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Andrew J. Plodkowski



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    MA11 - Immunotherapy in Special Populations and Predictive Markers (ID 135)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Immuno-oncology
    • Presentations: 1
    • Now Available
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      MA11.01 - Multifactorial Model to Predict Response to PD-(L)1 Blockade in Patients with High PD-L1 Metastatic Non-Small Cell Lung Cancer (Now Available) (ID 2322)

      14:00 - 15:30  |  Author(s): Andrew J. Plodkowski

      • Abstract
      • Presentation
      • Slides

      Background

      High PD-L1 expression (≥50%) is a routine biomarker but is incompletely predictive, with response rates to PD-1 monotherapy only 35-45% in patients with lung cancer. Beyond PD-L1, additional individual pre-treatment variables, including clinical (smoking history, BMI), genomic (TMB, STK11, EGFR), and laboratory features (baseline dNLR), individually associate with response but have not been comprehensively examined in combination. We hypothesized that a multifactorial model incorporating routinely available clinical, pathologic, and genomic variables could improve prediction of response in high PD-L1 patients receiving first line anti-PD-(L)1 monotherapy.

      Method

      190 patients from MSKCC with advanced, PD-L1 high NSCLC (PD-L1 ≥50%) treated with PD-1 or PD-L1 inhibitor were identified and separated into training (n=134, 70%) and validation cohorts (n=56, 30%). In addition to PD-L1 expression, 39 variables were collected, including histology, clinical (age, gender, performance status, smoking, clinical trial vs standard of care treatment), molecular (TMB, EGFR, KRAS, STK11, KEAP1, TP53, ALK, ROS1, BRAF), and baseline CBC (including dNLR). Radiologic response assessments were performed according to RECIST 1.1. To distinguish responders vs. non-responders, a logistic regression classifier with an elastic net penalty was used to restrict the number of variables considered and to optimize generalizability to independent cohorts. The parameters of the model were optimized using only the training cohort and its performance was measured on the validation cohort.

      Result

      In PD-L1 high NSCLC patients treated with PD-(L)1 blockade, the ORR was 43%. In the training cohort, 5 features (PD-L1 expression, current smoking status, lymphocyte count, platelets, total WBC) associated with response . Three features (EGFR mutation, STK11 mutation, standard of care treatment) associated with lack of response. TMB was not predictive within this selected PD-L1 high cohort. In the training cohort, the eight identified features were used to develop a multifactorial model which improved BOR prediction (AUC 0.83) compared to PD-L1 alone (AUC 0.65), p=0.02. Improved performance of the model was confirmed in the validation cohort (AUC 0.66 for multifactorial model vs. AUC 0.52 for PD-L1 alone).

      Conclusion

      Among patients with high PD-L1 expression, multiple clinical, molecular, and baseline laboratory features impact response to PD-(L)1 monotherapy. The addition of these routinely available variables to PD-L1 in a multifactorial model improves prediction of response to PD-(L)1 blockade in patients with high PD-L1. This approach may help further stratify patients within the PD-L1 high population and identify which patients are likely to benefit from PD-(L)1 monotherapy vs those who should consider chemotherapy + immunotherapy.

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    P1.14 - Targeted Therapy (ID 182)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Targeted Therapy
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.14-50 - A Phase 2 Trial of Cabozantinib in ROS1-Rearranged Lung Adenocarcinoma (Now Available) (ID 2753)

      09:45 - 18:00  |  Author(s): Andrew J. Plodkowski

      • Abstract
      • Slides

      Background

      To date, no ROS1 inhibitor is approved for the treatment of ROS1-rearranged lung cancers after progression on crizotinib. Progression on crizotinib can be mediated by the acquisition of ROS1 kinase domain mutations (e.g. ROS1G2032R or ROS1D2033N). Cabozantinib is a highly potent ROS1 tyrosine kinase inhibitor that has superior activity over lorlatinib against these mutations. We evaluated the activity of cabozantinib in patients with ROS1-rearranged lung cancers on a phase 2 trial.

      Method

      In this single-center, open-label, Simon two-stage, phase 2 study, eligible patients had ROS1-rearranged unresectable/metastatic non-small cell lung cancer, a Karnofsky performance status >70%, and measurable disease. ROS1 fusion was identified by local testing in a CLIA-compliant environment. Cabozantinib was dosed at 60 mg once daily. The primary endpoint was objective response (RECIST v1.1). In the first stage of this trial, 1 response was required to move to the second stage. Secondary endpoints included safety.

      Result

      Six patients received cabozantinib in the ongoing first stage of this study. All patients had >1 prior ROS1 inhibitor. The median age was 59 years; all were never smokers. The best response to therapy was: 1 partial response (-92%, confirmed), 1 unconfirmed partial response (-31%), and 4 stable disease. All patients had disease regression (-7 % to -92%); no patients had primary progressive disease. The only patient with a confirmed partial response was a patient whose cancer acquired a ROS1D2033N solvent front mutation after crizotinib. None of the other five ROS1 inhibitor pre-treated patients (who did not have a confirmed response) had a known on-target acquired resistance mutation in their cancer. After progression on cabozantinib (9.1 months after therapy initiation), the patient whose cancer harbored the ROS1D2033N mutation acquired a METD1228N kinase domain mutation on paired sequencing of pre-cabozantinib and post-progression tumor. The most common grade 3 treatment-related adverse events were hypertension (50%), and mucositis, palmar-plantar erythrodysesthesia, and hypophosphatemia (each in 17%). Most patients (83%) required a dose reduction.

      Conclusion

      Cabozantinib can re-establish disease control in ROS1-rearranged lung cancers after progression on a prior ROS1 inhibitor. The first stage of this ongoing trial met its prespecified endpoint for efficacy to move into the second stage. Response was only observed in the setting of a known ROS1 kinase domain resistance mutation.

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