One way a tumor might acquire resistance, however, is treatment. Insofar as any chemotherapy or immunotherapy destroys non-resistant cells but fails to destroy sensitive cells, selection will favor resistant cells, which renders future therapies of the same mechanism ineffective for as long as resistance is evolutionarily favored. This could explain why rotating different treatments that act upon the same pathway fail.

Dr van der Burg noted that “when a doctor gives immunotherapy, the immune system will once again fiercely attack the tumor…if this is not completely successful, new, more resistant clones may appear…they could already have been there (and now become more dominant), or they could develop under the immune system’s attack. Chemotherapy or targeted therapies may act similarly.”

Continue Reading

Therapy-induced resistance does not, of course, explain why some tumors are unresponsive to treatment in the first-line setting, though natural selection predicts that resistance will be perpetuated by further treatment. Biomarkers may help oncologists to assign therapies effectively for the first line, but acquired resistance should be seen as a distinct, treatment-induced phenomenon. The best recipes in cancer treatment must therefore be those that rely on distinct combinations that reduce the likelihood of a tumor’s acquiring resistance or suppressing immune activity before treatments like immunotherapies are introduced.

Evolutionary theory and likelihood of immunosuppression should be important factors not only for individualized treatment, but for trial design. A phase 3 trial testing a combination of drugs that act on the same pathway may be guaranteed to fail by logic before it does so in practice, not only making the study ineffective, but a waste of resources and participating patients’ time.

There are, however, far too many possible combinations of treatments and genetic variations to test for the optimal combinations of therapy timing in the clinical trial setting. Dr van der Burg noted that “If you want to test each combination for its effect in a randomized phase 3 trial, this is undoable. What we need to do is to understand the mechanisms of action of the compounds very well and also understand which of the blocks posed by the tumor are the most important/strongest. If so we can make an informed decision.”

Evolutionary theory may, however, function as a litmus test for studies unlikely to succeed: if researchers understand the selective pressures they are placing on tumors with treatments employed, the universe of practical studies is likely to shrink. While this process would still require sifting through a daunting set of variables, it may be possible to program tools like Watson to process tumor genomic data using a function, such as the Price equation, to determine the likelihood of a particular treatment inducing resistance in a particular tumor.

RELATED: Darwinian Oncology Comes of Age: Evolutionary Biologists Offer Competing Theories of Cancer

While there are many questions left to answer, it would be ideal if oncologists, drug developers, and evolutionary theorists collaborated to design treatments and treatment combinations that are the most likely to succeed given the laws of natural selection, though evolutionary reasoning is not often integrated into trial design.9 For the present the potential impact of evolutionary logic in oncology is largely speculative, though the empirical evidence noted above should be counted as evidence in favor of its integration.


  1. Magnuson WJ, Lester-Coll NH, et. al. Management of brain metastases in tyrosine kinase inhibitor-naïve epidermal growth factor receptor-mutant non-small-cell lung cancer: a retrospective multi-institutional analysis. J Clin Oncol. 2017 Jan 23. doi: 10.1200/JCO.2016.69.7144 [Epub ahead of print]
  2. Cirkel GA, Hamberg P, Sleijfer S, et al. Alternating treatment with pazopanib and everolimus vs continuous pazopanib to delay disease progression in patients with metastatic clear cell renal cell cancer: the ROPETAR randomized clinical trial. JAMA Oncol. 2016 Dec 1. doi: 10.1001/jamaoncol.2016.5202 [Epub ahead of print]
  3. Beyranvand Nejad E, Welters MJ, Arens R, van der Burg SH. The importance of correctly timing cancer immunotherapy. Expert Opin Biol Ther. 2017;17(1):87-103.
  4. Kenter GG, Welters MJ, Valentijn AR, et al. Vaccination against HPV-16 oncoproteins for vulvar intraepithelial neoplasia. N Engl J Med. 2009 Nov 5;361(19):1838-47. doi: 10.1056/NEJMoa0810097
  5. van Poelgeest MI, Welters MJ, van Esch EM, et al. HPV16 synthetic long peptide (HPV16-SLP) vaccination therapy of patients with advanced or recurrent HPV16-induced gynecological carcinoma, a phase II trial. J Transl Med. 2013;11:88. doi: 10.1186/1479-5876-11-88
  6. Bracci L, Moschella F, Sestili P, et al. Cyclophosphamide enhances the antitumor efficacy of adoptively transferred immune cells through the induction of cytokine expression, B-cell and T-cell homeostatic proliferation, and specific tumor infiltration. Clin Cancer Res. 2007;13(2 Pt 1):644-53.
  7. Welters MJ, van der Sluis TC, van Meir H, et al. Vaccination during myeloid cell depletion by cancer chemotherapy fosters robust T cell responses. Sci Transl Med. 2016;8(334):334ra52.
  8. Miwa S, Nishida H, Tanzawa Y, et al. Phase 1/2 study of immunotherapy with dendritic cells pulsed with autologous tumor lysate in patients with refractory bone and soft tissue sarcoma. Cancer. 2017 Feb 27. doi: 10.1002/cncr.30606 [Epub ahead of print]
  9. Aktipis CA, Kwan VS, Johnson KA, Neuberg SL, Maley CC. Overlooking evolution: a systematic analysis of cancer relapse and therapeutic resistance research. PLoS One. 2011;6(11):e26100. doi: 10.1371/journal.pone.0026100