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Abstract PS03-03: The spatially resolved single-cell atlas of the tumor immune architecture revealed the central role of IFN-alpha and plasmacytoid dendritic cells in triple-negative breast cancer in the Mayo Clinic cohort and FinXX trial

2024· article· en· W4396591286 on OpenAlexaff
Saranya Chumsri, Yi Liu, Yaohua Ma, Jodi M. Carter, Mark Gregory, S. Church, Jason Reeves, Heather Ann Brauer, Sarah Warren, Heikki Joensuu, Edith Perez, Roberto A. Leon‐Ferre, David W. Hillman, Judy C. Boughey, James N. Ingle, Krishna R. Kalari, Fergus J. Couch, Matthew P. Goetz, Keith L. Knutson, E. Aubrey Thompson

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsImmune systemTriple-negative breast cancerTriple negativeCancerBreast cancerCancer researchPathologyAtlas (anatomy)BiologyMedicineImmunologyInternal medicineAnatomy

Abstract

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Abstract Background: Multiple studies have confirmed the central role of preexisting immune response measured by stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC). Emerging studies showed that not only the number of TILs but also the location of TILs is important. There are 3 distinct immune architectures described based on the amount and locations of TILs, namely immune enriched (IN), immune excluded (IE), and immune desert (ID). Here we evaluated outcomes and characteristics associated with each immune landscape. Methods: NanoString Digital Spatial Profiling (DSP) and CosMx, a spatial multi-omics single-cell imaging platform, were performed in 75 samples from the Mayo Clinic (MC) TNBC cohort (Leon-Ferre BCRT 2018). NanoString IO360 was performed in 114 samples from the FinXX trial ( NCT00114816) . Firstly, tumors with sTIL quantified by H&E ≤ 30% were classified as ID. The rest of the tumors with high sTIL > 30% were categorized according to the intratumoral CD8 protein expression by DSP, with IE having intratumoral CD8 in the lower median and IN having intratumoral CD8 in the upper median. Chi-square test, gene set enrichment, Cox regression, and Kaplan-Meier analysis were used. Differential expression listed as log 2-fold change (FC) was estimated from the linear mixed model with significance defined as two-sided p< 0.05. Results: ID is associated with low Ki67 < 5% (23.3% vs. 9.6% ID, p 0.02) as well as apocrine (11/13, 84.6%) and metaplastic histology (10/12, 83%). In both univariate and multivariate analysis, patients with IN had significantly improved recurrence-free survival (RFS) compared to those with ID (HR 0.37, 95%CI 0.18-0.74, p 0.005). Despite having high sTILs, IE had poor outcomes similar to ID (HR 0.84, 95%CI 0.36-1.98). Strikingly, we identified that IE patients had significantly lower plasmacytoid dendritic cells (pDCs) compared to IN (mean 0 vs. 0.26/100 tumor cells, 95%CI 0.08-0.43 , p 0.01). Using Gene Set Enrichment Analysis to evaluate differential hallmarks between IN and IE, we identified IF Nɑ and IFNγ (FDR < 0.001) responses as significantly enriched in IN group, consistent wi th the function of pDCs, which are a subset of dendritic cells specialized in secreting high levels of type I interferon. To validate this finding, we further evaluated the 11 leading edge gene IFNɑ signature in the FinXX trial. A high IFNɑ signature score was associated with significantly improved outcomes in the FinXX trial (HR 0.21, 95%CI 0.09-0.51 , p < 0.001). Similar findings were observed using Kaplan-Meier analysis in the FinXX trial with significantly improved RFS (p 0.0006) and overall survival (p 0.0001) in patients with high IFNɑ signature scores. Furthermore, we evaluated the differential gene expression unique to IN tumors in the Mayo cohort. Expressions of MHC class I and class II in tumor cells, including HLA-A, HLA-B, HLA-C, HLA-DRA, HLA-DRB1, HLA-DPA1, and HLA-E, were associated with IN and significantly improved outcomes (p < 0.05) compared to ID and IE. Conclusions: Highlighting the importance of spatial context, we identified that patients with IE tumors had poor outcomes despite having high TILs. Moreover, u sing an in-depth analysis with spatially defined context, we identified the central role of pDC and the significance of IF Nɑ in TNBC. Support: Breast Cancer Research Foundation, Mayo Clinic Breast Cancer SPORE (P50CA116201-17) W81XWH-15-1-0292, P50CA015083, R35CA253187 Citation Format: Saranya Chumsri, Yi Liu, Yaohua Ma, Jodi Carter, Mark Gregory, Sarah Church, Jason Reeves, Heather Ann Brauer, Sarah Warren, Heikki Joensuu, Edith Perez, Roberto Leon-Ferre, David Hillman, Judy Boughey, James Ingle, Krishna Kalari, Fergus Couch, Matthew Goetz, Keith Knutson, E. Thompson. The spatially resolved single-cell atlas of the tumor immune architecture revealed the central role of IFN-alpha and plasmacytoid dendritic cells in triple-negative breast cancer in the Mayo Clinic cohort and FinXX trial [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 PS03-03.

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)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.022
GPT teacher head0.310
Teacher spread0.288 · 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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Citations0
Published2024
Admission routes1
Has abstractyes

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