Identification of differential molecular characteristics and key genes between low- and high-grade serous ovarian cancer by bioinformatics analysis

Background: Serous ovarian cancer (SOC) is classified into high-grade serous ovarian cancer (HGSOC) and low-grade serous ovarian cancer (LGSOC), with HGSOC and LGSOC differing significantly in terms of clinical processes, treatment methods and treatment targets. Herein, we emphasize the importance of ongoing molecular studies to distinguish between HGSOC and LGSOC to improve treatment options for patients with these specific subtypes. Methods: Two gene expression profiles (GSE27651 and GSE73168) from the Gene Expression Omnibus (GEO) database were analyzed using bioinformatics methods, and Metascape and the KEGG Orthology-Based Annotation System (KOBAS) online software were used to identify differentially expressed genes (DEGs) from Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways significantly enriched in HGSOC and LGSOC samples. Results: Our findings revealed that compared to LGSOC, HGSOC exhibited significant upregulation of 265 DEGs mainly associated with the KEGG pathway of p53 signaling and focal adhesion. Additionally, 423 significantly downregulated DEGs were mainly enriched in the KEGG pathway of the chemokine signaling pathway. Among these genes, tumor protein p53 (TP53), tumor protein p53-inducible protein 3 (TP53I3), ferredoxin reductase (FDXR), epidermal growth factor receptor (EGFR) and C-X-C motif chemokine ligand 11 (CXCL11) were identified as key hub genes through Protein-Protein Interaction (PPI) network analysis and ovarian cancer gene and protein expression analysis. Furthermore, we explored the correlation between the expression of these 5 hub genes and various factors, including ovarian cancer prognosis, immune infiltration, ovarian cancer stage, grade, age and drug targets. Conclusions: This study contributes to the understanding of differential signaling molecules between HGSOC and LGSOC, facilitating the transition from a monotherapy approach to a more precise treatment strategy tailored to the specific features of each subtype. Additionally, it provides valuable insights into the differential diagnosis and detection targets for these two types of ovarian cancer.

GEO database; HGSOC; LGSOC; Bioinformatics; Differentially expressed genes

[1] Ma H, Tian T, Cui Z. Targeting ovarian cancer stem cells: a new way out. Stem Cell Research & Therapy. 2023; 14: 28.

[2] Lu W, Xie B, Tan G, Dai W, Ren J, Pervaz S, et al. Elafin is related to immune infiltration and could predict the poor prognosis in ovarian cancer. Frontiers in Endocrinology. 2023; 14: 1088944.

[3] Allemani C, Matsuda T, Di Carlo V, Harewood R, Matz M, Nikšić M, et al. Global surveillance of trends in cancer survival 2000–14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. The Lancet. 2018; 391: 1023–1075.

[4] Miller DS, Blessing JA, Krasner CN, Mannel RS, Hanjani P, Pearl ML, et al. Phase II evaluation of pemetrexed in the treatment of recurrent or persistent platinum-resistant ovarian or primary peritoneal carcinoma: a study of the Gynecologic Oncology Group. Journal of Clinical Oncology. 2009; 27: 2686–2691.

[5] Beaver JA, Coleman RL, Arend RC, Armstrong DK, Bala S, Mills GB, et al. Advancing drug development in gynecologic malignancies. Clinical Cancer Research. 2019; 25: 4874–4880.

[6] Lu H, Liu Y, Wang J, Fu S, Wang L, Huang C, et al. Detection of ovarian cancer using plasma cell-free DNA methylomes. Clinical Epigenetics. 2022; 14: 74.

[7] Lim MC, Chang SJ, Park B, Yoo HJ, Yoo CW, Nam BH, et al. Survival after hyperthermic intraperitoneal chemotherapy and primary or interval cytoreductive surgery in ovarian cancer: a randomized clinical trial. JAMA Surgery. 2022; 157: 374–383.

[8] Gershenson DM. Low-grade serous carcinoma of the ovary or peritoneum. Annals of Oncology. 2016; 27: i45–i49.

[9] Barnes BM, Nelson L, Tighe A, Burghel GJ, Lin I, Desai S, et al. Distinct transcriptional programs stratify ovarian cancer cell lines into the five major histological subtypes. Genome Medicine. 2021; 13: 140.

[10] Bartoletti M, Musacchio L, Giannone G, Tuninetti V, Bergamini A, Scambia G, et al. Emerging molecular alterations leading to histology-specific targeted therapies in ovarian cancer beyond PARP inhibitors. Cancer Treatment Reviews. 2021; 101: 102298.

[11] Kaldawy A, Segev Y, Lavie O, Auslender R, Sopik V, Narod SA. Low-grade serous ovarian cancer: a review. Gynecologic Oncology. 2016; 143: 433–438.

[12] Bussies PL, Schlumbrecht M. Dual fulvestrant-trametinib therapy in recurrent low-grade serous ovarian cancer. The Oncologist. 2020; 25: e1124–e1126.

[13] King ER, Tung CS, Tsang YTM, Zu Z, Lok GTM, Deavers MT, et al. The anterior gradient homolog 3 (AGR3) gene is associated with differentiation and survival in ovarian cancer. American Journal of Surgical Pathology. 2011; 35: 904–912.

[14] Gao Q, Yang Z, Xu S, Li X, Yang X, Jin P, et al. Correction: heterotypic CAF-tumor spheroids promote early peritoneal metastatis of ovarian cancer. Journal of Experimental Medicine. 2019; 216: 2448.

[15] Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nature Communications. 2019; 10: 1523.

[16] Meng K, Cao J, Dong Y, Zhang M, Ji C, Wang X. Application of bioinformatics analysis to identify important pathways and hub genes in ovarian cancer affected by WT1. Frontiers in Bioengineering and Biotechnology. 2021; 9: 741051.

[17] Bu D, Luo H, Huo P, Wang Z, Zhang S, He Z, et al. KOBAS-i: intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Research. 2021; 49: W317–W325.

[18] Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Research. 2023; 51: D638–D646.

[19] Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research. 2003; 13: 2498–2504.

[20] Hoadley KA, Yau C, Hinoue T, Wolf DM, Lazar AJ, Drill E, et al. Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer. Cell. 2018; 173: 291–304.e6.

[21] Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Research. 2017; 45: W98–W102.

[22] Gyorffy B, Lánczky A, Szállási Z. Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients. Endocrine-Related Cancer. 2012; 19: 197–208.

[23] Győrffy B. Discovery and ranking of the most robust prognostic biomarkers in serous ovarian cancer. GeroScience. 2023; 45: 1889–1898.

[24] Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS, et al. TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Research. 2017; 77: e108–e110.

[25] Chandrashekar DS, Karthikeyan SK, Korla PK, Patel H, Shovon AR, Athar M, et al. UALCAN: an update to the integrated cancer data analysis platform. Neoplasia. 2022; 25: 18–27.

[26] Ru B, Wong CN, Tong Y, Zhong JY, Zhong SSW, Wu WC, et al. TISIDB: an integrated repository portal for tumor-immune system interactions. Bioinformatics. 2019; 35: 4200–4202.

[27] Chang L, Xia J. MicroRNA regulatory network analysis using miRNet 2.0. Transcription Factor Regulatory Networks. 2023; 146: 185–204.

[28] Sallum LF, Andrade L, Bastos Eloy da Costa L, Ramalho S, Ferracini AC, Natal RDA, et al. BRCA1, Ki67, and β-Catenin immunoexpression is not related to differentiation, platinum response, or prognosis in women with low- and high-grade serous ovarian carcinoma. International Journal of Gynecologic Cancer. 2018; 28: 437–447.

[29] Kang JH, Lai YL, Cheng WF, Kim HS, Kuo KT, Chen YL, et al. Clinical factors associated with prognosis in low-grade serous ovarian carcinoma: experiences at two large academic institutions in Korea and Taiwan. Scientific Reports. 2020; 10: 20012.

[30] Goulding EA, Simcock B, McLachlan J, van der Griend R, Sykes P. Low-grade serous ovarian carcinoma: a comprehensive literature review. Australian and New Zealand Journal of Obstetrics and Gynaecology. 2020; 60: 27–33.

[31] Romero I, Leskelä S, Mies BP, Velasco AP, Palacios J. Morphological and molecular heterogeneity of epithelial ovarian cancer: therapeutic implications. European Journal of Cancer Supplements. 2020; 15: 1–15.

[32] Huang J. Current developments of targeting the p53 signaling pathway for cancer treatment. Pharmacology & Therapeutics. 2021; 220: 107720.

[33] Li H, Zeng Z, Yang X, Chen Y, He L, Wan T. LncRNA GClnc1 may contribute to the progression of ovarian cancer by regulating p53 signaling pathway. European Journal of Histochemistry. 2020; 64: 3166.

[34] Golubovskaya VM, Kweh FA, Cance WG. Focal adhesion kinase and cancer. Histology & Histopathology. 2009; 24: 503–510.

[35] Tai Y, Chen L, Shen T. Emerging roles of focal adhesion kinase in cancer. BioMed Research International. 2015; 2015: 690690.

[36] Revach O, Grosheva I, Geiger B. Biomechanical regulation of focal adhesion and invadopodia formation. Journal of Cell Science. 2020; 133: jcs244848.

[37] Chen L, Qian J, You Q, Ma J. LIM domain-containing 2 (LIMD2) promotes the progress of ovarian cancer via the focal adhesion signaling pathway. Bioengineered. 2021; 12: 10089–10100.

[38] Nolasco-Quiroga M, Rosas-Díaz M, Moreno J, Godínez-Aguilar R, López-Ibarra MJ, Piña-Sánchez P, et al. Increased expression of FAK isoforms as potential cancer biomarkers in ovarian cancer. Oncology Letters. 2019; 17: 4779–4786.

[39] Mitra AK, Sawada K, Tiwari P, Mui K, Gwin K, Lengyel E. Ligand-independent activation of c-Met by fibronectin and α(5)β(1)-integrin regulates ovarian cancer invasion and metastasis. Oncogene. 2011; 30: 1566–1576.

[40] Chen C, Shyu M, Wang S, Chou C, Huang M, Lin T, et al. MUC20 promotes aggressive phenotypes of epithelial ovarian cancer cells via activation of the integrin β1 pathway. Gynecologic Oncology. 2016; 140: 131–137.

[41] Huang H, Lin Y, Chang H, Lai Y, Chen Y, Huang S, et al. Chemoresistant ovarian cancer enhances its migration abilities by increasing store-operated Ca2+ entry-mediated turnover of focal adhesions. Journal of Biomedical Science. 2020; 27: 36.

[42] Xu X, Chen F, Zhang L, Liu L, Zhang C, Zhang Z, et al. Exploring the mechanisms of anti-ovarian cancer of Hedyotis diffusa willd and Scutellaria barbata D. Don through focal adhesion pathway. Journal of Ethnopharmacology. 2021; 279: 114343.

[43] Balkwill FR. The chemokine system and cancer. The Journal of Pathology. 2012; 226: 148–157.

[44] Goenka A, Khan F, Verma B, Sinha P, Dmello CC, Jogalekar MP, et al. Tumor microenvironment signaling and therapeutics in cancer progression. Cancer Communications. 2023; 43: 525–561.

[45] Morein D, Erlichman N, Ben-Baruch A. Beyond cell motility: the expanding roles of chemokines and their receptors in malignancy. Frontiers in Immunology. 2020; 11: 952.

[46] Guo T, Dong X, Xie S, Zhang L, Zeng P, Zhang L. Cellular mechanism of gene mutations and potential therapeutic targets in ovarian cancer. Cancer Management and Research. 2021; 13: 3081–3100.

[47] Zhang M, Zhuang G, Sun X, Shen Y, Wang W, Li Q, et al. TP53 mutation-mediated genomic instability induces the evolution of chemoresistance and recurrence in epithelial ovarian cancer. Diagnostic Pathology. 2017; 12: 16.

[48] Chen M, Jin Y, Bi Y, Yin J, Wang Y, Pan L. A survival analysis comparing women with ovarian low-grade serous carcinoma to those with high-grade histology. OncoTargets and Therapy. 2014; 7: 1891–1899.

[49] Zhang W, Luo J, Chen F, Yang F, Song W, Zhu A, et al. BRCA1 regulates PIG3-mediated apoptosis in a p53-dependent manner. Oncotarget. 2015; 6: 7608–7618.

[50] Chaudhry SR, Lopes J, Levin NK, Kalpage H, Tainsky MA. Germline mutations in apoptosis pathway genes in ovarian cancer; the functional role of a TP53I3 (PIG3) variant in ROS production and DNA repair. Cell Death Discovery. 2021; 7: 62.

[51] Lopes JL, Chaudhry S, Lopes GS, Levin NK, Tainsky MA. FANCM, RAD1, CHEK1 and TP53i3 act as BRCA-like tumor suppressors and are mutated in hereditary ovarian cancer. Cancer Genetics. 2019; 235–236: 57–64.

[52] Zhang Y, Feng X, Zhang J, Chen M, Huang E, Chen X. Iron regulatory protein 2 is a suppressor of mutant p53 in tumorigenesis. Oncogene. 2019; 38: 6256–6269.

[53] Zhang Y, Qian Y, Zhang J, Yan W, Jung Y, Chen M, et al. Ferredoxin reductase is critical for p53-dependent tumor suppression via iron regulatory protein 2. Genes & Development. 2017; 31: 1243–1256.

[54] Zhang J, Chen X. P53 tumor suppressor and iron homeostasis. The FEBS Journal. 2019; 286: 620–629.

[55] Cai G, Zhu L, Chen X, Sun K, Liu C, Sen GC, et al. TRAF4 binds to the juxtamembrane region of EGFR directly and promotes kinase activation. Proceedings of the National Academy of Sciences. 2018; 115: 11531–11536.

[56] Chuang TC, Wu K, Lin YY, Kuo HP, Kao MC, Wang V, et al. Dual down-regulation of EGFR and ErbB2 by berberine contributes to suppression of migration and invasion of human ovarian cancer cells. Environmental Toxicology. 2021; 36: 737–747.

[57] Cui X, Song K, Lu X, Feng W, Di W. Liposomal delivery of MicroRNA-7 targeting EGFR to inhibit the growth, invasion, and migration of ovarian cancer. ACS Omega. 2021; 6: 11669–11678.

[58] Zhao J, Tan W, Zhang L, Liu J, Shangguan M, Chen J, et al. FGFR3 phosphorylates EGFR to promote cisplatin-resistance in ovarian cancer. Biochemical Pharmacology. 2021; 190: 114536.

[59] Zhang M, Cong Q, Zhang X, Zhang M, Lu Y, Xu C. Pyruvate dehydrogenase kinase 1 contributes to cisplatin resistance of ovarian cancer through EGFR activation. Journal of Cellular Physiology. 2019; 234: 6361–6370.

[60] Jin C, Xue Y, Li Y, Bu H, Yu H, Zhang T, et al. A 2-protein signature predicting clinical outcome in high-grade serous ovarian cancer. International Journal of Gynecologic Cancer. 2018; 28: 51–58.

[61] Rani MR, Foster GR, Leung S, Leaman D, Stark GR, Ransohoff RM. Characterization of beta-R1, a gene that is selectively induced by interferon beta (IFN-beta) compared with IFN-alpha. Journal of Biological Chemistry. 1996; 271: 22878–22884.

[62] Furuya M, Suyama T, Usui H, Kasuya Y, Nishiyama M, Tanaka N, et al. Up-regulation of CXC chemokines and their receptors: implications for proinflammatory microenvironments of ovarian carcinomas and endometriosis. Human Pathology. 2007; 38: 1676–1687.

[63] Cao Y, Jiao N, Sun T, Ma Y, Zhang X, Chen H, et al. CXCL11 correlates with antitumor immunity and an improved prognosis in colon cancer. Frontiers in Cell and Developmental Biology. 2021; 9: 646252.

[64] Liu K, Lai M, Wang S, Zheng K, Xie S, Wang X. Construction of a CXC chemokine-based prediction model for the prognosis of colon cancer. BioMed Research International. 2020; 2020: 6107865.

[65] Zhang J, Hu D. miR-1298-5p influences the malignancy phenotypes of breast cancer cells by inhibiting CXCL11. Cancer Management and Research. 2021; 13: 133–145.