BackgroundWe analyzed whether co-occurring mutations influence the outcome of systemic therapy in ALK-rearranged non-small-cell lung cancer (NSCLC).Patients and methods ALK-rearranged stage IIIB/IV NSCLC patients were analyzed with next-generation sequencing and fluorescence in situ hybridization analyses on a centralized diagnostic platform. Median progression-free survival (PFS) and overall survival (OS) were determined in the total cohort and in treatment-related sub-cohorts. Cox regression analyses were carried out to exclude confounders.ResultsAmong 216 patients with ALK-rearranged NSCLC, the frequency of pathogenic TP53 mutations was 23.8%, while other co-occurring mutations were rare events. In ALK/TP53 co-mutated patients, median PFS and OS were significantly lower compared with TP53 wildtype patients [PFS 3.9 months (95% CI: 2.4–5.6) versus 10.3 months (95% CI: 8.6–12.0), P < 0.001; OS 15.0 months (95% CI: 5.0–24.9) versus 50.0 months (95% CI: 22.9–77.1), P = 0.002]. This difference was confirmed in all treatment-related subgroups including chemotherapy only [PFS first-line chemotherapy 2.6 months (95% CI: 1.3–4.1) versus 6.2 months (95% CI: 1.8–10.5), P = 0.021; OS 2.0 months (95% CI: 0.0–4.6) versus 9.0 months (95% CI: 6.1–11.9), P = 0.035], crizotinib plus chemotherapy [PFS crizotinib 5.0 months (95% CI: 2.9–7.2) versus 14.0 months (95% CI: 8.0–20.1), P < 0.001; OS 17.0 months (95% CI: 6.7–27.3) versus not reached, P = 0.049] and crizotinib followed by next-generation ALK-inhibitor [PFS next-generation inhibitor 5.4 months (95% CI: 0.1–10.7) versus 9.9 months (95% CI: 6.4–13.5), P = 0.039; OS 7.0 months versus 50.0 months (95% CI: not reached), P = 0.001).ConclusionsIn ALK-rearranged NSCLC co-occurring TP53 mutations predict an unfavorable outcome of systemic therapy. Our observations encourage future research to understand the underlying molecular mechanisms and to improve treatment outcome of the ALK/TP53 co-mutated subgroup.

KRAS is one of the most frequently mutated oncogenes in human cancer. Despite substantial efforts, no clinically applicable strategy has yet been developed to effectively treat KRAS-mutant tumors. Here, we perform a cell-line-based screen and identify strong synergistic interactions between cell-cycle checkpoint-abrogating Chk1- and MK2 inhibitors, specifically in KRAS- and BRAF-driven cells. Mechanistically, we show that KRAS-mutant cancer displays intrinsic genotoxic stress, leading to tonic Chk1- and MK2 activity. We demonstrate that simultaneous Chk1- and MK2 inhibition leads to mitotic catastrophe in KRAS-mutant cells. This actionable synergistic interaction is validated using xenograft models, as well as distinct Kras- or Braf-driven autochthonous murine cancer models. Lastly, we show that combined checkpoint inhibition induces apoptotic cell death in KRAS- or BRAF-mutant tumor cells directly isolated from patients. These results strongly recommend simultaneous Chk1- and MK2 inhibition as a therapeutic strategy for the treatment of KRAS- or BRAF-driven cancers.

Cell 162, 146-159; July 2, 2015) Our paper presented a new algorithm, named PreCISE, designed to identify synergistic drug interactions that are effective at killing cancer cells harboring specific driver mutations. Using this platform and a cell-line-based screen, we identified a synergistic drug interaction between Chk1-and MK2 inhibitors in KRASor BRAF-driven cells, and that combination of therapy focused on these two kinase inhibitors is effective at inducing cell death of KRASand BRAF mutant tumors in vivo.While reviewing the paper after publication, we noticed that we had included two erroneous duplications of western blot loading control bands in the final version of Figure 2E. This figure shows that simultaneous inhibition of Chk1 and MK2 induces genotoxic stress and apoptosis in several KRAS-driven cancer cell lines and respective controls. The incorrect loading controls are presented for the HSP27 blot for the H1703 cell line, as well as for the CDC25B blot for the H1437 cell line. The errors occurred when we were copying each blot to construct the final figure. We recovered the original autoradiographs of these experiments and now provide a new version of the figure containing the correct loading controls. The correct data supports the original interpretation of the experiment, and the conclusions of the paper remain unchanged. In addition, we observed a typo in Figure S3A, showing the distribution of all cell lines used in the initial screen of our paper. In the pie chart, the slice of the pie in purple representing ''lung squamous'' cell lines was incorrectly labeled with n = 18. The correct value is n = 3, as depicted in the figure legend and in the main text. Both figures are now corrected online. We regret not being able to identify these errors before and sincerely apologize for any inconvenience they may have caused.

Background Identification of variable epidermal growth factor receptor ( EGFR ) gene mutations in non-small cell lung cancer (NSCLC) is important for the selection of appropriate targeted therapies. This meta-analysis was conducted to provide a worldwide overview of EGFR mutation and submutation (specifically exon 19 deletions, exon 21 L858R substitutions, and others) prevalence, and identify important covariates that influence EGFR mutation status in patients with advanced NSCLC to address this clinical data gap. Methods Embase ® and MEDLINE ® in Ovid were searched for studies published between 2004 and 2019 with cohorts of ≥ 50 adults with EGFR mutations, focusing on stage III/IV NSCLC (≤ 20% of patients with stage I/II NSCLC). Linear mixed-effects models were fitted to EGFR mutation endpoints using logistic transformation (logit), assuming a binomial distribution. The model included terms for an intercept reflecting European studies and further additive terms for other continents. EGFR submutations examined were exon 19 deletions, exon 21 L858R substitutions, and others. Results Of 3969 abstracts screened, 57 studies were included in the overall EGFR mutation analysis and 74 were included in the submutation analysis relative to the overall EGFR mutation population (Europe, n = 12; Asia, n = 51; North America, n = 5; Central America, n = 1; South America, n = 1; Oceania, n = 1; Global, n = 3). The final overall EGFR mutations model estimated Asian and European prevalence of 49.1% and 12.8%, respectively, and included an additive covariate for the proportion of male patients in a study. There were no significant covariates in the submutation analyses. Most submutations were actionable: exon 19 deletions (49.2% [Asia]; 48.4% [Europe]); exon 21 L858R substitutions (41.1% [Asia]; 29.9% [Europe]). Conclusions Although EGFR mutation prevalence was higher in Asian than Western countries, data support worldwide testing for EGFR overall and submutations to inform appropriate targeted treatment decisions. Supplementary Information The online version contains supplementary material available at 10.1007/s40291-021-00563-1.

We characterized genome alterations in 1255 clinically annotated lung tumors of all histological subgroups to identify genetically defined and clinically relevant subtypes. More than 55% of all cases had at least one oncogenic genome alteration potentially amenable to specific therapeutic intervention, including several personalized treatment approaches that are already in clinical evaluation. Marked differences in the pattern of genomic alterations existed between and within histological subtypes, thus challenging the original histomorphological diagnosis. Immunohistochemical studies confirmed many of these reassigned subtypes. The reassignment eliminated almost all cases of large cell carcinomas, some of which had therapeutically relevant alterations. Prospective testing of our genomics-based diagnostic algorithm in 5145 lung cancer patients enabled a genome-based diagnosis in 3863 (75%) patients, confirmed the feasibility of rational reassignments of large cell lung cancer, and led to improvement in overall survival in patients with EGFR-mutant or ALK-rearranged cancers. Thus, our findings provide support for broad implementation of genome-based diagnosis of lung cancer.