A deep learning-based automatic image quality assessment method for respiratory phase on computed tomography chest images.

Background: Computed tomography (CT) chest scans have become commonly used in clinical diagnosis. Image quality assessment (IQA) for CT images plays an important role in CT examination. It is worth noting that IQA is still a manual and subjective process, and even experienced radiologists make mistakes due to human limitations (fatigue, perceptual biases, and cognitive biases). There are also kinds of biases because of poor consensus among radiologists. Excellent IQA methods can reliably give an objective evaluation result and also reduce the workload of radiologists. This study proposes a deep learning (DL)-based automatic IQA method, to assess whether the image quality of respiratory phase on CT chest images are optimal or not, so that the CT chest images can be used in the patient's physical condition assessment. Methods: This retrospective study analysed 212 patients' chest CT images, with 188 patients allocated to a training set (150 patients), validation set (18 patients), and a test set (20 patients). The remaining 24 patients were used for the observer study. Data augmentation methods were applied to address the problem of insufficient data. The DL-based IQA method combines image selection, tracheal carina segmentation, and bronchial beam detection. To automatically select the CT image containing the tracheal carina, an image selection model was employed. Afterward, the area-based approach and score-based approach were proposed and used to further optimize the tracheal carina segmentation and bronchial beam detection results, respectively. Finally, the score about the image quality of the patient's respiratory phase images given by the DL-based automatic IQA method was compared with the mean opinion score (MOS) given in the observer study, in which four blinded experienced radiologists took part. Results: The DL-based automatic IQA method achieved good performance in assessing the image quality of the respiratory phase images. For the CT sequence of the same patient, the DL-based IQA method had an accuracy of 92% in the assessment score, while the radiologists had an accuracy of 88%. The Kappa value of the assessment score between the DL-based IQA method and radiologists was 0.75, with a sensitivity of 85%, specificity of 91%, positive predictive value (PPV) of 92%, negative predictive value (NPV) of 93%, and accuracy of 88%. Conclusions: This study develops and validates a DL-based automatic IQA method for the respiratory phase on CT chest images. The performance of this method surpassed that of the experienced radiologists on the independent test set used in this study. In clinical practice, it is possible to reduce the workload of radiologists and minimize errors caused by human limitations.

A computer-aided determining method for the myometrial infiltration depth of early endometrial cancer on MRI images.

To classify early endometrial cancer (EC) on sagittal T2-weighted images (T2WI) by determining the depth of myometrial infiltration (MI) using a computer-aided diagnosis (CAD) method based on a multi-stage deep learning (DL) model. This study retrospectively investigated 154 patients with pathologically proven early EC at the institution between January 1, 2018, and December 31, 2020. Of these patients, 75 were in the International Federation of Gynecology and Obstetrics (FIGO) stage IA and 79 were in FIGO stage IB. An SSD-based detection model and an Attention U-net-based segmentation model were trained to select, crop, and segment magnetic resonance imaging (MRl) images. Then, an ellipse fitting algorithm was used to generate a uterine cavity line (UCL) to obtain MI depth for classification. In the independent test datasets, the uterus and tumor detection model achieves an average precision rate of 98.70% and 87.93%, respectively. Selecting the optimal MRI slices method yields an accuracy of 97.83%. The uterus and tumor segmentation model with mean IOU of 0.738 and 0.655, mean PA of 0.867 and 0.749, and mean DSC of 0.845 and 0.779, respectively. Finally, the CAD method based on the calculated MI depth reaches an accuracy of 86.9%, a sensitivity of 81.8%, and a specificity of 91.7% for early EC classification. In this study, the CAD method implements an end-to-end early EC classification and is found to be on par with radiologists in terms of performance. It is more intuitive and interpretable than previous DL-based CAD methods.

Comprehensive analysis of the expression, prognosis and biological significance of FSCN family in clear cell renal cell carcinoma.

Fascin (FSCN) is an actin-binding protein that serves a critical role in cell migration and invasion, contributing to tumor metastasis. However, there is little known about the function of FSCN family in kidney renal clear cell carcinoma (KIRC). The present study used the UALCAN, gene expression profiling interactive analysis, The Cancer Genome Atlas, cBioPortal, STRING and The Tumor Immune Estimation Resource databases to investigate the transcription level, genetic alteration and biological function of FSCNs in KIRC and their association with the prognosis value and immune cell infiltration in patients with KIRC. Results showed that the expression of FSCN1 and FSCN3 was markedly upregulated in patients with KIRC, while the expression of FSCN2 showed an opposite trend, which was the same as the experiments. Furthermore, the expression levels of FSCNs were associated with pathological stage, molecular subtypes and tumor grade. The expression levels of FSCNs were statistically correlated with the immune cell infiltration in KIRC. Higher expression levels of FSCN1 and FSCN3 were associated with worse overall survival (OS) and progression-free interval of patients bearing KIRC. Univariate and multivariate analysis demonstrated that FSCN2 was an independent risk factor for OS time in KIRC. Furthermore, mutations in FSCNs were significantly associated with poor OS and progression-free survival in patients with KIRC. The FSCNs were involved in pathways including focal adhesion, endocytosis, hypertrophic cardiomyopathy, regulation of actin cytoskeleton. The results indicated that FSCN2 might serve as an independent prognostic factor for OS of KIRC and that FSCN1 and FSCN3 can be used as favorable biomarkers for predicting clinical outcomes in KIRC.

Laboratory blood test profiling reveals distinct biochemical and hemocyte features of KRAS mutated non-small cell lung cancer.

Background: The testing for capability of some routine blood test parameters to reflect the biology of non-small cell lung carcinoma with different driver mutations is of great interest and practice significance. We aim to screen these variables and, if allowed, develop a novel predictive model based on results of these routine blood tests commonly performed in clinical practice to inform which can help doctors assess the patient's genetic mutation status as early as possible before surgery. Methods: For the exploration cohort, we included 1,595 patients who were diagnosed with non-small cell lung cancer (NSCLC) and genetically profiled by a next-generation sequencing panel in the First Affiliated Hospital of Guangzhou Medical University. The external validation cohort, which consists of 197 NSCLC cancer patients from Sun Yat-sen University Cancer Hospital, was subsequently established. Results: We analyzed the association between 46 frequently tested laboratory variables and different genetic mutation types. KRAS mutation was found to be a unique subtype that exclusively correlated with several blood parameters in our study. Least absolute shrinkage and selection operator (LASSO) regression was performed, and the following parameters were found to be significantly associated with KRAS mutation: triglycerides [odds ratio (OR) =1.63], arterial oxygen partial pressure (OR =0.97), uric acid (OR =1.01), basophil count (OR =1.41), eosinophil count (OR =1.146), fibrinogen (OR =1.42), standard bicarbonate (OR =0.85), high-density lipoprotein cholesterol (OR =0.18), alpha-L-fucosidase (OR =1.07). The areas under the receiver-operator characteristic curve in the training set and the external validation set were 0.85 [95% confidence interval (CI): 0.81-0.88] and 0.81 (95% CI: 0.71-0.91), respectively. Conclusions: We developed a non-invasive, more cost-effective predictive model of NSCLC based on routinely available variables, with practical predictive power. This model can be used as a practical screening tool to guide the use of more specialized and expensive molecular assays for KRAS mutation in NSCLC. However, further studies are warranted to investigate the mechanism underlying such association between KRAS mutations and the related parameters of blood tests.

The value of folate receptor-positive circulating tumor cells in the diagnosis of lung cancer and its correlation with clinical characteristics.

OBJECTIVE: The aim of this research is to investigate the feasibility of folate receptor-positive circulating tumor cells (FR+CTCs) as a biomarker for the diagnosis of malignant pulmonary nodules and the correlation between clinicopathological factors and FR+CTC levels. METHODS: Patients initially diagnosed with one or more pulmonary nodules from a computed tomography scan were prospectively included. Three milliliters of peripheral blood was collected from each participant for FR+CTC analysis prior to surgery. Clinical and pathological parameters and FR+CTC levels were compared between patients with lung cancer and benign diseases. RESULTS: Six hundred fifty-three patients had lung cancer and the other 124 had benign lung diseases based on pathological examinations of the resected specimens. The median FR+CTC value of the lung cancer group was 12.0 (95% CI 9.6-16.2) FU/3 mL and that of the benign group was 7.2 (95% CI 5.78-11.2) FU/3 mL. The difference was statistically significant (P < 0.0001). In a receiver operating characteristic analysis to distinguish the two groups, the area under curve of FR+CTC was 0.7457 (95% CI 0.6893-0.8021; P < 0.0001) using a cutoff of 8.65 FU/3 mL. The sensitivity was 86.37%, and the specificity was 74.19%. Combined with conventional serum tumor biomarkers, the area under curve was 0.922 (0.499-0.963). The sensitivity was 92.20%, and the specificity was 83.05%. FR+CTC levels were related to tumor staging (P4 < 0.001), the degree of tumor invasion both in single (P = 0.011) and multiple lesions (P = 0.022), pathological subtypes (P = 0.013), and maximum tumor diameter (P = 0.014). CONCLUSIONS: FR+CTC is an effective and reliable biomarker for the diagnosis of lung cancer. Further, FR+CTC level is correlated with tumor staging, degree of invasion, pathological subtypes, and tumor size.

Intratumor heterogeneity of driver mutations and TMB distribution in 30 early-stage LUAD patients with multiple lesions.

Background: Differentiating multiple pulmonary lesions as multiple primary lung cancer (MLC) or intra-pulmonary metastasis (IPM) is critical. Lung cancer also has a high genetic heterogeneity, which influenced the treatment strategy. Genetic information may aid in tracing lineage information on multiple lung lesions. This study applied comprehensive genomic profiling to decipher the intrinsic genetics of multiple lung lesions. Methods: Sixty-six lung adenocarcinomas (LUAD) tumor lesions (FFEP) archived from 30 patients were included in this study. The 508 cancer-related genes were evaluated by targeted next-generation sequencing (MGI-seq 2000). Results: The study included a total of 30 LUADs (66 samples). The majority of tumors demonstrated intra-tumoral heterogeneity. Two hundred twenty-four mutations were detected by sequencing the 66 samples. We investigated the driver gene mutations of NSCLC patients with multiple lesions. EGFR was the most frequently (48/198) mutated driver gene. The codons in EGFR mainly affected by mutations were p.L858R (18/66 [27.3%]) and exon 19del (8/66 [12.1%]). In addition, additional driver genes were found, including TP53, BRAF, ERBB2, MET, and PIK3CA. We also found that the inter-component heterogeneity of different lesions and more than two different mutation types of EGFR were detected in seven patients with two lesions (P3, P10, P24, P25, P28, P29, and P30). The TMB values of different lesions in each patient were different in 26 patients (except P4, P5, P14, and P30). Conclusions: Comprehensive genomic profiling should be applied to distinguishing the nature of multiple lung lesions irrespective of radiologic and histologic diagnoses.

A deep learning-based automatic staging method for early endometrial cancer on MRI images.

Early treatment increases the 5-year survival rate of patients with endometrial cancer (EC). Deep learning (DL) as a new computer-aided diagnosis method has been widely used in medical image processing which can reduce the misdiagnosis by radiologists. An automatic staging method based on DL for the early diagnosis of EC will benefit both radiologists and patients. To develop an effective and automatic prediction model for early EC diagnosis on magnetic resonance imaging (MRI) images, we retrospectively enrolled 117 patients (73 of stage IA, 44 of stage IB) with a pathological diagnosis of early EC confirmed by postoperative biopsy at our institution from 1 January 2018, to 31 December 2020. Axial T2-weighted image (T2WI), axial diffusion-weighted image (DWI) and sagittal T2WI images from 117 patients have been classified into stage IA and stage IB according to the patient's pathological diagnosis. Firstly, a semantic segmentation model based on the U-net network is trained to segment the uterine region and the tumor region on the MRI images. Then, the area ratio of the tumor region to the uterine region (TUR) in the segmentation map is calculated. Finally, the receiver operating characteristic curves (ROCs) are plotted by the TUR and the results of the patient's pathological diagnosis in the test set to find the optimal staging thresholds for stage IA and stage IB. In the test sets, the trained semantic segmentation model yields the average Dice similarity coefficients of uterus and tumor on axial T2WI, axial DWI, and sagittal T2WI were 0.958 and 0.917, 0.956 and 0.941, 0.972 and 0.910 respectively. With pathological diagnostic results as the gold standard, the classification model on axial T2WI, axial DWI, and sagittal T2WI yielded an area under the curve (AUC) of 0.86, 0.85 and 0.94, respectively. In this study, an automatic DL-based segmentation model combining the ROC analysis of TUR on MRI images presents an effective early EC staging method.

Atrial Lesions in a Pedigree With PRKAG2 Cardiomyopathy: Involvement of Disrupted AMP-Activated Protein Kinase Signaling.

PRKAG2 cardiomyopathy is a rare progressive disease characterized by increased ventricular wall thickness and preexcitation. Dysfunction of the protein 5'-AMP-activated protein kinase (AMPK) plays a decisive role in the progression of ventricular lesions. Although patients with the PRKAG2-R302Q mutation have a high incidence of atrial fibrillation (AF), the molecular mechanism contributing to the disease remains unclear. We carried out whole-genome sequencing with linkage analysis in three affected members of a family. Atrial samples were obtained from the proband via surgical intervention. Control atrium biopsies were obtained from patients with persistent AF. Pathological changes were analyzed using the hematoxylin and eosin (H&E), Masson, and periodic acid-Schiff (PAS) staining. The AMPK signaling pathway was investigated by western blot. A murine atrial cardiomyocyte cell line (HL-1) and human induced pluripotent stem derived atrial cardiomyocytes (hiPSC-ACMs) were transfected with an adenovirus carrying the same mutation. We used enzyme linked immunosorbent assay (ELISA) to determine the AMPK activity in HL-1 cells and hiPSC-ACMs overexpressing PRKAG2-R302Q. Pathological results showed a large quantity of glycogen accumulation and vacuolization in cardiomyocytes from the proband atrial tissue. Western blot analysis revealed that the AMPK activity was significantly downregulated compared with that of the controls. Furthermore, remarkable glycogen deposition and impairment of AMPK activity were reproduced in HL-1 cells overexpressing PRKAG2-R302Q. Taken together, PRKAG2-R302Q mutation directly impair atrial cardiomyocytes. PRKAG2-R302Q mutation lead to glycogen deposition and promote the growth of atrial lesions by disrupting the AMPK pathway.

A multi-analyte cell-free DNA-based blood test for early detection of hepatocellular carcinoma.

The limited performance of guideline-recommended abdominal ultrasound and serum alpha-fetoprotein (AFP) highlights the urgent, unmet need for new biomarkers for more accurate detection of early hepatocellular carcinoma (HCC). To this end, we have conducted a prospective clinical validation study to evaluate the performance of the HelioLiver Test, a multi-analyte blood test combining cell-free DNA methylation patterns, clinical variables, and protein tumor markers. A blinded, multicenter validation study was performed with 247 subjects, including 122 subjects with HCC and 125 control subjects with chronic liver disease. The performance of the HelioLiver Test was compared with AFP and the GALAD score as established HCC surveillance blood tests. The performance of the HelioLiver Test (area under the receiver operating characteristic curve [AUROC] = 0.944) was superior to both AFP (AUROC = 0.851; p < 0.0001) and GALAD (AUROC = 0.899; p < 0.0001). Using a prespecified diagnostic algorithm, the HelioLiver Test showed sensitivities of 85% (95% confidence interval [CI], 78%-90%) for HCC of any stage and 76% (95% CI, 60%-87%) for early stage (American Joint Committee on Cancer [AJCC] I and II) HCC. In contrast, AFP (≥20 ng/mL) alone and the GALAD score (≥-0.63) showed lower sensitivities of 62% (95% CI, 54%-70%) and 75% (95% CI, 67%-82%) for HCC overall, and 57% (95% CI, 40%-71%) and 65% (95% CI, 49%-79%) for early stage (AJCC I and II) HCC, respectively. The specificities of the HelioLiver Test (91%; 95% CI, 85%-95%), AFP (97%; 95% CI, 92%-99%), and the GALAD score (94%; 95% CI, 88%-97%) were similar for control subjects. The HelioLiver Test showed superior performance for HCC detection compared to with both AFP and the GALAD score and warrants further evaluation in HCC surveillance settings.

Three-dimensional characterizations of two-photon excitation fluorescence images of elastic fibers affected by cutaneous scar duration.

BACKGROUND: The type or duration of a scar determines the choice of therapy available. Traditional detection methods can easily cause secondary trauma, so there is an urgent need for a non-invasive, rapid diagnostic approach. METHODS: A strategy for quantitative analysis of three-dimensional (3D) elastic fibers in human cutaneous scars was designed, which included 3D reconstruction, skeleton extraction, quantitative analysis, and random forest regression. RESULTS: Four reconstruction methods were used to reconstruct 3D two-photon excitation fluorescence images of elastic fibers for comparison. In the skeleton extraction stage, the 3D thinning algorithm was improved to prepare for accurate quantitative analysis, in which eight parameters comprising branches number (B-NUM), nodes number (N-NUM), averaged branch broken-line length (AB-BL), averaged linear branch length (AB-LL), averaged branch tortuosity (AB-T), branch direction consistency (B-DC), averaged branch volume (AB-V), and averaged branch sectional area (AB-SA) were presented. Six of them, except averaged branch tortuosity (AB-T) and branch direction consistency (B-DC), showed an explicit tendency to change with scar duration. In the random forests regression analysis, the six extracted parameters could be used to predict scar duration with R2=0.981 and RMSE=0.513. CONCLUSIONS: The parameters we extracted had a distinct relationship with scar duration, and random forests regression showed better performance in forecasting scar duration than unitary models.

Cucurbitacin B enhances apoptosis in gefitinib resistant non­small cell lung cancer by modulating the miR­17­5p/STAT3 axis.

Tyrosine kinase inhibitors, such as gefitinib, are currently widely used as targeted therapeutics for non­small cell lung cancer (NSCLC). Although drug resistance has become a major obstacle to successful treatment, mechanisms underlying resistance to gefitinib remain unclear. Therefore, the present study aimed to investigate the impact of adjunctive cucurbitacin B (CuB) on gefitinib resistance (GR) in the PC9 cell line, including identifying underlying mechanisms. Reverse transcription­quantitative PCR demonstrated significant downregulation of microRNA (miR)­17­5p expression in GR PC9 cells (PC9/GR), and this could be reversed by CuB. During combination treatment with CuB and gefitinib at IC25, PC9/GR cell proliferation was downregulated, and apoptosis was upregulated. The presence of a miR­17­5p inhibitor negated the effects of CuB and gefitinib, whereas the presence of a miR­17­5p mimic enhanced them. Luciferase assays demonstrated that the hypothetical target gene, signal transducer and activator of transcription 3 (STAT3), was directly targeted by miR­17­5p. Moreover, significant elevation of the STAT3 protein and phosphorylation levels in PC9/GR cells was reversed by the addition of CuB, despite a lack of change in STAT3 transcription level. During combined treatment with CuB and gefitinib at IC25, the STAT3 protein expression was negatively associated with the expression of miR­17­5p. Overexpression of STAT3 increased proliferation and decreased apoptosis and the protein levels of apoptosis­related factors cleaved caspase­3 and cleaved caspase­9 of PC9/GR cells. Findings indicated that STAT3 protein and phosphorylation levels became elevated in response to gefitinib, and that CuB­induced miR­17­5p expression led to STAT3 degradation, thereby ameliorating GR. In summary, CuB reduced the proliferation of GR PC9 cells by modulating the miR­17­5p/STAT3 axis, and may represent a promising potential novel strategy for the reversal of GR.

Dual-axis confocal configuration for depth sensitive fluorescence spectroscopy.

The dual-axis confocal (DAC) configuration provides a high axial resolution, long working distance (WD), and large dynamic range. These properties can reveal depth-resolved fluorescence spectra. We present a depth sensitive fluorescence spectroscopy based on the DAC configuration. The system enables high axial resolution of 3.23 µm and a long WD of 3.73 mm compared to that of 4.68 µm and 2.1 mm for comparable single-axis confocal configurations, respectively. Besides, a DAC configuration also offers a superior dynamic range and rejection of out-of-focus scattered light based on the principle of Huygens-Fresnel integrals. Additionally, to locate the target layer, the collection path of the DAC configuration will be used as the other illumination path, forming a dual-axis illumination configuration. These beam paths are used to locate the target layer using a white light imaging system with a commercial low numerical aperture objective. A multi-layer fluorescence phantom of Barrett's esophagus containing fluorescein isothiocyanate and Alexa Fluor 514 was used to verify the principle of depth-resolved fluorescence spectroscopy. The results show that the DAC configuration can collect fluorescence spectra from microscopic regions with high axial resolution.

Immunological and inflammatory profiles during acute and convalescent phases of severe/ critically ill COVID-19 patients.

BACKGROUND: The 2019 Coronavirus (COVID-19) pandemic poses a huge threat internationally; however, the role of the host immune system in the pathogenesis of COVID-19 is not well understood. METHODS: Cytokine and chemokine levels and characterisation of immune cell subsets from 20 COVID-19 cases after hospital admission (17 critically ill and 3 severe patients) and 16 convalescent patients were determined using a multiplex immunoassay and flow cytometry, respectively. RESULTS: IP-10, MCP-1, MIG, IL-6, and IL-10 levels were significantly higher in acute severe/critically ill patients with COVID-19, whereas were normal in patients who had reached convalescence. CD8 T cells in severe and critically ill COVID-19 patients expressed high levels of cytotoxic granules (granzyme B and perforin)and was hyperactivated as evidenced by the high proportions of CD38. Furthermore, the cytotoxic potential of natural killer (NK) cells, and the frequencies of myeloid dendritic cells and plasmacytoid dendritic cells was reduced in patients with severe and critical COVID-19; however, these dysregulations were found to be restored in convalescent phases. CONCLUSION: Thus, elicitation of the hyperactive cytokine-mediated inflammatory response, dysregulation of CD8 T and NK cells, and deficiency of host myeloid and plasmacytoid DCs, may contribute to COVID-19 pathogenesis and provide insights into potential therapeutic targets and strategies.

Clinical Features, Replication Competence, and Innate Immune Responses of Human Adenovirus Type 7 Infection.

BACKGROUND: Epidemiologic reports suggest that the most severe or fatal adenoviral disease in children might be associated with human adenovirus (HAdV) type 7. However, the pathogenesis of HAdV-7-induced severe disease remains poorly understood. METHODS: HAdV-3 and HAdV-7 replication kinetics and the host response to infection were compared using ex vivo human lung tissue cultures. Furthermore, cytokine and chemokine levels and the presence of adenovirus DNA in the serum of hospitalized children infected with HAdV-7 (n = 65) or HAdV-3 (n = 48) were measured (using a multiplex immunoassay and Taqman real-time polymerase chain reaction, respectively). RESULTS: Among 471 HAdV-positive specimens, HAdV-3 or HAdV-7 was the most prevalent genotype during 2014-2016 or 2018, respectively. The incidence of severe pneumonia was higher in HAdV-7-infected than in HAdV-3-infected individuals (30.1% vs 4.5%, respectively). HAdV-7 replicated more efficiently than HAdV-3 ex vivo. Interferon-induced protein 10, interleukin 6, and monocyte chemoattractant protein 1 levels were significantly higher in HAdV-7-infected than in HAdV-3-infected children. Adenovirus DNA was detected in serum samples from 40% and 4.2% of HAdV-7- and HAdV-3-infected children, respectively. Furthermore, viremia was strongly associated with severe clinical presentations. CONCLUSIONS: The pathogenesis of HAdV-7-induced severe disease was probably associated with high replication competence and hyperinflammatory responses. The detection of adenovirus DNA in blood may be useful in assessing risk for severe disease.

Definition and Risks of Cytokine Release Syndrome in 11 Critically Ill COVID-19 Patients With Pneumonia: Analysis of Disease Characteristics.

Corona virus disease 2019 (COVID-19) patients with severe immune abnormalities are at risk of cytokine release syndrome (CRS). The definition, prevention, and treatment of symptoms of CRS in critically ill patients with COVID-19 are important problems. We report a single-center case series of 11 COVID-19 patients with acute respiratory distress syndrome from The First Affiliated Hospital of Guangzhou Medical University in China from 26 January 2020 to 18 February 2020. The termination date of follow-up was 19 February 2020. Eight patients were determined to have characteristics of CRS, including pulmonary inflammation, fever, and dysfunction of nonpulmonary organs. An increase in interleukin-6 in peripheral blood was the highest risk factor and an early indicator of CRS in COVID-19.

Integrating Histologic and Genomic Characteristics to Predict Tumor Mutation Burden of Early-Stage Non-Small-Cell Lung Cancer.

Tumor mutation burden (TMB) serves as an effective biomarker predicting efficacy of mono-immunotherapy for non-small cell lung cancer (NSCLC). Establishing a precise TMB predicting model is essential to select which populations are likely to respond to immunotherapy or prognosis and to maximize the benefits of treatment. In this study, available Formalin-fixed paraffin embedded tumor tissues were collected from 499 patients with NSCLC. Targeted sequencing of 636 cancer related genes was performed, and TMB was calculated. Distribution of TMB was significantly (p < 0.001) correlated with sex, clinical features (pathological/histological subtype, pathological stage, lymph node metastasis, and lympho-vascular invasion). It was also significantly (p < 0.001) associated with mutations in genes like TP53, EGFR, PIK3CA, KRAS, EPHA3, TSHZ3, FAT3, NAV3, KEAP1, NFE2L2, PTPRD, LRRK2, STK11, NF1, KMT2D, and GRIN2A. No significant correlations were found between TMB and age, neuro-invasion (p = 0.125), and tumor location (p = 0.696). Patients with KRAS p.G12 mutations and FAT3 missense mutations were associated (p < 0.001) with TMB. TP53 mutations also influence TMB distribution (P < 0.001). TMB was reversely related to EGFR mutations (P < 0.001) but did not differ by mutation types. According to multivariate logistic regression model, genomic parameters could effectively construct model predicting TMB, which may be improved by introducing clinical information. Our study demonstrates that genomic together with clinical features yielded a better reliable model predicting TMB-high status. A simplified model consisting of less than 20 genes and couples of clinical parameters were sought to be useful to provide TMB status with less cost and waiting time.

Early and rapid prediction of postoperative infections following percutaneous nephrolithotomy in patients with complex kidney stones.

OBJECTIVES: To obtain more accurate and rapid predictors of postoperative infections following percutaneous nephrolithotomy (PCNL) in patients with complex kidney stones, and provide evidence for early prevention and treatment of postoperative infections. PATIENTS AND METHODS: A total of 802 patients with complex kidney stones who underwent PCNL, from September 2016 to September 2017, were recruited. Urine tests, urine cultures (UCs) and stone cultures (SCs) were performed, and the perioperative data were prospectively recorded. RESULTS: In all, 19 (2.4%) patients developed postoperative urosepsis. A multivariate logistic regression analysis revealed that an operating time of ≥100 min, urine test results with both positive urine white blood cells (WBC+) and positive urine nitrite (WBC+NIT+), positive UCs (UC+), and positive SCs (SC+) were independent risk factors of urosepsis. The incidence of postoperative urosepsis was higher in patients with WBC+NIT+ (10%) or patients with both UC+ and SC+ (UC+SC+; 8.3%) than in patients with negative urine test results or negative cultures (P < 0.01). Preoperative WBC+NIT+ was predictive of UC+SC+, with an accuracy of >90%. The main pathogens found in kidney stones were Escherichia coli (44%), Proteus mirabilis (14%) and Staphylococcus (7.4%); whilst the main pathogens found in urine were E. coli (54%), Enterococcus (9.4%) and P. mirabilis (7.6%). The incidence of E. coli was more frequent in the group with urosepsis than in the group without urosepsis (P < 0.05). CONCLUSIONS: WBC+NIT+ in preoperative urine tests could be considered as an early and rapid predictor of UC+SC+ and postoperative urosepsis. Urosepsis following PCNL was strongly associated with E. coli infections in patients with complex kidney stones.

Next generation sequencing-based molecular profiling of lung adenocarcinoma using pleural effusion specimens.

BACKGROUND: Molecular profiling of non-small cell lung cancer (NSCLC) is essential for therapeutic decision-making. Pleural effusion obtained by a non-invasive, repeatable procedure may provide an opportunity for molecular profiling and thereby possibly provide information enabling targeted therapy. In this study, we aimed to evaluate the diagnostic performance of pleural effusion as a specimen for molecular analysis. METHODS: Thirty patients with paired malignant pleural effusion and thoracic biopsy specimens were included. Clinically actionable mutations were assessed using a validated targeted next generation sequencing assay. EGFR/KRAS/ALK mutation status in thoracic biopsy specimens was tested using ARMS PCR. RESULTS: The concordance rate between gene status identified by ARMS and next-generation sequencing (NGS) analysis in the thoracic biopsy and pleural effusion samples was 86.7% (26/30). Compared with the thoracic biopsy specimens, the diagnostic performance of pleural effusion showed a sensitivity of 92.3%, a specificity of 50.0%, and a positive predictive value of 92.3%. Therefore, cases with a low percentage of tumor cells (<5%) can successfully be used to detect actionable mutations in pleural effusion specimens. CONCLUSIONS: These results suggest that pleural effusions are suitable specimens for oncogene mutation analysis and enable targeted therapy for patients with advanced NSCLC.

Comprehensive genomic profiling of lung cancer using a validated panel to explore therapeutic targets in East Asian patients.

People of East Asian ethnicity have a different prevalence of and show unique clinical characteristics and tumor histology of oncogenic mutations. However, only limited studies have explored the landscape of genomic alterations in lung adenocarcinoma derived from Asian patients thus far. In this single-center study, with an aim to elucidate the mutational profile of lung cancer in people of Chinese ethnicity and to use the obtained information to guide decision-making for treatment, we employed a well-validated assay to perform comprehensive genomic characterization of tumor specimens from 306 Chinese lung cancer patients. A total of 845 individual genomic alterations were found in 145 tumor-related genes with a median of 2.8 alterations (range: 1-18) per sample. The most frequently mutated genes were EGFR (46.7%), TP53 (21.2%), ALK (12.1%; 8.8% of mutation and 3.3% of rearrangement) and KRAS (10.1%). Upon comparison with the Cancer Genome Atlas dataset, we found that EGFR was mutated at a much higher frequency in our cohort than in Caucasians, whereas KRAS was only found in 10.1% of our Chinese patients. Clinically relevant genomic alterations were identified in 185 (60.5%) patients, including 50% in adenocarcinoma patients and 14% in squamous cell carcinoma patients. Our findings suggest that the Asian ethnicity is significantly different from the Caucasian ethnicity with regard to the presence of somatic driver mutations. Furthermore, we showed that the use of a comprehensive genotyping approach could help identify actionable genomic alterations that have potential impact on therapeutic decisions.