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Dive into the research topics where Joshua Babiarz is active.

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Featured researches published by Joshua Babiarz.


Ultrasound in Obstetrics & Gynecology | 2016

Clinical experience with single-nucleotide polymorphism-based non-invasive prenatal screening for 22q11.2 deletion syndrome.

Susan J. Gross; Melissa Stosic; Donna M. McDonald-McGinn; Anne S. Bassett; Anna Norvez; Rupin Dhamankar; Katie Kobara; Eser Kirkizlar; Bernhard Zimmermann; Nicholas Wayham; Joshua Babiarz; Allison Ryan; Kristine N. Jinnett; Zachary Demko; Peter Benn

To evaluate the performance of a single‐nucleotide polymorphism (SNP)‐based non‐invasive prenatal test (NIPT) for the detection of fetal 22q11.2 deletion syndrome in clinical practice, assess clinical follow‐up and review patient choices for women with high‐risk results.


Translational Oncology | 2015

Detection of Clonal and Subclonal Copy-Number Variants in Cell-Free DNA from Patients with Breast Cancer Using a Massively Multiplexed PCR Methodology.

Eser Kirkizlar; Bernhard Zimmermann; Tudor Constantin; Ryan Swenerton; Bin Hoang; Nicholas Wayham; Joshua Babiarz; Zachary Demko; Robert J. Pelham; Stephanie Kareht; Alexander L. Simon; Kristine N. Jinnett; Matthew Rabinowitz; Styrmir Sigurjonsson; Matthew Hill

We demonstrate proof-of-concept for the use of massively multiplexed PCR and next-generation sequencing (mmPCR-NGS) to identify both clonal and subclonal copy-number variants (CNVs) in circulating tumor DNA. This is the first report of a targeted methodology for detection of CNVs in plasma. Using an in vitro model of cell-free DNA, we show that mmPCR-NGS can accurately detect CNVs with average allelic imbalances as low as 0.5%, an improvement over previously reported whole-genome sequencing approaches. Our method revealed differences in the spectrum of CNVs detected in tumor tissue subsections and matching plasma samples from 11 patients with stage II breast cancer. Moreover, we showed that liquid biopsies are able to detect subclonal mutations that may be missed in tumor tissue biopsies. We anticipate that this mmPCR-NGS methodology will have broad applicability for the characterization, diagnosis, and therapeutic monitoring of CNV-enriched cancers, such as breast, ovarian, and lung cancer.


Cancer Research | 2015

Abstract P4-02-03: Detection of single nucleotide variations and copy number variations in breast cancer tissue and ctDNA samples using single-nucleotide polymorphism-targeted massively multiplexed PCR

Robert J. Pelham; Bernhard Zimmermann; Eser Kirkizlar; Ryan Swenerton; Bin Hoang; Onur Sakarya; Joshua Babiarz; Nicholas Wayham; Tudor Constantin; Styrmir Sigurjonsson; Matthew Rabinowitz; Matthew Hill

Genomic instability, the hallmark of cancer, presents with a variety of mutation types, most commonly single nucleotide variations (SNVs) and copy number variations (CNVs), which traditionally have required different methods for identification. It has proven challenging to simultaneously achieve sufficient breadth to detect CNVs and depth to detect SNVs on samples of limited input amount. The objective of this study was to validate a new methodology for detection of SNVs and CNVs in a single assay. We used a massively multiplex PCR/NGS approach combining an SNV panel covering 585 point mutation hotspots in breast cancer (Cosmic) and a CNV panel targeting 28,000 SNPs designed to detect copy number at chromosomes 1, 2, 13, 18, 21, and X, and focal regions 4p16, 5p15, 7q11, 15q, 17p, 22q11, and 22q13. We applied these panels to breast cancer cell lines and fresh frozen (FF) breast tumor samples; the presence of CNVs in circulating cell-free tumor DNA (ctDNA) in the plasma of breast cancer patients was also investigated. The CNV assay methodology was validated using genomic DNA isolated from 96 human samples with known karyotype; sensitivity to single region deletions or duplications was 100% (71/71) and specificity was 100% for normal regions in the same samples. Single-molecule sensitivity for the detection of CNVs was established by analyzing isolated single cells. Performance of the mutation assay was demonstrated with the analysis of 5 matched tumor and normal cell lines, with 24 out of 27 SNVs known to be present in these cell lines detected. The 3 undetected SNVs were determined to be a result of assay design failure. Also, multiple somatic CNVs (median: 13) were detected in all 5 tumor cell lines. Analysis of the normal cell lines found no cancer related SNVs or CNVs. In 32 FF tumor samples, 78.1% (25/32) had SNVs detected; of samples with SNVs, 88% (22/25) had SNVs in TP53 or PIK3CA. Of the same 32 FF breast tumor samples, 96.9% (31/32) showed full or partial CNVs in at least 1 and up to 15 regions; of the 31 samples with detected CNVs, 93.5% had a CNV of either 1q or 17p, two of the three most prevalent breast cancer CNVs (the 16q region was not represented in this panel). Overall, a combination of SNV and CNV testing allowed identification of genetic changes in 100% of the breast tumor samples, a significant improvement in diagnostic yield than using SNV detection alone. Of the 12 breast cancer patients with matched tumor tissue and plasma samples, 83.3% (10/12) had CNVs detected in tissue. The CNVs present in each primary tumor sample were identified in corresponding plasma ctDNA samples (1 stage IIa, 7 stage IIb, and 2 stage III). The ctDNA fractions in these samples ranged from 0.58 to 4.33%; detection required as few as 86 heterozygous SNPs per CNV. Analysis of ctDNA for cancer-associated mutations may allow earlier, safer and more accurate profiling and monitoring of breast cancer. Thus, this targeted PCR approach offers the promise of an assay able to detect both cancer-associated SNVs and CNVs in the same sample with good sensitivity and specificity, and improved detection rates compared to assays that only detect SNVs. Citation Format: Robert J Pelham, Bernhard G Zimmermann, Eser Kirkizlar, Ryan K Swenerton, Bin Hoang, Onur Sakarya, Joshua E Babiarz, Nicholas Wayham, Tudor Constantin, Styrmir Sigurjonsson, Matthew Rabinowitz, Matthew Hill. Detection of single nucleotide variations and copy number variations in breast cancer tissue and ctDNA samples using single-nucleotide polymorphism-targeted massively multiplexed PCR [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-02-03.


Archive | 2015

DETECTING MUTATIONS AND PLOIDY IN CHROMOSOMAL SEGMENTS

Joshua Babiarz; Tudor Constantin; Lane A. Eubank; George Gemelos; M. Hill; Huseyin Eser Kirkizlar; Matthew Rabinowitz; Onur Sakarya; Styrmir Sigurjonsson; Bernhard Zimmerman


Archive | 2014

Cell free dna diagnostic testing standards

Joshua Babiarz; Bernhard Zimmermann


Archive | 2016

DETECTING CANCER MUTATIONS AND ANEUPLOIDY IN CHROMOSOMAL SEGMENTS

Joshua Babiarz; Tudor Constantin; Lane A. Eubank; George Gemelos; M. Hill; Huseyin Eser Kirkizlar; Matthew Rabinowitz; Onur Sakarya; Styrmir Sigurjonsson; Bernhard Zimmermann


Archive | 2014

Prenatal diagnostic resting standards

Joshua Babiarz; Bernhard Zimmerman


/data/revues/00029378/unassign/S0002937814023746/ | 2015

Expanding the scope of noninvasive prenatal testing: detection of fetal microdeletion syndromes

Ronald J. Wapner; Joshua Babiarz; Brynn Levy; Melissa Stosic; Bernhard Zimmermann; Styrmir Sigurjonsson; Nicholas Wayham; Allison Ryan; Milena Banjevic; Phil Lacroute; Jing Hu; Megan P. Hall; Zachary Demko; Asim Siddiqui; Matthew Rabinowitz; Susan J. Gross; Matthew Hill; Peter Benn


Archive | 2014

Normes d'essais pour diagnostics prénataux

Joshua Babiarz; Bernhard Zimmerman


Cancer Genetics and Cytogenetics | 2014

Detection of Copy Number Variations in Breast Cancer Samples Using Single-nucleotide Polymorphism-targeted Massively Multiplexed PCR

Joshua Babiarz; Bernhard Zimmermann; Tudor Constantin; Ryan Swenerton; Eser Kirkizlar; Nicholas Wayham; Matthew Rabinowitz; Matthew Hill

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