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In this era of value-based healthcare, costs must be measured alongside patient outcomes to prioritize quality improvement and inform performance-based reimbursement strategies. We sought to identify drivers of costs for patients undergoing minimally invasive esophagectomy for esophageal cancer.Patients who underwent minimally invasive esophagectomy for esophageal cancer from December 2008 to March 2020 were included. Our institutional Society of Thoracic Surgeons database was merged with financial data to determine inpatient direct accounting costs in 2020 US dollars for total, operative (surgery and anesthesia), and postoperative (intensive care, floor, radiology, laboratory, etc) services. A supervised machine learning quantitative method, the lasso estimator with 10-fold cross-validation, was applied to identify predictors of costs.In the study cohort (n = 240) most had ≥cT2 pathology (82%), adenocarcinoma histology (90%), and received neoadjuvant therapy (78%). Mean length of stay was 8.00 days (SD, 4.13) with 45% inpatient morbidity rate and no deaths. The largest proportions of cost were from the operating room (30%), inpatient floor (30%), and postanesthesia care/intensive care units (20%). Preoperative predictors of operative costs were age (-5.18% per decade [95% confidence interval {CI}, -9.95 to -0.27], P = .039), body mass index ≥ 30 (+12.9% [95% CI, 0.00-27.5], P = .050), forced expiratory volume in 1 second (-3.24% per 10% forced expiratory volume in 1 second [95% CI, -5.80 to -0.61], P = .017), and year of surgery (+2.55% [95% CI, 0.97-4.15], P = .002). Predictors of postoperative costs were postoperative renal failure (+91.6% [95% CI, 9.93-233.8], P = .022), respiratory failure (+414.6% [95% CI, 158.7-923.6], P .001), pneumonia (+136.1% [95% CI, 71.1-225.8], P.001), and reoperation (+60.5% [95% CI, 21.5-111.9], P = .001).Costs associated with minimally invasive esophagectomy are driven by preoperative risk factors and postoperative outcomes. These data enable surgeons and policymakers to reduce cost variation, improve quality through standardization, and ultimately provide greater value to patients.

Acquired drug resistance to even the most effective anti-cancer targeted therapies remains an unsolved clinical problem. Although many drivers of acquired drug resistance have been identified1‒6, the underlying molecular mechanisms shaping tumor evolution during treatment are incompletely understood. The extent to which therapy actively drives tumor evolution by promoting mutagenic processes7 or simply provides the selective pressure necessary for the outgrowth of drug-resistant clones8 remains an open question. Here, we report that lung cancer targeted therapies commonly used in the clinic induce the expression of cytidine deaminase APOBEC3A (A3A), leading to sustained mutagenesis in drug-tolerant cancer cells persisting during therapy. Induction of A3A facilitated the formation of double-strand DNA breaks (DSBs) in cycling drug-treated cells, and fully resistant clones that evolved from drug-tolerant intermediates exhibited an elevated burden of chromosomal aberrations such as copy number alterations and structural variations. Preventing therapy-induced A3A mutagenesis either by gene deletion or RNAi-mediated suppression delayed the emergence of drug resistance. Finally, we observed accumulation of A3A mutations in lung cancer patients who developed drug resistance after treatment with sequential targeted therapies. These data suggest that induction of A3A mutagenesis in response to targeted therapy treatment may facilitate the development of acquired resistance in non-small-cell lung cancer. Thus, suppressing expression or enzymatic activity of A3A may represent a potential therapeutic strategy to prevent or delay acquired resistance to lung cancer targeted therapy.

BH3 mimetic drugs, which inhibit prosurvival BCL2 family proteins, have limited single-agent activity in solid tumor models. The potential of BH3 mimetics for these cancers may depend on their ability to potentiate the apoptotic response to chemotherapy and targeted therapies. Using a novel class of potent and selective MCL1 inhibitors, we demonstrate that concurrent MEK + MCL1 inhibition induces apoptosis and tumor regression in KRAS-mutant non–small cell lung cancer (NSCLC) models, which respond poorly to MEK inhibition alone. Susceptibility to BH3 mimetics that target either MCL1 or BCL-xL was determined by the differential binding of proapoptotic BCL2 proteins to MCL1 or BCL-xL, respectively. The efficacy of dual MEK + MCL1 blockade was augmented by prior transient exposure to BCL-xL inhibitors, which promotes the binding of proapoptotic BCL2 proteins to MCL1. This suggests a novel strategy for integrating BH3 mimetics that target different BCL2 family proteins for KRAS-mutant NSCLC. Significance: Defining the molecular basis for MCL1 versus BCL-xL dependency will be essential for effective prioritization of BH3 mimetic combination therapies in the clinic. We discover a novel strategy for integrating BCL-xL and MCL1 inhibitors to drive and subsequently exploit apoptotic dependencies of KRAS-mutant NSCLCs treated with MEK inhibitors. See related commentary by Leber et al., p. 1511. This article is highlighted in the In This Issue feature, p. 1494