Open Access

Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin

  • Authors:
    • Sheng Zhong
    • Bo Wu
    • Xinhui Wang
    • Dandan Sun
    • Daqun Liu
    • Shanshan Jiang
    • Junliang Ge
    • Yuan Zhang
    • Xinrui Liu
    • Xiaoli Zhou
    • Rihua Jin
    • Yong Chen
  • View Affiliations

  • Published online on: July 18, 2019     https://doi.org/10.3892/mmr.2019.10505
  • Pages: 2712-2724
  • Copyright: © Zhong et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The purpose of the present study was to identify the potential targets and markers for diagnosis, therapy and prognosis in patients with prolactinoma at the molecular level and to determine the therapeutic effects of genipin in prolactinoma. The gene expression profiles of GSE2175, GSE26966 and GSE36314 were obtained from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified after comparing between gene expression profiles of the prolactinoma tissues and normal tissues. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein‑protein interaction (PPI) network analysis were conducted. In addition, in vitro, scratch assay, colony‑forming assay, Cell Counting Kit 8 (CCK8) assay and flow cytometry were performed to verify the functional effects of genipin. An aggregate of 12,695, 3,847 and 5,310 DEGs were identified from GSE2175, GSE26966 and GSE36314, respectively. The results of GO and KEGG analysis showed that the DEGs significant and important for prolactinoma were mostly involved with ‘spindle pole’ and ‘oocyte meiosis’. A total of 20 genes were selected as hub genes with high degrees after PPI network analysis, including mitogen‑activated protein kinase 1 (MAPK1), MYC, early growth response 1 (EGR1), Bcl2 and calmodulin 1 (CALM1). CCK8 assay, colony‑forming assay and scratch assay were performed to verify the anti‑prolactinoma effect of genipin. The results of flow cytometry showed that apoptosis was increased by genipin. MAPK1, MYC, EGR1, Bcl2 and CALM1 were screened as main hub genes. Genipin upregulated the expression level of EGR1 and p21 (downstream mediator of EGR1) and EGR1, inhibited the proliferation and migration of prolactinoma cells. Genipin is a promising drug for treatment of patients with prolactinoma.

References

1 

Theodros D, Patel M, Ruzevick J, Lim M and Bettegowda C: Pituitary adenomas: Historical perspective, surgical management and future directions. CNS Oncol. 4:411–429. 2015. View Article : Google Scholar : PubMed/NCBI

2 

Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P and Ellison DW: The 2016 world health organization classification of tumors of the central nervous system: A summary. Acta Neuropathol. 131:803–820. 2016. View Article : Google Scholar : PubMed/NCBI

3 

Hirohata T, Ishii Y and Matsuno A: Treatment of pituitary carcinomas and atypical pituitary adenomas: A review. Neurol Med Chir (Tokyo). 54:966–973. 2014. View Article : Google Scholar : PubMed/NCBI

4 

Sinha S, Sharma BS and Mahapatra AK: Microsurgical management of prolactinomas-clinical and hormonal outcome in a series of 172 cases. Neurol India. 59:532–536. 2011. View Article : Google Scholar : PubMed/NCBI

5 

Manuylova E, Calvi LM, Hastings C, Vates GE, Johnson MD, Cave WT Jr and Shafiq I: Late presentation of acromegaly in medically controlled prolactinoma patients. Endocrinol Diabetes Metab Case Rep. 2016(pii): 16–0069. 2016.PubMed/NCBI

6 

Ghadirian H, Shirani M, Ghazi-Mirsaeed S, Mohebi S and Alimohamadi M: Pituitary apoplexy during treatment of prolactinoma with cabergoline. Asian J Neurosurg. 13:93–95. 2018. View Article : Google Scholar : PubMed/NCBI

7 

Chng E and Dalan R: Pituitary apoplexy associated with cabergoline therapy. J Clin Neurosci. 20:1637–1643. 2013. View Article : Google Scholar : PubMed/NCBI

8 

Nakhleh A, Shehadeh N, Hochberg I, Zloczower M, Zolotov S, Taher R and Daoud Naccache D: Management of cystic prolactinomas: A review. Pituitary. 21:425–430. 2018. View Article : Google Scholar : PubMed/NCBI

9 

Zhou W, Ma C and Yan Z: Microarray data analysis reveals differentially expressed genes in prolactinoma. Neoplasma. 62:53–60. 2015. View Article : Google Scholar : PubMed/NCBI

10 

Zhao L, Lin M and Wang S: Identification of human prolactinoma related genes by DNA microarray. J Cancer Res Ther. 10:544–548. 2014.PubMed/NCBI

11 

Zhan X, Wang X and Cheng T: Human pituitary adenoma proteomics: New progresses and perspectives. Front Endocrinol (Lausanne). 7:542016. View Article : Google Scholar : PubMed/NCBI

12 

Zhang W, Zang Z, Song Y, Yang H and Yin Q: Co-expression network analysis of differentially expressed genes associated with metastasis in prolactin pituitary tumors. Mol Med Rep. 10:113–118. 2014. View Article : Google Scholar : PubMed/NCBI

13 

Faraoni EY, Camilletti MA, Abeledo-Machado A, Ratner LD, De Fino F, Huhtaniemi I, Rulli SB and Díaz-Torga G: Sex differences in the development of prolactinoma in mice overexpressing hCGβ: Role of TGFβ1. J Endocrinol. 232:535–546. 2017. View Article : Google Scholar : PubMed/NCBI

14 

Ko H, Kim JM, Kim SJ, Shim SH, Ha CH and Chang HI: Induction of apoptosis by genipin inhibits cell proliferation in AGS human gastric cancer cells via Egr1/p21 signaling pathway. Bioorg Med Chem Lett. 25:4191–4196. 2015. View Article : Google Scholar : PubMed/NCBI

15 

Xu Z, Zhou Y, Cao Y, Dinh TL, Wan J and Zhao M: Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis. Med Oncol. 33:1302016. View Article : Google Scholar : PubMed/NCBI

16 

Morris DG, Musat M, Czirják S, Hanzély Z, Lillington DM, Korbonits M and Grossman AB: Differential gene expression in pituitary adenomas by oligonucleotide array analysis. Eur J Endocrinol. 153:143–151. 2005. View Article : Google Scholar : PubMed/NCBI

17 

Michaelis KA, Knox AJ, Xu M, Kiseljak-Vassiliades K, Edwards MG, Geraci M, Kleinschmidt-DeMasters BK, Lillehei KO and Wierman ME: Identification of growth arrest and DNA-damage-inducible gene beta (GADD45beta) as a novel tumor suppressor in pituitary gonadotrope tumors. Endocrinology. 152:3603–3613. 2011. View Article : Google Scholar : PubMed/NCBI

18 

Tong Y, Zheng Y, Zhou J, Oyesiku NM, Koeffler HP and Melmed S: Genomic characterization of human and rat prolactinomas. Endocrinology. 153:3679–3691. 2012. View Article : Google Scholar : PubMed/NCBI

19 

Abdul Aziz NA, Mokhtar NM, Harun R, Mollah MM, Mohamed Rose I, Sagap I, Mohd Tamil A, Wan Ngah WZ and Jamal R: A 19-Gene expression signature as a predictor of survival in colorectal cancer. BMC Med Genomics. 9:582016. View Article : Google Scholar : PubMed/NCBI

20 

Huang DW, Sherman BT and Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nat Protoc. 4:44–57. 2009. View Article : Google Scholar : PubMed/NCBI

21 

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B and Ideker T: Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13:2498–2504. 2003. View Article : Google Scholar : PubMed/NCBI

22 

Franken NA, Rodermond HM, Stao J, Haveman J and van Bree C: Clonogenic assay of cells in vitro. Nat Protoc. 1:2315–2319. 2006. View Article : Google Scholar : PubMed/NCBI

23 

Cooper O, Mamelak A, Bannykh S, Carmichael J, Bonert V, Lim S, Cook-Wiens G and Ben-Shlomo A: Prolactinoma ErbB receptor expression and targeted therapy for aggressive tumors. Endocrine. 46:318–327. 2014. View Article : Google Scholar : PubMed/NCBI

24 

Castro-Ferreira R, Neves JS, Ladeiras-Lopes R, Leite- Moreira AM, Neiva-Sousa M, Almeida-Coelho J, Ferreira-Martins J and F Leite-Moreira A: Revisiting the slow force response: The role of the PKG signaling pathway in the normal and the ischemic heart. Rev Port Cardiol. 33:493–499. 2014. View Article : Google Scholar : PubMed/NCBI

25 

Hou J and Kang YJ: Regression of pathological cardiac hypertrophy: Signaling pathways and therapeutic targets. Pharmacol Ther. 135:337–354. 2012. View Article : Google Scholar : PubMed/NCBI

26 

Babykutty S, Suboj P, Srinivas P, Nair AS, Chandramohan K and Gopala S: Insidious role of nitric oxide in migration/invasion of colon cancer cells by upregulating MMP-2/9 via activation of cGMP-PKG-ERK signaling pathways. Clin Exp Metastasis. 29:471–492. 2012. View Article : Google Scholar : PubMed/NCBI

27 

Browning DD, Kwon IK and Wang R: cGMP-dependent protein kinases as potential targets for colon cancer prevention and treatment. Future Med Chem. 2:65–80. 2010. View Article : Google Scholar : PubMed/NCBI

28 

Riquelme I, Tapia O, Espinoza JA, Leal P, Buchegger K, Sandoval A, Bizama C, Araya JC, Peek RM and Roa JC: The Gene Expression Status of the PI3K/AKT/mTOR pathway in gastric cancer tissues and cell lines. Pathol Oncol Res. 22:797–805. 2016. View Article : Google Scholar : PubMed/NCBI

29 

Guo H, German P, Bai S, Barnes S, Guo W, Qi X, Lou H, Liang J, Jonasch E, Mills GB and Ding Z: The PI3K/AKT pathway and renal cell carcinoma. J Genet Genomics. 42:343–353. 2015. View Article : Google Scholar : PubMed/NCBI

30 

Wu Y, Yuan M, Su W, Zhu M, Yao X, Wang Y, Qian H, Jiang L, Tao Y, Wu M, et al: The constitutively active PKG II mutant effectively inhibits gastric cancer development via a blockade of EGF/EGFR-associated signalling cascades. Ther Adv Med Oncol. 10:17588340177516352018. View Article : Google Scholar : PubMed/NCBI

31 

Chauvin TR, Herndon MK and Nilson JH: Cold-shock-domain protein A (CSDA) contributes posttranscriptionally to gonadotropin-releasing hormone-regulated expression of Egr1 and indirectly to Lhb. Biol Reprod. 86:532012. View Article : Google Scholar : PubMed/NCBI

32 

Kim ES, Jeong CS and Moon A: Genipin, a constituent of Gardenia jasminoides Ellis, induces apoptosis and inhibits invasion in MDA-MB-231 breast cancer cells. Oncol Rep. 27:567–572. 2012.PubMed/NCBI

33 

Wang R, MoYung KC, Zhao YJ and Poon K: A mechanism for the temporal potentiation of genipin to the cytotoxicity of cisplatin in colon cancer cells. Int J Med Sci. 13:507–516. 2016. View Article : Google Scholar : PubMed/NCBI

34 

Santarpia L, Lippman SM and El-Naggar AK: Targeting the MAPK-RAS-RAF signaling pathway in cancer therapy. Expert Opin Ther Targets. 16:103–119. 2012. View Article : Google Scholar : PubMed/NCBI

35 

Hu L, Wu H, Wan X, Liu L, He Y, Zhu L, Liu S, Yao H and Zhu Z: MicroRNA-585 suppresses tumor proliferation and migration in gastric cancer by directly targeting MAPK1. Biochem Biophys Res Commun. 499:52–58. 2018. View Article : Google Scholar : PubMed/NCBI

36 

Li C, Sun Z, Gui S, Liu F and Zhang Y: Effects of fulvestrant, an estrogen receptor antagonist, on MMQ cells and its mechanism. Neuro Endocrinol Lett. 30:268–274. 2009.PubMed/NCBI

37 

Tu WB, Helander S, Pilstål R, Hickman KA, Lourenco C, Jurisica I, Raught B, Wallner B, Sunnerhagen M and Penn LZ: Myc and its interactors take shape. Biochim Biophys Acta. 1849:469–483. 2015. View Article : Google Scholar : PubMed/NCBI

38 

Kim EY, Kim A, Kim SK and Chang YS: MYC expression correlates with PD-L1 expression in non-small cell lung cancer. Lung Cancer. 110:63–67. 2017. View Article : Google Scholar : PubMed/NCBI

39 

Li S, Lin P, Young KH, Kanagal-Shamanna R, Yin CC and Medeiros LJ: MYC/Bcl2 double-hit high-grade B-cell lymphoma. Adv Anat Pathol. 20:315–326. 2013. View Article : Google Scholar : PubMed/NCBI

40 

Zhang J, Yao YH, Li BG, Yang Q, Zhang PY and Wang HT: Prognostic value of pretreatment serum lactate dehydrogenase level in patients with solid tumors: A systematic review and meta-analysis. Sci Rep. 5:98002015. View Article : Google Scholar : PubMed/NCBI

41 

Jagani H, Kasinathan N, Meka SR and Josyula VR: Antiapoptotic Bcl-2 protein as a potential target for cancer therapy: A mini review. Artif Cells Nanomed Biotechnol. 44:1212–1221. 2016.PubMed/NCBI

42 

Okubo S, Kurebayashi J, Otsuki T, Yamamoto Y, Tanaka K and Sonoo H: Additive antitumour effect of the epidermal growth factor receptor tyrosine kinase inhibitor gefitinib (Iressa, ZD1839) and the antioestrogen fulvestrant (Faslodex, ICI 182,780) in breast cancer cells. Br J Cancer. 90:236–244. 2014. View Article : Google Scholar

43 

Geng X, Ma L, Li Z, Li Z, Li J, Li M, Wang Q, Chen Z and Sun Q: Bromocriptine induces autophagy-dependent cell death in pituitary adenomas. World Neurosurg. 100:407–416. 2017. View Article : Google Scholar : PubMed/NCBI

44 

Toutenhoofd SL, Foletti D, Wicki R, Rhyner JA, Garcia F, Tolon R and Strehler EE: Characterization of the human CALM2 calmodulin gene and comparison of the transcriptional activity of CALM1, CALM2 and CALM3. Cell Calcium. 23:232–238. 1998. View Article : Google Scholar

45 

Berchtold MW and Villalobo A: The many faces of calmodulin in cell proliferation, programmed cell death, autophagy, and cancer. Biochim Biophys Acta. 1843:398–435. 2014. View Article : Google Scholar : PubMed/NCBI

46 

Hughes A, Oxford AE, Tawara K, Jorcyk CL and Oxford JT: Endoplasmic reticulum stress and unfolded protein response in cartilage pathophysiology; contributing factors to apoptosis and osteoarthritis. Int J Mol Sci. 18(pii): E6652017. View Article : Google Scholar : PubMed/NCBI

47 

Tang MK and Wong AS: Exosomes: Emerging biomarkers and targets for ovarian cancer. Cancer Lett. 367:26–33. 2015. View Article : Google Scholar : PubMed/NCBI

48 

Siegel JM: The neurotransmitters of sleep. J Clin Psychiatry. 65 (Suppl 16):S4–S7. 2004.

49 

Tyson JA and Anderson SA: GABAergic interneuron transplants to study development and treat disease. Trends Neurosci. 37:169–177. 2014. View Article : Google Scholar : PubMed/NCBI

50 

Southwell DG, Nicholas CR, Basbaum AI, Stryker MP, Kriegstein AR, Rubenstein JL and Alvarez-Buylla A: Interneurons from embryonic development to cell-based therapy. Science. 344:12406222014. View Article : Google Scholar : PubMed/NCBI

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Copy and paste a formatted citation
APA
Zhong, S., Wu, B., Wang, X., Sun, D., Liu, D., Jiang, S. ... Chen, Y. (2019). Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin. Molecular Medicine Reports, 20, 2712-2724. https://doi.org/10.3892/mmr.2019.10505
MLA
Zhong, S., Wu, B., Wang, X., Sun, D., Liu, D., Jiang, S., Ge, J., Zhang, Y., Liu, X., Zhou, X., Jin, R., Chen, Y."Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin". Molecular Medicine Reports 20.3 (2019): 2712-2724.
Chicago
Zhong, S., Wu, B., Wang, X., Sun, D., Liu, D., Jiang, S., Ge, J., Zhang, Y., Liu, X., Zhou, X., Jin, R., Chen, Y."Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin". Molecular Medicine Reports 20, no. 3 (2019): 2712-2724. https://doi.org/10.3892/mmr.2019.10505