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Record W4284976473 · doi:10.1038/s41467-022-31510-1

Multi-modal molecular programs regulate melanoma cell state

2022· article· en· W4284976473 on OpenAlexaff
Miles C. Andrews, Junna Oba, Chang‐Jiun Wu, Haifeng Zhu, Tatiana V. Karpinets, Caitlin Creasy, Marie‐Andrée Forget, Xiaoxing Yu, Xingzhi Song, Xizeng Mao, A. Gordon Robertson, Gabriele Romano, Peng Li, Elizabeth M. Burton, Yiling Lu, Robert Szczepaniak‐Sloane, Khalida Wani, Kunal Rai, Alexander J. Lazar, Lauren E. Haydu, Matías A. Bustos, Jianjun Shen, Yueping Chen, Margaret Morgan, Jennifer A. Wargo, Lawrence N. Kwong, Cara Haymaker, Elizabeth A. Grimm, Patrick Hwu, Dave S.�B. Hoon, Jianhua Zhang, Jeffrey E. Gershenwald, Michael A. Davies, P. Andrew Futreal, Chantale Bernatchez, Scott E. Woodman

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsCanada's Michael Smith Genome Sciences Centre
FundersAmerican Cancer SocietyAIM at MelanomaNational Health and Medical Research CouncilNational Institutes of HealthCancer Prevention and Research Institute of TexasDr. Miriam and Sheldon G. Adelson Medical Research FoundationMedical Research CouncilNational Cancer InstituteMelanoma Research AllianceUniversity of Texas SystemUniversity of Texas MD Anderson Cancer CenterLyda Hill Foundation
KeywordsMelanomaTranscriptomeBiologyComputational biologyPhenotypemicroRNAImmune checkpointDNA methylationCancer researchGeneticsCancerGeneImmunotherapyGene expression

Abstract

fetched live from OpenAlex

Melanoma cells display distinct intrinsic phenotypic states. Here, we seek to characterize the molecular regulation of these states using multi-omic analyses of whole exome, transcriptome, microRNA, long non-coding RNA and DNA methylation data together with reverse-phase protein array data on a panel of 68 highly annotated early passage melanoma cell lines. We demonstrate that clearly defined cancer cell intrinsic transcriptomic programs are maintained in melanoma cells ex vivo and remain highly conserved within melanoma tumors, are associated with distinct immune features within tumors, and differentially correlate with checkpoint inhibitor and adoptive T cell therapy efficacy. Through integrative analyses we demonstrate highly complex multi-omic regulation of melanoma cell intrinsic programs that provide key insights into the molecular maintenance of phenotypic states. These findings have implications for cancer biology and the identification of new therapeutic strategies. Further, these deeply characterized cell lines will serve as an invaluable resource for future research in the field.

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 categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.348
Teacher spread0.315 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations25
Published2022
Admission routes1
Has abstractyes

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