Abstract A007: Circulating tumor DNA and tissue staining analyses reveal heterogeneous <i>ERBB2</i>/HER2 status in urothelial cancer
Bibliographic record
Abstract
Abstract Human epidermal growth factor receptor 2 (HER2) is encoded by the ERBB2 gene, and frequently mutated, amplified, and/or overexpressed in urothelial cancer (UC). Promising antibody-drug conjugates have led to new interest in HER2 as a UC clinical target. Patient selection for HER2-targeted therapy typically relies on immunohistochemistry (IHC) and fluorescence in-situ hybridization (FISH) of tumor tissue, however DNA sequencing can identify ERBB2 genomic alterations. Accurate biomarker-driven patient selection will be critical to optimize the clinical benefit of HER2-targeted therapy. Therefore, we evaluated plasma circulating tumor DNA (ctDNA) for ERBB2/HER2 status determination in UC, as compared to IHC and FISH of metachronous tissue. 411 plasma samples from 236 metastatic UC patients were profiled with targeted sequencing across >50 genes frequently altered in UC, including dense coverage flanking the ERBB2 locus. Using an established bioinformatics workflow, we determined the presence of ERBB2 alterations (mutations, amplifications, and/or structural variants) in the 181 patients with evidence of ctDNA in ≥1 sample. Clinical records were reviewed for the availability of archival tumor tissue; in total, 81 formalin-fixed paraffin-embedded tissue specimens were retrieved from 23 patients with ctDNA ERBB2 alterations and 20 ERBB2-wildtype controls. HER2 IHC was performed with a polyclonal rabbit anti-human Her2 antibody (Dako) and scored according to gastric cancer guidelines. HER2 FISH was performed with the PathVysion HER-2 DNA Probe Kit. Protein-altering ERBB2 mutations were identified in 14% of evaluable patients, with two-thirds at known oncogenic hotspots. ERBB2 copy gain was detected in 8% of patients overall, 9% when excluding low tumor fraction samples. IHC results were assessable for 82 tissue samples from 43 patients, and 33 patients had at least one sample with positive HER2 staining (2+/3+). IHC scores varied in 16/23 patients with ≥2 tissue samples, with the variation leading to a change in classification (HER2-negative [0/1+] versus positive [2+/3+]) in half (8/16). In two patients with mixed variant histology, the urothelial component showed IHC 3+ while the scores were 2+ (plasmacytoid) and 0 (squamous) in the variant regions. Frequent focal staining patterns were observed with both IHC and FISH. ERBB2 alterations in ctDNA were correlated with IHC positivity – when considering the most recent tissue sample per patient, 79% of ctDNA ERBB2-altered patient’s tumors were also positive by IHC. Conversely, 55% of ctDNA ERBB2-wildtype cases were positive by IHC. FISH results were available from 24 samples (20 positive, 4 negative), all from patients with ctDNA ERBB2 amplification. 18/20 samples with FISH positivity were HER2 IHC 2+/3+; the remaining two samples were IHC 1+. Our results demonstrate significant spatial and/or temporal heterogeneity in ERBB2/HER2 status, with implications for the rational implementation of biomarker-directed (HER2-targeted) therapy in UC. Citation Format: Gillian Vandekerkhove, Andrew J. Murtha, David C. Müller, Kimia Rostin, Carlos Vasquez-Rios, Jussi Nikkola, Maria Stephenson, Emily Fung, Jaskirat Atwal, Karan Parekh, Cecily Q. Bernales, Gráinne Donnellan, Gang Wang, Tilman Todenhöfer, Piet Ost, Peter C. Black, Kim N. Chi, Bernhard J. Eigl, Alexander W. Wyatt. Circulating tumor DNA and tissue staining analyses reveal heterogeneous ERBB2/HER2 status in urothelial cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr A007.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".