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Record W2535232402 · doi:10.1158/1538-7445.tme16-a15

Abstract A15: Mechanisms of CD8+ T cell immunosuppression in triple negative breast cancer

2016· article· en· W2535232402 on OpenAlexaff
Tina Gruosso, Mathieu Gigoux, Nicholas Bertos, Sadiq M.I. Saleh, Atilla Ömeroğlu, Dongmei Zuo, Hong Zhao, Margarita Souleimanova, Valerie M. Weaver, Sarkis Meterissian, Michael Hallett, Morag Park

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsTriple-negative breast cancerStromal cellCancer researchCytotoxic T cellCD8Estrogen receptorBreast cancerStromaTumor microenvironmentMedicineImmune systemCancerBiologyPathologyImmunologyInternal medicineImmunohistochemistry

Abstract

fetched live from OpenAlex

Abstract Triple negative breast cancer (TNBC), defined as tumors lacking expression of the estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), are especially difficult to treat effectively. While ER+ and HER2+ breast cancer subtypes can be treated with Tamoxifen and Herceptin, respectively, there are no targeted therapies for TNBC patients. Furthermore, while only 20-30% of TNBC patients respond to chemotherapy in the neoadjuvant setting, overall outcome remains poor for non-responding patients. However, mounting evidence suggests that immune-checkpoint inhibitor immunotherapies may be especially promising for TNBC patients. We and others have shown that the presence of CD8+ T cells, a crucial component of the cytotoxic arm of the adaptive immune response, is a sign of good clinical outcome in TNBC patients. However, good outcome only correlates with CD8+ T cell invasion of the tumor parenchyma. Here we show that some patients have an accumulation of CD8+ T cells in the surrounding tumor-associated stroma, but not the tumor epithelium, and these patients responded as poorly as patients with no CD8+ T cells at all. Yet how cancer associated fibroblasts (CAFs), a dominant cell type of the tumor-associated stroma, affects CD8+ T cell invasion into the tumor epithelium is still poorly understood. To identify potential stroma-dependent mechanisms that potentiate or inhibit CD8+ T cells invasion into the tumor epithelium, we performed gene expression profiling of laser-capture microdissected tumor-associated stroma (and matched epithelium) from 56 TNBC cases. Here we identify several key stromal features that may explain the accumulation of CD8+ T cells outside of the tumor epithelium. Preliminary data by immunohistochemistry and immunofluorescence validate some key stromal features and decipher the implication of other immune cell types in CD8+ T cells lack of tumor epithelium infiltration. These key stromal features that impair CD8+ T cell infiltration into the tumor in some patients might explain the relative low efficiency of immunotherapies in TNBC patients (20% of patients respond). One could speculate that targeting these key stromal features would allow a significant CD8+ T cell infiltration into the tumor and thus sensitize patients to immunotherapies. Citation Format: Tina Gruosso, Mathieu Gigoux, Nicholas Bertos, Sadiq Saleh, Atilla Omeroglu, Dongmei Zuo, Hong Zhao, Margarita Souleimanova, Valerie Weaver, Sarkis Meterissian, Michael Hallett, Morag Park. Mechanisms of CD8+ T cell immunosuppression in triple negative breast cancer. [abstract]. In: Proceedings of the AACR Special Conference: Function of Tumor Microenvironment in Cancer Progression; 2016 Jan 7–10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2016;76(15 Suppl):Abstract nr A15.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.050
GPT teacher head0.385
Teacher spread0.335 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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