RESEARCH ARTICLE
The Characteristics of Breast Cancer Subtypes: Implications for Treatment Guidelines and Individualized Treatment Strategies in China Shan Zheng, PhD,* Qing-Kun Song, PhD,w Yu Ren, PhD,z Wei-Liang Feng, MS,y Ya-Nan Kong, MS,8 Rong Huang, MS,wz Feng Xu, PhD,# Jing Li, PhD,w Bao-Ning Zhang, BS,** Jin-Hu Fan, BS,w Jian-Jun He, PhD,z and You-Lin Qiao, PhDw
Abstract: This study aimed at investigating the characteristics of invasive breast cancer among molecular subtypes. Patients with invasive breast cancer, with complete information on the expressions of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 (HER2), were recruited. w2 tests and an unconditional logistic regression model were used for statistical analysis. The percentages of luminal A, luminal B, HER2/neu, and triple-negative subtypes were 54.2% (1639/3021), 14.0% (422/3021), 8.9% (269/3021), and 22.9% (691/3021), respectively. Differences among molecular subtypes (P < 0.05) in tumor size, stage, pathologic type, and lymph node status were observed. The HER2/neu, luminal B, and triple-negative subtypes were more aggressive compared with the luminal A subtype in tumor stage, lymph node status, or pathologic type (P < 0.05), when the findings were adjusted for age. Molecular subtypes were distributed differently between both age groups and regional groups on the basis of the socioeconomic status (P < 0.05). In conclusion, luminal A and triple-negative subtypes were the 2 main subtypes of invasive breast cancer in China. The variations of molecular subtypes in pathology, age, and regional distribution
Received for publication February 3, 2013; accepted July 5, 2013. From the Departments of *Pathology; wCancer Epidemiology; **Center of Breast Disease, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing; zDepartment of Oncosurgery, the First Affiliated Hospital of Medical College, Xi’an Jiaotong University, Xi’an; yDepartment of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou; 8Department of Breast Oncology, Sun Yat-Sen University Cancer Center, Guangzhou; zDepartment of Epidemiology, West China School of Public Health, Sichuan University, Chengdu, Sichuan; and #Department of Breast-thyroid Surgery, Xiangya Second Hospital, Central South University, Changsha, China. S.Z. and Q.-K.S. contributed equally. S.Z. and Q.-K.S. helped analyze and interpret the data and drafted the initial manuscript. Y.R. and W.-L.F. helped design the study. Y.-N.K., R.H., and J.L. helped with the data management and analysis. F.X. and B.-N.Z. helped in local data collection. J.-H.F. and J.-J.H. did critical revisions of the manuscript. Y.-L.Q. was the PI of this study and helped design the study. The authors declare no conflict of interest. Reprints: Jin-Hu Fan, BS, Department of Cancer Epidemiology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 17 South Panjiayuan Lane, Beijing 100021, China (e-mail: [email protected]). Copyright r 2013 by Lippincott Williams & Wilkins
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may give some suggestions for updating treatment guidelines and individualized treatment strategies in China. Key Words: breast carcinoma, subtype, age, regional socioeconomic status, nationwide (Appl Immunohistochem Mol Morphol 2014;22:383–389)
B
reast cancer is one of the diseases that seriously threaten women’s health. In 2008, breast cancer accounted for 23% (1.38 million) of total cancer cases and 14% (458,400) of cancer deaths worldwide.1 It is also an age-related disease, which is influenced by the socioeconomic status (SES). Breast cancers vary in both their biology and their response to specific therapies. In landmark studies conducted by Perou et al,2 molecular subtypes of breast tumors had different backgrounds of gene expression profiling. These discoveries are already starting to have an impact on the classification and treatment for breast cancer.3 Today, the results of gene expression profiling have been applied to the management of breast cancer in the developed countries. However, it has not been the same in the developing countries, where the exploration of prognostic factors needs to be inexpensive and easy to replicate.1,4 Gene expression profiling is expensive and largely limited to fresh or frozen samples.5 These factors hold back its application in routine diagnostic practice in these countries. To develop a molecular classification of clinical significance, investigators have explored immunohistochemical (IHC) biomarkers surrogated for gene expression profiling. These IHC-based molecular classification systems, derived from the data of gene expression profiling, were correlated with therapy decision and were able to provide additional prognostic information. Although IHC can be used routinely and cheaply to monitor confirmed biomarkers, this process cannot hunt for new biomarkers. One of the IHC-based molecular classification systems—the combination test in the expressions of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2)—has been generally accepted and can now be taken into account in treatment strategies.6–8
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Breast cancer is currently the most common malignancy and the sixth leading cause of cancer death in Chinese female patients.9,10 The incidence and mortality rates show a rising trend and present significant age and regional differences.9–11 Our previous studies had established a methodology for random sampling of female breast cancer patients across China from 1999 to 2008 and introduced the pathologic characteristics of Chinese female patients.12,13 In the present study, we investigated the pathologic characteristics of different molecular subtypes in invasive breast carcinoma determined by IHC and described the distribution among age and regional socioeconomic groups. We hoped these investigations might yield some suggestions for updating treatment guidelines and individualized treatment strategies for breast cancer in Chinese female patients. We also hoped these might provide suggestions for treating female patients with breast cancer in low-income and middle-income countries (LMCs) where breast cancer may be more harmful because of the late stage at diagnosis, inadequate pain relief, and inadequate palliative care.14
MATERIALS AND METHODS Institutional Review Board This study was a constitutive part of a multicenter retrospective hospital-based research that was approved by the Cancer Foundation of China Institutional Review Board.12 Patient consent was not required for this study as there were no risks anticipated to the participants of the study. All data were stripped of any patient identifiers.
Patient Selection Chinese women with primary breast cancer were randomly selected from 7 tertiary hospitals or medical centers in 7 traditional districts (North China, Northeast China, Northwest China, Central China, East China, South China, and Southwest China). All patients enrolled in these series studies met 3 key inclusion criteria: (i) primary breast cancer with pathologic confirmation; (ii) in-patient admission date within the selected month in the hospital, and (iii) received or receiving treatment (surgery, medical oncology, and radiotherapy) for breast cancer in the hospital. The enrolment scheme was to recruit patients admitted in alternating months from year to year in each hospital or medical center. In-patients in January and February were excluded because during this period the Chinese celebrate the traditional Spring Festival and individuals seldom visit hospitals during this time. For example, in a particular hospital, in the year 1999 all of the patients admitted in March were enrolled in the study, in 2000 all of the patients admitted in April were enrolled, and so on. In each selected month, if in-patient admissions were 2 levels were analyzed by the Cochran-Armitage testing. Only the pathologic characteristics that showed a significant level in w2 or CochranArmitage testing were included in the unconditional logistic regression model with the adjustment of age, whereas luminal A was set as the reference group. All of the tests were 2-tailed tests with a significance level of 0.05.
RESULTS A total of 4211 cases were collected from 7 districts during 1999 to 2008. There were 3021 patients with invasive breast cancer recruited in this study whose ER, PR, and HER2 information was acquired. Table 1 gives detailed demographics and pathologic information. The mean age was 48.7 years, ranging from 22 to 86 years. There were 541 (17.9%) cases in the age group of 39 years or below, 1146 (37.9%) cases in the age group of 40 to 49 years, and 1334 (44.2%) cases in the age group of r
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1013 (61.8) 626 (38.2)
414 (28.2) 924 (63.1) 127 (8.7) 174
315 (21.2) 812 (54.7) 326 (22.0) 32 (2.1) 154
1482 (90.4) 74 (4.5) 83 (5.1)
813 (51.0) 781 (49.0) 45
458 (56.3) 234 (28.8) 121 (14.9)
47 (3.3) 1360 (96.7) 232
1396 (85.2) 243 (14.8)
1411 (86.1) 228 (13.9)
0 (0.0) 1639 (100.0)
(17.8) (57.9) (22.5) (1.8) 40
47.9 ± 9.5, 422
48.9 ± 10.5, 1639
Luminal B (n = 422)
(10.5) (66.1) (22.2) (1.2) 21
269 (100.0) 0 (0.0)
(19.7) (57.2) (21.0) (2.1) 81
0 (0.0) 691 (100.0)
0 (0.0) 691 (100.0)
0 (0.0) 691 (100.0)
19 (3.2) 566 (96.8) 106
173 (56.5) 81 (26.5) 52 (17.0)
306 (45.5) 367 (54.5) 18
619 (89.5) 17 (2.5) 55 (8.0)
120 349 128 13
185 (30.0) 358 (58.1) 73 (11.9) 75
421 (60.9) 270 (39.1)
48.2 ± 10.2, 691
Triple Negative (n = 691)
< 0.001
< 0.001
< 0.001
0.970
0.035
0.003
0.001
0.020
< 0.001
0.060 0.056
P*
691 (22.9) 2330 (77.1)
1772 (58.7) 1249 (41.3)
1747 (57.8) 1274 (42.2)
84 (3.3) 2490 (96.7) 447
831 (55.7) 406 (27.2) 255 (17.1)
1492 (51.6) 1457 (49.4) 72
2748 (91.0) 110 (3.6) 163 (5.4)
529 (19.4) 1546 (56.8) 595 (21.8) 55 (2.0) 296
831 (30.7) 1624 (60.0) 250 (9.3) 316
1865 (61.7) 1156 (38.3)
48.7 ± 10.3, 3021
All Cases (n = 3021)
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0 (0.0) 269 (100.0)
0 (0.0) 269 (100.0)
8 (3.5) 223 (96.5) 38
78 (57.8) 25 (18.5) 32 (23.7)
135 (51.1) 129 (48.9) 5
250 (93.0) 6 (2.2) 13 (4.8)
26 164 55 3
72 (29.8) 145 (59.9) 25 (10.3) 27
151 (56.1) 118 (43.9)
49.8 ± 10.2, 269
HER2+/neu (n = 269)
*Comparing the 4 subgroups (luminal A, luminal B, HER2+/neu, and triple negative). Age was analyzed by analysis of variance tests. The differences of categorical variables were estimated by w2 tests, and the ordinal variables with >2 levels were analyzed by the Cochran-Armitage test. wThese cases were not included in analysis. zOthers include other invasive breast cancer except IDC and ILC. + indicates positive; , negative; AJCC, American Joint Committee on Cancer; ER, estrogen receptor; HER2, human epidermal growth factor receptor-2; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; LNM, lymph node metastasis; PR, progesterone receptor.
Age (mean ± SD, n) Menopausal status Premenopausal Postmenopausal Tumor size group (cm) r2 > 2-5 >5 Unknownw AJCC stage I II III IV Unknownw Pathologic type IDC ILC Othersz Lymph node status + Unknownw Group of LNM+ 1-3 4-9 Z10 Multifocality + Unknownw ER status + PR status + HER2 status +
Luminal A (n = 1639)
N (%)
TABLE 1. Characteristics of Chinese Female Patients With Invasive Breast Cancer Patients of Different Subtypes
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50 years or above. There were 2008 (66.5%) cases in the high–regional SES group, which included patients from the North, Northeast, East, and South, and 1013 (33.5%) cases were in the low–regional SES group, which included patients from Northwest, Middle, and Southwest.
The Pathologic Characteristics Among Different Molecular Subtypes As shown in Table 1, the percentages of luminal A, luminal B, HER2/neu, and triple-negative subtypes were 54.2% (1639/3021), 14.0% (422/3021), 8.9% (269/3021), and 22.9% (691/3021), respectively. The 4 molecular subtypes had differences in the tumor size group, AJCC stage, pathologic type, lymph node status, and the group of LNM (P < 0.05). However, the mean age, menopausal status, and the rate of multifocality were not different among these subtypes. Luminal A was more common in patients with tumor size >2 to 5 cm and in AJCC stage II (Table 1). The predominant pathologic type of luminal A was invasive ductal carcinoma (IDC) and was more common in the LNM+ group (Table 1). Compared with luminal A and after adjustment for age, luminal B subtype appeared more frequently in the small-tumor group (P < 0.001) and in LNM (P = 0.011); the HER2/neu subtype showed a more advanced AJCC stage (P = 0.001); the triplenegative subtype appeared less frequently in the LNM group (P = 0.015) and was more common in other invasive breast cancers compared with IDC and invasive lobular carcinoma (P < 0.001) (Table 2).
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The Subtype Distribution in Different Age Groups The percentages of breast cancer subtype in the age group of 39 years or below, 40 to 49 year, and 50 years or above at diagnosis were, respectively: 52.9% (286/541), 56.4% (646/1146), and 53.0% (707/1334) for luminal A; 15.7% (85/541), 13.5% (155/1146), and 13.7% (182/1334) for luminal B; 6.1% (33/541), 8.2% (94/1146), and 10.6% (142/1334) for HER2/neu; and 25.3% (137/541), 21.9% (251/1146), and 22.7% (303/1334) for the triple-negative subtype. The differences among age groups were significant (P = 0.022) (Fig. 1).
The Subtype Distribution in Different Regional SES Groups The subtype distribution in different regional SES groups was similar to the distribution in age group. Luminal A and triple negative were the 2 main subtypes in both high–regional SES and low–regional SES groups. The percentages of molecular subtypes in high–regional SES and low–regional SES groups were, respectively: 57.1% (1146/2008) and 48.7% (493/1013) for luminal A; 13.8% (278/2008) and 14.2% (144/1013) for luminal B; 8.3% (166/2008) and 10.1% (103/1013) for HER2/neu; and 20.8% (418/2008) and 27.0% (273/1013) for triplenegative cancer. Subtypes were distributed differently between high–regional SES and low–regional SES groups (P < 0.001) (Fig. 2). Because molecular subtypes had age variation, we stratified the regional SES group data into 2 age groups, below 50 years and 50 years or above, and
TABLE 2. Adjusted Odds Ratio for Patient and Tumor Characteristics for Invasive Breast Cancer Subtypes* HER2+/neu
Luminal B OR (95% CI) Tumor size group r2 cm > 2-5 cm > 5 cm AJCC stage I II III IV Pathologic type IDC ILC Othersw LNM + Group of LNM+ 1-3 4-9 Z10
P
OR (95% CI)
< 0.001 1.00 0.56 (0.44, 0.71) 0.50 (0.31, 0.81)
OR (95% CI)
0.628
0.418
1.00 0.88 (0.71, 1.10) 1.19 (0.84, 1.70) 0.001
0.510
1.00 2.48 (1.58, 3.89) 2.04 (1.22, 3.39) 1.96 (1.54, 7.10) 0.096
1.00 0.66 (0.35, 1.28) 0.52 (0.26, 1.05)
1.00 1.15 (0.89, 1.48) 1.00 (0.74, 1.35) 1.38 (0.62, 3.06) 0.283
< 0.001
1.00 0.48 (0.19, 1.21) 0.89 (0.45, 1.76) 0.011
1.00 1.36 (1.07, 1.71)
1.00 0.53 (0.29, 0.97) 1.86 (1.27, 2.74) 0.745
0.015
1.00 1.05 (0.79, 1.38) 0.215
P 0.160
1.00 0.92 (0.67, 1.26) 1.15 (0.69, 1.94)
1.00 1.25 (0.92, 1.70) 1.21 (0.84, 1.73) 0.68 (0.20, 2.37)
1.00 1.13 (0.79, 1.60) 1.44 (0.96, 2.18)
Triple Negative P
1.00 0.79 (0.65, 0.95) 0.405
0.380
1.00 0.63 (0.38, 1.04) 1.48 (0.91, 2.41)
1.00 0.84 (0.60, 1.18) 1.14 (0.77, 1.68)
*Luminal A as the reference group, adjusting age. wOthers include other invasive breast cancer except IDC and ILC. + indicates positive; , negative; AJCC, American Joint Committee on Cancer; CI, confidence interval; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; LNM, lymph node metastasis; OR, odds ratio.
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100.0 90.0
≤39 years old
80.0 40-49 years old
Percent (%)
70.0
≥50 years old
60.0 50.0 40.0 30.0 20.0 10.0 0.0 Luminal A
Luminal B HER2/neu Molecular Subtype
Triple negative
FIGURE 1. The distribution of molecular subtype with invasive breast cancer in different age groups. White bars represent “the age group of 39 years or below.” Gray bars represent “the age group of 40 to 49 years.” Black bars represent “the age group of 50 years or above.” Luminal A subtype is more common in the age group of 40 to 49 years than in the other 2 age groups. Triple-negative and luminal B subtypes were more common in the age group 39 years or below. HER2/neu subtypes were more common in the age group 50 years or above. There are differences in distribution of molecular subtypes with invasive breast cancer in different age groups (P = 0.022).
the geographic variation was observed in both age groups (data not shown).
DISCUSSION China is one of the representative LMCs and has 7 traditional districts. The districts had different breast cancer burdens.9–11 There were a lot of studies on breast cancer in China. However, the previous researches22–26
FIGURE 2. The distribution of molecular subtypes with invasive breast cancer in different regional SES groups. White bars represent the “high–regional SES group.” Black bars represent the “low–regional SES group.” Luminal A subtype is more common in the high–regional SES group. Triple-negative subtype is more common in the low–regional SES group. There are differences in distribution of molecular subtypes with invasive breast cancer in different regional SES groups (P < 0.001). r
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Characteristics of Breast Cancer Subtypes in China
mainly focused on regions with a high socioeconomic level and breast cancer burden. There were few data about districts with a relatively low socioeconomic level and breast cancer burden. In this study, we described the characteristics of different molecular subtypes of invasive breast carcinoma among the whole population of China. For Chinese female patients, luminal A and triplenegative subtypes were the main subtypes in China. This finding was similar to those in other Eastern Asian countries27–31 but was different from those among the white population.7,32–37 The study showed some new evidence to add to the research of Leong et al38 who focused on the difference between the Asian and Western countries. Although the detail pathologic characteristics of different subtypes were similar to all these studies,22–31 we found 3 interesting phenomena. First, the triple-negative subtype showed less LNM and was more prevalent in invasive breast cancer other than IDC and invasive lobular carcinoma, compared with luminal A subtype (P < 0.05). This result may reflect the heterogeneity of the triple-negative subtype. The triple-negative subtype included 4 main subgroups: claudin-low, immune system related, DNA repair genes related, and androgen signaling.39 This result may reflect the combined action of different main subgroups in the triple-negative subtype. This also reminded us that we should evaluate the biological behavior of a given subtype comprehensively. Second, compared with the results of the previous studies from China,22–26 our results showed a little harmful behavior in pathologic characteristics. The previous studies focused on populations in districts with a relatively high socioeconomic level and breast cancer burden.22–26 However, our data included districts with a relatively low socioeconomic level and breast cancer burden. The result indicated that the socioeconomic level and burden of breast cancer may influence the pathologic characteristics. Therefore, it was meaningful to carry out a populationbased study including all 7 districts of China. Third, the lack of a well-accepted definition of molecular subtypes may to some degree affect the comparability between the previous studies and ours. As there were obvious differences in pathologic characteristics of breast cancer between the white and the Chinese,13 it was necessary to establish the definition of molecular subtypes suitable for Chinese. In this study, we divided our data into 3 age groups: 39 years or below, 40 to 49 years, and 50 years or above at diagnosis according to the data from GLOBCAN, 2008.20 The distribution of the molecular subtypes was different from other studies, except for the triple-negative subtype.40–42 Our results were similar to the result of Lin et al23 but were somewhat different from those of Su et al.22 On the one hand, these phenomena may reflect the difference between the West and Asia38; on the other hand, the diversities in the urbanization level may be one of the reasons for these phenomena.43 These phenomena also reminded us that we should take into account the age distribution of molecular subtypes for the individualized treatment strategies. www.appliedimmunohist.com |
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At last, we described the regional distribution of molecular subtypes. We divided 7 districts into 2 groups, according to the regional SES. SES may have a major role in producing prognostic differences in breast cancer behavior as it may reflect the level of family income, education, and health care insurance. In addition, there is some epidemiological evidence that low SES is associated with breast cancers that possess the biomarkers of aggressive tumor behavior.44,45 Further, our previous study also had showed that SES may influence the AJCC stage.21 Therefore, we thought that SES may influence the regional distribution of molecular subtypes. We found that luminal A was more common in high–regional SES groups, whereas the triple-negative subtype was prevalent in low–regional SES groups, independent of age. Our results confirmed that SES may influence the expression of biomarkers. The reasons are not clear. One possible explanation is that a low SES may result in obesity, which may induce the alterations in the ER environment.46 Our results suggest 2 possibilities. First, the emphasis on treatment modality may be different in different SES regions. Second, these phenomena should be interpreted cautiously, as they need a more thorough investigation in future population-based study. There are some potential limitations in this study. We selected patients from 7 tertiary hospitals in an effort to represent the whole population. Although this process might not have resulted in the degree of representation we were hoping for, we selected these tertiary hospitals for 2 reasons. First, patients in China preferred to go to the higher-ranked hospitals, so we thought these hospitals might give us a good sampling of patients with breast cancer in China. Second, these hospitals had the ability to offer comprehensive therapy for cancers and to keep complete records of pathologic tests. The pathologic reports of all the selected hospitals are standardized according to the national standard and mutual recognition, which minimize interhospital variations. Meanwhile, we defined breast subtype approximated by ER, PR, and HER2, which may introduce some misclassification of luminal B group as luminal A and of an as-yet unclassified group as triple negative.39,47 In addition, fluorescence in situ hybridization was not accepted widely during 1999 to 2008 because of its high cost, and therefore the data of HER2 amplification in fluorescence in situ hybridization could not be obtained, which may also have led to some misclassification of molecular subtypes. However, this definition offers several advantages as these 3 markers were routinely used in pathology laboratories in China during 1999 to 2008. All the selected hospitals had established the staining patterns, evaluation protocols, and quality control according to the national standard, which guaranteed the reliability of our results. So, this method appears to have the most clinical applicability in China. These results will give some suggestions for the population-based study representing the whole population of China. In conclusion, luminal A and triple-negative subtypes were the 2 main subtypes of invasive breast cancer
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in China. There were some differences in the characteristics among different subtypes in pathology, age, and regional distribution. As the introduction of molecular techniques has defined a new role for pathology that includes the treatment of breast cancer, we think our results may give some suggestions for updating the treatment guidelines and individualized treatment strategies in China. The implications were listed as follows: (1) Molecular subtypes showed different pathologic characteristics, which may indicate subtype-specific treatments. Early detection may be helpful in the treatment of luminal A subtype. Prevention of early LNM+ may be helpful in the treatment of luminal B subtype. The treatment of later-stage patients may be one of the emphases in the treatment of HER2/neu subtype. LNM+ may not be a key point of the treatment of the triple-negative subtype. (2) The age-related and SES-related regional distributions should be taken into account. ACKNOWLEDGMENTS The authors thank Cancer Foundation of China for initiating this retrospective clinical epidemiological study on breast cancer. The authors thank the local investigators from Beijing, Liaoning (Shenyang), Hunan (Changsha), Guangdong (Guangzhou), Zhejiang (Hangzhou), Shanxi (Xi’an), and Sichuan (Chengdu) for data collection and for assisting them in completing the project successfully. The authors also thank Pfizer for funding in the form of donations to Cancer Foundation of China. The authors thank Professor Robert Nelson and Professor Annette van Dyke for their kind help to revise the manuscript. REFERENCES 1. Jemal A, Bray F, Center MM, et al. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90. 2. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–752. 3. Wesolowski R, Ramaswamy B. Gene expression profiling: changing face of breast cancer classification and management. Gene Expr. 2011;15:105–115. 4. Penault-Llorca F, Viale G. Pathological and molecular diagnosis of triple-negative breast cancer: a clinical perspective. Ann Oncol. 2012;23(suppl 6):vi19–vi22. 5. Cianfrocca M, Gradishar W. New molecular classifications of breast cancer. CA Cancer J Clin. 2009;59:303–313. 6. Nguyen PL, Taghian AG, Katz MS, et al. Breast cancer subtype approximated by estrogen receptor, progesterone receptor, and HER-2 is associated with local and distant recurrence after breastconserving therapy. J Clin Oncol. 2008;26:2373–2378. 7. Caldarella A, Crocetti E, Bianchi S, et al. Female breast cancer status according to ER, PR and HER2 expression: a population based analysis. Pathol Oncol Res. 2011;17:753–758. 8. Garcia Fernandez A, Gimenez N, Fraile M, et al. Survival and clinicopathological characteristics of breast cancer patient according to different tumour subtypes as determined by hormone receptor and Her2 immunohistochemistry: a single institution survey spanning 1998 to 2010. Breast. 2012;21:366–373. 9. Chen XY, Kong ZL. Chinese Cancer Registry Annual Report 2009. Beijing: Military Medical Science Press; 2010. 10. National Office for Cancer Prevention and Control (NOCPC) of the Chinese Ministry of Health (2010). National survey on cancer mortality in China—the third sample survey on mortality. r
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11. He J, Zhao P, Chen WQ. Chinese Cancer Registry Annual Report 2011. Beijing: Military Medical Science Press; 2012. 12. Li J, Zhang BN, Fan JH, et al. A nation-wide multicenter 10-year (1999-2008) retrospective clinical epidemiological study of female breast cancer in China. BMC Cancer. 2011;11:364. 13. Zheng S, Bai JQ, Li J, et al. The pathologic characteristics of breast cancer in China and its shift during 1999-2008: a national-wide multicenter cross-sectional image over 10 years. Int J Cancer. 2012;131:2622–2631. 14. Porter PL. Global trends in breast cancer incidence and mortality. Salud Publica Mex. 2009;51(suppl 2):s141–s146. 15. American Joint Committee on Cancer. AJCC Cancer Staging Manual. Philadelphia: Lippincott-Raven; 1997. 16. American Joint Committee on Cancer. AJCC Cancer Staging Manual. New York: Springer; 2002. 17. World Health Organization. Histological Typing of Breast Tumors. Geneva: World Health Organization; 1981. 18. Tavassoli FA, Devilee P. Pathology and Genetics of Tumours of the Breast and Female Genital Organs. Lyon: IARC; 2003. 19. Zarbo RJ, Hammond ME. Conference summary, Strategic Science symposium. Her-2/neu testing of breast cancer patients in clinical practice. Arch Pathol Lab Med. 2003;127:549–553. 20. IARC. Breast cancer in different regions GLOBOCAN, 2008. Available at: http://globocan.iarc.fr.IARC. Accessed July 25, 2013. 21. Wang Q, Li J, Zheng S, et al. Breast cancer stage at diagnosis and area-based socioeconomic status: a multicenter 10-year retrospective clinical epidemiological study in China. BMC Cancer. 2012;12:122. 22. Su Y, Zheng Y, Zheng W, et al. Distinct distribution and prognostic significance of molecular subtypes of breast cancer in Chinese women: a population-based cohort study. BMC Cancer. 2011; 11:292. 23. Lin CH, Liau JY, Lu YS, et al. Molecular subtypes of breast cancer emerging in young women in Taiwan: evidence for more than just westernization as a reason for the disease in Asia. Cancer Epidemiol Biomarkers Prev. 2009;18:1807–1814. 24. Wang Y, Yin Q, Yu Q, et al. A retrospective study of breast cancer subtypes: the risk of relapse and the relations with treatments. Breast Cancer Res Treat. 2011;130:489–498. 25. Xue C, Wang X, Peng R, et al. Distribution, clinicopathologic features and survival of breast cancer subtypes in Southern China. Cancer Sci. 2012;103:1679–1687. 26. Xing P, Li J, Jin F. A case-control study of reproductive factors associated with subtypes of breast cancer in Northeast China. Med Oncol. 2010;27:926–931. 27. Kim RG, Kim EK, Kim HA, et al. Prognostic significance of molecular subtype in T1N0M0 breast cancer: Korean experience. Eur J Surg Oncol. 2011;37:629–634. 28. Choi YL, Oh E, Park S, et al. Triple-negative, basal-like, and quintuple-negative breast cancers: better prediction model for survival. BMC Cancer. 2010;10:507. 29. Iwase H, Kurebayashi J, Tsuda H, et al. Clinicopathological analyses of triple negative breast cancer using surveillance data from the Registration Committee of the Japanese Breast Cancer Society. Breast Cancer. 2010;17:118–124. 30. Kim MJ, Ro JY, Ahn SH, et al. Clinicopathologic significance of the basal-like subtype of breast cancer: a comparison with hormone
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33.
34. 35.
36. 37. 38. 39. 40. 41. 42. 43.
44.
45. 46. 47.
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receptor and Her2/neu-overexpressing phenotypes. Hum Pathol. 2006;37:1217–1226. Kurebayashi J, Moriya T, Ishida T, et al. The prevalence of intrinsic subtypes and prognosis in breast cancer patients of different races. Breast. 2007;16(suppl 2):S72–S77. Spitale A, Mazzola P, Soldini D, et al. Breast cancer classification according to immunohistochemical markers: clinicopathologic features and short-term survival analysis in a population-based study from the South of Switzerland. Ann Oncol. 2009;20:628–635. Durbecq V, Ameye L, Veys I, et al. A significant proportion of elderly patients develop hormone-dependant “luminal-B” tumours associated with aggressive characteristics. Crit Rev Oncol Hematol. 2008;67:80–92. Yang XR, Sherman ME, Rimm DL, et al. Differences in risk factors for breast cancer molecular subtypes in a population-based study. Cancer Epidemiol Biomarkers Prev. 2007;16:439–443. Crabb SJ, Cheang MC, Leung S, et al. Basal breast cancer molecular subtype predicts for lower incidence of axillary lymph node metastases in primary breast cancer. Clin Breast Cancer. 2008; 8:249–256. Carey LA, Perou CM, Livasy CA, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA. 2006;295:2492–2502. Munoz M, Fernandez-Acenero MJ, Martin S, et al. Prognostic significance of molecular classification of breast invasive ductal carcinoma. Arch Gynecol Obstet. 2009;280:43–48. Leong SP, Shen ZZ, Liu TJ, et al. Is breast cancer the same disease in Asian and Western countries? World J Surg. 2010;34:2308–2324. Metzger-Filho O, Tutt A, de Azambuja E, et al. Dissecting the heterogeneity of triple-negative breast cancer. J Clin Oncol. 2012;30:1879–1887. Jatoi I, Anderson WF, Rosenberg PS. Qualitative age-interactions in breast cancer: a tale of two diseases? Am J Clin Oncol. 2008;31:504–506. Anderson WF, Jatoi I, Sherman ME. Qualitative age interactions in breast cancer studies: mind the gap. J Clin Oncol. 2009;27: 5308–5311. Jatoi I, Anderson WF. Qualitative age interactions in breast cancer studies: a mini-review. Future Oncol. 2010;6:1781–1788. Department of Health, Executive Yuan, Republic of China (Taiwan). Health and national health insurance annual statistics information service, 2006. Available at: http://www.doh.gov.tw/ statistic/index.html. Accessed August 18, 2006. Brown M, Tsodikov A, Bauer KR, et al. The role of human epidermal growth factor receptor 2 in the survival of women with estrogen and progesterone receptor-negative, invasive breast cancer: the California Cancer Registry, 1999-2004. Cancer. 2008;112: 737–747. Salhia B, Tapia C, Ishak EA, et al. Molecular subtype analysis determines the association of advanced breast cancer in Egypt with favorable biology. BMC Womens Health. 2011;11:44. Vona-Davis L, Rose DP. The influence of socioeconomic disparities on breast cancer tumor biology and prognosis: a review. J Womens Health (Larchmt). 2009;18:883–893. Foulkes WD, Smith IE, Reis-Filho JS. Triple-negative breast cancer. N Engl J Med. 2010;363:1938–1948.
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The Characteristics of Breast Cancer Subtypes: Implications for Treatment Guidelines and Individualized Treatment Strategies in China Shan Zheng, PhD,* Qing-Kun Song, PhD,w Yu Ren, PhD,z Wei-Liang Feng, MS,y Ya-Nan Kong, MS,8 Rong Huang, MS,wz Feng Xu, PhD,# Jing Li, PhD,w Bao-Ning Zhang, BS,** Jin-Hu Fan, BS,w Jian-Jun He, PhD,z and You-Lin Qiao, PhDw
Abstract: This study aimed at investigating the characteristics of invasive breast cancer among molecular subtypes. Patients with invasive breast cancer, with complete information on the expressions of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 (HER2), were recruited. w2 tests and an unconditional logistic regression model were used for statistical analysis. The percentages of luminal A, luminal B, HER2/neu, and triple-negative subtypes were 54.2% (1639/3021), 14.0% (422/3021), 8.9% (269/3021), and 22.9% (691/3021), respectively. Differences among molecular subtypes (P < 0.05) in tumor size, stage, pathologic type, and lymph node status were observed. The HER2/neu, luminal B, and triple-negative subtypes were more aggressive compared with the luminal A subtype in tumor stage, lymph node status, or pathologic type (P < 0.05), when the findings were adjusted for age. Molecular subtypes were distributed differently between both age groups and regional groups on the basis of the socioeconomic status (P < 0.05). In conclusion, luminal A and triple-negative subtypes were the 2 main subtypes of invasive breast cancer in China. The variations of molecular subtypes in pathology, age, and regional distribution
Received for publication February 3, 2013; accepted July 5, 2013. From the Departments of *Pathology; wCancer Epidemiology; **Center of Breast Disease, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing; zDepartment of Oncosurgery, the First Affiliated Hospital of Medical College, Xi’an Jiaotong University, Xi’an; yDepartment of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou; 8Department of Breast Oncology, Sun Yat-Sen University Cancer Center, Guangzhou; zDepartment of Epidemiology, West China School of Public Health, Sichuan University, Chengdu, Sichuan; and #Department of Breast-thyroid Surgery, Xiangya Second Hospital, Central South University, Changsha, China. S.Z. and Q.-K.S. contributed equally. S.Z. and Q.-K.S. helped analyze and interpret the data and drafted the initial manuscript. Y.R. and W.-L.F. helped design the study. Y.-N.K., R.H., and J.L. helped with the data management and analysis. F.X. and B.-N.Z. helped in local data collection. J.-H.F. and J.-J.H. did critical revisions of the manuscript. Y.-L.Q. was the PI of this study and helped design the study. The authors declare no conflict of interest. Reprints: Jin-Hu Fan, BS, Department of Cancer Epidemiology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 17 South Panjiayuan Lane, Beijing 100021, China (e-mail: [email protected]). Copyright r 2013 by Lippincott Williams & Wilkins
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may give some suggestions for updating treatment guidelines and individualized treatment strategies in China. Key Words: breast carcinoma, subtype, age, regional socioeconomic status, nationwide (Appl Immunohistochem Mol Morphol 2014;22:383–389)
B
reast cancer is one of the diseases that seriously threaten women’s health. In 2008, breast cancer accounted for 23% (1.38 million) of total cancer cases and 14% (458,400) of cancer deaths worldwide.1 It is also an age-related disease, which is influenced by the socioeconomic status (SES). Breast cancers vary in both their biology and their response to specific therapies. In landmark studies conducted by Perou et al,2 molecular subtypes of breast tumors had different backgrounds of gene expression profiling. These discoveries are already starting to have an impact on the classification and treatment for breast cancer.3 Today, the results of gene expression profiling have been applied to the management of breast cancer in the developed countries. However, it has not been the same in the developing countries, where the exploration of prognostic factors needs to be inexpensive and easy to replicate.1,4 Gene expression profiling is expensive and largely limited to fresh or frozen samples.5 These factors hold back its application in routine diagnostic practice in these countries. To develop a molecular classification of clinical significance, investigators have explored immunohistochemical (IHC) biomarkers surrogated for gene expression profiling. These IHC-based molecular classification systems, derived from the data of gene expression profiling, were correlated with therapy decision and were able to provide additional prognostic information. Although IHC can be used routinely and cheaply to monitor confirmed biomarkers, this process cannot hunt for new biomarkers. One of the IHC-based molecular classification systems—the combination test in the expressions of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2)—has been generally accepted and can now be taken into account in treatment strategies.6–8
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Breast cancer is currently the most common malignancy and the sixth leading cause of cancer death in Chinese female patients.9,10 The incidence and mortality rates show a rising trend and present significant age and regional differences.9–11 Our previous studies had established a methodology for random sampling of female breast cancer patients across China from 1999 to 2008 and introduced the pathologic characteristics of Chinese female patients.12,13 In the present study, we investigated the pathologic characteristics of different molecular subtypes in invasive breast carcinoma determined by IHC and described the distribution among age and regional socioeconomic groups. We hoped these investigations might yield some suggestions for updating treatment guidelines and individualized treatment strategies for breast cancer in Chinese female patients. We also hoped these might provide suggestions for treating female patients with breast cancer in low-income and middle-income countries (LMCs) where breast cancer may be more harmful because of the late stage at diagnosis, inadequate pain relief, and inadequate palliative care.14
MATERIALS AND METHODS Institutional Review Board This study was a constitutive part of a multicenter retrospective hospital-based research that was approved by the Cancer Foundation of China Institutional Review Board.12 Patient consent was not required for this study as there were no risks anticipated to the participants of the study. All data were stripped of any patient identifiers.
Patient Selection Chinese women with primary breast cancer were randomly selected from 7 tertiary hospitals or medical centers in 7 traditional districts (North China, Northeast China, Northwest China, Central China, East China, South China, and Southwest China). All patients enrolled in these series studies met 3 key inclusion criteria: (i) primary breast cancer with pathologic confirmation; (ii) in-patient admission date within the selected month in the hospital, and (iii) received or receiving treatment (surgery, medical oncology, and radiotherapy) for breast cancer in the hospital. The enrolment scheme was to recruit patients admitted in alternating months from year to year in each hospital or medical center. In-patients in January and February were excluded because during this period the Chinese celebrate the traditional Spring Festival and individuals seldom visit hospitals during this time. For example, in a particular hospital, in the year 1999 all of the patients admitted in March were enrolled in the study, in 2000 all of the patients admitted in April were enrolled, and so on. In each selected month, if in-patient admissions were 2 levels were analyzed by the Cochran-Armitage testing. Only the pathologic characteristics that showed a significant level in w2 or CochranArmitage testing were included in the unconditional logistic regression model with the adjustment of age, whereas luminal A was set as the reference group. All of the tests were 2-tailed tests with a significance level of 0.05.
RESULTS A total of 4211 cases were collected from 7 districts during 1999 to 2008. There were 3021 patients with invasive breast cancer recruited in this study whose ER, PR, and HER2 information was acquired. Table 1 gives detailed demographics and pathologic information. The mean age was 48.7 years, ranging from 22 to 86 years. There were 541 (17.9%) cases in the age group of 39 years or below, 1146 (37.9%) cases in the age group of 40 to 49 years, and 1334 (44.2%) cases in the age group of r
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2013 Lippincott Williams & Wilkins 280 (66.4) 142 (33.7) 160 (41.9) 197 (51.6) 25 (6.5) 40 68 221 86 7 397 (94.1) 13 (3.1) 12 (2.8) 238 (56.9) 180 (43.1) 4 122 (51.3) 66 (27.7) 50 (21.0) 10 (2.8) 341 (97.2) 71 351 (83.2) 71 (16.8) 361 (85.5) 61 (14.5) 422 (100.0) 0 (0.0)
1013 (61.8) 626 (38.2)
414 (28.2) 924 (63.1) 127 (8.7) 174
315 (21.2) 812 (54.7) 326 (22.0) 32 (2.1) 154
1482 (90.4) 74 (4.5) 83 (5.1)
813 (51.0) 781 (49.0) 45
458 (56.3) 234 (28.8) 121 (14.9)
47 (3.3) 1360 (96.7) 232
1396 (85.2) 243 (14.8)
1411 (86.1) 228 (13.9)
0 (0.0) 1639 (100.0)
(17.8) (57.9) (22.5) (1.8) 40
47.9 ± 9.5, 422
48.9 ± 10.5, 1639
Luminal B (n = 422)
(10.5) (66.1) (22.2) (1.2) 21
269 (100.0) 0 (0.0)
(19.7) (57.2) (21.0) (2.1) 81
0 (0.0) 691 (100.0)
0 (0.0) 691 (100.0)
0 (0.0) 691 (100.0)
19 (3.2) 566 (96.8) 106
173 (56.5) 81 (26.5) 52 (17.0)
306 (45.5) 367 (54.5) 18
619 (89.5) 17 (2.5) 55 (8.0)
120 349 128 13
185 (30.0) 358 (58.1) 73 (11.9) 75
421 (60.9) 270 (39.1)
48.2 ± 10.2, 691
Triple Negative (n = 691)
< 0.001
< 0.001
< 0.001
0.970
0.035
0.003
0.001
0.020
< 0.001
0.060 0.056
P*
691 (22.9) 2330 (77.1)
1772 (58.7) 1249 (41.3)
1747 (57.8) 1274 (42.2)
84 (3.3) 2490 (96.7) 447
831 (55.7) 406 (27.2) 255 (17.1)
1492 (51.6) 1457 (49.4) 72
2748 (91.0) 110 (3.6) 163 (5.4)
529 (19.4) 1546 (56.8) 595 (21.8) 55 (2.0) 296
831 (30.7) 1624 (60.0) 250 (9.3) 316
1865 (61.7) 1156 (38.3)
48.7 ± 10.3, 3021
All Cases (n = 3021)
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0 (0.0) 269 (100.0)
0 (0.0) 269 (100.0)
8 (3.5) 223 (96.5) 38
78 (57.8) 25 (18.5) 32 (23.7)
135 (51.1) 129 (48.9) 5
250 (93.0) 6 (2.2) 13 (4.8)
26 164 55 3
72 (29.8) 145 (59.9) 25 (10.3) 27
151 (56.1) 118 (43.9)
49.8 ± 10.2, 269
HER2+/neu (n = 269)
*Comparing the 4 subgroups (luminal A, luminal B, HER2+/neu, and triple negative). Age was analyzed by analysis of variance tests. The differences of categorical variables were estimated by w2 tests, and the ordinal variables with >2 levels were analyzed by the Cochran-Armitage test. wThese cases were not included in analysis. zOthers include other invasive breast cancer except IDC and ILC. + indicates positive; , negative; AJCC, American Joint Committee on Cancer; ER, estrogen receptor; HER2, human epidermal growth factor receptor-2; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; LNM, lymph node metastasis; PR, progesterone receptor.
Age (mean ± SD, n) Menopausal status Premenopausal Postmenopausal Tumor size group (cm) r2 > 2-5 >5 Unknownw AJCC stage I II III IV Unknownw Pathologic type IDC ILC Othersz Lymph node status + Unknownw Group of LNM+ 1-3 4-9 Z10 Multifocality + Unknownw ER status + PR status + HER2 status +
Luminal A (n = 1639)
N (%)
TABLE 1. Characteristics of Chinese Female Patients With Invasive Breast Cancer Patients of Different Subtypes
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50 years or above. There were 2008 (66.5%) cases in the high–regional SES group, which included patients from the North, Northeast, East, and South, and 1013 (33.5%) cases were in the low–regional SES group, which included patients from Northwest, Middle, and Southwest.
The Pathologic Characteristics Among Different Molecular Subtypes As shown in Table 1, the percentages of luminal A, luminal B, HER2/neu, and triple-negative subtypes were 54.2% (1639/3021), 14.0% (422/3021), 8.9% (269/3021), and 22.9% (691/3021), respectively. The 4 molecular subtypes had differences in the tumor size group, AJCC stage, pathologic type, lymph node status, and the group of LNM (P < 0.05). However, the mean age, menopausal status, and the rate of multifocality were not different among these subtypes. Luminal A was more common in patients with tumor size >2 to 5 cm and in AJCC stage II (Table 1). The predominant pathologic type of luminal A was invasive ductal carcinoma (IDC) and was more common in the LNM+ group (Table 1). Compared with luminal A and after adjustment for age, luminal B subtype appeared more frequently in the small-tumor group (P < 0.001) and in LNM (P = 0.011); the HER2/neu subtype showed a more advanced AJCC stage (P = 0.001); the triplenegative subtype appeared less frequently in the LNM group (P = 0.015) and was more common in other invasive breast cancers compared with IDC and invasive lobular carcinoma (P < 0.001) (Table 2).
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The Subtype Distribution in Different Age Groups The percentages of breast cancer subtype in the age group of 39 years or below, 40 to 49 year, and 50 years or above at diagnosis were, respectively: 52.9% (286/541), 56.4% (646/1146), and 53.0% (707/1334) for luminal A; 15.7% (85/541), 13.5% (155/1146), and 13.7% (182/1334) for luminal B; 6.1% (33/541), 8.2% (94/1146), and 10.6% (142/1334) for HER2/neu; and 25.3% (137/541), 21.9% (251/1146), and 22.7% (303/1334) for the triple-negative subtype. The differences among age groups were significant (P = 0.022) (Fig. 1).
The Subtype Distribution in Different Regional SES Groups The subtype distribution in different regional SES groups was similar to the distribution in age group. Luminal A and triple negative were the 2 main subtypes in both high–regional SES and low–regional SES groups. The percentages of molecular subtypes in high–regional SES and low–regional SES groups were, respectively: 57.1% (1146/2008) and 48.7% (493/1013) for luminal A; 13.8% (278/2008) and 14.2% (144/1013) for luminal B; 8.3% (166/2008) and 10.1% (103/1013) for HER2/neu; and 20.8% (418/2008) and 27.0% (273/1013) for triplenegative cancer. Subtypes were distributed differently between high–regional SES and low–regional SES groups (P < 0.001) (Fig. 2). Because molecular subtypes had age variation, we stratified the regional SES group data into 2 age groups, below 50 years and 50 years or above, and
TABLE 2. Adjusted Odds Ratio for Patient and Tumor Characteristics for Invasive Breast Cancer Subtypes* HER2+/neu
Luminal B OR (95% CI) Tumor size group r2 cm > 2-5 cm > 5 cm AJCC stage I II III IV Pathologic type IDC ILC Othersw LNM + Group of LNM+ 1-3 4-9 Z10
P
OR (95% CI)
< 0.001 1.00 0.56 (0.44, 0.71) 0.50 (0.31, 0.81)
OR (95% CI)
0.628
0.418
1.00 0.88 (0.71, 1.10) 1.19 (0.84, 1.70) 0.001
0.510
1.00 2.48 (1.58, 3.89) 2.04 (1.22, 3.39) 1.96 (1.54, 7.10) 0.096
1.00 0.66 (0.35, 1.28) 0.52 (0.26, 1.05)
1.00 1.15 (0.89, 1.48) 1.00 (0.74, 1.35) 1.38 (0.62, 3.06) 0.283
< 0.001
1.00 0.48 (0.19, 1.21) 0.89 (0.45, 1.76) 0.011
1.00 1.36 (1.07, 1.71)
1.00 0.53 (0.29, 0.97) 1.86 (1.27, 2.74) 0.745
0.015
1.00 1.05 (0.79, 1.38) 0.215
P 0.160
1.00 0.92 (0.67, 1.26) 1.15 (0.69, 1.94)
1.00 1.25 (0.92, 1.70) 1.21 (0.84, 1.73) 0.68 (0.20, 2.37)
1.00 1.13 (0.79, 1.60) 1.44 (0.96, 2.18)
Triple Negative P
1.00 0.79 (0.65, 0.95) 0.405
0.380
1.00 0.63 (0.38, 1.04) 1.48 (0.91, 2.41)
1.00 0.84 (0.60, 1.18) 1.14 (0.77, 1.68)
*Luminal A as the reference group, adjusting age. wOthers include other invasive breast cancer except IDC and ILC. + indicates positive; , negative; AJCC, American Joint Committee on Cancer; CI, confidence interval; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; LNM, lymph node metastasis; OR, odds ratio.
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100.0 90.0
≤39 years old
80.0 40-49 years old
Percent (%)
70.0
≥50 years old
60.0 50.0 40.0 30.0 20.0 10.0 0.0 Luminal A
Luminal B HER2/neu Molecular Subtype
Triple negative
FIGURE 1. The distribution of molecular subtype with invasive breast cancer in different age groups. White bars represent “the age group of 39 years or below.” Gray bars represent “the age group of 40 to 49 years.” Black bars represent “the age group of 50 years or above.” Luminal A subtype is more common in the age group of 40 to 49 years than in the other 2 age groups. Triple-negative and luminal B subtypes were more common in the age group 39 years or below. HER2/neu subtypes were more common in the age group 50 years or above. There are differences in distribution of molecular subtypes with invasive breast cancer in different age groups (P = 0.022).
the geographic variation was observed in both age groups (data not shown).
DISCUSSION China is one of the representative LMCs and has 7 traditional districts. The districts had different breast cancer burdens.9–11 There were a lot of studies on breast cancer in China. However, the previous researches22–26
FIGURE 2. The distribution of molecular subtypes with invasive breast cancer in different regional SES groups. White bars represent the “high–regional SES group.” Black bars represent the “low–regional SES group.” Luminal A subtype is more common in the high–regional SES group. Triple-negative subtype is more common in the low–regional SES group. There are differences in distribution of molecular subtypes with invasive breast cancer in different regional SES groups (P < 0.001). r
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mainly focused on regions with a high socioeconomic level and breast cancer burden. There were few data about districts with a relatively low socioeconomic level and breast cancer burden. In this study, we described the characteristics of different molecular subtypes of invasive breast carcinoma among the whole population of China. For Chinese female patients, luminal A and triplenegative subtypes were the main subtypes in China. This finding was similar to those in other Eastern Asian countries27–31 but was different from those among the white population.7,32–37 The study showed some new evidence to add to the research of Leong et al38 who focused on the difference between the Asian and Western countries. Although the detail pathologic characteristics of different subtypes were similar to all these studies,22–31 we found 3 interesting phenomena. First, the triple-negative subtype showed less LNM and was more prevalent in invasive breast cancer other than IDC and invasive lobular carcinoma, compared with luminal A subtype (P < 0.05). This result may reflect the heterogeneity of the triple-negative subtype. The triple-negative subtype included 4 main subgroups: claudin-low, immune system related, DNA repair genes related, and androgen signaling.39 This result may reflect the combined action of different main subgroups in the triple-negative subtype. This also reminded us that we should evaluate the biological behavior of a given subtype comprehensively. Second, compared with the results of the previous studies from China,22–26 our results showed a little harmful behavior in pathologic characteristics. The previous studies focused on populations in districts with a relatively high socioeconomic level and breast cancer burden.22–26 However, our data included districts with a relatively low socioeconomic level and breast cancer burden. The result indicated that the socioeconomic level and burden of breast cancer may influence the pathologic characteristics. Therefore, it was meaningful to carry out a populationbased study including all 7 districts of China. Third, the lack of a well-accepted definition of molecular subtypes may to some degree affect the comparability between the previous studies and ours. As there were obvious differences in pathologic characteristics of breast cancer between the white and the Chinese,13 it was necessary to establish the definition of molecular subtypes suitable for Chinese. In this study, we divided our data into 3 age groups: 39 years or below, 40 to 49 years, and 50 years or above at diagnosis according to the data from GLOBCAN, 2008.20 The distribution of the molecular subtypes was different from other studies, except for the triple-negative subtype.40–42 Our results were similar to the result of Lin et al23 but were somewhat different from those of Su et al.22 On the one hand, these phenomena may reflect the difference between the West and Asia38; on the other hand, the diversities in the urbanization level may be one of the reasons for these phenomena.43 These phenomena also reminded us that we should take into account the age distribution of molecular subtypes for the individualized treatment strategies. www.appliedimmunohist.com |
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At last, we described the regional distribution of molecular subtypes. We divided 7 districts into 2 groups, according to the regional SES. SES may have a major role in producing prognostic differences in breast cancer behavior as it may reflect the level of family income, education, and health care insurance. In addition, there is some epidemiological evidence that low SES is associated with breast cancers that possess the biomarkers of aggressive tumor behavior.44,45 Further, our previous study also had showed that SES may influence the AJCC stage.21 Therefore, we thought that SES may influence the regional distribution of molecular subtypes. We found that luminal A was more common in high–regional SES groups, whereas the triple-negative subtype was prevalent in low–regional SES groups, independent of age. Our results confirmed that SES may influence the expression of biomarkers. The reasons are not clear. One possible explanation is that a low SES may result in obesity, which may induce the alterations in the ER environment.46 Our results suggest 2 possibilities. First, the emphasis on treatment modality may be different in different SES regions. Second, these phenomena should be interpreted cautiously, as they need a more thorough investigation in future population-based study. There are some potential limitations in this study. We selected patients from 7 tertiary hospitals in an effort to represent the whole population. Although this process might not have resulted in the degree of representation we were hoping for, we selected these tertiary hospitals for 2 reasons. First, patients in China preferred to go to the higher-ranked hospitals, so we thought these hospitals might give us a good sampling of patients with breast cancer in China. Second, these hospitals had the ability to offer comprehensive therapy for cancers and to keep complete records of pathologic tests. The pathologic reports of all the selected hospitals are standardized according to the national standard and mutual recognition, which minimize interhospital variations. Meanwhile, we defined breast subtype approximated by ER, PR, and HER2, which may introduce some misclassification of luminal B group as luminal A and of an as-yet unclassified group as triple negative.39,47 In addition, fluorescence in situ hybridization was not accepted widely during 1999 to 2008 because of its high cost, and therefore the data of HER2 amplification in fluorescence in situ hybridization could not be obtained, which may also have led to some misclassification of molecular subtypes. However, this definition offers several advantages as these 3 markers were routinely used in pathology laboratories in China during 1999 to 2008. All the selected hospitals had established the staining patterns, evaluation protocols, and quality control according to the national standard, which guaranteed the reliability of our results. So, this method appears to have the most clinical applicability in China. These results will give some suggestions for the population-based study representing the whole population of China. In conclusion, luminal A and triple-negative subtypes were the 2 main subtypes of invasive breast cancer
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in China. There were some differences in the characteristics among different subtypes in pathology, age, and regional distribution. As the introduction of molecular techniques has defined a new role for pathology that includes the treatment of breast cancer, we think our results may give some suggestions for updating the treatment guidelines and individualized treatment strategies in China. The implications were listed as follows: (1) Molecular subtypes showed different pathologic characteristics, which may indicate subtype-specific treatments. Early detection may be helpful in the treatment of luminal A subtype. Prevention of early LNM+ may be helpful in the treatment of luminal B subtype. The treatment of later-stage patients may be one of the emphases in the treatment of HER2/neu subtype. LNM+ may not be a key point of the treatment of the triple-negative subtype. (2) The age-related and SES-related regional distributions should be taken into account. ACKNOWLEDGMENTS The authors thank Cancer Foundation of China for initiating this retrospective clinical epidemiological study on breast cancer. The authors thank the local investigators from Beijing, Liaoning (Shenyang), Hunan (Changsha), Guangdong (Guangzhou), Zhejiang (Hangzhou), Shanxi (Xi’an), and Sichuan (Chengdu) for data collection and for assisting them in completing the project successfully. The authors also thank Pfizer for funding in the form of donations to Cancer Foundation of China. The authors thank Professor Robert Nelson and Professor Annette van Dyke for their kind help to revise the manuscript. REFERENCES 1. Jemal A, Bray F, Center MM, et al. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90. 2. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–752. 3. Wesolowski R, Ramaswamy B. Gene expression profiling: changing face of breast cancer classification and management. Gene Expr. 2011;15:105–115. 4. Penault-Llorca F, Viale G. Pathological and molecular diagnosis of triple-negative breast cancer: a clinical perspective. Ann Oncol. 2012;23(suppl 6):vi19–vi22. 5. Cianfrocca M, Gradishar W. New molecular classifications of breast cancer. CA Cancer J Clin. 2009;59:303–313. 6. Nguyen PL, Taghian AG, Katz MS, et al. Breast cancer subtype approximated by estrogen receptor, progesterone receptor, and HER-2 is associated with local and distant recurrence after breastconserving therapy. J Clin Oncol. 2008;26:2373–2378. 7. Caldarella A, Crocetti E, Bianchi S, et al. Female breast cancer status according to ER, PR and HER2 expression: a population based analysis. Pathol Oncol Res. 2011;17:753–758. 8. Garcia Fernandez A, Gimenez N, Fraile M, et al. Survival and clinicopathological characteristics of breast cancer patient according to different tumour subtypes as determined by hormone receptor and Her2 immunohistochemistry: a single institution survey spanning 1998 to 2010. Breast. 2012;21:366–373. 9. Chen XY, Kong ZL. Chinese Cancer Registry Annual Report 2009. Beijing: Military Medical Science Press; 2010. 10. National Office for Cancer Prevention and Control (NOCPC) of the Chinese Ministry of Health (2010). National survey on cancer mortality in China—the third sample survey on mortality. r
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