Abstract B019: Clinical and molecular characterization of chromophobe renal cell carcinoma: A focus on immunotherapy based regimens and the tumor immune microenvironment
Bibliographic record
Abstract
Abstract Background: Chromophobe renal cell carcinoma (ChRCC) represents 5% of all kidney cancers. In contrast to clear cell RCC (ccRCC), the immune landscape of ChRCC and its response to immunotherapy remain poorly characterized. We sought to evaluate the clinical outcomes of patients with ChRCC treated with immuno-oncology (IO)-based regimens, and assess the immune cell composition, phenotypic state, and T cell specificity in the tumor microenvironment of ChRCC. Methods: Using real-world data from the International Metastatic RCC Database Consortium, we analyzed the survival outcomes and objective responses of patients with advanced ChRCC to currently adopted IO-based regimens (i.e. dual IO therapy or IO + vascular endothelial growth factor targeted therapy [VEGF-TT]) in the first-line setting, as compared to patients with ccRCC. Single-cell RNA sequencing (scRNA-seq) and single-cell T-cell receptor sequencing (scTCR-seq) were performed on ChRCC and related oncocytic neoplasms (i.e. renal oncocytoma [RO] and low-grade oncocytic tumor [LOT]) samples with matched normal kidney specimens. The infiltration of CD45+ immune cells in renal oncocytic tumors and ccRCC samples was quantified using immunohistochemistry (IHC). Results: Compared to patients with ccRCC (n=856) treated with first-line IO-based regimens, patients with ChRCC (n=31) had a lower overall survival (median: 24.7 vs. 50.5 months, p<0.001) and lower time to treatment failure (median: 4.5 vs. 11.0 months, p<0.001). Similarly, patients with ChRCC had a significantly lower overall response rate than those with ccRCC (12.0 vs. 47.1%, respectively; p<0.001). When evaluating immune cell infiltration, renal oncocytic tumors (ChRCC, RO, and LOT) exhibited a low density of CD45+ cells (mean: 739 ± 114 cells/mm2; n=5) compared to ccRCC (mean: 3,420 ± 1,979 cells/mm2; n=5) (p<0.05). Single-cell analysis was performed on 46,817 cells from 5 tumors (ChRCC: n=3, RO: n=1 and LOT: n=1) and 4 samples from adjacent normal kidney. Across all tumors, CD8+ T cell clusters displayed a lower expression of immune checkpoints (i.e. PDCD1, CTLA4, LAG3, HAVCR2, and TIGIT) as compared to CD8+ T-cells from ccRCC. This was further validated in the analysis of bulk RNA-seq data from the TCGA, with a significantly lower expression of all immune checkpoints in ChRCC compared to both ccRCC (p<0.01) and papillary RCC (pRCC; p<0.01). Analysis of the T cell receptor repertoire (scTCR-seq) of ChRCC, RO and LOT samples did not show any pattern of clonal expansion, and a higher proportion of T cells in ChRCC were inferred to have a viral specificity, compared to ccRCC (0.79 vs. 0.1%, respectively). Conclusions: Patients with metastatic ChRCC appear to display poor clinical outcomes when treated with IO-based regimens, compared to ccRCC. Renal oncocytic tumors, including ChRCC, exhibit a low infiltration of immune cells, and a non-exhausted immune phenotype. Citation Format: Michel Alchoueiry, Chris Labaki, Long Zhang, Yue Hou, Kevin Bi, Charbel Hobeika, J. Connor Wells, Kosuke Takemura, Ziad Bakouny, Sabrina Camp, Carmen Priolo, Damir Khabibullin, Nicholas Schindler, Renee Maria Saliby, Eddy Saad, Samer Salem, Melissa Daou, Rana McKay, Sumanta Pal, Daniel Heng, Eliezer Van Allen, Sachet Shukla, Toni Choueiri, David Braun, Elizabeth Henske. Clinical and molecular characterization of chromophobe renal cell carcinoma: A focus on immunotherapy based regimens and the tumor immune microenvironment [abstract]. In: Proceedings of the AACR Special Conference: Advances in Kidney Cancer Research; 2023 Jun 24-27; Austin, Texas. Philadelphia (PA): AACR; Cancer Res 2023;83(16 Suppl):Abstract nr B019.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".