Showing papers by "Sanford A. Stass published in 2023"
TL;DR: In this article , the authors found that pneumococcus pneumoniae (SP) attaches to lung cancer cells via binding pneumococcal surface protein C (PspC) to platelet activating factor receptor (PAFR), which stimulates cell proliferation and activates PI3K/AKT and nuclear factor kB (NF-kB) signaling pathways.
2 citations
TL;DR: In this paper , the MiSeqDx system was used to profile cell-free circulating miRNAs in plasma and diagnose non-small cell lung cancer (NSCLC).
Abstract: Non-small cell lung cancer (NSCLC) is a major contributor to cancer-related deaths, but early detection can reduce mortality. NSCLC comprises mainly adenocarcinoma (AC) and squamous cell carcinoma (SCC). Circulating microRNAs (miRNAs) in plasma have emerged as promising biomarkers for NSCLC. However, existing techniques for analyzing miRNAs have limitations, such as restricted target detection and time-consuming procedures. The MiSeqDx System has been shown to overcome these limitations, making it a promising tool for routine clinical settings. We investigated whether the MiSeqDx could profile cell-free circulating miRNAs in plasma and diagnose NSCLC. We sequenced RNA from the plasma of patients with AC and SCC and from cancer-free smokers using the MiSeqDx to profile and compare miRNA expressions. The MiSeqDx exhibits high speed and accuracy when globally analyzing plasma miRNAs. The entire workflow, encompassing RNA to data analysis, was completed in under three days. We also identified panels of plasma miRNA biomarkers that can diagnose NSCLC with 67% sensitivity and 68% specificity, and detect SCC with 90% sensitivity and 94% specificity, respectively. This study is the first to demonstrate that rapid profiling of plasma miRNAs using the MiSeqDx has the potential to offer a straightforward and effective method for the early detection and classification of NSCLC.
TL;DR: In this paper , the potential of integrating diverse molecular biomarkers across both plasma and sputum to improve the accuracy of diagnosis, given the heterogeneous nature of lung cancer arising from multifactorial molecular aberrations.
Abstract: Purpose The early detection is crucial for improved outcomes in lung cancer, which remains a leading cause of cancer-erelated deaths. There is an urgent need for precise molecular biomarkers to diagnose early-stage lung cancer. To address this, we assessed the potential of integrating diverse molecular biomarkers across both plasma and sputum to improve the accuracy of diagnosis, given the heterogeneous nature of lung cancer arising from multifactorial molecular aberrations. Methods We utilized droplet digital PCR to quantify miRNAs in plasma and bacterial DNA in sputum collected from 114 lung cancer patients and 121 cancer-free smokers. The participants were randomly divided into a development cohort and a validation cohort. Logistic regression models with constrained parameters were employed to optimize a signature with the highest sensitivity and specificity for early detection of lung cancer. Results The individual plasma miRNAs and sputum bacterial biomarkers had sensitivities of 62%-71% and specificities of 61%-79% for diagnosing lung cancer. A panel of plasma miRNA or sputum bacterial biomarkers produced sensitivities of 79%-85% and specificities of 74%-82%. An integrated signature comprising two miRNAs in plasma and three bacterial biomarkers in sputum was developed in the development cohort, and it exhibited a higher sensitivity (87%) and specificity (89%) in comparison to individual biomarkers. The signature's diagnostic value was confirmed in the validation cohort, regardless of tumor stage, histological type, and demo-graphic factors. Conclusion The integration of miRNA and bacterial biomarkers across both plasma and sputum samples offered an effective approach for the diagnosis of lung cancer.