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Abstract

Background

Recent research has demonstrated the significance of Interferon Gamma-Inducible Protein 30 (IFI30), an interferon gamma-induced protein, in the immune response to cancerous growths. However, the relationship between IFI30 expression levels, patient prognosis, and tumor-infiltrating lymphocytes in clear cell renal cell carcinoma (ccRCC) remains inadequately defined.

Methods

To ascertain the potential link between IFI30 expression, clinical data, and overall survival (OS) in ccRCC patients, we employed diverse databases, which include TCGA, Gene Expression Profiling Interaction Analysis (GEPIA), and UALCAN. Furthermore, an in-depth analysis of the link between tumor-infiltrating immune cells (TIIC) and IFI30 was carried out using the TIMER, GEPIA, and TISIDB databases. Immunohistochemistry (IHC) was utilized to identify the IFI30 and PD-1 expression levels in a tissue microarray. Patents about molecular classification and drugs in ccRCC were reviewed through Worldwide Espacenet®.

Results

The expression of IFI30 demonstrated a strong association with sample type, lymph node stage, tumor grade, and cancer stage. Elevated IFI30 expression was linked to unfavorable Disease-Specific Survival (DSS) and Overall Survival (OS) outcomes ( <0.01). Furthermore, overexpression of IFI30 was strongly linked to immunomodulatory molecules, chemokines, and increased infiltration of regulatory T cells (Tregs), natural killer (NK) CD56 cells, T helper 1 (Th1) cells, cytotoxic T cells, and T helper cells. IHC analysis confirmed a robust correlation between IFI30 and PD-1 expression.

Conclusion

IFI30 is a prognostic biomarker for ccRCC patients. Targeting IFI30 may provide new strategies for cancer therapy and improve the prognosis of ccRCC patients.

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2025-02-06
2025-09-11

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References

  1. Capitanio U. Bensalah K. Bex A. Boorjian S.A. Bray F. Coleman J. Gore J.L. Sun M. Wood C. Russo P. Epidemiology of renal cell carcinoma. Eur. Urol. 2019 75 1 74 84 10.1016/j.eururo.2018.08.036 30243799
    [Google Scholar]
  2. Nabi S. Kessler E.R. Bernard B. Flaig T.W. Lam E.T. Renal cell carcinoma: A review of biology and pathophysiology. F1000 Res. 2018 7 307 10.12688/f1000research.13179.1 29568504
    [Google Scholar]
  3. Frew I.J. Moch H. A clearer view of the molecular complexity of clear cell renal cell carcinoma. Annu. Rev. Pathol. 2015 10 1 263 289 10.1146/annurev‑pathol‑012414‑040306 25387056
    [Google Scholar]
  4. Ricketts C.J. Linehan W.M. Multi-regional sequencing elucidates the evolution of clear cell renal cell carcinoma. Cell 2018 173 3 540 542 10.1016/j.cell.2018.03.077 29677504
    [Google Scholar]
  5. Sánchez-Gastaldo A. Kempf E. González del Alba A. Duran I. Systemic treatment of renal cell cancer: A comprehensive review. Cancer Treat. Rev. 2017 60 77 89 10.1016/j.ctrv.2017.08.010 28898679
    [Google Scholar]
  6. Atkins M.B. Tannir N.M. Current and emerging therapies for first-line treatment of metastatic clear cell renal cell carcinoma. Cancer Treat. Rev. 2018 70 127 137 10.1016/j.ctrv.2018.07.009 30173085
    [Google Scholar]
  7. Wettersten H.I. Aboud O.A. Lara P.N. Jr Weiss R.H. Metabolic reprogramming in clear cell renal cell carcinoma. Nat. Rev. Nephrol. 2017 13 7 410 419 10.1038/nrneph.2017.59 28480903
    [Google Scholar]
  8. Miess H. Dankworth B. Gouw A.M. Rosenfeldt M. Schmitz W. Jiang M. Saunders B. Howell M. Downward J. Felsher D.W. Peck B. Schulze A. The glutathione redox system is essential to prevent ferroptosis caused by impaired lipid metabolism in clear cell renal cell carcinoma. Oncogene 2018 37 40 5435 5450 10.1038/s41388‑018‑0315‑z 29872221
    [Google Scholar]
  9. Zou Y. Palte M.J. Deik A.A. Li H. Eaton J.K. Wang W. Tseng Y.Y. Deasy R. Kost-Alimova M. Dančík V. Leshchiner E.S. Viswanathan V.S. Signoretti S. Choueiri T.K. Boehm J.S. Wagner B.K. Doench J.G. Clish C.B. Clemons P.A. Schreiber S.L. A GPX4-dependent cancer cell state underlies the clear-cell morphology and confers sensitivity to ferroptosis. Nat. Commun. 2019 10 1 1617 10.1038/s41467‑019‑09277‑9 30962421
    [Google Scholar]
  10. West L.C. Cresswell P. Expanding roles for GILT in immunity. Curr. Opin. Immunol. 2013 25 1 103 108 10.1016/j.coi.2012.11.006 23246037
    [Google Scholar]
  11. Hastings K.T. Cresswell P. Disulfide reduction in the endocytic pathway: Immunological functions of gamma-interferon-inducible lysosomal thiol reductase. Antioxid. Redox Signal. 2011 15 3 657 668 10.1089/ars.2010.3684 21506690
    [Google Scholar]
  12. Arunachalam B. Phan U.T. Geuze H.J. Cresswell P. Enzymatic reduction of disulfide bonds in lysosomes: Characterization of a Gamma-interferon-inducible lysosomal thiol reductase (GILT). Proc. Natl. Acad. Sci. USA 2000 97 2 745 750 10.1073/pnas.97.2.745 10639150
    [Google Scholar]
  13. Barjaktarević I. Rahman A. Radoja S. Bogunović B. Vollmer A. Vukmanović S. Marić M. Inhibitory role of IFN-gamma-inducible lysosomal thiol reductase in T cell activation. J. Immunol. 2006 177 7 4369 4375 10.4049/jimmunol.177.7.4369 16982871
    [Google Scholar]
  14. Bogunovic B. Stojakovic M. Chen L. Maric M. An unexpected functional link between lysosomal thiol reductase and mitochondrial manganese superoxide dismutase. J. Biol. Chem. 2008 283 14 8855 8862 10.1074/jbc.M708998200 18218638
    [Google Scholar]
  15. Honey K. Duff M. Beers C. Brissette W.H. Elliott E.A. Peters C. Maric M. Cresswell P. Rudensky A. Cathepsin S regulates the expression of cathepsin L and the turnover of gamma-interferon-inducible lysosomal thiol reductase in B lymphocytes. J. Biol. Chem. 2001 276 25 22573 22578 10.1074/jbc.M101851200 11306582
    [Google Scholar]
  16. Luster A.D. Weinshank R.L. Feinman R. Ravetch J.V. Molecular and biochemical characterization of a novel gamma-interferon-inducible protein. J. Biol. Chem. 1988 263 24 12036 12043 10.1016/S0021‑9258(18)37889‑X 3136170
    [Google Scholar]
  17. Phan U.T. Arunachalam B. Cresswell P. Gamma-interferon-inducible lysosomal thiol reductase (GILT). Maturation, activity, and mechanism of action. J. Biol. Chem. 2000 275 34 25907 25914 10.1074/jbc.M003459200 10852914
    [Google Scholar]
  18. Hastings K.T. GILT: Shaping the MHC Class II-restricted peptidomeand CD4(+) T cell-mediated immunity. Front. Immunol. 2013 4 429 10.3389/fimmu.2013.00429 24409178
    [Google Scholar]
  19. Haque M.A. Li P. Jackson S.K. Zarour H.M. Hawes J.W. Phan U.T. Maric M. Cresswell P. Blum J.S. Absence of gamma-interferon-inducible lysosomal thiol reductase in melanomas disrupts T cell recognition of select immunodominant epitopes. J. Exp. Med. 2002 195 10 1267 1277 10.1084/jem.20011853 12021307
    [Google Scholar]
  20. Becker J.C. Schrama D. Control of central and peripheral tolerance to melanocyte differentiation antigens by GILT. J. Invest. Dermatol. 2012 132 1 15 17 10.1038/jid.2011.361 22158609
    [Google Scholar]
  21. Rausch M.P. Taraszka Hastings K. GILT modulates CD4+ T-cell tolerance to the melanocyte differentiation antigen tyrosinase-related protein 1. J. Invest. Dermatol. 2012 132 1 154 162 10.1038/jid.2011.236 21833020
    [Google Scholar]
  22. Chen S. Wang Q. Shao X. Di G. Dai Y. Jiang X. Cheng L. Lentivirus mediated γ-interferon-inducible lysosomal thiol reductase (GILT) knockdown suppresses human glioma U373MG cell proliferation. Biochem. Biophys. Res. Commun. 2019 509 1 182 187 10.1016/j.bbrc.2018.12.099 30587343
    [Google Scholar]
  23. Zhu C. Chen X. Guan G. Zou C. Guo Q. Cheng P. Cheng W. Wu A. IFI30 is a novel immune-related target with predicting value of prognosis and treatment response in glioblastoma. OncoTargets Ther. 2020 13 1129 1143 10.2147/OTT.S237162 32103982
    [Google Scholar]
  24. Phipps-Yonas H. Cui H. Sebastiao N. Brunhoeber P.S. Haddock E. Deymier M.J. Klapper W. Lybarger L. Roe D.J. Hastings K.T. Low GILT expression is Associated with poor patient survival in diffuse large B-Cell lymphoma. Front. Immunol. 2013 4 425 10.3389/fimmu.2013.00425 24409177
    [Google Scholar]
  25. Hathaway-Schrader J.D. Norton D. Hastings K. Doonan B.P. Fritz S.T. Bethard J.R. Blum J.S. Haque A. GILT expression in human melanoma cells enhances Generation of antigenic peptides for HLA class II-Mediated Immune Recognition. Int. J. Mol. Sci. 2022 23 3 1066 10.3390/ijms23031066 35162988
    [Google Scholar]
  26. Adams A.C. Borden E.S. Macy A.M. Thomson N. Cui H. Gimbel M.I. Wilson M.A. Buetow K.H. Roe D.J. DiCaudo D.J. Homsi J. Hastings K.T. High GILT expression is associated with improved survival in metastatic melanoma patients treated with immune checkpoint inhibition. Cancers (Basel) 2022 14 9 2200 10.3390/cancers14092200 35565329
    [Google Scholar]
  27. Nguyen J. Bernert R. In K. Kang P. Sebastiao N. Hu C. Hastings K.T. Gamma-interferon-inducible lysosomal thiol reductase is upregulated in human melanoma. Melanoma Res. 2016 26 2 125 137 10.1097/CMR.0000000000000230 26930048
    [Google Scholar]
  28. Ye C. Zhou W. Wang F. Yin G. Zhang X. Kong L. Gao Z. Feng M. Zhou C. Sun D. Wang L. Liu L. Zheng C. Xiang Y. Guo M. Huang S. Yu Z. Prognostic value of gamma‐interferon‐inducible lysosomal thiol reductase expression in female patients diagnosed with breast cancer. Int. J. Cancer 2022 150 4 705 717 10.1002/ijc.33843 34648659
    [Google Scholar]
  29. Xiang Y.J. Guo M.M. Zhou C.J. Liu L. Han B. Kong L.Y. Gao Z.C. Ma Z.B. Wang L. Feng M. Chen H.Y. Jia G.T. Gao D.Z. Zhang Q. Li L. Li Y.Y. Yu Z.G. Absence of gamma-interferon-inducible lysosomal thiol reductase (GILT) is associated with poor disease-free survival in breast cancer patients. PLoS One 2014 9 10 e109449 10.1371/journal.pone.0109449 25333930
    [Google Scholar]
  30. Ding G. Wang T. Liu S. Zhou Z. Ma J. Wu J. Wiskott-Aldrich syndrome gene as a prognostic biomarker correlated with immune infiltrates in clear cell renal cell carcinoma. Front. Immunol. 2023 14 1102824 10.3389/fimmu.2023.1102824 37122750
    [Google Scholar]
  31. Wang Z. Jensen M.A. Zenklusen J.C. A practical guide to The Cancer Genome Atlas (TCGA). Methods Mol. Biol. 2016 1418 111 141 10.1007/978‑1‑4939‑3578‑9_6 27008012
    [Google Scholar]
  32. Lee H. Palm J. Grimes S.M. Ji H.P. The Cancer Genome Atlas Clinical Explorer: A web and mobile interface for identifying clinical–genomic driver associations. Genome Med. 2015 7 1 112 10.1186/s13073‑015‑0226‑3 26507825
    [Google Scholar]
  33. Navani S. Manual evaluation of tissue microarrays in a high‐throughput research project: The contribution of Indian surgical pathology to the Human Protein Atlas (HPA) project. Proteomics 2016 16 8 1266 1270 10.1002/pmic.201500409 26748468
    [Google Scholar]
  34. Chandrashekar D.S. Bashel B. Balasubramanya S.A.H. Creighton C.J. Ponce-Rodriguez I. Chakravarthi B.V.S.K. Varambally S. UALCAN: A portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia 2017 19 8 649 658 10.1016/j.neo.2017.05.002 28732212
    [Google Scholar]
  35. Chandrashekar D.S. Karthikeyan S.K. Korla P.K. Patel H. Shovon A.R. Athar M. Netto G.J. Qin Z.S. Kumar S. Manne U. Creighton C.J. Varambally S. UALCAN: An update to the integrated cancer data analysis platform. Neoplasia 2022 25 18 27 10.1016/j.neo.2022.01.001 35078134
    [Google Scholar]
  36. 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 10.1089/omi.2011.0118 22455463
    [Google Scholar]
  37. Reimand J. Isserlin R. Voisin V. Kucera M. Tannus-Lopes C. Rostamianfar A. Wadi L. Meyer M. Wong J. Xu C. Merico D. Bader G.D. Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap. Nat. Protoc. 2019 14 2 482 517 10.1038/s41596‑018‑0103‑9 30664679
    [Google Scholar]
  38. Shannon P. Markiel A. Ozier O. Baliga N.S. Wang J.T. Ramage D. Amin N. Schwikowski B. Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003 13 11 2498 2504 10.1101/gr.1239303 14597658
    [Google Scholar]
  39. Bindea G. Mlecnik B. Tosolini M. Kirilovsky A. Waldner M. Obenauf A.C. Angell H. Fredriksen T. Lafontaine L. Berger A. Bruneval P. Fridman W.H. Becker C. Pagès F. Speicher M.R. Trajanoski Z. Galon J. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 2013 39 4 782 795 10.1016/j.immuni.2013.10.003 24138885
    [Google Scholar]
  40. Li T. Fan J. Wang B. Traugh N. Chen Q. Liu J.S. Li B. Liu X.S. TIMER: A web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res. 2017 77 21 e108 e110 10.1158/0008‑5472.CAN‑17‑0307 29092952
    [Google Scholar]
  41. Li T. Fu J. Zeng Z. Cohen D. Li J. Chen Q. Li B. Liu X.S. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020 48 W1 W509 W514 10.1093/nar/gkaa407 32442275
    [Google Scholar]
  42. Tang Z. Li C. Kang B. Gao G. Li C. Zhang Z. GEPIA: A web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017 45 W1 W98 W102 10.1093/nar/gkx247 28407145
    [Google Scholar]
  43. Tang Z. Kang B. Li C. Chen T. Zhang Z. GEPIA2: An enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res. 2019 47 W1 W556 W560 10.1093/nar/gkz430 31114875
    [Google Scholar]
  44. Ru B. Wong C.N. Tong Y. Zhong J.Y. Zhong S.S.W. Wu W.C. Chu K.C. Wong C.Y. Lau C.Y. Chen I. Chan N.W. Zhang J. TISIDB: An integrated repository portal for tumor–immune system interactions. Bioinformatics 2019 35 20 4200 4202 10.1093/bioinformatics/btz210 30903160
    [Google Scholar]
  45. Guo R. Dai H. Liu F. Liu M. Li X. Li T. Liao J. Chen Z.S. Liu Y. Fang S. The prognostic and drug-targeting value of lymphoid enhancer-binding factor-1 in Hepatocellular carcinoma. Recent Patents Anticancer Drug Discov. 2023 18 2 211 223 10.2174/1574892817666220831122226 36045537
    [Google Scholar]
  46. Curigliano G. Gyneco-oncological genomics and emerging biomarkers for cancer treatment with immune-checkpoint inhibitors. Semin. Cancer Biol. 2018 52 Pt 2 253 258 10.1016/j.semcancer.2018.05.004 29775688
    [Google Scholar]
  47. Klauschen F. Müller K.R. Binder A. Bockmayr M. Hägele M. Seegerer P. Wienert S. Pruneri G. de Maria S. Badve S. Michiels S. Nielsen T.O. Adams S. Savas P. Symmans F. Willis S. Gruosso T. Park M. Haibe-Kains B. Gallas B. Thompson A.M. Cree I. Sotiriou C. Solinas C. Preusser M. Hewitt S.M. Rimm D. Viale G. Loi S. Loibl S. Salgado R. Denkert C. International Immuno-Oncology Biomarker Working Group Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning. Semin. Cancer Biol. 2018 52 Pt 2 151 157 10.1016/j.semcancer.2018.07.001 29990622
    [Google Scholar]
  48. Buetow K.H. Meador L.R. Menon H. Lu Y.K. Brill J. Cui H. Roe D.J. DiCaudo D.J. Hastings K.T. High GILT expression and an active and intact MHC class II antigen presentation pathway are associated with improved survival in melanoma. J. Immunol. 2019 203 10 2577 2587 10.4049/jimmunol.1900476 31591149
    [Google Scholar]
  49. Liu X. Song C. Yang S. Ji Q. Chen F. Li W. IFI30 expression is an independent unfavourable prognostic factor in glioma. J. Cell. Mol. Med. 2020 24 21 12433 12443 10.1111/jcmm.15758 32969157
    [Google Scholar]
  50. Jayasingam S.D. Citartan M. Thang T.H. Mat Zin A.A. Ang K.C. Ch’ng E.S. Evaluating the polarization of tumor-associated macrophages into M1 and M2 phenotypes in human cancer tissue: Technicalities and challenges in routine clinical practice. Front. Oncol. 2020 9 1512 10.3389/fonc.2019.01512 32039007
    [Google Scholar]
  51. Su C. Jia S. Liu H. Immunolocalization of CD163+ tumor-associated macrophages and symmetric proliferation of Ki-67 as biomarkers to differentiate new different grades of laryngeal dysplasia. Am. J. Clin. Pathol. 2018 149 1 8 16 10.1093/ajcp/aqx107 29228085
    [Google Scholar]
  52. Sammarco G. Gadaleta C.D. Zuccalà V. Albayrak E. Patruno R. Milella P. Sacco R. Ammendola M. Ranieri G. Tumor-associated macrophages and mast cells positive to tryptase are correlated with angiogenesis in surgically-treated gastric cancer patients. Int. J. Mol. Sci. 2018 19 4 1176 10.3390/ijms19041176 29649166
    [Google Scholar]
  53. Zhang D. Qiu X. Li J. Zheng S. Li L. Zhao H. RETRACTED ARTICLE: TGF-β secreted by tumor-associated macrophages promotes proliferation and invasion of colorectal cancer via miR-34a-VEGF axis. Cell Cycle 2018 17 24 2766 2778 10.1080/15384101.2018.1556064 30523755
    [Google Scholar]
  54. Song W. Mazzieri R. Yang T. Gobe G.C. Translational significance for tumor metastasis of tumor-associated macrophages and epithelial-mesenchymal transition. Front Immunol. 2017 8 1106 10.3389/fimmu.2017.01106 28955335
    [Google Scholar]
  55. Wynn T.A. Chawla A. Pollard J.W. Macrophage biology in development, homeostasis and disease. Nature 2013 496 7446 445 455 10.1038/nature12034 23619691
    [Google Scholar]
  56. Wang Z. Wu X. Study and analysis of antitumor resistance mechanism of PD1/PD‐L1 immune checkpoint blocker. Cancer Med. 2020 9 21 8086 8121 10.1002/cam4.3410 32875727
    [Google Scholar]
  57. Loo K. Daud A. Emerging biomarkers as predictors to anti-PD1/PD-L1 therapies in advanced melanoma. Immunotherapy 2016 8 7 775 784 10.2217/imt‑2016‑0039 27349977
    [Google Scholar]
  58. Gu T. Tian X. Wang Y. Yang W. Li W. Song M. Zhao R. Wang M. Gao Q. Li T. Zhang C. Kundu J.K. Liu K. Dong Z. Lee M.H. Repurposing pentamidine for cancer immunotherapy by targeting the PD1/PD-L1 immune checkpoint. Front. Immunol. 2023 14 1145028 10.3389/fimmu.2023.1145028 37205112
    [Google Scholar]
  59. Kitsou M. Ayiomamitis G. Zaravinos A. High expression of immune checkpoints is associated with the TIL load, mutation rate and patient survival in colorectal cancer. Int. J. Oncol. 2020 57 1 237 248 10.3892/ijo.2020.5062 32468013
    [Google Scholar]
  60. Bruchbacher A. Lemberger U. Hassler M.R. Fajkovic H. Schmidinger M. PD1/PD-L1 therapy in metastatic renal cell carcinoma. Curr. Opin. Urol. 2020 30 4 534 541 10.1097/MOU.0000000000000788 32453005
    [Google Scholar]
  61. Zhu Z. Jin Y. Zhou J. Chen F. Chen M. Gao Z. Hu L. Xuan J. Li X. Song Z. Guo X. PD1/PD-L1 blockade in clear cell renal cell carcinoma: Mechanistic insights, clinical efficacy, and future perspectives. Mol. Cancer 2024 23 1 146 10.1186/s12943‑024‑02059‑y 39014460
    [Google Scholar]
  62. Zeuschner P. Junker K. Optimal selection of patients with genitourinary cancers for anti-PD1/PD-L1 treatment with a focus on urothelial and renal cell carcinoma. Eur. Urol. Focus 2022 8 4 907 909 10.1016/j.euf.2022.07.002 35918269
    [Google Scholar]
  63. Shen C. Liu J. Wang J. Zhong X. Dong D. Yang X. Wang Y. Development and validation of a prognostic immune-associated gene signature in clear cell renal cell carcinoma. Int. Immunopharmacol. 2020 81 106274 10.1016/j.intimp.2020.106274 32044664
    [Google Scholar]
  64. Wen X. Lei L. Wang F. Wang Y. Comprehensive analysis of the role of interferon gamma-inducible protein 30 on immune infiltration and prognosis in clear cell renal cell carcinoma. Biomolecules and Biomedicine 2024 24 2 411 422 10.17305/bb.2023.9693 37991414
    [Google Scholar]
  65. Chen X. Zhang Z. Qin Z. Zhu X. Wang K. Kang L. Li C. Wang H. Identification and validation of a novel signature based on macrophage marker genes for predicting prognosis and drug response in kidney renal clear cell carcinoma by integrated analysis of single cell and bulk RNA sequencing. Aging (Albany NY) 2024 16 6 5676 5702 10.18632/aging.205671 38517387
    [Google Scholar]
  66. Liu Y. Wu D. Chen H. Yan L. Xiang Q. Li Q. Wang T. Construction and verification of a novel prognostic risk model for kidney renal clear cell carcinoma based on immunity-related genes. Front. Genet. 2023 14 1107294 10.3389/fgene.2023.1107294 36741315
    [Google Scholar]
  67. Jialin M. Li Z. Xiaofan L. Renal clear cell carcinoma molecular classification model based on multi-omics data and establishment method thereof. China Patent CN116246709A 2023
  68. Pei D. Yulu P. Tingxuan H. Biomarker for prognosis prediction of renal clear cell carcinoma immunotherapy and application of biomarker. China Patent CN117965728A; CN117965728B 2024
  69. Cortellis Drug Discovery Intelligence Database. Available from: https://www.cortellis.com/drugdiscovery/ (Accessed on 7 July 2021).
  70. Schwartz L.M. Woloshin S. Zheng E. Tse T. Zarin D.A. ClinicalTrials.gov and Drugs@FDA: A comparison of results reporting for new drug approval trials. Ann. Intern. Med. 2016 165 6 421 430 10.7326/M15‑2658 27294570
    [Google Scholar]
  71. Janakiram N.B. Mohammed A. Bryant T. Lightfoot S. Collin P.D. Steele V.E. Rao C.V. Improved innate immune responses by Frondanol A5, a sea cucumber extract, prevent intestinal tumorigenesis. Cancer Prev. Res. (Phila.) 2015 8 4 327 337 10.1158/1940‑6207.CAPR‑14‑0380 25657017
    [Google Scholar]
  72. Li Y. Liu Y. Zhang J. Li J. Shu Y. Propofol suppresses glioma tumorigenesis by regulating circ_0047688/miR-516b-5p/IFI30 axis. Biochem. Genet. 2023 61 1 151 169 10.1007/s10528‑022‑10243‑2 35763173
    [Google Scholar]
  73. Li L. Fei Y. Dong T. Song Y. Chen X. Zhang H. Zhou H. Liang M. Tang J. IFI30 as a key regulator of PDL1 immunotherapy prognosis in breast cancer. Int. Immunopharmacol. 2024 133 112093 10.1016/j.intimp.2024.112093 38669947
    [Google Scholar]
  74. Yang W. Soares J. Greninger P. Edelman E.J. Lightfoot H. Forbes S. Bindal N. Beare D. Smith J.A. Thompson I.R. Ramaswamy S. Futreal P.A. Haber D.A. Stratton M.R. Benes C. McDermott U. Garnett M.J. Genomics of Drug Sensitivity in Cancer (GDSC): A resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res. 2012 41 D1 D955 D961 10.1093/nar/gks1111 23180760
    [Google Scholar]
  75. Basu A. Bodycombe N.E. Cheah J.H. Price E.V. Liu K. Schaefer G.I. Ebright R.Y. Stewart M.L. Ito D. Wang S. Bracha A.L. Liefeld T. Wawer M. Gilbert J.C. Wilson A.J. Stransky N. Kryukov G.V. Dancik V. Barretina J. Garraway L.A. Hon C.S.Y. Munoz B. Bittker J.A. Stockwell B.R. Khabele D. Stern A.M. Clemons P.A. Shamji A.F. Schreiber S.L. An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules. Cell 2013 154 5 1151 1161 10.1016/j.cell.2013.08.003 23993102
    [Google Scholar]
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The Prognostic Role of Interferon Gamma-inducible Protein 30 in Clear Cell Renal Cell Carcinoma with Immune Infiltrates
Bentham Science Publishers ; https://doi.org/10.2174/0115748928367598250124123411
/content/journals/pra/10.2174/0115748928367598250124123411
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  • Article Type:     Research Article
Keywords: IFI30 ; Prognosis ; clear cell renal cell carcinoma ; PD1 ; tumor immune microenvironment

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