MétaCan
Menu
Back to cohort
Record W3083711044 · doi:10.1158/1538-7445.am2020-779

Abstract 779: A phase I study of BI 754111, an anti-LAG-3 monoclonal antibody (mAb), in combination with BI 754091, an anti-PD-1 mAb: Biomarker analyses from the microsatellite stable metastatic colorectal cancer (MSS mCRC) cohort

2020· article· en· W3083711044 on OpenAlexaff
Johanna C. Bendell, Susanna V. Ulahannan, Quincy S. Chu, Manish R. Patel, Ben George, Aurélie Auguste, Theresia Leo-Kress, Kai Bernd Stadermann, Nicole Kraemer, Mabrouk Elgadi, Melissa L. Johnson

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsBoehringer Ingelheim (Canada)University of Alberta
Fundersnot available
KeywordsMedicineImmune checkpointMonoclonal antibodyImmune systemBiomarkerPeripheral blood mononuclear cellCD8AntibodyOncologyTumor microenvironmentImmunotherapyT cellInternal medicineCancer researchImmunologyBiologyIn vitro

Abstract

fetched live from OpenAlex

Abstract Introduction: LAG3 is an immune checkpoint receptor, often co-expressed with PD-1 on immune cell surfaces. PD-1 and LAG-3 signaling contribute to immune cell exhaustion in the tumor microenvironment. Dual blockade of PD-1 and LAG-3 is thus expected to improve response versus PD-1 blockade alone. A dose escalation/expansion trial (NCT03156114) is evaluating BI 754111, an anti-LAG-3 mAb, plus BI 754091, an anti-PD-1 mAb, in patients (pts) with advanced solid tumors. Here, we report data in pts with MSS mCRC, for whom checkpoint inhibitors (CPIs) have shown limited activity. We broadly evaluated biomarkers to provide information on mode of action and for their potential to predict responses. Methods: In this dose expansion cohort, pts with PD-(L)1-naïve, previously treated MSS mCRC tumors were enrolled. Pre- and on-treatment tumor biopsies and blood samples for biomarker analyses were collected. Cytokines, including interferon-gamma (IFN-γ), were quantified in plasma samples by multiplexed and high-sensitivity immunoassays. Activated effector memory T cell and other peripheral blood mononuclear cell counts were determined by flow cytometry. PD-L1, LAG-3 and CD8 expression was determined by immunohistochemistry (IHC). Exploratory gene expression analyses to determine immuno-oncology (IO)-related markers were conducted. Results: 40 pts with MSS mCRC received BI 754111 600 mg in combination with BI 754091 240 mg every 3 weeks. Pts had received a median (range) of 3.5 (1–10) prior treatments. To date (Sep 2019), 3 (7.5%) pts achieved a partial response (PR) and 11 (27.5%) had stable disease (SD) as best response. Peripheral blood analysis showed treatment led to coordinated upregulation of pro-inflammatory cytokines in some pts. Pts with greater cytokine induction were more likely to have SD. Also, upregulation of activated CD8 effector memory T cells in peripheral blood was observed in many pts. IHC analysis indicated that, in tumors that had CD8 T cells and PD-L1 expression at the tumor periphery at baseline, treatment led to infiltration of CD8 T cells into the tumor and an increase in PD-L1 expression. Analyses of pre-treatment tumors suggested that high PD-L1 gene expression was associated with clinical benefit. In addition, a treatment-associated increase of the IFN-γ gene signature scores was observed, supporting a treatment-induced activation of the immune system in the tumor; the effect was more pronounced in pts with PR/SD versus those with progressive disease. LAG-3 IHC levels at baseline were not predictive of outcome in this anti-PD-(L)1 naïve setting. Conclusion: BI 754111 plus BI 754091 showed encouraging results in this IO-refractory MSS mCRC population. Biomarker analyses showed activation of the immune system in peripheral blood and the tumor, consistent with other CPIs. Citation Format: Johanna Bendell, Susanna V. Ulahannan, Quincy Chu, Manish Patel, Ben George, Aurélie Auguste, Theresia Leo-Kress, Kai Bernd Stadermann, Nicole Kraemer, Mabrouk Elgadi, Melissa Johnson. A phase I study of BI 754111, an anti-LAG-3 monoclonal antibody (mAb), in combination with BI 754091, an anti-PD-1 mAb: Biomarker analyses from the microsatellite stable metastatic colorectal cancer (MSS mCRC) cohort [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 779.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.165
GPT teacher head0.479
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations10
Published2020
Admission routes1
Has abstractyes

Explore more

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