Abstract HER2-17: HER2-17 Novel Quantitative HER2 Assay for Determining Dynamic HER2 Expression in the HER2 IHC 0 “Ultra-Low” Setting: Implications for Precision Therapy in HER2- Breast Cancer
Bibliographic record
Abstract
Abstract Background: The HER2 antibody drug conjugate (ADC) fam-trastuzumab deruxtecan-nxki (T-DXd) significantly improves outcomes over standard chemotherapy in pts with HER2-LOW (IHC 1+ and IHC 2+ FISH-) metastatic breast cancer (MBC). Data from the DAISY (NCT04132960) trial in pts with HER2 IHC 0 or “ultra low” MBC revealed median progression-free survival (PFS) of 4.2 mos vs 6.7 mos in HER2-LOW and 11.1 mos in HER2 3+ pts (Diéras V, et al. Cancer Res. 2022;82(4_Suppl):PD8-02). There is an urgent need to develop methods to accurately discern HER2 LOW expression versus HER2 IHC 0/ultra-low expression so appropriate pts may receive T-DXd. We have developed a quantitative HER2 assay using reverse phase protein array (RPPA) technology with laser capture microdissection (LCM) enrichment of tumor epithelium that measures HER2 expression over a 65-fold dynamic range in HER2 IHC 0 to 3+ breast cancers. In I-SPY 1 and 2 trials we found that RPPA-assessed quantitative HER2 and activated/phosphorylated HER2 expression predicted for pathologic complete response in pts with HER2 IHC 0, HER2-LOW and HER2 3+ disease with various HER2 and other targeted agents. We then developed and validated the first CLIA/CAP-accredited quantitative HER2 protein expression and activation assay, and now explore quantitative HER2 expression in HER2 IHC 0/ultra low disease. Given the recent approval of sacituzumab govitecan-hziy in TNBC and the results of the TROPiCS-02 (NCT03901339), we also evaluated quantitative RPPA-based TROP-2 expression levels in HER2 IHC 0 breast cancer. Methods: LCM-enriched tumor epithelium was obtained from freshly cut FFPE core needle and resected breast cancer samples from 175 pts with pathology-determined HER2 IHC 0 status (N=68 ER+ and N=107 ER-). Quantitative HER2 output is generated as a relative intensity unit (RU) that is interpolated to an internal calibrator curve and a population referent comprised of known HER2+ (IHC 3+ and 2+/FISH+), HER2-LOW and HER2 IHC 0/ultra-low tumors to generate population-based cut-points as a referent. RPPA-based quantitative HER2 expression are reported as one of four levels of expression across the HER2 dynamic range observed: “non/extremely low”, “modest“, “moderate”, and “high”. Quantitative TROP2 protein expression levels were also measured for each case by the RPPA assay on the same lysate using the same adjectival determinants of relative expression as HER2. Results: For the HER2 IHC 0 ER+ cohort, we observed HER2 protein expression over a 25-fold dynamic range and that 57% (N=39) had HER2 non/extremely low, 37% (N=25) modest, and 4 (6%) moderate/high HER2 expression by RPPA. For the HER2 IHC 0 ER- cohort, we observed HER2 protein expression over a 15-fold dynamic range and that 71% (N=76) had non/extremely low, and 31% (N=29%) modest HER2 expression. We observed TROP-2 protein expression over a 35-fold dynamic range across all tumors measured, and it was found to be at least modestly expressed in 95% (37/39) ER+ and 95% (72/76) ER- of the IHC 0/ultra-low tumors that were also found to be HER2 non/extremely low by RPPA. Conclusions: LCM-RPPA quantitative assessment of HER2 expression showed that nearly 40% of ER+ IHC 0 and 30% of ER- IHC 0 “ultra-low” breast cancers actually had modest to moderate HER2 expression. Interestingly, this frequency approximates the response rate of 30% seen with T-DXd in HER2 IHC 0 pts in the DAISY trial. Quantitatively measured TROP2 is at least modestly expressed in the vast majority of RPPA-assessed HER2 IHC 0 cancers regardless of ER status, making a TROP2-directed ADC an attractive therapeutic option for these pts. If validated in larger studies, LCM-RPPA-based HER2 expression could provide a better understanding of the potential for therapeutic efficacy with T-DXd in patients with HER2 IHC “ultra-low” disease, and may better define true ultra-low HER2 expression in HER2 IHC 0 tumor biopsies at baseline and refine the lower limit of the HER2-LOW designation. Citation Format: Emanuel F. Petricoin, Brian A. Corgiat, Joyce O’Shaughnessy, Patricia LoRusso, Kris Weinberg, Justin Davis, Chelsea Gawryletz. HER2-17 Novel Quantitative HER2 Assay for Determining Dynamic HER2 Expression in the HER2 IHC 0 “Ultra-Low” Setting: Implications for Precision Therapy in HER2- Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr HER2-17.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".