28 research outputs found
AdS/CFT correspondence in the Euclidean context
We study two possible prescriptions for AdS/CFT correspondence by means of
functional integrals. The considerations are non-perturbative and reveal
certain divergencies which turn out to be harmless, in the sense that
reflection-positivity and conformal invariance are not destroyed.Comment: 20 pages, references and two remarks adde
Distinct immune evasion in APOBEC‐enriched, HPV‐negative HNSCC
Immune checkpoint inhibition leads to response in some patients with head and neck squamous cell carcinoma (HNSCC). Robust biomarkers are lacking to date. We analyzed viral status, gene expression signatures, mutational load and mutational signatures in whole exome and RNA-sequencing data of the HNSCC TCGA dataset (n = 496) and a validation set (DKTK MASTER cohort, n = 10). Public single-cell gene expression data from 17 HPV-negative HNSCC were separately reanalyzed. APOBEC3-associated TCW motif mutations but not total single nucleotide variant burden were significantly associated with inflammation. This association was restricted to HPV-negative HNSCC samples. An APOBEC-enriched, HPV-negative subgroup was identified, that showed higher T-cell inflammation and immune checkpoint expression, as well as expression of APOBEC3 genes. Mutations in immune-evasion pathways were also enriched in these tumors. Analysis of single-cell sequencing data identified expression of APOBEC3B and 3C genes in malignant cells. We identified an APOBEC-enriched subgroup of HPV-negative HNSCC with a distinct immunogenic phenotype, potentially mediating response to immunotherapy
Gammaretrovirus-mediated correction of SCID-X1 is associated with skewed vector integration site distribution in vivo
We treated 10 children with X-linked SCID (SCID-X1) using gammaretrovirus-mediated gene transfer. Those with sufficient follow-up were found to have recovered substantial immunity in the absence of any serious adverse events up to 5 years after treatment. To determine the influence of vector integration on lymphoid reconstitution, we compared retroviral integration sites (RISs) from peripheral blood CD3(+) T lymphocytes of 5 patients taken between 9 and 30 months after transplantation with transduced CD34(+) progenitor cells derived from 1 further patient and I healthy donor. Integration occurred preferentially in gene regions on either side of transcription start sites, was clustered, and correlated with the expression level in CD34(+) progenitors during transduction. In contrast to those in CD34(+) cells, RISs recovered from engrafted CD3(+)T cells were significantly overrepresented within or near genes encoding proteins with kinase or transferase activity or involved in phosphorus metabolism. Although gross patterns of gene expression were unchanged in transduced cells, the divergence of RIS target frequency between transduced progenitor cells and post-thymic T lymphocytes indicates that vector integration influences cell survival, engraftment, or proliferation
Analyzing the Number of Common Integration Sites of Viral Vectors – New Methods and Computer Programs
Vectors based on γ-retroviruses or lentiviruses have been shown to stably express therapeutical transgenes and effectively cure different hematological diseases. Molecular follow up of the insertional repertoire of gene corrected cells in patients and preclinical animal models revealed different integration preferences in the host genome including clusters of integrations in small genomic areas (CIS; common integrations sites). In the majority, these CIS were found in or near genes, with the potential to influence the clonal fate of the affected cell. To determine whether the observed degree of clustering is statistically compatible with an assumed standard model of spatial distribution of integrants, we have developed various methods and computer programs for γ-retroviral and lentiviral integration site distribution. In particular, we have devised and implemented mathematical and statistical approaches for comparing two experimental samples with different numbers of integration sites with respect to the propensity to form CIS as well as for the analysis of coincidences of integration sites obtained from different blood compartments. The programs and statistical tools described here are available as workspaces in R code and allow the fast detection of excessive clustering of integration sites from any retrovirally transduced sample and thus contribute to the assessment of potential treatment-related risks in preclinical and clinical retroviral gene therapy studies
Real-Time Definition of Non-Randomness in the Distribution of Genomic Events
Features such as mutations or structural characteristics can be non-randomly or non-uniformly distributed within a genome. So far, computer simulations were required for statistical inferences on the distribution of sequence motifs. Here, we show that these analyses are possible using an analytical, mathematical approach. For the assessment of non-randomness, our calculations only require information including genome size, number of (sampled) sequence motifs and distance parameters. We have developed computer programs evaluating our analytical formulas for the real-time determination of expected values and p-values. This approach permits a flexible cluster definition that can be applied to most effectively identify non-random or non-uniform sequence motif distribution. As an example, we show the effectivity and reliability of our mathematical approach in clinical retroviral vector integration site distribution
Sarcoma classification by DNA methylation profiling
Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications
Prolonged Survival of a Patient with Advanced-Stage Combined Hepatocellular-Cholangiocarcinoma
Combined hepatocellular-cholangiocarcinoma (cHCC/CCA) represents a rare type of primary liver cancer with a very limited prognosis. Although just recently genomic studies have contributed to a better understanding of the disease's genetic landscape, therapeutic options, especially for advanced-stage patients, are limited and often experimental, as no standardized treatment protocols have been established to date. Here, we report the case of a 38-year-old male patient who was diagnosed with extensive intrahepatic cHCC/CCA in an otherwise healthy liver without signs of chronic liver disease. An interdisciplinary stepwise therapeutic approach including locoregional liver-targeted therapy, systemic chemotherapy, liver transplantation, surgical pulmonary metastasis resection, and next-generation sequencing-based targeted therapy led to a prolonged overall survival beyond 5 years with an excellent quality of life. This case report comprises several provocative treatment decisions that are extensively discussed in light of the existing literature on this rare but highly aggressive malignancy
Comprehensive genomic characterization of gene therapy-induced T-cell acute lymphoblastic leukemia
Drug combinations that target critical pathways are a mainstay of cancer care. To improve current approaches to combination treatment of chronic lymphocytic leukemia (CLL) and gain insights into the underlying biology, we studied the effect of 352 drug combination pairs in multiple concentrations by analysing ex vivo drug response of 52 primary CLL samples, which were characterized by 'omics' profiling. Known synergistic interactions were confirmed for B-cell receptor (BCR) inhibitors with Bcl-2 inhibitors and with chemotherapeutic drugs, suggesting that this approach can identify clinically useful combinations. Moreover, we uncovered synergistic interactions between BCR inhibitors and afatinib, which we attribute to BCR activation by afatinib through BLK upstream of BTK and PI3K. Combinations of multiple inhibitors of BCR components (e.g., BTK, PI3K, SYK) had effects similar to the single agents. While PI3K and BTK inhibitors produced overall similar effects in combinations with other drugs, we uncovered a larger response heterogeneity of combinations including PI3K inhibitors, predominantly in CLL with mutated IGHV, which we attribute to the target's position within the BCR-signaling pathway. Taken together, our study shows that drug combination effects can be effectively queried in primary cancer cells, which could aid discovery, triage and clinical development of drug combinations