Generic Protocols for the Analytical Validation of Next-Generation Sequencing-Based ctDNA Assays: A Joint Consensus Recommendation of the BloodPAC's Analytical Variables Working Group.

Liquid biopsy, particularly the analysis of circulating tumor DNA (ctDNA), has demonstrated considerable promise for numerous clinical intended uses. Successful validation and commercialization of novel ctDNA tests have the potential to improve the outcomes of patients with cancer. The goal of the Blood Profiling Atlas Consortium (BloodPAC) is to accelerate the development and validation of liquid biopsy assays that will be introduced into the clinic. To accomplish this goal, the BloodPAC conducts research in the following areas: Data Collection and Analysis within the BloodPAC Data Commons; Preanalytical Variables; Analytical Variables; Patient Context Variables; and Reimbursement. In this document, the BloodPAC's Analytical Variables Working Group (AV WG) attempts to define a set of generic analytical validation protocols tailored for ctDNA-based Next-Generation Sequencing (NGS) assays. Analytical validation of ctDNA assays poses several unique challenges that primarily arise from the fact that very few tumor-derived DNA molecules may be present in circulation relative to the amount of nontumor-derived cell-free DNA (cfDNA). These challenges include the exquisite level of sensitivity and specificity needed to detect ctDNA, the potential for false negatives in detecting these rare molecules, and the increased reliance on contrived samples to attain sufficient ctDNA for analytical validation. By addressing these unique challenges, the BloodPAC hopes to expedite sponsors' presubmission discussions with the Food and Drug Administration (FDA) with the protocols presented herein. By sharing best practices with the broader community, this work may also save the time and capacity of FDA reviewers through increased efficiency.

Evidence of an epigenetic origin for high-risk 1q21 copy number aberrations in multiple myeloma.

Multiple myeloma is a B-cell malignancy stratified in part by cytogenetic abnormalities, including the high-risk copy number aberrations (CNAs) of +1q21 and 17p(-). To investigate the relationship between 1q21 CNAs and DNA hypomethylation of the 1q12 pericentromeric heterochromatin, we treated in vitro peripheral blood cultures of 5 patients with balanced constitutional rearrangements of 1q12 and 5 controls with the hypomethylating agent 5-azacytidine. Using G-banding, fluorescence in situ hybridization, and spectral karyotyping, we identified structural aberrations and copy number gains of 1q21 in the treated cells similar to those found in patients with cytogenetically defined high-risk disease. Aberrations included 1q12 triradials, amplifications of regions juxtaposed to 1q12, and jumping translocations 1q12. Strikingly, all 5 patients with constitutional 1q12 rearrangements showed amplifications on the derivative chromosomes distal to the inverted or translocated 1q12 region, including MYCN in 1 case. At the same time, no amplification of the 1q21 region was found when the 1q12 region was inverted or absent. These findings provide evidence that the hypomethylation of the 1q12 region can potentially amplify any genomic region juxtaposed to it and mimic CNAs found in the bone marrow of patients with high-risk disease.

Jumping translocations of 1q12 in multiple myeloma: a novel mechanism for deletion of 17p in cytogenetically defined high-risk disease.

Multiple myeloma (MM) is a B-cell malignancy driven in part by increasing copy number alterations (CNAs) during disease progression. Prognostically significant CNAs accumulate during clonal evolution and include gains of 1q21 and deletions of 17p, among others. Unfortunately, the mechanisms underlying the accumulation of CNAs and resulting subclonal heterogeneity in high-risk MM are poorly understood. To investigate the impact of jumping translocations of 1q12 (JT1q12) on receptor chromosomes (RCs) and subsequent clonal evolution, we analyzed specimens from 86 patients selected for unbalanced 1q12 aberrations by G-banding. Utilizing spectral karyotyping and locus-specific fluorescence in situ hybridization, we identified 10 patients with unexpected focal amplifications of an RC that subsequently translocated as part of a sequential JT1q12 to one or more additional RCs. Four patients exhibited amplification and translocation of 8q24 (MYC), 3 showed amplification of 16q11, and 1 each displayed amplification of 18q21.3 (BCL2), 18q23, or 4p16 (FGFR3). Unexpectedly, in 6 of 14 patients with the combination of the t(4;14) and deletion of 17p, we identified the loss of 17p as resulting from a JT1q12. Here, we provide evidence that the JT1q12 is a mechanism for the simultaneous gain of 1q21 and deletion of 17p in cytogenetically defined high-risk disease.

Enhancing cancer clonality analysis with integrative genomics.

INTRODUCTION: It is understood that cancer is a clonal disease initiated by a single cell, and that metastasis, which is the spread of cancer from the primary site, is also initiated by a single cell. The seemingly natural capability of cancer to adapt dynamically in a Darwinian manner is a primary reason for therapeutic failures. Survival advantages may be induced by cancer therapies and also occur as a result of inherent cell and microenvironmental factors. The selected "more fit" clones outmatch their competition and then become dominant in the tumor via propagation of progeny. This clonal expansion leads to relapse, therapeutic resistance and eventually death. The goal of this study is to develop and demonstrate a more detailed clonality approach by utilizing integrative genomics. METHODS: Patient tumor samples were profiled by Whole Exome Sequencing (WES) and RNA-seq on an Illumina HiSeq 2500 and methylation profiling was performed on the Illumina Infinium 450K array. STAR and the Haplotype Caller were used for RNA-seq processing. Custom approaches were used for the integration of the multi-omic datasets. RESULTS: Reported are major enhancements to CloneViz, which now provides capabilities enabling a formal tumor multi-dimensional clonality analysis by integrating: i) DNA mutations, ii) RNA expressed mutations, and iii) DNA methylation data. RNA and DNA methylation integration were not previously possible, by CloneViz (previous version) or any other clonality method to date. This new approach, named iCloneViz (integrated CloneViz) employs visualization and quantitative methods, revealing an integrative genomic mutational dissection and traceability (DNA, RNA, epigenetics) thru the different layers of molecular structures. CONCLUSION: The iCloneViz approach can be used for analysis of clonal evolution and mutational dynamics of multi-omic data sets. Revealing tumor clonal complexity in an integrative and quantitative manner facilitates improved mutational characterization, understanding, and therapeutic assignments.

Risk factors for MDS and acute leukemia following total therapy 2 and 3 for multiple myeloma.

Lenalidomide has been linked to myelodysplastic syndrome (MDS) after autotransplants for myeloma. Total therapy trials (TT; TT2(-/+) thalidomide) and TT3 (TT3a with bortezomib, thalidomide; TT3b with additional lenalidomide) offered the opportunity to examine the contribution of these immune-modulatory agents to MDS-associated cytogenetic abnormalities (MDS-CA) and clinical MDS or acute leukemia ("clinical MDS/AL"). Of 1080 patients with serial cytogenetic studies, MDS-CA occurred in 11% and clinical MDS/AL in 3%. Risk features of MDS-CA included TT3b, age ≥65 years, male gender, levels of ß-2-microglobulin >5.5 mg/L, and multiple myeloma relapse. Clinical MDS/AL occurred less frequently in the control arm of TT2 and more often with TT3a and TT3b. Since MDS-CA often antedated clinical disease, periodic cytogenetic monitoring is recommended. Larger CD34 quantities should be collected upfront as the risk of MDS could be reduced by applying higher CD34 doses with transplant. Thus, treatment, host, and myeloma features could be linked to MDS development after therapy for this malignancy. This trial was registered at www.clinicaltrials.gov: TT3A: NCT00081939, TT3B: NCT00572169.

Revealing the inherent heterogeneity of human malignancies by variant consensus strategies coupled with cancer clonal analysis.

Tumors are heterogeneous in composition. They are composed of cancer cells proper, along with stromal elements that collectively form a microenvironment, all of which are necessary to nurture the malignant process. In addition, many of the stromal cells are modified to support the unique needs of the malignant state. Tumors are composed of a variety of clones or subpopulations of cancer cells, which may differ in karyotype, growth rate, expression of cell surface markers, sensitivity to therapeutics, etc. New tools and methods to provide an improved understanding of tumor clonal architecture are needed to guide therapy.

Leveraging the new with the old: providing a framework for the integration of historic microarray studies with next generation sequencing.

Next Generation Sequencing (NGS) methods are rapidly providing remarkable advances in our ability to study the molecular profiles of human cancers. However, the scientific discovery offered by NGS also includes challenges concerning the interpretation of large and non-trivial experimental results. This task is potentially further complicated when a multitude of molecular profiling modalities are available, with the goal of a more integrative and comprehensive analysis of the cancer biology.

A Microdissection Protocol for Proteogenomic Analysis of Histological Sections to Advance Drug Development.

Combining proteogenomics with laser capture microdissection (LCM) in cancer research offers a targeted way to explore the intricate interactions between tumor cells and the different microenvironment components. This is especially important for immuno-oncology (IO) research where improvements in the predictability of IO-based drugs are sorely needed, and depends on a better understanding of the spatial relationships involving the tumor, blood supply, and immune cell interactions, in the context of their associated microenvironments. LCM is used to isolate and obtain distinct histological cell types, which may be routinely performed on complex and heterogeneous solid tumor specimens. Once cells have been captured, nucleic acids and proteins may be extracted for in-depth multimodality molecular profiling assays. Optimizing the minute tissue quantities from LCM captured cells is challenging. Following the isolation of nucleic acids, RNA-seq may be performed for gene expression and DNA sequencing performed for the discovery and analysis of actionable mutations, copy number variation, methylation profiles, etc. However, there remains a need for highly sensitive proteomic methods targeting small-sized samples. A significant part of this protocol is an enhanced liquid chromatography mass spectrometry (LC-MS) analysis of micro-scale and/or nano-scale tissue sections. This is achieved with a silver-stained one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) approach developed for LC-MS analysis of fresh-frozen tissue specimens obtained via LCM. Included is a detailed in-gel digestion method adjusted and specifically designed to maximize the proteome coverage from amount-limited LCM samples to better facilitate in-depth molecular profiling. Described is a proteogenomic approach leveraged from microdissected fresh frozen tissue. The protocols may also be applicable to other types of specimens having limited nucleic acids, protein quantity, and/or sample volume.

Towards Preanalytical Best Practices for Liquid Biopsy Studies: A BLOODPAC Landscape Analysis.

BLOODPAC is a public-private consortium that develops best practices, coordinates clinical and translational research, and manages the BLOODPAC Data Commons to broadly support the liquid biopsy community and accelerate regulatory review to aid patient accessibility. BLOODPAC previously recommended 11 preanalytical minimal technical data elements (MTDEs) for BLOODPAC-sponsored studies and data submitted to BLOODPAC Data Commons. The current landscape analysis evaluates the overlap of the BLOODPAC MTDEs with current best practices, guidelines, and standards documents related to clinical and research liquid biopsy applications. Our findings indicate an existing high degree of concordance among these documents. Where differences exist, the BLOODPAC preanalytical MTDEs can be considered a minimal practicable set for organizations to utilize. These MTDEs were developed following extensive examination of best practices and iterative conversations with the U.S. FDA. BLOODPAC recommends the use of these MTDEs in submissions to data commons and to support liquid biopsy clinical trials and research globally.

Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing.

Next-generation sequencing (NGS) has revolutionized genomic research by enabling high-throughput, cost-effective genome and transcriptome sequencing accelerating personalized medicine for complex diseases, including cancer. Whole genome/transcriptome sequencing (WGS/WTS) provides comprehensive insights, while targeted sequencing is more cost-effective and sensitive. In comparison to short-read sequencing, which still dominates the field due to high speed and cost-effectiveness, long-read sequencing can overcome alignment limitations and better discriminate similar sequences from alternative transcripts or repetitive regions. Hybrid sequencing combines the best strengths of different technologies for a more comprehensive view of genomic/transcriptomic variations. Understanding each technology's strengths and limitations is critical for translating cutting-edge technologies into clinical applications. In this study, we sequenced DNA and RNA libraries of reference samples using various targeted DNA and RNA panels and the whole transcriptome on both short-read and long-read platforms. This study design enables a comprehensive analysis of sequencing technologies, targeting protocols, and library preparation methods. Our expanded profiling landscape establishes a reference point for assessing current sequencing technologies, facilitating informed decision-making in genomic research and precision medicine.

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

BACKGROUND: Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. METHODS: Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. RESULTS: Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. CONCLUSION: A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

Metronomic therapy is an effective salvage treatment for heavily pre-treated relapsed/refractory multiple myeloma.

Relapsed/refractory multiple myeloma represents a major challenge in multiple myeloma therapy. For patients with relapsed/refractory multiple myeloma, we developed a treatment schema of metronomically scheduled drug therapy. We identified 186 patients who had been treated with metronomic therapy between March 2004 and January 2012 with a median follow up of 24.2 months. Median age was 61 years (range 36-83). Median number of prior therapies was 14 (range 1-51). Median number of completed metronomic therapy cycles was 1 (range 1-5), while 45 of 186 (25%) received 2 or more cycles. Responses included complete remission in 11 of 186 patients (6%), very good partial remission in 12 of 186 (7%), partial remission in 65 of 179 (36%), and minimal response in 29 of 186 (16%), for an overall response rate of 63% (117 of 186). Median overall survival and progression-free survival were 11.2 and 3.6 months, respectively. Hematologic toxicity grading was problematic as 146 of 186 (78%) of patients presented with at least grade 2 thrombocytopenia within 90 days prior to starting metronomic therapy. Grade 4 leukopenia, anemia, and/or thrombocytopenia following metronomic therapy occurred in 108 of 186 (58%), 12 of 186 (6%), and 147 of 186 (79%) patients, respectively. Incidence of grade 3-4 neutropenic fever was 4 of 186 (2%). Most patients (177 of 186, 95%) were treated in an outpatient unit and secondary admissions due to regimen-related toxicity occurred in 37 of 186 (20%). Treatment-related mortality was evident in 2 of 186 (1%). In conclusion, metronomic therapy is an effective late salvage treatment in relapsed/refractory multiple myeloma, with a high overall response rate and a favorable toxicity profile.

Assessments of tumor mutational burden estimation by targeted panel sequencing: A comprehensive simulation analysis.

Tumor mutational burden (TMB), when at a high level, is an emerging indicative factor of sensitivity to immune checkpoint inhibitors. Previous studies have shown that the more affordable and accurate targeted panels can be used to measure TMB as a substitute for whole exome sequencing (WES). However, additional processes, such as hotspot mutations exclusion and TMB adjustment, are usually required to deal with the effect of the limited panel sizes. A comprehensive investigation of the effective factors is needed for accurate TMB estimation by targeted panels. In this study, we quantitatively evaluated the variances of TMB values calculated by WES and targeted panels using 10,000 simulated targeted panels with panel sizes ranging from 0.2 to 3.1 million bases. With The Cancer Genome Atlas (TCGA) cancer samples and mutation profiles, we fixed regressions on WES-TMBs and panel-TMBs to assess the performance of a given targeted panel. Panel size was found as one of the major effective factors of TMB estimation. Meanwhile, by investigating the well-performing small panels that reported TMB values similar to those of WES, we demonstrated the evidence of the cancer type-specific impacts of genes on TMB estimation and identified high-impact gene sets for different cancer types based on the TCGA data. This study revealed the quantitative correlations between TMB variance and panel size, and the potential impacts of individual genes on TMB estimation. Our results suggested that for cancer patients diagnosed using targeted panels, it would be highly beneficial to have the capability to directly measure TMB from the targeted sequencing data. This would greatly assist in making decisions regarding the use of immunotherapies.

Contrived Materials and a Data Set for the Evaluation of Liquid Biopsy Tests: A Blood Profiling Atlas in Cancer (BLOODPAC) Community Study.

The Blood Profiling Atlas in Cancer (BLOODPAC) Consortium is a collaborative effort involving stakeholders from the public, industry, academia, and regulatory agencies focused on developing shared best practices on liquid biopsy. This report describes the results from the JFDI (Just Freaking Do It) study, a BLOODPAC initiative to develop standards on the use of contrived materials mimicking cell-free circulating tumor DNA, to comparatively evaluate clinical laboratory testing procedures. Nine independent laboratories tested the concordance, sensitivity, and specificity of commercially available contrived materials with known variant-allele frequencies (VAFs) ranging from 0.1% to 5.0%. Each participating laboratory utilized its own proprietary evaluation procedures. The results demonstrated high levels of concordance and sensitivity at VAFs of >0.1%, but reduced concordance and sensitivity at a VAF of 0.1%; these findings were similar to those from previous studies, suggesting that commercially available contrived materials can support the evaluation of testing procedures across multiple technologies. Such materials may enable more objective comparisons of results on materials formulated in-house at each center in multicenter trials. A unique goal of the collaborative effort was to develop a data resource, the BLOODPAC Data Commons, now available to the liquid-biopsy community for further study. This resource can be used to support independent evaluations of results, data extension through data integration and new studies, and retrospective evaluation of data collection.

Proteomic profiling of H-Ras-G12V induced hypertrophic cardiomyopathy in transgenic mice using comparative LC-MS analysis of thin fresh-frozen tissue sections.

Determination of disease-relevant proteomic profiles from limited tissue specimens, such as pathological biopsies and tissues from small model organisms, remains an analytical challenge and a much needed clinical goal. In this study, a transgenic mouse disease model of cardiac-specific H-Ras-G12V induced hypertrophic cardiomyopathy provided a system to explore the potential of using mass spectrometry (MS)-based proteomics to obtain a disease-relevant molecular profile from amount-limited specimens that are routinely used in pathological diagnosis. Our method employs a two-stage methanol-assisted solubilization to digest lysates prepared from 8-µm-thick fresh-frozen histological tissue sections of diseased/experimental and normal/control hearts. Coupling this approach with a nanoflow reversed-phase liquid chromatography (LC) and a hybrid linear ion trap/Fourier transform-ion cyclotron resonance MS resulted in the identification of 704 and 752 proteins in hypertrophic and wild-type (control) myocardium, respectively. The disease driving H-Ras protein along with vimentin were unambiguously identified by LC-MS in hypertrophic myocardium and cross-validated by immunohistochemistry and western blotting. The pathway analysis involving proteins identified by MS showed strong association of proteomic data with cardiovascular disease. More importantly, the MS identification and subsequent cross-validation of Wnt3a and ß-catenin, in conjunction with IHC identification of phosphorylated GSK-3ß and nuclear localization of ß-catenin, provided evidence of Wnt/ß-catenin canonical pathway activation secondary to Ras activation in the course of pathogenic myocardial hypertrophic transformation. Our method yields results indicating that the described proteomic approach permits molecular discovery and assessment of differentially expressed proteins regulating H-Ras induced hypertrophic cardiomyopathy. Selected proteins and pathways can be further investigated using immunohistochemical techniques applied to serial tissue sections of similar or different origin.

Ultra-deep sequencing data from a liquid biopsy proficiency study demonstrating analytic validity.

Recently we reported the accuracy and reproducibility of circulating tumor DNA (ctDNA) assays using a unique set of reference materials, associated analytical framework, and suggested best practices. With the rapid adoption of ctDNA sequencing in precision oncology, it is critical to understand the analytical validity and technical limitations of this cutting-edge and medical-practice-changing technology. The SEQC2 Oncopanel Sequencing Working Group has developed a multi-site, cross-platform study design for evaluating the analytical performance of five industry-leading ctDNA assays. The study used tailor-made reference samples at various levels of input material to assess ctDNA sequencing across 12 participating clinical and research facilities. The generated dataset encompasses multiple key variables, including a broad range of mutation frequencies, sequencing coverage depth, DNA input quantity, etc. It is the most comprehensive public-facing dataset of its kind and provides valuable insights into ultra-deep ctDNA sequencing technology. Eventually the clinical utility of ctDNA assays is required and our proficiency study and corresponding dataset are needed steps towards this goal.

An advanced molecular medicine case report of a rare human tumor using genomics, pathomics, and radiomics.

Background: Pulmonary Sclerosing Pneumocytoma (PSP) is a rare tumor of the lung with a low malignant potential that primarily affects females. Initial studies of PSP focused primarily on analyzing features uncovered using conventional X-ray or CT imaging. In recent years, because of the widespread use of next-generation sequencing (NGS), the study of PSP at the molecular-level has emerged. Methods: Analytical approaches involving genomics, radiomics, and pathomics were performed. Genomics studies involved both DNA and RNA analyses. DNA analyses included the patient's tumor and germline tissues and involved targeted panel sequencing and copy number analyses. RNA analyses included tumor and adjacent normal tissues and involved studies covering expressed mutations, differential gene expression, gene fusions and molecular pathways. Radiomics approaches were utilized on clinical imaging studies and pathomics techniques were applied to tumor whole slide images. Results: A comprehensive molecular profiling endeavor involving over 50 genomic analyses corresponding to 16 sequencing datasets of this rare neoplasm of the lung were generated along with detailed radiomic and pathomic analyses to reveal insights into the etiology and molecular behavior of the patient's tumor. Driving mutations (AKT1) and compromised tumor suppression pathways (TP53) were revealed. To ensure the accuracy and reproducibility of this study, a software infrastructure and methodology known as NPARS, which encapsulates NGS and associated data, open-source software libraries and tools including versions, and reporting features for large and complex genomic studies was used. Conclusion: Moving beyond descriptive analyses towards more functional understandings of tumor etiology, behavior, and improved therapeutic predictability requires a spectrum of quantitative molecular medicine approaches and integrations. To-date this is the most comprehensive study of a patient with PSP, which is a rare tumor of the lung. Detailed radiomic, pathomic and genomic molecular profiling approaches were performed to reveal insights regarding the etiology and molecular behavior. In the event of recurrence, a rational therapy plan is proposed based on the uncovered molecular findings.

Effect of Antigen Retrieval on Genomic DNA From Immunodissected Samples.

Immunohistochemical (IHC) staining is an established technique for visualizing proteins in tissue sections for research studies and clinical applications. IHC is increasingly used as a targeting strategy for procurement of labeled cells via tissue microdissection, including immunodissection, computer-aided laser dissection (CALD), expression microdissection (xMD), and other techniques. The initial antigen retrieval (AR) process increases epitope availability and improves staining characteristics; however, the procedure can damage DNA. To better understand the effects of AR on DNA quality and quantity in immunodissected samples, both clinical specimens (KRAS gene mutation positive cases) and model system samples (lung cancer patient-derived xenograft tissue) were subjected to commonly employed AR methods (heat induced epitope retrieval [HIER], protease digestion) and the effects on DNA were assessed by Qubit, fragment analysis, quantitative PCR, digital droplet PCR (ddPCR), library preparation, and targeted sequencing. The data showed that HIER resulted in optimal IHC staining characteristics, but induced significant damage to DNA, producing extensive fragmentation and decreased overall yields. However, neither of the AR methods combined with IHC prevented ddPCR amplification of small amplicons and gene mutations were successfully identified from immunodissected clinical samples. The results indicate for the first time that DNA recovered from immunostained slides after standard AR and IHC processing can be successfully employed for genomic mutation analysis via ddPCR and next-generation sequencing (NGS) short-read methods.

Microdissection Methods Utilizing Single-Cell Subtype Analysis and the Impact on Precision Medicine.

Improving the utilization of tumor tissue from diagnostic biopsies is an unmet medical need. This is especially relevant today in the rapidly evolving precision oncology field where tumor genotyping is often essential for the indication of many advanced and targeted therapies. National Comprehensive Cancer Network (NCCN) guidelines now mandate molecular testing for clinically actionable targets in certain malignancies. Utilizing advanced stage lung cancer as an example, an improved genotyping approach for solid tumors is possible. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from formalin-fixed paraffin-embedded (FFPE) specimens sharing similar characteristics, in other words, single-cell subtype analysis. The shared characteristics can include immunostaining status, cell phenotype, and/or spatial location within a histological section. Synergy between microdissection and droplet digital PCR (ddPCR) enhances the molecular analysis. We demonstrate here a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time- and cost-efficient manner, using immunostain targeting as an example.

Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples.

BACKGROUND: Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized diploid cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to different laboratories for targeted sequencing analysis by four oncopanels, and variants resulting from technical error were identified. RESULTS: Tissue sections that fail more frequently show low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces are more likely to show FFPE-specific errors, akin to "edge effects" seen in histology, while the inner samples display no quality degradation related to fixation time. CONCLUSIONS: To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence.