Independent Lung Research Articles

Two Distinct Primary EGFR-Mutated Lung Adenocarcinoma Within the Same Patient: A Case Report

Introduction Lung cancer remains the most common cause of cancer-related deaths worldwide, with Non-Small Cell Lung Cancer (NSCLC) the predominant histologic subtype. Increasingly, molecular mutations are identified and used as therapeutic targets. We describe the case of a woman diagnosed with locally metastatic NSCLC, and distinct pulmonary masses, later identified as two independent primary lung tumors based on molecular profiling. Case Report A 58-year-old-female presented with cough and hemoptysis. Chest Computed Tomography (CT) revealed a 4.3cm mass in the right lung apex, 2.0 cm nodule in the right lower lobe (RLL), and right paratracheal/hilar adenopathy. Subsequent Positron Emission Tomography-Computed Tomography (PET-CT) showed uptake in the right upper lobe (RUL) (SUV 12.2) and RLL (standard uptake value (SUV) 2.5) masses and mediastinal lymph nodes, but no distant metastases. Bronchoscopic biopsy of the RUL mass and 4R lymph node were positive for poorly differentiated adenocarcinoma, and molecular analysis revealed Epidermal Growth Factor Receptor (EGFR) L858R mutation. Subsequent Electromagnetic Navigation (EMN) biopsy of the RLL lesion also showed adenocarcinoma, but with an EGFR exon-19 deletion. Both were negative for T790M mutation. She was therefore diagnosed with two separate primaries instead of intrathoracic metastases. She started erlotinib and after 4 months, repeat PET-CT showed complete response (CR) in the RLL and partial response (PR) in the RUL. Decision was made to pursue surgery with RUL/RLL bilobectomy. Pathology showed evidence of N2 disease; therefore, at time of surgery she was stage IIIA, presumably from the RUL mass. The RLL mass was presumed to be stage I. These were successfully resected, and she was deemed to have no evidence of disease (NED) post-operatively. Discussion Although co-mutations within the same tumor have been reported in up to 12% of patients,28 we are not aware of other cases in which a single patient was diagnosed with two separate primary lung tumors based on genetic profiles. Consequently, she was able to be treated with curative rather than palliative intent.

Exploration of Novel Immunological Terms in Lung Cancer With Large Populations: Implications for Immunotherapy.

BackgroundIdeal biomarkers to predict the response to immunotherapy in lung cancer are still lacking. Therefore, there is a need to explore effective biomarkers in large populations.ObjectiveThe objective of this study is to explore novel immunological classifications that are associated with immunotherapy response through the ssGSEA algorithm.MethodsSix independent lung cancer cohorts were collected for analysis including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the EMBL-EBI database. The ssGSEA algorithm was performed to extract immune terms. Then, TCGA samples were involved as a training group and other cohorts were used as a validation group. After LASSO and Cox regression, prognostic associated immune terms were extracted and an immune-related risk score (IRS) signature was constructed. Furthermore, the association between IRS signature and clinical data, genome features, stemness indices analysis, tumor immune microenvironment, immunotherapy efficiency, and targeted therapy response was also investigated.ResultsA total of 1,997 samples were enrolled in this study including six large lung cancer cohorts. Fifty-four immune terms were calculated through the ssGSEA algorithm in combined cohorts. Then, a nine-immune-term risk score model named IRS signature was established to predict the prognosis in combined cohorts. We classified patients into high-risk and low-risk subgroups according to the cutoff point. Subsequently, analysis of clinical data and genome features indicated that the patients in the high-IRS group tend to have advanced clinical features (clinical stage and T classification), as well as a higher level of copy number variation burden, higher tumor burden mutation, and higher tumor stemness indices. Immune landscape analysis demonstrated that high-IRS groups exhibited lower immune cell infiltration and immune-suppressive state. More importantly, the predicted result of the Tumor Immune Dysfunction and Exclusion analysis showed that high-IRS groups might be more insensitive to immunotherapy. Meanwhile, we have also identified that high-IRS groups were associated with better efficiency of several targeted drugs.ConclusionTo summarize, we identified a novel IRS model based on nine immune terms, which was quantified by the ssGSEA algorithm. This model had good efficacy in predicting overall survival and immunotherapy response in non-small cell lung cancer patients, which might be an underlying biomarker.

A case of refractory pneumothorax and contralateral atelectasis after thoracoscopic subtotal esophagectomy treated with independent lung ventilation

BackgroundIndependent lung ventilation (ILV) allows separate positive end-expiratory pressures (PEEP) and inspiratory pressures for each lung. However, only a few articles have reported ILV management for lungs affected by different pathologies.Case presentationA 56-year-old man underwent video-assisted thoracic surgery for esophageal cancer. The right lung was injured during surgery, causing a bronchopleural fistula and necessitating chest drainage. On the third day in the intensive care unit, the patient’s oxygenation worsened during pressure support with continuous positive airway pressure ventilation. ILV was initiated for right-sided severe pneumothorax and left-sided atelectasis and pneumonia. ILV was continued for 2 days, and the patient’s trachea was successfully extubated the following day.ConclusionApplying high-level PEEP to the one lung and minimizing the airway pressure on the other lung could be achieved using ILV, which might contribute to successful tracheal extubation.

Abstract 5131: Deep learning-based tumor microenvironment cell types mapping from H&E images of lung adenocarcinoma using spatial transcriptomic data

Abstract Purpose Spatial characterization of cell types of the tumor microenvironment (TME) is a key to finding new targets as well as developing biomarkers for immuno-oncology treatment. Here, we develop and validate a deep learning model trained by integrating H&E images of lung adenocarcinoma and spatial transcriptomic data to decipher spatial mapping of multiple cell types in TME only using H&E images. Methods A total of 21 H&E images combined with spatial transcriptomic data of lung adenocarcinoma were used to develop a model. As each spot of spatial transcriptomic data consisted of a few cells, the cell types were inferred by CellDART, a domain adaptation-based method to estimating five cell types defined by single cell RNA-seq (scRNA-seq) data - B, T/NK, myeloid cells, fibroblasts, and epithelial cells. A convolutional neural network using H&E image patches as inputs was developed to predict the cell type scores for each corresponding spot. For the external validation, the model estimated the cell type scores from H&E-stained tissue image patches of lung adenocarcinoma of the Cancer Genome Atlas (TCGA-LUAD). Furthermore, the model inferred cell types from H&E images of lung adenocarcinoma tissues acquired by different patients and the results were compared with immunohistochemistry. Results The cell types inferred by the model using H&E image patches were significantly correlated with those derived by spatial transcriptomic data as an internal validation. The mean value of the deep learning-based cell types scores estimated by the TCGA-LUAD tissue images was significantly correlated with the cell type scores estimated by bulk RNA-seq data of corresponding TCGA data. When cell type inference maps of independent lung adenocarcinoma H&E images were spatially co-registered with immunohistochemistry slides, including CD3, CD20, and CD68, pixel-wise correlation analysis revealed positive significant correlations. Conclusions A deep learning model to infer spatial cell types of tumor microenvironment using H&E images was developed. The results of cell type scores were positively correlated with bulk RNA-seq-based immune cell enrichment scores and pixelwise analyses on immunohistochemistry images using typical cell type markers. This approach can provide objective and flexible deep learning-based models for characterizing tumor microenvironment. Citation Format: Hongyoon Choi, Kwon Joong Na, Jaemoon Koh, Young Tae Kim. Deep learning-based tumor microenvironment cell types mapping from H&E images of lung adenocarcinoma using spatial transcriptomic data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5131.

Selective Pneumoplegia Delivery System Facilitating Procurement in Donors After Circulatory Death

<h3>Purpose</h3> Donation after circulatory death (DCD Maastricht III) increases the donor pool, but the induction of organ preservation solutions necessitates a staged approach. As the heart has a low ischemic tolerance it is vital in a DCD retrieval to reanimate the heart quickly without waiting for pneumoplegia to finish. We have devised a selective pneumoplegia delivery system to aid independent lung procurement from the heart to reduce ischemic times. <h3>Methods</h3> Figure 1 shows the customized pneumoplegia delivery system. It consists of two self-inflated soft balloon retrograde cardioplegia cannulae connected with a ¼ inch y-connector and ¼ inch silicone tubes. During cardioplegia the pulmonary artery is transacted, the cannulae inserted into the right and left pulmonary arteries to deliver simultaneous selective antegrade pneumoplegia (Figure 2). After cardioplegia, the heart procurement and its reanimation on the organ care system can commence as the pneumoplegia is running. The self-inflated balloons of the cannulae do not require manual fixation, saving time as there are several litres of pneumoplegia. The same cannulae may be used to deliver the retrograde pneumoplegia. <h3>Results</h3> Between 2019-21 we performed three such procurements, with good immediate outcomes in all lung transplant recipients. <h3>Conclusion</h3> Our customized system allows simultaneous delivery of selective antegrade and retrograde pneumoplegia during and after cardiectomy in a DCD retrieval. This may reduce ischaemia for the heart and lung and improve organ utilisation. More studies are required to assess the potential benefit of our pneumoplegia delivery system.

Clinical and genetic characteristics of early-stage multiple primary and independent primary lung adenocarcinoma patients.

The difference between multiple primary lung cancers (MPLC) and intrapulmonary metastasis (IM) in patients with lung cancer is vital but controversial. Moreover, the genetic and clinical significance difference between MPLC and independent primary lung cancers (IPLC) patients is unknown. This study retrospectively researched clinical and genetic data of MPLC and IPLC patients from January 2019 to May 2021 at the affiliated hospital of Qingdao University, China. Ninety-four tissue samples from 41 early-stage patients with MPLC, and 94 tissue samples from 94 early-stage patients with IPLC were performed to targeted sequencing. A total of 36 patients (88%) showed inconsistent driver mutations, and five MPLC patients (12%) shared single identical EGFR/BRAF/TP53 hotspot mutations in the early stage. In MPLC patients, high-frequency mutations included EGFR (63%), TP53 (12%), BRAF (12%), KRAS (10%), ERBB2 (4%), PIK3CA (3%), and MET (3%). In IPLC patients, high-frequency mutations included EGFR (55%), TP53(26%), KRAS (13%), MAP2K1 (5%), PIK3CA (4%), ERBB2 (4%), NF1 (4%), RET (3%), and BRAF (2%). The higher BRAF and fewer TP53 mutations may be related to the lower malignancy in MPLC patients. The accuracy of pathological diagnosis in patients with early-stage MPLC does not need comprehensive molecular evaluation to supplement histology for differentiating early-stage MPLC and IM. Meanwhile, the molecular difference between MPLC and IPLC may be helpful to study the mechanism of MPLC pathogenesis.

The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma.

The identity of cancer cells is defined by the interplay between genetic, epigenetic transcriptional and post-transcriptional variation. A lot of this variation is present in RNA-seq data and can be captured at once using reference-free, k-mer analysis. An important issue with k-mer analysis, however, is the difficulty of distinguishing signal from noise. Here, we use two independent lung adenocarcinoma datasets to identify all reproducible events at the k-mer level, in a tumor versus normal setting. We find reproducible events in many different locations (introns, intergenic, repeats) and forms (spliced, polyadenylated, chimeric etc.). We systematically analyze events that are ignored in conventional transcriptomics and assess their value as biomarkers and for tumor classification, survival prediction, neoantigen prediction and correlation with the immune microenvironment. We find that unannotated lincRNAs, novel splice variants, endogenous HERV, Line1 and Alu repeats and bacterial RNAs each contribute to different, important aspects of tumor identity. We argue that differential RNA-seq analysis of tumor/normal sample collections would benefit from this type k-mer analysis to cast a wider net on important cancer-related events. The code is available at https://github.com/Transipedia/dekupl-lung-cancer-inter-cohort.

Lung protective strategy with independent lung ventilation：Case series using mechanical power in two unilateral pneumonia

Lung protective strategy with independent lung ventilation：Case series using mechanical power in two unilateral pneumonia

Proteomic Analysis of Human Lung Development.

Rationale: The current understanding of human lung development derives mostly from animal studies. Although transcript-level studies have analyzed human donor tissue to identify genes expressed during normal human lung development, protein-level analysis that would enable the generation of new hypotheses on the processes involved in pulmonary development are lacking. Objectives: To define the temporal dynamic of protein expression during human lung development. Methods: We performed proteomics analysis of human lungs at 10 distinct times from birth to 8 years to identify the molecular networks mediating postnatal lung maturation. Measurements and Main Results: We identified 8,938 proteins providing a comprehensive view of the developing human lung proteome. The analysis of the data supports the existence of distinct molecular substages of alveolar development and predicted the age of independent human lung samples, and extensive remodeling of the lung proteome occurred during postnatal development. Evidence of post-transcriptional control was identified in early postnatal development. An extensive extracellular matrix remodeling was supported by changes in the proteome during alveologenesis. The concept of maturation of the immune system as an inherent part of normal lung development was substantiated by flow cytometry and transcriptomics. Conclusions: This study provides the first in-depth characterization of the human lung proteome during development, providing a unique proteomic resource freely accessible at Lungmap.net. The data support the extensive remodeling of the lung proteome during development, the existence of molecular substages of alveologenesis, and evidence of post-transcriptional control in early postnatal development.

Independent Lung Ventilation-Experimental Studies on a 3D Printed Respiratory Tract Model.

Independent lung ventilation (ILV) is a life-saving procedure in unilateral pulmonary pathologies. ILV is underused in clinical practice, mostly due to the technically demanding placement of a double lumen endotracheal tube (ETT). Moreover, the determination of ventilation parameters for each lung in vivo is limited. In recent years, the development of 3D printing techniques enabled the production of highly accurate physical models of anatomical structures used for in vitro research, considering the high risk of in vivo studies. The purpose of this study was to assess the influence of double-lumen ETT on the gas transport and mixing in the anatomically accurate 3D-printed model of the bronchial tree, with lung lobes of different compliances, using various ventilation modes. The bronchial tree was obtained from Respiratory Drug Delivery (RDD Online, Richmond, VA, USA), processed and printed by a dual extruder FFF 3D printer. The test system was also composed of left side double-lumen endotracheal tube, Siemens Test Lung 190 and anesthetic breathing bag (as lobes). Pressure and flow measurements were taken at the outlets of the secondary bronchus. The measured resistance increased six times in the presence of double-lumen ETT. Differences between the flow distribution to the less and more compliant lobe were more significant for the airways with double-lumen ETT. The ability to predict the actual flow distribution in model airways is necessary to conduct effective ILV in clinical conditions.

Independent Lung Ventilation in a Pediatric Patient with a Firearm Injury.

Background: Chest trauma is uncommon in pediatric patients, however, it may be a cause of significant morbidity and mortality. The type and extent of the injury may lead to ventilation and perfusion problems, therefore, there may be a need for mechanical ventilation. Conclusions: "Independent lung ventilation" may be an appropriate option in selected cases in which the aim is to protect the healthy lung or ventilation cannot be obtained with known mechanical ventilation methods. Case: We presented a pediatric patient followed up in the intensive care unit because of a firearm injury, in whom left lung expansion could not be obtained despite repeated interventions, and independent lung ventilation resulted in success.

Construction of an immune-related lncRNA signature as a novel prognosis biomarker for LUAD.

The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-β signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.

The Effects of Sevoflurane vs. Propofol for Inflammatory Responses in Patients Undergoing Lung Resection: A Meta-Analysis of Randomized Controlled Trials.

Objective: Inflammatory cytokines are increased during one-lung ventilation in patients undergoing lung resection, and this increase can be fatal. Propofol and sevoflurane are the main anesthetics used for these patients. Unfortunately, there is no consensus on the best choice of an anesthetic agent concerning an inflammatory response in patients undergoing lung resection. This meta-analysis aimed to compare the effects of propofol and sevoflurane on the inflammatory response in patients undergoing lung resection.Methods: We searched electronic databases to identify randomized controlled trials comparing the effects of different anesthetics (sevoflurane vs. propofol) on the inflammatory response. The primary outcome concerned the concentration of systemic inflammatory cytokines. The secondary outcomes concerned the concentrations of inflammatory cytokines in the bronchoalveolar lavage (BAL) fluid from the dependent and independent lung. Random effects analysis of the meta-analyses were performed to synthesize the evidence and to assess the concentrations of inflammatory factors in the sevoflurane and propofol groups.Results: Eight trials involving 488 participants undergoing lung resection with one-lung ventilation were included. There was no significant difference in the concentrations of systemic interleukin (IL)-6, IL-10, or tumor necrosis factor α between the sevoflurane and propofol groups. Compared with the propofol group, BAL levels of IL-6 in the dependent ventilated lung were decreased in the sevoflurane group (three trials, 256 participants; standardized mean difference [SMD], −0.51; 95% confidence interval [CI], −0.90 to −0.11; p = 0.01; I2 = 46%). The BAL levels of IL-6 in the independent ventilated lung were also decreased by sevoflurane (four trials, 362 participants; SMD, −0.70; 95% [CI], −0.93 to −0.47; p < 0.00001; I2 = 0%).Conclusions: There was no difference in the systemic inflammatory response between the sevoflurane and propofol groups. However, compared with propofol, sevoflurane can reduce the local alveolar inflammatory response. Additional research is necessary to confirm whether the inflammatory response is direct or indirect.

Abstract 2706: Utilizing RNAscope to assess STK11-LoF-dependent transcriptional phenotypes in human NSCLC biopsies and evaluate its potential to predict anti-PD1 therapy response

Abstract Our work demonstrates RNAscope allows simultaneous quantitative assessment of multiple transcripts in situ using formalin fixed paraffin embedded (FFPE) human non-small cell lung cancer (NSCLC) biopsies and suggests this methodology could be used as a rapid surrogate biomarker for genotype/transcriptome profiling stemming for Serine Threonine Kinase 11 (STK11) loss of function (LoF). Recent clinical studies have correlated anti-PD1 therapy resistance in NSCLC with somatic disruption of STK11. Historically, rapid assessment of STK11 status using immunohistochemistry (IHC) has been a challenge. Our work in human NSCLC cell lines suggests that STK11 loss correlates with changes in tumor intrinsic cytokine expression. Several recent studies have suggested such changes may drive immune evasion. We therefore wondered whether cytokine expression profiles from primary human NSCLC biopsies might be used as a reliable biomarker to predict anti-PD1 therapy response. Here we present our findings using multiplexed RNAscope probes on KRAS-driven primary human NSCLC biopsies with and without STK11 loss. This initial work focuses on cytokines identified using our cell culture models as a proof of principle approach. Using CRISPR-Cas9 we engineered paired STK11 KO cell lines derived from 3 independent KRAS-driven human lung adenocarcinomas (NCI-H441, NCI-H1792, NCI-H2009). RNAseq and differential gene expression analysis revealed STK11-loss-dependent increases in IL-6, IL-8 and IL-32 in all three lines. We then created FFPE cell blocks using these cell lines and validated the RNAseq expression changes with multiplexed RNAscope probes in situ. Next, we informatically searched the molecular pathology archives at the UVM medical center and identified primary KRAS-driven human NSCLC biopsies with and without predicted STK11 loss. We then performed multiplexed RNAscope analysis on these samples to quantify IL-6, IL-8 and IL-32 gene expression as a function of tumor genotype in vivo. Our data suggest RNAscope represents a valid methodology to exploit quantitative differential gene expression as a reliable and reproducible surrogate biomarker of somatic STK11 disruption in NSCLC. Our future studies aim to establish whether genotype-dependent cytokine profiles predict anti-PD1 therapy response in KRAS-driven lung adenocarcinomas. Citation Format: Hailey M. Sarausky, Sean M. Lenahan, David Joseph Seward. Utilizing RNAscope to assess STK11-LoF-dependent transcriptional phenotypes in human NSCLC biopsies and evaluate its potential to predict anti-PD1 therapy response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2706.

The predictive prognostic values of CBFA2T3, STX3, DENR, EGLN1, FUT4, and PCDH7 in lung cancer.

BackgroundLung cancer is one of the most malignant tumors. However, neither the pathogenesis of lung cancer nor the prognosis markers are completely clear. The purpose of this study is to screen the diagnostic or prognostic markers of lung cancer.MethodsTCGA and GEO datasets were used to analyze the relationship between lung cancer-related genes and lung cancer samples. Common differential genes were screened, and a univariate Cox regression analysis was used to screen survival related genes. A univariable Cox proportional hazards regression analysis was used to verify the genes and construct risk model. The key factors affecting the prognosis of lung cancer were determined by univariate and multivariate regression analyses. The ROC curve, AUC and the survival of each risk gene was analyzed. Finally, the biological functions of high- and low-risk patients were explored by GSEA and an immune-infiltration analysis.ResultsBased on the common differential genes, 13 genes significantly related to lung cancer survival were identified. Eight risk genes (CBFA2T3, DENR, EGLN1, FUT2, FUT4, PCDH7, PHF14, and STX3) were screened out. The results showed that risk status may be an independent prognostic factor, and the risk score predicted the prognosis of lung cancer. CBFA2T3 and STX3 are protective genes, while DENR, EGLN1, FUT4 and PCDH7 are dangerous genes. These 6 genes can be used as independent lung cancer prognosis markers. The corresponding biological functions of genes expressed in high-risk patients were mostly related to tumor proliferation and inflammatory infiltration. Neutrophil, CD8+T, Macrophage M0, Macrophage M1- and mDC-activated cells were high in high-risk status samples.ConclusionsCBFA2T3, STX3, DENR, EGLN1, FUT4, and PCDH7 are important participants in the occurrence and development of lung cancer. High-risk patients display serious inflammatory infiltration. This study not only provides insight into the mechanism of occurrence and development of lung cancer, but also provides potential targets for targeted therapy of lung cancer.

LNCDS: A 2D-3D cascaded CNN approach for lung nodule classification, detection and segmentation

The early detection of lung cancer is attained with the detection of initial stage nodules (3−30mm) which can exorbitantly increase the 5-year survival rate of lung cancer patients. Nodules are very small size circumscribed structures in the lungs and are difficult to detect due to their size. The identification of nodule is also more challenging due to similarly resembling structures like non-nodules that contains features which could make it identifiable as a nodule. Therefore, to deal with these challenging issues, we proposed a novel approach for segmentation, classification and detection of lung nodules from CT scan images. In our proposed method we involve a maximum intensity projection technique as a part of image preprocessing method. We demonstrated our experimentation and proposed SquExUNet segmentation model and 3D-NodNet classification model on publicly available Lung Image Database Consortium – Image Database Resource Initiative (LIDC), LNDb Challenge Dataset and purely independent Indian Lung CT Image Database (ILCID) clinical dataset. We proposed a 2D-3D cascaded CNN strategy for detection of nodule that yields the accurately segmented and classified nodule. Results obtained with proposed method indicates that we have successfully detected and segmented the lung nodules effectively, compared to existing lung nodule detection and segmentation algorithms. We achieved a Dice-Coefficient metrics of 0.80 for segmentation of nodule and 90.01% Sensitivity for nodule detection.

Identification of downstream signaling cascades of ACK1 and prognostic classifiers in non-small cell lung cancer.

Activated Cdc42-associated kinase 1 (ACK1) is an oncogene in multiple cancers, but the underlying mechanisms of its oncogenic role remain unclear in non-small cell lung cancer (NSCLC). Herein, we comprehensively investigated the ACK1-regulated cell processes and downstream signaling pathways, as well as its prognostic value in NSCLC. We found that ACK1 gene amplification was associated with mRNA levels in The Cancer Genome Atlas (TCGA) lung cancer cohort. The Oncomine databases showed significantly elevated ACK1 levels in lung cancer. In vitro, an ACK1 inhibitor (dasatinib) increased the sensitivity of NSCLC cell lines to AKT or MEK inhibitors. RNA-sequencing results demonstrated that an ACK1 deficiency in A549 cells affected the MAPK, PI3K/AKT, and Wnt pathways. These results were validated by gene set enrichment analysis (GSEA) of data from 188 lung cancer cell lines. Using Cytoscape, we dissected 14 critical ACK1-regulated genes. The signature with the 14 genes and ACK1 could significantly dichotomize the TCGA lung cohort regarding overall survival. The prognostic accuracy of this signature was confirmed in five independent lung cancer cohorts and was further validated by a prognostic nomogram. Our study unveiled several downstream signaling pathways for ACK1, and the proposed signature may be a promising prognostic predictor for NSCLC.

Bronchopleural Fistula in the Mechanically Ventilated Patient: A Concise Review

To describe the physiology of air leak in bronchopleural fistula in mechanically ventilated patients and how understanding of its physiology drives management of positive-pressure ventilation. To provide guidance of lung isolation, mechanical ventilator, pleural catheter, and endobronchial strategies for the management of bronchopleural fistula on mechanical ventilation. Online search of PubMed and manual review of articles (laboratory and patient studies) was performed. Articles relevant to bronchopleural fistula, mechanical ventilation in patients with bronchopleural fistula, independent lung ventilation, high-flow ventilatory modes, physiology of persistent air leak, extracorporeal membrane oxygenation, fluid dynamics of bronchopleural fistula airflow, and intrapleural catheter management were selected. Randomized trials, observational studies, case reports, and physiologic studies were included. Data from selected studies were qualitatively evaluated for this review. We included data illustrating the physiology of driving pressure across a bronchopleural fistula as well as data, largely from case reports, demonstrating management and outcomes with various ventilator modes, intrapleural catheter techniques, endoscopic placement of occlusion and valve devices, and extracorporeal membrane oxygenation. Themes related to managing persistent air leak with mechanical ventilation were reviewed and extracted. In case reports that demonstrate different approaches to managing patients with bronchopleural fistula requiring mechanical ventilation, common themes emerge. Strategies aimed at decreasing peak inspiratory pressure, using lower tidal volumes, lowering positive end-expiratory pressure, decreasing the inspiratory time, and decreasing the respiratory rate, while minimizing negative intrapleural pressure decreases airflow across the bronchopleural fistula. Mechanical ventilation and intrapleural catheter management must be individualized and aimed at reducing air leak. Clinicians should emphasize reducing peak inspiratory pressures, reducing positive end-expiratory pressure, and limiting negative intrapleural pressure. In refractory cases, clinicians can consider lung isolation, independent lung ventilation, or extracorporeal membrane oxygenation in appropriate patients as well as definitive management with advanced bronchoscopic placement of valves or occlusion devices.

Effects of thoracic nerve block on perioperative lung injury, immune function, and recovery after thoracic surgery.

BackgroundTo investigate the effects of thoracic nerve block on perioperative lung injury, immune function, and recovery after thoracic surgeryMethodsA total of 120 patients with lung cancer were randomly allocated into three groups: general anesthesia group (GAL group), thoracic paravertebral nerve block (TPVB) combined with general anesthesia (TPL group), and TPVB (with paravertebral dexmedetomidine) combined with general anesthesia group (TDL group); 120 patients with esophageal cancer were randomly allocated into three groups: general anesthesia group (GAE group), TPVB combined with general anesthesia group (TPE group), and thoracic epidural block combined with general anesthesia group (TEE group). Lung injury and immune function were evaluated. Hemodynamic changes, early recovery in post‐anesthesia care unit, pain, 6‐min walking test (6MWT), drug consumption, and life quality were also observed. The duration in the PACU of patients was retrospectively analyzed. The effect of dexmedetomidine on lung injury was established in vitro.ResultsThe lung injury, including injury scores, apoptosis, and inflammation, were decreased in the TDL group compared with the GAL group and TPL group. The ratio of CD4+/CD8+ cells at the end of surgery was higher in the TPE group than in the GAE group. More stable hemodynamic was found in TPL group and TPE group. Acute pain was alleviated and the 6MWT was enhanced by TPVB with or without dexmedetomidine. Anesthetic consumption was decreased by thoracic nerve block.ConclusionsThoracic nerve block, especially TPVB with or without paravertebral dexmedetomidine, can enhance recovery after thoracic surgery. Protection against independent lung injury and cellular immune dysfunction may be a potential mechanism.

Regulatory Cross Talk Between SARS-CoV-2 Receptor Binding and Replication Machinery in the Human Host.

We dissect the mechanism of SARS-CoV-2 in human lung host from the initial phase of receptor binding to viral replication machinery. Two independent lung protein interactome were constructed to reveal the signaling process on receptor activation and host protein hijacking machinery in the pathogenesis of virus. Further, we test the functional role of the hubs derived from the interactome. Most hubs proteins were differentially regulated on SARS-CoV-2 infection. Also, the proteins in viral replication hubs were related with cardiovascular disease, diabetes and hypertension confirming the vulnerability and severity of infection in the risk individual. Additionally, the hub proteins were closely linked with other viral infection, including MERS and HCoVs which suggest similar infection pattern in SARS-CoV-2. We identified five hubs that interconnect both networks that show the preparation of optimal environment in the host for viral replication process upon receptor attachment. Interestingly, we propose that seven potential miRNAs, targeting the intermediate phase that connects receptor and viral replication process a better choice as a drug for SARS-CoV-2.