Search

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.

Mapping of protein signaling networks within tumors can identify new targets for therapy and provide a means to stratify patients for individualized therapy. Despite advances in combination chemotherapy, the overall survival for childhood rhabdomyosarcoma remains ∼60%. A critical goal is to identify functionally important protein signaling defects associated with treatment failure for the 40% nonresponder cohort. Here, we show, by phosphoproteomic network analysis of microdissected tumor cells, that interlinked components of the Akt/mammalian target of rapamycin (mTOR) pathway exhibited increased levels of phosphorylation for tumors of patients with short-term survival. Specimens (n = 59) were obtained from the Children's Oncology Group Intergroup Rhabdomyosarcoma Study (IRS) IV, D9502 and D9803, with 12-year follow-up. High phosphorylation levels were associated with poor overall and poor disease-free survival: Akt Ser473 (overall survival P < 0.001, recurrence-free survival P < 0.0009), 4EBP1 Thr37/46 (overall survival P < 0.0110, recurrence-free survival P < 0.0106), eIF4G Ser1108 (overall survival P < 0.0017, recurrence-free survival P < 0.0072), and p70S6 Thr389 (overall survival P < 0.0085, recurrence-free survival P < 0.0296). Moreover, the findings support an altered interrelationship between the insulin receptor substrate (IRS-1) and Akt/mTOR pathway proteins (P < 0.0027) for tumors from patients with poor survival. The functional significance of this pathway was tested using CCI-779 in a mouse xenograft model. CCI-779 suppressed phosphorylation of mTOR downstream proteins and greatly reduced the growth of two different rhabdomyosarcoma (RD embryonal P = 0.00008; Rh30 alveolar P = 0.0002) cell lines compared with controls. These results suggest that phosphoprotein mapping of the Akt/mTOR pathway should be studied further as a means to select patients to receive mTOR/IRS pathway inhibitors before administration of chemotherapy. [Cancer Res 2007;67(7):3431–40]

Supplementary Table 2 from Phosphoprotein Pathway Mapping: Akt/Mammalian Target of Rapamycin Activation Is Negatively Associated with Childhood Rhabdomyosarcoma Survival

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity, and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments, and proficiency testing on standardized cell line–derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas below this limit detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false-negatives) were more common than erroneous candidates (false-positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best-practice guidelines and provides a resource for precision oncology., Editorial summary: Reliable detection of mutations below 0.5% variant allele frequency remains a key challenge for circulating tumor DNA sequencing assays.

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.

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.

Advances in high-throughput sequencing have revolutionized the manner with which we can study T cell responses. We describe a woman who received a human papillomavirus (HPV) therapeutic vaccine called PepCan, and experienced complete resolution of her cervical high-grade squamous intraepithelial lesion. By performing bulk T cell receptor (TCR) β deep sequencing of peripheral blood mononuclear cells before and after 4 vaccinations, 70 putatively vaccine-specific clonotypes were identified for being significantly increased using a beta-binomial model. In order to verify the vaccine-specificity of these clonotypes, T cells with specificity to a region, HPV 16 E6 91-115, previously identified to be vaccine-induced using an interferon-γ enzyme-linked immunospot assay, were sorted and analyzed using single-cell RNA-seq and TCR sequencing. HPV specificity in 60 of the 70 clonotypes identified to be vaccine-specific was demonstrated. TCR β bulk sequencing of the cervical liquid-based cytology samples and cervical formalin-fixed paraffin-embedded samples before and after 4 vaccinations demonstrated the presence of these HPV-specific T cells in the cervix. Combining traditional and cutting-edge immunomonitoring techniques enabled us to demonstrate expansion of HPV-antigen specific T cells not only in the periphery but also in the cervix. Such an approach should be useful as a novel approach to assess vaccine-specific responses in various anatomical areas.

Background Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. Results In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5–100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. Conclusion These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

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 normal 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. Tissue sections that failed more frequently showed low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces were more likely to show FFPE-specific errors, akin to “edge effects” seen in histology, and the depth of formalin damage was related to fixation time. To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence.

We previously demonstrated that endogenous phosphatidic acid (PA) promotes liver regeneration after acetaminophen (APAP) hepatotoxicity. Here, we hypothesized that exogenous PA is also beneficial. To test that, we treated mice with a toxic APAP dose at 0 h, followed by PA or vehicle (Veh) post-treatment. We then collected blood and liver at 6, 24, and 52 h. Post-treatment with PA 2 h after APAP protected against liver injury at 6 h, and the combination of PA and N-acetyl-l-cysteine (NAC) reduced injury more than NAC alone. Interestingly, PA did not affect canonical mechanisms of APAP toxicity. Instead, transcriptomics revealed that PA activated interleukin-6 (IL-6) signaling in the liver. Consistent with that, serum IL-6 and hepatic signal transducer and activator of transcription 3 (Stat3) phosphorylation increased in PA-treated mice. Furthermore, PA failed to protect against APAP in IL-6-deficient animals. Interestingly, IL-6 expression increased 18-fold in adipose tissue after PA, indicating that adipose is a source of PA-induced circulating IL-6. Surprisingly, however, exogenous PA did not alter regeneration, despite the importance of endogenous PA in liver repair, possibly due to its short half-life. These data demonstrate that exogenous PA is also beneficial in APAP toxicity and reinforce the protective effects of IL-6 in this model., Graphical abstract Exogenous phosphatidic acid (PA) increases interleukin-6 (IL-6) production in peripheral adipose tissue. The IL-6 then enters circulation and signals to the liver to reduce early acetaminophen (APAP)-induced liver injury.Image 1

SUMMARYThe primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next generation sequencing (NGS) method that enables more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. This advancement was enabled by designing a synthetic internal standard spike-in for each actionable mutation target, suitable for use in NGS following hybrid-capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position, in each sample. True positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.

Background: The new and emerging discipline of data science demands reproducibility, which is vital in science and presents a significant challenge for high throughput genomics. To further complicate matters, large and complex projects require collaboration by multiple investigators examining and analyzing the massive data of multiple genomic modalities from different perspectives. Today, researchers are rarely able to reproduce published genomic studies for a variety of reasons, for example: i) differences between versions of software used, ii) lack of detail regarding software parameters, iii) lack of data access, and iv) source code not provided. Here we combine our data infrastructure approach with a molecular infrastructure and apply it to the exploration of a multimodality genomic analysis of a patient with a pulmonary pneumocytoma. Methods: Open source methods are utilized that include the SQLite database with R and python packages and custom code. Results: Our approach is able to generate a wide variety of plots and tables for the purposes of exploratory data analysis (EDA) and/or other user-specific analyses, such as finding differentially expressed genes (DEGs). In addition to traditional EDA plots, the R library RCircos is used to visualize multiple NGS studies (eg, 7) in single plot. Differential gene expression (DGE) analysis takes normalized RNA-based read count data and performs a statistical analysis, to find quantitative changes in expression levels between different experimental groups. A DGE analysis report is routinely generated. An abbreviated copy number variation (CNV) report derived from an ultra-low-pass whole genome (tumor/germline) NGS approach is also generated. A Python/Jupyter Notebook utilizing a library from scikit-learn is used to generate a clustergram plot. This approach is used as part of finding the optimal number of clusters for a K-Means analysis. RNA-seq data normalized across three sample types using DESeq2 were used in this example. Finally, advanced pathway analysis is performed for the identification of activated and deactivated molecular pathways. Conclusion: The next evolution in oncology research and cancer care are being driven by data science. In the field of genomic data science, accuracy and reproducibility remains a considerable challenge due to the sheer size, complexity, and dynamic nature of the experimental data plus relative inventiveness of the quantitative biology approaches. The accuracy and reproducibility challenge does not just block the path to new scientific discoveries, more importantly, it may lead to a scenario where critical findings used for medical decision making are found to be incorrect. Our approach has been developed to meet the unmet need of improving accuracy and reproducibility in genomic data science. Specific findings related to the rare pneumocytoma tumor will be presented. Citation Format: Li Ma, Erich Peterson, Mathew Steliga, Jason Muesse, Katy Marino, Konstantinos Arnaoutakis, Ikjae Shin, Donald J. Johann. Applying reproducible genomic data science methods for the analysis of a rare tumor type [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 5038.

Lung Cancer carcinogenesis is the outcome of a field of premalignant changes that occur in the bronchial tree leading to the overt emergence of the malignant lung cancer. We sought to study the proteome of the microbiome associated with the premalignant bronchial mucosa epithelia. The overall goal is the identify functional relationships between the bronchial mucosa microbiome and the risk of developing lung cancer. We evaluated the proteome of the microbiome using mass spectrometry and specialized microbiome authentication software. This method was applied to a case-control study of plasma samples donors of physician health study who donated plasma at different times prior to the onset of Non-Small Cell Lung Cancer. We also examined bronchial mucosa tissue samples near to, and distant from, the tumor harvested from surgical lobectomy specimens. Highly significant protein biomarker differences were found in the plasma and in the tissue samples that were blindly associated with cancer. These included specific proteins from the mucosal microbiome that may have functional role in the carcinogenic process. These key diagnostic risk markers were shared between the premalignant bronchial mucosa tissue and the plasma, supporting the concept that risk markers of bronchial mucosa lung cancer carcinogenesis can be detected in the peripheral circulation. Citation Format: Rayan I. Alhammad, Ngoc B. Vuong, Weidong Zhou, Claudius Mueller, Donald J Johann Jr, Amith R. Katta, Monique V. Hoek, Fahad M. Alsaab, Alessandra Luchini, Lance Liotta. Field cancerization and microbiome in lung cancer [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 3055.

It is not clear whether disrupted age-specific hematopoiesis contributes to the complex manifestations in leukemia patients who carry identical mutations, particularly in pediatric and adult patients with similar clinical characteristics. By studying a dual-age–specific mouse model, we demonstrate that (1) loss of Pten during the fetal-to-adult hematopoiesis switch (hematopoiesis switch) causes sustained fetal hematopoiesis, resulting in death in juvenile leukemia; (2) myeloid-biased hematopoiesis in juvenile mice is associated with the sustained fetal properties of hematopoietic stem cells (HSCs); (3) the age specificity of juvenile myelomonocytic leukemia depends on the copy number of Pten and Nf1; (4) single-allelic Pten deletion during the hematopoiesis switch causes constitutive activation of MAPK in juvenile mice with Nf1 loss of heterozygosity (LOH); and (5) Nf1 LOH causes monocytosis in juvenile mice with Pten haploinsufficiency but does not cause lethality until adulthood. Our data suggest that 1 copy of Pten is sufficient to maintain an intact negative-feedback loop of the Akt pathway and HSC function in reconstitution, despite MAPK being constitutively activated in juvenile Pten+/ΔNf1LOH mice. However, 2 copies of Pten are required to maintain the integrity of the MAPK pathway in juvenile mice with Nf1 haploinsufficiency. Our data indicate that previous investigations of Pten function in wild-type mice may not reflect the impact of Pten loss in mice with Nf1 mutations or other genetic defects. We provide a proof of concept that disassociated age-specific hematopoiesis contributes to leukemogenesis and pediatric demise.

The most widely used cancer animal model is the human-murine tumor xenograft. Unbiased molecular dissection of tumor parenchyma versus stroma in human-murine xenografts is critical for elucidating dysregulated protein networks/pathways and developing therapeutics that may target these two functionally codependent compartments. Although antibody-reliant technologies (e.g., immunohistochemistry, imaging mass cytometry) are capable of distinguishing tumor-proper versus stromal proteins, the breadth or extent of targets is limited. Here, we report an antibody-free targeted cross-species glycoproteomic (TCSG) approach that enables direct dissection of human tumor parenchyma from murine tumor stroma at the molecular/protein level in tumor xenografts at a selectivity rate presently unattainable by other means. This approach was used to segment/dissect and obtain the protein complement phenotype of the tumor stroma and parenchyma of the metastatic human lung adenocarcinoma A549 xenograft, with no need for tissue microdissection prior to mass-spectrometry analysis. An extensive molecular map of the tumor proper and the associated microenvironment was generated along with the top functional N-glycosylated protein networks enriched in each compartment. Importantly, immunohistochemistry-based cross-validation of selected parenchymal and stromal targets applied on human tissue samples of lung adenocarcinoma and normal adjacent tissue is indicative of a noteworthy translational capacity for this unique approach that may facilitate identifications of novel targets for next generation antibody therapies and development of real time preclinical tumor models.

Summary The primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next-generation sequencing (NGS) method that will enable more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. To accomplish this, a synthetic internal standard spike-in was designed for each actionable mutation target, suitable for use in NGS following hybrid capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position in each sample. True-positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.

Background - The domain of precision oncology includes improving patient treatment outcomes based on the application of advanced molecular profiling methodologies to pathological specimens. To this end, optimal utilization of tumor tissue from diagnostic biopsies is an unmet medical need. This is especially relevant today since precision oncology is a rapidly evolving field where timely tumor genotyping is 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. Patients diagnosed with advanced non-small cell lung cancer (NSCLC) are commonly of an older age and have significant co-morbidities. This frequently causes clinical dilemmas regarding the ability to obtain adequate amounts of tissue for tumor genotyping. In these cases, the tumor tissue may have been obtained by an image-guided biopsy, and the diagnosis of NSCLC proper determined via cytology. In certain instances, adequate tissue for tumor genotyping and/or a more advanced mutational analysis to identify oncogenic drivers may not be available. Methods - Formalin fixed paraffin embedded (FFPE) specimens were examined using advanced immuno-based laser capture microdissection (LCM), following a formal pathology review. In preparation for droplet digital PCR (ddPCR), DNA was extracted from samples and run with a series of positive and negative controls. Results - Utilizing lung cancer as an example, an improved genotyping approach for NSCLC solid tumors was developed and tested. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from FFPE specimens sharing similar characteristics, in other words, single-cell subtype analysis. Immunostaining status, cell phenotype, and spatial location within a histological section are examples of shared characteristics that can guide cell procurement. Conclusions - Synergy between microdissection and ddPCR enhances molecular analysis. Demonstrated is a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time and cost-efficient manner, using immunohistochemistry directed LCM and ddPCR detection. Citation Format: Donald J. Johann, Ikjae Shin, Erich Peterson, Mathew Steliga, Jason Muesse, Katy Marino, Sarah Laun, Adam Roberge, Robert Weigman, Michael Emmert-Buck, Michael Tangrea. Advancing precision oncology by synergizing ddPCR with microdissection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 373.

e15083 Background: Improving patient treatment outcomes based on the application of advanced molecular profiling methodologies applied to pathological specimens is the purview of precision oncology. Optimal utilization of tumor tissue from diagnostic biopsies remains an unmet medical need. This is especially relevant today since precision oncology is a rapidly evolving field where timely tumor genotyping is 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. Patients diagnosed with advanced non-small cell lung cancer (NSCLC) are commonly of an older age and have significant co-morbidities. Clinical dilemmas regarding the ability to obtain adequate amounts of tissue for tumor genotyping frequently occur. In these cases, the tumor tissue may have been obtained by an image-guided biopsy, and the diagnosis of NSCLC proper determined via cytology. Adequate tissue for tumor genotyping and/or a more advanced mutational analysis to identify oncogenic drivers may not be available, and the opportunity to explore more optimal therapy options (eg, TKI in lieu of chemotherapy) is lost. Methods: Following a formal pathology review formalin fixed paraffin embedded (FFPE) specimens were examined using advanced immuno-based laser capture microdissection (LCM). In preparation for droplet digital PCR (ddPCR), nucleic acids were extracted from samples and run with a series of positive and negative controls. Results: Utilizing lung cancer as an example, an improved genotyping approach for NSCLC solid tumors was developed and tested. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from FFPE specimens sharing similar characteristics, in other words, single-cell subtype analysis. Immunostaining status, cell phenotype, and spatial location within a histological section are examples of shared characteristics that can guide cell procurement. Conclusions: With this approach, tumor molecular analysis is enhanced through the synergy between microdissection and ddPCR. Here we demonstrate a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time and cost-efficient manner, using immunohistochemistry-directed LCM along with the detection and absolute quantitation of mutations by ddPCR.

Introduction: Precision medicine promises to improve patient treatment outcomes based on the application of molecular profiling methodologies to pathological specimens. This approach enables the development of rationally derived therapy assignments for each individual patient's tumor (versus categorical treatment assignments). Since tumors are composed of heterogeneous cells forming clusters of subtypes, dissimilar molecular profiles may emerge depending on which region is sampled and analyzed. Additionally, a manual slide scrape may result in a reduced or nearly absent molecular signal (i.e. key driver). Clearly, for cancer there is a need for an efficient, upfront enrichment method to specifically isolate specific tumor cell populations. Immuno-Laser Capture Microdissection (immuno-LCM) is a technology based on immunohistochemistry (IHC) that can isolate specific cell types from a heterogeneous cellular population. We sought to determine the impact of various IHC chromogens on the efficacy of microdissection and downstream molecular analysis from immuno-LCM samples. Methods: Histological tissue specimens (clinical colorectal and lung cancer PDX) were processed using traditional IHC methods with a variety of chromogens, including: Vector Black, Impact Vector Red, 3-amino-9-ethylcarbazole (AEC), and 3,3'-diaminobenzidine (DAB). These chromogens were evaluated for staining quality, microdissection efficiency, biomolecular extraction, and evaluation of specific molecular targets. Results: Interestingly, DAB, the most commonly used chromogen, demonstrated a negative impact on the retrieval of biomolecules from immuno-LCM samples. However, chromogens such as Vector Black and Impact Vector Red showed much improved biomolecule extraction compared to DAB even though the yield of microdissected material was comparable. While other chromogens, such as AEC, demonstrated a greater efficiency of biomolecule extraction but showed incomplete immuno-LCM of specific IHC-stained cells. Conclusions: The data indicate that traditional IHC chromogens should be carefully considered when using immuno-LCM to analyze biomolecules. Citation Format: Sarah Laun, Adam Roberge, Robert Weigman, Aubrey Lewis, Valarie Greisman, Meeiyueh Liu, Owen Stephens, Erich Peterson, Ikjae Shin, Michael Emmert-Buck, Michael Tangrea, Donald J. Johann. Towards advanced precision oncology assays - Selection of immunohistochemistry chromogen impacts microdissection and downstream molecular analysis of archival specimens [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 2947.

e15571 Background: 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 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. Patients diagnosed with advanced non-small cell lung cancer (NSCLC) are commonly of an older age and have significant co-morbidities. This frequently causes clinical dilemmas regarding the ability to obtain adequate amounts of tissue for tumor genotyping. In these cases, the tumor tissue may have been obtained by an image-guided biopsy, and the diagnosis of NSCLC proper determined via cytology. In certain instances, adequate tissue for tumor genotyping and/or a more advanced mutational analysis to identify oncogenic drivers may not be available. Methods: Following pathology review, formalin fixed paraffin embedded (FFPE) specimens were subjected to advanced immuno-based laser capture microdissection (LCM), DNA was extracted and prepped for droplet digital PCR (ddPCR) and run with a series of positive and negative controls. Results: 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 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. Conclusions: Synergy between microdissection and ddPCR enhances the molecular analysis. We demonstrate 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.

Liquid biopsy methodologies, for the purpose of plasma genotyping of cell-free DNA (cfDNA) of solid tumors, are a new class of novel molecular assays. Such assays are rapidly entering the clinical sphere of research-based monitoring in translational oncology, especially for thoracic malignancies. Potential applications for these blood-based cfDNA assays include: (i) initial diagnosis, (ii) response to therapy and follow-up, (iii) tumor evolution, and (iv) minimal residual disease evaluation. Precision medicine will benefit from cutting-edge molecular diagnostics, especially regarding treatment decisions in the adjuvant setting, where avoiding over-treatment and unnecessary toxicity are paramount. The use of innovative genetic analysis techniques on individual patient tumor samples is being pursued in several advanced clinical trials. Rather than using a categorical treatment plan, the next critical step of therapeutic decision making is providing the “right” cancer therapy for an individual patient, including correct dose and timeframe based on the molecular analysis of the tumor in question. Per the 21st Century Cures Act, innovative clinical trials are integral for biomarker and drug development. This will include advanced clinical trials utilizing: (i) innovative assays, (ii) molecular profiling with cutting-edge bioinformatics, and (iii) clinically relevant animal or tissue models. In this paper, a mini-review addresses state-of-the-art liquid biopsy approaches. Additionally, an on-going advanced clinical trial for lung cancer with novelty through synergizing liquid biopsies, co-clinical trials, and advanced bioinformatics is also presented. Impact statement Liquid biopsy technology is providing a new source for cancer biomarkers, and adds new dimensions in advanced clinical trials. Utilizing a non-invasive routine blood draw, the liquid biopsy provides abilities to address perplexing issues of tumor tissue heterogeneity by identifying mutations in both primary and metastatic lesions. Regarding the assessment of response to cancer therapy, the liquid biopsy is not ready to replace medical imaging, but adds critical new information; for instance, through a temporal assessment of quantitative circulating tumor DNA (ctDNA) assay results, and importantly, the ability to monitor for signs of resistance, via emerging clones. Adjuvant therapy may soon be considered based on a quantitative cfDNA assay. As sensitivity and specificity of the technology continue to progress, cancer screening and prevention will improve and save countless lives by finding the cancer early, so that a routine surgery may be all that is required for a definitive cure.

The heterogeneity present in solid tumors adds significant difficulty to scientific analysis and improved understanding. Fundamentally, solid tumor formation consists of cancer cells proper along with stromal elements. The burgeoning malignant process is dependent upon modified stromal elements. Collectively, the stroma forms an essential microenvironment, which is indispensable for the survival and growth of the malignant neoplasm. This cellular heterogeneity makes molecular profiling of solid tumors via mass spectrometry (MS)-based proteomics a daunting task. Laser capture microdissection (LCM) is commonly used to obtain distinct histological cell types (e.g., tumor parenchymal cells, stromal cells) from tumor tissue and attempt to address the tumor heterogeneity interference with downstream liquid chromatography (LC) MS analysis. To provide optimal LC-MS analysis of micro-scale and/or nano-scale tissue sections, we modified and optimized a silver-stained one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) protocol for the LC-MS analysis of LCM-procured fresh-frozen tissue specimens. Presented is a detailed in-gel digestion protocol adjusted specifically to maximize the proteome coverage of amount-limited LCM samples, and facilitate in-depth molecular profiling. Following LCM, targeted tissue sections are further fractionated using silver-stained 1D-SDS-PAGE to resolve and visualize tissue proteins prior to in-gel digestion and subsequent LC-MS analysis.

The heterogeneity present in solid tumors adds significant difficulty to scientific analysis and improved understanding. Fundamentally, solid tumor formation consists of cancer cells proper along with stromal elements. The burgeoning malignant process is dependent upon modified stromal elements. Collectively, the stroma forms an essential microenvironment, which is indispensable for the survival and growth of the malignant neoplasm. This cellular heterogeneity makes molecular profiling of solid tumors via mass spectrometry (MS)-based proteomics a daunting task. Laser capture microdissection (LCM) is commonly used to obtain distinct histological cell types (e.g., tumor parenchymal cells, stromal cells) from tumor tissue and attempt to address the tumor heterogeneity interference with downstream liquid chromatography (LC) MS analysis. To provide optimal LC-MS analysis of micro-scale and/or nano-scale tissue sections, we modified and optimized a silver-stained one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) protocol for the LC-MS analysis of LCM-procured fresh-frozen tissue specimens. Presented is a detailed in-gel digestion protocol adjusted specifically to maximize the proteome coverage of amount-limited LCM samples, and facilitate in-depth molecular profiling. Following LCM, targeted tissue sections are further fractionated using silver-stained 1D-SDS-PAGE to resolve and visualize tissue proteins prior to in-gel digestion and subsequent LC-MS analysis.

The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.

Background Invasion of CNS in MM is an extremely rare occurrence that is associated with advanced disease with poor prognosis. Patients and Methods Our MM database identified 35 CNS MM cases presenting between January 1996 and March 2012. Descriptive analyses were performed on available data on patient characteristics, disease course, and outcomes. Results The mean age at diagnosis was 55.4 years; 23.5% (n = 8) patients had elevated levels of beta-2-microglobulin > 5.5 mg/L; 68.6% (n = 24) of patients had elevated lactate dehydrogenase (LDH) levels (≥ 2 times upper limit of normal); and 14% (n = 5) of patients had secondary plasma cell leukemia. Magnetic resonance imaging (MRI), which was performed in 34 patients, showed diffuse or localized leptomeningeal disease in 20 patients (58.8%). Monoclonal malignant plasma cells were found by CSF analysis in all 35 patients. In total, 31 patients received chemotherapy, including intrathecal chemotherapy as a part of their treatment, with a median survival of 4 months after CNS MM diagnosis. Discussion In our experience, CNS MM is an aggressive terminal disease feature associated with high beta-2-microglobulin level, high LDH level, and secondary plasma cell leukemia. This study highlights an unmet need in this subset of patients with high-risk, relapsed or refractory MM. Conclusion Achieving adequate CSF penetration while limiting the off-target effects needs to be considered in MM-specific novel drug development.

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.

The discovery of clinically relevant cancer biomarkers using mass spectrometry (MS)-based proteomics has proven difficult, primarily because of the enormous dynamic range of blood-derived protein concentrations and the fact that the 22 most abundant blood-derived proteins constitute approximately 99% of the total plasma protein mass. Immunodepletion of clinical body fluid specimens (e.g., serum/plasma) for the removal of highly abundant proteins is a reasonable and reproducible solution. Often overlooked, clinical tissue specimens also contain a formidable amount of highly abundant blood-derived proteins present in tissue-embedded networks of blood/lymph capillaries and interstitial fluid. Hence, the dynamic range impediment to biomarker discovery remains a formidable obstacle, regardless of clinical sample type (solid tissue and/or body fluid). Thus, we optimized and applied simultaneous immunodepletion of blood-derived proteins from solid tissue and peripheral blood, using clear cell renal cell carcinoma as a model disease. Integrative analysis of data from this approach and genomic data obtained from the same type of tumor revealed concordant key pathways and protein targets germane to clear cell renal cell carcinoma. This includes the activation of the lipogenic pathway characterized by increased expression of adipophilin (PLIN2) along with ‘cadherin switching’, a phenomenon indicative of transcriptional reprogramming linked to renal epithelial dedifferentiation. We also applied immunodepletion of abundant blood-derived proteins to various tissue types (e.g., adipose tissue and breast tissue) showing unambiguously that the removal of abundant blood-derived proteins represents a powerful tool for the reproducible profiling of tissue proteomes. Herein, we show that the removal of abundant blood-derived proteins from solid tissue specimens is of equal importance to depletion of body fluids and recommend its routine use in the context of biological discovery and/or cancer biomarker research. Finally, this perspective presents the background, rationale and strategy for using tissue-directed high-resolution/accuracy MS-based shotgun proteomics to detect genuine tumor proteins in the peripheral blood of a patient diagnosed with nonmetastatic cancer, employing concurrent liquid chromatography–MS analysis of immunodepleted clinical tissue and blood specimens.

Introduction: Clinical applications and research studies routinely utilize immunohistochemistry (IHC) approaches on tissue sections. The aim is to selectively target antigens (proteins) in the cells of a tissue section by exploiting the principle of antibody binding, thus enabling target specificity. The antigen retrieval (AR) process employed at the beginning of most IHC protocols increases epitope availability and improves staining characteristics; however, the procedure can damage nucleic acids, in this case RNA, to an unknown extent. Experimental Procedures: To better understand the effects of AR on RNA quality and quantity, model system samples (lung cancer patient derived xenograft tissue) were subjected to a commonly employed AR method [heat induced epitope retrieval (HIER)] and the effects on RNA were assessed by Qubit, Fragment Analyzer, and digital droplet PCR (ddPCR). The ddPCR experiments were performed following reverse transcriptase (RT) product generation and construction of cDNA, which then served as input to the ddPCR assay. Absolute quantitation of gene expression levels and expressed mutations were evaluated by ddPCR. Data Summary: The results showed that HIER resulted in optimal staining characteristics, but induced significant damage to RNA, producing extensive fragmentation and decreased yields. In general, fragmentation showed an inflection point at ~200 nt transcript length. Variation in the HIER protocol mitigated but did not eliminate the negative effects. Apart from the AR procedure, the IHC process itself also resulted in a significant decreased yield of RNA. Of note, in these experiments DAB chromogen was used exclusively in the IHC process. However, in spite of the observed deleterious effects on RNA, none of the AR methods combined with IHC negatively affected RT product generation and PCR amplification of small amplicons. Regarding the detection of RT product under different conditions, the size of the amplicon was found to make a difference, with the detection of longer amplicons being more difficult. In addition to a number of successful human and mouse gene expression measurements, KRAS gene mutations were successfully identified in the clinical cases under all conditions. Conclusions: The data indicate that RNA recovered from histology slides after standard AR and IHC processing can be successfully employed for genomic applications utilizing RT product formation (cDNA) for gene expression and detection of expressed mutations, especially if the detection methods are based on relatively short length nucleic acids. Studies that require larger RNA fragments such as long-read sequencing should avoid the use of HIER. Citation Format: Donald J. Johann, Meeiyueh Liu, Adam Roberge, Sarah Laun, Michael Emmert-Buck, Michael Tangrea. Effect of antigen retrieval on immuno-based RNA microdissection methods [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1243.

Onco-panel sequencing targets sequencing reads to few small regions of the genome and thus is better enabled to detect of rare but clinically relevant sub-clonal mutations. Accurate diagnosis and subsequent tailoring of therapy depends on thorough characterization of tumor mutational spectra. The lack of tumor reference samples, comprehensive approaches to assessing reproducibility and detection sensitivity, and standard practice guidelines is hindering the development of onco-panel sequencing and the realization of its benefits in cancer diagnosis and treatment. As a component of the FDA-led SEQC project phase 2 (SEQC2), the Onco-panel Working Group has designed and characterized a set of reference materials. These materials were created using cell line gDNA pooling and dilution to enable such comprehensive assessments of targeted mutation detection approaches. To this end, a cross-lab evaluation of eight Pan-Cancer panels and five ctDNA liquid biopsy assays is currently underway. Each panel was tested in three independent laboratories. To further evaluate methods to boost reproducibility, synthetic spike-in controls and synthetic plasma were also incorporated into the testing samples. Contrived samples for liquid biopsy testing were prepared through enzymatic fragmentation and size selection to mimic cell-free DNA. The onco-panels tested represent two target enrichment approaches (amplicon based and capture based) and sequencing technologies (multiple Illumina platforms and Ion Torrent). Of note, the liquid biopsy assays employ various molecular barcoding techniques to improve their detection sensitivity of rare mutations. Extensive lab QC data has been collected along with sequencing data. Performance measures have been devised to evaluate reproducibility and sensitivity of the variant/mutation calling results that are produced by the panel providers. Meta-analysis of performance measures will then be conducted for cross panel comparison. This comprehensive study will yield insights into factors underpinning sensitivity and reproducibility of onco-panel sequencing. Quantitative performance metrics and actionable data analysis recommendations will be presented to the targeted sequencing panel community. Citation Format: Joshua Xu, Binsheng Gong, Wendell Jones, Don Johann, Onco-panel Working Group of the Sequencing QualityControl Phase 2 (SEQC2) Consortium. Sensitivity and reproducibility of onco-panel sequencing across multiple laboratories and technologies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4462.