11770 results for "cancer rna-seq"

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• Molecular evolution of metastatic clear cell renal cell carcinoma progressing under tyrosine kinase inhibitor therapy (HIPO-045)

  Background:Acquired resistance to targeted drugs is largely due to intra-tumor molecular heterogeneity and clonal selection. Objective:The objective of this study was to determine molecular alterations and mediating resistant mechanisms and to suggest additional treatment options.Design, Setting, and Participants:Four patients were enrolled into the MORE (Molecular Renal Cancer Evolution) trial. We investigated the mutational spectra of metastatic clear cell renal cell carcinoma (ccRCC) at baseline and compared them to those upon clonal evolution at progression on systemic therapy with tyrosine kinase inhibitors.Outcome Measurements:DNA was isolated from tumor tissues after surgery, metastasis biopsies after progression on sunitinib or axitinib, and subjected to whole-exome sequencing (WES). In addition, the exomes of circulating tumor DNA (ctDNA) from two patients were sequenced at baseline and at progression.Results and Limitations:Our data provide evidence for clonal evolution and various acquired resistance mechanisms of ccRCC with subclonal mutations in FLT4, MTOR, ITGA3/5, SETD2, and VHL on metastatic progression. The limited number of shared mutations in tissue and plasma biopsies indicates that both sources provide complementary information, possibly due to mutations present in metastatic lesions which were not amenable to tissue sampling but are represented in the ctDNA. Conclusion:Acquired resistance to targeted therapies in metastatic ccRCC is due to intra-tumor heterogeneity and clonal evolution. Larger patient cohorts have to be studied to estimate the benefit of WES from biopsies and ctDNA for therapy decision in metastatic ccRCC.Patient Summary:We analyzed the molecular profiles of ccRCC patients in primary tissues and metastatic tissues upon progression on tyrosine kinase inhibitor therapy. Clinically relevant mutations upon progression were detected in the metastatic sites of all of four patients, suggesting that it might be possible to derive therapies based on sequencing the metastases.?HIPO-045

  Study EGAS00001001861

• Ultra-Fast Patient-Derived Xenografts Identify Functional and Spatial Tumour Heterogeneities that Drive Therapeutic Resistance

  Treatment of patients with advanced cancers increasingly relies on agents targeting specific molecular or cellular aberrations. These expensive therapies often fail because of pre-existing drug resistance. Intra-tumoural molecular and micro-environmental heterogeneity resistance can create resistance in one or more subclones of a tumour, leading to spatio-functional heterogeneity. We created a rapid approach for quantifying tumour functional phenotypes based on tumour-implantation into the chorioallantoic membrane of chick embryos. We apply this technique to 43 separate biopsies from 6 patients with renal cell carcinoma (RCC) with 36 replicates per biopsy, achieving a 93.6% engraftment rate (1449/1548). Challenging these models with sunitinib, an anti-angiogenic therapy frequently used in RCC allowed us to quantify spatio-functional heterogeneity in individual patients. Prediction of de novo drug resistance in advanced cancer patients would facilitate precision medicine by tailoring systemic therapies and improve clinical trial design outcome measures. We describe a patient-derived xenograft platform where fresh patient tumour samples are implanted into the chorioallantoic membrane (CAM) of chick embryos at high engraftment efficiencies, permitting large scale “tumour avatar” studies to guide the selection of drugs and to predict clinical drug resistance outcomes in renal cell carcinoma (RCC) patients. Applying this “tumour avatar” model in a co-clinical trial on RCC patients, we observe intra-tumoural functional heterogeneity with sunitinib treatment, revealing the presence of drug-resistant clones prior to the initiation of therapy. Multi-regional exome Matched DNA sequencing of the primary tumour and metastases revealed DNA mutational signatures associated with sunitinib resistance at baseline and after treatment. These These studies demonstrate a rapid and affordable method of findings confirm the existence of genetic and surveying functional tumour heterogeneities heterogeneity.

  Study EGAS00001002627

• Exome sequencing from cfDNA blood samples. 159 samples at 2x101bp Illumina reads in Fastq format.

  Differential presence of exons (DPE) by next generation sequencing (NGS) is a method of interpretation of whole exome sequencing. This method has been proposed to design a predictive and diagnostic algorithm with clinical value in plasma from patients bearing colorectal cancer (CRC). The aim of the present study was to determine a common exonic signature to discriminate between different clinical pictures, such as non-metastatic, metastatic and non-disease (healthy), using a sustainable and novel technology in liquid biopsy. Through DPE analysis, we determined the differences in DNA exon levels circulating in plasma between patients bearing CRC vs. healthy, patients bearing CRC metastasis vs. non-metastatic and patients bearing CRC metastasis vs. healthy comparisons. We identified a set of 510 exons (469 up and 41 down) whose differential presence in plasma allowed us to group and classify between the three cohorts. Random forest classification (machine learning) was performed and an estimated out-of-bag (OOB) error rate of 35.9% was obtained and the predictive model had an accuracy of 75% with a confidence interval (CI) of 56.6-88.5. In conclusion, the DPE analysis allowed us to discriminate between different patho-physiological status such as metastatic, non-metastatic and healthy donors. In addition, this analysis allowed us to obtain very significant values with respect to previous published results, since we increased the number of samples in our study. These results suggest that circulating DNA in patient’s plasma may be actively released by cells and may be involved in intercellular communication and, therefore, may play a pivotal role in malignant transformation (genometastasis).

  Study EGAS00001006656

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• ExomeSeq Neoantigen Immunogenicity Landscapes

  Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.

  Study EGAS00001007508

• RNASeq Neoantigen Immunogenicity Landscape

  Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.

  Study EGAS00001007509

• Multi-Layered Molecular Profiling Informs the Diagnosis and Targeted Therapy of Desmoplastic Small Round Cell Tumor

  Desmoplastic small round cell tumor (DSRCT) is an ultra-rare soft tissue sarcoma with dismal prognosis and limited therapeutic options. Here, we identified individual therapeutic targets in a cohort of 30 DSRCT patients by use of multilayered molecular profiling (genomic, transcriptomic, and (phospho-)proteomic analyses) within the DKFZ NCT DKTK MASTER program. 28 of the 30 patients received at least one personalized treatment recommendation. In line with the observation that DSRCTs are an entity with a low mutational load, most of the treatment recommendations were based on target gene or -protein expression. 13 patients received a recommended therapy, resulting in four partial responses, four stable diseases, and five progressive diseases. Eight of 13 patients received the multi tyrosine kinase inhibitor pazopanib, with mixed response. Based on high ERBB2 expression levels, two patients received the antibody drug conjugate trastuzumab deruxtecan (T-DXd), showed exceptional, long-lasting responses and are currently (8/2024) still on treatment and progression-free. We detected high ERBB2 protein expression in all DSRCT samples with proteome data (n = 9), which suggests that ERBB2 may be a particularly useful therapeutic target for DSRCT patients. For one of the two exceptional responders we did not detect a substantial ERBB2/HER2 overexpression, which may indicate that T-DXd could also be efficacious in DSRCT patients with low levels of HER2, as also described for breast cancer patients. In conclusion, multi-omic molecular profiling revealed personalized therapeutic targets in patients with DSRCT with HER2 targeting, with T-DXd as a promising therapeutic option for this ultra-rare and difficult-to-treat tumor entity.

  Study EGAS00001007934

• Distinct evolutionary trajectories of primary high grade serous ovarian cancers revealed through spatial mutational profiling

  High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to emergence of treatment-resistant sub-clones. We sought to measure the degree of genomic diversity within primary, untreated HGSC to examine the natural state of tumor evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on thirty-one spatially and temporally separated HGSC tumor specimens (six patients) including ovarian masses, distant metastases, and fallopian tube lesions. We found widespread intra-tumoral variation in mutation, copy number, and gene expression profiles, with key driver alterations in genes present in only a subset of samples (e.g. PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range: 10.2% to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology with common etiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating diversity arises at early stages of tumorigenesis. Our results reveal that HGSC exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug resistance mechanisms.

  Study EGAS00001000547

• Prader-Willi Syndrome and Early-onset Morbid Obesity Natural History Protocol

  This observational study will involve the comprehensive assessment of the medical, behavioral and nutritional history and the clinical features of individuals with Prader-Willi syndrome and individuals with features of PWS-like/EMO. A blood sample will be obtained from the participants in order to create a DNA and RNA repository. In those PWS participants with a known deletion a blood sample will be collected for DNA in order to perform array comparative genome hybridization (aCGH) microarray or Methylation-Specific Multiplex Ligation-dependent Probe Amplification (MS-MLPA) studies to characterize the extent of the deletion. DNA samples will be sent to the Consortium Center at Baylor College of Medicine for the performance of the aCGH studies and to either Dr. Driscoll or Dr. Butler lab for MS-MLPA analysis. No drugs or treatments will be administered through this protocol. Our goal is to enroll as many participants as possible over a 8 year period. Currently we have enrolled 297 total subjects of which 265 have PWS and 32 EMO. Our original goal was to have enrolled over the first 5 years a clinical database of 200 individuals with PWS and 100 with EMO. We have exceeded expectations in PWS enrollment, but have fallen short in the enrollment of individuals with EMO. Therefore, we would like to reset our goals. We now propose to have an enrollment goal of 400 total subjects of which 350 will have PWS and 50 will have EMO. Eligible participants will be initially enrolled in the natural history study from the 4 clinic sites currently involved with PWS (University of Florida, Kansas University Medical Center, Vanderbilt University and University of California at Irvine). Participants assessed will serve to provide a background of information and a willing cohort for future interventional studies. All participants will have had standard genetic testing at a commercial laboratory prior to entry into the study. The PWS participants will be classified into one of the 3 main molecular classes (deletion, UPD and ID). The EMO participants will have had laboratory testing ruling out PWS and chromosomal aneuploidy (e.g., trisomy 21, Klinefelter syndrome, etc.). Going forward we feel it is important that all newly recruited EMO subjects have an aCGH as part of their evaluation so we can identify those with discrete deletions, duplications or copy number variants (CNV) and compare them to those without aCGH abnormalities. The participants will be assessed annually (0-3 years of age) or biennially (> 3 years) in the Clinical Research Center (or equivalent facility) using standardized protocol including photographs for documentation purposes to compare the evolution of the clinical phenotype.

  Study phs000575

• Kids First: Genomic Etiologies of CHARGE Syndrome, Related Conditions and Structural Anomalies

  Developmental disorders with structural birth defects account for the majority of morbidity and mortality in children's hospitals, and the genetic bases of many clinical phenotypes remain unknown. Genetic testing for individuals with structural malformations has uncovered the basis of many such birth defects; however, many more cases remain unsolved, posing challenges for diagnosis, treatment, and prevention. Multiple anomaly conditions are particularly challenging to diagnose, since they often present with unique combinations of clinical features that vary widely between affected individuals, even in the same family. CHARGE Syndrome (Coloboma of the eye, Heart Defects, Atresia of the choanae, Retardation of growth and development, Genital abnormalities including pubertal delay and infertility, Ear abnormalities with deafness and vestibular disorders) is a multiple anomaly condition that affects a wide variety of organ systems. CHARGE Syndrome is caused in most cases by monoallelic pathogenic variants in CHD7, the gene encoding ATP-dependent helicase chromodomain DNA binding protein 7. Both de novo and inherited variants in CHD7 have been reported in CHARGE, and a growing number of families present with individuals who test positive for a pathogenic CHD7 variant yet exhibit only mild features. Similarly, individuals with CHARGE Syndrome often exhibit broad variability and reduced penetrance of clinical features, consistent with pleiotropic roles for CHD7 during development and/or additional genetic contributors or modifying alleles. Recent work has also implicated RERE, KMT2D, EP300, and PUF60 in having a role in CHARGE Syndrome.We hypothesize that (1) some cases of CHARGE are due to other genetic etiologies including oligogenicity, and (2) genetic modifiers contribute to the broad clinical variability and reduced penetrance of CHARGE features. To address these hypotheses, we have generated a cohort of 223 deeply clinically phenotyped individuals with CHARGE Syndrome and related disorders and structural anomalies who tested negative by chromosomal microarray, single gene sequencing, next generation panel sequencing, or exome sequencing. These individuals exhibit clinical CHARGE-like features including structural birth defects affecting craniofacial, ocular, neurosensory, brain, heart, mediastinal, renal, genitourinary, and skeletal organs. Our cohort includes these 223 individuals as well as affected and unaffected family members who consented to clinical and research genetic testing and donated blood samples for DNA and RNA isolation and sequencing. Building on this valuable cohort, we propose to use exome and genome sequencing to identify novel genetic etiologies of CHARGE and related developmental disorders for which alternative genetic tests have been inconclusive. Identification of novel pathogenic genetic variants and contributing modifier alleles within the coding and non-coding portion of the genome of these individuals will improve genetic diagnosis and provide important insights toward understanding the developmental mechanisms of structural birth defects.

  Study phs002592