Abstract 2162: KIM–1 mediatesimmune evasioninrenal cell carcinoma
Bibliographic record
Abstract
Abstract Renal cell carcinoma (RCC) is the most common and lethal form of kidney cancer. Cancer immune evasion is a major obstacle for effective immunotherapy in RCC. Mechanisms of immune evasion are characterized by three phenotypes: Immune Inflamed; tumor contains infiltrating T cells which are rendered inactive within the tumor microenvironment due to localized inhibition. Immune Desert; tumor is devoid of activate T cells due to defective antigen presentation, and/or T cell activation. Lastly, Immune Excluded; tumor is surrounded by T cells that are unable to penetrate the parenchyma, caused by immunosuppression within the tumor stroma. Kidney Injury Molecule-1 (KIM-1) is a cell-surface glycoprotein aberrantly expressed in >90% of RCC tumors. The purpose of this study was to determine the pathophysiological significance of KIM-1 in RCC pathogenesis. We generated murine RCC cells (Renca) expressing KIM-1 (KIM-1pos) or control vector (KIM-1neg) using lentiviral transduction. We found that KIM-1 expression on RCC cells promoted more rapid tumor growth when injected contralaterally into syngeneic immunocompetent BALB/c mice (KIM-1neg = 263.75mm3, KIM-1pos = 849.72, p = 0.0149 & KIM-1neg = 0.32g, KIM-1pos = 0.58, p = 0.0229), but not in RAG1-/- immunodeficient BALB/c mice suggesting the KIM-1 promotes tumor growth through evasion of the adapt immune system. When analyzing tumor infiltrating lymphocytes (TILs) from both tumor groups, we found a relative scarcity of CD4+ and CD8+ T cells within the KIM-1pos vs. KIM-1neg tumors. To classify the immune evasion phenotype, we analyzed localization of the immune infiltrate using immunofluorescence within KIM-1pos and KIM-1neg RCC tumors. We found significantly fewer CD3+ cells within the KIM-1pos vs. KIM-1neg tumor parenchyma (KIM-1neg = 3625.78%, KIM-1pos = 272.36%, p = 0.0410). Moreover, CD3+ cells of the KIM-1neg tumors were observed in the parenchyma, whereas CD3+ cells of the KIM-1pos tumors were localized to the tumor stroma. In addition, we observed a higher frequency of myeloid derived suppressor cells (MDSCs) within the KIM-1pos vs the KIM-1neg tumor parenchyma (KIM-1neg = 0.05, KIM-1pos = 0.19, p = 0.0266). Transcriptomic profiling of both KIM-1pos and KIM-1neg Renca cells suggests that KIM-1 promotes deposition of extracellular matrix (KIM-1neg = -1.21, KIM-1pos = 1.96-fold change), which may contribute to KIM-1-mediated immune evasion Our data suggests that KIM-1 expression in RCC promotes immune evasion by altering the tumor microenvironment resulting in an Immune Excluded phenotype. Citation Format: Demitra M. Yotis, Bradly Shrum, Marie Sarabusky, Lakshman Gunaratnam. KIM–1 mediatesimmune evasioninrenal cell carcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2162.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".