99mTc-MAA accumulation within tumor in preoperative lung perfusion SPECT/CT associated with occult lymph node metastasis in patients with clinically N0 non-small cell lung cancer

Background 99mTc-MAA accumulation within the tumor representing pulmonary arterial perfusion, which is variable and may have a clinical significance. We evaluated the prognostic significance of 99mTc-MAA distribution within the tumor in non-small cell lung cancer (NSCLC) patients in terms of detecting occult nodal metastasis and lymphovascular invasion, as well as predicting the recurrence-free survival (RFS). Methods Two hundred thirty-nine NSCLC patients with clinical N0 status who underwent preoperative lung perfusion SPECT/CT were retrospectively evaluated and classified according to the visual grading of 99mTc-MAA accumulation in the tumor. Visual grade was compared with the quantitative parameter, standardized tumor to lung ratio (TLR). The predictive value of 99mTc-MAA accumulation with occult nodal metastasis, lymphovascular invasion, and RFS was assessed. Results Eighty-nine (37.2%) patients showed 99mTc-MAA accumulation and 150 (62.8%) patients showed the defect on 99mTc-MAA SPECT/CT. Among the accumulation group, 45 (50.5%) were classified as grade 1, 40 (44.9%) were grade 2, and 4 (4.5%) were grade 3. TLR gradually and significantly increased from grade 0 (0.009 ± 0.005) to grade 1 (0.021 ± 0.005, P < 0.05) and to grade 2–3 (0.033 ± 0.013, P < 0.05). The following factors were significant predictors for occult nodal metastasis in univariate analysis: central location, histology different from adenocarcinoma, tumor size greater than 3cm representing clinical T2 or higher, and the absence of 99mTc-MAA accumulation within the tumor. Defect in the lung perfusion SPECT/CT remained significant at the multivariate analysis (Odd ratio 3.25, 95%CI [1.24 to 8.48], p = 0.016). With a median follow-up of 31.5 months, the RFS was significantly shorter in the defect group (p = 0.008). Univariate analysis revealed that cell type of non-adenocarcinoma, clinical stage II-III, pathologic stage II-III, age greater than 65 years, and the 99mTc-MAA defect within tumor as significant predictors for shorter RFS. However, only the pathologic stage remained statistically significant, in multivariate analysis. Conclusion The absence of 99mTc-MAA accumulation within the tumor in preoperative lung perfusion SPECT/CT represents an independent risk factor for occult nodal metastasis and is relevant as a poor prognostic factor in clinically N0 NSCLC patients. 99mTc-MAA tumor distribution may serve as a new imaging biomarker reflecting tumor vasculatures and perfusion which can be associated with tumor biology and prognosis.This research was supported by the National Research Foundation of Korea (NRF) and funded by the Korean government (MSIT) (No.2020M3A9B6038086

Lobeglitazone Attenuates Airway Inflammation and Mucus Hypersecretion in a Murine Model of Ovalbumin-Induced Asthma

Lobeglitazone (LB) is a novel agonist of peroxisome proliferator-activated receptor (PPAR)-α and γ that was developed as a drug to treat diabetes mellitus. We explored the ameliorative effects of LB on allergic asthma using a murine model of ovalbumin (OVA)-induced asthma. To boost the immune response of animals, OVA sensitization was performed on days 0 and 14. LB (250 or 500 μg/kg) was administered by oral gavage on days 18 to 23, and the OVA challenge was performed using an ultrasonic nebulizer on days 21 to 23. Plethysmography showed airway hyperresponsiveness (AHR) on day 24. LB treatment effectively decreased inflammatory cell recruitment, T-helper type 2 cytokines in the bronchoalveolar lavage fluid, and immunoglobulin (Ig) E in the serum of the animals with OVA-induced asthma, which was accompanied by a marked reduction in AHR. It also decreased airway inflammation, mucus hypersecretion, phosphorylation of nuclear transcription factor-kappa-B (NF-κB), and expression of activating protein (AP)-1 and mucin 5AC (MUC5AC). Overall, LB effectively attenuated the pathophysiological changes of asthma and its effects appear related to a reduction in the phosphorylation of NF-κB and the expression of AP-1. Thus, our results suggest that LB has a potential to treat allergic asthma

Tumor immune profiles noninvasively estimated by FDG PET with deep learning correlate with immunotherapy response in lung adenocarcinoma

Rationale: The clinical application of biomarkers reflecting tumor immune microenvironment is hurdled by the invasiveness of obtaining tissues despite its importance in immunotherapy. We developed a deep learning-based biomarker which noninvasively estimates a tumor immune profile with fluorodeoxyglucose positron emission tomography (FDG-PET) in lung adenocarcinoma (LUAD). Methods: A deep learning model to predict cytolytic activity score (CytAct) using semi-automatically segmented tumors on FDG-PET trained by a publicly available dataset paired with tissue RNA sequencing (n = 93). This model was validated in two independent cohorts of LUAD: SNUH (n = 43) and The Cancer Genome Atlas (TCGA) cohort (n = 16). The model was applied to the immune checkpoint blockade (ICB) cohort, which consists of patients with metastatic LUAD who underwent ICB treatment (n = 29). Results: The predicted CytAct showed a positive correlation with CytAct of RNA sequencing in validation cohorts (Spearman rho = 0.32, p = 0.04 in SNUH cohort; spearman rho = 0.47, p = 0.07 in TCGA cohort). In ICB cohort, the higher predicted CytAct of individual lesion was associated with more decrement in tumor size after ICB treatment (Spearman rho = -0.54, p < 0.001). Higher minimum predicted CytAct in each patient associated with significantly prolonged progression free survival and overall survival (Hazard ratio 0.25, p = 0.001 and 0.18, p = 0.004, respectively). In patients with multiple lesions, ICB responders had significantly lower variance of predicted CytActs (p = 0.005). Conclusion: The deep learning model that predicts CytAct using FDG-PET of LUAD was validated in independent cohorts. Our approach may be used to noninvasively assess an immune profile and predict outcomes of LUAD patients treated with ICB.

Gestational Estimated Glomerular Filtration Rate and Adverse Maternofetal Outcomes

Background/Aims: The association between gestational estimated glomerular filtration rate (eGFR) and adverse pregnancy outcomes has not been fully investigated. Methods: This observational cohort study included pregnancy cases of singleton mothers whose serum creatinine levels were measured during pregnancy at two tertiary hospitals in Korea from 2000 to 2015. Those with identified substantial renal function impairment (eGFR &#x3c; 60 mL/min/1.73 m2 at baseline, during, or after pregnancy) were excluded. The Chronic Kidney Disease Epidemiology Collaboration equation was used for the eGFR calculation. We computed the time-averaged eGFR during gestation to determine representative values when there were multiple measurements. We studied the following three gestational complications: preterm birth (&#x3c; 37 weeks’ gestational age), low birth weight (&#x3c; 2.5 kg), and preeclampsia. Results: Among the 12,899 studied pregnancies, 4,360 cases experienced one or more gestational complications. The adjusted odds ratio (aOR) and 95% confidence interval of composite gestational complications for eGFR ranges other than the reference range of 120–150 mL/ min/1.73m2 were: ≥150 mL/min/1.73m2, aOR 1.64 (1.38–1.95), P&#x3c; 0.001; 90–120 mL/min/1.73m2, aOR 1.41 (1.28–1.56), P&#x3c; 0.001; and 60–90 mL/min/1.73m2, aOR 2.56 (1.70–3.84), P&#x3c; 0.001. Incidence of preterm birth or low birth weight showed similar U-shaped association with eGFR values; otherwise, preeclampsia or small for gestational age occurred more often in mothers with a lower gestational eGFR than in those with a higher value. Conclusion: Considering the unique association between gestational eGFR and pregnancy outcomes, carefully interpreting these results may help predict obstetric complications

Three-Dimensional Human Alveolar Stem Cell Culture Models Reveal Infection Response to SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the cause of a present pandemic, infects human lung alveolar type 2 (hAT2) cells. Characterizing pathogenesis is crucial for developing vaccines and therapeutics. However, the lack of models mirroring the cellular physiology and pathology of hAT2 cells limits the study. Here, we develop a feeder-free, long-term, three-dimensional (3D) culture technique for hAT2 cells derived from primary human lung tissue and investigate infection response to SARS-CoV-2. By imaging-based analysis and single-cell transcriptome profiling, we reveal rapid viral replication and the increased expression of interferon-associated genes and proinflammatory genes in infected hAT2 cells, indicating a robust endogenous innate immune response. Further tracing of viral mutations acquired during transmission identifies full infection of individual cells effectively from a single viral entry. Our study provides deep insights into the pathogenesis of SARS-CoV-2 and the application of defined 3D hAT2 cultures as models for respiratory diseases

Impact of supradiaphragmatic lymphadenectomy on the survival of patients in stage IVB ovarian cancer with thoracic lymph node metastasis

IntroductionTo evaluate the survival impact of supradiaphragmatic lymphadenectomy as part of debulking surgery in stage IVB ovarian cancer with thoracic lymph node metastasis (LNM).MethodsWe retrospectively enrolled patients diagnosed with stage IVB ovarian, fallopian or primary peritoneal cancer between 2010 and 2020, carrying cardiophrenic, parasternal, anterior mediastinal or supraclavicular lymph nodes ≥5 mm on axial chest computed tomography. All tumors were classified into the abdominal (abdominal tumors and cardiophrenic lymph nodes) and supradiaphragmatic (parasternal, anterior mediastinal or supraclavicular lymph nodes) categories depending on the area involved. Residual tumors were classified into &lt;5 vs ≥5 mm in the abdominal and supradiaphragmatic areas. Based on the site of recurrence, they were divided into abdominal, supradiaphragmatic and other areas.ResultsA total of 120 patients underwent primary debulking surgery (PDS, n=68) and interval debulking surgery after neoadjuvant chemotherapy (IDS/NAC, n=53). Residual tumors in the supradiaphragmatic area ≥5 mm adversely affected progression-free survival (PFS) and overall survival (OS) with marginal significance after PDS despite the lack of effect on survival after IDS/NAC (adjusted hazard ratios [HRs], 6.478 and 6.370; 95% confidence intervals [CIs], 2.224-18.864 and 0.953-42.598). Further, the size of residual tumors in the abdominal area measuring ≥5 mm diminished OS after IDS/NAC (adjusted HR, 9.330; 95% CIs, 1.386-62.800).ConclusionSupradiaphragmatic lymphadenectomy during PDS may improve survival in patients diagnosed with stage IVB ovarian cancer manifesting thoracic LNM. Further, suboptimal debulking surgery in the abdominal area may be associated with poor OS after IDS/NAC.Trial registrationClinicalTrials.gov (NCT05005650; https://clinicaltrials.gov/ct2/show/NCT05005650; first registration, 13/08/2021).Research Registry (Research Registry UIN, researchregistry7366; https://www.researchregistry.com/browse-the-registry#home/?view_2_search=researchregistry7366&amp;view_2_page=1)

Pan-cancer analysis of tumor metabolic landscape associated with genomic alterations

Abstract Although metabolic alterations are one of the hallmarks of cancer, there is a lack of understanding of how metabolic landscape is reconstituted according to cancer progression and which genetic alterations underlie its heterogeneity within cancer cells. Here, the configuration of the metabolic landscape according to genetic alteration is examined across 7648 subjects representing 29 cancers. The metabolic landscape and its reconfiguration according to the accumulated mutation maintained characteristics of their tissue of origin. However, there were some common patterns across cancers in terms of the association with cancer progression. Carbohydrate and pyrimidine metabolism showed the highest positive correlation with tumor metabolic burden and they were also common poor prognostic pathways in several cancer types. We additionally examined whether genetic alterations associated with the heterogeneity of metabolic landscape. Genetic alterations associated with each metabolic pathway differed between cancers, however, they were a part of cancer drivers in most cancer types

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these networks. The model was validated in two test sets. Survival analysis was performed using the output of the model to evaluate whether it could predict patients’ survival independent of clinicopathological variables. Five networks were significantly associated with patients’ survival. Considering prognostic significance and representativeness, genes of the two survival-related networks were selected for input of the model. The output of the model was significantly associated with patients’ survival in two test sets and training set (p<0.00001, p<0.0001 and p=0.02 for training and test sets 1 and 2, resp.). In multivariate analyses, the model was associated with patients’ prognosis independent of other clinicopathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature and clinical application of deep learning in genomic data science for prognosis prediction