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. 2025 Jun:81:104432.
doi: 10.1016/j.breast.2025.104432. Epub 2025 Mar 1.

A composite 18F-FDG PET/CT and HER2 tissue-based biomarker to predict response to neoadjuvant pertuzumab and trastuzumab in HER2-positive breast cancer (TBCRC026)

Maeve A Hennessy  1 , Ashley Cimino-Mathews  2 , Jodi M Carter  3 , Jennifer M Kachergus  4 , Yaohua Ma  4 , Jeffrey P Leal  2 , Lilja B Solnes  2 , Vandana G Abramson  5 , Lisa A Carey  6 , Mothaffar Rimawi  7 , Jennifer Specht  8 , Anna Maria Storniolo  9 , Christos Vaklavas  10 , Ian Krop  11 , Eric Winer  11 , Rita Denbow  2 , Vincente Valero  12 , Antonio C Wolff  2 , Richard L Wahl  13 , Chiung-Yu Huang  14 , Vered Stearns  2 , E Aubrey Thompson  4 , Roisin M Connolly  15
Affiliations

A composite 18F-FDG PET/CT and HER2 tissue-based biomarker to predict response to neoadjuvant pertuzumab and trastuzumab in HER2-positive breast cancer (TBCRC026)

Maeve A Hennessy et al. Breast. 2025 Jun.

Abstract

Background: Early metabolic change on PET/CT was predictive of response to neoadjuvant trastuzumab/pertuzumab (HP) in TBCRC026. We hypothesized that a composite biomarker incorporating PET/CT and HER2 tissue-based biomarkers could improve biomarker performance.

Methods: 83 patients with estrogen receptor-negative/HER2-positive breast cancer received neoadjuvant HP alone [pathologic complete response (pCR) 22 %]. PET/CT was performed at baseline and 15 days post initiation of therapy (C1D15). Promising imaging biomarkers included ≥40 % SULmax decline between baseline and C1D15, and C1D15 SULmax ≤3. Baseline tissue-based biomarkers included HER2-enriched intrinsic subtype (72 %, 46/64; NanoString), tumor HER2 protein abundance (median log2 13.5, range log2 7.1-15.9; NanoString DSP), and HER2 3+ (83 %, 64/77; immunohistochemistry). Logistic regressions were fitted to predict pCR with HER2/PET-CT biomarkers. The C statistic assessed overall prediction power. The optimal composite score cut-off was determined by maximizing Youden's index.

Results: Factors most predictive for pCR in single predictor models included C1D15 SULmax (OR 0.43; p = 0.007, c = 0.77), % reduction in SULmax (OR 1.03, p = 0.006, c = 0.72) and tumor HER2 protein abundance (OR 1.75; p = 0.01, c = 0.76). The composite of C1D15 SULmax and % reduction in SULmax and their interaction term, had improved probability (c = 0.89 from c = 0.78), with high sensitivity (100 %) and negative predictive value (100 %). The addition of tumor HER2 protein did not further improve prediction power (c = 0.90).

Conclusion: The HER2/PET-CT biomarker had high prediction power for pCR, however was not superior to the prediction power of PET/CT alone. Non-invasive PET/CT biomarkers may facilitate a response-guided approach to neoadjuvant therapy, allowing intensification and de-intensification of treatment, pending further evaluation.

Keywords: (18)F-FDG PET/CT; Breast cancer; HER2-Biomarkers; Neoadjuvant.

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Figures

Fig. 1
Fig. 1
Receiver Operating Characteristic curve for C1D15 SULmax. Abbreviations: AUC: Area Under the Curve, NPV: Negative Predictive Value, PPV: Positive Predicitive Value.
Fig. 2
Fig. 2
Receiver Operating Characteristic curve for the composite of D15SULmax and Log 2 HER2 tumor protein abundance. Abbreviations: AUC: Area Under the Curve, NPV: Negative Predictive Value, PPV: Positive Predicitive Value.
Fig. 3A
Fig. 3A
Receiver Operating Characteristic curve for the composite of D15 SULmax and % reduction in SULmax. Abbreviations: AUC: Area Under the Curve, NPV: Negative Predictive Value, PPV: Positive Predicitive Value.
Fig. 3B
Fig. 3B
Receiver Operating Characteristic curve for the composite of D15 SULmax and % reduction in SULmax including interaction term. Abbreviations: AUC: Area Under the Curve, NPV: Negative Predictive Value, PPV: Positive Predicitive Value.
See this image and copyright information in PMC

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