Identification of ADIPOQ as a favorable prognostic biomarker for liposarcoma based on GEO database

Published on May. 29, 2024Total Views: 300 times Total Downloads: 233 times Download Mobile

Author: ZHAO Huanhuan ^1, ²  ZHANG Guochuan ¹

Affiliation: 1. Department of Orthopedic Oncology, Hebei Medical University Third Hospital, Shijiazhuang 050051, China 2. Fourth Department of Orthopedics, Baoding NO.1 Central Hospital, Baoding 071000, Hebei Province, China

Keywords: Liposarcoma ADIPOQ GEO database Prognosis Biomarker

DOI: 10.12173/j.issn.1004-4337.202403095

Reference: Zhao HH, Zhang GC. Identification of ADIPOQ as a favorable prognostic biomarker for liposarcoma based on GEO database[J]. Journal of Mathematical Medicine, 2024, 37(5): 341-348. DOI: 10.12173/j.issn.1004-4337.202403095[Article in Chinese]  Copied

Abstract
Full-text
References

Abstract

Objective To explore the prognostic biomarkers for liposarcoma as potential therapeutic targets.

Methods GSE21122, GSE159659, and GSE30929 datasets were downloaded from Gene Expression Omnibus (GEO) database. The significantly differentially expressed genes between liposarcoma and normal adipose tissues were identified using the limma package of R language. The common differentially expressed genes were obtained using the ggvenn package. The survival and survminer packages were performed for Cox regression analysis and Kaplan-Meier survival analysis. The correlation between ADIPOQ and multiple immune checkpoint molecules was analyzed using the corr. text function. Functional enrichment analysis of differentially expressed genes between liposarcomas with high and low ADIPOQ was performed by clusterProfiler package.

Results In GSE21122 and GSE159659 datasets, 155 and 39 significantly differentially expressed genes were identified, respectively. The Venn plot displayed the 25 common differentially expressed genes. Multivariate Cox regression analysis showed that ADIPOQ could serve as an independent factor for the favorable prognosis of liposarcoma [HR=0.68, 95%CI (0.49, 0.94), P=0.022]. Compared with normal adipose tissues, ADIPOQ was significantly downregulated in liposarcoma tissues (P<0.001). Kaplan-Meier survival analysis showed that liposarcoma patients with high level of ADIPOQ had significantly longer distant recurrence free survival (DRFS) than those with low ADIPOQ (P<0.001). Spearman correlation analysis showed that ADIPOQ was negatively correlated with immune checkpoint molecules such as ICOS, TNFSF9, LAG3, CTLA4, CD47, CD200, CD86, and PDCD1LG2 (P<0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the upregulated genes between liposarcomas with high and low ADIPOQ were abundant in nutrient metabolism and metabolism-related pathways, while downregulated genes were involved in biological function of cell division and cell cycle.

Conclusion ADIPOQ could serve as a favorable prognostic biomarker for liposarcoma, and it may have the effect of inhibiting the expression of multiple immune checkpoints, thereby improving the prognosis of liposarcoma patients.

Full-text

Please download the PDF version to read the full text: download

References

1.Fletcher CDM, Hogendoorn PCW, Mertens F. WHO classification of tumors of soft tissue and bone[M]. Lyon: IARC Press, 2013.

2.Smyczyńska U, Strzemecki D, Czarnecka AM, et al. TP53- deficient angiosarcoma expression profiling in rat model[J]. Cancers (Basel), 2020, 12(6): 1525. DOI: 10.3390/cancers12061525.

3.Jagosky MH, Anderson CJ, Symanowski JT, et al. Genomic alterations and clinical outcomes in patients with dedifferentiated liposarcoma[J]. Cancer Med, 2023, 12(6): 7029-7038. DOI: 10.1002/cam4.5502.

4.Suarez-Kelly LP, Baldi GG, Gronchi A. Pharmacotherapy for liposarcoma: current state of the art and emerging systemic treatments[J]. Expert Opin Pharmacother, 2019, 20(12): 1503-1515. DOI: 10.1080/14656566.2019. 1618271.

5.Saponara M, Stacchiotti S, Gronchi A. Pharmacological therapies for liposarcoma[J]. Expert Rev Clin Pharmacol, 2017, 10(4): 361-377. DOI: 10.1080/17512433.2017. 1289086.

6.Dancsok AR, Asleh-Aburaya K, Nielsen TO. Advances in sarcoma diagnostics and treatment[J]. Oncotarget, 2017, 8(4): 7068-7093. DOI: 10.18632/oncotarget.12548.

7.Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets-update[J]. Nucleic Acids Res, 2013, 41(Database issue): D991-D995. DOI: 10.1093/nar/gks1193.

8.Ritchie ME, Phipson B, Wu D, et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies[J]. Nucleic Acids Res, 2015, 43(7): e47. DOI: 10.1093/nar/gkv007.

9.Ito K, Murphy D. Application of ggplot2 to pharmacometric graphics[J]. CPT Pharmacometrics Syst Pharmacol, 2013, 2(10): e79. DOI: 10.1038/psp.2013.56.

10.Hegde PS, Chen DS. Top 10 challenges in cancer immunotherapy[J]. Immunity, 2020, 52(1): 17-35. DOI: 10.1016/j.immuni.2019.12.011.

11.Zhao H, Zhang G. Identification of differentiation-related biomarkers in liposarcoma tissues using weighted gene co-expression network analysis[J]. J Biol Regul Homeost Agents, 2023, 37(12): 6807-6819. DOI: 10.23812/j.biol.regul.homeost.agents.20233712.644.

12.Elfaki I, Mir R, Tayeb F, et al. Potential association of the pathogenic Kruppel-like factor 14 (KLF14) and Adiponectin (ADIPOQ) SNVs with susceptibility to T2DM[J]. Endocr Metab Immune Disord Drug Targets, 2024, 24(9): 1090-1100. DOI: 10.2174/0118715303258744231117064253.

13.Zhu M, Lv Y, Peng Y, et al. GCKR and ADIPOQ gene polymorphisms in women with gestational diabetes mellitus[J]. Acta Diabetol, 2023, 60(12): 1709-1718. DOI: 10.1007/s00592-023-02165-1.

14.Hou WK, Xu YX, Yu T, et al. Adipocytokines and breast cancer risk[J]. Chin Med J (Engl), 2007, 120(18): 1592-1596. https://pubmed.ncbi.nlm.nih.gov/17908478/.

15.Byeon JS, Jeong JY, Kim MJ, et al. Adiponectin and adiponectin receptor in relation to colorectal cancer progression[J]. Int J Cancer, 2010, 127(12): 2758-2767. DOI: 10.1002/ijc.25301.

16.Habeeb BS, Kitayama J, Nagawa H. Adiponectin supports cell survival in glucose deprivation through enhancement of autophagic response in colorectal cancer cells[J]. Cancer Sci, 2011, 102(5): 999-1006. DOI: 10.1111/j.1349-7006. 2011.01902.x.

17.Sugiyama M, Takahashi H, Hosono K, et al. Adiponectin inhibits colorectal cancer cell growth through the AMPK/ mTOR pathway[J]. Int J Oncol, 2009, 34(2): 339-344. DOI: 10.3892/ijo_00000156.

18.Kim AY, Lee YS, Kim KH, et al. Adiponectin represses colon cancer cell proliferation via AdipoR1-and-R2- mediated AMPK activation[J]. Mol Endocrinol, 2010, 24(7): 1441-1452. DOI: 10.1210/me.2009-0498.

19.Zakikhani M, Dowling RJO, Sonenberg N, et al. The effects of adiponectin and metformin on prostate and colon neoplasia involve activation of AMP-activated protein kinase[J]. Cancer Prev Res (Phila), 2008, 1(5): 369-375. DOI: 10.1158/1940-6207.CAPR-08-0081.

20.Michalakis K, Williams CJ, Mitsiades N, et al. Serum adiponectin concentrations and tissue expression of adiponectin receptors are reduced in patients with prostate cancer: a case control study[J]. Cancer Epidemiol Biomarkers Prev, 2007, 16(2): 308-313. DOI: 10.1158/1055-9965.EPI-06-0621.

21.Goktas S, Yilmaz MI, Caglar K, et al. Prostate cancer and adiponectin[J]. Urology, 2005, 65(6): 1168-1172. DOI: 10.1016/j.urology.2004.12.053.

22.Jiang Y, Chen M, Nie H, et al. PD-1 and PD-L1 in cancer immunotherapy: clinical implications and future considerations[J]. Hum Vaccin Immunother, 2019, 15(5): 1111-1122. DOI: 10.1080/21645515.2019.1571892.

23.Puhr HC, Ilhan-Mutlu A. New emerging targets in cancer immunotherapy: the role of LAG3[J]. ESMO Open, 2019, 4(2): e000482. DOI: 10.1136/esmoopen-2018-000482.

24.He Y, Cao J, Zhao C, et al. TIM-3, a promising target for cancer immunotherapy[J]. Onco Targets Ther, 2018, 11: 7005-7009. DOI: 10.2147/OTT.S170385.

25.Shiravand Y, Khodadadi F, Kashani SMA, et al. Immune checkpoint inhibitors in cancer therapy[J]. Curr Oncol, 2022, 29(5): 3044-3060. DOI: 10.3390/curroncol29050247.