Project description:This study is a repository for all RNAseq data obtained from High Throuput Seqeuncing of Patient Derived Xenograft models of Breast Cancer studied at the Baylor College of Medicine Breast Center.
Project description:<p>A large proportion of common cancers affecting patients around the world have been selected for comprehensive cancer genome studies. Further efforts will be needed to tackle the remaining tumor types, including the rare forms of cancers. Although rare, these cancers tend to be more aggressive and fast growing with an early recurrence following initial chemotherapy and poor prognosis. Besides, patients diagnosed with rare cancers may have difficulty finding a physician knowledgeable in treating their type of cancer. While sample collection is a major challenge, the integrated genomic analyses would identify novel causative genes in these rare cancers, shed new light on the biology of the rare cancers, as well as guide novel targeted cancer therapies. Through efficient collaboration, the Human Genome Sequencing Center (HGSC) at Baylor College of Medicine (BCM) has collected/is expected to collect 20 different types of rare cancers, 15-30 cases each. Whole-exome sequencing and high-resolution SNP array analysis were/will be performed for all cases and whole-genome sequencing was designed for a selected subset of the cases.</p> <p><b>The Rare Cancer Tumors Cohort is utilized in the following dbGaP sub-studies.</b> To view genotypes, other molecular data, and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" box located on the right hand side of this top-level study page <a href="./study.cgi?study_id=phs000725">phs000725</a> Rare Cancer Tumors Cohort. <ul> <li><a href="./study.cgi?study_id=phs000754">phs000754</a> Intracranial Germ Cell Tumors</li> <li><a href="./study.cgi?study_id=phs000861">phs000861</a> Craniopharyngioma Tumors</li> <li><a href="./study.cgi?study_id=phs000859">phs000859</a> Sezary Syndrome Genomic Analysis</li> </ul> </p>
Project description:We applied DNA content flow cytometry to ten patient derived triple negative breast cancer (TNBC) xenografts (PDXs) from the Baylor College of Medicine (BCM). We interrogated purified sorted tumor fractions from each sample with whole genome copy number variant (CNV) analyses. These identified a variety of somatic genomic lesions that are common in TNBC including three cases with 9p24.1 amplification targeting PD-L1-PDL2 and JAK2 (PDJ amplicon) and recurring focal amplicons of oncogenic drivers found commonly in the TNBC PDXs including MYC and EGFR. In addition, homozygous deletions of known tumor suppressor genes including PTEN, CDKN2A, RB1, and BRCA2, and unique targets such as CUX1 and FYN were identified. Of the three PDJ-positive amplified PDXs, 2/3 two had focal MYC amplifications and 1/3 had a RB1 homozygous deletion.
Project description:The purpose of this study was to search for microgravity-sensitive genes, specifically for apoptotic genes influenced by the microgravity environment and other genes related to immune response. Experiment Overall Design: Two-group design with paired samples, i.e., one 1G and one MMG culture came from the same donor. Therefore, 6 samples came from 3 different donors. Experiment Overall Design: Donor 1 :GSM96146,GSM96147 Experiment Overall Design: Donor 2: GSM96148, GSM96149 Experiment Overall Design: Donor 3: GSM96150,GSM96151 Experiment Overall Design: Total RNA was submitted to, and then labeled, hybridized and data generated by the Baylor College Medicine Microarray Core Facility (333E One Baylor Plaza, Houston, TX 77030).
Project description:Goal: To define the digital transcriptome of three breast cancer subtypes (TNBC, Non-TNBC, and HER2-positive) using RNA-sequencing technology. To elucidate differentially expressed known and novel transcripts, alternatively spliced genes and differential isoforms and lastly expressed variants in our dataset. Method: Dr. Suzanne Fuqua (Baylor College of Medicine) provided the human breast cancer tissue RNA samples. All of the human samples were used in accordance with the IRB procedures of Baylor College of Medicine. The breast tumour types, TNBC, Non-TNBC and HER2-positive, were classified on the basis of immunohistochemical and RT-qPCR classification. Results: Comparative transcriptomic analyses elucidated differentially expressed transcripts between the three breast cancer groups, identifying several new modulators of breast cancer. We discovered subtype specific differentially spliced genes and splice isoforms not previously recognized in human transcriptome. Further, we showed that exon skip and intron retention are predominant splice events in breast cancer. In addition, we found that differential expression of primary transcripts and promoter switching are significantly deregulated in breast cancer compared to normal breast. We also report novel expressed variants, allelic prevalence and abundance, and coexpression with other variation, and splicing signatures. Additionally we describe novel SNPs and INDELs in cancer relevant genes with no prior reported association of point mutations with cancer
Project description:The below table includes a smaller list of data that was analyzed by dChip and filtered by pvalue such that a file with about 4600 genes was obtained, which allowed for ease of use from 40,000 genes. Experiment Overall Design: The total RNA was extracted from 2T3 pre-osteoblast cells exposed to static or simulated microgravity (Rotating Wall Vessel) conditions. The RNA was then sent to Affymetrix microarray core facility at Baylor College of Medicine (Houston, TX) for microarray analysis.
Project description:We utilized non-transformed, human pancreatic ductal epithelial (HPDE) cells, previously engineered with the E6 and E7 proteins of the HPV16 virus to emulate loss of p53 and inactivation of the Rb pathway, respectively. Given the frequent activation of KRAS (>90% PDAC tumors) and its early role in pancreatic neoplasia, we sought to engineer HPDE cells containing KRASG12D to provide the appropriate context in which to screen for novel drivers that might represent KRAS effectors. The KRAS-induced transcription analysis was conducted using RNAs extracted from HPDE cells transduced with either control, wild-type KRAS or KRASG12D(pInducer) with or without DOX (100ng/ml) for 72 h, followed by hybridization of labeled cDNA onto Agilent arrays (Agilent G3 Human GE 8x60K) by the Baylor College of Medicine Genome Profiling Core Facility. multi-group comparison