Open Access

Comprehensive serial analysis of gene expression of the cervical transcriptome

  • Ashleen Shadeo1Email author,
  • Raj Chari1,
  • Greg Vatcher1,
  • Jennifer Campbell1,
  • Kim M Lonergan1,
  • Jasenka Matisic2,
  • Dirk van Niekerk2,
  • Thomas Ehlen3, 4,
  • Dianne Miller3, 4,
  • Michele Follen5,
  • Wan L Lam1 and
  • Calum MacAulay6
BMC Genomics20078:142

DOI: 10.1186/1471-2164-8-142

Received: 11 December 2006

Accepted: 01 June 2007

Published: 01 June 2007

Abstract

Background

More than half of the approximately 500,000 women diagnosed with cervical cancer worldwide each year will die from this disease. Investigation of genes expressed in precancer lesions compared to those expressed in normal cervical epithelium will yield insight into the early stages of disease. As such, establishing a baseline from which to compare to, is critical in elucidating the abnormal biology of disease. In this study we examine the normal cervical tissue transcriptome and investigate the similarities and differences in relation to CIN III by Long-SAGE (L-SAGE).

Results

We have sequenced 691,390 tags from four L-SAGE libraries increasing the existing gene expression data on cervical tissue by 20 fold. One-hundred and eighteen unique tags were highly expressed in normal cervical tissue and 107 of them mapped to unique genes, most belong to the ribosomal, calcium-binding and keratinizing gene families. We assessed these genes for aberrant expression in CIN III and five genes showed altered expression. In addition, we have identified twelve unique HPV 16 SAGE tags in the CIN III libraries absent in the normal libraries.

Conclusion

Establishing a baseline of gene expression in normal cervical tissue is key for identifying changes in cancer. We demonstrate the utility of this baseline data by identifying genes with aberrant expression in CIN III when compared to normal tissue.

Background

Approximately 500,000 women are diagnosed with cervical cancer worldwide each year and more than half of them will die from this disease [1]. The highest incidence rates are observed in developing countries where it is the second most prevalent cancer in women and remains a leading cause of cancer related death [1]. Widely implemented screening programs have been responsible for the much lower incidence and mortality rates seen in the developed world. Present day screening methods primarily identify precancer lesions termed cervical intraepithelial neoplasia (CIN). CIN lesions are classified into three subgroups, CIN I, CIN II and CIN III, corresponding to mild, moderate and severe dysplasia/carcinoma in situ (CIS), respectively. CIN III lesions have a high likelihood of progression to invasive disease if left untreated [2]. Human Papillomavirus (HPV) has long been established as a necessary but not sufficient cause for cervical carcinoma development. HPV is detected in 99% of invasive disease, 94% of CIN lesions and 46% of normal cervical epithelium [2]. The high risk strains HPV 16 and HPV 18 are most prevalent in invasive disease.

A comprehensive characterization of gene expression of the normal cervical tissue is critical to establish a baseline for comparison against transcriptomes of precancer and cancer. A recent report described the global expression of genes in cervical epithelium using a serial analysis of gene expression (SAGE) based method, enumerating 30,418 sequence tags generated from one normal uterine ectocervical tissue [3]. Another study compared cDNA microarray profiles of cervical tissue to exfoliated cervical cells used in cytology-based cancer screening [4].

In this study, we increased the depth of our understanding of the normal cervical transcriptome and identified gene expression changes in CINIII. We achieved this (i) by using an unbiased Long SAGE (L-SAGE) approach to improve the accuracy of tag-to-gene mapping [57], and (ii) by examining 691,390 L-SAGE tags thus increasing publicly available cervical SAGE data by greater than 20 fold.

Results

In this study, we sequenced 691,390 SAGE tags from four libraries. Cervical L-SAGE libraries N1, N2, C1, and C2 were sequenced to 165,624, 181,224, 173,534, and 171,008 tags, respectively. Duplicate ditags were eliminated from analysis resulting in 136,276, 139,656, 154,828 and 136,386 useful tags respectively and a total of 24, 058 unique tags (Figure 1A). 15,438 of the unique tags mapped to annotated UniGene identifiers. The raw data of the sequence tags have been made publicly available (Gene Expression Omnibus, series accession number GSE6252). We characterized the transcriptome of normal cervical tissue and evaluated the highly expressed genes in terms of tissue specificity, concordant expression among the normal libraries and their altered expression in CIN III lesions (Figure 1B).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-142/MediaObjects/12864_2006_Article_855_Fig1_HTML.jpg
Figure 1

Flow diagram of SAGE analysis and tag-to-gene mapping. A. Sequence tags yielded from the four SAGE libraries were catagorized. Useful tags indicate all sequenced tags less duplicate ditags. B. The abundance and classification of unique tags in the SAGE libraries of normal cervix tissue (N1, N2) are summarized.

Genes Highly Expressed in Normal Cervical Epithelium

118 unique tags were found to be highly expressed in the normal cervical epithelium (at >500 tpm in both normal libraries). 103 of these tags mapped to UniGene clusters and represent 100 unique genes and hypothetical proteins (Figure 1). Manual examination of tags not mapped by SAGE Genie yielded three additional tags. This results in a total of 107 unique tag-to-gene mappings and 103 unique genes. The abundance of the 118 tags and the genes they represent are summarized in Table 1.
Table 1

Tags expressed in normal cervical libraries at ≥500 tags per million.

Gene Symbol

N1 tpm

N2 tpm

C1 tpm

C2 tpm

SAGE Tag

unknown

2510

3623

2655

873

TGATTTCACTTCCACTC

unknown

2517

3430

3307

1672

CTAAGACTTCACCAGTC

unknown

594

559

497

594

GTAGGGGTAAAAGGAGG

unknown

2033

1683

2280

1239

CACCTAATTGGAAGCGC

unknown

807

852

1298

0

CAAGCATCCCCGTTCCA

unknown

822

680

814

631

AGGTGGCAAGAAATGGG

unknown

3757

2714

4134

2757

ACTTTTTCAAAAAAAAA

unknown

616

687

782

374

ACTAACACCCTTAATTC

unknown

1519

1525

2222

2126

AAAAAAAAAAAAAAAAA

unknown

565

780

588

308

TTTAACGGCCGCGGTAC

unknown

6289

6602

6510

4326

TTCATACACCTATCCCC

ACTB

2099

1031

1292

1459

GCTTTATTTGTTTTTTT

ACTG1

1424

1955

1195

1598

CTAGCCTCACGAAACTG

ANXA1

3713

6480

3701

10162

AGAAAGATGTCTATGTA

ANXA2

1644

1754

1298

887

CTTCCAGCTAACAGGTC

AQP3

609

573

930

1136

TTTGCTTTTGTTTTGTT

ATP5G3

543

773

743

851

GGAATGTACGTTATTTC

B2M

8718

2821

9443

5712

GTTGTGGTTAATCTGGT

BZRP

550

960

794

675

GAATTTTATAAGCTGAA

CCNB1IP1

580

924

988

565

CCACTGCACTCCAGCCT

CD24

851

559

775

697

GGAACAAACAGATCGAA

CD74

2348

573

1789

1444

GTTCACATTAGAATAAA

CEACAM7

793

866

891

594

AATCACAAATAAAAGCC

CFL1

1937

1031

1744

1679

GAAGCAGGACCAGTAAG

COX4I1

646

523

969

616

CCTATTTACTGGAAACC

CSTB

712

3881

1227

2676

ATGAGCTGACCTATTTC

CTSD

2502

931

2894

1987

GAAATACAGTTGTTGGC

EEF1A1

2245

1353

1737

1496

TGTGTTGAGAGCTTCTC

EEF1B2

961

1210

1072

1298

GCATTTAAATAAAAGAT

EEF1G

726

501

807

418

TGGGCAAAGCCTTCAAT

FLJ20701

550

501

685

264

ATTTGAGAAGCCTTCGC

FTH1

2311

1275

2325

5176

TTGGGGTTTCCTTTACC

GAPD

1666

2363

2312

2816

TACCATCAATAAAGTAC

GJA1

741

1310

504

513

TGTTCTGGAGAGTGTTC

GLUL

1658

1275

1905

2845

TACAGTATGTTCAAAGT

IGHG1

14118

788

349

4715

GAAATAAAGCACCCACC

IGHG1

18286

773

601

6548

GAAATAAAGCACCCAGC

ITM2B

1203

1031

1369

865

TAAGTAGCAAACAGGGC

K-ALPHA-1

1181

795

1783

1239

TGTACCTGTAATATTTT

KRT13

1380

8206

1815

2046

AAAGCGGGGCTGGAGAA

KRT15

1152

3494

2713

2427

TAATAAAGAATTACTTT

KRT5

2216

1539

1892

1371

GCCCCTGCTGACACGAG

KRT6A

1181

2657

975

1166

AAAGCACAAGTGACTAG

LAMR1

2987

2370

3268

2911

GAAAAATGGTTGATGGA

LGALS7

682

2220

446

425

TAAACCTGCTGTGCGGG

LOC44051

719

702

588

719

GGGTTGGCTTGAAACCA

LY6D

1424

2248

1796

3072

GAGATAAATGATTTAAA

MGC71999

998

1353

924

565

TCACAAGCAAATGTGTC

MYL6

1115

559

995

1063

GTGCTGAATGGCTGAGG

NET-5

1783

780

1298

997

CACAAACGGTAGTTTTG

PERP

1306

2828

1828

2236

CCACAGGAGAATTCGGG

PLCB4

866

752

1072

733

AAAACATTCTCCTCCGC

PPIA

1504

1697

1951

1452

CCTAGCTGGATTGCAGA

PTMA

1049

1017

1518

697

TTCATTATAATCTCAAA

RPL10

2223

1797

1944

1283

AGGGCTTCCAATGTGCT

RPL10A

998

652

1414

821

GGCAAGCCCCAGCGCCT

RPL11

1130

773

1124

829

CGCTGGTTCCAGCAGAA

RPL12

932

580

865

726

ACATCATCGATGACATC

RPL13A

2818

1998

2855

2383

AGGCTACGGAAACAGGC

RPL13A

1490

716

1434

1195

CTCCTCACCTGTATTTT

RPL21

2091

1353

1899

1554

GCATAATAGGTGTTAAA

RPL23

1196

1031

1072

1114

ATTCTCCAGTATATTTG

RPL27A

1923

1310

1989

1899

GAGGGAGTTTCATTAAA

RPL28

1996

1504

1983

1833

GCAGCCATCCGCAGGGC

RPL29

1049

773

1104

814

GGGCTGGGGTCCTCCTG

RPL3

917

702

840

983

GGACCACTGAAGAAAGA

RPL30

1541

1017

1259

961

CCAGAACAGACTGGTGA

RPL31

609

573

568

491

AAGGAGATGGGAACTCC

RPL32

1512

1024

1550

1371

TGCACGTTTTCTGTTTA

RPL35

638

551

665

572

CGCCGCCGGCTCAACAA

RPL36

1570

1275

1628

1173

AGGAAAGCTGCTGCCAA

RPL37

5063

3272

6362

6064

CAATAAATGTTCTGGTT

RPL37A

1350

938

1259

953

AAGACAGTGGCTGGCGG

RPL4

521

537

465

359

CGCCGGAACACCATTCT

RPL41

2649

1812

2609

1906

TTGGTCCTCTGCCCTGG

RPL7

1702

1160

1427

1180

ATTATTTTTCTAAGCTG

RPLP0

815

1239

846

601

CTCAACATCTCCCCCTT

RPLP1

3574

2735

3507

2398

TTCAATAAAAAGCTGAA

RPLP2

2422

1461

2196

2376

GGATTTGGCCTTTTTGA

RPS11

1365

802

917

770

TCTGTACACCTGTCCCC

RPS12

690

695

601

396

GCCGAGGAAGGCATTGC

RPS14

1159

859

1240

843

TAAAAAAAAAAAAAAAA

RPS18

1071

1053

1085

858

TGGTGTTGAGGAAAGCA

RPS19

2598

1604

2357

2618

CTGGGTTAATAAATTGC

RPS20

903

695

1020

667

GCTTTTAAGGATACCGG

RPS23

961

637

833

704

CTGTTGGTGATATTCCT

RPS25

1042

988

924

660

AATAGGTCCAACCAGCT

RPS26

2576

1002

1938

873

TAAGGAGCTGAGTTCTT

RPS27A

815

623

988

887

AACTAAAAAAAAAAAAA

RPS28

998

902

1053

1034

GACGACACGAGCCGATC

RPS29

2245

1940

2325

2317

ATAATTCTTTGTATATA

RPS3A

1218

823

1427

1232

GTGAAGGCAGTAGTTCT

RPS4X

1541

952

1615

924

TCAGATCTTTGTACGTA

RPS8

4021

3587

4282

3996

TAATAAAGGTGTTTATT

RPS9

587

530

407

521

CCAGTGGCCCGGAGCTG

S100A10

514

501

543

506

AGCAGATCAGGACACTT

S100A2

2950

723

2235

3505

GATCTCTTGGGCCCAGG

S100A7

2899

752

388

5990

GAGCAGCGCCCTGTTCC

S100A8

690

1031

827

1466

GCTTTTTTTGTGGGCTG

S100A8

11880

25205

8855

24629

TACCTGCAGAATAATAA

S100A9

13561

17078

10089

18660

GTGGCCACGGCCACAGC

SERPINB3

1137

1454

704

917

CCTTTCTCTCTTTCTCT

SFN

1255

1976

1505

1569

TTTCCTCTCAATAAAGT

SMAD2

2935

2341

3378

1987

CCCATCGTCCTAGAATT

SPINK5

712

4189

0

1305

TCCACCAAGTCTGAGCC

SPRR3

1600

11757

3888

5968

TTTCCTGCTCTGCCCTC

SPRR3

1636

13068

4121

8329

TTTCCTGCTCTTCCCTC

STX3A

646

1905

1318

1312

TAAAATGTTTATGATAA

SUI1

1446

1239

1259

2009

CAATAAACTGAAAAGAG

TAGLN2

660

616

769

543

GTCTGGGGCTTGAGGAA

TMSB4X

2245

616

1175

917

TTGGTGAAGGAAGAAGT

TPI1

947

1382

1589

1584

TGAGGGAATAAACCTGG

TPT1

4726

3659

4915

4568

TAGGTTGTCTAAAAATA

TXNL5

660

838

258

924

TTAGCAATAAATGATGT

UQCRH

646

508

930

726

GGTTTGGCTTAGGCTGG

VAMP8

521

795

459

491

TGGCTGGGAAACTGTTG

VPS13B

763

594

911

0

CACTACTCACCAGACGC

YWHAZ

587

702

517

814

TAAGTGGAATAAAAGTT

To determine cervical tissue specific expression, we first investigated the expression of the 107 genes using expression data available at the National Center for Biotechnology Information (NCBI) Unigene database and the National Cancer Institute (NCI) Cancer Genome Anatomy Project (CGAP) SAGE Anatomical Viewer. Based on CGAP information, only four of the 107 genes were unique to cervical tissue: carcinoembryonic antigen-related cell adhesion molecule 7 (CEACAM7), keratin 6A (KRT6A), small proline-rich protein 3 (SPRR3) and S100 calcium binding protein A7 (S100A7). These genes were further investigated for expression by RT-PCR in 20 different tissue types and three normal cervical specimens (Figure 2). CEACAM7 was found to be expressed in colon, larynx, pancreas and two of the three normal cervical specimens. KRT6A expression was detected in placenta, thymus, tongue, prostate, larynx, colon, skin and in all three of the normal cervical specimens. SPRR3 was found strongly expressed in placenta, thymus, colon, tongue, larynx and all three of the normal cervical cases. S100A7 showed expression in placenta, thymus, and tongue and in all three of the normal cervical specimens. All four genes were prominently expressed in the cervical epithelium but this combination of genes was not expressed in the tissues examined (Figure 2).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-142/MediaObjects/12864_2006_Article_855_Fig2_HTML.jpg
Figure 2

Validation of tissue specificity of gene expression. Reverse transcriptase PCR of four genes in 20 tissue types and three normal cervical specimens. Heart (Ht), breast (Br), placenta (Pl), lung (Lg), liver (Lv), skeletal muscle (Sk), kidney (Kd), pancreas (Pn), spleen (Sp), thymus (Ty), prostate (Pr), testis (Ts), ovary (Ov), small intestine (Sm), colon (Co), peripheral leukocytes (Lk), tongue (Tg) larynx (Lx), stomach (St), skin (Sn). Ca, Cb and Cc are three individual normal cervical tissue specimens.

Disrupted Gene Expression in CIN III

All tags were assessed for altered expression in CIN III. Four hundred and seventy-six tag show greater than two fold increase in CIN III and are expressed at greater than 15 tpm (see Additional file 1) while 315 tags were decreased in CIN III (see Additional file 2).

We determined if the expression of the 107 unique tags, that were highly expressed in normal cervical libraries (> 500 TPM), were disrupted in CIN III. Comparison of expression levels in N1, N2 to the CIN III libraries using the Z-test revealed five differentially expressed genes (Table 2). Annexin 2 (ANXA2), galectin 7 (LGALS7) and connexin 43 (GJA1) exhibited decreased expression in CIN III (Z < -1.96) while aquaporin 3 (AQP3) and ribosomal-like protein 37 (RPL37) increased in expression (Z > 1.96). Real-time PCR was performed on a panel of 6 new cervical specimens, three each of normal and CIN III for all five of these genes (Figure 3). Expression results were normalized to housekeeping gene ACTB and 18S (Figure 3A and 3B, respectively). Decrease in expression of ANXA2, LGALS7 and GJA1 in CIN III was confirmed while increase in expression of AQP3 and RPL37 were not.
Table 2

Highly expressed genes with altered expression in CIN III.

     

Z_Scorea

 

Tag

N1 tpm

N2 tpm

C1 tpm

C2 tpm

N1 vs C2

N1 vs C1

N2 vs C2

N2 vs C1

Gene Symbol

TTTGCTTTTGTTTTGTT

    

-4.7

-3.1

-5.1

-3.5

AQP3

CAATAAATGTTCTGGTT

5063

3272

6362

6064

-3.5

-4.6

-10.8

-12

RPL37

TGTTCTGGAGAGTGTTC

741

1310

504

513

2.4

2.6

6.9

7.3

GJA1

TAAACCTGCTGTGCGGG

682

2220

446

425

2.9

2.7

12.9

13.4

LGALS7

CTTCCAGCTAACAGGTC

1644

1754

1298

887

5.6

2.4

6.3

3.2

ANXA2

a Z > 1.96; reduced expression in CIN III, Z < -1.96; increased expression in CIN III.

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-142/MediaObjects/12864_2006_Article_855_Fig3_HTML.jpg
Figure 3

Summary of test panel quantitative PCR results of genes with altered expression in CIN III L-SAGE libraries. A panel of three new CIN III cases (CIN III A, CIN III B, CIN III C) were investigated for expression and compared to three new normal specimens. Gene expression was normalized to ACTB and 18S (Figure 3A and 3B, respectively). Zero on the Y-axis denotes mean expression levels of the respective genes in normal cervical tissue. All five genes investigated showed decreased expression.

Viral (HPV 16) tags in L-SAGE libraries

HPV transcripts were also detected by L-SAGE. Tags from all four libraries were mapped against the genomes of HPV 16 and HPV 18. While no tags mapped to HPV 18, twelve tags from the CIN III libraries mapped to the more prevalent HPV 16 genome (Table 3). The highest transcript counts of known genes belonged to E5 at 1,180 and 290 tpm and E2 at 240 and 20 tpm, in libraries C2 and C1, respectively. Compared by BLAST [8] against the RefSeq Genome collection, none of the twelve tags matched 100% to the human genome. All twelve tags were also mapped against human transcript sets (mitochondrial genome, RefSeq, UCSC gene set, Unigene, Ensembl, UCSC mRNA, UCSC EST, SAGEmap and SAGEgenie SAGE tag sets). No tags matched to any of the described transcript sets with the exception of CATGCACGCTTTTTAATTACA and CATGTGTATGTATTAAAAATA which mapped to human EST BF909200. The full length EST sequence is 97% identical with the HPV 16 E5 gene and was likely amplified from HPV sequences in the originating uterine tumour lesion.
Table 3

Tags mapping to HPV16 genome.

Tag

Strand

Gene

N1 tpm

N2 tpm

C1 tpm

C2 tpm

CATGCACGCTTTTTAATTACA

+

E5

0

0

290

1,180

CATGCAACATAAATAAACTTA

+

-

0

0

6

770

CATGGCATTGGACAGGACATA

+

E2

0

0

6

240

CATGTGTATGTATTAAAAATA

-

E5

0

0

6

155

CATGACACAATAGTTACACAA

+

-

0

0

6

125

CATGGGGAGGAATATGATTTA

+

L1/L2

0

0

0

30

CATGTAGACGACACTGCAGTA

-

E2

0

0

0

20

CATGGTAGATTATGGTTTCTG

-

E7

0

0

6

7

CATGTCGTAGGTACTCCTTAA

-

L1/L2

0

0

0

7

CATGGGGATCCTTTGCCCCAG

-

L1/L2

0

0

0

7

CATGATAATATATGTTTGTGC

-

L1/L2

0

0

0

7

CATGCGCCTAGAATGTGCTAT

+

E2

0

0

0

0

Discussion

This study represents the most comprehensive gene expression analysis of cervical tissue reported to date. In total, 691,390 L-SAGE tags were sequenced (Figure 1A). The length of the L-SAGE tags (21 bp as compared to 14 bp in conventional SAGE) greatly reduces tag-to-gene mapping ambiguity [6]. 107 of the 118 (88%) highly expressed tags (i.e. >500 tpm) were mapped to known genes or hypothetical proteins encompassing 103 unique genes (Figure 1B).

Assessing Highly Expressed Tags by Functional Group

Of the 107 highly expressed tags (>500 tpm), 47 were expressed at extremely high levels (>103 tpm) including genes frequently used as controls in expression analysis, GAPDH and ACTB. High expression of 20 genes in normal cervical tissue was reported in a previous study [3]. Fifteen of these genes are encompassed by our list of 107 high expressers. The most highly expressed tags expressed at >104 tpm (GTGGCCACGGCCACAGC and TACCTGCAGAATAATAA) mapped to the genes S100A9 and S100A8, respectively. Both genes belong to the calcium binding protein family. These findings are in agreement with a previous report of high S100A8 and S100A9 levels in cervical tissue [3]. Although the function of these genes is not well understood, genes within this family have been proposed to participate in a variety of cellular process including cell cycle, wound healing and cell differentiation [9].

Assigning the 103 highly expressed genes to one of eleven broad functional groups allowed for an assessment of those cellular processes represented by the most abundant transcripts. These cellular processes include calcium binding proteins, cell cycle or cell death, cytoskeleton, immune functioning, keratinization, membrane proteins, mitochondrial, protein processing, translation (ribosomal proteins), translation (non ribosomal proteins) with a small fraction of tags mapping to other functional groups or to genes with no known function (Figure 4A). The 41 ribosomal genes account for the greatest proportion of highly expressed genes at 28% and 31% (normal and CIN III, respectively). In contrast, only five calcium binding genes account for the second largest functional subgroup of highly expressed tags, 18% and 19% (normal and CIN III, respectively).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-142/MediaObjects/12864_2006_Article_855_Fig4_HTML.jpg
Figure 4

Functional groupings of tags highly expressed (>500 tpm) in normal libraries. Categories are as described. The Other group consists of tags which map to known genes but are not encompassed by any of the ten categories. The Unknown function group consists of tags mapping to no known genes. A) Tag counts in the normal libraries are categorized by functional group. B) Tags found in A were quantified in both CIN III libraries and categorized according to the same functional grouping scheme. In both groups Ribosomal genes accounted for the greatest number of tags while only the keratins changed in expression or were decreased in the CIN III libraries.

The relative expression levels of the functional groups do not change greatly between the normal and CIN III libraries however the keratin and immune related functional groups show slight decrease from 12% and 17% in CIN III to 9% and 14% in normal tissue (keratin and immune groups, respectively).

All tags expressed at or greater than 15 tpm in Normal and CIN III libraries (2,814 and 3,279 respectively) were also evaluated according functional group using Onto-Express (see Additional File 3) [10]. The most represented groups included DNA dependent transcription regulators and transcription in both the Normal and CIN III libraries.

Cervical Tissue Gene Signature

Four of the 103 unique genes we found to be abundantly expressed in normal cervical tissue were documented to have limited or no expression in other tissues according to the web resources NCBI UniGene [11] and NCI CGAP SAGE Anatomical Viewer [12, 13] (Figure 1B). These genes (CEACAM7, SPRR3, S100A7 and KRT6A) are our candidates for an expression signature unique to normal cervical tissue and were further investigated in a panel of 20 different tissue types and three new normal cervical specimens. We found that all four of these genes were not abundantly expressed simultaneously in any of the 20 tissues examined (Figure 2). Placenta, thymus and tongue were found to express a combination of three genes (S100A7, SPRR3 and KRT6A), while colon expressed another combination (CEACAM7, SPRR3 and KRT6A). KRT6A and SPRR3 expression was observed in larynx tissue with only minimal expression detected for S100A7 and CEACAM7. In contrast, two of the cervical cases strongly expressed all four genes investigated while only the third showed very low CEACAM7 expression. Significantly, our study is the first to document CEACAM7 expression in cervix. The data suggest that abundant expression of CEACAM7 and S100A7 collectively, are unique to cervical tissue and have the potential to serve as useful biomarkers in identifying origins of metastatic disease.

It is interesting to note that decreased expression of three of the genes is linked to abnormal growth and organization of epithelium. For example, CEACAM7 is a member of the carcinoembryonic antigen family of genes and expression has been documented in highly differentiated normal colon epithelium and the apical surface of normal ductal pancreas epithelium, while loss of expression has been reported in colon hyperplastic polyps [14]. Another member of this gene family, CEACAM1, is shown to have no or very low expression in cervical carcinoma [15]. Decreased expression of KRT6A and S100A7 have been associated with breast, lung and ovarian cancer [1620]. SPRR3 belongs to the class of small proline rich genes which are expressed in differentiated keratinocytes and has previously been shown to be highly expressed in normal cervical tissue [21].

Genes Altered in Expression in CIN III

The 107 highly expressed unique tags in the normal libraries were assessed for expression changes in CIN III. Two genes showed increased expression (AQP3 and RPL37) while three genes declined in transcript counts in the CIN III libraries (ANXA2, GJA1 and LGALS7). All five were evaluated by real-time PCR in a new cervical tissue panel. Results for ANXA2, LGALS7 and GJA1 confirmed L-SAGE findings.

Panel results for GJA1 are in agreement with those reported by King et al. in that GJA1 expression was detected in normal cervical epithelium while reduced expression was observed in CIN III lesions investigated [22]. It has been suggested that this pattern may be a consequence of epithelial disorganization and not causative in dysplasia development [23, 24].

The high expression of LGALS7 in normal cervical epithelium contrasted by the low expression seen in the CIN III lesions in the tissue panel we report here is similar to those expression patterns seen in studies of other normal tissue types compared to their respective carcinomas including cornea and larynx [25]. LGALS7 expression has been hypothesized in all stratified epithelium tissue types and has been experimentally detected in human cornea, heart, larynx, tongue, skin, thymus and thyroid [2628]. Though, LGALS7 has been investigated in the context of cell line models, it is interesting to note that expression of this gene in cervical epithelium has not been previously reported [2628]. LGALS7 is one of fifteen members of the B-galactoside-binding lectin family, some of which have been shown to influence cell growth, cell cycle, apoptosis and cell migration via their predicted role in homeostasis, however, the role of LGALS7 in cancer is unclear [27, 29]. Support for the pro-apoptotic function of LGALS7 was reported by Kuwabara et al. and Bernard et al. who identified cells more sensitive to apoptosis when LGALS7 expression was high in the epithelium derived cells [28, 30, 31]. In contrast, Demers et al. showed an increase in LGALS7 expression in lymphoma cells and suggested a positive role in cell growth and dispersal through induced matrix metalloproteinase 9 (MMP9) expression [32]. We did not observe a statistically significant change in MMP9 in the four libraries investigated. This variance in expression suggests multiple roles for LGALS7 that may be tissue-type dependent.

The third gene investigated, ANXA2, is known to be highly expressed in epithelial cells and is localized to the plasma membrane and endosome. It has been suggested to function in linking membrane to membrane and membrane to cytoskeleton [33]. The decrease in expression we observe suggests that the loss of ANXA2 may be a causative factor in disorganisation of the epithelial architecture, which is characteristic of cervical neoplastic lesions. ANXA2 is also known to bind with S100A10 and participates in transport channel function across the plasma membrane [33]. Interestingly, the ANXA2 binding site on S100A10 also binds NS3, a viral protein from the bluetongue virus, and therefore directly competes with ANXA2. The S100A10 protein has also been shown inhibit Hepatitis B virus polymerase (HBV pol) activity [34]. It is plausible that a S100A10-ANXA2 complex may have a role in HPV infection or viral lifecycle. S100A10 expression was high and consistent in Normal and CIN III libraries whereas ANXA2 decreased in the CIN III libraries.

The above real-time PCR results were normalized to the widely accepted housekeeping gene ACTB (Figure 3A). For comparison we also normalized the genes to a second housekeeping gene 18S (Figure 3B). Briefly, results for GJA1 and LGALS7 were in agreement to those when normalizing to ACTB, however ANXA2 was shown to be increased in CIN III as expected by the SAGE data. but this does not concur with the QPCR results when normalized to ACTB. One possible explanation is that on average, the ACTB cycle threshold was >1.3 Ct lower in the CIN III cases indicating an increase in ACTB expression in CIN III lesions. Any Ct decrease less than this in the genes investigated would appear as a decrease in gene expression in CIN III when normalized to ACTB but and increase when normalized to 18S.

The real-time PCR results for AQP3 and RPL37 did not concur with L-SAGE data and may be due to interindividual differences rather than a representation of changes present in CIN lesions or cancer. It is interesting to note that RPL37 overexpression in prostate cancer, colon cancer cell lines and clinical specimens have been reported [35, 36]. Our L-SAGE results also suggest a similar pattern in cervical neoplasia. Results for these genes when normalized to 18S showed an increase in expression in only CIN III A (see Additional file 3).

Wong et al investigated gene expression in invasive cervical carcinoma by DNA microarray [37]. We investigated this publicly available data through NCBI GEO [38]. Briefly, in this data, GJA1 showed a small decrease in expression in invasive disease while LGALS7 was detected in only four of the 26 specimens, three of which were normal tissue. Moderate AQP3 expression was detected in the majority of cases including the control group. Expression of ANXA2 and RPL37 was not assessed in the microarray study.

Human L-SAGE Tags Map to the HPV Genome

HPV is an established etiological factor in cervical cancer [2]. There are over 100 known strains of HPV, however HPV 16 and HPV 18 are considered to be the frequent high risk types owing to higher rates of persistent infection, higher rates of progression to cervical neoplasia, and shorter median progression times than other HPV strains [2]. HPV 16 is the most common strain and can be detected in approximately 60% of cervical cancers, while HPV 18 infection occurs in approximately 10–20%. Uncontrolled expression of E6 and E7 genes from strains 16 or 18 are considered to be essential for oncogenic transformation and function through inhibition of host cell tumour suppressors p53 and the retinoblastoma protein (Rb) [2].

This is the first study to mine human SAGE libraries for viral transcripts. Overall, CIN III library C2 (2,548 tpm) possessed a greater number of tag counts from the more prevalent HPV 16 strain when compared to C1 (320 tpm) (Table 3). HPV 18 tags were not found in any library and no viral tags were detected in the normal libraries. With the exception of two tags, the viral tags expressed in cervical SAGE did not map to known human genes or expressed sequences. The exceptions, CATGCACGCTTTTTAATTACA and CATGTGTATGTATTAAAAATA, mapped to a single human EST isolated from a uterine tumour (EST BF909200). The full length EST sequence is 97% identical with the HPV 16 genome, more specifically the E5 gene, and therefore was likely amplified from HPV sequences in the original lesion.

Tags mapping to the E5 gene accounted for the greatest proportion of HPV tags mapping to known transcripts in both C1 and C2 (93% and 52%, respectively). E5 is considered to be one of three HPV 16 oncogenes (E5, E6 and E7) and is highly expressed in basal cells of premalignant cervical lesions [39]. This expression declines as cells differentiate and move toward the apical face of the epithelium whereas E6 and E7 expression increases [39]. E5 is detected throughout all epithelium layers in high grade lesions such as CIN III. In contrast, expression is restricted to layers closest to the basal cells in low grade lesions, implying that E5 expression may be limited to undifferentiated basal cells [40, 41]. The high expression of E5 we observe in the CIN III libraries and the absence of HPV 16 genes in the normal libraries is in concordance with such studies.

An increase in sample size and inclusion of mild and moderate stages of cervical intraepithelial neoplasia will aid in quantifying the relationship between viral gene expression and disease. This will also assist in further elucidating genes important in early lesion transcriptome events. A comparison of such events with those seen in later stages will help to identify genes important in the molecular pathogenesis of the disease.

Conclusion

In this study we have described the transcriptome of normal cervical tissues and compared against that of CIN III lesions. This was achieved by construction of four L-SAGE libraries and sequencing to the depth of 172,848 tags per library on average. We highlighted that the Long-SAGE technique provides a comprehensive profile of the transcriptome without focusing on only known genes. Potent tumour suppressors (e.g. PTEN), cell cycle mediators (e.g. CCND1), and cellular respiration genes (e.g. NDUFA1) were found to be tightly regulated in the normal libraries. An expression signature of four highly expressed genes (KRT6A, CEACAM7, S100A7 and SPRR3) in normal cervical epithelium was identified and confirmed, and three abundantly expressed genes (ANXA2, GJA1 and LGALS7) were found to have altered expression in CIN III. Furthermore, this is the first study to have identified viral tags in human SAGE libraries demonstrating the versatile nature of SAGE data, which allows for mining and re-mining according to newly posed questions. HPV 16 E5 transcripts were found most highly expressed while few E7 and no E6 transcripts were enumerated.

The identification of expression changes associated with stages of disease progression will help further our understanding of cervical cancer development and potentially elucidate novel targets for diagnosis and treatment. Establishing a baseline from which to compare is essential to the identification of such aberrations and the 20 fold increase in cervical gene expression data presented here is a significant contribution to this effort.

Methods

Sample selection

The specimens were collected immediately prior to the LEEP (Loop electrosurgical excision procedure) cone biopsy targeting a small portion of the affected epithelium. These specimens were collected with patient consent at the Vancouver General Hospital Women's Clinic at Vancouver Hospital & Health Science Centre. Cases were assessed by cervical cancer pathologists at Vancouver Hospital and Health Science Centre and were selected without prior knowledge of HPV status. Specimens N1 and N2 in this study were observed to be normal squamous epithelia whereas C1 and C2 were identified as high grade dysplasia or CIN III. Detailed information on specimen pathology based on the LEEP cone specimens can be found in Additional file 4. All samples were stored immediately in RNA later and stored at -80°C. Three cases each of CIN III (CIN III A, CIN III B and CIN III C) and normal cervical tissue (NA, NB and NC) which were used for target validation through real-time PCR were also collected, assessed and stored in the same manner.

L-SAGE Library Construction and Sequence Tag Analysis

The biopsies were individually homogenised in Lysis Binding buffer (100 mM Tris-HCl, pH7.5, 500 mM LiCl, 10 mM EDTA, pH 8.0, 1% LiDS, 5 mM dithiothreitol). Long SAGE libraries were constructed according to the L-SAGE kit manual (Invitrogen, Ontario, Canada). Sequencing was performed at the BC Cancer Agency Michael Smith Genome Sciences Centre. L-SAGE employs 21 basepair sequence tags, reducing the ambiguity in tag-to-gene mapping that is sometimes encountered in classic SAGE libraries which use 14 basepair sequence tags.

Data Analysis

Tags were mapped using the February 12, 2006 version of SAGE Genie [13], and raw tag counts excluding duplicate ditags were normalized to tags per million (tpm). A Z-test analysis, standard for SAGE data analysis, was performed as previously established by Kal et al. for comparison of one SAGE library to another using an established cut-off of 1.96 on the absolute Z-score to determine statistically significant differences in expression levels between normal and CIN III [42].

Reverse Transcriptase PCR

For validation of cervical tissue gene signature, human Multiple Tissue cDNA Panel I and II (Clontech, Mississauga, Ontario) and total RNA for human larynx, skin, stomach and tongue (Stratagene, Cedar Creek, Texas) were used. Five-hundred nanograms from larynx, skin, stomach and tongue was used to generate cDNA. Final concentrations of PCR reagents for cervical tissue signature were 0.5 μM primer, 2 mM MgCl2, 0.2 mM dNTP, 1× PCR buffer (Invitrogen), 0.5 U Taq polymerase and 1 μL of cDNA (annealing temperatures: 55°C (ACTB, CEACAM7), 60°C (KRT6A), 65°C (SPRR3 and S100A7). Total RNA for the panel of six cervical specimens used for validation of genes was isolated using Trizol (Invitrogen) and cDNA was generated using the High Capacity TaqMan Reverse Transcription Reagents, according to the manufacturer's instructions (Applied Biosystems, Foster City, CA).

Expression of genes selected by data analysis were analyzed by real-time PCR using TaqMan® Gene Expression Assays on the ABI 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA), according to manufacturer's instructions. Samples were run in duplicate and normalized against an beta-actin (ACTB) endogenous control (HuACTB, Applied Biosytems). Assay IDs include AQP3, Hs00185020_m1; GAL7, Hs00170104_m1; RPL37, Hs02340038_g1; and GJA-1, Hs00748445_s1. The relative quantification of these target genes in CIN III (CIN III A, CIN III B and CIN III C) samples compared to normal tissue (NA, NB and NC) samples was performed using the established 2-ΔΔCt method, (Applied Biosystems, Relative Quantitation Of Gene Expression, ABI PRISM 7700 Sequence Detection System: User Bulletin #2). The cycle threshold (Ct) value of the target gene was normalized to ACTB by subtracting the Ct value for ACTB from that of the target gene (ΔCt gene = Ct gene - Ct ACTB). This number was then averaged from the three normal cases (ave ΔCt normal). The mean fold change of each gene between normal and CIN III was calculated using the following equation: 2 -(ΔCt gene - ave ΔCt normal). The relative quantification values were then plotted, one indicating no change with respect to normal cervical tissue.

HPV Tag-to-Gene Mapping

Viral genomic sequence files (viral1.genomic.fna and HPV11.txt) were downloaded from public repositories and processed into 21 bp SAGE tags at every Nla III site in both orientations using custom Perl scripts [43, 44].

Abbreviations

(CIN): 

Cervical Intraepithelial Neoplasia

(EST): 

Expressed Sequence Tag

(HPV): 

Human Papillomavirus

(SAGE): 

Serial Analysis of Gene Expression

(tpm): 

Tags per million

Declarations

Acknowledgements

We are grateful to Anita Carraro for sample coordination and retrieval and Blair Gervan, Lana Galac and Ariane Williams for their technical assistance. This work was made possible by support from the National Institute of Health (5 P0l CA 82710-07 and 7P0l CA 103830).

Authors’ Affiliations

(1)
Cancer Genetics & Developmental Biology, British Columbia Cancer Research Centre
(2)
Pathology, British Columbia Cancer Agency
(3)
Obstetrics and Gynaecology, The University of British Columbia
(4)
Gynecologic Oncology, British Columbia Cancer Agency
(5)
Gynecologic Oncology, The University of Texas M.D. Anderson Cancer Center
(6)
Cancer Imaging, British Columbia Cancer Research Centre

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© Shadeo et al; licensee BioMed Central Ltd. 2007

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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