Tissue transcriptomics with CyteFinder® II Instruments
Video Transcript
Hi, my name is Jennifer Chao, principal scientist at RareCyte. I will present an overview of RareCyte’s, tissue applications, and how our technology enables transcriptomics research for a wide variety of applications, including immune profiling and biomarker discovery.
Discovery applications using the RareCyte platform involve the CyteFinder instrument, which integrates whole-slide, multiple parameter imaging with needle based retrieval. This workflow termed PicSeq enables deep sample characterization at multiple levels from large scale tissue organization to individual cellular interactions and phenotypes to DNA and RNA profiling of small regions of interest. Because sample integrity is preserved and DNA and RNA can be profiled in an unbiased manner, PicSeq enables many applications including tumor microenvironment characterization and biomarker discovery.
Our multiplex tissue imaging and PicSeq workflow involves staining the tissue sample with fluorescently labeled antibodies, followed by imaging on the CyteFinder II instrument. Images are reviewed and regions of interest identified using our CyteHub software. These regions of interest can then be retrieved with the CytePicker Retrieval Module and further characterized by RNA sequencing using commercially available kits.
PicSeq can be performed on fresh-frozen, or FFPE tissue types. In this first example, T-cell infiltration in breast cancer was characterized in fresh-frozen tissue stained with T-cell and tumor markers. The T-cells of interest were chosen based on staining and distribution within the tumor and are circled in the left panel. Each of the regions were retrieved with a 40 micron diameter needle and the tissue after picking is shown in the inset. The narrow needle bore allows for very precise retrieval, each containing approximately 10 to 20 cells.
After retrieval RNA was extracted in sequenced from each of the picked regions. Cibersort is a computational method to quantify cell fractions from a mixed population and was used to deconvolve the RNA signatures. The results are shown on the right. As expected, the T-cell picks are largely made up of T-cell expression signatures, while the tumor picks are largely comprised of tumor signatures. The tumor infiltrating lymphocytes had a mixture signature of tumor and TIL that corresponded to the number of T cells identified during imaging. These results demonstrate the power of the PicSeq workflow to deeply characterize your tissue of interest from the spatial organization and the cellular phenotyping right down to molecular profiling.
CyteFinder II and PicSeq also enable immune cell profiling and biomarker discovery applications. The following experiment was performed on FFPE tonsil tissue. The section was first stained to identify the T-cell and B-cell zones with CD3 and CD20 respectively. Unlike frozen tissue, FFPE sections require extensive antigen retrieval for staining, which precludes efficient RNA extraction. Therefore, RNA sequencing from FFPE tissue requires the retrieval and staining to be done on adjacent sections. In this experiment, all picks for RNA sequencing were taken from section 2 guided by staining on section 1. Cibersort RNA sequencing deconvolution of the tonsil picks revealed expression signatures of multiple different immune cell types within each of the T-cell zone and B-cell zone picks as indicated in the graph on the right. This demonstrates that even with the extensive fixation in FFPE tissue sections, we can extract and sequence RNA from PicSeq retrieved regions to identify and characterize immune cell populations.
Principle component analysis of the RNA data from the retrieved regions revealed that the ROIs from the two follicles clustered differently from each other as well as from the T-cell zone. Gene expression analysis based on the frequency of mapped reads revealed that CD21 was one of the genes differentially expressed between the adjacent follicles.
To validate the RNA sequencing results, we performed immunofluorescent staining on a serial tonsil section with CD21, the gene identified to be differentially expressed in the two B cell follicles by RNA sequencing. As you can see, the differential staining of CD21 was confirmed by immunofluorescence. This example demonstrates the utility of PicSeq as a powerful method of RNA driven biomarker discovery in tissue.
To conclude, oncology and immuno-oncology studies require investigation at multiple levels, architectural, morphological and molecular. The CyteFinder II system and the PicSeq workflow enable comprehensive characterization at all of these levels to obtain the maximum information from each precious tissue section.