Citations

AbstractBACKGROUNDDroplet digital PCR (ddPCR) is an emerging technology for quantitative cell-free DNA oncology applications. However, assay performance criteria must be established in a standardized manner to harness this potential. We reasoned that standard protocols used in clinical chemistry assay validation should be able to fill this need.METHODSWe validated KRAS, EGFR, and BRAF quantitative ddPCR assays based on the Clinical Laboratory Improvement Act regulations for laboratory-developed tests in clinical chemistry and the matching Clinical and Laboratory Standards Institute guidelines. This included evaluation of limit of the blank (LOB), limit of detection (LOD), limit of quantification (LOQ), intraassay and interassay imprecision, analytical range, dilution linearity, accuracy (including comparison with orthogonal platforms), reference range study, interference, and stability studies.RESULTSFor the ddPCR assays, the LOB was 4 mutant copies, LODs were 12 to 22 copies, and LOQs were 35 to 64 copies. The upper limit of the dynamic range was 30000 copies, and dilutions were linear down to the LOQs with good accuracy of spike recovery of Horizon reference material. Method comparisons with next-generation sequencing and an alternative ddPCR platform showed complete qualitative agreement and quantitative concordance, with slopes of 0.73 to 0.97 and R2s of 0.83 to 0.99. No substantial interferences were discovered. Wild-type copy numbers in plasma ranged from 462 to 6169/mL in healthy individuals.CONCLUSIONSStandard clinical chemistry assay validation protocols can be applied to quantitative ddPCR assays. This should facilitate comparison of the performance of different assays and allow establishment of minimal significant change thresholds in monitoring applications.

Abstract Patient derived xenografts (PDX) mouse models for many types of cancer have demonstrated therapeutic responses similar to those seen in patients. Thus, resected patient tumor tissue directly implanted into immune compromised mice followed by therapy and tumor growth analysis is thought to be the closest preclinical model to predict patient therapeutic responses. To date, few models are available for the different histotypes of thyroid cancer derived from follicular thyrocytes; these include papillary, follicular, Hurthle cell, squamous and anaplastic thyroid carcinoma. We have developed eight PDX models in athymic nude mice representing all of these subtypes. The models have been extensively characterized for mutational status (i.e. BRAF, telomerase, RAS, PTEN, TP53, RB, etc) as well as validation by short tandem repeat (STR) analysis to match that of the originating patient tumor tissue. Squamous and anaplastic thyroid cancers are rare tumor types with no FDA approved therapies. Each model demonstrated their own unique responses to radiation, cytotoxic or molecular targeted therapies such as doxorubicin, sorafenib (tyrosine kinase inhibitor), cisplatin, paclitaxel, sunitinib (tyrosine kinase inhibitor), erlotinib (EGFR inhibitor), trametinib (MEK inhibitor) and vemurafenib (BRAF inhibitor). We expect that these models may provide useful in vivo models for thyroid cancer research as well as models for therapeutic guidance based upon histotype, mutational status and response to therapies. Citation Format: Laura A. Marlow, Adam C. Mathias, Louis K. Dawson, William F. Durham, Kenneth A. Meshaw, Robert J. Mullin, Daniel L. Small, Aidan J. Synnott, Dragana Milosevic, Brian C. Netzel, Stefan K. Grebe, Kevin Wu, Robert C. Smallridge, John A. Copland. Characterization of novel thyroid PDX models and their response to combination therapies. [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 1458. doi:10.1158/1538-7445.AM2015-1458

Abstract The success of clinical trials for patients with malignant melanoma (MM) designed from the “promising” results using pre-clinical models is minimal. With its increase in incidence, there is a dire need to develop both pre-clinical models comparable to clinical practice that have the capability to translate from bench-to-bedside and novel therapeutic agents for this life-threatening form of skin cancer. To address this concern, we have developed a panel of pre-clinical MM models including patient matched cell lines, patient cell-line derived xenograft models and patient tumor tissue-derived xenograft models. Patient derived xenograft (PDX) models are purported to most closely replicate a patient's response to therapy. Since the development of patient-derived cell lines and tumors grown in mice were more efficacious, their genetic, phenotypic, and therapeutic responses were compared to those of their corresponding patient-matched PDX model. Each model was molecularly characterized to confirm a match to that of the originating patient tumor tissue via protein immunohistochemistry (IHC), mRNA quantitative polymerase chain reaction (qPCR), DNA short tandem repeat (STR) analysis, and Sanger sequencing. Each pre-clinical model provided a genetic match to their respective patient tumor sample. All pre-clinical models were positive for the melanoma-specific markers (S-100 beta, HMB-45, and Melan-A) confirming a melanoma phenotype. Soft agar studies and tumor growth of our PDX and patient cell-line derived xenograft models confirmed tumorigenicity within our models providing the foundation to perform therapeutic studies. Mutation status data (i.e. BRAF, RAS), patient therapeutic clinical history and oncogene overexpression analysis (pERK, pAKT, PI3K, pmTOR, etc.) provide the platform and rationale behind the use of specific therapeutic agents per model. BRAF, NRAS and KRAS mutations were identified along with elevated pERK, pAKT and pmTOR in the models. Targeted therapies (trametinib/MEK inhibitor; vemurafenib/BRAF inhibitor; MK-2206/pAKT inhibitor; and everolimus/mTOR inhibitor) demonstrated dose dependent inhibition of cell proliferation in each of the models based upon oncogenic expression or mutations. In vivo experiments are in progress, which will allow comparison of the three models. The next steps include combination therapy to identify antitumor synergy targeting oncogenic signaling pathways. Citation Format: Antoneicka L. Harris, Laura Marlow, Adam Mathias, Louis Dawson, William Durham, Kenneth Meshaw, Robert Mullin, Daniel Small, Aidan Synnott, Kevin Wu, Dragana Milosevic, Brian Netzel, Stefan Grebe, Svetomir Markovic, John Copland. Characterization of novel patient derived melanoma xenografts and cell lines in response to targeted therapies. [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 2417. doi:10.1158/1538-7445.AM2015-2417

Abstract Peripheral T-cell lymphomas (PTCLs) are aggressive malignancies of mature T lymphocytes with 5-year overall survival rates of only ∼ 35%. Improvement in outcomes has been stymied by poor understanding of the genetics and molecular pathogenesis of PTCL, with a resulting paucity of molecular targets for therapy. We developed bioinformatic tools to identify chromosomal rearrangements using genome-wide, next-generation sequencing analysis of mate-pair DNA libraries and applied these tools to 16 PTCL patient tissue samples and 6 PTCL cell lines. Thirteen recurrent abnormalities were identified, of which 5 involved p53-related genes (TP53, TP63, CDKN2A, WWOX, and ANKRD11). Among these abnormalities were novel TP63 rearrangements encoding fusion proteins homologous to ΔNp63, a dominant-negative p63 isoform that inhibits the p53 pathway. TP63 rearrangements were seen in 11 (5.8%) of 190 PTCLs and were associated with inferior overall survival; they also were detected in 2 (1.2%) of 164 diffuse large B-cell lymphomas. As TP53 mutations are rare in PTCL compared with other malignancies, our findings suggest that a constellation of alternate genetic abnormalities may contribute to disruption of p53-associated tumor suppressor function in PTCL.

BACKGROUND There is great interest in circulating microRNAs (miRNAs) as disease biomarkers. Translating promising miRNAs into validated clinical tests requires the characterization of many preanalytical and analytical parameters. METHODS miRNAs were extracted from serum and plasma samples of healthy volunteers, and miRNAs known to be present in serum and plasma (miR-15b, miR-16, miR-24, and miR-122) were amplified by reverse-transcription quantitative PCR. Stability and the effects of hemolysis were determined. Assay variation and its components, including the effect of adding control miRNA, were assessed by nested ANOVA. RESULTS miRNA concentrations were higher in plasma than in serum. Processing of plasma to remove subcellular/cellular components reduced miRNA concentrations to those of serum. The miRNAs analyzed were stable refrigerated or frozen for up to 72 h and were stable at room temperature for 24 h. Hemolysis increased the apparent concentration of 3 of the miRNAs. The total variability of replicate miRNA concentrations was <2.0-fold, with most of the variability attributable to the extraction process and interassay imprecision. Normalizing results to those of spiked exogenous control miRNAs did not improve this variability. CONCLUSIONS Detailed validation of the preanalytical steps affecting miRNA detection and quantification is critical when considering the use of individual miRNAs as clinical biomarkers. Unless these causes of imprecision are considered and mitigated, only miRNAs that are extremely up- or downregulated will be suitable as clinical biomarkers.

Abstract Background: Molecular testing of thyroid malignancies, in combination with cytologic and histologic examination, is becoming increasingly attractive as a tool for refining traditional morphologic diagnosis. The molecular changes associated with follicular thyroid carcinoma (FTC) are point mutations in RAS oncogenes or the presence of PAX8/PPARG (paired box 8/peroxisome proliferator-activated receptor gamma) rearrangement. Methods: We developed and validated a clinical assay for the detection of PAX8/PPARG rearrangements that uses a 4-color reverse-transcription PCR (RT-PCR) assay and high-resolution fragment analysis. Results: The RT-PCR assay is applicable for detecting the various described fusion transcripts of PAX8/PPARG in formalin-fixed, paraffin-embedded thyroid tissue and in fine-needle aspirate biopsy washes from thyroid nodules. The analytical sensitivity of the assay is 1 abnormal cell in a background of 100–10 000 translocation-negative cells. A comparison of the RT-PCR assay with dual-fusion fluorescence in situ hybridization showed an overall concordance of 95%. With this assay, we obtained a prevalence for the PAX8/PPARG rearrangement in FTC of 62% (13 of 21 cases), compared with a 5% prevalence (3 of 55) for other follicular cell–derived neoplasms. Conclusions: The introduction of this assay into clinical practice could provide useful information for the diagnosis and possibly for the prognosis and treatment of thyroid cancer in the future.