Top

World Journal of Surgical Oncology

Published in:

Open Access 01-12-2021 | Research

Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm

Authors: Xiaoqing Shen, Zhujuan Yang, Songwei Feng, Yi Li

Published in: World Journal of Surgical Oncology | Issue 1/2021

Abstract

Background

While large-scale genomic analyses symbolize a precious attempt to decipher the molecular foundation of uterine leiomyosarcoma (ULMS), bioinformatics results associated with the occurrence of ULMS based totally on WGCNA and CIBERSORT have not yet been reported. This study aimed to screen the hub genes and the immune cell infiltration pattern in ULMS by bioinformatics methods.

Methods

Firstly, the GSE67463 dataset, including 25 ULMS tissues and 29 normal myometrium (NL) tissues, was downloaded from the public database. The differentially expressed genes (DEGs) were screened by the ‘limma’ package and hub modules were identified by weighted gene co-expression network analysis (WGCNA). Subsequently, gene function annotations were performed to investigate the biological role of the genes from the intersection of two groups (hub module and DEGs). The above genes were calculated in the protein–protein interaction (PPI) network to select the hub genes further. The hub genes were validated using external data (GSE764 and GSE68295). In addition, the differential immune cell infiltration between UL and ULMS tissues was investigated using the CIBERSORT algorithm. Finally, we used western blot to preliminarily detect the hub genes in cell lines.

Results

WGCNA analysis revealed a green-yellow module possessed the highest correlation with ULMS, including 1063 genes. A total of 172 DEGs were selected by thresholds set in the ‘limma’ package. The above two groups of genes were intersected to obtain 72 genes for functional annotation analysis. Interestingly, it indicated that 72 genes were mainly involved in immune processes and the Neddylation pathway. We found a higher infiltration of five types of cells (memory B cells, M0-type macrophages, mast cells activated, M1-type macrophages, and T cells follicular helper) in ULMS tissues than NL tissues, while the infiltration of two types of cells (NK cells activated and mast cells resting) was lower than in NL tissues. In addition, a total of five genes (KDR, CCL21, SELP, DPT, and DCN) were identified as the hub genes. Internal and external validation demonstrated that the five genes were over-expressed in NL tissues compared with USML tissues. Finally, the correlation analysis results indicate that NK cells activated and mast cells activated positively correlated with the hub genes. However, M1-type macrophages had a negative correlation with the hub genes. Moreover, only the DCN may be associated with the Neddylation pathway.

Conclusion

A series of evidence confirm that the five hub genes and the infiltration of seven types of immune cells are related to USML occurrence. These hub genes may affect the occurrence of USML through immune-related and Neddylation pathways, providing molecular evidence for the treatment of USML in the future.

Available only for authorised users

Kobayashi H, Uekuri C, Akasaka J, et al. The biology of uterine sarcomas: a review and update. Mol Clin Oncol. 2013;1(4):599–609. https://doi.org/10.3892/mco.2013.124.CrossRefPubMedPubMedCentral

Roberts ME, Aynardi JT, Chu CS. Uterine leiomyosarcoma: a review of the literature and update on management options. Gynecol Oncol. 2018;151(3):562–72. https://doi.org/10.1016/j.ygyno.2018.09.010.CrossRefPubMed

Cui RR, Wright JD, Hou JY. Uterine leiomyosarcoma: a review of recent advances in molecular biology, clinical management and outcome. BJOG. 2017;124(7):1028–37. https://doi.org/10.1111/1471-0528.14579.CrossRefPubMed

Bobiński M, Kraczkowski JJ, Witt E, et al. Management of uterine leiomyosarcoma. Wiad Lek. 2016;69(6):799–803.PubMed

Zagouri F, Dimopoulos AM, Fotiou S, Kouloulias V, Papadimitriou CA. Treatment of early uterine sarcomas: disentangling adjuvant modalities. World J Surg Oncol. 2009;7:38. https://doi.org/10.1186/1477-7819-7-38 Published 2009 Apr 8.CrossRefPubMedPubMedCentral

Petruzziello A, Kondo W, Hatschback SB, et al. Surgical results of pelvic exenteration in the treatment of gynecologic cancer. World J Surg Oncol. 2014;12:279. https://doi.org/10.1186/1477-7819-12-279 Published 2014 Sep 8.CrossRefPubMedPubMedCentral

Koulaxouzidis G, Schwarzkopf E, Bannasch H, Stark GB. Is revisional surgery mandatory when an unexpected sarcoma diagnosis is made following primary surgery? World J Surg Oncol. 2015;13:306. https://doi.org/10.1186/s12957-015-0719-y Published 2015 Oct 24.CrossRefPubMedPubMedCentral

Hirsch FR, Scagliotti GV, Mulshine JL, et al. Lung cancer: current therapies and new targeted treatments. Lancet. 2017;389(10066):299–311. https://doi.org/10.1016/S0140-6736(16)30958-8.CrossRefPubMed

Odunsi K. Immunotherapy in ovarian cancer. Ann Oncol. 2017;28(suppl_8):viii1–7. https://doi.org/10.1093/annonc/mdx444.CrossRefPubMedPubMedCentral

10.

Lee YT, Tan YJ, Oon CE. Molecular targeted therapy: treating cancer with specificity. Eur J Pharmacol. 2018;834:188–96. https://doi.org/10.1016/j.ejphar.2018.07.034.CrossRefPubMed

11.

Chen Z, Li Y, Tan B, et al. Progress and current status of molecule-targeted therapy and drug resistance in gastric cancer. Drugs Today (Barc). 2020;56(7):469–82. https://doi.org/10.1358/dot.2020.56.7.3112071.CrossRef

12.

Cancer Genome Atlas Research Network Electronic address: elizabeth.demicco@sinaihealthsystem.ca; Cancer Genome Atlas Research Network. Comprehensive and integrated genomic characterization of adult soft tissue sarcomas. Cell. 2017;171(4):950-965.e28. https://doi.org/10.1016/j.cell.2017.10.014.CrossRef

13.

Fares CM, Van Allen EM, Drake CG, Allison JP, Hu-Lieskovan S. Mechanisms of resistance to immune checkpoint blockade: why does checkpoint inhibitor immunotherapy not work for all patients? Am Soc Clin Oncol Educ Book. 2019;39:147–64. https://doi.org/10.1200/EDBK_240837.CrossRefPubMed

14.

Shanes ED, Friedman LA, Mills AM. PD-L1 expression and tumor-infiltrating lymphocytes in uterine smooth muscle tumors: implications for immunotherapy. Am J Surg Pathol. 2019;43(6):792–801. https://doi.org/10.1097/PAS.0000000000001254.CrossRefPubMed

15.

George S, Miao D, Demetri GD, et al. Loss of PTEN is associated with resistance to anti-PD-1 checkpoint blockade therapy in metastatic uterine leiomyosarcoma. Immunity. 2017;46(2):197–204. https://doi.org/10.1016/j.immuni.2017.02.001.CrossRefPubMedPubMedCentral

16.

Pei G, Chen L, Zhang W. WGCNA application to proteomic and metabolomic data analysis. Methods Enzymol. 2017;585:135–58. https://doi.org/10.1016/bs.mie.2016.09.016.CrossRefPubMed

17.

Botía JA, Vandrovcova J, Forabosco P, et al. An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks. BMC Syst Biol. 2017;11(1):47. https://doi.org/10.1186/s12918-017-0420-6 Published 2017 Apr 12.CrossRefPubMedPubMedCentral

18.

Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559. https://doi.org/10.1186/1471-2105-9-559 Published 2008 Dec 29.CrossRefPubMedPubMedCentral

19.

Chen B, Khodadoust MS, Liu CL, Newman AM, Alizadeh AA. Profiling tumor infiltrating immune cells with CIBERSORT. Methods Mol Biol. 2018;1711:243–59. https://doi.org/10.1007/978-1-4939-7493-1_12.CrossRefPubMedPubMedCentral

20.

Newman AM, Liu CL, Green MR, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–7. https://doi.org/10.1038/nmeth.3337.CrossRefPubMedPubMedCentral

21.

Yang Y, Zheng Y, Liu X, et al. Comprehensive analysis of gene regulation network and immune signatures of prognostic biomarker YAP1 in pancreatic cancer. J Cancer. 2020;11(23):6960–9. https://doi.org/10.7150/jca.49117 Published 2020 Oct 8.CrossRefPubMedPubMedCentral

22.

Chen H, Chong W, Teng C, Yao Y, Wang X, Li X. The immune response-related mutational signatures and driver genes in non-small-cell lung cancer. Cancer Sci. 2019;110(8):2348–56. https://doi.org/10.1111/cas.14113.CrossRefPubMedPubMedCentral

23.

Zhou H, Chen L, Lei Y, Li T, Li H, Cheng X. Integrated analysis of tumor mutation burden and immune infiltrates in endometrial cancer. Curr Probl Cancer. 2021;45(2). https://doi.org/10.1016/j.currproblcancer.2020.100660.

24.

Cai Y, Tsai HC, Yen RC, et al. Critical threshold levels of DNA methyltransferase 1 are required to maintain DNA methylation across the genome in human cancer cells. Genome Res. 2017;27(4):533–44. https://doi.org/10.1101/gr.208108.116.CrossRefPubMedPubMedCentral

25.

Song Q, Feng S, Peng W, et al. Cullin-Ring Ligases as promising targets for gastric carcinoma treatment. Pharmacol Res. 2021;105493. [published online ahead of print, 2021 Feb 15]. https://doi.org/10.1016/j.phrs.2021.105493

26.

Kim Y, Park JB, Fukuda J, Watanabe M, Chun YS. The effect of Neddylation blockade on slug-dependent cancer cell migration is regulated by p53 mutation status. Cancers (Basel). 2021;13(3):531. https://doi.org/10.3390/cancers13030531 Published 2021 Jan 30.CrossRef

27.

Fu DJ, Cui XX, Zhu T, et al. Discovery of novel indole derivatives that inhibit NEDDylation and MAPK pathways against gastric cancer MGC803 cells. Bioorg Chem. 2021;107. https://doi.org/10.1016/j.bioorg.2021.104634.

28.

Yu Q, Sun Y. Targeting protein Neddylation to inactivate Cullin-RING ligases by Gossypol: a lucky hit or a new start? Drug Des Devel Ther. 2021;15:1–8. https://doi.org/10.2147/DDDT.S286373 Published 2021 Jan 6.CrossRefPubMedPubMedCentral

29.

Tsuyoshi H, Yoshida Y. Molecular biomarkers for uterine leiomyosarcoma and endometrial stromal sarcoma. Cancer Sci. 2018;109(6):1743–52. https://doi.org/10.1111/cas.13613.CrossRefPubMedPubMedCentral

30.

Ganjoo KN. Uterine sarcomas. Curr Probl Cancer. 2019;43(4):283–8. https://doi.org/10.1016/j.currproblcancer.2019.06.001.CrossRefPubMed

31.

Desar IME, Ottevanger PB, Benson C, van der Graaf WTA. Systemic treatment in adult uterine sarcomas. Crit Rev Oncol Hematol. 2018;122:10–20. https://doi.org/10.1016/j.critrevonc.2017.12.009.CrossRefPubMed

32.

Bu H, Jin C, Fang Y, et al. Successful pregnancy after complete resection of leiomyomatosis peritonealis disseminate without recurrence: a case report with next-generation sequencing analysis and literature review. World J Surg Oncol. 2020;18(1):85. https://doi.org/10.1186/s12957-020-01857-0 Published 2020 May 2.CrossRefPubMedPubMedCentral

33.

Hensley ML, Chavan SS, Solit DB, et al. Genomic landscape of uterine sarcomas defined through prospective clinical sequencing. Clin Cancer Res. 2020;26(14):3881–8. https://doi.org/10.1158/1078-0432.CCR-19-3959.CrossRefPubMedPubMedCentral

34.

Pinto A, Mackrides N, Nadji M. PD-L1 Expression in carcinosarcomas of the gynecologic tract: a potentially actionable biomarker. Appl Immunohistochem Mol Morphol. 2018;26(6):393–7. https://doi.org/10.1097/PAI.0000000000000457.CrossRefPubMed

35.

Cuppens T, Moisse M, Depreeuw J, et al. Integrated genome analysis of uterine leiomyosarcoma to identify novel driver genes and targetable pathways. Int J Cancer. 2018;142(6):1230–43. https://doi.org/10.1002/ijc.31129.CrossRefPubMed

36.

Mäkinen N, Aavikko M, Heikkinen T, et al. Exome sequencing of uterine leiomyosarcomas identifies frequent mutations in TP53, ATRX, and MED12. PLoS Genet. 2016;12(2):e1005850. https://doi.org/10.1371/journal.pgen.1005850 Published 2016 Feb 18.CrossRefPubMedPubMedCentral

37.

Gotoh O, Kiyotani K, Chiba T, et al. Immunogenomic landscape of gynecologic carcinosarcoma. Gynecol Oncol. 2021;160(2):547–56. https://doi.org/10.1016/j.ygyno.2020.11.030.CrossRefPubMed

38.

Chen JX, Yi XJ, Gu PL, Gao SX. The role of KDR in intrauterine adhesions may involve the TGF-β1/Smads signaling pathway. Braz J Med Biol Res. 2019;52(10):e8324. https://doi.org/10.1590/1414-431X20198324 Published 2019 Oct 7.CrossRefPubMedPubMedCentral

39.

Sharma S, Kadam P, Dubinett S. CCL21 programs immune activity in tumor microenvironment. Adv Exp Med Biol. 2020;1231:67–78. https://doi.org/10.1007/978-3-030-36667-4_7.CrossRefPubMed

40.

Rong Y, Chen X, Fan D, et al. Influence of CCL21 on the invasion and metastasis of colorectal cancer. Zhonghua Wei Chang Wai Ke Za Zhi. 2017;20(11):1300–5.

41.

Fejes Z, Póliska S, Czimmerer Z, et al. Hyperglycaemia suppresses microRNA expression in platelets to increase P2RY12 and SELP levels in type 2 diabetes mellitus. Thromb Haemost. 2017;117(3):529–42. https://doi.org/10.1160/TH16-04-0322.CrossRef

42.

Hua X, Liu Z, Zhou M, et al. LSAMP-AS1 binds to microRNA-183-5p to suppress the progression of prostate cancer by up-regulating the tumor suppressor DCN. EBioMedicine. 2019;50:178–90. https://doi.org/10.1016/j.ebiom.2019.10.009.

43.

Edwards IJ. Proteoglycans in prostate cancer. Nat Rev Urol. 2012;9(4):196–206. https://doi.org/10.1038/nrurol.2012.19 Published 2012 Feb 21.CrossRefPubMed

44.

Henke A, Grace OC, Ashley GR, et al. Stromal expression of decorin, Semaphorin6D, SPARC, Sprouty1 and Tsukushi in developing prostate and decreased levels of decorin in prostate cancer. PLoS ONE. 2012;7(8). https://doi.org/10.1371/journal.pone.0042516.

45.

Mao H, Sun Y. Neddylation-independent activities of MLN4924. Adv Exp Med Biol. 2020;1217:363–72. https://doi.org/10.1007/978-981-15-1025-0_21.CrossRefPubMed

46.

Hao R, Song Y, Li R, et al. MLN4924 protects against interleukin-17A-induced pulmonary inflammation by disrupting ACT1-mediated signaling. Am J Physiol Lung Cell Mol Physiol. 2019;316(6):L1070–80. https://doi.org/10.1152/ajplung.00349.2018.CrossRefPubMed

Title: Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm
Authors: Xiaoqing Shen
Zhujuan Yang
Songwei Feng
Yi Li
Publication date: 01-12-2021
Publisher: BioMed Central
Published in: World Journal of Surgical Oncology / Issue 1/2021
Electronic ISSN: 1477-7819
DOI: https://doi.org/10.1186/s12957-021-02333-z

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 1/2021

Improvement in distal pancreatectomy for tumors in the body and tail of the pancreas

Revisit the practice of lymph node biopsy in patients diagnosed as ductal carcinoma in situ before operation: a retrospective analysis of 682 cases and evaluation of the role of breast MRI

The application of rigid and flexible mediastinoscopy in esophagectomy: our experience and a new technology

Primary metastatic prostate cancer between prognosis or adequate/proper medical therapy

Analysis of EGFR, KRAS, and PIK3CA gene mutation rates and clinical distribution in patients with different types of lung cancer

A nomogram model for predicting prognosis of obstructive colorectal cancer