EGFR feedback-inhibition by Ran-binding protein 6 is disrupted in cancer

Transport of macromolecules through the nuclear pore by importins and exportins plays a critical role in the spatial regulation of protein activity. How cancer cells co-opt this process to promote tumorigenesis remains unclear. The epidermal growth factor receptor (EGFR) plays a critical role in normal development and in human cancer. Here we describe a mechanism of EGFR regulation through the importin β family member RAN-binding protein 6 (RanBP6), a protein of hitherto unknown functions. We show that RanBP6 silencing impairs nuclear translocation of signal transducer and activator of transcription 3 (STAT3), reduces STAT3 binding to the EGFR promoter, results in transcriptional derepression of EGFR, and increased EGFR pathway output. Focal deletions of the RanBP6 locus on chromosome 9p were found in a subset of glioblastoma (GBM) and silencing of RanBP6 promoted glioma growth in vivo. Our results provide an example of EGFR deregulation in cancer through silencing of components of the nuclear import pathway.This research was supported by the National Brain Tumor Society (I.K.M.), the National Institutes of Health grants 1R01NS080944-01 (I.K.M.), 1 R35 NS105109 01 (I.K.M.), and P30CA008748 (MSKCC Core Grant), the Geoffrey Beene Cancer Research Foundation (I.K.M.), the Cycle of Survival (I.K.M.), and the Seve Ballesteros Foundation (M.S.). B.O. was supported by an American–Italian Cancer Foundation fellowship and a MSKCC Brain Tumor Center grant. W.-Y.H. is the recipient of a FY15 Horizon Award from the U.S. Department of Defense (W81XWH-15-PRCRP-HA). A.C.-G. is the recipient of the Severo-Ochoa PhD fellowship. Further support was provided by the Sontag Foundation (B.S.T.). We thank all members of the Mellinghoff laboratory for helpful suggestions. We thank Dr. Fiona Ginty (Diagnostic Imaging and Biomedical Technologies, GE Global Research Center, Niskayuna, New York, USA) for assistance with multiplexed immunofluorescence. We thank A.J. Schuhmacher and C.S. Clemente-Troncone for assistance with the in vivo experiments, M. Kaufmann for assistance in the luciferase assays and N. Yannuzzi for assistance in cloning.S

Epstein-Barr virus shapes the tumor-immune architecture in classical Hodgkin lymphoma

NanoString IO360 panel, raw and normalized data

Multiplexed spatial profiling of Hodgkin Reed-Sternberg cell neighborhoods in Classic Hodgkin lymphoma unveils distinct immune escape mechanisms

<p>***Please refer to Version v3***</p> <p> </p> <p>Raw TIFF images and corresponding single-cell data from multiplexed imaging (Leica Cell DIVE) of 29 proteins in 587 fields of view across 30 classic Hodgkin lymphoma patients.</p> <p>Bulk RNA sequencing (NanoString IO360 panel) raw and normalized data for 32 classic Hodgkin lymphoma patients.</p> <p>Meta data containing information about patients, cell type and state information, and statistical comparisons.</p><p>Individual file descriptions</p> <ul> <li>RawData.csv <ul> <li>Raw NanoString data (32 patients)</li> </ul> </li> <li>NormaizedData.csv <ul> <li>Normalized NanoString data (32 patients)</li> </ul> </li> <li>Files beginning with HL_* <ul> <li>Normallized single-cell mpIF data (30 patients, 1 per file)</li> </ul> </li> <li>HodgkinLymphoma_Samples.xlsx <ul> <li>Meta data containing patient-level information</li> </ul> </li> <li>HodgkinLymphoma_FOVs.xlsx <ul> <li>Meta data containing field of view-level information</li> </ul> </li> <li>HodgkinLymphoma_Markers.xlsx <ul> <li>Meta data containing information on markers in cell dive panel</li> </ul> </li> <li>HodgkinLymphoma_CellTypes.xlsx <ul> <li>Meta data containing cell type definitions</li> </ul> </li> <li>HodgkinLymphoma_CellStates.xlsx <ul> <li>Meta data containing cell state information</li> </ul> </li> <li>HodgkinLymphoma_Questions.xlsx <ul> <li>Meta data containing list of statistical comparisons</li> </ul> </li> </ul> <p>*Note: all meta data is formatted for use with the pipeline</p&gt

Supplementary Tables S1-S2 from Moving Spatially Resolved Multiplexed Protein Profiling toward Clinical Oncology

Supplementary Table S1: Overview of multiplexed antibody-based imaging technologies.Supplementary Table S2: Application of multiplexed antibody-based imaging in cancer research.</p

Supplementary Tables S1-S2 from Moving Spatially Resolved Multiplexed Protein Profiling toward Clinical Oncology

Supplementary Table S1: Overview of multiplexed antibody-based imaging technologies.Supplementary Table S2: Application of multiplexed antibody-based imaging in cancer research.</p

Abstract 2125: Towards a spatial view of immune cell function in cancer

Abstract Immunotherapy can result in lasting tumor regressions, but despite its success, only a subset of patients and cancer types benefit from immunotherapy. Thus, uncovering features of the tumor microenvironment (TME) that contribute to this differential response can inform candidates for novel therapies and biomarkers for patient stratification. Recent advances in single-cell technologies allow for profiling of cell states and their spatial interactions within a tumor. Here, we performed multiplexed immunofluorescence (mpIF), a method for in situ single-cell measurement of 30+ proteins, as well as bulk transcriptomics and genomics on 180 tumor samples across 4 immunotherapy-responsive and -resistant solid and liquid cancers: in-transit melanoma (ITM), non-small cell lung cancer (NSCLC), glioblastoma multiforme (GBM), and classical Hodgkin lymphoma (cHL). In aggregate, we measured over 100 million single cells and identified over 1,000 unique tumor and immune cell states. We uncovered immune-suppressive cell states, such as macrophages negative for PD-L1 and B7-H3 in immunotherapy-resistant ITM tumors and all GBM tumors, which generally fail to respond to immunotherapy. In GBM, macrophages exhibited two distinct spatial topologies, infiltrated or excluded. In ITM, we identified pre-treatment cell states and gene expression signatures that associate with immunotherapy response such as MHC class I expression on the tumor cell surface, B cell aggregates, “exhausted” PD-1/LAG-3/TIM-3 triple-positive CD8+ T cells, and expression of interferon-gamma genes. We observed a similar immune checkpoint-rich (PD-1/LAG-3/TIM-3 triple-positive) TME in all cHL tumors, which have remarkably high immunotherapy response rates. We spatially defined the microniche (30-micron radius neighborhood) of “exhausted” CD8+ T cells, and within the microniches, found antigen presentation competent tumor cells, proliferating T cells, and B7-H3 positive macrophages, which together contribute to an activated TME. Together, we present a statistical workflow for the integrated analysis of spatially resolved multidimensional data for cancer target discovery that is tailored towards application in routinely collected formalin-fixed paraffin-embedded cancer biospecimens. Citation Format: Maryam Pourmaleki, Caitlin J. Jones, Brian D. Greenstein, Sabrina D. Mellinghoff, Daniel A. Navarrete, Smrutiben A. Mehta, Nicholas D. Socci, Ingo K. Mellinghoff, Travis J. Hollmann. Towards a spatial view of immune cell function in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2125.</jats:p

Tumor MHC Class I Expression Associates with Intralesional IL2 Response in Melanoma

Abstract Cancer immunotherapy can result in lasting tumor regression, but predictive biomarkers of treatment response remain ill-defined. Here, we performed single-cell proteomics, transcriptomics, and genomics on matched untreated and IL2 injected metastases from patients with melanoma. Lesions that completely regressed following intralesional IL2 harbored increased fractions and densities of nonproliferating CD8+ T cells lacking expression of PD-1, LAG-3, and TIM-3 (PD-1−LAG-3−TIM-3−). Untreated lesions from patients who subsequently responded with complete eradication of all tumor cells in all injected lesions (individuals referred to herein as “extreme responders”) were characterized by proliferating CD8+ T cells with an exhausted phenotype (PD-1+LAG-3+TIM-3+), stromal B-cell aggregates, and expression of IFNγ and IL2 response genes. Loss of membranous MHC class I expression in tumor cells of untreated lesions was associated with resistance to IL2 therapy. We validated this finding in an independent cohort of metastatic melanoma patients treated with intralesional or systemic IL2. Our study suggests that intact tumor-cell antigen presentation is required for melanoma response to IL2 and describes a multidimensional and spatial approach to develop immuno-oncology biomarker hypotheses using routinely collected clinical biospecimens. </jats:sec

Genomic Correlates of Disease Progression and Treatment Response in Prospectively Characterized Gliomas

Abstract Purpose: The genomic landscape of gliomas has been characterized and now contributes to disease classification, yet the relationship between molecular profile and disease progression and treatment response remain poorly understood. Experimental Design: We integrated prospective clinical sequencing of 1,004 primary and recurrent tumors from 923 glioma patients with clinical and treatment phenotypes. Results: Thirteen percent of glioma patients harbored a pathogenic germline variant, including a subset associated with heritable genetic syndromes and variants mediating DNA repair dysfunctions (29% of the total) that were associated with somatic biallelic inactivation and mechanism-specific somatic phenotypes. In astrocytomas, genomic alterations in effectors of cell-cycle progression correlated with aggressive disease independent of IDH mutation status, arose preferentially in enhancing tumors (44% vs. 8%, P &amp;lt; 0.001), were associated with rapid disease progression following tumor recurrence (HR = 2.6, P = 0.02), and likely preceded the acquisition of alkylating therapy-associated somatic hypermutation. Thirty-two percent of patients harbored a potentially therapeutically actionable lesion, of whom 11% received targeted therapies. In BRAF-mutant gliomas, response to agents targeting the RAF/MEK/ERK signaling axis was influenced by the type of mutation, its clonality, and its cellular and genomic context. Conclusions: These data reveal genomic correlates of disease progression and treatment response in diverse types of glioma and highlight the potential utility of incorporating genomic information into the clinical decision-making for patients with glioma. </jats:sec

Supplementary Data from Tumor MHC Class I Expression Associates with Intralesional IL2 Response in Melanoma

Supplementary Data from Tumor MHC Class I Expression Associates with Intralesional IL2 Response in Melanom