Fusobacterium nucleatum-induced exosomal HOTTIP promotes gastric cancer progression through the microRNA-885-3p/EphB2 axis.

Recent studies have reported that Fusobacterium nucleatum (Fn) is associated with gastric cancer (GC). Cancer-derived exosomes contain key regulatory noncoding RNAs and are a crucial medium of intercellular communication. However, the function and regulatory mechanism of exosomes (Fn-GCEx) secreted from Fn-infected GC cells remains unclear. In this study, Fn-GCEx enhanced the proliferation, migration, and invasion capacity of GC cells in vitro, as well as tumor growth and metastasis in vivo. HOTTIP was also upregulated in GC cells treated with Fn-GCEx. Moreover, knockdown of HOTTIP weakened the effects of Fn-GCEx in recipient GC cells. Mechanistically, HOTTIP promoted EphB2 expression by sponging microRNA (miR)-885-3p, thus activating the PI3K/AKT pathway in Fn-GCEx treated GC cells. Overall, Fn infection induced the upregulation of exosomal HOTTIP from GC cells that subsequently promoted GC progression through the miR-885-3p/EphB2/PI3K/AKT axis. Herein, we identify a potential molecular pathway and therapeutic target for GC.

Serum-volatile organic compounds in the diagnostics of esophageal cancer.

The early diagnosis of esophageal cancer (EC) is extremely challenging due to a lack of effective diagnostic methods. The study presented herein aims to assess whether serum volatile organic compounds (VOCs) could be utilised as emerging diagnostic biomarkers for EC. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in the serum samples of 55 patients with EC, with samples from 84 healthy controls (HCs) patients analysed as a comparison. All machine learning analyses were based on data from serum VOCs obtained by GC-IMS. A total of 33 substance peak heights were detected in all patient serum samples. The ROC analysis revealed that four machine learning models were effective in facilitating the diagnosis of EC. In addition, the random forests model for 5 VOCs had an AUC of 0.951, with sensitivities and specificities of 94.1 and 96.0%, respectively.

Serum soluble immune checkpoint levels predict cervical lymph node metastasis of differentiated thyroid carcinoma patients.

BACKGROUND: Cervical lymph node metastasis (CLNM) is common in patients with differentiated thyroid carcinoma (DTC); however, the efficiency to distinguish CLNM before surgery is limited. T cell exhaustion, characterized by the overexpression of immune checkpoints, plays a critical role in the immune evasion of tumors. The aim of this study is to analyze the association between serum levels of soluble immune checkpoints (sICs) and CLNM in DTC patients. METHODS: Levels of sICs in serum of 71 DTC patients and 56 healthy volunteers were analyzed by ELISA. Peripheral blood mononuclear cells and cervical lymph nodes of DTC patients were isolated and their expression of sICs were analyzed. Lymphocytes in cervical lymph nodes were analyzed for immune checkpoints expression and transcription of exhaustion-associated factors. 30 out of 71 DTC patients were followed up from 3 to 9 months after the operation, and postoperative sTIM-3 were analyzed. RESULTS: Four sICs, including LAG-3, PD-1, PD-L1, and TIM-3, were increased in DTC patients. All four sICs exhibited higher sensitivity at discriminating CLNM than cervical ultrasound. In the patient-matched comparison, higher sTIM-3 levels were observed in tumor-involved lymph nodes (TILNs) than in normal lymph nodes (nLNs). T lymphocytes in TILNs had higher TIM-3 surface expression and increased secretion of sTIM-3 than those in patient-matched nLNs. Finally, postoperative serum sTIM-3 levels were decreased in DTC patients with CLNM compared to their preoperative levels. CONCLUSION: Serum levels of sICs, especially sTIM-3, could help to predict CLNM and provide evidence for surgical decision-making in DTC.

Identification and validation of volatile organic compounds in bile for differential diagnosis of perihilar cholangiocarcinoma.

Early and differential diagnosis of perihilar cholangiocarcinoma (PHCCA) is highly challenging. This study aimed to evaluate whether volatile organic compounds (VOCs) in bile samples could be emerging diagnostic biomarkers for PHCCA. We collected 200 bile samples from patients with PHCCA and benign biliary diseases (BBD), including a 140-patient training cohort and an 60-patient test cohort. Gas chromatography-ion mobility spectrometry (GC-IMS) was used for VOCs detection. The predictive models were constructed using machine learning algorithms. Our analysis detected 19 VOC substances using GC-IMS in the bile samples and resulted in the identification of three new VOCs, 2-methoxyfuran, propyl isovalerate, and diethyl malonate that were found in bile. Unsupervised hierarchical clustering analysis supported that VOCs detected in the bile could distinguish PHCCA from BBD. Twelve VOCs defined according to 32 signal peaks had significant statistical significance between BBD and PHCCA, including four up-regulated VOCs in PHCCA, such as 2-ethyl-1-hexanol, propyl isovalerate, cyclohexanone, and acetophenone, while the rest eight VOCs were down-regulated. ROC curve analysis revealed that machine learning models based on VOCs could help diagnosing PHCCA. Among them, SVM provided the highest AUC of 0·966, with a sensitivity and specificity of 93·1% and 100%, respectively. The diagnostic model based on different VOC spectra could be a feasible method for the differential diagnosis of PHCCA.

A Panel of Bile Volatile Organic Compounds Servers as a Potential Diagnostic Biomarker for Gallbladder Cancer.

As no reliable diagnostic methods are available, gallbladder cancer (GBC) is often diagnosed until advanced stages, resulting in a poor prognosis. In the present study, we assessed whether volatile organic compounds (VOCs) could be used as a diagnostic tool for GBC. The VOCs in bile samples collected from 32 GBC patients were detected by gas chromatography-ion mobility spectrometry (GC-IMS), and 54 patients with benign gallbladder diseases (BGD) were used as controls. Both principal component analysis and unsupervised hierarchical clustering analysis gave a clear separation of GBC and BGD based on the bile VOC data collected from GC-IMS. A total of 12 differentially expressed VOCs were identified, including four upregulated (cyclohexanone, 2-ethyl-1-hexanol, acetophenone, and methyl benzoate) and eight downregulated [methyl acetate, (E)-hept-2-enal, hexanal, (E)-2-hexenal, (E)-2-pentenal, pentan-1-ol, 1-octen-3-one, and (E)-2-octenal] in GBC compared with BGD. ROC analysis demonstrated a 12-VOC panel con-structed by four machine learning algorithms, which was superior to the traditional tumor marker, CA19-9. Among them, support vector machines and linear discriminant analysis provided the highest AUCs of 0.972, with a sensitivity of 100% and a specificity of 94.4% in the diagnosis of GBC. Collectively, VOCs might be used as a potential tool for the diagnosis of GBC.

Salivary Fusobacterium nucleatum serves as a potential biomarker for colorectal cancer.

Fusobacterium nucleatum (Fn) is primarily colonized in the oral cavity. Recently, Fn has been closely associated with the tumorigenesis of colorectal cancer (CRC). Here, we showed that the relative level of Fn DNA was increased in the saliva of the CRC group compared with the normal colonoscopy, hyperplastic polyp, and adenoma groups. Receiver operating characteristic curve analysis illustrated that Fn DNA was superior to carcinoembryonic antigen and carbohydrate antigen 19-9 in CRC diagnosis. Moreover, levels of Fn DNA were associated with the overall survival and disease-free survival of CRC patients, which was an independent factor for prognostic prediction. Transcriptome sequencing identified 1,287 differentially expressed mRNAs in tumor tissues between CRC patients with high-Fn and low-Fn infection. Kyoto encyclopedia of genes and genomes analysis showed that ECM-receptor interaction and focal adhesion were the top two significant pathways. Overall, salivary Fn DNA may be a noninvasive diagnostic and prognostic biomarker for CRC patients.