Skip to content
2000
image of Establishment of Centrosome Amplification-Correlated Model to Evaluate the Tumor Immune Microenvironment and Prognosis of Patients with Glioblastoma

Abstract

Introduction

Centrosome Amplification (CA) is a state where malignant cells contain excessive centrosomes due to cell cycle dysregulation. Altered CA has been observed in Glioblastoma (GBM). This study developed a CA-related gene model to assess the Tumor Immune Microenvironment (TIME) and prognostic outcomes for patients with GBM.

Methods

TCGA-GBM and mRNAseq_325 cohorts were obtained from the Chinese Glioma Genome Atlas (CGGA) database. CA-relevant gene modules and feature genes were identified WGCNA analysis. Key genes were selected to develop a risk model, followed by validation of the model’s performance. We further compared the gene mutation landscape, TIME characteristics, drug sensitivity, and enriched pathways between high- and low-risk patient groups.

Results

The brown module, which showed the highest correlation with CA, was selected to identify CA-related key genes to develop a Riskscore model. The model can accurately categorize patients into high- and low-risk groups and predict their clinical outcomes with precision. Notably, high-risk GBM patients exhibited higher StromalScore and dendritic score, and the Riskscore was positively correlated with fibroblast infiltration. Moreover, patients with different risk levels displayed distinct enriched pathways and gene mutation landscapes. Further, the high-risk group showed an evidently higher CAF score, and the differential relation between drug sensitivity and the Riskscore was detected.

Discussion

Though CA was altered in GBM, its prognostic utility remained to be explored. The current study addressed this gap by developing a 6-gene risk model capable of predicting the prognosis and TIME of GBM patients.

Conclusion

A CA-related model was constructed to assess the prognosis and TIME of GBM patients, contributing to the management of GBM in clinical practice.

Loading

Article metrics loading...

/content/journals/cmc/10.2174/0109298673425433251104052702
2026-01-08
2026-02-22
Loading full text...

Full text loading...

References

  1. Schaff L.R. Mellinghoff I.K. Glioblastoma and other primary brain malignancies in adults. JAMA 2023 329 7 574 587 10.1001/jama.2023.0023 36809318
    [Google Scholar]
  2. Venkataramani V. Yang Y. Schubert M.C. Reyhan E. Tetzlaff S.K. Wißmann N. Botz M. Soyka S.J. Beretta C.A. Pramatarov R.L. Fankhauser L. Garofano L. Freudenberg A. Wagner J. Tanev D.I. Ratliff M. Xie R. Kessler T. Hoffmann D.C. Hai L. Dörflinger Y. Hoppe S. Yabo Y.A. Golebiewska A. Niclou S.P. Sahm F. Lasorella A. Slowik M. Döring L. Iavarone A. Wick W. Kuner T. Winkler F. Glioblastoma hijacks neuronal mechanisms for brain invasion. Cell 2022 185 16 2899 2917.e31 10.1016/j.cell.2022.06.054 35914528
    [Google Scholar]
  3. Zhang L. He S. Wu L. Wang X. Bai Y. Current advancements in PD-L1 modulation by CMTM6 in malignant tumors. Oncologie 2025 27 1 45 55 10.1515/oncologie‑2024‑0377
    [Google Scholar]
  4. Roda D. Veiga P. Melo J.B. Carreira I.M. Ribeiro I.P. Principles in the management of glioblastoma. Genes (Basel) 2024 15 4 501 10.3390/genes15040501 38674436
    [Google Scholar]
  5. Chang C. Chavarro V.S. Gerstl J.V.E. Blitz S.E. Spanehl L. Dubinski D. Valdes P.A. Tran L.N. Gupta S. Esposito L. Mazzetti D. Gessler F.A. Arnaout O. Smith T.R. Friedman G.K. Peruzzi P. Bernstock J.D. Recurrent glioblastoma-molecular underpinnings and evolving treatment paradigms. Int. J. Mol. Sci. 2024 25 12 6733 10.3390/ijms25126733 38928445
    [Google Scholar]
  6. Marenco-Hillembrand L. Wijesekera O. Suarez-Meade P. Mampre D. Jackson C. Peterson J. Trifiletti D. Hammack J. Ortiz K. Lesser E. Spiegel M. Prevatt C. Hawayek M. Quinones-Hinojosa A. Chaichana K.L. Trends in glioblastoma: Outcomes over time and type of intervention: A systematic evidence based analysis. J. Neurooncol. 2020 147 2 297 307 10.1007/s11060‑020‑03451‑6 32157552
    [Google Scholar]
  7. van Linde M.E. Brahm C.G. de Witt Hamer P.C. Reijneveld J.C. Bruynzeel A.M.E. Vandertop W.P. van de Ven P.M. Wagemakers M. van der Weide H.L. Enting R.H. Walenkamp A.M.E. Verheul H.M.W. Treatment outcome of patients with recurrent glioblastoma multiforme: A retrospective multicenter analysis. J. Neurooncol. 2017 135 1 183 192 10.1007/s11060‑017‑2564‑z 28730289
    [Google Scholar]
  8. Tarin M. Oryani M.A. Javid H. Karimi-Shahri M. Exosomal PD-L1 in non-small cell lung Cancer: Implications for immune evasion and resistance to immunotherapy. Int. Immunopharmacol. 2025 155 114519 10.1016/j.intimp.2025.114519 40199140
    [Google Scholar]
  9. Rastin F. Javid H. Oryani M.A. Rezagholinejad N. Afshari A.R. Karimi-Shahri M. Immunotherapy for colorectal cancer: Rational strategies and novel therapeutic progress. Int. Immunopharmacol. 2024 126 111055 10.1016/j.intimp.2023.111055 37992445
    [Google Scholar]
  10. Zhao J.Z. Ye Q. Wang L. Lee S.C. Centrosome amplification in cancer and cancer-associated human diseases. Biochim. Biophys. Acta. Rev. Cancer 2021 1876 1 188566 10.1016/j.bbcan.2021.188566 33992724
    [Google Scholar]
  11. Holland A.J. Lan W. Cleveland D.W. Centriole duplication. Cell Cycle 2010 9 14 2803 2808 10.4161/cc.9.14.12184 20647763
    [Google Scholar]
  12. Loncarek J. Khodjakov A. Ab ovo or de novo? Mechanisms of centriole duplication. Mol. Cells 2009 27 2 135 142 10.1007/s10059‑009‑0017‑z 19277494
    [Google Scholar]
  13. D’Assoro A.B. Lingle W.L. Salisbury J.L. Centrosome amplification and the development of cancer. Oncogene 2002 21 40 6146 6153 10.1038/sj.onc.1205772 12214243
    [Google Scholar]
  14. Marteil G. Guerrero A. Vieira A.F. de Almeida B.P. Machado P. Mendonça S. Mesquita M. Villarreal B. Fonseca I. Francia M.E. Dores K. Martins N.P. Jana S.C. Tranfield E.M. Barbosa-Morais N.L. Paredes J. Pellman D. Godinho S.A. Bettencourt-Dias M. Over-elongation of centrioles in cancer promotes centriole amplification and chromosome missegregation. Nat. Commun. 2018 9 1 1258 10.1038/s41467‑018‑03641‑x 29593297
    [Google Scholar]
  15. Mittal K. Kaur J. Jaczko M. Wei G. Toss M.S. Rakha E.A. Janssen E.A.M. Søiland H. Kucuk O. Reid M.D. Gupta M.V. Aneja R. Centrosome amplification: A quantifiable cancer cell trait with prognostic value in solid malignancies. Cancer Metastasis Rev. 2021 40 1 319 339 10.1007/s10555‑020‑09937‑z 33106971
    [Google Scholar]
  16. de Freitas G.P.A. Geraldo L.H.M. Faria B.M. Alves-Leon S.V. de Souza J.M. Moura-Neto V. Pontes B. Romão L.F. Garcez P.P. Centromere protein J is overexpressed in human glioblastoma and promotes cell proliferation and migration. J. Neurochem. 2022 162 6 501 513 10.1111/jnc.15660 35797221
    [Google Scholar]
  17. Sonkin D. Thomas A. Teicher B.A. Cancer treatments: Past, present, and future. Cancer Genet. 2024 286-287 18 24 10.1016/j.cancergen.2024.06.002 38909530
    [Google Scholar]
  18. Liu H. Dong A. Rasteh A.M. Wang P. Weng J. Identification of the novel exhausted T cell CD8+ markers in breast cancer. Sci. Rep. 2024 14 1 19142 10.1038/s41598‑024‑70184‑1 39160211
    [Google Scholar]
  19. Liu H. Weng J. A comprehensive bioinformatic analysis of cyclin-dependent kinase 2 (CDK2) in glioma. Gene 2022 822 146325 10.1016/j.gene.2022.146325 35183683
    [Google Scholar]
  20. Liu H. Tang T. A bioinformatic study of IGFBPs in glioma regarding their diagnostic, prognostic, and therapeutic prediction value. Am. J. Transl. Res. 2023 15 3 2140 2155 37056850
    [Google Scholar]
  21. Liu H. Weng J. Huang C.L.H. Jackson A.P. Is the voltage-gated sodium channel β3 subunit (SCN3B) a biomarker for glioma? Funct. Integr. Genomics 2024 24 5 162 10.1007/s10142‑024‑01443‑7 39289188
    [Google Scholar]
  22. Liu H. Expression and potential immune involvement of cuproptosis in kidney renal clear cell carcinoma. Cancer Genet. 2023 274-275 21 25 10.1016/j.cancergen.2023.03.002 36963335
    [Google Scholar]
  23. Liu H. Li Y. Potential roles of Cornichon Family AMPA Receptor Auxiliary Protein 4 (CNIH4) in head and neck squamous cell carcinoma. Cancer biomarkers: section. Dis. Markers 2022 35 4 439 450
    [Google Scholar]
  24. Li Y. Liu H. Clinical powers of Aminoacyl tRNA Synthetase Complex Interacting Multifunctional Protein 1 (AIMP1) for head-neck squamous cell carcinoma. Cancer Biomark. 2022 34 3 359 374 10.3233/CBM‑210340 35068446
    [Google Scholar]
  25. Ou L. Liu H. Peng C. Zou Y. Jia J. Li H. Feng Z. Zhang G. Yao M. Helicobacter pylori infection facilitates cell migration and potentially impact clinical outcomes in gastric cancer. Heliyon 2024 10 17 e37046 10.1016/j.heliyon.2024.e37046 39286209
    [Google Scholar]
  26. Qiu J. Zhou T. Wang D. Hong W. Qian D. Meng X. Liu X. Pan-cancer analysis identifies AIMP2 as a potential biomarker for breast cancer. Curr. Genomics 2023 24 5 307 329 10.2174/0113892029255941231014142050 38235352
    [Google Scholar]
  27. Zhao Z. Zhang K.N. Wang Q. Li G. Zeng F. Zhang Y. Wu F. Chai R. Wang Z. Zhang C. Zhang W. Bao Z. Jiang T. Chinese Glioma Genome Atlas (CGGA): A comprehensive resource with functional genomic data from chinese glioma patients. Genomic. Proteom. Bioinform. 2021 19 1 1 12 10.1016/j.gpb.2020.10.005 33662628
    [Google Scholar]
  28. Yan S. Han Z. Wang T. Wang A. Liu F. Yu S. Xu L. Shen H. Liu L. Lin Z. Na M. Exploring the immune-related molecular mechanisms underlying the comorbidity of temporal lobe epilepsy and major depressive disorder through integrated data set analysis. Curr. Mol. Pharmacol. 2025 17 17 10.2174/0118761429380394250217093030 39976098
    [Google Scholar]
  29. Langfelder P. Horvath S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics 2008 9 1 559 10.1186/1471‑2105‑9‑559 19114008
    [Google Scholar]
  30. Song Z. Yu J. Wang M. Shen W. Wang C. Lu T. Shan G. Dong G. Wang Y. Zhao J. CHDTEPDB: Transcriptome expression profile database and interactive analysis platform for congenital heart disease. Congenit. Heart Dis. 2023 18 6 693 701 10.32604/chd.2024.048081
    [Google Scholar]
  31. Engebretsen S. Bohlin J. Statistical predictions with glmnet. Clin. Epigenetics 2019 11 1 123 10.1186/s13148‑019‑0730‑1 31443682
    [Google Scholar]
  32. Xu J. Huang L. Sha Y. Mo C. Gong W. Tian X. Hou X. Chen W. Ou M. High-throughput sequencing reveals crebanine inhibits colorectal cancer by modulating Tregs immune prognostic target genes. Oncologie 2024 26 4 643 656 10.1515/oncologie‑2024‑0073
    [Google Scholar]
  33. Shi Y. Wang Y. Dong H. Niu K. Zhang W. Feng K. Yang R. Zhang Y. Crosstalk of ferroptosis regulators and tumor immunity in pancreatic adenocarcinoma: Novel perspective to mRNA vaccines and personalized immunotherapy. Apoptosis 2023 28 9 1423 1435 10.1007/s10495‑023‑01846‑2
    [Google Scholar]
  34. Geeleher P. Cox N. Huang R.S. pRRophetic: An R package for prediction of clinical chemotherapeutic response from tumor gene expression levels. PLoS One 2014 9 9 e107468 10.1371/journal.pone.0107468 25229481
    [Google Scholar]
  35. Sabat-Pośpiech D. Fabian-Kolpanowicz K. Prior I.A. Coulson J.M. Fielding A.B. Targeting centrosome amplification, an Achilles’ heel of cancer. Biochem. Soc. Trans. 2019 47 5 1209 1222 10.1042/BST20190034 31506331
    [Google Scholar]
  36. Marthiens V. Rujano M.A. Pennetier C. Tessier S. Paul-Gilloteaux P. Basto R. Centrosome amplification causes microcephaly. Nat. Cell Biol. 2013 15 7 731 740 10.1038/ncb2746 23666084
    [Google Scholar]
  37. Klein A. Reichardt W. Jung V. Zang K. Meese E. Urbschat S. Overexpression and amplification of STK15 in human gliomas. Int. J. Oncol. 2004 25 6 1789 1794 10.3892/ijo.25.6.1789 15547718
    [Google Scholar]
  38. Yuan Q. Gao W. Guo M. Liu B. Identifying and validating necroptosis-associated features to predict clinical outcome and immunotherapy response in patients with glioblastoma. Environ. Toxicol. 2024 39 10 4729 4743 10.1002/tox.24309 39162363
    [Google Scholar]
  39. Hu J. Xu L. Fu W. Sun Y. Wang N. Zhang J. Yang C. Zhang X. Zhou Y. Wang R. Zhang H. Mou R. Du X. Li X. Hu S. Xie R. Development and validation a prognostic model based on natural killer T cells marker genes for predicting prognosis and characterizing immune status in glioblastoma through integrated analysis of single-cell and bulk RNA sequencing. Funct. Integr. Genomics 2023 23 3 286 10.1007/s10142‑023‑01217‑7 37650991
    [Google Scholar]
  40. Abate M. Laezza C. Pisanti S. Torelli G. Seneca V. Catapano G. Montella F. Ranieri R. Notarnicola M. Gazzerro P. Bifulco M. Ciaglia E. Deregulated expression and activity of farnesyl diphosphate synthase (FDPS) in glioblastoma. Sci. Rep. 2017 7 1 14123 10.1038/s41598‑017‑14495‑6 29075041
    [Google Scholar]
  41. Cao R. Liu Y. Wei K. Jin N. Liang Y. Ao R. Pan W. Wang X. Wang X. Zhang L. Xie J. Genes related to neural tube defects and glioblastoma. Sci. Rep. 2025 15 1 3777 10.1038/s41598‑025‑86891‑2 39885289
    [Google Scholar]
  42. Saurty-Seerunghen M.S. Daubon T. Bellenger L. Delaunay V. Castro G. Guyon J. Rezk A. Fabrega S. Idbaih A. Almairac F. Burel-Vandenbos F. Turchi L. Duplus E. Virolle T. Peyrin J.M. Antoniewski C. Chneiweiss H. El-Habr E.A. Junier M.P. Glioblastoma cell motility depends on enhanced oxidative stress coupled with mobilization of a sulfurtransferase. Cell Death Dis. 2022 13 10 913 10.1038/s41419‑022‑05358‑8 36310164
    [Google Scholar]
  43. Tang Q. Li Y. He J. MANF: an emerging therapeutic target for metabolic diseases. Trends Endocrinol. Metab. 2022 33 4 236 246 10.1016/j.tem.2022.01.001 35135706
    [Google Scholar]
  44. Xiong Z. Yang L. Zhang C. Huang W. Zhong W. Yi J. Feng J. Zouxu X. Song L. Wang X. MANF facilitates breast cancer cell survival under glucose-starvation conditions via PRKN-mediated mitophagy regulation. Autophagy 2025 21 1 80 101 10.1080/15548627.2024.2392415 39147386
    [Google Scholar]
  45. Jiaze Y. Sinan H. Minjie Y. Yongjie Z. Nan D. Liangwen W. Wen Z. Jianjun L. Zhiping Y. Rcl1 suppresses tumor progression of hepatocellular carcinoma: A comprehensive analysis of bioinformatics and in vitro experiments. Cancer Cell Int. 2022 22 1 114 10.1186/s12935‑022‑02533‑x 35264160
    [Google Scholar]
  46. Sharaby Y. Lahmi R. Amar O. Elbaz I. Lerer-Goldshtein T. Weiss A.M. Appelbaum L. Tzur A. Gas2l3 is essential for brain morphogenesis and development. Dev. Biol. 2014 394 2 305 313 10.1016/j.ydbio.2014.08.006 25131197
    [Google Scholar]
  47. Liu H. Karsidag M. Chhatwal K. Wang P. Tang T. Single-cell and bulk RNA sequencing analysis reveals CENPA as a potential biomarker and therapeutic target in cancers. PLoS One 2025 20 1 e0314745 10.1371/journal.pone.0314745 39820192
    [Google Scholar]
  48. Liu H. Dilger J.P. Different strategies for cancer treatment: Targeting cancer cells or their neighbors? Chin. J. Cancer Res. 2025 37 2 289 292 10.21147/j.issn.1000‑9604.2025.02.015
    [Google Scholar]
  49. Wang L.J. Xue Y. Lou Y. Tumor-associated macrophages related signature in glioma. Aging (Albany NY) 2022 14 6 2720 2735 10.18632/aging.203968 35332109
    [Google Scholar]
  50. Srivastava S. Jackson C. Kim T. Choi J. Lim M. A characterization of dendritic cells and their role in immunotherapy in glioblastoma: From preclinical studies to clinical trials. Cancers 2019 11 4 537 10.3390/cancers11040537 30991681
    [Google Scholar]
  51. Marino S. Menna G. Di Bonaventura R. Lisi L. Mattogno P. Figà F. Bilgin L. D’Alessandris Q.G. Olivi A. Della Pepa G.M. The extracellular matrix in glioblastomas: A glance at its structural modifications in shaping the tumoral microenvironment: A systematic review. Cancers 2023 15 6 1879 10.3390/cancers15061879 36980765
    [Google Scholar]
  52. Encarnação C.C. Faria G.M. Franco V.A. Botelho L.G.X. Moraes J.A. Renovato-Martins M. Interconnections within the tumor microenvironment: Extracellular vesicles as critical players of metabolic reprogramming in tumor cells. J. Cancer Metastasis Treat. 2024 10 0 28 10.20517/2394‑4722.2024.78
    [Google Scholar]
  53. Fan W. Wang D. Li G. Xu J. Ren C. Sun Z. Wang Z. Ma W. Zhao Z. Bao Z. Jiang T. Zhang Y. A novel chemokine-based signature for prediction of prognosis and therapeutic response in glioma. CNS Neurosci. Ther. 2022 28 12 2090 2103 10.1111/cns.13944 35985661
    [Google Scholar]
  54. Tong M. Xu Z. Wang L. Chen H. Wan X. Xu H. Yang S. Tu Q. An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism. Neurobiol. Dis. 2025 211 106935 10.1016/j.nbd.2025.106935 40348204
    [Google Scholar]
  55. Yang J. Shen L. Yang J. Qu Y. Gong C. Zhou F. Liu Y. Luo M. Zhao L. Complement and coagulation cascades are associated with prognosis and the immune microenvironment of lower-grade glioma. Transl. Cancer Res. 2024 13 1 112 136 10.21037/tcr‑23‑906 38410234
    [Google Scholar]
  56. Barros C.S. Franco S.J. Müller U. Extracellular matrix: Functions in the nervous system. Cold Spring Harb. Perspect. Biol. 2011 3 1 a005108 10.1101/cshperspect.a005108 21123393
    [Google Scholar]
  57. Zeng H.L. Li H. Yang Q. Li C.X. Transcriptomic characterization of copper-binding proteins for predicting prognosis in glioma. Brain Sci. 2023 13 10 1460 10.3390/brainsci13101460 37891828
    [Google Scholar]
  58. Hariharan S. Whitfield B.T. Pirozzi C.J. Waitkus M.S. Brown M.C. Bowie M.L. Irvin D.M. Roso K. Fuller R. Hostettler J. Dharmaiah S. Gibson E.A. Briley A. Mangoli A. Fraley C. Shobande M. Stevenson K. Zhang G. Malgulwar P.B. Roberts H. Roskoski M. Spasojevic I. Keir S.T. He Y. Castro M.G. Huse J.T. Ashley D.M. Interplay between ATRX and IDH1 mutations governs innate immune responses in diffuse gliomas. Nat. Commun. 2024 15 1 730 10.1038/s41467‑024‑44932‑w 38272925
    [Google Scholar]
  59. Zhao J. Chen A.X. Gartrell R.D. Silverman A.M. Aparicio L. Chu T. Bordbar D. Shan D. Samanamud J. Mahajan A. Filip I. Orenbuch R. Goetz M. Yamaguchi J.T. Cloney M. Horbinski C. Lukas R.V. Raizer J. Rae A.I. Yuan J. Canoll P. Bruce J.N. Saenger Y.M. Sims P. Iwamoto F.M. Sonabend A.M. Rabadan R. Immune and genomic correlates of response to anti-PD-1 immunotherapy in glioblastoma. Nat. Med. 2019 25 3 462 469 10.1038/s41591‑019‑0349‑y 30742119
    [Google Scholar]
  60. Hao Z. Guo D. EGFR mutation: Novel prognostic factor associated with immune infiltration in lower-grade glioma; an exploratory study. BMC Cancer 2019 19 1 1184 10.1186/s12885‑019‑6384‑8 31801484
    [Google Scholar]
  61. Hossain S.M. Shetty J. Tha K.K. Chowdhury E.H. α-Ketoglutaric acid-modified carbonate apatite enhances cellular uptake and cytotoxicity of a raf-kinase inhibitor in breast cancer cells through inhibition of MAPK and PI-3 kinase pathways. Biomedicines 2019 7 1 4 10.3390/biomedicines7010004 30609867
    [Google Scholar]
  62. Dinoto A. Cheli M. Bratina A. Sartori A. Manganotti P. Bortezomib in anti-N-Methyl-d-Aspartate-Receptor (NMDA-R) encephalitis: A systematic review. J. Neuroimmunol. 2021 356 577586 10.1016/j.jneuroim.2021.577586 33975246
    [Google Scholar]
  63. Wen Y.D. Zhu X.S. Li D.J. Zhao Q. Cheng Q. Peng Y. Proteomics-based prognostic signature and nomogram construction of hypoxia microenvironment on deteriorating glioblastoma (GBM) pathogenesis. Sci. Rep. 2021 11 1 17170 10.1038/s41598‑021‑95980‑x 34446747
    [Google Scholar]
  64. Jin Z. Zhang W. Liu H. Ding A. Lin Y. Wu S.X. Lin J. Potential therapeutic application of local anesthetics in cancer treatment. Recent Patent. Anticancer. Drug. Discov. 2022 17 4 326 342 10.2174/1574892817666220119121204 35043766
    [Google Scholar]
  65. Ou L. Liu H. Shi X. Peng C. Zou Y. Jia J. Li H. Zhu Z. Wang Y. Su B. Lai Y. Chen M. Zhu W. Feng Z. Zhang G. Yao M. Terminalia chebula Retz. aqueous extract inhibits the Helicobacter pylori-induced inflammatory response by regulating the inflammasome signaling and ER-stress pathway. J. Ethnopharmacol. 2024 320 117428 10.1016/j.jep.2023.117428 37981121
    [Google Scholar]
  66. Liu H. Wang P. CRISPR screening and cell line IC50 data reveal novel key genes for trametinib resistance. Clin. Exp. Med. 2024 25 1 21 10.1007/s10238‑024‑01538‑2 39708249
    [Google Scholar]
  67. Liu H.R. Harnessing traditional medicine and biomarker- driven approaches to counteract Trichostatin A-induced esophageal cancer progression. World J. Gastroenterol. 2025 31 20 106443 10.3748/wjg.v31.i20.106443 40495945
    [Google Scholar]
  68. McBrearty N. Bahal D. Platero S. Fast-tracking drug development with biomarkers and companion diagnostics. J. Cancer Metastasis Treat. 2024 10 0 3 10.20517/2394‑4722.2023.134
    [Google Scholar]
  69. Ai X. Smith M.C. Feltus F.A. Generative adversarial networks applied to gene expression analysis: An interdisciplinary perspective. Comput. Syst. Oncol. 2023 3 3 e1050 10.1002/cso2.1050
    [Google Scholar]
/content/journals/cmc/10.2174/0109298673425433251104052702
Loading
/content/journals/cmc/10.2174/0109298673425433251104052702
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test