A radiomics nomogram prediction for survival of patients with "driver gene-negative" lung adenocarcinomas (LUAD).

BACKGROUND: To study the role of computed tomography (CT)-derived radiomics features and clinical characteristics on the prognosis of "driver gene-negative" lung adenocarcinoma (LUAD) and to explore the potential molecular biological which may be helpful for patients' individual postoperative care. METHODS: A total of 180 patients with stage I-III "driver gene-negative" LUAD in the First Affiliated Hospital of Sun Yat-Sen University from September 2003 to June 2015 were retrospectively collected. The Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model was used to screen radiomics features and calculated the Rad-score. The prediction performance of the nomogram model based on radiomics features and clinical characteristics was validated and then assessed with respect to calibration. Gene set enrichment analysis (GSEA) was used to explore the relevant biological pathways. RESULTS: The radiomics and the clinicopathological characteristics were combined to construct a nomogram resulted in better performance for the estimation of OS (C-index: 0.815; 95% confidence interval [CI]: 0.756-0.874) than the clinicopathological nomogram (C-index: 0.765; 95% CI: 0.692-0.837). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the traditional staging system and the clinicopathological nomogram. The clinical prognostic risk score of each patient was calculated based on the radiomics nomogram and divided by X-tile into high-risk (> 65.28) and low-risk (≤ 65.28) groups. GSEA results showed that the low-risk score group was directly related to amino acid metabolism, and the high-risk score group was related to immune and metabolism pathways. CONCLUSIONS: The radiomics nomogram was promising to predict the prognosis of patients with "driver gene-negative" LUAD. The metabolism and immune-related pathways may provide new treatment orientation for this genetically unique subset of patients, which may serve as a potential tool to guide individual postoperative care for those patients.

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in patients with advanced esophageal squamous cell carcinoma (ESCC). METHODS: A total of 64 patients with advance ESCC receiving first-line ICI + CT at two centers between January 2019 and June 2020 were enrolled in this study. Both 2D ROIs and 3D ROIs were segmented. ComBat correction was applied to minimize the potential bias on the results due to different scan protocols. A total of 788 features were extracted and radiomics models were built on corrected/uncorrected 2D and 3D features by using 5-fold cross-validation. The performance of the radiomics models was assessed by its discrimination, calibration and clinical usefulness with independent validation. RESULTS: Five features and support vector machine algorithm were selected to build the 2D uncorrected, 2D corrected, 3D uncorrected and 3D corrected radiomics models. The 2D radiomics models significantly outperformed the 3D radiomics models in both primary and validation cohorts. When ComBat correction was used, the performance of 2D models was better (p = 0.0059) in the training cohort, and significantly better (p < 0.0001) in the validation cohort. The 2D corrected radiomics model yielded the optimal performance and was used to build the nomogram. The calibration curve of the radiomics model demonstrated good agreement between prediction and observation and the decision curve analysis confirmed the clinical utility. CONCLUSIONS: The easy-to-use 2D corrected radiomics model could facilitate noninvasive preselection of ESCC patients who would benefit from ICI + CT.

[Testicular injection of lipopolysaccharide: An effective method for establishing the mouse model of orchitis].

OBJECTIVE: To search for a method of establishing a reliable mouse model of orchitis and investigate the association of orchitis with the activation of the inflammasome. METHODS: We equally randomized 40 adult male KM mice into groups A (sham operation), B (intraperitoneal injection of lipopolysaccharide ï¼»LPSï¼½), C (unilateral testicular injection of glacial acetic acid ï¼»GAAï¼½), and D (unilateral testicular injection of LPS). At 3 weeks after modeling, we measured the sperm concentration and percentage of progressively motile sperm (PMS) in the epididymis by computer-assisted semen analysis, observed the pathological changes in the testis tissue by HE staining, and determined the expressions of the Caspase-1 and interleukin (IL)-1ß proteins by Western blot. RESULTS: The sperm concentration in the epididymis was significantly decreased in groups B (ï¼»25.74 ± 3.19ï¼½ ×106/ml), C (ï¼»17.16 ± 4.41ï¼½ ×106/ml) and D (ï¼»16.92 ± 7.13ï¼½ ×106/ml) as compared with that in group A (ï¼»28.20 ± 1.63ï¼½ ×106/ml) (all P < 0.05), even more significantly in B than in C and D (P < 0.01), and so was PMS in groups B (ï¼»29.57 ± 2.16ï¼½%), C (ï¼»18.10 ± 2.38ï¼½%) and D (ï¼»7.34 ± 1.63ï¼½%) in comparison with group A (ï¼»59.34 ± 1.10ï¼½%) (P < 0.01), even more significantly in B and C than in D (P < 0.01). Light microscopy revealed different degrees of pathological changes in the testis tissue, most significant in group D, followed by C and B. Both the expressions of Caspase-1 and IL-1ß were remarkably up-regulated in groups B, C and D compared with those in group A (P < 0.01), even more markedly in D than in B and C (P < 0.05). CONCLUSIONS: Unilateral testicular injection of LPS is a more efficient method than either unilateral testicular injection of GAA or intraperitoneal injection of LPS for establishing the mouse model of orchitis. Orchitis may be pathologically associated with the activation of the NLRP3 inflammasome.