4 research outputs found
sj-xls-2-cix-10.1177_11769351221136081 – Supplemental material for A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy
sj-xls-2-cix-10.1177_11769351221136081 for A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy by Emma Bigelow, Suchi Saria, Brian Piening, Brendan Curti, Alexa Dowdell, Roshanthi Weerasinghe, Carlo Bifulco, Walter Urba, Noam Finkelstein, Elana J Fertig, Alex Baras, Neeha Zaidi, Elizabeth Jaffee and Mark Yarchoan in Cancer Informatics</p
sj-docx-1-cix-10.1177_11769351221136081 – Supplemental material for A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy
Supplemental material, sj-docx-1-cix-10.1177_11769351221136081 for A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy by Emma Bigelow, Suchi Saria, Brian Piening, Brendan Curti, Alexa Dowdell, Roshanthi Weerasinghe, Carlo Bifulco, Walter Urba, Noam Finkelstein, Elana J Fertig, Alex Baras, Neeha Zaidi, Elizabeth Jaffee and Mark Yarchoan in Cancer Informatics</p
Rapid Characterization of Candidate Biomarkers for Pancreatic Cancer Using Cell Microarrays (CMAs)
Tissue microarrays have become a valuable tool for high-throughput
analysis using immunohistochemical labeling. However, the large majority
of biochemical studies are carried out in cell lines to further characterize
candidate biomarkers or therapeutic targets with subsequent studies
in animals or using primary tissues. Thus, cell line-based microarrays
could be a useful screening tool in some situations. Here, we constructed
a cell microarray (CMA) containing a panel of 40 pancreatic cancer
cell lines available from American Type Culture Collection in addition
to those locally available at Johns Hopkins. As proof of principle,
we performed immunocytochemical labeling of an epithelial cell adhesion
molecule (Ep-CAM), a molecule generally expressed in the epithelium,
on this pancreatic cancer CMA. In addition, selected molecules that
have been previously shown to be differentially expressed in pancreatic
cancer in the literature were validated. For example, we observed
strong labeling of CA19-9 antigen, a prognostic and predictive marker
for pancreatic cancer. We also carried out a bioinformatics analysis
of a literature curated catalog of pancreatic cancer biomarkers developed
previously by our group and identified two candidate biomarkers, HLA
class I and transmembrane protease, serine 4 (TMPRSS4), and examined
their expression in the cell lines represented on the pancreatic cancer
CMAs. Our results demonstrate the utility of CMAs as a useful resource
for rapid screening of molecules of interest and suggest that CMAs
can become a universal standard platform in cancer research
Rapid Characterization of Candidate Biomarkers for Pancreatic Cancer Using Cell Microarrays (CMAs)
Tissue microarrays have become a valuable tool for high-throughput
analysis using immunohistochemical labeling. However, the large majority
of biochemical studies are carried out in cell lines to further characterize
candidate biomarkers or therapeutic targets with subsequent studies
in animals or using primary tissues. Thus, cell line-based microarrays
could be a useful screening tool in some situations. Here, we constructed
a cell microarray (CMA) containing a panel of 40 pancreatic cancer
cell lines available from American Type Culture Collection in addition
to those locally available at Johns Hopkins. As proof of principle,
we performed immunocytochemical labeling of an epithelial cell adhesion
molecule (Ep-CAM), a molecule generally expressed in the epithelium,
on this pancreatic cancer CMA. In addition, selected molecules that
have been previously shown to be differentially expressed in pancreatic
cancer in the literature were validated. For example, we observed
strong labeling of CA19-9 antigen, a prognostic and predictive marker
for pancreatic cancer. We also carried out a bioinformatics analysis
of a literature curated catalog of pancreatic cancer biomarkers developed
previously by our group and identified two candidate biomarkers, HLA
class I and transmembrane protease, serine 4 (TMPRSS4), and examined
their expression in the cell lines represented on the pancreatic cancer
CMAs. Our results demonstrate the utility of CMAs as a useful resource
for rapid screening of molecules of interest and suggest that CMAs
can become a universal standard platform in cancer research