Genomic characteristics and evolution of Multicentric Esophageal and gastric Cardiac Cancer.

BACKGROUND: Esophageal carcinoma (EC) and gastric cardiac adenocarcinoma (GCA) have high incidence rates in the Chaoshan region of South China. Multifocal esophageal and cardiac cancer (MECC) is commonly observed in this region in clinical practice. However, the genomic characteristics of MECC remains unclear. MATERIALS AND METHODS: In this study, a total of 2123 clinical samples of EC and GCA were analyzed to determine the frequency of multifocal tumors, as well as their occurrence sites and pathological types. Cox proportional hazards regression was used to model the relationship between age, sex, and tumor state concerning survival in our analysis of the cohort of 541 patients with available follow-up data. We performed whole-genome sequencing on 20 tumor foci and 10 normal samples from 10 MECC patients to infer clonal structure on 6 MECC patients to explore genome characteristics. RESULT: The MECC rate of EC and GCA was 5.65% (121 of 2123). Age and sex were potential factors that may influence the risk of MECC (p < 0.001). Furthermore, MECC patients showed worse survival compared with single tumor patients. We found that 12 foci from 6 patients were multicentric origin model (MC), which exhibited significant heterogeneity of variations in paired foci and had an increased number of germline mutations in immune genes compared to metastatic model. In MC cases, different lesions in the same patient were driven by distinct mutation and copy number variation (CNV) events. Although TP53 and other driver mutation genes have a high frequency in the samples, their mutation sites show significant heterogeneity in paired tumor specimens. On the other hand, CNV genes exhibited higher concordance in paired samples, especially in the amplification of oncogenes and the deletion of tumor suppressor genes. CONCLUSIONS: The extent of inter-tumor heterogeneity suggests both monoclonal and polyclonal origins of MECC, which could provide insight into the genome diversity of MECC and guide clinical implementation.

Alzheimer's disease diagnosis from multi-modal data via feature inductive learning and dual multilevel graph neural network.

Multi-modal data can provide complementary information of Alzheimer's disease (AD) and its development from different perspectives. Such information is closely related to the diagnosis, prevention, and treatment of AD, and hence it is necessary and critical to study AD through multi-modal data. Existing learning methods, however, usually ignore the influence of feature heterogeneity and directly fuse features in the last stages. Furthermore, most of these methods only focus on local fusion features or global fusion features, neglecting the complementariness of features at different levels and thus not sufficiently leveraging information embedded in multi-modal data. To overcome these shortcomings, we propose a novel framework for AD diagnosis that fuses gene, imaging, protein, and clinical data. Our framework learns feature representations under the same feature space for different modalities through a feature induction learning (FIL) module, thereby alleviating the impact of feature heterogeneity. Furthermore, in our framework, local and global salient multi-modal feature interaction information at different levels is extracted through a novel dual multilevel graph neural network (DMGNN). We extensively validate the proposed method on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and experimental results demonstrate our method consistently outperforms other state-of-the-art multi-modal fusion methods. The code is publicly available on the GitHub website. (https://github.com/xiankantingqianxue/MIA-code.git).

Multi-risk factors joint prediction model for risk prediction of retinopathy of prematurity.

Purpose: Retinopathy of prematurity (ROP) is a retinal vascular proliferative disease common in low birth weight and premature infants and is one of the main causes of blindness in children.In the context of predictive, preventive and personalized medicine (PPPM/3PM), early screening, identification and treatment of ROP will directly contribute to improve patients' long-term visual prognosis and reduce the risk of blindness. Thus, our objective is to establish an artificial intelligence (AI) algorithm combined with clinical demographics to create a risk model for ROP including treatment-requiring retinopathy of prematurity (TR-ROP) infants. Methods: A total of 22,569 infants who underwent routine ROP screening in Shenzhen Eye Hospital from March 2003 to September 2023 were collected, including 3335 infants with ROP and 1234 infants with TR-ROP among ROP infants. Two machine learning methods of logistic regression and decision tree and a deep learning method of multi-layer perceptron were trained by using the relevant combination of risk factors such as birth weight (BW), gestational age (GA), gender, whether multiple births (MB) and mode of delivery (MD) to achieve the risk prediction of ROP and TR-ROP. We used five evaluation metrics to evaluate the performance of the risk prediction model. The area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUCPR) were the main measurement metrics. Results: In the risk prediction for ROP, the BW + GA demonstrated the optimal performance (mean ± SD, AUCPR: 0.4849 ± 0.0175, AUC: 0.8124 ± 0.0033). In the risk prediction of TR-ROP, reasonable performance can be achieved by using GA + BW + Gender + MD + MB (AUCPR: 0.2713 ± 0.0214, AUC: 0.8328 ± 0.0088). Conclusions: Combining risk factors with AI in screening programs for ROP could achieve risk prediction of ROP and TR-ROP, detect TR-ROP earlier and reduce the number of ROP examinations and unnecessary physiological stress in low-risk infants. Therefore, combining ROP-related biometric information with AI is a cost-effective strategy for predictive diagnostic, targeted prevention, and personalization of medical services in early screening and treatment of ROP.

A fundus image dataset for intelligent retinopathy of prematurity system.

Image-based artificial intelligence (AI) systems stand as the major modality for evaluating ophthalmic conditions. However, most of the currently available AI systems are designed for experimental research using single-central datasets. Most of them fell short of application in real-world clinical settings. In this study, we collected a dataset of 1,099 fundus images in both normal and pathologic eyes from 483 premature infants for intelligent retinopathy of prematurity (ROP) system development and validation. Dataset diversity was visualized with a spatial scatter plot. Image classification was conducted by three annotators. To the best of our knowledge, this is one of the largest fundus datasets on ROP, and we believe it is conducive to the real-world application of AI systems.

Efficacy of the induced pluripotent stem cell derived and engineered CD276-targeted CAR-NK cells against human esophageal squamous cell carcinoma.

Introduction: Chimeric antigen receptor natural killer (CAR-NK) cells have been found to be successful in treating hematologic malignancies and present potential for usage in solid tumors. Methods: In this study, we created CD276-targeted CAR-expressing NK cells from pluripotent stem cells (iPSC CD276-targeted CAR-NK cells) and evaluated their cytotoxicity against esophageal squamous cell carcinoma (ESCC) using patient-specific organoid (PSO) models comprising of both CD276-positive and CD276-negative adjacent epithelium PSO models (normal control PSO, NC PSO) as well as primary culture of ESCC cell models. In addition, in vitro and in vivo models such as KYSE-150 were also examined. iPSC NK cells and NK-free media were used as the CAR-free and NK-free controls, respectively. Results: The positive CD276 staining was specifically detected on the ESCC membrane in 51.43% (54/105) of the patients of all stages, and in 51.35% (38/74) of stages III and IV. The iPS CD276-targeted CAR-NK cells, comparing with the iPS NK cells and the NK-free medium, exhibited specific and significant cytotoxic activity against CD276-positive ESCC PSO rather than CD276-negative NC PSO, and exhibited significant cytotoxicity against CD276-expressing cultured ESCC cells, as well as against CD276-expressing KYSE-150 in vitro and in BNDG mouse xenograft. Discussion: The efficacy of the iPSC CD276-targeted CAR-NK cells demonstrated by their successful treatment of CD276-expressing ESCC in a multitude of pre-clinical models implied that they hold tremendous therapeutic potential for treating patients with CD276-expressing ESCC.

Federated Domain Adaptation via Transformer for Multi-Site Alzheimer's Disease Diagnosis.

In multi-site studies of Alzheimer's disease (AD), the difference of data in multi-site datasets leads to the degraded performance of models in the target sites. The traditional domain adaptation method requires sharing data from both source and target domains, which will lead to data privacy issue. To solve it, federated learning is adopted as it can allow models to be trained with multi-site data in a privacy-protected manner. In this paper, we propose a multi-site federated domain adaptation framework via Transformer (FedDAvT), which not only protects data privacy, but also eliminates data heterogeneity. The Transformer network is used as the backbone network to extract the correlation between the multi-template region of interest features, which can capture the brain abundant information. The self-attention maps in the source and target domains are aligned by applying mean squared error for subdomain adaptation. Finally, we evaluate our method on the multi-site databases based on three AD datasets. The experimental results show that the proposed FedDAvT is quite effective, achieving accuracy rates of 88.75%, 69.51%, and 69.88% on the AD vs. NC, MCI vs. NC, and AD vs. MCI two-way classification tasks, respectively.

Salivary Extracellular MicroRNAs for Early Detection and Prognostication of Esophageal Cancer: A Clinical Study.

BACKGROUND & AIMS: Early detection of esophageal squamous cell carcinoma (ESCC) will facilitate curative treatment. We aimed to establish a microRNA (miRNA) signature derived from salivary extracellular vesicles and particles (EVPs) for early ESCC detection and prognostication. METHODS: Salivary EVP miRNA expression was profiled in a pilot cohort (n = 54) using microarray. Area under the receiver operator characteristic curve (AUROC) and least absolute shrinkage and selector operation regression analyses were used to prioritize miRNAs that discriminated patients with ESCC from controls. Using quantitative reverse transcription polymerase chain reaction, the candidates were measured in a discovery cohort (n = 72) and cell lines. The prediction models for the biomarkers were derived from a training cohort (n = 342) and validated in an internal cohort (n = 207) and an external cohort (n = 226). RESULTS: The microarray analysis identified 7 miRNAs for distinguishing patients with ESCC from control subjects. Because 1 was not always detectable in the discovery cohort and cell lines, the other 6 miRNAs formed a panel. A signature of this panel accurately identified patients with all-stage ESCC in the training cohort (AUROC = 0.968) and was successfully validated in 2 independent cohorts. Importantly, this signature could distinguish patients with early-stage (stage Ⅰ/Ⅱ) ESCC from control subjects in the training cohort (AUROC = 0.969, sensitivity = 92.00%, specificity = 89.17%) and internal (sensitivity = 90.32%, specificity = 91.04%) and external (sensitivity = 91.07%, specificity = 88.06%) validation cohorts. Moreover, a prognostic signature based on the panel was established and efficiently predicted the high-risk cases with poor progression-free survival and overall survival. CONCLUSIONS: The salivary EVP-based 6-miRNA signature can serve as noninvasive biomarkers for early detection and risk stratification of ESCC. Chinese Clinical Trial Registry, ChiCTR2000031507.

Identification and Prognostic Effect of Extramural Venous Invasion in Locally Advanced Esophageal Squamous Cell Carcinoma.

The role of extramural venous invasion (EMVI) in esophageal cancer is still unclear. This study aimed to identify EMVI and assess its impact on survival and recurrences in esophageal squamous cell carcinoma (ESCC). Retrospectively, we reviewed resection specimens of 147 locally advanced ESCC (pT3-T4aN0-3M0) patients who had a curative intended surgery alone at the Cancer Hospital of Shantou University from March 2009 to December 2013. After confirming pT≥3 in hematoxylin-eosin tumor slides, EMVI was evaluated by Verhoeff and Caldesmon staining. The impact of EMVI with other clinicopathological characteristics and survival were analyzed using the χ 2 test, Cox regression, and Kaplan-Meier method. EMVI was present in 30.6% (45/147) of the P ≥T3 ESCCs and associated with lymph-vascular invasion and poor differentiation grade ( P <0.05). Disease-free survival and overall survival in patients with EMVI-absent tumors were about 2.0 times longer than in those with EMVI-present tumors. In pN0 patients, EMVI-presence was associated with poor overall survival (HR 4.829, 95% CI 1.434-16.26, P =0.003) and Disease-free Survival (HR 4.026, 95% CI 0.685-23.32, P =0.018). In pN1-3 patients, EMVI had no additional effect on survival. Conclusions EMVI has an independent adverse prognostic effect on survival in ESCC patients after surgery alone. EMVI should be included in pathology reports as it might contribute to identify high-risk patients for potential additional treatment.

Impact of adjuvant chemotherapy for radically resected esophageal squamous cell carcinoma: a propensity score matching analysis.

Background: The aim of this study was to evaluate the impact of adjuvant chemotherapy in patients with radically resected esophageal squamous cell carcinoma (ESCC). Methods: Patients with esophageal cancer who underwent esophagectomy at our hospital from 2010 to 2019 were retrospectively analyzed. Only patients with radically resected ESCC who did not receive neoadjuvant therapy or adjuvant radiotherapy were enrolled in this study. Propensity score matching (1:1) was used to balance the baseline. Results: A total of 1,249 patients met the inclusion criteria and were enrolled in the study, and 263 patients received adjuvant chemotherapy. After matching, 260 pairs were analyzed. The 1-, 3-, and 5-year overall survival (OS) rates were 93.4%, 66.1% and 59.6%, respectively, for patients with adjuvant chemotherapy compared with 83.8%, 58.4% and 48.8%, respectively, for patients with surgery alone (P = 0.003). The 1-, 3-, and 5-year disease-free survival (DFS) rates were 82.3%, 58.8% and 51.3%, respectively, for patients with adjuvant chemotherapy compared with 68.0%, 48.3% and 40.8%, respectively, for patients with surgery alone (P = 0.002). In multivariate analyses, adjuvant chemotherapy was found to be an independent prognostic factor. In subgroup analyses, only the patients in certain subgroups were found to benefit from adjuvant chemotherapy, such as patients who underwent right thoracotomy, pT3 diseases, pN1-pN3 diseases, or pTNM stage III and IVA diseases. Conclusions: Postoperative adjuvant chemotherapy can improve the OS and DFS of ESCC patients after radical resection but may only work for patients in certain subgroups.

Image quality evaluation of diffusion-weighted imaging in bladder cancer: a comparison between integrated slice-specific dynamic shimming and single-shot echo-planar imaging.

Background: Diffusion-weighted imaging (DWI) image quality will affect how well radiologists detect lesions and judge muscular invasion. This study qualitatively and quantitatively compared the image quality of DWI with integrated slice-specific dynamic shimming (iShim) and single-shot echo-planar imaging (SS-EPI) in the diagnosis of bladder cancer (BC) using 3.0 T magnetic resonance imaging (MRI). We also investigated the application value of iShim DWI in BC. Methods: This retrospective study enrolled 97 patients with BC who underwent a preoperative MRI examination, including iShim and SS-EPI DWI. Two radiologists, blinded to the type of DWI, independently rated DWIs on a 5-point Likert scale regarding image quality features (anatomical details, distortion, lesion conspicuity, artifacts, and overall image quality) and evaluated tumor muscular invasion. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), apparent diffusion coefficient (ADC) values, and tumor numbers were manually recorded by another 2 radiologists. Pathologists recorded tumor numbers and sizes in a standard manner. Results: The inter- and intraobserver consistency of image quality features scoring was good to excellent (κ >0.75; P<0.001). The scores of iShim DWI were higher than those of SS-EPI DWI in terms of distortion, artifacts, and overall image quality (P<0.001). The SNR and CNR of iShim DWI were higher than those of SS-EPI DWI (P<0.001), but there was no significant difference in ADC values between the 2 sequences (P>0.05). Based on pathological findings, the sensitivity of iShim and SS-EPI DWI in diagnosing tumor that diameter less than 1 cm was 100% (79/79) and 93.7% (74/79), respectively. The specificity and accuracy (95.2% and 90.2%, respectively) of iShim DWI in diagnosing tumor muscular invasion were significantly higher than those of SS-EPI DWI (76.2% and 80.4%, respectively). The area under the receiver operating characteristic curve of iShim DWI was significantly higher than that of SS-EPI DWI in diagnosing tumor muscular invasion (P=0.017). Conclusions: Compared with SS-EPI DWI, iShim DWI provided higher image quality. iShim DWI effectively detected BC and better identified muscular invasion. This finding can guide the clinical selection of appropriate treatments for patients with BC.

FIT-Net: Feature Interaction Transformer Network for Pathologic Myopia Diagnosis.

Automatic and accurate classification of retinal optical coherence tomography (OCT) images is essential to assist physicians in diagnosing and grading pathological changes in pathologic myopia (PM). Clinically, due to the obvious differences in the position, shape, and size of the lesion structure in different scanning directions, ophthalmologists usually need to combine the lesion structure in the OCT images in the horizontal and vertical scanning directions to diagnose the type of pathological changes in PM. To address these challenges, we propose a novel feature interaction Transformer network (FIT-Net) to diagnose PM using OCT images, which consists of two dual-scale Transformer (DST) blocks and an interactive attention (IA) unit. Specifically, FIT-Net divides image features of different scales into a series of feature block sequences. In order to enrich the feature representation, we propose an IA unit to realize the interactive learning of class token in feature sequences of different scales. The interaction between feature sequences of different scales can effectively integrate different scale image features, and hence FIT-Net can focus on meaningful lesion regions to improve the PM classification performance. Finally, by fusing the dual-view image features in the horizontal and vertical scanning directions, we propose six dual-view feature fusion methods for PM diagnosis. The extensive experimental results based on the clinically obtained datasets and three publicly available datasets demonstrate the effectiveness and superiority of the proposed method. Our code is avaiable at: https://github.com/chenshaobin/FITNet.

Synthesis and in vitro anticancer evaluation of novel flavonoid-based amide derivatives as regulators of the PI3K/AKT signal pathway for TNBC treatment.

Aberrant activation of the PI3K/AKT pathway is considered in many malignant tumors and plays a crucial role in mediating malignancy progression, metastasis, and chemoresistance. Consequently, development of PI3K/AKT pathway targeted drugs is currently an attractive research field for tumor treatment. In this study, twenty-six flavonoid-based amide derivatives were synthesized and evaluated for their antiproliferation effects against seven cancer cell lines, including MDA-MB-231, MCF-7, HCC1937, A549, HepG2, GTL-16 and HeLa. Among them, compound 7t possessed the best specific cytotoxicity against triple negative breast cancer MDA-MB-231 cells with an IC50 value of 1.76 ± 0.91 µM and also presented inhibitory ability on clonal-formation, migration and invasion of MDA-MB-231 cells. Further cell-based mechanistic studies demonstrated that compound 7t caused cell cycle arrest of MDA-MB-231 cells at the G0/G1 phase and induced apoptosis. Meanwhile, the western blot assay revealed that compound 7t could down-regulate the expression of p-PI3K, p-AKT, and Bcl-2 and up-regulate the production of PTEN, Bax, and caspase-3. Molecular docking also showed a possible binding mode of 7t with PI3Kα. Together, compound 7t was eligible as a potential TNBC therapeutic candidate for further development.

Surgical resection for esophageal adenosquamous carcinoma: an analysis of 56 cases.

BACKGROUND: Esophageal adenosquamous carcinoma (EASC) is a rare disease. The biological behavior and treatment of this malignancy are not well studied. METHODS: Data from 56 patients with EASC who underwent esophagectomy were retrospectively analyzed and compared with 5028 patients with esophageal squamous cell carcinoma (ESCC). The impact of clinicopathological factors on the survival of patients with EASC was analyzed. The survival differences between patients with EASC and ESCC were also compared. RESULTS: There were 43 males and 13 females with a mean age of 59.7 ± 1.3 years (range, 39-79 years). Only 1 of the 43 patients who received preoperative esophagoscopic biopsy was diagnosed with EASC. The median survival time for patients with EASC was 32.0 months, and the 1-, 3-, and 5-year overall survival rates were 78.3%, 46.1%, and 29.6%, respectively. Resection margin, pN category, and adjuvant chemotherapy were found to be independent predictors. After 1:1 propensity score matching, the 5-year overall survival rate of 29.6% for patients with EASC was similar to that of 42.5% for patients with ESCC (P = 0.179). CONCLUSIONS: EASC is a rare disease and is easily misdiagnosed by esophagoscopic biopsy. The prognosis of EASC was similar to that of ESCC. Postoperative adjuvant chemotherapy may improve the survival of patients with EASC after esophagectomy.

Esophageal Mucoepidermoid Carcinoma: A Review of 58 Cases.

Background: Esophageal mucoepidermoid carcinoma (EMEC) is a rare disease. The biological behavior and treatment of this malignancy are not well established. Methods: Data from 58 patients with EMEC who underwent esophagectomy were retrospectively analyzed and compared with 5028 patients with esophageal squamous cell carcinoma (ESCC). Kaplan-Meier and multivariate Cox regression analyses were conducted to investigate the association between clinicopathological factors and survival. Results: The study cohort included 36 males and 22 females with a median age of 59 years (range, 40-78 years). Of the 47 patients who underwent preoperative esophagoscopic biopsy, only 1 patient was diagnosed with EMEC. EMEC was more often found in female patients (39.7% versus 25.8%, P=0.036) and patients with EMEC had a significantly lower rate of lymph node metastasis (25.0% versus 49.4%, P<0.001) than patients with ESCC. After 1:1 propensity score matching, the 5-year overall survival rate of 55.2% for patients with EMEC was similar to that of 61.9% for patients with ESCC (P=0.399). Conclusions: EMEC is a rare disease that more often affects females and these patients has less lymph node metastasis than patients with ESCC. Preoperative esophagoscopic biopsy has difficulty obtaining an accurate pathological diagnosis for EMEC patients. The prognosis for EMEC is similar to that for ESCC.

TLR3 Expression is a Potential Prognosis Biomarker and Shapes the Immune-Active Tumor Microenvironment in Esophageal Squamous Cell Carcinoma.

BACKGROUND: Toll-like receptor 3 (TLR3) not only plays a crucial role in innate immune and inflammation but also in anti-cancer immunity. Nevertheless, the clinicopathological outcome of TLR3 in ESCC is still ambiguous. METHODS: Immunohistochemistry was performed to investigate TLR3 expression and its impact on survival in 137 ESCC patients (including paired esophageal tissues with different stages of early lesions from 37 patients). Furthermore, we downloaded ESCC RNA-seq datasets (including phenotype and survival data) from The Cancer Genome Atlas (TCGA). The relationship between TLR3 and prognosis, biological landscape, and immune infiltration was assessed to verify the immunohistochemical results of our tissue samples, explore the possible mechanism of prognostic outcomes, and predict the sensitivity of immunotherapy. RESULTS: TLR3 protein expression displayed an increasing trend in the progression through different grades of cellular atypia, from normal, esophageal simple hyperplasia (ESSH), intraepithelial neoplasia (IEN) to ESCC (P < 0.0083). TLR3 protein had a positive association with inflammation level (Rho = 0.341, P < 0.001). TLR3 mRNA expression was significantly higher in comparison to adjacent normal tissues (P < 0.001). Cox regression analysis indicated high TLR3 protein and mRNA expression conferred good prognosis in our samples and TCGA, especially for advanced ESCC patients (TNM stage III and IV). Overexpression of TLR3 resulted in an immune-active microenvironment via the recruitment of immune-active cells including cytotoxic lymphocytes (CTLs), CD8+ T cells, NK cells, dendritic cells, and M1-type macrophages. TLR3 expression was correlated with the pro-inflammatory cytokines and chemokines relating to anti-tumor immunity. Moreover, GSEA analysis indicated upregulated expression of TLR3 could activate the apoptotic pathway. CONCLUSION: High TLR3 expression in ESCC patients was associated with a more favorable prognosis, immune-active cell infiltration, and an activated apoptotic pathway. TLR3 has potential applications for immunotherapy and immune response prediction in patients with ESCC.

Prognostic Value of Body Mass Index Stratified by Alcohol Drinking Status in Patients With Esophageal Squamous Cell Carcinoma.

BACKGROUND: The goal of this study was to investigate the prognostic value of body mass index (BMI) in patients with esophageal squamous cell carcinoma (ESCC) when stratified by alcohol drinking status. METHODS: A total of 620 patients with ESCC who underwent esophagectomy were analyzed. A receiver operating characteristic curve was constructed to set the appropriate cutoff point for BMI. Alcohol drinking was divided into ever and never. Kaplan-Meier and multivariate Cox regression analyses were conducted to investigate the association between clinicopathological factors and survival. RESULTS: The cutoff point was 18.75 kg/m2 for BMI. Two hundred and twenty-nine patients were ever drinkers, while the other 391 patients were never drinkers. The ever drinker group was found to have more males, longer tumor lengths, advanced pT category disease, advanced pN category disease, and lower tumor locations. However, no significant difference in BMI was found between ever drinkers and never drinkers. For ever drinkers, low BMI was significantly correlated with worse overall survival (hazard ratio = 1.690; P=0.035) and cancer-specific survival (hazard ratio = 1.763; P=0.024) than high BMI after adjusting for other factors. However, BMI was not a prognostic factor in univariate and multivariate analyses for never drinkers. CONCLUSIONS: BMI is a prognostic factor only in ever drinkers with ESCC but not in never drinkers. Further studies are needed to elucidate the mechanism underlying the effect of the interaction between BMI and alcohol consumption on the prognosis of patients with ESCC.

A signature of saliva-derived exosomal small RNAs as predicting biomarker for esophageal carcinoma: a multicenter prospective study.

BACKGROUND: The tRNA-derived small RNAs (tsRNAs) are produced in a nuclease-dependent manner in responses to variety of stresses that are common in cancers. We focus on a cancer-enriched tsRNA signature to develop a salivary exosome-based non-invasive biomarker for human esophageal squamous cell carcinoma (ESCC). METHODS: Cancer-enriched small RNAs were identified by RNA sequencing of salivary exosomes obtained from ESCC patients (n = 3) and healthy controls (n = 3) in a pilot study and further validated in discovery cohort (n = 66). A multicenter prospective observational study was conducted in two ESCC high-incidence regions (n = 320 and 200, respectively) using the newly developed biomarker signature. RESULTS: The tsRNA (tRNA-GlyGCC-5) and a previously undocumented small RNA were specifically enriched in salivary exosomes of ESCC patients, ESCC tissues and ESCC cells. The bi-signature composed of these small RNAs was able to discriminate ESCC patients from the controls with high sensitivity (90.50%) and specificity (94.20%). Based on the bi-signature Risk Score for Prognosis (RSP), patients with high-RSP have both shorter overall survival (OS) (HR 4.95, 95%CI 2.90-8.46) and progression-free survival (PFS) (HR 3.69, 95%CI 2.24-6.10) than those with low-RSP. In addition, adjuvant therapy improved OS (HR 0.47, 95%CI 0.29-0.77) and PFS (HR 0.36, 95%CI 0.21-0.62) only for patients with high but not low RSP. These findings are consistent in both training and validation cohort. CONCLUSIONS: The tsRNA-based signature not only has the potential for diagnosis and prognosis but also may serve as a pre-operative biomarker to select patients who would benefit from adjuvant therapy. TRIAL REGISTRATION: A prospective study of diagnosis biomarkers of esophageal squamous cell carcinoma, ChiCTR2000031507 . Registered 3 April 2016 - Retrospectively registered.

Feasibility of Early Evaluation for the Recurrence of Bladder Cancer after Trans-Urethral Resection: A Comparison between Magnetic Resonance Imaging and Multidetector Computed Tomography.

(1) Background: This study investigates the early evaluation value of magnetic resonance imaging (MRI) and multidetector computed tomography (MDCT) in diagnosing the recurrence of bladder cancer (BC) after trans-urethral resection (TUR) alone or combined with intravesical perfusion chemotherapy. (2) Methods: This retrospective study enrolled 92 patients with BC who underwent MRI and MDCT after TUR. The time interval between MRI and MDCT was no more than 1 week. Tumor recurrence was recorded by two experienced radiologists who were double-blind. Recurrent patients were divided into nodular masses, irregular wall thickening and smooth wall thickening groups according to tumor morphology in cystoscopy and resected gross specimens. Inter- and intra-observer agreement was evaluated using the Kappa test. Imaging diagnostic performance was assessed using receiver operating characteristic (ROC) analysis and McNemar's test based on pathology. (3) Results: There were 56 relapsed and 36 non-relapsed patients. The intra-observer agreement for the imaging diagnosis was excellent (κ = 0.96 for MRI and κ = 0.91 for MDCT, both p < 0.001). The area under the ROC curve of MRI was higher than that for MDCT (0.91 vs. 0.74, p < 0.001) in identifying tumor recurrence and benign treatment-related changes. The sensitivity, specificity and accuracy of MRI (87.5%, 94.4% and 90.2%, respectively) were higher than those of MDCT (67.9%, 80.6% and 72.8%, respectively) in diagnosing tumor recurrence. Two observers missed 10 cases of small lesions (<1 cm) on MDCT. The accuracy of MRI (100%, 90.0% and 25.0%, respectively) was higher than that of MDCT (92.1%, 30.0% and 0%, respectively) in diagnosing nodular masses, irregular wall thickening and smooth wall thickening recurrence patterns. (4) Conclusions: Compared with MDCT, MRI had a higher accuracy in detecting BC recurrence early, especially for nodular masses and irregular wall thickening, and could better differentiate tumor recurrence from benign treatment-related changes.

Mean Corpuscular Volume as a Prognostic Factor for Patients With Habitual Alcohol or Tobacco Use After Esophagectomy.

BACKGROUND: The goal of this study was to investigate the impact of mean corpuscular volume (MCV) in patients with esophageal squamous cell carcinoma (ESCC) who underwent surgical resection. METHODS: A total of 615 patients with ESCC who underwent esophagectomy were analyzed. Patients were divided into two groups according to the standard MCV: the high MCV group (>100 fl) and the low MCV group (≤100 fl). Survival analyses were performed to calculate overall survival (OS) and cancer-specific survival (CSS) and investigate the independent prognostic factors. RESULTS: Fifty-one patients (8.3%) were in the high MCV group, and the other 564 patients (91.7%) were defined as the low MCV group. MCV was significantly correlated with sex, habitual alcohol or tobacco use, tumor length, body mass index, and multiple primary malignancies (P < 0.05). Elevated MCV was significantly correlated with poor survival in univariate and multivariate analyses. However, in subgroup analyses, MCV was found to be correlated with survival only in patients with alcohol or tobacco consumption and not in patients without alcohol or tobacco consumption. CONCLUSIONS: Pretreatment MCV was correlated with survival in ESCC patients after esophagectomy. However, its prognostic value might only exist in patients with alcohol or tobacco consumption.

Biomimetic nanotherapy: core-shell structured nanocomplexes based on the neutrophil membrane for targeted therapy of lymphoma.

BACKGROUND: Non-Hodgkin's lymphoma (NHL) is a malignant disease of lymphoid tissue. At present, chemotherapy is still the main method for the treatment of NHL. R-CHOP can significantly improve the survival rate of patients. Unfortunately, DOX is the main cytotoxic drug in R-CHOP and it can lead to adverse reactions. Therefore, it is particularly important to uncover new treatment options for NHL. RESULTS: In this study, a novel anti-tumor nanoparticle complex Nm@MSNs-DOX/SM was designed and constructed in this study. Mesoporous silica nanoparticles (MSNs) loaded with Doxorubicin (DOX) and anti-inflammatory drugs Shanzhiside methylester (SM) were used as the core of nanoparticles. Neutrophil membrane (Nm) can be coated with multiple nanonuclei as a shell. DOX combined with SM can enhance the anti-tumor effect, and induce apoptosis of lymphoma cells and inhibit the expression of inflammatory factors related to tumorigenesis depending on the regulation of Bcl-2 family-mediated mitochondrial pathways, such as TNF-α and IL-1ß. Consequently, the tumor microenvironment (TME) was reshaped, and the anti-tumor effect of DOX was amplified. Besides, Nm has good biocompatibility and can enhance the EPR effect of Nm@MSNs-DOX/SM and increase the effect of active targeting tumors. CONCLUSIONS: This suggests that the Nm-modified drug delivery system Nm@MSNs-DOX/SM is a promising targeted chemotherapy and anti-inflammatory therapy nanocomplex, and may be employed as a specific and efficient anti-Lymphoma therapy.