Genomic dissection and mutation-specific target discovery for breast cancer PIK3CA hotspot mutations.

BACKGROUND: Recent advancements in high-throughput genomics and targeted therapies have provided tremendous potential to identify and therapeutically target distinct mutations associated with cancers. However, to date the majority of targeted therapies are used to treat all functional mutations within the same gene, regardless of affected codon or phenotype. RESULTS: In this study, we developed a functional genomic analysis workflow with a unique isogenic cell line panel bearing two distinct hotspot PIK3CA mutations, E545K and H1047R, to accurately identify targetable differences between mutations within the same gene. We performed RNA-seq and ATAC-seq and identified distinct transcriptomic and epigenomic differences associated with each PIK3CA hotspot mutation. We used this data to curate a select CRISPR knock out screen to identify mutation-specific gene pathway vulnerabilities. These data revealed AREG as a E545K-preferential target that was further validated through in vitro analysis and publicly available patient databases. CONCLUSIONS: Using our multi-modal genomics framework, we discover distinct differences in genomic regulation between PIK3CA hotspot mutations, suggesting the PIK3CA mutations have different regulatory effects on the function and downstream signaling of the PI3K complex. Our results demonstrate the potential to rapidly uncover mutation specific molecular targets, specifically AREG and a proximal gene regulatory region, that may provide clinically relevant therapeutic targets. The methods outlined provide investigators with an integrative strategy to identify mutation-specific targets for the treatment of other oncogenic mutations in an isogenic system.

Alternative Tissue Fixation Protocols Dramatically Reduce the Impact of DNA Artifacts, Unraveling the Interpretation of Clinical Comprehensive Genomic Profiling.

Formalin-fixed paraffin-embedded (FFPE) samples represent the cornerstone of tissue-based analysis in precision medicine. Targeted next-generation sequencing panels are routinely used to analyze a limited number of genes to guide treatment decision-making for advanced-stage patients. The number and complexity of genetic alterations to be investigated are rapidly growing; in several instances, a comprehensive genomic profiling analysis is needed. The poor quality of genetic material extracted from FFPE samples may impact the feasibility/reliability of sequencing data. We sampled 9 colorectal cancers to allow 4 parallel fixations: (1) neutral buffered formalin (NBF), (2) acid-deprived formalin fixation (ADF), (3) precooled ADF (coldADF), and (4) glyoxal acid free (GAF). DNA extraction, fragmentation analysis, and sequencing by 2 large next-generation sequencing panels (OCAv3 and TSO500) followed. We comprehensively analyzed library and sequencing quality controls and the quality of sequencing results. Libraries from coldADF samples showed significantly longer reads than the others with both panels. ADF-derived and coldADF-derived libraries showed the lowest level of noise and the highest levels of uniformity with the OCAv3 panel, followed by GAF and NBF samples. The data uniformity was confirmed by the TSO500 results, which also highlighted the best performance in terms of the total region sequenced for the ADF and coldADF samples. NBF samples had a significantly smaller region sequenced and displayed a significantly lower number of evaluable microsatellite loci and a significant increase in single-nucleotide variations compared with other protocols. Mutational signature 1 (aging and FFPE artifact related) showed the highest (37%) and lowest (17%) values in the NBF and coldADF samples, respectively. Most of the identified genetic alterations were shared by all samples in each lesion. Five genes showed a different mutational status across samples and/or panels: 4 discordant results involved NBF samples. In conclusion, acid-deprived fixatives (GAF and ADF) guarantee the highest DNA preservation/sequencing performance, thus allowing more complex molecular profiling of tissue samples.

Genomic dissection and mutation-specific target discovery for breast cancer PIK3CA hotspot mutations.

Background: Recent advancements in high-throughput genomics and targeted therapies have provided tremendous potential to identify and therapeutically target distinct mutations associated with cancers. However, to date the majority of targeted therapies are used to treat all functional mutations within the same gene, regardless of affected codon or phenotype. Results: In this study, we developed a functional genomic analysis workflow with a unique isogenic cell line panel bearing two distinct hotspot PIK3CA mutations, E545K and H1047R, to accurately identify targetable differences between mutations within the same gene. We performed RNA-seq and ATAC-seq and identified distinct transcriptomic and epigenomic differences associated with each PIK3CA hotspot mutation. We used this data to curate a select CRISPR knock out screen to identify mutation-specific gene pathway vulnerabilities. These data revealed AREG as a E545K-preferential target that was further validated through in vitro analysis and publicly available patient databases. Conclusions: Using our multi-modal genomics framework, we discover distinct differences in genomic regulation between PIK3CA hotspot mutations, suggesting the PIK3CA mutations have different regulatory effects on the function and downstream signaling of the PI3K complex. Our results demonstrate the potential to rapidly uncover mutation specific molecular targets, specifically AREG and a proximal gene regulatory region, that may provide clinically relevant therapeutic targets. The methods outlined provide investigators with an integrative strategy to identify mutation-specific targets for the treatment of other oncogenic mutations in an isogenic system.

scCircle-seq unveils the diversity and complexity of extrachromosomal circular DNAs in single cells.

Extrachromosomal circular DNAs (eccDNAs) have emerged as important intra-cellular mobile genetic elements that affect gene copy number and exert in trans regulatory roles within the cell nucleus. Here, we describe scCircle-seq, a method for profiling eccDNAs and unraveling their diversity and complexity in single cells. We implement and validate scCircle-seq in normal and cancer cell lines, demonstrating that most eccDNAs vary largely between cells and are stochastically inherited during cell division, although their genomic landscape is cell type-specific and can be used to accurately cluster cells of the same origin. eccDNAs are preferentially produced from chromatin regions enriched in H3K9me3 and H3K27me3 histone marks and are induced during replication stress conditions. Concomitant sequencing of eccDNAs and RNA from the same cell uncovers the absence of correlation between eccDNA copy number and gene expression levels, except for a few oncogenes, including MYC, contained within a large eccDNA in colorectal cancer cells. Lastly, we apply scCircle-seq to one prostate cancer and two breast cancer specimens, revealing cancer-specific eccDNA landscapes and a higher propensity of eccDNAs to form in amplified genomic regions. scCircle-seq is a scalable tool that can be used to dissect the complexity of eccDNAs across different cell and tissue types, and further expands the potential of eccDNAs for cancer diagnostics.