Abstract 3744: Peripheral immune indices predict pathologic complete response and residual cancer burden in inflammatory breast cancers

Abstract Background: Circulating immune profiles offer a noninvasive approach to monitor treatment response in breast cancer. Inflammatory breast cancer (IBC), although clinically distinct, shares resistance and immune evasion features among each other. To identify immune escape mechanisms and early predictors of response in IBC, we profiled longitudinal peripheral immune markers and evaluated their association with pathologic complete response (pCR) and residual cancer burden (RCB) across treatment regimens and subtypes and developed composite immune indices to improve prediction under class imbalance. Methods: Peripheral blood samples (n=93) from patients treated with neoadjuvant or induction therapy for IBC were analyzed by multiparameter flow cytometry and annotated for subtype, regimen, pCR, and RCB. Group comparisons used Mann-Whitney U (pCR) and Kruskal-Wallis (RCB). Predictive models included logistic regression and random forest classifiers with class-weighting. Composite indices included CD8 Exhaustion, CD8 Memory, NK-ADCC scores derived from z-scaled components. Model performance was assessed using 5-fold cross-validation with AUC, PR-AUC, and calibration. Planned extensions include leave-one-regimen validation, temporal analyses, and external evaluation using a pre-registered pipeline. Results: Univariate analyses identified significant associations between pCR and the CD8 Exhaustion Index (p≈0.007) and CD8 Memory Index (p≈0.038), with NK-ADCC trending (p≈ 0.078). Logistic regression and random forest models incorporating combined indices improved AUC from ∼0.70 when individually associated, to ∼0.92 ± 0.07 (5-fold CV), albeit with wide uncertainty due to only up to 5 pCR events. Individual markers linked to pCR included Stem_Memory_CD8, NKG2A_ADCC, and CTLA4_CD8, while CD56hi NK and NKG2A +CD56hi NK distinguished RCB gradients (p<0.05 before correction). No markers remained significant after FDR adjustment given sample size. Conclusions: Peripheral immune signatures, particularly combined CD8 exhaustion, memory indices, NK ADCC were associate with higher pCR and lower RCB. Composite indices outperform single markers and capture the balance between immune activation and suppression. Ongoing cross-cohort validation will assess generalizability across regimens and subtypes. Severe class imbalance (∼5/93 pCR) and small subgroup sizes constrain precision of our analysis. Findings are hypothesis-generating and warrant external validation in larger prospective cohorts. Citation Format: Hui Gao, Ranjan Upadhyay, Angela Alexander, Angela N. Marx, Megumi Kai, Chelain R. Goodman, Azadeh Nasrazadani, Savitri Krishnamurthy, Anthony Lucci, Rachel M. Layman, Sadia Saleem, Vicente Valero, Michael C. Stauder, Susie X. Sun, Gary J. Whitman, Miral M. Patel, Huong C. Le-Petross, Chasity L. Yajima, Lily Villarreal, Heather Lopez, Bora Lim. Peripheral immune indices predict pathologic complete response and residual cancer burden in inflammatory breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3744.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-3744
Primary Topic
Advanced Breast Cancer Therapies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 3744: Peripheral immune indices predict pathologic complete response and residual cancer burden in inflammatory breast cancers

Gary J. Whitman, Azadeh Nasrazadani, Susie X. Sun, Heather Lopez et al.
Cancer Research
Advanced Breast Cancer Therapies
article

Abstract 3744: Peripheral immune indices predict pathologic complete response and residual cancer burden in inflammatory breast cancers

Gary J. Whitman, Azadeh Nasrazadani, Susie X. Sun, Heather Lopez, Miral Patel, Michael C. Stauder, Anthony Lucci, Chasity Yajima, Chelain R. Goodman, Sadia Saleem, Ranjan Upadhyay, Rachel M. Layman, Angela Alexander, Bora Lim, Vicente Valero, Angela Marx, Megumi Kai, Huong Le-Petross, Hui Gao, Lily Villarreal, Savitri Krishnamurthy
article en

Abstract

Abstract Background: Circulating immune profiles offer a noninvasive approach to monitor treatment response in breast cancer. Inflammatory breast cancer (IBC), although clinically distinct, shares resistance and immune evasion features among each other. To identify immune escape mechanisms and early predictors of response in IBC, we profiled longitudinal peripheral immune markers and evaluated their association with pathologic complete response (pCR) and residual cancer burden (RCB) across treatment regimens and subtypes and developed composite immune indices to improve prediction under class imbalance. Methods: Peripheral blood samples (n=93) from patients treated with neoadjuvant or induction therapy for IBC were analyzed by multiparameter flow cytometry and annotated for subtype, regimen, pCR, and RCB. Group comparisons used Mann-Whitney U (pCR) and Kruskal-Wallis (RCB). Predictive models included logistic regression and random forest classifiers with class-weighting. Composite indices included CD8 Exhaustion, CD8 Memory, NK-ADCC scores derived from z-scaled components. Model performance was assessed using 5-fold cross-validation with AUC, PR-AUC, and calibration. Planned extensions include leave-one-regimen validation, temporal analyses, and external evaluation using a pre-registered pipeline. Results: Univariate analyses identified significant associations between pCR and the CD8 Exhaustion Index (p≈0.007) and CD8 Memory Index (p≈0.038), with NK-ADCC trending (p≈ 0.078). Logistic regression and random forest models incorporating combined indices improved AUC from ∼0.70 when individually associated, to ∼0.92 ± 0.07 (5-fold CV), albeit with wide uncertainty due to only up to 5 pCR events. Individual markers linked to pCR included Stem_Memory_CD8, NKG2A_ADCC, and CTLA4_CD8, while CD56hi NK and NKG2A +CD56hi NK distinguished RCB gradients (p<0.05 before correction). No markers remained significant after FDR adjustment given sample size. Conclusions: Peripheral immune signatures, particularly combined CD8 exhaustion, memory indices, NK ADCC were associate with higher pCR and lower RCB. Composite indices outperform single markers and capture the balance between immune activation and suppression. Ongoing cross-cohort validation will assess generalizability across regimens and subtypes. Severe class imbalance (∼5/93 pCR) and small subgroup sizes constrain precision of our analysis. Findings are hypothesis-generating and warrant external validation in larger prospective cohorts. Citation Format: Hui Gao, Ranjan Upadhyay, Angela Alexander, Angela N. Marx, Megumi Kai, Chelain R. Goodman, Azadeh Nasrazadani, Savitri Krishnamurthy, Anthony Lucci, Rachel M. Layman, Sadia Saleem, Vicente Valero, Michael C. Stauder, Susie X. Sun, Gary J. Whitman, Miral M. Patel, Huong C. Le-Petross, Chasity L. Yajima, Lily Villarreal, Heather Lopez, Bora Lim. Peripheral immune indices predict pathologic complete response and residual cancer burden in inflammatory breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3744.

Cancer ResearchVol. 86(7_Supplement)
The University of Texas MD Anderson Cancer Center (US), Foundation for Individual Rights in Education (US)
Good health and well-being
Openalex Percentile: Top 30%
Advanced Breast Cancer Therapies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.