The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Association of TP53 mutations with response and longer survival under immune checkpoint inhibitors in advanced non-small-cell lung cancer
Open accessAbstract
INTRODUCTION: Tumor mutational burden (TMB) correlates with response to immune checkpoint inhibitors (ICI) in advanced non-small-cell lung cancer (aNSCLC). We hypothesized that TP53 mutations could reflect TMB and be associated with ICI benefit. METHODS: TP53 mutations were assessed by next-generation sequencing in aNSCLC patients treated with programmed death-1 (PD-1) blockers. Clinical data, tumor programmed death ligand-1 (PD-L1) expression, and KRAS mutational status were collected. The primary endpoint was overall survival (OS). RESULTS: In total, 72 patients (median [interquartile range] age: 61 [33-83] years) were included; 52 (72%) were male; 39 (54%) had performance status 0-1; 53 (74%) had adenocarcinoma; 20 (28%) received first-line ICI, 52 (72%) second line or more. In 65 patients with available data, 36 (55%) expressed PD-L1 in ≥50% of tumor cells, 20 (31%) in 1-49% of cells, and nine (14%) were PD-L1-negative. Non-synonymous TP53 mutations were observed in 41 (57%) and 25 (35%) harbored KRAS-mutated tumors. After a median follow-up of 15.2 months (95% confidence interval [CI] 10.3-17.4 m), the median OS in the TP53-mutated group was 18.1 months (95% CI 6.6-not reached), vs. 8.1 months (95% CI 2.2-14.5, hazard ratio [HR] = 0.48; 95% CI 0.25-0.95, p = 0.04) in the TP53-wild-type group. Median progression-free survival was significantly longer in TP53-mutated patients (4.5 months, 95% CI 2.8-18.1 versus 1.4, 95% CI 1.1-3.5; p = 0.03), although TP53 mutation status failed to significantly influence PFS in the multivariate analysis (p = 0.32). Objective response rate (ORR) was higher in patients with TP53 mutation (51.2% vs. 20.7%; p = 0.01). In multivariate analysis, TP53 mutations independently associated with longer OS (HR = 0.35, 95% CI 0.16-0.77, p = 0.009). CONCLUSIONS: TP53-mutated status correlated with immunotherapy OS benefit in aNSCLC.
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PD-1 Blockade in Tumors with Mismatch-Repair Deficiency
Le, D. T., Uram, J. N., Wang, H., Bartlett, B. R., Kemberling, H., Eyring, A. D., Skora, A. D., Luber, B. S., Azad, N. S., Laheru, D., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1500596 · Cited by 9,377
Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer
Borghaei, H., Paz-Ares, L., Horn, L., Spigel, D. R., Steins, M., Ready, N. E., Chow, L. Q., Vokes, E. E., Felip, E., Holgado, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1507643 · Cited by 9,335
Nivolumab versus Docetaxel in Advanced Squamous-Cell Non–Small-Cell Lung Cancer
Brahmer, J., Reckamp, K. L., Baas, P., Crinò, L., Eberhardt, W. E. E., Poddubskaya, E., Antonia, S., Pluzanski, A., Vokes, E. E., Holgado, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1504627 · Cited by 8,447
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade
Le, D. T., Durham, J. N., Smith, K. N., Wang, H., Bartlett, B. R., Aulakh, L. K., Lu, S., Kemberling, H., Wilt, C., Luber, B. S., et al. (2017) · Science · doi:10.1126/science.aan6733 · Cited by 6,645
Pembrolizumab for the Treatment of Non–Small-Cell Lung Cancer
Garon, E. B., Rizvi, N. A., Hui, R., Leighl, N., Balmanoukian, A. S., Eder, J. P., Patnaik, A., Aggarwal, C., Gubens, M., Horn, L., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1501824 · Cited by 6,198
Neoantigens in cancer immunotherapy
Schumacher, T. N., & Schreiber, R. D. (2015) · Science · doi:10.1126/science.aaa4971 · Cited by 4,783
Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden
Hellmann, M. D., Ciuleanu, T.-E., Pluzanski, A., Lee, J. S., Otterson, G. A., Audigier-Valette, C., Minenza, E., Linardou, H., Burgers, S., Salman, P., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1801946 · Cited by 3,063
Somatic mutations affect key pathways in lung adenocarcinoma
Ding, L., Getz, G., Wheeler, D. A., Mardis, E. R., McLellan, M. D., Cibulskis, K., Sougnez, C., Greulich, H., Muzny, D. M., Morgan, M. B., et al. (2008) · Nature · doi:10.1038/nature07423 · Cited by 2,681
TP53 mutations in human cancers: origins, consequences, and clinical use.
Olivier, M., Hollstein, M., & Hainaut, P. (2010) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a001008 · Cited by 2,199
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Frost, N., Kollmeier, J., Vollbrecht, C., Grah, C., Matthes, B., Pultermann, D., von Laffert, M., Lüders, H., Olive, E., Raspe, M., et al. (2021) · Translational Lung Cancer Research · doi:10.21037/tlcr-20-958 · Cited by 61
Efficacy and safety of immune checkpoint blockade in patients with Li-Fraumeni syndrome
Bottosso, M., Verret, B., Caron, O., Hamzaoui, N., Pasmant, E., Danlos, F.-X., Boudou-Rouquette, P., Srikaran, A., Blons, H., Guarneri, V., et al. (2024) · JCO Precision Oncology · doi:10.1200/po.24.00139 · Cited by 6
Metadata
- Authors
- Assoun, S., Theou-Anton, N., Nguenang, M., Cazes, A., Danel, C., Abbar, B., Pluvy, J., Gounant, V., Khalil, A., Namour, C., Brosseau, S., & Zalcman, G.
- Venue
- Lung Cancer
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 132
- Pages
- 65-71
- ISSN
- 0169-5002 (ISSN-L)
- OpenAlex
- W2936661866
- Cited by
- 172
- References
- 15
- FWCI
- 7.44
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Assoun, S., Theou-Anton, N., Nguenang, M., Cazes, A., Danel, C., Abbar, B., Pluvy, J., Gounant, V., Khalil, A., Namour, C., Brosseau, S., & Zalcman, G. (2019). Association of TP53 mutations with response and longer survival under immune checkpoint inhibitors in advanced non-small-cell lung cancer. Lung Cancer. https://doi.org/10.1016/j.lungcan.2019.04.005
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