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Mini Oral session 3

LBA2 - Assessment of Ki67 and FOXC1-based response predictor tracking proliferation and plasticity as a complementary diagnostic for neoadjuvant Olaparib+Paclitaxel+Darvalumab in primary triple negative breast cancer: retrospective analysis of the I-SPY2 Trial

Date

05 May 2022

Session

Mini Oral session 3

Topics

Cytotoxic Therapy;  Tumour Immunology;  Targeted Therapy;  Clinical Research;  Immunotherapy;  Cancer Biology;  Translational Research;  Pathology/Molecular Biology

Tumour Site

Breast Cancer

Presenters

Partha Ray

Citation

Annals of Oncology (2022) 33 (suppl_3): S123-S147. 10.1016/annonc/annonc888

Authors

P.S. Ray, T. Ray, R. Hussa

Author affiliations

  • Onconostic Technologies, Evanston/US

Resources

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Abstract LBA2

Background

Immune checkpoint inhibitors (ICIs) have shown clinical efficacy when administered in combination with neoadjuvant chemotherapy (NACT) for the treatment of triple negative breast cancer (TNBC). However, suitable complementary diagnostics to help guide and tailor treatment recommendations are still lacking. Ki67 is a well accepted and routinely used marker that tracks proliferation and has been shown to predict efficacy of neoadjuvant chemotherapy. Forkhead Box C1 (FOXC1), a transcriptional driver of cell plasticity/partial EMT/metastasis/immune evasion has proven prognostic value, but remains of uncertain predictive value. We sought to evaluate the potential of a Ki67 and FOXC1-based response predictor as a possible complementary diagnostic for a neoadjuvant regimen comprising of a PARP inhibitor (Olaparib), a Taxane chemotherapeutic (Paclitaxel) and an ICI of the PDL1 class (Durvalumab) in patients diagnosed with primary TNBC.

Methods

41 Pre-NACT tumor biopsy MKI67 and FOXC1 mRNA expression values were retrospectively obtained from TNBC patients who had been enrolled and treated in the I-SPY2 clinical trial (Durvalumab arm: 21, Control arm: 20) and correlated with the rate of observed pathologic complete response (pCR). The area under the curve (AUC) of each model was calculated and used to determine suitable cutoff values to maximize Negative Predictive Value (NPV) and Sensitivity for pCR prediction.

Results

Predicted responders in the Durvalumab Arm had a pCR rate of 75% vs 0% in predicted non-responders, p=0.00013) with NPV and sensitivity of 100%, accuracy of 85.7%, Odds Ratio 51.57 (2.33-1141.00,95% CI). The strategy was not predictive in the Control Arm. Multiple logistic regression pCR-predictive models may further improve predictive accuracy.

Conclusions

Complementary diagnostic role of pre-NACT MKI67 + FOXC1 expression merits prospective clinical trial evaluation in TNBC treated with neoadjuvant combination regimens that include ICIs. This may help to optimize achieved pCR rates and extend disease-free survival in patients diagnosed with TNBC.

Legal entity responsible for the study

The authors

Funding

Has not received any funding

Disclosure

P.S. Ray: Financial Interests, Institutional, Advisory Board: Onconostic Technologies. T. Ray: Financial Interests, Institutional, Full or part-time Employment: Onconostic Technologies. R. Hussa: Financial Interests, Institutional, Member of the Board of Directors: Onconostic Technologies.

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