scholarly journals Targeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chunxiao Fu ◽  
Michal Marczyk ◽  
Michael Samuels ◽  
Alexander J. Trevarton ◽  
Jiaxin Qu ◽  
...  
Keyword(s):  
Point Mutations ◽  
Nonparametric Tests ◽  
Bulk Solution ◽  
Amplification Efficiency ◽  
Breast Cancers ◽  
Cancer Genes ◽  
Library Size ◽  
Mutant Transcript ◽  
Two Samples ◽  
Ffpe Samples

Abstract Background Our objective was to assess whether modifications to a customized targeted RNA sequencing (RNAseq) assay to include unique molecular identifiers (UMIs) that collapse read counts to their source mRNA counts would improve quantification of transcripts from formalin-fixed paraffin-embedded (FFPE) tumor tissue samples. The assay (SET4) includes signatures that measure hormone receptor and PI3-kinase related transcriptional activity (SETER/PR and PI3Kges), and measures expression of selected activating point mutations and key breast cancer genes. Methods Modifications included steps to introduce eight nucleotides-long UMIs during reverse transcription (RT) in bulk solution, followed by polymerase chain reaction (PCR) of labeled cDNA in droplets, with optimization of the polymerase enzyme and reaction conditions. We used Lin’s concordance correlation coefficient (CCC) to measure concordance, including precision (Rho) and accuracy (Bias), and nonparametric tests (Wilcoxon, Levene’s) to compare the modified (NEW) SET4 assay to the original (OLD) SET4 assay and to whole transcriptome RNAseq using RNA from matched fresh frozen (FF) and FFPE samples from 12 primary breast cancers. Results The modified (NEW) SET4 assay measured single transcripts (p< 0.001) and SETER/PR (p=0.002) more reproducibly in technical replicates from FFPE samples. The modified SET4 assay was more precise for measuring single transcripts (Rho 0.966 vs 0.888, p< 0.01) but not multigene expression signatures SETER/PR (Rho 0.985 vs 0.968) or PI3Kges (Rho 0.985 vs 0.946) in FFPE, compared to FF samples. It was also more precise than wtRNAseq of FFPE for measuring transcripts (Rho 0.986 vs 0.934, p< 0.001) and SETER/PR (Rho 0.993 vs 0.915, p=0.004), but not PI3Kges (Rho 0.988 vs 0.945, p=0.051). Accuracy (Bias) was comparable between protocols. Two samples carried a PIK3CA mutation, and measurements of transcribed mutant allele fraction was similar in FF and FFPE samples and appeared more precise with the modified SET4 assay. Amplification efficiency (reads per UMI) was consistent in FF and FFPE samples, and close to the theoretically expected value, when the library size exceeded 400,000 aligned reads. Conclusions Modifications to the targeted RNAseq protocol for SET4 assay significantly increased the precision of UMI-based and reads-based measurements of individual transcripts, multi-gene signatures, and mutant transcript fraction, particularly with FFPE samples.

scholarly journals SVFX: a machine-learning framework to quantify the pathogenicity of structural variants

2019 ◽  
Author(s):  
Sushant Kumar ◽  
Arif Harmanci ◽  
Jagath Vytheeswaran ◽  
Mark B. Gerstein
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Three Dimensional ◽  
Point Mutations ◽  
Dimensional Structure ◽  
Rapid Decline ◽  
Ras Signaling ◽  
Cancer Genes ◽  
Structural Variations ◽  
Pathogenic Variants

AbstractA rapid decline in sequencing cost has made large-scale genome sequencing studies feasible. One of the fundamental goals of these studies is to catalog all pathogenic variants. Numerous methods and tools have been developed to interpret point mutations and small insertions and deletions. However, there is a lack of approaches for identifying pathogenic genomic structural variations (SVs). That said, SVs are known to play a crucial role in many diseases by altering the sequence and three-dimensional structure of the genome. Previous studies have suggested a complex interplay of genomic and epigenomic features in the emergence and distribution of SVs. However, the exact mechanism of pathogenesis for SVs in different diseases is not straightforward to decipher. Thus, we built an agnostic machine-learning-based workflow, called SVFX, to assign a “pathogenicity score” to somatic and germline SVs in various diseases. In particular, we generated somatic and germline training models, which included genomic, epigenomic, and conservation-based features for SV call sets in diseased and healthy individuals. We then applied SVFX to SVs in six different cancer cohorts and a cardiovascular disease (CVD) cohort. Overall, SVFX achieved high accuracy in identifying pathogenic SVs. Moreover, we found that predicted pathogenic SVs in cancer cohorts were enriched among known cancer genes and many cancer-related pathways (including Wnt signaling, Ras signaling, DNA repair, and ubiquitin-mediated proteolysis). Finally, we note that SVFX is flexible and can be easily extended to identify pathogenic SVs in additional disease cohorts.

scholarly journals Influence of Germline BRCA Genotype on the Survival of Patients with Triple-Negative Breast Cancer

2021 ◽  
Vol 1 (3) ◽  
pp. 140-147
Author(s):  
Cynthia Villarreal-Garza ◽  
Ana S. Ferrigno ◽  
Alejandro Aranda-Gutierrez ◽  
Paul H. Frankel ◽  
Nora H. Ruel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Point Mutations ◽  
Treatment Resistance ◽  
Cancer Center ◽  
Breast Cancers ◽  
Entire Cohort ◽  
Pathogenic Variants ◽  
Mutational Status

The presence of BRCA pathogenic variants (PV) in triple-negative breast cancer (TNBC) is associated with a distinctive genomic profile that makes the tumor particularly susceptible to DNA-damaging treatments. However, patients with BRCA PVs can develop treatment resistance through the appearance of reversion mutations and restored BRCA expression. As copy-number variants (CNV) could be less susceptible to reversion mutations than point mutations, we hypothesize that carriers of BRCA CNVs may have improved survival after treatment compared with carriers of other BRCA PVs or BRCA wild-type. Women diagnosed with stage I–III TNBC at ≤50 years at a cancer center in Mexico City were screened for BRCA PVs using a recurrent PV assay (HISPANEL; 77% sensitivity). Recurrence-free survival (RFS) and overall survival (OS) were compared according to the mutational status. Among 180 women, 17 (9%) were carriers of BRCA1 ex9–12del CNVs and 26 (14%) of other BRCA PVs. RFS at ten years for the whole cohort was 79.2% [95% confidence interval (CI), 72.3–84.6], with no significant differences according to mutational status. 10-year OS for the entire cohort was 85.3% (95% CI, 78.7–90.0), with BRCA CNV carriers demonstrating numerically superior OS rates other PV carriers and noncarriers (100% vs. 78.6% and 84.7%; log-rank P = 0.037 and P = 0.051, respectively). This study suggests that BRCA1 ex9–12del CNV carriers with TNBC may have a better OS, and supports the hypothesis that the genotype of BRCA PVs may influence survival by limiting treatment resistance mediated by reversion mutations among CNV carriers. Significance: Large CNV BRCA carriers in a cohort of young Mexican patients with TNBC had superior OS rates than carriers of other BRCA pathogenic variants (i.e., small indels or point mutations). We hypothesize that this is due to the resistance of CNVs to reversion mutations mediating resistance to therapy. If validated, these findings have important prognostic and clinical treatment implications for BRCA-associated breast cancers.

Comprehensive Highly Multiplexed Single-Tube Liquid Bead Microarray Assay for Constitutively Activated Tyrosine Kinases in Chronic Myeloproliferative Disorders.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 1551-1551
Author(s):  
Mark J. Roberts ◽  
Yening Zhou ◽  
Kenneth B. Miller ◽  
German A. Pihan
Keyword(s):  
Cell Lines ◽  
Tyrosine Kinases ◽  
Point Mutations ◽  
Myeloproliferative Disorders ◽  
Turnaround Time ◽  
Complex Problem ◽  
Amplification Efficiency ◽  
Gain Of Function ◽  
Single Tube ◽  
Chronic Myeloproliferative Disorders

Abstract Chronic Myeloproliferative disorders (CMPDs) are malignancies characterized by excessive proliferation of one or more of the myeloid lineages driven by constitutively activated tyrosine kinases (CATKs). CATKs are increasingly serving as targets for cancer-specific therapy and newer and more potent TK inhibitors are becoming available for clinical use. CATKs in CMPDs may result from karyotypically evident or cryptic chromosomal translocations leading to TK gene fusions or from karyotypically silent gain-of-function point mutations. More than ten CATK genes have been shown to result in CMPDs by imparting a demonstrable positive growth drive. CATK inhibitors important in the treatment of CMPDs have different inhibitory profiles, making it critical to identify the specific mutation involved in patients receiving targeted therapy. Of these TK genes, ABL, PDGFRB, PDGFRA, FGFR1, ETV6, JAK2 and MPL are the most frequently involved. Since most of these TK genes can participate in chromosome translocations with a large number of partner genes, the resulting number of possible CATKs is rather large, making detection and identification a challenging task. To date, two classic (B2A2 and B3A2) and seven less common fusions of the ABL and BCR genes have been described. In addition, over twenty non-BCR-ABL mutations have been shown to have pathogenetic relevance in CMPDs. We have developed a simple, high-throughput assay with a fast turnaround time that solves the complex problem of detecting and identifying multiple translocations and point mutations. Two steps are involved in this expandable assay. The first is a multiplex RT-PCR reaction that amplifies fusion transcripts and point mutations described in CMPDs from peripheral blood or bone marrow. This PCR reaction employs internal specific primers targeted to each of eight BCR-ABL mutations (E1A2, E1A3, B2A2, B3A2, E6A2, E8A2, E15A2, E19A2) eight non-BCR-ABL mutations (FIP1L1-PDGFRA, BCR-PDGFRA, BCR-FGFR1, MYO18A-FGFR1, CDK5RAP2-PDGFRA, ETV6-PDGFRB, RABAPTIN-5-PDGFRB, H4-PDGFRB) and two gain of function mutations (JAK2V617F and MPLW515L) and a biotinylated common primer set to increase amplification efficiency. The second is a liquid bead microarray (Luminex) which uses optically encoded beads to detect probes specific for multiple known translocations in a single tube. To date, we have selectively detected four BCR-ABL and three non-BCR-ABL mutations from cloned patient samples and the cell lines SupB15 (E1A2 p190 BCR-ABL fusion), K562 (B3A2 p210 BCR-ABL fusion) and BV173 (B2A2 p210 BCR-ABL fusion). Dilution studies using these cell lines demonstrate detection down to between 1/1000 and 1/100000 cell equivalents without significant cross-talk. Figure Figure Figure Figure

Validation of an exome and transcriptome based diagnostic platform enabling clinical cancer therapy selection and emerging composite biomarkers for immunotherapy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15583-e15583
Author(s):  
Juan-Sebstian Saldivar ◽  
Jason Harris ◽  
Sejal Desai ◽  
Erin Ayash ◽  
Prateek Tandon ◽  
...  
Keyword(s):  
Biomarker Discovery ◽  
High Sensitivity ◽  
Cancer Genes ◽  
Patient Response ◽  
Diagnostic Biomarkers ◽  
Dna And Rna ◽  
Clinical Biomarkers ◽  
Whole Exome ◽  
Ffpe Samples ◽  
Small Set

e15583 Background: While immunotherapy has become a pillar of cancer treatment, diagnostic biomarkers that consistently predict patient response to these therapies have remained elusive. There is an increasing need for the development of integrative, composite biomarkers that can model the complex biology driving response and/or resistance to immunotherapy more effectively than existing single-analyte approaches. However, the majority of current cancer diagnostic panels, with their focus on a small set of genes, provide limited ability to support these emerging advanced biomarkers. Methods: To address these limitations, we developed and validated NeXT Dx, a comprehensive enhanced exome and transcriptome based diagnostic platform designed to simultaneously characterize tumor and immune genomics from a single limited FFPE sample. To achieve higher accuracy and sensitivity for an exome scale diagnostic platform, we developed an augmented exome assay that improves uniformity of coverage across all ~20,000 genes, including boosted coverage of 248 clinically-relevant cancer genes. We validated this assay using genomic DNA and RNA extracted from tumor-derived cell-lines, constructs, clinical FFPE samples, and proficiency testing samples. The assay utilizes > = 25ng of co-extracted DNA and RNA which were sequenced using Illumina NovaSeq instruments at our CAP-accredited, CLIA-certified laboratory. Additional assay enhancements for HLA, immune repertoire, and oncoviruses were designed to further optimize the platform for immunotherapy biomarker discovery applications. Results: Validation of NeXT Dx demonstrated a performance of 99.5% sensitivity and 99.8% positive predictive value (PPV) for SNVs with > = 5% AF; 98.7% sensitivity and 97.4% PPV for indels with > = 10% AF; 97.2% sensitivity and 94.6% PPV for CNAs in samples with > = 30% tumor content; 94.9% sensitivity and 94.9% PPV for fusions; and a 2.1% error rate for MSI classification. TMB was calculated using gold-standard whole exome data from SNVs and indels. Typical median coverage depth was > 1,000X for 248 clinically-relevant genes, ~300X for the remaining (whole exome) footprint. Conclusions: With NeXT Dx, we demonstrate a exome/transcriptome scale diagnostic platform that can detect current clinical biomarkers with high sensitivity as well as support emerging, advanced biomarkers that integrate across both tumor and immune features.

scholarly journals A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations

2018 ◽  
Author(s):  
Paul Ashford ◽  
Camilla S.M. Pang ◽  
Aurelio A. Moya-García ◽  
Tolulope Adeyelu ◽  
Christine A. Orengo
Keyword(s):  
Zinc Finger Protein ◽  
Point Mutations ◽  
Driver Mutations ◽  
Cancer Genes ◽  
Driver Genes ◽  
Recurrent Point ◽  
Cancer Driver ◽  
Functional Sites ◽  
Cancer Driver Genes ◽  
Family Based

Tumour sequencing identifies highly recurrent point mutations in cancer driver genes, but rare functional mutations are hard to distinguish from large numbers of passengers. We developed a novel computational platform applying a multi-modal approach to filter out passengers and more robustly identify putative driver genes. The primary filter identifies enrichment of cancer mutations in CATH functional families (CATH-FunFams) – structurally and functionally coherent sets of evolutionary related domains. Using structural representatives from CATH-FunFams, we subsequently seek enrichment of mutations in 3D and show that these mutation clusters have a very significant tendency to lie close to known functional sites or conserved sites predicted using CATH-FunFams. Our third filter identifies enrichment of putative driver genes in functionally coherent protein network modules confirmed by literature analysis to be cancer associated.Our approach is complementary to other domain enrichment approaches exploiting Pfam families, but benefits from more functionally coherent groupings of domains. Using a set of mutations from 22 cancers we detect 151 putative cancer drivers, of which 79 are not listed in cancer resources and include recently validated cancer genes EPHA7, DCC netrin-1 receptor and zinc-finger protein ZNF479.

scholarly journals Analysis of the p53 gene by PCR-SSCP in ten cases of Wilms’ tumor

2000 ◽  
Vol 118 (2) ◽  
pp. 49-52 ◽  
Author(s):  
Ricardo Defavery ◽  
José Alexandre Rodrigues Lemos ◽  
Simone Kashima ◽  
José Eduardo Bernardes ◽  
Carlos Alberto Scridelli ◽  
...  
Keyword(s):  
Case Report ◽  
Dna Sequencing ◽  
Wilms Tumor ◽  
Point Mutations ◽  
Low Frequency ◽  
P53 Gene ◽  
Suppressor Gene ◽  
Stage Disease ◽  
Two Samples ◽  
Renal Neoplasia

CONTEXT: Mutations of the p53 tumor suppressor gene are the most frequent alterations observed in human neoplasias affecting adults. In pediatric oncology, however, they have seldom been identified. Wilms’ tumor is a renal neoplasia commonly occurring in children and is associated with mutations of the WT1 gene. The correlation between Wilms’ tumor and alterations of the p53 gene has not been well established, with a low frequency of mutations having been reported in this type of tumor. Mutation may be associated with advanced stage disease and unfavorable histology. OBJECTIVE: To screen for mutations of the p53 gene by the PCR-SSCP method and DNA sequencing in cases of Wilms’ tumor sug-gestive of mutation. DESIGN: Case Report. CASE REPORT: Evaluations of exons 5-9 of the p53 gene in DNA samples extracted by PCR-SSCP from 10 Wilms’ tumors in children at different stages, and DNA sequencing. Changes in SSCP analy-sis were observed in exon 8 in two samples. The probable muta-tions were not confirmed by DNA sequencing. The absence of point mutations in p53 gene observed in the 10 samples of Wilms’ tumor studied agrees with literature data, with DNA sequencing being of fundamental importance for the confirmation of possible mutations.

scholarly journals Molecular Insights into the Classification of Luminal Breast Cancers: The Genomic Heterogeneity of Progesterone-Negative Tumors

2019 ◽  
Vol 20 (3) ◽  
pp. 510 ◽  
Author(s):  
Gianluca Lopez ◽  
Jole Costanza ◽  
Matteo Colleoni ◽  
Laura Fontana ◽  
Stefano Ferrero ◽  
...  
Keyword(s):  
Cancer Genomics ◽  
Molecular Taxonomy ◽  
The Cancer Genome Atlas ◽  
Rank Test ◽  
Breast Cancers ◽  
Cancer Genes ◽  
Kaplan Meier ◽  
Er Positive ◽  
Cancer Genome Atlas ◽  
Student’S T

Estrogen receptor (ER)-positive progesterone receptor (PR)-negative breast cancers are infrequent but clinically challenging. Despite the volume of genomic data available on these tumors, their biology remains poorly understood. Here, we aimed to identify clinically relevant subclasses of ER+/PR− breast cancers based on their mutational landscape. The Cancer Genomics Data Server was interrogated for mutational and clinical data of all ER+ breast cancers with information on PR status from The Cancer Genome Atlas (TCGA), Memorial Sloan Kettering (MSK), and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) projects. Clustering analysis was performed using gplots, ggplot2, and ComplexHeatmap packages. Comparisons between groups were performed using the Student’s t-test and the test of Equal or Given Proportions. Survival curves were built according to the Kaplan–Meier method; differences in survival were assessed with the log-rank test. A total of 3570 ER+ breast cancers (PR− n = 959, 27%; PR+ n = 2611, 73%) were analyzed. Mutations in well-known cancer genes such as TP53, GATA3, CDH1, HER2, CDH1, and BRAF were private to or enriched for in PR− tumors. Mutual exclusivity analysis revealed the presence of four molecular clusters with significantly different prognosis on the basis of PIK3CA and TP53 status. ER+/PR− breast cancers are genetically heterogeneous and encompass a variety of distinct entities in terms of prognostic and predictive information.

Combining semiconductor-based sequencing with amplicon-based cancer gene panels: A rapid next-gen approach to clinical cancer genotyping.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10591-10591
Author(s):  
Christopher L. Corless ◽  
Tanaya Neff ◽  
Michael C. Heinrich ◽  
Carol Beadling
Keyword(s):  
Point Mutations ◽  
Read Length ◽  
Cancer Genes ◽  
Automated Identification ◽  
Average Read Length ◽  
Clinical Cancer ◽  
Multiplexed Pcr ◽  
Next Gen Sequencing ◽  
Gene Panels ◽  
Personalized Cancer

10591 Background: Bringing next-gen sequencing into clinical (CLIA-licensed) laboratories is an important step in the advancement of personalized cancer care. We have validated a new sequencing approach on the Ion Torrent (IT) PGM using the AmpliSeq Cancer Panel, which covers hotspot regions across 46 commonly mutated cancer genes. Methods: The AmpliSeq panel is comprised of 190 primer pairs that are co-amplified in a single tube to generate amplicons for sequencing. In our testing only 10ng of input DNA was used. Initial PCR was for 20 cycles, after which the amplicons were ligated with sequencing/barcode adapters, amplified for an additional 7 cycles, and then subjected to emulsion PCR. The resulting nanospheres were sequenced on an IT 316 chip. Results: We sequenced 44 samples of FFPE-derived tumor DNA that were previously genotyped on a mass spectroscopy (MS)-based panel. Samples were barcoded and sequenced in batches of 4, yielding an average of 2034 reads per amplicon (range: 95-5162) and an average read length of 76bp. Overall, 95.4% of reads were on target, and 79% of reads were AQ20 or better; 95% of the 190 amplicons had over 500 reads. All 42 known point mutations were accurately identified by the variant caller software. Seventeen in/dels from 4 to 63 bp in length were at least partially visible upon manual inspection of the read alignments, but some were not accurately called by the software. In addition, 22 new mutations were identified in gene regions not covered on our MS-based panel. We demonstrated sensitivity to the level of 5% mutant allele, and the correlation between allelic ratios measured by MS and IT sequencing was excellent (r2=0.81). Two DNA samples from laser-captured tumor worked well with the AmpliSeq Panel. Conclusions: Combining solid-state sequencing with a highly multiplexed PCR method for library construction is a rapid (48 hr) approach for next-gen sequencing of clinical cancer samples. The process is highly scalable and larger, cancer-specific amplicon panels are in development. Automated identification of in/dels remains a challenge in next-gen sequencing output.

Relationship of MET exon 14 splicing variants and MET exon 14 skipping expression in NSCLC FFPE samples.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14603-e14603
Author(s):  
John B. Williamson ◽  
Xia Li ◽  
Guang Liu ◽  
Haigang Gu ◽  
Janet Orton ◽  
...  
Keyword(s):  
Splice Site ◽  
Variant Calling ◽  
Diagnostic Procedures ◽  
Cancer Genes ◽  
Mrna Isoforms ◽  
Activating Mutations ◽  
Splicing Variants ◽  
Ffpe Samples ◽  
Dna Alterations ◽  
Next Generation Sequencing Ngs

e14603 Background: MET is the target of recurrent somatic alterations in approximately 7% of non-small cell lung carcinomas (NSCLC). A key class of therapeutically relevant MET mutations results in aberrant mRNA splicing, deletion of exon 14 from the mRNA transcript (METex14 skipping), and MET overexpression. METex14 skipping assays routinely use next-generation sequencing (NGS). However, because most NGS assays are DNA based, the relationship between METex14 DNA alterations and METex14 skipping mRNA expression is not well understood. Furthermore, because METex14 skipping may have low background levels, setting a threshold for calling METex14 skipping based on RNA levels alone is challenging. To investigate these relationships, we initiated a research study in 3 CLIA/CAP laboratories using an NGS panel (OCAv3, for research use only, not for use in diagnostic procedures) that includes 161 cancer genes and detects METex14 splicing variants and METex14 skipping mRNA isoforms. Methods: OCAv3 libraries were prepared following kit instructions with templating and sequencing performed on the Ion Chef and S5 XL systems. Reads were aligned to hg19 using Torrent Suite Software and variant calling was performed using Ion Reporter software. Two cell lines (HS746T and NCI-H596) known to contain METex14 splice site mutations were used as controls. Results: Of the first 28 NSCLC FFPE specimens selected having a range of METex14 RNA expression, we detected METex14 skipping alterations in 9 cases: 6 cases with variants at exon 14 canonical splice sites and 3 cases of novel deletions in the intron 13 poly-pyrimidine tract. METex14 skipping alterations were exclusive to other oncogenic driver variants but occasionally associated with MDM2 amplification. All cases with splice site variants showed elevated METex14 skipping expression. Cases without splicing variants had no or lower METex14 skipping expression and commonly harbor activating mutations in other oncogenes (6 KRAS, 5 EGFR, 1 ERBB2, 1 MYC and 1 CD74-NRG1 fusion). Conclusions: We demonstrate a framework for interpreting MET alterations that considers both MET splice site variants and METex14 skipping transcript expression in the context of additional oncogenic mutations. An update will be presented as additional cases accrue.

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