MétaCan
Menu
Back to cohort

Abstract B021: In vivo gain-of-function screen identifies CREB5, a novel ECM modulator that promotes immunotherapy resistance via the Collagen-Lair1 axis

2023· article· en· W4389227786 on OpenAlexaboutno aff
Payal Tiwari, Kayla J. Colvin, Sarah Kim, Ashwin V. Kammula, Seth Anderson, Or‐Yam Revach, Maulik Vyas, Jessica A. Talamas, Shadmehr Demehri, Kathleen B. Yates, John G. Doench, William C. Hahn, Robert T. Manguso

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
Fundersnot available
KeywordsImmunotherapyImmune systemCancer immunotherapyCancer researchIn vivoBiologyImmune checkpointStromal cellCancer cellDownregulation and upregulationCell biologyCancerImmunologyMedicineGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Treatment with immune checkpoint inhibitors induce remarkable clinical responses in several cancer types. However, most cancer patients do not respond to immunotherapy, and patients who initially respond often exhibit acquired resistance. Understanding the universe of immune evasion strategies will enable the design of more effective immunotherapies. Here, we identified genes that drive immune evasion by performing a genome scale in vivo CRISPR gain-of-function screen in tumors treated with anti-PD-1 antibodies; and discovered the transcription factor CREB5 as a top resistance mediator. Using transcriptional profiling, we showed CREB5 drives upregulation of extracellular matrix genes including collagen and collagen-stabilizing factors. We found CREB5 or collagen (Col1a1, Col4a1, or Col16a1) overexpressing tumors exhibit poor responses to anti-PD-1. Collagen is the major ligand for the inhibitory receptor LAIR1, which is broadly expressed on T cells, B cells, NK cells, and myeloid cells. Deletion of LAIR1 in mice or overexpression of the decoy receptor LAIR2 in tumors abrogates the resistance-causing effect of CREB5 or collagen overexpression, suggesting that CREB5 overexpression drives resistance partly via collagen-LAIR1 inhibitory signaling. In summary, we have identified a gene that can induce fibroblast-like features in tumor cells to promote immunotherapy resistance. Further investigation of pathways that induces stromal mimicry in cancer cells could identify novel immunotherapy targets. Citation Format: Payal Tiwari, Kayla Colvin, Sarah Kim, Ashwin Kammula, Seth Anderson, Or-Yam Revach, Maulik Vyas, Jessica A Talamas, Shadmehr Demehri, Kathleen Yates, John Doench, William C Hahn, Robert Manguso. In vivo gain-of-function screen identifies CREB5, a novel ECM modulator that promotes immunotherapy resistance via the Collagen-Lair1 axis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B021.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.085
GPT teacher head0.372
Teacher spread0.286 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCancer Immunology ResearchSame topicCancer Immunotherapy and BiomarkersFrench-language works237,207