Systematic Analysis of Tumor Stem Cell-related Gene Characteristics to Predict the PD-L1 Immunotherapy and Prognosis of Gastric Cancer


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Abstract

Aims:We aimed to develop a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in gastric cancer (GC).

Background:Tumor stemness is related to intratumoral heterogeneity, immunosuppression, and anti-tumor resistance. We developed a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in GC.

Objective:We aimed to develop a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in GC.

Methods:We downloaded single-cell RNA sequencing (scRNA-seq) data of GC patients from the Gene-Expression Omnibus (GEO) database and screened GC stemness- related genes using CytoTRACE. We characterized the association of tumor stemness with immune checkpoint blockade (ICB) and immunity. Thereafter, a 9-stemness signature-based prognostic model was developed using weighted gene co-expression network analysis (WGCNA), univariate Cox regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis. The model predictive value was evaluated with a nomogram.

Results:Early GC patients had significantly higher levels of stemness. The stemness score showed a negative relationship to tumor immune dysfunction and exclusion (TIDE) score and immune infiltration, especially T cells and B cells. A stemness-based signature based on 9 genes (ERCC6L, IQCC, NKAPD1, BLMH, SLC25A15, MRPL4, VPS35, SUMO3, and CINP) was constructed with good performance in prognosis prediction, and its robustness was validated in GSE26942 cohort. Additionally, nomogram and risk score exhibited the most powerful ability for prognosis prediction. High-risk patients exhibited a tendency to develop immune escape and low response to PD-L1 immunotherapy.

Conclusion:We developed a stemness-based gene signature for prognosis prediction with accuracy and reliability. This signature also helps clinical decision-making of immunotherapy for GC patients.

About the authors

Chenchen Wang

Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center

Email: info@benthamscience.net

Ying Chen

Department of Oncology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine,

Email: info@benthamscience.net

Ru Zhou

Department of General Surgery,, Ruijin Hospital Luwan Branch, Shanghai Jiaotong University School of Medicine

Email: info@benthamscience.net

Ya’nan Yang

Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center

Email: info@benthamscience.net

Yantian Fang

Department of Oncology, Shanghai Medical College, Fudan University

Author for correspondence.
Email: info@benthamscience.net

References

  1. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin., 2021, 71(3), 209-249. doi: 10.3322/caac.21660 PMID: 33538338
  2. Chen, L.; Lu, L.; Gong, X.; Xu, Y.; Chu, X.; Huang, G. Gastric cancer with bone marrow invasion and disseminated intravascular coagulation: A case report. Oncologie, 2022, 24(3), 599-604. doi: 10.32604/oncologie.2022.023310
  3. Han, F; Qu, J; Li, F; Zhang, D; Qu, J; Li, G. Serum long non-coding RNA CCAT2 is a potential diagnostic and prognostic marker for gastric cancer. Oncologie, 2021, 23(1), 131-140. doi: 10.32604/Oncologie.2021.014153
  4. Cao, M.; Li, H.; Sun, D.; He, S.; Yan, X.; Yang, F.; Zhang, S.; Xia, C.; Lei, L.; Peng, J.; Chen, W. Current cancer burden in China: Epidemiology, etiology, and prevention. Cancer Biol. Med., 2022, 19(8), 1121-1138. doi: 10.20892/j.issn.2095-3941.2022.0231 PMID: 36069534
  5. Wang, D.; Chen, H.; Hu, Y. Polarized Autologous Macrophages (PAM) can be a tumor vaccine. Oncologie, 2022, 24(3), 441-449. doi: 10.32604/oncologie.2022.024898
  6. Li, K.; Zhang, A.; Li, X.; Zhang, H.; Zhao, L. Advances in clinical immunotherapy for gastric cancer. Biochimica et Biophysica Acta (BBA)-. Rev. Can., 2021, 1876(2), 188615.
  7. Fu, Q.; Zhang, X.; Zhang, Y. The presence of human papillomavirus and Epstein-Barr virus in male Chinese lichen sclerosus patients: A single center study. Asian J. Androl., 2016, 18(4), 650-653. doi: 10.4103/1008-682X.160261 PMID: 26289401
  8. Kwak, Y.; Seo, A.N.; Lee, H.E.; Lee, H.S. Tumor immune response and immunotherapy in gastric cancer. J. Pathol. Transl. Med., 2020, 54(1), 20-33. doi: 10.4132/jptm.2019.10.08 PMID: 31674166
  9. Fu, Y.; Du, P.; Zhao, J.; Hu, C.; Qin, Y.; Huang, G. Gastric cancer stem cells: Mechanisms and therapeutic approaches. Yonsei Med. J., 2018, 59(10), 1150-1158. doi: 10.3349/ymj.2018.59.10.1150 PMID: 30450848
  10. Galassi, C.; Musella, M.; Manduca, N.; Maccafeo, E.; Sistigu, A. The immune privilege of cancer stem cells: A key to understanding tumor immune escape and therapy failure. Cells, 2021, 10(9), 2361. doi: 10.3390/cells10092361 PMID: 34572009
  11. Chen, X.; Zhang, D.; Jiang, F.; Shen, Y.; Li, X.; Hu, X.; Wei, P.; Shen, X. Prognostic prediction using a stemness index-related signature in a cohort of gastric cancer. Front. Mol. Biosci., 2020, 7, 570702. doi: 10.3389/fmolb.2020.570702 PMID: 33134315
  12. Liu, M.; Zhou, R.; Zou, W.; Yang, Z.; Li, Q.; Chen, Z.; jiang, L.; Zhang, J. Machine learning-identified stemness features and constructed stemness-related subtype with prognosis, chemotherapy, and immunotherapy responses for non-small cell lung cancer patients. Stem Cell Res. Ther., 2023, 14(1), 238. doi: 10.1186/s13287-023-03406-4 PMID: 37674202
  13. Yi, L.; Huang, P.; Zou, X.; Guo, L.; Gu, Y.; Wen, C.; Wu, G. Integrative stemness characteristics associated with prognosis and the immune microenvironment in esophageal cancer. Pharmacol. Res., 2020, 161, 105144. doi: 10.1016/j.phrs.2020.105144 PMID: 32810627
  14. Zheng, H.; Liu, H.; Li, H.; Dou, W.; Wang, J.; Zhang, J.; Liu, T.; Wu, Y.; Liu, Y.; Wang, X. Characterization of stem cell landscape and identification of stemness-relevant prognostic gene signature to aid immunotherapy in colorectal cancer. Stem Cell Res. Ther., 2022, 13(1), 244. doi: 10.1186/s13287-022-02913-0 PMID: 35681225
  15. Lu, X.; Ying, Y.; Zhang, W.; Li, R.; Wang, W. Identification of stemness subtypes and features to improve endometrial cancer treatment using machine learning. Artif. Cells Nanomed. Biotechnol., 2023, 51(1), 57-73. doi: 10.1080/21691401.2023.2172027 PMID: 36748358
  16. Yang, F; Gan, L; Pan, J; Chen, Y; Zhang, H; Huang, L. Integrated single-cell RNA-sequencing analysis of gastric cancer identifies FABP1 as a novel prognostic biomarker. J Oncol., 2022, 2022, 4761403.
  17. Gulati, G.S.; Sikandar, S.S.; Wesche, D.J.; Manjunath, A.; Bharadwaj, A.; Berger, M.J.; Ilagan, F.; Kuo, A.H.; Hsieh, R.W.; Cai, S.; Zabala, M.; Scheeren, F.A.; Lobo, N.A.; Qian, D.; Yu, F.B.; Dirbas, F.M.; Clarke, M.F.; Newman, A.M. Single-cell transcriptional diversity is a hallmark of developmental potential. Science, 2020, 367(6476), 405-411. doi: 10.1126/science.aax0249 PMID: 31974247
  18. Yu, G.; Wang, L.G.; Han, Y.; He, Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS, 2012, 16(5), 284-287. doi: 10.1089/omi.2011.0118 PMID: 22455463
  19. Danilova, L.; Ho, W.J.; Zhu, Q.; Vithayathil, T.; De Jesus-Acosta, A.; Azad, N.S.; Laheru, D.A.; Fertig, E.J.; Anders, R.; Jaffee, E.M.; Yarchoan, M. Programmed cell death ligand-1 (PD-L1) and CD8 expression profiling identify an immunologic subtype of pancreatic ductal adenocarcinomas with favorable survival. Cancer Immunol. Res., 2019, 7(6), 886-895. doi: 10.1158/2326-6066.CIR-18-0822 PMID: 31043417
  20. Jiang, P.; Gu, S.; Pan, D.; Fu, J.; Sahu, A.; Hu, X.; Li, Z.; Traugh, N.; Bu, X.; Li, B.; Liu, J.; Freeman, G.J.; Brown, M.A.; Wucherpfennig, K.W.; Liu, X.S. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat. Med., 2018, 24(10), 1550-1558. doi: 10.1038/s41591-018-0136-1 PMID: 30127393
  21. Ritchie, ME; Phipson, B; Wu, D; Hu, Y; Law, CW; Shi, W limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res., 2015, 43(7), e47.
  22. Langfelder, P.; Horvath, S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics, 2008, 9(1), 559. doi: 10.1186/1471-2105-9-559 PMID: 19114008
  23. Liao, Y.; Wang, J.; Jaehnig, E.J.; Shi, Z.; Zhang, B. WebGestalt 2019: Gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Res., 2019, 47(W1), W199-W205. doi: 10.1093/nar/gkz401 PMID: 31114916
  24. Hastie, T.; Qian, J.; Tay, K. An Introduction to glmnet; CRAN R Repositary, 2021.
  25. Charoentong, P.; Finotello, F.; Angelova, M.; Mayer, C.; Efremova, M.; Rieder, D.; Hackl, H.; Trajanoski, Z. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep., 2017, 18(1), 248-262. doi: 10.1016/j.celrep.2016.12.019 PMID: 28052254
  26. Balar, A.V.; Galsky, M.D.; Rosenberg, J.E.; Powles, T.; Petrylak, D.P.; Bellmunt, J.; Loriot, Y.; Necchi, A.; Hoffman-Censits, J.; Perez-Gracia, J.L.; Dawson, N.A.; van der Heijden, M.S.; Dreicer, R.; Srinivas, S.; Retz, M.M.; Joseph, R.W.; Drakaki, A.; Vaishampayan, U.N.; Sridhar, S.S.; Quinn, D.I.; Durán, I.; Shaffer, D.R.; Eigl, B.J.; Grivas, P.D.; Yu, E.Y.; Li, S.; Kadel, E.E., III; Boyd, Z.; Bourgon, R.; Hegde, P.S.; Mariathasan, S.; Thåström, A.; Abidoye, O.O.; Fine, G.D.; Bajorin, D.F. Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: A single-arm, multicentre, phase 2 trial. Lancet, 2017, 389(10064), 67-76. doi: 10.1016/S0140-6736(16)32455-2 PMID: 27939400
  27. Hugo, W.; Zaretsky, J.M.; Sun, L.; Song, C.; Moreno, B.H.; Hu-Lieskovan, S.; Berent-Maoz, B.; Pang, J.; Chmielowski, B.; Cherry, G.; Seja, E.; Lomeli, S.; Kong, X.; Kelley, M.C.; Sosman, J.A.; Johnson, D.B.; Ribas, A.; Lo, R.S. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell, 2016, 165(1), 35-44. doi: 10.1016/j.cell.2016.02.065 PMID: 26997480
  28. Hass, R.; von der Ohe, J.; Ungefroren, H. Impact of the tumor microenvironment on tumor heterogeneity and consequences for cancer cell plasticity and stemness. Cancers, 2020, 12(12), 3716. doi: 10.3390/cancers12123716 PMID: 33322354
  29. Sarvaria, A.; Madrigal, J.A.; Saudemont, A. B cell regulation in cancer and anti-tumor immunity. Cell. Mol. Immunol., 2017, 14(8), 662-674. doi: 10.1038/cmi.2017.35 PMID: 28626234
  30. Miranda, A.; Hamilton, P.T.; Zhang, A.W.; Pattnaik, S.; Becht, E.; Mezheyeuski, A.; Bruun, J.; Micke, P.; de Reynies, A.; Nelson, B.H. Cancer stemness, intratumoral heterogeneity, and immune response across cancers. Proc. Natl. Acad. Sci., 2019, 116(18), 9020-9029. doi: 10.1073/pnas.1818210116 PMID: 30996127
  31. Zhang, Z.; Wang, Z.X.; Chen, Y.X.; Wu, H.X.; Yin, L.; Zhao, Q.; Luo, H.Y.; Zeng, Z.L.; Qiu, M.Z.; Xu, R.H. Integrated analysis of single-cell and bulk RNA sequencing data reveals a pan-cancer stemness signature predicting immunotherapy response. Genome Med., 2022, 14(1), 45. doi: 10.1186/s13073-022-01050-w PMID: 35488273
  32. Chen, P.; Hsu, W.H.; Han, J.; Xia, Y.; DePinho, R.A. Cancer stemness meets immunity: From mechanism to therapy. Cell Rep., 2021, 34(1), 108597. doi: 10.1016/j.celrep.2020.108597 PMID: 33406434
  33. Wang, J.; Ren, H.; Wu, W.; Zeng, Q.; Chen, J.; Han, J.; Lin, M.; Zhang, C.; He, Y.; Li, M. Immune infiltration, cancer stemness, and targeted therapy in gastrointestinal stromal tumor. Front. Immunol., 2021, 12, 691713. doi: 10.3389/fimmu.2021.691713 PMID: 34925310
  34. Wang, W; Xu, C; Ren, Y; Wang, S; Liao, C; Fu, X A novel cancer stemness-related signature for predicting prognosis in patients with colon adenocarcinoma. Stem Cells Int, 2021, 2021, 7036059. doi: 10.1155/2021/7036059
  35. Anselmi, M.; Fontana, F.; Marzagalli, M.; Gagliano, N.; Sommariva, M.; Limonta, P. Melanoma stem cells educate neutrophils to support cancer progression. Cancers, 2022, 14(14), 3391. doi: 10.3390/cancers14143391 PMID: 35884452
  36. Gener, P; Seras-Franzoso, J; Callejo, PG; Andrade, F; Rafael, D; Martínez, F Dynamism, sensitivity, and consequences of mesenchymal and stem-like phenotype of cancer cells. Stem Cells Int., 2018, 2018, 4516454. doi: 10.1155/2018/4516454
  37. Dai, W.; Li, Y.; Mo, S.; Feng, Y.; Zhang, L.; Xu, Y.; Li, Q.; Cai, G. A robust gene signature for the prediction of early relapse in stage I–III colon cancer. Mol. Oncol., 2018, 12(4), 463-475. doi: 10.1002/1878-0261.12175 PMID: 29377588
  38. De Francesco, E.M.; Maggiolini, M.; Tanowitz, H.B.; Sotgia, F.; Lisanti, M.P. Targeting hypoxic cancer stem cells (CSCs) with Doxycycline: Implications for optimizing anti-angiogenic therapy. Oncotarget, 2017, 8(34), 56126-56142. doi: 10.18632/oncotarget.18445 PMID: 28915578
  39. Li, X.; Cao, Y.; Yu, X.; Jin, F.; Li, Y. A novel autophagy-related genes prognostic risk model and validation of autophagy-related oncogene VPS35 in breast cancer. Cancer Cell Int., 2021, 21(1), 265. doi: 10.1186/s12935-021-01970-4 PMID: 34001111
  40. Wu, Q.; Fu, C.; Li, M.; Li, J.; Li, Z.; Qi, L.; Ci, X.; Ma, G.; Gao, A.; Fu, X.; A, J.; An, N.; Liu, M.; Li, Y.; King, J.L.; Fu, L.; Zhang, B.; Dong, J.T. CINP is a novel cofactor of KLF5 required for its role in the promotion of cell proliferation, survival and tumor growth. Int. J. Cancer, 2019, 144(3), 582-594. doi: 10.1002/ijc.31908 PMID: 30289973

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