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Tsao, M. S.

Publications and source records attributed to Tsao, M. S..

2 recordsLinked to original sources

Cell-free Tumor Methylome Analysis of Small Cell Lung Cancer Patients Identifies Subgroups with Prognostic Associations

IntroductionSmall cell lung cancer (SCLC) is a highly aggressive type of cancer with a high risk of recurrence. The SCLC methylome may yield biologic insight but is understudied due to difficulty in acquiring primary patient tissue. Here, we comprehensively profile the SCLC methylome using cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq). MethodscfDNA was extracted from plasma samples collected from 74 SCLC patients prior to initiation of first-line treatment and from 20 non-cancer smoker participants. Genomic DNA (gDNA) was also extracted from paired peripheral blood leukocytes from the 74 SCLC patients and 7 accompanying circulating-tumour-cell patient-derived xenografts (CDX). cfDNA and gDNA were used as input for cfMeDIP-seq. We developed PeRIpheral blood leukocyte MEthylation (PRIME) subtraction as an algorithm to improve tumour specificity of cell-free methylome. ResultsSCLC total plasma cfDNA methylation profiles obtained using cfMeDIP-seq are representative of CDX tumour methylation. SCLC cfDNA methylation is distinct from non-cancer plasma. Using PRIME and k-means consensus clustering, we identified two SCLC methylome clusters with prognostic associations. These clusters had methylated biological pathways related to axon guidance, neuroactive ligand-receptor interaction, pluripotency of stem cells, and were differentially methylated at long noncoding RNA, LINEs, SINEs, retrotransposons, and other repeats features. ConclusionsWe have comprehensively profiled the SCLC methylome using cfMeDIP-seq in a large patient cohort and identified methylome clusters with prognostic associations. Our work demonstrates the potential of liquid biopsies in examining SCLC biology encoded in the methylome.

cancer biology↗

Evosep One Enables Robust Quantitative Deep Proteome Coverage using Tandem Mass Tags while Significantly Reducing Instrument Time

The balance between comprehensively analyzing the proteome and using valuable mass spectrometry time is a genuine challenge in the field of proteomics. Multidimensional fractionation strategies have significantly increased proteome coverage, but often at the cost of increased mass analysis time, despite advances in mass spectrometer acquisition rates. Recently, the Evosep One liquid chromatography system was shown to analyze peptide samples in a high throughput manner without sacrificing in depth proteomics coverage. We demonstrate incorporation of Evosep One technology into our multiplexing workflow for quantitative analysis of tandem mass tag (TMT)-labeled non-small cell lung carcinoma (NSCLC) patient-derived xenografts (PDXs). Using a 30 samples per day Evosep workflow, >12,000 proteins were identified in 48 hours of mass spectrometry time, which is comparable to the number of proteins identified by our conventional concatenated EASY-nLC workflow in 67.5 hours. Shorter Evosep gradient lengths reduced the number of protein identifications by 10%, while decreasing mass analysis time by 50%. Thus, our Evosep workflow enables quantitative analysis of multiplexed samples in less time without conceding depth of proteome coverage.

systems biology↗