Spatial assessment of stromal B cell aggregates predicts response to checkpoint inhibitors in unresectable melanoma
Smithy, J. W.; Peng, X.; Ehrich, F. D.; Moy, A. P.; Yosofvand, M.; Maher, C.; Aleynick, N.; Vanguri, R.; Zhuang, M.; Lee, J.; Bleile, M.; Li, Y.; Postow, M. A.; Panageas, K. S.; Hollmann, T.; Callahan, M. K.; Shen, R.
Show abstract
Quantitative assessment of multiplex immunofluorescence (mIF) data represents a powerful tool for immunotherapy biomarker discovery in melanoma and other solid tumors. In addition to providing detailed phenotypic information of immune cells of the tumor microenvironment, these datasets contain spatial information that can reveal biologically relevant interactions among cell types. To assess quantitative mIF analysis as a platform for biomarker discovery, we used a 12-plex mIF panel to characterize tumor samples collected from 50 patients with melanoma prior to treatment with immune checkpoint inhibitors (ICI). Consistent with prior studies, we identified a strong association between stromal B cell percentage and response to ICI therapy. We then compared pathologist assessment of lymphoid aggregates with a density based clustering algorithm, DBSCAN, to both automatically detect B cell aggregates and quantify their size, morphology, and distance to tumor. Spatial neighborhood analysis identified TCF1+ and LAG3-T cell subpopulations enriched near stromal B cells. These analyses provide a roadmap for the further development and validation of spatial immunotherapy biomarkers in melanoma and other diseases.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer 95%
- Myeloid cell-associated resistance to PD-1/PD-L1 blockade in urothelial cancer revealed through bulk and single-cell RNA sequencing 94%
- Circulating tumor DNA analysis in advanced urothelial carcinoma: insights from biological analysis and extended clinical follow-up 93%
Similar papers in this journal
- Identification of tumor-intrinsic drivers of immune exclusion in acral melanoma 97%
- Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+ T cells in the tumor microenvironment and predicts clinical outcome in early- and late-phase clinical trials 96%
- KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response 95%
Similar papers in this journal
- Tertiary lymphoid structure-related immune infiltrates in NSCLC tumor lesions correlate with low tumor-reactivity of TIL products 95%
- Patient-derived tumor explant models of tumor immune microenvironment reveal distinct and reproducible immunotherapy responses 94%
- Increased Tryptophan, But Not Increased Glucose Metabolism, Predict Resistance of Pembrolizumab in Stage III/IV Melanoma 94%
Similar papers in this journal
- An Omic and Multidimensional Spatial Atlas from Serial Biopsies of an Evolving Metastatic Breast Cancer 96%
- Conserved angio-immune subtypes of the cancer microenvironment predict response to immune checkpoint blockade therapy 95%
- Bexmarilimab-induced macrophage activation leads to treatment benefit in solid tumors: the phase I/II first-in-human MATINS trial 95%
Similar papers in this journal
- Small gene networks can delineate immune cell states and characterize immunotherapy response in melanoma 95%
- Microenvironmental correlates of immune checkpoint inhibitor response in human melanoma brain metastases revealed by T cell receptor and single-cell RNA sequencing 95%
- Tertiary lymphoid structures are associated with enhanced macrophage activation, immune checkpoint expression and predict outcome in cervical cancer. 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.