Targeted high throughput sequencing in clinical cancer Settings: formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity

Abstract

BackgroundMassively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings.MethodsUsing identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.ResultsWe show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance.Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations.ConclusionsThe application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - in the long term - result in a more reliable prediction of individual cancer therapies.

Comparison of Clinical Targeted Next-Generation Sequence Data from Formalin-Fixed and Fresh-Frozen Tissue Specimens

“…A recent study by Forshew et al 18 found a similar background frequency of nonreference base changes in 47 FFPE samples enriched by multiplex PCR. In another study, Kerick et al 21 reported a false-positive rate of 0.98% for SNV calls from low coverage (Â20) NGS data from FFPE tissue; the authors note, however, that the false-positive rate can be reduced with increased (> Â80) coverage. Although we detected differences in the spectrum of base changes in our FFPE data, including an increase in the frequency of transitions, the differences were small (0.041% of high-quality discrepancies in FFPE versus 0.035% in frozen samples), the overall frequency of discrepancies was not increased between sample A: Percentage of mapped, on-target, and unique reads for a single surgical resection specimen that was snap frozen (red) or subjected to 24-hour (light purple), 48-hour (medium purple), or 72-hour (dark purple) formalin fixation.…”

“…6,18e21 Prior work has suggested that deamination and other damage caused by fixation could account for as many as 1% of the SNV calls in low-coverage sequence data (eg, 20-fold coverage) and may skew the transition to transversion ratio in sequence data from FFPE tissue samples. 19,21 Although these studies have limitations, such as the use of cell lines and unrelated specimens as controls rather than paired fresh tissue, they raise the possibility that damage caused by fixation could result in erroneous clinical test results.…”

Evaluating the repair of DNA derived from formalin-fixed paraffin-embedded tissues prior to genomic profiling by SNP–CGH analysis

“…While the power of these approaches is being realized for FF tumors, [11][12][13] there are currently few studies to have realized this potential for FFPE samples, owing to the inherent problems of working with chemically modified and damaged DNA, the requirements for larger amounts of genomic DNA and/or high depth of sequencing coverage to minimize ambiguous read mapping and the subsequent added bioinformatics challenges that this brings. 28,[32][33][34][35] Large consortia such as the ICGC and TCGA also continue to analyze tumor genomes by SNP arrays as an important support tool for CNA detection and assessment of tumor cellularity, [11][12][13] and so for these reasons it remains important to optimize CGH platforms for whole-genome CNA detection of FFPE tumor samples.…”

Next-generation sequencing in the clinic: Promises and challenges

“…Another strategy is to increase sequencing depth. In a whole-exome sequencing study, a high rate of discordant loci as false positives in FFPE tissues compared to paired snap-frozen tissues was detected at 20× coverage [187]. While false positives were reduced but still present at 40× coverage, no discordance was observed at 80× coverage.…”

“…While false positives were reduced but still present at 40× coverage, no discordance was observed at 80× coverage. Hence, it is seen that accurate detection of somatic mutations in FFPE tumor samples can be achieved at high coverages, especially using targeted sequencing approaches [187,188].…”