Early Detection and Interception of Lung Cancer.

Recent advances in lung cancer treatment have led to dramatic improvements in 5-year survival rates. And yet, lung cancer remains the leading cause of cancer-related mortality, in large part, because it is often diagnosed at an advanced stage, when cure is no longer possible. Lung cancer screening (LCS) is essential for intercepting the disease at an earlier stage. Unfortunately, LCS has been poorly adopted in the United States, with less than 5% of eligible patients being screened nationally. This article will describe the data supporting LCS, the obstacles to LCS implementation, and the promising opportunities that lie ahead.

Tumor cell-based liquid biopsy using high-throughput microfluidic enrichment of entire leukapheresis product.

Circulating Tumor Cells (CTCs), interrogated by sampling blood from patients with cancer, contain multiple analytes, including intact RNA, high molecular weight DNA, proteins, and metabolic markers. However, the clinical utility of tumor cell-based liquid biopsy has been limited since CTCs are very rare, and current technologies cannot process the blood volumes required to isolate a sufficient number of tumor cells for in-depth assays. We previously described a high-throughput microfluidic prototype utilizing high-flow channels and amplification of cell sorting forces through magnetic lenses. Here, we apply this technology to analyze patient-derived leukapheresis products, interrogating a mean blood volume of 5.83 liters from patients with metastatic cancer, with a median of 2,799 CTCs purified per patient. Isolation of many CTCs from individual patients enables characterization of their morphological and molecular heterogeneity, including cell and nuclear size and RNA expression. It also allows robust detection of gene copy number variation, a definitive cancer marker with potential diagnostic applications. High-volume microfluidic enrichment of CTCs constitutes a new dimension in liquid biopsies.

Phase II Study of Osimertinib in Patients With Epidermal Growth Factor Receptor Mutations: Results From the NCI-MATCH ECOG-ACRIN (EAY131) Trial Subprotocol E.

PURPOSE: The National Cancer Institute Molecular Analysis for Therapy Choice trial is a signal-finding genomically driven platform trial that assigns patients with any advanced refractory solid tumor, lymphoma, or myeloma to targeted therapies on the basis of next-generation sequencing results. Subprotocol E evaluated osimertinib, an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, in patients with EGFR mutations. METHODS: Eligible patients had EGFR mutations (T790M or rare activating) and received osimertinib 80 mg once daily. Patients with lung cancer with EGFR T790M were excluded. The primary end point was objective response rate (ORR), and the secondary end points were 6-month progression-free survival (PFS), overall survival, and toxicity. RESULTS: A total of 19 patients were enrolled: 17 were evaluable for toxicity and 13 for efficacy. The median age of the 13 included in the efficacy analysis was 63 years, 62% had Eastern Cooperative Oncology Group performance status 1, and 31% received >three previous systemic therapies. The most common tumor type was brain cancers (54%). The ORR was 15.4% (n = 2 of 13; 90% CI, 2.8 to 41.0) and 6-month PFS was 16.7% (90% CI, 0 to 34.4). The two confirmed RECIST responses were observed in a patient with neuroendocrine carcinoma not otherwise specified (EGFR exon 20 S768T and exon 18 G719C mutation) and a patient with low-grade epithelial carcinoma of the paranasal sinus (EGFR D770_N771insSVD). The most common (>20%) treatment-related adverse events were diarrhea, thrombocytopenia, and maculopapular rash. CONCLUSION: In this pretreated cohort, osimertinib did not meet the prespecified end point threshold for efficacy, but responses were seen in a neuroendocrine carcinoma with an EGFR exon 20 S768T and exon 18 G719C mutation and an epithelial carcinoma with an EGFR D770_N771insSVD mutation. Osimertinib was well tolerated and had a safety profile consistent with previous studies.

Pack-Year Smoking History: An Inadequate and Biased Measure to Determine Lung Cancer Screening Eligibility.

PURPOSE: Pack-year smoking history is an imperfect and biased measure of cumulative tobacco exposure. The use of pack-year smoking history to determine lung cancer screening eligibility in the current US Preventive Services Task Force (USPSTF) guideline may unintentionally exclude many high-risk individuals, especially those from racial and ethnic minority groups. It is unclear whether using a smoking duration cutoff instead of a smoking pack-year cutoff would improve the selection of individuals for screening. METHODS: We analyzed 49,703 individuals with a smoking history from the Southern Community Cohort Study (SCCS) and 22,126 individuals with a smoking history from the Black Women's Health Study (BWHS) to assess eligibility for screening under the USPSTF guideline versus a proposed guideline that replaces the ≥20-pack-year criterion with a ≥20-year smoking duration criterion. RESULTS: Under the USPSTF guideline, only 57.6% of Black patients with lung cancer in the SCCS would have qualified for screening, whereas a significantly higher percentage of White patients with lung cancer (74.0%) would have qualified (P < .001). Under the proposed guideline, the percentage of Black and White patients with lung cancer who would have qualified for screening increased to 85.3% and 82.0%, respectively, eradicating the disparity in screening eligibility between the groups. In the BWHS, using a 20-year smoking duration cutoff instead of a 20-pack-year cutoff increased the percentage of Black women with lung cancer who would have qualified for screening from 42.5% to 63.8%. CONCLUSION: Use of a 20-year smoking duration cutoff instead of a 20-pack-year cutoff greatly increases the proportion of patients with lung cancer who would qualify for screening and eliminates the racial disparity in screening eligibility between Black versus White individuals; smoking duration has the added benefit of being easier to calculate and being a more precise assessment of smoking exposure compared with pack-year smoking history.

Deploying blood-based cancer screening.

AI-based risk assessment may enable personalized blood-based multicancer screening.

Lung Cancer in Women: The Past, Present, and Future.

Lung cancer is the leading cause of cancer death for women in multiple countries including the United States. Women are exposed to unique risk factors that remain largely understudied such as indoor pollution, second-hand tobacco exposure, biological differences, gender differences in tolerability and response to therapy in lung cancer, and societal gender roles, that create distinct survivorship needs. Women continue to lack representation in lung cancer clinical trials and are typically treated with data generated from majority male patient study populations, which may be inappropriate to extrapolate and generalize to females. Current lung cancer treatment and screening guidelines do not incorporate sex-specific differences and physicians also often do not account for gender differences when choosing treatments or discussing survivorship needs. To best provide targeted treatment approaches, greater representation of women in lung cancer clinical trials and further research is necessary. Clinicians should understand the unique factors and consequences associated with lung cancer in women; thus, a holistic approach that acknowledges environmental and societal factors is necessary.

Role of sex in lung cancer risk prediction based on single low-dose chest computed tomography.

A validated open-source deep-learning algorithm called Sybil can accurately predict long-term lung cancer risk from a single low-dose chest computed tomography (LDCT). However, Sybil was trained on a majority-male cohort. Use of artificial intelligence algorithms trained on imbalanced cohorts may lead to inequitable outcomes in real-world settings. We aimed to study whether Sybil predicts lung cancer risk equally regardless of sex. We analyzed 10,573 LDCTs from 6127 consecutive lung cancer screening participants across a health system between 2015 and 2021. Sybil achieved AUCs of 0.89 (95% CI: 0.85-0.93) for females and 0.89 (95% CI: 0.85-0.94) for males at 1 year, p = 0.92. At 6 years, the AUC was 0.87 (95% CI: 0.83-0.93) for females and 0.79 (95% CI: 0.72-0.86) for males, p = 0.01. In conclusion, Sybil can accurately predict future lung cancer risk in females and males in a real-world setting and performs better in females than in males for predicting 6-year lung cancer risk.

Artificial Intelligence and Machine Learning in Lung Cancer Screening.

Recent advances in artificial intelligence and machine learning (AI/ML) hold substantial promise to address some of the current challenges in lung cancer screening and improve health equity. This article reviews the status and future directions of AI/ML tools in the lung cancer screening workflow, focusing on determining screening eligibility, radiation dose reduction and image denoising for low-dose chest computed tomography (CT), lung nodule detection, lung nodule classification, and determining optimal screening intervals. AI/ML tools can assess for chronic diseases on CT, which creates opportunities to improve population health through opportunistic screening.

Germline mutations and developmental mosaicism underlying EGFR-mutant lung cancer.

While the development of multiple primary tumors in smokers with lung cancer can be attributed to carcinogen-induced field cancerization, the occurrence of multiple primary tumors in individuals with EGFR-mutant lung cancer who lack known environmental exposures remains unexplained. We identified ten patients with early-stage, resectable non-small cell lung cancer who presented with multiple anatomically distinct EGFR-mutant tumors. We analyzed the phylogenetic relationships among multiple tumors from each patient using whole exome sequencing (WES) and hypermutable poly-guanine (poly-G) repeat genotyping, as orthogonal methods for lineage tracing. In two patients, we identified germline EGFR variants, which confer moderately enhanced signaling when modeled in vitro. In four other patients, developmental mosaicism is supported by the poly-G lineage tracing and WES, indicating a common non-germline cell-of-origin. Thus, developmental mosaicism and germline variants define two distinct mechanisms of genetic predisposition to multiple EGFR-mutant primary tumors, with implications for understanding their etiology and clinical management.

Efficacy and Tolerability of ALK/MET Combinations in Patients With ALK-Rearranged Lung Cancer With Acquired MET Amplification: A Retrospective Analysis.

Introduction: MET amplification is a potentially actionable resistance mechanism in ALK-rearranged (ALK+) lung cancer. Studies describing treatment outcomes of this molecular subgroup are lacking. Methods: We assembled a cohort of patients with ALK+ lung cancer and acquired MET amplification (identified by tissue or plasma) who received regimens targeting both ALK and MET. Efficacy and safety were assessed using the Response Evaluation Criteria in Solid Tumors version 1.1 and Common Terminology Criteria for Adverse Events version 4.03, respectively. Results: A total of 12 patients were included in the series. MET amplification was detected after a median of 1.5 (range 1-5) lines of therapy. Four distinct regimens were implemented to address MET amplification: crizotinib (n = 2), lorlatinib plus crizotinib (n = 6), alectinib plus capmatinib (n = 3), and alectinib plus crizotinib (n = 1). Partial responses were observed in five (42%) of 12 patients, including patients who received crizotinib (n = one of two), lorlatinib plus crizotinib (n = three of six), and alectinib plus capmatinib (n = one of three). Primary progression was observed in four patients (33%). Grades 1 to 2 peripheral edema, occurring in seven (58%) patients, was found with both crizotinib and capmatinib. One patient required dose reduction of capmatinib plus alectinib for persistent grade 2 edema. Across the regimens, one patient discontinued therapy for toxicity, specifically neurocognitive toxicity from lorlatinib plus crizotinib. At progression on ALK+ MET therapy, potential resistance mechanisms included MET copy number changes and ALK kinase domain mutations. Conclusions: Combined ALK and MET inhibition is associated with moderate antitumor activity in patients with ALK+ NSCLC with concurrent MET amplification. Prospective studies are indicated to confirm activity and identify individuals most likely to benefit from the treatment.

Therapy-induced APOBEC3A drives evolution of persistent cancer cells.

Acquired drug resistance to anticancer targeted therapies remains an unsolved clinical problem. Although many drivers of acquired drug resistance have been identified1-4, the underlying molecular mechanisms shaping tumour evolution during treatment are incompletely understood. Genomic profiling of patient tumours has implicated apolipoprotein B messenger RNA editing catalytic polypeptide-like (APOBEC) cytidine deaminases in tumour evolution; however, their role during therapy and the development of acquired drug resistance is undefined. Here we report that lung cancer targeted therapies commonly used in the clinic can induce cytidine deaminase APOBEC3A (A3A), leading to sustained mutagenesis in drug-tolerant cancer cells persisting during therapy. Therapy-induced A3A promotes the formation of double-strand DNA breaks, increasing genomic instability in drug-tolerant persisters. Deletion of A3A reduces APOBEC mutations and structural variations in persister cells and delays the development of drug resistance. APOBEC mutational signatures are enriched in tumours from patients with lung cancer who progressed after extended responses to targeted therapies. This study shows that induction of A3A in response to targeted therapies drives evolution of drug-tolerant persister cells, suggesting that suppression of A3A expression or activity may represent a potential therapeutic strategy in the prevention or delay of acquired resistance to lung cancer targeted therapy.

B-Cell Infiltrate in the Tumor Microenvironment Is Associated With Improved Survival in Resected Lung Adenocarcinoma.

Introduction: Relapse is common after resection of lung adenocarcinoma (LUAD). Features of the tumor microenvironment (TME) which influence postsurgical survival outcomes are poorly characterized. Here, we analyzed the TME of more than 1500 LUAD specimens to identify the relationship between B-cell infiltration and prognosis. Methods: Whole exome sequencing and bulk RNA sequencing were performed on LUADs and adjacent normal lung tissue. Relapse-free survival and overall survival (OS) were retrospectively correlated with characteristics of the tumor and TME in three data sets. Results: High B-cell content (defined as >10% B cells) was associated with improved OS in both a The Cancer Genome Atlas-resected LUAD data set (p = 0.01) and a separate institutional stage II LUAD data set (p = 0.04, median not reached versus 89.5 mo). A validation cohort consisting of pooled microarray data representing more than 1400 resected stage I to III LUADs confirmed the association between greater B-cell abundance, specifically higher B-cell expression, and longer postsurgical survival (median OS 90 versus 71 mo, p < 0.01). Relapse-free survival was longer for patients with adenocarcinomas with high B-cell content across data sets, but it did not reach statistical significance. Subcategorization of B-cell subsets indicated that high naive B-cell content was most predictive of survival. There was no correlation between programmed death-ligand 1 expression, lymphoid aggregates, or overall immune infiltrate density and survival outcomes across the cohorts. Conclusions: The growing adjuvant immunotherapy repertoire has increased the urgency for identifying prognostic and predictive biomarkers. Comprehensive profiling of more than 1500 LUADs suggests that high tumor-infiltrating B-cell content is a favorable prognostic marker.

Phase III Study of Afatinib or Cisplatin Plus Pemetrexed in Patients With Metastatic Lung Adenocarcinoma With EGFR Mutations.

PURPOSE: The LUX-Lung 3 study investigated the efficacy of chemotherapy compared with afatinib, a selective, orally bioavailable ErbB family blocker that irreversibly blocks signaling from epidermal growth factor receptor (EGFR/ErbB1), human epidermal growth factor receptor 2 (HER2/ErbB2), and ErbB4 and has wide-spectrum preclinical activity against EGFR mutations. A phase II study of afatinib in EGFR mutation-positive lung adenocarcinoma demonstrated high response rates and progression-free survival (PFS). PATIENTS AND METHODS: In this phase III study, eligible patients with stage IIIB/IV lung adenocarcinoma were screened for EGFR mutations. Mutation-positive patients were stratified by mutation type (exon 19 deletion, L858R, or other) and race (Asian or non-Asian) before two-to-one random assignment to 40 mg afatinib per day or up to six cycles of cisplatin plus pemetrexed chemotherapy at standard doses every 21 days. The primary end point was PFS by independent review. Secondary end points included tumor response, overall survival, adverse events, and patient-reported outcomes (PROs). RESULTS: A total of 1,269 patients were screened, and 345 were randomly assigned to treatment. Median PFS was 11.1 months for afatinib and 6.9 months for chemotherapy (hazard ratio [HR], 0.58; 95% CI, 0.43 to 0.78; P = .001). Median PFS among those with exon 19 deletions and L858R EGFR mutations (n = 308) was 13.6 months for afatinib and 6.9 months for chemotherapy (HR, 0.47; 95% CI, 0.34 to 0.65; P = .001). The most common treatment-related adverse events were diarrhea, rash/acne, and stomatitis for afatinib and nausea, fatigue, and decreased appetite for chemotherapy. PROs favored afatinib, with better control of cough, dyspnea, and pain. CONCLUSION: Afatinib is associated with prolongation of PFS when compared with standard doublet chemotherapy in patients with advanced lung adenocarcinoma and EGFR mutations.

Expanding the Reach and Grasp of Lung Cancer Screening.

Low-dose computer tomographic (LDCT) lung cancer screening reduces lung cancer-specific and all-cause mortality among high-risk individuals, but implementation has been challenging. Despite health insurance coverage for lung cancer screening in the United States since 2015, fewer than 10% of eligible persons have participated; striking geographic, racial, and socioeconomic disparities were already evident, especially in the populations at greatest risk of lung cancer and, therefore, most likely to benefit from screening; and adherence to subsequent testing is significantly lower than that reported in clinical trials, potentially reducing the realized benefit. Lung cancer screening is a covered health care benefit in very few countries. Obtaining the full population-level benefit of lung cancer screening will require improved participation of already eligible persons (the grasp of screening) and improved eligibility criteria that more closely match up with the full spectrum of persons at risk (the reach of screening), irrespective of smoking history. We used the socioecological framework of health care to systematically review implementation barriers to lung cancer screening and discuss multilevel solutions. We also discussed guideline-concordant management of incidentally detected lung nodules as a complementary approach to early lung cancer detection that can extend the reach and strengthen the grasp of screening. Furthermore, we discussed ongoing efforts in Asia to explore the possibility of LDCT screening in populations in whom lung cancer risk is relatively independent of smoking. Finally, we summarized innovative technological solutions, including biomarker selection and artificial intelligence strategies, to improve the safety, effectiveness, and cost-effectiveness of lung cancer screening in diverse populations.

Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography.

PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely to benefit. We hypothesized that a deep learning model assessing the entire volumetric LDCT data could be built to predict individual risk without requiring additional demographic or clinical data. METHODS: We developed a model called Sybil using LDCTs from the National Lung Screening Trial (NLST). Sybil requires only one LDCT and does not require clinical data or radiologist annotations; it can run in real time in the background on a radiology reading station. Sybil was validated on three independent data sets: a heldout set of 6,282 LDCTs from NLST participants, 8,821 LDCTs from Massachusetts General Hospital (MGH), and 12,280 LDCTs from Chang Gung Memorial Hospital (CGMH, which included people with a range of smoking history including nonsmokers). RESULTS: Sybil achieved area under the receiver-operator curves for lung cancer prediction at 1 year of 0.92 (95% CI, 0.88 to 0.95) on NLST, 0.86 (95% CI, 0.82 to 0.90) on MGH, and 0.94 (95% CI, 0.91 to 1.00) on CGMH external validation sets. Concordance indices over 6 years were 0.75 (95% CI, 0.72 to 0.78), 0.81 (95% CI, 0.77 to 0.85), and 0.80 (95% CI, 0.75 to 0.86) for NLST, MGH, and CGMH, respectively. CONCLUSION: Sybil can accurately predict an individual's future lung cancer risk from a single LDCT scan to further enable personalized screening. Future study is required to understand Sybil's clinical applications. Our model and annotations are publicly available.[Media: see text].

Osimertinib + Savolitinib to Overcome Acquired MET-Mediated Resistance in Epidermal Growth Factor Receptor-Mutated, MET-Amplified Non-Small Cell Lung Cancer: TATTON.

MET-inhibitor and EGFR tyrosine kinase inhibitor (EGFR-TKI) combination therapy could overcome acquired MET-mediated osimertinib resistance. We present the final phase Ib TATTON (NCT02143466) analysis (Part B, n = 138/Part D, n = 42) assessing oral savolitinib 600 mg/300 mg once daily (q.d.) + osimertinib 80 mg q.d. in patients with MET-amplified, EGFR-mutated (EGFRm) advanced non-small cell lung cancer (NSCLC) and progression on prior EGFR-TKI. An acceptable safety profile was observed. In Parts B and D, respectively, objective response rates were 33% to 67% and 62%, and median progression-free survival (PFS) was 5.5 to 11.1 months and 9.0 months. Increased antitumor activity may occur with MET copy number ≥10. EGFRm circulating tumor DNA clearance on treatment predicted longer PFS in patients with detectable baseline ctDNA, while acquired resistance mechanisms to osimertinib + savolitinib were mediated by MET, EGFR, or KRAS alterations. SIGNIFICANCE: The savolitinib + osimertinib combination represents a promising therapy in patients with MET-amplified/overexpressed, EGFRm advanced NSCLC with disease progression on a prior EGFR-TKI. Acquired resistance mechanisms to this combination include those via MET, EGFR, and KRAS. On-treatment ctDNA dynamics can predict clinical outcomes and may provide an opportunity to inform earlier decision-making. This article is highlighted in the In This Issue feature, p. 1.

Clinicopathologic Characteristics and Outcomes for Patients With KRAS G12D-Mutant NSCLC.

Introduction: Co-occurring mutations in KRAS-mutant NSCLC are associated with discrete biological properties and modulate therapeutic susceptibilities. As G12D-specific inhibitors are expected to enter the clinic, we sought to investigate the characteristics and outcomes of patients with KRAS G12D-mutant NSCLC. Methods: This was a retrospective single-institution study. Patients with NSCLC and KRAS G12D mutations detected by the Massachusetts General Hospital SNaPshot next-generation sequencing assay were identified. Clinical and pathologic characteristics were collected by chart review. Results: A total of 107 patients with KRAS G12D-mutant NSCLC were identified. Most patients were former smokers (80, 74.8%) and had tumors with adenocarcinoma pathologic subtype (93, 86.9%). Among 56 patients evaluated for programmed death-ligand 1 expression, tumor proportion score was less than 50% in 43 (76.8%). Concomitant mutations were identified in STK11 (17 of 107, 15.9%), KEAP1 (10 of 58, 17.2%), TP53 (36 of 107, 33.6%), and SMARCA4 (11 of 107, 10.3%). Among 57 patients treated with first-line therapy, patients with STK11 co-mutations had shorter progression-free survival (1.2 mo, 95% confidence interval [CI]: 0.6-2.9 versus 4.1 mo, 95% CI: 2.5-6.0, p = 0.0235) and overall survival (4.3 mo, 95% CI: 1.2-10.6 versus 17.9 mo, 95% CI: 8.6-31.1, p = 0.0018) compared with wild type. Patients with KEAP1 co-mutations had shorter overall survival (4.6 mo, 95% CI: 1.2-10.6 versus 17.9 mo, 95% CI: 7.1-30.1, p = 0.0125) than those without. TP53 co-mutations exerted no influence on survival. Conclusions: Co-occurring mutations were common in patients with KRAS G12D-mutant NSCLC. STK11 and KEAP1 co-mutations were associated with worse clinical outcomes, whereas co-occurring TP53 did not affect survival.