Project description:Recent progress in unbiased metagenomic next-generation sequencing (mNGS) allows simultaneous examination of microbial and host genetic material in a single test. Leveraging affordable bronchoalveolar lavage fluid (BALF) mNGS data, we employed machine learning to create a diagnostic approach distinguishing lung cancer from pulmonary infections, conditions prone to misdiagnosis in clinical settings. This prospective study analyzed BALF-mNGS data from lung cancer and pulmonary infection patients, delineating differences in DNA/RNA microbial composition, bacteriophage abundances, and host responses, including gene expression, transposable element levels, immune cell composition, and tumor fraction derived from copy number variation (CNV). Integrating these metrics into a host/microbe metagenomics-driven machine learning model (Model VI) demonstrated robustness, achieving an AUC of 0.87 (95% CI = 0.857-0.883), sensitivity = 73.8%, and specificity = 84.5% in the training cohort, and an AUC of 0.831 (95% CI = 0.819-0.843), sensitivity = 67.1%, and specificity = 94.4% in the validation cohort for distinguishing lung cancer from pulmonary infections. The application of a rule-in and rule-out strategy-based composite predictive model significantly enhances accuracy (ACC) in distinguishing between lung cancer and tuberculosis (ACC=0.913), fungal infection (ACC=0.955), and bacterial infection (ACC=0.836). These findings highlight the potential of cost-effective mNGS-based analysis as a valuable tool for early differentiation between lung cancer and pulmonary infections, offering significant benefits through a single comprehensive testing.
Project description:In order to examine the impact our probe filtering efforts might have on the analysis of real-world primary data, we analyzed clinical prostate cancer specimens. This included profiling of four prostate tumour tissue samples and four benign prostate tissues using the Illumina Infinium Human Methylation450 (HM450K bead array) BeadChip. These samples were used to explore the effects on analysis with and without a probe filtering.
Project description:Raw data for our manuscript in prep, titled: "Real time health monitoring through urine analysis: A preliminary observational study."
Project description:Raw data for our manuscript in prep, titled: "Real time health monitoring through urine analysis: A preliminary observational study."
Project description:In order to examine the impact our probe filtering efforts might have on the analysis of real-world primary data, we analyzed clinical prostate cancer specimens. This included profiling of four prostate tumour tissue samples and four benign prostate tissues using the Illumina Infinium Human Methylation450 (HM450K bead array) BeadChip. These samples were used to explore the effects on analysis with and without a probe filtering. Four tumour samples containing Gleason 6 cancer and four benign samples from other prostate glands containing Gleason 6 cancer were selected for study. Tissue samples were cryosectioned for histopathological assessment. Genomic DNA was extracted from the homogenized samples using the Allprep Micro Kit (Qiagen, CA, USA) following manufacturer’s instructions and bisulfite converted using the Zymo EZ DNA Methylation kit (Zymo Research Corporation, CA, USA). The resulting libraries were hybridized onto the Illumina HumanMethylation450 (HM450K bead array) BeadChip. Raw intensity data was generated using an iScan microarray reader (Illumina).
Project description:The study is a real-world observational clinical study. Patients diagnosed as colorectal cancer through histopathology were screened and enrolled. Before anti-tumor treatment, colonoscopy biopsy tissue specimens, surgical specimens, and malignant pleural effusion or ascites specimens, etc. are collected. The investigators will perform a drug sensitivity testing based on a novel drug susceptibility testing method to test the commonly used anti-tumor treatment regimens. Patients were given conventional anti-tumor treatment according to the medical judgment of the doctors. Finally, the investigator will evaluate the consistency of clinical efficacy in colorectal cancer treatment and drug susceptibility outcomes.
Project description:Real-World Effectiveness of Regorafenib in the Treatment of Patients with Metastatic Colorectal Cancer- A Retrospective, Observational Study
