Kelli Bramlett, Jeoffrey Schageman, Varun Bagai, Jian Gu, Kristi Lea, Jose Cienfuegos, James L. Wittliff *Thermo Fisher Scientific 2130 Woodward St, Austin TX 78744

*Department of Biochemistry & Molecular Genetics, University of Louisville Louisville, KY 40292

I. ABSTRACT

Forecasting clinical behavior and therapeutic response of human cancer currently utilizes a limited number of tumor markers in combination with characteristics of the patient and their disease. Although few tumor markers and molecular targets exist for evaluation, the wealth of information derived from recent sequencing advancements provides greater opportunities to develop more precise tests for diagnostics, prognostics, therapy selection and monitoring in the future. The objectives of this study are to study miRNA and mRNA expression profiles of laser capture microdissection (LCM)-procured tumor cells and intact serial sections of breast tissue samples using next generation sequencing (NGS) methods. Our hypothesis is that miRNA signatures discerned from specific tumor cell populations more precisely correlate with behavior than that provided by conventional biomarkers from intact tissue samples. Additionally, we hypothesize the data generated in this study will present mRNA signatures informative for breast tumor research and support our miRNA findings through suggesting relevant miRNA:mRNA target associations.

De-identified frozen research samples of primary invasive ductal tumors of known grade and biomarker status containing 35-70% tumor were selected from an IRB-approved Biorepository. Comparison of expressed miRNAs from intact tissue sections with those of cognate tumor cells procured by LCM revealed, in general, that smaller defined miRNA gene sets were expressed in LCM isolated populations of tumor cells. In addition to miRNA sequencing, targeted RNA sequencing with the Ion AmpliSeq™ Transcriptome Human Gene Expression Kit was used to capture mRNA expression information. Data presented here demonstrates high mapping rates for targeted mRNA (>91% of reads) and miRNA (> 88% of reads) libraries. We also demonstrate high technical reproducibility between multiple libraries from the same tumor sample for both mRNA (R>0.99) and miRNA (R>0.97) libraries. We also report suggested miRNA:mRNA target associations identified in our set of breast tumor research samples. These data provide insights into breast cancer biology that may lead to new molecular diagnostics and targets for drug design in the future as well as an improved understanding of the molecular basis of clinical behavior and potential therapeutic response.

II. MATERIALS AND METHODS

Tissue Preparation & Laser Capture Microdissection:Using an IRB-approved study, frozen serial tissue sections containing 55 +/- 23% tumor were prepared and stained with H & E using established protocols and tumor cells (~ 14,000 LCM pulses) were procured from an adjacent section using a Pixcell IIe (Arcturus/Thermo Fisher Scientific) instrument.

Sample Preparation: For invasive ductal tumor samples, RNA was extracted from intact tissue sections using mirVana™ miRNA Isolation kits (Thermo Fisher P/N AM 1650). Ion AmpliSeq™ Transcriptome libraries were generated from 4 different invasive ductal tumor samples using the Human Gene Expression Panel (Thermo Fisher P/N A26325) targeting ~21,000 well annotated human genes from 10ng of total RNA (effective range of 1-100ng input). Triplicate libraries were generated from each sample.

Small RNA libraries were generated using the Ion Total RNA-Seq Kit V2 (Thermo Fisher Cat # 4475936). Triplicate libraries were prepared.

Advances in Breast Tumor Biomarker Discovery Methods

IV. SUMMARY

•Gene expression information can be obtained from very small amounts of RNA from breast tissue samples in a technically reproducible method

•A subset of genes identified as overexpressed by NGS in breast tumor tissue are found to be significant by Cox regression for disease free survival and overall survival

•Next Generation Sequencing of miRNAs using LCM-procured carcinoma cells combined with mRNA expression obtained via targeted sequencing methods provides an innovative approach for decoding miRNA:mRNA pairs involved in breast tumor behavior

For Research Use Only. Not for use in diagnostic procedures.© 2015 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries unless otherwise specified. 

Figure 5. Most highly expressed genes identified by NGS in breast tumor tissue sections were compared to gene expression data from microarrays of LCM procured neoplastic cells available in the IRB-approved biorepository. 40 genes in the original list from NGS analysis also were significant by COX regression analysis for disease free survival, overall survival or both. A subset of the 40 genes identified as significant in breast tumor samples by both NGS analysis and microarray analysis were chosen for Kaplan-Meier analysis above; GLUL, and XBP1.

Figure 6: Retrospective breast tumor research sample from an 84 year old Caucasian with node negative invasive ductal carcinoma, grade 3. MA plot comparing miRNA expression from an intact tissue section compared to LCM procured carcinoma cells is shown on the left. Some of the most differentially regulated miRNAs are highlighted in the table to the right. Negative fold change values indicate higher miRNA expression in the LCM procured cells.

Next Generation Sequencing:Ion AmpliSeq™ Transcriptome libraries were barcoded, templated and sequenced on the Proton Sequencing System. Multiplexed libraries were templated using the Ion PI™ Template OT2 200 kit v3 and sequenced using the Ion PI™ Sequencing 200 kit v3 on Ion PI™ v2 chips (Thermo Fisher Scientific P/N 4488318, 4488315, 4482321) as two six-plex library pools. The data analysis is performed on the Torrent Server using a free ampliSeqRNA plug-in that provides simple QC, visualization, and normalized counts per gene that corresponds to gene expression information.Multiplexed small RNA libraries were templated using the Ion PI™ Template OT2 200 kit v2 and sequenced using the Ion PI™ Sequencing 200 kit v2 on two Ion PI™ v2 chips (Thermo Fisher Scientific) as multiplexed library pools. Small RNA data was aligned to miRNA precursors using the Ion small RNA pipeline in Partek® Flow® data analysis software package.

miRNA sequencing data: correlations between replicates from the same tissue sample

Sample 1 Sample 2 Sample 3 Sample 4

0.989-0.997 0.975-0.994 0.990-1.0 0.996-0.999

mRNA sequencing data: correlations between replicates from the same tissue sample

Sample 1 Sample 2 Sample 3 Sample 4

0.993-0.996 0.995 0.981-0.994 0.991-0.994

III. RESULTS

Figure 1: Sequencing microRNA library performance: (A) Representative miRNA expression correlation scatterplot between two replicate libraries from the same sample. (B) PCA analysis shows tight clusters of triplicate libraries while clusters (colored) representing four independent invasive ductal tumor samples are more distant due to global miRNA expression differences

Figure 2: Sequencing mRNA library performance. (A) Pair-wise scatter plot showing gene expression correlation between 6 multiplexed libraries. (B) PCA analysis of the same 4 samples described in Figure 1. As with global miRNA clustering, replicate libraries are tightly clustered with more cluster distance observed at the sample level

Figure 3. Gene Expression profiles driving sample level differences in the four independent invasive ductal tumor samples. (A) All genes with mean expression ≥ 200 counts (N = 804) driving hierarchical clustering. (B) Subset of 174 genes with greatest expression differences between the four samples. AmpliSeqRNA plugin normalized counts are used for the hierarchical clustering shown here.

Sample type

0 50 100 150 2000

50

100

Survival proportions: Survival of TMSB10 OS

OS (mo)

Perc

ent s

urvi

val

below median gene expressionabove median gene expression

P value 0.0280

n = 247

0 50 100 150 2000

50

100

Survival proportions: Survival of TMSB10 DFS

DFS (mo)

Perc

ent s

urvi

val

below median gene expressionabove median gene expression

P value 0.1237

n = 247

XBP1

GLUL

miRNABase Mean Log2 Fold

Change

hsa-mir-520f 347 3.96

hsa-mir-517b 219 -5.74

hsa-mir-1227 79.5 6.29

hsa-mir-3180-1 82 -5.32

hsa-mir-514b 50 -6.62

hsa-mir-4300 180 -4.73

hsa-mir-3916 141 5.10

chr11.trna11-LysTTT 767 -5.34

chr16.trna23-LysTTT 481.5 -5.98

chr6.trna112-PheGAA 83.5 -5.35

Figure 7: Expression profiles of mRNA target MTDH and miRNA regulator, miR-136-5p are inversely correlated in research samples suggesting this miRNA represses MTDH expression in breast tumors. This target identified by referencing differentially expressed miRNAs from LCM vs. in tact tissue measurements to miRNA:mRNA predicted pairs in the four independent invasive ductal tumor samples (Fig 1-3).

A B

A B

A B

Log2 normalized NGS counts