Genomic profiling in locally advanced and inflammatory breast cancer and its link to DCE-MRI and overall survival

Figures & data

Figure 1. Wash-in parameter (WiP) maps generated from DCE-MRI in LABC patients. WiP maps are surrogates for perfusion/permeability [7]. The right image shows the CF enhancement pattern which is a uniform enhancement from centre to periphery. The left image is the CP enhancement pattern which is an inhomogeneous ring-type enhancement. The 10–250 scale represents the range of the WiP as previously described in detail [7].

Figure 2. Heat map cluster plot of Affymetrix microarray data in LABC samples. This heat map plot records post-normalisation between-probes distances measured by their absolute median difference. The left diagram represents all the top probe sets associated with144 genes, which were differentially expressed in CF versus CP (p < 0.008); 80% of the probes had higher expression levels in the CP enhancement pattern and only 20% had higher expression levels in CF. The right diagram is the enlarged heat map for MTA1, PARP6, SULT1A1 and SULT1A2. In the table, test statistic (teststat) is the smaller of two sums of ranks of given sign. Negative test statistics represent higher expression level of a gene in the CF pattern, and positive test statistics represent higher expression level in the CP perfusion pattern.

Figure 3. Differential expression levels in the CF enhancement pattern compared to the CP. (A and B) Our analysis demonstrates an overexpression of SULTs (SULT1A1 and SULT1A2) in the CP enhancement compare to CF. (C) The CP enhancement pattern is associated with higher expression levels of PARP6. (D) MTA1 shows higher expression levels in the CF enhancement pattern compared to the CP.

Table 1. Association between gene expression patterns and overall survival in IBC patients.

Probe	Symbol	p Value	HR	Sctest p value	Cox HR
226914_at	ARPC5L	4.00E-04	1.8	4.42E-04	1.8
219366_at	AVEN	1.90E-03	1.5	1.03E-03	1.5
236331_at	CDKL2	1.50E-03	1.5	1.20E-03	1.5
226372_at	CHST11	0.00E + 00	2.4	7.88E-05	2.4
32094_at	CHST3	7.00E-04	1.5	5.84E-04	1.5
229779_at	COL4A4	9.00E-04	1.6	7.82E-04	1.6
213274_s_at	CTSB	6.00E-04	1.6	4.63E-04	1.6
200825_s_at	HYOU1	1.00E-04	1.7	1.99E-04	1.7
213093_at	PRKCA	1.00E-03	1.6	6.56E-04	1.6
209325_s_at	RGS16	1.00E-03	1.6	6.26E-04	1.6
212701_at	TLN2	5.00E-04	1.6	5.25E-04	1.6
201645_at	TNC	1.50E-03	1.7	9.01E-04	1.7

The complete list of the 45 genes associated with OS is presented in the supplementary data.

The HR and p value are computed based on the permutation resampling inference test for survival data. The ‘sctest p value’ and ‘cox HR’ columns are based on the log rank test.

Figure 4. Gene expression patterns and overall survival in IBC patients. ARPC5L and CDKL2 expression levels are significantly associated with long-term OS in IBC patients. Survival time represents years. Three of the patients from the Duke clinical trial who are alive are represented with a triangle symbol in the graph.

Figure 5. External confirmation for gene expression patterns and overall survival in LABC using TCGA database. In TCGA LABC cohort differential expression of four genes exhibited the same significant concordance and association with overall survival as in the IBC patients. The black lines in the graph represent high expression levels and the red lines represent low expression levels of the genes. The “sctest p-value” and “HR” (which is a cox HR) columns are based on the log rank test.

Table 2. Overview of some of the biological processes associated with differential expression of our genes of interest.

Gene symbol	Gene function
A. Genes differentially expressed in the DCE-MRI enhancement patterns (centripetal vs. centrifugal)
MTA1	MTA1 is a potential predictor for breast tumour aggressiveness, involved in angiogenesis and is a predictor of early disease relapse [44,45]
	Can repress the ESR1 trans-activation function [46,47]
	Can inactivate the tumour suppressor TP53 [48,49]
	Can de-acetylate and stabilise the hypoxia-inducible factor-1 alpha (HIF-1α) which is a key regulator of angiogenic factors [50–52]
	MTA proteins, including MTA1, have been reported as a possible set of ‘master co-regulatory molecules’ involved in the carcinogenesis and progression of various malignancies [47]
PARP6	PARP superfamily is involved in the regulation of angiogenesis, differentiation, proliferation, cell death, tumour transformation and DNA damage recovery [53,54]
	PARP inhibitors can decrease angiogenesis since inhibition of PARP will affect VEGF-induced proliferation and migration [55,56]
SULT1A1, SULT1A2	Alterations in the expression of SULT enzymes and their genetic polymorphisms have been reported in lung, prostate, and breast cancer [57,58]
	Several members of the SULT family are responsible for the sulphation of oestrogens, therapeutic estrogenic compounds, and hormone replacement therapy agents; SULTs play a key role in the metabolism and inactivation of oestrogen [59]
B. Genes differentially expressed in the survival analysis for inflammatory breast cancer patients*
ARPC5L	ARPC5 family has been implicated in invasion and metastasis in human head and neck squamous cell carcinoma [38]
AVEN	Considered a regulator of apoptosis. Resistance to apoptosis is associated with carcinogenesis, tumour progression, and treatment resistance. Overexpression associated with poor prognosis in tumours such as childhood acute lymphoblastic leukaemia and acute myeloid leukaemia [60–62]
CDKL2	CDKL2 is a member of a large family of CDC2-related serine/threonine protein kinase. CDC2 overexpression in breast tumours has been associated with infiltrative tumour border pattern and histological high grade breast carcinomas [40]
CHST11, CHST3	CHST11 and CHST3 are involved in the sulphur metabolism pathway. CHST11 mediates 4-O sulphation of chondroitin, CHST3 mediates 4-O sulphation of chondroitin [63]
	Chondroitin sulphates are involved in breast tumour aggressiveness and metastasis and CHST11 and CHST3 overexpression have been reported to be associated with more aggressive breast tumours [35]
COL4A4	COL4A4 protein belongs to the type IV collagen family. Overexpression of type IV collagen family members has been associated with tumour size, higher grade, metastasis and invasion in malignancies such as breast, ovarian, cervical, colorectal and gastric cancers [64–66]
CTSB	Overexpression has been reported to be associated with tumour invasiveness and poor patient prognosis in melanoma, prostate and breast cancers [67]
	CTSB overexpression in inflammatory breast cancer has been suggested as a prognosis biomarker associated with poor survival and increased number of positive metastatic lymph nodes [41]
HYOU1	Associated with tumour invasiveness and resistance to therapy. Suppression also results in increased apoptosis [68–70]
PRKCA	A member of the protein kinase C family which can play an important role in cell signalling pathways by phosphorylating protein targets. High expression levels of PRKCA have been reported as a potential marker for poor prognosis and associated with breast cancer progression [71]
RGS16	A member of the RGS superfamily, a class of intracellular signalling regulators. Considered as therapeutic targets, including in breast cancer [42,43]
TLN2	In the FAK pathway, FAK and TLN are two key players in matrix-cell adhesion assembly required for cell migration which can result in tumour metastasis and progression [72,73]
TNC	Frequently up-regulated in breast cancer and promotes tumour invasion. Associated with promoting cell migration, angiogenesis and can act as a cell survival factor [39]

The complete list of the 45 genes associated with OS is presented in the supplementary data.

Craciunescu OI, Blackwell KL, Jones EL, Macfall JR, Yu D, Vujaskovic Z, et al. DCE-MRI parameters have potential to predict response of locally advanced breast cancer patients to neoadjuvant chemotherapy and hyperthermia: A pilot study. Int J Hyperthermia 2009;25:405–15

 PubMed Web of Science ®Google Scholar

Jang K-S, Paik SS, Chung H, Oh Y-H, Kong G. MTA1 overexpression correlates significantly with tumor grade and angiogenesis in human breast cancers. Cancer Sci 2006;97:374–9

 PubMed Web of Science ®Google Scholar

Martin MD, Hilsenbeck SG, Mohsin SK, Hopp TA, Clark GM, Osborne CK, et al. Breast tumors that overexpress nuclear metastasis-associated 1 (MTA1) protein have high recurrence risks but enhanced responses to systemic therapies. Breast Cancer Res Treat 2006;95:7–12

 PubMed Web of Science ®Google Scholar

Kumar R, Wang RA, Mazumdar A, Talukder AH, Mandal M, Yang Z, et al. A naturally occurring MTA1 variant sequesters oestrogen receptor-alpha in the cytoplasm. Nature 2002;418(6898):654–7

 PubMedGoogle Scholar

Toh Y, Nicolson G. The role of the MTA family and their encoded proteins in human cancers: Molecular functions and clinical implications. Clin Exper Metastasis 2009;26:215–27

 PubMed Web of Science ®Google Scholar

Li DQ, Pakala SB, Reddy SD, Ohshiro K, Peng SH, Lian Y, et al. Revelation of p53-independent function of MTA1 in DNA damage response via modulation of the p21 WAF1-proliferating cell nuclear antigen pathway. J Biol Chem 2010;285:10044–52

 PubMedGoogle Scholar

Moon HE, Cheon H, Lee MS. Metastasis-associated protein 1 inhibits p53-induced apoptosis. Oncol Rep 2007;18:1311–14

 PubMedGoogle Scholar

Amé JC, Spenlehauer C, de Murcia G. The PARP superfamily. Bioessays 2004;26:882–93

 PubMed Web of Science ®Google Scholar

Kim MY, Zhang T, Kraus WL. Poly(ADP-ribosyl)ation by PARP-1: ‘PAR-laying’ NAD+ into a nuclear signal. Genes Dev 2005;19:1951–67

 PubMed Web of Science ®Google Scholar

Pyriochou A, Olah G, Deitch EA, Szabo C, Papapetropoulos A. Inhibition of angiogenesis by the poly(ADP-ribose) polymerase inhibitor PJ-34. Int J Mol Med 2008;22:113–18

 PubMed Web of Science ®Google Scholar

Rajesh M, Mukhopadhyay P, Batkai S, Godlewski G, Hasko G, Liaudet L, et al. Pharmacological inhibition of poly(ADP-ribose) polymerase inhibits angiogenesis. Biochem Biophys Res Commun 2006;350:352–7

 PubMed Web of Science ®Google Scholar

Aust S, Obrist P, Klimpfinger M, Tucek G, Jager W, Thalhammer T. Altered expression of the hormone- and xenobiotic-metabolizing sulfotransferase enzymes 1A2 and 1C1 in malignant breast tissue. Int J Oncol 2005;26:1079–85

 PubMed Web of Science ®Google Scholar

Wang Y, Spitz MR, Tsou AM, Zhang K, Makan N, Wu X. Sulfotransferase (SULT) 1A1 polymorphism as a predisposition factor for lung cancer: A case-control analysis. Lung Cancer 2002;35:137–42

 PubMed Web of Science ®Google Scholar

Falany JL, Falany CN. Interactions of the human cytosolic sulfotransferases and steroid sulfatase in the metabolism of tibolone and raloxifene. J Steroid Biochem Mol Biol 2007;107:202–10

 PubMed Web of Science ®Google Scholar

Kinoshita T, Nohata N, Watanabe-Takano H, Yoshino H, Hidaka H, Fujimura L, et al. Actin-related protein 2/3 complex subunit 5 (ARPC5) contributes to cell migration and invasion and is directly regulated by tumor-suppressive microRNA-133a in head and neck squamous cell carcinoma. Int J Oncol 2012;40:1770–8

 Google Scholar

Chae SW, Sohn JH, Kim DH, Choi YJ, Park YL, Kim K, et al. Overexpressions of Cyclin B1, cdc2, p16 and p53 in human breast cancer: The clinicopathologic correlations and prognostic implications. Yonsei Med J 2011;52:445–53

 PubMedGoogle Scholar

Kluppel M. The roles of chondroitin-4-sulfotransferase-1 in development and disease. Prog Mol Biol Transl Sci 2010;93:113–32

 PubMedGoogle Scholar

Cooney CA, Jousheghany F, Yao-Borengasser A, Phanavanh B, Gomes T, Kieber-Emmons AM, et al. Chondroitin sulfates play a major role in breast cancer metastasis: A role for CSPG4 and CHST11 gene expression in forming surface P-selectin ligands in aggressive breast cancer cells. Breast Cancer Res 2011;13:R58

 PubMed Web of Science ®Google Scholar

Jedeszko C, Sloane BF. Cysteine cathepsins in human cancer. Biol Chem 2004;385:1017–27

 PubMed Web of Science ®Google Scholar

Nouh M, Mohamed M, El-Shinawi M, Shaalan M, Cavallo-Medved D, Khaled H, et al. Cathepsin B: A potential prognostic marker for inflammatory breast cancer. J Transl Med 2011;9:1

 PubMed Web of Science ®Google Scholar

Lonne GK, Cornmark L, Zahirovic IO, Landberg G, Jirstrom K, Larsson C. PKCalpha expression is a marker for breast cancer aggressiveness. Mol Cancer 2010;9:76 . PubMed PMID: 20398285. Pubmed Central PMCID: PMC2873434. Epub 2010/04/20. eng

 PubMed Web of Science ®Google Scholar

Bosch DE, Zielinski T, Lowery RG, Siderovski DP. Evaluating modulators of ‘Regulator of G-protein Signaling’ (RGS) proteins. Curr Protoc Pharmacol 2012;2:2.8

 Google Scholar

Kimple AJ, Willard FS, Giguere PM, Johnston CA, Mocanu V, Siderovski DP. The RGS protein inhibitor CCG-4986 is a covalent modifier of the RGS4 Galpha-interaction face. Biochim Biophys Acta 2007;1774:1213–20

 PubMedGoogle Scholar

Jevnikar Z, Rojnik M, Jamnik P, Doljak B, Fonovic UP, Kos J. Cathepsin H mediates the processing of talin and regulates migration of prostate cancer cells. J Biol Chem 2013;288:2201–9

 PubMedGoogle Scholar

Lawson C, Lim ST, Uryu S, Chen XL, Calderwood DA, Schlaepfer DD. FAK promotes recruitment of talin to nascent adhesions to control cell motility. J Cell Biol 2012;196:223–32

 PubMed Web of Science ®Google Scholar

Hancox RA, Allen MD, Holliday DL, Edwards DR, Pennington CJ, Guttery DS, et al. Tumour-associated tenascin-C isoforms promote breast cancer cell invasion and growth by matrix metalloproteinase-dependent and independent mechanisms. Breast Cancer Res 2009;11:R24

 PubMed Web of Science ®Google Scholar