Tumor-Intrinsic and Microenvironmental Determinants of Impaired Antitumor Immunity in Chromophobe Renal Cell Carcinoma
Bibliographic record
Abstract
PURPOSE While immune checkpoint inhibition (ICI) has transformed the management of many advanced renal cell carcinomas (RCCs), the determinants of effective antitumor immunity for chromophobe RCC (ChRCC) and renal oncocytic tumors remain an unmet clinical and scientific need. METHODS Single-cell transcriptomic and T-cell receptor profiling was performed on tumor and adjacent normal tissue of patients with ChRCC and renal oncocytic neoplasms. Using machine learning, the cellular origin of renal oncocytic neoplasms was evaluated, with analysis of associated oncogenic pathways. Using immunohistochemistry, immune infiltration was analyzed in renal oncocytic neoplasms in comparison with clear cell RCC (ccRCC). Immune checkpoint expression, clonal expansion, and tumor specificity were compared between ChRCC and ccRCC. Using the International Metastatic RCC Database Consortium data set, clinical outcomes of patients with metastatic ChRCC (mChRCC) treated with first-line systemic regimens were compared with those of patients with ccRCC. RESULTS We validated α-intercalated cells as the cellular origin of renal oncocytic neoplasms. We identified a downregulation of HLA class I molecules with enrichment of potentially targetable pathways including mammalian target of rapamycin and ferroptosis in ChRCC. The tumor microenvironment of ChRCC showed markedly decreased immune infiltration, with a pronounced depletion in tumor-infiltrating CD8 + T cells. ChRCC-infiltrating CD8 + T cells demonstrated lower immune checkpoint expression, diminished clonal expansion, and decreased tumor specificity. Clinical analysis identified poor survival outcomes selectively among patients with mChRCC treated with immune-based therapies. CONCLUSION Immunogenomic analysis of ChRCC revealed profound depletion of T cells, with an immune phenotype marked by a lack of expression of immune checkpoints and poor tumor specificity, suggesting that the few T cells in these tumor types are likely nonspecific bystanders. This immune-cold environment hinders an effective response to immunotherapy and underscores the need for ChRCC-tailored treatments designed to improve tumor-specific T-cell infiltration into the microenvironment.
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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) | 0.000 | 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 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".