[Home ] [Archive]    
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
IJRR Information::
For Authors::
For Reviewers::
Subscription::
News & Events::
Web Mail::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
ISSN
Hard Copy 2322-3243
Online 2345-4229
..
Online Submission
Now you can send your articles to IJRR office using the article submission system.
..

AWT IMAGE

AWT IMAGE

:: Volume 22, Issue 4 (10-2024) ::
Int J Radiat Res 2024, 22(4): 1009-1017 Back to browse issues page
Impact of neoadjuvant chemotherapy and cytoreductive surgery on patients with advanced ovarian cancer based on bioinformatics analysis
L. Luo , W. He , Q. Guo , CY. Wang
Department of Gynaecology, Affiliated Hospital of Southwest Medical University, Sichuan Provincial Center for Gynaecology & Breast Disease, China , wangchunyan0215@126.com
Abstract:   (554 Views)
Background: surgery (CRS) and neoadjuvant chemotherapy (NACT) are recommended for advanced ovarian cancer (aOC) treatment. This study aimed to investigate the therapy-induced genomic changes and immune microenvironment alteration in patients with aOC. Materials and methods: The microarray data of ovarian cancer samples from naïve or treated patients were collected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between samples were screened. Consensus clustering was conducted to explore the molecular subtypes of ovarian cancer samples. The correlation between tertiary lymphoid structure (TLS) signatures with the molecular subtypes was subject to Gene set variation analysis (GSVA). The prognostic signature of aOC was constructed using machine learning based on lasso-cox regression. Finally, immune infiltration analysis was performed for immune landscape evaluation in aOC. Results: Totally 28 DEGs were found between the control and treatment groups. Enrichment analysis indicated the association of these genes with the immune changes. Moreover, the cluster 1/2 (C1/C2) of ovarian cancer were identified, and the C1 subtype had higher enrichment of TLS-related biomarkers. Moreover, 15 genes were revealed as independent factors for the prediction of ovarian cancer prognosis. Immune infiltration levels were significantly higher in the C1 subtype, which indicated the distinct immune landscape between the two molecular subtypes of ovarian cancer. Conclusion: The NACT and CRS induced genomic changes were related to immune response in aOC. The findings of our study might deepen our understanding of the TLS-related signature and immune pattern in aOC patients.
Keywords: Ovarian cancer, neoadjuvant chemotherapy, cytoreductive surgery, differentially expressed genes, tertiary lymphoid structure, immune infiltration.
Full-Text [PDF 1824 kb]   (102 Downloads)    
Type of Study: Original Research | Subject: Radiation Biology
References
1. 1. Sung H, Ferlay J, Siegel RL, et al. (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 71(3): 209-249. [DOI:10.3322/caac.21660] [PMID]
2. Ray-Coquard I, Pautier P, Pignata S, et al. (2019) Olaparib plus bevacizumab as first-line maintenance in ovarian cancer. N Engl J Med, 381(25): 2416-2428. [DOI:10.1056/NEJMoa1911361] [PMID]
3. Gogineni V, Morand S, Staats H, et al. (2021) Current ovarian cancer maintenance strategies and promising new developments. J Cancer, 12(1): 38-53. [DOI:10.7150/jca.49406] [PMID] []
4. Armstrong DK, Alvarez RD, Bakkum-Gamez JN, et al. (2021) Ovarian cancer, version 2.2020, NCCNclinical practice guidelines in oncology. J Natl Compr Canc Netw, 19(2): 191-226.
5. Vergote I, Coens C, Nankivell M, et al. (2018) Neoadjuvant chemotherapy versus debulking surgery in advanced tubo-ovarian cancers: pooled analysis of individual patient data from the EORTC 55971 and CHORUS trials. Lancet Oncol, 19(12): 1680-1687. [DOI:10.1016/S1470-2045(18)30566-7]
6. Coleridge SL, Bryant A, Kehoe S, Morrison J (2021) Neoadjuvant chemotherapy before surgery versus surgery followed by chemotherapy for initial treatment in advanced ovarian epithelial cancer. Cochrane Database Syst Rev, 7(7): Cd005343. [DOI:10.1002/14651858.CD005343.pub6] [PMID] []
7. Eshaghi M (2020) The effect of pain management on pain reduction in women with breast cancer. Sjmshm, 2(2): 1-5. [DOI:10.29252/sjmshm.2.2.1]
8. Merlo LM, Pepper JW, Reid BJ, Maley CC (2006) Cancer as an evolutionary and ecological process. Nat Rev Cancer, 6(12): 924-935. [DOI:10.1038/nrc2013] [PMID]
9. Xiao Y and Yu D (2021) Tumor microenvironment as a therapeutic target in cancer. Pharmacol Ther, 221: 107753. [DOI:10.1016/j.pharmthera.2020.107753] [PMID] []
10. Schumacher TN, Thommen DS (2022) Tertiary lymphoid structures in cancer. Science, 375(6576): eabf9419. [DOI:10.1126/science.abf9419] [PMID]
11. Munoz-Erazo L, Rhodes JL, Marion VC, Kemp RA (2020) Tertiary lymphoid structures in cancer - considerations for patient prognosis. Cell Mol Immunol, 17(6): 570-575. [DOI:10.1038/s41423-020-0457-0] [PMID] []
12. Cottrell TR, Thompson ED, Forde PM, et al. (2018) Pathologic features of response to neoadjuvant anti-PD-1 in resected non-small-cell lung carcinoma: a proposal for quantitative immune-related pathologic response criteria (irPRC). Ann Oncol, 29(8): 1853-1860. [DOI:10.1093/annonc/mdy218] [PMID] []
13. Vanhersecke L, Brunet M, Guégan JP, et al. (2021) Mature tertiary lymphoid structures predict immune checkpoint inhibitor efficacy in solid tumors independently of PD-L1 expression. Nat Cancer, 2(8): 794-802. [DOI:10.1038/s43018-021-00232-6] [PMID] []
14. Yang M, Lu J, Zhang G, et al. (2021) CXCL13 shapes immunoactive tumor microenvironment and enhances the efficacy of PD-1 checkpoint blockade in high-grade serous ovarian cancer. J Immunother Cancer, 9(1). [DOI:10.1136/jitc-2020-001136] [PMID] []
15. Amini J and Hasanramezani A (2022) AAK1 circular regulates neuronal development by interacting with miR-132, miR-146a and miR484. Alkhass, 4(4): 1-4. [DOI:10.47176/alkhass.4.4.1]
16. Sautès-Fridman C, Petitprez F, Calderaro J, Fridman WH (2019) Tertiary lymphoid structures in the era of cancer immunotherapy. Nat Rev Cancer, 19(6): 307-325. [DOI:10.1038/s41568-019-0144-6] [PMID]
17. Lu H, Lou H, Wengert G, et al. (2023) Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer. Cell Rep Med, 4(7): 101092. [DOI:10.1016/j.xcrm.2023.101092] [PMID] []
18. Taminau J, Meganck S, Lazar C, et al. (2012) Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages. BMC Bioinformatics, 13: 335. [DOI:10.1186/1471-2105-13-335] [PMID] []
19. Johnson WE, Li C, Rabinovic A (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8(1): 118-127. [DOI:10.1093/biostatistics/kxj037] [PMID]
20. McEligot AJ, Poynor V, Sharma R, Panangadan A (2020) Logistic LASSO Regression for Dietary Intakes and Breast Cancer. Nutrients, 12(9). [DOI:10.3390/nu12092652] [PMID] []
21. Becht E, Giraldo NA, Lacroix L, et al. (2016) Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biol, 17(1): 218. https://doi.org/10.1186/s13059-016-1113-y [DOI:10.1186/s13059-016-1070-5] [PMID] []
22. Elies A, Rivière S, Pouget N, et al. (2018) The role of neoadjuvant chemotherapy in ovarian cancer. Expert Rev Anticancer Ther, 18(6): 555-566. [DOI:10.1080/14737140.2018.1458614] [PMID]
23. Javellana M, Eckert MA, Heide J, et al. (2022) Neoadjuvant chemotherapy induces genomic and transcriptomic changes in ovarian cancer. Cancer Res, 82(1): 169-176. [DOI:10.1158/0008-5472.CAN-21-1467] [PMID] []
24. Dieu-Nosjean MC, Giraldo NA, Kaplon H, et al. (2016) Tertiary lymphoid structures, drivers of the anti-tumor responses in human cancers. Immunol Rev, 271(1): 260-275. [DOI:10.1111/imr.12405] [PMID]
25. Feng H, Yang F, Qiao L, et al. (2021) Prognostic significance of gene signature of tertiary lymphoid structures in patients with lung adenocarcinoma. Front Oncol, 11: 693234. [DOI:10.3389/fonc.2021.693234] [PMID] []
26. An Y, Sun JX, Xu MY, et al. (2022) Tertiary lymphoid structure patterns aid in identification of tumor microenvironment infiltration and selection of therapeutic agents in bladder cancer. Front Immunol, 13: 1049884. [DOI:10.3389/fimmu.2022.1049884] [PMID] []
27. Swanson K, Wu E, Zhang A, Alizadeh AA, Zou J (2023) From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment. Cell, 186(8): 1772-1791. [DOI:10.1016/j.cell.2023.01.035] [PMID]
28. Zhang L, Wu X, Fan X, Ai H (2023) MUM1L1 as a tumor suppressor and potential biomarker in ovarian cancer: Evidence from bioinformatics analysis and basic experiments. Comb Chem High Throughput Screen, 26(14): 2487-2501. [DOI:10.2174/1386207326666230301141912] [PMID]
29. Zhao E, Gao K, Xiong J, et al. (2023) The roles of FXYD family members in ovarian cancer: an integrated analysis by mining TCGA and GEO databases and functional validations. J Cancer Res Clin Oncol. [DOI:10.1007/s00432-023-05445-z] [PMID]
30. Zeng B, Yuan C, Yang X, Atkin SL, Xu SZ (2013) TRPC channels and their splice variants are essential for promoting human ovarian cancer cell proliferation and tumorigenesis. Curr Cancer Drug Targets, 13(1): 103-116. [DOI:10.2174/156800913804486629]
31. Chetry M, Li S, Liu H, Hu X, Zhu X (2018) Prognostic values of aquaporins mRNA expression in human ovarian cancer. Biosci Rep, 38(2). [DOI:10.1042/BSR20180108] [PMID] []
32. Bijsmans IT, Smits KM, de Graeff P, et al. (2011) Loss of serpinA5 protein expression is associated with advanced-stage serous ovarian tumors. Mod Pathol, 24(3): 463-470. [DOI:10.1038/modpathol.2010.214] [PMID]
33. Liang L, Li J, Yu J, et al. (2022) Establishment and validation of a novel invasion-related gene signature for predicting the prognosis of ovarian cancer. Cancer Cell Int, 22(1):118. [DOI:10.1186/s12935-022-02502-4] [PMID] []
34. Kandalaft LE, Dangaj Laniti D, Coukos G (2022) Immunobiology of high-grade serous ovarian cancer: lessons for clinical translation. Nat Rev Cancer, 22(11):640-656. [DOI:10.1038/s41568-022-00503-z] [PMID]
35. Hornburg M, Desbois M, Lu S, et al. (2021) Single-cell dissection of cellular components and interactions shaping the tumor immune phenotypes in ovarian cancer. Cancer Cell, 39(7): 928-944.e6. [DOI:10.1016/j.ccell.2021.04.004] [PMID]
36. Li X, Liang W, Zhao H, et al. (2021) Immune cell infiltration landscape of ovarian cancer to identify prognosis and immunotherapy-related genes to aid immunotherapy. Front Cell Dev Biol, 9: 749157. [DOI:10.3389/fcell.2021.749157] [PMID] []
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML     Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Luo L, He W, Guo Q, Wang C. Impact of neoadjuvant chemotherapy and cytoreductive surgery on patients with advanced ovarian cancer based on bioinformatics analysis. Int J Radiat Res 2024; 22 (4) :1009-1017
URL: http://ijrr.com/article-1-5789-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 22, Issue 4 (10-2024) Back to browse issues page
International Journal of Radiation Research
Persian site map - English site map - Created in 0.05 seconds with 48 queries by YEKTAWEB 4700