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The morbidity and mortality of gastrointestinal (GI) malignancies are among the highest in the world, posing a serious threat to human health. Because of the insidious onset of the cancer, it is difficult for patients to be diagnosed at an early stage, and it rapidly progresses to an advanced stage, resulting in poor treatment and prognosis. Fusobacterium nucleatum (F. nucleatum) is a gram-negative, spore-free anaerobic bacterium that primarily colonizes the oral cavity and is implicated in the development of colorectal, esophageal, gastric, and pancreatic cancers via various intricate mechanisms. Recent development in novel research suggests that F. nucleatum may function as a biomarker in GI malignancies. Detecting the abundance of F. nucleatum in stool, saliva, and serum samples of patients may aid in the diagnosis, risk assessment, and prognosis monitoring of GI malignancies. This editorial systematically describes the biological roles and mechanisms of F. nucleatum in GI malignancies focusing on the application of F. nucleatum as a biomarker in the diagnosis and prognosis of GI malignancies to promote the clinical translation of F. nucleatum and GI tumors-related research.
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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.
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Biomarcadores Tumorais , Neoplasias Esofágicas , Compostos Orgânicos Voláteis , Humanos , Compostos Orgânicos Voláteis/análise , Compostos Orgânicos Voláteis/sangue , Neoplasias Esofágicas/sangue , Neoplasias Esofágicas/diagnóstico , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Biomarcadores Tumorais/sangue , Aprendizado de Máquina , Curva ROC , Cromatografia Gasosa-Espectrometria de Massas/métodos , Estudos de Casos e Controles , Espectrometria de Mobilidade Iônica/métodos , Adulto , Detecção Precoce de Câncer/métodos , Sensibilidade e EspecificidadeRESUMO
Early diagnosis of esophageal cancer (EC) is extremely challenging. The study presented herein aimed to assess whether urinary volatile organic compounds (VOCs) may be emerging diagnostic biomarkers for EC. Urine samples were collected from EC patients and healthy controls (HCs). Gas chromatography-ion mobility spectrometry (GC-IMS) was next utilised for volatile organic compound detection and predictive models were constructed using machine learning algorithms. ROC curve analysis indicated that an 8-VOCs based machine learning model could aid the diagnosis of EC, with the Random Forests having a maximum AUC of 0.874 and sensitivities and specificities of 84.2% and 90.6%, respectively. Urine VOC analysis aids in the diagnosis of EC.
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Neoplasias Esofágicas , Compostos Orgânicos Voláteis , Humanos , Compostos Orgânicos Voláteis/análise , Detecção Precoce de Câncer , Cromatografia Gasosa-Espectrometria de Massas/métodos , Biomarcadores , Neoplasias Esofágicas/diagnósticoRESUMO
Fusobacterium nucleatum (Fn) infection and microRNAs (miRNAs) are closely associated with colorectal cancer (CRC) development, but the mechanism by which Fn regulates tumor-suppressive miRNAs via exosomes and facilitates CRC metastasis remains unclear. Here, we identified that Fn infection significantly increased exosomal miR-122-5p levels in the serum of CRC patients and CRC cell culture supernatants through two miRNA panels of high-throughput sequencing and RT-qPCR analysis. In Fn-infected patients, the serum exosomal levels of miR-122-5p were negatively associated with their expression levels of tissues. Downregulated miR-122-5p was demonstrated to enhance the migration, invasion, and metastasis abilities of CRC cells in vivo and in vitro. Secretion of miR-122-5p into exosomes is mediated by hnRNPA2B1. Mechanistically, Fn activated the TGF-ß1/Smads signaling pathway to promote EMT by regulation of the miR-122-5p/FUT8 axis. In conclusion, Fn infection may stimulate CRC cells to excrete exosome-wrapped miR-122-5p, and activate the FUT8/TGF-ß1/Smads axis to promote metastasis.
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Cisplatin is the first-line chemotherapy for gastric cancer (GC). However, its efficacy is dampened by the development of chemoresistance, which leads to poor prognosis in GC patients. Recently, evidence has revealed that circular RNAs (circRNAs) and dysregulation of autophagy-dependent ferroptosis play critical roles in cancer chemoresistance. Herein, for the first time we report that circHIPK3 has a vital role in GC cisplatin resistance. CircHIPK3 regulated cisplatin resistance by targeting autophagy and ferroptosis. In brief, knockdown circHIPK3 decreased GC cell cisplatin resistance by enhancing ferroptosis via the miR-508-3p/Bcl-2/beclin1/SLC7A11 axis. Taken together, our results demonstrate that ferroptosis is a promising strategy to ameliorate cisplatin resistance. Importantly, serum exosomal circHIPK3 could also be a noninvasive indicator to evaluate cisplatin resistance in GC.
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Prostate cancer (PCa) is one of the most common cancers in men worldwide. Early diagnosis of PCa is extremely challenging due to the lack of effective diagnostic methods. The study presented here aims to evaluate whether urine volatile organic compounds (VOCs) can be used as an emerging diagnostic biomarker for PCa. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in urine samples from 66 patients with PCa and to comparatively analyze samples from 87 patients with non-cancerous controls (NCs). A total of 86 substance peak heights were detected in urine samples from all patients. Analysis using four machine learning algorithms suggested that the diagnosis of PCa could be effectively facilitated. Ultimately, diagnostic models were constructed based on the four VOCs selected. The AUC for the RF and SVM model were 0.955 and 0.981, respectively. Both the NN and DT diagnostic models also achieved an AUC of 0.8 or more, but their sensitivity or specificity was poor compared to the RF and SVM models.
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Necroptosis is a newly identified programmed cell death associated with the biological process of various cancers, including esophageal carcinoma (ESCA). Meanwhile, the dysregulation of long non-coding RNAs (lncRNAs) is greatly implicated in ESCA progression and necroptosis regulation. However, the lncRNAs involved in regulating necroptosis in ESCA are still unclear. In this study, we aim to explore the expression profile of necroptosis-related lncRNAs (NRLs), and evaluate their roles in ESCA prognosis and treatment. In the present study, 198 differentially expressed NRLs were identified between the ESCA and adjacent normal tissues through screening the data extracted from the Cancer Genome Atlas (TCGA) database. And, a prognostic panel consisting of 6 NRLs was constructed using the LASSO algorithm and multivariate Cox regression analysis. The ESCA patients with high risks had a markedly reduced survival time and higher mortality prevalence. Moreover, C-index of 6 NRLs-panel was superior to 48 published prognostic models based on lncRNAs or mRNAs for ESCA. There were significant differences between the high-risk and low-risk groups in tumor-related pathways, genetic mutations, and drug sensitivity responses. In vitro analysis revealed that inhibition of PVT1 impeded the proliferation, migration, and colony formation of ESCA cells, increased the expressions of p-RIP1 and p-MLKL and promoted necroptosis. By contrast, PVT1 overexpression resulted in a decrease in necroptotic cell death events, thus promoting tumor progression. Collectively, the established 6-NRLs panel was a promising biomarker for the prognostic prediction of ESCA. Moreover, our current findings provided potential targets for individualized therapy for ESCA patients.
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Carcinoma , Neoplasias Esofágicas , RNA Longo não Codificante , Humanos , RNA Longo não Codificante/genética , Necroptose/genética , Prognóstico , Neoplasias Esofágicas/genéticaRESUMO
Colorectal cancer (CRC) is one of the most common malignancies of the digestive tract, with the annual incidence and mortality increasing consistently. Oxaliplatin-based chemotherapy is a preferred therapeutic regimen for patients with advanced CRC. However, most patients will inevitably develop resistance to oxaliplatin. Many studies have reported that non-coding RNAs (ncRNAs), such as microRNAs, long non-coding RNAs, and circular RNAs, are extensively involved in cancer progression. Moreover, emerging evidence has revealed that ncRNAs mediate chemoresistance to oxaliplatin by transcriptional and post-transcriptional regulation, and by epigenetic modification. In this review, we summarize the mechanisms by which ncRNAs regulate the initiation and development of CRC chemoresistance to oxaliplatin. Furthermore, we investigate the clinical application of ncRNAs as promising biomarkers for liquid CRC biopsy. This review provides new insights into overcoming oxaliplatin resistance in CRC by targeting ncRNAs.