Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Conventional chemotherapy: millions of cures, unresolved therapeutic index

Subjects

Abstract

In recent decades, millions of patients with cancer have been cured by chemotherapy alone. By ‘cure’, we mean that patients with cancers that would be fatal if left untreated receive a time-limited course of chemotherapy and their cancer disappears, never to return. In an era when hundreds of thousands of cancer genomes have been sequenced, a remarkable fact persists: in most patients who have been cured, we still do not fully understand the mechanisms underlying the therapeutic index by which the tumour cells are killed, but normal cells are somehow spared. In contrast, in more recent years, patients with cancer have benefited from targeted therapies that usually do not cure but whose mechanisms of therapeutic index are, at least superficially, understood. In this Perspective, we will explore the various and sometimes contradictory models that have attempted to explain why chemotherapy can cure some patients with cancer, and what gaps in our understanding of the therapeutic index of chemotherapy remain to be filled. We will summarize principles which have benefited curative conventional chemotherapy regimens in the past, principles which might be deployed in constructing combinations that include modern targeted therapies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Apoptotic priming determines whether conventional chemotherapy induces cell death.
Fig. 2: Therapeutic index in tumours is dictated by replication stress, oxidative stress, p53 or DNA repair statuses.

Similar content being viewed by others

References

  1. Kantarjian, H. M. et al. The cure of leukemia through the optimist’s prism. Cancer 128, 240–259 (2022).

    PubMed  Google Scholar 

  2. Howlader, N. et al. Cancer-specific mortality, cure fraction, and noncancer causes of death among diffuse large B-cell lymphoma patients in the immunochemotherapy era. Cancer 123, 3326–3334 (2017).

    PubMed  Google Scholar 

  3. Cheng, L. et al. Testicular cancer. Nat. Rev. Dis. Prim. 4, 29 (2018).

    PubMed  Google Scholar 

  4. Sargent, D. et al. Evidence for cure by adjuvant therapy in colon cancer: observations based on individual patient data from 20,898 patients on 18 randomized trials. J. Clin. Oncol. 27, 872–877 (2009).

    PubMed  PubMed Central  Google Scholar 

  5. Anampa, J., Makower, D. & Sparano, J. A. Progress in adjuvant chemotherapy for breast cancer: an overview. BMC Med. 13, 195 (2015).

    PubMed  PubMed Central  Google Scholar 

  6. Malhotra, V. & Perry, M. C. Classical chemotherapy: mechanisms, toxicities and the therapeutic window. Cancer Biol. Ther. 2, S2–S4 (2003).

    PubMed  Google Scholar 

  7. Valeriote, F. & van Putten, L. Proliferation-dependent cytotoxicity of anticancer agents: a review. Cancer Res. 35, 2619–2630 (1975).

    CAS  PubMed  Google Scholar 

  8. Komlodi-Pasztor, E., Sackett, D., Wilkerson, J. & Fojo, T. Mitosis is not a key target of microtubule agents in patient tumors. Nat. Rev. Clin. Oncol. 8, 244–250 (2011).

    CAS  PubMed  Google Scholar 

  9. Komlodi-Pasztor, E., Sackett, D. L. & Fojo, A. T. Inhibitors targeting mitosis: tales of how great drugs against a promising target were brought down by a flawed rationale. Clin. Cancer Res. 18, 51–63 (2012).

    CAS  PubMed  Google Scholar 

  10. Tubiana, M., Pejovic, M. H., Koscielny, S., Chavaudra, N. & Malaise, E. Growth rate, kinetics of tumor cell proliferation and long-term outcome in human breast cancer. Int. J. Cancer 44, 17–22 (1989).

    CAS  PubMed  Google Scholar 

  11. Mitchison, T. J. The proliferation rate paradox in antimitotic chemotherapy. Mol. Biol. Cell 23, 1–6 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Stryckmans, P., Debusscher, L., Ronge-Collard, E., Socquet, M. & Zittoun, R. The labelling index of marrow myeloblasts: a predictive test for relapse of acute non-lymphoblastic leukemia. Leuk. Res. 4, 79–87 (1980).

    CAS  PubMed  Google Scholar 

  13. Staber, P. B. et al. Common alterations in gene expression and increased proliferation in recurrent acute myeloid leukemia. Oncogene 23, 894–904 (2004).

    CAS  PubMed  Google Scholar 

  14. Alba, E. et al. High proliferation predicts pathological complete response to neoadjuvant chemotherapy in early breast cancer. Oncologist 21, 150–155 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Amadori, D. et al. Cell proliferation as a predictor of response to chemotherapy in metastatic breast cancer: a prospective study. Breast Cancer Res. Treat. 43, 7–14 (1997).

    CAS  PubMed  Google Scholar 

  16. Viale, G. et al. Predictive value of tumor Ki-67 expression in two randomized trials of adjuvant chemoendocrine therapy for node-negative breast cancer. J. Natl Cancer Inst. 100, 207–212 (2008).

    CAS  PubMed  Google Scholar 

  17. Granada, A. E. et al. The effects of proliferation status and cell cycle phase on the responses of single cells to chemotherapy. Mol. Biol. Cell 31, 845–857 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. de Azambuja, E. et al. Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br. J. Cancer 96, 1504–1513 (2007).

    PubMed  PubMed Central  Google Scholar 

  19. Abubakar, M. et al. Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups. Breast Cancer Res. 18, 104 (2016).

    PubMed  PubMed Central  Google Scholar 

  20. Volpi, A. et al. Prognostic relevance of histological grade and its components in node-negative breast cancer patients. Mod. Pathol. 17, 1038–1044 (2004).

    PubMed  Google Scholar 

  21. Siddhartha, G. & Vijay, P. R-CHOP versus R-CVP in the treatment of follicular lymphoma: a meta-analysis and critical appraisal of current literature. J. Hematol. Oncol. 2, 14 (2009).

    PubMed  PubMed Central  Google Scholar 

  22. Hallek, M. et al. Addition of rituximab to fludarabine and cyclophosphamide in patients with chronic lymphocytic leukaemia: a randomised, open-label, phase 3 trial. Lancet 376, 1164–1174 (2010).

    CAS  PubMed  Google Scholar 

  23. Chiorazzi, N. Cell proliferation and death: forgotten features of chronic lymphocytic leukemia B cells. Best. Pract. Res. Clin. Haematol. 20, 399–413 (2007).

    CAS  PubMed  Google Scholar 

  24. Petrackova, A., Turcsanyi, P., Papajik, T. & Kriegova, E. Revisiting Richter transformation in the era of novel CLL agents. Blood Rev. 49, 100824 (2021).

    CAS  PubMed  Google Scholar 

  25. Skipper, H. E., Schabel, F. M. Jr & Wilcox, W. S. Experimental evaluation of potential anticancer agents. XIII. On the criteria and kinetics associated with “curability” of experimental leukemia. Cancer Chemother. Rep. 35, 1–111 (1964).

    CAS  PubMed  Google Scholar 

  26. Makin, G. & Hickman, J. A. Apoptosis and cancer chemotherapy. Cell Tissue Res. 301, 143–152 (2000).

    CAS  PubMed  Google Scholar 

  27. Brunelle, J. K. & Letai, A. Control of mitochondrial apoptosis by the Bcl-2 family. J. Cell Sci. 122, 437–441 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Deng, J. et al. BH3 profiling identifies three distinct classes of apoptotic blocks to predict response to ABT-737 and conventional chemotherapeutic agents. Cancer Cell 12, 171–185 (2007).

    CAS  PubMed  Google Scholar 

  29. Ryan, J. A., Brunelle, J. K. & Letai, A. Heightened mitochondrial priming is the basis for apoptotic hypersensitivity of CD4+CD8+ thymocytes. Proc. Natl Acad. Sci. USA 107, 12895–12900 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Ni et al. Pretreatment mitochondrial priming correlates with clinical response to cytotoxic chemotherapy. Science 334, 1129–1133 (2011).

    Google Scholar 

  31. Wei, M. C. et al. Proapoptotic BAX and BAK: a requisite gateway to mitochondrial dysfunction and death. Science 292, 727–730 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Koss, B. et al. Defining specificity and on-target activity of BH3-mimetics using engineered B-ALL cell lines. Oncotarget 7, 11500–11511 (2016).

    PubMed  PubMed Central  Google Scholar 

  33. Pourzia, A. L. et al. Quantifying requirements for mitochondrial apoptosis in CAR T killing of cancer cells. Cell Death Dis. 14, 267 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Vo, T. T. et al. Relative mitochondrial priming of myeloblasts and normal HSCs determines chemotherapeutic success in AML. Cell 151, 344–355 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Davids, M. S. et al. Decreased mitochondrial apoptotic priming underlies stroma-mediated treatment resistance in chronic lymphocytic leukemia. Blood 120, 3501–3509 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Aries, I. M. et al. PRC2 loss induces chemoresistance by repressing apoptosis in T cell acute lymphoblastic leukemia. J. Exp. Med. 215, 3094–3114 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Bhatt, S. et al. Reduced mitochondrial apoptotic priming drives resistance to BH3 mimetics in acute myeloid leukemia. Cancer Cell 38, 872–890.e6 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Siegel, S. E. et al. Pediatric-inspired treatment regimens for adolescents and young adults with Philadelphia chromosome-negative acute lymphoblastic leukemia: a review. JAMA Oncol. 4, 725–734 (2018).

    PubMed  PubMed Central  Google Scholar 

  39. Tan, D. S. et al. “BRCAness” syndrome in ovarian cancer: a case–control study describing the clinical features and outcome of patients with epithelial ovarian cancer associated with BRCA1 and BRCA2 mutations. J. Clin. Oncol. 26, 5530–5536 (2008).

    PubMed  Google Scholar 

  40. Sakai, W. et al. Secondary mutations as a mechanism of cisplatin resistance in BRCA2-mutated cancers. Nature 451, 1116–1120 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Moore, K. et al. Maintenance olaparib in patients with newly diagnosed advanced ovarian cancer. N. Engl. J. Med. 379, 2495–2505 (2018).

    CAS  PubMed  Google Scholar 

  42. Tutt, A. N. J. et al. Adjuvant olaparib for patients with BRCA1- or BRCA2-mutated breast cancer. N. Engl. J. Med. 384, 2394–2405 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Saxena, S. & Zou, L. Hallmarks of DNA replication stress. Mol. Cell 82, 2298–2314 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Bartkova, J. et al. DNA damage response as a candidate anti-cancer barrier in early human tumorigenesis. Nature 434, 864–870 (2005).

    CAS  PubMed  Google Scholar 

  45. Gorgoulis, V. G. et al. Activation of the DNA damage checkpoint and genomic instability in human precancerous lesions. Nature 434, 907–913 (2005).

    CAS  PubMed  Google Scholar 

  46. Bester, A. C. et al. Nucleotide deficiency promotes genomic instability in early stages of cancer development. Cell 145, 435–446 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Bartkova, J. et al. Oncogene-induced senescence is part of the tumorigenesis barrier imposed by DNA damage checkpoints. Nature 444, 633–637 (2006).

    CAS  PubMed  Google Scholar 

  48. Gaillard, H., Garcia-Muse, T. & Aguilera, A. Replication stress and cancer. Nat. Rev. Cancer 15, 276–289 (2015).

    CAS  PubMed  Google Scholar 

  49. Cybulla, E. & Vindigni, A. Leveraging the replication stress response to optimize cancer therapy. Nat. Rev. Cancer 23, 6–24 (2023).

    CAS  PubMed  Google Scholar 

  50. da Costa, A., Chowdhury, D., Shapiro, G. I., D’Andrea, A. D. & Konstantinopoulos, P. A. Targeting replication stress in cancer therapy. Nat. Rev. Drug. Discov. 22, 38–58 (2023).

    PubMed  Google Scholar 

  51. Kotsantis, P., Petermann, E. & Boulton, S. J. Mechanisms of oncogene-induced replication stress: jigsaw falling into place. Cancer Discov. 8, 537–555 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Milano, L., Gautam, A. & Caldecott, K. W. DNA damage and transcription stress. Mol. Cell 84, 70–79 (2024).

    CAS  PubMed  Google Scholar 

  53. Dobbelstein, M. & Sorensen, C. S. Exploiting replicative stress to treat cancer. Nat. Rev. Drug. Discov. 14, 405–423 (2015).

    CAS  PubMed  Google Scholar 

  54. Toledo, L. I. et al. A cell-based screen identifies ATR inhibitors with synthetic lethal properties for cancer-associated mutations. Nat. Struct. Mol. Biol. 18, 721–727 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Yap, T. A. et al. Camonsertib in DNA damage response-deficient advanced solid tumors: phase 1 trial results. Nat. Med. 29, 1400–1411 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Zoppoli, G. et al. Putative DNA/RNA helicase Schlafen-11 (SLFN11) sensitizes cancer cells to DNA-damaging agents. Proc. Natl Acad. Sci. USA 109, 15030–15035 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Metzner, F. J. et al. Mechanistic understanding of human SLFN11. Nat. Commun. 13, 5464 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Willis, S. E. et al. Retrospective analysis of Schlafen11 (SLFN11) to predict the outcomes to therapies affecting the DNA damage response. Br. J. Cancer 125, 1666–1676 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Zhang, B. et al. A wake-up call for cancer DNA damage: the role of Schlafen 11 (SLFN11) across multiple cancers. Br. J. Cancer 125, 1333–1340 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Mavrommatis, E., Fish, E. N. & Platanias, L. C. The Schlafen family of proteins and their regulation by interferons. J. Interferon Cytokine Res. 33, 206–210 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Grote, I. et al. TP53 mutations are associated with primary endocrine resistance in luminal early breast cancer. Cancer Med. 10, 8581–8594 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Dhakal, P. et al. Acute myeloid leukemia resistant to venetoclax-based therapy: what does the future hold? Blood Rev. 59, 101036 (2023).

    CAS  PubMed  Google Scholar 

  63. Wendel, H. G. et al. Loss of p53 impedes the antileukemic response to BCR-ABL inhibition. Proc. Natl Acad. Sci. USA 103, 7444–7449 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Johnstone, R. W., Ruefli, A. A. & Lowe, S. W. Apoptosis: a link between cancer genetics and chemotherapy. Cell 108, 153–164 (2002).

    CAS  PubMed  Google Scholar 

  65. Mansur, M. B. et al. Evolutionary determinants of curability in cancer. Nat. Ecol. Evol. 7, 1761–1770 (2023).

    PubMed  Google Scholar 

  66. Stengel, A. et al. Interplay of TP53 allelic state, blast count, and complex karyotype on survival of patients with AML and MDS. Blood Adv. 7, 5540–5548 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Bernard, E. et al. Implications of TP53 allelic state for genome stability, clinical presentation and outcomes in myelodysplastic syndromes. Nat. Med. 26, 1549–1556 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Daver, N. G. et al. TP53-mutated myelodysplastic syndrome and acute myeloid leukemia: biology, current therapy, and future directions. Cancer Discov. 12, 2516–2529 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Kennedy, M. C. & Lowe, S. W. Mutant p53: it’s not all one and the same. Cell Death Differ. 29, 983–987 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Wang, Z. et al. Loss-of-function but not gain-of-function properties of mutant TP53 are critical for the proliferation, survival, and metastasis of a broad range of cancer cells. Cancer Discov. 14, 362–379 (2024).

    PubMed  Google Scholar 

  71. Bunz, F. et al. Disruption of p53 in human cancer cells alters the responses to therapeutic agents. J. Clin. Invest. 104, 263–269 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Vousden, K. & Prives, C. P53 and prognosis; new insights and further complexity. Cell 120, 7–10 (2005).

    CAS  PubMed  Google Scholar 

  73. Keogh, A., Finn, S. & Radonic, T. Emerging biomarkers and the changing landscape of small cell lung cancer. Cancers 14, 3772 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Bertheau, P. et al. Effect of mutated TP53 on response of advanced breast cancers to high-dose chemotherapy. Lancet 360, 852–854 (2002).

    CAS  PubMed  Google Scholar 

  75. Welch, J. S. et al. TP53 and decitabine in acute myeloid leukemia and myelodysplastic syndromes. N. Engl. J. Med. 375, 2023–2036 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Bertheau, P. et al. Exquisite sensitivity of TP53 mutant and basal breast cancers to a dose-dense epirubicin–cyclophosphamide regimen. PLoS Med. 4, e90 (2007).

    PubMed  PubMed Central  Google Scholar 

  77. Jackson, J. G. et al. p53-mediated senescence impairs the apoptotic response to chemotherapy and clinical outcome in breast cancer. Cancer Cell 21, 793–806 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Varna, M. et al. p53 dependent cell-cycle arrest triggered by chemotherapy in xenografted breast tumors. Int. J. Cancer 124, 991–997 (2009).

    CAS  PubMed  Google Scholar 

  79. Jackson, J. G. & Lozano, G. The mutant p53 mouse as a pre-clinical model. Oncogene 32, 4325–4330 (2013).

    CAS  PubMed  Google Scholar 

  80. Shahbandi, A., Nguyen, H. D. & Jackson, J. G. TP53 mutations and outcomes in breast cancer: reading beyond the headlines. Trends Cancer 6, 98–110 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Milanovic, M. et al. Senescence-associated reprogramming promotes cancer stemness. Nature 553, 96–100 (2018).

    CAS  PubMed  Google Scholar 

  82. Shallis, R. M. et al. TP53-altered acute myeloid leukemia and myelodysplastic syndrome with excess blasts should be approached as a single entity. Cancer 129, 175–180 (2023).

    CAS  PubMed  Google Scholar 

  83. Sies, H. & Jones, D. P. Reactive oxygen species (ROS) as pleiotropic physiological signalling agents. Nat. Rev. Mol. Cell Biol. 21, 363–383 (2020).

    CAS  PubMed  Google Scholar 

  84. Hayes, J. D., Dinkova-Kostova, A. T. & Tew, K. D. Oxidative stress in cancer. Cancer Cell 38, 167–197 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Cheung, E. C. & Vousden, K. H. The role of ROS in tumour development and progression. Nat. Rev. Cancer 22, 280–297 (2022).

    CAS  PubMed  Google Scholar 

  86. Wu, K., El Zowalaty, A. E., Sayin, V. I. & Papagiannakopoulos, T. The pleiotropic functions of reactive oxygen species in cancer. Nat. Cancer 5, 384–399 (2024).

    CAS  PubMed  Google Scholar 

  87. Gorrini, C., Harris, I. S. & Mak, T. W. Modulation of oxidative stress as an anticancer strategy. Nat. Rev. Drug. Discov. 12, 931–947 (2013).

    CAS  PubMed  Google Scholar 

  88. Sayin, V. I. et al. Antioxidants accelerate lung cancer progression in mice. Sci. Transl. Med. 6, 221ra215 (2014).

    Google Scholar 

  89. Taguchi, K. & Yamamoto, M. The KEAP1–NRF2 system in cancer. Front. Oncol. 7, 85 (2017).

    PubMed  PubMed Central  Google Scholar 

  90. Humeau, J. et al. Inhibition of transcription by dactinomycin reveals a new characteristic of immunogenic cell stress. EMBO Mol. Med. 12, e11622 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Wallace, K. B., Sardao, V. A. & Oliveira, P. J. Mitochondrial determinants of doxorubicin-induced cardiomyopathy. Circ. Res. 126, 926–941 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Jiang, X., Stockwell, B. R. & Conrad, M. Ferroptosis: mechanisms, biology and role in disease. Nat. Rev. Mol. Cell Biol. 22, 266–282 (2021).

    PubMed  PubMed Central  Google Scholar 

  93. Weiss-Sadan, T. et al. NRF2 activation induces NADH-reductive stress, providing a metabolic vulnerability in lung cancer. Cell Metab. 35, 487–503.e7 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Jiang, L. et al. Ferroptosis as a p53-mediated activity during tumour suppression. Nature 520, 57–62 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Lacroix, M., Riscal, R., Arena, G., Linares, L. K. & Le Cam, L. Metabolic functions of the tumor suppressor p53: implications in normal physiology, metabolic disorders, and cancer. Mol. Metab. 33, 2–22 (2020).

    CAS  PubMed  Google Scholar 

  96. Veninga, V. & Voest, E. E. Tumor organoids: opportunities and challenges to guide precision medicine. Cancer Cell 39, 1190–1201 (2021).

    CAS  PubMed  Google Scholar 

  97. Chen, M. & Pandolfi, P. P. Preclinical and coclinical studies in prostate cancer. Cold Spring Harb. Perspect. Med. 8, a030544 (2018).

    PubMed  PubMed Central  Google Scholar 

  98. Lallemand-Breitenbach, V. et al. Retinoic acid and arsenic synergize to eradicate leukemic cells in a mouse model of acute promyelocytic leukemia. J. Exp. Med. 189, 1043–1052 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. de The, H., Pandolfi, P. P. & Chen, Z. Acute promyelocytic leukemia: a paradigm for oncoprotein-targeted cure. Cancer Cell 32, 552–560 (2017).

    PubMed  Google Scholar 

  100. Bercier, P. et al. Structural basis of PML–RARA oncoprotein targeting by arsenic unravels a cysteine rheostat controlling PML body assembly and function. Cancer Discov. 13, 2548–2565 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Rerolle, D. & de The, H. The PML hub: an emerging actor of leukemia therapies. J. Exp. Med. 220, e20221213 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  102. Zuber, J. et al. Mouse models of human AML accurately predict chemotherapy response. Genes. Dev. 23, 877–889 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Soverini, S. Resistance mutations in CML and how we approach them. Hematol. Am. Soc. Hematol. Educ. Program. 2023, 469–475 (2023).

    Google Scholar 

  104. Yang, F. et al. Chemotherapy and mismatch repair deficiency cooperate to fuel TP53 mutagenesis and ALL relapse. Nat. Cancer 2, 819–834 (2021).

    CAS  PubMed  Google Scholar 

  105. Falini, B., Brunetti, L. & Martelli, M. P. Dactinomycin in NPM1-mutated acute myeloid leukemia. N. Engl. J. Med. 373, 1180–1182 (2015).

    PubMed  Google Scholar 

  106. Gionfriddo, I. et al. Dactinomycin induces complete remission associated with nucleolar stress response in relapsed/refractory NPM1-mutated AML. Leukemia 35, 2552–2562 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  107. Wu, H. C. et al. Actinomycin D targets NPM1c-primed mitochondria to restore PML-driven senescence in AML therapy. Cancer Discov. 11, 3198–3213 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Dal Bello, R. et al. A multiparametric niche-like drug screening platform in acute myeloid leukemia. Blood Cancer J. 12, 95 (2022).

    PubMed  PubMed Central  Google Scholar 

  109. Pardieu, B. et al. Cystine uptake inhibition potentiates front-line therapies in acute myeloid leukemia. Leukemia 36, 1585–1595 (2022).

    CAS  PubMed  Google Scholar 

  110. Ballesta, A., Innominato, P. F., Dallmann, R., Rand, D. A. & Levi, F. A. Systems chronotherapeutics. Pharmacol. Rev. 69, 161–199 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  111. Fernandez, H. F. et al. Anthracycline dose intensification in acute myeloid leukemia. N. Engl. J. Med. 361, 1249–1259 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. Early Breast Cancer Trialists’ Collaborative Group. Increasing the dose intensity of chemotherapy by more frequent administration or sequential scheduling: a patient-level meta-analysis of 37 298 women with early breast cancer in 26 randomised trials. Lancet 393, 1440–1452 (2019).

    Google Scholar 

  113. Boissel, N. New developments in ALL in AYA. Hematol. Am. Soc. Hematol. Educ. Program. 2022, 190–196 (2022).

    Google Scholar 

  114. Arriagada, R. et al. Initial chemotherapeutic doses and survival in patients with limited small-cell lung cancer. N. Engl. J. Med. 329, 1848–1852 (1993).

    CAS  PubMed  Google Scholar 

  115. Arriagada, R., Pignon, J. P. & Le Chevalier, T. Initial chemotherapeutic doses and long-term survival in limited small-cell lung cancer. N. Engl. J. Med. 345, 1281–1282 (2001).

    CAS  PubMed  Google Scholar 

  116. Lyko, F. The DNA methyltransferase family: a versatile toolkit for epigenetic regulation. Nat. Rev. Genet. 19, 81–92 (2018).

    CAS  PubMed  Google Scholar 

  117. Roulois, D. et al. DNA-demethylating agents target colorectal cancer cells by inducing viral mimicry by endogenous transcripts. Cell 162, 961–973 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  118. Chiappinelli, K. B. et al. Inhibiting DNA methylation causes an interferon response in cancer via dsRNA including endogenous retroviruses. Cell 162, 974–986 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  119. Issa, J. P. DNA methylation as a therapeutic target in cancer. Clin. Cancer Res. 13, 1634–1637 (2007).

    CAS  PubMed  Google Scholar 

  120. Yabushita, T. et al. Mitotic perturbation is a key mechanism of action of decitabine in myeloid tumor treatment. Cell Rep. 42, 113098 (2023).

    CAS  PubMed  Google Scholar 

  121. DiNardo, C. D. & Konopleva, M. Y. A venetoclax bench-to-bedside story. Nat. Cancer 2, 3–5 (2021).

    PubMed  PubMed Central  Google Scholar 

  122. Wei, A. H. et al. Oral azacitidine maintenance therapy for acute myeloid leukemia in first remission. N. Engl. J. Med. 383, 2526–2537 (2020).

    CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

The authors contributed equally to all aspects of the article.

Corresponding authors

Correspondence to Anthony Letai or Hugues de The.

Ethics declarations

Competing interests

A.L. is on the scientific advisory board of Zentalis Pharmaceuticals and Flash Therapeutics.

Peer review

Peer review information

Nature Reviews Cancer thanks Adam Palmer who co-reviewed with Robert Allen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

SEER 12 database: https://seer.cancer.gov/statfacts/html/dlbcl.html

Glossary

Conventional chemotherapy

Cytotoxic cancer drugs generally targeting DNA or microtubules, whose use originated in the twentieth century.

Cyclophosphamide

A type of conventional chemotherapy classified as an alkylating agent, derived from the original nitrogen mustard drugs, whose mode of action is most commonly considered to be direct DNA alkylation.

Doxorubicin

A type of conventional chemotherapy classified as an anthracycline, derived from bacteria, whose mode of action is most commonly considered to be indirect inhibition of topoisomerase II following intercalation of DNA.

Etoposide

A type of conventional chemotherapy whose mode of action is most commonly considered to be inhibition of topisomerase II.

Platinum-based chemotherapies

A family of conventional chemotherapeutic drugs including cisplatin, carboplatin and oxaliplatin, whose mode of action is most commonly considered to be cross-linking of DNA strands.

Prednisone

A high-potency corticosteroid given orally to kill malignant lymphocytes.

Rituximab

A monoclonal antibody drug recognizing CD20 used in the treatment of B cell lymphomas.

Taxanes

A family of conventional chemotherapeutic drugs including paclitaxel, docetaxel and carbazitaxel, initially derived from the western yew tree, whose mode of action is most commonly considered to be inhibition of microtubule depolymerization.

Vincristine

A type of conventional chemotherapy classified as a vinca alkaloid, derived from the periwinkle plant family, whose mode of action is most commonly considered to be disruption of microtubules.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Letai, A., de The, H. Conventional chemotherapy: millions of cures, unresolved therapeutic index. Nat Rev Cancer 25, 209–218 (2025). https://doi.org/10.1038/s41568-024-00778-4

Download citation

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41568-024-00778-4

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing