7411 results for "canc*"

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• Somatic_mutation_in_skin_epidermis__SMS_

  We aim to assess the range and depth of mutations in genes linked with cancer in skin epidermis surrounding lesions which are undergoing surgical removal. Patient history will be collected to provide a detailed outline of tumour type (including histology), skin type, and sunlight exposure. We will perform ultra-deep targeted sequencing using genes implicated in cancer to try and understand the background of mutations surrounding these lesions

  Study EGAS00001002165

• Genetics and therapeutic responses to TIL therapy of pancreatic cancer PDX models

  Pancreatic cancer is the 7th leading cause of cancer-related deaths worldwide. Checkpoint immunotherapy has not yet showed encouraging results in pancreatic cancer possibly owing to a poor immunogenicity and/or an immune suppressive microenvironment. The aim of this study was to develop patient-derived xenografts (PDX) models and to assess if autologous tumor-infiltrating lymphocytes (TILs) would have anti-tumoral activity in pancreatic cancer. Tumor biopsies from 29 patients were subcutaneously transplanted into NOG mice. Tumor growths were confirmed in 11 out of 29 transplantations. The PDX tumors histologically resembled their original biopsies, but since stromal cells in the PDX model tumors were from mouse, their gene expression differed from the original biopsies. Immune checkpoint ligands other than PD-L1 were expressed in pancreatic cancers but PD-L1 was rarely expressed. One of the three tumors that did express PD-L1 was an adenosquamous cancer and another had a mismatch repair deficiency. TILs were expanded from six tumors and were injected into NOG or human interleukin-2 transgenic-NOG (hIL2-NOG) mice carrying PDX tumors. Regression of tumors could be verified in hIL2-NOG mice in 3 of the 6 PDX models treated with autologous TILs, including the adenosquamous PDX model. In conclusion, PDX models of pancreatic cancer can be used to learn more about tumor characteristics and biomarkers, and to evaluate responses to ACT and combination therapies. The major benefit of the model is that modifications of T cells can be tested in an autologous humanized mouse model to gain preclinical data to support the initiation of a clinical trial.

  Study EGAS00001005596

• Gene expression-based prediction of pazopanib efficacy in sarcoma (HIPO, H021)

  The multi-receptor tyrosine kinase (RTK) inhibitor pazopanib is approved for the treatment of advanced non-adipocytic soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to date to select patients who are most likely to benefit from this drug. We analyzed the molecular profiles and clinical outcomes of pazopanib-treated sarcoma patients enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing (WGS/WES) and transcriptome sequencing to inform the care of adults with advanced cancer across histologies who are younger than 51 and patients with rare tumors, including rare subtypes of more common entities, regardless of age.​ Among a total of 109 patients with available WGS/WES data, there was no correlation between clinical parameters, specific genetic alterations, or mutational signatures and clinical outcome. In contrast, analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR]=0.53, p=0.021), IGF1R (HR=1.82, p=0.027), and KDR (HR=0.50, p=0.011) were independently associated with progression-free survival (PFS). Based on the expression of these RTK genes, i.e., the features NTRK3-high, IGF1R-low, and KDR-high, we developed a pazopanib efficacy predictor (PEP) that stratified patients into three groups with significantly different PFS (p<0.0001). Application of the PEP to an independent cohort of pazopanib-treated sarcoma patients from DKTK MASTER (n=43) confirmed its potential to separate patient groups with significantly different PFS (p=0.02), whereas no such association was observed in sarcoma patients from DKTK MASTER (n=77) or The Cancer Genome Atlas sarcoma cohort (n=256) who were not treated with pazopanib. A score based on the combined expression of NTRK3, IGF1R, and KDR allows identification of sarcoma patients with good, intermediate, and poor outcome following pazopanib therapy and warrants investigation as a predictive tool in prospective studies to optimize the use of this drug in the clinic.

  Study EGAS00001005836

• The evolution of hematopoietic cells under cancer therapy

  Chemotherapies may increase mutagenesis of healthy cells and change the selective pressures in tissues thus influencing their evolution. However, their contributions to the mutation burden and clonal expansions of healthy somatic tissues are not clear. Here, exploiting the mutational footprint of some chemotherapies, we explore their influence on the evolution of hematopoietic cells. Cells of Acute Myeloid Leukemia (AML) secondary to treatment with platinum-based drugs showed the mutational footprint of these drugs, indicating that non-malignant blood cells received chemotherapy mutations. No trace of 5-fluorouracil (5FU) mutational signature was found in AML secondary to exposure to 5FU, suggesting that cells establishing the AML were quiescent during treatment. Using the platinum-based mutational signature as a barcode, we determined that secondary AMLs began their clonal expansion after the start of the cytotoxic treatment. Its absence in clonal hematopoiesis cases is consistent with a clonal expansion that predates the exposure to the cytotoxic agent.

  Study EGAS00001005234

• Whole-exome sequencing of ovarian clear cell carcinoma in clinical outliers

  Whole-exome sequencing dataset for the Australian Ovarian Cancer Study (AOCS) and The Jikei University School of Medicine (JIKEI) ovarian clear cell carcinoma (OCCC) clinical outliers project, representing 10 donors. Although OCCC are commonly resistant to platinum based chemotherapy, good clinical outcomes are observed in a subset of patients. Exome sequencing was performed in 10 patients who had either unusually long survival (N=5) or had a very short time to progression (N=5).

  Study EGAS00001004248

• Chemotherapy accelerates genomic aging of normal blood in children treated for cancer

  Whole genome sequencing (WGS) data obtained from clonally expanded hematopoietic stem and progenitor cells (HSPCs) from pediatric cancer patients before and after therapy exposure. In addition, WGS data of cord-blood derived HSPCs clones exposed to various chemotherapeutics and radiation was obtained.

  Study EGAS00001005141

• Molecular origins of mpMRI visibility

  Multiparametric magnetic resonance imaging (mpMRI) has transformed the landscape of prostate cancer (PCa) management. Prostate Imaging Reporting and Data System (PI-RADSv2) scores reflect function and correlate phenotypic features with tumor aggressiveness, is an independent predictor of biochemical recurrence, and may distinguish low-risk tumors requiring no treatment from high-risk tumors requiring aggressive management. We hypothesize that differences in functional mpMRI of prostate tumors reflect the genetic and epigenetic heterogeneity of PCa. We profiled the genomes and transcriptomes of 40 Gleason score 3+4 tumors, of which 20 tumors were mpMRI invisible (not PI-RADSv2 3-5) and 20 tumors were visible (PI-RADSv2 5). Genomes of visible tumors were more unstable than those of invisible tumors. We identified 62 enriched transcripts, including numerous snoRNAs, Relaxin 1 and SCHLAP1, in visible tumors. These data suggest a confluence of aggressive pathological and microenvironmental phenomenon in PI-RADSv2 5 tumors reminiscent of nimbosus, while linking the molecular profiles of tumor aggressiveness with their functional features on mpMRI.

  Study EGAS00001003179

• Targeted sequencing of paired tumour/blood of 34 T1 stage bladder cancer patients

  Stage T1 bladder cancer presents a high risk of progression and requires improved understanding. In continuation of our whole-exome sequencing study on this subtype of the disease, we carried out this targeted paired tumour/blood sequencing study including 34 T1 stage bladder cancer patients. Agilent’s SureDesign tool was used to design a 1.133 Mb SureSelect custom capture for all coding exons of the 140 selected candidate genes.

  Study EGAS00001005767

• Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer

  Mismatch repair deficient colorectal cancers have high mutation loads and many respond to immune checkpoint-inhibitors. We investigated how genetic and immune landscapes co-evolve in these tumors. All cases had high truncal mutation loads. Driver aberrations showed a clear hierarchy despite pervasive intratumor heterogeneity: Those in WNT/βCatenin, mitogen-activated protein kinase and TGFβ receptor family genes were almost always truncal. Immune evasion drivers were predominantly subclonal and showed parallel evolution. Pan-tumor evolution, subclonal evolution, and evolutionary stasis of genetic immune evasion drivers defined three MMRd CRC subtypes with distinct T-cell infiltrates. These immune evasion drivers have been implicated in checkpoint-inhibitor resistance. Clonality and subtype assessments are hence critical for predictive immunotherapy biomarker development. Cancer cell PD-L1 expression was conditional on loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and likely contributes to the high recurrence risk of MMRd CRCs with impaired CDX2 expression.

  Study EGAS00001005769

• arrayCGH for copy number profiling on tumor DNA from pediatric cancer tissue samples

  This dataset contains arrayCGH (HumanCytoSNP 850k and HumanCytoSNP v12.1) data from tumor DNA samples of various pediatric cancer entities. Files are provided in IDAT format and as text files processed with GenomeStudio 2.0.

  Study EGAS00001005197