Adopting duplex sequencing technology for genetic toxicity testing: A proof-of-concept mutagenesis experiment with N-ethyl-N-nitrosourea (ENU)-exposed rats

Duplex sequencing (DS) is an error-corrected next-generation sequencing method in which molecular barcodes informatically link PCR-copies back to their source DNA strands, enabling computational removal of errors in consensus sequences. The resulting background of less than one artifactual mutation per 107 nucleotides allows for direct detection of somatic mutations. TwinStrand Biosciences, Inc. has developed a DS-based mutagenesis assay to sample the rat genome, which can be applied to genetic toxicity testing. To evaluate this assay for early detection of mutagenesis, a time-course study was conducted using male Hsd:Sprague Dawley SD rats (3 per group) administered a single dose of 40 mg/kg N-ethyl-N-nitrosourea (ENU) via gavage, with mutation frequency (MF) and spectrum analyzed in stomach, bone marrow, blood, and liver tissues at 3 h, 24 h, 7 d, and 28 d post-exposure. Significant increases in MF were observed in ENU-exposed rats as early as 24 h for stomach (site of contact) and bone marrow (a highly proliferative tissue) and at 7 d for liver and blood. The canonical, mutational signature of ENU was established by 7 d post-exposure in all four tissues. Interlaboratory analysis of a subset of samples from different tissues and time points demonstrated remarkable reproducibility for both MF and spectrum. These results demonstrate that MF and spectrum can be evaluated successfully by directly sequencing targeted regions of DNA obtained from various tissues⁠, a considerable advancement compared to currently used in vivo gene mutation assays.

Duplex sequencing provides detailed characterization of mutation frequencies and spectra in the bone marrow of MutaMouse males exposed to procarbazine hydrochloride

Mutagenicity testing is an essential component of health safety assessment. Duplex Sequencing (DS), an emerging high-accuracy DNA sequencing technology, may provide substantial advantages over conventional mutagenicity assays. DS could be used to eliminate reliance on standalone reporter assays and provide mechanistic information alongside mutation frequency (MF) data. However, the performance of DS must be thoroughly assessed before it can be routinely implemented for standard testing. We used DS to study spontaneous and procarbazine (PRC)-induced mutations in the bone marrow (BM) of MutaMouse males across a panel of 20 diverse genomic targets. Mice were exposed to 0, 6.25, 12.5, or 25 mg/kg-bw/day for 28 days by oral gavage and BM sampled 42 days post-exposure. Results were compared with those obtained using the conventional lacZ viral plaque assay on the same samples. DS detected significant increases in mutation frequencies and changes to mutation spectra at all PRC doses. Low intra-group variability within DS samples allowed for detection of increases at lower doses than the lacZ assay. While the lacZ assay initially yielded a higher fold-change in mutant frequency than DS, inclusion of clonal mutations in DS mutation frequencies reduced this discrepancy. Power analyses suggested that three animals per dose group and 500 million duplex base pairs per sample is sufficient to detect a 1.5-fold increase in mutations with > 80% power. Overall, we demonstrate several advantages of DS over classical mutagenicity assays and provide data to support efforts to identify optimal study designs for the application of DS as a regulatory test.

Error-corrected duplex sequencing enables direct detection and quantification of mutations in human TK6 cells with strong inter-laboratory consistency

Error-corrected duplex sequencing (DS) enables direct quantification of low-frequency mutations and offers tremendous potential for chemical mutagenicity assessment. We investigated the utility of DS to quantify induced mutation frequency (MF) and spectrum in human lymphoblastoid TK6 cells exposed to a prototypical DNA alkylating agent, N-ethyl-N-nitrosourea (ENU). Furthermore, we explored appropriate experimental parameters for this application, and assessed inter-laboratory reproducibility. In two independent experiments in two laboratories, TK6 cells were exposed to ENU (25-200 µM) and DNA was sequenced 48, 72, and 96 h post-exposure. A DS mutagenicity panel targeting twenty 2.4-kb regions distributed across the genome was used to sample diverse, genome-representative sequence contexts. A significant increase in MF that was unaffected by time was observed in both laboratories. Concentration-response in the MF from the two laboratories was strongly positively correlated (r = 0.97). C:G>T:A, T:A>C:G, T:A>A:T, and T:A>G:C mutations increased in consistent, concentration-dependent manners in both laboratories, with high proportions of C:G>T:A at all time points. The consistent results across the three time points suggest that 48 h may be sufficient for mutation analysis post-exposure. The target sites responded similarly between the two laboratories and revealed a higher average MF in intergenic regions. These results, demonstrating remarkable reproducibility across time and laboratory for both MF and spectrum, support the high value of DS for characterizing chemical mutagenicity in both research and regulatory evaluation.

Adopting Duplex Sequencing™ Technology for Genetic Toxicity Testing: A Proof-of-Concept Mutagenesis Experiment with N-Ethyl-N-Nitrosourea (ENU)-Exposed Rats

Duplex sequencing (DuplexSeq) is an error-corrected next-generation sequencing (ecNGS) method in which molecular barcodes informatically link PCR-copies back to their source DNA strands, enabling computational removal of errors by comparing grouped strand sequencing reads. The resulting background of less than one artifactual mutation per 10 7 nucleotides allows for direct detection of somatic mutations. TwinStrand Biosciences, Inc. has developed a DuplexSeq-based mutagenesis assay to sample the rat genome, which can be applied to genetic toxicity testing. To evaluate this assay for early detection of mutagenesis, a time-course study was conducted using male Hsd:Sprague Dawley SD rats (3 per group) administered a single dose of 40 mg/kg N-ethyl-N-nitrosourea (ENU) via gavage, with mutation frequency (MF) and spectrum analyzed in stomach, bone marrow, blood, and liver tissues at 3 h, 24 h, 7 d, and 28 d post-exposure. Significant increases in MF were observed in ENU-exposed rats as early as 24 h for stomach (site of contact) and bone marrow (a highly proliferative tissue) and at 7 d for liver and blood. The canonical, mutational signature of ENU was established by 7 d post-exposure in all four tissues. Interlaboratory analysis of a subset of samples from different tissues and time points demonstrated remarkable reproducibility for both MF and spectrum. These results demonstrate that MF and spectrum can be evaluated successfully by directly sequencing targeted regions of DNA obtained from various tissues, a considerable advancement compared to currently used in vivo gene mutation assays.

HIGHLIGHTS

DuplexSeq is an ultra-accurate NGS technology that directly quantifies mutationsENU-dependent mutagenesis was detected 24 h post-exposure in proliferative tissuesMultiple tissues exhibited the canonical ENU mutation spectrum 7 d after exposureResults obtained with DuplexSeq were highly concordant between laboratoriesThe Rat-50 Mutagenesis Assay is promising for applications in genetic toxicology.

Abstract A008: TP53 field defects in uterine fluid are associated with ovarian cancer risk

This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR005) of the Conference Proceedings.

Citation Format: Rosana Risques, Thomas H. Smith, Zachary K. Norgaard, Roniz Katz, Fang Yin Lo, Elizabeth K. Schmidt, Jacob E. Higgins, Martin Filipits, Intidhar Labidi-Galy, David Cibula, Lukáš Dostálek, Gabriel Jelenek, Magdalena Plch, Jiří Bouda, Alexander Mustea, Mateja Condic, Sabine Grill, Noreen Gleeson, Peter Oppelt, Gunda Pristauz-Telsnigg, Adriaan Vanderstichele, Siel Obrecht, Adam Rosenthal, Paul Speiser, Jesse Salk. TP53 field defects in uterine fluid are associated with ovarian cancer risk [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A008.

Abstract 3147: Non-invasive detection of aristolochic acid exposure using ultra-sensitive duplex sequencing

Aristolochic acids (AA) are a potent class of mutagen that occur in plants of the genera Aristolochia and Asarum. Exposures to AA are caused both by intentional ingestion of traditional herbal medicines containing Aristolochia and through inadvertent consumption from contaminated crops. The carcinogenic potential and epidemiologic connection of AA exposure with upper-tract urothelial cancers (UTUC), liver cancer and kidney failure have been known for years; however, the extent of AA exposure and its influence on cancer risk and mortality have yet to be fully explored in many world populations.

Using whole exome sequencing of tumor samples, a recent study determined that 78% of HCCs from Taiwan exhibit distinct mutation signatures of AA exposure (Ng, Poon, Huang, et al., 2017). Exposure to AA is geographically widespread and there is a major opportunity for primary and secondary prevention of AA-associated diseases if it were possible to detect the exposure through non-invasively sampled body fluids such as blood or urine sediment.

Although AA adducts can be measured in body fluids, this measurement only reflects recent ingestion, not the life-integrated exposure that better approximates disease risk. A mutation burden-based assay could circumvent this problem; however, a major challenge is that AA-mediated mutations are extremely rare in bulk tissue or fluid samples from non-tumor sources. Duplex Sequencing (DS) is a tag-based NGS error-correction method that enables the detection of ultra-rare mutations that exist at the mutation frequency of normal tissues (~10e-8). DS can be applied to DNA from any tissue of any organism without the need for tumor formation or ex vivo cloning.

We developed a DS-based assay that measures mutations across a 50 kb genome-representative panel and applied it to the tissues and liquid biopsies of cancer patients of known AA-exposure status. We sampled the blood, urine, kidney, normal-adjacent urothelium and ureteral tumors from 12 UTUC patients where 6 of the patients were exposed to AA, and 6 were not.

Under blinded conditions, we positively identified AA mutation signatures in the normal adjacent urothelium tissues of 5 AA-exposed patients. Remarkably, we also detected AA signatures in all available blood and urine samples from the same patients. The proportion of mutations attributed to AA-exposure ranged from 2.5% in blood to 67.8% in kidney. These mutations, on the order of one-in-a-million, were exposure-related, not tumor derived. We did not detect AA mutation signatures in any samples from the non-AA-exposed patients.

To our knowledge, this is the first time an AA mutation signature has been detected in non-invasively sampled body fluids. DS is a promising approach for the detection of mutagenic signatures caused by environmental carcinogens, and we foresee it being a powerful metric that can be used to measure life-integrated carcinogenic processes and cancer risk.

Citation Format: Fang Yin Lo, Charles Valentine, Elizabeth Schmidt, Lindsey Williams, Arnoud Boot, Steve Rozen, Jesse Salk. Non-invasive detection of aristolochic acid exposure using ultra-sensitive duplex sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3147.

Abstract 3418: Cross-comparison of targeted gene expression technologies for patient stratification

Colorectal cancer (CRC) is one of the major causes of global cancer mortality. Until recently, KRAS has been the only predictive biomarker for anti-EGFR therapy for metastatic CRC, and yet predicting prognosis in clinical practice is still poor. Therefore, a more accurate method for prognosis of CRC patients is needed. Gene expression profiling has shown great promise in predicting prognosis of individual patients in diverse cancers. The development of RNA-sequencing has greatly facilitated identification of biomarkers that can be used to stratify patients for targeted therapies. Despite the decrease in cost of sequencing in last few years, the time and the resources needed for analysis limit its use in clinical trials for patient selection. Targeted gene expression technologies like qPCR and NanoString enable highly customizable assays that can be conveniently performed for patient recruitment. The aim of this study was to investigate potential alternatives for gene profiling using a novel NanoString Plex Set technology. The Plex Set system comes with prepackaged and custom code sets in identifying genetic markers. Up to 8 samples can be pooled to each nCounter cartridge lane, enabling a total of 96 samples per run, thus making the total cost relatively affordable. For this study, gene expression signature was developed using RNA-Seq data where we have profiled 74 CRC samples, 20 of which have matching normal samples. A RAS signature score based on expression profile was calculated for each sample. In order to look for potential gene signatures, differential gene expression analysis was performed between the following groups: (a) samples with high versus those with low RAS signature scores in the 54 CRC, (b) KRAS mutant versus wild-type samples, and (c) tumor versus normal samples in the clinical study. We hypothesized that our genes of interest are most likely significantly differentially expressed in one of these groups. The counts of significantly expressed gene for the groups (a-c) are 1560 and 34, respectively, and we are working on the third case. Therefore, significantly deferentially expressed genes between groups were selected and ranked based on frequency of occurrence. These genes of interest are being analyzed using NanoString Plex Set and qPCR to evaluate the potential of using NanoString Plex Set system for targeted gene expression profiling. Results of these analyses will be presented.

Citation Format: Raghavee Venkatramanan, Tuuli Saloranta, Inah Golez, Elliot Swanson, Kimberly Kruse, Vickie Satele, Saman Tahir, Sally Dow, Evan Anderson, Briana Hudson, Spencer Chee, Kerry Deutsch, Steve Anderson, Fang Yin Lo, Anup Madan. Cross-comparison of targeted gene expression technologies for patient stratification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3418.

Abstract 5379: Stratification of colorectal cancer patients based on various sequencing platforms and tumor mutational burden

Colorectal cancer (CRC) is the third most common type of cancer in the United States. Although chemotherapy, radiation and targeted therapies can improve survival rates, recent studies have shown the potential benefit of immunotherapies to improve outcomes for patients with advanced CRC. Targeted therapies that use monoclonal antibodies (mAbs) to EGFR have been shown to benefit some CRC patients. Until recently, KRAS has been the only predictive biomarker for anti-EGFR therapy for metastatic CRC. However, 40% to 60% of patients with wild-type KRAS do not respond to anti-EGFR therapy. Therefore, to accurately predict patients' response to treatments and improve clinical outcomes, additional prediction and treatment methods are imperative. One of the many efforts to improve prediction for CRC patient's response to the anti-EGFR therapy is the development of gene expression based RAS signature scores for identification of RAS activated tumors independent of mutations in the KRAS gene. There is also considerable effort being placed on combinations of targeted therapy and immunotherapies to improve responses for these cancers. Previously, we have stratified 55 CRC samples by applying a RAS gene signature score which measures MEK pathway functional output independent of tumor genotype. We showed that samples that have RAS activating mutations such as KRAS and BRAF have significant higher RAS scores (p<0.001). Here we investigate 120 colorectal cancer patients using exome sequencing, targeted panel sequencing, and RNA sequencing. Specifically, we acquired 40 normal-tumor pair samples and performed GATK tumor-normal pair mutation calling. Among these 120 samples, 65 of them are from patients treated with either cetuximab or panitumumab. Continued from our previous study, we stratified these samples based on calculated RAS scores, and showed how the results correlate with clinical outcome. Tumor mutational burden (TMB) can help predict the likelihood that a patient will benefit from certain immunotherapies; however, clinical applicability is limited due to cost and computing requirements of whole-exome sequencing to detect variants with high degree of accuracy. Therefore it would be helpful if TMB can be identified based on targeted sequencing. Here we investigate how TMB calculated based on different sequencing platform correlates with each other and whether targeted sequencing panel can be used instead of exome sequencing for stratifying patients. In addition, we investigated if Illumina's global screening array can be used for TMB analysis. Furthermore, to investigate the potential immune reactivity in these CRC samples, and thereby the potential benefit of immunotherapy, we performed in-silico prediction of neo-antigens and peptide binding affinity between tumor antigens derived from mutations and human HLA alleles.

Citation Format: Fang Yin Lo, Claire Olson, Kerry Deutsch, Tuuli Saloranta, Inah Golez, Timothy Yeatman, Steven Anderson, Anup Madan. Stratification of colorectal cancer patients based on various sequencing platforms and tumor mutational burden [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5379.

Abstract 413: Neo-epitope detection and immune infiltrate analysis of colorectal cancer samples

Colorectal cancer (CRC) is the third most common type of cancer in the United States. Targeted therapies that use monoclonal antibodies (mAbs) to EGFR have been shown to benefit some CRC patients. Until recently, KRAS has been the only predictive biomarker for anti-EGFR therapy for metastatic CRC. However, 40% to 60% of patients with wild-type KRAS do not respond to anti-EGFR therapy. Previously we have stratified 55 CRC samples by applying a RAS gene signature score which measures MEK pathway functional output independent of tumor genotype. We showed that samples that have RAS activating mutations such as KRAS and BRAF have significant higher RAS scores (p<0.001). Here, we further investigate the potential immune reactivity in these CRC samples, and thereby the potential benefit of immunotherapy, by evaluating the tumor neo-epitope burden, and the quality of immune cell infiltration based on exome-seq and RNA-seq analysis. In the 53 samples that were sequenced, 779 unique non-synonymous mutations were detected by exome-seq. These 779 mutations spanned across 263 genes. The majority of these mutations are not shared between samples (~ 5% of the mutations were shared by more than 2 samples). Several driver gene mutations were identified in this study, including KRAS, TP53, PIK3CA, APC and HER2. HLA prediction based on Exome-Seq and RNA-Seq data shows that ~86.7% of the alleles predicted to be present in 53 samples were concordant between the two RNA-seq datasets. The predicted alleles based on exome-seq and RNA-seq results have 67-69% concordance. Prediction of neo-epitopes show that HLA-binding neo-epitopes are more frequent than TCR-binding ones, and that most neo-epitopes are private and not shared between samples. A more in-depth analysis of the tumor microenvironment was performed using the RNA-seq data. The epithelial, stromal and immune content of the tumors was comparable to tumors from TCGA CRC data. Next, the immune cell compartment was further stratified into 7 different immune cell types using signatures specific to CD8 andCD4 T, T-regulatory, NK, B-cells, Macrophages and Myeloid derived suppressor cells (MDSC). The immune make up of colorectal cancer is dominated by macrophages and MDSCs. Interestingly, both granulocytic G- and monocytic M-MDSCs are present together, supporting the idea that MDSCs confer an immune suppressive microenvironment in this cancer. Significantly, high MDSC infiltrated tumors showed upregulated expression of pro-tumorigenic insulin-like growth factor pathway genes. Additionally, tumors with lower burden of MDSC showed signature of complement activation suggesting innate cell-mediated anti-tumorigenic mechanisms of tumor control in CRC. These analyses provide potential biomarkers to stratify CRC patients based on their immune reactivity and predict response to cancer immunotherapy drugs.

Citation Format: Fang Yin Lo, Nitin Mandloi, Timothy Yeatman, Kiran Paul, Ashwini Patil, Steven Anderson, Ravi Gupta, Anup Madan. Neo-epitope detection and immune infiltrate analysis of colorectal cancer samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 413. doi:10.1158/1538-7445.AM2017-413

Adaptation of a RAS pathway activation signature from FF to FFPE tissues in colorectal cancer

BACKGROUND

The KRAS gene is mutated in about 40 % of colorectal cancer (CRC) cases, which has been clinically validated as a predictive mutational marker of intrinsic resistance to anti-EGFR inhibitor (EGFRi) therapy. Since nearly 60 % of patients with a wild type KRAS fail to respond to EGFRi combination therapies, there is a need to develop more reliable molecular signatures to better predict response. Here we address the challenge of adapting a gene expression signature predictive of RAS pathway activation, created using fresh frozen (FF) tissues, for use with more widely available formalin fixed paraffin-embedded (FFPE) tissues.

METHODS

In this study, we evaluated the translation of an 18-gene RAS pathway signature score from FF to FFPE in 54 CRC cases, using a head-to-head comparison of five technology platforms. FFPE-based technologies included the Affymetrix GeneChip (Affy), NanoString nCounter™ (NanoS), Illumina whole genome RNASeq (RNA-Acc), Illumina targeted RNASeq (t-RNA), and Illumina stranded Total RNA-rRNA-depletion (rRNA).

RESULTS

Using Affy_FF as the "gold" standard, initial analysis of the 18-gene RAS scores on all 54 samples shows varying pairwise Spearman correlations, with (1) Affy_FFPE (r = 0.233, p = 0.090); (2) NanoS_FFPE (r = 0.608, p < 0.0001); (3) RNA-Acc_FFPE (r = 0.175, p = 0.21); (4) t-RNA_FFPE (r = -0.237, p = 0.085); (5) and t-RNA (r = -0.012, p = 0.93). These results suggest that only NanoString has successful FF to FFPE translation. The subsequent removal of identified "problematic" samples (n = 15) and genes (n = 2) further improves the correlations of Affy_FF with three of the five technologies: Affy_FFPE (r = 0.672, p < 0.0001); NanoS_FFPE (r = 0.738, p < 0.0001); and RNA-Acc_FFPE (r = 0.483, p = 0.002).

CONCLUSIONS

Of the five technology platforms tested, NanoString technology provides a more faithful translation of the RAS pathway gene expression signature from FF to FFPE than the Affymetrix GeneChip and multiple RNASeq technologies. Moreover, NanoString was the most forgiving technology in the analysis of samples with presumably poor RNA quality. Using this approach, the RAS signature score may now be reasonably applied to FFPE clinical samples.

Abstract 104: Investigation of genetic architecture of multiple myeloma by next generation sequencing

Myeloma is a genetically heterogeneous disease and is sub-classified based on the presence of structural variants and genetic mutations. Structural variants/copy number changes are historically identified by traditional methods such as karyotyping and fluorescence in situ hybridization (FISH). Although microarray based genome wide analyses greatly improve the resolution of structural variation, they may be limited by probe density. Consequently, identification of structural variation may be insensitive to specific disrupted gene(s), neglecting the sequence complexity that might underlie these rearrangements. Determination of the specific breakpoints of structural variants at the nucleotide level is required for a better understanding of the genetic causes and to enhance the development of therapeutics for patients. The emergence of Next-Generation Sequencing (NGS) technology has led to the identification of structural variants in the genome at a higher resolution relative to currently used cytogenetic methods. We analyzed DNA extracted from a set of patients with multiple myeloma, who had Affymetrix SNP array (∼2.7 million probes) data, by whole exome sequencing (WES) at 100X coverage on the Illumina HiSeq platform to identify the full spectrum of associated genomic aberrations. Sequence data was mapped to the hg19 reference sequence and analyzed by various in-house developed and open source data analytic tools. Additionally, a custom sequence analysis pipeline was written to interrogate chromosomal deletions and translocations in these samples. Our analysis showed that ∼43% (6/14) of patients have deletions in chr17p and/or chr13q. We further confirmed structural variants using the Integrative Genomics Viewer (IGV). These data indicate the efficacy of WES for the precise determination of translocation and inversion breakpoints. In addition, we were able to identify single nucleotide variants (SNVs) and insertions/deletions (indels) in these samples. We then used the Ingenuity Variant Analysis (IGV) program to identify clinically actionable variants. These datasets are being further analyzed by various pathway analysis tools to define possible pathogenic mechanisms in multiple myeloma.

Citation Format: Kerry Deutsch, Fang Yin Lo, Claire Olson, Sharon Austin, Kellie Howard, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Christopherson, Kathryn Shiji, Shradha Patil, Stuart Schwartz, Peter Papenhausen, Steven Anderson, Anup Madan. Investigation of genetic architecture of multiple myeloma by next generation sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 104.

Abstract 4436: Synergistic effects of promoter associated DNA methylation and genetic alterations to better understand oncogenic gene expression profiles

The emergence of Next Generation Sequencing (NGS) along with computational biology has broadened the scope in which diverse cellular processes can be interrogated. While there has been considerable progress in understanding the impact of genetic and epigenetic mechanisms in tumorigenesis using whole genomic, epigenomic and transcriptional analysis by NGS, there has been little consideration of the importance of interplay between these processes. We performed a comparative analysis of array and NGS technologies to identify differentially methylated CpG sites in colorectal cancer cell lines. NGS had more specificity in addition to profiling more CpG sites relative to Illumina 450K arrays.

Base-level resolution of sequencing data can identify any strand specific methylation bias. Our analysis shows that methylation frequency between the sense and antisense strand are highly correlated (average R2 ∼ 0.81), and coefficient of variance (CV) between the strands is generally low (about half of observed sites have &lt;10% CV). However, a small percentage of bases had strand specific biases. Using a minimum of 100% CV and difference in methylation frequency greater than 50% as filtering criteria, we found 1210, 569, 638, and 1484 CpG sites have strand specific biases with 7 overlapping bases among the samples tested. Further investigation will identify whether these bases are random or reside within a particular region, where biases occur, and what genes are potentially affected.

We also used NGS and publically available gene expression datasets in colorectal cancer cell lines-HCT116 and HCT116 DKO (cell line with genetic knockouts of both DNA methyltransferases DNMT1 and DMNT3b) to identify roles of differential methylation in regulating gene expression. A majority of genes were down-regulated between HCT116 and HCT116 DKO cell lines including those involved in chromatin, nucleic acid, and nucleotide binding and cell cycle regulation. Interestingly, many differentially expressed genes are also involved in immune response. We then used bisulfite treated genomic data to evaluate genetic regulation of gene expression. For this, we converted bisulfite treated data into genomic space using custom in-house developed bio-informatics tools that were first tested using DNA isolated from NA12878 cell line. Our analysis showed that 65% of the known variants detected in NA12878 cell line by the genome in a bottle consortium can be identified by bisulfite sequencing of promoter associated CpG islands. One limitation of this analysis is the inability to identify C&gt;T genomic variants. This data is being analyzed to evaluate effects of genetic mutations in promoter binding sites on gene expression in colorectal cancers. Comparative analysis of genetic and epigenetic regulation of gene expression will allow better understanding of gene regulatory networks in colorectal cancer.

Citation Format: Claire Olson, Fang Yin Lo, Kerry Deutsch, Sharon Austin, Kellie Howard, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Christopherson, Kathryn Shiji, Shradha Patil, Steven Anderson, Anup Madan. Synergistic effects of promoter associated DNA methylation and genetic alterations to better understand oncogenic gene expression profiles. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4436.

Abstract 498: Meta-analysis of genomic aberrations identified in CTCs andctDNA in triple negative breast cancer

Technological innovation and scientific advances in understanding cancer at the molecular level have accelerated the discovery and development of both diagnostics and therapeutics. Circulating tumor cells (CTCs) and plasma circulating tumor DNA (ctDNA) are non-invasive prognostic markers that have been associated with metastatic and aggressive disease. Both CTCs and ctDNA allow molecular characterization of a tumor that is inaccessible or too risky to biopsy. The analysis of genomic aberrations in both sample types provides insights into drug resistance and can help determine appropriate, targeted cancer treatments. Mutations found in the primary or metastatic tumor can be identified in both CTCs and ctDNA as well as novel mutations that may reflect intratumoral and intermetastatic heterogeneity. When collected and evaluated over an extended period of time, changes in the CTC and/or ctDNA mutational profile can offer guidance into the effectiveness of a treatment, indicate the progression of disease, and detect recurrence of disease earlier.

We have performed whole exome sequencing of CTCs and ctDNA from a metastatic triple negative breast cancer (TNBC) patient to better understand the evolution of tumor heterogeneity during therapy. The patient was enrolled in the Intensive Trial of OMics in Cancer clinical Trial (ITOMIC-001) and initially received weekly cisplatin infusions followed by additional targeted therapy. Longitudinal peripheral blood samples were collected over a period of 272 days following enrollment in the clinical trial. CTCs were identified using the AccuCyte-CyteFinder system (RareCyte, Seattle WA).

We used next generation sequencing, and computational biology tools to analyze genomic DNA from multiple CTCs, white blood cells (WBCs) and ctDNA from various time points. We observed similar genomic aberrations in both CTCs and ctDNA that could be classified into three groups: a) a static group that remains unchanged during the course of therapy, b) a sample-specific group that is unique to each time point and c) an intermediate group that has variants that are short-lived but are present across multiple time points. Variants identified in the liquid biopsy samples were compared with variants observed in primary breast tumor, metastatic bone marrow tumor and publically available pan-cancer datasets. We then performed meta-analysis on somatic variants to identify changes in affected networks in response to therapy over time. Several key nodes were identified that could rationally have been targeted for therapy using compounds currently in clinical trials. We then compared and combined the perturbed networks obtained from the CTCs and ctDNA to better understand the etiology of TNBC. These studies represent the first step of a synergistic partnership between the genetic information obtained from the analysis of CTCs and ctDNA with innovative health care for patients with metastatic breast cancer.

Citation Format: Kellie Howard, Sharon Austin, Fang Yin Lo, Arturo Ramirez, Debbie Boles, John Pruitt, Elisabeth Mahen, Heather Collins, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Christopherson, Kerry Deutsch, Jackie Stilwell, Eric Kaldjian, Michael Dorschner, Sibel Blau, Anthony Blau, Marcia Eisenberg, Steven Anderson, Anup Madan. Meta-analysis of genomic aberrations identified in CTCs andctDNA in triple negative breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 498.

A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC

Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinicopathologic staging for decades. There is a need to stratify subpopulations of CRC on a molecular basis to better predict outcome and assign therapies. Here we report targeted exome-sequencing of 1,321 cancer-related genes on 468 tumour specimens, which identified a subset of 17 genes that best classify CRC, with APC playing a central role in predicting overall survival. APC may assume 0, 1 or 2 truncating mutations, each with a striking differential impact on survival. Tumours lacking any APC mutation carry a worse prognosis than single APC mutation tumours; however, two APC mutation tumours with mutant KRAS and TP53 confer the poorest survival among all the subgroups examined. Our study demonstrates a prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.

Abstract 1609: Comprehensive multi-omic analysis of circulating tumor cells isolated from a metastatic triple-negative breast cancer patient to identify pathogenic genomic aberrations

Increasing evidence confirms the prognostic relevance of Circulating Tumor Cells (CTCs) in a variety of cancers including advanced breast cancer. Recent data also suggests that CTCs are a useful tool for monitoring treatment and identifying potential targets for therapeutic intervention. The objective of this study was to investigate technologies that can be used for defining the genomic landscape of CTCs in order to compare the derived genomic information (1) among CTCs to assess genetic heterogeneity and (2) with that derived from bone-marrow metastasis tissue biopsy (BMM) samples to assess how reflective the molecular profile from CTCs is to the metastasis. To evaluate these potential applications, positive CTCs were identified using the AccuCyte -CyteFinder (AC/CF) system (RareCyte, Seattle WA) from the blood of a patient with triple negative breast cancer (TNBC). Twenty CTCs and twenty white blood cells (WBCs) were picked from slides using the AC/CF system. To determine whether tumor specific genomic characteristics are reflected in the isolated cells, we used whole genome amplification (WGA) followed by next-generation sequencing to perform a comprehensive analysis using WBCs as genome controls. Whole genome, exome and targeted sequencing of known cancer-associated genes using Illumina and Life Tech panels identified mutations in TP53, PTEN, ERBB2, STK11, ABL1, HRAS, MLL2 and INPPL1 which were present in the CTCs alone and not in the WBCs. Further analysis comparing the results between CTCs revealed that the majority of the identified mutations were specific to individual CTCs revealing a high degree of genetic heterogeneity. Only 5% of mutations were shared between at least 40% of the CTCs examined and included mutations in ATM, ALK, BRAF, NOTCH1, ATR, JAK3, COL1A1 and XPC. Additionally, all of the profiled CTCs contained two novel mutations in LPP and HLA-A which were not present in the WBCs. Mutations in these genes have recently been associated with aggressive solid tumors. Genetic heterogeneity was also observed in the WBC population enabling the calculation and subsequent subtraction of background noise associated with WGA of single cells. Molecular information derived from the CTCs is being compared to multiple BMM samples from the same patient. Additional analyses of copy number and structural variations and transcriptomic analysis are being performed in order to gain further insights into the genetic heterogeneity of CTCs and identify genomic markers to establish the utility of CTCs as a non-invasive real-time liquid biopsy for breast cancer.

Citation Format: Kellie Howard, Sharon Austin, Arturo Ramirez, Leila Ritter, Debbie Boles, James Cox, Fang Yin Lo, Kerry Deutsch, Christopher Subia, Tuuli Saloranta, Nicole Heying, Heather Collins, Amanda Leonti, Lindsey Maassel, Jackie Stilwell, Eric Kaldjian, Michael Dorschner, Anthony Blau, Marcia Eisenberg, Steven Anderson, Anup Madan. Comprehensive multi-omic analysis of circulating tumor cells isolated from a metastatic triple-negative breast cancer patient to identify pathogenic genomic aberrations. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1609. doi:10.1158/1538-7445.AM2015-1609

Abstract 4842: Pharmacodynamic stratification of metastatic colorectal cancer patients using genomic datasets

Previously, the mutation status of KRAS was the only validated predictive biomarker for metastatic colorectal cancer (CRC). While KRAS mutated tumors demonstrated resistance to epidermal growth factor (EGFR) inhibitors like cetuximab, KRAS WT and EGFR-expressing tumors were predicted to be responsive. However, KRAS WT metastatic colorectal cancer (CRC) patients have a poor prognosis even with EGFR inhibitor therapy as not all KRAS WT CRCs are responsive to such targeted agents. A gene expression based RAS signature score was developed based on multiple tumor tissue samples to identify RAS activated tumors independent of mutations in the KRAS gene [1, 2]. To further refine this score and define technologies that can be used on FFPE samples isolated in a clinical setting, we analyzed DNA and RNA derived from fifty-five (55) FFPE preserved colorectal cancer tumor biopsies using multiple sequencing, digital and array-based technologies. These samples were selected from a CRC cohort in which the initial gene expression-based RAS signature score was calculated utilizing data compiled from fresh frozen (FF) tumor samples from the same 55 patients. The 55 samples were selected for this study as they had representative samples with high, medium and low RAS signature scores. Transcriptomic analyses (RNA-Seq, Affymetrix microarrays, Nanostring and Targeted RNA-Seq) were performed on all 55 FFPE samples and three new RAS scores were calculated from the gene expression datasets. These RAS scores were based on different gene signatures (1) an 18 gene signature (2) a 13 gene signature, and (3) a 147 gene signature. A significant correlation was identified between RAS scores calculated from the 18 and 13 gene signatures (Correlation coefficient ∼ 0.88 and ∼0.76 respectively, p-value &lt; 0.0001). To further refine gene expression signatures, samples were grouped based upon their mutation status obtained by whole exome sequencing (WES) and targeted DNA sequencing data (Illumina TruSight and LifeTech Cancer Panels). In our sample set, the 18 gene RAS score was found to be dependent on the mutation status of KRAS. Further analysis is being carried out to better understand the relationship between the calculated RAS signature scores and the mutation status of other genes. This analysis will lead to the development of a novel genomic signature for better pharmacodynamic stratification of colorectal carcinoma patients.

1. Loboda A et al. A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

2. BMC Medical Genomics 2010, 3:26Dry JR et al. Transcriptional Pathway Signatures Predict MEK Addiction and Response to Selumetinib (AZD6244). Cancer Res. 2010 Mar 15;70(6):2264-73.

Citation Format: Sharon Austin, Fang Yin Lo, Kellie Howard, Mollie McWhorter, Heather Collins, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Heying, Leila Ritter, Kerry Deutsch, James Cox, Steven Anderson, Anup Madan, Timothy Yeatman. Pharmacodynamic stratification of metastatic colorectal cancer patients using genomic datasets. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4842. doi:10.1158/1538-7445.AM2015-4842

Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

metaXCMS: second-order analysis of untargeted metabolomics data

Mass spectrometry-based untargeted metabolomics often results in the observation of hundreds to thousands of features that are differentially regulated between sample classes. A major challenge in interpreting the data is distinguishing metabolites that are causally associated with the phenotype of interest from those that are unrelated but altered in downstream pathways as an effect. To facilitate this distinction, here we describe new software called metaXCMS for performing second-order ("meta") analysis of untargeted metabolomics data from multiple sample groups representing different models of the same phenotype. While the original version of XCMS was designed for the direct comparison of two sample groups, metaXCMS enables meta-analysis of an unlimited number of sample classes to facilitate prioritization of the data and increase the probability of identifying metabolites causally related to the phenotype of interest. metaXCMS is used to import XCMS results that are subsequently filtered, realigned, and ultimately compared to identify shared metabolites that are up- or down-regulated across all sample groups. We demonstrate the software's utility by identifying histamine as a metabolite that is commonly altered in three different models of pain. metaXCMS is freely available at http://metlin.scripps.edu/metaxcms/.

Adaptation of cells to new environments

The evolutionary success of an organism is a testament to its inherent capacity to keep pace with environmental conditions that change over short and long periods. Mechanisms underlying adaptive processes are being investigated with renewed interest and excitement. This revival is partly fueled by powerful technologies that can probe molecular phenomena at a systems scale. Such studies provide spectacular insight into the mechanisms of adaptation, including rewiring of regulatory networks via natural selection of horizontal gene transfers, gene duplication, deletion, readjustment of kinetic parameters, and myriad other genetic reorganizational events. Here, we discuss advances in prokaryotic systems biology from the perspective of evolutionary principles that have shaped regulatory networks for dynamic adaptation to environmental change.

Resistance of a single domain wall in (Co/Pt)7 multilayer nanowires

Single (Co/Pt)_{7} multilayer nanowires prepared by electron beam lithography with perpendicular magnetic anisotropy are locally modified by means of Ga-ion implantation generating 180 degrees domain walls which are pinned at the edges of underlying thin Pt wires. Since we can exclude contributions from the anisotropic and the Lorentz magnetoresistance this allows us to determine the resistance of a single domain wall at room temperature. We find a positive relative resistance increase of DeltaR/R=1.8% inside the domain wall which agrees well with the model of Levy and Zhang [Phys. Rev. Lett. 79, 5110 (1997)10.1103/PhysRevLett.79.5110].