Analysis of the cluster efficacy and prescription characteristics of traditional Chinese medicine intervention for non-small cell lung cancer based on a clustering algorithm.

Background: In recent years, malignant tumors have gradually become one of the main causes of death for Chinese residents, of which lung cancer ranks first in both the incidence and mortality in China.

Objective: To mine the text of traditional Chinese medicine (TCM) clinical medical cases after data cleaning, analyze it, and study the experience of TCM doctors in treating non-small cell lung cancer (NSCLC).

Methods: The applied approach was based on the data mining methods of decentralized and hierarchical system clustering of data from a drug and prescription database.

A large-scale, multicentered trial evaluating the sensitivity and specificity of digital PCR versus ARMS-PCR for detecting ctDNA-based p.T790M in non-small-cell lung cancer patients.

Background: Developing liquid biopsy technology with higher sensitivity and specificity especially for low-frequency mutations remains crucial. This study demonstrated superior performance of the newly developed digital PCR (dPCR) kit for ctDNA-based p.T790M detection in metastatic non-small-cell lung cancer (NSCLC) against ARMS-PCR.

Abnormal spindle-like microcephaly-associated protein enhances cell invasion through Wnt/β-catenin-dependent regulation of epithelial-mesenchymal transition in non-small cell lung cancer cells.

Background: Lung cancer is one of the most common cancer worldwide, invasion and metastasis are still the bottleneck in the clinical setting. More diagnostic markers and drug targets need to be clarified. Therefore, we screened abnormal spindle-like microcephaly-associated protein () as our candidate gene, which is associated with the poor prognosis.