Skip to content
2000
image of Dysregulation of the cAMP Signaling Pathway Mediated by Shared Hub Genes: Diagnostic, Prognostic, and Therapeutic Insights into Thyroid Cancer and Graves' Disease

Abstract

Background

Graves' disease and thyroid cancer share overlapping molecular mechanisms that may reveal potential biomarkers and therapeutic targets. Identifying shared hub genes can provide insights into disease progression and improve diagnostic and therapeutic strategies.

Methodology

Gene expression profiles from Graves' disease (GSE71956) and thyroid cancer (GSE153659) datasets were analyzed to identify differentially expressed genes using the limma package. Common genes were determined by cross-dataset comparison, and hub genes were identified using the degree method. CD44, RHOC, HCN4, and MYH10 were validated by RT-qPCR in thyroid cancer and normal cell lines, and their roles were examined through siRNA-mediated knockdown. Genetic and epigenetic alterations were explored using OncoDB and cBioPortal, while functional enrichment and prognostic analyses were performed through DAVID, GeneMANIA, GSCA, and cSurvival databases

Results

Twenty-three common genes were identified, among which CD44, RHOC, HCN4, and MYH10 were significantly upregulated in thyroid cancer. These genes were associated with cAMP signaling and epithelial-mesenchymal transition pathways. Knockdown of CD44 and RHOC reduced proliferation, colony formation, and migration in SW579 cells.

Discussion

The findings suggest that the overlap between autoimmune and oncogenic pathways may promote tumor development through dysregulated signaling in cell adhesion, migration, and inflammation. The identified genes act as molecular mediators linking immune activation in Graves' disease with oncogenic progression in thyroid cancer.

Conclusion

CD44, RHOC, HCN4, and MYH10 serve as potential diagnostic and therapeutic biomarkers, offering new insights into shared mechanisms underlying thyroid autoimmune and malignant diseases.

Loading

Article metrics loading...

/content/journals/cchts/10.2174/0113862073389123250723210633
2025-08-06
2025-11-29
Loading full text...

Full text loading...

References

  1. Toro-Tobon D. Stan M MN Graves’ disease and the manifestations of thyrotoxicosis. In: Endotext; MDText.com: South Dartmouth (MA) 2024
    [Google Scholar]
  2. Lanzolla G. Marinò M. Menconi F. Graves disease: Latest understanding of pathogenesis and treatment options. Nat. Rev. Endocrinol. 2024 20 11 647 660 10.1038/s41574‑024‑01016‑5 39039206
    [Google Scholar]
  3. Aulanniam; Rudijanto, A.; Wijaya, A.B. Advances in thyroid peroxidase (TPO) and thyroid stimulating hormone receptor (TSHR) biomarkers for autoimmune thyroid diseases. Acta. Biochimica Indonesiana 2024 7 2 182 10.32889/actabioina.182
    [Google Scholar]
  4. Pinto C.M. Romero J.L.G. Carrasco M.G. Graves’ disease. In:Autoimmune Disease Diagnosis: Systemic and Organ-specific Diseases. Springer 2025 355 360
    [Google Scholar]
  5. Achonu C.U. Olopade O.B. Yusuf B.O. Fadeyi A.A. Fasanmade O.A. Case report of Graves’ disease in a 45-year-old woman secondary to herceptin treatment for breast cancer. Monoclon. Antib. Immunodiagn. Immunother. 2023 42 6 194 202 10.1089/mab.2023.0011 38156888
    [Google Scholar]
  6. Harahap A.S. Jung C.K. Cytologic hallmarks and differential diagnosis of papillary thyroid carcinoma subtypes. J. Pathol. Transl. Med. 2024 58 6 265 282 10.4132/jptm.2024.10.11 39557408
    [Google Scholar]
  7. Sakr M. Malignant thyroid disease. In:Head and Neck and Endocrine Surgery: From Clinical Presentation to Treatment Success. Springer 2024 341 404 10.1007/978‑3‑031‑64102‑2_13
    [Google Scholar]
  8. Lavikainen P.T. Lehtimäki A-V. Heiskanen J. Luoto R.M. Ademi Z. Martikainen J.A. The impact of chronic conditions on productivity-adjusted life-years in both the workplace and household settings in the general adult population in Finland. Value Health 2024 39426512
    [Google Scholar]
  9. Kim J. Gosnell J.E. Roman S.A. Geographic influences in the global rise of thyroid cancer. Nat. Rev. Endocrinol. 2020 16 1 17 29 10.1038/s41574‑019‑0263‑x 31616074
    [Google Scholar]
  10. Khan M. Hameed Y. Discovery of novel six genes-based cervical cancer-associated biomarkers that are capable to break the heterogeneity barrier and applicable at the global level. J. Cancer Res. Ther. 2023
    [Google Scholar]
  11. Abdel-Maksoud M.A. Ullah S. Nadeem A. Shaikh A. Zia M.K. Zakri A.M. Almanaa T.N. Alfuraydi A.A. Mubarak A. Hameed Y. Unlocking the diagnostic, prognostic roles, and immune implications of BAX gene expression in pan-cancer analysis. Am. J. Transl. Res. 2024 16 1 63 74 10.62347/TWOY1681 38322551
    [Google Scholar]
  12. Yanagawa T. Hidaka Y. Guimaraes V. Soliman M. DeGroot L.J. CTLA-4 gene polymorphism associated with Graves’ disease in a Caucasian population. J. Clin. Endocrinol. Metab. 1995 80 1 41 45 7829637
    [Google Scholar]
  13. Li-qun G. Wei Z. Shuang-xia Z. Lin Z. Min-jia Z. Bin C. Huai-dong S. Guang N. Yong-ju Z. Clinical associations of the genetic variants of CTLA‐4, Tg, TSHR, PTPN22, PTPN12 and FCRL3 in patients with Graves’ disease. Clin. Endocrinol. (Oxf.) 2010 72 2 248 255 10.1111/j.1365‑2265.2009.03617.x 19438904
    [Google Scholar]
  14. Pastuszak-Lewandoska D. Sewerynek E. Domańska D. Gładyś A. Skrzypczak R. Brzeziańska E. CTLA-4 gene polymorphisms and their influence on predisposition to autoimmune thyroid diseases (Graves’ disease and Hashimoto’s thyroiditis). Arch. Med. Sci. 2012 3 3 415 421 10.5114/aoms.2012.28593 22851994
    [Google Scholar]
  15. Crescenzi E. Leonardi A. Pacifico F. NF-κB in thyroid cancer: An update. Int. J. Mol. Sci. 2024 25 21 11464 10.3390/ijms252111464 39519020
    [Google Scholar]
  16. Landa I. Cabanillas M.E. Genomic alterations in thyroid cancer: Biological and clinical insights. Nat. Rev. Endocrinol. 2024 20 2 93 110 10.1038/s41574‑023‑00920‑6 38049644
    [Google Scholar]
  17. Ogunjobi T.T. Ohaeri P.N. Akintola O.T. Atanda D.O. Orji F.P. Adebayo J.O. Bioinformatics applications in chronic diseases: A comprehensive review of genomic, transcriptomics, proteomic, metabolomics, and machine learning approaches. Medinformatics 2024 1 17 10.47852/bonviewMEDIN42022335
    [Google Scholar]
  18. Clark A.J. Lillard J.W. A comprehensive review of bioinformatics tools for genomic biomarker discovery driving precision oncology. Genes (Basel) 2024 15 8 1036 10.3390/genes15081036 39202397
    [Google Scholar]
  19. Stefan M. Wei C. Lombardi A. Li C.W. Concepcion E.S. Inabnet W.B. Owen R. Zhang W. Tomer Y. Genetic–epigenetic dysregulation of thymic TSH receptor gene expression triggers thyroid autoimmunity. Proc. Natl. Acad. Sci. USA 2014 111 34 12562 12567 10.1073/pnas.1408821111 25122677
    [Google Scholar]
  20. Lee H.J. Stefan-Lifshitz M. Li C.W. Tomer Y. Genetics and epigenetics of autoimmune thyroid diseases: Translational implications. Best Pract. Res. Clin. Endocrinol. Metab. 2023 37 2 101661 10.1016/j.beem.2022.101661 35459628
    [Google Scholar]
  21. Huang L. Irshad S. Sultana U. Ali S. Jamil A. Zubair A. Sultan R. Abdel-Maksoud M.A. Mubarak A. Almunqedhi B.M. Almanaa T.N. Malik A. Alamri A. Kodous A.S. Mares M. Zaky M.Y. Saba Sajjad S. Hameed Y. Pan-cancer analysis of HS6ST2: Associations with prognosis, tumor immunity, and drug resistance. Am. J. Transl. Res. 2024 16 3 873 888 10.62347/NCPH5416 38586106
    [Google Scholar]
  22. Hameed Y. Decoding the significant diagnostic and prognostic importance of maternal embryonic leucine zipper kinase in human cancers through deep integrative analyses. J. Cancer Res. Ther. 2023 19 7 1852 1864 10.4103/jcrt.jcrt_1902_21 38376289
    [Google Scholar]
  23. Hameed Y. Ejaz S. Integrative analysis of multi-omics data highlighted TP53 as a potential diagnostic and prognostic biomarker of survival in breast invasive carcinoma patients. Comput. Biol. Chem. 2021 92 107457 10.1016/j.compbiolchem.2021.107457 33610131
    [Google Scholar]
  24. Karamat U. Ejaz S. Hameed Y. In silico-analysis of the multi-omics data identified the ataxia telangiectasia mutated gene as a potential biomarker of breast invasive carcinoma. Genet. Test. Mol. Biomarkers 2021 25 4 263 275 10.1089/gtmb.2020.0249 33877897
    [Google Scholar]
  25. Jiang F. Ahmad S. kanwal, S.; Hameed, Y.; Tang, Q. Key wound healing genes as diagnostic biomarkers and therapeutic targets in uterine corpus endometrial carcinoma: An integrated in silico and in vitro study. Hereditas 2025 162 1 5 10.1186/s41065‑025‑00369‑9 39833941
    [Google Scholar]
  26. Sial N. Ahmad M. Hussain M.S. Iqbal M.J. Hameed Y. Khan M. Abbas M. Asif R. Rehman J.U. Atif M. Khan M.R. Hameed Z. Saeed H. Tanveer R. Saeed S. Sharif A. Asif H.M. CTHRC1 expression is a novel shared diagnostic and prognostic biomarker of survival in six different human cancer subtypes. Sci. Rep. 2021 11 1 19873 10.1038/s41598‑021‑99321‑w 34615943
    [Google Scholar]
  27. Clough E. Barrett T. The Gene Expression Omnibus database. Methods Mol. Biol. 2016 1418 93 110 10.1007/978‑1‑4939‑3578‑9_5
    [Google Scholar]
  28. Ritchie M.E. Phipson B. Wu D. Hu Y. Law C.W. Shi, W limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015 43 7 e47
    [Google Scholar]
  29. Szklarczyk D. Kirsch R. Koutrouli M. Nastou K. Mehryary F. Hachilif R. Gable A.L. Fang T. Doncheva N.T. Pyysalo S. Bork P. Jensen L.J. von Mering C. The STRING database in 2023: Protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023 51 D1 D638 D646 10.1093/nar/gkac1000 36370105
    [Google Scholar]
  30. Livak K.J. Schmittgen T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 2001 25 4 402 408 10.1006/meth.2001.1262
    [Google Scholar]
  31. Liu C.J. Hu F.F. Xie G.Y. Miao Y.R. Li X.W. Zeng Y. Guo A.Y. GSCA: An integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels. Brief. Bioinform. 2023 24 1 bbac558 10.1093/bib/bbac558 36549921
    [Google Scholar]
  32. Tang G. Cho M. Wang X. Onco D.B. An interactive online database for analysis of gene expression and viral infection in cancer. Nucleic Acids Res. 2022 50 D1 D1334 D1339 10.1093/nar/gkab970 34718715
    [Google Scholar]
  33. Cerami E. Gao J. Dogrusoz U. Gross B.E. Sumer S.O. Aksoy B.A. Jacobsen A. Byrne C.J. Heuer M.L. Larsson E. Antipin Y. Reva B. Goldberg A.P. Sander C. Schultz N. The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012 2 5 401 404 10.1158/2159‑8290.CD‑12‑0095 22588877
    [Google Scholar]
  34. Cheng X. Liu Y. Wang J. Chen Y. Robertson A.G. Zhang X. Jones S.J.M. Taubert S. cSurvival: A web resource for biomarker interactions in cancer outcomes and in cell lines. Brief. Bioinform. 2022 23 3 bbac090 10.1093/bib/bbac090 35368077
    [Google Scholar]
  35. Park S.J. Yoon B.H. Kim S.K. Kim S.Y. GENT2: An updated gene expression database for normal and tumor tissues. BMC Med. Genomics 2019 12 S5 101 10.1186/s12920‑019‑0514‑7 31296229
    [Google Scholar]
  36. Warde-Farley D. Donaldson S.L. Comes O. Zuberi K. Badrawi R. Chao P. Franz M. Grouios C. Kazi F. Lopes C.T. Maitland A. Mostafavi S. Montojo J. Shao Q. Wright G. Bader G.D. Morris Q. The GeneMANIA prediction server: Biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010 38 W214 W220 10.1093/nar/gkq537 20576703
    [Google Scholar]
  37. Sherman B.T. Hao M. Qiu J. Jiao X. Baseler M.W. Lane H.C. Imamichi T. Chang W. DAVID: A web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res. 2022 50 W1 W216 W221 10.1093/nar/gkac194 35325185
    [Google Scholar]
  38. Agarwal V. Bell G.W. Nam J.W. Bartel D.P. Predicting effective microRNA target sites in mammalian mRNAs. eLife 2015 4 4 05005 10.7554/eLife.05005 26267216
    [Google Scholar]
  39. Livingston E.H. Who was student and why do we care so much about his t-test?1. J. Surg. Res. 2004 118 1 58 65 10.1016/j.jss.2004.02.003 15093718
    [Google Scholar]
  40. Sedgwick P. One way analysis of variance: Post hoc testing. BMJ 2014 349 2 g7067 10.1136/bmj.g7067 25416414
    [Google Scholar]
  41. Marcet Rius M. Pageat P. Bienboire-Frosini C. Teruel E. Monneret P. Leclercq J. Lafont-Lecuelle C. Cozzi A. Tail and ear movements as possible indicators of emotions in pigs. Appl. Anim. Behav. Sci. 2018 205 14 18 10.1016/j.applanim.2018.05.012
    [Google Scholar]
  42. Jin B. Xu X. Carbon emission allowance price forecasting for China Guangdong carbon emission exchange via the neural network. Glob. Finance Rev. 2024 6 1 3491 10.18282/gfr.v6i1.3491
    [Google Scholar]
  43. Jin B. Xu X. Machine learning predictions of regional steel price indices for east China. Ironmak. Steelmak. 2024 52 3 03019233241254891 10.1177/03019233241254891
    [Google Scholar]
  44. Jin B. Xu X. Pre-owned housing price index forecasts using Gaussian process regressions. J. Model. Manag. 2024 19 6 1927 1958 10.1108/JM2‑12‑2023‑0315
    [Google Scholar]
  45. Sriwastava A.K. Role of epigenetics in breast cancer: Current status and future perspectives. In:Advances in Cancer Biomarkers Research. Academic Press 2025 191 204 10.1016/B978‑0‑323‑95258‑3.00011‑4
    [Google Scholar]
  46. Li M. Dal Maso L. Pizzato M. Vaccarella S. Evolving epidemiological patterns of thyroid cancer and estimates of overdiagnosis in 2013–17 in 63 countries worldwide: A population-based study. Lancet Diabetes Endocrinol. 2024 12 11 824 836 10.1016/S2213‑8587(24)00223‑7 39389067
    [Google Scholar]
  47. Moleti M. Aversa T. Crisafulli S. Trifirò G. Corica D. Pepe G. Cannavò L. Di Mauro M. Paola G. Fontana A. Calapai F. Cannavò S. Wasniewska M. Global incidence and prevalence of differentiated thyroid cancer in childhood: Systematic review and meta-analysis. Front. Endocrinol. 2023 14 1270518 10.3389/fendo.2023.1270518 37795368
    [Google Scholar]
  48. Vargas-Uricoechea H. Molecular mechanisms in autoimmune thyroid disease. Cells 2023 12 6 918 10.3390/cells12060918 36980259
    [Google Scholar]
  49. Carlucci P. Spataro F. Cristallo M. Di Gioacchino M. Nettis E. Gangemi S. immune-molecular link between thyroid and skin autoimmune diseases: A narrative review. J. Clin. Med. 2024 13 18 5594 10.3390/jcm13185594 39337081
    [Google Scholar]
  50. Nozhat Z. Hedayati M. PI3K/AKT pathway and its mediators in thyroid carcinomas. Mol. Diagn. Ther. 2016 20 1 13 26 10.1007/s40291‑015‑0175‑y 26597586
    [Google Scholar]
  51. Kustrimovic N. Gallo D. Piantanida E. Bartalena L. Lai A. Zerbinati N. Tanda M.L. Mortara L. Regulatory T cells in the pathogenesis of Graves’ disease. Int. J. Mol. Sci. 2023 24 22 16432 10.3390/ijms242216432 38003622
    [Google Scholar]
  52. Morshed S.A. Latif R. Davies T.F. Delineating the autoimmune mechanisms in Graves’ disease. Immunol. Res. 2012 54 1-3 191 203 10.1007/s12026‑012‑8312‑8 22434518
    [Google Scholar]
  53. Crosas-Molist E. Samain R. Kohlhammer L. Orgaz J.L. George S.L. Maiques O. Barcelo J. Sanz-Moreno V. Rho GTPase signaling in cancer progression and dissemination. Physiol. Rev. 2022 102 1 455 510 10.1152/physrev.00045.2020 34541899
    [Google Scholar]
  54. Ouhtit A. Rizeq B. Saleh H.A. Rahman M.D.M. Zayed H. Novel CD44-downstream signaling pathways mediating breast tumor invasion. Int. J. Biol. Sci. 2018 14 13 1782 1790 10.7150/ijbs.23586 30443182
    [Google Scholar]
  55. Fang M. Wu J. Lai X. Ai H. Tao Y. Zhu B. Huang L. CD44 and CD44v6 are correlated with gastric cancer progression and poor patient prognosis: Evidence from 42 studies. Cell. Physiol. Biochem. 2016 40 3-4 567 578 10.1159/000452570 27889771
    [Google Scholar]
  56. Kim M.S. Lee J. Sidransky D. DNA methylation markers in colorectal cancer. Cancer Metastasis Rev. 2010 29 1 181 206 10.1007/s10555‑010‑9207‑6 20135198
    [Google Scholar]
  57. Joshua B. Kaplan M.J. Doweck I. Pai R. Weissman I.L. Prince M.E. Ailles L.E. Frequency of cells expressing CD44, a Head and Neck cancer stem cell marker: Correlation with tumor aggressiveness. Head Neck 2012 34 1 42 49 10.1002/hed.21699 21322081
    [Google Scholar]
  58. Li L. Qi L. Liang Z. Song W. Liu Y. Wang Y. Sun B. Zhang B. Cao W. Transforming growth factor-β1 induces EMT by the transactivation of epidermal growth factor signaling through HA/CD44 in lung and breast cancer cells. Int. J. Mol. Med. 2015 36 1 113 122 10.3892/ijmm.2015.2222 26005723
    [Google Scholar]
  59. Choi C. Thi Thao Tran N. Van Ngu T. Park S.W. Song M.S. Kim S.H. Bae Y.U. Ayudthaya P.D.N. Munir J. Kim E. Baek M.J. Song S. Ryu S. Nam K.H. Promotion of tumor progression and cancer stemness by MUC15 in thyroid cancer via the GPCR/ERK and integrin-FAK signaling pathways. Oncogenesis 2018 7 11 85 10.1038/s41389‑018‑0094‑y 30420637
    [Google Scholar]
  60. Murugan A.K. Qasem E. Al-Hindi H. Alzahrani A.S. GPCR-mediated PI3K pathway mutations in pediatric and adult thyroid cancer. Oncotarget 2019 10 41 4107 4124 10.18632/oncotarget.26993 31289610
    [Google Scholar]
  61. Li L. Mou Y.P. Wang Y.Y. Wang H.J. Mou X.Z. miR-199a-3p targets ETNK1 to promote invasion and migration in gastric cancer cells and is associated with poor prognosis. Pathol. Res. Pract. 2019 215 9 152511 10.1016/j.prp.2019.152511 31255331
    [Google Scholar]
  62. Mancini M. Grasso M. Muccillo L. Babbio F. Precazzini F. Castiglioni I. Zanetti V. Rizzo F. Pistore C. De Marino M.G. Zocchi M. Del Vescovo V. Licursi V. Giurato G. Weisz A. Chiarugi P. Sabatino L. Denti M.A. Bonapace I.M. DNMT3A epigenetically regulates key microRNAs involved in epithelial-to-mesenchymal transition in prostate cancer. Carcinogenesis 2021 42 12 1449 1460 10.1093/carcin/bgab101
    [Google Scholar]
  63. Ren Y. Qian Y. Zhang Q. Li X. Li M. Li W. Yang P. Ren H. Li H. Weng Y. Li D. Xu K. Yu W. High LGALS3 expression induced by HCP5/hsa-miR-27b-3p correlates with poor prognosis and tumor immune infiltration in hepatocellular carcinoma. Cancer Cell Int. 2024 24 1 142 10.1186/s12935‑024‑03309‑1 38643145
    [Google Scholar]
  64. He S. Li Z. Yu Y. Zeng Q. Cheng Y. Ji W. Xia W. Lu S. Exosomal miR-499a-5p promotes cell proliferation, migration and EMT via mTOR signaling pathway in lung adenocarcinoma. Exp. Cell Res. 2019 379 2 203 213 10.1016/j.yexcr.2019.03.035 30978341
    [Google Scholar]
  65. Fornari F. Milazzo M. Chieco P. Negrini M. Calin G.A. Grazi G.L. Pollutri D. Croce C.M. Bolondi L. Gramantieri L. MiR-199a-3p regulates mTOR and c-Met to influence the doxorubicin sensitivity of human hepatocarcinoma cells. Cancer Res. 2010 70 12 5184 5193 10.1158/0008‑5472.CAN‑10‑0145 20501828
    [Google Scholar]
  66. Choi D.W. Cho K.A. Kim J. Lee H.J. Kim Y.H. Park J.W. Woo S.Y. Extracellular vesicles from tonsil derived mesenchymal stromal cells show anti tumor effect via miR 199a 3p. Int. J. Mol. Med. 2021 48 6 221 10.3892/ijmm.2021.5054 34676871
    [Google Scholar]
  67. Gao Y. Foster R. Yang X. Feng Y. Shen J.K. Mankin H.J. Hornicek F.J. Amiji M.M. Duan Z. Up-regulation of CD44 in the development of metastasis, recurrence and drug resistance of ovarian cancer. Oncotarget 2015 6 11 9313 9326 10.18632/oncotarget.3220 25823654
    [Google Scholar]
  68. Horiuchi A. Imai T. Wang C. Ohira S. Feng Y. Nikaido T. Konishi I. Up-regulation of small GTPases, RhoA and RhoC, is associated with tumor progression in ovarian carcinoma. Lab. Invest. 2003 83 6 861 870 10.1097/01.LAB.0000073128.16098.31 12808121
    [Google Scholar]
  69. Kim J.S. Kurie J.M. Ahn Y.H. BMP4 depletion by miR-200 inhibits tumorigenesis and metastasis of lung adenocarcinoma cells. Mol. Cancer 2015 14 1 173 10.1186/s12943‑015‑0441‑y 26395571
    [Google Scholar]
  70. Phan N.N. Huynh T.T. Lin Y.C. Hyperpolarization-activated cyclic nucleotide-gated gene signatures and poor clinical outcome of cancer patient. Transl. Cancer Res. 2017 6 4 698 708 10.21037/tcr.2017.07.22
    [Google Scholar]
  71. Pham P.V. Phan N.L.C. Nguyen N.T. Truong N.H. Duong T.T. Le D.V. Truong K.D. Phan N.K. Differentiation of breast cancer stem cells by knockdown of CD44: promising differentiation therapy. J. Transl. Med. 2011 9 1 209 10.1186/1479‑5876‑9‑209 22152097
    [Google Scholar]
  72. Lou Y. Jiang Y. Liang Z. Liu B. Li T. Zhang D. Role of RhoC in cancer cell migration. Cancer Cell Int. 2021 21 1 527 10.1186/s12935‑021‑02234‑x 34627249
    [Google Scholar]
  73. Bourguignon L.Y.W. Gilad E. Brightman A. Diedrich F. Singleton P. Hyaluronan-CD44 interaction with leukemia-associated RhoGEF and epidermal growth factor receptor promotes Rho/Ras co-activation, phospholipase C ϵ-Ca2+ signaling, and cytoskeleton modification in head and neck squamous cell carcinoma cells. J. Biol. Chem. 2006 281 20 14026 14040 10.1074/jbc.M507734200 16565089
    [Google Scholar]
  74. Xu H. Niu M. Yuan X. Wu K. Liu A. CD44 as a tumor biomarker and therapeutic target. Exp. Hematol. Oncol. 2020 9 1 36 10.1186/s40164‑020‑00192‑0 33303029
    [Google Scholar]
  75. Thomas P. Pranatharthi A. Ross C. Srivastava S. Rho C. A fascinating journey from a cytoskeletal organizer to a Cancer stem cell therapeutic target. J. Exp. Clin. Cancer Res. 2019 38 1 328 10.1186/s13046‑019‑1327‑4 31340863
    [Google Scholar]
  76. Kim H.T. Yin W. Jin Y.J. Panza P. Gunawan F. Grohmann B. Buettner C. Sokol A.M. Preussner J. Guenther S. Kostin S. Ruppert C. Bhagwat A.M. Ma X. Graumann J. Looso M. Guenther A. Adelstein R.S. Offermanns S. Stainier D.Y.R. Myh10 deficiency leads to defective extracellular matrix remodeling and pulmonary disease. Nat. Commun. 2018 9 1 4600 10.1038/s41467‑018‑06833‑7 30389913
    [Google Scholar]
  77. Servatius H. Porro A. Pless S.A. Schaller A. Asatryan B. Tanner H. de Marchi S.F. Roten L. Seiler J. Haeberlin A. Baldinger S.H. Noti F. Lam A. Fuhrer J. Moroni A. Medeiros-Domingo A. Phenotypic spectrum of HCN4 mutations: A clinical case. Circ. Genom. Precis. Med. 2018 11 2 002033 10.1161/CIRCGEN.117.002033 29440115
    [Google Scholar]
/content/journals/cchts/10.2174/0113862073389123250723210633
Loading
/content/journals/cchts/10.2174/0113862073389123250723210633
Loading

Data & Media loading...


  • Article Type:
    Research Article
Keywords: biomarker ; Graves' disease ; diagnosis ; therapeutic target ; c-AMP signaling ; thyroid cancer
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test