Genotype-Specific Differences in Circulating Tumor DNA Levels in Advanced NSCLC.

INTRODUCTION: Plasma-based circulating tumor DNA (ctDNA) is an established biomarker for molecular profiling with emerging applications in disease monitoring in multiple tumor types, including, NSCLC. However, determinants of ctDNA shedding and correlation with tumor burden are incompletely understood, particularly in advanced-stage disease. METHODS: We retrospectively analyzed ctDNA-based and tissue-based genomic data and imaging from 144 patients with NSCLC. Tumor burden was quantified with computed tomography (CT) and brain magnetic resonance imaging for the overall cohort and 18F-fludeoxyglucose positron emission tomography-CT in a subset of patients. RESULTS: There was a moderate but statistically significant correlation between ctDNA variant allele frequency and multiple imaging measures of tumor burden such as CT volume (rho = 0.34, p ≤ 0.0001) and metabolic tumor volume (rho = 0.36, p = 0.003). This correlation was strongest in KRAS-mutant tumors (rho = 0.56, p ≤ 0.001), followed by TP53 mutants (rho = 0.43, p ≤ 0.0001), and weakest in EGFR-mutated (EGFR+) tumors (rho = 0.24, p = 0.077). EGFR+ tumors with EGFR copy number gain had significantly higher variant allele frequency than EGFR+ without copy number gain (p ≤ 0.00001). In multivariable analysis, TP53 and EGFR mutations, visceral metastasis, and tumor burden were independent predictors of increased ctDNA shedding. CONCLUSIONS: Levels of detectable ctDNA were affected not only by tumor burden but also by tumor genotype. The genotype-specific differences observed may be due to variations in DNA shedding and cellular turnover. These findings have implications for the emerging use of ctDNA in NSCLC disease monitoring and early detection.

Neoadjuvant Chemotherapy Increases Cytotoxic T Cell, Tissue Resident Memory T Cell, and B Cell Infiltration in Resectable NSCLC.

INTRODUCTION: The combination of programmed cell death protein-1 or programmed death-ligand 1 immune checkpoint blockade and chemotherapy has revolutionized the treatment of advanced NSCLC, but the mechanisms underlying this synergy remain incompletely understood. In this study, we explored the relationships between neoadjuvant chemotherapy and the immune microenvironment (IME) of resectable NSCLC to identify novel mechanisms by which chemotherapy may enhance the effect of immune checkpoint blockade. METHODS: Genomic, transcriptomic, and immune profiling data of 511 patients treated with neoadjuvant chemotherapy followed by surgery (NCT) versus upfront surgery (US) were compared with determined differential characteristics of the IMEs derived from whole-exome sequencing (NCT = 18; US = 73), RNA microarray (NCT = 45; US = 202), flow cytometry (NCT = 17; US = 39), multiplex immunofluorescence (NCT = 10; US = 72), T-cell receptor sequencing (NCT = 16 and US = 63), and circulating cytokines (NCT = 18; US = 73). RESULTS: NCT was associated with increased infiltration of cytotoxic CD8+ T cells and CD20+ B cells. Moreover, NCT was associated with increases in CD8+CD103+ and CD4+CD103+PD-1+TIM3- tissue resident memory T cells. Gene expression profiling supported memory function of CD8+ and CD4+ T cells. However, NCT did not affect T-cell receptor clonality, richness, or tumor mutational burden. Finally, NCT was associated with decreased plasma BDNF (TrkB) at baseline and week 4 after surgery. CONCLUSIONS: Our study supports that, in the context of resectable NSCLC, neoadjuvant chemotherapy promotes antitumor immunity through T and B cell recruitment in the IME and through a phenotypic change toward cytotoxic and memory CD8+ and CD4+ memory helper T cells.

Multiomics profiling of primary lung cancers and distant metastases reveals immunosuppression as a common characteristic of tumor cells with metastatic plasticity.

BACKGROUND: Metastasis is the primary cause of cancer mortality accounting for 90% of cancer deaths. Our understanding of the molecular mechanisms driving metastasis is rudimentary. RESULTS: We perform whole exome sequencing (WES), RNA sequencing, methylation microarray, and immunohistochemistry (IHC) on 8 pairs of non-small cell lung cancer (NSCLC) primary tumors and matched distant metastases. Furthermore, we analyze published WES data from 35 primary NSCLC and metastasis pairs, and transcriptomic data from 4 autopsy cases with metastatic NSCLC and one metastatic lung cancer mouse model. The majority of somatic mutations are shared between primary tumors and paired distant metastases although mutational signatures suggest different mutagenesis processes in play before and after metastatic spread. Subclonal analysis reveals evidence of monoclonal seeding in 41 of 42 patients. Pathway analysis of transcriptomic data reveals that downregulated pathways in metastases are mainly immune-related. Further deconvolution analysis reveals significantly lower infiltration of various immune cell types in metastases with the exception of CD4+ T cells and M2 macrophages. These results are in line with lower densities of immune cells and higher CD4/CD8 ratios in metastases shown by IHC. Analysis of transcriptomic data from autopsy cases and animal models confirms that immunosuppression is also present in extracranial metastases. Significantly higher somatic copy number aberration and allelic imbalance burdens are identified in metastases. CONCLUSIONS: Metastasis is a molecularly late event, and immunosuppression driven by different molecular events, including somatic copy number aberration, may be a common characteristic of tumors with metastatic plasticity.

Molecular Landscape of BRAF-Mutant NSCLC Reveals an Association Between Clonality and Driver Mutations and Identifies Targetable Non-V600 Driver Mutations.

INTRODUCTION: Approximately 4% of NSCLC harbor BRAF mutations, and approximately 50% of these are non-V600 mutations. Treatment of tumors harboring non-V600 mutations is challenging because of functional heterogeneity and lack of knowledge regarding their clinical significance and response to targeted agents. METHODS: We conducted an integrative analysis of BRAF non-V600 mutations using genomic profiles of BRAF-mutant NSCLC from the Guardant360 database. BRAF mutations were categorized by clonality and class (1 and 2: RAS-independent; 3: RAS-dependent). Cell viability assays were performed in Ba/F3 models. Drug screens were performed in NSCLC cell lines. RESULTS: A total of 305 unique BRAF mutations were identified. Missense mutations were most common (276, 90%), and 45% were variants of unknown significance. F468S and N581Y were identified as novel activating mutations. Class 1 to 3 mutations had higher clonality than mutations of unknown class (p < 0.01). Three patients were treated with MEK with or without BRAF inhibitors. Patients harboring G469V and D594G mutations did not respond, whereas a patient with the L597R mutation had a durable response. Trametinib with or without dabrafenib, LXH254, and lifirafenib had more potent inhibition of BRAF non-V600-mutant NSCLC cell lines than other MEK, BRAF, and ERK inhibitors, comparable with the inhibition of BRAF V600E cell line. CONCLUSIONS: In BRAF-mutant NSCLC, clonality is higher in known functional mutations and may allow identification of variants of unknown significance that are more likely to be oncogenic drivers. Our data indicate that certain non-V600 mutations are responsive to MEK and BRAF inhibitors. This integration of genomic profiling and drug sensitivity may guide the treatment for BRAF-mutant NSCLC.

Programmed Death-Ligand 1 Heterogeneity and Its Impact on Benefit From Immune Checkpoint Inhibitors in NSCLC.

INTRODUCTION: Programmed death-ligand 1 (PD-L1) expression may vary in different disease sites and at different time points of the disease course. We aimed to investigate PD-L1 heterogeneity and its usefulness as a predictive value for immune checkpoint inhibitor (ICI) therapy in patients with NSCLC. METHODS: PD-L1 expression was analyzed in 1398 patients with NSCLC. The predictive value of PD-L1 for ICIs in 398 patients with metastatic NSCLC was assessed. RESULTS: PD-L1 was significantly associated with biopsy sites (p = 0.004). Adrenal, liver, and lymph node (LN) metastases had the highest PD-L1 expression as a continuous variable and at 1% or 50% cutoff. PD-L1 expression was lower in bone and brain metastases. Among 112 patients with two specimens tested, 55 (49%) had major changes in PD-L1 falling into different clinically relevant categories (<1%, 1%-49%, ≥50%) at different time points. Previous ICI therapy was associated with significant decrease in PD-L1 compared with treatment-naive counterparts (p = 0.015). Patients with metastatic NSCLC treated with ICI (n = 398) were divided into three cohorts on the basis of biopsy sites: lung (n = 252), LN (n = 85), and distant metastasis (n = 61). Higher PD-L1 in lung or distant metastasis specimens was associated with higher response rate, longer progression-free survival, and overall survival. However, PD-L1 in LN biopsies was not associated with either response or survival. CONCLUSIONS: PD-L1 varies substantially across different anatomical sites and changes during the clinical course. PD-L1 from different biopsy sites may have different predictive values for benefit from ICIs in NSCLC.

Simplified molecular classification of lung adenocarcinomas based on EGFR, KRAS, and TP53 mutations.

BACKGROUND: Gene expression profiling has consistently identified three molecular subtypes of lung adenocarcinoma that have prognostic implications. To facilitate stratification of patients with this disease into similar molecular subtypes, we developed and validated a simple, mutually exclusive classification. METHODS: Mutational status of EGFR, KRAS, and TP53 was used to define seven mutually exclusive molecular subtypes. A development cohort of 283 cytology specimens of lung adenocarcinoma was used to evaluate the associations between the proposed classification and clinicopathologic variables including demographic characteristics, smoking history, fluorescence in situ hybridization and molecular results. For validation and prognostic assessment, 63 of the 283 cytology specimens with available survival data were combined with a separate cohort of 428 surgical pathology specimens of lung adenocarcinoma. RESULTS: The proposed classification yielded significant associations between these molecular subtypes and clinical and prognostic features. We found better overall survival in patients who underwent surgery and had tumors enriched for EGFR mutations. Worse overall survival was associated with older age, stage IV disease, and tumors with co-mutations in KRAS and TP53. Interestingly, neither chemotherapy nor radiation therapy showed benefit to overall survival. CONCLUSIONS: The mutational status of EGFR, KRAS, and TP53 can be used to easily classify lung adenocarcinoma patients into seven subtypes that show a relationship with prognosis, especially in patients who underwent surgery, and these subtypes are similar to classifications based on more complex genomic methods reported previously.

Lymphovascular Invasion Is Associated With Mutational Burden and PD-L1 in Resected Lung Cancer.

BACKGROUND: High tumor mutational burden (TMB) and programmed death ligand 1 (PD-L1) expression are leading biomarkers in metastatic non-small cell lung cancer (NSCLC) and predict favorable response to checkpoint inhibitors. We sought to identify clinicopathologic characteristics associated with elevated TMB and PD-L1 expression among patients who underwent resection for NSCLC. METHODS: NSCLC patients undergoing primary resection (2016-2018) were prospectively enrolled in an immunogenomic profiling project. Multiplex immunofluorescence quantified densities (cells/mm2) of CD3+, CD3+CD8+, CD3+CD8+PD-1+, malignant cells (MCs), MCsPD-L1+, CD68+, CD68+PD-L1+, and CD20+ cells. Whole-exome sequencing quantified TMB (mutations/megabase). TMB and MCsPD-L1+ were dichotomized according to the median of each. RESULTS: A total of 55 patients completed multiplex immunofluorescence and whole-exome sequencing profiling. In this sample, 41.8% (23 of 55) had pathologic stage I disease. Median TMB and MCsPD-L1+ were 3.91 and 0.62 cells/mm2, respectively. TMB was higher among smokers (P = .001) and tumors with lymphovascular invasion (LVI) (P = .051). TMB was positively correlated with densities of MCsPD-L1+ (r = 0.293, P = .030), CD68+PD-L1+ (r = 0.289, P = .033), and CD20+ (r = 0.310, P = .043) cells. The density of MCsPD-L1+ was associated with increased CD3+CD8+ (r = 0.319, P = .018) and CD68+PD-L1+ (r = 0.371, P = .005) cells. Patients with PD-L1HighTMBHigh tumors (30.9%, 17 of 55) had higher intratumoral densities of CD3+, CD3+CD8+, CD68+, CD68+PD-L1+, and CD20+ cells. On multivariable analysis LVI was associated with synchronous elevated TMB and PD-L1 expression (odds ratio 3.53, P = .039). CONCLUSIONS: NSCLC tumors with elevated TMB and PD-L1 expression are associated with LVI and increased intratumoral immune cell infiltration. These findings may potentially improve patient selection for checkpoint inhibitor therapy trials in the adjuvant setting.

The Prognostic and Therapeutic Role of Genomic Subtyping by Sequencing Tumor or Cell-Free DNA in Pulmonary Large-Cell Neuroendocrine Carcinoma.

PURPOSE: The optimal systemic treatment for pulmonary large-cell neuroendocrine carcinoma (LCNEC) is still under debate. Previous studies showed that LCNEC with different genomic characteristics might respond differently to different chemotherapy regimens. In this study, we sought to investigate genomic subtyping using cell-free DNA (cfDNA) analysis in advanced LCNEC and assess its potential prognostic and predictive value. EXPERIMENTAL DESIGN: Tumor DNA and cfDNA from 63 patients with LCNEC were analyzed by target-captured sequencing. Survival and response analyses were applied to 54 patients with advanced stage incurable disease who received first-line chemotherapy. RESULTS: The mutation landscape of frequently mutated cancer genes in LCNEC from cfDNA closely resembled that from tumor DNA, which led to a 90% concordance in genomic subtyping. The 63 patients with LCNEC were classified into small-cell lung cancer (SCLC)-like and non-small cell lung cancer (NSCLC)-like LCNEC based on corresponding genomic features derived from tumor DNA and/or cfDNA. Overall, patients with SCLC-like LCNEC had a shorter overall survival than those with NSCLC-like LCNEC despite higher response rate (RR) to chemotherapy. Furthermore, treatment with etoposide-platinum was associated with superior response and survival in SCLC-like LCNEC compared with pemetrexed-platinum and gemcitabine/taxane-platinum doublets, while treatment with gemcitabine/taxane-platinum led to a shorter survival compared with etoposide-platinum or pemetrexed-platinum in patients with NSCLC-like LCNEC. CONCLUSIONS: Genomic subtyping has potential in prognostication and therapeutic decision-making for patients with LCNEC and cfDNA analysis may be a reliable alternative for genomic profiling of LCNEC.

Multi-region exome sequencing reveals genomic evolution from preneoplasia to lung adenocarcinoma.

There has been a dramatic increase in the detection of lung nodules, many of which are preneoplasia atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (ADC). The molecular landscape and the evolutionary trajectory of lung preneoplasia have not been well defined. Here, we perform multi-region exome sequencing of 116 resected lung nodules including AAH (n = 22), AIS (n = 27), MIA (n = 54) and synchronous ADC (n = 13). Comparing AAH to AIS, MIA and ADC, we observe progressive genomic evolution at the single nucleotide level and demarcated evolution at the chromosomal level supporting the early lung carcinogenesis model from AAH to AIS, MIA and ADC. Subclonal analyses reveal a higher proportion of clonal mutations in AIS/MIA/ADC than AAH suggesting neoplastic transformation of lung preneoplasia is predominantly associated with a selective sweep of unfit subclones. Analysis of multifocal pulmonary nodules from the same patients reveal evidence of convergent evolution.

Targeting the Interplay between Epithelial-to-Mesenchymal-Transition and the Immune System for Effective Immunotherapy.

Over the last decade, both early diagnosis and targeted therapy have improved the survival rates of many cancer patients. Most recently, immunotherapy has revolutionized the treatment options for cancers such as melanoma. Unfortunately, a significant portion of cancers (including lung and breast cancers) do not respond to immunotherapy, and many of them develop resistance to chemotherapy. Molecular characterization of non-responsive cancers suggest that an embryonic program known as epithelial-mesenchymal transition (EMT), which is mostly latent in adults, can be activated under selective pressures, rendering these cancers resistant to chemo- and immunotherapies. EMT can also drive tumor metastases, which in turn also suppress the cancer-fighting activity of cytotoxic T cells that traffic into the tumor, causing immunotherapy to fail. In this review, we compare and contrast immunotherapy treatment options of non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC). We discuss why, despite breakthrough progress in immunotherapy, attaining predictable outcomes in the clinic is mostly an unsolved problem for these tumors. Although these two cancer types appear different based upon their tissues of origin and molecular classification, gene expression indicate that they possess many similarities. Patient tumors exhibit activation of EMT, and resulting stem cell properties in both these cancer types associate with metastasis and resistance to existing cancer therapies. In addition, the EMT transition in both these cancers plays a crucial role in immunosuppression, which exacerbates treatment resistance. To improve cancer-related survival we need to understand and circumvent, the mechanisms through which these tumors become therapy resistant. In this review, we discuss new information and complementary perspectives to inform combination treatment strategies to expand and improve the anti-tumor responses of currently available clinical immune checkpoint inhibitors.

PD-L1 Expression, Tumor Mutational Burden, and Cancer Gene Mutations Are Stronger Predictors of Benefit from Immune Checkpoint Blockade than HLA Class I Genotype in Non-Small Cell Lung Cancer.

INTRODUCTION: Immune checkpoint blockade (ICB) has revolutionized the treatment of NSCLC, but only approximately 15% of patients achieve durable benefit. Understanding mechanisms of resistance to ICB is pivotal in developing more effective treatment strategies. Recent studies showed that human leukocyte antigen (HLA) class I heterozygosity might be important in mediating benefit from ICB. We aimed to investigate the impact of HLA class I genotype on outcomes of patients with NSCLC treated with ICB. METHODS: We collected HLA typing, genomic, and clinical data from patients with advanced NSCLC treated with ICB at M. D. Anderson Cancer Center. We compared HLA class I-heterozygous and HLA class I-homozygous patients for progression-free survival (PFS) and overall survival (OS). HLA I supertype/alleles were also analyzed. To validate our findings, we also analyzed two previously published independent cohorts of patients with NSCLC (the CheckMate-012 and Chowell cohorts). RESULTS: No significant correlations were observed for HLA class I zygosity and PFS or OS in the M. D. Anderson Cancer Center (n = 200), CheckMate-012 (n = 75), or Chowell (n = 371) cohorts. No HLA class I supertype/allele was consistently shown to be correlated with PFS or OS. Predictors of worse outcome across the three cohorts included presence of targetable driver mutation, serine/threonine kinase 11 gene (STK11) mutation, negative programmed death ligand 1 expression, and low tumor mutational burden. CONCLUSIONS: HLA class I genotype is not correlated with survival in advanced NSCLC treated with ICB. This suggests that the impact of HLA class I diversity may be disease specific and that tumor genomic and immune markers are more impactful in predicting benefit from ICB in NSCLC.

Author Correction: Circulating tumor DNA analysis depicts subclonal architecture and genomic evolution of small cell lung cancer.

The original version of this Article contained an error in Fig. 2, in which the left y-axis labels 'tDNA' and 'ctDNA' were inadvertently inverted. This has been corrected in the PDF and HTML versions of the Article.

Targeted Tissue and Cell-Free Tumor DNA Sequencing of Advanced Lung Squamous-Cell Carcinoma Reveals Clinically Significant Prevalence of Actionable Alterations.

BACKGROUND: Major guidelines do not recommend routine molecular profiling of lung squamous-cell carcinoma (LUSC) because the prevalence of actionable alterations is thought to be low. Increased utilization of next-generation sequencing (NGS), particularly with cell-free circulating tumor DNA, facilitates reevaluation of this premise. PATIENTS AND METHODS: We retrospectively evaluated the prevalence of actionable alterations in 2 distinct LUSC cohorts totaling 492 patients. A total of 410 consecutive patients with stage 3B or 4 LUSC were tested with a targeted cell-free circulating DNA NGS assay, and 82 patients with LUSC of any stage were tested with a tissue NGS cancer panel. RESULTS: In the overall cohort, 467 patients (94.9%) had a diagnosis of LUSC, and 25 patients (5.1%) had mixed histology with a squamous component. A total of 10.5% of the LUSC subgroup had somatic alterations with therapeutic relevance, including in EGFR (2.8%), ALK/ROS1 (1.3%), BRAF (1.5%), and MET amplification or exon 14 skipping (5.1%). Sixteen percent of patients with mixed histology had an actionable alteration. In the LUSC subgroup, 3 evaluable patients were treated with targeted therapy for an actionable alteration; all of them experienced partial response. CONCLUSION: In this large, real-world LUSC cohort, we observed a clinically significant prevalence of actionable alterations. Accurate local histopathologic assessment in advanced-stage LUSC can be challenging. Further evaluation of the genomic landscape in this setting is warranted to potentially identify underappreciated treatment options.

Local Consolidation Therapy (LCT) After First Line Tyrosine Kinase Inhibitor (TKI) for Patients With EGFR Mutant Metastatic Non-small-cell Lung Cancer (NSCLC).

INTRODUCTION: Although most NSCLC patients with sensitizing epidermal growth factor receptor (EGFR) mutations have an impressive initial response, the vast majority has residual disease and develops acquired resistance after 9 to 14 months of EGFR tyrosine kinase (TKI) therapy. We recently reported a phase II trial showing that, for patients with molecularly unselected oligometastatic NSCLC who did not progress after first-line systemic therapy, local consolidation therapy (LCT) with surgery or radiation improved progression-free survival (PFS), compared with maintenance therapy alone. Herein, we report a retrospective analysis of LCT after TKI in patients with metastatic EGFR mutant NSCLC. PATIENTS AND METHODS: We identified patients with metastatic EGFR mutant NSCLC treated with TKI plus LCT or with TKI alone in the MD Anderson GEMINI (Genomic Marker-Guided Therapy Initiative) database and in our recently published LCT trial. PFS was compared between LCT plus TKI and TKI only treated patients using the log-rank test. RESULTS: We identified 129 patients with EGFR mutant NSCLC who were treated with first-line TKI and 12 that were treated with TKI followed by LCT. Among the 12 patients treated with TKI plus LCT, 8 patients had oligometastatic disease (defined as ≤ 3 metastases), and 4 patients had > 3 metastases. LCT regimens were hypofractionated radiotherapy or stereotactic ablative body radiotherapy for 11 patients and surgery for 1 patient. TKI followed by LCT resulted in a significantly longer PFS (36 months) compared with TKI alone (PFS, 14 months; log-rank P = .0024). CONCLUSIONS: Our data suggests that first-line TKI plus LCT is a promising therapeutic strategy for patients with EGFR mutant NSCLC that merits further investigation.

Applying Artificial Intelligence to Address the Knowledge Gaps in Cancer Care.

BACKGROUND: Rapid advances in science challenge the timely adoption of evidence-based care in community settings. To bridge the gap between what is possible and what is practiced, we researched approaches to developing an artificial intelligence (AI) application that can provide real-time patient-specific decision support. MATERIALS AND METHODS: The Oncology Expert Advisor (OEA) was designed to simulate peer-to-peer consultation with three core functions: patient history summarization, treatment options recommendation, and management advisory. Machine-learning algorithms were trained to construct a dynamic summary of patients cancer history and to suggest approved therapy or investigative trial options. All patient data used were retrospectively accrued. Ground truth was established for approximately 1,000 unique patients. The full Medline database of more than 23 million published abstracts was used as the literature corpus. RESULTS: OEA's accuracies of searching disparate sources within electronic medical records to extract complex clinical concepts from unstructured text documents varied, with F1 scores of 90%-96% for non-time-dependent concepts (e.g., diagnosis) and F1 scores of 63%-65% for time-dependent concepts (e.g., therapy history timeline). Based on constructed patient profiles, OEA suggests approved therapy options linked to supporting evidence (99.9% recall; 88% precision), and screens for eligible clinical trials on ClinicalTrials.gov (97.9% recall; 96.9% precision). CONCLUSION: Our results demonstrated technical feasibility of an AI-powered application to construct longitudinal patient profiles in context and to suggest evidence-based treatment and trial options. Our experience highlighted the necessity of collaboration across clinical and AI domains, and the requirement of clinical expertise throughout the process, from design to training to testing. IMPLICATIONS FOR PRACTICE: Artificial intelligence (AI)-powered digital advisors such as the Oncology Expert Advisor have the potential to augment the capacity and update the knowledge base of practicing oncologists. By constructing dynamic patient profiles from disparate data sources and organizing and vetting vast literature for relevance to a specific patient, such AI applications could empower oncologists to consider all therapy options based on the latest scientific evidence for their patients, and help them spend less time on information "hunting and gathering" and more time with the patients. However, realization of this will require not only AI technology maturation but also active participation and leadership by clincial experts.

Landscape of EGFR-Dependent and -Independent Resistance Mechanisms to Osimertinib and Continuation Therapy Beyond Progression in EGFR-Mutant NSCLC.

PURPOSE: Osimertinib was initially approved for T790M-positive non-small cell lung cancer (NSCLC) and, more recently, for first-line treatment of EGFR-mutant NSCLC. However, resistance mechanisms to osimertinib have been incompletely described. EXPERIMENTAL DESIGN: Using cohorts from The University of Texas MD Anderson Lung Cancer Moonshot GEMINI and Moffitt Cancer Center lung cancer databases, we collected clinical data for patients treated with osimertinib. Molecular profiling analysis was performed at the time of progression in a subset of the patients. RESULTS: In the 118 patients treated with osimertinib, 42 had molecular profiling at progression. T790M was preserved in 21 (50%) patients and lost in 21 (50%). EGFR C797 and L792 (26%) mutations were the most common resistance mechanism and were observed exclusively in T790M-preserved cases. MET amplification was the second most common alteration (14%). Recurrent alterations were observed in 22 genes/pathways, including PIK3CA, FGFR, and RET. Preclinical studies confirmed MET, PIK3CA, and epithelial-to-mesenchymal transition as potential resistance drivers. Alterations of cell-cycle genes were associated with shorter median progression-free survival (PFS, 4.4 vs. 8.8 months, P = 0.01). In 76 patients with progression, osimertinib was continued in 47 cases with a median second PFS (PFS2) of 12.6 months; 21 patients received local consolidation radiation with a median PFS of 15.5 months. Continuation of osimertinib beyond progression was associated with a longer overall survival compared with discontinuation (11.2 vs. 6.1 months, P = 0.02). CONCLUSIONS: Osimertinib resistance is associated with diverse, predominantly EGFR-independent genomic alterations. Continuation of osimertinib after progression, alone or in conjunction with radiotherapy, may provide prolonged clinical benefit in selected patients.See related commentary by Devarakonda and Govindan, p. 6112.

Circulating tumor DNA analysis depicts subclonal architecture and genomic evolution of small cell lung cancer.

Subclonal architecture and genomic evolution of small-cell lung cancer (SCLC) under treatment has not been well studied primarily due to lack of tumor specimens, particularly longitudinal samples acquired during treatment. SCLC is characterized by early hematogenous spread, which makes circulating cell-free tumor DNA (ctDNA) sequencing a promising modality for genomic profiling. Here, we perform targeted deep sequencing of 430 cancer genes on pre-treatment tumor biopsies, as well as on plasma samples collected prior to and during treatment from 22 SCLC patients. Similar subclonal architecture is observed between pre-treatment ctDNA and paired tumor DNA. Mean variant allele frequency of clonal mutations from pre-treatment ctDNA is associated with progression-free survival and overall survival. Pre- and post-treatment ctDNA mutational analysis demonstrate that mutations of DNA repair and NOTCH signaling pathways are enriched in post-treatment samples. These data suggest that ctDNA sequencing is promising to delineate genomic landscape, subclonal architecture, and genomic evolution of SCLC.

Mechanisms and clinical activity of an EGFR and HER2 exon 20-selective kinase inhibitor in non-small cell lung cancer.

Although most activating mutations of epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancers (NSCLCs) are sensitive to available EGFR tyrosine kinase inhibitors (TKIs), a subset with alterations in exon 20 of EGFR and HER2 are intrinsically resistant and lack an effective therapy. We used in silico, in vitro, and in vivo testing to model structural alterations induced by exon 20 mutations and to identify effective inhibitors. 3D modeling indicated alterations restricted the size of the drug-binding pocket, limiting the binding of large, rigid inhibitors. We found that poziotinib, owing to its small size and flexibility, can circumvent these steric changes and is a potent inhibitor of the most common EGFR and HER2 exon 20 mutants. Poziotinib demonstrated greater activity than approved EGFR TKIs in vitro and in patient-derived xenograft models of EGFR or HER2 exon 20 mutant NSCLC and in genetically engineered mouse models of NSCLC. In a phase 2 trial, the first 11 patients with NSCLC with EGFR exon 20 mutations receiving poziotinib had a confirmed objective response rate of 64%. These data identify poziotinib as a potent, clinically active inhibitor of EGFR and HER2 exon 20 mutations and illuminate the molecular features of TKIs that may circumvent steric changes induced by these mutations.

Multiregion gene expression profiling reveals heterogeneity in molecular subtypes and immunotherapy response signatures in lung cancer.

Intra-tumor heterogeneity may be present at all molecular levels. Genomic intra-tumor heterogeneity at the exome level has been reported in many cancer types, but comprehensive gene expression intra-tumor heterogeneity has not been well studied. Here, we delineated the gene expression intra-tumor heterogeneity by exploring gene expression profiles of 35 tumor regions from 10 non-small cell lung cancer tumors (three or four regions/tumor), including adenocarcinoma, squamous cell carcinoma, large-cell carcinoma, and pleomorphic carcinoma of the lung. Using Affymetrix Gene 1.0 ST arrays, we generated the gene expression data for every sample. Inter-tumor heterogeneity was generally higher than intra-tumor heterogeneity, but some tumors showed a substantial level of intra-tumor heterogeneity. The analysis of various clinically relevant gene expression signatures including molecular subtype, epithelial-to-mesenchymal transition, and anti-PD-1 resistance signatures also revealed heterogeneity between different regions of the same tumor. The gene expression intra-tumor heterogeneity we observed was associated with heterogeneous tumor microenvironments represented by stromal and immune cells infiltrated. Our data suggest that RNA-based prognostic or predictive molecular tests should be carefully conducted in consideration of the gene expression intra-tumor heterogeneity.