SITC 2022 recap: Single cell, spatial, and in situ tools for cancer immunotherapy research
At the 37th annual Society for Immunotherapy of Cancer (SITC) meeting, it was apparent just how much single cell and spatial tools have advanced our understanding and application of cancer immunotherapies. Not only are these technologies enabling a deeper characterization of the tumor and its microenvironment to better understand disease etiology, they’re also being applied to translational and clinical research to unravel the complexities of treatment response, toxicities, and resistance.
We were thrilled to be able to share the latest innovations in our Chromium Single Cell, Visium Spatial, and Xenium In Situ platforms. If you weren’t able to stop by our booth, attend our workshop, or check out our poster presentations, we’ve got you. In this blog post, we summarize each of our four posters led by 10x Genomics scientists, offering a glimpse of how our different platforms can be used to research cancer immunotherapies.
High performance in situ made fast and easy
A highlight among our presentations was an application of our latest spatial profiling instrument, the Xenium Analyzer. In a poster titled, “Characterization of human breast cancer tissue with the Xenium In Situ platform reveals a novel marker for invasiveness,” 10x Genomics scientists used Xenium to investigate the myoepithelial layer of human ductal carcinoma in situ (DCIS) breast cancer tissue. Since DCIS is a non-invasive form of breast cancer, identifying its presence before the pre-cancerous cells become invasive is key to preventing some 20% of invasive breast cancer cases.
They used single cell gene expression and spatial analysis combined with the Xenium platform to map DCIS FFPE tumor tissue at the single cell level, identifying 17 different cell types. Investigating three molecularly distinct tumor subtypes (low-grade and high-grade DCIS, and invasive carcinoma), Xenium allowed them to describe the cellular composition and differentially expressed genes within these subtypes. For example, in DCIS non-invasive tumor areas, they saw high keratin 14 (KRT14) expression and intact myoepithelial tissue. But in invasive tumor areas, they observed low KRT14 expression and a disrupted myoepithelial layer.
The same areas of low KRT14 expression were also positive for progesterone receptor (PGR). PGR, which has previously been identified to play a role in driving luminal B-cell proliferation and invasion (1), may represent a novel biomarker for the transition from non-invasive DCIS to invasive breast cancer. This study demonstrates the power of our high-throughput in situ technology by showing how sensitive and specific the platform can be. By integrating multiomic data from three platforms, our scientists were able to not only identify 17 different cell types, but they were also able to localize whole genome expression changes to specific cells as well as identify a new biomarker for the transition from early to invasive stage breast cancer.
Our gold standard, transformed: Fixed RNA profiling for single cell whole transcriptome analysis
In another poster titled, “Single cell FFPE and spatial transcriptomic profiling of an invasive ductal carcinoma enhances cellular and spatial insights,” our scientists looked at human breast cancer in the form of invasive ductal carcinoma (IDC), the most common type of invasive breast cancer. By combining Chromium Fixed RNA Profiling (now, Chromium Single Cell Gene Expression Flex) and Visium Spatial Gene Expression for FFPE, they could more accurately estimate cell-type proportions for each Visium spot.
They performed clustering analysis of the single cell FFPE data and identified 17 distinct cell populations, including one cluster with a strong correlation with a basal-like cancer subtype. Comparing single cell and spatial data, they observed distinct regions for mature and progenitor luminal cells. The mature luminal cells mapped to the pathology-mapped region of invasive carcinoma while T and B cells colocalized outside of the carcinogenic region, which may have implications for prognosis. Their study points out that single cell gene expression and spatial profiling on FFPE tissue adds a new layer of information to clinical studies and provides opportunities for the analysis of large biobanked cohorts and longitudinal samples of clinical relevance.
Maximize spatial insights with Visium CytAssist
In a poster titled, “Spatial whole transcriptome profiling of the tumor microenvironment in archived and freshly-mounted FFPE tissues,” 10x Genomics scientists used the Visium CytAssist instrument and Visium Spatial Gene Expression for FFPE to study cellular behavior in and around tumors of various types, yielding new insights into tumor heterogeneity and its microenvironment. Combining CytAssist with Visium for FFPE, they measured gene expression within the tumor microenvironment of archived human lung and ovarian cancer FFPE samples. In the lung cancer sample, well-known tumor markers TP63 and KRT5 confirmed the general phenotype of non-small cell carcinoma. In addition, other keratin and mucin genes revealed intra-tumor heterogeneity. In the same lung cancer sample, they found immune cell subsets, such as activated T, B, and regulatory dendritic cells. Freshly prepared breast and liver cancer samples were screened with fluorescently labeled antibodies in addition to transcriptomic profiling. In particular, proliferating cell nuclear antigen (PCNA) and Vimentin showed the precision and accuracy of transcriptomic probe transfer using Visium for FFPE.
The data highlighted that CytAssist can retrieve transcriptome information from archived and freshly prepared FFPE sections in a spatial context. Visium CytAssist provides a more comprehensive understanding of clinical tissue samples and offers novel insights into architectural and cellular heterogeneity across multiple diseases.
To advance your own immunotherapy studies, get started with Xenium, CytAssist, and Flex today.
References:
- McFall T, et al. Role of the short isoform of the progesterone receptor in breast cancer cell invasiveness at estrogen and progesterone levels in the pre- and post-menopausal ranges. Oncotarget 6: 33146–64 (2015). doi: 10.18632/oncotarget.5082