The transformative potential of mRNA vaccines for glioblastoma and human cancer: technological advances and translation to clinical trials.

Originally devised for cancer control, mRNA vaccines have risen to the forefront of medicine as effective instruments for control of infectious disease, notably their pivotal role in combating the COVID-19 pandemic. This review focuses on fundamental aspects of the development of mRNA vaccines, e.g., tumor antigens, vector design, and precise delivery methodologies, - highlighting key technological advances. The recent, promising success of personalized mRNA vaccines against pancreatic cancer and melanoma illustrates the potential value for other intractable, immunologically resistant, solid tumors, such as glioblastoma, as well as the potential for synergies with a combinatorial, immunotherapeutic approach. The impact and progress in human cancer, including pancreatic cancer, head and neck cancer, bladder cancer are reviewed, as are lessons learned from first-in-human CAR-T cell, DNA and dendritic cell vaccines targeting glioblastoma. Going forward, a roadmap is provided for the transformative potential of mRNA vaccines to advance cancer immunotherapy, with a particular focus on the opportunities and challenges of glioblastoma. The current landscape of glioblastoma immunotherapy and gene therapy is reviewed with an eye to combinatorial approaches harnessing RNA science. Preliminary preclinical and clinical data supports the concept that mRNA vaccines could be a viable, novel approach to prolong survival in patients with glioblastoma.

Single Cell Droplet-Based Efficacy and Transcriptomic Analysis of a Novel Anti-KLRG1 Antibody for Elimination of Autoreactive T Cells.

Progress in developing improvements in the treatment of autoimmune disease has been gradual, due to challenges presented by the nature of these conditions. Namely, the need to suppress a patient's immune response while maintaining the essential activity of the immune system in controlling disease. Targeted treatments to eliminate the autoreactive immune cells driving disease symptoms present a promising new option for major improvements in treatment efficacy and side effect management. Monoclonal antibody therapies can be applied to target autoreactive immune cells if the cells possess unique surface marker expression patterns. Killer cell lectin like receptor G1 (KLRG1) expression on autoreactive T cells presents an optimal target for this type of cell depleting antibody therapy. In this study, we apply a variety of in vitro screening methods to determine the efficacy of a novel anti-KLRG1 antibody at mediating specific natural killer (NK) cell mediated antibody-dependent cellular cytotoxicity (ADCC). The methods include single-cell droplet microfluidic techniques, allowing timelapse imaging and sorting based on cellular interactions. Included in this study is the development of a novel method of sorting cells using a droplet-sorting platform and a fluorescent calcium dye to separate cells based on CD16 recognition of cell-bound antibody. We applied this novel sorting method to visualize transcriptomic variation between NK cells that are or are not activated by binding the anti-KLRG1 antibody using RNA sequencing. The data in this study reveals a reliable and target-specific cytotoxicity of the cell depleting anti-KLRG1 antibody, and supports our droplet-sorting calcium assay as a novel method of sorting cells based on receptor activation.

Region of interest localization, tissue storage time, and antibody binding density-a technical note on the GeoMx® Digital Spatial Profiler.

Background: Spatial biology is an emerging concept to interrogate tumor heterogeneity. The NanoString GeoMx® Digital Spatial Profiling (DSP) platform has become increasingly available. It combines high-plex analysis of protein or messenger RNA expression using barcoded antibodies or oligonucleotide probes with investigator-driven selection of regions of interest. Cell populations, e.g. immune cells, can be selectively analyzed via segmentation. A key advantage is the use of archived formalin-fixed, paraffin-embedded tissue, however, begging the question whether and to what extent tissue fixation and storage time affect the results. Materials and methods: Antibody binding density (ABD), i.e. the number of barcodes/µm2, is a key quality control measure for DSP spatial proteomics. To assess whether regional differences in tissue fixation have an influence on ABD, we compared 652 regions of interest selected from tumor center and periphery of 49 prostate cancer and 25 renal cell carcinoma (RCC) specimens. Moreover, the effect of tissue storage time on ABD was examined. Finally, we tested whether regional differences have an influence on ABD of segmented CD45+ or CD8+ cells. Results: No significant differences in ABD between tumor center and periphery were found in prostate cancer or RCC. However, ABD was significantly higher in recent specimens (≤5 years) when compared with those that were older (>5 years; P = 0.027). There was a trend towards higher ABD in the tumor periphery of RCC specimens after segmentation for immune cells, albeit without reaching statistical significance. Conclusions: The NanoString GeoMx® DSP platform delivers robust data to interrogate tumor heterogeneity, but tissue storage time should be considered when interpreting the results.

Small molecule innate immune modulators in cancer therapy.

Immunotherapy has proved to be a breakthrough in cancer treatment. So far, a bulk of the approved/late-stage cancer immunotherapy are antibody-based. Although these antibody-based drugs have demonstrated great promise, a majority of them are limited due to their access to extracellular targets, lack of oral bioavailability, tumor microenvironment penetration, induction of antibody dependent cytotoxicity etc. In recent times, there has been an increased research focus on the development of small molecule immunomodulators since they have the potential to overcome the aforementioned limitations posed by antibodies. Furthermore, while most biologics based therapeutics that are in clinical use are limited to modulating the adaptive immune system, very few clinically approved therapeutic modalities exist that modulate the innate immune system. The innate immune system, which is the body's first line of defense, has the ability to turn cold tumors hot and synergize strongly with existing adaptive immune modulators. In preclinical studies, small molecule innate immune modulators have demonstrated synergistic efficacy as combination modalities with current standard-of-care immune checkpoint antibodies. In this review, we highlight the recent advances made by small molecule innate immunomodulators in cancer immunotherapy.

Real-world Treatment Sequencing and Outcomes With Cabozantinib After First-line Immune Checkpoint Inhibitor-based Combination Therapy For Patients With Advanced Renal Cell Carcinoma: CARINA Study Results.

INTRODUCTION: Real-world data are limited on treatment sequencing and outcomes after first-line (1L) immune checkpoint inhibitor (CPI)-based combination treatment of advanced renal cell carcinoma (aRCC). PATIENTS AND METHODS: In this real-world, UK-based, retrospective study (CARINA; NCT04957160), data were obtained from hospital and electronic prescribing records. Patients were aged ≥ 18 years at aRCC diagnosis and had received 1L CPI-CPI or tyrosine kinase inhibitor (TKI)-CPI combination therapy before second-line (2L) therapy including cabozantinib. We describe treatment outcomes including 1L and 2L durations of treatment (DoT) and overall survival (OS). RESULTS: Data from April 2015 to June 2022 were collected on 281 patients from nine UK centres. Median 1L DoT was 2.3 months for CPI-CPI therapy (n = 171) and 5.0 months for TKI-CPI therapy (n = 58). After 1L CPI-CPI or TKI-CPI therapy, median 2L DoT was 5.8 versus 4.2 months, respectively, for cabozantinib (n = 163), and 3.8 versus 2.4 months for other therapies (n = 118); median 2L OS was 15.2 and 15.3 months, respectively, for cabozantinib, and 14.6 and 24.2 months for other therapies. CONCLUSION: DoT for 2L treatment was numerically better for cabozantinib than for other therapies, and after 1L CPI-CPI therapy than after 1L TKI-CPI therapy. Median OS was similar for 2L cabozantinib and other 2L therapies, and median OS for 2L cabozantinib was similar after both 1L therapy types. These results demonstrate the antitumour effect of 2L therapies, including cabozantinib, after 1L CPI-based combination treatment, regardless of whether 1L CPI-CPI or TKI-CPI therapy is used.

SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology.

Recent technological advancements have enabled spatially resolved transcriptomic profiling but at a multicellular resolution that is more cost-effective. The task of cell type deconvolution has been introduced to disentangle discrete cell types from such multicellular spots. However, existing benchmark datasets for cell type deconvolution are either generated from simulation or limited in scale, predominantly encompassing data on mice and are not designed for human immuno-oncology. To overcome these limitations and promote comprehensive investigation of cell type deconvolution for human immuno-oncology, we introduce a large-scale spatial transcriptomic deconvolution benchmark dataset named SpatialCTD, encompassing 1.8 million cells and 12,900 pseudo spots from the human tumor microenvironment across the lung, kidney, and liver. In addition, SpatialCTD provides more realistic reference than those generated from single-cell RNA sequencing (scRNA-seq) data for most reference-based deconvolution methods. To utilize the location-aware SpatialCTD reference, we propose a graph neural network-based deconvolution method (i.e., GNNDeconvolver). Extensive experiments show that GNNDeconvolver often outperforms existing state-of-the-art methods by a substantial margin, without requiring scRNA-seq data. To enable comprehensive evaluations of spatial transcriptomics data from flexible protocols, we provide an online tool capable of converting spatial transcriptomic data from various platforms (e.g., 10× Visium, MERFISH, and sci-Space) into pseudo spots, featuring adjustable spot size. The SpatialCTD dataset and GNNDeconvolver implementation are available at https://github.com/OmicsML/SpatialCTD, and the online converter tool can be accessed at https://omicsml.github.io/SpatialCTD/.

ALK5/VEGFR2 dual inhibitor TU2218 alone or in combination with immune checkpoint inhibitors enhances immune-mediated antitumor effects.

Transforming growth factor ß (TGFß) is present in blood of patients who do not respond to anti-programmed cell death (ligand) 1 [PD-(L)1] treatment, and through synergy with vascular endothelial growth factor (VEGF), it helps to create an environment that promotes tumor immune evasion and immune tolerance. Therefore, simultaneous inhibition of TGFß/VEGF is more effective than targeting TGFß alone. In this study, the dual inhibitory mechanism of TU2218 was identified through in vitro analysis mimicking the tumor microenvironment, and its antitumor effects were analyzed using mouse syngeneic tumor models. TU2218 directly restored the activity of damaged cytotoxic T lymphocytes (CTLs) and natural killer cells inhibited by TGFß and suppressed the activity and viability of regulatory T cells. The inactivation of endothelial cells induced by VEGF stimulation was completely ameliorated by TU2218, an effect not observed with vactosertib, which inhibits only TGFß signaling. The combination of TU2218 and anti-PD1 therapy had a significantly greater antitumor effect than either drug alone in the poorly immunogenic B16F10 syngeneic tumor model. The mechanism of tumor reduction was confirmed by flow cytometry, which showed upregulated VCAM-1 expression in vascular cells and increased influx of CD8 + CTLs into the tumor. As another strategy, combination of anti-CTLA4 therapy and TU2218 resulted in high complete regression (CR) rates in CT26 and WEHI-164 tumor models. In particular, immunological memory generated by the combination of anti-CTLA4 and TU2218 in the CT26 model prevented the development of tumors after additional tumor cell transplantation, suggesting that the TU2218-based combination has therapeutic potential in immunotherapy.

Clinical outcomes and prognostic factors in metastatic nonclear cell renal cell carcinoma treated with immuno-oncology combination therapy.

BACKGROUND: Metastatic nonclear cell renal cell carcinoma (nccRCC) is a heterogeneous disease with poor prognosis. The clinical characteristics and prognostic factors of immuno-oncology (IO) combination therapy for nccRCC are not well known. This study analyzed patients with metastatic nccRCC treated with IO combination therapy. METHODS: We retrospectively collected data from 447 patients with metastatic RCC treated with IO-based combination therapy as first-line treatment between September 2018 and July 2023 in a Japanese multicenter study. The primary endpoints were objective response rate, progression-free survival (PFS), and overall survival (OS), comparing groups treated with IO-IO and IO-tyrosine kinase inhibitor (TKI) therapies. RESULTS: Seventy-five patients with metastatic nccRCC were eligible for analysis: 39 were classified into the IO-IO group and 36 into the IO-TKI group. Median PFS was 5.4 months (95% CI: 1.6-9.1) for the IO-IO group and 5.6 (95% CI: 3.4-12.0) for the IO + TKI group. Median OS was 24.2 months (95% CI: 7.5-NA) for the IO-IO group and 23.4 (95% CI: 18.8-NA) for the IO + TKI group, with no significant difference. In univariate analysis, International Metastatic Renal Cell Carcinoma Database Consortium scores, Karnofsky performance status, neutrophil-to-lymphocyte ratio, and the presence of liver metastases were significantly associated with OS, whereas in multivariate analysis, only the presence of liver metastases was significantly associated with OS (P = .035). CONCLUSIONS: There was no significant difference in OS or PFS between IO-IO and IO-TKI combination therapy as first-line treatment for patients with nccRCC. Liver metastasis is a poor prognostic factor for such patients.

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology.

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

LAG-3 and PD-1 synergize on CD8+ T cells to drive T cell exhaustion and hinder autocrine IFN-γ-dependent anti-tumor immunity.

Overcoming immune-mediated resistance to PD-1 blockade remains a major clinical challenge. Enhanced efficacy has been demonstrated in melanoma patients with combined nivolumab (anti-PD-1) and relatlimab (anti-LAG-3) treatment, the first in its class to be FDA approved. However, how these two inhibitory receptors synergize to hinder anti-tumor immunity remains unknown. Here, we show that CD8+ T cells deficient in both PD-1 and LAG-3, in contrast to CD8+ T cells lacking either receptor, mediate enhanced tumor clearance and long-term survival in mouse models of melanoma. PD-1- and LAG-3-deficient CD8+ T cells were transcriptionally distinct, with broad TCR clonality and enrichment of effector-like and interferon-responsive genes, resulting in enhanced IFN-γ release indicative of functionality. LAG-3 and PD-1 combined to drive T cell exhaustion, playing a dominant role in modulating TOX expression. Mechanistically, autocrine, cell-intrinsic IFN-γ signaling was required for PD-1- and LAG-3-deficient CD8+ T cells to enhance anti-tumor immunity, providing insight into how combinatorial targeting of LAG-3 and PD-1 enhances efficacy.

terraFlow, a high-parameter analysis tool, reveals T cell exhaustion and dysfunctional cytokine production in classical Hodgkin's lymphoma.

Immune cells express an incredible variety of proteins; by measuring combinations of these, cell types influencing disease can be precisely identified. We developed terraFlow, a platform that defines cell subsets exhaustively by combinatorial protein expression. Using high-parameter checkpoint-focused and function-focused panels, we studied classical Hodgkin's lymphoma (cHL), where systemic T cells have not been investigated in detail. terraFlow revealed immune perturbations in patients, including elevated activated, exhausted, and interleukin (IL)-17+ phenotypes, along with diminished early, interferon (IFN)γ+, and tumor necrosis factor (TNF)+ T cells before treatment; many perturbations remained after treatment. terraFlow identified more disease-associated differences than other tools, often with better predictive power, and included a non-gating approach, eliminating time-consuming and subjective manual thresholds. It also reports a method to identify the smallest set of markers distinguishing study groups. Our results provide mechanistic support for past reports of immune deficiency in cHL and demonstrate the value of terraFlow in immunotherapy and biomarker studies.

Get to know your neighbors with a SNAQ™: A framework for single cell spatial neighborhood analysis in immunohistochemical images.

Motivation: Analyzing the local microenvironment of tumor cells can provide significant insights into their complex interactions with their cellular surroundings, including immune cells. By quantifying the prevalence and distances of certain immune cells in the vicinity of tumor cells through a neighborhood analysis, patterns may emerge that indicate specific associations between cell populations. Such analyses can reveal important aspects of tumor-immune dynamics, which may inform therapeutic strategies. This method enables an in-depth exploration of spatial interactions among different cell types, which is crucial for research in oncology, immunology, and developmental biology. Results: We introduce an R Markdown script called SNAQ™ (Single-cell Spatial Neighborhood Analysis and Quantification), which conducts a neighborhood analysis on immunofluorescent images without the need for extensive coding knowledge. As a demonstration, SNAQ™ was used to analyze images of pancreatic ductal adenocarcinoma. Samples stained for DAPI, PanCK, CD68, and PD-L1 were segmented and classified using QuPath. The resulting CSV files were exported into RStudio for further analysis and visualization using SNAQ™. Visualizations include plots revealing the cellular composition of neighborhoods around multiple cell types within a customizable radius. Additionally, the analysis includes measuring the distances between cells of certain types relative to others across multiple regions of interest. Availability and implementation: The R Markdown files that comprise the SNAQ™ algorithm and the input data from this paper are freely available on the web at https://github.com/AryehSilver1/SNAQ.

Immune-Related Adverse Events Associated with Atezolizumab: Insights from Real-World Pharmacovigilance Data.

The advancement of immuno-oncology has brought about a significant shift in cancer treatment methods, with antibody-based immune checkpoint inhibitors like atezolizumab leading the way in this regard. However, the use of this checkpoint blockade can result in immune-related adverse events due to increased T-cell activity. The full spectrum of these events is not yet completely understood. In this study, the United States FDA Adverse Event Reporting System (FAERS) was utilized to investigate immune-related adverse events linked with the use of atezolizumab. The study identified forty-nine immune-related adverse events that affected multiple organ systems, including cardiovascular, respiratory, hematologic, hepatic, renal, gastrointestinal, neurologic, musculoskeletal, dermatologic, endocrine, and systemic disorders. The strongest signals for relative risk occurred for immune-mediated encephalitis (RR = 93.443), autoimmune myocarditis (RR = 56.641), immune-mediated hepatitis (RR = 49.062), immune-mediated nephritis (RR = 40.947), and autoimmune arthritis (RR = 39.382). Despite the morbidity associated with these adverse events, emerging evidence suggests potential associations with improved survival outcomes. Overall, this report sheds light on the widespread immune-related adverse events that cause significant morbidity and mortality in patients with cancer being treated with atezolizumab and brings attention to them for the clinicians treating these patients.

Adverse Events of PD-1, PD-L1, CTLA-4, and LAG-3 Immune Checkpoint Inhibitors: An Analysis of the FDA Adverse Events Database.

This study aimed to identify the 25 most prevalent adverse events (AEs) associated with FDA-approved immune checkpoint inhibitors (ICIs)-specifically, PD-1, PD-L1, CTLA-4, and LAG-3 inhibitors-using data from the FDA Adverse Events Reporting System (FAERS), a publicly available repository of reported drug adverse events, and AERSMine, an open-access pharmacovigilance tool, to investigate these adverse events. For PD-1 inhibitors, the most common AEs were diarrhea, fatigue, and pyrexia, with notable instances of neutropenia and hypothyroidism, particularly with toripalimab and dostarlimab. PD-L1 inhibitors also frequently caused pyrexia, diarrhea, and fatigue, with interstitial lung disease and hypothyroidism showing a class effect, and drug-specific AEs such as hepatotoxicity and chills. CTLA-4 inhibitors predominantly resulted in diarrhea and colitis, with ipilimumab frequently causing pyrexia and rash, while tremelimumab exhibited unique AEs such as biliary tract infection. The LAG-3 inhibitor relatlimab reported fewer AEs, including pyrexia and pneumonia. Rare but significant AEs across all inhibitors included myocarditis and myasthenia gravis. This study provides a detailed overview of the 25 most common AEs associated with ICIs, offering valuable insights for clinical decision-making and AE management. Further research is necessary to elucidate the mechanisms underlying these AEs and to develop targeted interventions to enhance the safety and efficacy of ICI therapy in patients with cancer.

Immunohistochemical Detection of Indoleamine 2,3-Dioxygenase in Spontaneous Mammary Carcinomas of 96 Pet Rabbits.

For mammary carcinomas in pet rabbits, prognostic biomarkers are poorly defined, and treatment is limited to surgical excision. Additional treatment options are needed for rabbit patients for which surgery is not a suitable option. In human breast cancer, the immunosuppressive enzyme indoleamine 2,3-dioxygenase 1 (IDO1) represents a prognostic biomarker and possible therapeutic target. This retrospective immunohistochemical study examined IDO1 in 96 pet rabbit mammary carcinomas with known mitotic count, hormone receptor status, and percentage of stromal tumor infiltrating lymphocytes (TILs). Tumors were obtained from 96 pet rabbits with an average of 5.5 years. All rabbits with reported sex (n = 88) were female or female-spayed. Of the carcinomas, 94% expressed IDO1, and 86% had sparse TILs consistent with cold tumors. Statistically significant correlations existed between a higher percentage of IDO1-positive tumor cells, lower mitotic counts, and increased estrogen receptor expression. The threshold for significance was IDO1 staining in >10% of tumor cells. These results lead to the assumption that IDO1 expression contributes to tumorigenesis and may represent a prognostic biomarker and possible therapeutic target also in pet rabbit mammary carcinomas. They also support the value of rabbits for breast cancer research.

A Microdissection Protocol for Proteogenomic Analysis of Histological Sections to Advance Drug Development.

Combining proteogenomics with laser capture microdissection (LCM) in cancer research offers a targeted way to explore the intricate interactions between tumor cells and the different microenvironment components. This is especially important for immuno-oncology (IO) research where improvements in the predictability of IO-based drugs are sorely needed, and depends on a better understanding of the spatial relationships involving the tumor, blood supply, and immune cell interactions, in the context of their associated microenvironments. LCM is used to isolate and obtain distinct histological cell types, which may be routinely performed on complex and heterogeneous solid tumor specimens. Once cells have been captured, nucleic acids and proteins may be extracted for in-depth multimodality molecular profiling assays. Optimizing the minute tissue quantities from LCM captured cells is challenging. Following the isolation of nucleic acids, RNA-seq may be performed for gene expression and DNA sequencing performed for the discovery and analysis of actionable mutations, copy number variation, methylation profiles, etc. However, there remains a need for highly sensitive proteomic methods targeting small-sized samples. A significant part of this protocol is an enhanced liquid chromatography mass spectrometry (LC-MS) analysis of micro-scale and/or nano-scale tissue sections. This is achieved with a silver-stained one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) approach developed for LC-MS analysis of fresh-frozen tissue specimens obtained via LCM. Included is a detailed in-gel digestion method adjusted and specifically designed to maximize the proteome coverage from amount-limited LCM samples to better facilitate in-depth molecular profiling. Described is a proteogenomic approach leveraged from microdissected fresh frozen tissue. The protocols may also be applicable to other types of specimens having limited nucleic acids, protein quantity, and/or sample volume.

Model-based population pharmacokinetic and exposure response analyses for safety and efficacy of nivolumab as adjuvant treatment in subjects with resected oesophageal or gastroesophageal junction cancer.

AIMS: Nivolumab is approved as adjuvant treatment in subjects with resected oesophageal or gastroesophageal junction cancer (EC/GEJC) based on results from the pivotal CheckMate 577 trial. We present a model-based clinical pharmacology profiling and benefit-risk assessment of nivolumab as adjuvant treatment in subjects with resected EC/GEJC supporting a less frequent dosing regimen. METHODS: Population pharmacokinetic (popPK) analysis was conducted to characterize nivolumab pharmacokinetics (PK) using clinical data from 1493 subjects from seven monotherapy clinical studies across multiple solid tumours. The exposure-response (E-R) analyses included data from 756 patients from CheckMate 577. E-R relationships for efficacy and safety were characterized by evaluating the relationship between nivolumab exposure and disease-free survival (DFS) for efficacy; and time to first occurrence of Grade ≥2 immune-mediated adverse events (Gr2 + IMAEs) for safety. RESULTS: Nivolumab exposure was found to be associated with both DFS and risk of Gr2 + IMAEs. However, the hazard ratios (HRs) (95% confidence interval [CI]) at the 5th and 95th percentiles of nivolumab exposure were similar for DFS and Gr2 + IMAEs, indicating flat E-R relationships within the exposure range produced by the studied regimen. Model-predicted probability of DFS and Gr2 + IMAEs were similar between the two regimens of 240 mg every 2 weeks or 480 mg every 4 weeks for 16 weeks followed by 480 mg Q4W up to 1 year. CONCLUSIONS: The analyses demonstrated a flat E-R relationship over the range of exposures produced by the studied regimen and supported the approval of an alternative dosing regimen with less frequent dosing in patients with adjuvant EC/GEJC.