Androgen-dependent alternative mRNA isoform expression in prostate cancer cells

Background: Androgen steroid hormones are key drivers of prostate cancer. Previous work has shown that androgens can drive the expression of alternative mRNA isoforms as well as transcriptional changes in prostate cancer cells. Yet to what extent androgens control alternative mRNA isoforms and how these are expressed and differentially regulated in prostate tumours is unknown. Methods: Here we have used RNA-Seq data to globally identify alternative mRNA isoform expression under androgen control in prostate cancer cells, and profiled the expression of these mRNA isoforms in clinical tissue. Results: Our data indicate androgens primarily switch mRNA isoforms through alternative promoter selection. We detected 73 androgen regulated alternative transcription events, including utilisation of 56 androgen-dependent alternative promoters, 13 androgen-regulated alternative splicing events, and selection of 4 androgen-regulated alternative 3′ mRNA ends. 64 of these events are novel to this study, and 26 involve previously unannotated isoforms. We validated androgen dependent regulation of 17 alternative isoforms by quantitative PCR in an independent sample set. Some of the identified mRNA isoforms are in genes already implicated in prostate cancer (including LIG4, FDFT1 and RELAXIN), or in genes important in other cancers (e.g. NUP93 and MAT2A). Importantly, analysis of transcriptome data from 497 tumour samples in the TGCA prostate adenocarcinoma (PRAD) cohort identified 13 mRNA isoforms (including TPD52, TACC2 and NDUFV3) that are differentially regulated in localised prostate cancer relative to normal tissue, and 3 ( OSBPL1A, CLK3 and TSC22D3) which change significantly with Gleason grade and tumour stage. Conclusions: Our findings dramatically increase the number of known androgen regulated isoforms in prostate cancer, and indicate a highly complex response to androgens in prostate cancer cells that could be clinically important.


Introduction
A single human gene can potentially yield a diverse array of alternative mRNA isoforms, thereby expanding both the repertoire of gene products and subsequently the number of alternative proteins produced. mRNAs with different exon combinations are transcribed from most (up to 90%) human genes, and can generate variants that differ in regulatory untranslated regions, or encode proteins with different sub-cellular localisations and functions [1][2][3][4][5] . Altered splicing patterns have been suggested as a new hallmark of cancer cells [6][7][8] , and in prostate cancer there is emerging evidence that expression of specific mRNA isoforms derived from cancer-relevant genes may contribute to disease progression 9-11 . Androgen steroid hormones and the androgen receptor (AR) play a key role in the development and progression of prostate cancer, with alternative splicing enabling cancer cells to produce constitutively active ARs 11-13 . The AR belongs to the nuclear receptor superfamily of transcription factors, and is essential for prostate cancer cell survival, proliferation and invasion [14][15][16] . Classically, androgen binding promotes AR dimerization and its translocation to the nucleus, where it acts as either a transcriptional activator or a transcriptional repressor to dictate prostate specific gene expression patterns 17-23 . The major focus for prostate cancer therapeutics has been to reduce androgen levels through androgen deprivation therapy (ADT), either with inhibitors of androgen synthesis (for example, abiraterone) or with antagonists that prevent androgen binding to the AR (such as bicalutamide or enzalutamide) 24 . Although ADT is usually initially effective, most patients ultimately develop lethal castrate resistant disease for which there are limited treatment options 11,12 .
Androgens and other steroid hormones have also been associated with alternative splicing. Recent RNA-sequencing-based analysis of the androgen response of prostate cancer cells grown in vitro and within patients following ADT identified a set of 700 genes whose transcription is regulated by the AR in prostate cancer cells 25 . However, in addition to regulating transcriptional levels, steroid hormone receptors can control exon content of mRNA 10,26-29 . In prostate cancer androgens can modulate the expression of mRNA isoforms via pre-mRNA processing and promoter selection 9,10,18,30 . The AR can recruit the RNA binding proteins Sam68 and p68 as cofactors to influence alternative splicing of specific genes, and studies using minigenes driven from steroid responsive promoters indicate that the AR can affect both the transcriptional activity and alternative splicing of a subset of target genes 11,31,32 . Other steroid hormones also coordinate both transcription and splicing decisions 29 . The thyroid hormone receptor (TR) is known to play a role in coordinating the regulation of transcription and alternative splicing 27 , and the oestrogen receptor (ER) can both regulate alternative promoter selection and induce alternative splicing of specific gene sets that can influence breast cancer cell behaviour 28,33-35 .
In previous work we used exon level microarray analysis to identify 7 androgen dependent changes in mRNA isoform expression 10 .
However, to what extent androgen-regulated mRNA isoforms are expressed in clinical prostate cancer is unclear. To address this, here we have used RNA-Sequencing data to globally profile alternative isoform expression in prostate cancer cells exposed to androgens, and correlated the results with transcriptomic data from clinical tissue. Our findings increase the number of known AR regulated mRNA isoforms by 10 fold and imply that pre-mRNA processing is an important mechanism through which androgens regulate gene expression in prostate cancer.
RNA-Seq analysis RNA-seq transcript expression analysis of previously generated data 25 was performed according to the Tuxedo protocol 37 . All reads were first mapped to human transcriptome/genome (build hg19) with TopHat 38 /Bowtie 39 , followed by per-sample transcript assembly with Cufflinks 40 . The mapped data was processed with Cuffmerge, Cuffdiff and Cuffcompare, followed by extraction of significantly differentially expressed genes/isoforms; expression changes between cells grown with androgen and cells grown without androgens were assessed. Reference files for the human genome (UCSC build hg19) were downloaded from the Cufflinks pages: (UCSC-hg19 package from June 2012 was used.). The software versions used for the analysis were: TopHat v1.4.1, SAM tools Version: 0.1.18 (r982:295), bowtie version 0.12.8 (64-bit) and cufflinks v1.3.0 (linked against Boost version 104000). The Tuxedo protocol 37 was carried out as follows: For steps 1-5, no parameters (except for paths to input/ output files) were altered. In step 15, additional switches -s, -R, and -C were used when running cuffcompare. Steps 16-18 (extraction of significant results) were performed on the command line.
RNA extraction, RT-PCR and real-time PCR Cells were harvested and total RNA extracted using TRIzol (Invitrogen, 15596-026) according to manufacturer's instructions. RNA was treated with DNase 1 (Ambion, AM2222) and cDNA was generated by reverse transcription of 500ng of total RNA using the Superscript VILO cDNA synthesis kit (Invitrogen, 11754-050). Alternative events were analysed by either reverse transcriptase PCR or real-time PCR. Exon profiles were monitored and quantified using the Qiaxcel capillary electrophoresis system (Qiagen) and percentage inclusion was calculated as described previously 10 . Real time PCR was performed in triplicate on cDNA using SYBR® Green PCR Master Mix (Invitrogen, 4309155) and the QuantStudio 7 Flex Real-Time PCR System (Thermo Fisher Scientific). Samples were normalised using the average of three reference genes, GAPDH, β -tubulin and actin. Ct values for each sample were calculated using SDS 2.4 software (Applied Biosystems) and relative mRNA expression was calculated using the 2-ΔΔCt method. All primer sequences are listed in Supplementary Table 1. Raw Ct values are given in Dataset 1 41 .
Gene ontology analysis Gene ontology (GO) analysis of RNA-Seq data was carried out as described previously 42 . Enrichment of GO terms (with b500 annotations) was calculated using the goseq R package (version 1.18.0). Genes were considered significant at a p-value threshold of 0.05 after adjustment using the Benjamini-Hochberg false discovery rate.
Bioinformatic analysis of patient transcriptome data Available clinical and processed RNA-Seq data from The Cancer Genome Atlas (TCGA) prostate adenocarcinoma (PRAD) cohort, comprising 497 tumour samples from as many patients with different stages / Gleason grades and 52 matched samples taken from normal prostate tissue (were downloaded from the Broad Institute TCGA Genome Analysis Center (Firehose 16/01/28 run https://doi.org/10.7908/C11G0KM9 43 ). Transcriptome data from the TCGA PRAD cohort were analysed for alternative isoform expression, with transcript models relying on TCGA GAF2.1, corresponding to the University of California, Santa Cruz (UCSC) genome annotation from June 2011 (hg19 assembly). This annotation encompassed 42 of the 73 androgenregulated alternative mRNA isoform pairs identified. These were studied using two types of analysis: 1) differential transcript expression between tumour and normal prostate tissue and 2) correlation between isoform expression in tumour samples and Gleason score or tumour stage. Differential isoform and gene expression analysis was performed on estimated read counts using the limma software R package (version 3.7) following its RNA-Seq analysis workflow 44 . This workflow was also used for differential isoform ratio analysis, relying on logit-transformed ratio (see below). An FDR-adjusted p-value of 0.05 for the moderated t-statistics was used as threshold for significance of differential expression. Individual isoform expression was estimated in TPM (transcripts per million mapped reads). The expression ratio, henceforth called PSI (percent spliced-in), of each annotated androgen-regulated isoform pair in each TCGA sample was calculated as the ratio between the expression of isoform 1 and the total expression of isoforms 1 and 2 combined, i.e. the sum of their expressions. For each isoform pair, ΔPSI is the difference of median PSI between the tumour and the normal groups of samples.
Two-tailed Spearman's rank correlation tests were used to study the association between isoform expression and both Gleason score and tumour stage (these were used herein as numeric variables). An FDR-adjusted p-value of 0.05 was used as threshold for significance. Isoform expression differences between tumour and normal samples were considered equivalent to those detected in LNCaP cells under androgen stimulation when there was a statistically significant consistent change in the levels of the expected induced or repressed isoform (1 or 2), concomitant with no contradictory change in the PSI. Isoform "switches" were considered equivalent when there was a minimum (ΔPSI > 2.5%) and statistically significant consistent change in the PSI. Equivalent criteria were used to evaluate the equivalence between androgen-dependence and the associations with Gleason score and tumour stage.

Statistical analysis
Statistical analyses were conducted using the GraphPad Prism software (version 5.04/d). PCR quantification of mRNA isoforms was assessed using the unpaired student's t-test.

Results
Global identification of androgen-dependent mRNA isoform production in prostate cancer cells predicts a major role for alternative promoter utilisation We analysed previously published RNAseq data from LNCaP cells 25 to globally profile how frequently androgens drive production of alternative mRNA isoforms in prostate cancer cells. This analysis identified a group of 73 androgen regulated alternative mRNA isoforms, which could be validated by visualisation on the UCSC Genome Browser 45 (Table 1). 64 AR regulated mRNA isoforms were novel to this study. Experimental validation in an independent RNA sample set using RT-PCR confirmed 17/17 of these alternative events at the mRNA level (Supplementary Figure 1). 73% of genes (53/73) with identified alternative androgen regulated mRNA isoforms also changed their overall expression levels in response to androgens ( Table 2). Some of the androgen regulated alternative events are in genes are already implicated in in either prostate cancer or other cancer types (summarised in Table 3). However, Gene Ontology analysis of these 73 genes did not identify any significantly enriched biological processes.
The 73 identified mRNA isoforms were generated via androgenregulated utilisation of 56 alternative promoters, 4 alternative 3' ends and 13 alternative splicing events ( Figure 1A).  Table 2. Quantitative changes in gene expression in response to androgens for the 73 genes with AR regulated alternative mRNA isoforms.

ZNF226
Of the 56 androgen regulated alternative promoters that were identified, 23 alternative promoters were induced by androgens (including LIG4, Figure 1B), 26 promoters were repressed by androgens, and for 7 genes there was a switch in usage from one promoter to another ( Table 1). The alternative splicing events that were under androgen control included 12 alternative exons and one androgen-regulated intron retention ( Table 1). 10 of these are novel to this study, including exclusion of an alternative exon in ZNF678 ( Figure 1C). Of the alternative exons, six genes contained switches in previously unannotated protein-coding exons in response to androgen-exposure. We also identified four androgen regulated alternative mRNA 3' end isoform switches, including a switch in the 3' end of the mRNA transcript for the MAT2A gene ( Figure 1D).
Androgen regulated events control the production of alternative protein isoforms, non-coding RNAs and alternative 5' UTRs 48/73 (66%) of the androgen regulated alternative events detected in response to androgen stimulation are predicted to change the amino acid sequence of the resulting protein ( Table 1). Some of these are already known to have a well characterised role in prostate cancer progression, including an alternative promoter in the oncogene TPD52 that produces a protein isoform called PrLZ (Figure 2A) 46-49 . Others are not so well characterised. Using western blotting we could detect a novel shorter protein isoform corresponding to androgendriven selection of an alternative promoter in the TACC2 gene ( Figure 2B); and exclusion of a cassette exon in the NDUFV3 gene, which we show also produces a novel shorter protein isoform ( Figure 2C). We also detected a switch in the 3' end of the mRNA transcript for the MAT2A gene, which is predicted to produce a protein isoform with a shorter C-terminal domain ( Figure 1D); and induction of an alternative 3' isoform of CNNM2, which is predicted to be missing a conserved CBS domain (Table 1 and Supplementary Figure 1).
11 of the remaining identified androgen-regulated alternative events change the expression of mRNAs from coding to noncoding or untranslated (not predicted to produce a protein) ( Table 1). These included promoter switches for the RLN1 and RLN2 genes which encode peptide hormones that may be important in prostate cancer 5,50-55 . Androgens drive a promoter switch in both RLN1 and RLN2 to produce predicted non-coding or untranslated mRNA isoforms, reducing expression of protein-coding RLN1 and RLN2 mRNA isoforms. To   Androgens induce an alternative promoter in the oncogene TPD52 that produces an isoform called PrLZ. Visualisation of our LNCaP cell RNA-seq reads for the TPD52 gene on the UCSC genome browser identified a switch from promoter 1 to alternative promoter 2 in cells grown in the presence of androgens. Promoter 2 is known to produce an alternative protein isoform of TPD52 known as PrLZ (left panel). Quantitative PCR using primers specific to each promoter indicate an induction of the PrLZ isoform in response to androgens (middle panel). PrLZ has an alternative N-terminal amino acid sequence which results in an alternative protein isoform and disrupts a known Pfam domain (right panel). (B) Androgens induce an alternative promoter in the TACC2 gene that produces a novel alternative protein isoform. Visualisation of our LNCaP cell RNA-seq reads for the TACC2 gene on the UCSC genome browser identified a switch from promoter 1 to alternative promoter 2 in cells grown in the presence of androgens. Promoter 2 is predicted to produce an alternative shorter protein isoform of TACC2 (isoform 2) (left panel). Quantitative PCR using primers specific to each promoter indicate a switch from isoform 1 to isoform 2 in response to androgens (middle panel). Detection of TACC2 protein in LNCaP by western blotting (cells were grown with or without androgens for 24 or 48 hours). Tubulin was used as a loading control. Exposure to androgens for 48 hours induces expression of the alternative TACC2 protein isoform (right panel). (C) Androgens drive alternative splicing of the NDUFV3 gene. Visualisation of our LNCaP cell RNA-seq reads for the NDUFV3 gene on the UCSC genome browser identified a switch to exclusion of a cassette exon in the presence of androgens (left panel). Quantitative PCR using primers in flanking exons confirmed less inclusion of the alternative exon in LNCaP cells exposed to androgens (middle panel). Exclusion of the alternative cassette exon is predicted to produce an alternative protein isoform. Detection of NDUFV3 protein in LNCaP cells using western blotting (right panel). (D) Androgens suppress an alternative promoter in the RLN2 gene, which produces a shorter noncoding mRNA isoform. Visualisation of our LNCaP cell RNA-seq reads for the RLN2 gene on the UCSC genome browser identified a switch from promoter 1 to alternative promoter 2 in cells grown in the presence of androgens. Promoter 2 is predicted to produce an untranslated non-coding mRNA isoform (left panel). Quantitative PCR using primers specific to each promoter indicated a significant switch in promoter usage in response to androgens (middle panel). Detection of RLN2 protein in LNCaP by western blotting (cells were grown with or without androgens for 48 hours). Actin was used as a loading control. As seen previously 55 , androgens suppress RLN2 protein levels.
test whether prostate cancer cells turn off gene expression by switching between utilisation of promoters that generate coding and noncoding mRNAs, we analysed RLN2 protein levels. Consistent with our hypothesis and a previous study 55 , RLN2 protein production was negatively regulated by androgens in parallel to the switch to the non-coding mRNA isoform ( Figure 2D).
14 of the identified androgen-dependent mRNA isoforms lead to/result in coding mRNAs with altered 5' untranslated regions (5' UTR) with no impact on the coding sequence. These include a promoter switch in the LIG4 gene ( Figure 1B).
Differential expression of androgen-dependent mRNA isoforms in prostate adenocarcinoma versus normal tissue To investigate potential links between androgen-dependent mRNA isoforms and tumourigenesis, we analysed the expression of 41 androgen-regulated mRNA isoform pairs in clinical prostate adenocarcinoma and normal prostate tissues. This analysis utilised transcriptomic data from 497 tumour samples and 52 normal samples in the PRAD TCGA cohort 104 . The remaining isoform pairs identified within our dataset have not been previously annotated by UCSC, therefore it was not possible to include them in our comparison. A description of the cohort used is summarised in Table 4. 33 of the 42 mRNA isoform pairs exhibited significant differences in the expression of at least one of the isoforms, or in the isoform expression ratio between tumour and normal tissues ( Table 5). 13 of those tumour-specific alterations mimicked the effect of androgen stimulation in LNCaP cells: the changes were in form of alternative promoters for TACC2, TPD52, NUP93, PIK3R1, RDH13, ZFAND6, CDIP1, YIF1B, LIMK2, and FDFT1; an alternative 3´ end in CNNM2; and alternative exons in     Figure 2). Two of the alternative promoters (ZFAND6 and CDIP1) are predicted to introduce a change in the 5'UTR, whereas all the others are predicted to alter the resulting protein isoform. A number of mRNA isoforms that were androgen responsive in LNCaP cells showed tumour specific alterations opposite to the effect of androgen stimulation. These were LIG4, MAPRE2, OSBPL1A, SEPT5, NR4A1, and RCAN1 (all predicted to alter the resulting protein isoform except LIG4). For the remaining 14 mRNA isoform pairs, the data was inconclusive according to the consistency conditions listed in the methods section (Table 5).
Changes in androgen-dependent mRNA isoform expression during tumour progression We next investigated whether the identified androgen-dependent mRNA isoforms are differentially expressed during prostate cancer progression by correlating the expression levels of each isoform with Gleason scores and prostate tumour grades within the PRAD TCGA cohort (Figure 4 & Figure 5, Table 6 & Table 7 and

Discussion
The main function of the androgen receptor (AR) is as a DNA binding transcription factor that regulates gene expression.
Here we show the AR can couple hormone induced gene transcription to alternative mRNA isoform expression in prostate cancer. In response to androgens, the AR can induce the use of alternative promoters, induce the expression of alternatively spliced mRNA isoforms, regulate the expression of non-coding mRNA transcripts, and promote the transcription of mRNA isoforms encoding different protein isoforms. Importantly, we also find that some of these alternative mRNA isoforms are differentially regulated in prostate cancer versus normal tissue and also significantly change expression during tumour progression. Our data suggest that most androgen regulated alternative mRNA isoforms are generated through alternative promoter selection rather than through internal alternative exon splicing mechanisms. This suggests expression of alternative isoforms of specific genes can be a consequence of RNA polymerase being recruited to different promoters in response to androgen stimulation. Alternative promoter usage has been observed for many genes and is believed to play a significant role in the control of gene expression 4,105,106 . Alternative promoter use can also generate mRNA isoforms with distinct functional activities from the same gene, sometimes having opposing functions 11 .
Androgen exposure further drives a smaller number of alternative splicing events suggesting that the AR could contribute to altered patterns of splicing in prostate cancer cells. Tumour progression is believed to be associated with a coordinated change in splicing patterns which is regulated by several factors including signalling molecules 7 . We also identified 4 AR regulated alternative mRNA 3' end isoform switches. This is the first time that regulation of 3' mRNA end processing has been shown to be controlled by androgens. The selection of alternative 3' ends can produce mRNA isoforms differing in the length of their 3' UTRs (which can lead to the inclusion or exclusion of regulatory elements and influence gene expression), or in their C-terminal coding region (which can contribute to proteome diversity) 107-114 . Defective 3' mRNA processing of numerous genes has been linked to an oncogenic phenotype 115-119 , and the 3' mRNA end profiles of samples from multiple cancer types significantly differ from those of healthy tissue samples 115,119-121 .
Based on the findings presented in this study, we propose that activated AR has the ability to coordinate both transcriptional activity and mRNA isoform decisions through the recruitment of co-regulators to specific promoters. The genomic action of the AR is influenced by a large number of collaborating transcription factors 122-124 . Specifically, Sam68 and p68 have been shown to modulate AR dependent alternative splicing of specific genes and are significantly overexpressed in prostate cancer 31,32 . In future work it will be important to define the role of specific AR co-regulators in AR mediated isoform selection.
Some of the androgen dependent mRNA isoforms identified here are predicted to yield protein isoforms that may be clinically important, or to switch off protein production via generation of noncoding mRNA isoforms. Although the functional significance of the alternative mRNA isoforms identified in this study is yet largely unexplored, as is their role in the cellular response to androgens, the presented results emphasize the importance of analysing gene regulation and function at the mRNA isoform level.      Prostate cancer is a common cancer in men that is driven in part through deregulated androgen signalling. The importance of androgen inhibitors in prostate cancer therapy and the clinical challenges posed by the development of androgen-resistant disease both justify the detailed description of the effects of androgen treatment on gene transcription and alternative splicing in prostate cancer cells. In this sense, the analyses reported by Munkley and colleagues represent valuable additions to the literature. However, further explanation of the results presented would increase the reader's ability to understand these results and their significance, and to identify which results should be prioritised for further research. I have therefore provided some specific suggestions to increase the accessibility of the data as they are currently presented.

Specific comments
The genes shown in Tables 1, 2, 3 and 5 are not shown in alphabetical order. It is unclear how these genes are ranked and why they are shown in the orders displayed. It would be helpful for any groupings of genes to be more clearly displayed in these tables where this is relevant. It would be helpful to more clearly indicate which findings are novel and which are supported by the literature in Tables and/or Figures. In Table 1, a number of genes are shown in bold, but this is not explained. In Table 1, it would be helpful to annotate the isoform ID's shown (columns towards the right side of Table). What does "comparable" mean here? It is challenging to show data for a large number of genes, most of which the authors will not be familiar with. However, in Figure 2, incorrect information is shown for the TPD52 gene (panel A). The PrLZ isoform is actually longer than the TPD52 isoform (through an extended N-terminal sequence specific to PrLZ), yet the sizes of these isoforms indicated in the diagram at the right have been switched (TPD52 is incorrectly shown to be the longer isoform). The authors should check whether this is an isolated error or whether other data for the TPD52 and PrLZ isoforms have been switched (for example in Figure 3). It would be helpful for Table 4 to include percentages as well as sample numbers so that readers can compare the composition of the TCGA PRAD cohort with other published cohorts. Analyses compared differential isoform expression in prostate cancer and normal tissue. The cohort included 497 prostate cancer patients, for which 52 had matched normal tissue (Table 5, Figure 3). I've assumed that these analyses compared transcript levels in the 497 prostate cancer cases with those in the 52 normal tissue cases. However, given that the 52 normal tissue cases had matched tumour samples available, were analyses conducted to compare the 52 matched 7.
8. 9. 10. 11. had matched tumour samples available, were analyses conducted to compare the 52 matched cases? These analyses could be argued to be more robust through comparing matched samples, albeit in a smaller cohort. Table 5 should indicate the numbers of tumour and normal tissue samples compared. Some data in Tables 5, 6, and 6 are shown in bold, but this is not explained. I could not open Dataset 2. Could this be made available as a pdf file? All violin plots (Figures 3-5, also supplementary data) should specify the sample numbers compared, either below the X axis or in the figure legend if the same sample numbers apply to every plot shown.

Is the work clearly and accurately presented and does it cite the current literature? Yes
Is the study design appropriate and is the work technically sound? Yes

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility? Partly

Are the conclusions drawn adequately supported by the results? Yes
No competing interests were disclosed.

Competing Interests:
I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This paper by Munkley and colleagues identifies in a comprehensive manner novel alternative mRNA isoforms regulated by androgens. Interestingly most isoforms result from a choice between alternative promoters, suggesting that regulation takes place mostly at the transcriptional level, but they identified also a few alternative cassette exons and 3' ends. They show experimental validation for 17 isoforms. Beside increasing the number of identified genes in the context of androgen-treated prostate cancer LNCaP cells, the authors analysed the expression of those new isoforms in a large cohort of prostate tumours. They found the expression of some of the mRNA isoforms is positively correlated in the androgen-treated cell and in cancer versus normal samples, and find further correlation with the tumour I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
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