Although clinical studies have shown promise for targeting programmed cell death protein-1 (PD-1) and ligand (PD-L1) signaling in non-small cell lung cancer (NSCLC), the factors that predict which ...subtype patients will be responsive to checkpoint blockade are not fully understood.
We performed an integrated analysis on the multiple-dimensional data types including genomic, transcriptomic, proteomic, and clinical data from cohorts of lung adenocarcinoma public (discovery set) and internal (validation set) database and immunotherapeutic patients. Gene set enrichment analysis (GSEA) was used to determine potentially relevant gene expression signatures between specific subgroups.
We observed that
mutation significantly increased expression of immune checkpoints and activated T-effector and interferon-γ signature. More importantly, the
comutated subgroup manifested exclusive increased expression of PD-L1 and a highest proportion of
Meanwhile,
or
-mutated tumors showed prominently increased mutation burden and specifically enriched in the transversion-high (TH) cohort. Further analysis focused on the potential molecular mechanism revealed that
or
mutation altered a group of genes involved in cell-cycle regulating, DNA replication and damage repair. Finally, immunotherapeutic analysis from public clinical trial and prospective observation in our center were further confirmed that
or
mutation patients, especially those with co-occurring
mutations, showed remarkable clinical benefit to PD-1 inhibitors.
This work provides evidence that
and
mutation in lung adenocarcinoma may be served as a pair of potential predictive factors in guiding anti-PD-1/PD-L1 immunotherapy.
.
The ADJUVANT study reported the comparative superiority of adjuvant gefitinib over chemotherapy in disease-free survival of resected EGFR-mutant stage II-IIIA non-small cell lung cancer (NSCLC). ...However, not all patients experienced favorable clinical outcomes with tyrosine kinase inhibitors (TKI), raising the necessity for further biomarker assessment. In this work, by comprehensive genomic profiling of 171 tumor tissues from the ADJUVANT trial, five predictive biomarkers are identified (TP53 exon4/5 mutations, RB1 alterations, and copy number gains of NKX2-1, CDK4, and MYC). Then we integrate them into the Multiple-gene INdex to Evaluate the Relative benefit of Various Adjuvant therapies (MINERVA) score, which categorizes patients into three subgroups with relative disease-free survival and overall survival benefits from either adjuvant gefitinib or chemotherapy (Highly TKI-Preferable, TKI-Preferable, and Chemotherapy-Preferable groups). This study demonstrates that predictive genomic signatures could potentially stratify resected EGFR-mutant NSCLC patients and provide precise guidance towards future personalized adjuvant therapy.
Background
The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in ...asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic.
Measure
Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset.
Results
A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months.
Conclusion
Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.
The combination of NAT and serological testing for IgM antibody significantly improves the detection sensitivity of asymptomatic COVID‐19 infections, compared with NAT alone. S1‐specific IgM antibody response with rapid emergence and disappearance might be helpful to assist NAT for early identification of infectious individuals. A majority of asymptomatics induce very low levels of neutralizing antibody that disappear in two months. Abbreviations: NAT, nucleic acid testing; FI, fluorescence intensity; NT50, half‐maximal neutralizing titer.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
ADJUVANT-CTONG1104 (ClinicalTrials.gov identifier: NCT01405079), a randomized phase III trial, showed that adjuvant gefitinib treatment significantly improved disease-free survival (DFS) versus ...vinorelbine plus cisplatin (VP) in patients with epidermal growth factor receptor (
) mutation-positive resected stage II-IIIA (N1-N2) non-small-cell lung cancer (NSCLC). Here, we report the final overall survival (OS) results.
From September 2011 to April 2014, 222 patients from 27 sites were randomly assigned 1:1 to adjuvant gefitinib (n = 111) or VP (n = 111). Patients with resected stage II-IIIA (N1-N2) NSCLC and
-activating mutation were enrolled, receiving gefitinib for 24 months or VP every 3 weeks for four cycles. The primary end point was DFS (intention-to-treat ITT population). Secondary end points included OS, 3-, 5-year (y) DFS rates, and 5-year OS rate. Post hoc analysis was conducted for subsequent therapy data.
Median follow-up was 80.0 months. Median OS (ITT) was 75.5 and 62.8 months with gefitinib and VP, respectively (hazard ratio HR, 0.92; 95% CI, 0.62 to 1.36;
= .674); respective 5-year OS rates were 53.2% and 51.2% (
= .784). Subsequent therapy was administered upon progression in 68.4% and 73.6% of patients receiving gefitinib and VP, respectively. Subsequent targeted therapy contributed most to OS (HR, 0.23; 95% CI, 0.14 to 0.38) compared with no subsequent therapy. Updated 3y DFS rates were 39.6% and 32. 5% with gefitinib and VP (
= .316) and 5y DFS rates were 22. 6% and 23.2% (
= .928), respectively.
Adjuvant therapy with gefitinib in patients with early-stage NSCLC and
mutation demonstrated improved DFS over standard of care chemotherapy. Although this DFS advantage did not translate to a significant OS difference, OS with adjuvant gefitinib was one of the longest observed in this patient group compared with historic data.
Abstract
It has recently been established that the evolution of protoplanetary disks is primarily driven by magnetized disk winds, requiring a large-scale magnetic flux threading the disks. The size ...of such disks is expected to shrink with time, as opposed to the conventional scenario of viscous expansion. We present the first global 2D non-ideal magnetohydrodynamic simulations of protoplanetary disks that are truncated in the outer radius, aiming to understand the interaction of the disk with the interstellar environment, as well as the global evolution of the disk and magnetic flux. We find that as the system relaxes, the poloidal magnetic field threading the disk beyond the truncation radius collapses toward the midplane, leading to a rapid reconnection. This process removes a substantial amount of magnetic flux from the system and forms closed poloidal magnetic flux loops encircling the outer disk in quasi-steady state. These magnetic flux loops can drive expansion beyond the truncation radius, corresponding to substantial mass loss through a magnetized disk outflow beyond the truncation radius analogous to a combination of viscous spreading and external photoevaporation. The magnetic flux loops gradually shrink over time, the rates of which depend on the level of disk magnetization and the external environment, which eventually governs the long-term disk evolution.
Abstract
Hydrodynamical interactions between binaries and circumbinary disks (CBDs) play an important role in a variety of astrophysical systems, from young stellar binaries to supermassive black ...hole binaries. Previous simulations of CBDs have mostly employed locally isothermal equations of state. We carry out 2D viscous hydrodynamic simulations of CBDs around equal-mass, circular binaries, treating the gas thermodynamics by thermal relaxation toward equilibrium temperature (the constant-
β
cooling ansatz, where
β
is the cooling time in units of the local Keplerian time). As an initial study, we use the grid-based code
Athena++
on a polar grid, covering an extended disk outside the binary co-orbital region. We find that with a longer cooling time, the accretion variability is gradually suppressed, and the morphology of the CBD becomes more symmetric. The disk also shows evidence of hysteresis behavior depending on the initial conditions. Gas cooling also affects the rate of angular momentum transfer between the binary and the CBD, where given our adopted disk thickness and viscosity (
H
/
r
∼ 0.1 and
α
∼ 0.1), the binary orbit expands while undergoing accretion for most
β
values between 0 and 4.0 except over a narrow range of intermediate
β
values. The validity of using a polar grid excising the central domain is also discussed.
To assess the benefits of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors as neoadjuvant/adjuvant therapies in locally advanced
mutation-positive non-small-cell lung cancer.
This ...was a multicenter (17 centers in China), open-label, phase II, randomized controlled trial of erlotinib versus gemcitabine plus cisplatin (GC chemotherapy) as neoadjuvant/adjuvant therapy in patients with stage IIIA-N2 non-small-cell lung cancer with
mutations in exon 19 or 21 (EMERGING). Patients received erlotinib 150 mg/d (neoadjuvant therapy, 42 days; adjuvant therapy, up to 12 months) or gemcitabine 1,250 mg/m
plus cisplatin 75 mg/m
(neoadjuvant therapy, two cycles; adjuvant therapy, up to two cycles). Assessments were performed at 6 weeks and every 3 months postsurgery. The primary end point was objective response rate (ORR) by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1; secondary end points were pathologic complete response, progression-free survival (PFS), overall survival, safety, and tolerability.
Of 386 patients screened, 72 were randomly assigned to treatment (intention-to-treat population), and 71 were included in the safety analysis (one patient withdrew before treatment). The ORR for neoadjuvant erlotinib versus GC chemotherapy was 54.1% versus 34.3% (odds ratio, 2.26; 95% CI, 0.87 to 5.84;
= .092). No pathologic complete response was identified in either arm. Three (9.7%) of 31 patients and zero of 23 patients in the erlotinib and GC chemotherapy arms, respectively, had a major pathologic response. Median PFS was significantly longer with erlotinib (21.5 months) versus GC chemotherapy (11.4 months; hazard ratio, 0.39; 95% CI, 0.23 to 0.67;
< .001). Observed adverse events reflected those most commonly seen with the two treatments.
The primary end point of ORR with 42 days of neoadjuvant erlotinib was not met, but the secondary end point PFS was significantly improved.
Background
Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical ...fields, we attempt to integrate a well‐trained deep learning algorithm to detect and classify pulmonary nodules derived from clinical CT images.
Materials and Methods
Open‐source data sets and multicenter data sets have been used in this study. A three‐dimensional convolutional neural network (CNN) was designed to detect pulmonary nodules and classify them into malignant or benign diseases based on pathologically and laboratory proven results.
Results
The sensitivity and specificity of this well‐trained model were found to be 84.4% (95% confidence interval CI, 80.5%–88.3%) and 83.0% (95% CI, 79.5%–86.5%), respectively. Subgroup analysis of smaller nodules (<10 mm) have demonstrated remarkable sensitivity and specificity, similar to that of larger nodules (10–30 mm). Additional model validation was implemented by comparing manual assessments done by different ranks of doctors with those performed by three‐dimensional CNN. The results show that the performance of the CNN model was superior to manual assessment.
Conclusion
Under the companion diagnostics, the three‐dimensional CNN with a deep learning algorithm may assist radiologists in the future by providing accurate and timely information for diagnosing pulmonary nodules in regular clinical practices.
Implications for Practice
The three‐dimensional convolutional neural network described in this article demonstrated both high sensitivity and high specificity in classifying pulmonary nodules regardless of diameters as well as superiority compared with manual assessment. Although it still warrants further improvement and validation in larger screening cohorts, its clinical application could definitely facilitate and assist doctors in clinical practice.
摘要
背景。在肺癌的诊断中，计算机断层扫描 (CT) 对于肺结节的检测必不可少。近几年，随着医学领域逐渐认识到深度学习算法这种技术的价值，本研究试图集成一种训练有素的深度学习算法，对临床 CT 图像中的肺结节进行检测和分类。
材料和方法。本研究使用了开源数据集和多中心数据集。本文设计了一种三维卷积神经网络 (CNN) 来检测肺结节，然后根据病理和实验室证实的结果，判断为恶性或良性结节。
结果。这种训练有素的模型敏感性和特异性分别为 84.4% 95% 可信区间 (CI)， 80.5%‐88.3%和83.0%(95% CI，79.5%‐86.5%)。小结节 (< 10mm) 亚组分析显示的敏感性和特异性显著，与大结节 (10‐30mm) 相似。对比不同级别医生的人工评估结果与三维 CNN 的评估结果，进行了额外的模型验证。结果表明，CNN 模型的表现优于人工评估。
结论。通过伴随诊断可知，加入深度学习算法的三维 CNN 能够提供准确、及时的信息，有助于放射科医生在常规临床实践中的肺结节诊断工作。
实践意义:在对各种直径的肺结节分类中，本文所述的三维卷积神经网络具有较高的敏感性和特异性，与人工评估结果相比具有优越性。虽然仍需在更大的筛选队列中进行进一步改进和验证，但可以肯定的是，临床应用三维卷积神经网络可以促进和协助医生的临床实践工作。
Interest in deep convolutional neural networks (CNN) is growing because of demonstrated accuracy with less manual intervention in computer vision tasks. This article describes efforts to use a pre‐trained CNN model integrating with multi‐centers datasets for detection and classification of pulmonary nodules.
amplification, responsible for 20% of acquired resistance to EGFR tyrosine kinase inhibitor (TKI) in patients with advanced non-small cell lung cancer (NSCLC), presents an attractive target. Numerous ...studies have conferred susceptibility of
mutations and focal amplification to targeted MET-TKIs. However, the mechanism underlying MET-TKIs-induced resistance remains elusive.
We conducted a cohort of 12 patients with advanced NSCLC who developed resistance to a combinatorial therapy consisting of gefitinib and a type I MET-TKI. We performed capture-based targeted ultra-deep sequencing on serial tumor biopsies and plasmas ctDNA samples to detect and quantify genetic alterations.
We identified 2 newly acquired
mutations, Y1248H and D1246N, in 2 patients and further confirmed their resistance against type I MET-TKIs
, and
Interestingly, NIH3T3 cells harboring either mutation exhibited responses to type II MET-TKIs, suggesting sequential use of MET-TKIs may offer a more durable response. In addition, we also discovered that EGFR amplification may act as an alternative MET-TKI resistance mechanism.
Our study provides insight into the diversity of mechanisms underlying MET-TKI-induced resistance and highlights the potential of sequential use of MET-TKIs.
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