Evolutionary therapy

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Evolutionary therapy is a subfield of evolutionary medicine that utilizes concepts from evolutionary biology in management of diseases caused by evolving entities such as cancer and microbial infections. [1] These evolving disease agents adapt to selective pressure introduced by treatment, allowing them to develop resistance to therapy, making it ineffective. [2]

Contents

Evolutionary therapy relies on the notion that Darwinian evolution is the main reason behind lethality of late stage cancer and multi-drug resistant bacterial infections such as methicillin-resistant Staphylococcus aureus. [3] Thus, evolutionary therapy suggests that treatment of such highly dynamic evolving diseases should be changing over time to account for changes in disease populations. [4] Adaptive treatment strategies typically cycle between different drugs or drug doses to take advantage of predictable patterns of disease evolution. This is in contrast to standardized treatment approach which is applied to all patients and equally based on their cancer type and grade. There are still numerous obstacles to the use of evolutionary therapy in clinical practice. These obstacles include high contingency of trajectory, speed of evolution, and inability to track the population state of disease over time.

Context

Resistance to chemotherapy and molecularly targeted therapies is a major problem facing current cancer research. [5] All malignant cancers are fundamentally governed by Darwinian dynamics of the somatic evolution in cancer. Malignant cancers are dynamically evolving clades of cells living in distinct microhabitats that almost certainly ensure the emergence of therapy-resistant populations. Cytotoxic cancer therapies also impose intense evolutionary selection pressures on the surviving cells and thus increase the evolutionary rate. Importantly, the principles of Darwinian dynamics also embody fundamental principles that can illuminate strategies for the successful management of cancer. [6] [7] Eradicating the large, diverse and adaptive populations found in most cancers presents a formidable challenge. One centimetre cubed of cancer contains about 10^9 transformed cells and weighs about 1 gram, which means there are more cancer cells in 10 grams of tumour than there are people on Earth. Unequal cell division and differences in genetic lineages and microenvironmental selection pressures mean that the cells within a tumour are diverse both in genetic make-up and observable characteristics.

Mechanisms

Collateral sensitivity

Resistance to one drug can lead to unwanted cross-resistance to some other drugs [8] and "collateral" sensitivity to yet other drugs [9] [10] [11] Alternative methods include incorporating analyatically tractable stochastic control algorithms to direct the evolution to specific states of resistance that encode sensitivity to other drugs, [12] or machine learning based approaches like reinforcement learning. [13]

Treatment strategies

Adaptive therapy

The standard approach to treating cancer is giving patients the maximum tolerated amount of chemotherapy with the goal of doing the maximum possible damage to the tumor without killing the patient. This method is relatively effective, but it also causes major toxicities. [14] Adaptive therapy is an evolutionary therapy that aims to maintain or reduce tumor volume by employing minimum effective drug doses or timed drug holidays. [15] [16] The timing and duration of these holidays, which relies on the ability to modulate resistant vs. sensitive populations of cancer cells through competition, is a subject which has been studied using optimal control [17] in theoretical studies based on Evolutionary game theory based models. The ability to modulate these populations secondary relies on the assumption that there is a both frequency-dependent selection, and an associated fitness cost to that resistance.

Proof of principle for adaptive therapy has also been established in a recent phase 2 clinical trial [18] [19] as well as in vivo. [14]

Double bind

In the evolutionary double bind, one drug causes increased susceptibility of the evolving cancer to another drug. Some have found that effectiveness might be based on interactions of populations through commensalism. [20] Others imply that population control may be possible if resistance to therapy requires a substantial and costly phenotypic adaptation that reduces the organism's fitness. [21]

Extinction therapy

Extinction therapy is inspired by mass extinction events from the Anthropocene era. [22] This treatment strategy is also sometimes referred to as first strike-second strike, where the first strike reduces the size and heterogeneity of a population so that the second strike that follows can kill the surviving, often fragmented population below a threshold by stochastic perturbations. [23]

Current state

Although there is extensive modeling work on evolutionary therapy, [24] there are only a few completed and ongoing clinical trials that use evolutionary therapy. First one conducted in Moffitt Cancer Center on patients with metastatic castrate-resistant prostate cancer showed outcomes that "show significant improvement over published studies and a contemporaneous population." [25] This study met with some criticism. [26]

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<span class="mw-page-title-main">Prostate cancer</span> Male reproductive organ cancer

Prostate cancer is the uncontrolled growth of cells in the prostate, a gland in the male reproductive system below the bladder. Abnormal growth of prostate tissue is usually detected through screening tests, typically blood tests that check for prostate-specific antigen (PSA) levels. Those with high levels of PSA in their blood are at increased risk for developing prostate cancer. Diagnosis requires a biopsy of the prostate. If cancer is present, the pathologist assigns a Gleason score, and a higher score represents a more dangerous tumor. Medical imaging is performed to look for cancer that has spread outside the prostate. Based on the Gleason score, PSA levels, and imaging results, a cancer case is assigned a stage 1 to 4. A higher stage signifies a more advanced, more dangerous disease.

Combination therapy or polytherapy is therapy that uses more than one medication or modality. Typically, the term refers to using multiple therapies to treat a single disease, and often all the therapies are pharmaceutical. 'Pharmaceutical' combination therapy may be achieved by prescribing/administering separate drugs, or, where available, dosage forms that contain more than one active ingredient.

<span class="mw-page-title-main">CYP17A1</span> Mammalian protein found in Homo sapiens

Cytochrome P450 17A1 is an enzyme of the hydroxylase type that in humans is encoded by the CYP17A1 gene on chromosome 10. It is ubiquitously expressed in many tissues and cell types, including the zona reticularis and zona fasciculata of the adrenal cortex as well as gonadal tissues. It has both 17α-hydroxylase and 17,20-lyase activities, and is a key enzyme in the steroidogenic pathway that produces progestins, mineralocorticoids, glucocorticoids, androgens, and estrogens. More specifically, the enzyme acts upon pregnenolone and progesterone to add a hydroxyl (-OH) group at carbon 17 position (C17) of the steroid D ring, or acts upon 17α-hydroxyprogesterone and 17α-hydroxypregnenolone to split the side-chain off the steroid nucleus.

<span class="mw-page-title-main">Abiraterone acetate</span> Chemical compound

Abiraterone acetate, sold under the brand name Zytiga among others, is a medication used to treat prostate cancer. Specifically it is used together with a corticosteroid for metastatic castration-resistant prostate cancer (mCRPC) and metastatic high-risk castration-sensitive prostate cancer (mCSPC). It should either be used following removal of the testicles or along with a gonadotropin-releasing hormone (GnRH) analog. It is taken by mouth.

<span class="mw-page-title-main">Clonal interference</span> Phenomenon in evolutionary biology

Clonal interference is a phenomenon in evolutionary biology, related to the population genetics of organisms with significant linkage disequilibrium, especially asexually reproducing organisms. The idea of clonal interference was introduced by American geneticist Hermann Joseph Muller in 1932. It explains why beneficial mutations can take a long time to get fixated or even disappear in asexually reproducing populations. As the name suggests, clonal interference occurs in an asexual lineage ("clone") with a beneficial mutation. This mutation would be likely to get fixed if it occurred alone, but it may fail to be fixed, or even be lost, if another beneficial-mutation lineage arises in the same population; the multiple clones interfere with each other.

<span class="mw-page-title-main">Enzalutamide</span> Antiandrogen medication used in treatment of prostate cancer

Enzalutamide, sold under the brand name Xtandi, is a nonsteroidal antiandrogen (NSAA) medication which is used in the treatment of prostate cancer. It is indicated for use in conjunction with castration in the treatment of metastatic castration-resistant prostate cancer (mCRPC), nonmetastatic castration-resistant prostate cancer, and metastatic castration-sensitive prostate cancer (mCSPC). It is taken by mouth.

Somatic evolution is the accumulation of mutations and epimutations in somatic cells during a lifetime, and the effects of those mutations and epimutations on the fitness of those cells. This evolutionary process has first been shown by the studies of Bert Vogelstein in colon cancer. Somatic evolution is important in the process of aging as well as the development of some diseases, including cancer.

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<span class="mw-page-title-main">Galeterone</span> Chemical compound

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<span class="mw-page-title-main">Tasquinimod</span> Chemical compound

Tasquinimod is an experimental drug currently being investigated for the treatment of solid tumors. Tasquinimod has been mostly studied in prostate cancer, but its mechanism of action suggests that it could be used to treat other cancers. Castration-resistant prostate cancer (CRPC), formerly called hormone-resistant or hormone-refractory prostate cancer, is prostate cancer that grows despite medical or surgical androgen deprivation therapy. Tasquinimod targets the tumor microenvironment and counteracts cancer development by inhibiting angiogenesis and metastasis and by modulating the immune system. It is now in phase III development, following successful phase II trial outcomes.

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PROSTVAC is a cancer immunotherapy candidate in clinical development by Bavarian Nordic for the treatment of all prostate cancer although clinical trials are focusing on more advanced cases of metastatic castration-resistant prostate cancer (mCRPC). PROSTVAC is a vaccine designed to enable the immune system to recognize and attack prostate cancer cells by triggering a specific and targeted T cell immune response to cancer cells that express the tumor-associated antigen prostate-specific antigen (PSA).

<span class="mw-page-title-main">Seviteronel</span> Chemical compound

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Darolutamide, sold under the brand name Nubeqa, is an antiandrogen medication which is used in the treatment of non-metastatic castration-resistant prostate cancer in men. It is specifically approved to treat non-metastatic castration-resistant prostate cancer (nmCRPC) in conjunction with surgical or medical castration. The medication is taken by mouth twice per day with food.

<span class="mw-page-title-main">Apalutamide</span> Chemical compound

Apalutamide, sold under the brand name Erleada among others, is a nonsteroidal antiandrogen (NSAA) medication which is used in the treatment of prostate cancer. It is specifically indicated for use in conjunction with castration in the treatment of non-metastatic castration-resistant prostate cancer (NM-CRPC). It is taken by mouth.

<span class="mw-page-title-main">Ralaniten acetate</span> Chemical compound

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<i>N</i>-Desmethylenzalutamide Chemical compound

N-Desmethylenzalutamide is a nonsteroidal antiandrogen (NSAA) and the major metabolite of enzalutamide, an NSAA which is used as a hormonal antineoplastic agent in the treatment of metastatic prostate cancer. It has similar activity to that of enzalutamide and, with enzalutamide therapy, circulates at similar concentrations to those of enzalutamide at steady state. N-Desmethylenzalutamide is formed from enzalutamide in the liver by the cytochrome P450 enzymes CYP2C8 and CYP3A4. It has a longer terminal half-life than enzalutamide.

<span class="mw-page-title-main">Custirsen</span> Chemical compound

Custirsen, with aliases including custirsen sodium, OGX-011, and CC-8490, is an investigational drug that is under clinical testing for the treatment of cancer. It is an antisense oligonucleotide (ASO) targeting clusterin expression. In metastatic prostate cancer, custirsen showed no benefit in improving overall survival.

References

  1. ↑ "Evolutionary Therapy". Moffitt Cancer Center. Open Publishing. Retrieved 2022-02-25.
  2. ↑ Greaves M, Maley CC (January 2012). "Clonal evolution in cancer". Nature. 481 (7381): 306–313. Bibcode:2012Natur.481..306G. doi:10.1038/nature10762. PMC   3367003 . PMID   22258609.
  3. ↑ Davies J, Davies D (September 2010). "Origins and evolution of antibiotic resistance". Microbiology and Molecular Biology Reviews. 74 (3): 417–433. doi:10.1128/MMBR.00016-10. PMC   2937522 . PMID   20805405.
  4. ↑ Gatenby RA, Brown JS (November 2020). "Integrating evolutionary dynamics into cancer therapy". Nature Reviews. Clinical Oncology. 17 (11): 675–686. doi:10.1038/s41571-020-0411-1. PMID   32699310. S2CID   220681064.
  5. ↑ Holohan C, Van Schaeybroeck S, Longley DB, Johnston PG (October 2013). "Cancer drug resistance: an evolving paradigm". Nature Reviews. Cancer. 13 (10): 714–726. doi:10.1038/nrc3599. PMID   24060863. S2CID   24719097.
  6. ↑ Gillies RJ, Verduzco D, Gatenby RA (June 2012). "Evolutionary dynamics of carcinogenesis and why targeted therapy does not work". Nature Reviews. Cancer. 12 (7): 487–493. doi:10.1038/nrc3298. PMC   4122506 . PMID   22695393.
  7. ↑ Gatenby RA (May 2009). "A change of strategy in the war on cancer". Nature. 459 (7246): 508–509. Bibcode:2009Natur.459..508G. doi: 10.1038/459508a . PMID   19478766. S2CID   205046753.
  8. ↑ "CROSS resistance to antibiotics". Journal of the American Medical Association. 148 (6): 470–471. February 1952. doi:10.1001/jama.1952.02930060052015. PMID   14888510.
  9. ↑ Santos-Lopez, Alfonso; Marshall, Christopher W; Haas, Allison L; Turner, Caroline; Rasero, Javier; Cooper, Vaughn S (25 August 2021). "The roles of history, chance, and natural selection in the evolution of antibiotic resistance". eLife. 10: e70676. doi: 10.7554/eLife.70676 . PMC   8412936 . PMID   34431477.
  10. ↑ Maltas J, Wood KB (October 2019). "Pervasive and diverse collateral sensitivity profiles inform optimal strategies to limit antibiotic resistance". PLOS Biology. 17 (10): e3000515. doi: 10.1371/journal.pbio.3000515 . PMC   6834293 . PMID   31652256.
  11. ↑ Acar A, Nichol D, Fernandez-Mateos J, Cresswell GD, Barozzi I, Hong SP, et al. (April 2020). "Exploiting evolutionary steering to induce collateral drug sensitivity in cancer". Nature Communications. 11 (1): 1923. Bibcode:2020NatCo..11.1923A. doi:10.1038/s41467-020-15596-z. PMC   7174377 . PMID   32317663.
  12. ↑ Iram, S. (2021). "Controlling the speed and trajectory of evolution with counterdiabatic driving". Nature Physics. 17: 135–142. arXiv: 1912.03764 . doi:10.1038/s41567-020-0989-3.
  13. ↑ Weaver, D. (2024). "Reinforcement Learning informs optimal treatment strategies to limit antibiotic resistance". Proceedings of the National Academy of Sciences. 121.16: e2303165121. doi:10.1073/pnas.2303165121. PMC   11032439 .
  14. 1 2 Enriquez-Navas PM, Kam Y, Das T, Hassan S, Silva A, Foroutan P, et al. (February 2016). "Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer". Science Translational Medicine. 8 (327). 327ra24. doi:10.1126/scitranslmed.aad7842. PMC   4962860 . PMID   26912903.
  15. ↑ Kim E, Brown JS, Eroglu Z, Anderson AR (February 2021). "Adaptive Therapy for Metastatic Melanoma: Predictions from Patient Calibrated Mathematical Models". Cancers. 13 (4): 823. doi: 10.3390/cancers13040823 . PMC   7920057 . PMID   33669315.
  16. ↑ Gatenby RA, Silva AS, Gillies RJ, Frieden BR (June 2009). "Adaptive therapy". Cancer Research. 69 (11): 4894–4903. doi:10.1158/0008-5472.CAN-08-3658. PMC   3728826 . PMID   19487300.
  17. ↑ Cunningham J, Brown J, Gatenby R, Stankova K (December 2018). "Optimal control to develop therapeutic strategies for metastatic castrate resistant prostate cancer". JAMA Oncology. 459: 67–78. Bibcode:2018JThBi.459...67C. doi:10.1016/j.jtbi.2018.09.022. PMID   30243754. S2CID   52340340.
  18. ↑ Zhang J, Cunningham JJ, Brown JS, Gatenby RA (November 2017). "Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer". Nature Communications. 8 (1): 1816. Bibcode:2017NatCo...8.1816Z. doi:10.1038/s41467-017-01968-5. PMC   5703947 . PMID   29180633.
  19. ↑ Zhang J, Cunningham JJ, Brown JS, Gatenby RA (June 2022). "Evolution-based mathematical models significantly prolong response to abiraterone in metastatic castrate-resistant prostate cancer and identify strategies to further improve outcomes". eLife. 11. doi: 10.7554/eLife.76284 . PMC   9239688 . PMID   35762577.
  20. ↑ Basanta D, Gatenby RA, Anderson AR (April 2012). "Exploiting evolution to treat drug resistance: combination therapy and the double bind". Mol Pharm. 9 (4): 914–921. doi:10.1021/mp200458e. PMC   3325107 . PMID   22369188.
  21. ↑ Gatenby R, Brown J, Vincent T (September 2014). "Lessons from applied ecology: cancer control using an evolutionary double bind". Cancer Research. 69 (19): 7499–7502. doi:10.1158/0008-5472.CAN-09-1354. PMID   19752088.
  22. ↑ Gatenby RA, Artzy-Randrup Y, Epstein T, Reed DR, Brown JS (February 2021). "Eradicating Metastatic Cancer and the Eco-Evolutionary Dynamics of Anthropocene Extinctions". Cancer Research. 80 (3): 613–623. doi:10.1158/0008-5472.CAN-19-1941. PMC   7771333 . PMID   31772037.
  23. ↑ Gatenby RA, Zhang J, Brown JS (July 2019). "First Strike–Second Strike Strategies in Metastatic Cancer: Lessons from the Evolutionary Dynamics of Extinction". Cancer Research. 79 (13): 3174–3177. doi:10.1158/0008-5472.CAN-19-0807. PMC   6606376 . PMID   31221821.
  24. ↑ Wölfl B, Te Rietmole H, Salvioli M, Kaznatcheev A, Thuijsman F, Brown JS, et al. (2021). "The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer". Dynamic Games and Applications. 12 (2): 313–342. doi:10.1007/s13235-021-00397-w. PMC   9117378 . PMID   35601872. S2CID   239673089.
  25. ↑ Zhang J, Cunningham JJ, Brown JS, Gatenby RA (November 2017). "Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer". Nature Communications. 8 (1): 1816. Bibcode:2017NatCo...8.1816Z. doi:10.1038/s41467-017-01968-5. PMC   5703947 . PMID   29180633.
  26. ↑ Mistry HB (January 2021). "On the reporting and analysis of a cancer evolutionary adaptive dosing trial". Nature Communications. 12 (1): 316. Bibcode:2021NatCo..12..316M. doi:10.1038/s41467-020-20174-4. PMC   7804309 . PMID   33436546.
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