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L. Gay
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MA 05 - Immuno-Oncology: Novel Biomarker Candidates (ID 658)
- Event: WCLC 2017
- Type: Mini Oral
- Track: Immunology and Immunotherapy
- Presentations: 1
- Moderators:Yoichi Nakanishi, P. Mitchell
- Coordinates: 10/16/2017, 15:45 - 17:30, Room 303 + 304
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MA 05.02 - STK11/LKB1 Loss of Function Genomic Alterations Predict Primary Resistance to PD-1/PD-L1 Axis Blockade in KRAS-Mutant NSCLC (ID 10367)
15:45 - 17:30 | Author(s): L. Gay
- Abstract
- Presentation
Background:
The genomic landscape of primary resistance to PD-1 blockade in lung adenocarcinoma (LUAD) is largely unknown. We previously reported that co-mutations in STK11/LKB1 (KL) or TP53 (KP) define subgroups of KRAS-mutant LUAD with distinct therapeutic vulnerabilities and immune profiles. Here, we present updated data on the clinical efficacy of PD-1/PD-L1 inhibitors in co-mutation defined KRAS mutant and wild-type LUAD patients and examine the relationship between genetic alterations in individual genes, tumor cell PD-L1 expression and tumor mutational burden (TMB) using cohorts form the SU2C/ACS Lung Cancer Dream Team and Foundation Medicine (FM).
Method:
The cohorts included 924 LUAD with NGS (FM cohort) and 188 patients with KRAS non-squamous NSCLC (SU2C cohort) who received at least one cycle of PD-1/PD-L1 inhibitor therapy and had available molecular profiling. Tumor cell PD-L1 expression was tested using E1L3N IHC (SU2C) and the VENTANA PD-L1 (SP142) assay (FM). TMB was defined as previously described and was classified as high (TMB-H), intermediate (TMB-I) or low (TMB-L).
Result:
188 immunotherapy-treated (83.5% nivolumab, 11.7% pembrolizumab, 4.8% anti-PD1/PD-L1 plus anti-CTLA-4) pts with KRAS-mutant NSCLC were included in the efficacy analysis. The ORR differed significantly between the KL (8.8%), KP (35.9%) and K-only sub-groups (27.3%) (P=0.0011, Fisher’s exact test). KL LUAC exhibited significantly shorter PFS (mPFS 1.8m vs 2.7m, HR=0.53, 95% CI 0.34-0.84, P<0.001, log-rank test) and OS (mOS 6.8m vs 15.6m, HR 0.53, 95% CI 0.34 to 0.84, P=0.0072, log rank test) compared to KRAS-mutant NSCLC with wild-type STK11. Loss-of function (LOF) genetic alterations in STK11 were the only significantly enriched event in PD-L1 negative, TMB-I/H compared to PD-L1 high positive (TPS≥50%), TMB-I/H tumors in the overall FMI cohort (Bonferroni adjusted P=2.38x10[-4], Fisher’s exact test) and among KRAS-mutant tumors (adjusted P=0.05, Fisher’s exact test) . Notably, PD-1 blockade demonstrated activity among 10 PD-L1-negative KP tumors, with 3 PRs and 4SDs recorded. In syngeneic isogenic murine models PD-1 blockade significantly inhibited the growth of Kras mutant tumors with wild-type LKB1 (K), but not those with LKB1 loss (KL), providing evidence that LKB1 loss can play a causative role in promoting PD-1 inhibitor resistance.
Conclusion:
Loss of function genomic alterations in STK11 represent a dominant driver of de novo resistance to PD-1/PD-L1 blockade in KRAS-mutant NSCLC. In addition to tumor PD-L1 status and tumor mutational burden precision immunotherapy approaches should take into consideration the STK11 status of individual tumors.
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P1.01 - Advanced NSCLC (ID 757)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Advanced NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 10/16/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P1.01-031 - Utilization and Timing of Foundation Medicine (FMI) Testing in U.S. Advanced Non-Small Cell Lung Cancer (aNSCLC) Patients (ID 8529)
09:30 - 16:00 | Author(s): L. Gay
- Abstract
Background:
Actionable insights generated by FMI’s hybrid capture-based next-generation sequencing (NGS) comprehensive genomic profiling services are increasingly important for navigating cancer care in aNSCLC patients. FMI and other NGS platforms support treatment decisions by detecting a variety of genetic alterations implicated in oncogenesis. We describe: 1) the characteristics of aNSCLC patients receiving FMI testing and 2) the utilization patterns and timing of FMI testing in relation to treatment and other molecular tests using a real world oncology electronic health record (EHR) database.
Method:
Flatiron Health has a longitudinal, demographically and geographically diverse database containing EHR data, reflecting routine clinical practice, from over 265 cancer clinics in the US. Inclusion criteria were aNSCLC diagnosis and ≥2 clinic visits within the Flatiron network on or after January 1, 2011. Data pertaining to molecular testing was available on 5 biomarkers (EGFR, ALK, KRAS, ROS1, PDL1) and used to identify 3 mutually exclusive testing groups: FMI, other NGS and non-NGS.
Result:
As of March 31, 2017, the aNSCLC cohort included 33,473 patients. Of 1,395 patients with FMI testing, 738 (53%) also had ≥1 non-FMI test (43% EGFR, 40% ALK, 20% ROS1, 17% PDL1, 16% KRAS). In FMI-tested patients, 45% received results before starting a first line of therapy (vs. 57% of other NGS tested and 79% of non-NGS tested patients). Table 1 details patient and testing characteristics for FMI tested patients, along with first treatments received after FMI testing.Table 1. Patient, Testing and Treatment Characteristics for Patients Receiving FMI testing FMI Other NGS Non-NGS No tests Patient count (%) (Total N=33,473) 1,395 (4%) 1,946 (6%) 17,002 (51%) 13,128 (39%) Patient and Testing characteristics Age at aNSCLC diagnosis (years) (median, [IQR]) 67 [59, 73] 68 [60, 75] 69 [61, 76] No history of smoking 335 (24%) 376 (19%) 2,731 (16%) Squamous cell histology 194 (14%) 195 (10%) 1,532 (9%) No. of tests 1 1,224 (88%) 1,587 (82%) n/a ≥2 171 (12%) 359 (18%) Year of testing[a] <2011 0 (0%) 1 (0%) 137 (1%) 2011 0 (0%) 5 (0%) 1,215 (7%) 2012 2 (0%) 16 (1%) 2,368 (14%) 2013 59 (4%) 117 (6%) 2,894 (17%) 2014 185 (13%) 235 (12%) 3,263 (19%) 2015 377 (27%) 560 (29%) 3,099 (18%) 2016 634 (45%) 818 (42%) 2,921 (17%) 2017 (through March 31, 2017) 123 (9%) 186 (10%) 670 (4%) Number and Timing of Other Tests in patients with an FMI test FMI tested prior to start of 1st LoT FMI tested during 1st and before start of 2nd LoT FMI tested during 2nd and before start 3[rd] LoT FMI tested during or after 3rd LoT Patient count (%) (Total N=1,386)[b] 626 (45%) 489 (35%) 157 (11%) 114 (8%) Other tests conducted before FMI testing[c,d] ALK 111 (18%) 188 (38%) 100 (64%) 86 (75%) EGFR 133 (21%) 204 (42%) 110 (70%) 86 (75%) KRAS 51 (8%) 60 (12%) 25 (16%) 29 (25%) PDL1 41 (7%) 44 (9%) 23 (15%) 22 (19%) ROS1 53 (9%) 92 (19%) 40 (26%) 32 (28%) Other tests conducted after FMI testing[c,d] ALK 48 (8%) 34 (7%) 8 (5%) 3 (3%) EGFR 53 (9%) 38 (8%) 9 (6%) 5 (4%) KRAS 35 (6%) 30 (6%) 7 (5%) 2 (2%) PDL1 49 (8%) 33 (7%) 7 (5%) 3 (3%) ROS1 37 (6%) 28 (6%) 6 (4%) 1 (1%) First Treatment immediately following FMI testing Patient count (%) (Total N=802)[e] 424 (68%) 252 (52%) 77 (49%) 49 (43%) NCCN-recommended targeted treatment for aNSCLC (N=196)[f,i] 105 (25%) 56 (22%) 20 (26%) 15 (31%) NCCN-recommended immunotherapy (N=227)[g,i] 82 (19%) 110 (44%) 22 (29%) 13 (27%) Non NCCN-recommended targeted treatment for aNSCLC (N=13)[h,i] 1 (0%) 7 (3%) 1 (1%) 4 (8%) [a] If a patient had more than 1 FMI test, the year of the first FMI test is shown; similarly if a patient had more than 1 other NGS (ie. non-FMI), the first test is shown. If an FMI tested patient had both an FMI and non-FMI NGS test, the year of the first FMI test is shown; similarly if a other NGS tested patient has both an other NGS and non-NGS test, the year of the first other NGS test is shown. [b] 9 patients where the date of FMI test (ie. test result date or sample collection date) in relation to dates of treatment and line of therapy were missing or unknown are not included in this table. [c] Total of 738 patients (53% of all FMI tested patients) also received a non-FMI test in addition to their FMI test. [d] Percentages may not add up to 100% because of patients received more than one test. [e] Based on 802 total patients who received FMI testing and where treatment data was reported following their FMI test. [f ]NCCN-recommended targeted treatments received included the following: erlotinib (N=63), gefitinib (N=10), afatinib (N=56), crizotinib (N=36), ceritinib (N=4), alectinib (N=8), trastuzumab (N=1), vemurafenib (N=2), dabrafenib (N=2), osimertinib (N=19), cabozantinib (N=0); it may be possible for patients to receive regimens containing more than 1 NCCN-recommended targeted treatment. [g] NCCN-recommended immunotherapy (immune checkpoint inhibitors) received included the following: nivolumab (N=189), pembrolizumab (N=29), atezolizumab (N=9); it may be possible for patients to receive regimens containing more than 1 NCCN-recommended immunotherapy. In addition, 2 patients received ipilimumab, an immune checkpoint inhibitor currently not recommended by NCCN for aNSCLC. [h] Non NCCN-recommended targeted treatments received included the following: olaparib (N=2), necitumumab (N=2), cetuximab (N=2), palbociclib (N=1), pazopanib (N=1), temsirolimus (N=1), trametinib (with no dabrafenib) (N=4) ; it may be possible for patients to receive regimens containing more than 1 non NCCN-recommended targeted treatment. [i] Based on the National Comprehensive Cancer Network (NCCN) guidelines for NSCLC, version 6.2017 LoT: line of therapy as recorded in the Flatiron data, IQR: inter-quartile range. Patients with missing data are excluded from the table; Percentages are rounded to closest decimals.
Conclusion:
Patients with FMI testing tended to be younger, non-smokers, and have squamous histology compared to patients receiving non-FMI tests. Nearly 50% of all FMI testing occurred prior to first treatment. Patients receiving FMI testing earlier were less likely to have a non-FMI biomarker test beforehand. Regardless of when FMI testing occurred, ~20-30% of patients received a NCCN-recommended targeted therapy immediately after the FMI test.
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P2.02 - Biology/Pathology (ID 616)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P2.02-016 - Pulmonary Sarcomas: A Comprehensive Genomic Profiling Study (ID 10169)
09:30 - 16:00 | Author(s): L. Gay
- Abstract
Background:
Pulmonary sarcomas (PSRC) are uncommon primary thoracic malignancies that are often clinically aggressive. Comprehensive genomic profiling (CGP) can identify biomarkers for both targeted and immunotherapy. We used CGP to analyze novel treatment options for patients with advanced PSRC.
Method:
CGP using hybridization-captured, adaptor ligation-based libraries for up to 406 genes plus select introns from 31 genes frequently rearranged in cancer was performed on 19 PSRC; 15 cases also underwent RNA sequencing for enhanced fusion detection in 265 of these genes. All classes of genomic alteration (GA) were assessed simultaneously: base substitutions, indels, rearrangements, and copy number changes. Clinically relevant GA (CRGA) are GA associated with drugs on the market or under evaluation in clinical trials. Tumor mutational burden (TMB) was determined on 1.1 Mb of sequenced DNA.
Result:
In this cohort were 10 sarcoma NOS, 5 pulmonary artery intimal sarcomas, 2 pleomorphic/MFH sarcomas, 1 primary IMT, and 1 primary SFT, including 1 stage I, 1 stage II, 9 stage III and 8 stage IV tumors. Patient median age was 52 years (range 33–81 years), with 7 female and 12 male patients. The mean GA per sarcoma was 5.7. Notable alterations not presently considered actionable affected TP53 (53%), CDKN2A (32%), CDKN2B (27%), and RB1 (21%). CRGA alterations were detected in PDGFRA, RICTOR, CDK4 and KIT (11% each), and EGFR, TSC2, ALK and BRAF (5% each); 9 (47%) PSRC featured ≥1 CRGA. An ALK fusion was detected in an IMT localized only to the lung and diagnosed as a primary lesion. Inactivation of SMARCA4 through mutation and loss of heterozygosity was found in 1 case. Mean TMB was 8.65 mutations/Mb (16% had TMB >10 mut/Mb, 11% had TMB >20 mut/Mb); cases with TMB >20 mut/Mb lacked characteristically targetable CRGA. All samples tested for MSI (n=7) were microsatellite stable. Assessment of therapeutic intervention and responses is ongoing.
Conclusion:
PSRC is an extremely rare primary lung malignancy characterized by a relatively high frequency of GA. CGP identified various potentially targetable alterations in this small series, particularly driver mutations or fusions in tyrosine kinases and cell cycle regulatory genes. Furthermore, characteristic genomic profiles can provide diagnostic insight, as for SMARCA loss or ALK fusions. This study also identified a significant number of PSRC with intermediate or high TMB, indicating potential immunotherapy options for these patients. Further study of CGP to help manage patient care and minimize suffering from this rare pulmonary malignancy appears warranted.
