A Multidisciplinary Biospecimen Bank of Renal Cell Carcinomas Compatible with Discovery Platforms at Mayo Clinic, Scottsdale, Arizona

<div><p>To address the need to study frozen clinical specimens using next-generation RNA, DNA, chromatin immunoprecipitation (ChIP) sequencing and protein analyses, we developed a biobank work flow to prospectively collect biospecimens from patients with renal cell carcinoma (RCC). We describe our standard operating procedures and work flow to annotate pathologic results and clinical outcomes. We report quality control outcomes and nucleic acid yields of our RCC submissions (N=16) to The Cancer Genome Atlas (TCGA) project, as well as newer discovery platforms, by describing mass spectrometry analysis of albumin oxidation in plasma and 6 ChIP sequencing libraries generated from nephrectomy specimens after histone H3 lysine 36 trimethylation (H3K36me3) immunoprecipitation. From June 1, 2010, through January 1, 2013, we enrolled 328 patients with RCC. Our mean (SD) TCGA RNA integrity numbers (RINs) were 8.1 (0.8) for papillary RCC, with a 12.5% overall rate of sample disqualification for RIN <7. Banked plasma had significantly less albumin oxidation (by mass spectrometry analysis) than plasma kept at 25°C (<i>P</i><.001). For ChIP sequencing, the FastQC score for average read quality was at least 30 for 91% to 95% of paired-end reads. In parallel, we analyzed frozen tissue by RNA sequencing; after genome alignment, only 0.2% to 0.4% of total reads failed the default quality check steps of Bowtie2, which was comparable to the disqualification ratio (0.1%) of the 786-O RCC cell line that was prepared under optimal RNA isolation conditions. The overall correlation coefficients for gene expression between Mayo Clinic vs TCGA tissues ranged from 0.75 to 0.82. These data support the generation of high-quality nucleic acids for genomic analyses from banked RCC. Importantly, the protocol does not interfere with routine clinical care. Collections over defined time points during disease treatment further enhance collaborative efforts to integrate genomic information with outcomes.</p></div

Comparison of Mapped Reads Between the Mayo Clinic and TCGA Nephrectomy Samples.

<p>Abbreviation: TCGA, The Cancer Genome Atlas.</p><p>Comparison of Mapped Reads Between the Mayo Clinic and TCGA Nephrectomy Samples.</p

Quality Assessment of Chromatin Immunoprecipitation Coupled With High-throughput Sequkencing.

<p>A, First end-read and, B, second end-read average quality score per base pair (bp) position assessment using FastQC. Higher scores correspond to better base calls. C, Box plots of enrichment of H3K36me3 immunoprecipitation (IP; red) over the matched control input library (Input; green). The human genome was split into 500-bp nonoverlapping windows, and the number of mapped pairs per window was calculated using BEDTools and normalized to a library size of 10 million uniquely mapped reads. The plots represent the top 5% of the 500-bp windows with the highe st counts in IP and the corresponding windows in input. D, Gene-body coverage by H3K36me3-binding sites. H3K36me3-binding sites identified by SICER (Spatial Clustering for Identification of ChIP-Enriched Regions) were intersected with gene coordinates to calculate the gene-body coverage (y-axis). On the x-axis, 1 to 22 represents chromosomes 1 to 22; 23 represents the X chromosome; and 24 represents the Y chromosome. ccRCC1 indicates clear cell renal cell carcinoma 1; ccRCC2, clear cell renal cell carcinoma 2; ccRCC3, clear cell renal cell carcinoma 3; Uninv., uninvolved.</p

Quality Assessment of Chromatin Immunoprecipitation Coupled With High-throughput Sequkencing.

<p>A, First end-read and, B, second end-read average quality score per base pair (bp) position assessment using FastQC. Higher scores correspond to better base calls. C, Box plots of enrichment of H3K36me3 immunoprecipitation (IP; red) over the matched control input library (Input; green). The human genome was split into 500-bp nonoverlapping windows, and the number of mapped pairs per window was calculated using BEDTools and normalized to a library size of 10 million uniquely mapped reads. The plots represent the top 5% of the 500-bp windows with the highe st counts in IP and the corresponding windows in input. D, Gene-body coverage by H3K36me3-binding sites. H3K36me3-binding sites identified by SICER (Spatial Clustering for Identification of ChIP-Enriched Regions) were intersected with gene coordinates to calculate the gene-body coverage (y-axis). On the x-axis, 1 to 22 represents chromosomes 1 to 22; 23 represents the X chromosome; and 24 represents the Y chromosome. ccRCC1 indicates clear cell renal cell carcinoma 1; ccRCC2, clear cell renal cell carcinoma 2; ccRCC3, clear cell renal cell carcinoma 3; Uninv., uninvolved.</p

Expression Profiles and Correlation of Genes in the Mayo Clinic and TCGA Cohorts.

<p>A, Expression of the most abundant genes in Mayo Clinic tissues. Expression levels of the 30 most-abundant genes in frozen tumors (upper 6 bars) and TCGA kidney tumors (averaged from 553 samples) are shown in stacked bars, with percentages of total normalized counts. Reads for <i>TPT1</i> occupied up to 9.5% of total reads. B, Correlation of gene expression between the Mayo Clinic and TCGA kidney tumors. Normalized expression values of a representative Mayo Clinic tumor and TCGA kidney tumor samples (averaged from 553 samples) were compared. Genes in the boxed area have normalized expression values ≥128. ccRCC1 indicates clear cell renal cell carcinoma 1; ccRCC2, clear cell renal cell carcinoma 2; ccRCC3, clear cell renal cell carcinoma 3; TCGA, The Cancer Genome Atlas; Uninv, uninvolved.</p

Papillary Renal Cell Carcinoma Samples With Available Genomic Data from The Cancer Genome Atlas Data Portal^a.

<p>Abbreviations: ID, identifier; RPPA, reverse phase protein array; SNP, single nucleotide polymorphism; TCGA, The Cancer Genome Atlas.</p><p>^a Entries with checkmarks indicate availability as of 4/22/15 from TCGA Data Portal.</p><p>Papillary Renal Cell Carcinoma Samples With Available Genomic Data from The Cancer Genome Atlas Data Portal<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132831#t003fn002" target="_blank">^a</a>.</p

Papillary Renal Cell Carcinoma (RCC) Samples Submitted to The Cancer Genome Atlas (TCGA).

<p>A, Representative mirror images of top slides sent for independent pathology review to the Biospecimen Core Resource of TCGA. H&E indicates hematoxylin-eosin stain; original magnification ×10 (left) and ×40 (right). B, Scatterplot of TCGA quality assessment of RNA processed from papillary RCC specimens. The black horizontal dotted line represents the mean, with the vertical error bars representing the SD. RNA integrity numbers (RINs) were assessed by TCGA RNA bioanalyzer. Two samples with RIN <7 were disqualified.</p

Albumin Oxidation (S-Cysteinylation) Observed in the Banked Renal Cell Carcinoma (RCC) Plasma Samples.

<p>Control plasma was freshly collected from a nominally healthy donor, and albumin oxidation levels were observed at 25°C Significantly less albumin oxidation was observed in samples from patients with RCC compared with albumin in plasma kept at 25°C for ≥17.5 hours (<i>P</i><.001; Mann-Whitney U test). (Data from Borges CR et al [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132831#pone.0132831.ref012" target="_blank">12</a>].)</p

Chromatin Immunoprecipitation Quantitative Polymerase Chain Reaction Analysis of Histone H3 Lysine 36 Trimethylation (H3K36me3).

<p>H3K36me3 is enriched at the actin locus, but not in the intergenic region, in both tumor and uninvolved kidney. Error bars represent SD as determined from duplicate experiments. ccRCC indicates clear cell renal cell carcinoma.</p

Multidisciplinary Genitourinary Diseases Biospecimen Bank Work Flow.

<p>Left, Standard operating procedures involved obtaining patient consent, prospective specimen processing, clinical data collection, and scheduling of future collections associated with standard-of-care blood draws. Right, The pathology work flow for banking frozen tissue. (Data from Pena-Llopis S, Brugarolas J. Simultaneous isolation of high-quality DNA, RNA, miRNA and proteins from tissues for genomic applications. Nat Protoc. 2013 Nov;8[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132831#pone.0132831.ref011" target="_blank">11</a>]:2240–55. Epub 2013 Oct 17.) A portion of the tissue is frozen (A) and the rest is embedded in paraffin (C). A standardized cube of tissue (B) is cut and frozen for future genomic analyses, with parallel mirror slides representing (A) and (C) for assessment of cellularity as an addendum in the pathology synoptic report. Either slide is sent for independent pathology review to the Biospecimen Core Resource of The Cancer Genome Atlas. FFPE, indicates formalin-fixed, paraffin-embedded; lab, laboratory; preop, preoperative; REDCap, Research Electronic Data Capture; RLIMS, Research and Laboratory Information Management System.</p