Ultra-rapid meningeal metastasis in triple-negative breast cancer: A case report.

Introduction And Importance: Triple-negative breast cancer (TNBC) is highly invasive and poorly responsive to standard treatments, making it prone to brain metastasis, which exhibits significant intracranial invasiveness. But brain metastasis is extremely rare within one month after neoadjuvant therapy and standard modified radical surgery. Here, we report a case of a patient who, after completing neoadjuvant chemotherapy and achieving partial remission (PR), was diagnosed with brain metastasis one month post-surgery.

Identification of therapeutic targets in lung adenocarcinoma using Mendelian randomization and multi-omics.

Background: Lung adenocarcinoma (LUAD) remains associated with limited effective pharmacological treatment options. This study aimed to identify potential therapeutic targets for LUAD through the integration and analysis of multi-omics datasets.

Methods: A meta-analysis was conducted using two extensive proteomics datasets, the UK Biobank Proteomics Project (UKB-PPP) and the Fenland study, to identify disease-associated targets for LUAD through the Summary-Data-Based Mendelian Randomization method.

Mendelian Randomization Assessment of the Genetic Effects of Lipid-Lowering Drugs on Digestive System Cancers.

The relationship between lipid-lowering drugs and the risk of digestive system cancers remains unclear. This study aims to assess the risk association between lipid-lowering drugs and digestive system cancers through mendelian randomization (MR) analysis. We utilized genetic instruments to substitute for the exposure to lipid-lowering drugs, including expression quantitative trait loci (eQTL) for HMGCR, PCSK9, and NPC1L1, as well as genetic variants associated with low-density lipoprotein (LDL) from the Global Lipids Genetics Consortium's genome-wide association study (GWAS) data for target genes.

Assessing the genetic estimates of the association between plasma caffeine and cancer risk through Mendelian randomization.

Background: Observational studies still cannot establish a causal relationship between plasma caffeine levels and cancer risk. This study aimed to investigate the genetic effects of plasma caffeine levels on cancer risk through Mendelian randomization (MR).

Methods: Plasma caffeine's genome-wide association study (GWAS) data were derived from a meta-analysis of 9,876 individuals of European ancestry.

Machine learning methods predict recurrence of pN3b gastric cancer after radical resection.

Background: The incidence of stage pN3b gastric cancer (GC) is low, and the clinical prognosis is poor, with a high rate of postoperative recurrence. Machine learning (ML) methods can predict the recurrence of GC after surgery. However, the prognostic significance for pN3b remains unclear.

Development and validation of the novel subclassification of pN3 for patients with esophageal cancer.

Background: Patients with stage pN3 esophageal cancer (EC) have a large number of metastatic lymph nodes (mLNs) and have poor prognosis. This study was to elucidate whether subclassification of pN3 according to the number of mLNs could improve the discrimination ability of EC patients.

Methods: This study retrospectively analyzed patients with pN3 EC from the Surveillance, Epidemiology, and End Results (SEER) database as a training cohort and SEER validation cohort.

Nomogram Based on Preoperative Fibrinogen and Systemic Immune-Inflammation Index Predicting Recurrence and Prognosis of Patients with Borrmann Type III Advanced Gastric Cancer.

Background And Objectives: The prognosis is known to differ significantly among advanced gastric cancer (AGC) with Borrmann type III. This study aimed to evaluate the prognosis of these patients more individually.

Methods: We selected 542 AGC patients with Borrmann type III.

Improvement of ACK1-targeted therapy efficacy in lung adenocarcinoma using chloroquine or bafilomycin A1.

Background: Activated Cdc42-associated kinase 1 (ACK1) is a promising druggable target for cancer, but its inhibitors only showed moderate effects in clinical trials. The study aimed to investigate the underlying mechanisms and improve the antitumor efficacy of ACK1 inhibitors.

Methods: RNA-seq was performed to determine the downstream pathways of ACK.

Prognostic Value of Combination of Controlling Nutritional Status and Tumor Marker in Patients with Radical Non-Small-Cell Lung Cancer.

Background: Controlling nutritional status (CONUT) and tumor markers are associated with prognosis in patients with non-small-cell lung cancer (NSCLC). This study is aimed at exploring the potential usefulness of T-CONUT, constructed by combining CONUT and tumor markers, for NSCLC patients undergoing radical surgery.

Methods: A total of 483 patients with NSCLC underwent radical surgical resection.

Integrated analysis of immune infiltration in esophageal carcinoma as prognostic biomarkers.

Background: Esophageal cancer (EC) is one of the most aggressive and lethal malignancies in the world. The quantity and distribution of immune cells are very important factors in determining cancer. Tumor-infiltrating mast cells (TIM) are a class of immune cells with an important immune regulation function for tumor progression.

Development of immune gene pair-based signature predictive of prognosis and immunotherapy in esophageal cancer.

Background: Esophageal cancer (EC) is one of the deadliest solid malignancies, mainly consisting of esophageal squamous cell carcinoma (ESCC) and adenocarcinoma (EAC). Robust biomarkers that can improve patient risk stratification are needed to optimize cancer management. We sought to establish potent prognostic signatures with immune-related gene (IRG) pairs for ESCC and EAC.

Prediction of prognosis and immunotherapy response with a robust immune-related lncRNA pair signature in lung adenocarcinoma.

The tumor immune microenvironment plays essential roles in regulating inflammation, angiogenesis, immune modulation, and sensitivity to therapies. Here, we developed a powerful prognostic signature with immune-related lncRNAs (irlncRNAs) in lung adenocarcinoma (LUAD). We obtained differentially expressed irlncRNAs by intersecting the transcriptome dataset for The Cancer Genome Atlas (TCGA)-LUAD cohort and the ImmLnc database.