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Xinru Mao
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EP1.12 - Small Cell Lung Cancer/NET (ID 202)
- Event: WCLC 2019
- Type: E-Poster Viewing in the Exhibit Hall
- Track: Small Cell Lung Cancer/NET
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 08:00 - 18:00, Exhibit Hall
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EP1.12-10 - Molecular Characterization of NSCLC-Like and SCLC-Like Subsets in Chinese Pulmonary Large-Cell Neuroendocrine Carcinoma (LCNEC) (Now Available) (ID 1341)
08:00 - 18:00 | Author(s): Xinru Mao
- Abstract
Background
LCNEC is an aggressive, biologically heterogenous carcinoma which can be molecularly characterized as SCLC-like and NSCLC-like. Accurate distinction of molecular subset is of major clinical relevance since it may guide treatment choices in LCNEC. Here we determined the genomic characteristics of the two LCNEC subsets in a Chinese cohort to clarify their correlations with traditional lung cancer histologies.
Method
FFPE samples from 31 LCNECs were sequenced using a 520-cancer-related gene panel, with an average sequencing depth of 1385X. Comparative mutational analysis was conducted between NSCLC-like LCNECs from our cohort and adenocarcinomas from TCGA dataset
Result
Despite similar clinical features in terms of stage and age at diagnosis, NSCLC-like (42%, 13/31) and SCLC-like (32%, 10/31) subsets from LCNEC displayed distinct molecular characteristics. NSCLC-like subset harbored significant higher mutation frequencies of STK11, KEAP1 and FAT3 (53.8%, 38.5% and 38.5%, p=.007, .046 and .046), while SCLC-like subset was characterized by highly mutated RB1 (100%, p<.001) and PTEN (50%, p=.007). Compared with TCGA adenocarcinomas, NSCLC-like LCNEC displayed more frequent mutations in TP53, STK11, APC, KMT2D and SMARCA4 (76.9%, 53.8%, 30.8%, 30.8% and 23.1%; p=.043, .004, .045, .005 and .049). In addition, potential targetable alterations were present in 46.2% (6/13) pts of NSCLC-like subset. For those advanced stage pts, 2/5 NSCLC-like and 5/5 SCLC-like pts received relevant chemotherapy according to their molecular characteristics. The clinical outcomes of these pts are still under follow-up.
Conclusion
This study demonstrates the distinct molecular features between NSCLC-like and SCLC-like subsets, and highlights the predominant genomic similarity and separate entities between NSCLC-like LCNEC with adenocarcinoma. Given the evidence that genomic profiling may aid in informing treatment decisions for pts with LCNEC, our study indicates that, based on accurate molecular typing, 46.2% NSCLC-like pts may benefit from potential targeted therapy and the rest of them may be more suitable to receive NSCLC-chemotherapy
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OA03 - Systemic Therapies for SCLC: Novel Targets and Patients' Selection (ID 121)
- Event: WCLC 2019
- Type: Oral Session
- Track: Small Cell Lung Cancer/NET
- Presentations: 1
- Now Available
- Moderators:Christine Lee Hann, Makoto Nishio
- Coordinates: 9/08/2019, 13:30 - 15:00, Hilton Head (1978)
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OA03.05 - Characterization of Genomic Alterations in Chinese LCNEC and SCLC via Comprehensive Genomic Profiling (Now Available) (ID 1486)
13:30 - 15:00 | Author(s): Xinru Mao
- Abstract
- Presentation
Background
LCNEC and SCLC are aggressive neuroendocrine carcinomas with overlap in clinical, histopathologic, morphologic and genomic features. Differential molecular features between the two subtypes have not been well elucidated, contributing the uncertainty for optimal clinical strategy for each subtype. Here we interrogated the genomic characteristics in LCNEC as compared to SCLC along with their histologically related subtypes: carcinoids and atypical carcinoids via comprehensive genomic profiling.
Method
FFPE samples from 31 LCNECs, 35 SCLCs, 14 carcinoids and 22 atypical carcinoids were sequenced in a CLIA-certified sequencing laboratory using 520-cancer-related gene panel, with an average sequencing depth of 1385X.
Result
Comparative mutational analysis revealed that both LCNEC and SCLC sub-cohorts displayed higher rate of TP53 alterations than that of carcinoid (p<0.001, p<0.001). SCLC patients harbored more RB1 and PIK3CA mutations than LCNECs (p<0.001, p=0.014) and carcinoids (p<0.001, p=0.018). In addition, mutation frequencies of LRP1B, FAT1, PRKDC, PIK3CA, NOTCH1, SPTA1 and EPHA3 in SCLC were significantly higher than that in carcinoid. Mutations in TP53 and RB1 occurred concurrently in 83% (29/35) SCLC patients, whereas in only 32.3% (10/31) LCNECs.（Fig.1） We further investigated the distribution of mutations across KEGG pathways and found that mutation frequencies in both HIF-1 and Notch signaling pathways were lower in LCNEC than SCLC (p=0.032, p=0.025). Copy number variation (CNV) analysis revealed that LCNEC and SCLC had comparable CNVs which were significantly higher than carcinoid (p<0.001, p<0.001) and atypical carcinoid (p=0.010, p=0.028). TMB analysis also revealed a comparable TMB status of LCNEC (12.7/Mb) and SCLC (11.9/Mb), and relatively lower TMB in both carcinoid (2.4/Mb, p<0.001, p<0.001) and atypical carcinoid (5.6/Mb, p=0.003, p=0.009) than LCNEC and SCLC.
Conclusion
We demonstrated the differential genomic characteristics in the four subtypes of neuroendocrine carcinomas. Compared with SCLC, LCNEC has lower mutation frequencies in RB1, PIK3CA, as well as HIF-1 and Notch signaling pathways. In addition, LCNEC and SCLC had comparable CNV and TMB status, which significantly higher than that of carcinoids and atypical carcinoid.
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P1.01 - Advanced NSCLC (ID 158)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Advanced NSCLC
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.01-92 - Underlying Mechanisms That Potentially Affect Prognosis to EGFR-TKI in EGFR-Positive Patients with Non-Small Cell Lung Cancer (Now Available) (ID 1158)
09:45 - 18:00 | Author(s): Xinru Mao
- Abstract
Background
Conventional detection methods cannot fully reflect the overall landscape of tumor, which misguide the use of targeted drugs and lead to poor prognosis. Here, based on the results of genomic profiling obtained by NGS, we interrogate the underlying mechanism of differential response to EGFR-TKI in EGFR-positive patients with lung cancer.
Method
207 patients with advanced non-small cell lung cancer (NSCLC) carrying EGFR_L858 or 19del (identified by conventional methods) from 7 clinical trials (such as FLAURA, CTONG1405 and CTONG1509) were enrolled. 457 plasma (n=335) or tissue (n=122) samples from baseline and follow-up points of the cohort were profiled using 168-/520-cancer-related gene panels. Molecular characteristics in patients with rapid progression (PFS<3 months, n=10) and durable response (PFS>24 months, n=6) to EGFR-TKI treatment were analyzed.
Result
The accuracy of NGS and conventional methods for identifying EGFR driver mutations in tissue samples was 97.1%, and that of driver mutation detection in plasma and tissue samples was 81.9%. Using NGS, several alterations at baseline that may potentially affect prognosis were identified, in addition to EGFR oncogenic mutations revealed by traditional methods. Ten patients progressed rapidly on EGFR-TKI therapy (no response, n=4; stable disease, SD, n=2; partial response, PR, n=4). Of the 4 patients who did not respond to EGFR-TKI, ALK fusion, NTRK fusion, MET amplification (METamp) and EGFR_E709A were identified at baseline using NGS. Of the 2 patients received SD, NGS revealed that one case carried mutations in TP53, PMS2, PALB2 and ARID1A, while another case carried TP53_R213* and ERBB2amp. As to the 4 patients achieved PR, NGS results showed that one patient carried TP53_R342* and EGFR_L62R; one patient with CDK4amp and RET pathogenic mutation; one patient had TP53_V216L, CDK4amp, ERBB2amp and EGFRamp; and another patient harbored CDK4amp. In contrast, of the 6 patients achieved durable response to EGFR-TKI, NGS revealed that 4 patients did not carry any alteration or well-established factor associated with poor prognosis other than EGFR driver mutations. The other 2 patients with TP53 mutation and EGFRamp received combination treatment of EGFR TKI and chemotherapy.
Conclusion
NGS had good consistency with conventional methods in identifying EGFR-driver mutation. Compared with traditional methods, NGS can represent more comprehensive landscape of tumor and provide more reliable guidance for treatment. For patients with EGFR-driver mutations along with tumor suppressor or oncogene mutations, combination therapy of TKI and chemotherapy might be a better option than TKI alone. In addition, we revealed that EGFR_E709A and EGFR_L62R may be potential resistance mechanisms of EGFR TKI.
