| Literature DB >> 32759236 |
Marco Mazzotta1, Marco Filetti2, Mario Occhipinti3, Daniele Marinelli2, Stefano Scalera4, Irene Terrenato5, Francesca Sperati6, Matteo Pallocca4, Francesco Rizzo2, Alain Gelibter3, Andrea Botticelli3, Giorgia Scafetta7, Arianna Di Napoli7, Eriseld Krasniqi1, Laura Pizzuti1, Maddalena Barba1, Silvia Carpano1, Patrizia Vici1, Maurizio Fanciulli4, Francesca De Nicola4, Ludovica Ciuffreda4, Frauke Goeman8, Ruggero De Maria9,10, Andrea Vecchione7, Raffaele Giusti11, Gennaro Ciliberto12, Paolo Marchetti2,3, Marcello Maugeri-Saccà13.
Abstract
BACKGROUND: Immune checkpoint inhibitors (ICIs) provide significant survival benefits in non-small cell lung cancer (NSCLC). Nevertheless, while some patients obtain a prolonged benefit, a non-negligible fraction of patients experiences an ultrarapid disease progression. Identifying specific molecular backgrounds predicting opposite outcomes is instrumental to optimize the use of these agents in clinical practice.Entities:
Keywords: immunotherapy; lung neoplasms; tumor biomarkers
Year: 2020 PMID: 32759236 PMCID: PMC7409965 DOI: 10.1136/jitc-2020-000946
Source DB: PubMed Journal: J Immunother Cancer ISSN: 2051-1426 Impact factor: 13.751
Figure 1Characteristics of the patients. Panel A: study flow diagram. Panel B: OncoPrint illustrating the mutational status of NOTCH1-3 and homologous repair (HR) genes in the Rome cohort. The red box within the OncoPrint highlights the co-occurrence pattern (patient 1–4: co-occurring mutations; patient 5: NOTCH-only mutation). In the upper section, the OncoPrint treatment-related features are reported (progression-free survival (PFS) time and status, treatment administered, tumor mutation burden, programmed death-ligand 1 (PD-L1) expression, hyperprogressive disease (HPD), line of treatment). In the lower section, baseline characteristics (gender, histology, smoking history and number of metastatic sites) are summarized. ICI, immune checkpoint inhibitor; NSCLC, non-small cell lung cancer; TMB, tumor mutation burden.
Characteristics of patients with NSCLC treated with ICIs included in the Rome cohort (n=35)
| Characteristics | N (%) |
| Age at diagnosis | |
| Median (IQR) | 64.08 (42.20–75.61) |
| Gender | |
| Male | 21 (60.0) |
| Female | 14 (40.0) |
| Histology | |
| LAC | 27 (77.1) |
| LSCC | 8 (22.9) |
| Smoking status | |
| Ever | 30 (85.7) |
| Never | 5 (14.3) |
| Performance status | |
| 0 | 26 (74.3) |
| 1 | 9 (25.7) |
| ICI line of treatment | |
| First | 19 (54.3) |
| Second | 14 (40.0) |
| Third | 2 (5.7) |
| PD-L1 (IHC) | |
| ≥50% | 16 (45.7) |
| 1%–49% | 10 (28.6) |
| negative | 9 (25.7) |
| TMB | |
| Low | 9 (25.7) |
| Intermediate | 21 (60.0) |
| Not available | 5 (14.3) |
| Treatment | |
| Pembrolizumab | 24 (68.6) |
| Atezolizumab | 7 (20.0) |
| Nivolumab | 4 (11.4) |
| HPD | |
| No | 29 (82.9) |
| Yes | 6 (17.1) |
HPD, hyperprogressive disease; ICI, immune checkpoint inhibitor; IHC, immunohistochemistry; LAC, lung adenocarcinoma; LSCC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer; PD-L1, programmed death-ligand 1; TMB, tumor mutational burden.
Figure 2Relationship between the NOTCHmut/HRmut signature and progression-free survival (PFS) in the MSKCC/POPLAR/OAK metadataset. Panel A and B: Kaplan-Meier survival curves of PFS comparing NOTCHmut/HRmut-positive versus NOTCHmut/HRmut-negative cases (ICI metadataset: MSKCC/POPLAR/OAK). Panel C: bar chart summarizing the association between the NOTCHmut/HRmut predictor and metastatic burden (number of metastatic sites) in the whole OAK/POPLAR cohort (atezolizumab or docetaxel). Panel D: forest plot illustrating univariate Cox regression analyses for PFS in the MSKCC and OAK/POPLAR studies (red box), and the multivariate Cox regression model in the metadataset (MSKCC/POPLAR/OAK, blue box). ICI, immune checkpoint inhibitor; MSKCC, Memorial Sloan Kettering Cancer Center; tTMB, tissue-based tumor mutation burden; bTMB, blood-based tumor mutation burden.
Figure 3Relationship between the NOTCHmut/HRmut signature and overall survival (OS). Panel A and B: Kaplan-Meier survival curves of OS comparing NOTCHmut/HRmut-positive versus NOTCHmut/HRmut-negative cases in the ICI metadataset (MSKCC/POPLAR/OAK). Panel C: forest plot illustrating the multivariate Cox regression model for OS in the ICI metadataset. Panel D: Kaplan-Meier survival curves for OS comparing NOTCHmut/HRmut-positive versus NOTCHmut/HRmut-negative cases in the MSKCC pan-cancer cohort (excluding NSCLC).