Blood cell traits and venous thromboembolism in East Asians: Observational and genetic evidence.

Previous studies have indicated that various blood cell traits are associated with a higher risk of venous thromboembolism (VTE). However, the causal relationship remains uncertain. We collected data from the China pulmonary thromboembolism registry study and the China pulmonary health study, using propensity score matching and two-sample Mendelian randomization analyses with summary statistics from genome-wide association studies of blood cell traits and VTE in the East Asian population.

Oncogenic pathways refine a new perspective on the classification of hepatocellular carcinoma.

Background: Genetic alterations in oncogenic pathways are critical for cancer initiation, development, and treatment resistance. However, studies are limited regarding pathways correlated with prognosis, sorafenib, and transcatheter arterial chemoembolization (TACE) in hepatocellular carcinoma (HCC).

Methods: In this study, 1928 patients from 11 independent datasets and a clinical in-house cohort were screened to explore the relationships among canonical pathway alterations in HCC patients.

Prognosis and Personalized Treatment Prediction in Different Mutation-Signature Hepatocellular Carcinoma.

Introduction: Mutation patterns have been extensively explored to decipher the etiologies of hepatocellular carcinoma (HCC). However, the study and potential clinical role of mutation patterns to stratify high-risk patients and optimize precision therapeutic strategies remain elusive in HCC.

Methods: Using exon-sequencing data in public (n=362) and in-house (n=30) cohorts, mutation signatures were extracted to decipher relationships with the etiology and prognosis in HCC.

Recent advances and applications of CRISPR-Cas9 in cancer immunotherapy.

The incidence and mortality of cancer are the major health issue worldwide. Apart from the treatments developed to date, the unsatisfactory therapeutic effects of cancers have not been addressed by broadening the toolbox. The advent of immunotherapy has ushered in a new era in the treatments of solid tumors, but remains limited and requires breaking adverse effects.

Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients.

Background: Severe acute respiratory syndrome coronavirus 2 causes coronavirus disease 19 (COVID-19). The number of confirmed cases of COVID-19 is also rapidly increasing worldwide, posing a significant challenge to human safety. Asthma is a risk factor for COVID-19, but the underlying molecular mechanisms of the asthma-COVID-19 interaction remain unclear.

Construction of a diagnostic signature and immune landscape of pulmonary arterial hypertension.

Background: Molecular biomarkers are widely used for disease diagnosis and exploration of pathogenesis. Pulmonary arterial hypertension (PAH) is a rapidly progressive cardiopulmonary disease with delayed diagnosis. Studies were limited regarding molecular biomarkers correlated with PAH from a broad perspective.

Integrative bioinformatics analysis to explore a robust diagnostic signature and landscape of immune cell infiltration in sarcoidosis.

Background: The unknown etiology of sarcoidosis with variable clinical features leads to delayed diagnosis and limited therapeutic strategies. Hence, exploring the latent mechanisms and constructing an accessible and reliable diagnostic model of sarcoidosis is vital for innovative therapeutic approaches to improve prognosis.

Methods: This retrospective study analyzed transcriptomes from 11 independent sarcoidosis cohorts, comprising 313 patients and 400 healthy controls.

Use of machine learning models to predict prognosis of combined pulmonary fibrosis and emphysema in a Chinese population.

Background: Combined pulmonary fibrosis and emphysema (CPFE) is a novel clinical entity with a poor prognosis. This study aimed to develop a clinical nomogram model to predict the 1-, 2- and 3-year mortality of patients with CPFE by using the machine learning approach, and to validate the predictive ability of the interstitial lung disease-gender-age-lung physiology (ILD-GAP) model in CPFE.

Methods: The data of CPFE patients from January 2015 to October 2021 who met the inclusion criteria were retrospectively collected.