Cell-free DNA methylation-defined prognostic subgroups in small-cell lung cancer identified by leukocyte methylation subtraction.

Small-cell lung cancer (SCLC) methylome is understudied. Here, we comprehensively profile SCLC using cell-free methylated DNA immunoprecipitation followed by sequencing (cfMeDIP-seq). Cell-free DNA (cfDNA) from plasma of 74 patients with SCLC pre-treatment and from 20 non-cancer participants, genomic DNA (gDNA) from peripheral blood leukocytes from the same 74 patients, and 7 accompanying circulating tumor cell-derived xenografts (CDXs) underwent cfMeDIP-seq. Peripheral blood leukocyte methylation (PRIME) subtraction to improve tumor specificity. SCLC cfDNA methylation is distinct from non-cancer but correlates with CDX tumor methylation. PRIME and k-means consensus identified two methylome clusters with prognostic associations that related to axon guidance, neuroactive ligand-receptor interaction, pluripotency of stem cells, and differentially methylated at long noncoding RNA and other repeats features. We comprehensively profiled the SCLC methylome in a large patient cohort and identified methylome clusters with prognostic associations. Our work demonstrates the potential of liquid biopsies in examining SCLC biology encoded in the methylome.

Tobacco Use and Response to Immune Checkpoint Inhibitor Therapy in Non-Small Cell Lung Cancer.

Tobacco is a known risk factor for lung cancer, and continued tobacco use is associated with poorer outcomes across multiple lung cancer treatment modalities including surgery, chemotherapy and radiation therapy. Less is known about the association of tobacco use and outcomes with immune checkpoint inhibitors (ICIs), which are becoming an important part of the treatment landscape in lung cancer, both in metastatic and curative settings. We reviewed the literature on the association of tobacco and tumor biology as it relates to immunotherapy. We also reviewed the association of tobacco use on outcomes among phase III randomized clinical trials involving ICIs in non-small cell lung cancer (NSCLC). We identified that patients with a smoking history may have a greater benefit with ICI treatment compared to never smokers in both treatment-naïve (HR 0.82, 95% CI 0.69-0.97, vs. HR 1.06, 95% CI 0.81-1.38) and pre-treated (HR 0.79, 95% CI 0.70-0.90 vs. 1.03, 95% CI 0.74-1.43) settings. In trials where smoking status was further defined, ex-smokers appear to demonstrate greater benefit with ICI therapy compared to current smokers (HR 0.78, 95% CI 0.59-1.01 vs. 0.91, 95% CI 0.72-1.14). We conclude by offering our perspective on future directions in this area of research, including implementation of standardized collection and analysis of tobacco use in clinical trials involving ICI therapy in lung cancer and other disease sites, and also evaluating how tobacco may affect toxicities related to ICI therapy. Based on our review, we believe that a patient's history of tobacco smoking does have a role to play in guiding treatment decision making in patients with lung cancer.

Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer.

In advanced non-small cell lung cancer (NSCLC), patients with actionable genomic alterations may derive additional clinical benefit from targeted treatment compared to cytotoxic chemotherapy. Current guidelines recommend extensive testing with next generation sequencing (NGS) panels. We investigated the impact of using a targeted NGS panel (TruSight Tumor 15, Illumina) as reflex testing for NSCLC samples at a single institution. Molecular analysis examined 15 genes for hotspot mutation variants, including AKT1, BRAF, EGFR, ERBB2, FOXL2, GNA11, GNAQ, KIT, KRAS, MET, NRAS, PDGFRA, PIK3CA, RET and TP53 genes. Between February 2017 and October 2020, 1460 samples from 1395 patients were analyzed. 1201 patients (86.1%) had at least one variant identified, most frequently TP53 (47.5%), KRAS (32.2%) or EGFR (24.2%). Among these, 994 patients (71.3%) had clinically relevant variants eligible for treatment with approved therapies or clinical trial enrollment. The incremental cost of NGS beyond single gene testing (EGFR, ALK) was CAD $233 per case. Reflex upfront NGS identified at least one actionable variant in more than 70% of patients with NSCLC, with minimal increase in testing cost. Implementation of NGS panels remains essential as treatment paradigms continue to evolve.

PD-L1 assessment in cytology samples predicts treatment response to checkpoint inhibitors in NSCLC.

BACKGROUND: Testing for tumor programmed death ligand-1 (PD-L1) expression was initially developed with histology specimens in non-small cell lung cancer (NSCLC). However, cytology specimens are widely used for primary diagnosis and biomarker studies in clinical practice. Limited clinical data exist on the predictiveness of cytology-derived PD-L1 scores for response to immune checkpoint inhibitor (ICI) therapy. METHODS: We reviewed all NSCLC specimens clinically tested at the University Health Network (UHN) for PD-L1 with 22C3pharmDx, from 01/2013 to 04/2021. Treatment outcomes in patients treated with single agent ICI therapy were reviewed and compared according to cytology- and histology-derived PD-L1 scores. RESULTS: We identified 494 and 1942 unique patients with cytology- and histology-derived tumor proportion scores, respectively, during the study period. Informative testing rates were 95 % vs 98 % for cytology and histology, respectively. Clinical data were available for 152 patients treated with single agent ICI: 61 cytology and 91 histology. Overall response rates (ORR) were similar for cytology and histology (36 % vs 34 %; p = 0.23), as well as median progression free survival (PFS) (4.9 vs 4.2 months; p = 0.99) and overall survival (23.4 vs 19.7 months; p = 0.99). The results remained similar even after adjusting for PD-L1 expression levels and line of ICI treatment (PFS HR 1.15; 95 %CI 0.78-1.70; p = 0.47). CONCLUSIONS: Treatment outcomes to single agent ICI based on cytology-derived PD-L1 scores were comparable to histology controls. Our results support PD-L1 biomarker testing on both cytology and histology specimens.

Automating Access to Real-World Evidence.

Introduction: Real-world evidence is important in regulatory and funding decisions. Manual data extraction from electronic health records (EHRs) is time-consuming and challenging to maintain. Automated extraction using natural language processing (NLP) and artificial intelligence may facilitate this process. Whereas NLP offers a faster solution than manual methods of extraction, the validity of extracted data remains in question. The current study compared manual and automated data extraction from the EHR of patients with advanced lung cancer. Methods: Previously, we extracted EHRs from 1209 patients diagnosed with advanced lung cancer (stage IIIB or IV) between January 2015 and December 2017 at Princess Margaret Cancer Centre (Toronto, Canada) using the commercially available artificial intelligence engine, DARWEN (Pentavere, Ontario, Canada). For comparison, 100 of 333 patients that received systemic therapy were randomly selected and clinical data manually extracted by two trained abstractors using the same accepted gold standard feature definitions, including patient, disease characteristics, and treatment data. All cases were re-reviewed by an expert adjudicator. Accuracy and concordance between automated and manual methods are reported. Results: Automated extraction required considerably less time (<1 day) than manual extraction (∼225 person-hr). The collection of demographic data (age, sex, diagnosis) was highly accurate and concordant with both methods (96%-100%). Accuracy (for either extraction approach) and concordance were lower for unstructured data elements in EHR, such as performance status, date of diagnosis, and smoking status (NLP accuracy: 88%-94%; Manual accuracy: 78%-94%; concordance: 71%-82%). Concurrent medications (86%-100%) and comorbid conditions (96%-100%), were reported with high accuracy and concordance. Treatment details were also accurately captured with both methods (84%-100%) and highly concordant (83%-99%). Detection of whether biomarker testing was performed was highly accurate and concordant (96%-98%), although detection of biomarker test results was more variable (accuracy 84%-100%, concordance 84%-99%). Features with syntactic or semantic variation requiring clinical interpretation were extracted with slightly lower accuracy by both NLP and manual review. For example, metastatic sites were more accurately identified through NLP extraction (NLP: 88%-99%; manual: 71%-100%; concordance: 70%-99%) with the exception of lung and lymph node metastases (NLP: 66%-71%; manual: 87%-92%; concordance: 58%) owing to analogous terms used in radiology reports not being included in the accepted gold standard definition. Conclusions: Automated data abstraction from EHR is highly accurate and faster than manual abstraction. Key challenges include poorly structured EHR and the use of analogous terms beyond the accepted gold standard definition. The application of NLP can facilitate real-world evidence studies at a greater scale than could be achieved with manual data extraction.

Integrating circulating-free DNA (cfDNA) analysis into clinical practice: opportunities and challenges.

In the current era of precision medicine, the identification of genomic alterations has revolutionised the management of patients with solid tumours. Recent advances in the detection and characterisation of circulating tumour DNA (ctDNA) have enabled the integration of liquid biopsy into clinical practice for molecular profiling. ctDNA has also emerged as a promising biomarker for prognostication, monitoring disease response, detection of minimal residual disease and early diagnosis. In this Review, we discuss current and future clinical applications of ctDNA primarily in non-small cell lung cancer in addition to other solid tumours.

Effects of Ethnicity on Outcomes of Patients With EGFR Mutation-Positive NSCLC Treated With EGFR Tyrosine Kinase Inhibitors and Surgical Resection.

INTRODUCTION: In addition to the higher prevalence of EGFR mutations found among lung cancer cases in East Asian patients, it is unclear whether there are differences in treatment outcomes by ethnicity-that is, East Asian versus non-East Asian. METHODS: Patients diagnosed with EGFR-mutant lung cancer between January 2004 and October 2014 at a single center were reviewed. Data captured included demographics, tumor and treatment information, and survival. Survival of patients of East Asian and non-East Asian ancestry was compared, including in the subgroup that received EGFR tyrosine kinase inhibitor (TKI) for advanced disease and in those with early-stage disease that underwent surgical resection. RESULTS: A total of 348 patients with EGFR-mutant NSCLC were identified. There was a higher proportion of nonsmokers among those of East Asian ethnicity. No significant difference in survival was seen between patients of East Asian and non-East Asian ethnicity, median 6.7 years (95% confidence interval [CI]: 5.4-not applicable) and 5.4 years (95% CI: 4.1-7.2), respectively (p = 0.09). Among 196 patients that received treatment with EGFR TKI, the median survival from TKI initiation was also similar for those of East Asian and non-East Asian ethnicity, 3.0 years (95% CI: 2.1-3.5) and 2.7 years (95% CI: 2.2-3.5), respectively. Among the early-stage patients that underwent surgical resection (n = 163), those of East Asian ethnicity had similar median recurrence-free survival from surgery compared with non-East Asian patients, 5.3 years (95% CI: 3.5-not applicable) and 5.1 years (95% CI: 3.3-7.2), respectively. CONCLUSIONS: In a cohort of patients with EGFR-mutant lung cancer with access to uniform standards of care, East Asian ethnicity was not associated with improved survival after treatment with EGFR TKI or surgical resection.

Reflex ROS1 IHC Screening with FISH Confirmation for Advanced Non-Small Cell Lung Cancer-A Cost-Efficient Strategy in a Public Healthcare System.

ROS1 rearrangements are identified in 1-2% of lung adenocarcinoma cases, and reflex testing is guideline-recommended. We developed a decision model for population-based ROS1 testing from a Canadian public healthcare perspective to determine the strategy that optimized detection of true-positive (TP) cases while minimizing costs and turnaround time (TAT). Eight diagnostic strategies were compared, including reflex single gene testing via immunohistochemistry (IHC) screening, fluorescence in-situ hybridization (FISH), next-generation sequencing (NGS), and biomarker-informed (EGFR/ALK/KRAS wildtype) testing initiated by pathologists and clinician-initiated strategies. Reflex IHC screening with FISH confirmation of positive cases yielded the best results for TAT, TP detection rate, and cost. IHC screening saved CAD 1,000,000 versus reflex FISH testing. NGS was the costliest reflex strategy. Biomarker-informed testing was cost-efficient but delayed TAT. Clinician-initiated testing was the least costly but resulted in long TAT and missed TP cases, highlighting the importance of reflex testing. Thus, reflex IHC screening for ROS1 with FISH confirmation provides a cost-efficient strategy with short TAT and maximizes the number of TP cases detected.

Tobacco exposure and immunotherapy response in PD-L1 positive lung cancer patients.

BACKGROUND: Tobacco exposure contributes to over 80 % of lung cancer cases. Smoking is associated with programmed death-ligand 1 (PD-L1) tumor expression and better outcomes from anti-programmed cell death protein 1 (anti-PD-1) therapy in patients with advanced non-small cell lung cancer (NSCLC). PD-L1 tumor expression is now routinely used to predict benefit from anti-PD-1 therapy in patients with advanced NSCLC. In this study, we explored the impact of smoking status on patient outcomes with anti-PD-1 therapy in addition to PD-L1 tumor expression. METHODS: A prospective real-world cohort of 268 patients with advanced NSCLC treated with anti-PD-1 monotherapy at the Princess Margaret Cancer Centre (PMCC) was used for this analysis. Logistic regression was performed to test factors associated with treatment response (RECIST v1.1), including PD-L1 tumour proportion score (TPS) and smoking status. RESULTS: Overall response rates (ORR) to immunotherapy were significantly higher in current and former smokers than never smokers (36 % vs 26 % vs 14 %; p = 0.02). In patients with PD-L1 tumour proportion score (TPS) ≥50 %, current smokers continued to experience better ORR to anti-PD-1 therapy than never smokers (58 % vs 19 %; p = 0.03). Current smoking was associated with higher response even after adjusting for level of PD-L1 TPS expression (adjusted odds ratio 5.9, 95 % CI 1.6-25.0, p = 0.03). Exploratory analysis demonstrated higher 1-year survival rates in smokers compared to never smokers (p = 0.003). CONCLUSIONS: Smoking remains an important factor associated with response to anti-PD-1 monotherapy. Advanced NSCLC patients with positive PD-L1 expression are more likely to respond to anti-PD-1 monotherapy if they are current smokers compared to never smokers.

Mechanisms of osimertinib resistance and emerging treatment options.

Osimertinib is an irreversible EGFR-tyrosine kinase inhibitor initially approved for treatment of EGFR-positive patients exhibiting a T790 M resistance mutation in the second line setting and now emerging as the new standard of care for all EGFR positive patients as first-line treatment. Despite its efficacy, resistance to osimertinib inevitably develops and mechanisms of resistance can be grouped broadly in two categories: on-target EGFR-dependent and off-target EGFR-independent mechanisms. EGFR-dependent resistance typically is associated with additional EGFR-mutations disrupting the osimertinib binding through changes in the binding site by allosteric/ conformational transitions; EGFR-independent mechanisms are related mostly to alternate pathway activation or aberrant downstream signalling but also to lineage plasticity leading to small cell transformation. MET amplification is the most frequent off-target mechanisms of resistance to osimertinib treatment and recently published early trials show promising results for combination of MET-inhibitors with osimertinib upon development of resistance. This review will summarize mechanisms of resistance overall and in different treatment settings and will focus on potential new treatment options targeting specific acquired alterations after osimertinib failure.