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Accurate and early detection of oncogenic markers may one day be the key to fighting cancer. However, with complex workflows, long turnaround times, and numerous user touch points of most sequencing platforms does not make the process attainable. In contrast, the fully automated Genexus࣪ system provides a specimen-to-report workflow for cancer research with minimal user touchpoints and single day turnaround time. FFPE (formalin-fixed paraffin embedded) tissues and liquid biopsy are two of the main sample types used in oncology research. Here we report the use of the Oncomine࣪ Precision Assay (OPA) with the Genexus࣪ System which provides a comprehensive genetic profile across 50 key genes using DNA and RNA from FFPE tissues or cfTNA (cell free total nucleic acid) from liquid biopsy samples. To evaluate the nucleic acid (NA) extraction and sequencing performance of the Genexus࣪ system, contrived control samples with known variants and clinical research samples were used in the OPA FFPE and liquid biopsy workflows (n = 30). NA was quantified using the Genexus࣪ purification instrument’s onboard Qubit࣪ quantitation feature after purification. Output plates with extracted NA were transferred to the Genexus࣪ Integrated Sequencer for library preparation and sequencing using the OPA assay. Data were analyzed using the Ion torrent Genexus࣪ software to evaluate assay performance and variant calling.The OPA assay only requires 10ng of DNA and RNA from FFPE samples and 20ng of cfTNA from liquid biopsy samples. Genexus࣪ purification instrument onboard quantitation data showed successful extraction of NA exceeding the required yields for library preparation. Excess NA was automatically aliquoted into an archive plate and stored for future use. Sequencing results for four samples of FFPE or liquid biopsy were reported within 24 hours. Both Control and clinical research samples showed expected assay metrices including read coverage, molecular coverage, and uniformity. The results reported all expected variants at correct allele frequencies, including BRAF V600E, KRAS G12C, PIK3CA N345K, AKT1 etc. Overall, this study demonstrates that the Genexus࣪ system provides a user-friendly workflow with automated NA purification, quantitation, sample dilution, library preparation, sequencing, and data analysis with minimal hands-on time that can be performed with limited expertise to obtain results within 24 hours. Reliable identification of variants from control and clinical research samples of FFPE and liquid biopsy origin with optimal assay metrics demonstrates the successful use of the OPA assay and Genexus࣪ system that can be confidently used in clinical oncology research.(For Research Use Only. Not for use in diagnostic procedures.) Citation Format: Thilanka Jayaweera, Nicholas Siepert, Brian Hradecky, Emilia Ostrowska, Iris Casuga, kristy Lea, Priyanka Kshatriya, Jian Gu, Jeff Schageman, Ru Cao, Angie Cheng, Kelli Bramlett. Automation meets reliability: Use of Oncomine࣪precision assay on the Genexus࣪system for accurate identification of cancer biomarkers in FFPE and liquid biopsy samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2939.

e14614 Background: Assessing tumor-derived somatic variants from blood plasma provides minimally invasive tumor profiling, decreased cost relative to traditional tissue biopsy and rapid turn-around-time. We describe here the analytical validation of the Oncomine Pan-Cancer Cell-Free assay in a CAP-accredited, CLIA-certified laboratory. The assay is designed to detect somatic DNA single-nucleotide variants (SNV), insertions/deletions (INDEL), copy number variants (CNV), and gene fusions in cell-free total nucleic acid (cfTNA) across 52 genes. For research use only. Not for use in diagnostic procedures. Methods: We assessed the sensitivity, specificity, accuracy, and precision of the assay. Pre-characterized reference materials with alterations at known allelic frequencies (AF) were used to establish performance characteristics for each variant class followed by verification on clinical specimens. Whole blood (n = 73) from healthy (10), breast cancer (9), colorectal cancer (32), and lung cancer (22) donors were collected in K2EDTA tubes and plasma was separated within 8 hours of collection. cfTNA was isolated using the MagMAX Cell-Free Total Nucleic Acid Isolation Kit on the KingFisher Flex. Libraries were prepared following kit instructions. Templating and sequencing were performed using the Ion 550 Kit on the Ion Chef and S5 XL systems. Alignment to hg19 and variant calling were performed using Torrent Suite and Ion Reporter software. Results: We observed a sensitivity of 80% at 0.1% AF and > 99.9% at 0.5% AF for SNV/INDEL. Sensitivity was > 99.9% at 1.34 fold-change for CNV, and > 99.9% at 0.4% fusion fraction. Specificity and accuracy were > 99% for all variant classes. Precision was 98% for SNV/INDEL and > 99.9% for CNV/fusions. Analysis of donor plasma demonstrated clinical feasibility; on average, we detected 1 hotspot SNV/INDEL (range 0-4) across the 3 cancer types. For SNV/INDEL in plasma where matched tissue genotyping was available (n = 17), we observed > 99% concordance (AF range 0.09%-52%). Conclusions: We have demonstrated that this assay is a sensitive method for evaluating tumor-derived somatic variants in blood plasma. It may provide an alternative and minimally invasive method for mutation profiling.

MicroRNAs have been increasingly implicated in human cancer and interest has grown about the potential to use microRNAs to combat cancer. Lung cancer is the most prevalent form of cancer worldwide and lacks effective therapies. Here we have used both in vitro and in vivo approaches to show that the let-7 microRNA directly represses cancer growth in the lung. We find that let-7 inhibits the growth of multiple human lung cancer cell lines in culture, as well as the growth of lung cancer cell xenografts in immunodeficient mice. Using an established orthotopic mouse lung cancer model, we show that intranasal let-7 administration reduces tumor formation in vivo in the lungs of animals expressing a G12D activating mutation for the K-ras oncogene. These findings provide direct evidence that let-7 acts as a tumor suppressor gene in the lung and indicate that this miRNA may be useful as a novel therapeutic agent in lung cancer.

DNA and RNA provide valuable information in order to detect differences such as chromosomal mutations and imbalances in gene expression. Common sample types for these analyses include surgical and needle biopsies, which are very limited in material making the downstream measurement of more than one analyte rather difficult. Obtaining another biopsy, using a different section or splitting the sample can raise issues of tumor heterogeneity. Even adjacent areas of the same tumor tissue can result in a different profile so the ability to isolate multiple analytes from the same sample offer a number of benefits, which include preserving small samples and data consistency eliminating any sample to sample variation. Here we describe the efficient isolation of RNA and DNA from the same starting sample without splitting using the RecoverAll™ Multi-Sample RNA/DNA workflow, followed by versatile and informative downstream analysis. This workflow was applied to FFPE tissue samples, fine needle aspirates, degraded samples as well as fresh cultured cells from a number of different cancer types. As an example, we have shown that DNA and RNA can be isolated from the same non-small cell lung adenocarcinoma FFPE tumor sample and with the recovered analytes, both mutation analysis and fusion transcript detection can be performed by either qPCR or next-generation sequencing (NGS). Citation Format: Angie Cheng, Natalie Hernandez, Mu Li, Charmaine San Jose Hinahon, Susan Magdaleno. Maximize genomic analysis through dual recovery of DNA and RNA from the same clinical sample. [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 4755. doi:10.1158/1538-7445.AM2015-4755

The presence of certain chromosomal rearrangements and the subsequent fusion gene derived from translocations has been implicated in a number of cancers. Hundreds of translocations have been described in the literature recently but the need to efficiently detect and further characterize these chromosomal translocations is growing exponentially. The two main methods to identify and monitor translocations, fluorescent in situ hybridization (FISH) and comparative genomic hybridization (CGH) are challenging, labor intensive, the information obtained is limited, and sensitivity is rather low. Common sample types for these analyses are biopsies or small tumors, which are very limited in material making the downstream measurement of more than one analyte rather difficult; obtaining another biopsy, using a different section or splitting the sample can raise issues of tumor heterogeneity. The ability to study mutation status as well as measuring fusion transcript expression from the same sample is powerful because you're maximizing the information obtained from a single precious sample and eliminating any sample to sample variation. Here we describe the efficient isolation of two valuable analytes, RNA and DNA, from the same starting sample without splitting, followed by versatile and informative downstream analysis. This methodology was applied to FFPE and degraded samples as well as fresh tissues and cells. DNA and RNA were recovered from the same non-small lung adenocarcinoma sample and both mutation analysis, as well as fusion transcript detection was performed using the Ion Torrent PGM™ platform on the same Ion 318™ chip. Using 10ng of DNA and 10ng of RNA input, we applied the Ion AmpliSeq™ Colon and Lung Cancer panel to analyze over 500 COSMIC mutations in 22 genes and the Ion AmpliSeq™ RNA Lung Fusion panel to detect 40 different fusion transcripts. Citation Format: Angie Cheng, Varun Bagai, Joey Cienfuegos, Natalie Hernandez, Mu Li, Jeff Schageman, Richard Fekete, Rosella Petraroli, Alexander Vlassov, Susan Magdaleno. Hotspot mutation and fusion transcript detection from the same non-small lung adenocarcinoma sample. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3580. doi:10.1158/1538-7445.AM2014-3580

Chromosomal translocations and corresponding gene fusions play an important role in the initiation of tumorigenesis and these processes have been strongly associated with distinct tumor subtypes. The recent association of ALK, ROS and RET fusion transcripts as lung tumor therapy predictive biomarkers has increased the need of a technology that could detect these biomarkers starting from limited amount of material. Life Technologies and OncoNetwork consortium collaborated for the development of a lung fusion panel based on Ion AmpliSeq™ RNA chemistry. The OncoNetwork consortium is comprised of twelve -translational cancer research institutes with many years of experience in adopting the latest molecular techniques for lung therapy research. Material and Methods: Consortia's requirements for the panel development : 1) detect all variants of ALK, ROS1, or RET fusion transcripts described in COSMIC in a single reaction using 10 ng of total RNA 2) Include 5′ and 3′ ALK, ROS1, RET gene expression assays as an indicator of a translocation at this gene. 3) Include endogenous RNA assay controls to determine if the quality of the results could be affected by RNA quality. 4) Provide similar results on archived FFPE samples tested by FISH. Human lung adenocarcinoma cell lines H2228 (EML4-ALK positive), HCC78 (SLC4A2-ROS1 positive ) ,LC-2/ad (CCDC6-RET positive) and Ambion® FirstChoice® Human Brain Reference (HBR) RNA was used as positive and negative control for the study. Formalin fixed paraffin embedded (FFPE) tissue was isolated using different extraction methods. After amplification using Ion AmpliSeq™ RNA chemistry samples were sequenced on the Ion Torrent PGM™ sequencer using the Ion PGM™ 200 Sequencing Kit. The presence of the fusions was confirmed by custom TaqMan® gene expression assays when possible. Preliminary results of the panel on ALK or ROS1 or RET positive cell lines and FFPE archived cancer research samples gave good concordance with FISH results. Expected negative samples were confirmed negative. We found a KIF5B-RET fusion positive sample in a sample not previously tested for RET fusions. Two of the expected positive samples by FISH were found negative due to limited amount to tumor cells present in the sample. Cell line RNA dilutions were performed to determine the panel's limit of detection. We demonstrate a limit of detection of 1 % tumor RNA in the presence of 99 % normal RNA using the panel with 10 ng of RNA extracted by cell lines. Gene expression controls work well as an indicator of the RNA quality and of the translocation presence. The Ion AmpliSeq™ RNA lung cancer fusion panel workflow is easier and faster to perform in comparison to the FISH method. The results obtained to date are highly encouraging for panel to be used in the clinical research setting. More data needs to be analyzed before a final conclusion is made. Citation Format: Susan M. Magdaleno, Angie Cheng, Rosella Petraroli, Orla Sheils, Bastiaan Tops, Delphine Le Corre, Henriette Kurth, Helene Blons, Eliana Amato, Andrea Mafficini, Anna Maria Rachiglio, Anne Reimann, Christoph Noppen, Chrysanthi Ainali, Jin Katayama, Renato Franco, Harriet Feilotter, Jeoffrey Schageman, Ian Cree, Andrew Felton, Jose Luis Costa, Alain Rico, Aldo Scarpa, Jose Carlos Machado, Kazuto Nishio, Nicola Normanno, Marjolijn Ligtenberg, Cecily P. Vaughn, Ludovic Lacroix, Pierre Laurent-Puig. The OncoNetwork Consortium: A global collaborative research study on the development and verification of an Ion AmpliSeq RNA gene lung fusion panel. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3575. doi:10.1158/1538-7445.AM2014-3575

Gene expression profiling of cancer cells has become increasingly common over the past five years. Especially important is identifying changes in gene expression caused by drug treatment leading to side populations with altered pathways. These populations can escape drug treatment and lead to recurrence. Characterizing gene expression of proliferating cells requires a method of identifying proliferation while simultaneously maintaining high quality RNA. Typically, cells are screened in a drug panel in the presence of tritiated thymidine or BrdU to identify the drug resistance in the proliferating population. Proliferation detection with these methods is neither rapid nor does it yield high quality RNA for profiling. A new proliferation method based on click chemistry using an alkyne modified thymidine analog (EdU), which can be used to rapidly identify replicating cells appears ideally suited for this application; however, copper used for the catalysis of the click reaction causes undesired degradation of RNA. Recent improvements to the copper based click reaction are presented here whereby the copper is tightly controlled, resulting in higher quality RNA useful for sequencing. In this study we demonstrate gene expression changes in the proliferating population of a drug resistant cancer cell line compared to the parental cell lines. Proliferating cells were identified using an improved click reaction comprising of a copper(I) ligand combined with a picolyl modified dye azide detection reagent. Total RNA from these cells was isolated and gene expression was assessed by targeted RNA sequencing using an RNA Apoptosis panel and an RNA Cancer panel using proton based sequencing technology. Use of an improved copper “safe” click reaction for detection of nascent DNA, allows for detection of incorporated click analog for measuring proliferation and subsequent isolation of high quality RNA for use in sequence analysis. Citation Format: Scott T. Clarke, Angie Cheng, Aleksey Rukavishnikov, Michelle Yan, Upinder Singh, Kyle Gee, Susan Magdaleno. Gene expression of EdU proliferating cells made possible with improved click chemistry. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4033. doi:10.1158/1538-7445.AM2013-4033

DNA, RNA or proteins are routinely analyzed as markers to define the type and state of tumorigenicity. Each of these analytes provide a unique set of information in order to detect differences such as chromosomal mutations, imbalances in gene expression, and changes in protein signaling networks. Limited samples, such as biopsies and small tumors, are a common sample type, however, due to their small size the analysis of more than one of these analytes from the same sample can be challenging. Taking more than one sample (biopsy), or splitting a sample in order to isolate one of these anlaytes from each section raises questions regarding sample heterogeneity. This is particularly important where one section of a tumor may be different from another, and can even provide misleading information regarding the correlation of DNA, RNA or protein markers. Another issue raised with splitting samples is that two of the analytes are lost when the third is isolated. This can lead to the loss of important information, and the low yield can limit the number and methods used for analysis. Being able to analyze DNA, RNA and proteins from the same sample is particularly crucial during biomarker discovery and correlation. Here we describe a new, quick and easy to use method to isolate DNA, RNA and proteins from small sized tumor and normal adjacent tissue and demonstrate that not only is the entire sample maintained giving us more sample for analysis (no analyte is lost when isolating the other), but there is no concern regarding heterogeneity. Using these samples we demonstrate the correlation of DNA, mRNA, miRNA and protein using Next Generation Sequencing, qPCR, Western and ELISA and associate these with tumorigenicity. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3205. doi:1538-7445.AM2012-3205