Ribosomal RNAs (rRNAs) are extremely abundant, often constituting 80% to 90% of total RNA. Since rRNA sequences are often not of interest in genomic RNA sequencing experiments, rRNAs can be removed from the sample before the library preparation step, in order to prevent the majority of the library and the majority of sequencing reads from being rRNA. Removal of rRNA can be especially challenging for low quality and formalin-fixed paraffin-embedded (FFPE) RNA samples due to the fragmented nature of these RNA molecules. The NEBNext rRNA Depletion Kit (Human/Mouse/Rat) depletes both cytoplasmic (5 S rRNA, 5.8 S rRNA, 18 S rRNA, and 28 S rRNA) and mitochondrial rRNA (12 S rRNA and 16 S rRNA) from total RNA preparations from human, mouse, and rat samples. Due to the high similarity among mammalian rRNA sequences, it is likely that rRNA depletion can also be achieved for other mammals but has not been empirically tested. This product is compatible with both intact and degraded RNA (e.g., FFPE RNA). The resulting rRNA-depleted RNA is suitable for RNA-seq, random-primed cDNA synthesis, or other downstream RNA analysis applications. Regardless of the quality or amount of input RNA, this method efficiently removes rRNA, while retaining non-coding and other non-poly(A) RNAs. The NEBNext rRNA Depletion Kit thus provides a more complete picture of the transcript repertoire than oligo d(T) poly(A) mRNA enrichment methods. © 2016 by John Wiley & Sons, Inc.

Background: Analytically and clinically validated non-invasive blood tests that quantify breast cancer burden and clinical drug response/resistance are greatly needed. Many groups have successfully detected tumor markers in blood using a variety of technologies, including next generation sequencing (NGS). We performed a comprehensive NGS study on a small number of patients to evaluate the value of global versus individual markers for the quantitation of tumor-derived cell free DNA (cfDNA) in plasma. Methods: DNA isolated from formalin-fixed primary tumor, buffy coat cells, and plasma from 2 patients with metastatic breast cancer were characterized simultaneously for copy number aberrations (CNAs) and differentially methylated regions (DMRs) using whole genome bisulfite sequencing (WBGS), and targeted sequencing-based genotyping of 346 cancer-associated single nucleotide variations (SNVs). CNA and DMR regions were identified from log normalized, GC content corrected counts and DMR data using Poisson and binomial distribution theory and false discovery rate controlling methods. Percent tumor in cfDNA was estimated from the normalized ratio (plasma: primary tumor) of CNA or DMR compared to buffy coat, aggregating over genomic regions. Sample sets from 8 non-metastatic patients were also profiled using the targeted SNV panel in order to compare SNVs between samples and estimate percent tumor cfDNA. Results: WGBS detected tumor specific alterations in each primary tumor compared to buffy coat. By analyzing the genome using 100 Kb bins, we observed over 1000 bins with detectable CNA signal and, among 56 million CpG sites, over 30,000 DMRs. As expected, 5 or fewer informative somatic SNVs were detected in each patient. Analysis of these somatic changes in plasma revealed that the tumor fraction estimated from SNV detected in cfDNA varied widely between sites originally discovered in the patient’s primary tumor. In contrast, similar estimates of tumor fraction in cfDNA were obtained using CNA and DMR profiles within each patient; both methods yielded similar estimates of over 50% in one patient and less than 10% in the other. For the patient with high tumor fraction, both CNA and DMR profiles contained examples of individual large genomic regions that displayed additional clear aberrations in the plasma compared to the original tumor, such as a striking loss of a >25 Mb region of chromosome 4. Conclusions: Although individual somatic SNV in cfDNA can be detected in metastatic disease, calculated allelic fraction based on individual SNVs varies greatly within the same patient. Measuring and integrating CNA or DMR across the genome provided more consistent and reliable estimates of tumor DNA fraction in plasma, and also revealed alterations in plasma from patients with metastatic disease that were not prominent in the primary tumor. Citation Format: Ellen M Beasley, Richard D Abramson, Gregory E Alexander, David Chan, Kristen Bradley, Francois Collin, Michael Crager, Andrew Dei Rossi, Joseph Dorado, Adam Friedman, William J Gibb, Jennie Jeong, Col Jones, C J Ku, Yan Ma, John Morlan, Kunbin Qu, Aibing Rao, Aaron Scott, Haluk Tezcan. Global quantitative measures using next-generation sequencing for breast cancer presence outperform individual tumor markers in plasma [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 P4-02-08.

11018 Background: While several recently discovered gene fusions already play an important role in personalized cancer treatment, many cancer gene fusions remain to be discovered. Next generation sequencing has enabled identification of many rare gene fusion events in fresh or frozen solid tumors. There is a need to detect gene fusions in transcriptomes of formalin-fixed paraffin-embedded (FFPE) tumor tissue, for which there is long-term clinical outcome data. We therefore sought to develop bioinformatics methods to detect fusion transcripts in FFPE tissue and to characterize their association with clinical outcomes. Methods: RNA sequencing libraries were created and sequenced from tumor biopsy tissues (Plos One 2012 7(7): e40092) of two ER+ breast cancer cohorts consisting of 136 and 77 patients, for which clinical outcomes were available. The fusion junctions were nominated by the RNA-seq aligner GSNAP and further filtered to consider discontinuous expression patterns at exon/intron levels. Results: A total of 108 candidate fusion transcripts were detected and RT-PCR assays confirmed 89% of the top ranking fusion transcript candidates. The majority (82%) of identified fusion gene partners are listed in the COSMIC database of known cancer sequence variations. Of note, several patients expressed multiple fusion transcripts that are significantly associated with tumor progression (P<0.001), including genes associated with cell proliferation and cellular metabolism. Furthermore, these patients also harbored inter-chromosomal gene fusions. It is noteworthy that several gene fusions were present in multiple patients. In one of these recurrent fusions the estrogen receptor gene acts as the fusion pair donor. Conclusions: Novel bioinformatics approaches developed here demonstrate the ability to detect fusion transcripts as biomarkers from archival FFPE tissues that associate with breast cancer progression. Some gene fusions were common in multiple patients and deserved further study.

RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue form the basis for widely used clinical diagnostic tests; however, RT-PCR is practically constrained in the number of transcripts that can be interrogated. We have developed and optimized RNA-Seq library chemistry as well as bioinformatics and biostatistical methods for whole transcriptome profiling from FFPE tissue. The chemistry accommodates low RNA inputs and sample multiplexing. These methods both enable rediscovery of RNA biomarkers for disease recurrence risk that were previously identified by RT-PCR analysis of a cohort of 136 patients, and also identify a high percentage of recurrence risk markers that were previously discovered using DNA microarrays in a separate cohort of patients, evidence that this RNA-Seq technology has sufficient precision and sensitivity for biomarker discovery. More than two thousand RNAs are strongly associated with breast cancer recurrence risk in the 136 patient cohort (FDR <10%). Many of these are intronic RNAs for which corresponding exons are not also associated with disease recurrence. A number of the RNAs associated with recurrence risk belong to novel RNA networks. It will be important to test the validity of these novel associations in whole transcriptome RNA-Seq screens of other breast cancer cohorts.

We report a method for Selective Depletion of abundant RNA (SDRNA) species from Human total RNA isolated from formalin-fixed, paraffin-embedded (FFPE) tissue, here demonstrating removal of ribosomal and mitochondrial transcripts from clinical FFPE tissue RNA archived up to 20 years. Importantly, SDRNA removes 98% of targeted RNAs while preserving relative abundance profiles of non-targeted RNAs, enabling routine whole transcriptome analysis of clinically valuable archival tissue specimens by Next-Generation Sequencing.

Abstract We have used RNA-seq to profile and compare normal and cancerous human breast tissue. FFPE breast specimens from a total of 24 patients, 12 normal (N) and 12 tumor (T) specimens from surgical resections, were analyzed on an Illumina's GA IIx sequencer. Whole transcriptome RNA-Seq libraries were prepared after depletion of ribosomal RNA by a protocol developed at Genomic Health Inc. (GHI). The analysis was multiplexed across two flow cells using barcoding, with two specimens per sequencing lane (1 T and 1 closely age-matched N library from a different patient). FFPE tissue archive times ranged from 10 to 13 years and they were also closely matched within each lane. To evaluate reproducibility, triplicate libraries were created from 4 of the specimens and analyzed within and across flow cells. Libraries yielded, on average, 19 million 51 bp sequences. R2 values obtained from replicate libraries prepared from the same patient RNA were > 0.9 within and between flow cells. More than 80% of known genes in the human genome were detected in all patients. Several thousand intergenic transcripts were identified by an algorithm developed at GHI. A negative binomial model with tag-wise estimates of dispersion was applied to the known genes and intergenic regions. Inter-patient count variance is generally higher in the set of intergenic sequences than in the set of gene (RefSeq) sequences. Thousands of gene (RefSeq) and intergenic sequences were found to be differentially expressed between T and N tissues. We sought to build classifiers based on flow cell #1 data that could stratify T and N tissues when applied to flow cell #2 data. Sets of genes and intergenic regions were selected for analysis based on high inter-patient count variance. Support vector machine classifiers were trained and then applied to the data from flow cell #2, and also to another GHI tumor/normal RNA-Seq study. Either a set of 100 genes (RefSeq), or a set of 70 intergenic sequences accurately distinguished tumor and normal tissues. Our results offer further evidence of the potential of RNA-Seq for discovery of biomarkers. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4859. doi:10.1158/1538-7445.AM2011-4859

Abstract Background: RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue are the basis for very precise and sensitive clinical diagnostic tests, such as the 21 gene Oncotype DX® breast cancer assay. Both inherent limits of technical scalability and the small amounts of patient FFPE RNA available place practical constraints on the number of transcripts that can be interrogated by RT-PCR. We developed new methods for RNA profiling through massively parallel “next generation” sequencing (RNA-Seq) of archival FFPE specimens. We report here the technical performance of this methodology and compare the results to RT-PCR results obtained in one of the studies that were carried out to develop the 21 gene assay. Methods: RNA was extracted in 2002 from 136 invasive breast tumors that were formalin-fixed and paraffin-embedded between 1990 and 1997. RNA-Seq was carried out using minor modifications to methods we have reported previously (Sinicropi et al., Advances in Genome Biology and Technology Conference, p. 170, 2010 and p. 198, 2011). Briefly, 0.1 mg of total RNA was selectively depleted of ribosomal RNA and sequencing libraries were prepared using a modification of the ScriptSeq™ kit from Epicentre. The libraries were sequenced on an Illumina HiSeq 2000 instrument with multiplexing of two libraries per lane for 50 cycles in one direction. The resulting FASTQ sequences were mapped to version hg19 of the human genome using the Illumina CASAVA pipeline. The total number of sequences (reads) that uniquely mapped to all exons of each RefSeq entry was used for quantification of expression levels. Results: On average, there were 43 million reads per sample (range 31 - 58 million; SD=4.6 million) of which 69% uniquely mapped to the human genome. Ribosomal RNA was effectively removed and accounted for <0.3% of total counts. Significant coverage of a high proportion of the human genome was obtained, with 40% of RefSeq transcripts represented by a median of more than 100 reads. Using Cox proportional hazards analysis to evaluate the association of quantitative gene expression with breast cancer recurrence, the standardized hazard ratios and p-values for the 21 Oncotype DX genes determined by RNA-Seq were comparable to those originally obtained using RT-PCR. Moreover, whole transcriptome RNA-Seq identified more than 1800 new coding, intronic, and intergenic transcripts that strongly associated with breast cancer recurrence risk (at a false discovery rate <10%) and revealed heretofore unappreciated co-expressed gene networks. Summary: New methodology has been developed for application of next generation sequencing-based whole transcriptome profiling to small amounts of archival FFPE tissue. This technology has sensitivity and selectivity comparable to RT-PCR, can provide a vast increase in the number of interrogated transcripts, can reveal new biological relationships, and has excellent performance suitable for the discovery of RNA biomarkers. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr PD03-09.

Molecular analysis of archival tumor specimens has accelerated the discovery of clinically useful biomarkers. RNA-seq of RNA extracted from formalin fixed, paraffin-embedded (FFPE) specimens, a potentially valuable source of biomarkers, is hampered by the presence of highly abundant ribosomal RNA (rRNA), which is difficult to remove due to extensive RNA degradation. Here we report RNA-seq results from human FFPE samples. RNA was extracted from estrogen receptor positive (ER+) and negative (ER-) FFPE breast tumors 7-8 years after fixation and embedding. Sequencing libraries were prepared using a proprietary protocol with known strand direction. On average, 14 million reads were obtained from each lane of the Illumina GAII. After employing a proprietary rRNA depletion method, 18S and 28S rRNA are reduced to less than 5% of total mapped reads. Approximately 25 000 unique Ref-seq gene transcripts were detected in each library, demonstrating detection of most rare and intermediate transcripts as well as abundantly expressed transcripts. The relative abundance of the estrogen receptor gene ESR1 and co-expressed transcripts in the ESR1+ and ESR1- tumors correlated with expression differences measured by qPCR. Directional analysis indicated that 95% of the reads mapped to known genes had the correct direction, whereas remaining 5% with antisense direction, which possibly serve as regulatory functions. Among the uniquely mapped reads, ~ 25% were within known exons, 41% in introns, and 34% in intergenic regions. 'Valleys' and 'hills' were commonly observed across the three mapped regions. A proprietary region analysis method was developed to identify any region (not limited to known Ref-seqs) exhibiting differential expression. Using this method, we identified 34 regions that were highly differentially expressed between the ESR1+ and ESR1- tumor specimens. These regions represent exons, introns and intergenic areas. Our findings were confirmed by qPCR. These preliminary studies demonstrate the feasibility of using RNA-seq with FFPE tumor specimens. We anticipate that RNA-seq will provide a new perspective about transcriptional changes that underlie the phenotypes of individual tumors.

BACKGROUND:Molecular tests for diagnosis of disease, particularly cancer, are gaining increased acceptance by physicians and their patients for disease prognosis and selection of treatment options. Gene expression profiles and genetic mutations are key parameters used for the molecular characterization of tumors. A variety of methods exist for mutation analysis but the development of assays with high selectivity tends to require a process of trial and error, and few are compatible with real-time PCR. We sought to develop a real-time PCR-based mutation assay methodology that successfully addresses these issues.METHODOLOGY/PRINCIPAL FINDINGS:The method we describe is based on the widely used TaqMan real-time PCR technology, and combines Allele-Specific PCR with a Blocking reagent (ASB-PCR) to suppress amplification of the wildype allele. ASB-PCR can be used for detection of germ line or somatic mutations in either DNA or RNA extracted from any type of tissue, including formalin-fixed paraffin-embedded tumor specimens. A set of reagent design rules was developed enabling sensitive and selective detection of single point substitutions, insertions, or deletions against a background of wild-type allele in thousand-fold or greater excess.CONCLUSIONS/SIGNIFICANCE:ASB-PCR is a simple and robust method for assaying single nucleotide mutations and polymorphisms within the widely used TaqMan protocol for real time RT-PCR. The ASB-PCR design rules consistently produce highly selective mutation assays while obviating the need for redesign and optimization of the assay reagents. The method is compatible with formalin-fixed tissue and simultaneous analysis of gene expression by RT-PCR on the same plate. No proprietary reagents other than those for TaqMan chemistry are required, so the method can be performed in any research laboratory with real-time PCR capability.

The importance of Bax for induction of tumor apoptosis through death receptors remains unclear. Here we show that Bax can be essential for death receptor–mediated apoptosis in cancer cells. Bax-deficient human colon carcinoma cells were resistant to death-receptor ligands, whereas Bax-expressing sister clones were sensitive. Bax was dispensable for apical death-receptor signaling events including caspase-8 activation, but crucial for mitochondrial changes and downstream caspase activation. Treatment of colon tumor cells deficient in DNA mismatch repair with the death-receptor ligand apo2 ligand (Apo2L)/tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) selected in vitro or in vivo for refractory subclones with Bax frameshift mutations including deletions at a novel site. Chemotherapeutic agents upregulated expression of the Apo2L/TRAIL receptor DR5 and the Bax homolog Bak in Bax−/− cells, and restored Apo2L/TRAIL sensitivity in vitro and in vivo. Thus, Bax mutation in mismatch repair–deficient tumors can cause resistance to death receptor–targeted therapy, but pre-exposure to chemotherapy rescues tumor sensitivity.

Philosophy, methods and procedures for delivery of a quality programme of higher education with an emphasis on Instructional Technology to a small emerging island nation are described. Celebrating a decade of co‐operation with San Jose State University (SJSU), the Commonwealth of the Northern Mariana Islands now offers public education from pre‐school through an accredited community college. Several of the key courses are described, along with the processes of course selection and development, and faculty selection and evaluation. The authors attribute much of the success to respected SJSU faculty who were willing to teach in the Western Pacific during their summers and intersessions, and during sabbatical and other leaves, so as to deliver courses leading to an MA degree curriculum to the site rather than requiring the students to study in residence on the campus.