Literature DB >> 31681601

Prognostic Value of Ki-67 in Patients With Resected Triple-Negative Breast Cancer: A Meta-Analysis.

Qiang Wu1, Guangzhi Ma1, Yunfu Deng1, Wuxia Luo2, Yaqin Zhao3, Wen Li1, Qinghua Zhou1.   

Abstract

Background: Ki-67 is a widely used marker of tumor proliferation, but the prognostic value of ki-67 in triple-negative breast cancer (TNBC) has not been comprehensively reviewed. This meta-analysis was conducted to evaluate the association between ki-67 expression and survival of patients with resected TNBC. Materials and
Methods: Relevant studies, evaluating the prognostic impact of pretreatment ki-67 in resected TNBC patients, were identified from PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Cochrane Library until March 14, 2019. Hazard ratios (HRs) with 95% confidence intervals (CI) were calculated as effect values for disease-free survival (DFS) and overall survival (OS).
Results: In present meta-analysis, 35 studies with 7,716 enrolled patients were eligible for inclusion. Pooled results showed that a high ki-67 expression was significantly associated with poor DFS (HR = 1.73, 95% CI: 1.45-2.07, p < 0.001) and poor OS (HR = 1.65, 95% CI: 1.27-2.14, p < 0.001) in resected TNBC. In the subgroup analysis, when a cutoff of Ki-67 staining ≥40% was applied, the pooled HR for DFS and OS was 2.30 (95% CI 1.54-3.44, p < 0.001) and 2.95 (95% CI 1.67-5.19, p < 0.001), respectively.
Conclusion: A high Ki-67 expression is a poor prognostic factor of resected TNBC. The cut-off of ki-67 ≥40% is associated with a greater risk of recurrence and death compared with lower expression rates, despite the Ki-67 threshold with the greatest prognostic significance is as yet unknown.
Copyright © 2019 Wu, Ma, Deng, Luo, Zhao, Li and Zhou.

Entities:  

Keywords:  Ki-67; TNBC; meta-analysis; prognosis; triple-negative breast cancer

Year:  2019        PMID: 31681601      PMCID: PMC6811517          DOI: 10.3389/fonc.2019.01068

Source DB:  PubMed          Journal:  Front Oncol        ISSN: 2234-943X            Impact factor:   6.244


Introduction

Breast cancer is one of the most frequently diagnosed cancers and the leading cause of cancer morbidity in women worldwide. It affected more than 1.6 million individuals in 2012 and constituted ~15% of all cancer-related deaths among females (1). Triple-negative breast cancer (TNBC) is a subtype of breast cancer and accounts for about 12 to 17% of all breast cancers (2). Due to lacking the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor type 2 (HER2) in tumor cells, patients with TNBC are neither sensitive to endocrine therapy nor therapies targeted to HER2 (3). TNBC is usually a high-grade invasive ductal carcinoma without a special pathological type, and it is also a heterogeneous disease because some of these patients are obviously sensitive to chemotherapy with likelihood to achieve a favorable prognosis (4, 5). Thus, sufficient and valid prognostic factors of TNBC should be identified. Ki-67, a non-histone nuclear protein, is present in the cell nucleus during all of the active phases of the cell cycle (G1, S, G2, and mitosis) but absent in quiescent cells (G0), which makes it a widely used biomarker of tumor proliferation and a crucial element of pathological assessment (6, 7). The prognostic significance of Ki-67 has been extensively evaluated in various malignancies, including breast cancer. Ki-67 is established as a vital factor in the distinction between luminal A and luminal B breast cancer subtypes by the 2011 and 2013 St. Gallen International Breast Cancer Conference (8, 9). Unlike its role in luminal diseases whose low Ki-67 expression achieves an enhanced prognosis after standard systematic treatments, the prognostic value of Ki-67 in TNBC is still unclear and no consensus has been reached (10). Therefore, this study focused on the assessment of the prognostic value of Ki-67 in resected TNBC patients.

Methods

Our meta-analysis was conducted in line with the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) statement (11).

Search Strategy

A comprehensive electronic search of PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Cochrane Library was conducted without language restriction to identify all relevant full-length studies on the prognostic role of Ki-67 in patients with TNBC. To retrieve data as much as possible, we expand the search scope by using the keywords as follow: (“Ki-67” or “mib-1” or “proliferative marker”) and (“breast cancer” or “breast tumor” or “breast carcinoma” or “breast neoplasm”). The beginning date was not limited, and the search was up to March 14, 2019. References cited in eligible studies were also searched manually to obtain additional pertinent articles.

Study Selection

The inclusion criteria were as follows: (1) studies or subsets in studies investigating the association between Ki-67 and prognosis in resected TNBC who has received neo-adjuvant or adjuvant treatment; (2) studies have adequate data for calculation including the hazard ratio (HR) and its corresponding 95% confidence interval (CI), and (3) the threshold value of Ki-67 was determined by pretreatment biopsy specimen. The exclusion criteria were as follows: (1) non-original research articles with limited data, such as reviews, letters, comments, conference abstracts, or case reports; (2) studies without adequate survival or recurrence data for further calculation; (3) studies involving metastatic diseases; (4) overlapping or duplicate data; and (5) studies with a sample size of <30 analyzable cases.

Data Extraction and Quality Assessment

The following data was extracted: first author's name, year of publication, country, study design and sample size, demographic characteristics (e.g., age, gender, and geographical background), cut-off value of Ki-67 expression, percentage of positive lymph nodes, treatment, and the HR with 95% CI of disease-free survival (DFS) and overall survival (OS). Multivariate outcomes were preferred when multivariate and univariate analyses performed simultaneously. Newcastle–Ottawa Scale (NOS) was used to examine the qualities of the included studies (12). This evaluation tool covered the selection, comparability, and clinical outcomes, and studies were considered to be of high quality when they scored 6 or more.

Statistical Analysis

Prognostic outcomes, including DFS and OS, were the primary endpoints of this study. DFS was defined as the interval period from the date of operation to the first observation of recurrence or the last follow-up without evidence of recurrence. OS was defined as the time from the first diagnosis of primary breast cancer to the time of death from any cause. HRs with 95% CIs for prognostic outcomes were extracted for further calculation. For those that were indirectly given in publications, published data and figures from original papers were extracted to calculate the corresponding HRs by utilizing the methods described by Tierney et al. (13). Cochrane's Q (P < 0.1 was considered significant) and Higgins's I2 (I2 > 50% was considered substantially heterogeneous) statistic tests were used to evaluate the heterogeneity among the eligible studies (14). A fixed-effect model would be preferred in the analyses to acquire precise results if the heterogeneities were insignificant. Otherwise, a random-effect model should be utilized (15). Subgroup analyses were also conducted to investigate the role of Ki-67 in specific populations and the potential source of heterogeneity. Publication bias was assessed with a funnel plot via Egger's and Begg's tests, and results were considered insignificant when P > 0.1 (16). Sensitivity analysis was performed to explore the influence of individual studies on the summarized results. Kaplan–Meier curves were recognized by Engauge Digitizer 4.1 (free software downloaded for http://getdata-graph-digitizer.com/). All tests were two sided, and P < 0.05 indicated statistical significance. Data analyses were performed with Stata 12.0 (StataCorp LP, TX, USA).

Results

Selection of Studies

A total of 1,684 potential studies were identified by the search algorithm. After duplicates were removed, abstracts of the 1,264 remaining studies were reviewed. Of these studies, 1,128 were excluded, and 136 potentially relevant studies were selected for further examination. A total of 101 studies were excluded because the prognosis of TNBC did not focus on Ki-67 (n = 44); the prognosis of Ki-67 did not highlight TNBC (n = 25); and Ki-67 of TNBC did not cover prognosis (n = 13), metastatic disease (n = 9), insufficient survival data (n = 5), no cutoff for Ki-67 (n = 3), duplication (n = 1), and retracted study (n = 1). Finally, 35 studies regarding the prognostic role of Ki-67 in TNBC subjected to neo-adjuvant or adjuvant chemotherapy were eligible for this meta-analysis (17–51). The flow diagram of studies selection was summarized in Figure 1.
Figure 1

Flow chart of the included studies.

Flow chart of the included studies.

Study Characteristics

A total of 7,716 patients with TNBC were enrolled in the 35 included studies for analyses. The patients' median age ranged from 50 to 60 years, and the median follow-up varied from 11 to 112 months. The cutoff of Ki-67 was 10%−50%. The article quality assessed by NOS was 6–9, and 80% of the included studies had a quality of 7–9. None of these studies included patients who underwent surgery alone without neoadjuvant or adjuvant treatment. Table 1 summarizes the main characteristics of the included studies.
Table 1

Characteristics of the included studies in this meta-analysis.

ReferencesAnalysis of survival dataNeoadjuvant or adjuvantNumber of patientsChemotherapy regimenRegionTest tissueKi-67 cut off value (%)ER/PR cut off value (%)
Toyama et al. (17)UVAAdjuvant715-FUAsianOperative specimen1010
Trere et al. (18)Survival CurveAdjuvant24CMFEuropeanOperative specimen2010
Lee et al. (19)MVAAdjuvant1550NRAsianOperative specimen2010
Nishimura et al. (20)MVAAdjuvant356CMF, CE(F), TaxaneAsianOperative specimen2010
Wang et al. (21)UVAAdjuvant42Paclitaxel-basedAsianOperative specimen3010
Keam et al. (23)MVANeoadjuvant105Taxel/anthracyclin-basedAsianPre-NAC1010
Li et al. (24)UVAAdjuvant125NRAsianOperative specimenNR10
Masuda et al. (25)MVANeoadjuvant33Taxel/anthracyclin-basedAsianPre-NAC5010
Miyashita et al. (26)MVAAdjuvant102NRAsianOperative specimen401
Kashiwagi et al. (22)Survival CurveAdjuvant1905-FU/anthracyclin-basedAsianOperative specimen301
Munzone et al. (27)Survival CurveAdjuvant496Anthracyclin-based, CMFEuropeanOperative specimen351
Ryu et al. (28)UVAAdjuvant94Anthracyclin-basedAsianOperative specimen1010
Xue et al. (29)MVAAdjuvant913Taxel/anthracyclin-based, CMFAsianOperative specimen145
Huang et al. (30)MVAAdjuvant185Taxel/anthracyclin-based, CMFAsianOperative specimen201
Milde-Langosch et al. (31)MVAAdjuvant95CMF/ECEuropeanOperative specimenNRNR
Xu et al. (32)MVAAdjuvant122CMFAsianOperative specimen1010
Yamashita et al. (33)MVAAdjuvant82NRAsianOperative specimen301
Zhang et al. (34)MVAAdjuvant428Taxel/anthracyclin-basedAsianOperative specimen1410
Zhou et al. (35)UVAAdjuvant31Taxel/anthracyclin-based, CMFAsianOperative specimen1010
Schmidt et al. (38)Survival CurveAdjuvant/neoadjuvant103Taxel-basedEuropeanNR141
Park et al. (36)UVAAdjuvant1551NRAsianOperative specimen501
Pistelli et al. (37)UVAAdjuvant81Anthracyclin-based, CMFEuropeanOperative specimen3010
Hao et al. (40)MVAAdjuvant571NRAsianOperative specimen351
Khalifa et al. (41)UVAAdjuvant/neoadjuvant106Taxel/anthracyclin-basedEuropeanPre-NAC2010
Liu et al. (42)UVAAdjuvant154NRAsianOperative specimen301
Asano et al. (39)UVANeoadjuvant61Taxel/anthracyclin-basedAsianPre-NAC141
Wang et al. (43)MVAAdjuvant363Taxel/anthracyclin-basedAsianOperative specimen401
Yang and Han (50)UVAAdjuvant199NRAsianOperative specimen14NR
Yue et al. (44)MVAAdjuvant192NROthersOperative specimen501
Zakaria et al. (45)MVAAdjuvant77Taxel/anthracyclin-basedOthersOperative specimen1010
Zhong et al. (46)UVAAdjuvant90NRAsianOperative specimen141
Ieni et al. (47)MVAAdjuvant65NREuropeanOperative specimen201
Kwon et al. (48)UVAAdjuvant/neoadjuvant230Taxel/anthracyclin-basedAsianPre-NAC201
Najafi et al. (49)Survival CurveAdjuvant119NRAsianOperative specimen2010
Wang and Liu (51)MVAAdjuvant110NRAsianOperative specimen20NR

UVA, unitivariate analysis; MVA, multivariate analysis; NR, not reported; NAC, neoadjuvant chemotherapy; CMF, cyclophosphamide, methotrexate, and 5-fluorouracil; CEF, cyclophosphamide, epirubicin, and 5-FU; EC, epirubicin/cyclophosphamide.

Characteristics of the included studies in this meta-analysis. UVA, unitivariate analysis; MVA, multivariate analysis; NR, not reported; NAC, neoadjuvant chemotherapy; CMF, cyclophosphamide, methotrexate, and 5-fluorouracil; CEF, cyclophosphamide, epirubicin, and 5-FU; EC, epirubicin/cyclophosphamide.

Relationship Between Ki-67 Expression and Prognosis

In Figure 2, 29 studies reported the association between Ki-67 and DFS, whereas 24 determined the OS. The pooled HR of DFS comparing the high Ki-67 expression level to the low was 1.73 (95% CI: 1.45–2.07; p < 0.001; Figure 2A). No significant heterogeneity (I2 = 43.7%) was found, and the fixed effect model was used. The pooled HR of OS was 1.65 (95% CI: 1.27–2.14; p < 0.001; Figure 2B), and moderate heterogeneity (I2 = 62.6%) existed among these studies.
Figure 2

Meta-analysis of the association between Ki-67 and DFS (A) and OS (B).

Meta-analysis of the association between Ki-67 and DFS (A) and OS (B).

Subgroup Analyses

Subgroup analyses were conducted in accordance with Ki-67 cutoffs, positive ER/PR expression thresholds (1% or 10%), treatment strategies (neo-adjuvant or adjuvant), and geographic regions (Europe, Asian, or other regions). Despite the limited number of studies in some subgroups, the results of DFS (Figure 3A) and OS (Figure 3B) stratified by these factors were consistent. Noticeably, the pooled HR for DFS and OS was 2.30 (95% CI 1.54–3.44, p < 0.001) and 2.95 (95% CI 1.67–5.19, p < 0.001), respectively, under the circumstance of a cutoff of Ki-67 staining ≥40%.
Figure 3

Subgroup analysis of the association between Ki-67 and DFS (A) and OS (B).

Subgroup analysis of the association between Ki-67 and DFS (A) and OS (B).

Publication Bias

In Begg's plots of publication bias, p-value was 0.209 (Figure 4), implying that publication bias did not exist in the present meta-analysis.
Figure 4

Funnel plot for the publication bias tests.

Funnel plot for the publication bias tests.

Discussion

TNBC has a worse prognosis than other phenotypes of breast cancer because of its aggressive biology and insensitivity to targeted therapy (52). Biomarkers useful in the selection of appropriate treatment strategies and the prediction of prognosis should be identified. Previous studies demonstrated the prognostic role of Ki-67, as a critical biomarker of cell proliferation, in various malignancies that originate from organs and tissues, such as prostate, stomach, esophagus, cervix, and breast. A high expression level of Ki-67 protein was accompanied with poor prognostic outcomes (53). Several meta-analyses have shown that a high Ki-67 expression level is associated with the likelihood of achieving a pathological complete response (pCR) after patients with TNBC receive neo-adjuvant chemotherapy (NAC), and these patients may have favorable outcomes. Nevertheless, most of these studies included small sample sizes and contained diverse cut-offs of Ki-67 (54, 55). In this meta-analysis, data were pooled to assess the prognostic value of Ki-67 in patients who suffered from resected TNBC and received neo-adjuvant or adjuvant chemotherapy. The results showed that patients with a high Ki-67 expression substantially had worse DFS and OS than their counterparts regardless of treatment strategies, study regions, Ki-67 cutoffs, or ER/PR thresholds. Despite the consistency obtained in our study, the optimized cutoff of Ki-67 is still under deliberation (56). Some investigators suggested that Ki-67 should be used as a continuous marker to fully reflect the biological behavior of tumor proliferation and simultaneously resolve the cutoff issue; however, confronting diverse therapeutic strategies is impractical for clinical decision making (7). A previous meta-analysis indicated that a 25% cutoff of Ki-67 is adequate to distinguish patients with breast cancer at different risks of death (57). The cutoff selection of Ki-67 may be apparent if this parameter is considered within each subtype, and a 14% cutoff for the classification of luminal A and luminal B cancers was proposed in the 2011 St. Gallen Consensus (9). Considering that the baseline Ki-67 values of TNBC are usually higher than those of luminal diseases, Leskandarany et al. reported that the optimized Ki-67 cutoff within a TNBC subgroup population is 70% as determined by X-tile (58). Different Ki-67 values were selected as a cut-point in our included studies, and the threshold of Ki-67 varied between 10 and 50%. The subgroup analysis based on the Ki-67 cutoff indicated that the prediction was significant in all of the subgroups expect one subgroup (Ki-67 < 20%). This finding might indicate that further prospective studies should be performed to optimize the cutoff of Ki-67 in TNBC. Baseline Ki-67 confirms the high chemosensitivity of highly proliferating TNBC after patients receive NAC, TNBC with a high Ki-67 expression likely has a high rate of pCR, which predicts favorable outcomes (59). However, studies have shown that TNBC with a high Ki-67 expression is associated with a poor prognosis because of rapid recurrence within 3 years despite a high pCR rate. A Korean study has demonstrated that a high Ki-67 expression (≥10%) is significantly associated with poor relapse-free survival and OS in preoperative TNBC despite a high pCR rate (26). Our subgroup analyses showed that a high Ki-67 expression is an adverse prognostic factor of DFS and OS both in the two groups of patients treated with adjuvant or neo-adjuvant therapy. Keam et al. reported that patients who suffer from TNBC and receive neo-adjuvant therapy with a high Ki-67 expression have a pattern of early recurrence. By contrast, the low-Ki-67-expressing subgroup did not have any pattern, indicating that a high Ki-67 expression, which indicated a high proliferation potential, might result in early recurrence. This phenomenon might partly explain why a high Ki-67 expression remained an adverse prognostic factor in the neo-adjuvant subgroup (23). The American Society of Clinical Oncology and the College of American Pathologists Guideline Recommendations indicated that the cutoff for positive ER or PR should be ≥1% of immunoreactive tumor cell nuclei in 2010, and the previous threshold was >10%. Hence, a subgroup analysis classified by ER cut-off was performed. The results showed that a high Ki-67 expression was an adverse prognostic factor of all the subgroups, indicating that Ki-67 might be a prognostic factor of patients whose ER expression ranged from 2 to 10. Another study showed that defining triple-negative breast cancer as HER2-negative breast cancer with <10% rather than <1% of ER and progesterone receptor expression because HER2-negative primary breast cancer with ER < 10% clinically behaves like TNBC in terms of survival outcomes (60). This phenomenon might partly explain why Ki-67 was a poor prognostic factor of this patient subgroup. Subgroup analyses on regions where these studies were conducted yielded the following classifications: Europe, Asia, and others. The results showed that a high Ki-67 expression was consistently an adverse prognostic factor of DFS and OS in these three subgroups. Moreover, the pooled data showed that TNBC was more likely to recur in Europe than in Asia. However, only eight studies were from Europe, while 27 studies were from Asia. Therefore, these findings should be carefully considered, and further studies should be performed to verify these results. Notably, our study has a few limitations. First, due to linguistic constraints, we included studies written in English and Chinese only, hence publications in other languages could have been omitted. Second, we failed to perform subgroup analyses on other parameters, such as age or tumor stage, because of insufficient background information and thus might cause heterogeneity in the pooled results. Other clinical heterogeneities among studies, such as different NAC and adjuvant regimens, were not analyzed. In conclusion, this study demonstrated that higher Ki-67 expression is a poorer prognostic factor of resected TNBC. The cut-off of ki-67 ≥40% is associated with a greater risk of recurrence and death compared with lower expression rates, despite the Ki-67 threshold with the greatest prognostic significance is as yet unknown.

Data Availability Statement

All datasets generated for this study are included in the manuscript/supplementary files.

Author Contributions

QW, WLi, and QZ contributed to the conception and design of this research. QW, GM, YD, WLu, YZ, WLi, and QZ contributed to the drafting of the article and final approval of the submitted version, and contributed to data analyses and the interpretation and completion of the figures and tables. All authors read and approved the final manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  56 in total

1.  Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement and publication bias.

Authors:  Karsten Knobloch; Uzung Yoon; Peter M Vogt
Journal:  J Craniomaxillofac Surg       Date:  2010-12-09       Impact factor: 2.078

2.  Predictive factors for the effectiveness of neoadjuvant chemotherapy and prognosis in triple-negative breast cancer patients.

Authors:  Hiroko Masuda; Norikazu Masuda; Yoshinori Kodama; Masami Ogawa; Michiko Karita; Jun Yamamura; Kazunori Tsukuda; Hiroyoshi Doihara; Shinichiro Miyoshi; Masayuki Mano; Shoji Nakamori; Toshimasa Tsujinaka
Journal:  Cancer Chemother Pharmacol       Date:  2010-07-01       Impact factor: 3.333

3.  Immunoexpression of lactoferrin in triple-negative breast cancer patients: A proposal to select a less aggressive subgroup.

Authors:  Antonio Ieni; Valeria Barresi; Luana Licata; Roberta Cardia; Carmine Fazzari; Giuseppe Nuciforo; Francesco Caruso; Michele Caruso; Vincenzo Adamo; Giovanni Tuccari
Journal:  Oncol Lett       Date:  2017-03-14       Impact factor: 2.967

4.  Identification of prognostic different subgroups in triple negative breast cancer by Her2-neu protein expression.

Authors:  Gilda Schmidt; Gabriele Meyberg-Solomayer; Christoph Gerlinger; Ingolf Juhasz-Böss; Daniel Herr; Achim Rody; Cornelia Liedtke; Erich-Franz Solomayer
Journal:  Arch Gynecol Obstet       Date:  2014-07-11       Impact factor: 2.344

5.  Validity of the proliferation markers Ki67, TOP2A, and RacGAP1 in molecular subgroups of breast cancer.

Authors:  Karin Milde-Langosch; Thomas Karn; Volkmar Müller; Isabell Witzel; Achim Rody; Markus Schmidt; Ralph M Wirtz
Journal:  Breast Cancer Res Treat       Date:  2012-11-08       Impact factor: 4.872

6.  Distribution, clinicopathologic features and survival of breast cancer subtypes in Southern China.

Authors:  Cong Xue; Xi Wang; Roujun Peng; Yanxia Shi; Tao Qin; Donggen Liu; Xiaoyu Teng; Shusen Wang; Li Zhang; Zhongyu Yuan
Journal:  Cancer Sci       Date:  2012-07-04       Impact factor: 6.716

7.  TNBCtype: A Subtyping Tool for Triple-Negative Breast Cancer.

Authors:  Xi Chen; Jiang Li; William H Gray; Brian D Lehmann; Joshua A Bauer; Yu Shyr; Jennifer A Pietenpol
Journal:  Cancer Inform       Date:  2012-07-24

8.  New insights into the prognostic value of Ki-67 labeling index in patients with triple-negative breast cancer.

Authors:  Shuang Hao; Zhi-Xian He; Ke-Da Yu; Wen-Tao Yang; Zhi-Min Shao
Journal:  Oncotarget       Date:  2016-04-26

Review 9.  Triple-negative breast cancer: is there a treatment on the horizon?

Authors:  Hui Yao; Guangchun He; Shichao Yan; Chao Chen; Liujiang Song; Thomas J Rosol; Xiyun Deng
Journal:  Oncotarget       Date:  2017-01-03

10.  Androgen receptor expression in early triple-negative breast cancer: clinical significance and prognostic associations.

Authors:  Mirco Pistelli; Miriam Caramanti; Tommasina Biscotti; Alfredo Santinelli; Alessandra Pagliacci; Mariagrazia De Lisa; Zelmira Ballatore; Francesca Ridolfi; Elena Maccaroni; Raffaella Bracci; Rossana Berardi; Nicola Battelli; Stefano Cascinu
Journal:  Cancers (Basel)       Date:  2014-06-27       Impact factor: 6.639

View more
  19 in total

1.  Radiomics features on ultrasound imaging for the prediction of disease-free survival in triple negative breast cancer: a multi-institutional study.

Authors:  Feihong Yu; Jing Hang; Jing Deng; Bin Yang; Jianxiang Wang; Xinhua Ye; Yun Liu
Journal:  Br J Radiol       Date:  2021-09-03       Impact factor: 3.629

2.  Correlation Between Mammographic Radiomics Features and the Level of Tumor-Infiltrating Lymphocytes in Patients With Triple-Negative Breast Cancer.

Authors:  Hongwei Yu; Xianqi Meng; Huang Chen; Xiaowei Han; Jingfan Fan; Wenwen Gao; Lei Du; Yue Chen; Yige Wang; Xiuxiu Liu; Lu Zhang; Guolin Ma; Jian Yang
Journal:  Front Oncol       Date:  2020-04-15       Impact factor: 6.244

3.  Triple-Negative Breast Cancer: Assessing the Role of Immunohistochemical Biomarkers on Neoadjuvant Treatment.

Authors:  Jesse Lopes da Silva; Fabiana Resende Rodrigues; Guilherme Gomes de Mesquita; Priscila Valverde Fernandes; Luiz Claudio Santos Thuler; Andreia Cristina de Melo
Journal:  Breast Cancer (Dove Med Press)       Date:  2021-01-11

4.  Presence of myxoid stromal change and fibrotic focus in pathological examination are prognostic factors of triple-negative breast cancer: Results from a retrospective single-center study.

Authors:  Hirotsugu Yanai; Katsuhiro Yoshikawa; Mitsuaki Ishida; Koji Tsuta; Mitsugu Sekimoto; Tomoharu Sugie
Journal:  PLoS One       Date:  2021-02-11       Impact factor: 3.240

5.  Sophoridine Inhibits the Tumour Growth of Non-Small Lung Cancer by Inducing Macrophages M1 Polarisation via MAPK-Mediated Inflammatory Pathway.

Authors:  Bei Zhao; Xiaodan Hui; Hairong Zeng; Yinan Yin; Jian Huang; Qingfeng Tang; Guangbo Ge; Tao Lei
Journal:  Front Oncol       Date:  2021-02-24       Impact factor: 6.244

6.  Prognostic significance of PD-L1-positive cancer-associated fibroblasts in patients with triple-negative breast cancer.

Authors:  Katsuhiro Yoshikawa; Mitsuaki Ishida; Hirotsugu Yanai; Koji Tsuta; Mitsugu Sekimoto; Tomoharu Sugie
Journal:  BMC Cancer       Date:  2021-03-06       Impact factor: 4.430

7.  KI-67 LI Expression in Triple-Negative Breast Cancer Patients and Its Significance.

Authors:  Maria A Arafah; Abderrahman Ouban; Omar Z Ameer; Ko Jin Quek
Journal:  Breast Cancer (Auckl)       Date:  2021-05-30

8.  Breast-Gynaecological & Immuno-Oncology International Cancer Conference (BGICC) Consensus and Recommendations for the Management of Triple-Negative Breast Cancer.

Authors:  Hesham Elghazaly; Hope S Rugo; Hamdy A Azim; Sandra M Swain; Banu Arun; Matti Aapro; Edith A Perez; Benjamin O Anderson; Frederique Penault-Llorca; Pierfranco Conte; Nagi S El Saghir; Cheng-Har Yip; Marwan Ghosn; Philip Poortmans; Mohamed A Shehata; Armando E Giuliano; Jessica W T Leung; Valentina Guarneri; Joseph Gligorov; Bahadir M Gulluoglu; Hany Abdel Aziz; Mona Frolova; Mohamed Sabry; Charles M Balch; Roberto Orecchia; Heba M El-Zawahry; Sana Al-Sukhun; Khaled Abdel Karim; Alaa Kandil; Ruslan M Paltuev; Meteb Foheidi; Mohamed El-Shinawi; Manal ElMahdy; Omalkhair Abulkhair; Wentao Yang; Adel T Aref; Joaira Bakkach; Nermean Bahie Eldin; Hagar Elghazawy
Journal:  Cancers (Basel)       Date:  2021-05-08       Impact factor: 6.639

9.  Adipophilin expression is an independent marker for poor prognosis of patients with triple-negative breast cancer: An immunohistochemical study.

Authors:  Katsuhiro Yoshikawa; Mitsuaki Ishida; Hirotsugu Yanai; Koji Tsuta; Mitsugu Sekimoto; Tomoharu Sugie
Journal:  PLoS One       Date:  2020-11-17       Impact factor: 3.240

10.  High Prevalence of Triple-Negative Breast Cancer in Southern Shaanxi Province, China.

Authors:  Xuemei Xing; Zhigang Fan; Yue Gao; Zheng Liu
Journal:  Cancer Manag Res       Date:  2021-02-17       Impact factor: 3.989

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.