The immunogenomic landscape of primary and metastatic gastroesophageal adenocarcinoma.
Bibliographic record
Abstract
493 Background: Metastatic gastroesophageal adenocarcinoma (GEA) is a heterogeneous disease with an overall poor prognosis. The tumour microenvironment (TME) between the primary and metastatic compartment is not well characterized. This study aims to describe the immunogenomic features of matched primary and metastatic GEA and their correlation with clinical outcomes. Methods: We performed whole exome sequencing (WES, n=36) and total RNA sequencing (RNA-seq, n=36) on a prospectively collected cohort of metastatic GEA, of which 14 had matched primary and metastatic tissues. We used TME deconvolution (Bagaev et al., 2021) comparing between the primary and metastatic compartments. Using an orthogonal technology, we further integrated immune checkpoint-directed multiplex immunohistochemistry (mIHC) for 22 patients with matched primary and metastatic samples. Results: The median age of our cohort was 61 (range 27-89), primarily male (n=28, 77%), and non-Asian (n=32, 89%). All had metastatic GEA at time of diagnosis. Differential expression showed activation of immune pathways such as tumor necrosis factor signalling and interferon-gamma response in the metastatic compartment. Deconvolution of the TME demonstrated 29% of primary tissues having an immune-inflamed TME compared to 61% of metastatic tissues (p=0.032). Exploring immune cell types, metastatic compartment is characterized by higher abundance of naïve and mature B cell populations (p<0.001), while primary compartment is enriched with CD4+ T cells (p<0.01). In matched cases, only 2 of 14 (14%) had concordant TME subtypes between primary and metastatic samples suggesting high degree of immune divergence. Furthermore, expression of common immune checkpoints aligned more with TME subtypes than within patient compartments suggesting common pathways of immune evasion. M-IHC showed both T-cell and immune checkpoint markers are enriched at the tumor margins compared to the tumor center in both primary and metastatic compartments (CD4; p<0.0001, CD8; p<0.001, CD68; p<0.001). There was a significant increase in the number of CD68+/CD163+/PDL1+ M2-like macrophages in the tumor margins (p<0.0001). Consistent with our deconvolution analysis, there are higher CD4+ T cells in the matched primary compared to metastatic samples. Long-term survivors (>16 months) had decreased number of CD68+ macrophages in the tumor center (p=0.019). Conclusions: Primary and metastatic GEA have divergent TME. This may partially explain varying responses to chemo-immunotherapy approaches. Therapies aimed at modifying TME may provide personalized treatment options.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".