Pan-cancer proteogenomics characterization of tumor immunity.

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

RT-PCR assay to detect FGFR3::TACC3 fusions in formalin-fixed, paraffin-embedded glioblastoma samples.

Background: One targeted treatment option for isocitrate dehydrogenase (IDH)-wild-type glioblastoma focuses on tumors with fibroblast growth factor receptor 3::transforming acidic coiled-coil-containing protein 3 (FGFR3::TACC3) fusions. FGFR3::TACC3 fusion detection can be challenging, as targeted RNA next-generation sequencing (NGS) is not routinely performed, and immunohistochemistry is an imperfect surrogate marker. Fusion status can be determined using reverse transcription polymerase chain reaction (RT-PCR) on fresh frozen (FF) material, but sometimes only formalin-fixed, paraffin-embedded (FFPE) tissue is available. Aim: To develop an RT-PCR assay to determine FGFR3::TACC3 status in FFPE glioblastoma samples. Methods: Twelve tissue microarrays with 353 historical glioblastoma samples were immunohistochemically stained for FGFR3. Samples with overexpression of FGFR3 (n = 13) were subjected to FGFR3::TACC3 RT-PCR on FFPE, using 5 primer sets for the detection of 5 common fusion variants. Fusion-negative samples were additionally analyzed with NGS (n = 6), FGFR3 Fluorescence In Situ Hybridization (n = 6), and RNA sequencing (n = 5). Results: Using RT-PCR on FFPE material of the 13 samples with FGFR3 overexpression, we detected an FGFR3::TACC3 fusion in 7 samples, covering 3 different fusion variants. For 5 of these FF was available, and the presence of the fusion was confirmed through RT-PCR on FF. With RNA sequencing, 1 additional sample was found to harbor an FGFR3::TACC3 fusion (variant not covered by current RT-PCR for FFPE). The frequency of FGFR3::TACC3 fusion in this cohort was 9/353 (2.5%). Conclusions: RT-PCR for FGFR3::TACC3 fusions can successfully be performed on FFPE material, with a specificity of 100% and (due to limited primer sets) a sensitivity of 83.3%. This assay allows for the identification of potential targeted treatment options when only formalin-fixed tissue is available.

TARGET: A phase I/II open-label multicenter study to assess safety and efficacy of fexagratinib in patients with relapsed/refractory FGFR fusion-positive glioma.

Background: Oncogenic FGFR-TACC fusions are present in 3-5% of high-grade gliomas (HGGs). Fexagratinib (AZD4547) is an oral FGFR1-3 inhibitor with preclinical activity in FGFR-TACC+ gliomas. We tested its safety and efficacy in patients with recurrent FGFR-TACC + HGGs. Patients and Methods: TARGET (NCT02824133) is a phase I/II open-label multicenter study that included adult patients with FGFR-TACC + HGGs relapsing after ≥1 line of standard chemoradiation. Patients received fexagratinib 80 mg bd on a continuous schedule until disease progression or unacceptable toxicity. The primary endpoint was the 6-month progression-free survival rate (PFS6). Results: Twelve patients with recurrent IDH wildtype FGFR-TACC + HGGs (all FGFR3-TACC3+) were included in the efficacy cohort (male/female ratio = 1.4, median age = 61.5 years). Most patients (67%) were included at the first relapse. The PFS6 was 25% (95% confidence interval 5-57%), with a median PFS of 1.4 months. All patients without progression at 6 months (n = 3) were treated at first recurrence (versus 56% of those in progression) and remained progression-free for 14-23 months. The best response was RANO partial response in 1 patient (8%), stable disease in 5 (42%), and progressive disease in 6 (50%). Median survival was 17.5 months from inclusion. Grade 3 toxicities included lymphopenia, hyperglycaemia, stomatitis, nail changes, and alanine aminotransferase increase (n = 1 each). No grade 4-5 toxicities were seen. A 32-gene signature was associated with the benefit of FGFR inhibition in FGFR3-TACC3 + HGGs. Conclusions: Fexagratinib exhibited acceptable toxicity but limited efficacy in recurrent FGFR3-TACC3 + HGGs. Patients treated at first recurrence appeared more likely to benefit, yet additional evidence is required.

Triggering receptor expressed on myeloid cells 2 (TREM2) regulates phagocytosis in glioblastoma.

BACKGROUND: Glioblastomas (GBMs) are central nervous system tumors that resist standard-of-care interventions and even immune checkpoint blockade. Myeloid cells in the tumor microenvironment can contribute to GBM progression; therefore, emerging immunotherapeutic approaches include reprogramming these cells to achieve desirable antitumor activity. Triggering receptor expressed on myeloid cells 2 (TREM2) is a myeloid signaling regulator that has been implicated in a variety of cancers and neurological diseases with contrasting functions, but its role in GBM immunopathology and progression is still under investigation. METHODS: Our reverse translational investigations leveraged single-cell RNA sequencing and cytometry of human gliomas to characterize TREM2 expression across myeloid subpopulations. Using 2 distinct murine glioma models, we examined the role of Trem2 on tumor progression and immune modulation of myeloid cells. Furthermore, we designed a method of tracking phagocytosis of glioma cells in vivo and employed in vitro assays to mechanistically understand the influence of TREM2 signaling on tumor uptake. RESULTS: We discovered that TREM2 expression does not correlate with immunosuppressive pathways, but rather showed strong a positive association with the canonical phagocytosis markers lysozyme (LYZ) and macrophage scavenger receptor (CD163) in gliomas. While Trem2 deficiency was found to be dispensable for gliomagenesis, Trem2+ myeloid cells display enhanced tumor uptake compared to Trem2- cells. Mechanistically, we demonstrate that TREM2 mediates phagocytosis via Syk signaling. CONCLUSIONS: These results indicate that TREM2 is not associated with immunosuppression in gliomas. Instead, TREM2 is an important regulator of phagocytosis that may be exploited as a potential therapeutic strategy for brain tumors.

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.

BACKGROUND AND OBJECTIVE: Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome. METHODS: We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. RESULTS: WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes. CONCLUSIONS: This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

Integrated proteogenomic characterization of glioblastoma evolution.

The evolutionary trajectory of glioblastoma (GBM) is a multifaceted biological process that extends beyond genetic alterations alone. Here, we perform an integrative proteogenomic analysis of 123 longitudinal glioblastoma pairs and identify a highly proliferative cellular state at diagnosis and replacement by activation of neuronal transition and synaptogenic pathways in recurrent tumors. Proteomic and phosphoproteomic analyses reveal that the molecular transition to neuronal state at recurrence is marked by post-translational activation of the wingless-related integration site (WNT)/ planar cell polarity (PCP) signaling pathway and BRAF protein kinase. Consistently, multi-omic analysis of patient-derived xenograft (PDX) models mirror similar patterns of evolutionary trajectory. Inhibition of B-raf proto-oncogene (BRAF) kinase impairs both neuronal transition and migration capability of recurrent tumor cells, phenotypic hallmarks of post-therapy progression. Combinatorial treatment of temozolomide (TMZ) with BRAF inhibitor, vemurafenib, significantly extends the survival of PDX models. This study provides comprehensive insights into the biological mechanisms of glioblastoma evolution and treatment resistance, highlighting promising therapeutic strategies for clinical intervention.

Immune landscape of isocitrate dehydrogenase-stratified primary and recurrent human gliomas.

BACKGROUND: Human gliomas are classified using isocitrate dehydrogenase (IDH) status as a prognosticator; however, the influence of genetic differences and treatment effects on ensuing immunity remains unclear. METHODS: In this study, we used sequential single-cell transcriptomics on 144,678 and spectral cytometry on over two million immune cells encompassing 48 human gliomas to decipher their immune landscape. RESULTS: We identified 22 distinct immune cell types that contribute to glioma immunity. Specifically, brain-resident microglia (MG) were reduced with a concomitant increase in CD8+ T lymphocytes during glioma recurrence independent of IDH status. In contrast, IDH-wild-type-associated patterns, such as an abundance of antigen-presenting cell-like MG and cytotoxic CD8+ T cells, were observed. Beyond elucidating the differences in IDH, relapse, and treatment-associated immunity, we discovered novel inflammatory MG subpopulations expressing granulysin, a cytotoxic peptide, which is otherwise expressed in lymphocytes only. Furthermore, we provide a robust genomic framework for defining macrophage polarization beyond M1/M2 paradigm and reference signatures of glioma-specific tumor immune microenvironment (termed Glio-TIME-36) for deconvoluting transcriptomic datasets. CONCLUSIONS: This study provides advanced optics of the human pan-glioma immune contexture as a valuable guide for translational and clinical applications.

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen.

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype. SIGNIFICANCE: Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.