Searching for Goldilocks: How Evolution and Ecology Can Help Uncover More Effective Patient-Specific Chemotherapies

Park, Derek S.; Luddy, Kimberly A.; Robertson-Tessi, Mark; O’Farrelly, Cliona; Gatenby, Robert A.; Anderson, Alexander R.A.

doi:10.1158/0008-5472.can-19-3981

Cited by 11 publications

(9 citation statements)

References 105 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Instead, decisions on what factor to vary have often been influenced by historical precedent, methodological constraints, or even personal biases. One approach that can assist in identifying the dominant factors influencing carcinogenesis involves mathematical models that have their origins in studies of interactions between species in an ecosystem [49][50][51][52]. Despite some obvious differences between animal and cellular societies, the results of these simulations have laid down priorities for cancer research.…”

Section: What Cancer Patients and Mathematical Models Tell Us About The Optimal Design Of Experiments Using Cell Linesmentioning

confidence: 99%

What do cellular responses to acidity tell us about cancer?

Błaszczak¹,

Swietach²

2021

Cancer Metastasis Rev

View full text Add to dashboard Cite

The notion that invasive cancer is a product of somatic evolution is a well-established theory that can be modelled mathematically and demonstrated empirically from therapeutic responses. Somatic evolution is by no means deterministic, and ample opportunities exist to steer its trajectory towards cancer cell extinction. One such strategy is to alter the chemical microenvironment shared between host and cancer cells in a way that no longer favours the latter. Ever since the first description of the Warburg effect, acidosis has been recognised as a key chemical signature of the tumour microenvironment. Recent findings have suggested that responses to acidosis, arising through a process of selection and adaptation, give cancer cells a competitive advantage over the host. A surge of research efforts has attempted to understand the basis of this advantage and seek ways of exploiting it therapeutically. Here, we review key findings and place these in the context of a mathematical framework. Looking ahead, we highlight areas relating to cellular adaptation, selection, and heterogeneity that merit more research efforts in order to close in on the goal of exploiting tumour acidity in future therapies.

show abstract

Section: What Cancer Patients and Mathematical Models Tell Us About The Optimal Design Of Experiments Using Cell Linesmentioning

confidence: 99%

What do cellular responses to acidity tell us about cancer?

Błaszczak¹,

Swietach²

2021

Cancer Metastasis Rev

View full text Add to dashboard Cite

show abstract

“…One example of such an area is adaptive and evolutionary chemotherapy. [42,43] Another example of a clinically validated, AIderived system is phenotypic personalized medicine (PPM), where prospectively generated, pre-designed, small, but high-quality datasets are used to personalize drug combinations and dose selection. [44][45][46][47][48][49][50] In one use case, CURATE.AI, an AI-derived platform from the PPM family, was used to prospectively optimize chemotherapy doses taken by a patient with advanced cancer (metastatic castration-resistant prostate cancer), which led to halting the disease progression at the doses lower than the maximum tolerated doses (MTD)-a standard of care in cancer treatment.…”

Section: Proposed Approachesmentioning

confidence: 99%

Overcoming Pilotitis in Digital Medicine at the Intersection of Data, Clinical Evidence, and Adoption

Egermark

Blasiak

Remus

et al. 2022

Advanced Intelligent Systems

View full text Add to dashboard Cite

The number of digital medicine technologies, a category of tools that use software and algorithmically driven products to measure or intervene to improve human health, [1] has expanded enormously in recent years, further accelerated by the need for remote care delivery during the COVID-19 pandemic, and now ranges from telemedicine to serious gaming, wearable devices, AI-supported diagnostics, and clinical decision support systems (CDSSs), among others. Building on the experiences during the pandemic, there is a real potential for the digital transformation of health care to the benefit of patients worldwide. However, the promising developments to date are at risk of stalling due to inherent limitations in the way digital medicine and especially medical artificial intelligence (AI) technologies are being developed and implemented today. [2] Already in 2017, the number of digital medicine technologies on the worldwide market exceeded 318 000, with the mobile application segment growing by over 200 daily. [3] There are widespread expectations that the surge will lead to improvement of health care globally, [4] not least evidenced by the WHO declaration on digital health, [5] and by the rapid growth of private and public investment in this field. [6,7] The advent of digital medicine bears special promise for low-and middleincome countries (LMIC), where applications such as telemedicine and CDSS may enable these countries to "leapfrog" from today's often insufficient healthcare systems into more efficient, accessible, and patient-centric models, [8] similar to what has been seen in Africa's finance sector. [9] The level of improvement possible would correspond to the digital transformation seen in other sectors of society, such as media and retail industries, with the digitalization of processes and service models, beyond the mere digitization of traditional healthcare practices seen so

show abstract

“…Indeed, intermittent therapy for prostate and breast cancer [ 46 ], melanoma [ 47 ], rectal cancer [ 48 ], and pediatric sarcomas [ 49 ] are currently being evaluated in the clinic with promising results. In some other cancers, e.g., non-small cell lung cancer, our preclinical data obtained using a Team Medicine approach also indicate that such strategies may prove successful as well [ 50 ].…”

Section: Intermittent or ‘Adaptive’ Therapy—an Eco-evolutionary Princ...mentioning

confidence: 99%

Addressing Drug Resistance in Cancer: A Team Medicine Approach

Kulkarni

Mohanty

Bhattacharya

et al. 2022

JCM

View full text Add to dashboard Cite

Drug resistance remains one of the major impediments to treating cancer. Although many patients respond well initially, resistance to therapy typically ensues. Several confounding factors appear to contribute to this challenge. Here, we first discuss some of the challenges associated with drug resistance. We then discuss how a ‘Team Medicine’ approach, involving an interdisciplinary team of basic scientists working together with clinicians, has uncovered new therapeutic strategies. These strategies, referred to as intermittent or ‘adaptive’ therapy, which are based on eco-evolutionary principles, have met with remarkable success in potentially precluding or delaying the emergence of drug resistance in several cancers. Incorporating such treatment strategies into clinical protocols could potentially enhance the precision of delivering personalized medicine to patients. Furthermore, reaching out to patients in the network of hospitals affiliated with leading academic centers could help them benefit from such innovative treatment options. Finally, lowering the dose of the drug and its frequency (because of intermittent rather than continuous therapy) can also have a significant impact on lowering the toxicity and undesirable side effects of the drugs while lowering the financial burden carried by the patient and insurance providers.

show abstract

Searching for Goldilocks: How Evolution and Ecology Can Help Uncover More Effective Patient-Specific Chemotherapies

Cited by 11 publications

References 105 publications

What do cellular responses to acidity tell us about cancer?

What do cellular responses to acidity tell us about cancer?

Overcoming Pilotitis in Digital Medicine at the Intersection of Data, Clinical Evidence, and Adoption

Addressing Drug Resistance in Cancer: A Team Medicine Approach

Contact Info

Product

Resources

About