Machine learning-based automated sponge cytology for screening of oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction: a nationwide, multicohort, prospective study.

BACKGROUND: Oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction have a dismal prognosis, and early detection is key to reduce mortality. However, early detection depends on upper gastrointestinal endoscopy, which is not feasible to implement at a population level. We aimed to develop and validate a fully automated machine learning-based prediction tool integrating a minimally invasive sponge cytology test and epidemiological risk factors for screening of oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction before endoscopy. METHODS: For this multicohort prospective study, we enrolled participants aged 40-75 years undergoing upper gastrointestinal endoscopy screening at 39 tertiary or secondary hospitals in China for model training and testing, and included community-based screening participants for further validation. All participants underwent questionnaire surveys, sponge cytology testing, and endoscopy in a sequential manner. We trained machine learning models to predict a composite outcome of high-grade lesions, defined as histology-confirmed high-grade intraepithelial neoplasia and carcinoma of the oesophagus and oesophagogastric junction. The predictive features included 105 cytological and 15 epidemiological features. Model performance was primarily measured with the area under the receiver operating characteristic curve (AUROC) and average precision. The performance measures for cytologists with AI assistance was also assessed. FINDINGS: Between Jan 1, 2021, and June 30, 2022, 17 498 eligible participants were involved in model training and validation. In the testing set, the AUROC of the final model was 0·960 (95% CI 0·937 to 0·977) and the average precision was 0·482 (0·470 to 0·494). The model achieved similar performance to consensus of cytologists with AI assistance (AUROC 0·955 [95% CI 0·933 to 0·975]; p=0·749; difference 0·005, 95% CI, -0·011 to 0·020). If the model-defined moderate-risk and high-risk groups were referred for endoscopy, the sensitivity was 94·5% (95% CI 88·8 to 97·5), specificity was 91·9% (91·2 to 92·5), and the predictive positive value was 18·4% (15·6 to 21·6), and 90·3% of endoscopies could be avoided. Further validation in community-based screening showed that the AUROC of the model was 0·964 (95% CI 0·920 to 0·990), and 92·8% of endoscopies could be avoided after risk stratification. INTERPRETATION: We developed a prediction tool with favourable performance for screening of oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction. This approach could prevent the need for endoscopy screening in many low-risk individuals and ensure resource optimisation by prioritising high-risk individuals. FUNDING: Science and Technology Commission of Shanghai Municipality.

LncRNA Lnc-APUE is Repressed by HNF4α and Promotes G1/S Phase Transition and Tumor Growth by Regulating MiR-20b/E2F1 Axis.

Many long noncoding RNAs (lncRNAs) have been annotated, but their functions remain unknown. The authors found a novel lnc-APUE (lncRNA accelerating proliferation by upregulating E2F1) that is upregulated in different cancer types, including hepatocellular carcinoma (HCC), and high lnc-APUE level is associated with short recurrence-free survival (RFS) of HCC patients. Gain- and loss-of-function analyses showed that lnc-APUE accelerated G1/S transition and tumor cell growth in vitro and allows hepatoma xenografts to grow faster in vivo. Mechanistically, lnc-APUE binds to miR-20b and relieves its repression on E2F1 expression, resulting in increased E2F1 level and accelerated G1/S phase transition and cell proliferation. Consistently, lnc-APUE level is positively associated with the expression of E2F1 and its downstream target genes in HCC tissues. Further investigations disclose that hepatocyte nuclear factor 4 alpha (HNF4α) binds to the lnc-APUE promoter, represses lnc-APUE transcription, then diminishes E2F1 expression and cell proliferation. HNF4α expression is reduced in HCC tissues and low HNF4α level is correlated with high lnc-APUE expression. Collectively, a HNF4α/lnc-APUE/miR-20b/E2F1 axis in which HNF4α represses lnc-APUE expression and keeps E2F1 at a low level is identified. In tumor cells, HNF4α downregulation leads to lnc-APUE upregulation, which prevents the inhibition of miR-20b on E2F1 expression and thereby promotes cell cycle progression and tumor growth.

Functional long non-coding RNAs in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a prevalent human malignancy with high morbidity worldwide. Hepatocarcinogenesis is a complex multistep process, and its underlying molecular mechanisms remain largely unknown. Recently, long non-coding RNAs (lncRNAs), a class of newly discovered molecules, have been revealed as essential regulators in the development of HCC. HCC-associated lncRNAs affect multiple malignant phenotypes by modulating gene expression or protein activity. Moreover, the dysregulation of lncRNAs in the liver is also associated with diseases predisposing to HCC, such as chronic viral infection, nonalcoholic steatohepatitis, and liver fibrosis/cirrhosis. A deeper understanding of the lncRNA regulatory network in the multistep processes of HCC development will provide new insights into the diagnosis and treatment of HCC. In this review, we introduce the biogenesis and function of lncRNAs and summarize recent knowledge on how lncRNAs regulate the malignant hallmarks of HCC, such as uncontrolled cell proliferation, resistance to cell death, metabolic reprogramming, immune escape, angiogenesis, and metastasis. We also review emerging insights into the role of lncRNAs in HCC-associated liver diseases. Finally, we discuss the potential applications of lncRNAs as early diagnostic biomarkers and therapeutic targets.