T2WI-based texture analysis predicts preoperative lymph node metastasis of rectal cancer.

BACKGROUND: To prospectively develop and validate the T2WI texture analysis model based on a node-by-node comparison for improving the diagnostic accuracy of lymph node metastasis (LNM) in rectal cancer. METHODS: A total of 381 histopathologically confirmed lymph nodes (LNs) were collected. LNs texture features were extracted from MRI-T2WI. Spearman's rank correlation coefficient and the least absolute shrinkage and selection operator were used for feature selection to construct the LN rad-score. Then the clinical risk factors and LN texture features were combined to establish combined predictive model. Model performance was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Decision curve analysis (DCA) and nomogram were used to evaluate the clinical application of the model. RESULTS: A total of 107 texture features were extracted from LN-MRI images. After selection and dimensionality reduction, the radiomics prediction model consisting of 8 texture features showed well-predictive performance in the training and validation cohorts (AUC, 0.676; 95% CI 0.582-0.771) (AUC, 0.774; 95% CI 0.648-0.899). A clinical-radiomics prediction model with the best performance was created by combining clinical and radiomics features, 0.818 (95% CI 0.742-0.893) for the training and 0.922 (95% CI 0.863-0.980) for the validation cohort. The LN Rad-score in clinical-radiomics nomogram obtained the highest classification contribution and was well calibrated. DCA demonstrated the superiority of the clinical-radiomics model. CONCLUSION: The lymph node T2WI-based texture features can help to improve the preoperative prediction of LNM.

Head-to-head comparison of the diagnostic performance between 68Ga-FAPI-04 PET/CT and 18F-FDG PET/CT in colorectal cancer: a systematic review and meta-analysis.

This study aimed to compare the detection rates of 68Ga-FAPI-04 PET/CT and 18F-FDG PET/CT in colorectal cancer. A systematic search of major medical databases was conducted to identify studies up to September 2023. The primary outcome assessed was the detection rate of 68Ga-FAPI-04 PET/CT and 18F-FDG PET/CT in the primary tumor. Pooled risk ratios with a 95% CI were calculated using random-effect models to adjust for heterogeneity. Eight studies were included in the meta-analysis. 68Ga-FAPI-04 PET/CT has higher uptakes in lymph nodes, bone, and peritoneal metastasis compared with 18F-FDG PET/CT. The detection rate of 68Ga-FAPI-04 PET/CT based on lesion was better for lymph node metastasis (RR = 0.63, 95% CI 0.47-0.84, P = 0.002) and peritoneal metastasis (RR = 0.52, 95% CI 0.32-0.85, P = 0.009), both imaging modalities had essentially the same diagnostic efficacy in primary tumor (RR = 0.99, 95% CI 0.96-1.02, P = 0.49). 68Ga-FAPI-04 as a highly promising PET/CT tracer was superior to 18F-FDG PET/CT in colorectal cancer, especially in detecting lymph node metastases and peritoneal metastases.

Integrative analysis of senescence-related genes identifies robust prognostic clusters with distinct features in hepatocellular carcinoma.

INTRODUCTION: Senescence refers to a state of permanent cell growth arrest and is regarded as a tumor suppressive mechanism, whereas accumulative evidence demonstrate that senescent cells play an adverse role during cancer progression. The scarcity of specific and reliable markers reflecting senescence level in cancer impede our understanding of this biological basis. OBJECTIVES: Senescence-related genes (SRGs) were collected for integrative analysis to reveal the role of senescence in hepatocellular carcinoma (HCC). METHODS: Consensus clustering was used to subtype HCC based on SRGs. Several computational methods, including single sample gene set enrichment analysis (ssGSEA), fuzzy c-means algorithm, were performed. Data of drug sensitivities were utilized to screen potential therapeutic agents for different senescence patients. Additionally, we developed a method called signature-related gene analysis (SRGA) for identification of markers relevant to phenotype of interest. Experimental strategies consisting quantitative real-time PCR (qRT-PCR), ß-galactosidase assay, western blot, and tumor-T cell co-culture system were used to validate the findings in vitro. RESULTS: We identified three robust prognostic clusters of HCC patients with distinct survival outcome, mutational landscape, and immune features. We further extracted signature genes of senescence clusters to construct the senescence scoring system and profile senescence level in HCC at bulk and single-cell resolution. Senescence-induced stemness reprogramming was confirmed both in silico and in vitro. HCC patients with high senescence were immune suppressed and sensitive to Tozasertib and other drugs. We suggested that MAFG, PLIN3, and 4 other genes were pertinent to HCC senescence, and MAFG potentially mediated immune suppression, senescence, and stemness. CONCLUSION: Our findings provide insights into the role of SRGs in patients stratification and precision medicine.