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Medical Oncology

Erschienen in:

01.11.2023 | Review Article

Recent advancement in targeted therapy and role of emerging technologies to treat cancer

verfasst von: Shrikant Barot, Henis Patel, Anjali Yadav, Igor Ban

Erschienen in: Medical Oncology | Ausgabe 11/2023

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Abstract

Cancer is a complex disease that causes abnormal cell growth and spread. DNA mutations, chemical or environmental exposure, viral infections, chronic inflammation, hormone abnormalities, etc., are underlying factors that can cause cancer. Drug resistance and toxicity complicate cancer treatment. Additionally, the variability of cancer makes it difficult to establish universal treatment guidelines. Next-generation sequencing has made genetic testing inexpensive. This uncovers genetic mutations that can be treated with specialty drugs. AI (artificial intelligence), machine learning, biopsy, next-generation sequencing, and digital pathology provide personalized cancer treatment. This allows for patient-specific biological targets and cancer treatment. Monoclonal antibodies, CAR-T, and cancer vaccines are promising cancer treatments. Recent trial data incorporating these therapies have shown superiority in clinical outcomes and drug tolerability over conventional chemotherapies. Combinations of these therapies with new technology can change cancer treatment and help many. This review discusses the development and challenges of targeted therapies like monoclonal antibodies (mAbs), bispecific antibodies (BsAbs), bispecific T cell engagers (BiTEs), dual variable domain (DVD) antibodies, CAR-T therapy, cancer vaccines, oncolytic viruses, lipid nanoparticle-based mRNA cancer vaccines, and their clinical outcomes in various cancers. We will also study how artificial intelligence and machine learning help find new cancer treatment targets.

Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646–74. https://doi.org/10.1016/j.cell.2011.02.013.CrossRefPubMed

Vogelstein B, Papadopoulos N, Velculescu VE, et al. Cancer genome landscapes. Science. 2013;339:1546–58. https://doi.org/10.1126/science.1235122.CrossRefPubMedPubMedCentral

Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature. 2009;458:719–24. https://doi.org/10.1038/nature07943.CrossRefPubMedPubMedCentral

Pao W, Miller V, Zakowski M, et al. EGF receptor gene mutations are common in lung cancers from “never smokers” and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci USA. 2004;101:13306–11. https://doi.org/10.1073/pnas.0405220101.CrossRefPubMedPubMedCentral

Samuels Y, Wang Z, Bardelli A, et al. High frequency of mutations of the PIK3CA gene in human cancers. Science. 2004;304:554–554. https://doi.org/10.1126/science.1096502.CrossRefPubMed

Prior IA, Hood FE, Hartley JL. The frequency of Ras mutations in cancer. Can Res. 2020;80:2969–74. https://doi.org/10.1158/0008-5472.CAN-19-3682.CrossRef

Lane DP. p53, guardian of the genome. Nature. 1992;358:15–6. https://doi.org/10.1038/358015a0.CrossRefPubMed

Sullivan KD, Galbraith MD, Andrysik Z, Espinosa JM. Mechanisms of transcriptional regulation by p53. Cell Death Differ. 2018;25:133–43. https://doi.org/10.1038/cdd.2017.174.CrossRefPubMed

Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420:860–7. https://doi.org/10.1038/nature01322.CrossRefPubMedPubMedCentral

10.

Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflammation. Nature. 2008;454:436–44. https://doi.org/10.1038/nature07205.CrossRefPubMed

11.

Daling JR, Madeleine MM, Johnson LG, et al. Human papillomavirus, smoking, and sexual practices in the etiology of anal cancer. Cancer. 2004;101:270–80. https://doi.org/10.1002/cncr.20365.CrossRefPubMed

12.

de Sanjose S, Quint WG, Alemany L, et al. Human papillomavirus genotype attribution in invasive cervical cancer: a retrospective cross-sectional worldwide study. Lancet Oncol. 2010;11:1048–56. https://doi.org/10.1016/S1470-2045(10)70230-8.CrossRefPubMed

13.

Chlebowski RT, Hendrix SL, Langer RD, et al. Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the Women’s Health Initiative Randomized Trial. JAMA. 2003;289:3243. https://doi.org/10.1001/jama.289.24.3243.CrossRefPubMed

14.

Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet. 2011;378:771–84. https://doi.org/10.1016/S0140-6736(11)60993-8.CrossRef

15.

Parsons JK, Carter HB, Platz EA, et al. Serum testosterone and the risk of prostate cancer: potential implications for testosterone therapy. Cancer Epidemiol Biomark Prev. 2005;14:2257–60. https://doi.org/10.1158/1055-9965.EPI-04-0715.CrossRef

16.

Phi LTH, Sari IN, Yang Y-G, et al. Cancer stem cells (CSCs) in drug resistance and their therapeutic implications in cancer treatment. Stem Cells Int. 2018;2018:1–16. https://doi.org/10.1155/2018/5416923.CrossRef

17.

Song G, Ouyang G, Bao S. The activation of Akt/PKB signaling pathway and cell survival. J Cell Mol Med. 2005;9:59–71. https://doi.org/10.1111/j.1582-4934.2005.tb00337.x.CrossRefPubMedPubMedCentral

18.

Printezi MI, Kilgallen AB, Bond MJG, et al. Toxicity and efficacy of chronomodulated chemotherapy: a systematic review. Lancet Oncol. 2022;23:e129–43. https://doi.org/10.1016/S1470-2045(21)00639-2.CrossRefPubMed

19.

Patel H, Palekar S, Patel A, Patel K. Ibrutinib amorphous solid dispersions with enhanced dissolution at colonic pH for the localized treatment of colorectal cancer. Int J Pharm. 2023;641:123056. https://doi.org/10.1016/j.ijpharm.2023.123056.CrossRefPubMed

20.

Turajlic S, Sottoriva A, Graham T, Swanton C. Resolving genetic heterogeneity in cancer. Nat Rev Genet. 2019;20:404–16. https://doi.org/10.1038/s41576-019-0114-6.CrossRefPubMed

21.

Dieci MV, Smutná V, Scott V, et al. Whole exome sequencing of rare aggressive breast cancer histologies. Breast Cancer Res Treat. 2016;156:21–32. https://doi.org/10.1007/s10549-016-3718-y.CrossRefPubMed

22.

Zhong L, Li Y, Xiong L, et al. Small molecules in targeted cancer therapy: advances, challenges, and future perspectives. Sig Transduct Target Ther. 2021;6:1–48. https://doi.org/10.1038/s41392-021-00572-w.CrossRef

23.

Padma VV. An overview of targeted cancer therapy. Biomedicine (Taipei). 2015;5:19. https://doi.org/10.7603/s40681-015-0019-4.CrossRefPubMed

24.

Gonzalez H, Hagerling C, Werb Z. Roles of the immune system in cancer: from tumor initiation to metastatic progression. Genes Dev. 2018;32:1267–84. https://doi.org/10.1101/gad.314617.118.CrossRefPubMedPubMedCentral

25.

Chan W, Lee M, Yeo ZX, et al. Development and validation of next generation sequencing based 35-gene hereditary cancer panel. Hereditary Cancer Clin Pract. 2020;18:9. https://doi.org/10.1186/s13053-020-00141-2.CrossRef

26.

Dlamini Z, Francies FZ, Hull R, Marima R. Artificial intelligence (AI) and big data in cancer and precision oncology. Comput Struct Biotechnol J. 2020;18:2300–11. https://doi.org/10.1016/j.csbj.2020.08.019.CrossRefPubMedPubMedCentral

27.

Mosele F, Remon J, Mateo J, et al. Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: a report from the ESMO Precision Medicine Working Group. Ann Oncol. 2020;31:1491–505. https://doi.org/10.1016/j.annonc.2020.07.014.CrossRefPubMed

28.

Bruzas S, Kuemmel S, Harrach H, et al. Next-generation sequencing-directed therapy in patients with metastatic breast cancer in routine clinical practice. Cancers (Basel). 2021;13:4564. https://doi.org/10.3390/cancers13184564.CrossRefPubMed

29.

Zahavi D, Weiner L. Monoclonal antibodies in cancer therapy. Antibodies. 2020;9:34. https://doi.org/10.3390/antib9030034.CrossRefPubMedPubMedCentral

30.

Hafeez U, Parakh S, Gan HK, Scott AM. Antibody-drug conjugates for cancer therapy. Molecules. 2020;25:4764. https://doi.org/10.3390/molecules25204764.CrossRefPubMedPubMedCentral

31.

Arteaga CL, Engelman JA. ERBB receptors: from oncogene discovery to basic science to mechanism-based cancer therapeutics. Cancer Cell. 2014;25:282–303. https://doi.org/10.1016/j.ccr.2014.02.025.CrossRefPubMedPubMedCentral

32.

Tebbutt N, Pedersen MW, Johns TG. Targeting the ERBB family in cancer: couples therapy. Nat Rev Cancer. 2013;13:663–73. https://doi.org/10.1038/nrc3559.CrossRefPubMed

33.

Hsu JL, Hung M-C. The role of HER2, EGFR, and other receptor tyrosine kinases in breast cancer. Cancer Metastasis Rev. 2016;35:575–88. https://doi.org/10.1007/s10555-016-9649-6.CrossRefPubMedPubMedCentral

34.

Rotow J, Bivona TG. Understanding and targeting resistance mechanisms in NSCLC. Nat Rev Cancer. 2017;17:637–58. https://doi.org/10.1038/nrc.2017.84.CrossRefPubMed

35.

Roskoski R. The ErbB/HER family of protein-tyrosine kinases and cancer. Pharmacol Res. 2014;79:34–74. https://doi.org/10.1016/j.phrs.2013.11.002.CrossRefPubMed

36.

Takegawa N, Yonesaka K. HER2 as an emerging oncotarget for colorectal cancer treatment after failure of anti-epidermal growth factor receptor therapy. Clin Colorectal Cancer. 2017;16:247–51. https://doi.org/10.1016/j.clcc.2017.03.001.CrossRefPubMed

37.

Boku N. HER2-positive gastric cancer. Gastric Cancer. 2014;17:1–12. https://doi.org/10.1007/s10120-013-0252-z.CrossRefPubMed

38.

Hayes DF. HER2 and breast cancer—a phenomenal success story. N Engl J Med. 2019;381:1284–6. https://doi.org/10.1056/NEJMcibr1909386.CrossRefPubMed

39.

Pietrantonio F, Morano F, Corallo S, et al. Maintenance therapy with Panitumumab alone vs Panitumumab plus fluorouracil-Leucovorin in patients with RAS wild-type metastatic colorectal cancer: a phase 2 randomized clinical trial. JAMA Oncol. 2019;5:1268–75. https://doi.org/10.1001/jamaoncol.2019.1467.CrossRefPubMedPubMedCentral

40.

Dean L, Kane M, et al. Cetuximab therapy and RAS and BRAF genotype. In: Pratt VM, Scott SA, Pirmohamed M, et al., editors. Medical genetics summaries. Bethesda: National Center for Biotechnology Information; 2012.

41.

Van Cutsem E, Köhne C-H, Hitre E, et al. Cetuximab and chemotherapy as initial treatment for metastatic colorectal cancer. N Engl J Med. 2009;360:1408–17. https://doi.org/10.1056/NEJMoa0805019.CrossRefPubMed

42.

Herbst RS, Giaccone G, de Marinis F, et al. Atezolizumab for First-Line Treatment of PD-L1–Selected Patients with NSCLC. N Engl J Med. 2020;383:1328–39. https://doi.org/10.1056/NEJMoa1917346.CrossRefPubMed

43.

Colevas AD, Bahleda R, Braiteh F, et al. Safety and clinical activity of atezolizumab in head and neck cancer: results from a phase I trial. Ann Oncol. 2018;29:2247–53. https://doi.org/10.1093/annonc/mdy411.CrossRefPubMed

44.

Syed YY. Sacituzumab Govitecan: first approval. Drugs. 2020;80:1019–25. https://doi.org/10.1007/s40265-020-01337-5.CrossRefPubMedPubMedCentral

45.

Goldenberg DM, Cardillo TM, Govindan SV, et al. Trop-2 is a novel target for solid cancer therapy with sacituzumab govitecan (IMMU-132), an antibody-drug conjugate (ADC). Oncotarget. 2015;6:22496–512. https://doi.org/10.18632/oncotarget.4318.CrossRefPubMedPubMedCentral

46.

Bardia A, Hurvitz SA, Tolaney SM, et al. Sacituzumab Govitecan in metastatic triple-negative breast cancer. N Engl J Med. 2021;384:1529–41. https://doi.org/10.1056/NEJMoa2028485.CrossRefPubMed

47.

Queudeville M, Ebinger M. Blinatumomab in pediatric acute lymphoblastic leukemia—from salvage to first line therapy (a systematic review). JCM. 2021;10:2544. https://doi.org/10.3390/jcm10122544.CrossRefPubMedPubMedCentral

48.

Labrijn AF, Janmaat ML, Reichert JM, Parren PWHI. Bispecific antibodies: a mechanistic review of the pipeline. Nat Rev Drug Discov. 2019;18:585–608. https://doi.org/10.1038/s41573-019-0028-1.CrossRefPubMed

49.

Zhao Q. Bispecific antibodies for autoimmune and inflammatory diseases: clinical progress to date. BioDrugs. 2020;34:111–9. https://doi.org/10.1007/s40259-019-00400-2.CrossRefPubMed

50.

Huehls AM, Coupet TA, Sentman CL. Bispecific T-cell engagers for cancer immunotherapy. Immunol Cell Biol. 2015;93:290–6. https://doi.org/10.1038/icb.2014.93.CrossRefPubMed

51.

Van Der Sluis IM, De Lorenzo P, Kotecha RS, et al. Blinatumomab added to chemotherapy in infant lymphoblastic leukemia. N Engl J Med. 2023;388:1572–81. https://doi.org/10.1056/NEJMoa2214171.CrossRefPubMed

52.

Syed YY. Amivantamab: first approval. Drugs. 2021;81:1349–53. https://doi.org/10.1007/s40265-021-01561-7.CrossRefPubMed

53.

Park K, Haura EB, Leighl NB, et al. Amivantamab in EGFR Exon 20 insertion-mutated non-small-cell lung cancer progressing on platinum chemotherapy: initial results from the CHRYSALIS Phase I Study. J Clin Oncol. 2021;39:3391–402. https://doi.org/10.1200/JCO.21.00662.CrossRefPubMedPubMedCentral

54.

Vormittag P, Gunn R, Ghorashian S, Veraitch FS. A guide to manufacturing CAR T cell therapies. Curr Opin Biotechnol. 2018;53:164–81. https://doi.org/10.1016/j.copbio.2018.01.025.CrossRefPubMed

55.

Stock S, Schmitt M, Sellner L. Optimizing manufacturing protocols of chimeric antigen receptor T cells for improved anticancer immunotherapy. Int J Mol Sci. 2019;20:6223. https://doi.org/10.3390/ijms20246223.CrossRefPubMedPubMedCentral

56.

Pampusch MS, Haran KP, Hart GT, et al. Rapid transduction and expansion of transduced T cells with maintenance of central memory populations. Mol Ther. 2020;16:1–10. https://doi.org/10.1016/j.omtm.2019.09.007.CrossRef

57.

Vannucci L, Lai M, Chiuppesi F, et al. Viral vectors: a look back and ahead on gene transfer technology. New Microbiol. 2013;36:1–22.PubMed

58.

Rupp LJ, Schumann K, Roybal KT, et al. CRISPR/Cas9-mediated PD-1 disruption enhances anti-tumor efficacy of human chimeric antigen receptor T cells. Sci Rep. 2017;7:737. https://doi.org/10.1038/s41598-017-00462-8.CrossRefPubMedPubMedCentral

59.

Guedan S, Calderon H, Posey AD, Maus MV. Engineering and design of chimeric antigen receptors. Mol Ther. 2019;12:145–56. https://doi.org/10.1016/j.omtm.2018.12.009.CrossRef

60.

CAR-T design: Elements and their synergistic function—ScienceDirect. https://www.sciencedirect.com/science/article/pii/S2352396420303078. Accessed 15 May 2023

61.

Thistlethwaite FC, Gilham DE, Guest RD, et al. The clinical efficacy of first-generation carcinoembryonic antigen (CEACAM5)-specific CAR T cells is limited by poor persistence and transient pre-conditioning-dependent respiratory toxicity. Cancer Immunol Immunother. 2017;66:1425–36. https://doi.org/10.1007/s00262-017-2034-7.CrossRefPubMedPubMedCentral

62.

van der Stegen SJC, Hamieh M, Sadelain M. The pharmacology of second-generation chimeric antigen receptors. Nat Rev Drug Discov. 2015;14:499–509. https://doi.org/10.1038/nrd4597.CrossRefPubMedPubMedCentral

63.

Chmielewski M, Abken H. TRUCKs: the fourth generation of CARs. Expert Opin Biol Ther. 2015;15:1145–54. https://doi.org/10.1517/14712598.2015.1046430.CrossRefPubMed

64.

Tokarew N, Ogonek J, Endres S, et al. Teaching an old dog new tricks: next-generation CAR T cells. Br J Cancer. 2019;120:26–37. https://doi.org/10.1038/s41416-018-0325-1.CrossRefPubMed

65.

Sengsayadeth S, Savani BN, Oluwole O, Dholaria B. Overview of approved CAR-T therapies, ongoing clinical trials, and its impact on clinical practice. JHaem. 2022;3:6–10. https://doi.org/10.1002/jha2.338.CrossRef

66.

Locke FL, Miklos DB, Jacobson CA, et al. Axicabtagene ciloleucel as second-line therapy for large B-cell lymphoma. N Engl J Med. 2022;386:640–54. https://doi.org/10.1056/NEJMoa2116133.CrossRefPubMed

67.

Sterner RC, Sterner RM. CAR-T cell therapy: current limitations and potential strategies. Blood Cancer J. 2021;11:1–11. https://doi.org/10.1038/s41408-021-00459-7.CrossRef

68.

Lee DW, Santomasso BD, Locke FL, et al. ASTCT consensus grading for cytokine release syndrome and neurologic toxicity associated with immune effector cells. Biol Blood Marrow Transplant. 2019;25:625–38. https://doi.org/10.1016/j.bbmt.2018.12.758.CrossRefPubMed

69.

Santomasso BD, Park JH, Salloum D, et al. Clinical and biological correlates of neurotoxicity associated with CAR T-cell therapy in patients with B-cell acute lymphoblastic leukemia. Cancer Discov. 2018;8:958–71. https://doi.org/10.1158/2159-8290.CD-17-1319.CrossRefPubMedPubMedCentral

70.

Ruella M, Xu J, Barrett DM, et al. Induction of resistance to chimeric antigen receptor T cell therapy by transduction of a single leukemic B cell. Nat Med. 2018;24:1499–503. https://doi.org/10.1038/s41591-018-0201-9.CrossRefPubMedPubMedCentral

71.

Hinrichs CS. Self-defeating CAR-Ts protect leukemic cells. Sci Transl Med. 2018;10:eaav3888. https://doi.org/10.1126/scitranslmed.aav3888.CrossRef

72.

Lin MJ, Svensson-Arvelund J, Lubitz GS, et al. Cancer vaccines: the next immunotherapy frontier. Nat Cancer. 2022;3:911–26. https://doi.org/10.1038/s43018-022-00418-6.CrossRefPubMed

73.

Cheever MA, Higano CS. PROVENGE (Sipuleucel-T) in prostate cancer: the first FDA-approved therapeutic cancer vaccine. Clin Cancer Res. 2011;17:3520–6. https://doi.org/10.1158/1078-0432.CCR-10-3126.CrossRefPubMed

74.

Madan RA, Antonarakis ES, Drake CG, et al. Putting the pieces together: completing the mechanism of action jigsaw for Sipuleucel-T. JNCI. 2020;112:562–73. https://doi.org/10.1093/jnci/djaa021.CrossRefPubMedPubMedCentral

75.

Kantoff PW, Higano CS, Shore ND, et al. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N Engl J Med. 2010;363:411–22. https://doi.org/10.1056/Nejmoa1001294.CrossRefPubMed

76.

Haitz K, Khosravi H, Lin JY, et al. Review of talimogene laherparepvec: a first-in-class oncolytic viral treatment of advanced melanoma. J Am Acad Dermatol. 2020;83:189–96. https://doi.org/10.1016/j.jaad.2020.01.039.CrossRefPubMed

77.

Liu BL, Robinson M, Han Z-Q, et al. ICP34.5 deleted herpes simplex virus with enhanced oncolytic, immune stimulating, and anti-tumour properties. Gene Ther. 2003;10:292–303. https://doi.org/10.1038/sj.gt.3301885.CrossRefPubMed

78.

Hawkins LK, Lemoine NR, Kirn D. Oncolytic biotherapy: a novel therapeutic platform. Lancet Oncol. 2002;3:17–26. https://doi.org/10.1016/S1470-2045(01)00618-0.CrossRefPubMed

79.

Rehman H, Silk AW, Kane MP, Kaufman HL. Into the clinic: talimogene laherparepvec (T-VEC), a first-in-class intratumoral oncolytic viral therapy. J Immunother Cancer. 2016;4:53. https://doi.org/10.1186/s40425-016-0158-5.CrossRefPubMedPubMedCentral

80.

Ferrucci PF, Pala L, Conforti F, Cocorocchio E. Talimogene laherparepvec (T-VEC): an intralesional cancer immunotherapy for advanced melanoma. Cancers (Basel). 2021;13:1383. https://doi.org/10.3390/cancers13061383.CrossRefPubMed

81.

Andtbacka RHI, Kaufman HL, Collichio F, et al. Talimogene laherparepvec improves durable response rate in patients with advanced melanoma. J Clin Oncol. 2015;33:2780–8. https://doi.org/10.1200/JCO.2014.58.3377.CrossRefPubMed

82.

Hou X, Zaks T, Langer R, Dong Y. Lipid nanoparticles for mRNA delivery. Nat Rev Mater. 2021;6:1078–94. https://doi.org/10.1038/s41578-021-00358-0.CrossRefPubMedPubMedCentral

83.

Tenchov R, Bird R, Curtze AE, Zhou Q. Lipid nanoparticles─from liposomes to mRNA vaccine delivery, a landscape of research diversity and advancement. ACS Nano. 2021;15:16982–7015. https://doi.org/10.1021/acsnano.1c04996.CrossRefPubMed

84.

Kulkarni JA, Cullis PR, van der Meel R. Lipid nanoparticles enabling gene therapies: from concepts to clinical utility. Nucleic Acid Ther. 2018;28:146–57. https://doi.org/10.1089/nat.2018.0721.CrossRefPubMed

85.

Rojas LA, Sethna Z, Soares KC, et al. Personalized RNA neoantigen vaccines stimulate T cells in pancreatic cancer. Nature. 2023. https://doi.org/10.1038/s41586-023-06063-y.CrossRefPubMedPubMedCentral

86.

Jia D, Li S, Li D, et al. Mining TCGA database for genes of prognostic value in glioblastoma microenvironment. Aging. 2018;10:592–605. https://doi.org/10.18632/aging.101415.CrossRefPubMedPubMedCentral

87.

Tomczak K, Czerwińska P, Wiznerowicz M. Review the cancer genome atlas (TCGA): an immeasurable source of knowledge. WO. 2015;1A:68–77. https://doi.org/10.5114/wo.2014.47136.CrossRef

88.

The International Cancer Genome Consortium. International network of cancer genome projects. Nature. 2010;464:993–8. https://doi.org/10.1038/nature08987.CrossRefPubMedCentral

89.

Zhang J, Bajari R, Andric D, et al. The International Cancer Genome Consortium Data Portal. Nat Biotechnol. 2019;37:367–9. https://doi.org/10.1038/s41587-019-0055-9.CrossRefPubMed

90.

Uhlen M, Oksvold P, Fagerberg L, et al. Towards a knowledge-based human protein atlas. Nat Biotechnol. 2010;28:1248–50. https://doi.org/10.1038/nbt1210-1248.CrossRefPubMed

91.

Thul PJ, Lindskog C. The human protein atlas: a spatial map of the human proteome: the human protein atlas. Protein Sci. 2018;27:233–44. https://doi.org/10.1002/pro.3307.CrossRefPubMed

92.

Vizcaíno JA, Deutsch EW, Wang R, et al. ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat Biotechnol. 2014;32:223–6. https://doi.org/10.1038/nbt.2839.CrossRefPubMedPubMedCentral

93.

Edgar R. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30:207–10. https://doi.org/10.1093/nar/30.1.207.CrossRefPubMedPubMedCentral

94.

Suntsova M, Gaifullin N, Allina D, et al. Atlas of RNA sequencing profiles for normal human tissues. Sci Data. 2019;6:36. https://doi.org/10.1038/s41597-019-0043-4.CrossRefPubMedPubMedCentral

95.

Chiu Y-C, Chen H-IH, Gorthi A, et al. Deep learning of pharmacogenomics resources: moving towards precision oncology. Brief Bioinform. 2020;21:2066–83. https://doi.org/10.1093/bib/bbz144.CrossRefPubMed

96.

Wu Z, Ramsundar B, Feinberg EN, et al. MoleculeNet: a benchmark for molecular machine learning. Chem Sci. 2018;9:513–30. https://doi.org/10.1039/C7SC02664A.CrossRefPubMed

97.

Vamathevan J, Clark D, Czodrowski P, et al. Applications of machine learning in drug discovery and development. Nat Rev Drug Discov. 2019;18:463–77. https://doi.org/10.1038/s41573-019-0024-5.CrossRefPubMedPubMedCentral

98.

Breiman L. Random forests. Mach Learn. 2001;45:5–32. https://doi.org/10.1023/A:1010933404324.CrossRef

99.

Sundar R, Barr Kumarakulasinghe N, Huak Chan Y, et al. Machine-learning model derived gene signature predictive of paclitaxel survival benefit in gastric cancer: results from the randomised phase III SAMIT trial. Gut. 2022;71:676–85. https://doi.org/10.1136/gutjnl-2021-324060.CrossRefPubMed

100.

Lee J, Yoon W, Kim S, et al. BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics. 2019. https://doi.org/10.1093/bioinformatics/btz682.CrossRefPubMedPubMedCentral

101.

Paul A, Anand R, Karmakar SP, et al. Exploring gene knockout strategies to identify potential drug targets using genome-scale metabolic models. Sci Rep. 2021;11:213. https://doi.org/10.1038/s41598-020-80561-1.CrossRefPubMedPubMedCentral

102.

Dukhande VV, Barot S, Husein S, Palaguachi C. Inhibition of glycogen metabolism as a potential strategy for anticancer therapy. FASEB J. 2017;31:942.10.

103.

Barot S, Abo-Ali EM, Palaguachi C, Dukhande VV. Insights into Glycogen Metabolic Inhibition-Induced Death of Hepatocellular Carcinoma. FASEB J. 2018;32:811.15.CrossRef

104.

Barot S, Abo-Ali EM, Zhou D, et al. Glycogen phosphorylase inhibition activates intrinsic apoptosis pathway and potentiates multi-kinase inhibitors in liver cancer cells. FASEB J. 2019;33:652–61.CrossRef

105.

Barot S, Abo-Ali EM, Zhou DL, et al. Inhibition of glycogen catabolism induces intrinsic apoptosis and augments multikinase inhibitors in hepatocellular carcinoma cells. Exp Cell Res. 2019;381:288–300.CrossRefPubMed

106.

Barot S (2021) Effect of inhibition of glycogen catabolism in hepatocellular carcinoma cells

107.

Barot S, Stephenson OJ, Priya Vemana H, et al. Metabolic alterations and mitochondrial dysfunction underlie hepatocellular carcinoma cell death induced by a glycogen metabolic inhibitor. Biochem Pharmacol. 2022;203:115201. https://doi.org/10.1016/j.bcp.2022.115201.CrossRefPubMedPubMedCentral

108.

Zhang J, Stevens MFG, Bradshaw TD. Temozolomide: mechanisms of action, repair and resistance. Curr Mol Pharmacol. 2012;5:102–14. https://doi.org/10.2174/1874467211205010102.CrossRefPubMed

Titel: Recent advancement in targeted therapy and role of emerging technologies to treat cancer
verfasst von: Shrikant Barot
Henis Patel
Anjali Yadav
Igor Ban
Publikationsdatum: 01.11.2023
Verlag: Springer US
Erschienen in: Medical Oncology / Ausgabe 11/2023
Print ISSN: 1357-0560
Elektronische ISSN: 1559-131X
DOI: https://doi.org/10.1007/s12032-023-02184-6

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Live-Webinar "Urologie und Sexualmedizin in der Praxis"

Springer Medizin

Recent advancement in targeted therapy and role of emerging technologies to treat cancer

Abstract

Neu im Fachgebiet Onkologie

Erhebliches Risiko für Kehlkopfkrebs bei mäßiger Dysplasie

15% bedauern gewählte Blasenkrebs-Therapie

Erhöhtes Risiko fürs Herz unter Checkpointhemmer-Therapie

Costims – das nächste heiße Ding in der Krebstherapie?

Update Onkologie

Live-Webinar "Urologie und Sexualmedizin in der Praxis"

Springer Medizin

Abstract

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Weitere Artikel der Ausgabe 11/2023

Tamoxifen induces eryptosis through calcium accumulation and oxidative stress

How gallic acid regulates molecular signaling: role in cancer drug resistance

Diosmetin induces apoptosis and protective autophagy in human gastric cancer HGC-27 cells via the PI3K/Akt/FoxO1 and MAPK/JNK pathways

Lysates from the probiotic bacterium Streptococcus thermophilus enhances the survival of T cells and triggers programmed cell death in neuroblastoma cells

Whole-exome sequencing reveals mutational profiles of anorectal and gynecological melanoma

C2orf48 promotes the progression of nasopharyngeal carcinoma by regulating high mobility group AT-hook 2

Neu im Fachgebiet Onkologie

Erhebliches Risiko für Kehlkopfkrebs bei mäßiger Dysplasie

15% bedauern gewählte Blasenkrebs-Therapie

Erhöhtes Risiko fürs Herz unter Checkpointhemmer-Therapie

Costims – das nächste heiße Ding in der Krebstherapie?

Update Onkologie