Association of TP53 mutations with response and longer survival under immune checkpoint inhibitors in advanced non-small-cell lung cancer

Assoun, Sandra; Théou–Anton, Nathalie; Nguenang, Marina; Cazes, Aurélie; Danel, Claire; Abbar, Baptiste; Pluvy, Johan; Gounant, V.; Khalil, Antoine; Namour, Céline; Brosseau, Solenn; Zalcman, Gérard

doi:10.1016/j.lungcan.2019.04.005

Cited by 134 publications

(114 citation statements)

References 39 publications

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“…However, an increased understanding of the effects of distinct mutations on p53 activity has led to the recognition of the different properties of specific mutations. Furthermore, several studies have produced controversial outcomes in evaluating TP53 as biomarkers for ICIs which overlooked its heterogeneity till now [ 6 , 30 ].…”

Section: Discussionmentioning

confidence: 99%

“…Multiple recent studies have shown that TMB can serve as a surrogate for overall neoantigen load, and disruption of the DNA damage repair pathway can result in an elevated TMB level [ 6 , 27 ]. P53 plays an important role in guarding genomic stability by orchestrating a variety of DNA damage response (DDR) mechanisms, and p53-null tumor cells are defective in certain DNA repair activities [31] .…”

Section: Discussionmentioning

confidence: 99%

“…However, growing evidence demonstrates that different p53 mutants differ substantially in form and function, and not all p53 mutants have equivalent cellular effects [5] . But no researches have been set up to address the question whether all TP53 alternations could be equally taken as a biomarker for ICIs till now, as several studies have produced controversial outcomes in evaluating TP53 as biomarkers for ICIs which overlooked its heterogeneity [6] .…”

Section: Introductionmentioning

confidence: 99%

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Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma

et al. 2020

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Background Although TP53 co-mutation with KRAS/ATM/EGFR/STK11 have been proved to have predictive value for response to immune checkpoint inhibitors (ICIs), not all TP53 mutations are equal in this context. As the main part of TP53 mutant types, Missense and Nonsense alternations in TP53 as independent factors to predict the response to ICIs within Lung Adenocarcinoma (LUAD) patients have not yet been reported. Methods An integrated analysis based on multiple-dimensional data types including genomic, transcriptomic, proteomic and clinical data from published lung adenocarcinoma data and local database of LUAD taking immune checkpoint inhibitors. Gene set enrichment analysis (GSEA) was used to determine potentially relevant gene expression signatures between specific subgroups. Single-sample GSEA (GSVA) is conducted to calculate the score for enrichment of a set of genes regulating DNA damage repair (DDR) pathway. Findings The TP53-missense-mutation group showed increased PD-L1 (CD274) level and enriched IFN-γ signatures compared with the TP53-wild-type subgroup, but no differences were noted in patients with nonsense-mutant vs wild-type p53. Furthermore, a group of suppressor Immune cells like M2 Macrophage and Neutrophils are found enriched in nonsense group. On the other-side, both TP53 missense and nonsense mutations are associated with elevated TMB and neoantigen levels and contribute equally to DNA damage repair deficiency. The distribution regarding to multi-dimensional factors determining the efficacy of ICIs finally transformed into diverse clinical benefits for LUAD. TP53 missense but not -nonsense Mutants are associated with better clinical benefits taking antiPD-1/1L. However, all such TP53 subgroups responds well to nivolumab (antiPD-L1) plus ipilimumab (antiCTLA-4) therapy. Interpretation Our study demonstrated that not all TP53 mutations are equal in predicting efficacy in patients with LUAD treated with ICIs. Multi-center data showed that TP53 missense and nonsense mutations were significantly different in terms of associations with PD-L1 expression, IFN-γ signatures and TME composition. Special attention should be paid to potential TP53 mutation heterogeneity when evaluating TP53 status as biomarker for ICIs. Funding The study was supported by Key Lab System Project of Guangdong Science and Technology Department – Guangdong Provincial Key Lab of Translational Medicine in Lung Cancer (Grant No. 2017B030314120, to Yi-Long WU)

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma

et al. 2020

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“…In addition, the genes TP53 and NRXN1 with the higher degree were chosen as the hub genes in the PPI network. Assoun et al uncovered that TP53‐mutated status was correlated with an immunotherapy OS benefit in advanced NSCLC 22 . Craig et al showed that a biomarker comprising TP53 , PIK3CA , and BRAF somatic mutations may better stratify individuals for optimal lung cancer screening and prevention outcomes 23 .…”

Section: Discussionmentioning

confidence: 99%

Screening and identification of biomarkers associated with the diagnosis and prognosis of lung adenocarcinoma

Wang

Zhang²,

Chen³

et al. 2020

Clinical Laboratory Analysis

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Background In this study, we aimed to identify the pathogenesis and prognostic biomarkers of lung adenocarcinoma (LUAD). Methods Differentially expressed mRNAs (DEmRNAs) and single nucleotide polymorphism (SNP) mutant genes were screened. In addition, enrichment and protein‐protein interaction (PPI) network analyses of the SNP‐mutated genes were performed. Thereafter, the correlation between gene mutation and expression was analyzed. Finally, the mutated genes associated with LUAD prognosis were validated on the basis of The Cancer Genome Atlas (TCGA) database. Results A total of 2502 DEmRNAs were initially screened in this study. We identified 756 SNP‐mutated genes from more than 30 cases. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the mutated genes involved in LUAD were mainly associated with the ECM‐receptor interaction, focal adhesion, and calcium signaling pathways. Tumor protein p53 (TP53) and neurexin 1 (NRXN1) with the higher degree were chosen as the hub genes in the PPI network. In addition, the correlation analysis revealed six genes, including assembly factor for spindle microtubules (ASPM), centromere protein F (CENPF), contactin 3 (CNTN3), catenin delta 2 (CTNND2), PKHD1 like 1 (PKHD1L1), and semaphorin 6D (SEMA6D), and three SNP mutations at ASPM rs368020495, CENPF rs762653487, and PKHD1L1 rs768349010 sites that were found to be associated with LUAD prognosis. Further validation showed that among the aforementioned six mutated genes, CENPF was upregulated and SEMA6D was downregulated. Conclusion CENPF, SEMA6D, TP53, and NRXN1 were found to be closely associated with the development of LUAD.

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“…Favourable clinical benefit of PD-1/PD-L1 inhibition has been observed in NSCLC patients with TP53 mutations or combinations of KRAS and TP53 mutations in the same tumour independent of TMB. [34][35][36] In contrast, co-occurrence of mutations in KRAS and STK11 is associated with lack of response to ICB. Thus, tumours with STK11 mutations seem to be associated with a worse outcome of ICB therapy and it has also been shown that co-occurrence of STK11 with, for example, KEAP1 or KRAS may be prognostic rather than predictive.…”

Section: Additional Clinically Relevant Genomic Alterationsmentioning

confidence: 99%

Immune checkpoint blockade and biomarkers of clinical response in non–small cell lung cancer

2020

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Association of TP53 mutations with response and longer survival under immune checkpoint inhibitors in advanced non-small-cell lung cancer

Cited by 134 publications

References 39 publications

Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma

Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma

Screening and identification of biomarkers associated with the diagnosis and prognosis of lung adenocarcinoma

Immune checkpoint blockade and biomarkers of clinical response in non–small cell lung cancer

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