Spatially informed gene signatures for response to immunotherapy in melanoma.

PURPOSE: We aim to improve the prediction of response or resistance to immunotherapies in melanoma patients. This goal is based on the hypothesis that current gene signatures predicting immunotherapy outcomes show only modest accuracy due to the lack of spatial information about cellular functions and molecular processes within tumors and their microenvironment. EXPERIMENTAL DESIGN: We collected gene expression data spatially from three cellular compartments defined by CD68+macrophages, CD45+leukocytes and S100B+tumor cells in 55-immunotherapy-treated melanoma specimens using Digital Spatial Profiling-Whole Transcriptome Atlas (DSP-WTA). We developed a computational pipeline to discover compartment-specific gene signatures and determine if adding spatial information can improve patient stratification. RESULTS: We achieved robust performance of compartment-specific signatures in predicting the outcome to ICI in the discovery cohort. Of the three signatures, S100B signature showed the best performance in the validation cohort (N=45). We also compared our compartment-specific signatures with published bulk signatures and found the S100B tumor spatial signature outperformed previous signatures. Within the 8-gene S100B signature, 5 genes (PSMB8, TAX1BP3, NOTCH3, LCP2, NQO1) with positive coefficients predict the response and 3 genes (KMT2C, OVCA2, MGRN1) with negative coefficients predict the resistance to treatment. CONCLUSION: We conclude that the spatially defined compartment signatures utilize tumor and TME-specific information, leading to more accurate prediction of treatment outcome, and thus merit prospective clinical assessment.

High-Plex Assessment of Biomarkers in Tumors.

The assessment of biomarkers plays a critical role in the diagnosis and treatment of many cancers. Biomarkers not only provide diagnostic, prognostic, or predictive information but also can act as effective targets for new pharmaceutical therapies. As the utility of biomarkers increases, it becomes more important to utilize accurate and efficient methods for biomarker discovery and, ultimately, clinical assessment. High-plex imaging studies, defined here as assessment of 8 or more biomarkers on a single slide, have become the method of choice for biomarker discovery and assessment of biomarker spatial context. In this review, we discuss methods of measuring biomarkers in slide-mounted tissue samples, detail the various high-plex methods that allow for the simultaneous assessment of multiple biomarkers in situ, and describe the impact of high-plex biomarker assessment on the future of anatomic pathology.

Quantitative, Spatially Defined Expression of Leukocyte-associated Immunoglobulin-like Receptor in Non-small Cell Lung Cancer.

Targeting the interaction of leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) and its ligands has been shown to reinstate antitumor immunity. In addition, the introduction of the LAIR-1 decoy protein, LAIR-2, sensitizes previously resistant lung tumors to programmed death-1 (PD-1) blockade, indicating the potential of LAIR-1 as an alternative marker for anti-PD-1 resistance in lung cancer. Here, we assessed LAIR-1 as compared with programmed death-ligand 1 (PD-L1) expression in various tumors, with a focus on non-small cell lung cancer (NSCLC) and its histologic subtypes using multiplexed quantitative immunofluorescence (mQIF) in 287 (discovery cohort) and 144 (validation cohort) patients with NSCLC. In addition, using multispectral imaging technology on mQIF images, we evaluated the localization of LAIR-1 on various cell types. We observed that CD14+, CD68+, and CD163+ monocytes and CK+ tumor cells predominantly expressed LAIR-1 more than other cell types. Furthermore, LAIR-1 expression in the tumor compartment was significantly higher in patients with lung adenocarcinoma (LUAD) than those with lung squamous cell carcinoma subtype (**, P = 0.003). Our results indicated that high tumor LAIR-1 expression in patients with LUAD is negatively associated with OS (overall survival, HR = 2.4; *, P = 0.02) highlighting its prognostic value in LUAD but not in other subtypes. The Pearson correlation between LAIR-1 and PD-L1 is 0.31; however, mutual exclusive staining pattern (i.e., several cases were positive for LAIR-1 and negative for PD-L1) was observed. Altogether, our data suggest that the combination therapy of anti-PD-1/PD-L1 with anti-LAIR-1 or the anti-LAIR-1 monotherapy alone may be promising cancer immunotherapeutic strategies. Significance: The spatial, quantitative assessment of LAIR-1 in NSCLC shows positive association of OS with high LAIR-1+/CD68+ cell densities and negative association of OS with high LAIR-1 expression in LUAD tumor subtype.

Spatially Resolved and Quantitative Analysis of the Immunological Landscape in Human Meningiomas.

The immunological status of human meningiomas is not well understood, hindering the development of rational immunotherapeutic strategies. We measured the levels of PD-L1, PD-L2, and immune cell subsets using multiplex quantitative immunofluorescence in a tissue microarray composed of 73 human meningiomas (56 WHO Grade 1, 13 WHO Grade 2, and 4 WHO Grade 3). We analyzed tumor-infiltrating immune cell populations, T-cell activation/dysfunction, and macrophage phenotypes. PD-L1 and PD-L2 were detected in 5.8% and 68.7% of cases, respectively. There was a higher PD-L1 expression in CD68+ macrophages compared with tumor cells (p < 0.001). There was a weak positive correlation between PD-L1 expression and CD3+ T-cell infiltration. The level of CD3+ cells and T-cell activation/proliferation in human meningiomas were highly variable with an increased CD4-to-CD8 ratio in higher grade tumors (p < 0.05). There was a stronger correlation between GZMB/Ki67 with PD-L2 than PD-L1. We found that 15.23%, 6.66%, and 5.49% of macrophages were CD163+, CD68+, and CD163+CD68+, respectively. In cases where there is high CD3+ T-cell infiltration, 23.5% and 76.5% had dormant and activated T-cell phenotypes, respectively. We conclude that human meningiomas are either PD-L1low TILlow or PD-L1low TILhigh tumors and harbor variable TIL infiltration and phenotypes.