MétaCan
Menu
Back to cohort

Designing a broad-spectrum integrative approach for cancer prevention and treatment

2015· review· en· W2177390620 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSeminars in Cancer Biology · 2015
Typereview
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoDalhousie UniversityHealth Sciences CentreMcGill UniversityUniversity of WindsorChild and Family Research Institute
FundersNational Institute of Environmental Health SciencesNational Institute of Allergy and Infectious DiseasesNational Center for Research ResourcesNational Institute of General Medical SciencesNational Cancer InstituteNational Heart, Lung, and Blood InstituteMedical Research CouncilCanadian Institutes of Health ResearchNational Institutes of HealthJunta de Castilla y LeónUnited Arab Emirates UniversityMinisterio de Ciencia e InnovaciónVetenskapsrådetKarolinska InstitutetNational Institute of Neurological Disorders and StrokeIkerbasque, Basque Foundation for ScienceRegione CampaniaMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungAssociazione Italiana per la Ricerca sul CancroCancer Society of New ZealandAmerican Cancer SocietyMinistry of Science, ICT and Future PlanningShireBayer HealthCareNational Center for Complementary and Alternative MedicineCalifornia Breast Cancer Research ProgramBreast Cancer CampaignNational Research FoundationNational Institute for Health and Care ResearchTerry Fox FoundationSky FoundationU.S. Department of DefenseCancer Research UKBarbara Ann Karmanos Cancer InstituteWest Virginia Higher Education Policy CommissionMinisterstvo Zdravotnictví Ceské RepublikyNational Institute on Minority Health and Health DisparitiesEuropean CommissionNational Institute of Arthritis and Musculoskeletal and Skin DiseasesUniversity of MiamiState Council of Higher Education for VirginiaScottish GovernmentCancer Prevention and Research Institute of TexasRural and Environment Science and Analytical Services DivisionAvon Foundation for WomenWellcome TrustNational Science FoundationCancer Research WalesNational Institute on AgingHuntsman Cancer FoundationPfizerBristol-Myers SquibbNational Center for Complementary and Integrative HealthAgentura Pro Zdravotnický Výzkum České RepublikyTerry Fox Research InstituteAmerican Diabetes AssociationDamon Runyon Cancer Research FoundationEuropean Regional Development FundV Foundation for Cancer ResearchElsa U. Pardee FoundationInstituto de Salud Carlos IIINational Research Foundation of KoreaPancreatic Cancer Action NetworkBreast Cancer Research FoundationUniverzita Karlova v PrazeNational Institute of Diabetes and Digestive and Kidney DiseasesGilead SciencesNational Institute on Alcohol Abuse and AlcoholismUniversity of New South WalesNatural Environment Research CouncilUniversity of GlasgowU.S. Department of Veterans AffairsGrantová Agentura České RepublikyUnited Soybean Board
KeywordsBroad spectrumTumor microenvironmentCancerMechanism (biology)Personalized medicineComputational biologyMedicineBioinformaticsDiseaseCancer therapyPrecision medicineBiologyCancer researchInternal medicineChemistryPathology

Abstract

fetched live from OpenAlex

Targeted therapies and the consequent adoption of "personalized" oncology have achieved notable successes in some cancers; however, significant problems remain with this approach. Many targeted therapies are highly toxic, costs are extremely high, and most patients experience relapse after a few disease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistant immortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are not reliant upon the same mechanisms as those which have been targeted). To address these limitations, an international task force of 180 scientists was assembled to explore the concept of a low-toxicity "broad-spectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspects of relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a wide range of high-priority targets (74 in total) that could be modified to improve patient outcomes. For these targets, corresponding low-toxicity therapeutic approaches were then suggested, many of which were phytochemicals. Proposed actions on each target and all of the approaches were further reviewed for known effects on other hallmark areas and the tumor microenvironment. Potential contrary or procarcinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixed evidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of the relationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. This novel approach has potential to be relatively inexpensive, it should help us address stages and types of cancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for future research is offered.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.124
GPT teacher head0.452
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it