Thyroid cancer is the most prevalent endocrine malignancy, with increasing incidence due to advancements in diagnostic techniques. Ultrasound (US) and fine needle aspiration (FNA) cytology, widely used in clinical practice, have detection accuracies ranging from 65 % to 95 %. However, these methods may yield inconclusive or difficult-to-interpret results, emphasizing the need for complementary diagnostic techniques. This study explores the integration of Raman spectroscopy and gene expression analysis via RT-qPCR to improve the diagnosis of thyroid lesions, classified into groups: follicular thyroid carcinoma (FTC), papillary thyroid carcinoma (PTC) and goiter tissues. Healthy tissue samples were used as normalizing controls in both analysis. Raman spectroscopy analyzed 35 samples, while RT-qPCR assessed 33 samples. For comparison, the same 19 samples previously analyzed by both techniques were examined. Raman spectroscopy, a non-invasive technique, has shown effectiveness in distinguishing between benign and malignant thyroid tissues by identifying key biochemical components such as DNA, RNA, proteins, and lipids. The distinguishing of FTC from goiter using Raman spectroscopy achieved an accuracy rate of 82.3 %. Gene expression analysis via RT-qPCR focused on six genes: TG, TPO, PDGFB, SERPINA1, TFF3, and LGALS3. Specifically, SERPINA1 was overexpressed in PTC, TFF3 showed elevated levels in FTC, and LGALS3 was elevated in both PTC and FTC compared to goiter and normal tissues. These findings align with existing literature, suggesting that these genes could serve as valuable diagnostic molecular markers. The expression analysis of these genes within this subset of samples demonstrated concordance with the classification derived from PCA of Raman spectroscopy data. The integration of Raman spectroscopy and RT-qPCR offers a complementary approach to traditional histological analysis, providing enhanced sensitivity and specificity in diagnosing thyroid lesions.