Identification of gene variation feature for targeted therapy of non-small cell lung cancer through combined method of DNA and RNA sequencing.

Next generation sequencing (NGS) is typically used to reveal tumor gene variation feature for targeted therapy of various types of human cancers, including non-small cell lung cancer (NSCLC). Here, we report the role and potential applicable value of combining DNA and RNA sequencing in gene variation detection in NSCLC. 386 NSCLC patients with stage II-IV were enrolled and detected using NGS sequencing of DNA and RNA panels that covered all well-documented target driver genes from the Chinese Society of Clinical Oncology (CSCO). The rate of epidermal growth factor receptor (EGFR) single nucleotide variation (SNV)/indel, mesenchymal-epithelial transition factor (MET) copy number variation (CNV) and anaplastic lymphoma kinase (ALK) fusion were 52.1%, 4.1% and 6.0% in the NSCLC cohort. The landscapes of SNV/indel, CNV and gene fusion in the cohort were depicted as well. Meanwhile, we assessed detection efficacy of DNA and RNA sequencing in gene fusion. Detected number and types of gene fusion using the RNA sequencing were better than those using the DNA sequencing. Gene fusion with intergenic region was only detected by DNA sequencing and MET exon 14 skipping (METΔex14) was more easily identified by RNA sequencing. Finally, we investigated clinical correlations of SNV/indel/CNV/fusion with clinicopathologic features in the NSCLC cohort. Taken together, RNA sequencing significantly complements deficiency of DNA sequencing for gene fusion, which cooperatively presents comprehensive and reliable gene variation features and facilitate the identification of potential drug targets for NSCLC patients.

The DDUP protein encoded by the DNA damage-induced CTBP1-DT lncRNA confers cisplatin resistance in ovarian cancer.

Sustained activation of DNA damage response (DDR) signaling has been demonstrated to play vital role in chemotherapy failure in cancer. However, the mechanism underlying DDR sustaining in cancer cells remains unclear. In the current study, we found that the expression of the DDUP microprotein, encoded by the CTBP1-DT lncRNA, drastically increased in cisplatin-resistant ovarian cancer cells and was inversely correlated to cisplatin-based therapy response. Using a patient-derived human cancer cell model, we observed that DNA damage-induced DDUP foci sustained the RAD18/RAD51C and RAD18/PCNA complexes at the sites of DNA damage, consequently resulting in cisplatin resistance through dual RAD51C-mediated homologous recombination (HR) and proliferating cell nuclear antigen (PCNA)-mediated post-replication repair (PRR) mechanisms. Notably, treatment with an ATR inhibitor disrupted the DDUP/RAD18 interaction and abolished the effect of DDUP on prolonged DNA damage signaling, which resulted in the hypersensitivity of ovarian cancer cells to cisplatin-based therapy in vivo. Altogether, our study provides insights into DDUP-mediated aberrant DDR signaling in cisplatin resistance and describes a potential novel therapeutic approach for the management of platinum-resistant ovarian cancer.

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.

OBJECTIVES: Using contrast-enhanced computed tomography (CECT) and deep learning technology to develop a deep learning radiomics nomogram (DLRN) to preoperative predict risk status of patients with thymic epithelial tumors (TETs). METHODS: Between October 2008 and May 2020, 257 consecutive patients with surgically and pathologically confirmed TETs were enrolled from three medical centers. We extracted deep learning features from all lesions using a transformer-based convolutional neural network and created a deep learning signature (DLS) using selector operator regression and least absolute shrinkage. The predictive capability of a DLRN incorporating clinical characteristics, subjective CT findings and DLS was evaluated by the area under the curve (AUC) of a receiver operating characteristic curve. RESULTS: To construct a DLS, 25 deep learning features with non-zero coefficients were selected from 116 low-risk TETs (subtypes A, AB, and B1) and 141 high-risk TETs (subtypes B2, B3, and C). The combination of subjective CT features such as infiltration and DLS demonstrated the best performance in differentiating TETs risk status. The AUCs in the training, internal validation, external validation 1 and 2 cohorts were 0.959 (95% confidence interval [CI]: 0.924-0.993), 0.868 (95% CI: 0.765-0.970), 0.846 (95% CI: 0.750-0.942), and 0.846 (95% CI: 0.735-0.957), respectively. The DeLong test and decision in curve analysis revealed that the DLRN was the most predictive and clinically useful model. CONCLUSIONS: The DLRN comprised of CECT-derived DLS and subjective CT findings showed a high performance in predicting risk status of patients with TETs. CLINICAL RELEVANCE STATEMENT: Accurate risk status assessment of thymic epithelial tumors (TETs) may aid in determining whether preoperative neoadjuvant treatment is necessary. A deep learning radiomics nomogram incorporating enhancement CT-based deep learning features, clinical characteristics, and subjective CT findings has the potential to predict the histologic subtypes of TETs, which can facilitate decision-making and personalized therapy in clinical practice. KEY POINTS: • A non-invasive diagnostic method that can predict the pathological risk status may be useful for pretreatment stratification and prognostic evaluation in TET patients. • DLRN demonstrated superior performance in differentiating the risk status of TETs when compared to the deep learning signature, radiomics signature, or clinical model. • The DeLong test and decision in curve analysis revealed that the DLRN was the most predictive and clinically useful in differentiating the risk status of TETs.

Predicting lymphovascular invasion in clinically node-negative breast cancer detected by abbreviated magnetic resonance imaging: Transfer learning vs. radiomics.

Objective: To compare the performance of abbreviated breast magnetic resonance imaging (AB-MRI)-based transfer learning (TL) algorithm and radionics analysis for lymphovascular invasion (LVI) prediction in patients with clinically node-negative invasive breast cancer (IBC). Methods: Between November 2017 and October 2020, 233 clinically node-negative IBCs detected by AB-MRI were retrospectively enrolled. One hundred thirty IBCs from center 1 (37 LVI-positive and 93 LVI-negative) were assigned as the training cohort and 103 from center 2 (25 LVI-positive and 78 LVI-negative) as the validation cohort. Based on AB-MRI, a TL signature (TLS) and a radiomics signature (RS) were built with the least absolute shrinkage and selection operator (LASSO) logistic regression. Their diagnostic performances were validated and compared using areas under the receiver operating curve (AUCs), net reclassification improvement (NRI), integrated discrimination improvement (IDI), decision curve analysis (DCA), and stratification analysis. A convolutional filter visualization technique was used to map the response areas of LVI on the AB-MRI. Results: In the validation cohort, compared with RS, the TLS showed better capability in discriminating LVI-positive from LVI-negative lesions (AUC: 0.852 vs. 0.726, p < 0.001; IDI = 0.092, p < 0.001; NRI = 0.554, p < 0.001). The diagnostic performance of TLS was not affected by the menstrual state, molecular subtype, or contrast agent type (all p > 0.05). Moreover, DCA showed that the TLS added more net benefit than RS for clinical utility. Conclusions: An AB-MRI-based TLS was superior to RS for preoperative LVI prediction in patients with clinically node-negative IBC.

ARHGEF37 overexpression promotes extravasation and metastasis of hepatocellular carcinoma via directly activating Cdc42.

BACKGROUND: The extravasation capability of hepatocellular carcinoma (HCC) cells plays a vital role in distant metastasis. However, the underlying mechanism of extravasation in HCC lung metastasis remains largely unclear. METHODS: The expression of ARHGEF37 in human HCC specimens and HCC cell lines was examined by quantitative RT-PCR, western blot, and immunohistochemistry (IHC) analyses. The biological roles and mechanisms of ARHGEF37/Cdc42 in promoting lung metastasis were investigated in vitro and in vivo using cell lines, patient samples, xenograft models. RESULTS: In the current study, we found that Rho guanine nucleotide exchange factor 37 (ARHGEF37) was upregulated in human HCC samples and was associated with tumor invasiveness, pulmonary metastasis and poor prognosis. Overexpressing ARHGEF37 significantly enhanced the extravasation and metastatic capability of HCC cells via facilitating tumor cell adhesion to endothelial cells and trans-endothelial migration. Mechanistically, ARHGEF37 directly interacted with and activated Cdc42 to promote the invadopodia formation in HCC cells, which consequently disrupted the interaction between endothelial cells and pericytes. Importantly, treatment with ZCL278, a specific inhibitor of Cdc42, dramatically inhibited the attachment of ARHGEF37-overexpressing HCC cells to endothelial cells, and the adherence and extravasation in the lung alveoli, resulting in suppression of lung metastasis in mice. CONCLUSION: Our findings provide a new insight into the underlying mechanisms on the ARHGEF37 overexpression-mediated extravasation and pulmonary metastasis of HCC cells, and provided a potential therapeutic target for the prevention and treatment of HCC pulmonary metastasis.

Application of Ultrasound-Guided Cervical Plexus Block in Type I Thyroid Cartilage Laryngoplasty and Vocal Cord Medialization Surgery.

BACKGROUND: Under the background that cervical plexus block (CPB) is often adopted for type I thyroid cartilage laryngoplasty (TCL) and vocal cord medialization (VCM), the present study sought to investigate whether ultrasound-guided CPB (USCPB) could improve the efficiency of type I TCL and VCM. METHODS: Patients with TCL were enrolled and subjected to deep and superficial USCPBs. Intravenous dexmedetomidine pumping was used to assist the painless sedation and ensure the patients to be awake for phonation during surgery. Blood pressure, electrocardiogram, heart rate (HR), and blood oxygen saturation (SpO2) of patients were recorded. The complications, like local anesthetic toxicity and total spinal anesthesia, were monitored. RESULTS: All patients underwent CPB without infiltration anesthesia and complication. The use of Sufentanil at the dose of 5-10 µg was reported in 2 of 15 patients. No Horner syndrome was discovered in patients after anesthesia, and total intravenous anesthesia with intravenous pumping of dexmedetomidine was effective. During surgery, HR, diastolic blood pressure and mean blood pressure were barely changed, but systolic blood pressure was decreased. CONCLUSION: Ultrasound-guided CPB with the intravenous dexmedetomidine pumping is a safe anesthesia method for patients during TCL.

Small lesion classification on abbreviated breast MRI: training can improve diagnostic performance and inter-reader agreement.

OBJECTIVE: To determine whether the diagnostic performance and inter-reader agreement for small lesion classification on abbreviated breast MRI (AB-MRI) can be improved by training, and can achieve the level of full diagnostic protocol MRI (FDP-MRI). METHODS: This retrospective study enrolled 1165 breast lesions (≤ 2 cm; 409 malignant and 756 benign) from 1165 MRI examinations for reading test. Twelve radiologists were assigned into a trained group and a non-trained group. They interpreted each AB-MRI twice, which was extracted from FDP-MRI. After the first read, the trained group received a structured training for AB-MRI interpretation while the non-trained group did not. FDP-MRIs were interpreted by the trained group after the second read. BI-RADS category for each lesion was compared to the standard of reference (histopathological examination or follow-up) to calculate diagnostic accuracy. Inter-reader agreement was assessed using multirater k analysis. Diagnostic accuracy and inter-reader agreement were compared between the trained and non-trained groups, between the first and second reads, and between AB-MRI and FDP-MRI. RESULTS: After training, the diagnostic accuracy of AB-MRI increased from 77.6 to 84.4%, and inter-reader agreement improved from 0.410 to 0.579 (both p < 0.001), which were higher than those of the non-trained group (accuracy, 84.4% vs 78.0%; weighted k, 0.579 vs 0.461; both p < 0.001). The post-training accuracy and inter-reader agreement of AB-MRI were lower than those of FDP-MRI (accuracy, 84.4% vs 92.8%; weighted k, 0.579 vs 0.602; both p < 0.001). CONCLUSIONS: Training can improve the diagnostic performance and inter-reader agreement for small lesion classification on AB-MRI; however, it remains inferior to those of FDP-MRI. KEY POINTS: • Training can improve the diagnostic performance for small breast lesions on AB-MRI. • Training can reduce inter-observer variation for breast lesion classification on AB-MRI, especially among junior radiologists. • The post-training diagnostic performance and inter-reader agreement of AB-MRI remained inferior to those of FDP-MRI.

Nanoarchitectonics for High Adsorption Capacity Carboxymethyl Cellulose Nanofibrils-Based Adsorbents for Efficient Cu2+ Removal.

In the present study, carboxymethyl cellulose nanofibrils (CMCNFs) with different carboxyl content (0.99-2.01 mmol/g) were prepared via controlling the ratio of monochloroacetic acid (MCA) and sodium hydroxide to Eucalyptus bleached pulp (EBP). CMCFs-PEI aerogels were obtained using the crosslinking reaction of polyethyleneimine (PEI) and CMCNFs with the aid of glutaraldehyde (GA). The effects of pH, contact time, temperature, and initial Cu2+ concentration on the Cu2+ removal performance of CMCNFs-PEI aerogels was highlighted. Experimental data showed that the maximum adsorption capacity of CMCNF30-PEI for Cu2+ was 380.03 ± 23 mg/g, and the adsorption results were consistent with Langmuir isotherm (R2 > 0.99). The theoretical maximum adsorption capacity was 616.48 mg/g. After being treated with 0.05 M EDTA solution, the aerogel retained an 85% removal performance after three adsorption-desorption cycles. X-ray photoelectron spectroscopy (XPS) results demonstrated that complexation was the main Cu2+ adsorption mechanism. The excellent Cu2+ adsorption capacity of CMCNFs-PEI aerogels provided another avenue for the utilization of cellulose nanofibrils in the wastewater treatment field.

The pathological tissue expression pattern and clinical significance of m6A-regulatory genes in non-small cell lung cancer.

BACKGROUND: Aberrant expression of m6A-related proteins contributes to the occurrence and progression of non-small cell lung cancer (NSCLC). Current studies mainly focus on single m6A regulatory genes and their underlying mechanisms, and the expression of multiple m6A regulatory proteins in NSCLC remains unclear. Therefore, it is necessary to systematically examine these proteins, particularly in clinical specimens. METHODS: Bioinformatic analysis was used to determine the expression of m6A regulatory genes and their correlation with common gene mutations, such as TP53, EGFR and KRAS, using The Cancer Genome Atlas (TCGA) and the AE-meta databases. Immunohistochemistry was employed to analyze the protein expression of m6A regulatory proteins in 61 benign lung tissues and 316 NSCLC tissues. Statistical analysis was performed to calculate the correlation between the expression of m6A regulatory proteins and clinicopathological features, survival, and common gene mutations in lung carcinoma patients. RESULTS: Analysis of the mRNA levels of 13 core m6A regulators, using information from TCGA and the AE-meta databases, revealed that YTHDF1 levels were upregulated in NSCLC compared to those in adjacent normal tissues. Immunohistochemical staining showed that the expression of METTL3, ALKBH5, YTHDC2 and YTHDF1 was significantly upregulated in NSCLC tissues. Further analyses demonstrated a positive correlation between differentially expressed m6A regulatory proteins, including METTL3, ALKBH5, YTHDC2 and YTHDF1, and the poor clinicopathological features and survival of NSCLC patients. According to the statistics of NSCLC patients enrolled in the present study, the protein levels of METTL3 in patients with EGFR exon-19 mutation were higher than those in patients with wild-type EGFR. CONCLUSIONS: Our results indicate that m6A regulators, including METTL3, ALKBH5, YTHDC2 and YTHDF1, could serve as predictive markers of NSCLC, which will facilitate the early detection and diagnosis of NSCLC.

Computed Tomography-Based Radiomics Nomogram: Potential to Predict Local Recurrence of Gastric Cancer After Radical Resection.

OBJECTIVE: Accurate prediction of postoperative recurrence risk of gastric cancer (GC) is critical for individualized precision therapy. We aimed to investigate whether a computed tomography (CT)-based radiomics nomogram can be used as a tool for predicting the local recurrence (LR) of GC after radical resection. MATERIALS AND METHODS: 342 patients (194 in the training cohort, 78 in the internal validation cohort, and 70 in the external validation cohort) with pathologically proven GC from two centers were included. Radiomics features were extracted from the preoperative CT imaging. The clinical model, radiomics signature, and radiomics nomogram, which incorporated the radiomics signature and independent clinical risk factors, were developed and verified. Furthermore, the performance of these three models was assessed by using the area under the curve (AUC) of receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). RESULTS: The radiomics signature, which was comprised of two selected radiomics features, namely, contrast_GLCM and dissimilarity_GLCM, showed better performance than the clinical model in predicting the LR of GC, with AUC values of 0.83 in the training cohort, 0.84 in the internal validation cohort, and 0.73 in the external cohort, respectively. By integrating the independent clinical risk factors (N stage, bile acid duodenogastric reflux and nodular or irregular outer layer of the gastric wall) into the radiomics signature, the radiomics nomogram achieved the highest accuracy in predicting LR, with AUC values of 0.89, 0.89 and 0.80 in the three cohorts, respectively. DCA in the validation cohort showed that radiomics nomogram added more net benefit than the clinical model within the range of 0.01-0.98. CONCLUSION: The CT-based radiomics nomogram has the potential to predict the LR of GC after radical resection.

Silencing ZIC2 abrogates tumorigenesis and anoikis resistance of non-small cell lung cancer cells by inhibiting Src/FAK signaling.

Aberrant expression of the zinc finger protein (ZIC) family has been extensively reported to contribute to progression and metastasis in multiple human cancers. However, the functional roles and underlying mechanisms of ZIC2 in non-small cell lung cancer (NSCLC) are largely unknown. In this study, ZIC2 expression was evaluated using qRT-PCR, western blot, and immunohistochemistry, respectively. Animal experiments in vivo and functional assays in vitro were performed to investigate the role of ZIC2 in NSCLC. Luciferase assays and chromatin immunoprecipitation (ChIP) were carried out to explore the underlying target involved in the roles of ZIC2 in NSCLC. Here, we reported that ZIC2 was upregulated in NSCLC tissues, and high expression of ZIC2 predicted worse overall and progression-free survival of NSCLC patients. Silencing ZIC2 repressed tumorigenesis and reduced the anoikis resistance of NSCLC cells. Mechanical investigation further revealed that silencing ZIC2 transcriptionally inhibited Src expression and inactivated steroid receptor coactivator/focal adhesion kinase signaling, which further attenuated the anoikis resistance of NSCLC cells. Importantly, our results showed that the number of circulating tumor cells (CTCs) was positively correlated with ZIC2 expression in NSCLC patients. Collectively, our findings unravel a novel mechanism implicating ZIC2 in NSCLC, which will facilitate the development of anti-tumor strategies in NSCLC.

Beta-1 syntrophin (SNTB1) regulates colorectal cancer progression and stemness via regulation of the Wnt/ß-catenin signaling pathway.

BACKGROUND: Beta-1 syntrophin (SNTB1) is an intracellular scaffold protein that provides a platform for the formation of signal transduction complexes, thereby modulating and coordinating various intracellular signaling events and crucial cellular processes. However, the physiological role of SNTB1 is poorly understood. This study aims to explore the role of SNTB1 in colorectal cancer (CRC) tumorigenesis and progression, with particular focus on SNTB1's expression pattern, clinical relevance, and possible molecular mechanism in CRC development. METHODS: SNTB1 expression was analyzed in both clinical tissues and The Cancer Genome Atlas (TCGA) database. Real-time polymerase chain reaction (PCR), Western blot, and immunohistochemical assays were used to detect the relative mRNA and protein levels of SNTB1. Statistical analysis was performed to examine the correlation between SNTB1 expression and the clinicopathological characteristics of patients with CRC. Bioinformatics gene set enrichment analysis (GSEA), Western blot, luciferase assay, and agonist recovery assays were conducted to evaluate the relevance of SNTB1 and the ß-catenin signaling pathway in CRC. A flow cytometry-based Hoechst 33342 efflux assay was applied to assess the proportion of the side population (SP) within total CRC cells. RESULTS: Elevated levels of SNTB1 were identified in CRC tissues and cell lines. The elevation of SNTB1 was positively correlated with the degree of malignancy and poor prognosis in CRC. We further revealed that, by modulating the ß-catenin signaling pathway, silencing SNTB1 expression suppressed tumor growth and cancer stemness in vitro, as well as tumorigenesis in vivo. CONCLUSIONS: These findings suggest that SNTB1 plays a crucial role in colorectal tumorigenesis and progression by modulating ß-catenin signaling and the stemness maintenance of cancer cells.

A novel index for staging hepatitis B related liver cirrhosis in patients with hepatocellular carcinoma.

Information on the stage of liver cirrhosis is essential for prognostication and decisions on surgical planning for hepatocellular carcinoma (HCC) patients. But a non-invasive liver cirrhosis staging model is still lacking. The aim of our study was to develop a non-invasive model based on routine clinical parameters to evaluate the severity of cirrhosis in hepatitis B related HCC patients. A total of 226 HCC patients with chronic hepatitis B virus (HBV) infection who had liver resection were analyzed in this retrospective study. We found that platelets, prothrombin activity, maximum oblique diameter of right hepatic lobe and spleen length were the independent predictors of liver cirrhosis in HCC patients. By cumulating the weight of risk scores of independent variables, we constructed the PPMS (PLT/PTA/maximum oblique diameter of right hepatic lob/spleen length) index. The areas under the receiver operating characteristic curves (AUROC) of PPMS index were 0.820, 0.667, and 0.650 in predicting ≥cirrhosis 1 (C1), ≥cirrhosis 2 (C2), and ≥cirrhosis 3 (C3), respectively. The optimal cut-off value of the PPMS index for predicting ≥C1, ≥C2, and ≥C3 was 4.392, 4.471, and 4.784, respectively. And the corresponding sensitivity was 63.1%, 63.2%, and 64.7%, the corresponding specificity was 89.4%, 64.3%, and 62.5%, respectively. Our study constructed a non-invasive liver cirrhosis index (PPMS) could distinguish patients from different stages of liver cirrhosis, which might add more preoperative information for HCC patients.

ALKAL1 gene silencing prevents colorectal cancer progression via suppressing Sonic Hedgehog (SHH) signaling pathway.

Anaplastic lymphoma kinase (ALK) has been described in a range of human cancers and is involved in cancer initiation and progression via activating multiple signaling pathways, such as the PI3K-AKT, CRKL-C3G, MEKK2/3-MEK5-ERK5, JAK-STAT and MAPK signal pathways. Recently ALK and LTK ligand 1 (ALKAL1) also named "augmentor-ß" or "FAM150A" is identified as a potent activating ligands for human ALK that bind to the extracellular domain of ALK. However, due to its poor stability, the mechanisms of ALKAL1 underlying the tumor progression in the human cancers including colorectal cancer have not been well documented. Herein, ALKAL1 expression was evaluated by RNA sequencing datasets from The Cancer Genome Atlas (TCGA) of 625 cases colorectal cancer, immunohistochemical analysis of 377 cases colorectal cancer tissues, and Western blotting even Real-time PCR of 10 pairs of colorectal cancer tissues and adjacent normal tissues, as well as 8 colorectal cancer cell lines. Statistical analysis was performed to explore the correlation between ALKAL1 expression and clinicopathological features in colorectal cancer. Univariate and multivariate Cox regression analysis were performed to examine the association between ALKAL1 expression and overall survival. In vitro and in vivo assays were performed to assess the biological roles of ALKAL1 in colorectal cancer. Gene set enrichment analysis (GSEA), Western blotting and luciferase assays were used to identify the underlying signal pathway involved in the tumor progression role of ALKAL1. As a result, we showed that ALKAL1 was upregulated in colorectal cancer tissues and cell lines. Upregulation of ALKAL1 correlated with tumor malignancy and poor prognosis in colorectal cancer. ALKAL1 silencing inhibited tumorigenesis, metastasis and invasion of colorectal cancer cells, and inhibited SHH signaling pathway, which is essential for ALKAL1 induced migration. Our findings reveal a new mechanism by which ALKAL1 participates in colorectal cancer migration and invasion via activating the SHH signaling pathway.

LncRNA SOX2OT Knockdown Alleviates Lipopolysaccharide-Induced Damage of PC12 Cells by Regulating miR-331-3p/Neurod1 Axis.

BACKGROUND: Long noncoding RNAs (lncRNAs) serve as crucial regulators in the pathogenesis of spinal cord injury (SCI). However, the role of lncRNA SOX2 overlapping transcript (SOX2OT) in SCI remains to be well revealed. METHODS: An SCI rat model was established and assessed by the Basso-Beattie-Bresnahan (BBB) method. An SCI PC12 cell model was established through lipopolysaccharide (LPS) treatment. Quantitative real-time polymerase chain reaction assay was used for SOX2OT, miR-331-3p, and neurogenic differentiation 1 (Neurod1) mRNA levels. Cell counting kit-8 assay and flow cytometry analysis were performed for cell viability and apoptosis, respectively. Enzyme-linked immunosorbent assay was performed for the levels of inflammatory cytokines. The production of superoxide dismutase and malondialdehyde was determined with relevant kits. Dual-luciferase reporter and RNA immunoprecipitation assays were conducted for the relationships among SOX2OT, miR-331-3p, and Neurod1. Western blot assay was employed for protein levels. RESULTS: SOX2OT was elevated in SCI rat and cell models. SOX2OT knockdown relieved the injury of SCI in SCI rat model. Moreover, the suppressive role in PC12 cell viability and the promotional roles in apoptosis, inflammation, and oxidative stress mediated by LPS were all restored by silencing SOX2OT. For mechanism analysis, SOX2OT was identified as a sponge of miR-331-3p to positively regulate Neurod1 expression. Inhibition of miR-331-3p reversed the effect of SOX2OT knockdown on LPS-induced PC12 damage. Overexpression of miR-331-3p protected PC12 cells from LPS-induced damage by binding to Neurod1. In addition, SOX2OT knockdown relieved PC12 cell injury by inactivation of Janus kinase-signal transducer and activator of transcription pathway. CONCLUSIONS: SOX2OT promoted PC12 cell injury through modulating miR-331-3p/Neurod1 axis and activating Janus kinase-signal transducer and activator of transcription pathway.

Cleavage factor Im 25 as a potential biomarker for prognosis of colorectal cancer.

BACKGROUND: Cleavage factor Im 25 (CFIm25) affects the prognosis and progression of cancer by regulating alternative polyadenylation; however, its role in colorectal cancer remains unclear. METHODS: A standard EnVision tissue microarray was used to evaluate the expression of CFIm25 by immunohistochemistry in 363 patients with colorectal cancer. The correlation between CFIm25 expression and clinicopathological characteristics was analyzed using the χ2 test. Univariate analysis was used to study the relationship between clinicopathological characteristics and patient prognosis. Multivariate analysis was performed using the Cox regression model to identify independent prognostic factors for patients with colorectal cancer. RESULTS: Statistical analysis revealed that CFIm25 expression was significantly associated with vascular invasion (P=0.000), serous invasion (P=0.007), pT stage (P=0.016), and clinical stage (P=0.007). Age, vascular invasion, nerve invasion, serosal invasion, differentiation, clinical stage, recurrence, and CFIm25 expression were significantly correlated with the survival time of colorectal cancer patients (P<0.05). The mean overall survival rate in colorectal cancer patients with decreased CFIm25 expression was only 88.53 months, compared with 110.69 months in the high expression group (P=0.000). Decreased CFIm25 expression indicated a worse prognosis in patients with colorectal cancer. Further analysis by the Cox multivariate model showed that CFIm25 (HR, 0.543; 95% CI: 0.372-0.792; P=0.002) and serosa invasion (HR, 1.470; 95% CI: 1.032-2.094; P=0.033) are independent prognostic factors for colorectal cancer. CONCLUSIONS: Decreased CFIm25 expression indicates a worse prognosis of colorectal cancer patients and could be a novel target for the treatment of colorectal cancer in the future. KEYWORDS: Polyadenylation; survival analysis; colorectal cancer (CRC); CFIm25.

A Heterogeneity Radiomic Nomogram for Preoperative Differentiation of Primary Gastric Lymphoma From Borrmann Type IV Gastric Cancer.

OBJECTIVE: This study aimed to preoperatively differentiate primary gastric lymphoma from Borrmann type IV gastric cancer by heterogeneity nomogram based on routine contrast-enhanced computed tomographic images. METHODS: We enrolled 189 patients from 2 hospitals (90 in the training cohort and 99 in the validation cohort). Subjective findings, including high-enhanced mucosal sign, high-enhanced serosa sign, nodular or an irregular outer layer of the gastric wall, and perigastric fat infiltration, were assessed to construct a subjective finding model. A deep learning model was developed to segment tumor areas, from which 1680 three-dimensional heterogeneity radiomic parameters, including first-order entropy, second-order entropy, and texture complexity, were extracted to build a heterogeneity signature by least absolute shrinkage and selection operator logistic regression. A nomogram that integrates heterogeneity signature and subjective findings was developed by multivariate logistic regression. The diagnostic performance of the nomogram was assessed by discrimination and clinical usefulness. RESULTS: High-enhanced serosa sign and nodular or an irregular outer layer of the gastric wall were identified as independent predictors for building the subjective finding model. High-enhanced serosa sign and heterogeneity signature were significant predictors for differentiating the 2 groups (all, P < 0.05). The area under the curve with heterogeneity nomogram was 0.932 (95% confidence interval, 0.863-0.973) in the validation cohort. Decision curve analysis and stratified analysis confirmed the clinical utility of the heterogeneity nomogram. CONCLUSIONS: The proposed heterogeneity radiomic nomogram on contrast-enhanced computed tomographic images may help differentiate primary gastric lymphoma from Borrmann type IV gastric cancer preoperatively.

MIP image derived from abbreviated breast MRI: potential to reduce unnecessary sub-nipple biopsies during nipple-sparing mastectomy for breast cancer.

OBJECTIVE: To determine the value of a maximum-intensity projection (MIP) image derived from abbreviated breast MRI for excluding occult nipple-areolar complex (NAC) involvement in patients with breast cancer. METHODS: This prospective study included breast cancer patients with clinically normal NACs between April 2016 and May 2019. Abbreviated breast MRI was performed, and an MIP image was generated for each patient. MIP images were examined for the following features: asymmetric nipple enhancement, tumor-nipple distance (TND), tumor diameter, lesion type, location, and multifocality. Independent predictive MIP features for occult NAC involvement were identified by univariable and multivariable logistic regression analyses. Models based on independent predictive MIP features were developed, and their diagnostic performances were evaluated using ROC analysis. The utility of an MIP image for excluding occult NAC involvement was assessed by considering NPVs across patient subgroups. RESULTS: Eight hundred forty-three patients (67 NAC-positive and 776 NAC-negative) were enrolled. On MIP images, asymmetric nipple enhancement (odds ratio, 6.098; p < 0.001) and TND (odds ratio, 0.564; p = 0.003) were independent predictors of occult NAC involvement. A parallel test model of "asymmetric nipple enhancement or TND ≤ 15 mm" yielded the highest AUC value (0.838) among prediction models. The NPV of MIP images for excluding occult NAC involvement was 99.5%, which was applicable across various patient subgroups. CONCLUSIONS: A single MIP image derived from abbreviated breast MRI has utility for excluding occult NAC involvement in breast cancer patients and reducing the number of unnecessary sub-nipple biopsies in nipple-sparing mastectomy. KEY POINTS: • On MIP images derived from abbreviated breast MRI, asymmetric nipple enhancement and tumor-nipple distance were independent predictors for occult nipple involvement in patients with breast cancer. • Negative findings on MIP image can help select patients at minimal risk of occult nipple involvement, for whom unnecessary intraoperative sub-nipple biopsies in nipple-sparing mastectomy can be omitted.

Overexpression of the SARS-CoV-2 receptor ACE2 is induced by cigarette smoke in bronchial and alveolar epithelia.

Angiotensin-converting enzyme 2 (ACE2) has been identified as the functional receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and a target for disease prevention. However, the relationship between ACE2 expression and its clinical implications in SARS-CoV-2 pathogenesis remains unknown. Here, we explored the location and expression of ACE2, and its correlation with gender, age, and cigarette smoke (CS), in a CS-exposed mouse model and 224 non-malignant lung tissues (125 non-smokers, 81 current smokers, and 18 ex-smokers) by immunohistochemistry. Moreover, the correlations of ACE2 with CS-induced oxidative stress-related markers, hypoxia-inducible factor-1α (HIF-1α), inducible nitric oxide synthase (iNOS), and 4-hydroxynonenal (4-HNE) were investigated. Chromatin immunoprecipitation and luciferase reporter assays identified the cause of ACE2 overexpression in human primary lung epithelial cells. We demonstrated that ACE2 was predominantly overexpressed on the apical surface of bronchial epithelium, while reduced in alveolar epithelium, owing to the dramatically decreased abundance of alveolar type II pneumocytes in CS-exposed mouse lungs. Consistent with this, ACE2 was primarily significantly overexpressed in human bronchial and alveolar epithelial cells in smokers regardless of age or gender. Decreased ACE2 expression was observed in bronchial epithelial cells from ex-smokers compared with current smokers, especially in those who had ceased smoking for more than 10 years. Moreover, ACE2 expression was positively correlated with the levels of HIF-1α, iNOS, and 4-HNE in both mouse and human bronchioles. The results were further validated using a publicly available dataset from The Cancer Genome Atlas (TCGA) and our previous integrated data from Affymetrix U133 Plus 2.0 microarray (AE-meta). Finally, our results showed that HIF-1α transcriptionally upregulates ACE2 expression. Our results indicate that smoking-induced ACE2 overexpression in the apical surface of bronchial epithelial cells provides a route by which SARS-CoV-2 enters host cells, which supports clinical relevance in attenuating the potential transmission risk of COVID-19 in smoking populations by smoking cessation. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Ectodysplasin A receptor (EDAR) promotes colorectal cancer cell proliferation via regulation of the Wnt/ß-catenin signaling pathway.

Colorectal cancer is the second leading cause of cancer mortality worldwide with poor prognosis and high recurrence. Aberrant Wnt/ß-catenin signaling promotes oncogenesis by transcriptional activation of c-Myc and its downstream signals. EDAR is characterized as an important effector of canonical Wnt signaling in developing skin appendages, but the interplay between EDAR and Wnt signaling in tumorigenesis and progression remains to be elucidated. In this study, we revealed that EDAR expression is prevalently elevated in colorectal cancer tissues compared with normal tissues. Further analysis suggests there is a strict correlation between EDAR expression and colorectal cancer progression. EDAR silencing by shRNA in colorectal cancer cells showed proliferative suppression via retarding cell cycle at G1 phase. Xenograft mice transplanted with shEDAR-transduced tumor cells significantly alleviated tumor burden in comparison with control mice. Furthermore, downregulation of EDAR was accompanied by reduction of ß-catenin, c-Myc and other G1 cell cycle regulators, while ß-catenin agonist restored the expression of these proteins and overrode the proliferative block induced by EDAR knockdown. These findings indicate that EDAR functions as a component of Wnt/ß-catenin signaling pathway, and is a potential modulator in colorectal carcinogenesis.