Safety and efficacy of protective stent insertion to prevent carotid blowout syndrome at the distal internal carotid artery in nasopharyngeal carcinoma patients: a comparison with endovascular occlusion.

Background: Carotid blowout syndrome (CBS) frequently occurs at the distal internal carotid artery (distal-ICA) in patients with nasopharyngeal carcinoma (NPC), and remedial treatments run a high risk for neurologic complications. A case-control study was conducted to evaluate the safety and efficacy of protective stent insertion at the distal-ICA to prevent CBS in NPC patients, with a comparison to endovascular coil occlusion. Methods: A total of 28 consecutive NPC patients at high risk of CBS from June 2019 to December 2021 in Shanghai Sixth People's Hospital (a tertiary institution) were retrospectively included and divided into a stent protection group and occlusion group. Technique feasibility, treatment outcomes and neurological deficiency were compared between the two groups by two-sample test. Kaplan-Meier analysis compared patients' survival rates at mid-term follow-up. Results: Stent insertion was performed in 15 patients and ICA occlusion in 13 patients. The technical success rate was 100% in both groups. Procedure-related ischemic stroke was identified in 2 patients (15.4%) in the occlusion group, compared with none in the stent protection group. Bleeding was encountered in one patient in the stent protection group and one patient in the occlusion group, each. During a median follow-up of 10.5 (range, 2-31) months, 3 patients (20%) showed asymptomatic in-stent occlusion in the stent protection group. Notably, the median survival time was significantly longer in the stent protection group than in the occlusion group (23.3 vs. 15.8 months, P=0.04). Conclusions: Protective stenting the distal-ICA was similarly effective in preventing CBS in NPC patients but was safer than endovascular occlusion of ICA.

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer.

Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a deep learning signature based on positron emission tomography/computed tomography to predict ONM of clinical stage N0 NSCLC. An internal cohort (n = 1911) is included to construct the deep learning nodal metastasis signature (DLNMS). Subsequently, an external cohort (n = 355) and a prospective cohort (n = 999) are utilized to fully validate the predictive performances of the DLNMS. Here, we show areas under the receiver operating characteristic curve of the DLNMS for occult N1 prediction are 0.958, 0.879 and 0.914 in the validation set, external cohort and prospective cohort, respectively, and for occult N2 prediction are 0.942, 0.875 and 0.919, respectively, which are significantly better than the single-modal deep learning models, clinical model and physicians. This study demonstrates that the DLNMS harbors the potential to predict ONM of clinical stage N0 NSCLC.

Corrigendum: Convolutional neural network-based diagnostic model for a solid, indeterminate solitary pulmonary nodule or mass on computed tomography.

[This corrects the article DOI: 10.3389/fonc.2021.792062.].

The Prognostic Impact of Epidermal Growth Factor Receptor Mutation in Clinical Stage I Lung Adenocarcinoma.

BACKGROUND: This study investigated the prognostic impact of epidermal growth factor receptor (EGFR) mutation in clinical stage I lung adenocarcinoma patients. METHODS: Data for 952 patients who received surgical resection and underwent detection of oncogenic driver mutations were retrospectively collected. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method and compared using the log-rank test. The adjusted hazard ratio (aHR) with 95% CI of the prognosticator was calculated by Cox proportional hazards model, and cumulative incidence function was measured by competing risk regression model. RESULTS: EGFR mutation was detected in 581 patients (61.0%) and was more frequent in women (63.9%), nonsmokers (85.5%), and those with ground-glass nodules (GGNs; 56.6%). EGFR mutation was not associated with recurrence and death in the entire cohort or GGN cohort. However, for patients with radiologic pure-solid appearance, EGFR mutation was an independent risk factor for RFS (aHR, 1.623; 95% CI, 1.192-2.210) and distant recurrence (aHR, 1.863; 95% CI, 1.311-2.650), but not OS. Subsequently, subgroup analysis based on EGFR mutation subtypes, including exon 19 deletions (19-Del), exon 21 L858R substitution (L858R), and rare mutations in patients with radiologic pure-solid appearance, revealed that all 3 subtypes have poorer RFS (19-Del: aHR, 1.424; 95% CI, 0.991-2.047; L858R: aHR, 1.708; 95% CI, 1.172-2.490; rare mutations: aHR, 2.500; 95% CI, 1.400-4.465) and higher prevalent distant recurrence (19-Del: aHR, 1.595; 95% CI, 1.061-2.400; L858R: aHR, 2.073; 95% CI, 1.371-3.140; rare mutations: aHR, 2.657; 95% CI, 1.397-5.050) compared with wild-type. CONCLUSIONS: In clinical stage I lung adenocarcinoma, EGFR mutation was associated with worse RFS and higher prevalent distant recurrence in patients with radiologic pure-solid appearance but not in patients with GGN.

[Application of ethmoid artery pedicled septal floor mucosa flap in repair of postoperative cerebrospinal fluid leak after transsphenoidal pituitary surgery].

Objective:To investigate the safety and effectiveness of the ethmoid artery pedicled septal floor mucosal flap in repair of postoperative cerebrospinal fluid leakage after transsphenoidal pituitary tumor surgery.Methods: The clinical data of 6 patients with cerebrospinal fluid leak in Department of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from June 2011 to June 2022. In 6 patients with postoperative cerebrospinal fluid leakage after transsphenoidal pituitary surgery, the bilateral posterior septal arteries were sacrificed due to the endoscopic transsphenoidal expanded approach, so the ethmoid artery pedicled septal floor mucosal flaps were adopted.Results:All patients had good growth of the mucosal flaps during postoperative follow-up without recurrent cerebrospinal fluid leakage. Conclusion:Cerebrospinal fluid leakage is still one of the postoperative complications of pituitary surgery. For patients with bilateral posterior septal arteries sacrificed through the transsphenoidal approach, when the classic posterior septal artery pedicled mucosal flap is not available, the ethmoid artery pedicled septal floor mucosal flap is one of the alternative methods.

Increased CYR61 expression activates CCND1/c-Myc pathway to promote nasal epithelial cells proliferation in chronic rhinosinusitis with nasal polyps.

PURPOSE: Chronic rhinosinusitis (CRS) with nasal polyps (CRSwNP) is a chronic sinonasal inflammatory disease characterized histologically by hyperplastic nasal epithelium and epithelial cells proliferation. Cysteine-rich angiogenic inducer 61 (CYR61) acts as a positive regulator of cell cycle process. Cyclin D1 (CCND1) and c-Myc play key roles in the processes of cell cycle and cell growth. The purpose of our research was to explore the expression and roles of CYR61, CCND1 and c-Myc in CRSwNP. METHODS: FeaturePlot and vlnPlot functions embedded in the seurat package (version 4.1.1) of R software (version 4.2.0) were applied to explore the cellular distribution of CYR61, CCND1 and c-Myc in the single-cell RNA sequencing (scRNA-seq) dataset of nasal tissue samples. CYR61, CCND1 and c-Myc immunolabeling and mRNA levels in nasal tissue samples were assessed by immunohistochemistry and real-time PCR. Co-localization of CYR61, CCND1 and c-Myc with basal epithelial cell marker P63 was assayed using double-label immunofluorescence staining. Furthermore, we collected and cultured human nasal epithelial cells (HNEC) to assess the regulation and role of CYR61 in vitro study. RESULTS: CYR61, CCND1 and c-Myc were primarily expressed by nasal epithelial cells. Significant upregulation of CYR61, CCND1 and c-Myc positive cells and increased levels of CYR61, CCND1 and c-Myc mRNA were found in nasal polyps in comparison to control samples. Of note, CYR61 mRNA and protein levels were altered by SEB, LPS, IFN-γ, IL-13, IL-17A and TGF-ß1 in HNEC. In addition, CYR61 intervention could increase CCND1 and c-Myc mRNA and protein levels to promote HNEC proliferation, and siRNA against ITGA2 (si-ITGA2) could reverse CYR61 induced upregulation of CCND1 and c-Myc mRNA and protein levels in HNEC and cell proliferation of HNEC. CONCLUSIONS: CYR61, CCND1 and c-Myc were primarily expressed by epithelial cells in nasal mucosa. CYR61, CCND1 and c-Myc expression levels were increased in CRSwNP compared with controls. CYR61 could interact with ITGA2 to enhance HNEC proliferation via upregulating CCND1 and c-Myc levels in the HNEC, leading to hyperplastic nasal epithelium in CRSwNP.

The Different Evaluative Significance of Enlarged Lymph Nodes on Preoperative CT in the N Stage for Patients with Suspected Subsolid and Solid Lung Cancers.

RATIONALE AND OBJECTIVES: To investigate the clinical value of enlarged mediastinal and/or hilar lymph nodes on CT for patients with lung subsolid and solid nodules. MATERIALS AND METHODS: The study was performed on patients who underwent surgical treatment for suspected lung cancer. One hundred seventeen subsolid nodules and 101 solid nodules with enlarged lymph nodes (LNs) were included in the study group. The same number of cases with normal LNs with a balanced distribution of the clinical T stage were randomly selected as the control group for each study group. The pathological statuses of the lymph nodes of these patients proven by histopathology after surgery were collected. RESULTS: Lung solid lesions with enlarged LNs were more prone to lymph node metastasis (37.6% vs. 13.9%, p <0.001). However, there were only two and one metastatic lesions in the subsolid group with and without enlarged LNs, respectively. (2/117 vs. 1/117, p = 1.000). No pathological lymph node metastasis was observed in subsolid lesions under clinical stage T1b (cT1b), even though some of them (117/234) with enlarged LNs. CONCLUSION: The evaluative significance of enlarged LNs on CT is different for subsolid and solid lesions. CT is useful for lymph node evaluation and N staging of solid lesions but may has little value for subsolid lesions. There is a very low possibility of lymph node metastasis occurring in patients with subsolid lesions under cT1b. Enlarged LNs on CT may not be critical in subsequent management and treatment for subsolid nodules.

M2 macrophage-related gene signature in chronic rhinosinusitis with nasal polyps.

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a common sinonasal inflammatory disorder with high heterogeneity. Increasing evidence have indicated that the infiltration of macrophages especially M2 macrophages play pivotal roles in the pathogenesis of CRSwNP, but the underlying mechanisms remain undetermined. This study sought to identify potential biomarkers related to M2 macrophages in CRSwNP. Methods: The expression datasets of GSE136825 and GSE179265 were download from Gene Expression Omnibus (GEO) database and merged. Then, CIBERSORT and weighted gene co-expression network analysis (WGCNA) algorithms were applied to identify M2 macrophage-related gene modules. Thereafter, differentially expressed genes (DEGs) related to M2 macrophages were selected to perform functional enrichment analyses. A protein-protein interaction (PPI) network was built to identify hub genes and quantitative real-time reverse transcriptions PCR was used to verify the bioinformatics results. Results: A total of 92 DEGs associated with M2 macrophages were identified for further analysis. The results of Gene ontology (GO) and Kyoto Encyclopedia of genes and genomes (KEGG) analyses illustrated that M2 macrophage-associated DEGs primarily enriched in immune responses and extracellular matrix structure. PPI network analysis identified 18 hub genes related to M2 macrophages that might be pivotal in the pathogenesis of CRSwNP. After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP. Conclusion: These findings yield new insights into the hub genes and mechanisms related to M2 macrophages in the pathogenesis of CRSwNP. Further studies of these hub genes would help better understand the disease progression and identify potential treatment targets.

Deep learning for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: A multicentre study.

BACKGROUND: This study, based on multicentre cohorts, aims to utilize computed tomography (CT) images to construct a deep learning model for predicting major pathological response (MPR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC) and further explore the biological basis under its prediction. METHODS: 274 patients undergoing curative surgery after neoadjuvant chemoimmunotherapy for NSCLC at 4 centres from January 2019 to December 2021 were included and divided into a training cohort, an internal validation cohort, and an external validation cohort. ShuffleNetV2x05-based features of the primary tumour on the CT scans within the 2 weeks preceding neoadjuvant administration were employed to develop a deep learning score for distinguishing MPR and non-MPR. To reveal the underlying biological basis of the deep learning score, a genetic analysis was conducted based on 25 patients with RNA-sequencing data. FINDINGS: MPR was achieved in 54.0% (n = 148) patients. The area under the curve (AUC) of the deep learning score to predict MPR was 0.73 (95% confidence interval [CI]: 0.58-0.86) and 0.72 (95% CI: 0.58-0.85) in the internal validation and external validation cohorts, respectively. After integrating the clinical characteristic into the deep learning score, the combined model achieved satisfactory performance in the internal validation (AUC: 0.77, 95% CI: 0.64-0.89) and external validation cohorts (AUC: 0.75, 95% CI: 0.62-0.87). In the biological basis exploration for the deep learning score, a high deep learning score was associated with the downregulation of pathways mediating tumour proliferation and the promotion of antitumour immune cell infiltration in the microenvironment. INTERPRETATION: The proposed deep learning model could effectively predict MPR in NSCLC patients treated with neoadjuvant chemoimmunotherapy. FUNDING: This study was supported by National Key Research and Development Program of China, China (2017YFA0205200); National Natural Science Foundation of China, China (91959126, 82022036, 91959130, 81971776, 81771924, 6202790004, 81930053, 9195910169, 62176013, 8210071009); Beijing Natural Science Foundation, China (L182061); Strategic Priority Research Program of Chinese Academy of Sciences, China (XDB38040200); Chinese Academy of Sciences, China (GJJSTD20170004, QYZDJ-SSW-JSC005); Shanghai Hospital Development Center, China (SHDC2020CR3047B); and Science and Technology Commission of Shanghai Municipality, China (21YF1438200).

Exosomal microRNA-506 inhibits biological activity of lung adenocarcinoma cells and increases sensitivity to cisplatin-based hyperthermia.

Exosomal microRNAs (miRNAs) play a vital role in the occurrence and development of lung adenocarcinoma (LUAD). Based on the bioinformatics analyses, the current study sought to explore the effects of exosomal miR-506 on LUAD cell biology and the efficacy of cisplatin (CDDP)-based hyperthermia (HT). After sample preparation, we identified decreased miR-506 and elevated ATAD2. LUAD cells were subsequently transfected with miR-506 mimic, oe-ATAD2 and PI3K/AKT signaling pathway inhibitor LY294002 to analyze effects of the miR-506/ATAD2/PI3K/AKT axis on cell biological processes and chemoresistance. Effects of exosomal miR-506 on sensitivity of LUAD cells to CDDP-based HT were further assessed in a co-culture system of BMSC-derived exosomes and LUAD cells, which was also validated in tumor-bearing nude mice. miR-506 down-regulated ATAD2 to inhibit the PI3K/AKT signaling pathway, thereby inhibiting the malignant phenotypes of LUAD cells and augmenting LUAD cell sensitivity to CDDP-based HT. Further, BMSCs-derived exosomes harboring miR-506 sensitized LUAD cells to DDP/HT both in vitro and in vivo. Collectively, our findings revealed that exosomal miR-506 sensitized LUAD cells to CDDP-based HT by inhibiting ATAD2/PI3K/AKT signaling pathway, offering a potential therapeutic target for LUAD treatment.

Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk.

Background: Radiomics based on computed tomography (CT) images is potential in promoting individualized treatment of non-small cell lung cancer (NSCLC), however, its role in immunotherapy needs further exploration. The aim of this study was to develop a CT-based radiomics score to predict the efficacy of immune checkpoint inhibitor (ICI) monotherapy in patients with advanced NSCLC. Methods: Two hundred and thirty-six ICI-treated patients were retrospectively included and divided into a training cohort (n=188) and testing cohort (n=48) at a ratio of 8 to 2. The efficacy outcomes of ICI were evaluated based on overall survival (OS) and progression-free survival (PFS). We designed a survival network and combined it with a Cox regression model to obtain patients' OS risk score (OSRS) and PFS risk score (PFSRS). Results: Based on OSRS and PFSRS, patients were divided into high- and low-risk groups in the training cohort and the test cohort with distinctly different [training cohort, log-rank P<0.001, hazard ratio (HR): 4.14; test cohort, log-rank P=0.014, HR: 4.54] and PFS (training cohort, log-rank P<0.001, HR: 4.52; test cohort, log-rank P<0.001, HR: 6.64). Further joint evaluation of OSRS and PFSRS showed that both were significant in the Cox regression model (P<0.001), and multi-overall survival risk score (MOSRS) displayed more outstanding stratification capabilities than OSRS in both the training (P<0.001) and test cohorts (P=0.002). None of the clinical characteristics were significant in the Cox regression model, and the score that predicted the best immune response was not as good as the risk score from follow-up information in the performance of prognostic stratification. Conclusions: We developed a CT imaging-based score with the potential to become an independent prognostic factor to screen patients who would benefit from ICI treatment, which suggested that CT radiomics could be applied for individualized immunotherapy of NSCLC. Our findings should be further validated by future larger multicenter study.

Impact of genetic status on the survival outcomes of patients with clinical stage I non-small cell lung cancer with a radiological pure-solid appearance.

PURPOSE: To investigate whether genetic status is associated with the prognosis of patients with clinical stage (c-stage) I non-small cell lung cancer (NSCLC) with radiological pure-solid manifestations. MATERIALS AND METHODS: We included 340 patients with pure-solid c-stage I NSCLC and evaluated their clinicopathological and genetic information. Disease recurrence and death were also observed at the end of the 5-year follow-up period. A Cox proportional hazards model was performed to identify the effect of clinicopathological variables, including genetic status, on oncological outcomes. Recurrence-free survival (RFS) and overall survival (OS) were calculated by Kaplan-Meier curves and were compared using log-rank tests. RESULTS: The gene-mutation rate of c-stage I NSCLC with a radiological pure-solid appearance was 55.9% (190/340), and the frequencies of EGFR, KRAS, ALK, ROS1 and fused genes were 69.5% (132/190), 16.8% (32/190), 8.9% (17/190), 1.6% (3/190) and 3.2% (6/190), respectively. The 5-year RFS and OS rates of eligible patients were 57.1% and 76.5%, respectively. A multivariable analysis revealed that genetic status was an independent significant prognostic factor associated with RFS (hazard ratio [HR] = 1.416, 95% confidence interval [CI]: 1.020-1.964, p = 0.038) but not with OS. RFS was lower in the genetic mutation group compared with the wild-type group (p = 0.027), with 5-year RFS rate (65.7 vs. 51.6%), but the difference in OS (mutated group vs. wild-type group: 78.0% vs. 75.3%) was not statistically significant (p = 0.602). Additionally, we found that pathological nodal involvement (HR = 2.455, 95% CI: 1.745-3.454, p < 0.001 for RFS; HR = 2.204, 95% CI: 1.409-3.447, p = 0.001 for OS) was also a valuable prognostic factor in patients with pure-solid c-stage I NSCLC. CONCLUSION: Our study provides a comprehensive description of the mutational landscape of c-stage I NSCLC, and indicates that genetic status has an impact on disease recurrence in patients with c-stage I NSCLC with pure-solid appearance.

Accurate prediction of epidermal growth factor receptor mutation status in early-stage lung adenocarcinoma, using radiomics and clinical features.

OBJECTIVES: To develop a nomogram based on CT radiomics and clinical features to predict the epidermal growth factor receptor (EGFR) mutations in early-stage lung adenocarcinomas. METHODS: A retrospective analysis of postoperative patients with pathologically confirmed lung adenocarcinoma, which had been tested for EGFR mutations was performed from January 2015 to December 2015. Patients were randomly assigned to training and validation cohorts. A total of 1,078 radiomics features were extracted. least absolute shrinkage and selection operator (LASSO) regression analysis was applied to select clinical and radiomics features, and to establish predictive models. The radiomics score (rad-score) of each patient was calculated. The discrimination of the model was evaluated with area under the curve. RESULTS: 1092 patients (444 men and 648 women; mean age: 59.59±9.6) were enrolled. The radiomics signature consisted of 28 radiomics features and emphysema. The mean validation cohort result of the rad-score for patients with EGFR mutations (0.814±0.988) was significantly higher than those with EGFR wild-type (0.315±1.237; p = 0.001). When combined with clinical features, LASSO regression analysis revealed four radiomics features, emphysema, and three clinical features including sex, age, and histologic subtype as associated with to EGFR mutation status. The nomogram that combined radiomics and clinical features significantly improved the predictive discrimination (AUC: 0.723), which is better than that of the radiomics signature alone (AUC: 0.646). CONCLUSION: A relationship between selected radiomics features and EGFR mutant lung adenocarcinomas is demonstrated. A nomogram, combining radiomics features and clinical features for EGFR prediction in early-stage lung adenocarcinomas, has shown a moderate discriminatory efficiency and high sensitivity, providing additional information for clinicians.

Radiomics for Survival Risk Stratification of Clinical and Pathologic Stage IA Pure-Solid Non-Small Cell Lung Cancer.

Background Radiomics-based biomarkers enable the prognostication of resected non-small cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA pure-solid tumors requires further determination. Purpose To construct an efficient radiomics signature for survival risk stratification personalized for patients with clinical stage and pathologic stage IA pure-solid NSCLC. Materials and Methods In this retrospective study, six radiomics signatures were constructed for patients with stage IA pure-solid NSCLC who underwent resection between January 2011 and December 2013 at authors' institution and were tested in the radiogenomics data set. The radiomics features were extracted from the intratumoral two-dimensional region, three-dimensional volume, and peritumoral area using PyRadiomics. The discriminative abilities of the signatures were quantified using the area under the time-dependent receiver operating characteristic curve (AUC), and the optimal signature was selected for patient stratification. Results The study included 592 patients with stage IA pure-solid NSCLC (median age, 61 years; interquartile range, 55-66 years; 269 women) for radiomics analysis: 381 patients for training, 163 for internal validation, and 48 for external validation. The radiomics signature combining three-region features yielded the highest 3- and 5-year AUCs of 0.77 and 0.78, respectively, in the internal validation set and 0.76 and 0.75, respectively, in the external validation set. Multivariable analysis suggested that the radiomics signature remained an independent prognostic factor (hazard ratio, 6.2; 95% CI: 3.5, 11.0; P < .001) and improved the discriminative ability and clinical usefulness of conventional clinical predictors. Conclusion The radiomics signature with multiregional features helped stratify the survival risk of patients with clinical stage and pathologic stage IA pure-solid non-small cell lung cancer. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Hsu and Sohn in this issue.

Sinonasal diffuse large B-cell lymphoma in a patient with Wiskott-Aldrich syndrome: A case report and literature review.

Wiskott-Aldrich syndrome (WAS) is a rare primary immunodeficiency disease with a predisposition towards autoimmunity and lymphoproliferative diseases. Non-Hodgkin lymphoma (NHL) is reported to be the predominant form of malignant tumor in WAS sufferers. Diffuse large B-cell lymphoma (DLBCL) is one of the most common types of NHL while it is uncommon to occur in paranasal sinuses and especially when associated with WAS. In this article, we report a unique case of WAS associated with DLBCL in paranasal sinuses and review the major publications of WAS-related lymphomas that occurred in the head and neck area. This study extends the available therapies for WAS-related lymphomas and emphasizes the significance of recognition for sinonasal lymphomas in WAS patients presenting with sinusitis.

Development and Validation of a Radiomics Nomogram for Differentiating Pulmonary Cryptococcosis and Lung Adenocarcinoma in Solitary Pulmonary Solid Nodule.

OBJECTIVE: To establish a CT-based radiomics nomogram model for classifying pulmonary cryptococcosis (PC) and lung adenocarcinoma (LAC) in patients with a solitary pulmonary solid nodule (SPSN) and assess its differentiation ability. MATERIALS AND METHODS: A total of 213 patients with PC and 213 cases of LAC (matched based on age and gender) were recruited into this retrospective research with their clinical characteristics and radiological features. High-dimensional radiomics features were acquired from each mask delineated by radiologists manually. We adopted the max-relevance and min-redundancy (mRMR) approach to filter the redundant features and retained the relevant features at first. Then, we used the least absolute shrinkage and operator (LASSO) algorithms as an analysis tool to calculate the coefficients of features and remove the low-weight features. After multivariable logistic regression analysis, a radiomics nomogram model was constructed with clinical characteristics, radiological signs, and radiomics score. We calculated the performance assessment parameters, such as sensitivity, specificity, accuracy, negative predictive value (NPV), and positive predictive value (PPV), in various models. The receiver operating characteristic (ROC) curve analysis and the decision curve analysis (DCA) were drawn to visualize the diagnostic ability and the clinical benefit. RESULTS: We extracted 1,130 radiomics features from each CT image. The 24 most significant radiomics features in distinguishing PC and LAC were retained, and the radiomics signature was constructed through a three-step feature selection process. Three factors-maximum diameter, lobulation, and pleural retraction-were still statistically significant in multivariate analysis and incorporated into a combined model with radiomics signature to develop the predictive nomogram, which showed excellent classification ability. The area under curve (AUC) yielded 0.91 (sensitivity, 80%; specificity, 83%; accuracy, 82%; NPV, 80%; PPV, 83%) and 0.89 (sensitivity, 81%; specificity, 83%; accuracy, 82%; NPV, 81%; PPV, 82%) in training and test cohorts, respectively. The net reclassification indexes (NRIs) were greater than zero (p < 0.05). The Delong test showed a significant difference (p < 0.0001) between the AUCs from the clinical model and the nomogram. CONCLUSIONS: The radiomics technology can preoperatively differentiate PC and lung adenocarcinoma. The nomogram-integrated CT findings and radiomics feature can provide more clinical benefits in solitary pulmonary solid nodule diagnosis.

Evaluation of the Radiomics Method for the Prediction of Atypical Adenomatous Hyperplasia in Patients With Subcentimeter Pulmonary Ground-Glass Nodules.

OBJECTIVES: We aimed to develop a prediction model to distinguish atypical adenomatous hyperplasia (AAH) from early lung adenocarcinomas in patients with subcentimeter pulmonary ground-glass nodules (GGNs), which may help avoid aggressive surgical resection for patients with AAH. METHODS: Surgically confirmed cases of AAH and lung adenocarcinomas manifesting as GGNs of less than 1 cm were retrospectively collected. A prediction model based on radiomics and clinical features identified from a training set of cases was built to differentiate AAH from lung adenocarcinomas and tested on a validation set. RESULTS: Four hundred and eighty-five eligible cases were included and randomly assigned to the training (n = 339) or the validation sets (n = 146). The developed radiomics prediction model showed good discrimination performance to distinguish AAH from adenocarcinomas in both the training and the validation sets, with, respectively, 84.1% and 82.2% of accuracy, and AUCs of 0.899 (95% CI: 0.867-0.931) and 0.881 (95% CI: 0.827-0.936). CONCLUSION: The prediction model based on radiomics and clinical features can help differentiate AAH from adenocarcinomas manifesting as subcentimeter GGNs and may prevent aggressive resection for AAH patients, while reserving this treatment for adenocarcinomas.

A novel protein encoded by circASK1 ameliorates gefitinib resistance in lung adenocarcinoma by competitively activating ASK1-dependent apoptosis.

Acquired resistance to growth factor receptor tyrosine kinase inhibitors limits the therapeutic benefits gained by EGFR-mutant lung adenocarcinoma (LUAD) patients treated with gefitinib. Circular RNAs (circRNAs) are novel noncoding RNAs implicated in the regulation of chemoresistance in malignancies. However, whether circRNAs participate in the development of EGFR-TKI resistance in LUAD remains to be clarified. Here, we report that circASK1 (hsa_circ_0007798) is significantly downregulated in gefitinib-resistant cells and enhances the gefitinib sensitivity of LUAD cells. Mechanistically, we identified a novel protein encoded by circASK1, ASK1-272a.a, which is essential for ASK1/JNK/p38 signaling activation and mediates the chemosensitivity-inducing effect of circASK1 in LUAD. Importantly, this novel isoform competes with ASK1 for binding to Akt1, therefore antagonizing Akt1-induced ASK1 phosphorylation and inactivation, leading to the activation of ASK1-induced apoptosis and alleviating gefitinib resistance. Moreover, increased YTHDF2-mediated endoribonucleolytic cleavage of m6A-modified circASK1 accounts for its downregulation in gefitinib-resistant cells. The clinical data and in vivo model further corroborated the suppressive effect of circASK1 and its encoded protein on gefitinib resistance. Our study provides a novel therapeutic target to overcome gefitinib resistance in LUAD patients.

Clinical Value and Pathologic Basis of Cystic Airspace Within Subsolid Nodules Confirmed as Lung Adenocarcinomas by Surgery.

PURPOSE: To investigate the clinical value and pathologic basis of cystic airspace within lung adenocarcinomas manifesting as subsolid nodules. PATIENTS AND METHODS: A retrospective study was conducted on a total of 541 surgically confirmed lung adenocarcinomas manifesting as subsolid nodules in computed tomography images, including 87 cases with cystic airspace and 454 cases without cystic airspace. The pathologic characteristics of the cases with and without cystic airspace were compared. The investigation of the pathologic structure of cystic airspace was attempted on the postoperative paraffin sections. RESULTS: There was a significant difference in the containing of cystic airspace between preinvasive and invasive adenocarcinomas (10.5 vs 26.6%; P < .001). Multivariate analysis indicated that cystic airspace is an independent predictor of invasive adenocarcinomas (odds ratio, 3.220; 95% confidence interval, 1.822-5.687). Nodules containing multiple cystic airspaces are more likely to be invasive adenocarcinomas than nodules with a single cystic airspace (47.1 vs 72.2%; P < .05). On paraffin sections, the walls of the cystic airspace seemed to be mainly composed of atypical hyperplasia and/or tumor cells on the surface and the remaining smooth muscle cells and stroma below, which is similar to the structure of bronchi. CONCLUSIONS: Cystic airspace may be a reliable predictor of invasive adenocarcinomas, the classification method based on the number of cystic airspaces might be suitable for the computed tomography-based typing of cystic airspace within subsolid nodules. Cystic airspace may derive from the destroyed and enlarged bronchi owing to the growth or infiltration of atypical hyperplasia and/or tumor cells.