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Pellini, B.

Publications and source records attributed to Pellini, B..

2 recordsLinked to original sources

Pharmacokinetic Acceleration via CYP3A4 Hyperactivation as a Clinically Actionable Mechanism of Targeted Therapy Resistance in NSCLC

Resistance of cancers to targeted therapies is traditionally framed as a tumor-intrinsic phenomenon, mediated by tumor cell-intrinsic or microenvironmental mechanisms. Here, we identify a tumor-extrinsic, systemic resistance mechanism resulting from hyperactivation of the hepatic cytochrome P450 enzyme, CYP3A4. This tumor-extrinsic resistance mechanism can function independently of, or in tandem with, tumor-intrinsic resistance. Focusing on experimental mouse models of targetable lung cancer, we find that xenobiotic-mediated induction of CYP3A4 results in accelerated drug metabolism and a drastic reduction in systemic and tumor-drug exposure in vivo. CYP3A4 activation can be triggered by chemically unrelated xenobiotics, leading to resistance to a wide range of targeted therapies, including ALK, EGFR, and KRASG12C inhibitors. Retrospective analysis of clinical cohorts suggests that variability in CYP3A4 activity might be a major contributor to variability in clinical outcomes. While higher CYP3A4 activity leads to sub-therapeutic tumor drug exposure and shorter progression-free survival, reduced drug metabolism is expected to result in supratherapeutic exposure and increased systemic toxicity. To address the consequences of abnormal CYP3A4 activity, we utilized mathematical modeling to demonstrate that drug concentrations can be restored through the optimization of dosing amounts and intervals. Further, we show that tumor sensitivity to targeted therapies can be rescued through pharmacological inhibition of CYP3A4. Our findings establish systemic metabolic variability as a bona fide resistance and toxicity driver, providing a translational framework for personalized dosing to maximize both safety and efficacy.

cancer biology↗

Trastuzumab deruxtecan combination strongly enhances responses and overcomes sotorasib resistance in KRASG12C-mutant NSCLC

IntroductionRecent advances in the treatment of KRAS-mutant non-small cell lung cancer (NSCLC) have led to the development of KRASG12C inhibitors, such as sotorasib and adagrasib. However, resistance and disease progression remain significant challenges. In this study, we investigated the therapeutic potential of combining trastuzumab deruxtecan (T-DXd), an anti-HER2 antibody-drug conjugate, with sotorasib in KRASG12C-mutant NSCLC, while also evaluating HER2 expression in NSCLC samples. MethodsThe HER2 expression dependence of xenograft responses to sotorasib, T-DXd, and their combination was evaluated in therapy-naive and sotorasib-treated tumors by immunohistochemistry (IHC). Also, we analyzed 191 clinical (pre- or on-treatment) and rapid autopsy (post-treatment) samples from 31 patients with driver-positive and driver-negative advanced stage NSCLC, assessing HER2 expression using interpretation guidelines developed for breast cancer (BC) and gastroesophageal adenocarcinoma (GEA). ResultsIn the majority of preclinical models, including sotorasib-resistant tumors, the sotorasib-T-DXd combination induced stronger and more durable responses compared to monotherapies. The strong effect of the combination therapy was likely attributable to sotorasib-induced adaptive HER2 upregulation; stronger HER2 expression in sotorasib-treated tumors was linked with stronger responses. Although HER2 expression was higher in samples from patients with KRASG12C-mutant NSCLC compared to NSCLC with other driver mutations or no drivers, the difference was not statistically significant. HER2 IHC score discrepancy was also observed between BC and GEA interpretation guidelines. ConclusionsOur results support the potential clinical utility of the sotorasib-T-DXd combination, including tumors with intrinsic and acquired resistance to sotorasib monotherapy. Since the strengths of the responses depend on HER2 expression levels, successful clinical implementation necessitates optimizing patient selection. Our results highlight the complexities of accurate HER2 interpretation in NSCLC and highlight the need for standardized testing methods.

cancer biology↗