A unifying theory of carcinogenesis, and why targeted therapy doesn't work

Deep reinforcement learning identifies personalized intermittent androgen deprivation therapy for prostate cancer

The evolution of drug resistance leads to treatment failure and tumor progression. Intermittent androgen deprivation therapy (IADT) helps responsive cancer cells compete with resistant cancer cells in intratumoral competition. However, conventional IADT is population-based, ignoring the heterogeneity of patients and cancer. Additionally, existing IADT relies on pre-determined thresholds of prostate-specific antigen to pause and resume treatment, which is not optimized for individual patients. To address these challenges, we framed a data-driven method in two steps. First, we developed a time-varied, mixed-effect and generative Lotka-Volterra (tM-GLV) model to account for the heterogeneity of the evolution mechanism and the pharmacokinetics of two ADT drugs Cyproterone acetate and Leuprolide acetate for individual patients. Then, we proposed a reinforcement-learning-enabled individualized IADT framework, namely, I$^{2}$ADT, to learn the patient-specific tumor dynamics and derive the optimal drug administration policy. Experiments with clinical trial data demonstrated that the proposed I$^{2}$ADT can significantly prolong the time to progression of prostate cancer patients with reduced cumulative drug dosage. We further validated the efficacy of the proposed methods with a recent pilot clinical trial data. Moreover, the adaptability of I$^{2}$ADT makes it a promising tool for other cancers with the availability of clinical data, where treatment regimens might need to be individualized based on patient characteristics and disease dynamics. Our research elucidates the application of deep reinforcement learning to identify personalized adaptive cancer therapy.

Collapse of Intra-Tumor Cooperation Induced by Engineered Defector Cells

Anti-cancer therapies promote clonal selection of resistant cells that evade treatment. Effective therapy must be stable against the evolution of resistance. A potential strategy based on concepts from evolutionary game theory is to impair intra-tumor cooperation using genetically modified cells in which genes coding for essential growth factors have been knocked out. Such engineered cells would spread by clonal selection, driving the collapse of intra-tumor cooperation and a consequent reduction in tumor growth. Here, I test this idea in vitro in four cancer types (neuroendocrine pancreatic cancer, mesothelioma, lung adenocarcinoma and multiple myeloma). A reduction, or even complete eradication, of the producer clone and the consequent reduction in cell proliferation, is achieved in some but not all cases by introducing a small fraction of non-producer cells in the population. I show that the collapse of intra-tumor cooperation depends on the cost/benefit ratio of growth factor production. When stable cooperation among producer and non-producer cells occurs, its collapse can be induced by increasing the number of growth factors available to the cells. Considerations on nonlinear dynamics in the framework of evolutionary game theory explain this as the result of perturbation of the equilibrium of a system that resembles a public goods game, in which the production of growth factors is a cooperative phenotype. Inducing collapse of intra-tumor cooperation by engineering cancer cells will require the identification of growth factors that are essential for the tumor and that have a high cost of production for the cell.

Cancer as a form of life: Musings of the cancer and evolution symposium

Advanced cancer is one of the major problems in oncology as currently, despite the recent technological and scientific advancements, the mortality of metastatic disease remains very high at 70-90%. The field of oncology is in urgent need of novel ideas in order to improve quality of life and prognostic of cancer patients. The Cancer and Evolution Symposium organized online October 14-16, 2020 brought together a group of specialists from different fields that presented innovative strategies for better understanding, preventing, diagnosing, and treating cancer. Today still, the main reasons behind the high incidence and mortality of advanced cancer are, on one hand, the paucity of funding and effort directed to cancer prevention and early detection, and, on the other hand, the lack of understanding of the cancer process itself. I argue that besides being a disease, cancer is also a form of life, and, this frame of reference may provide a fresh look on this complex process. Here, I provide a different angle to several contemporary cancer theories discussing them from the perspective of "cancer-forms of life" (i.e. bionts) point of view. The perspectives and the several "bionts" introduced here, by no means exclusive or comprehensive, are just a shorthand that will hopefully encourage the readers, to further explore the contemporary oncology theoretical landscape.

Intratumor heterogeneity index of breast carcinomas based on DNA methylation profiles

Background

Cancer cells evolve and constitute heterogeneous populations that fluctuate in space and time and are subjected to selection generating intratumor heterogeneity. This phenomenon is determined by the acquisition of genetic/epigenetic alterations and their selection over time which has clinical implications on drug resistance.

Methods

DNA extracted from different tumor cell populations (breast carcinomas, cancer cell lines and cellular clones) were analyzed by MS-MLPA. Methylation profiles were used to generate a heterogeneity index to quantify the magnitude of epigenetic heterogeneity in these populations. Cellular clones were obtained from single cells derived of MDA-MB 231 cancer cell lines applying serial limiting dilution method and morphology was analyzed by optical microscopy and flow cytometry. Clones characteristics were examined through cellular proliferation, migration capacity and apoptosis. Heterogeneity index was also calculated from beta values derived from methylation profiles of TCGA tumors.

Results

The study of methylation profiles of 23 fresh breast carcinomas revealed heterogeneous allele populations in these tumor pieces. With the purpose to measure the magnitude of epigenetic heterogeneity, we developed an heterogeneity index based on methylation information and observed that all tumors present their own heterogeneity level. Applying the index calculation in pure cancer cell populations such as cancer cell lines (MDA-MB 231, MCF-7, T47D, HeLa and K-562), we also observed epigenetic heterogeneity. In addition, we detected that clones obtained from the MDA-MB 231 cancer cell line generated their own new heterogeneity over time. Using TCGA tumors, we determined that the heterogeneity index correlated with prognostic and predictive factors like tumor size (p = 0.0088), number of affected axillary nodes (p = 0.007), estrogen receptor expression (p < 0.0001) and HER2 positivity (p = 0.0007). When we analyzed molecular subtypes we found that they presented different heterogeneity levels. Interestingly, we also observed that all mentioned tumor cell populations shared a similar Heterogeneity index (HI) mean.

Conclusions

Our results show that each tumor presents a unique epigenetic heterogeneity level, which is associated with prognostic and predictive factors. We also observe that breast tumor subtypes differ in terms of epigenetic heterogeneity, which could serve as a new contribution to understand the different prognosis of these groups.

Combined PET/MRI: Global Warming-Summary Report of the 6th International Workshop on PET/MRI, March 27-29, 2017, Tübingen, Germany

The 6th annual meeting to address key issues in positron emission tomography (PET)/magnetic resonance imaging (MRI) was held again in Tübingen, Germany, from March 27 to 29, 2017. Over three days of invited plenary lectures, round table discussions and dialogue board deliberations, participants critically assessed the current state of PET/MRI, both clinically and as a research tool, and attempted to chart future directions. The meeting addressed the use of PET/MRI and workflows in oncology, neurosciences, infection, inflammation and chronic pain syndromes, as well as deeper discussions about how best to characterise the tumour microenvironment, optimise the complementary information available from PET and MRI, and how advanced data mining and bioinformatics, as well as information from liquid biomarkers (circulating tumour cells and nucleic acids) and pathology, can be integrated to give a more complete characterisation of disease phenotype. Some issues that have dominated previous meetings, such as the accuracy of MR-based attenuation correction (AC) of the PET scan, were finally put to rest as having been adequately addressed for the majority of clinical situations. Likewise, the ability to standardise PET systems for use in multicentre trials was confirmed, thus removing a perceived barrier to larger clinical imaging trials. The meeting openly questioned whether PET/MRI should, in all cases, be used as a whole-body imaging modality or whether in many circumstances it would best be employed to give an in-depth study of previously identified disease in a single organ or region. The meeting concluded that there is still much work to be done in the integration of data from different fields and in developing a common language for all stakeholders involved. In addition, the participants advocated joint training and education for individuals who engage in routine PET/MRI. It was agreed that PET/MRI can enhance our understanding of normal and disrupted biology, and we are in a position to describe the in vivo nature of disease processes, metabolism, evolution of cancer and the monitoring of response to pharmacological interventions and therapies. As such, PET/MRI is a key to advancing medicine and patient care.

Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer

Abiraterone treats metastatic castrate-resistant prostate cancer by inhibiting CYP17A, an enzyme for testosterone auto-production. With standard dosing, evolution of resistance with treatment failure (radiographic progression) occurs at a median of ~16.5 months. We hypothesize time to progression (TTP) could be increased by integrating evolutionary dynamics into therapy. We developed an evolutionary game theory model using Lotka–Volterra equations with three competing cancer “species”: androgen dependent, androgen producing, and androgen independent. Simulations with standard abiraterone dosing demonstrate strong selection for androgen-independent cells and rapid treatment failure. Adaptive therapy, using patient-specific tumor dynamics to inform on/off treatment cycles, suppresses proliferation of androgen-independent cells and lowers cumulative drug dose. In a pilot clinical trial, 10 of 11 patients maintained stable oscillations of tumor burdens; median TTP is at least 27 months with reduced cumulative drug use of 47% of standard dosing. The outcomes show significant improvement over published studies and a contemporaneous population.

Evolution of resistance is a common cause of cancer treatment failure and tumor progression. Here, the authors present a method for integrating evolutionary principles based on adaptive therapy into abiraterone therapy for metastatic castrate-resistant prostate cancer and show the positive results of an interim analysis of a trial cohort.

Metabolic Profiling of healthy and cancerous tissues in 2D and 3D

Metabolism is a compartmentalized process, and it is apparent in studying cancer that tumors, like normal tissues, demonstrate metabolic cooperation between different cell types. Metabolic profiling of cells in 2D culture systems often fails to reflect the metabolism occurring within tissues in vivo due to lack of other cell types and 3D interaction. We designed a tooling and methodology to metabolically profile and compare 2D cultures with cancer cell spheroids, and microtissue slices from tumors, and normal organs. We observed differences in the basal metabolism of 2D and 3D cell cultures in response to metabolic inhibitors, and chemotherapeutics. The metabolic profiles of microtissues derived from normal organs (heart, kidney) were relatively consistent when comparing microtissues derived from the same organ. Treatment of heart and kidney microtissues with cardio- or nephro-toxins had early and marked effects on tissue metabolism. In contrast, microtissues derived from different regions of the same tumors exhibited significant metabolic heterogeneity, which correlated to histology. Hence, metabolic profiling of complex microtissues is necessary to understand the effects of metabolic co-operation and how this interaction, not only can be targeted for treatment, but this method can be used as a reproducible, early and sensitive measure of drug toxicity.

Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer

Conventional cancer treatment strategies assume that maximum patient benefit is achieved through maximum killing of tumor cells. However, by eliminating the therapy-sensitive population, this strategy accelerates emergence of resistant clones that proliferate unopposed by competitors-an evolutionary phenomenon termed "competitive release." We present an evolution-guided treatment strategy designed to maintain a stable population of chemosensitive cells that limit proliferation of resistant clones by exploiting the fitness cost of the resistant phenotype. We treated MDA-MB-231/luc triple-negative and MCF7 estrogen receptor-positive (ER(+)) breast cancers growing orthotopically in a mouse mammary fat pad with paclitaxel, using algorithms linked to tumor response monitored by magnetic resonance imaging. We found that initial control required more intensive therapy with regular application of drug to deflect the exponential tumor growth curve onto a plateau. Dose-skipping algorithms during this phase were less successful than variable dosing algorithms. However, once initial tumor control was achieved, it was maintained with progressively smaller drug doses. In 60 to 80% of animals, continued decline in tumor size permitted intervals as long as several weeks in which no treatment was necessary. Magnetic resonance images and histological analysis of tumors controlled by adaptive therapy demonstrated increased vascular density and less necrosis, suggesting that vascular normalization resulting from enforced stabilization of tumor volume may contribute to ongoing tumor control with lower drug doses. Our study demonstrates that an evolution-based therapeutic strategy using an available chemotherapeutic drug and conventional clinical imaging can prolong the progression-free survival in different preclinical models of breast cancer.

Extracellular pH Modulates Neuroendocrine Prostate Cancer Cell Metabolism and Susceptibility to the Mitochondrial Inhibitor Niclosamide

Neuroendocrine prostate cancer is a lethal variant of prostate cancer that is associated with castrate-resistant growth, metastasis, and mortality. The tumor environment of neuroendocrine prostate cancer is heterogeneous and characterized by hypoxia, necrosis, and numerous mitoses. Although acidic extracellular pH has been implicated in aggressive cancer features including metastasis and therapeutic resistance, its role in neuroendocrine prostate cancer physiology and metabolism has not yet been explored. We used the well-characterized PNEC cell line as a model to establish the effects of extracellular pH (pH 6.5, 7.4, and 8.5) on neuroendocrine prostate cancer cell metabolism. We discovered that alkalinization of extracellular pH converted cellular metabolism to a nutrient consumption-dependent state that was susceptible to glucose deprivation, glutamine deprivation, and 2-deoxyglucose (2-DG) mediated inhibition of glycolysis. Conversely, acidic pH shifted cellular metabolism toward an oxidative phosphorylation (OXPHOS)-dependent state that was susceptible to OXPHOS inhibition. Based upon this mechanistic knowledge of pH-dependent metabolism, we identified that the FDA-approved anti-helminthic niclosamide depolarized mitochondrial potential and depleted ATP levels in PNEC cells whose effects were enhanced in acidic pH. To further establish relevance of these findings, we tested the effects of extracellular pH on susceptibility to nutrient deprivation and OXPHOS inhibition in a cohort of castrate-resistant prostate cancer cell lines C4-2B, PC-3, and PC-3M. We discovered similar pH-dependent toxicity profiles among all cell lines with these treatments. These findings underscore a potential importance to acidic extracellular pH in the modulation of cell metabolism in tumors and development of an emerging paradigm that exploits the synergy of environment and therapeutic efficacy in cancer.

Clinical management of breast cancer heterogeneity

Traditionally, intertumour heterogeneity in breast cancer has been documented in terms of different histological subtypes, treatment sensitivity profiles, and clinical outcomes among different patients. Results of high-throughput molecular profiling studies have subsequently revealed the true extent of this heterogeneity. Further complicating this scenario, the heterogeneous expression of the oestrogen receptor (ER), progesterone receptor (PR), and HER2 has been reported in different areas of the same tumour. Furthermore, discordance, in terms of ER, PR and HER2 expression, has also been reported between primary tumours and their matched metastatic lesions. High-throughput molecular profiling studies have confirmed that spatial and temporal intratumour heterogeneity of breast cancers exist at a level beyond common expectations. We describe the different levels of tumour heterogeneity, and discuss the strategies that can be adopted by clinicians to tackle treatment response and resistance issues associated with such heterogeneity, including a rationally selected combination of agents that target driver mutations, the targeting of deleterious passenger mutations, identifying and eradicating the 'lethal' clone, targeting the tumour microenvironment, or using adaptive treatments and immunotherapy. The identification of the most-appropriate strategies and their implementation in the clinic will prove highly challenging and necessitate the adoption of radically new practices for the optimal clinical management of breast malignancies.

Dynamics of preventive vs post-diagnostic cancer control using low-impact measures

Cancer poses danger because of its unregulated growth, development of resistance, and metastatic spread to vital organs. We currently lack quantitative theory for how preventive measures and post-diagnostic interventions are predicted to affect risks of a life threatening cancer. Here we evaluate how continuous measures, such as life style changes and traditional treatments, affect both neoplastic growth and the frequency of resistant clones. We then compare and contrast preventive and post-diagnostic interventions assuming that only a single lesion progresses to invasive carcinoma during the life of an individual, and resection either leaves residual cells or metastases are undetected. Whereas prevention generally results in more positive therapeutic outcomes than post-diagnostic interventions, this advantage is substantially lowered should prevention initially fail to arrest tumour growth. We discuss these results and other important mitigating factors that should be taken into consideration in a comparative understanding of preventive and post-diagnostic interventions.

DOI:http://dx.doi.org/10.7554/eLife.06266.001

About one person in every two will get cancer during their lives. Surgery and chemotherapy have long been mainstays of cancer treatment. Both, however, have substantial downsides. Surgery may leave behind undetected cancer cells that can grow into new tumours. Furthermore, in response to chemotherapy drugs, some cancer cells may emerge that resist further treatment. There is therefore interest in whether preventive strategies—including lifestyle changes and medications—could reduce the likelihood of confronting a life-threatening cancer.

Now, Akhmetzhanov and Hochberg have developed a mathematical model to help compare the effectiveness of preventive strategies and traditional cancer treatments. The model—which assumes that a person can only develop a single cancer from a single region of pre-cancerous cells—suggests that long-term cancer prevention strategies reduce the risk of a life-threatening cancer by more than traditional treatment that begins after a tumour is discovered. The preventive measures may be less effective in some cases compared to traditional treatments if they initially fail to stop a tumour growing, although on average they still work better than treating the cancer after detection.

According to Akhmetzhanov and Hochberg's model, surgical removal followed by chemotherapy is less likely to be successful than prevention, and when successful, requires larger impacts on the cancer (and therefore creates more side-effects for the patient) to achieve the same level of control as prevention. The model also suggests that even at very low levels of impact on residual cancer cells, chemotherapies are likely to be counterproductive by boosting the subsequent emergence of treatment-resistant tumours.

Akhmetzhanov and Hochberg's model predicts how effective preventive measures need to be in terms of slowing the growth of cancer cells to result in given reductions in the future risk of a life-threatening cancer. Future work should test this model by measuring the effects on tumour growth of prevention and of traditional therapies.

DOI:http://dx.doi.org/10.7554/eLife.06266.002

Boveri at 100: cancer evolution, from preneoplasia to malignancy

In the 100 years since the publication of Boveri's manuscript, 'Concerning the origin of human tumours', we have seen many advances in our understanding of how tumours originate, develop and progress. However, reading this article now, it is possible to find conclusions, or more often predictions, of what we now consider basic tenets of tumour biology. These include predicting the stochastic nature of the malignant change and that all tumours are necessarily of clonal origin, perhaps the basis of the modern concepts of field cancerization, of tumour heterogeneity and the clonal evolution of tumours. Modern researchers rarely refer to this paper, yet as a source of ideas it must rank amongst the landmarks in tumour biology of the last 100 years.