Literature DB >> 28476037

Increased levels of LAPTM4B, VEGF and survivin are correlated with tumor progression and poor prognosis in breast cancer patients.

Sha Li1, Lu Wang1, Yue Meng1, Yanli Chang1, Jianjun Xu1, Qingyun Zhang1.   

Abstract

OBJECTIVE: This study explored the relationships among the expression of LAPTM4B, VEGF, and survivin and clinicopathological characteristics and prognosis in breast cancer patients.
METHODS: The expression of these three molecules in 110 stage I-III breast cancer patients with clinicopathological and follow-up data was detected via immunohistochemistry. Kaplan-Meier and Cox proportional hazard regression analyses were performed to assess the prognostic significance of these markers in breast cancer. Moreover, expression levels of these markers were evaluated in 5 breast cell lines via Western blot analysis.
RESULTS: LAPTM4B, VEGF, and survivin were over-expressed in breast cancer specimens and highly expressed in MDA-MB-231 cells. VEGF and nuclear survivin expression was significantly correlated with LAPTM4B expression, and high levels of all three were associated with a tumor size >2cm, TNM stage II+III and lymph node metastasis, which had worse impacts on overall survival and progression-free survival in breast cancer patients. A multivariate Cox analysis identified LAPTM4B over-expression as an independent prognostic marker in breast cancer.
CONCLUSIONS: These findings suggest that LAPTM4B, VEGF, and nuclear survivin expression are significantly correlated in breast cancer, which may be predictive of prognosis as well as effective therapeutic targets for new anticancer therapies.

Entities:  

Keywords:  LAPTM4B; VEGF; breast cancer; prognosis; survivin

Mesh:

Substances:

Year:  2017        PMID: 28476037      PMCID: PMC5522199          DOI: 10.18632/oncotarget.17176

Source DB:  PubMed          Journal:  Oncotarget        ISSN: 1949-2553


INTRODUCTION

Breast cancer is one of the most common cancers among women, and epidemiological statistics show that the incidence of this disease and its associated mortality are increasing yearly [1]. The identification of key genes that determine progression and metastasis in breast cancer is urgently needed for early diagnoses and molecular targeted therapies. Lysosome-associated protein transmembrane-4 beta (LAPTM4B), a novel oncogene that belongs to the mammalian 4-tetra-transmembrane spanning protein superfamily, was initially identified in human hepatocellular carcinoma [2, 3]. Previous studies showed that LAPTM4B-35 activity was elevated in various malignant tumors, which was associated with poor prognosis [4-6]. Moreover, it was indicated that LAPTM4B could increase the proliferation and metastasis of tumor cells, reduce apoptosis, and assist drug resistance, which involved in activated PI3K/AKT and Ras-MAPK signaling pathways [7]. Angiogenesis is an important feature of carcinogenesis, progression and metastasis in many human malignancies. Vascular endothelial growth factor (VEGF) is thought to be a major mediator of angiogenesis that promotes the proliferation of tumor cells and boosts invasion and metastasis via the activation of the PI3K/AKT pathway [8-10]. The vascular density of tumors, including breast cancer, has been proven to be closely correlated with prognosis [11]. Survivin is a 16.5-kDa intracellular protein that is a well-known member of the inhibitor of apoptosis protein family, and its expression is elevated in the majority of tumors [12]. It potentially facilitates cell cycle processes and cell division and reduces apoptotic indices, which is strongly related with poor prognosis in breast cancer [13, 14]. Transcription from the survivin gene locus gives rise to 5 splice variants [15]. The relation of the splicing variants with prognosis is currently unclear. Interestingly, a previous study revealed that tissues with elevated expression of LAPTM4B had significantly more new capillary blood vessels than tissues with reduced expression in a mouse xenograft model of liver cancer, indicating that LAPTM4B over-expression might be significantly associated with increased angiogenic activity [16]. Recent studies have also shown that silencing LAPTM4B remarkably reduces the expression of VEGF in HeLa cells [17] and that increased LAPTM4B-35 combined with positive VEGF expression might serve as a new biological marker to predict outcomes in cervical carcinoma [18]. In addition, it has been proven that the upregulation of LAPTM4B-35 promotes the activation of AKT and Bad, which would maintain cell survival [16]. The correlations among LAPTM4B, VEGF, and survivin have not been investigated in breast cancer. Therefore, we performed a retrospective study including 110 breast cancer patients who underwent surgical resection, primarily exploring relationships among the expression of these three markers, clinical variables and survival.

RESULTS

Expression of LAPTM4B, VEGF, and survivin

Statistical analyses showed that the expression of these three markers was significantly elevated in breast cancer specimens (P<0.05) (Table 1). As shown in Figure 1a-1k, LAPTM4B and VEGF protein staining were localized in the cytoplasm. Survivin staining differed among the cases: 63 cases (57.27%) showed expression only in the nucleus, 21 (19.09%) only in the cytoplasm, and 17 (15.45%) in both the nucleus and cytoplasm. Additionally, high VEGF and nuclear survivin protein expression were linearly correlated with that of LAPTM4B (P<0.001), as shown in Table 2.
Table 1

Expression of LAPTM4B, VEGF and survivin in breast tissue specimens

GroupsNLAPTM4B expressionPaVEGF expressionPaSurvivin expressionPa
High expression%High expression%High expression%
Benign breast tumor101100.013*1100.007*3300.038*
Breast cancer1106256.36660.07568.1

aCalculated by χ2 test.

*P < 0.05.

Figure 1

Representative pictures by immunohistochemistry for LAPTM4B, VEGF, and survivin in 110 breast cancer patients

LAPTM4B expression: (a) low expression in benign breast tumor specimens, (b) low expression in breast cancer, (c) high expression in breast cancer. VEGF expression: (d) low expression in benign breast tumor specimens, (e) low expression in breast cancer, (f) high expression in breast cancer. Survivin expression: (g) low expression in benign breast tumor specimens, (h) low nuclear expression in breast cancer, (i) high nuclear expression in breast cancer, (j) only cytoplasmic expression in breast cancer, (k) both nuclear and cytoplasmic expression in breast cancer. (a–k, original magnification, ×200).

Table 2

Correlations among LAPTM4B, VEGF and survivin in 110 breast cancer patients

Total no.LAPTM4BPa
Low expressionHigh expression
VEGF< 0.001*
Total no.1104862
Low expression441452
High expression663410
Nuclear survivin< 0.001*
Total no.893554
Low expression271250
High expression62234
Cytoplasmic survivin0.103
Total no.473314
Low expression221510
High expression25184

aCalculated by χ2 test.

*P < 0.001.

aCalculated by χ2 test. *P < 0.05.

Representative pictures by immunohistochemistry for LAPTM4B, VEGF, and survivin in 110 breast cancer patients

LAPTM4B expression: (a) low expression in benign breast tumor specimens, (b) low expression in breast cancer, (c) high expression in breast cancer. VEGF expression: (d) low expression in benign breast tumor specimens, (e) low expression in breast cancer, (f) high expression in breast cancer. Survivin expression: (g) low expression in benign breast tumor specimens, (h) low nuclear expression in breast cancer, (i) high nuclear expression in breast cancer, (j) only cytoplasmic expression in breast cancer, (k) both nuclear and cytoplasmic expression in breast cancer. (a–k, original magnification, ×200). aCalculated by χ2 test. *P < 0.001. Figure 2a shows that LAPTM4B, VEGF and survivin expression levels were increased in MDA-MB-231 cells, which were more highly metastatic than the other cell lines. Furthermore, we extracted the nuclear and cytoplasmic fractions in 5 breast cell lines and found that survivin protein expression was highest in the nuclear fractions of highly malignant MDA-MB-231 cells. For the cytoplasmic protein samples, survivin expression in MDA-MB-231 cells was lower than in the other cell lines (Figure 2b).
Figure 2

LAPTM4B, VEGF, nuclear and cytoplasmic survivin protein expression in breast cell lines by Western blot analysis

Protein samples were obtained from 5 breast cell lines (MDA-MB-231, ZR-75-1, T47D, MCF-7 and MCF-10A). (a) β-Actin was used as an internal control for the total protein. High expression of LAPTM4B, VEGF and survivin was detected in MDA-MB-231 cells. (b) Histone H3 and β-Actin were used as an internal control for the nuclear and cytoplasmic protein samples, respectively. High levels of survivin were expressed in the nuclear protein of MDA-MB-231 cells.

LAPTM4B, VEGF, nuclear and cytoplasmic survivin protein expression in breast cell lines by Western blot analysis

Protein samples were obtained from 5 breast cell lines (MDA-MB-231, ZR-75-1, T47D, MCF-7 and MCF-10A). (a) β-Actin was used as an internal control for the total protein. High expression of LAPTM4B, VEGF and survivin was detected in MDA-MB-231 cells. (b) Histone H3 and β-Actin were used as an internal control for the nuclear and cytoplasmic protein samples, respectively. High levels of survivin were expressed in the nuclear protein of MDA-MB-231 cells.

Relationships between LAPTM4B, VEGF, and survivin protein expression and clinicopathological factors in breast cancer patients

As shown in Table 3, high levels of LAPTM4B, VEGF, and nuclear survivin were found in cases where factors related to tumor progression were present, such as tumor sizes >2 cm, TNM stage II+III and lymph node metastasis. Moreover, there was a significantly positive correlation between LAPTM4B and VEGF expression levels and the probability of tumor-associated venous thrombus (P=0.012 and P<0.001, respectively).
Table 3

Associations between the expression levels of LAPTM4B, VEGF and survivin and clinicopathological factors in 110 breast cancer patients

CharacteristicsLAPTM4B expressionPaVEGF expressionPaNuclear survivin expressionPaCytoplasmic survivin expressionPa
High/LowHigh/LowHigh/LowHigh/Low
Patient No.62/4866/4462/2725/22
Age (years)0.2900.9360.4240.344
≤5521/2125/1722/128/10
>5541/2741/2740/1517/12
Menopausal status0.1780.5070.2790.351
Pre-menopausal17/1920/1618/117/9
Post-menopausal45/2946/2844/1618/13
Tumor size (cm)<0.001*<0.001*0.001*0.355
≤28/2411/2113/156/8
>254/2455/2349/1219/14
Histological type0.6070.3500.8730.280
IDC55/4156/4052/2322/22
Others7/710/410/43/0
Histological grade0.0530.0890.2300.697
G15/106/98/72/2
G2/G357/3860/3554/2023/20
TNM stage<0.001*<0.001*0.001*0.355
I6/239/2011/146/8
II/III56/2557/2451/1319/14
Lymph node metastasis<0.001*<0.001*<0.001*0.072
No16/3320/2919/1913/17
Yes46/1546/1543/812/5
Tumor thrombus in vena0.012*<0.001*0.6070.058
No38/4038/4045/2114/18
Yes24/828/417/611/4
ER status0.1210.2340.0770.137
Negative15/615/612/28/3
Positive47/4251/3850/2517/19
PR status Negative20/140.72722/120.65618/80.95410/80.798
Positive42/3444/3244/1915/14
Her-2 status0.1300.1190.4780.556
Negative44/4047/3748/1920/16
Positive18/819/714/85/6
Recurrence0.3360.044*0.0900.855
No47/4048/3945/2421/19
Yes15/818/517/34/3

aCalculated by χ2 test.

*P < 0.05.

aCalculated by χ2 test. *P < 0.05.

Univariate and multivariate survival analyses

As shown by the survival analyses, death and recurrence occurred in 12 (10.91%) and 23 cases (20.91%), respectively. The Kaplan–Meier and log-rank tests showed that tumor sizes >2 cm and lymph node metastasis were correlated with poor overall survival (OS) and progression-free survival (PFS) in breast cancer (Table 4; Figures 3 and 4). A more advanced TNM stage was closely associated with a significantly worse PFS. The univariate model indicated that OS and PFS were significantly lower in cases with elevated LAPTM4B, VEGF, and nuclear survivin levels than in cases with lower levels of these molecules.
Table 4

Univariate Kaplan–Meier survival analysis of OS and PFS in 110 breast cancer patients

VariablesNOS (months)PaPFS (months)Pa
Mean ± SE95 % CIMean ± SE95 % CI
Age (years)0.4370.366
≤554250.000±1.56146.941-53.05948.000±3.12141.882-54.118
>556846.000±2.25741.577-50.42344.000±1.80540.463-47.537
Menopausal status0.1860.183
Pre-menopausal3651.000±1.42048.218-53.78250.000±2.86044.394-55.606
Post-menopausal7446.000±2.12141.842-50.15844.000±1.88540.306-47.694
Tumor size (cm)0.027*0.009*
≤23252.000±1.69748.674-55.32652.000±1.69748.674-55.326
>27845.000±1.77841.514-48.48643.000±1.06840.907-45.093
Histological type0.6130.665
IDC9648.000±1.85444.367-51.63346.000±1.72242.625-49.375
Others1451.000±4.33042.513-59.48747.000±6.06235.118-58.882
Histological grade0.3900.333
G11552.000±3.14645.835-58.16552.000±1.79748.477-55.523
G2/G39548.000±1.91444.248-51.75244.000±1.49941.063-46.937
TNM stage0.0770.033*
I2952.000±2.59646.911-57.08952.000±2.59646.911-57.089
II/III8147.000±2.20542.678-51.32244.000±0.97642.087-45.913
Lymph node metastasis0.021*0.010*
No4951.000±1.91647.244-54.75651.000±2.00047.080-54.920
Yes6145.000±1.76041.550-48.45044.000±1.43941.179-46.821
Tumor thrombus in vena0.3660.315
No7849.000±1.61245.840-52.16048.000±1.88144.313-51.687
Yes3247.000±3.33940.456-53.54444.000±2.78238.546-49.454
ER status0.2010.190
Negative2145.000±1.83141.411-48.58943.000±1.14440.757-45.243
Positive8950.000±1.34747.360-52.64048.000±1.88644.304-51.696
PR status0.8410.931
Negative3447.000±2.32842.436-51.56443.000±1.45840.143-45.857
Positive7650.000±1.33747.379-52.62148.000±1.74344.584-51.416
Her-2 status0.9820.669
Negative8449.000±1.30946.434-51.56648.000±1.66644.735-51.265
Positive2645.000±2.55040.003-49.99744.000±3.38937.357-50.643
LAPTM4B0.004*0.001*
Low4851.000±1.95441.170-54.83050.000±1.87346.329-53.671
High6245.000±1.68741.693-48.30744.000±0.78142.470-45.530
VEGF0.010*0.003*
Low4451.000±1.87347.329-54.67151.000±1.56147.941-54.059
High6645.000±1.19542.658-47.34244.000±0.44643.126-44.874
Nuclear survivin0.022*0.009*
Low2748.000±3.67440.799-55.20148.000±3.67440.799-55.201
High6247.000±2.78941.534-52.46644.000±0.97042.099-45.901
Cytoplasmic survivin0.8750.868
Low2248.000±2.15243.782-52.21848.000±2.15243.782-52.218
High2553.000±1.20850.633-55.36753.000±3.01947.083-58.917

OS, overall survival; PFS, progression-free survival; CI, confidence interval.

aLog-rank test.

*P < 0.05.

Figure 3

Kaplan-Meier curves for overall survival in 110 patients with breast cancer

High expression of LAPTM4B (a), VEGF (b) and nuclear survivin (c) was significantly associated with poor overall survival (P = 0.004, 0.01 and 0.022).

Figure 4

Kaplan-Meier curves for progression-free survival in 110 patients with breast cancer

The progression-free survival was statistically shorter in groups with elevated expression of LAPTM4B (a), VEGF (b) and nuclear survivin (c) (P = 0.001, 0.003 and 0.009). Expression of cytoplasmic survivin (d) was not related to the progression-free survival.

OS, overall survival; PFS, progression-free survival; CI, confidence interval. aLog-rank test. *P < 0.05.

Kaplan-Meier curves for overall survival in 110 patients with breast cancer

High expression of LAPTM4B (a), VEGF (b) and nuclear survivin (c) was significantly associated with poor overall survival (P = 0.004, 0.01 and 0.022).

Kaplan-Meier curves for progression-free survival in 110 patients with breast cancer

The progression-free survival was statistically shorter in groups with elevated expression of LAPTM4B (a), VEGF (b) and nuclear survivin (c) (P = 0.001, 0.003 and 0.009). Expression of cytoplasmic survivin (d) was not related to the progression-free survival. The multivariate analysis showed that high levels of LAPTM4B were an independent prognostic marker for both OS and PFS in breast cancer (Table 5; P=0.007 and P=0.002, respectively).
Table 5

Multivariate Cox regression analysis of various predictive factors for OS and PFS in 110 breast cancer patients

VariablesOS (months)PFS (months)
RR95 % CIPaRR95 % CIPa
Tumor size (cm)N/AN/AN/AN/AN/AN/A
TNM stageN/AN/AN/AN/AN/AN/A
Lymph node metastasisN/AN/AN/AN/AN/AN/A
LAPTM4B1.7301.163-2.5740.007*1.8391.239-2.7300.002*
VEGFN/AN/AN/AN/AN/AN/A
Nuclear survivinN/AN/AN/AN/AN/AN/A
Cytoplasmic survivinN/AN/AN/AN/AN/AN/A

OS, overall survival; PFS, progression-free survival; RR, relative risk; CI, confidence interval.

a Cox regression test.

*P < 0.05.

OS, overall survival; PFS, progression-free survival; RR, relative risk; CI, confidence interval. a Cox regression test. *P < 0.05.

DISCUSSION

Despite the fact that an increasing number of genes have been discovered and various targeted therapies have also been developed in recent years, the survival rate for breast cancer is not satisfactory [19]. Thus, it is of great importance to identify biomarkers that are effective in helping to improve the prognosis in breast cancer. A number of studies have shown that the proliferation of cells overexpressing LAPTM4B is closely correlated with tumor progression and metastasis [20, 21]. In our study, increased LAPTM4B expression was strongly associated with prognosis-related features, including tumor size, TNM stage and lymph node metastasis. Further analysis revealed that breast cancer patients with high levels of LAPTM4B protein expression had worse OS and PFS rates. Our study found that the relationship between VEGF and nuclear survivin expression levels and the expression of LAPTM4B was remarkable. Furthermore, several reports have shown that VEGF could stimulate survivin expression via the PI3K/AKT pathway [22]. This up-regulation of survivin was found to enhance tumor angiogenesis mediated by VEGF [15, 23], suggesting the need for further research into the clinical relevance of these three molecules. In a further step, strategies should be developed to determine whether the detection of LAPTM4B in combination with other molecules is of diagnostic and prognostic value in assessing breast carcinoma cases. Tang et al. examined LAPTM4B and CD34 proteins in non-small cell lung cancer, and their results revealed that LAPTM4B might promote tumor progression by inducing tumor angiogenesis [24]. Meng et al. indicated that the downregulation of LAPTM4B suppressed tumor migration and invasion and significantly decreased VEGF expression. Subsequently, they verified that the coexpression of LAPTM4B and VEGF resulted in poor prognosis for cervical cancer [17, 18]. Consistent with these findings, our results show that high levels of LAPTM4B and VEGF led to poor clinical outcomes with regard to OS and PFS. Li et al. revealed that nuclear survivin levels might predict poor survival in breast cancer [25]. The present study indicates that survivin expression is predominantly nuclear rather than cytoplasmic [26], which is line with the majority of previous results. Interestingly, a few reports have indicated that the expression of survivin is nearly equivalent in the nucleus and cytoplasm [27] or only occurs in the cytoplasm [28], which might be attributed to differences in reagents, tissues and clinical stages. In our studies, we separately analyzed the expression of nuclear and cytoplasmic survivin. According to the statistical analyses, nuclear survivin protein expression was dramatically associated with tumor progression and poor survival. Researchers have found LAPTM4B-35 accelerates tumorigenesis in transgenic mice by upregulating the antiapoptotic molecule Bcl-2 and downregulating the proapoptotic molecule Bax. However, the expression of survivin in Ad-AE-infected cells was not altered [16]. Hence, the relationship of the subcellular localization of survivin with other molecules should be further investigated as a greater understanding of this relationship could improve prognostic assessments and individualized therapies. Fan et al. suggested that LAPTM4B*2 was associated with an increased risk of breast cancer in a cohort of Chinese women [29]. Li et al. demonstrated that MDA-MB-231 cells that had the *2/2 genotype exhibited increased LAPTM4B expression [30]. Similar to these results, our study demonstrated that increased VEGF and nuclear survivin expression occurs in MDA-MB-231 cells. In conclusion, our findings indicate for the first time that LAPTM4B, VEGF, and survivin protein expression is significantly associated with various clinicopathological characteristics and prognosis in breast cancer patients. In particular, the relation of VEGF and survivin protein levels with the expression of LAPTM4B indicates that they could have clinical potential as promising prognostic markers to identify individuals with poor outcomes and may be regarded as therapeutic targets for breast cancer. However, the limitations in this study included the small sample size and its retrospective nature, such as the limited follow-up time, which could be why the expression of VEGF and survivin was not linked to OS and PFS in the multivariate analysis.

MATERIALS AND METHODS

Patients and tissue samples

Specimens were collected from 110 breast cancer patients with stages I-III and 10 patients with benign breast tumors who underwent surgical resection at the Beijing Cancer Hospital between January 2011 and July 2013. All patients provided written informed consent, and none of the patients received chemotherapy, immunotherapy, or radiotherapy before surgery. The Ethics Committee of Beijing Cancer Hospital approved this protocol. All patients with breast cancer were followed-up for the survival analysis until September 2016 (median, 49 months; range, 10–67 months).

Immunohistochemical staining

Paraffin-embedded samples were cut into four-micrometer sections and stained with hematoxylin and eosin for tumor confirmation. Selected sections were immersed in a retrieval buffer solution for antigen recovery and incubated with a polyclonal rabbit anti-LAPTM4B antibody (dilution 1:200, bs-6542R, Bioss, USA), a polyclonal rabbit anti-VEGF antibody (dilution 1:150, ZA-0509, ZSGB, China) and a monoclonal mouse anti-survivin antibody (dilution 1:2000, produced by our lab) overnight at 4°C. Finally, the slides were stained and mounted. Negative controls were provided by replacing the primary antibodies with normal goat serum.

Staining evaluation

LAPTM4B, VEGF, and survivin protein expression levels were semi-quantitatively classified. The percentage of positive cells was measured as follows: 0, less than 9% staining; 1, 10% to 25% staining; 2, 26%-50% staining; 3, 51%-75% staining and 4, >75% staining. The staining intensity was evaluated as follows: 0, no staining; 1, weak staining; 2, moderate staining; 3, strong staining. The total score of stained cells was calculated by multiplying the above two scores to define the expression levels: 0, negative expression; 1 to 4, weak expression; 5 to 8, positive expression; 9 to 12, strong expression. Tumor tissues with scores of 0–4 were defined as having low expression and those with scores of 5–12, as having high expression.

Follow-up

Each patient was scheduled for an examination, which included a physical examination, blood analysis, and computed tomography analysis. Tumor progression was based on clinical, radiological or histological diagnosis, and the site and time of tumor progression were both recorded. Follow-up was performed until September 2016 for 110 patients.

Cell lines

Breast cancer cell lines (MDA-MB-231, ZR-75-1, T47D, and MCF-7) were kindly provided by Dr. SHOU Cheng-chao from Department of Biochemistry and Molecular Biology, Peking University Cancer Hospital & Institute. MCF-10A cells were obtained from MeiXuan Biological Technology Company Limited of Shanghai, China. They were cultured in appropriate media supplemented with essential materials in the 5% CO2 incubator [31].

Western blot analysis

Protein extracts were separated via 12% SDS polyacrylamide gel electrophoresis and transferred onto PVDF filters. The filters were incubated with a rabbit anti-LAPTM4B polyclonal antibody (dilution 1:1000, AP20870a, ABGENT, China), a rabbit anti-VEGF polyclonal antibody (dilution 1:500, 19003-1-AP, Proteintech, USA) and a rabbit anti-survivin monoclonal antibody (dilution 1:1000, 2808, Cell Signaling Technology, USA) overnight at 4°C. The blots were detected using a chemiluminescence detection system. β-Actin and histone H3 were used as internal controls for the total, cytoplasmic protein expression and nuclear protein expression.

Statistical analysis

SPSS 18.0 software was used to perform the statistical analyses, and χ2 tests were used to evaluate the associations between the three biomarkers and the clinicopathological characteristics. The follow-up data was analyzed using the Kaplan–Meier method and Cox regression tests. P<0.05 was considered statistically significant.
  31 in total

1.  Structure analysis and expressions of a novel tetratransmembrane protein, lysosoma-associated protein transmembrane 4 beta associated with hepatocellular carcinoma.

Authors:  Xin-Rong Liu; Rou-Li Zhou; Qing-Yun Zhang; Ye Zhang; Yue-Ying Jin; Ming Lin; Jing-An Rui; Da-Xiong Ye
Journal:  World J Gastroenterol       Date:  2004-06-01       Impact factor: 5.742

2.  Upregulation of LAPTM4B-35 promotes malignant transformation and tumorigenesis in L02 human liver cell line.

Authors:  Li Li; Yi Shan; Hua Yang; Sha Zhang; Ming Lin; Ping Zhu; Xin-Yu Chen; Jing Yi; Michael A McNutt; Gen-Ze Shao; Rou-Li Zhou
Journal:  Anat Rec (Hoboken)       Date:  2011-05-26       Impact factor: 2.064

3.  Overexpression of LAPTM4B: an independent prognostic marker in breast cancer.

Authors:  Min Xiao; Shusheng Jia; Hongbin Wang; Jinsong Wang; Yuanxi Huang; Zhigao Li
Journal:  J Cancer Res Clin Oncol       Date:  2013-01-06       Impact factor: 4.553

4.  Nuclear expression of survivin is associated with improved survival in metastatic ovarian carcinoma.

Authors:  Lilach Kleinberg; Vivi Ann Flørenes; Ilvars Silins; Kristiane Haug; Claes G Trope; Jahn M Nesland; Ben Davidson
Journal:  Cancer       Date:  2007-01-15       Impact factor: 6.860

5.  Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012.

Authors:  Jacques Ferlay; Isabelle Soerjomataram; Rajesh Dikshit; Sultan Eser; Colin Mathers; Marise Rebelo; Donald Maxwell Parkin; David Forman; Freddie Bray
Journal:  Int J Cancer       Date:  2014-10-09       Impact factor: 7.396

6.  LAPTM4B-35 protein as a potential therapeutic target in gastric cancer.

Authors:  Hongying Zhang; Buxian Tian; Hongyu Yu; Hongyue Yao; Zhian Gao
Journal:  Tumour Biol       Date:  2014-11-22

7.  STAT3-survivin signaling mediates a poor response to radiotherapy in HER2-positive breast cancers.

Authors:  Jae-Sung Kim; Hyun-Ah Kim; Min-Ki Seong; Hyesil Seol; Jeong Su Oh; Eun-Kyu Kim; Jong Wook Chang; Sang-Gu Hwang; Woo Chul Noh
Journal:  Oncotarget       Date:  2016-02-09

8.  LAPTM4B allele *2 is associated with breast cancer susceptibility and prognosis.

Authors:  Xiaoyan Li; Xiangnan Kong; Xi Chen; Ning Zhang; Liyu Jiang; Tingting Ma; Qifeng Yang
Journal:  PLoS One       Date:  2012-09-12       Impact factor: 3.240

9.  Survivin expression promotes VEGF-induced tumor angiogenesis via PI3K/Akt enhanced β-catenin/Tcf-Lef dependent transcription.

Authors:  Jaime G Fernández; Diego A Rodríguez; Manuel Valenzuela; Claudia Calderon; Ulises Urzúa; David Munroe; Carlos Rosas; David Lemus; Natalia Díaz; Mathew C Wright; Lisette Leyton; Julio C Tapia; Andrew Fg Quest
Journal:  Mol Cancer       Date:  2014-09-09       Impact factor: 27.401

10.  Gamabufotalin, a major derivative of bufadienolide, inhibits VEGF-induced angiogenesis by suppressing VEGFR-2 signaling pathway.

Authors:  Ning Tang; Lei Shi; Zhenlong Yu; Peipei Dong; Chao Wang; Xiaokui Huo; Baojing Zhang; Shanshan Huang; Sa Deng; Kexin Liu; Tonghui Ma; Xiaobo Wang; Lijun Wu; Xiao-Chi Ma
Journal:  Oncotarget       Date:  2016-01-19
View more
  20 in total

1.  Survivin Inhibitors Mitigate Chemotherapeutic Resistance in Breast Cancer Cells by Suppressing Genotoxic Nuclear Factor-κB Activation.

Authors:  Wei Wang; Bo Zhang; Arul M Mani; Zhongzhi Wu; Yu Fan; Wei Li; Zhao-Hui Wu
Journal:  J Pharmacol Exp Ther       Date:  2018-05-07       Impact factor: 4.030

2.  Multi-antigen-targeted T-cell therapy to treat patients with relapsed/refractory breast cancer.

Authors:  Valentina Hoyos; Spyridoula Vasileiou; Manik Kuvalekar; Ayumi Watanabe; Ifigeneia Tzannou; Yovana Velazquez; Matthew French-Kim; Wingchi Leung; Suhasini Lulla; Catherine Robertson; Claudette Foreman; Tao Wang; Shaun Bulsara; Natalia Lapteva; Bambi Grilley; Matthew Ellis; Charles Kent Osborne; Angela Coscio; Julie Nangia; Helen E Heslop; Cliona M Rooney; Juan F Vera; Premal Lulla; Mothaffar Rimawi; Ann M Leen
Journal:  Ther Adv Med Oncol       Date:  2022-07-15       Impact factor: 5.485

3.  Long Non-Coding RNA TP73-AS1 Promotes the Development of Lung Cancer by Targeting the miR-27b-3p/LAPTM4B Axis.

Authors:  Qingfeng Jiang; Wenqun Xing; Jinhua Cheng; Yongkui Yu
Journal:  Onco Targets Ther       Date:  2020-07-20       Impact factor: 4.147

4.  [Association of JMJD3, MMP-2 and VEGF expressions with clinicopathological features of invasive ductal breast carcinoma].

Authors:  Xiaoyan Xu; Jianjun Wang; Chen Yan; Yingli Men; Huang Jiang; Huijuan Fang; Xianwei Xu; Jinhua Yang
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2020-11-30

5.  TAB3 upregulates Survivin expression to promote colorectal cancer invasion and metastasis by binding to the TAK1-TRAF6 complex.

Authors:  Chen Luo; Rongfa Yuan; Leifeng Chen; Wei Zhou; Wei Shen; Yumin Qiu; Jun Shao; Jinlong Yan; Jianghua Shao
Journal:  Oncotarget       Date:  2017-11-18

6.  Prognostic Significance of BIRC5/Survivin in Breast Cancer: Results from Three Independent Cohorts.

Authors:  Nina Oparina; Malin C Erlandsson; Anna Fäldt Beding; Toshima Parris; Khalil Helou; Per Karlsson; Zakaria Einbeigi; Maria I Bokarewa
Journal:  Cancers (Basel)       Date:  2021-05-04       Impact factor: 6.639

7.  Long Noncoding RNA HCAL Facilitates the Growth and Metastasis of Hepatocellular Carcinoma by Acting as a ceRNA of LAPTM4B.

Authors:  Cheng-Rong Xie; Fei Wang; Sheng Zhang; Fu-Qiang Wang; Sen Zheng; Zhao Li; Jie Lv; He-Qiang Qi; Qin-Liang Fang; Xiao-Min Wang; Zhen-Yu Yin
Journal:  Mol Ther Nucleic Acids       Date:  2017-10-28

8.  AP4 positively regulates LAPTM4B to promote hepatocellular carcinoma growth and metastasis, while reducing chemotherapy sensitivity.

Authors:  Yue Meng; Lu Wang; Jianjun Xu; Qingyun Zhang
Journal:  Mol Oncol       Date:  2018-02-06       Impact factor: 6.603

9.  Detection of urinary survivin using a magnetic particles-based chemiluminescence immunoassay for the preliminary diagnosis of bladder cancer and renal cell carcinoma combined with LAPTM4B.

Authors:  Yang Yang; Jianjun Xu; Qingyun Zhang
Journal:  Oncol Lett       Date:  2018-03-22       Impact factor: 2.967

Review 10.  The Regulation and Function of the L-Type Amino Acid Transporter 1 (LAT1) in Cancer.

Authors:  Travis B Salisbury; Subha Arthur
Journal:  Int J Mol Sci       Date:  2018-08-12       Impact factor: 5.923

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.