients did not exhibit significant differences from untreated patients. Different RET pathogenic variants are not biomarkers of RETi response in TC. Selpercatinib showed a tendency to achieve a complete response. All patients with RET pathogenic variants should receive treatment with selpercatinib or pralsetinib at any moment of the therapeutic schedule owing to off‐target inhibition and toxicity. Therefore, new targets for drug sensitivity and resistance should be explored.

The educational-Pink Innovation Grade Index (e-PIGI) is a novel metric designed to assess and quantify the level of innovation within educational practices and pedagogical projects. This work introduces the e-PIGI tool, an interactive and survey-based software that enables educators, institutions, and project designers to identify both strengths and limitations in their initiatives across ten key dimensions. These include different categories such as: (i) emerging technologies, (ii) adaptability to diversity, (iii) promotion of 21st-century skills, (iv) collaboration, (v) alignment with regulatory frameworks, (vi) active methodologies, (vii) impact, (viii) sustainability, (ix) evaluation and (x) multidisciplinarity. Each dimension is scored using a pink color-based scale ranging from 0 to 10, with darker tones indicating a higher degree of innovation. The resulting output includes a color-coded innovation score and a circular-shaped pictogram that offers a visual representation of the project’s innovative profile. A threshold value of 50 points is proposed as an operational criterion for identifying projects considered innovative. The tool was validated through expert judgment for content validity and through empirical reliability analysis (Cronbach’s coefficient α = 0.833, n = 126), confirming good internal consistency. To demonstrate its utility, the new tool was applied to a set of educational initiatives, helping to highlight their pedagogical strengths and areas for improvement. As an accessible and scalable instrument, e-PIGI aims to support reflective teaching practices, promote ongoing developments, and facilitate the comparison of innovation across diverse educational contexts. This software highlights the potential of e-PIGI to contribute to a more evidence-based and strategically guided culture of innovation in education.