MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20%-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to help surgeons make precise treatment decisions. AIM: To construct and evaluate a preoperative diagnostic method to predict occult lymph node metastasis (OCLNM) in early-stage oral and oropharyngeal squamous cell carcinoma (OC and OP SCC) based on deep learning features (DLFs) and radiomics features. METHODS: A total of 319 patients diagnosed with early-stage OC or OP SCC were retrospectively enrolled and divided into training, test and external validation sets. Traditional radiomics features and DLFs were extracted from their MRI images. The least absolute shrinkage and selection operator (LASSO) analysis was employed to identify the most valuable features. Prediction models for OCLNM were developed using radiomics features and DLFs. The effectiveness of the models and their clinical applicability were evaluated using the area under the curve (AUC), decision curve analysis (DCA) and survival analysis. RESULTS: Seventeen prediction models were constructed. The Resnet50 deep learning (DL) model based on the combination of radiomics and DL features achieves the optimal performance, with AUC values of 0.928 (95% CI: 0.881-0.975), 0.878 (95% CI: 0.766-0.990), 0.796 (95% CI: 0.666-0.927) and 0.834 (95% CI: 0.721-0.947) in the training, test, external validation set1 and external validation set2, respectively. Moreover, the Resnet50 model has great prediction value of prognosis in patients with early-stage OC and OP SCC. CONCLUSION: The proposed MRI-based Resnet50 deep learning model demonstrated high capability in diagnosis of OCLNM and prognosis prediction in the early-stage OC and OP SCC. The Resnet50 model could help refine the clinical diagnosis and treatment of the early-stage OC and OP SCC.

Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer.

The current staging method is inadequate to identify high-risk recurrence patients with stage II colon cancer (CC). Using a systematic and comprehensive-biomarker discovery and validation method, we aimed to construct a lncRNA-based signature to improve the prognostic prediction of stage II CC. We identified 1,377 differently expressed lncRNAs by analyzing 16 paired stage II CC tumor tissue and adjacent normal mucosal tissue from the TCGA dataset. Subsequently, using a univariable and step multivariable Cox regression model, we trained an 11-lncRNA signature in the training cohort (n = 141), which could divide patients into high-risk and low-risk groups (AUC at 3 years = 0.801, 95% CI: 0.724-0.877; AUC at 5 years = 0.801, 95% CI: 0.718-0.885). Significantly, patients in the high-risk group had poorer recurrence-free survival (RFS) compared with the low-risk group (log-rank test, P < 0.001 in the training cohort). This lncRNA-based signature was further confirmed in the validation cohort (P < 0.001). Multivariate Cox regression and stratified survival analyses showed that the prognostic value of this signature was independent of other clinicopathological risk factors (CEA, T stage, and chemotherapy). Time-dependent receiver operating characteristic (ROC) analysis demonstrated that this signature had better prognostic ability than any other clinical risk factors or single lncRNAs (all P < 0.05). A nomogram was constructed for clinical use, which integrated both the lncRNA-based signature and clinical risk factors (CEA and T stage) and performed well in the calibration plots. Altogether, our lncRNA-based signature was an independent prognostic factor and possessed a stronger predictive power compared with the currently used clinicopathological risk factors when predicting the recurrence of patients with stage II CC. Collectively, this lncRNA-based signature might facilitate individualized treatment decisions and postoperative counseling, ultimately contributing to improved survival.

TIPE1 promotes liver regeneration by enhancing ROS-FoxO1 axis mediated autophagy.

The strong regenerative ability of the liver safeguards the crucial hepatic functions. The balance between hepatocyte proliferation and death is critical for restoring liver size and physiology. Tumour necrosis factor (TNF) alpha-induced protein 8-like 1 (TIPE1) is highly expressed in liver and has been identified as a candidate regulator for cell proliferation and death, being involved in a variety of biological processes and diseases. However, the role of TIPE1 in liver regeneration remains unexplored. In the present study, we found that TIPE1 expression was elevated in the regenerating liver induced by either partial hepatectomy or 10% carbon tetrachloride administration. Mice with hepatocyte conditional Tipe1 knockout presented significantly impaired liver regeneration. Mechanistically, hepatic Tipe1 deficiency decreased the level of reactive oxygen species in hepatocytes, which in turn led to the inhibition of Forkhead box O1 acetylation and microtubule-associated protein 1 light chain 3 I to microtubule-associated protein 1 light chain 3 II conversion, and the accumulation of sequestosome 1. By contrast, forced expression of TIPE1 in hepatocyte significantly promoted liver regeneration following 70% partial hepatectomy and enhanced hepatocyte reactive oxygen species/acetylated-Forkhead box O1 level and autophagy. These findings indicate that TIPE1 plays a crucial role in liver regeneration by finely regulating the oxidative stress and autophagy and is a potential target for medical intervention of liver regeneration.

Risk of cervical lesions in high-risk HPV positive women with normal cytology: a retrospective single-center study in China.

BACKGROUND: To investigate high-risk HPV (hr-HPV) genotype distributions and the association between hr-HPV infection with severity of the cervical lesions in women with normal cytology. METHODS: In this cross-sectional study, the result of the hr-HPV test and biopsy of colposcopy of women with normal cytology from January 2012 to January 2019 were analyzed. The detection rate of high-grade squamous intraepithelial lesion (HSIL) and cervical cancer were calculated among different hr-HPV genotypes, viral load group, and age groups. RESULTS: Five thousand eight hundred eighty women were enrolled in this study. Overall, 59.97% had normal histological results, 19.32% had HSIL, and 1.07% had cervical cancer. The detection rate of HSIL or worse (HSIL+) in women with single HPV16(34.00%), HPV31(27.50%), HPV33(25.58%), and HPV52(20.88%) infection were higher significantly than single HPV18 (15.59%) infection, respectively. The HSIL+ detection rate between HPV16 single infection and multiple infections (excluding HPV18) was no significant difference (34% vs 35.47%, P = 0.638), contrary to HPV18(12.59% vs 21.67%, P = 0.022). In women without HPV16/18 infections, HSIL+ detection rates for single, double, and triple or more hr-HPV infections were 12.28, 20.31, and 37.50%, the risk of detection of HSIL+ significantly increasing. With the hr-HPV DNA load increases, the risk of detection of HSIL+ (χ2 = 91.01, P < 0.0001) and invasive cervical cancer (χ2 = 5.757, P = 0.016) increase. In age < 30, 31-40, 41-50, 51-60, > 60 group, HSIL+ detection rate were 24.80%、22.10%、19.59%、14.29, and 12.61%, respectively. CONCLUSION: Women who have normal cytology with HPV 16/18/31/33/52/58 infections, multiple HPV infections and high viral load, have a higher detection rate of HSIL+.

Saponin-Based Near-Infrared Nanoparticles with Aggregation-Induced Emission Behavior: Enhancing Cell Compatibility and Permeability.

Fluorescence imaging is critical for physiological activities and cell biology but limited by the poor solubility, cell compatibility, and permeability. Herein, we develop a novel engineering methodology to prepare biocompatible and penetrable aggregation-induced emission (AIE) nanoparticles with the assistance of flash nanoprecipitation (FNP) technology. On the basis of the donor-π-acceptor (D-π-A) system, the AIE building block of tricyano-methylene-pyridine (TCM) is fine-tuned to long emission wavelength by modulating the π-conjugation bridge and electron-donating group, thereby achieving high solid fluorescent quantum yield, near-infrared (NIR) characteristic, large Stokes shift, and excellent photostability. On the basis of the FNP technology, the amphiphilic saponin solution and TCMN-5 in organic solvent are quickly mixed in the multi-inlet vortex mixer (MIVM), followed by saponin-encapsulation of the hydrophobic AIE nucleation with inhibiting further growth of nanoparticles. The biocompatible amphiphilic saponin such as α-hederin can encapsulate and micellize the AIE TCM fluorophore for efficient cell imaging. The kinetic FNP technology can not only modulate the uniform diameter size, but also distinctly increase the micelle stability when compared to the conventional thermodynamic self-aggregation method, which provides an alternative opportunity for scale-up preparation of drugs and probes in delivery vehicles.

Serum miR-210 Contributes to Tumor Detection, Stage Prediction and Dynamic Surveillance in Patients with Bladder Cancer.

MiR-210 is the master hypoxamir that generally exhibits oncogenic properties in most human solid tumors including bladder cancer (BC). However, it remains unknown about the clinical significance of circulating miR-210 levels in BC. In this study, we found that serum miR-210 was up-regulated in patients with BC, and serum levels of miR-210 increased with advancing stage and grade. Moreover, serum miR-210 expression was found to be significantly reduced in paired post-operative samples and elevated in most patients with relapsed BC. Taken together, our data suggest that serum miR-210 could be a potential noninvasive biomarker for screening, predicting and monitoring BC.