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Abstract PS03-04: Tumor immune microenvironment modulates resistance to estrogen suppression in ER+ breast cancer

2024· article· en· W4396591833 on OpenAlexaff
Fabiana Napolitano, Yunguan Wang, Dhivya R. Sudhan, Paula I. González-Ericsson, Luigi Formisano, Lei Guo, M Rosario Chica-Parrado, Chang‐Ching Lin, Kyung‐min Lee, Hongli Ma, Nathaniel Evans, Alberto Servetto, Saurabh Mendiratta, Spencer Barnes, Yisheng Fang, Lin Xu, Justin M. Balko, Gordon B. Mills, Marilyne Labrie, Ariella B. Hanker, Carlos L. Arteaga

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsTumor microenvironmentBreast cancerEstrogenImmune systemCancerMedicineCancer researchEstrogen receptorInternal medicineOncologyImmunology

Abstract

fetched live from OpenAlex

Abstract Despite major advances in the treatment of estrogen receptor positive (ER+) breast cancer (BC), advanced disease continues to be the main cause of death from this disease. The role of the tumor immune microenvironment (TIME) in the progression of ER+ BC and its response to treatment is not completely understood. The aim of this study was to elucidate the role the TIME in the response of ER+ tumors to estrogen deprivation (ED). We collected samples from 215 postmenopausal patients with stage I-III ER+ BC, treated with letrozole for 2-4 weeks, to induce ED. We used AQUA on pre-treatment biopsies and on-treatment surgical biopsies to assess ER, PR, HER2, and Ki67. Then, we categorized the patients’ response to ED based on the Ki67 score in on-treatment samples: ED-sensitive (ED-S) if natural log (ln) of the Ki67 score ≤1.0 or ≤2.7% Ki67+ cells vs. ED-resistant (ED-R) if ln ≥2.0 or ≥7.4% Ki67+ cells. Firstly, we assessed TIME composition by investigating stromal tumor-infiltrating lymphocytes (sTILs) in H&E-stained FFPE of on-treatment tumor sections. ED-R tumors exhibited a significantly higher stromal TILs score (p=0.0001) relative to ED-S tumors. We next prepared tissue microarrays from 227 (on-treatment) surgical sections and subjected them to cyclic immunofluorescence (CycIF) with 38 antibodies to examine their intra-tumoral immune cell infiltration. From each tumor core, we segmented single cells and labeled them as immune, cancer, or stromal cells based on expression of a set of markers. Briefly, cells that stained strongly for CD45 (leukocyte marker), and/or CD4 (T lymphocyte marker), or CD68 (macrophage marker) were labeled immune cells. CD45/CD4/CD68-negative cells were categorized as tumor if E-cadherin and/or cytokeratin-positive, or stromal cells if -negative. Next, we assessed cell specific spatial enrichment by quantifying the expression of immune markers in the area immediately adjacent to each tumor cell. Immune-suppressive T-reg (FOXP3+) cells were enriched in the ED-S tumors (p=0.0004), as well as PD1+ (exhausted) T cells (p=0.0004), and CD68+ cells (p < 0.0001) compared to ED-R tumors. ED-R tumors exhibited higher CD20+ B cells (p < 0.0001), higher CD8+ T cells (p=0.0329), in addition to higher CD45+ cells (p < 0.0001), compared to ED-S tumors. RNA-sequencing of the same surgical samples showed a higher T cells cytolytic score in ED-R relative to ED-S (p=0.0058), suggesting enhanced CD8+ T cells activity, in addition to their higher infiltration. We are currently analyzing letrozole-induced changes in TIME composition using Geomix digital spatial profiler in paired pre- and on-treatment biopsies from ED-R and ED-S tumors and will be presented at the meeting. Consistent with the CycIF findings, GSEA of hallmark gene signatures from bulk RNA-sequencing of treated tumors revealed that immune-related gene sets, such as “IFN α response”, “IFNɣ response”, and “allograft rejection” were upregulated in ED-R vs. ED-S cancers. ED-R tumors showed enrichment of CXCL9, CXCL10, and CXCL11 chemokines and their receptor, CXCR3. Publicly available datasets of patients with ER+ breast cancers showed that higher expression CXCL9 (HR 1.36; p=0.016), CXCL10 (HR 1.71; p< 0.0001), and CXCL11 (HR 1.5; p=0.0016) are predictive of shorter relapse-free survival on antiestrogen therapy. We are currently investigating whether these chemokines play a causal role in resistance to ED, and if this is phenocopied by co-cultures of ER+ BC cells and CD8+ T-cells. Conclusions ED-resistant tumors are enriched with stromal TILs and exhibit higher immune cell intra-tumoral infiltration and CD8+T cells cytolytic activity compared to ER+ tumors sensitive to estrogen suppression. In contrast, ED-S tumors showed a more immunosuppressed milieu. The role of CXCL9, CXCL10 and CXCL11 in inducing resistance to ED warrants further investigation. Citation Format: Fabiana Napolitano, Yunguan Wang, Dhivya Sudhan, Paula Gonzalez-Ericsson, Luigi Formisano, Lei Guo, M Rosario Chica-Parrado, Chang-Ching Lin, Kyung-Min Lee, Hongli Ma, Nathaniel Evans, Alberto Servetto, Saurabh Mendiratta, Spencer Barnes, Yisheng Fang, Lin Xu, Justin Balko, Gordon Mills, Marilyne Labrie, Ariella Hanker, Carlos Arteaga. Tumor immune microenvironment modulates resistance to estrogen suppression in ER+ breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS03-04.

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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 score0.004
Threshold uncertainty score0.015

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)0.0040.000

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 head0.370
Teacher spread0.337 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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