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Dual blockade of the EGFR and VEGF pathways in EGFR-mutated metastatic non-small-cell lung cancer (NSCLC) is supported by preclinical and clinical data, yet the approach is not widely implemented. RELAY assessed erlotinib, an EGFR tyrosine kinase inhibitor (TKI) standard of care, plus ramucirumab, a human IgG1 VEGFR2 antagonist, or placebo in patients with untreated EGFR-mutated metastatic NSCLC. This is a worldwide, double-blind, phase 3 trial done in 100 hospitals, clinics, and medical centres in 13 countries. Eligible patients were aged 18 years or older (20 years or older in Japan and Taiwan) at the time of study entry, had stage IV NSCLC, with an EGFR exon 19 deletion (ex19del) or exon 21 substitution (Leu858Arg) mutation, an Eastern Cooperative Oncology Group performance status of 0 or 1, and no CNS metastases. We randomly assigned eligible patients in a 1:1 ratio to receive oral erlotinib (150 mg/day) plus either intravenous ramucirumab (10 mg/kg) or matching placebo once every 2 weeks. Randomisation was done by an interactive web response system with a computer-generated sequence and stratified by sex, geographical region, EGFR mutation type, and EGFR testing method. The primary endpoint was investigator-assessed progression-free survival in the intention-to-treat population. Safety was assessed in all patients who received at least one dose of study treatment. This trial is registered at ClinicalTrials.gov, NCT02411448, and is ongoing for long-term survival follow-up. Between Jan 28, 2016, and Feb 1, 2018, 449 eligible patients were enrolled and randomly assigned to treatment with ramucirumab plus erlotinib (n=224) or placebo plus erlotinib (n=225). Median duration of follow-up was 20·7 months (IQR 15·8–27·2). At the time of primary analysis, progression-free survival was significantly longer in the ramucirumab plus erlotinib group (19·4 months [95% CI 15·4–21·6]) than in the placebo plus erlotinib group (12·4 months [11·0–13·5]), with a stratified hazard ratio of 0·59 (95% CI 0·46–0·76; p<0·0001). Grade 3–4 treatment-emergent adverse events were reported in 159 (72%) of 221 patients in the ramucirumab plus erlotinib group versus 121 (54%) of 225 in the placebo plus erlotinib group. The most common grade 3–4 treatment-emergent adverse events in the ramucirumab plus erlotinib group were hypertension (52 [24%]; grade 3 only) and dermatitis acneiform (33 [15%]), and in the placebo plus erlotinib group were dermatitis acneiform (20 [9%]) and increased alanine aminotransferase (17 [8%]). Treatment-emergent serious adverse events were reported in 65 (29%) of 221 patients in the ramucirumab plus erlotinib group and 47 (21%) of 225 in the placebo plus erlotinib group. The most common serious adverse events of any grade in the ramucirumab plus erlotinib group were pneumonia (seven [3%]) and cellulitis and pneumothorax (four [2%], each); the most common in the placebo plus erlotinib group were pyrexia (four [2%]) and pneumothorax (three [1%]). One on-study treatment-related death due to an adverse event occurred (haemothorax after a thoracic drainage procedure for a pleural empyema) in the ramucirumab plus erlotinib group. Ramucirumab plus erlotinib demonstrated superior progression-free survival compared with placebo plus erlotinib in patients with untreated EGFR-mutated metastatic NSCLC. Safety was consistent with the safety profiles of the individual compounds in advanced lung cancer. The RELAY regimen is a viable new treatment option for the initial treatment of EGFR-mutated metastatic NSCLC. Eli Lilly.

Single-cell technologies have revealed the complexity of the tumour immune microenvironment with unparalleled resolution 1 – 9 . Most clinical strategies rely on histopathological stratification of tumour subtypes, yet the spatial context of single-cell phenotypes within these stratified subgroups is poorly understood. Here we apply imaging mass cytometry to characterize the tumour and immunological landscape of samples from 416 patients with lung adenocarcinoma across five histological patterns. We resolve more than 1.6 million cells, enabling spatial analysis of immune lineages and activation states with distinct clinical correlates, including survival. Using deep learning, we can predict with high accuracy those patients who will progress after surgery using a single 1-mm 2 tumour core, which could be informative for clinical management following surgical resection. Our dataset represents a valuable resource for the non-small cell lung cancer research community and exemplifies the utility of spatial resolution within single-cell analyses. This study also highlights how artificial intelligence can improve our understanding of microenvironmental features that underlie cancer progression and may influence future clinical practice. Using imaging mass cytometry, the tumour and immunological spatial landscapes of 416 lung adenocarcinomas are characterized, which, when combined with deep learning, can predict clinical outcomes with high accuracy.

The objective of this study was to develop a nomogram model based on the natural progression of tumor and other radiological features to discriminate between solitary nodular pulmonary mucinous adenocarcinoma and non-mucinous adenocarcinomas. A retrospective analysis was conducted on 15,655 cases of lung adenocarcinoma diagnosed at our institution between January 2010 and June 2023. Primary nodular invasive mucinous adenocarcinomas and non-mucinous adenocarcinomas with at least two preoperative CT scans were included. These patients were randomly assigned to training and validation sets. Univariate and multivariate analyses were employed to compare tumor growth rates and clinical radiological characteristics between the two groups in the training set. A nomogram model was constructed based on the results of multivariate analysis. The diagnostic value of the model was evaluated in both the training and validation sets using calibration curves and receiver operating characteristic curves (ROC). The study included 174 patients, with 58 cases of mucinous adenocarcinoma and 116 cases of non-mucinous adenocarcinoma. The nomogram model incorporated the maximum tumor diameter, the consolidation/tumor ratio (CTR), and the specific growth rate (SGR) to generate individual scores for each patient, which were then accumulated to obtain a total score indicative of the likelihood of developing mucinous or non-mucinous adenocarcinoma. The model demonstrated excellent discriminative ability with an area under the receiver operating characteristic curve of 0.784 for the training set and 0.833 for the testing set. The nomogram model developed in this study, integrating SGR with other radiological and clinical parameters, provides a valuable and accurate tool for differentiating between solitary nodular pulmonary mucinous adenocarcinoma and non-mucinous adenocarcinomas. This prognostic model offers a robust and objective basis for personalized management of patients with pulmonary adenocarcinomas.

BackgroundLung adenocarcinoma (LUAD) is a common pulmonary malignant disease with a poor prognosis. There were limited studies investigating the influences of the tumor immune microenvironment on LUAD patients’ survival and response to immune checkpoint inhibitors (ICIs). MethodsBased on TCGA-LUAD dataset, we constructed a prognostic immune signature and validated its predictive capability in the internal as well as total datasets. Then, we explored the differences of tumor-infiltrating lymphocytes, tumor mutation burden, and patients’ response to ICI treatment between the high-risk score group and low-risk score group.ResultsThis immune signature consisted of 17 immune-related genes, which was an independent prognostic factor for LUAD patients. In the low-risk score group, patients had better overall survival. Although the differences were non-significant, patients with low-risk scores had more tumor-infiltrating follicular helper T cells and fewer macrophages (M0), which were closely related to clinical outcomes. Additionally, the total TMB was markedly decreased in the low-risk score group. Using immunophenoscore as a surrogate of ICI response, we found that patients with low-risk scores had significantly higher immunophenoscore.ConclusionThe 17-immune-related genes signature may have prognostic and predictive relevance with ICI therapy but needs prospective validation.

Advanced metastatic cancer poses utmost clinical challenges and may present molecular and cellular features distinct from an early-stage cancer. Herein, we present single-cell transcriptome profiling of metastatic lung adenocarcinoma, the most prevalent histological lung cancer type diagnosed at stage IV in over 40% of all cases. From 208,506 cells populating the normal tissues or early to metastatic stage cancer in 44 patients, we identify a cancer cell subtype deviating from the normal differentiation trajectory and dominating the metastatic stage. In all stages, the stromal and immune cell dynamics reveal ontological and functional changes that create a pro-tumoral and immunosuppressive microenvironment. Normal resident myeloid cell populations are gradually replaced with monocyte-derived macrophages and dendritic cells, along with T-cell exhaustion. This extensive single-cell analysis enhances our understanding of molecular and cellular dynamics in metastatic lung cancer and reveals potential diagnostic and therapeutic targets in cancer-microenvironment interactions. Understanding the mechanisms that lead to lung adenocarcinoma metastasis is important for identifying new therapeutics. Here, the authors document the changes in the transcriptome of human lung adenocarcinoma using single-cell sequencing and link cancer cell signatures to immune cell dynamics.

Background There is a growing interest in utilizing a combination of brain radiotherapy (RT) and tyrosine kinase inhibitors (TKIs) for patients diagnosed with brain metastases (BM) in epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma (LAC). The current status of this treatment strategy remains a subject of debate. Methods We initiated our study by conducting a comprehensive literature search using the SCI-expanded database of Web of Science Core Collection (WoSCC). We utilized the VOSPviewer software to analyze various aspects of the research, including the year of publication, authorship, keywords, and country.Subsequently, we performed an extensive and systematic literature search on popular online databases. Our primary outcome measures were overall survival (OS) and intracranial progression-free survival (iPFS), both quantified by hazard ratios (HRs). Additionally, for data verification, we included data from patients in non-small cell lung cancer with brain metastasis who underwent therapeutic intervention at the Cancer Prevention and Treatment Center of Sun Yat-sen University and the Radiotherapy Department of Hanzhong Central Hospital between August 2012 and November 2021. Results The bibliometric analysis revealed an increasing trend in research focused on the combination of RT and TKIs for the management of lung cancer brain metastases over the previous decade. Then, nine studies consistent with the research direction were included for meta-analysis. The meta-analysis showed that the OS (HR = 0.81, 95% confidence interval: 0.69–0.94; P  = 0.007) and iPFS (HR = 0.71, 95% confidence interval: 0.61–0.82; P  < 0.001) of the combination therapy were significantly prolonged. Finally, 168 EGFR-mutated BM advanced LAC patients in the real world were verified, and the median iPFS of the combination therapy ( n  = 88 and EGFR-TKIs alone ( n  = 80) were 16.0 and 9.0 months, respectively, ( P  < 0.001). The median OS was 29.0 and 27.0 months, respectively, with no dramatic difference ( P  = 0.188). Conclusions Research on EGFR-mutant LAC brain metastasis has turned towards exploring optimal treatment strategies for this condition. Our meta-analysis and real-world data analysis consistently demonstrate that combination therapy offers a substantial improvement in patient survival compared to EGFR-TKI monotherapy. Notably, among patients undergoing salvage radiotherapy (RT), our subgroup analysis reveals that those initially treated with third-generation TKIs experience more significant benefits than those treated with first- or second-generation TKIs.

Metastasis frequently develops from disseminated cancer cells that remain dormant after the apparently successful treatment of a primary tumour. These cells fluctuate between an immune-evasive quiescent state and a proliferative state liable to immune-mediated elimination 1 – 6 . Little is known about the clearing of reawakened metastatic cells and how this process could be therapeutically activated to eliminate residual disease in patients. Here we use models of indolent lung adenocarcinoma metastasis to identify cancer cell-intrinsic determinants of immune reactivity during exit from dormancy. Genetic screens of tumour-intrinsic immune regulators identified the stimulator of interferon genes (STING) pathway as a suppressor of metastatic outbreak. STING activity increases in metastatic progenitors that re-enter the cell cycle and is dampened by hypermethylation of the STING promoter and enhancer in breakthrough metastases or by chromatin repression in cells re-entering dormancy in response to TGFβ. STING expression in cancer cells derived from spontaneous metastases suppresses their outgrowth. Systemic treatment of mice with STING agonists eliminates dormant metastasis and prevents spontaneous outbreaks in a T cell- and natural killer cell-dependent manner—these effects require cancer cell STING function. Thus, STING provides a checkpoint against the progression of dormant metastasis and a therapeutically actionable strategy for the prevention of disease relapse. STING signalling is activated in metastatic cancer cells that exit from an immune-evasive dormant state, blocking their progression and cancer relapse.

Background Clinically differentiating preinvasive lesions (atypical adenomatous hyperplasia, AAH and adenocarcinoma in situ, AIS) from invasive lesions (minimally invasive adenocarcinomas, MIA and invasive adenocarcinoma, IA) manifesting as ground-glass opacity nodules (GGOs) is difficult due to overlap of morphological features. Hence, the current study was performed to explore the diagnostic efficiency of radiomics in assessing the invasiveness of lung adenocarcinoma manifesting as GGOs. Methods A total of 1018 GGOs pathologically confirmed as lung adenocarcinoma were enrolled in this retrospective study and were randomly divided into a training set (n = 712) and validation set (n = 306). The nodules were delineated manually and 2446 intra-nodular and peri-nodular radiomic features were extracted. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used for feature selection. Clinical and semantic computerized tomography (CT) feature model, radiomic model and a combined nomogram were constructed and compared. Decision curve analysis (DCA) was used to evaluate the clinical value of the established nomogram. Results 16 radiomic features were selected and used for model construction. The radiomic model exhibited significantly better performance (AUC = 0.828) comparing to the clinical-semantic model (AUC = 0.746). Further analysis revealed that peri-nodular radiomic features were useful in differentiating between preinvasive and invasive lung adenocarcinomas appearing as GGOs with an AUC of 0.808. A nomogram based on lobulation sign and radiomic features showed the best performance (AUC = 0.835), and was found to have potential clinical value in assessing nodule invasiveness. Conclusions Radiomic model based on both intra-nodular and peri-nodular features showed good performance in differentiating between preinvasive lung adenocarcinoma lesions and invasive ones appearing as GGOs, and a nomogram based on clinical, semantic and radiomic features could provide clinicians with added information in nodule management and preoperative evaluation.

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS) . Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive . Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma . We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response.

Lung cancer is the world’s leading cause of cancer death and shows strong ancestry disparities. By sequencing and assembling a large genomic and transcriptomic dataset of lung adenocarcinoma (LUAD) in individuals of East Asian ancestry (EAS; n  = 305), we found that East Asian LUADs had more stable genomes characterized by fewer mutations and fewer copy number alterations than LUADs from individuals of European ancestry. This difference is much stronger in smokers as compared to nonsmokers. Transcriptomic clustering identified a new EAS-specific LUAD subgroup with a less complex genomic profile and upregulated immune-related genes, allowing the possibility of immunotherapy-based approaches. Integrative analysis across clinical and molecular features showed the importance of molecular phenotypes in patient prognostic stratification. EAS LUADs had better prediction accuracy than those of European ancestry, potentially due to their less complex genomic architecture. This study elucidated a comprehensive genomic landscape of EAS LUADs and highlighted important ancestry differences between the two cohorts. Genomic and transcriptomic analysis of lung adenocarcinoma (LUAD) in Asia indicates that Asian LUADs have fewer mutations, lower driver prevalence and fewer copy number alterations than European LUADs.