Project description:Over 20 million archival tissue samples are stored annually in the United States as formalin-fixed, paraffin-embedded (FFPE) tissue blocks, but only recently has whole-genome expression profiling from these samples become technically feasible. Here, we introduce novel general methods for assessing, summarizing, and visualizing expression data quality from archival samples. We validated these methods in technical study of 144 clinical breast cancer and autopsy samples and in an overview of all current publicly available FFPE whole-genome expression data. We additionally performed a case study incorporating over 1,000 colorectal cancer (CRC) samples collected from patients across the United States over a period of more than 25 years, integrating clinicopathological information, tumor molecular data, and archival tissue gene expression on an unparalleled scale. Both large-scale clinical studies presented a much greater range of data quality than previous smaller studies, emphasizing the need for rigorous quality control in translational applications of archival tissue gene expression profiling.
Project description:The BESPOKE CRC study will prospectively enroll patients who have undergone surgery for stage I to IV colorectal cancer (CRC) and who have residual formalin-fixed paraffin-embedded (FFPE) tissue available will provide FFPE and whole blood samples. Patients will receive SIGNATERA test results and may be recommended for post-operative systemic therapy or observation by their treating clinician. Patients will be followed for up to two years with periodic whole blood collection. The study also has a control arm that will consist of matched Stage I to IV CRC cases that have a minimum of least 2 years clinical follow-up data.
Project description:Background and Aims Formalin-fixed, paraffin-embedded (FFPE) tissue is the most commonly available form of archived clinical specimens, which are often stored as thin sections on glass slides. RNA isolated from such archived section (AS) of FFPE tissue is more degraded compared to freshly cut (FC) FFPE section because of prolonged air exposure. In this study, we evaluated performance of transcriptome profiling-based disease classification in AS-FFPE tissue. Methods Genome-wide gene-expression profiles of AS-FFPE tissues of 83 hepatocellular carcinoma (HCC) and 47 liver cirrhosis samples were generated by using whole-genome DASL assay (Illumina), and compared with the profiles previously produced by using FC tissue sections from the same FFPE blocks. Quality of the profiles and performance of gene signature-based class prediction were systematically evaluated. Results RNA quality and assay reproducibility of AS-FFPE RNA were comparable to intermediate ~ poor quality FC-FFPE samples (R2 as high as 0.93). Gene-expression signal was detected in lower number of probes in AS FFPE samples compared to FC-FFPE samples (proportion of probes with present signal (%P-call): 10%~60% and 70%~90% in AS- and FC-FFPE profiles, respectively). Based on %P-call quality threshold of 20%, 64/88 (77%) HCC and 37/48 (77%) liver profiles were judged as having relatively good quality data with comparable inter-sample correlation. Inter-sample correlation coefficient, as a measure to detect outlier profiles due to poor RNA quality, was also lower in AS-FFPE (0.4~0.9) compared to FC-FFPE (0.6~1.0). In the genome-wide profiling analysis, previously identified molecular subclasses of HCC tumors were reproduced in 67/83 (81%) samples, which was improved to 43/48 (90%) samples when we focused on statistically confident predictions (p<0.05). A 186-gene prognostic signature in liver cirrhosis was reproduced in 32/47 (68%) samples, which was slightly improved to 11/16 (69%) when focused on statistically significant predictions. Conclusions We observed decay of genome-wide transcriptional profiles in AS-FFPE tissues in quantitative manner. However, disease classification was still possible, which suggests potential of AS-FFPE material for clinical diagnosis and prognosis.
Project description:Defining molecular features that can predict the response to chemotherapy for stage II-III colorectal cancer (CRC) patients remains challenging in cancer research. Most available clinical samples are Formalin-Fixed and Paraffin-Embedded (FFPE). Affymetrix GeneChip® Human Transcriptome Array 2.0 (HTA) is one platform marketed for high-throughput gene expression profiling for FFPE tissue samples. In this study, we analyzed the whole transcriptom gene expression of 156 CRC patient samples measured by this platform to identify biomarkers predicting the response to chemotherapy for stage II-III CRC patients.
Project description:Transcriptional profiling of intestinal tissue samples from germ-free and conventionally raised mice which are either wild-type or Myd88-/-