Construction and validation of a diagnostic model for high-risk papillary thyroid microcarcinoma.

Objective: The purpose of this study was to construct a diagnostic model by exploring the potential predictors of high-risk Papillary Thyroid Microcarcinoma (PTMC) and verifying its reliability.

Methods: A retrospective analysis of PTMC patients who underwent surgical treatment from 2004 to 2015 in the SEER database (training set) and the clinical pathological ultrasound information of PTMC patients at the Sichuan Provincial People's Hospital from 2020 to 2022 (external validation set) was conducted. In the training set, univariate and multivariate logistic regression analyses were used to screen independent predictive factors for high-risk PTMC patients in pathology.

Characteristics of Ovarian Cancer Immune Cell Invasion and Bioinformatics to Predict the Effect of Immunotherapy.

Recent studies have confirmed that tumor immune cell infiltration (ICI) is associated with sensitivity of ovarian cancer (OC) immunotherapy and disease progression of OC patients. However, studies related to immune infiltration in OC, has not been elucidated. Two algorithms are used to analyze the OC data in the TCGA and GEO databases.

CDCA8 as an independent predictor for a poor prognosis in liver cancer.

Background: Human cell division cycle associated 8 (CDCA8) a key regulator of mitosis, has been described as a potential prognostic biomarker for a variety of cancers, such as breast, colon and lung cancers. We aimed to evaluate the potential role of CDCA8 expression in the prognosis of liver cancer by analysing data from The Cancer Genome Atlas (TCGA).

Methods: The Wilcoxon rank-sum test was used to compare the difference in CDCA8 expression between liver cancer tissues and matched normal tissues.

Correction to: ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition.

The article ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition, written by Yu Shuai, Erxi Fan, Qiuyue Zhong, Guangyong Feng, Qiying Chen, Xiaoxia Gou, Guihai Zhang, was originally published.

ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition.

Purpose: This study aimed to investigate the effects of activating transcription factor-5 (ATF5) on nasopharyngeal carcinoma (NPC) cell radioresistance.

Methods: HONE-1 nasopharyngeal carcinoma cells were irradiated by conventional fractionation to generate HONE-1R radiotherapy-resistant cells. Short hairpin RNA (shRNA) expression plasmids targeting the ATF5 gene were constructed and transfected into the HONE-1R cell line.

A gene expression-based study on immune cell subtypes and glioma prognosis.

Object: Glioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumours. Therefore, given this increasing evidence, we explored the levels of some immune cell genes for predicting the prognosis of patients with glioma.

Five genes as a novel signature for predicting the prognosis of patients with laryngeal cancer.

In this study, we purpose to investigate a novel five-gene signature for predicting the prognosis of patients with laryngeal cancer. The laryngeal cancer datasets were obtained from The Cancer Genome Atlas (TCGA). Both univariate and multivariate Cox regression analysis was applied to screening for prognostic differential expressed genes (DEGs), and a novel gene signature was obtained.

Identification and potential mechanisms of a 4-lncRNA signature that predicts prognosis in patients with laryngeal cancer.

Purpose: This study aimed to describe the use of a novel 4-lncRNA signature to predict prognosis in patients with laryngeal cancer and to explore its possible mechanisms.

Methods: We identified lncRNAs that were differentially expressed between 111 tumor tissue samples and 12 matched normal tissue samples from The Cancer Genome Atlas Database (TCGA). We used Cox regression analysis to identify lncRNAs that were correlated with prognosis.