COMPARISON OF THE GENE EXPRESSION PROFILES OF METAPLASTIC
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COMPARISON OF THE GENE EXPRESSION PROFILES OF METAPLASTIC BREAST CANCER AND BASAL-LIKE BREAST CANCER. Mangesh A. Thorat 1 , Tanuja M Shet 2 , Akira Morimiya 1 , Roshni F Chinoy 2 , Rajendra A. Badwe 3 , Sunil Badve 1

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COMPARISON OF THE GENE EXPRESSION PROFILES OF METAPLASTIC

BREAST CANCER AND BASAL-LIKE BREAST CANCER

Mangesh A. Thorat 1, Tanuja M Shet 2, Akira Morimiya 1, Roshni F Chinoy 2, Rajendra A. Badwe 3, Sunil Badve 1

1Dept. of Pathology & Translational Genomics Core, IU School of Medicine, 2Dept. of Pathology, Tata Memorial Hospital, Mumbai, India, 3Dept. of Surgical Oncology, Tata Memorial Hospital, Mumbai, India

LIST OF SERVICES

BACKGROUND

Metaplastic cancers of the breast (MCBs) are a distinct subgroup of breast cancers. These are a heterogeneous group of tumours with mixed epithelial and sarcomatoid components, or mixed adenocarcinoma and squamous cell carcinoma components. (1) Many studies have reported aggressive clinical behavior of these tumours associated with poor survival. (1-4) Recently, few studies (5, 6) have proposed that MCBs belong to basal-like subtype of invasive ductal cancers (IDC). High-throughput gene expression profiling followed by hierarchical clustering led to identification of breast cancer subtypes. (7) Such approach can reliably determine whether MCBs belong to basal-like breast cancers (BBCs). However, rarity of these tumors has been a handicap for conventional gene expression profiling. (8) If MCBs belong to basal-like subtype, these should cluster together on multi-parameter hierarchical clustering as in microarray. Number of parameters to be used for such clustering should be more than 100; (9) smaller number of markers (5, 6) can yield spurious results. We tested this hypothesis by performing quantitative gene expression analysis of 502 cancer-related genes on archived FFPE tumors using a novel cDNA-mediated annealing, selection, extension, and ligation (DASL) assay to identify clustering pattern and differentially expressed genes between MCBs and BBCs identified by their triple negative receptor status.

Gene expression profiling:Whole genomeFocused (DASL on FFPE), standard panel or customizedDASL Whole genome

Genotyping: Standard panel or customized, up to 1536 SNPs

miRNA expression profiling

Methylation profiling

Ancillary services:

Nucleic Acid quantitation using NanoDrop

RNA QC using Bioanalyzer

Additional details available at: http://www.cancer.iu.edu/research/facilities/translational_genomics/

Figure 1: A) Metaplastic breast cancer with squamous differentiation. (200X) B) Basal (triple negative) breast cancer. (400X)

Table 1: Patient Characteristics

Table 2: Genes under-expressed in squamous MCBs

METHODS

QUALITY CONTROL AND ASSURANCES

We selected 8 MCBs with squamous differentiation (Figure 1A), and 25 IDCs, 11 of which were triple negative tumors (TN) (Figure 1B); clinical characteristics of these patients are described in Table 1. RNA (200 ng) was extracted using HighPure RNA Paraffin Kit (Roche Applied Bioscience, Indianapolis, IN, USA). RNA was pre-qualified using iScript (Bio-Rad Laboratories Inc, Hercules, CA, USA) to reverse transcribe and SYBR Green Master Mix (Applied Biosystems, Foster City, CA, USA) to perform qPCR. DASL assay was performed using the Sentrix Universal Array (Illumina Corp., San Diego, CA, USA) of 502 known cancer genes. Statistical analyses and clustering were performed using BeadStudio v3.0 (Illumina Corp.).

  • All nucleic acid extractions have been standardized for each type of material.

  • All nucleic acid material from samples to be used on assay is checked for quality using NanoDrop &/or Bioanalyzer &/or pre-assay qPCR.

  • Appropriate duplicates incorporated in each assay for making inter-chip comparisons and checking assay performance.

  • Excellent R2 values obtained routinely for technical duplicates; above 0.99 for intact RNA and above 0.95 for degraded RNA.

RESULTS

CONTACT INFORMATION

Unsupervised hierarchical clustering of 33 cases showed two main branches, MCB and IDC (Figure 2). IDC group broadly comprised two subgroups; 9-case-subgroup clustering farthest from MCB branch contained 7 TN (78%), and 16-case-subgroup between these branches contained 4 TN (25%). Analysis of TN (n=11) vs. MCBs (n=8) revealed significant down-regulation of 10 genes (after correction for false-discovery) in MCBs (Table 2). Number of differentially expressed genes without correction for false-discovery was 53.

Translational Genomics Core

MS-B037,

635 Barnhill Drive, Indianapolis, IN 46202

Phone: 317-274-5583/5565

Fax: 317-274-5565

Email: [email protected]

Dr. Sunil Badve (Core Director)

CPL 4050,

350 W 11th st., Indianapolis, IN 46202

Phone: 317-491-6417

Fax: 317-491-6417

Email: [email protected]

Figure 2: Unsupervised Hierarchical clustering

CONCLUSION

MCBs and TN have distinct gene expression profiles and do not cluster together as one group. Contrary to recent hypothesis, MCBs are a distinct group of breast cancers and do not belong to BBCs.

REFERENCES

  • Tse GM, et al.J Clin Pathol 2006; 59(10): 1079-83.

  • Al Sayed AD, et al.Acta Oncol 2006; 45(2): 188-95.

  • Beatty JD, et al.Am J Surg 2006; 191(5): 657-64.

  • Luini A, et al.Breast Cancer Res Treat 2007; 101(3): 349-53.

  • Reis-Filho JS, et al.Histopathology 2006; 49(1): 10-21.

  • Savage K, et al.Clin Cancer Res 2007; 13(1): 90-101.

  • Perou CM, et al.Nature 2000; 406(6797): 747-52.

  • Lien HC, et al.Oncogene 2007; 26(57): 7859-71.

  • Son CG, et al.Genome Res 2005; 15(3): 443-50.


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