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Warren, Sarah H.

https://orcid.org/0000-0002-5046-2890

Mayo Clinic

Kite (United States)

Citations 2

Advances in the understanding and therapeutic manipulation of cancer immune responsiveness: a Society for Immunotherapy of Cancer (SITC) review
Cesano, Alessandra, Augustin, Ryan C. , Barrea, Luigi , Carturan, Alberto , Ho, Winson S. , Kather, Jakob Nikolas , Lu, Rongze O., McQuade, Jennifer L. , Najjar, Yana G. , Shen, Rhine R. , Warner, Allison Betof , Warren, Sarah H. , Ziv, Elad , Marincola, Francesco M, Augustin, Ryan, Carturan, Alberto , Najjar, Yana G , Ruella, Marco , Betof Warner, Allison , Warren, Sarah , Ziv, Elad , Bedognetti, Davide , Bruno, Tullia Carmela , Hammer, Christian , Kather, Jakob Nikolas , Kirchhoff, Tomas , Pietrobon, Violena , Ruella, Marco , Soldati, Laura , Spencer, Christine N. , Marincola, Francesco M.

Journal for ImmunoTherapy of Cancer | January 17, 2025 | Volume: 13 | Issue: 1 | Pages: e008876

10.1136/jitc-2024-008876 Get It

Cancer immunotherapy—including immune checkpoint inhibition (ICI) and adoptive cell therapy (ACT)—has become a standard, potentially curative treatment for a subset of advanced solid and liquid tumors. However, most patients with cancer do not benefit from the rapidly evolving improvements in the understanding of principal mechanisms determining cancer immune responsiveness (CIR); including patient-specific genetically determined and acquired factors, as well as intrinsic cancer cell biology. Though CIR is multifactorial, fundamental concepts are emerging that should be considered for the design of novel therapeutic strategies and related clinical studies. Recent advancements as well as novel approaches to address the limitations of current treatments are discussed here, with a specific focus on ICI and ACT.
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.