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Review Open Access

Thyroid cancer: From molecular insights to therapy (Review)

  • Authors:
    • Zhuozheng Li
    • Nuofan Wang
    • Xiao Li
    • Yongfang Xie
    • Zemin Dou
    • Hongbing Xin
    • Yuzhuo Lin
    • Yan Si
    • Tingting Feng
    • Guohui Wang
  • View Affiliations / Copyright

    Affiliations: School of Life Science and Technology, Shandong Second Medical University, Weifang, Shandong 261053, P.R. China, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, P.R. China, Department of Thyroid and Breast Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu 210000, P.R. China, Department of Ultrasound, The Fourth Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China, Clinical Medicine, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 21000, P.R. China, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China, Central Laboratory, The Fourth Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
    Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 520
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    Published online on: September 10, 2025
       https://doi.org/10.3892/ol.2025.15266
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Abstract

Thyroid cancer, a prevalent endocrine malignancy with rising global incidence, encompasses four primary subtypes: Papillary (PTC), follicular (FTC), medullary (MTC) and anaplastic thyroid carcinoma (ATC). PTC, accounting for 85‑90% of cases, is primarily driven by BRAF V600E mutations alongside dysregulated non‑coding RNAs, such as long non‑coding RNA metastasis‑associated lung adenocarcinoma transcript 1 and microRNA (miR)‑1270. These alterations collectively activate MAPK signaling, promoting tumorigenesis. Furthermore, PTC exhibits metabolic reprogramming characterized by dysregulated glucose and lipid metabolism, where tumor suppressors, including family with sequence similarity 111 member B and fat mass and obesity‑associated genes, constrain glycolytic flux. FTC, characterized by Ras mutations, exhibits enhanced lipid metabolism and PI3K/AKT pathway activation. Methyltransferase‑like protein 16 and sclerostin domain‑containing protein 1 have been highlighted as regulators of FTC progression. MTC, associated with rearranged during transfection (RET) proto‑oncogene mutations, demonstrates programmed cell death protein‑1/programmed death ligand‑1 pathway involvement, which offers potential immunotherapy targets. ATC, the most aggressive subtype, is characterized by recurrent genetic alterations such as telomerase reverse transcriptase promoter and tumor protein p53 mutations, cAMP‑responsive element‑binding protein 3‑like 1‑driven activation of cancer‑associated fibroblasts and hematological and neurological expressed 1‑stathmin 1 signaling‑mediated invasiveness. Recent diagnostic innovations encompass serum biomarkers, such as stanniocalcin‑1, microRNA signatures (including miR‑26b‑5p) for PTC and MTC detection, radiomics‑based differentiation of ATC from other subtypes and optical imaging techniques for precision diagnosis. Molecularly targeted therapies constitute the cornerstone of current strategies, with vemurafenib inhibiting BRAF/MEK in PTC, sorafenib acting as a multikinase suppressor in FTC, vandetanib blocking RET in MTC and berberine‑doxorubicin combinations overcoming chemoresistance in ATC. Metabolic interventions, including metformin for glucose modulation in PTC and novel delivery systems such as micelle‑encapsulated AB3 for MTC, demonstrate translational potential. The present review summarizes molecular mechanisms, diagnostic tools and emerging therapies while emphasizing the necessity of subtype‑specific approaches to improve clinical outcomes in thyroid oncology.
View Figures

Figure 1

Emerging regulatory nodes across
molecular mechanisms, diagnostic biomarkers and therapeutic targets
in papillary, follicular, medullary and anaplastic thyroid
carcinomas. RET, rearranged during transfection; HRAS, Harvey rat
sarcoma viral oncogene homolog; miR, microRNA; TP53, tumor protein
53; TERT, telomerase reverse transcriptase; FNA, fine needle
aspiration; METTL, methyltransferase-like protein; IMUP,
immortalization-upregulated protein; USP14, ubiquitin-specific
protease 14; TIMP-1, tissue inhibitor of MMP-1; BRAF, B-Raf
proto-oncogene, serine/threonine kinase; MKL1, megakaryoblastic
leukemia 1; RET, rearranged during transfection proto-oncogene;
KRAS, Kirsten rat sarcoma viral oncogene homolog; RAS, rat sarcoma
virus; PIK3CA, phosphatidylinositol-4,5-bisphosphate 3-kinase
catalytic subunit α; FLT3, FMS-like tyrosine kinase 3; EZH2,
enhancer of zeste homolog 2; SMYD3, SET and MYND domain containing
3; ARHGAP36, Rho GTPase activating protein 36; AKIP1, A kinase
interacting protein 1; E-cadherin, epithelial cadherin; IGF2BP1,
insulin-like growth factor 2 mRNA-binding protein 1; TFRC,
transferrin receptor; DTL, denticleless E3 ubiquitin protein ligase
homolog; RBX1, ring-box 1; CDK5, cyclin-dependent kinase 5; LKB1,
liver kinase B1; ETV4, ETS variant transcription factor 4; PAX8,
paired box 8; PATZ1, POZ/BTB and AT hook containing zinc finger 1;
CREB3L1, CAMP responsive element binding protein 3 like 1; CXCL10,
C-X-C motif chemokine ligand 10; ICAM1, intercellular adhesion
molecule 1; SRPX2, sushi repeat containing protein X-linked 2F12,
coagulation factor XII; MMP, matrix metalloproteinase; SOSTDC1,
sclerostin domain containing 1; SBSN, Suprabasin; ST6GAL2, ST6
β-galactoside α-2,6-sialyltransferase 2; FAM172A, family with
sequence similarity 172 member A; FAM83F, family with sequence
similarity 83 member F; Siglec-15, sialic acid-binding Ig-type
lectin 15; SLC6A15, solute carrier family 6 member 15; STIM1,
stromal interaction molecule 1; ORAI1, ORAI calcium
release-activated calcium modulator 1; RET-PTC, RET/papillary
thyroid carcinoma; PAX8/PPARγ, PAX8/peroxisome
proliferator-activated receptor gamma; LRRC52-AS1, LRRC52 antisense
RNA 1; cfDNA, cell-free DNA; MAGEA3, melanoma associated antigen
A3; CXCL13+ T, CXCL13-positive T cells; MKI, multikinase
inhibitor; MAPK, mitogen-activated protein kinase; Erk1/2,
extracellular signal-regulated kinases 1 and 2; JNK, c-Jun
N-terminal kinase.

Figure 2

Dysregulated signaling pathways and
non-coding RNA networks drive PTC pathogenesis at the molecular
level. The schematic delineates the integrated molecular network
driving PTC proliferation, migration and invasion. Key signaling
cascades include the ERK/Fra-1/ZEB1 axis and JAK/STAT pathway,
modulated by non-coding RNAs (lncRNA AK023507 and circ-100395) and
epigenetic regulators (KMT5A). The BRAF V600E mutation activates
MAPK signaling, upregulating glycolytic enzymes (HK2 and LDHA) and
lipid metabolism mediators (SCD1 and FASN). GLUT1-mediated glucose
uptake and metformin-sensitive pathways coordinate metabolic
reprogramming, involving glycolysis-derived pyruvate, fatty acid
oxidation and TCA cycle dynamics. Regulatory nodes such as SREBP1
and YTHDC2 orchestrate lipid biosynthesis, while miR-1270 and TEL4
fine-tune tumor progression. These interconnected mechanisms
collectively sustain PTC malignancy through proliferative signaling
and microenvironment adaptation. The black arrows indicate
conventional signaling pathway interactions; blue arrows
specifically denote metabolic pathway relationships. PTC, papillary
thyroid cancer; Fra-1, Fos-related antigen 1; ZEB1, Zinc finger
E-box binding homeobox 1; JAK, Janus kinase; lncRNA, long
non-coding RNA; KMT5A, lysine methyltransferase 5A; HK2, hexokinase
2; LDHA, lactate dehydrogenase A; SCD1, stearoyl-CoA desaturase 1;
FASN, fatty acid synthase; GLUT1, glucose transporter 1; TCA,
tricarboxylic acid; SREBP1, sterol regulatory element-binding
protein 1; YTHDC2, YT521-B homology domain-containing protein 2;
miR, microRNA TEL4, translocation-Ets-leukemia 4; ABCA1,
ATP-binding cassette subfamily A Member 1; SCAI, suppressor of
cancer cell invasion; SCD1, tearoyl-CoA desaturase 1; REPIN1,
replication initiator 1; GLTC, glucose transporter 4; FTO, fat mass
and obesity-associated gene; FAM111B, family with sequence
similarity 111 member B; KCNJ13, potassium inwardly rectifying
channel subfamily J member 13; PDZK1IP1, PDZK1-interacting protein
1; TMC3, transmembrane channel-like 3; LRP2, low-density
lipoprotein receptor-related protein 2; SREBP1, sterol regulatory
element-binding protein 1; ACC, acetyl-CoA carboxylase; α-KG,
α-ketoglutarate; METTL, methyltransferase-like; IMUP,
immuno-upregulated protein; SRPX2, sushi repeat-containing protein
X-linked 2; ARHGAP36, Rho GTPase-activating protein 36; LRRC52-AS1,
LRRC52 antisense RNA 1; MKL1, megakaryoblastic leukemia 1.

Figure 3

Molecular mechanisms underlying FTC
progression. The diagram systematically delineates: i) Calcium
signaling through ORAI calcium release-activated calcium modulator
1/STIM1 channels; ii) TSH receptor activation; and iii) core
regulatory pathways (TGF-β, MAPK, PI3K/AKT, NF-κB and Hippo)
coordinating cellular proliferation, migration and invasion. Key
components include USP14-mediated autophagy regulation, ERK
activation through the IGF1/TFR1 axis and iron accumulation
facilitated by the FAM83F/SOSTDC1/SBSN/ST6GAL network. Immune
microenvironment interactions featuring Tregs and tumor-associated
macrophages are indicated in the lower right quadrant. Resveratrol
is presented as a potential therapeutic agent targeting these
molecular pathways. The black arrows indicate conventional
signaling pathway interactions. FTC, follicular thyroid cancer;
STIM1, stromal interaction molecule 1; TSH, thyroid stimulating
hormone; USP14, ubiquitin-specific protease 14; IGF1, insulin-like
growth factor 1; TFR1, transferrin receptor 1; SOSTDC1, sclerostin
domain-containing protein 1; SBSN, suprabasin; ST6GAL2,
β-galactoside α-2,6-sialyltransferase 2; Tregs, regulatory T cells;
ORAI, ORAI calcium release-activated calcium modulator 1; PROX1,
prospero homeobox 1; FAM83F, family with sequence similarity 83
member F.

Figure 4

Schematic illustrating the
therapeutic and diagnostic mechanisms in MTC. The schematic is
structured as: i) Targeted therapy with tyrosine kinase inhibitors
(vandetanib, cabozantinib and GDNK) blocking RET/VEGFR signaling;
ii) diagnostic workflow exhibiting ultrasound-guided FNA followed
by liquid-based cytology and immunocytochemical analysis; and iii)
molecular mechanisms involving CDK5-mediated STAT3 phosphorylation
at Ser727 (P). The histone deacetylase inhibitor AB3 is shown in
the epigenetic regulation domain (upper left).
Mitochondrial-targeted agents are indicated interacting with
membrane receptors (green, VEGFR; orange, RET). Directional arrows
denote signaling amplification. MTC, medullary thyroid cancer; FNA,
fine-needle aspiration; RET, rearranged during transfection;
Ser727, serine 727; miR, microRNA; P, phosphorylation; GDNF, glial
cell line-derived neurotrophic factor; AB3, A new histone
deacetylase inhibitor.

Figure 5

Molecular circuitry and therapeutic
targeting in ATC pathogenesis. This schematic illustrates the
molecular mechanisms driving ATC proliferation and metastasis,
alongside therapeutic strategies. CAFs remodel the ECM through the
CREB3L1/miR-205 axis and JAK-STAT signaling modulated by GANT61.
Metabolic reprogramming involves HDAC6/SMAR1-mediated PKM splicing
and RBX1-STMN1 regulation. DOX triggers ROS-dependent apoptosis via
PI3K-AKT, while targeted therapies include lenvatinib (multikinase
inhibitor), pembrolizumab (anti-PD-1) and BRAF/EGFR inhibitors
(dabrafenib + erlotinib). ATC, anaplastic thyroid cancer; CAFs,
cancer-associated fibroblasts; ECM, extracellular matrix; CREB3L1,
cAMP-responsive element-binding protein 3-like 1; miR, microRNA;
JAK, Janus kinase; GANT61, Gli-antagonist 61; HDAC6, histone
deacetylase 6; SMAR1, scaffold/matrix attachment region binding
protein 1; PKM, pyruvate kinase M1/2; RBX1, RING-box protein 1;
STMN1, stathmin 1; DOX, doxorubicin; ROS, reactive oxygen species;
PD-1, programmed cell death protein-1; HN1, hematological and
neurological expressed 1; CTCF, CCCTC-binding factor; REGγ,
proteasome activator subunit 3; AKIP1, A kinase-interacting protein
1; BER, base excision repair.
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Copy and paste a formatted citation
Spandidos Publications style
Li Z, Wang N, Li X, Xie Y, Dou Z, Xin H, Lin Y, Si Y, Feng T, Wang G, Wang G, et al: Thyroid cancer: From molecular insights to therapy (Review). Oncol Lett 30: 520, 2025.
APA
Li, Z., Wang, N., Li, X., Xie, Y., Dou, Z., Xin, H. ... Wang, G. (2025). Thyroid cancer: From molecular insights to therapy (Review). Oncology Letters, 30, 520. https://doi.org/10.3892/ol.2025.15266
MLA
Li, Z., Wang, N., Li, X., Xie, Y., Dou, Z., Xin, H., Lin, Y., Si, Y., Feng, T., Wang, G."Thyroid cancer: From molecular insights to therapy (Review)". Oncology Letters 30.5 (2025): 520.
Chicago
Li, Z., Wang, N., Li, X., Xie, Y., Dou, Z., Xin, H., Lin, Y., Si, Y., Feng, T., Wang, G."Thyroid cancer: From molecular insights to therapy (Review)". Oncology Letters 30, no. 5 (2025): 520. https://doi.org/10.3892/ol.2025.15266
Copy and paste a formatted citation
x
Spandidos Publications style
Li Z, Wang N, Li X, Xie Y, Dou Z, Xin H, Lin Y, Si Y, Feng T, Wang G, Wang G, et al: Thyroid cancer: From molecular insights to therapy (Review). Oncol Lett 30: 520, 2025.
APA
Li, Z., Wang, N., Li, X., Xie, Y., Dou, Z., Xin, H. ... Wang, G. (2025). Thyroid cancer: From molecular insights to therapy (Review). Oncology Letters, 30, 520. https://doi.org/10.3892/ol.2025.15266
MLA
Li, Z., Wang, N., Li, X., Xie, Y., Dou, Z., Xin, H., Lin, Y., Si, Y., Feng, T., Wang, G."Thyroid cancer: From molecular insights to therapy (Review)". Oncology Letters 30.5 (2025): 520.
Chicago
Li, Z., Wang, N., Li, X., Xie, Y., Dou, Z., Xin, H., Lin, Y., Si, Y., Feng, T., Wang, G."Thyroid cancer: From molecular insights to therapy (Review)". Oncology Letters 30, no. 5 (2025): 520. https://doi.org/10.3892/ol.2025.15266
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