Immune checkpoint blockade with Programmed cell death 1 (PD-1)/PD-L1 inhibitors has been effective in various malignancies and is considered as a standard treatment modality for patients with ...non-small-cell lung cancer (NSCLC). However, emerging evidence show that PD-1/PD-L1 blockade can lead to hyperprogressive disease (HPD), a flair-up of tumor growth linked to dismal prognosis. This study aimed to evaluate the incidence of HPD and identify the determinants associated with HPD in patients with NSCLC treated with PD-1/PD-L1 blockade.
We enrolled patients with recurrent and/or metastatic NSCLC treated with PD-1/PD-L1 inhibitors between April 2014 and November 2018. Clinicopathologic variables, dynamics of tumor growth, and treatment outcomes were analyzed in patients with NSCLC who received PD-1/PD-L1 blockade. HPD was defined according to tumor growth kinetics (TGK), tumor growth rate (TGR), and time to treatment failure (TTF). Immunophenotyping of peripheral blood CD8+ T lymphocytes was conducted to explore the potential predictive biomarkers of HPD.
A total of 263 patients were analyzed. HPD was observed in 55 (20.9%), 54 (20.5%), and 98 (37.3%) patients according to the TGK, TGR, and TTF. HPD meeting both TGK and TGR criteria was associated with worse progression-free survival hazard ratio (HR) 4.619; 95% confidence interval (CI) 2.868–7.440 and overall survival (HR, 5.079; 95% CI, 3.136–8.226) than progressive disease without HPD. There were no clinicopathologic variables specific for HPD. In the exploratory biomarker analysis with peripheral blood CD8+ T lymphocytes, a lower frequency of effector/memory subsets (CCR7−CD45RA− T cells among the total CD8+ T cells) and a higher frequency of severely exhausted populations (TIGIT+ T cells among PD-1+CD8+ T cells) were associated with HPD and inferior survival rate.
HPD is common in NSCLC patients treated with PD-1/PD-L1 inhibitors. Biomarkers derived from rationally designed analysis may successfully predict HPD and worse outcomes, meriting further investigation of HPD.
Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop ...and validate a deep learning-based automatic brain segmentation and classification algorithm for the diagnosis of Alzheimer disease using 3D T1-weighted brain MR images.
A deep learning-based algorithm was developed using a dataset of T1-weighted brain MR images in consecutive patients with Alzheimer disease and mild cognitive impairment. We developed a 2-step algorithm using a convolutional neural network to perform brain parcellation followed by 3 classifier techniques including XGBoost for disease prediction. All classification experiments were performed using 5-fold cross-validation. The diagnostic performance of the XGBoost method was compared with logistic regression and a linear Support Vector Machine by calculating their areas under the curve for differentiating Alzheimer disease from mild cognitive impairment and mild cognitive impairment from healthy controls.
In a total of 4 datasets, 1099, 212, 711, and 705 eligible patients were included. Compared with the linear Support Vector Machine and logistic regression, XGBoost significantly improved the prediction of Alzheimer disease (
< .001). In terms of differentiating Alzheimer disease from mild cognitive impairment, the 3 algorithms resulted in areas under the curve of 0.758-0.825. XGBoost had a sensitivity of 68% and a specificity of 70%. In terms of differentiating mild cognitive impairment from the healthy control group, the 3 algorithms resulted in areas under the curve of 0.668-0.870. XGBoost had a sensitivity of 79% and a specificity of 80%.
The deep learning-based automatic brain segmentation and classification algorithm allowed an accurate diagnosis of Alzheimer disease using T1-weighted brain MR images. The widespread availability of T1-weighted brain MR imaging suggests that this algorithm is a promising and widely applicable method for predicting Alzheimer disease.
Autism spectrum disorders (ASDs) are neurodevelopmental disorders caused by various genetic and environmental factors that result in synaptic abnormalities. ASD development is suggested to involve ...microglia, which have a role in synaptic refinement during development. Autophagy and related pathways are also suggested to be involved in ASDs. However, the precise roles of microglial autophagy in synapses and ASDs are unknown. Here, we show that microglial autophagy is involved in synaptic refinement and neurobehavior regulation. We found that deletion of atg7, which is vital for autophagy, from myeloid cell-specific lysozyme M-Cre mice resulted in social behavioral defects and repetitive behaviors, characteristic features of ASDs. These mice also had increases in dendritic spines and synaptic markers and altered connectivity between brain regions, indicating defects in synaptic refinement. Synaptosome degradation was impaired in atg7-deficient microglia and immature dendritic filopodia were increased in neurons co-cultured with atg7-deficient microglia. To our knowledge, our results are the first to show the role of microglial autophagy in the regulation of the synapse and neurobehaviors. We anticipate our results to be a starting point for more comprehensive studies of microglial autophagy in ASDs and the development of putative therapeutics.
Immune checkpoint inhibitors (ICIs) have been shown to be beneficial for some patients with advanced non-small-cell lung cancer (NSCLC). However, the underlying mechanisms mediating the limited ...response to ICIs remain unclear.
We carried out whole-exome sequencing on 198 advanced NSCLC tumors that had been sampled before anti-programmed cell death 1 (anti-PD-1)/programmed death-ligand 1 (PD-L1) therapy. Detailed clinical characteristics were collected on these patients. We designed a new method to estimate human leukocyte antigen (HLA)-corrected tumor mutation burden (TMB), a modification which considers the loss of heterozygosity of HLA from conventional TMB. We carried out external validation of our findings utilizing 89 NSCLC samples and 110 melanoma samples from two independent cohorts of immunotherapy-treated patients.
Homology-dependent recombination deficiency was identified in 37 patients (18.7%) and was associated with longer progression-free survival (PFS; P = 0.049). Using the HLA-corrected TMB, non-responders to ICIs were identified, despite having a high TMB (top 25%). Ten patients (21.3% of the high TMB group) were reclassified from the high TMB group into the low TMB group. The objective response rate (ORR), PFS, and overall survival (OS) were all lower in these patients compared with those of the high TMB group (ORR: 20% versus 59%, P = 0.0363; PFS: hazard ratio = 2.91, P = 0.007; OS: hazard ratio = 3.43, P = 0.004). Multivariate analyses showed that high HLA-corrected TMB was associated with a significant survival advantage (hazard ratio = 0.44, P = 0.015), whereas high conventional TMB was not associated with a survival advantage (hazard ratio = 0.63, P = 0.118). Applying this approach to the independent cohorts of 89 NSCLC patients and 110 melanoma patients, TMB-based survival prediction was significantly improved.
HLA-corrected TMB can reconcile the observed disparity in relationships between TMB and ICI responses, and is of predictive and prognostic value for ICI therapies.
•TMB alone is not sufficiently reliable or accurate as a biomarker of response to ICIs in NSCLC.•TMB-based survival prediction is improved by using the HLA-corrected TMB algorithm (TMB in combination with loss of heterozygosity of HLA).•Notably, additional predictive and prognostic value of the HLA-corrected TMB is not limited to certain types of cancer.•The HLA-corrected TMB could be a new strategy for selecting patients who may benefit from immunotherapy.
Summary
Background
High‐mobility group box 1 protein (HMGB1) belonging to endogenous danger signals prolongs eosinophil survival and acts as a chemoattractant.
Objective
The authors evaluated the ...role of HMGB1 in the pathogenesis of asthma characterized by eosinophilic airway inflammation.
Methods
Firstly, HMGB1 expressions in induced sputum obtained from human asthmatics were determined. This was followed by an evaluation of the role of HMGB1 in a murine model of asthma using anti‐HMGB1 antibodies. Then the effect of HMGB1 on the receptor of advanced glycation end products (RAGE) expressions on CD11b‐CD11c+ cells isolated from a murine model of asthma were measured to elucidate the mechanisms involved.
Results
Sputum HMGB1 expressions were markedly higher in asthmatics than in normal controls, and were positively correlated with sputum eosinophilia and sputum TNF‐α, IL‐5 and IL‐13 expressions. In a murine model of asthma, HMGB1 expressions in lung tissue and HMGB1 levels in bronchoalveolar lavage fluid were significantly elevated and eosinophilic airway inflammation, non‐specific airway hyperresponsiveness, and pathological changes were attenuated by blocking HMGB1 activity. Furthermore, we found that enhanced RAGE expressions on CD11b‐CD11c+ also significantly decreased when HMGB1 activity was blocked.
Conclusion and Clinical Relevance
Our findings suggest that HMGB1 plays a key role in the pathogenesis of clinical and experimental asthma characterized by eosinophilic airway inflammation.
To determine the frequency and predictive impact of ROS1 rearrangements on treatment outcomes in never-smoking patients with lung adenocarcinoma.
We concurrently analyzed ROS1 and ALK rearrangements ...and mutations in the epidermal growth factor receptor (EGFR), and KRAS in 208 never smokers with lung adenocarcinoma. ROS1 and ALK rearrangements were identified by fluorescent in situ hybridization.
Of 208 tumors screened, 7 (3.4%) were ROS1 rearranged, and 15 (7.2%) were ALK-rearranged. CD74-ROS1 fusions were identified in two patients using reverse transcriptase–polymerase chain reaction. The frequency of ROS1 rearrangement was 5.7% (6 of 105) among EGFR/KRAS/ALK-negative patients. Patients with ROS1 rearrangement had a higher objective response rate (ORR; 60.0% versus 8.5%; P = 0.01) and a longer median progression-free survival (PFS; not reached versus 3.3 months; P = 0.008) to pemetrexed than those without ROS1/ALK rearrangement. The PFS to EGFR-tyrosine kinase inhibitors in patients harboring ROS1 rearrangement was shorter than those without ROS1/ALK rearrangement (2.5 versus 7.8 months; P = 0.01).
The frequency of ROS1 rearrangements in clinically selected patients is higher than that reported for unselected patients, suggesting that ROS1 rearrangement is a druggable target in East-Asian never smokers with lung adenocarcinoma. Given the different treatment outcomes to conventional therapies and availability of ROS1 inhibitors, identification of ROS1 rearrangement can lead to successful treatment in ROS1-rearranged lung adenocarcinomas.
We conducted co-clinical trials in patient-derived xenograft (PDX) models to identify predictive biomarkers for the multikinase inhibitor dovitinib in lung squamous cell carcinoma (LSCC).
The ...PDX01-02 were established from LSCC patients enrolled in the phase II trial of dovitinib (NCT01861197) and PDX03-05 were established from LSCC patients receiving surgery. These five PDX tumors were subjected toin vivo test of dovitinib efficacy, whole exome sequencing and gene expression profiling.
The PDX tumors recapitulate histopathological properties and maintain genomic characteristics of originating tumors. Concordant with clinical outcomes of the trial enrolled-LSCC patients, dovitinib produced substantial tumor regression in PDX-01 and PDX-05, whereas it resulted in tumor progression in PDX-02. PDX-03 and -04 also displayed poor antitumor efficacy to dovitinib. Mutational and genome-wide copy number profiles revealed no correlation between genomic alterations ofFGFR1-3 and sensitivity to dovitinib. Of note, gene expression profiles revealed differentially expressed genes including FGF3 and FGF19 between PDX-01 and 05 and PDX-02-04. Pathway analysis identified two FGFR signaling-related gene sets, FGFR ligand binding/activation and SHC-mediated cascade pathway were substantially up-regulated in PDX-01 and 05, compared with PDX-02-04. The comparison of gene expression profiles between dovitinib-sensitive versus -resistant lung cancer cell lines in the Cancer Cell Line Encyclopedia database also found that transcriptional activation of 18 key signaling components in FGFR pathways can predict the sensitivity to dovitinib both in cell lines and PDX tumors. These results highlight FGFR pathway activation as a key molecular determinant for sensitivity to dovitinib.
FGFR gene expression signatures are predictors for the response to dovitinib in LSCC.
Measuring local temperature with a spatial resolution on the order of a few nanometers has a wide range of applications in the semiconductor industry and in material and life sciences. For example, ...probing temperature on the nanoscale with high precision can potentially be used to detect small, local temperature changes like those caused by chemical reactions or biochemical processes. However, precise nanoscale temperature measurements have not been realized so far owing to the lack of adequate probes. Here we experimentally demonstrate a novel nanoscale temperature sensing technique based on optically detected electron spin resonance in single atomic defects in diamonds. These diamond sensor sizes range from a micrometer down to a few tens of nanometers. We achieve a temperature noise floor of 5 mK/Hz1/2 for single defects in bulk sensors. Using doped nanodiamonds as sensors the temperature noise floor is 130 mK/Hz1/2 and accuracies down to 1 mK for nanocrystal sizes and therefore length scales of a few tens of nanometers. This combination of precision and position resolution, combined with the outstanding sensor photostability, should allow the measurement of the heat produced by chemical interactions involving a few or single molecules even in heterogeneous environments like cells.
Iron was shocked and probed at unprecedented time and strain rate to show all of its known structural types in 2.5 ns.
Iron is one of the most studied chemical elements due to its sociotechnological ...and planetary importance; hence, understanding its structural transition dynamics is of vital interest. By combining a short pulse optical laser and an ultrashort free electron laser pulse, we have observed the subnanosecond structural dynamics of iron from high-quality x-ray diffraction data measured at 50-ps intervals up to 2500 ps. We unequivocally identify a three-wave structure during the initial compression and a two-wave structure during the decaying shock, involving all of the known structural types of iron (α-, γ-, and ε-phase). In the final stage, negative lattice pressures are generated by the propagation of rarefaction waves, leading to the formation of expanded phases and the recovery of γ-phase. Our observations demonstrate the unique capability of measuring the atomistic evolution during the entire lattice compression and release processes at unprecedented time and strain rate.
We aimed to compare tissue-specific expression profiles and biological pathways of RNA from amniocytes and amniotic fluid supernatant (AFS) from second-trimester pregnancies by using transcriptome ...analysis. Additionally, we wanted to explore whether cell-free RNA from AFS exhibits a unique gene expression signature that more adequately reflects the fetal developmental process than amniocyte RNA.
Amniotic fluid samples were prospectively collected in the second trimester of pregnancy from euploid fetuses. Total RNA was extracted from amniocytes and AFS and hybridized to Affymetrix GeneChip Human Arrays. Significantly differentially expressed transcripts between amniocytes and AFS were obtained by using Welch's t-test. Unsupervised hierarchical clustering was used to visualize overall expression characteristics and differences in transcripts between AFS and amniocytes. The biological functions of selected genes were analyzed using various online Gene Ontology databases.
A total of 3,072 and 15,633 transcripts were detected in the second-trimester AFS and amniocytes, respectively. Hierarchical clustering revealed differential transcript expression between AFS and amniocytes. We found 353 genes that were specifically enriched in the AFS only, and tissue expression analysis showed enrichment of brain-specific genes in the AFS. Biological pathway analysis revealed that AFS-specific transcripts were mainly involved in embryonic development, cardiovascular development, and cellular morphology pathways.
This study demonstrated differential tissue-specific gene expression profiles and biological pathways between AFS and amniocytes. The results suggested that AFS is the preferred RNA source to investigate potential biomarkers of fetal neurodevelopment.
PDF
