Faculty Bibliography

BACKGROUND:G2032R. METHODS:fusion-positive NSCLC. The primary efficacy end point in the phase 2 trial was confirmed objective response; efficacy analyses included patients from phase 1 and phase 2. Duration of response, progression-free survival, and safety were secondary end points in phase 2. RESULTS:G2032R mutation had a response. A total of 426 patients received the phase 2 dose; the most common treatment-related adverse events were dizziness (in 58% of the patients), dysgeusia (in 50%), and paresthesia (in 30%), and 3% discontinued repotrectinib owing to treatment-related adverse events. CONCLUSIONS:fusion-positive NSCLC, regardless of whether they had previously received a ROS1 TKI. Adverse events were mainly of low grade and compatible with long-term administration. (Funded by Turning Point Therapeutics, a wholly owned subsidiary of Bristol Myers Squibb; TRIDENT-1 ClinicalTrials.gov number, NCT03093116.).

Up to 71% of lung cancer patients admitted to the ICU are newly diagnosed. The decision to initiate cancer directed treatments in lung cancer patients admitted to the ICU remains complex. For those with identified oncogene driver mutations, targeted therapies with rapid and high response rates are attractive treatment options. However, mechanically ventilated patients face additional barriers in which enteral tube administration of oral therapies may require tablets or capsules to be crushed or opened and diluted. Data on the pharmacodynamics and pharmacokinetics of this alternative route of administration are often very limited. Here we describe the first case report of an intubated patient with newly diagnosed NSCLC who was successfully treated with opened dabrafenib capsules and crushed trametinib tablets administered through a nasogastric tube. We also provide a review of the existing literature on feeding tube administration of commonly used tyrosine kinase inhibitors in lung cancer. Tyrosine kinase inhibitors administered through feeding tubes can lead to a clinically meaningful recovery in critically ill patients.

WHAT IS THIS SUMMARY ABOUT?/UNASSIGNED:G12C mutation. The CodeBreaK 100 study looked at whether sotorasib is a safe and effective treatment for advanced non-small-cell lung cancer. Sotorasib is designed to specifically target and lock the mutated KRAS protein in the inactive state to treat non-small-cell lung cancer. WHAT WERE THE RESULTS?/UNASSIGNED:were seen in 70% of patients and were severe in 21% of patients. The most common side effects included diarrhea, increased liver enzymes, nausea and tiredness. 70 (41%) patients responded to sotorasib and 144 (84%) patients had tumors that either remained stable or shrunk in size. 29 (41%) patients who responded to sotorasib responded for over 12 months. After 2 years, 9 patients with a response remained on sotorasib; there were no notable increases in tumor size or development of new tumors over this time. There were 5patients who received sotorasib for more than 2 years and continued to respond. Long-term benefit was seen for some patients. Patients also benefitted from treatment when the tumor expressed different amounts of a protein called PD-L1.In total, 33% of patients were still alive after 2 years. WHAT DO THE RESULTS MEAN?/UNASSIGNED:: NCT03600883 (CodeBreaK 100) (ClinicalTrials.gov).

UNLABELLED:Non-small lung cancers (NSCLC) frequently (∼30%) harbor KRAS driver mutations, half of which are KRASG12C. KRAS-mutant NSCLC with comutated STK11 and/or KEAP1 is particularly refractory to conventional, targeted, and immune therapy. Development of KRASG12C inhibitors (G12Ci) provided a major therapeutic advance, but resistance still limits their efficacy. To identify genes whose deletion augments efficacy of the G12Cis adagrasib (MRTX-849) or adagrasib plus TNO155 (SHP2i), we performed genome-wide CRISPR/Cas9 screens on KRAS/STK11-mutant NSCLC lines. Recurrent, potentially targetable, synthetic lethal (SL) genes were identified, including serine-threonine kinases, tRNA-modifying and proteoglycan synthesis enzymes, and YAP/TAZ/TEAD pathway components. Several SL genes were confirmed by siRNA/shRNA experiments, and the YAP/TAZ/TEAD pathway was extensively validated in vitro and in mice. Mechanistic studies showed that G12Ci treatment induced gene expression of RHO paralogs and activators, increased RHOA activation, and evoked ROCK-dependent nuclear translocation of YAP. Mice and patients with acquired G12Ci- or G12Ci/SHP2i-resistant tumors showed strong overlap with SL pathways, arguing for the relevance of the screen results. These findings provide a landscape of potential targets for future combination strategies, some of which can be tested rapidly in the clinic. SIGNIFICANCE/UNASSIGNED:Identification of synthetic lethal genes with KRASG12C using genome-wide CRISPR/Cas9 screening and credentialing of the ability of TEAD inhibition to enhance KRASG12C efficacy provides a roadmap for combination strategies. See related commentary by Johnson and Haigis, p. 4005.

Recent statistics on lung cancer, including the steady decline of advanced diseases and the dramatically increasing detection of early-stage diseases and indeterminate pulmonary nodules, mark the significance of a comprehensive understanding of early lung carcinogenesis. Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, largely due to insufficient materials from ADC precursors. Here, we employed state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used hematoxylin and eosin histopathology images and extracted 9 biology-relevant pathomic features to decode lung preneoplasia evolution. We analyzed 3 distinct cohorts (Japan, China, and United States) covering 98 patients, 162 slides, and 669 regions of interest, including 143 normal, 129 atypical adenomatous hyperplasia, 94 AIS, 98 MIA, and 205 ADC. Extracted pathomic features revealed progressive increase of atypical epithelial cells and progressive decrease of lymphocytic cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine hematoxylin and eosin staining.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

PURPOSE/OBJECTIVE:Lung cancer is the leading cause of cancer-related deaths in the United States. This study aims to analyze lung cancer incidence, mortality, and related statistics from 1990 to 2019, focusing on national- and state-level trends and exploring potential disparities between sexes. METHODS:The Global Burden of Disease database was used to extract tracheal, bronchus, and lung cancer mortality data from 1990 to 2019 for both males and females and across all states of the United States. Age-standardized incidence rates, age-standardized mortality rates, disability-adjusted life years (DALYs), and mortality-to-incidence indices (MIIs) were studied to assess for gender-based, geographic, and temporal disparities. Joinpoint regression analysis was performed to further evaluate trends. RESULTS:The incidence of these cancers in the United States decreased between 1990 and 2019 by 23.35%, with a more significant decline in males (37.73%) than females (1.41%). Similarly, for mortality, a decrease was observed for both sexes combined (26.83%), but much more significantly for males (40.23%) than females (6.01%). The MIIs decreased overall, but there were variations across states. DALYs decreased for both sexes combined, with males experiencing a larger reduction, but an increase was noted in some states for females. CONCLUSION/CONCLUSIONS:This analysis reveals diverse trends pertaining to the incidence, mortality, and disability burden associated with lung cancer by sex and states in the United States, emphasizing the need for targeted interventions to reduce disparities. These findings contribute to our understanding of the current landscape of lung cancer and can inform future strategies for prevention, early detection, and management.

Small cell lung cancers (SCLCs) rapidly resist cytotoxic chemotherapy and immune checkpoint inhibitor (ICI) treatments. New, non-cross-resistant therapies are thus needed. SCLC cells are committed into neuroendocrine lineage then maturation arrested. Implicating DNA methyltransferase 1 (DNMT1) in the maturation arrests, we find (1) the repression mark methylated CpG, written by DNMT1, is retained at suppressed neuroendocrine-lineage genes, even as other repression marks are erased; (2) DNMT1 is recurrently amplified, whereas Ten-Eleven-Translocation 2 (TET2), which functionally opposes DNMT1, is deleted; (3) DNMT1 is recruited into neuroendocrine-lineage master transcription factor (ASCL1, NEUROD1) hubs in SCLC cells; and (4) DNMT1 knockdown activated ASCL1-target genes and released SCLC cell-cycling exits by terminal lineage maturation, which are cycling exits that do not require the p53/apoptosis pathway used by cytotoxic chemotherapy. Inhibiting DNMT1/corepressors with clinical compounds accordingly extended survival of mice with chemorefractory and ICI-refractory, p53-null, disseminated SCLC. Lineage commitment of SCLC cells can hence be leveraged into non-cytotoxic therapy able to treat chemo/ICI-refractory SCLC.

BACKGROUND:Brain metastases (BM) have long been considered a terminal diagnosis with management mainly aimed at palliation and little hope for extended survival. Use of brain stereotactic radiosurgery (SRS) and/or resection, in addition to novel systemic therapies, has enabled improvements in overall and progression-free (PFS) survival. OBJECTIVE:To explore the possibility of extended survival in patients with non-small-cell lung cancer (NSCLC) BM in the current era. METHODS:During the years 2008 to 2020, 606 patients with NSCLC underwent their first Gamma Knife SRS for BM at our institution with point-of-care data collection. We reviewed clinical, molecular, imaging, and treatment parameters to explore the relationship of such factors with survival. RESULTS:The median overall survival was 17 months (95% CI, 13-40). Predictors of increased survival in a multivariable analysis included age <65 years (P < .001), KPS ≥80 (P < .001), absence of extracranial metastases (P < .001), fewer BM at first SRS (≤3, P = .003), and targeted therapy (P = .005), whereas chemotherapy alone was associated with shorter survival (P = .04). In a subgroup of patients managed before 2016 (n = 264), 38 (14%) were long-term survivors (≥5 years), of which 16% required no active cancer treatment (systemic or brain) for ≥3 years by the end of their follow-up. CONCLUSION/CONCLUSIONS:Long-term survival in patients with brain metastases from NSCLC is feasible in the current era of SRS when combined with the use of effective targeted therapeutics. Of those living ≥5 years, the chance for living with stable disease without the need for active treatment for ≥3 years was 16%.

BACKGROUND:Only around 20-30% of patients with non-small-cell lung cancer (NCSLC) have durable benefit from immune-checkpoint inhibitors. Although tissue-based biomarkers (eg, PD-L1) are limited by suboptimal performance, tissue availability, and tumour heterogeneity, radiographic images might holistically capture the underlying cancer biology. We aimed to investigate the application of deep learning on chest CT scans to derive an imaging signature of response to immune checkpoint inhibitors and evaluate its added value in the clinical context. METHODS:In this retrospective modelling study, 976 patients with metastatic, EGFR/ALK negative NSCLC treated with immune checkpoint inhibitors at MD Anderson and Stanford were enrolled from Jan 1, 2014, to Feb 29, 2020. We built and tested an ensemble deep learning model on pretreatment CTs (Deep-CT) to predict overall survival and progression-free survival after treatment with immune checkpoint inhibitors. We also evaluated the added predictive value of the Deep-CT model in the context of existing clinicopathological and radiological metrics. FINDINGS/RESULTS:Our Deep-CT model demonstrated robust stratification of patient survival of the MD Anderson testing set, which was validated in the external Stanford set. The performance of the Deep-CT model remained significant on subgroup analyses stratified by PD-L1, histology, age, sex, and race. In univariate analysis, Deep-CT outperformed the conventional risk factors, including histology, smoking status, and PD-L1 expression, and remained an independent predictor after multivariate adjustment. Integrating the Deep-CT model with conventional risk factors demonstrated significantly improved prediction performance, with overall survival C-index increases from 0·70 (clinical model) to 0·75 (composite model) during testing. On the other hand, the deep learning risk scores correlated with some radiomics features, but radiomics alone could not reach the performance level of deep learning, indicating that the deep learning model effectively captured additional imaging patterns beyond known radiomics features. INTERPRETATION/CONCLUSIONS:This proof-of-concept study shows that automated profiling of radiographic scans through deep learning can provide orthogonal information independent of existing clinicopathological biomarkers, bringing the goal of precision immunotherapy for patients with NSCLC closer. FUNDING/BACKGROUND:National Institutes of Health, Mark Foundation Damon Runyon Foundation Physician Scientist Award, MD Anderson Strategic Initiative Development Program, MD Anderson Lung Moon Shot Program, Andrea Mugnaini, and Edward L C Smith.