Browsing by Author "Hummon, Amanda B."

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    ColoType: a forty gene signature for consensus molecular subtyping of colorectal cancer tumors using whole-genome assay or targeted RNA-sequencing
    (Nature Publishing group, 2020-07-21) Buechler, Steven A.; Stephens, Melissa T.; Hummon, Amanda B.; Ludwig, Katelyn; Cannon, Emily; Carter, Tonia C.; Resnick, Jeffrey; Gökmen-Polar, Yesim; Badve, Sunil S.; Pathology and Laboratory Medicine, School of Medicine
    Colorectal cancer (CRC) tumors can be partitioned into four biologically distinct consensus molecular subtypes (CMS1-4) using gene expression. Evidence is accumulating that tumors in different subtypes are likely to respond differently to treatments. However, to date, there is no clinical diagnostic test for CMS subtyping. In this study, we used novel methodology in a multi-cohort training domain (n = 1,214) to develop the ColoType scores and classifier to predict CMS1-4 based on expression of 40 genes. In three validation cohorts (n = 1,744, in total) representing three distinct gene-expression measurement technologies, ColoType predicted gold-standard CMS subtypes with accuracies 0.90, 0.91, 0.88, respectively. To accommodate for potential intratumoral heterogeneity and tumors of mixed subtypes, ColoType was designed to report continuous scores measuring the prevalence of each of CMS1–4 in a tumor, in addition to specifying the most prevalent subtype. For analysis of clinical specimens, ColoType was also implemented with targeted RNA-sequencing (Illumina AmpliSeq). In a series of formalin-fixed, paraffin-embedded CRC samples (n = 49), ColoType by targeted RNA-sequencing agreed with subtypes predicted by two independent methods with accuracies 0.92, 0.82, respectively. With further validation, ColoType by targeted RNA-sequencing, may enable clinical application of CMS subtyping with widely-available and cost-effective technology.
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    Deep top-down proteomics revealed significant proteoform-level differences between metastatic and nonmetastatic colorectal cancer cells
    (American Association for the Advancement of Science, 2022) McCool, Elijah N.; Xu, Tian; Chen, Wenrong; Beller, Nicole C.; Nolan, Scott M.; Hummon, Amanda B.; Liu, Xiaowen; Sun, Liangliang; BioHealth Informatics, School of Informatics and Computing
    Understanding cancer metastasis at the proteoform level is crucial for discovering previously unknown protein biomarkers for cancer diagnosis and drug development. We present the first top-down proteomics (TDP) study of a pair of isogenic human nonmetastatic and metastatic colorectal cancer (CRC) cell lines (SW480 and SW620). We identified 23,622 proteoforms of 2332 proteins from the two cell lines, representing nearly fivefold improvement in the number of proteoform identifications (IDs) compared to previous TDP datasets of human cancer cells. We revealed substantial differences between the SW480 and SW620 cell lines regarding proteoform and single amino acid variant (SAAV) profiles. Quantitative TDP unveiled differentially expressed proteoforms between the two cell lines, and the corresponding genes had diversified functions and were closely related to cancer. Our study represents a pivotal advance in TDP toward the characterization of human proteome in a proteoform-specific manner, which will transform basic and translational biomedical research.
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    Evaluation of the mirn23a Cluster through an iTRAQ-based Quantitative Proteomic Approach
    (ACS Publications, 2016-05-06) Ludwig, Katelyn R.; Dahl, Richard; Hummon, Amanda B.; Department of Microbiology and Immunology, School of Medicine
    MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression that are implicated in a number of disease states. MiRNAs can exist as individual entities, or may be clustered and transcribed as a single polycistron. The mirn23a cluster consists of three miRNAs, miR-23a, miR-24-2, and miR-27a. While these miRNAs are transcribed together, they often exist at varying levels in the cell. Despite the fact that the mirn23a cluster is known to play a role in a number of diseases and developmental processes, few direct targets have been identified. In this study, we examined the effects of miR-23a, miR-24-2, miR-27a, or the mirn23a cluster overexpression on the proteome of 70Z/3 pre-B lymphoblast cells. Quantitative mass spectrometry using isobaric tags for relative and absolute quantification (iTRAQ) allowed for global profiling of cell lines after miRNA overexpression. We identified a number of targets of each miRNA that contained predicted miRNA seed sequences and are likely direct targets. In addition, we discovered a cohort of shared miRNA targets and cluster targets, demonstrating the importance of studying miRNA clusters in their entirety.