Abstract A16: Genomic and immunologic characterization of a cohort of INI1-deficient pediatric cancers
Bibliographic record
Abstract
Abstract Several aggressive cancers impacting children are characterized by alterations in the SWI/SNF complex, including rhabdoid tumors, epithelioid sarcoma, and chordoma. With recent early-phase trials showing responses to EZH2 inhibitors, it is important to understand the optimal approach to identifying INI1-deficient cancers. As tumor profiling is becoming a more routine part of clinical care, this study was designed to determine the relationship between SMARCB1 genetic variants identified by a sequencing panel test and INI1 protein expression. Beyond EZH2 inhibitors, therapeutic approaches for INI1-deficient tumors are limited. Thus, we also sought to investigate PD-L1 expression in a cohort of INI1-deficient pediatric brain and solid malignancies. Patients were identified by two methods: 1) search of our institutional pathology database from 2000-2015 for INI1-deficient tumors and 2) presence of SMARCB1 genomic alteration in a database of 280 cases with somatic panel sequencing results. Patients were included in the study if sufficient archival tumor tissue was available for repeat, confirmatory sequencing and immunohistochemistry (IHC). Somatic next-generation sequencing (NGS) was performed via a panel assay, OncoPanel, which surveys exonic DNA sequences of 447 cancer genes and 191 regions across 60 genes for rearrangement detection. IHC stains for INI1 and PD-L1 were performed according to standardized procedure on Leica Bond automated platforms and expression was assessed by two investigators (AA, JP) who were blinded to sequencing results. The study included 43 patients. IHC was performed on at least one specimen for all patients and repeat, confirmatory NGS was successful in 91% (39/43). Single-copy deletion of SMARCB1 on NGS panel was not predictive of loss of INI1 expression by IHC with only 1/10 (10%) SMARCB1 single-copy deletion cases having INI1 loss. In the 26 cases with INI1 loss by IHC and successful tumor sequencing, 23 (89%) had a genomic alteration in SMARCB1 detected. Five cases (22%) had 1-copy deletion, 12 (52%) had 2-copy deletion, 2 (9%) had nonsense mutations, and 4 (17%) had two inactivating alterations. 40% (12/30) of the patients with INI1-deficient tumors had at least one tumor specimen that was PD-L1 positive (≥1%). PD-L1 status was not associated with timing of tumor sampling or prior treatment. TMB ranged from 0.76 to 9.13 mut/Mb of DNA. We have observed 2 patients with INI1-deficient cancers with evidence of efficacy of immune checkpoint inhibitors. SMARCB1 2-copy deletions and inactivating mutations are associated with loss of INI1 protein expression, but 1-copy deletion of INI1 in histologies other than those already known to be INI1-deficient is not predictive of loss of protein expression. These results, along with two case reports of successful disease control with immune checkpoint inhibitors, suggest that clinical trials of PD-1 or PD-L1 inhibitors, either as single agents or in combination with an EZH2 inhibitor, are warranted in malignancies with INI1 loss. Citation Format: Suzanne J. Forrest, Alyaa Al-Ibraheemi, Abigail Ward, Duong Doan, Catherine Clinton, Juan Putra, R. Seth Pinches, Cigall Kadoch, Susan Chi, Steve G. Dubois, Patrick Leavy, Natalie Collins, Alanna Church, Katherine A. Janeway. Genomic and immunologic characterization of a cohort of INI1-deficient pediatric cancers [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A16.
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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 | 0.001 |
| 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".