Characteristics associated with spatially resolved immune landscapes in triple-negative breast cancer in the FinXX trial and Mayo Clinic cohort.
Bibliographic record
Abstract
581 Background: Several studies have established the crucial role of preexisting immune response measured by tumor-infiltrating lymphocytes (TILs) in triple-negative breast cancer (TNBC). Emerging studies showed that not only the number of TILs but also the location of TILs is as critical. There are 3 distinct immune landscapes described based on the locations of TILs, namely immune enriched (IN), immune excluded (IE), and immune desert (ID), which are associated with outcomes in TNBC treated with immune-checkpoint inhibitors. Here we evaluated characteristics associated with each immune landscape. Methods: NanoString IO360, Digital Spatial Profiling (DSP), and CosMx, a spatial multi-omics single-cell imaging platform, were used. DSP was used to quantify 39 immune-related proteins in stromal and tumor-enriched segments from 44 TNBC samples from the FinXX trial (NCT00114816) and 276 samples from the Mayo Clinic (MC) TNBC cohort (Leon-Ferre BCRT 2018). CosMx was performed in 75 samples from the MC TNBC cohort. First, tumors with TIL quantified by H&E ≤ 30% were classified as ID. The rest of the tumors 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. Differential expression listed as log fold change (FC) was estimated from the linear mixed model with significance defined as two-sided p < 0.05. Results: Using DSP in the FinXX trial, intratumoral and stromal higher HLA-DR (FC 1.68, p = 0.001), B2M (FC 0.8, p = 0.005), CD4 (FC 0.74, p = 0.01), and CD40 (FC 1.56, p = 0.001) were associated with IN compared to ID. When comparing IE and IN, higher intratumoral CD11c (FC 0.97, p = 0.01) and stromal CD4 (FC 0.89, p = 0.047), CD20 (FC 0.85, p = 0.016), CD40 (FC 0.95, p = 0.045), and CD27 (FC 0.84, p = 0.024) were associated with IN. Similar findings were observed in the MC cohort. Moreover, intratumoral NY-ESO-1 expression (FC 0.55, p = 0.03) was associated with IN. Using GSEA with IO360 in the FinXX trial, PI3K-Akt signaling was associated with ID compared to IN (p = 0.01). We further evaluated the differential gene expression in a spatially resolved manner using CosMx with single-cell sequencing in the MC 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 compared to ID and IE. Conclusions: Using an in-depth analysis with spatially defined context, we identified characteristics associated with distinct immune landscapes in TNBC. Our study highlights the potential future implications of intratumoral MHC expression, CD40, and PI3K-AKT as biomarkers and therapeutic targets. Clinical trial information: NCT00114816 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".