Detection of ubiquitous and heterogeneous mutations in cell-free DNA from patients with early-stage non-small-cell lung cancer

BACKGROUND

The aim of this pilot study was to assess whether both ubiquitous and heterogeneous somatic mutations could be detected in cell-free DNA (cfDNA) from patients with early-stage non-small-cell lung cancer (NSCLC).

PATIENTS AND METHODS

Three stage I and one stage II primary NSCLC tumors were subjected to multiregion whole-exome sequencing (WES) and validated with AmpliSeq. A subset of ubiquitous and heterogeneous single-nucleotide variants (SNVs) were chosen. Multiplexed PCR using custom-designed primers, coupled with next-generation sequencing (mPCR-NGS), was used to detect these SNVs in both tumor DNA and cfDNA isolated from plasma obtained before surgical resection of the tumors. The limit of detection for each assay was determined using cfDNA from 48 presumed-normal healthy volunteers.

RESULTS

Tumor DNA and plasma-derived cfDNA was successfully amplified and sequenced for 37/50 (74%) SNVs using the mPCR-NGS method. Twenty-five (68%) were ubiquitous and 12 (32%) were heterogeneous SNVs. Variant detection by mPCR-NGS and WES-AmpliSeq in tumor tissue was well correlated (R(2) = 0.8722, P < 0.0001). Sixteen (43%) out of 37 SNVs were detected in cfDNA. Twelve of these were ubiquitous SNVs with a variant allele frequency (VAF) range of 0.15-23.25%, and four of these were heterogeneous SNVs with a VAF range of 0.28-1.71%. There was a statistically significant linear relationship between the VAFs for tumor and cfDNA (R(2) = 0.5144; P = 0.0018). For all four patients, at least two variants were detected in plasma. The estimated number of copies of variant DNA present in each sample ranged from 5 to 524. The average number of variant copies required for detection (VCRD) was 3.16 (range: 0.2-7.6 copies).

CONCLUSIONS

The mPCR-NGS method revealed intratumor heterogeneity in early-stage NSCLC tumors, and was able to detect both ubiquitous and heterogeneous SNVs in cfDNA. Further validation of mPCR-NGS in cfDNA is required to define its potential use in clinical practice.

Abstract PD01-08: Decoding the Transcriptional Landscape of Triple-Negative Breast Cancer Using Next-Generation Whole Transcriptome Sequencing

Background: Triple-negative breast cancer (TNBC) has been plagued by the absence of targeted therapies. Discovery of therapeutic targets in TNBC has in part, been hampered by an inadequate understanding of the transcriptional biology of the normal breast as an optimal comparator. Using next-generation sequencing, we embarked on a study to compare the transcriptomes of TNBC and normal breast to comprehensively identify novel targets by analyzing all full length transcripts expressed in these tissues.

Methods: Normal breast tissues from healthy pre-menopausal volunteers with no history of disease were procured from the Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center. To eliminate bias from stromal tissue, normal tissues were laser capture microdissected for ductal epithelium. cDNA libraries from 10 TNBC tumors and 10 normal breast tissues were sequenced on an Applied Biosystems (AB) SOLiD3 sequencer using 50bp fragment runs. For gene expression, mapping of reads to the genome was performed using the AB BioScope 1.2 Pipeline and outputs imported into Partek Genomics Suite for analysis. In Partek, mapped reads were cross-referenced against known genes from the UCSC database followed by statistical comparison of RPKM values for each gene between TNBC and normal. Dimensionality reduction analyses (PCA & Hierarchical clustering) and identification of Novel Transcribed Regions were also performed in Partek, whereas construction of gene networks was performed using Ingenuity Pathway Analysis. To identify gene fusions, partially mapped reads were interrogated utilizing a novel algorithm that searched for reads spanning exons from two different genes. Fusions that were supported by at least 3 reads (of which 2 had to be unique) were considered candidates and were subsequently validated. Results/Discussion: Sequencing produced 1.1 billion reads equaling 57.3GB of data of which 36.0GB (63%) mapped to the human genome. In comparing RPKM values between TNBC and Normal, we report 7140 RefSeq Genes, 22 pre-miRNAs, 109 lincRNA exons, and 15 ultraconserved regions that were differentially expressed between these tissues (FDR&lt;0.01). Biological interpretation of these results reveals upregulation of genes and miRNAs involved in DNA repair, angiogenesis, and inhibitors of Estrogen Receptor-alpha. Some previous drug targets (e.g. EGFR and c-kit) were not found to be upregulated here which may explain lack of clinical success to date. Conversely, PARP was significantly upregulated and early trial results suggest a strong signal for efficacy with inhibition of PARP. We also surveyed the genome for Novel Transcribed Regions (NTRs), defined as areas of significant transcription where no annotated gene is present. When comparing between TNBC and Normal, we report 6408 NTRs to be differentially expressed (FDR&lt;0.01). Lastly, when analyzing the dataset for gene fusions, we identified several gene fusions in the TNBC samples, though no individual fusion was present in more than one sample.

Conclusion: We report an extensive comparison of the transcriptomes of TNBC and normal ductal epithelium. We identified numerous genes previously unknown to be dysregulated in TNBC that can be utilized for therapeutic discovery.

Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr PD01-08.

Evolutionary expansion and specialization of the PDZ domains

PDZ domains are protein-protein interaction modules widely used to assemble membranous signaling complexes including those found in the neuronal synapse. PDZ-containing genes encoded in metazoan genomes vastly outnumber those in prokaryotes, plants, and fungi. By comparing 40 proteomes to track the evolutionary history of the PDZ domain, we observed that the variety of associations between PDZ and other domains expands greatly along the stem leading to metazoans and choanoflagellates. We asked whether the expansion of PDZ domains was due to random or specific sequence changes. Studying the sequence signatures of 58 PDZ lineages that are common to bilaterian animals, we showed that six common amino acid residues are able to classify 96% of PDZ domains to their correct evolutionary lineage. In PDZ domain-ligand cocrystals, four of these "classifying positions" lie in direct contact with the -1 and -3 residues of the ligand. This suggests coevolution of the more flexible regions of the binding interaction as a central mechanism of specialization inherent within the PDZ domain. To identify these positions, we devised two independent algorithms--a metric termed within-clade entropy (WCE) and an average mutual information (AvgMI) score--that both reached similar results. Extending these tools to the choanoflagellate, Monosiga brevicollis, we compared its PDZ domains with their putative metazoan orthologs. Interestingly, the M. brevicollis genes lack conservation at the classifying positions suggesting dissociation between domain organization in multidomain proteins and specific changes within the PDZ domain.