Abstract IA007: Distinct immune landscapes characterize highly and minimally invasive brain metastases
Bibliographic record
Abstract
Abstract Background: Cancer metastasis to the brain is a common complication of advanced disease with limited therapeutic options. Inefficient treatment is influenced, in part, by the unique composition of the brain microenvironment. Brain metastases (BrM) grow in two distinct patterns, either as minimally invasive (MI) masses with well-defined borders, or as tumors with highly invasive (HI) growth into surrounding brain tissue. HI BrM are associated with poor prognoses compared to MI BrM; however, differences in the tumor immune microenvironments (TIME) between these two lesion types remain largely unknown. Here, we investigate how the TIME differs between HI and MI BrM. Methods: We use Nanostring Digital Spatial Profiling coupled with the Cancer Transcriptome Atlas panel on 5 MI and 15 HI BrM patient samples (lung and breast cancer). This technique enables specific isolation of cancer cells at the tumor-brain interface and quantification of 1,825 cancer-specific RNA targets. Additionally, we perform imaging mass cytometry (IMC) on 119 BrM samples (lung cancer, breast cancer, melanoma, other) from 46 patients, encompassing over 350,000 cells. Samples represent BrM from various primary sites, including cancers of the lung, breast, and skin, and include patient-matched samples from the brain-tumor interface (‘margin’) or the centre of the metastatic lesion (‘core’). Results: The Nanostring Digital Spatial Profiling revealed a list of 106 and 73 differentially expressed genes in MI vs HI breast and lung BrM, respectively. Gene set enrichment analyses revealed that an interferon gamma (IFNγ) pathway signature was enriched in MI BrM and lost in HI BrM, which was confirmed by immunohistochemical staining for pSTAT1, consistent with an “immune hot” TIME in MI BrM when compared to HI lesions. Using IMC technology, we identified 20 different cell types, activation states, and spatially-defined cellular neighborhoods across our BrM patient samples. In comparison to MI samples, HI BrM have lower numbers of B cells, CD4+ T cells, and CD4- CD8- T cells in both the core and margin samples, and lower numbers of CD8+ T cells and regulatory T cells in the margin samples only. Conclusion: These data suggest that HI BrM invade into an immunosuppressed microenvironment while MI BrM are characterized by an active anti-tumor immune infiltrate. Together, this work suggests potential immune regulation of BrM invasion, which warrants further investigation. Citation Format: Peter Siegel. Distinct immune landscapes characterize highly and minimally invasive brain metastases [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr IA007.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".