HD-SCA HIGH-DEFINITION SINGLE CELL ANALYSIS TO CHARACTERIZE CANCER

Click on the link below to start the application (please be patient as it may take 120 seconds or so to load the first time). The pane along the left-hand side displays the parameters that are used to filter the data. The large area in the middle displays images of cells that meet the criteria chosen from the left-hand panel. Clicking on a single image in the center pane will zoom in on that cell and display additional information for the chosen cell in the right-hand pane.

Click here for a presentation describing the HD-SCA method. Please contact us (kolatkar at usc dot edu) if you have trouble accessing any of the content.

Circulating Tumor Cell Kinetics and Morphology from the Liquid Biopsy Predict Disease Progression in Patients with Metastatic Colorectal Cancer Following Resection as reported in
Cancers, 2022
This study evaluated 161 peripheral blood samples that were collected around surgical resection from 47 metastatic colorectal cancer patients using the HDSCA workflow. In addition to standard CTC enumeration, cellular morphology, and kinetics between time-points of collection were considered in the survival analysis. The data highlights 1) time-point-conscious cell enumeration for determining patient positivity and cellular kinetics, and 2) CTC subtypes and their association with clinical metrics and patient survival
Click for Pivot

Single cell correlation analysis for liquid and solid biopsies in metastatic colorectal cancer as reported in
Oncotarget, 2019, Vol.10
Samples from 10 patients were included in the liquid and solid biopsy correlation analysis. For 3 of these patients, both primary and metastatic solid biopsies had been collected at the time of surgery. Cells were relocated and imaged at 40X magnification using identical optical setup and exposure times for liquid and solid biopsy cells. A total of 1,058 CRC cells were analyzed with an average
Click for Pivot

HD-SCA and Anatomical Pathology: Development of the assay as reported in
Marrinucci et al. Phys Biol 2012.
This dataset is large so please be patient while it loads.
Click for Pivot

HD-SCA and single-cell genomics:tracing therapy response in a prostate cancer patient reported in
Dago et al. PLoS ONE 2014.
Click for Pivot

HD-SCA data from a Breast cancer patient cohort as reported in
Shishido et al. J Mol Diagn 2020.
Click for Pivot

HD-SCA and single-cell genomics: tracing disease evolution in a breast cancer patient.
Click for Pivot

HD-SCA and single-cell genomics: limited heterogeneity in a melanoma patient as reported in
Ruiz et al. Phys Biol 2015.
Click for Pivot

HD-SCA data for a metastatic castrate-resistant prostate cancer cohort undergoing a cabazitaxel � carboplatin clinical trial (MD Anderson prostate cancer) as reported in
Malihi et al. Clin Cancer Res 2020.
Click for Pivot

CTC and DTC data from a cohort with low- to high-risk, localized prostate cancer (Johns Hopkins Hospital prostate cancer).
Click for Pivot

HD-SCA data from a phase III randomized placebo-controlled trial in post-menopausal patients with hormone-receptor positive stage IV breast cancer
(S1222 breast cancer).
Click for Pivot

Disease characterization from the liquid biopsy in patients with HER2 mutated, non-amplified metastatic breast cancer (HER2mut mBC) treated with neratinib as reported in
npj Breast Cancer, 2022
The data presented in this small cohort study demonstrates the feasibility of real-time molecular profiling of the cellular and acellular fractions of the liquid biopsy using the HDSCA methodology. Utilizing a comprehensive liquid biopsy (CTCs and cfDNA) for genomic characterization, we have identified pre-existing and acquired alterations relevant to the disease state and potential treatment response

Click for Pivot

High-Definition Single-Cell Assay (HD-SCA) analysis produces both image and numerical data. It can be difficult to filter through the diverse data types to find data fitting specific parameters. Towards that end, we have developed a graphical web-based approach to enable researchers to quickly obtain a subset of image and associated assay data based on the filters chosen. Pivot, a Microsoft application, is used to provide a graphical interface that enable non-computer savvy users to quickly find the data they want.