MétaCan
Menu
Back to cohort
Record W4390350671 · doi:10.1016/j.ccell.2023.12.003

Melanoma and microbiota: Current understanding and future directions

2023· review· en· W4390350671 on OpenAlexaff
Bertrand Routy, Tanisha Jackson, Laura Mählmann, Christina K. Baumgartner, Martin J. Blaser, Allyson L. Byrd, Nathalie Corvaı̈a, Kasey L. Couts, Diwakar Davar, Lisa Derosa, Howard C. Hang, Geke A.P. Hospers, Morten L. Isaksen, Guido Kroemer, Florent Malard, Kathy D. McCoy, Marlies Meisel, Sumanta K. Pal, Ze’ev A. Ronai, Eran Segal, Gregory D. Sepich‐Poore, Fyza Y. Shaikh, Randy F. Sweis, Giorgio Trinchieri, Marcel R.M. van den Brink, Rinse K. Weersma, Katrine Whiteson, Liping Zhao, Jennifer L. McQuade, Hassane M. Zarour, Laurence Zitvogel

Bibliographic record

VenueCancer Cell · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of CalgaryUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersNational Institute of Environmental Health SciencesHorizon 2020EMD SeronoDirection Générale de l’offre de SoinsGenentechInstitut Gustave-RoussyInstitut Universitaire de FranceCentre National de la Recherche ScientifiqueLigue Contre le CancerUniversité Paris-SaclayFondation pour la Recherche MédicaleFondation LeducqAgence Nationale de la RechercheInstitut National Du CancerAstraZenecaSeres TherapeuticsInstitut National de la Santé et de la Recherche MédicalePfizerIncyteModernaJuno TherapeuticsAstellas PharmaEisaiE-RareBeiGeneIpsenJazz PharmaceuticalsEuropean CommissionNational Institute of Diabetes and Digestive and Kidney DiseasesSanofiExelixisDaiichi Sankyo EuropeNational Cancer InstituteHORIZON EUROPE Framework ProgrammeGilead SciencesLabex Immuno-OncologyNational Institutes of HealthEuropean Research Area Network on Cardiovascular DiseasesRegeneron PharmaceuticalsCastle BiosciencesTherakosMelanoma Research AllianceSeerave FoundationAssociation pour la Recherche sur le CancerEli Lilly and CompanyBristol-Myers Squibb
KeywordsGut floraImmunotherapyContext (archaeology)BiologyCancer immunotherapyImmune systemMelanomaCancerImmunologyComputational biologyBioinformaticsCancer researchGenetics

Abstract

fetched live from OpenAlex

Over the last decade, the composition of the gut microbiota has been found to correlate with the outcomes of cancer patients treated with immunotherapy. Accumulating evidence points to the various mechanisms by which intestinal bacteria act on distal tumors and how to harness this complex ecosystem to circumvent primary resistance to immune checkpoint inhibitors. Here, we review the state of the microbiota field in the context of melanoma, the recent breakthroughs in defining microbial modes of action, and how to modulate the microbiota to enhance response to cancer immunotherapy. The host-microbe interaction may be deciphered by the use of "omics" technologies, and will guide patient stratification and the development of microbiota-centered interventions. Efforts needed to advance the field and current gaps of knowledge are also discussed.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.075
GPT teacher head0.356
Teacher spread0.282 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations78
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCancer CellSame topicGut microbiota and healthFrench-language works237,207