Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are a promising class of targeted cancer drugs, but their individual target profiles beyond the PARP family, which could result in differential clinical use or toxicity, are unknown. Using an unbiased, mass spectrometry-based chemical proteomics approach, we generated a comparative proteome-wide target map of the four clinical PARPi, olaparib, veliparib, niraparib, and rucaparib. PARPi as a class displayed high target selectivity. However, in addition to the canonical targets PARP1, PARP2, and several of their binding partners, we also identified hexose-6-phosphate dehydrogenase (H6PD) and deoxycytidine kinase (DCK) as previously unrecognized targets of rucaparib and niraparib, respectively. Subsequent functional validation suggested that inhibition of DCK by niraparib could have detrimental effects when combined with nucleoside analog pro-drugs. H6PD silencing can cause apoptosis and further sensitize cells to PARPi, suggesting that H6PD may be, in addition to its established role in metabolic disorders, a new anticancer target.

To better understand the signaling complexity of AXL, a member of the tumor-associated macrophage (TAM) receptor tyrosine kinase family, we created a physical and functional map of AXL signaling interactions, phosphorylation events, and target-engagement of three AXL tyrosine kinase inhibitors (TKI). We assessed AXL protein complexes using proximity-dependent biotinylation (BioID), effects of AXL TKI on global phosphoproteins using mass spectrometry, and target engagement of AXL TKI using activity-based protein profiling. BioID identifies AXL-interacting proteins that are mostly involved in cell adhesion/migration. Global phosphoproteomics show that AXL inhibition decreases phosphorylation of peptides involved in phosphatidylinositol-mediated signaling and cell adhesion/migration. Comparison of three AXL inhibitors reveals that TKI RXDX-106 inhibits pAXL, pAKT, and migration/invasion of these cells without reducing their viability, while bemcentinib exerts AXL-independent phenotypic effects on viability. Proteomic characterization of these TKIs demonstrates that they inhibit diverse targets in addition to AXL, with bemcentinib having the most off-targets. AXL and EGFR TKI cotreatment did not reverse resistance in cell line models of erlotinib resistance. However, a unique vulnerability was identified in one resistant clone, wherein combination of bemcentinib and erlotinib inhibited cell viability and signaling. We also show that AXL is overexpressed in approximately 30% to 40% of nonsmall but rarely in small cell lung cancer. Cell lines have a wide range of AXL expression, with basal activation detected rarely. Our study defines mechanisms of action of AXL in lung cancers which can be used to establish assays to measure drug targetable active AXL complexes in patient tissues and inform the strategy for targeting it's signaling as an anticancer therapy.

Patients with epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) often develop resistance to current standard third-generation EGFR tyrosine kinase inhibitors (TKIs); no targeted treatments are approved in the osimertinib-relapsed setting. In this open-label, dose-escalation and dose-expansion phase 1 trial, the potential for improved anti-tumor activity by combining amivantamab, an EGFR-MET bispecific antibody, with lazertinib, a third-generation EGFR TKI, was evaluated in patients with EGFR-mutant NSCLC whose disease progressed on third-generation TKI monotherapy but were chemotherapy naive (CHRYSALIS cohort E). In the dose-escalation phase, the recommended phase 2 combination dose was established; in the dose-expansion phase, the primary endpoints were safety and overall response rate, and key secondary endpoints included progression-free survival and overall survival. The safety profile of amivantamab and lazertinib was generally consistent with previous experience of each agent alone, with 4% experiencing grade ≥3 events; no new safety signals were identified. In an exploratory cohort of 45 patients who were enrolled without biomarker selection, the primary endpoint of investigator-assessed overall response rate was 36% (95% confidence interval, 22-51). The median duration of response was 9.6 months, and the median progression-free survival was 4.9 months. Next-generation sequencing and immunohistochemistry analyses identified high EGFR and/or MET expression as potential predictive biomarkers of response, which will need to be validated with prospective assessment. ClinicalTrials.gov identifier: NCT02609776 .

Background

Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer.

Methods and findings

We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results.

Conclusions

Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.