Abstract 6154: Distinct immunosuppressive environments elicited in vessel co-opting and angiogenic colorectal cancer liver metastases and changes following treatment
Bibliographic record
Abstract
Abstract Colorectal cancer (CRC) is the third most common cancer worldwide and 50% of CRC patients develop liver metastases. Colorectal cancer liver metastases (CRCLM) present as two major histological growth patterns (HGP) that predict response to treatment/survival: 1. angiogenic tumors characterized by a desmoplastic stroma separating CRC cells from the liver parenchyma and are highly angiogenic and 2. co-opting tumors where tumor cells infiltrate the parenchymal cells in the liver and grow by co-opting the sinusoidal blood vessels between the liver cell plates without sprouting angiogenesis. Angiogenic tumors receiving neoadjuvant anti-angiogenics (anti-VEGF) and chemotherapy have more than double the 5-year overall survival compared to patients with co-opting tumors who have received the same neoadjuvant regimen. In addition, our clinical data revealed that anti-angiogenics could negatively affect outcomes in patients with co-opting lesions. The goal of our study is to understand how the immune system affects the development of the two distinct CRCLM tumors. We used both Nanostring GeoMX spatial protein profiling platform, immunohistochemistry and immunofluorescence, to identify the immune landscapes in chemonaïve and treated human CRCLM tumors. We observed that angiogenic tumors were rich in both CD4 and CD8 T cells with a near absence of neutrophils and macrophages. These adaptive immune cells were also FOXP3 positive indicating an immunosuppressive phenotype. Interestingly, we observed that vessel co-opting tumors have far fewer infiltrating lymphocytes than angiogenic tumors, but interestingly have greater numbers of innate cells - mostly neutrophils and macrophages. The macrophages were further characterized as being M2, tumor promoting, leading to an immunosuppressive environment. We then went on to analyze treated tumors. For those patients treated with chemotherapy alone we observed a larger infiltration of T cells in the angiogenic tumors and the appearance of T cells infiltrating the co-opting tumors. Surprisingly, in patients treated with chemotherapy and anti-angiogenic drugs (ie. anti-VEGF), which is part of the standard of care, the co-opting tumors no longer demonstrated the presence of T cell infiltration and had a similar profile to the chemonaïve tumors. This could explain why chemotherapy in co-opting tumors had a higher overall survival compared to those treated with chemotherapy and anti-VEGF. These results suggest developing treatments aimed at reshaping the different immune landscape in angiogenic and co-opting CRCLM to yield beneficial results for patient overall survival. Furthermore, the identification of immune cells or immune mediators facilitating the development of these two tumor would identify immune cell targets for immunotherapies. Citation Format: Diane H. Kim, Thomas Z. Mayer, Stephanie K. Petrillo, Anthoula Lazaris, Peter Metrakos. Distinct immunosuppressive environments elicited in vessel co-opting and angiogenic colorectal cancer liver metastases and changes following treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6154.
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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 | 0.000 | 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".