Emerging Technologies in Molecular Pathology

1. Emerging Technologies in Molecular Pathology Edward C. Stack, Ph.D. January 5, 2012

2. Molecular techniques can offer tremendous insight into disease processes. However, indiscriminate use of these techniques, without a clear understanding of underlying pathology, can lead to false assumptions. • How pathology guides molecular analysis • Dissection methods and consequences

3. How pathology guides molecular analysis

4. How pathology guides molecular analysis

5. Dissection methods and consequences Microdissection Macrodissection

6. Dissection methods and consequences Nucleic Acid Extraction RNA Profiles Fresh FFPE Robot Row in CMOP

7. Emerging tools in the molecular pathology armory As new tools avail themselves, it is important to understand those currently used and how new assays, such as nanoString or RNAseq, compare to those currently considered the ‘gold’ standard, such as TaqManqPCR. • NanoStringfor limited transcriptome analysis • Affy ST microarrays for more complete transcriptome coverage • RNAseq for whole transcriptome coverage • Fresh v. FFPE • RNA species differences • analysis issues and biocomputational evolution

8. Emerging tools in the molecular pathology armory qPCR A technical advancement over standard PCR, as developed by Mullis and Faloona. PCR allows for exponential amplification of DNA sequences, when the genomic sequence at each end of the target is known. Importantly, quantification (the q in qPCR) of expressed transcripts is not possible with standard PCR, which is more qualitative and at best, semi-quantitative. Why? It is essential to understand standard PCR in order to make effective use of qPCR.

9. Emerging tools in the molecular pathology armory qPCR Standard PCR Strand Separation Primer Hybridization DNA synthesis

10. Emerging tools in the molecular pathology armory qPCR The RT portion – can be performed as either a one- or two-step process

11. Emerging tools in the molecular pathology armory qPCR Using TaqMan Reagents (Applied Biosciences) http://www.appliedbiosystems.com/absite/us/en/home/applications-technologies/real-time-pcr/taqman-and-sybr-green-chemistries.html

12. Emerging tools in the molecular pathology armory qPCR qPCR allows reactions to be characterized by the point in time during cycling when amplification of a PCR product achieves a fixed level of fluorescence. In the initial PCR cycles (baseline), fluorescence is negligible. Software then calculates the Rn (normalized reporter), with an algorithm determining the point on the amplification plot at which the ∆Rn crosses the threshold. The cycle at which this occurs is defined as CT.

13. Emerging tools in the molecular pathology armory qPCR In practice - interrogating miR 146a (with RNU48 snoRNA control).

14. Emerging tools in the molecular pathology armory NanoString This novel transcription analysis was developed within the last 5 years, and is proving to be an attractive alternative to qPCR for comprehensive, though still small, transcriptome studies. Developed by Geiss and colleagues -

15. Emerging tools in the molecular pathology armory NanoString Through use of a capture and reporter pairing, this assay is capable of detecting ~16K individual transcripts. How it works: From Geiss, et al (2008)

16. Emerging tools in the molecular pathology armory NanoString Analysis of spiked-in controls provided demonstrates linearity and reproducibility of the assay From Geiss, et al (2008)

17. Emerging tools in the molecular pathology armory NanoString Scatterplot analysis of normalized NanoString signal shows very tight R2. GEP alterations also observed. From Geiss, et al (2008)

18. Emerging tools in the molecular pathology armory NanoString Comparison between NanoString and an Affy array demonstrated higher transcript detection in the Nanostring platform. From Geiss, et al (2008)

19. Emerging tools in the molecular pathology armory NanoString Further comparisons of fold-changes between NanoString and an Affy array demonstrated fairly good agreement (R2 = 0.788). For 202 transcripts significantly regulated in both the NanoString and Affy platforms, the two platforms demonstrated significant agreement (Correlation coefficient of 0.788). . From Geiss, et al (2008)

20. Emerging tools in the molecular pathology armory NanoString Additional validation of detected fold changes between NanoString and Affy using TaqMan revealed very high concordance (more so than Affy). Furthermore, using human reference RNA, the concordance between NanoString and TaqMan persists (R2 = 0.945). What does this mean? From Geiss, et al (2008)

21. Emerging tools in the molecular pathology armory NanoString So how well does it work on FFPE? NanoString qPCR Pearson Coefficient r = 0.50 Pearson Coefficient r = 0.90 Samples are FFPE oral carcinomas Pearson Coefficient r = 0.59

22. Emerging tools in the molecular pathology armory Affy ST microarray The Affy 1.0 ST Array interrogates 28,869 genes using 764,885 unique probes (~40/gene), based on more than a 3’-based interrogation. Why might this be important in FFPE? whole transcriptome amplification Total RNA cDNA Figure courtesy of Neil Martin, MD

23. Emerging tools in the molecular pathology armory Affy ST microarray How does the array work?

24. Emerging tools in the molecular pathology armory • Affy ST microarray • Does the array work well in FFPE? • Pilot data from sample 1175. Log2 ratios between paired fresh and FFPE Correlation trending correctly.

25. Emerging tools in the molecular pathology armory Affy ST microarray Does the array work well in FFPE? Normalized data clusters based on tissue type – squamous cell carcinoma or adenocarcinoma. Putative p63 signature (correlative and anti-correlative changes) between SCC and AC. From Hall, et al, 2011

26. Emerging tools in the molecular pathology armory • Affy ST microarray • Post-assay considerations: • Bioinformatics required for parsing of the data. • Unlike the NanoString, calls of gene up/down regulation need to be verified by an independent method – typically TaqMan.

27. Emerging tools in the molecular pathology armory RNAseq Shorthand for RNASequencing. Developed in the late 1990’s by Cambridge scientists Shankar Balasubramanian and David Klenerman, in part through their work on fluoroescently labeled captured DNA molecules. Allows for the sequencing of ALL RNA species, providing an unparalleled view of the entire transcriptome.

28. Emerging tools in the molecular pathology armory RNAseq Overview. Transcriptome reconstruction Expression quantification From Wang et al, 2009

29. Emerging tools in the molecular pathology armory RNAseq Library Construction – Fresh RNA TruSeq Library Prep RNA Isolation Typical RNA Profile from FFPE Blunt End °° Adenylate °° Ligate Adapter °° Enrich Library RNA from FreshTissue 1st Strand 2nd Strand FreshTissue Cores Typical TruSeq Library Profile from FFPE

30. Emerging tools in the molecular pathology armory RNAseq Library Construction – FFPE RNA RNA Isolation Typical RNA Profile from FFPE TruSeq Library Prep Blunt End °° Adenylate °° Ligate Adapter °° Enrich Library RNA from FFPE Tissue FFPE Tissue Cores RNA from FFPE Tissue 1st Strand 2nd Strand Typical TruSeq Library Profile from FFPE

31. Emerging tools in the molecular pathology armory RNAseq Data Generated – Fresh RNA Reads / Aligned Reads Chromosome Map

32. Emerging tools in the molecular pathology armory RNAseq Data Generated – Feasibility in FFPE RNA Reads / Aligned / Not / Multi Chromosome Map

33. Emerging tools in the molecular pathology armory RNAseq Data Visualized – Feasibility in FFPE RNA Typical visualization of expression (PTEN) in replicate samples from FFPE blocks containing prostate cancer tissue. While expression is not restricted to exons, there is a tight segregation of reads within identified gene regions, and a general absence of reads outside of identified transcripts.

34. Emerging tools in the molecular pathology armory RNAseq Data Visualized – Feasibility in FFPE RNA Gene FPKM Concordance TSS FPKM Concordance R2, FPKM R2, FPKM R1, FPKM R1, FPKM Concordance over 10,000 gene transcripts detected by RNAseq in replicate FFPE PrCa samples. R2 = 0.9838 Concordance over 7000 transcription starts sites (TSS) detected by RNAseq in replicate FFPE PrCa samples. R2 = 0.9989 A Sample of PrCa-relevant genes detected include: MMP10, SMTN, ERG, TMPRSS2, BIRC5, UBE2C, CDKN3, VEGF, and TK1.

35. Emerging tools in the molecular pathology armory RNAseq Feasibility in FFPE RNA A fairly robust read depth via single end sequencing results in ~ 40% alignment to hg18 sufficient to support interrogation of the transcriptome. Inter-assay reproducibility is demonstrated by high concordant replicates, for both gene transcripts and transition start site sequences, demonstrating high assay fidelity. Lack of poly-A selection offers more transcriptome coverage, providing a more complete snapshot of the RNA environment, including mRNA, ncRNA, etc.. Does this mean RNAseq is ready for research?

36. Emerging tools in the molecular pathology armory RNAseq Issues with FFPE RNA Bioinformatic challenges include: Data handling and storage (sequencing leads to massive data outputs). Contig assembly and genomic alignment (we currently use TopHat, though there are others). Complex genomes though have problems with: exon spanning sequences (junction library); sequence reads that map to multiple genomic locations (proportional assignment based on neighboring unique sequences). Cost versus coverage and depth – real world concerns.

37. Emerging tools in the molecular pathology armory RNAseq Issues with FFPE RNA Mapping aligned reads to UCSC Genome browser demonstrate marked differences between fresh and FFPE RNAseq samples in the housekeeping gene transcript ALDOA - aldolase A, fructose-bisphosphate. From Dr. SvitlanaTyekucheva

38. Emerging tools in the molecular pathology armory RNAseq Issues with FFPE RNA KLK3 A similar trend was observed when mapping aligned reads to UCSC Genome browser demonstrate marked differences between fresh and FFPE RNAseq samples in: the Pca specific gene transcript KLK3 - kallikrein-related peptidase 3 (or PSA); or the housekeeping gene transcript GAPDH - glyceraldehyde-3-phosphate dehydrogenase. GAPDH From Dr. SvitlanaTyekucheva

39. Emerging tools in the molecular pathology armory RNAseq Issues with FFPE RNA ACTNB A similar trend was observed when mapping aligned reads to UCSC Genome browser demonstrate marked differences between fresh and FFPE RNAseq samples in: the housekeeping gene transcript ACTNB- Actin B; or the housekeeping gene transcript RPL32- ribosomalprotein L321. While the apparentloss of alignedsignalis less thanideal, the overallpicturesuggeststhat the development of novelbioinformaticapproaches to FFPE RNAseq data willlead to a new era in transcriptomeanalyses. RPL32 From Dr. SvitlanaTyekucheva

40. Emerging tools in the molecular pathology armory RNAseq FFPE small RNA – miR RNAseq in practice! Small RNAseq (smRNAseq), where the assay can detect miRNAsnoRNA, scRNA, snRNA, as well at tRNA. Mt-tRNA, rRNA, introninc, exonic, and more…

41. Emerging tools in the molecular pathology armory RNAseq FFPE small RNA – miR RNAseq in practice! Unsupervised cluster analysis of miR expression calls between RCC and normal as assessed by RNAseq in both fresh and FFPE samples demonstrates the ability of each substrate to classify tumor from normal. Notice anything unusual? From Weng et al, 2010

42. Emerging tools in the molecular pathology armory RNAseq FFPE small RNA – miR RNAseq in practice! Correlational analysis of miR expression calls between RCC and normal as assessed by both RNAseq and microarray in fresh samples demonstrates high correlation of expression alterations (R=~0.8). Same is true for differentially expressed miR’s (R=0.77). Data demonstrate practical suitability for large-scale smRNAseq. From Weng et al, 2010

43. Emerging tools in the molecular pathology armory RNAseq FFPE small RNA – miR RNAseq in practice! Correlational analysis of miR expression calls between RCC and normal as assessed by RNAseq in fresh and FFPE samples also demonstrates high correlation of expression alterations (R=~0.96). Differentially expressed miR’s show similar concordance as before (R=0.79). Anything unusual about this approach? From Weng et al, 2010

44. Emerging tools in the molecular pathology armory RNAseq FFPE small RNA – miR RNAseq in practice! Specific miR expression levels by RNAseq, microarray, and qPCR in fresh samples Does the data presented leave any impression? From Weng et al, 2010

46. Emerging Technologies in Molecular Pathology Reference List: GeissGK, et al.. (2008) Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat Biotechnol26:317-325. Hall JS, Leong HS, Armenoult LS, Newton GE, Valentine HR, Irlam JJ, Möller-Levet C, Sikand KA, Pepper SD, Miller CJ, West CM. (2011) Exon-array profiling unlocks clinically and biologically relevant gene signatures from formalin-fixed paraffin-embedded tumoursamples. Br J Cancer 104:971-981. Mullis KB, Faloona FA. (1987) Specific synthesis of DNA in vitro via a polymerase-catalyzed chain reaction. Methods Enzymol155:335-350. Osborne MA, Furey WS, Klenerman D, Balasubramanian S.(2000) Single-molecule analysis of DNA immobilized on microspheres. Anal Chem72:3678-3681. Reis PP, Waldron L, Goswami RS, Xu W, Xuan Y, Perez-Ordonez B, Gullane P, Irish J, Jurisica I, Kamel-Reid S. (2011) mRNA transcript quantification in archival samples using multiplexed, color-coded probes. BMC Biotechnol11:46-56. Weng L, Wu X, Gao H, Mu B, Li X, Wang JH, Guo C, Jin JM, Chen Z, Covarrubias M, Yuan YC, Weiss LM, Wu H. (2010) MicroRNA profiling of clear cell renal cell carcinoma by whole-genome small RNA deep sequencing of paired frozen and formalin-fixed, paraffin-embedded tissue specimens. J Pathol222:41-51. Wang Z, Gerstein M, Snyder M. (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57-63.