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• Combining a Universal Telomerase Based Cancer Vaccine with Ipilimumab in Patients with Metastatic Melanoma - Five-year Follow up of a Phase I/IIa Trial

  Background Ipilimumab improves survival for patients with metastatic malignant melanoma. Combining a therapeutic cancer vaccine with ipilimumab may increase efficacy by providing enhanced anti-tumor immune responses. UV1 consists of three synthetic long peptides from human telomerase reverse transcriptase (hTERT). These peptides comprise epitopes recognized by T cells from cancer patients experiencing long-term survival following treatment with a first-generation hTERT vaccine, and generate long-lasting immune responses in cancer patients when used as monotherapy. The objective of this trial was to investigate the safety and efficacy of combining UV1 with ipilimumab in metastatic melanoma. Patients and methods In this phase I/IIa, single center trial [NCT02275416], patients with metastatic melanoma received repeated UV1 vaccinations, with GM-CSF as an adjuvant, in combination with ipilimumab. Patients were evaluated for safety, efficacy and immune response. Immune responses against vaccine peptides were monitored in peripheral blood by measuring antigen-specific proliferation and IFN-γ production. Results Twelve patients were recruited. Adverse events were mainly diarrhea, injection site reaction, pruritus, rash, nausea and fatigue. Ten patients showed a Th1 immune response to UV1 peptides, occurring early and after few vaccinations. Three patients obtained a partial response and one patient a complete response. Overall survival was 50% at 5 years. Conclusion Treatment was well tolerated. The rapid expansion of UV1-specific Th1 cells in the majority of patients indicates synergy between UV1 vaccine and CTLA-4 blockade. This may have translated into clinical benefit, encouraging the combination of UV1 vaccination with standard of care treatment regimes containing ipilimumab/CTLA-4 blocking antibodies.

  Study EGAS00001005253

• Exploration of coding and non-coding variants in cancer using GenomePaint.

  GenomePaint (https://proteinpaint.stjude.org/genomepaint) is a dynamic visualization platform for whole-genome, whole-exome, transcriptome, and epigenomic data, featuring a novel design that captures the inter-relatedness between DNA variations and RNA expression. Regulatory non-coding variants can be inspected and discovered along with coding variants, and their functional impact further explored by examining 3D genome and/or ChIP-seq data generated from cancer cell lines. Further, GenomePaint correlates mutation and expression patterns with patient outcomes, and can display external data such as adult cancer datasets and user-provided custom tracks. We used GenomePaint to analyze multi-omics data from 3,652 pediatric cancers representing 16 histotypes, and demonstrate the visualization features through examples, including two that led to new insights into oncogenic mechanisms in pediatric cancer. The first is the discovery of a new class of pathogenic recurrent variants that cause aberrant splicing, disrupting the RING domain of CREBBP, a driver gene frequently mutated in relapsed pediatric leukemia. The second is the cis-activation of the MYC oncogene in a subset of B-lineage acute lymphoblastic leukemia (B-ALL) via duplication of the NOTCH1-MYC enhancer (N-ME), previously discovered only in T-lineage ALL. The regulatory impact of N-ME enhancer amplification was initially confirmed by allelic imbalance in published gene expression and ChIP-seq data and verified by additional Capture-C and fluorescence in situ hybridization data generated by follow-up experiments. These examples demonstrate the power of GenomePaint in enabling not only data visualization but also integrative genomic analysis that can lead to novel biological insight for follow-up experimental validation.

  Study EGAS00001004669

• Combination of CDK4/6 with BET-bromodomain and PI3K/mTOR inhibitors in medulloblastoma in vitro and in vivo

  Despite improvement in the treatment of medulloblastoma (MB) over the last years, numerous patients with MYC- and MYCN-driven tumors still fail the current therapeutic regimen. The retinoblastoma (RB) pathway is often compromised in MB with RB remaining intact suggesting that CDK4/6 inhibition might represent a therapeutic strategy for which drug combination remains understudied. Using tumor lines grown in stem cell conditions referred as tumorspheres as well as tumor cells freshly dissociated from the brain of mice harboring intracranial patient-derived xenografts (PDX) of Group3 (G3) and Sonic Hedgehog (SHH) MB, we conducted high throughput drug combination screens using the CDK4/6 inhibitor (CDK4/6i) ribociclib as an anchor and 87 oncology drugs approved by FDA or currently in clinical trials. Bromodomain and extra terminal (BET) and PI3K/mTOR inhibitors potentiated ribociclib’s inhibition of proliferation in G3 and SHH MB. A reverse combination screen using BET inhibitor JQ1 as the anchor, revealed the three FDA approved CDK4/6i as the most potentiating drugs. Those synergistic combinations were tested in vivo in mice intracranially implanted with G3 and SHH MB tumor cells. Ribociclib showed single agent activity in several in vivo MB models. However, despite in vitro synergy, combinations of ribociclib with JQ1 and ribociclib with the PI3K/mTOR inhibitor paxalisib failed to improve the survival of MB bearing mice compared to ribociclib alone. Our data illustrates the difficulty in translating in vitro findings to in vivo for brain tumors partly due to insufficient free brain concentration and altered signaling pathways activation in vitro compared to in vivo.

  Study EGAS00001006286

• Multi-omic analysis of the tumor microenvironment shows clinical correlations in Ph1 study of atezolizumab +/- SoC in MM

  Multiple myeloma (MM) remains incurable, and treatment of relapsed/refractory (R/R) disease is challenging. There is an unmet need for more targeted therapies in this setting; deep cellular and molecular phenotyping of the tumor and microenvironment in MM could help guide such therapies. This phase 1b study (NCT02431208) evaluated the safety and efficacy of the anti-programmed death-ligand 1 monoclonal antibody atezolizumab (Atezo) alone or in combination with the standard of care (SoC) treatments lenalidomide (Len) or pomalidomide (Pom) and/or daratumumab (Dara) in patients with R/R MM. Study endpoints included incidence of adverse events (AEs) and overall response rate (ORR). A novel unsupervised integrative multi-omic analysis was performed using RNA sequencing, mass cytometry immunophenotyping, and proteomic profiling of baseline and on-treatment bone marrow samples from patients receiving Atezo monotherapy or Atezo+Dara. A similarity network fusion (SNF) algorithm was applied to preprocessed data. Eighty-five patients were enrolled. Treatment-emergent deaths occurred in 2 patients; both deaths were considered unrelated to study treatment. ORRs ranged from 11.1% (Atezo+Len cohorts, n=18) to 83.3% (Atezo+Dara+Pom cohort, n=6). High-dimensional multi-omic profiling of the tumor microenvironment and integrative SNF analysis revealed novel correlations between cellular and molecular features of the tumor and immune microenvironment, patient selection criteria, and clinical outcome. Atezo monotherapy and SoC combinations were safe in this patient population and demonstrated some evidence of clinical efficacy. Integrative analysis of high dimensional genomics and immune data identified novel clinical correlations that may inform patient selection criteria and outcome assessment in future immunotherapy studies for myeloma.

  Study EGAS00001007286

• Transcriptomics-driven classification of ALAL

  Acute leukemia of ambiguous lineage (ALAL) is a rare, poor-prognosis subtype of acute leukemia that cannot be assigned to a single hematopoietic lineage. Although ALAL patients are typically treated with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) regimens, optimal treatment choice is hindered by their lineage ambiguity. Therefore, we investigated the added value of transcriptomics for improving lineage assignment, currently based mainly on surface markers. First, we used an in-house pipeline to comprehensively detect genetic lesions in RNA-sequencing data (n=23) with a sensitivity >90%, as confirmed by targeted DNA sequencing. Second, we compared ALAL gene expression profiles (GEPs) with representative AML (n=145), B-ALL (n=223) and T-ALL (n=85) cases. In a principal component analysis, ALALs did not form a separate group, but clustered with AML, B-ALL or T-ALL. Accordingly, a machine learning classifier trained with GEPs of acute leukemias segregated 20/23 ALALs into myeloid-, B- or T-lymphoid leukemia. These 20 cases harbored genetic abnormalities consistent with the classifier-assigned leukemia. Furthermore, ALAL GEPs were deconvoluted with single-cell transcriptional profiles of normal hematopoietic cells using CIBERSORTx, revealing enrichment for signatures of lineages corresponding to the leukemic type predicted by our algorithm. The classifier was validated on an external ALAL cohort (n=24), assigning 75% of the patients to a lineage matching their immunophenotypic and methylation profiles. In conclusion, integrative analysis of RNA-sequencing data can accurately classify most ALAL cases. The pipeline and classifier developed in our study are valuable tools to improve ALAL diagnosis and guide therapeutic decisions.

  Study EGAS00001007967

• A study of the genetic basis of evation by Acute Myeloid Leukaemia of Graft vs Leukaemia effects after allogeneic bone marrow transplantation

  Acute myeloid leukaemia (AML) is an aggressive and molecularly diverse disease with a poor overall survival of 20-25%. With an annual incidence of 2.9 per 100,000, AML is currently the commonest myeloid malignancy in Europe, yet the two main therapeutic options for this disease, anthracyclines and purine analogues, have remained unchanged for over 20 years. Currently patients are stratified at diagnosis according to a series of clinicopathological parameters (e.g. age, white cell count and presence/absence of previous clonal haematological disease) and molecular markers (e.g. chromosomal translocations/deletions, aneuploidy and mutations in genes such as FLT3 and NPM1). Patients with adverse prognostic features, whose prognosis is particularly poor (e.g. <15% long-term survival) are offered treatment with allogeneic bone marrow transplantation (allo-BMT) if a sibling or unrelated donor is available. This can significantly improve survival (e.g. up to 40% long-term survival in some contexts), albeit at the expense of significant toxicity and transplant-related mortality (TRM). Allo-BMT is thought to work in part by allowing the delivery of large doses of chemotherapy followed by haemopoietic "rescue" with donor haemopoietic stem cells (haemopoietic failure would otherwise ensue). However, potentially the most potent effect of allo-BMT is the cytotoxic effect of donor lymphocytes against AML blasts, a phenomenon known as graft-vs-leukaemia (GVL) effect. Increasingly, transplants using reduced chemotherapy intensity (mini-allografts) are being used that partially circumvent the toxicity from chemotherapy and rely on GVL to effect cure. Nevertheless, AML relapse after allo-BMT still occurs at a significant rate of up to 80% depending on the type of transplant. There is accumulating evidence that genetic events in residual leukaemic cells enable them to evade immunodetection and therefore survive the GVL effect and expand to cause relapse. The most striking example of this is the loss of HLA antigens after transplants in which donor and recipient are not fully HLA-matched. In these cases, the leukaemia "deletes" the genomic region containing the disparate HLA antigen which was preferentially targeted as "foreign" by the GVL effect. However, the genetic basis of immune evasion in the majority of transplants, which are fully HLA matched, is not known. One possibility is that loss of genes coding for antigens outside the HLA locus but which are also targets of GVL may operate, alternatively genetic events that affect processes downstream of immunological cytotoxicity may be responsible. The identification of genetic events that mediate immune evasion would not only facilitate the understanding of this process but can help plan therapeutic interventions that improve the outcomes of allogeneic transplantation for AML and other disorders. We intend to study this by conducting exome sequencing on 6 cases of AMLs from patients that attend my clinic at Addenbrooke's hospital and have relapsed after allogeneic transplantation. Samples from AML diagnosis, remission/normal and AML relapse (total n=18) will be studied to identify somatic mutations in the primary AML and those acquired by the relapsed clone. The 18 samples will also be studied by array CGH to detect regions of genomic amplification or deletion.

  Dataset EGAD00001000404

• SC_DDD-G-1

  Batch 1 of unfiltered genotype data for DDD Study patients (N=2,997), some of which were used in the neurodevelopmental disorder discovery GWAS (Niemi et al., Nature 2018). Samples were genotyped on the Illumina HumanCoreExome BeadChip. QC'd data is available in release EGAD00010001604

  Dataset EGAD00010001598

• SC_DDD-G-2

  Batch 2 of unfiltered genotype for DDD Study patients (N=8,286), some of which were used in the neurodevelopmental disorder discovery GWAS (Niemi et al., Nature 2018). Samples were genotyped on the Illumina InfiniumCoreExome Beadchip. QC'd data is available in release EGAD00010001604

  Dataset EGAD00010001600

• Expression array

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed.
This dataset contains expression array data for 32 patients of the screening cohort with 8 of them having paired normal tissue plus an additional relapse tumor/normal pair of one of those 8 patients and a patient only with normal tissue. Data was generated on a HumanHT-12 v4 Bead Array (Illumina) and is stored in IDAT file format.

  Dataset EGAD00010002596

• The University of Tasmania MS Stem Data Access Committee

  Data access committee for data related to the Multiple Sclerosis Stem (MS Stem) biobank. A biobank of human induced pluripotent stem cell (iPSC) lines. MS Stem is a biobank of human induced pluripotent stem cell (iPSC) lines, derived from people living with and without multiple sclerosis. The biobank provides researchers with fully characterised iPSC lines from well phenotyped and genotyped individuals. This provides a unique opportunity to research the pathophysiology of MS in human cell models or conduct preclinical screening of putative therapeutics.

  Dac EGAC50000000120