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Kathryn C. Arbour



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    MA07 - Clinical Questions and Potential Blood Markers for Immunotherapy (ID 125)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Immuno-oncology
    • Presentations: 1
    • Now Available
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      MA07.02 - Early Change of dNLR Is Correlated with Outcomes in Advanced NSCLC Patients Treated with Immunotherapy (Now Available) (ID 2676)

      13:30 - 15:00  |  Author(s): Kathryn C. Arbour

      • Abstract
      • Presentation
      • Slides

      Background

      The [neutrophils/[leucocytes-neutrophils] ratio (dNLR) correlates with immune checkpoint inhibitors (ICI) outcomes in advanced non-small cell lung cancer (aNSCLC) patients. Significance of early dNLR change after the first course of ICI is unknown.

      Method

      Patients with NSCLC treated with ICI (PD(L)1+/-CTLA4) between Nov. 2012 and Jun. 2018 at 16 EU/US centers were included. A control group treated with chemotherapy (CT) only was also evaluated (NCT02105168). dNLR was collected at baseline (B) and at cycle 2 (C2). Patients were categorized as low vs high dNLR at each timepoint (defined as < vs > 3, as previously done), and the change between B and C2 (good = low at both timepoints, poor = high at both timepoints, mixed = different at each timepoint).

      Result

      1485 patients treated with ICI were analyzed. PDL1 was negative in 162 (11%), 1-49% in 178 (12%), ≥50% in 201 (14%), and missing in 944 (64%). dNLR at B and C2 did not associate with PD-L1 status.

      At baseline, dNLR was high in 509 (34%) patients and associated with worse PFS compared to those patients with low dNLR at baseline (HR 1.56, P<0.0001) and OS (HR 2.02, P<0.0001). At C2, dNLR was high in 484 (34%) and similarly associated with worse outcomes compared to patients with low dNLR at C2 (PFS HR 1.64, P<0.0001; OS HR 2.13, P<0.0001).

      Between B and C2, dNLR remained low in 804 (56%, « good ») or high in 327 (23%, « poor ») or changed in 310 pts (22%, « intermediate »). Those with a good dNLR demonstrated mPFS 5.3, mOS 18.6 mo), followed by those intermediate with mixed dNLR (mPFS 3, mOS 9.2 mo), and finally poor dNLR (mPFS 2, mOS 5mo). Outcomes were independant of PD-L1 expression (adjusted HR for PFS 1.94 for intermediate and 3.16 for poor groups, compared to good dNLR group, P<.001; adjusted HR for OS was 2.08 for intermediate and 3.67 for poor groups, P<0.001).A bootstrap tested the stability of OS/PFS prediction (P<0.001).

      In the chemo-cohort (n=173), high C1-dNLR (n=81, 47%) was not associated with OS (P=0.84).

      Conclusion

      dNLR at baseline, at cycle 2, and the change between these two timepoints associated with outcomes in patients treated with immunotherapy independent of PD-L1, but not in patients treated with chemotherapy alone. dNLR is specifically prognostic in the context of immunotherapy.

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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: 2
    • 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  |  Presenting Author(s): Kathryn C. Arbour

      • 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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      MA11.11 - STK11/LKB1 Genomic Alterations Are Associated with Inferior Clinical Outcomes with Chemo-Immunotherapy in Non-Squamous NSCLC (Now Available) (ID 2898)

      14:00 - 15:30  |  Author(s): Kathryn C. Arbour

      • Abstract
      • Presentation
      • Slides

      Background

      Addition of pembrolizumab (P) to platinum-doublet chemotherapy [carboplatin (or cisplatin) and pemetrexed (CP)] prolongs overall survival and is a standard of care (SOC) for the 1st line treatment of metastatic EGFR/ALK wild-type (wt) non-squamous non-small cell lung cancer (mnsNSCLC). Despite widespread use of the CPP regimen, molecular determinants of clinical benefit from the addition of P to CP remain poorly defined. We previously identified genomic alterations in STK11/LKB1 as a major driver of primary resistance to PD-1/PD-L1 blockade in mnsNSCLC. Here, we present updated data on the impact of STK11/LKB1 alterations on clinical outcomes with CPP chemo-immunotherapy from a large retrospective multi-institution international study.

      Method

      620 pts with mnsNSCLC and tumor genomic profiling encompassing STK11/LKB1 from 21 academic institutions in the US and Europe were included in this study. Clinical outcomes were collected for two distinct patient cohorts: a) 468 pts treated with first-line CPP (or >1st line following FDA-approved TKIs) that were alive for 14 days thereafter and b) 152 STK11/LKB1-mt pts that received CP prior to regulatory approval of CPP.

      Result

      Among 468 CPP-treated pts, STK11/LKB1 genomic alterations (N=118) were associated with significantly shorter PFS (mPFS 5.0m vs 6.8m, HR 1.45, 95% CI 1.11 to 1.91; P=0.007) and shorter OS (mOS 10.6m vs 16.7m, HR 1.46, 95% CI 1.04 to 2.07; P=0.031) compared with STK11/LKB1-wt tumors (N=350). The likelihood of disease progression as BOR to CPP differed significantly between the two groups (29.5% vs 17%, P= 0.006). Similar results were obtained when limiting the analysis to EGFR and ALK-wt tumors (N=435) (mPFS 5.0m vs 6.9m, HR 1.48, 95% CI 1.12-1.95, P=0.006 and mOS 10.6m vs 16.7m, HR 1.45, 95% CI 1.02-2.05, P=0.036). Importantly, in pts with STK11/LKB1-mt mnsNSCLC, addition of pembrolizumab to CP did not result in significant improvement of PFS (mPFS 5.0m vs 3.9m, HR 0.82, 95% CI 0.63 to 1.07, P=0.14) or OS (mOS 10.6m vs 9.1m, HR 0.93, 95% CI 0.67 to 1.30, P=0.69) compared to CP alone.

      Conclusion

      In mnsNSCLC, STK11/LKB1 alterations define a subgroup of pts with inferior clinical outcomes with CPP and lack of benefit from the addition of pembrolizumab to CP chemotherapy. Novel therapeutic strategies are required to establish effective antitumor immunity in STK11/LKB1-mutant NSCLC.

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