Fourth International Biannual Evolution and Cancer Conference (Resistance, resilience, and robustness: Can we target cancer's evolutionary and ecological nature?)
Bibliographic record
Abstract
Many biological systems are resilient to shock and have the ability to return to a previous state following a disturbance. In the case of cancer, this resilience may jeopardize our understanding of tumorous cell proliferation and presents many clinical problems, including therapeutic resistance. Indeed, during progression and treatment, cancer has the capacity to exhibit resistance, resilience, and robustness, making its dynamics very challenging to forecast. Furthermore, organisms have evolved defenses that increase the robustness to mutations and other perturbations that can increase cancer susceptibility. Considering cancer and defense mechanisms to control oncogenesis through the lens of resilience and resistance can help identify challenges and opportunities in cancer therapy as well as expand the horizons for novel cancer prevention approaches. The fourth biannual international Evolution and Cancer Conference of the International Society for Evolution, Ecology and Cancer (ISEEC), which had the theme “Resistance, Resilience and Robustness,” was held between December 7 and 10, 2017, in Tempe (AZ, USA). The biannual meeting aimed to bring together clinicians, theoreticians, and evolutionary scientists from all over the world to present the latest research developments in the field. Around 80 people attended the 2017 conference. Below we provide a report on the meeting, briefly summarize the plenary talks, and discuss the proceedings of the parallel sessions. The meeting began on December 7 with a keynote address by Dr. Paul Turner (Yale University, CT, USA) on the evolutionary robustness of oncolytic RNA viruses. The first session, chaired by Dr. Carlo Maley (Arizona State University, AZ, USA), focused on the general theme “Evolution and Cancer.” The first speaker, Dr. Alexander Anderson from the Moffitt Cancer Center (Miami, FL, USA), talked about the evolution of cancer metaphenotypes. Using a hybrid multiscale mathematical model of tumor growth in vascularized tissue, the study showed that tumors develop heterogeneous spatiotemporal structures called metaphenotypes that collectively have an evolutionary advantage in the tumor. By categorizing each therapy response as a function of the initial tumor metaphenotype, drug sequences that promote a synergistic response can be identified. Carlo Maley then discussed resistance management for cancer, especially drawing on knowledge from pest management that has led to three heuristic achievements in resistance management that could also be related to oncology. Maley explained that the overall aim is to transform cancer from a deadly disease into one that we can live with. This can be summarized as limiting the use of each mode of action (MoA) to the lowest practical level, diversifying the use of MoAs as much as possible, limiting each MoA to no more than two nonconsecutive uses, and partitioning MoAs in space or time so as to segregate their use as much as practically possible. Dr. James DeGregori (University of Colorado, CO, USA) presented his research on the coevolution of somatic maintenance programs and mutation rates. Through stochastic modeling, he showed that the evolution of extended lifespans dramatically alters selection acting on germline mutation rates, significantly impacting on the ability to evolve while limiting somatic risks in populations of large animals. This may have been critical in enabling the evolution of large multicellular animals. In parallel, a new method of mutation detection allowing the observation of unselected mutations in normal tissues has shed new light on how somatic maintenance programs influence mutation rate tolerance (limiting tumor evolution) by impacting germline mutation rates and the variability of mutation rates in populations. The work of Dr. Athena Aktipis (Arizona State University, AZ, USA) focuses on understanding how multicellular bodies “decide” if a cell poses a cancer threat. By developing a model relying on the cheater detection principle (benefits/costs of a false alarm, detecting cellular cheating where it is not happening), it becomes possible to predict how body size and longevity will influence selection on the information-processing components of cancer suppression systems. Therefore, by applying cheater detection and signal detection theories to the problem of cancer suppression, we can better understand the function of complex gene regulatory networks that protect multicellular bodies from cancer and how they interact with other cancer suppression mechanisms such as immune surveillance. Then, Dr. Aurora Nedelcu (University of New Brunswick, NB, Canada) presented her work exploring the role of selection in shaping cancer's evolutionary potential and resilience. After the application of several selective pressures on a cancer line that expresses adherent and nonadherent cells (to mimic cells in a solid tumor or circulating metastatic cells, respectively), the cells successfully evolved into five distinct cell lines that differ from the ancestral line in several traits related to fitness. Interestingly, although imposing a specific selective regime resulted in traits favoring adaptation to that environment, additional traits were also coselected. These traits (by-products of selection) can either reduce or increase the fitness of the evolved line (relative to the ancestral line), depending on the environment. Dr. Noemi Andor (Stanford University, CA, USA) presented her work on the identity of surviving and extinct clones in a longitudinal study of the DNA damage therapy response in gliomas. Overall, she showed that more than half of the clones detected among all patients were found across multiple biopsies of the same patient. Moreover, mutation profiles and clonal compositions from proximal biopsies were more similar to each other than those from distant biopsies. The study revealed a higher growth rate among clones with more amplifications but only among patients who had received DNA damage therapy. This first session closed with the keynote talk was given by Dr. Christina Curtis on the way to quantify the evolutionary dynamics of therapeutic resistance and metastasis. The second day of the meeting opened with a discussion panel that was chaired by Carlo Maley and entitled the “Future of Evolution, Ecology and Cancer.” The panel included Dr. Anna Barker (former Deputy Director of NCI), Dr. Alex Sekulic (Mayo AZ Cancer Center Director), and Dr. Dan Gallahan (Deputy Director of the Division of Cancer Biology at NCI). This was followed by a plenary session given by Dr. Deborah Gordon (Stanford University) on the ecology of collective behavior. The first session of the day focused on ecosystem robustness and resilience. The first speaker, Dr. Frédéric Thomas (Centre for Ecological and Evolutionary Research on Cancer, CNRS, Montpellier, France), talked about the concept of oncobiota as an underappreciated component of animal evolutionary ecology. Indeed, given that malignant cells are omnipresent in the body of multicellular organisms, as are microbiota and parasites, they too may be involved in reciprocal interactions with the host phenotype. Therefore, malignant cells may also be involved in reciprocal interactions with microbiota and parasites, thus setting the scene for fascinating—yet complex—tripartite interactions; this appears to be a promising avenue to investigate. The next talk, given by Dr. Beata Ujvari (Deakin University, Australia), was on adaptive evolution in the face of a transmissible cancer. While cancer is widespread in the animal kingdom, its impact on life history traits and strategies have rarely been documented. One exception is the devil facial tumor disease (DFTD), a transmissible cancer afflicting Tasmanian devils (Sarcophilus harrisii), where the phenotypic and genetic evolution of Tasmanian devils suffering from DFTD has been documented. This study shows that, akin to parasites, cancer can directly and indirectly affect devil life history traits and trigger host evolutionary responses. Dr. Michael J. Metzger (Columbia University, NY, USA) next presented a study on the discovery a new kind of contagious cancer (leukemia-like disease) in the soft-shell clam (Mya arenaria), the Pacific blue mussel (Mytilus trossulus), the cockle (Cerastoderma edule), and the carpet shell clam (Polytitapes aureus). Transmission within each of these species is due to the independent horizontal spread of a clonal cancer lineage. However, while the cancer lineages in soft-shell clams, mussels, and cockles are each derived from their respective host species, the cancer cells in P. aureus are derived from Venerupis corrugata, a different species that lives in the same geographic area but which itself is not known to be highly susceptible to disseminated neoplasia. These findings show that transmission of cancer in the marine environment is common in multiple species, that it has originated many times, and that both cross-species transmission and species-specific resistance occur. Dr. Chandler Gatenbee (Moffitt Cancer Center, FL, USA) followed with a talk on the characterization of the immunogenic bottleneck. Based on a branching hybrid nonspatial cellular automaton, this study investigated whether the explosive antigenic diversity observed in colorectal cancer can be explained by either a “get lucky” strategy, where clones can have low enough antigenicity to avoid immune detection, or a “get smart” strategy, where clones can acquire active escape mechanisms. Only the “get smart” model is able to recapitulate the observed patterns of antigen burden and in immune that an active immune escape is for and that the immune is the first tumors evolve resistance The parallel session with cancer evolutionary The first talk by Dr. (Arizona State University, AZ, USA) presented the which is a new method for the of somatic evolution somatic This as a in the is to the evolution of somatic cells, or somatic This method has been to the rate of somatic in and its through has that the observed rate of evolution in this is due to a low rate at the level, the low rate of progression from to by that clones with mutation rates to this The second talk, by Dr. (Yale University, CT, USA), was entitled of or additional mutation in or to of mutations in are with of all new the are very or mutation can to resistance these After of tumors to the of other mutations within or within that could resistance at the time of treatment, were to the potential for novel mutations to during tumor of that could the therapy within tumors or was These findings that resistance of tumors to therapy is to be present at the time of among the mutations to resistance, mutations in gene with in with the fitness The next talk was given by Dr. of Cancer on the evolutionary selection of from five different populations in the and to for of selection in gene with cancer the aim of this study was to understand are so While no selection was found for a signal for selection was found in with or cancer in all populations and selection was found for with cancer. 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The day December began with a plenary by Dr. on the somatic evolution in normal followed by plenary by Dr. (University of AZ, USA) on we can from resistance to The with from Carlo Maley and Athena This was an additional that the Evolution and Cancer is and and to understand and cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".