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Reeves, Jason

https://orcid.org/0000-0003-0685-9644

Mayo Clinic

Nanostring Technologies (United States)

Citations 2

Abstract PS03-03: The spatially resolved single-cell atlas of the tumor immune architecture revealed the central role of IFN-alpha and plasmacytoid dendritic cells in triple-negative breast cancer in the Mayo Clinic cohort and FinXX trial
Chumsri, Saranya , Ma, Yaohua , Church, S. , Reeves, Jason , Brauer, Heather Ann , Warren, Sarah , Perez, Edith , Leon‐Ferre, Roberto A. , Knutson, Keith L. , Thompson, E. Aubrey , Liu, Yi , Carter, Jodi M. , Gregory, Mark , Joensuu, Heikki , Hillman, David W. , Boughey, Judy C. , Ingle, James N. , Kalari, Krishna R. , Couch, Fergus J. , Goetz, Matthew P. , Knutson, Keith L.

Cancer Research | May 2, 2024 | Volume: 84 | Issue: 9_Supplement | Pages: PS03-03-PS03-03

10.1158/1538-7445.sabcs23-ps03-03 Get It

Abstract Background: Multiple studies have confirmed the central role of preexisting immune response measured by stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC). Emerging studies showed that not only the number of TILs but also the location of TILs is important. There are 3 distinct immune architectures described based on the amount and locations of TILs, namely immune enriched (IN), immune excluded (IE), and immune desert (ID). Here we evaluated outcomes and characteristics associated with each immune landscape. Methods: NanoString Digital Spatial Profiling (DSP) and CosMx, a spatial multi-omics single-cell imaging platform, were performed in 75 samples from the Mayo Clinic (MC) TNBC cohort (Leon-Ferre BCRT 2018). NanoString IO360 was performed in 114 samples from the FinXX trial ( NCT00114816) . Firstly, tumors with sTIL quantified by H&E ≤ 30% were classified as ID. The rest of the tumors with high sTIL > 30% were categorized according to the intratumoral CD8 protein expression by DSP, with IE having intratumoral CD8 in the lower median and IN having intratumoral CD8 in the upper median. Chi-square test, gene set enrichment, Cox regression, and Kaplan-Meier analysis were used. Differential expression listed as log 2-fold change (FC) was estimated from the linear mixed model with significance defined as two-sided p< 0.05. Results: ID is associated with low Ki67 < 5% (23.3% vs. 9.6% ID, p 0.02) as well as apocrine (11/13, 84.6%) and metaplastic histology (10/12, 83%). In both univariate and multivariate analysis, patients with IN had significantly improved recurrence-free survival (RFS) compared to those with ID (HR 0.37, 95%CI 0.18-0.74, p 0.005). Despite having high sTILs, IE had poor outcomes similar to ID (HR 0.84, 95%CI 0.36-1.98). Strikingly, we identified that IE patients had significantly lower plasmacytoid dendritic cells (pDCs) compared to IN (mean 0 vs. 0.26/100 tumor cells, 95%CI 0.08-0.43 , p 0.01). Using Gene Set Enrichment Analysis to evaluate differential hallmarks between IN and IE, we identified IF Nɑ and IFNγ (FDR < 0.001) responses as significantly enriched in IN group, consistent wi th the function of pDCs, which are a subset of dendritic cells specialized in secreting high levels of type I interferon. To validate this finding, we further evaluated the 11 leading edge gene IFNɑ signature in the FinXX trial. A high IFNɑ signature score was associated with significantly improved outcomes in the FinXX trial (HR 0.21, 95%CI 0.09-0.51 , p < 0.001). Similar findings were observed using Kaplan-Meier analysis in the FinXX trial with significantly improved RFS (p 0.0006) and overall survival (p 0.0001) in patients with high IFNɑ signature scores. Furthermore, we evaluated the differential gene expression unique to IN tumors in the Mayo cohort. Expressions of MHC class I and class II in tumor cells, including HLA-A, HLA-B, HLA-C, HLA-DRA, HLA-DRB1, HLA-DPA1, and HLA-E, were associated with IN and significantly improved outcomes (p < 0.05) compared to ID and IE. Conclusions: Highlighting the importance of spatial context, we identified that patients with IE tumors had poor outcomes despite having high TILs. Moreover, u sing an in-depth analysis with spatially defined context, we identified the central role of pDC and the significance of IF Nɑ in TNBC. Support: Breast Cancer Research Foundation, Mayo Clinic Breast Cancer SPORE (P50CA116201-17) W81XWH-15-1-0292, P50CA015083, R35CA253187 Citation Format: Saranya Chumsri, Yi Liu, Yaohua Ma, Jodi Carter, Mark Gregory, Sarah Church, Jason Reeves, Heather Ann Brauer, Sarah Warren, Heikki Joensuu, Edith Perez, Roberto Leon-Ferre, David Hillman, Judy Boughey, James Ingle, Krishna Kalari, Fergus Couch, Matthew Goetz, Keith Knutson, E. Thompson. The spatially resolved single-cell atlas of the tumor immune architecture revealed the central role of IFN-alpha and plasmacytoid dendritic cells in triple-negative breast cancer in the Mayo Clinic cohort and FinXX trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS03-03.
Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler
Bergholtz, Helga , Carter, Jodi M. , Cesano, Alessandra, Cheang, Maggie C.U. , Church, S. , Divakar, Prajan , Fuhrman, Christopher A. , Goel, Shom , Gong, Jingjing , Guerriero, Jennifer L. , Hoang, Margaret L. , Hwang, E. Shelley , Kuasne, Hellen, Lee, Jinho , Liang, Yan , Perez, Jessica, Prat, Aleix , Pusztai, Lajos , Reeves, Jason , Riazalhosseini, Yasser , Richer, Jennifer K. , Şahin, Özgür , Sato, Hiromi , Sørlie, Thérese , Swarbrick, Alexander , Thompson, E. Aubrey , Tolaney, Sara M. , Warren, Sarah H. , Cheang, Maggie Chon U , Church, Sarah E , Prat, Aleix , Pusztai, Lajos , Sahin, Özgür , Sørlie, Therese , Liang, Yan , Carter, Jodi , Mittendorf, EA , Schlam, Ilana Miriam , Stover, Daniel G. , Swain, Sandra M. , Warren, Sarah

Cancers | September 6, 2021 | Volume: 13 | Issue: 17 | Pages: 4456

10.3390/cancers13174456 Get It

Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.