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Clinical Research Papers:

FGFR1 is an adverse outcome indicator for luminal A breast cancers

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Oncotarget. 2016; 7:5063-5073. https://doi.org/10.18632/oncotarget.6563

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Yu-Jie Shi, Julia Y.S. Tsang, Yun-Bi Ni, Siu-Ki Chan, Kui-Fat Chan and Gary M. Tse _

Abstract

Yu-Jie Shi1, Julia Y.S. Tsang2, Yun-Bi Ni2, Siu-Ki Chan3, Kui-Fat Chan4, Gary M. Tse2

1Department of Pathology, Henan Province People's Hospital, Zhengzhou, Henan, China

2Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, NT, Hong Kong

3Department of Pathology, Kwong Wah Hospital, Kowloon, Hong Kong

4Department of Pathology, Tuen Mun Hosiptal, Tuen Mun, Hong Kong

Correspondence to:

Gary M. Tse, e-mail: garytse@cuhk.edu.hk

Keywords: fibroblast growth factor receptor 1, breast cancer, luminal subtype, immunohistochemistry

Received: August 21, 2015     Accepted: November 21, 2015     Published: December 11, 2015

ABSTRACT

Fibroblast growth factor receptor 1 (FGFR1) has been suggested to be the candidate gene for 8p11–12 amplification in breast cancer and its therapeutic/ prognostic value is explored. Most previous studies focused on FGFR1 gene amplification, which may not necessarily lead to protein expression. Therefore, analysis of protein level may have more clinical relevance. We evaluated FGFR1 expression in a large cohort of breast cancer by immunohistochemistry, correlated with the tumor clinic-pathologic features, biomarkers expression, and patient’s survival. FGFR1 expression was associated mainly with luminal cancers, particularly luminal B subtype (23.5%; p < 0.001), and it also showed adverse prognostic impact on luminal A cancers. FGFR1 expression was associated with higher pN (p = 0.023), pT (p = 0.003) stages, lymphovascular invasion (p = 0.010), p-cadherin (p = 0.028), synaptophysin (p = 0.009) and SOX2 expression (p = 0.034) in luminal A cancers. FGFR1 expressing luminal A cancers showed a similar outcome as luminal B cancers. Multivariate Cox regression analysis demonstrated FGFR1 positive luminal A cancers to be an independently poor prognosticator for disease free survival in luminal cancers (hazard ratio = 3.341, p = 0.008). Thus FGFR1 could be useful in identifying the aggressive cases amongst heterogeneous luminal A cancers. Given the relevance of FGFR pathway in treatment resistance in luminal cancers, FGFR1 could be an important tumor biomarker and adverse prognostic factor potentially exploitable in the clinical management of luminal cancers.


INTRODUCTION

Breast carcinogenesis may involve genetic alterations including activation or amplification of oncogenes [1]. Amplification at 8p11–12 is frequent, being reported in approximately 10–15% of breast cancers [2, 3]. Fibroblast growth factor receptor 1 (FGFR1) which encodes for a tyrosine kinase receptor in the FGFR family (FGFR1–4), is suggested to be the candidate gene [2, 4].

FGFR1 plays critical functions in the normal mammary physiologic development and tissue homeostasis. It is expressed in the mammary epithelium during ductal morphogenesis. Prenatal deletion of FGFR1 resulted in delayed mammary gland development and a transient reduction in cellular proliferation [5]. In breast cancers, FGFR1 is mainly localized in the cytoplasm and cell membrane. Aberrant FGFR regulation or expression induced mammary tumor cell proliferation, anti-apoptosis, drug resistance, epithelial-to-mesenchymal transition (EMT) and invasion [6, 7]. Recent investigations have highlighted the potential clinical values of FGFR1 as a therapeutic target and prognostic biomarker in breast cancers. FGFR1 amplification might be important in the invasive transition processes [8]. More FGFR1 amplification was observed in invasive breast cancer than the non-invasive ductal carcinoma in situ [9]. In addition, FGFR1 amplification was associated with distant metastasis, early relapse and poor survival [3, 911], and contributed to poor prognosis in luminal breast cancers by driving anchorage independent proliferation and endocrine therapy resistance [10]. In triple negative breast cancers (TNBC), the role of FGFR1 is less clear. While one study showed no effect of FGFR1 amplification on patient survival [12], another study showed FGFR1 protein expression correlated with decreased OS [13]. Whether this discrepancy was related to analysis at gene or protein levels was uncertain. It was important to note that FGFR1 gene amplification did not necessarily lead to a high protein expression, as low protein expression level in FGFR1 amplified tumors had also been observed [10].

While most previous studies focused on the FGFR1 amplification in clinical breast cancers as a group, FGFR1 protein expression in different molecular breast cancer subtypes and its association with other important biomarkers and prognosis are far from clear. In this study, the expression of FGFR1 in a large cohort of breast cancer was evaluated and correlated with various clinic-pathological features, biomarker expression and outcome, as well as with different breast cancer molecular groupings.

RESULTS

A total of 1,093 primary invasive breast cancers were included in this cohort. Details of the clinic-pathological features are summarized in Table 1. Overall, 941 cases (86.1%) were negative for FGFR1 and 152 cases (13.9%) were positive. Representative FGFR1 staining is shown in Figure 1.

Table 1: Correlations of FGFR1 expression with clinic-pathological features

 

FGFR1 Negative (%)

FGFR1 Positive (%)

Total

p Value

Grade

 

 

 

0.136

 1

144 (90)

16 (10)

160

 

 2

375 (86.0)

61 (14.0)

436

 

 3

422 (84.9)

75 (15.1)

497

 

FF

 

 

 

0.073

 Absence

700 (87.3)

101 (12.6)

801

 

 Presence

220 (83.0)

45 (17.0)

265

 

 Total

920 (86.3)

146 (13.7)

1066

 

LVI

 

 

 

0.066

 Absence

651 (87.6)

92 (12.4)

743

 

 Presence

244 (83.3)

49 (16.7)

293

 

 Total

895 (86.4)

141 (13.6)

1036

 

pN

 

 

 

0.042

 0

481 (88.3)

64 (11.7)

545

 

 1

265 (83.9)

51 (16.1)

316

 

 2

113 (87.6)

16 (12.4)

129

 

 3

68 (79.1)

18 (20.9)

86

 

Total

927 (86.2)

149 (13.8)

1076

 

 pT

 

 

 

0.037

 1

389 (88.2)

52 (11.8)

441

 

 2

470 (84.5)

86 (15.5)

556

 

 3

48 (82.8)

10 (17.2)

58

 

 4

13 (76.5)

4 (23.5)

17

 

 Total

920 (85.8)

152 (14.2)

1072

 

Molecular

 

 

 

< 0.001

 Lum A

403 (89.6)

47 (10.4)

450

 

 Lum B

287 (76.5)

88 (23.5)

375

 

 HER2-OE

106 (95.5)

5 (4.5)

111

 

 BLBC

60 (88.2)

8 (11.8)

68

 

 5NP

77 (93.9)

5 (6.1)

82

 

Age

 

 

 

0.062

 Mean

55 (100.5)

52.3 (95.6)

54.7

 

 SD

12.9 (100.8)

12 (93.8)

12.8

 

 Range

22–97

28–91

 

 

Tumor size

 

 

 

0.017

 Mean

2.63

2.9

2.67

 

 SD

1.491

1.5

1.5

 

 Range

0.2–13.9

0.3–9.5

 

 

BOLD: statistically significant

Representative immunohistochemical stainings of FGFR1 (200x).

Figure 1: Representative immunohistochemical stainings of FGFR1 (200x).

Correlation with tumor clinic-pathological characteristics, molecular subtypes and biomarkers

FGFR1 expression was found to be associated with high pN (p = 0.042), pT (p = 0.037) stages and large tumor size (p = 0.017), but not with tumor grade, LVI, FF and patients’ age (Table 1).

Among the 1086 invasive cancers with complete data for IHC based molecular classification, 450 (41.4%) were Lum A, 375 (34.5%) were Lum B, 111 (10.2%) were HER2-OE and 150 (13.9%) were TNBC (including 68 cases (6.3%) of BLBC and 82 cases (7.6%) unclassified). The expression rate of FGFR1 was 10.4% in Lum A, 23.5% in Lum B, 4.5% in HER2-OE, and 17.9% in TNBC (11.8% in BLBC and 6.1% in unclassified) cancers. Significant difference in FGFR1 expression was found among different molecular subtypes (p < 0.001), with the highest expression rate seen in Lum B cancers (Table 1).

For biomarkers, FGFR1 expression correlated with overall high ER, Ki67, P63, SOX2 and markers of neuroendocrine differentiation (CG and SYN) (p ≤ 0.001 for all, except p = 0.038 for SOX2). There was no significant correlation with other biomarkers, including PR, EGFR, HER2, c-kit, CK5/6, CK14 and P-cadherin (Table 2).

Table 2: Correlations of FGFR1 expression with biomarkers

 

FGFR1 Negative (%)

FGFR1 Positive (%)

Total

p Value

ER

 

 

 

< 0.001

 Neg

299 (92.3)

25 (7.7)

324

 

 Pos

641 (83.4)

128 (16.6)

769

 

 Total

940 (86.0)

153 (14.0)

1093

 

PR

 

 

 

0.969

 < 20%

411 (86.0)

67 (14.0)

478

 

 ≥ 20%

524 (85.9)

86 (14.1)

610

 

 Total

935 (86.0)

153 (14.0)

1088

 

HER2

 

 

 

0.674

 Neg

760 (85.6)

128 (14.4)

888

 

 Pos

189 (86.7)

29 (13.3)

218

 

 Total

949 (85.8)

157 (14.2)

1106

 

Ki67

 

 

 

< 0.001

 < 20%

699 (88.7)

89 (11.3)

788

 

 ≥ 20%

234 (78.5)

64 (21.5)

298

 

 Total

933 (85.9)

153 (14.1)

1086

 

P63

 

 

 

0.001

 Neg

904 (86.5)

141 (13.5)

1045

 

 Pos

31 (72.1)

12 (27.9)

43

 

 Total

935 (85.9)

153 (14.1)

1088

 

CK5/6

 

 

 

0.814

 Neg

837 (86.0)

136 (14.0)

973

 

 Pos

98 (85.2)

17 (14.8)

115

 

 Total

935 (85.9)

153 (14.0)

1088

 

CK14

 

 

 

0.118

 Neg

881 (86.5)

138 (13.5)

1019

 

 Pos

55 (79.7)

14 (20.3)

69

 

 Total

936 (86.0)

152 (14.0)

1088

 

P-cadherin

 

 

 

0.733

 Neg

713 (86.0)

116 (14.0)

829

 

 Pos

218 (85.2)

38 (14.8)

256

 

 Total

931 (85.8)

154 (14.2)

1085

 

CG

 

 

 

0.001

 Neg

902 (86.8)

137 (13.2)

1039

 

 Pos

30 (66.7)

15 (33.3)

45

 

 Total

932 (86.0)

152 (14.0)

1084

 

SYN

 

 

 

< 0.001

 Neg

854 (87.0)

127 (13.0)

981

 

 Pos

81 (75.7)

26 (24.3)

107

 

 Total

935 (86.0)

153 (14.0)

1088

 

Sox2

 

 

 

0.038

 Neg

343 (84.9)

61 (15.1)

404

 

 Pos

81 (76.4)

25 (23.6)

106

 

 Total

424 (83.1)

86 (16.9)

510

 

*statistically significant

FGFR1 expression in luminal subtypes

Given the significant correlation of FGFR1 the luminal subtypes, the relationship of FGFR1 with clinical features was investigated for luminal subtypes separately. FGFR1 was expressed in 134 out of 824 cases (16.3%) and 18 out of 261 cases (6.9%) of luminal and non-luminal cancers respectively.

In Lum cancers, FGFR1 expression was associated with high tumor grade (p = 0.005), pN (p = 0.004) and pT stages (p = 0.001), large tumor size (p = 0.001), and the presence of LVI (p = 0.031) (Table 3). For biomarkers, FGFR1 expression was positively associated with high Ki67 (p < 0.001), p-cadherin (p = 0.011), CG (p = 0.007), SYN (p = 0.001) and SOX2 (p = 0.013) but negatively with PR (p = 0.003). In addition, it was predominantly expressed in luminal B over luminal A subtype (p < 0.001) (Supplementary Table S2).

Table 3: Association of FGFR1 expression of clinic-pathological features and biomarker expression according to different luminal subtypes

 

Luminal A FGFR1 (%)

Luminal B FGFR1 (%)

Negative

Positive

Total

p-value

Negative

Positive

Total

p-value

Clinic-pathological features

Grade

 

 

 

0.124

 

 

 

0.784

 1

110 (92.4)

9 (7.6)

119

 

25 (78.1)

7 (21.9)

32

 

 2

213 (89.5)

25 (10.5)

238

 

114 (77.0)

34 (23.0)

148

 

 3

79 (85.9)

13 (14.1)

92

 

147 (76.2)

46 (23.8)

193

 

 Total

402 (89.5)

47 (10.5)

449

 

286 (76.7)

87 (23.3)

373

 

FF

 

 

 

0.177

 

 

 

0.376

 Absence

229 (90.9)

30 (9.1)

329

 

209 (78.0)

59 (22.0)

268

 

 Presence

95 (86.4)

15 (13.9)

110

 

69 (73.4)

25 (26.6)

94

 

 Total

394 (89.7)

45 (10.3)

439

 

278 (76.8)

84 (23.2)

362

 

LVI

 

 

 

0.010

 

 

 

0.972

 Absence

309 (92.0)

27 (8.0)

336

 

172 (76.4)

53 (23.6)

225

 

 Presence

78 (83.0)

16 (17.0)

94

 

95 (76.6)

29 (23.4)

124

 

 Total

387 (90.0)

43 (10.0)

430

 

267 (76.5)

82 (23.5)

349

 

pN

 

 

 

0.023

 

 

 

0.279

 0

225 (93.4)

16 (6.6)

241

 

138 (78.0)

39 (22.0)

177

 

 1

117 (84.2)

22 (15.8)

139

 

76 (77.6)

22 (22.4)

98

 

 2

38 (92.7)

3 (7.3)

41

 

42 (77.8)

12 (22.2)

54

 

 3

14 (77.8)

4 (22.2)

19

 

27 (67.5)

13 (32.5)

40

 

 Total

394 (89.7)

45 (10.3)

439

 

283 (76.7)

86 (23.3)

369

 

pT

 

 

 

0.003

 

 

 

0.330

 1

207 (93.2)

15 (6.8)

222

 

102 (77.9)

29 (22.1)

131

 

 2

174 (86.1)

28 (13.9)

202

 

156 (75.7)

50 (24.3)

206

 

 3

10 (76.9)

3 (23.1)

13

 

17 (77.3)

5 (22.7)

22

 

 4

3 (75.0)

1 (25.0)

4

 

3 (50.0)

3 (50.0)

6

 

 Total

394 (89.3)

47 (10.7)

441

 

278 (76.2)

87 (23.8)

365

 

Age

 

 

 

0.282

 

 

 

0.720

 Mean

56.7

54.5

56.4

 

52.3

52.0

52.2

 

 SD

13.1

13.6

13.1

 

12.2

11.2

12.0

 

 Range

30–97

28–91

 

 

22–85

31–89

 

 

Tumor size

 

 

 

0.005

 

 

 

0.311

 Mean

2.31

2.91

2.37

 

2.81

2.94

2.84

 

 SD

1.16

1.54

1.22

 

1.78

1.61

1.73

 

 Range

0.2–9.0

0.3–7.2

 

 

0.3–13.9

0.5–9.5

 

 

Biomarker

ER

 

 

 

0.490

 

 

 

0.137

 Neg

17 (94.4)

1 (5.6)

18

 

36 (85.7)

6 (14.3)

42

 

 Pos

386 (89.4)

46 (10.6)

432

 

251 (75.4)

82 (24.6)

333

 

 Total

403 (89.6)

47 (10.4)

450

 

287 (76.5)

88 (23.5)

375

 

 P63

 

 

 

0.488

 

 

 

0.346

 Neg

396 (89.6)

46 (10.4)

442

 

271 (77.0)

81 (23.0)

352

 

 Pos

5 (83.3)

1 (16.7)

6

 

15 (68.2)

7 (31.8)

22

 

 Total

401 (89.5)

47 (10.5)

448

 

286 (76.5)

88 (23.5)

374

 

CK5/6

 

 

 

0.664

 

 

 

0.829

 Neg

389 (89.6)

45 (10.4)

434

 

267 (76.3)

83 (23.7)

350

 

 Pos

13 (86.7)

2 (13.3)

15

 

18 (78.3)

5 (21.7)

23

 

 Total

402 (89.5)

47 (10.5)

449

 

285 (76.4)

88 (23.6)

373

 

CK14

 

 

 

0.406

 

 

 

0.654

 Neg

387 (89.8)

44 (10.2)

431

 

272 (76.4)

84 (23.6)

356

 

 Pos

14 (82.4)

3 (17.6)

17

 

13 (81.3)

3 (18.8)

16

 

 Total

401 (89.5)

47 (10.5)

448

 

285 (76.6)

87 (23.4)

372

 

P-cadherin

 

 

 

0.028

 

 

 

0.641

 Neg

378 (90.4)

40 (9.6)

418

 

223 (76.9)

67 (23.1)

290

 

 Pos

20 (76.9)

6 (23.1)

26

 

58 (74.7)

20 (25.6)

78

 

 Total

398 (89.6)

46 (10.4)

444

 

281 (76.4)

87 (23.6)

368

 

CG

 

 

 

0.515

 

 

 

0.003

 Neg

377 (90.0)

42 (10.0)

419

 

272 (77.9)

77 (22.1)

349

 

 Pos

24 (85.7)

4 (14.3)

28

 

11 (50.0)

11 (50.0)

22

 

 Total

401 (89.7)

46 (10.3)

447

 

283 (76.3)

88 (23.7)

371

 

SYN

 

 

 

0.009

 

 

 

0.030

 Neg

347 (91.1)

34 (8.9)

383

 

250 (78.4)

69 (21.6)

319

 

 Pos

54 (80.6)

13 (19.4)

67

 

35 (64.8)

19 (35.2)

54

 

 Total

403 (89.6)

47 (10.4)

450

 

285 (76.4)

88 (23.6)

373

 

Sox2

 

 

 

0.034

 

 

 

0.313

 Neg

159 (88.8)

20 (11.2)

179

 

119 (75.8)

38 (24.2)

157

 

 Pos

20 (74.1)

7 (25.9)

27

 

35 (68.6)

16 (31.4)

51

 

 Total

179 (86.9)

27 (13.1)

206

 

154 (74.0)

54 (26.0)

208

 

Bold: statistically significant

Further analysis basing on the different Lum subtypes revealed that FGFR1 correlated with the high pN (p = 0.023), pT stages (p = 0.003), large tumor size (p = 0.005), the presence of LVI (p = 0.010), p-cadherin (p = 0.028), SYN (p = 0.009) and SOX2 (p = 0.034) expression in Lum A subtype only. There was no significant correlations with any clinicopathological features and most biomarkers (except for CG (p = 0.003) and SYN (p = 0.030)) in Lum B subtype (Table 3).

Relationship of FGFR1 expression with patient outcome in different molecular breast cancer subtypes

Follow-up data were available in 944 cases with a mean follow-up duration of 65.8 months (1–210 months). Overall, FGFR1 expression was associated with poor DFS (log- rank = 4.104, p = 0.043) but not OS (log- rank = 1.720, p = 0.190) (Figure 2). The associations with poor outcome were mainly observed in Lum cancers (DFS: log-rank = 8.939, p = 0.003; OS: log-rank = 4.211, p = 0.040) but not in non-Lum cancers (DFS: log-rank = 0.365, p = 0.546; OS: log-rank = 0.739, p = 0.390) (Figure 2).

Kaplan-Meier analysis of DFS and OS in overall, non-liminal and luminal cancers.

Figure 2: Kaplan-Meier analysis of DFS and OS in overall, non-liminal and luminal cancers.

In fact, when subtypes of Lum cancers were analyzed, the poor DFS (log-rank = 10.951, p = 0.001) in FGFR1-expressing cancers was only observed in Lum A cancers, but not in Lum B cancers with or without FGFR1 expression (log-rank = 0.268, p = 0.605). The worse DFS in FGFR1 expressing Lum A cancers was comparable to that of luminal B cancers (compared to FGFR1-expressing luminal B: log-rank = 0.324, p = 0.569; FGFR1 negative luminal B: log-rank = 0.056, p = 0.812) (Figure 3). Multivariate cox regression analysis on DFS also showed that FGFR1 expression in different luminal subtypes together with grade, pT and pN stages were independent prognostic factor in Lum cancers (Lum A FGFR1 neg as reference: Lum A FGFR1 pos: HR = 3.341, p = 0.008; Lum B FGFR1 neg: HR = 2.789, p = 0.001; Lum B FGFR1 pos: HR = 2.500, p = 0.013) (Table 4).

Kaplan-Meier analysis of DFS according to luminal subtypes and FGFR1 expression.

Figure 3: Kaplan-Meier analysis of DFS according to luminal subtypes and FGFR1 expression.

Table 4: Multivariate cox regression analysis for DFS in luminal cancers

 

p-value

HR

95.0% CI

 

 

Lower

Upper

Initial step

Grade

0.009

1.711

1.142

2.563

age

0.885

1.001

0.982

1.021

LVI

0.185

1.424

0.844

2.405

ER

0.232

0.659

0.332

1.306

PR

0.128

0.624

0.340

1.145

pT

< 0.001

2.140

1.418

3.229

pN

< 0.001

1.656

1.302

2.106

Lum A FGFR neg (ref)

0.026

 

 

 

Lum B FGFR neg

0.014

2.270

1.182

4.358

Lum A FGFR pos

0.010

3.235

1.318

7.941

Lum B FGFR pos

0.022

2.410

1.132

5.131

Final step

Grade

0.006

1.722

1.165

2.546

pT

< 0.001

2.207

1.474

3.304

pN

< 0.001

1.808

1.454

2.249

Lum A FGFR neg (ref)

0.005

 

 

 

Lum B FGFR neg

0.001

2.789

1.538

5.058

Lum A FGFR pos

0.008

3.341

1.372

8.136

Lum B FGFR pos

0.013

2.500

1.209

5.173

DISCUSSION

There are ongoing interests for FGFR as a prognostic marker and treatment target in breast cancer [18]. However, most studies focuses mainly on its gene amplification [3, 810, 12]. The FGFR amplicon is complex, composing of several candidate oncogenes which may drive cancer development [19]. In fact, while high FGFR1 protein expression was related to gene amplification, the reverse may not be true [10, 12, 20, 21]. Therefore, this study was designed to investigate FGFR1 protein expression in a large cohort of breast cancers by IHC staining. The relationship of FGFR1 expression with multiple relevant clinicopathologic features, tumor biomarker panels as well as the prognostic value in different molecular subtypes of breast cancer was investigated. The overall FGFR1 expression rate in breast cancer was 14.3%, occurring predominantly in Lum B cancers (24.9%). This observation was concordant with its reported gene amplification [10]. Little has been reported regarding the clinicopathologic and biomarker association of FGFR1 protein expression in breast cancer. One study that analyzed FGFR1 amplification by FISH on TMA did not demonstrate any association with histologic parameters, including grade, size, nodal status, vascular invasion or a number of biomarkers [3]. We observed significant correlation of FGFR1 expression with high tumor pN, pT stages, large tumor size, and increased expression of several biomarkers (ER, Ki67, P63, CG, SYN and SOX2). Its positive association with ER and Ki67 expression corroborated its prevalence in Lum B cancer subtype. FGFR signaling is one of the most common pathways implicated in controlling stemness [22]. Here, we observed a positive association of FGFR1 with the transcriptional factor SOX2 with neural stem cell renewal [23], and particularly with neuroendocrine differentiation in breast cancer.

Previously, we reported the specific association of SOX2 with expression of hormonal receptor and neuroendocrine differentiation in breast cancers [20]. Given the role of SOX2 in neural stem cell renewal, its expression have been reported in other types of neuroendocrine tumor [2123]. Of interest, FGFR1 expression was also related to cancers with neuroendocrine differentiation. High copy number gain of FGFR1 was detected in pulmonary neuroendocrine tumors [24]. Ectopic expression of FGFR1 in mouse prostate cancer model was shown to associate with the acquisition of an aggressive neuroendocrine phenotype and metastasis [25]. However, the underlying mechanism for these observations was not completely clear. Notably, previous study has shown that blocking FGF signaling with FGFR1 inhibitor can reduce the level of SOX2 expression [26]. FGF signaling could control osteoblast differentiation through induction of SOX2 and regulation of the Wnt-β-catenin pathway [27]. Together with the current findings, we postulated that FGFR1 expression could regulate SOX2 expression and subsequently neuroendocrine differentiation in breast cancer.

Another interesting finding was the association of FGFR1 expression with poor outcome in Lum cancer. We found that FGFR1 expression was predominantly in luminal cancers, in particularly Lum B cancers. Concordantly, a significant association with the related biomarkers can be demonstrated. A significant association of FGFR1 with ER and Ki67 in the overall cohort while significant correlation with low PR and high Ki67 as well as a near significance with HER in luminal cancers were observed. Although there was a lack of association with PR and HER2 in the overall cohort, both luminal B and non-luminal cancers exhibited low PR and high HER2 expression. High FGFR1 was in the former and low was in the latter subtypes. The opposite relationship of FGFR1 with different subtypes could nullify its association with PR and HER2. By contrast, FGFR1 expression associated with Ki67 regardless of subtypes. FGFR1 activation has shown to induce proliferation in breast cancer [28]; thus its expression could have a direct cause-effect on increased Ki67 rather than merely an epiphenomenon. FGFR1 amplification was shown to be associated with poor outcome in hormone receptor-positive breast cancer and resistance to endocrine therapy [3, 9, 10]. Interestingly, here, we showed that its prognostic impact mainly associated with Lum A cancers. The FGFR1 expression in Lum A subtype was shown to be an independent prognostic feature. It had a similar hazard ratio as luminal B cancers for DFS. In addition, it correlated with poor prognostic features positively, including LVI, high pT, pN and P-cadherin expression mainly in Lum A. Lum B cancers are genetically and genomically altered to a greater extent than Lum A cancers [29]. Apart from FGFR1, other genes overexpressed in Lum B have also shown to affect cancer growth and patients outcome [30]. It appeared that multiple drivers could be involved in Lum B cancers. Lum A subtype is a diverse and the most frequent subtype in breast cancer. Within this subtype, four major subgroups, namely 1p/16q, copy number quiet, chr8-associated and copy number high (CNH), have been identified recently by genomic analysis [31]. CNH subgroup has shown to have poor prognosis. However, the prognostication in other subgroups, including Chr8-associated subgroup which associated with focal FGFR1 amplification, has not been reported. Our data showing poor outcome of FGFR1 expressing Lum A cancers may implicate the poor prognostication also for this Chr8-associated subgroup [31]. In the Chr8-associated subgroup, MAP3K1 mutation was frequently found. FGFR signaling can cause persistent MAPK activation, subsequently leading to tamoxifen resistance [4]. It could contribute to the poor outcome in the FGFR1 expressing Lum A cancers. Our results may be useful in further stratification and thus management of tamoxifen resistant Lum A cancers.

In summary, FGFR1 protein expression was shown to be associated with Lum cancers. Although it is more prevalent in Lum B subtype, its expression showed adverse prognostication significance in only Lum A cancers. FGFR-expressing Lum A cancers showed a similar outcome as Lum B cancers, suggesting its role in identifying the aggressive subset of the heterogeneous Lum A cancers. Agents targeting FGFR pathway are currently actively explored as breast cancer treatment, which could be especially relevant for tamoxifen resistant Lum A cancer.

MATERIALS AND METHODS

Patients and database

The histologic files of the 3 involved institutions were searched for breast carcinoma over a period of 4 (2002–2005), 7 (2003–2009), and 2 (2003–2004) years respectively. All consecutive cases with excision specimens were included. The study was approved by Joint Chinese University of Hong Kong—New Territories East Cluster clinical research ethics committee. All the specimens were routinely processed and stained with hematoxylin and eosin (H & E). All the slides form all the cases were reviewed, graded (modified Bloom and Richardson) [32], and histotyped (WHO 2012) by two pathologists separately in a blinded manner [33]. Lymphovascular invasion (LVI) and fibrotic focus (FF) were also evaluated as present or absent, as previously reported criteria [2]. Patients’ age, tumor size, lymph node involvement, pN stage, pT stage, and outcome data were retrieved from the medical records. Overall survival (OS) was defined as the time interval from the date of initial diagnosis to the date of breast cancer related death. Disease free survival (DFS) was defined as the duration from the date of initial diagnosis to the first detection of breast cancer specific relapse or death. If no relapse or death observed, the survival time was censored at the last follow up visit.

Tissue microarray (TMA) construction and immunohistochemistry

TMAs containing representative tumor areas were constructed with duplicated 0.6-mm cores as previously described [18]. The TMAs were assembled with a tissue arrayer (Beecher Instruments, Silver Springs, MD). One section from each TMA was stained with H&E and reviewed to confirm the presence of representative tumors. Immunohistochemical (IHC) staining was performed on the TMA with the selected antibodies using Ultraview Universal DAB Detection Kit (Ventana, Tucson, AZ) after deparaffinization, rehydration, and antigen retrieval of the slides. All slides were counterstained with hematoxylin. The TMA slides were assessed for the staining intensity, and the actual percentage of stained cells in the nucleus, cytoplasm, or membrane according to different antibodies by 2 of the authors blinded to the clinical information and the staining results of other markers. For FGFR1 staining, the reactivity was assessed both membranous and cytoplasmic. The staining was considered positive when unequivocal staining was detected in at least 1% of tumor cells [13]. Several groups of other markers were examined, including basal markers (EGFR, c-kit, p63, CK5/6 and CK14), markers related to stem cell features (SOX2 and p-cadherin), neuroendocrine markers (chromogranin (CG) and synaptophysin (SYN)), hormonal receptors (ER and PR) and other common cancer markers (HER2 and Ki67). The staining was considered positive when there was moderate or strong immune reactivity at the appropriate location over the cut-off point. Any discordant results were resolved by reading the slides at a multi-head microscope and discussed. Further details of the IHC stainings and their assessment are shown in Supplementary Table S1.

In addition, all cases were also classified into molecular subtypes basing on IHC surrogates, listed as follows [34, 35].

Luminal A (Lum A) (ER+, PR ≥ 20%, HER2−, Ki67 < 20%),

Luminal B (Lum B) (ER+, PR < 20% and/or HER2+ and /or Ki67 ≥ 20%), HER2-overexpressed (HER2-OE) (ER−, PR−, HER2+),

Basal-like breast cancer (BLBC) (ER−, PR−, HER2−, CK5/6+, and EGFR+),

Unclassified (5NP) (ER−, PR, HER2−, CK5/6−, EGFR−).

Statistical analysis

Statistical analysis was performed using SPSS for Windows, Version 21. For association between FGFR1 IHC staining and clinic-pathologic parameters, χ2 and Fisher exact tests were applied as appropriate. Survival analysis was accomplished using Kaplan–Meier method and comparison between groups was done using log-rank statistics. Multivariate cox regression analysis was performed to survival hazard ratios (HR) and corresponding 95% confidence intervals (95% CI) using the backwald method. Statistical significance was defined as p < 0.05.

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

REFERENCES

1. Network TCGA. Comprehensive molecular portraits of human breast tumours. Nature. 2012; 490:61–70.

2. Dienstmann R, Rodon J, Prat A, Perez-Garcia J, Adamo B, Felip E, Cortes J, Iafrate AJ, Nuciforo P, Tabernero J. Genomic aberrations in the FGFR pathway: opportunities for targeted therapies in solid tumors. Ann Oncol. 2014; 25:552–563.

3. Elbauomy Elsheikh S, Green AR, Lambros MB, Turner NC, Grainge MJ, Powe D, Ellis IO, Reis-Filho JS. FGFR1 amplification in breast carcinomas: a chromogenic in situ hybridisation analysis. Breast Cancer Res. 2007; 9:R23.

4. Turner N, Grose R. Fibroblast growth factor signalling: from development to cancer. Nat Rev Cancer. 2010; 10:116–129.

5. Pond AC, Bin X, Batts T, Roarty K, Hilsenbeck S, Rosen JM. Fibroblast growth factor receptor signaling is essential for normal mammary gland development and stem cell function. Stem Cells. 2013; 31:178–189.

6. Heinzle C, Sutterluty H, Grusch M, Grasl-Kraupp B, Berger W, Marian B. Targeting fibroblast-growth-factor-receptor-dependent signaling for cancer therapy. Expert Opin Ther Targets. 2011; 15:829–846.

7. Korc M, Friesel RE. The role of fibroblast growth factors in tumor growth. Curr Cancer Drug Targets. 2009; 9:639–651.

8. Gru AA, Allred DC. FGFR1 amplification and the progression of non-invasive to invasive breast cancer. Breast Cancer Res. 2012; 14:116.

9. Jang M, Kim E, Choi Y, Lee H, Kim Y, Kim J, Kang E, Kim SW, Kim I, Park S. FGFR1 is amplified during the progression of in situ to invasive breast carcinoma. Breast Cancer Res. 2012; 14:R115.

10. Turner N, Pearson A, Sharpe R, Lambros M, Geyer F, Lopez-Garcia MA, Natrajan R, Marchio C, Iorns E, Mackay A, Gillett C, Grigoriadis A, Tutt A, et al. FGFR1 amplification drives endocrine therapy resistance and is a therapeutic target in breast cancer. Cancer Res. 2010; 70:2085–2094.

11. Cuny M, Kramar A, Courjal F, Johannsdottir V, Iacopetta B, Fontaine H, Grenier J, Culine S, Theillet C. Relating genotype and phenotype in breast cancer: an analysis of the prognostic significance of amplification at eight different genes or loci and of p53 mutations. Cancer Res. 2000; 60:1077–1083.

12. Lee HJ, Seo AN, Park SY, Kim JY, Park JY, Yu JH, Ahn JH, Gong G. Low prognostic implication of fibroblast growth factor family activation in triple-negative breast cancer subsets. Ann Surg Oncol. 2014; 21:1561–1568.

13. Cheng CL, Thike AA, Tan SY, Chua PJ, Bay BH, Tan PH. Expression of FGFR1 is an independent prognostic factor in triple-negative breast cancer. Breast Cancer Res Treat. 2015; 151:99–111.

14. Andre F, Cortes J. Rationale for targeting fibroblast growth factor receptor signaling in breast cancer. Breast Cancer Res Treat. 2015; 150:1–8.

15. Gelsi-Boyer V, Orsetti B, Cervera N, Finetti P, Sircoulomb F, Rouge C, Lasorsa L, Letessier A, Ginestier C, Monville F, Esteyries S, Adelaide J, Esterni B, et al. Comprehensive profiling of 8p11-12 amplification in breast cancer. Mol Cancer Res. 2005; 3:655–667.

16. Ray ME, Yang ZQ, Albertson D, Kleer CG, Washburn JG, Macoska JA, Ethier SP. Genomic and expression analysis of the 8p11-12 amplicon in human breast cancer cell lines. Cancer Res. 2004; 64:40–47.

17. Reis-Filho JS, Simpson PT, Turner NC, Lambros MB, Jones C, Mackay A, Grigoriadis A, Sarrio D, Savage K, Dexter T, Iravani M, Fenwick K, Weber B, et al. FGFR1 emerges as a potential therapeutic target for lobular breast carcinomas. Clin Cancer Res. 2006; 12:6652–6662.

18. Dvorak P, Dvorakova D, Hampl A. Fibroblast growth factor signaling in embryonic and cancer stem cells. FEBS Lett. 2006; 580:2869–2874.

19. Episkopou V. SOX2 functions in adult neural stem cells. Trends Neurosci. 2005; 28:219–221.

20. Huang YH, Luo MH, Ni YB, Tsang JY, Chan SK, Lui PC, Yu AM, Tan PH and Tse GM. Increased SOX2 expression in less differentiated breast carcinomas and their lymph node metastases. Histopathology. 2014; 64:494–503.

21. Yu X, Cates JM, Morrissey C, You C, Grabowska MM, Zhang J, DeGraff DJ, Strand DW, Franco OE, Lin-Tsai O, Hayward SW, Matusik RJ. SOX2 expression in the developing, adult, as well as, diseased prostate. Prostate Cancer Prostatic Dis. 2014; 17:301–309.

22. Sholl LM, Long KB, Hornick JL. Sox2 expression in pulmonary non-small cell and neuroendocrine carcinomas. Appl Immunohistochem Mol Morphol. 2010; 18:55–61.

23. Laga AC, Lai CY, Zhan Q, Huang SJ, Velazquez EF, Yang Q, Hsu MY, Murphy GF. Expression of the embryonic stem cell transcription factor SOX2 in human skin: relevance to melanocyte and merkel cell biology. Am J Pathol. 2010; 176:903–913.

24. Voortman J, Lee JH, Killian JK, Suuriniemi M, Wang Y, Lucchi M, Smith WI, Jr., Meltzer P, Giaccone G. Array comparative genomic hybridization-based characterization of genetic alterations in pulmonary neuroendocrine tumors. Proc Natl Acad Sci USA. 2010; 107:13040–13045.

25. Yang F, Gao Y, Geng J, Qu D, Han Q, Qi J, Chen G. Elevated expression of SOX2 and FGFR1 in correlation with poor prognosis in patients with small cell lung cancer. Int J Clin Exp Pathol. 2013; 6:2846–2854.

26. Millimaki BB, Sweet EM, Riley BB. Sox2 is required for maintenance and regeneration, but not initial development, of hair cells in the zebrafish inner ear. Dev Biol. 2010; 338:262–269.

27. Mansukhani A, Ambrosetti D, Holmes G, Cornivelli L, Basilico C. Sox2 induction by FGF and FGFR2 activating mutations inhibits Wnt signaling and osteoblast differentiation. J Cell Biol. 2005; 168:1065–1076.

28. Welm BE, Freeman KW, Chen M, Contreras A, Spencer DM, Rosen JM. Inducible dimerization of FGFR1: development of a mouse model to analyze progressive transformation of the mammary gland. J Cell Biol. 2002; 157:703–714.

29. Creighton CJ. The molecular profile of luminal B breast cancer. Biologics. 2012; 6:289–297.

30. Karn T, Ruckhaberle E, Hanker L, Muller V, Schmidt M, Solbach C, Gatje R, Gehrmann M, Holtrich U, Kaufmann M, Rody A. Gene expression profiling of luminal B breast cancers reveals NHERF1 as a new marker of endocrine resistance. Breast Cancer Res Treat. 2011; 130:409–420.

31. Ciriello G, Sinha R, Hoadley KA, Jacobsen AS, Reva B, Perou CM, Sander C and Schultz N. The molecular diversity of Luminal A breast tumors. Breast Cancer Res Treat. 2013; 141:409–420.

32. Elston CW, Ellis IO. Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology. 1991; 19:403–410.

33. Lakhani SR, Ellis IO, Schnitt SJ, Tan PH and van de Vijver MJ. World Health Organisation classification of tumors of the Breast. (Lyon: IARC Press). (2012).

34. Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B and Senn HJ. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol. 2013; 24:2206–2223.

35. Coates AS, Winer EP, Goldhirsch A, Gelber RD, Gnant M, Piccart-Gebhart M, Thurlimann B, Senn HJ. -Tailoring therapies-improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol. 2015; 26:1533–1546.


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