Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Medicinal Chemistry
  4. Fast Track Articles
  5. Fast Track Article
image of The Risk Genes SIRP5, CMC1, and ASAH1 as Potential Targets for the Diagnosis, Immunotherapy, and Treatment of Colon Adenocarcinoma by Single-Cell and Bulk RNA Sequencing Analysis

Abstract

Objective

Globally, one of the main causes of cancer-related mortality is Colon Adenocarcinoma (COAD). In this study, a new special Immune Cell Functions (ICF) risk model was constructed using single-cell and bulk RNA sequencing data to develop a new understanding and clinical applications for COAD.

Methods

The immune function gene sets were downloaded from a literature reference, and the COAD single-cell dataset GSE146771 was downloaded from the Tumour Immune Single Cell Hub database. Using Lasso analysis, a multiple gene signature was made from the enrichment scores of immune function gene sets that were enriched in different ways. Robust validation of the signature was then performed in multiple independent cohorts. After that, we built the model using a 10-fold cross-test and evaluated its independence for clinical usage using a nomogram. We also investigated the connection between signature and immune function, genetic variation, immunotherapy, and the cancer immunological microenvironment. Lastly, we used qPCR and immunohistochemistry to examine the expression of the unreported model genes. To find the regulatory functions of unreported model genes, an EdU assay was employed.

Results

First, 20 differentially enriched immune function gene sets were identified. Ten genes can be used as a risk profile to assess the prognosis of colon cancer, according to Lasso regression analysis. Signature performance was stable in both the training cohort and two independent GEO external cohorts, and risk scores were confirmed as independent prognostic factors. At the same time, our risk model continued to be highly predictive across various clinical clusters and clinical characteristics, such as immune checkpoints, tumour genome mutations, and chemotherapeutic drug resistance. Patients in the low-risk group have exhibited a higher chance of benefiting from immunotherapy, according to immunotherapy response research. qPCR and immunohistochemistry analysis have revealed SIRP5 expression as high in COAD tissues, while CMC1 and ASAH1 expression has been found to be low. According to the findings of the functional experiment, SIRP5, CMC1, and ASAH1 may control the ability of CRC cells to proliferate.

Conclusion

In this study, using scRNA-seq and bulk RNA-seq data, we created a risk model to predict the prognosis and effectiveness of immunotherapy in patients with COAD. In addition, we have discovered three model genes (SIRP5, CMC1, and ASAH1) that have not been reported before. These genes have the potential to be novel therapeutic targets in Colorectal Cancer (CRC). These findings suggest that this model could be used to evaluate the prognostic risk and identify potential targets for COAD patient treatment.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cmc/10.2174/0109298673331144241009082052
2024-11-07
2025-01-18

  • From This Site

    /content/journals/cmc/10.2174/0109298673331144241009082052
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Siegel R.L. Miller K.D. Fuchs H.E. Jemal A. Cancer statistics, 2022. CA Cancer J. Clin. 2022 72 1 7 33 10.3322/caac.21708 35020204
    [Google Scholar]
  2. 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 10.3322/caac.21660 33538338
    [Google Scholar]
  3. Dekker E. Tanis P.J. Vleugels J.L.A. Kasi P.M. Wallace M.B. Colorectal cancer. Lancet 2019 394 10207 1467 1480 10.1016/S0140‑6736(19)32319‑0 31631858
    [Google Scholar]
  4. Ciardiello F. Ciardiello D. Martini G. Napolitano S. Tabernero J. Cervantes A. Clinical management of metastatic colorectal cancer in the era of precision medicine. CA Cancer J. Clin. 2022 72 4 372 401 10.3322/caac.21728 35472088
    [Google Scholar]
  5. Brandi G. Ricci A.D. Rizzo A. Zanfi C. Tavolari S. Palloni A. De Lorenzo S. Ravaioli M. Cescon M. Is post‐transplant chemotherapy feasible in liver transplantation for colorectal cancer liver metastases? Cancer Commun. (Lond.) 2020 40 9 461 464 10.1002/cac2.12072 32762027
    [Google Scholar]
  6. Rizzo A. Mollica V. Tateo V. Tassinari E. Marchetti A. Rosellini M. De Luca R. Santoni M. Massari F. Hypertransaminasemia in cancer patients receiving immunotherapy and immune-based combinations: The MOUSEION-05 study. Cancer Immunol. Immunother. 2023 72 6 1381 1394 10.1007/s00262‑023‑03366‑x 36695827
    [Google Scholar]
  7. Guven D.C. Sahin T.K. Erul E. Rizzo A. Ricci A.D. Aksoy S. Yalcin S. The association between albumin levels and survival in patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis. Front. Mol. Biosci. 2022 9 1039121 10.3389/fmolb.2022.1039121 36533070
    [Google Scholar]
  8. Sahin T.K. Rizzo A. Aksoy S. Guven D.C. Prognostic Significance of the Royal Marsden Hospital (RMH) Score in Patients with Cancer: A Systematic Review and Meta-Analysis. Cancers (Basel) 2024 16 10 1835 10.3390/cancers16101835 38791914
    [Google Scholar]
  9. Rizzo A. Nannini M. Novelli M. Dalia Ricci A. Scioscio V.D. Pantaleo M.A. Dose reduction and discontinuation of standard-dose regorafenib associated with adverse drug events in cancer patients: A systematic review and meta-analysis. Ther. Adv. Med. Oncol. 2020 12 10.1177/1758835920936932 32684988
    [Google Scholar]
  10. Riedesser J.E. Ebert M.P. Betge J. Precision medicine for metastatic colorectal cancer in clinical practice. Ther. Adv. Med. Oncol. 2022 14 10.1177/17588359211072703 35237350
    [Google Scholar]
  11. Di Nicolantonio F. Vitiello P.P. Marsoni S. Siena S. Tabernero J. Trusolino L. Bernards R. Bardelli A. Precision oncology in metastatic colorectal cancer — From biology to medicine. Nat. Rev. Clin. Oncol. 2021 18 8 506 525 10.1038/s41571‑021‑00495‑z 33864051
    [Google Scholar]
  12. Di Z. Zhou S. Xu G. Ren L. Li C. Ding Z. Huang K. Liang L. Yuan Y. Single-cell and WGCNA uncover a prognostic model and potential oncogenes in colorectal cancer. Biol. Proced. Online 2022 24 1 13 10.1186/s12575‑022‑00175‑x 36117173
    [Google Scholar]
  13. Sun W. Shen J. Liu J. Han K. Liang L. Gao Y. Gene Signature and Prognostic Value of Ubiquitin-Specific Proteases Members in Hepatocellular Carcinoma and Explored the Immunological Role of USP36. Frontiers in Bioscience-Landmark 2022 27 6 190 10.31083/j.fbl2706190 35748266
    [Google Scholar]
  14. Yuan Y. Wang J. Xu M. Zhang Y. Wang Z. Liang L. Sun P. 20(S)-ginsenoside Rh2 as agent for the treatment of LMN-CRC via regulating epithelial–mesenchymal transition. Biosci. Rep. 2020 40 3 BSR20191507 10.1042/BSR20191507 32141497
    [Google Scholar]
  15. Hinshaw D.C. Shevde L.A. The Tumor Microenvironment Innately Modulates Cancer Progression. Cancer Res. 2019 79 18 4557 4566 10.1158/0008‑5472.CAN‑18‑3962 31350295
    [Google Scholar]
  16. Lei X. Lei Y. Li J.K. Du W.X. Li R.G. Yang J. Li J. Li F. Tan H.B. Immune cells within the tumor microenvironment: Biological functions and roles in cancer immunotherapy. Cancer Lett. 2020 470 126 133 10.1016/j.canlet.2019.11.009 31730903
    [Google Scholar]
  17. Ascierto M.L. Kmieciak M. Idowu M.O. Manjili R. Zhao Y. Grimes M. Dumur C. Wang E. Ramakrishnan V. Wang X.Y. Bear H.D. Marincola F.M. Manjili M.H. A signature of immune function genes associated with recurrence-free survival in breast cancer patients. Breast Cancer Res. Treat. 2012 131 3 871 880 10.1007/s10549‑011‑1470‑x 21479927
    [Google Scholar]
  18. Kim K. Jeon S. Kim T.M. Jung C. Immune Gene Signature Delineates a Subclass of Papillary Thyroid Cancer with Unfavorable Clinical Outcomes. Cancers (Basel) 2018 10 12 494 10.3390/cancers10120494 30563160
    [Google Scholar]
  19. Shen S. Wang G. Zhang R. Zhao Y. Yu H. Wei Y. Chen F. Development and validation of an immune gene-set based Prognostic signature in ovarian cancer. EBioMedicine 2019 40 318 326 10.1016/j.ebiom.2018.12.054 30594555
    [Google Scholar]
  20. Liu Y. Wu J. Huang W. Weng S. Wang B. Chen Y. Wang H. Development and validation of a hypoxia-immune-based microenvironment gene signature for risk stratification in gastric cancer. J. Transl. Med. 2020 18 1 201 10.1186/s12967‑020‑02366‑0 32410620
    [Google Scholar]
  21. Yang W. Lai Z. Li Y. Mu J. Yang M. Xie J. Xu J. Immune signature profiling identified prognostic factors for gastric cancer. Chin. J. Cancer Res. 2019 31 3 463 470 10.21147/j.issn.1000‑9604.2019.03.08 31354215
    [Google Scholar]
  22. Owens B. Genomics: The single life. Nature 2012 491 7422 27 29 10.1038/491027a 23128208
    [Google Scholar]
  23. Xu Y. Wang Y. Liang L. Song N. Single-cell RNA sequencing analysis to explore immune cell heterogeneity and novel biomarkers for the prognosis of lung adenocarcinoma. Front. Genet. 2022 13 975542 10.3389/fgene.2022.975542 36147484
    [Google Scholar]
  24. Kolodziejczyk A.A. Kim J.K. Svensson V. Marioni J.C. Teichmann S.A. The technology and biology of single-cell RNA sequencing. Mol. Cell 2015 58 4 610 620 10.1016/j.molcel.2015.04.005 26000846
    [Google Scholar]
  25. Zappia L. Phipson B. Oshlack A. Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database. PLOS Comput. Biol. 2018 14 6 e1006245 10.1371/journal.pcbi.1006245 29939984
    [Google Scholar]
  26. Assefa A.T. Vandesompele J. Thas O. SPsimSeq: Semi-parametric simulation of bulk and single-cell RNA-sequencing data. Bioinformatics 2020 36 10 3276 3278 10.1093/bioinformatics/btaa105 32065619
    [Google Scholar]
  27. Liu J. Lichtenberg T. Hoadley K.A. Poisson L.M. Lazar A.J. Cherniack A.D. Kovatich A.J. Benz C.C. Levine D.A. Lee A.V. Omberg L. Wolf D.M. Shriver C.D. Thorsson V. Hu H. Caesar-Johnson S.J. Demchok J.A. Felau I. Kasapi M. Ferguson M.L. Hutter C.M. Sofia H.J. Tarnuzzer R. Wang Z. Yang L. Zenklusen J.C. Zhang J.J. Chudamani S. Liu J. Lolla L. Naresh R. Pihl T. Sun Q. Wan Y. Wu Y. Cho J. DeFreitas T. Frazer S. Gehlenborg N. Getz G. Heiman D.I. Kim J. Lawrence M.S. Lin P. Meier S. Noble M.S. Saksena G. Voet D. Zhang H. Bernard B. Chambwe N. Dhankani V. Knijnenburg T. Kramer R. Leinonen K. Liu Y. Miller M. Reynolds S. Shmulevich I. Thorsson V. Zhang W. Akbani R. Broom B.M. Hegde A.M. Ju Z. Kanchi R.S. Korkut A. Li J. Liang H. Ling S. Liu W. Lu Y. Mills G.B. Ng K-S. Rao A. Ryan M. Wang J. Weinstein J.N. Zhang J. Abeshouse A. Armenia J. Chakravarty D. Chatila W.K. de Bruijn I. Gao J. Gross B.E. Heins Z.J. Kundra R. La K. Ladanyi M. Luna A. Nissan M.G. Ochoa A. Phillips S.M. Reznik E. Sanchez-Vega F. Sander C. Schultz N. Sheridan R. Sumer S.O. Sun Y. Taylor B.S. Wang J. Zhang H. Anur P. Peto M. Spellman P. Benz C. Stuart J.M. Wong C.K. Yau C. Hayes D.N. Parker J.S. Wilkerson M.D. Ally A. Balasundaram M. Bowlby R. Brooks D. Carlsen R. Chuah E. Dhalla N. Holt R. Jones S.J.M. Kasaian K. Lee D. Ma Y. Marra M.A. Mayo M. Moore R.A. Mungall A.J. Mungall K. Robertson A.G. Sadeghi S. Schein J.E. Sipahimalani P. Tam A. Thiessen N. Tse K. Wong T. Berger A.C. Beroukhim R. Cherniack A.D. Cibulskis C. Gabriel S.B. Gao G.F. Ha G. Meyerson M. Schumacher S.E. Shih J. Kucherlapati M.H. Kucherlapati R.S. Baylin S. Cope L. Danilova L. Bootwalla M.S. Lai P.H. Maglinte D.T. Van Den Berg D.J. Weisenberger D.J. Auman J.T. Balu S. Bodenheimer T. Fan C. Hoadley K.A. Hoyle A.P. Jefferys S.R. Jones C.D. Meng S. Mieczkowski P.A. Mose L.E. Perou A.H. Perou C.M. Roach J. Shi Y. Simons J.V. Skelly T. Soloway M.G. Tan D. Veluvolu U. Fan H. Hinoue T. Laird P.W. Shen H. Zhou W. Bellair M. Chang K. Covington K. Creighton C.J. Dinh H. Doddapaneni H.V. Donehower L.A. Drummond J. Gibbs R.A. Glenn R. Hale W. Han Y. Hu J. Korchina V. Lee S. Lewis L. Li W. Liu X. Morgan M. Morton D. Muzny D. Santibanez J. Sheth M. Shinbro E. Wang L. Wang M. Wheeler D.A. Xi L. Zhao F. Hess J. Appelbaum E.L. Bailey M. Cordes M.G. Ding L. Fronick C.C. Fulton L.A. Fulton R.S. Kandoth C. Mardis E.R. McLellan M.D. Miller C.A. Schmidt H.K. Wilson R.K. Crain D. Curley E. Gardner J. Lau K. Mallery D. Morris S. Paulauskis J. Penny R. Shelton C. Shelton T. Sherman M. Thompson E. Yena P. Bowen J. Gastier-Foster J.M. Gerken M. Leraas K.M. Lichtenberg T.M. Ramirez N.C. Wise L. Zmuda E. Corcoran N. Costello T. Hovens C. Carvalho A.L. de Carvalho A.C. Fregnani J.H. Longatto-Filho A. Reis R.M. Scapulatempo-Neto C. Silveira H.C.S. Vidal D.O. Burnette A. Eschbacher J. Hermes B. Noss A. Singh R. Anderson M.L. Castro P.D. Ittmann M. Huntsman D. Kohl B. Le X. Thorp R. Andry C. Duffy E.R. Lyadov V. Paklina O. Setdikova G. Shabunin A. Tavobilov M. McPherson C. Warnick R. Berkowitz R. Cramer D. Feltmate C. Horowitz N. Kibel A. Muto M. Raut C.P. Malykh A. Barnholtz-Sloan J.S. Barrett W. Devine K. Fulop J. Ostrom Q.T. Shimmel K. Wolinsky Y. Sloan A.E. De Rose A. Giuliante F. Goodman M. Karlan B.Y. Hagedorn C.H. Eckman J. Harr J. Myers J. Tucker K. Zach L.A. Deyarmin B. Hu H. Kvecher L. Larson C. Mural R.J. Somiari S. Vicha A. Zelinka T. Bennett J. Iacocca M. Rabeno B. Swanson P. Latour M. Lacombe L. Têtu B. Bergeron A. McGraw M. Staugaitis S.M. Chabot J. Hibshoosh H. Sepulveda A. Su T. Wang T. Potapova O. Voronina O. Desjardins L. Mariani O. Roman-Roman S. Sastre X. Stern M-H. Cheng F. Signoretti S. Berchuck A. Bigner D. Lipp E. Marks J. McCall S. McLendon R. Secord A. Sharp A. Behera M. Brat D.J. Chen A. Delman K. Force S. Khuri F. Magliocca K. Maithel S. Olson J.J. Owonikoko T. Pickens A. Ramalingam S. Shin D.M. Sica G. Van Meir E.G. Zhang H. Eijckenboom W. Gillis A. Korpershoek E. Looijenga L. Oosterhuis W. Stoop H. van Kessel K.E. Zwarthoff E.C. Calatozzolo C. Cuppini L. Cuzzubbo S. DiMeco F. Finocchiaro G. Mattei L. Perin A. Pollo B. Chen C. Houck J. Lohavanichbutr P. Hartmann A. Stoehr C. Stoehr R. Taubert H. Wach S. Wullich B. Kycler W. Murawa D. Wiznerowicz M. Chung K. Edenfield W.J. Martin J. Baudin E. Bubley G. Bueno R. De Rienzo A. Richards W.G. Kalkanis S. Mikkelsen T. Noushmehr H. Scarpace L. Girard N. Aymerich M. Campo E. Giné E. Guillermo A.L. Van Bang N. Hanh P.T. Phu B.D. Tang Y. Colman H. Evason K. Dottino P.R. Martignetti J.A. Gabra H. Juhl H. Akeredolu T. Stepa S. Hoon D. Ahn K. Kang K.J. Beuschlein F. Breggia A. Birrer M. Bell D. Borad M. Bryce A.H. Castle E. Chandan V. Cheville J. Copland J.A. Farnell M. Flotte T. Giama N. Ho T. Kendrick M. Kocher J-P. Kopp K. Moser C. Nagorney D. O’Brien D. O’Neill B.P. Patel T. Petersen G. Que F. Rivera M. Roberts L. Smallridge R. Smyrk T. Stanton M. Thompson R.H. Torbenson M. Yang J.D. Zhang L. Brimo F. Ajani J.A. Angulo Gonzalez A.M. Behrens C. Bondaruk J. Broaddus R. Czerniak B. Esmaeli B. Fujimoto J. Gershenwald J. Guo C. Lazar A.J. Logothetis C. Meric-Bernstam F. Moran C. Ramondetta L. Rice D. Sood A. Tamboli P. Thompson T. Troncoso P. Tsao A. Wistuba I. Carter C. Haydu L. Hersey P. Jakrot V. Kakavand H. Kefford R. Lee K. Long G. Mann G. Quinn M. Saw R. Scolyer R. Shannon K. Spillane A. Stretch J. Synott M. Thompson J. Wilmott J. Al-Ahmadie H. Chan T.A. Ghossein R. Gopalan A. Levine D.A. Reuter V. Singer S. Singh B. Tien N.V. Broudy T. Mirsaidi C. Nair P. Drwiega P. Miller J. Smith J. Zaren H. Park J-W. Hung N.P. Kebebew E. Linehan W.M. Metwalli A.R. Pacak K. Pinto P.A. Schiffman M. Schmidt L.S. Vocke C.D. Wentzensen N. Worrell R. Yang H. Moncrieff M. Goparaju C. Melamed J. Pass H. Botnariuc N. Caraman I. Cernat M. Chemencedji I. Clipca A. Doruc S. Gorincioi G. Mura S. Pirtac M. Stancul I. Tcaciuc D. Albert M. Alexopoulou I. Arnaout A. Bartlett J. Engel J. Gilbert S. Parfitt J. Sekhon H. Thomas G. Rassl D.M. Rintoul R.C. Bifulco C. Tamakawa R. Urba W. Hayward N. Timmers H. Antenucci A. Facciolo F. Grazi G. Marino M. Merola R. de Krijger R. Gimenez-Roqueplo A-P. Piché A. Chevalier S. McKercher G. Birsoy K. Barnett G. Brewer C. Farver C. Naska T. Pennell N.A. Raymond D. Schilero C. Smolenski K. Williams F. Morrison C. Borgia J.A. Liptay M.J. Pool M. Seder C.W. Junker K. Omberg L. Dinkin M. Manikhas G. Alvaro D. Bragazzi M.C. Cardinale V. Carpino G. Gaudio E. Chesla D. Cottingham S. Dubina M. Moiseenko F. Dhanasekaran R. Becker K-F. Janssen K-P. Slotta-Huspenina J. Abdel-Rahman M.H. Aziz D. Bell S. Cebulla C.M. Davis A. Duell R. Elder J.B. Hilty J. Kumar B. Lang J. Lehman N.L. Mandt R. Nguyen P. Pilarski R. Rai K. Schoenfield L. Senecal K. Wakely P. Hansen P. Lechan R. Powers J. Tischler A. Grizzle W.E. Sexton K.C. Kastl A. Henderson J. Porten S. Waldmann J. Fassnacht M. Asa S.L. Schadendorf D. Couce M. Graefen M. Huland H. Sauter G. Schlomm T. Simon R. Tennstedt P. Olabode O. Nelson M. Bathe O. Carroll P.R. Chan J.M. Disaia P. Glenn P. Kelley R.K. Landen C.N. Phillips J. Prados M. Simko J. Smith-McCune K. VandenBerg S. Roggin K. Fehrenbach A. Kendler A. Sifri S. Steele R. Jimeno A. Carey F. Forgie I. Mannelli M. Carney M. Hernandez B. Campos B. Herold-Mende C. Jungk C. Unterberg A. von Deimling A. Bossler A. Galbraith J. Jacobus L. Knudson M. Knutson T. Ma D. Milhem M. Sigmund R. Godwin A.K. Madan R. Rosenthal H.G. Adebamowo C. Adebamowo S.N. Boussioutas A. Beer D. Giordano T. Mes-Masson A-M. Saad F. Bocklage T. Landrum L. Mannel R. Moore K. Moxley K. Postier R. Walker J. Zuna R. Feldman M. Valdivieso F. Dhir R. Luketich J. Mora Pinero E.M. Quintero-Aguilo M. Carlotti C.G. Jr Dos Santos J.S. Kemp R. Sankarankuty A. Tirapelli D. Catto J. Agnew K. Swisher E. Creaney J. Robinson B. Shelley C.S. Godwin E.M. Kendall S. Shipman C. Bradford C. Carey T. Haddad A. Moyer J. Peterson L. Prince M. Rozek L. Wolf G. Bowman R. Fong K.M. Yang I. Korst R. Rathmell W.K. Fantacone-Campbell J.L. Hooke J.A. Kovatich A.J. Shriver C.D. DiPersio J. Drake B. Govindan R. Heath S. Ley T. Van Tine B. Westervelt P. Rubin M.A. Lee J.I. Aredes N.D. Mariamidze A. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell 2018 173 2 400 416.e11 10.1016/j.cell.2018.02.052 29625055
    [Google Scholar]
  28. Yang K. Shi Y. Luo M. Mao M. Zhang X. Chen C. Liu Y. He Z. Liu Q. Wang W. Luo C. Yin W. Wang C. Niu Q. Zeng H. Bian X.W. Ping Y.F. Identification of a unique tumor cell subset employing myeloid transcriptional circuits to create an immunomodulatory microenvironment in glioblastoma. OncoImmunology 2022 11 1 2030020 10.1080/2162402X.2022.2030020 35096487
    [Google Scholar]
  29. Hänzelmann S. Castelo R. Guinney J. GSVA: Gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics 2013 14 1 7 10.1186/1471‑2105‑14‑7 23323831
    [Google Scholar]
  30. Li F. Wan B. He X. Li X. Identification of Novel Subtypes in Lung Adenocarcinoma: Evidence from Gene Set Variation Analysis in Tumor and Adjacent Nontumor Samples. Dis. Markers 2022 2022 1 10 10.1155/2022/2602812 35096200
    [Google Scholar]
  31. Tan Z. Chen X. Zuo J. Fu S. Wang H. Wang J. Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model. J. Transl. Med. 2023 21 1 223 10.1186/s12967‑023‑04056‑z 36973787
    [Google Scholar]
  32. Wang F. Zhang K. Zhang R. Liu H. Zhang W. Jia Z. Wang C. PolyReco: A Method to Automatically Label Collinear Regions and Recognize Polyploidy Events Based on the KS Dotplot. Front. Genet. 2022 13 842387 10.3389/fgene.2022.842387 35518356
    [Google Scholar]
  33. Luo C. Zhu Y. Zhou J. Sun X. Zhang S. Tan S. Li Z. Lin H. Zhang W. Increased CYR61 expression activates CCND1/c-Myc pathway to promote nasal epithelial cells proliferation in chronic rhinosinusitis with nasal polyps. Clin. Immunol. 2023 247 109235 10.1016/j.clim.2023.109235 36681101
    [Google Scholar]
  34. Jin S. Guerrero-Juarez C.F. Zhang L. Chang I. Ramos R. Kuan C.H. Myung P. Plikus M.V. Nie Q. Inference and analysis of cell-cell communication using CellChat. Nat. Commun. 2021 12 1 1088 10.1038/s41467‑021‑21246‑9 33597522
    [Google Scholar]
  35. Lin J. Cai Y. Wang Z. Ma Y. Pan J. Liu Y. Zhao Z. Novel biomarkers predict prognosis and drug-induced neuroendocrine differentiation in patients with prostate cancer. Front. Endocrinol. (Lausanne) 2023 13 1005916 10.3389/fendo.2022.1005916 36686485
    [Google Scholar]
  36. Li Y. Bian Y. Wang K. Wan X.P. POLE mutations improve the prognosis of endometrial cancer via regulating cellular metabolism through AMF/AMFR signal transduction. BMC Med. Genet. 2019 20 1 202 10.1186/s12881‑019‑0936‑2 31864301
    [Google Scholar]
  37. Geisler A.N. Phillips G.S. Barrios D.M. Wu J. Leung D.Y.M. Moy A.P. Kern J.A. Lacouture M.E. Immune checkpoint inhibitor–related dermatologic adverse events. J. Am. Acad. Dermatol. 2020 83 5 1255 1268 10.1016/j.jaad.2020.03.132 32454097
    [Google Scholar]
  38. Topalian S.L. Taube J.M. Anders R.A. Pardoll D.M. Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy. Nat. Rev. Cancer 2016 16 5 275 287 10.1038/nrc.2016.36 27079802
    [Google Scholar]
  39. Galluzzi L. Humeau J. Buqué A. Zitvogel L. Kroemer G. Immunostimulation with chemotherapy in the era of immune checkpoint inhibitors. Nat. Rev. Clin. Oncol. 2020 17 12 725 741 10.1038/s41571‑020‑0413‑z 32760014
    [Google Scholar]
  40. Lu J. Li L. Lan Y. Liang Y. Meng H. Immune checkpoint inhibitor‐associated pituitary‐adrenal dysfunction: A systematic review and meta‐analysis. Cancer Med. 2019 8 18 7503 7515 10.1002/cam4.2661 31679184
    [Google Scholar]
  41. Fridman W.H. Pagès F. Sautès-Fridman C. Galon J. The immune contexture in human tumours: impact on clinical outcome. Nat. Rev. Cancer 2012 12 4 298 306 10.1038/nrc3245 22419253
    [Google Scholar]
  42. Picard E. Verschoor C.P. Ma G.W. Pawelec G. Relationships Between Immune Landscapes, Genetic Subtypes and Responses to Immunotherapy in Colorectal Cancer. Front. Immunol. 2020 11 369 10.3389/fimmu.2020.00369 32210966
    [Google Scholar]
  43. Xu H. Van der Jeught K. Zhou Z. Zhang L. Yu T. Sun Y. Li Y. Wan C. So K.M. Liu D. Frieden M. Fang Y. Mosley A.L. He X. Zhang X. Sandusky G.E. Liu Y. Meroueh S.O. Zhang C. Wijeratne A.B. Huang C. Ji G. Lu X. Atractylenolide I enhances responsiveness to immune checkpoint blockade therapy by activating tumor antigen presentation. J. Clin. Invest. 2021 131 10 e146832 10.1172/JCI146832 33830945
    [Google Scholar]
  44. Sulit A.K. Daigneault M. Allen-Vercoe E. Silander O.K. Hock B. McKenzie J. Pearson J. Frizelle F.A. Schmeier S. Purcell R. Bacterial lipopolysaccharide modulates immune response in the colorectal tumor microenvironment. NPJ Biofilms Microbiomes 2023 9 1 59 10.1038/s41522‑023‑00429‑w 37612266
    [Google Scholar]
  45. Li X. Wen D. Li X. Yao C. Chong W. Chen H. Identification of an Immune Signature Predicting Prognosis Risk and Lymphocyte Infiltration in Colon Cancer. Front. Immunol. 2020 11 1678 10.3389/fimmu.2020.01678 33013820
    [Google Scholar]
  46. Chen W. Huang J. Xiong J. Fu P. Chen C. Liu Y. Li Z. Jie Z. Cao Y. Identification of a Tumor Microenvironment‐Related Gene Signature Indicative of Disease Prognosis and Treatment Response in Colon Cancer. Oxid. Med. Cell. Longev. 2021 2021 1 6290261 10.1155/2021/6290261 34497681
    [Google Scholar]
  47. Zhang X. Zhao H. Shi X. Jia X. Yang Y. Identification and validation of an immune-related gene signature predictive of overall survival in colon cancer. Aging (Albany NY) 2020 12 24 26095 26120 10.18632/aging.202317 33401247
    [Google Scholar]
  48. Barja-Fernández S. Folgueira C. Castelao C. Pena-León V. González-Saenz P. Vázquez-Cobela R. Aguilera C.M. Gil-Campos M. Bueno G. Gil Á. Moreno L.A. Ruiz-Piñon M. García-Palacios M. Casanueva F.F. Diéguez C. Nogueiras R. Leis R. Seoane L.M. ANGPTL-4 is Associated with Obesity and Lipid Profile in Children and Adolescents. Nutrients 2019 11 6 1340 10.3390/nu11061340 31207920
    [Google Scholar]
  49. Lu Q. Lu P. Chen W. Lu L. Zheng Z. ANGPTL-4 induces diabetic retinal inflammation by activating Profilin-1. Exp. Eye Res. 2018 166 140 150 10.1016/j.exer.2017.10.009 29031854
    [Google Scholar]
  50. Chang H. Kwon O. Shin M.S. Kang G.M. Leem Y.H. Lee C.H. Kim S.J. Roh E. Kim H.K. Youn B.S. Kim M.S. Role of Angptl4/Fiaf in exercise-induced skeletal muscle AMPK activation. J Appl Physiol 2018 125 3 715 722 10.1152/japplphysiol.00984.2016.
    [Google Scholar]
  51. Yang Y.H. Wang Y. Lam K.S.L. Yau M.H. Cheng K.K.Y. Zhang J. Zhu W. Wu D. Xu A. Suppression of the Raf/MEK/ERK signaling cascade and inhibition of angiogenesis by the carboxyl terminus of angiopoietin-like protein 4. Arterioscler. Thromb. Vasc. Biol. 2008 28 5 835 840 10.1161/ATVBAHA.107.157776 18340008
    [Google Scholar]
  52. Le Jan S. Amy C. Cazes A. Monnot C. Lamandé N. Favier J. Philippe J. Sibony M. Gasc J.M. Corvol P. Germain S. Angiopoietin-like 4 is a proangiogenic factor produced during ischemia and in conventional renal cell carcinoma. Am. J. Pathol. 2003 162 5 1521 1528 10.1016/S0002‑9440(10)64285‑X 12707035
    [Google Scholar]
  53. Deng T. Lyon C.J. Bergin S. Caligiuri M.A. Hsueh W.A. Obesity, Inflammation, and Cancer. Annu. Rev. Pathol. 2016 11 1 421 449 10.1146/annurev‑pathol‑012615‑044359 27193454
    [Google Scholar]
  54. El-Shal A.S. Zidan H.E. Rashad N.M. Wadea F.M. Angiopoietin-like protein 3 and 4 expression 4 and their serum levels in hepatocellular carcinoma. Cytokine 2017 96 75 86 10.1016/j.cyto.2017.03.006 28371666
    [Google Scholar]
  55. Shibata K. Nakayama T. Hirakawa H. Hidaka S. Nagayasu T. Clinicopathological significance of angiopoietin-like protein 4 expression in oesophageal squamous cell carcinoma. J. Clin. Pathol. 2010 63 12 1054 1058 10.1136/jcp.2010.078600 20861003
    [Google Scholar]
  56. Nakayama T. Hirakawa H. Shibata K. Abe K. Nagayasu T. Taguchi T. Expression of angiopoietin-like 4 in human gastric cancer: ANGPTL4 promotes venous invasion. Oncol. Rep. 2010 24 3 599 606 10.3892/or_00000897 20664963
    [Google Scholar]
  57. Nakayama T. Hirakawa H. Shibata K. Nazneen A. Abe K. Nagayasu T. Taguchi T. Expression of angiopoietin-like 4 (ANGPTL4) in human colorectal cancer: ANGPTL4 promotes venous invasion and distant metastasis. Oncol. Rep. 2011 25 4 929 935 10.3892/or.2011.1176 21308352
    [Google Scholar]
  58. Li X. Chen T. Shi Q. Li J. Cai S. Zhou P. Zhong Y. Yao L. Angiopoietin-like 4 enhances metastasis and inhibits apoptosis via inducing bone morphogenetic protein 7 in colorectal cancer cells. Biochem. Biophys. Res. Commun. 2015 467 1 128 134 10.1016/j.bbrc.2015.09.104 26417691
    [Google Scholar]
  59. Würtz S.Ø. Würtz S.Ø. Schrohl A-S. Mouridsen H. Brünner N. TIMP-1 as a tumor marker in breast cancer – An update. Acta Oncol. 2008 47 4 580 590 10.1080/02841860802022976 18465326
    [Google Scholar]
  60. Wang Y.Y. Li L. Zhao Z.S. Wang H.J. Clinical utility of measuring expression levels of KAP1, TIMP1 and STC2 in peripheral blood of patients with gastric cancer. World J. Surg. Oncol. 2013 11 1 81 10.1186/1477‑7819‑11‑81 23548070
    [Google Scholar]
  61. Hawthorn L. Stein L. Varma R. Wiseman S. Loree T. Tan D. TIMP1 and SERPIN‐A overexpression and TFF3 and CRABP1 underexpression as biomarkers for papillary thyroid carcinoma. Head Neck 2004 26 12 1069 1083 10.1002/hed.20099 15515157
    [Google Scholar]
  62. Zurac S. Neagu M. Constantin C. Cioplea M. Nedelcu R. Bastian A. Popp C. Nichita L. Andrei R. Tebeica T. Tanase C. Chitu V. Caruntu C. Ghita M. Popescu C. Boda D. Mastalier B. Maru N. Daha C. Andreescu B. Marinescu I. Rebosapca A. Staniceanu F. Negroiu G. Ion D.A. Nikitovic D. Tzanakakis G.N. Spandidos D.A. Tsatsakis A.M. Variations in the expression of TIMP1, TIMP2 and TIMP3 in cutaneous melanoma with regression and their possible function as prognostic predictors. Oncol. Lett. 2016 11 5 3354 3360 10.3892/ol.2016.4391 27123116
    [Google Scholar]
  63. He S. Liu M. Zhang W. Xu N. Zhu H. Over expression of p21-activated kinase 7 associates with lymph node metastasis in esophageal squamous cell cancers. Cancer Biomark. 2016 16 2 203 209 10.3233/CBM‑150557 26682509
    [Google Scholar]
  64. Xi C. Zhang G. Sun N. Liu M. Ju N. Shen C. Song H. Luo Q. Qiu Z. Repurposing homoharringtonine for thyroid cancer treatment through TIMP1/FAK/PI3K/AKT signaling pathway. iScience 2024 27 6 109829 10.1016/j.isci.2024.109829 38770133
    [Google Scholar]
  65. Xu Y. Xie Y.M. Sun W.S. Zi R. Lu H.Q. Xiao L. Gong K.M. Guo S.K. Exploration of an Prognostic Signature Related to Endoplasmic Reticulum Stress in Colorectal Adenocarcinoma and Their Response Targeting Immunotherapy. Technol. Cancer Res. Treat. 2023 22 10.1177/15330338231212073 37920989
    [Google Scholar]
  66. Liu T. Xia R. Li C. Chen X. Cai X. Li W. mRNA expression level of CDH2, LEP, POSTN, TIMP1 and VEGFC modulates 5‑fluorouracil resistance in colon cancer cells. Exp. Ther. Med. 2021 22 3 1023 10.3892/etm.2021.10455 34373709
    [Google Scholar]
  67. Peña C. García J.M. Larriba M.J. Barderas R. Gómez I. Herrera M. García V. Silva J. Domínguez G. Rodríguez R. Cuevas J. de Herreros A.G. Casal J.I. Muñoz A. Bonilla F. SNAI1 expression in colon cancer related with CDH1 and VDR downregulation in normal adjacent tissue. Oncogene 2009 28 49 4375 4385 10.1038/onc.2009.285 19802011
    [Google Scholar]
  68. Zhu Y. Wang C. Becker S.A. Hurst K. Nogueira L.M. Findlay V.J. Camp E.R. miR-145 Antagonizes SNAI1-Mediated Stemness and Radiation Resistance in Colorectal Cancer. Mol. Ther. 2018 26 3 744 754 10.1016/j.ymthe.2017.12.023 29475734
    [Google Scholar]
  69. Wang F. Zhao S. Gu Z. Zhao X. Yang N. Guan L. Liu T. Wang L. Fang S. Zhu C. Luo L. Li M. Wang L. Gao C. S1PR5 regulates NK cell responses in preventing graft‐versus‐host disease while preserving graft‐versus‐tumour activity in a murine allogeneic haematopoietic stem cell transplantation model. Hematol. Oncol. 2020 38 1 89 102 10.1002/hon.2669 31465552
    [Google Scholar]
  70. Yuan Y. Jia G. Wu C. Wang W. Cheng L. Li Q. Li Z. Luo K. Yang S. Yan W. Su Z. Shao Z. Structures of signaling complexes of lipid receptors SIRP1 and S1PR5 reveal mechanisms of activation and drug recognition. Cell Res. 2021 31 12 1263 1274 10.1038/s41422‑021‑00566‑x 34526663
    [Google Scholar]
  71. Xie Z. Liu H. Geng M. Targeting sphingosine-1-phosphate signaling for cancer therapy. Sci. China Life Sci. 2017 60 6 585 600 10.1007/s11427‑017‑9046‑6 28623546
    [Google Scholar]
  72. Patmanathan S.N. Wang W. Yap L.F. Herr D.R. Paterson I.C. Mechanisms of sphingosine 1-phosphate receptor signalling in cancer. Cell. Signal. 2017 34 66 75 10.1016/j.cellsig.2017.03.002 28302566
    [Google Scholar]
  73. Zhou H. Yin X. Bai F. Liu W. Jiang S. Zhao J. The Role and Mechanism of S1PR5 in Colon Cancer. Cancer Manag. Res. 2020 12 4759 4775 10.2147/CMAR.S239118 32606966
    [Google Scholar]
  74. Li J. Ji Z. Qiao C. Qi Y. Shi W. Overexpression of ADAM9 Promotes Colon Cancer Cells Invasion. J. Invest. Surg. 2013 26 3 127 133 10.3109/08941939.2012.728682 26981956
    [Google Scholar]
  75. Hirao T. Nanba D. Tanaka M. Ishiguro H. Kinugasa Y. Doki Y. Yano M. Matsuura N. Monden M. Higashiyama S. Overexpression of ADAM9 enhances growth factor-mediated recycling of E-cadherin in human colon cancer cell line HT29 cells. Exp. Cell Res. 2006 312 3 331 339 10.1016/j.yexcr.2005.10.032 16336960
    [Google Scholar]
  76. Mazzocca A. Coppari R. De Franco R. Cho J.Y. Libermann T.A. Pinzani M. Toker A. A secreted form of ADAM9 promotes carcinoma invasion through tumor-stromal interactions. Cancer Res. 2005 65 11 4728 4738 10.1158/0008‑5472.CAN‑04‑4449 15930291
    [Google Scholar]
  77. Dwyer J.M. Liu J.P. Ets2 transcription factor, telomerase activity and breast cancer. Clin. Exp. Pharmacol. Physiol. 2010 37 1 83 87 10.1111/j.1440‑1681.2009.05236.x 19566835
    [Google Scholar]
  78. Seth A. Watson D.K. ETS transcription factors and their emerging roles in human cancer. Eur. J. Cancer 2005 41 16 2462 2478 10.1016/j.ejca.2005.08.013 16213704
    [Google Scholar]
  79. Ito Y. Takeda T. Okada M. Matsuura N. Expression of ets-1 and ets-2 in colonic neoplasms. Anticancer Res. 2002 22 3 1581 1584 12168840
    [Google Scholar]
  80. Flavin P. Redmond A. McBryan J. Cocchiglia S. Tibbitts P. Fahy-Browne P. Kay E. Treumann A. Perrem K. McIlroy M. Hill A.D.K. Young L.S. RuvBl2 cooperates with Ets2 to transcriptionally regulate hTERT in colon cancer. FEBS Lett. 2011 585 15 2537 2544 10.1016/j.febslet.2011.07.005 21763315
    [Google Scholar]
  81. Múnera J. Ceceña G. Jedlicka P. Wankell M. Oshima R.G. Ets2 regulates colonic stem cells and sensitivity to tumorigenesis. Stem Cells 2011 29 3 430 439 10.1002/stem.599 21425406
    [Google Scholar]
  82. Miyasaka K. Hosoya H. Tanaka Y. Uegaki S. Kino K. Shimokata H. Kawanami T. Funakoshi A. Association of aldehyde dehydrogenase 2 gene polymorphism with pancreatic cancer but not colon cancer. Geriatr. Gerontol. Int. 2010 10 s1 S120 S126 10.1111/j.1447‑0594.2010.00616.x 20590827
    [Google Scholar]
  83. Matsuo K. Hamajima N. Hirai T. Kato T. Koike K. Inoue M. Takezaki T. Tajima K. Aldehyde dehydrogenase 2 (ALDH2) genotype affects rectal cancer susceptibility due to alcohol consumption. J. Epidemiol. 2002 12 2 70 76 10.2188/jea.12.70 12033531
    [Google Scholar]
/content/journals/cmc/10.2174/0109298673331144241009082052
Loading
The Risk Genes SIRP5, CMC1, and ASAH1 as Potential Targets for the Diagnosis, Immunotherapy, and Treatment of Colon Adenocarcinoma by Single-Cell and Bulk RNA Sequencing Analysis
Bentham Science Publishers ; https://doi.org/10.2174/0109298673331144241009082052
/content/journals/cmc/10.2174/0109298673331144241009082052
/content/journals/cmc/10.2174/0109298673331144241009082052
Loading

Data & Media loading...

Supplements

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

file format download Download

  • Article Type:     Research Article
Keywords: SIRP5 ; scRNA-seq ; immunotherapy ; ICF model ; therapeutic targets ; CMC1 ; bulk RNA-seq ; Colon adenocarcinoma ; ASAH1

Most Cited Most Cited RSS feed

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