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Abstract P3-05-12: VISTA expression on tumor-infiltrating lymphocytes in breast cancer: Clinical correlates and association with PD-1

2018· article· en· W2791564187 on OpenAlexaff
S Burugu, Dongxia Gao, TO Nielsen

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsCentre for Advancing Health Outcomes
Fundersnot available
KeywordsTumor-infiltrating lymphocytesBreast cancerImmune checkpointTissue microarrayMedicineImmunohistochemistryOncologyInternal medicineCancerPD-L1Immune systemAntibodyProportional hazards modelCancer researchImmunotherapyImmunology

Abstract

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Abstract Background: The V-domain containing Ig Suppressor of T Cell Activation (VISTA) is a recently discovered immune checkpoint receptor with homology to PD-1. VISTA expression on tumor-infiltrating lymphocytes (TILs) blocks their proliferation and effector functions. Recent pre-clinical data in cancer mouse models treated with anti-VISTA and anti-PD-L1 combinations showed promising results and non-redundant functions of VISTA and PD-L1 blockade. However, the expression and prognostic value of VISTA+ TILs in primary breast tumors has not been investigated in detail. Here we assess expression, prognostic value, and associations of VISTA+TILs with other immune checkpoint markers (PD-1/PD-L1, LAG-3, and IDO-1) and with H&E TIL counts. Methods: A tissue microarray consisting of breast carcinoma primary excision specimens (n=330) from the University of British Columbia hospital, linked to detailed clinicopathological data and outcomes, was used in this study. Patients from this cohort did not receive neoadjuvant treatment. A VISTA antibody (Clone D1L2G) was applied on a 4μm section of the tissue microarray by immunohistochemistry using a Ventana automated stainer. VISTA+TILs in direct contact with tumor nest were scored and reported as absolute count per 0.6mm core. Positive cases were defined as cases with VISTA+TILs≥1. All descriptive and survival analyses were conducted using SPSS software. Results: VISTA+TILs were present in 30% of cases and were significantly (p<0.05) associated with younger age (<50 years old), larger tumors (>2cm), hormone receptor negativity (ER/PR) and high Ki67proliferation index (≥13.25%). Almost half (48%) of basal-like breast cancers were positive for VISTA expressing TILs. No significant prognostic associations were observed in this cohort. Among the immune checkpoint receptors analyzed, VISTA+TILs were highly associated with PD-1+ TILs: 79% of cases positive for PD-1+TILs were also infiltrated by VISTA+TILs. Interestingly, we found that VISTA+TILs and PD-1+TILs were enriched in cases with otherwise low levels (<10%) of H&E TILs. Conclusions: Our study identifies the presence of VISTA+TILs in breast cancer patients and its strong association with PD-1+TILs. These results suggest that VISTA blockade could be a good candidate for combination therapy with other immune checkpoint inhibitors, a concept being tested in early phase clinical trials. Validation of these findings in a larger independent cohort powered for multivariate analysis is currently ongoing. Citation Format: Burugu S, Gao D, Nielsen TO. VISTA expression on tumor-infiltrating lymphocytes in breast cancer: Clinical correlates and association with PD-1 [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-05-12.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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)0.0040.001

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 head0.060
GPT teacher head0.421
Teacher spread0.362 · 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 designObservational
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".

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Citations1
Published2018
Admission routes1
Has abstractyes

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