Rapid human papillomavirus (HPV) screening is urgently needed for preventing and early diagnosis of cervical cancer in rural areas. To date, no HPV nucleic acid test (NAT) can be implemented within a single patient visit starting from clinical samples. Here, we develop a hydrogel loop-mediated isothermal amplification (LAMP) method in a fashion of large-scale parallel (about 1000 cells) in situ HPV DNA detection in clinical cervical exfoliated cells at the single-cell level. It can be used with a hotplate and smartphone to obtain HPV NAT results in less than 30 min, which is especially suitable for the on-site scenario. We apply this rapid HPV NAT on 40 clinical cervical exfoliated cell samples and compare the results to a clinical gold standard quantitative polymerase chain reaction (qPCR) method [area under curve (AUC), 1.00]. Meanwhile, our assay can provide HPV infection information for large-scale parallel single clinical cervical exfoliated cells, which cannot be received from traditional NAT methods. Our findings suggest the potential of in situ hydrogel LAMP as a powerful tool for clinical HPV screening and fundamental research.

Aim Cervical cancer is one of the most aggressive female cancers. RNA methylation is a necessary epigenetic modification in biological process. This study aimed to construct an RNA methylation regulator‐based risk model for predicting the prognosis of cervical cancer patients. Methods The transcriptome profiles of cervical cancer data were obtained from The Cancer Genome Atlas (TCGA) and GSE44001. An RNA methylation‐related risk model was constructed and assessed by the Least absolute shrinkage and selection operator (Lasso)‐penalized Cox regression model and receiver operating characteristic (ROC). Kaplan–Meier and Cox regression analyses were used to evaluate the prognostic effect of the risk model and calculated scores. The immune infiltration difference was further analyzed between the subgroups with a single‐sample gene set enrichment analysis (ssGSEA). Results A total of 63 methylation modulators were included in this study, and 618 cervical cancer patients were identified from TCGA and GSE44001. Differential expression genes profiling RNA methylation regulators between normal and tumor samples were distinct. A four‐gene signature panel was constructed to predict the prognostic risk. The predictive ability was satisfactory. Cervical cancer patients were classified into high‐ or low‐risk subgroups according to the median risk score. Moreover, the immune infiltration patterns between them differed. Conclusions A risk model including four RNA methylation regulators was constructed, which will provide new perspectives for further investigation of the relationship between RNA methylation and cervical cancer.