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M. Nounou, Fatema Elamrawy, Nada Ahmed, Kamilia Abdelraouf, Satyanarayana Goda, Hussaini Syed-Sha-Qhattal (2015)Breast Cancer: Conventional Diagnosis and Treatment Modalities and Recent Patents and Technologies
Breast Cancer : Basic and Clinical Research, 9
D. Pan, P. Marcato, Dae-Gyun Ahn, S. Gujar, L. Pan, M. Shmulevitz, Patrick Lee (2013)Activation of p53 by Chemotherapeutic Agents Enhances Reovirus Oncolysis
PLoS ONE, 8
N. Harbeck, Michael Gnant (2017)Breast cancer
The Lancet, 389
M. Griffiths, M. Sinderen, Katarzyna Rainczuk, E. Dimitriadis (2019)miR-29c overexpression and COL4A1 downregulation in infertile human endometrium reduces endometrial epithelial cell adhesive capacity in vitro implying roles in receptivity
Scientific Reports, 9
H. Sung, P. Rosenberg, Wanqing Chen, M. Hartman, W. Lim, K. Chia, Oscar Mang, C. Chiang, D. Kang, R. Ngan, L. Tse, W. Anderson, Xiaohong Yang (2015)Female breast cancer incidence among Asian and Western populations: more similar than expected.
Journal of the National Cancer Institute, 107 7
Yixiao Feng, Mia Spezia, Shifeng Huang, Chengfu Yuan, Z. Zeng, Linghuan Zhang, Xiaojuan Ji, Wei Liu, Bo Huang, Wenping Luo, Bo Liu, Yan Lei, S. Du, Akhila Vuppalapati, H. Luu, R. Haydon, T. He, G. Ren (2018)Breast cancer development and progression: Risk factors, cancer stem cells, signaling pathways, genomics, and molecular pathogenesis
Genes & Diseases, 5
M. Gasco, S. Shami, T. Crook (2002)The p53 pathway in breast cancer
Breast Cancer Research : BCR, 4
V. Botchkarev, E. Komarova, F. Siebenhaar, N. Botchkareva, P. Komarov, M. Maurer, Barbara Gilchrest, A. Gudkov (2000)p53 is essential for chemotherapy-induced hair loss.
Cancer research, 60 18
M. Pathak, S. Dwivedi, S. Deo, B. Thakur, V. Sreenivas, G. Rath (2018)Neoadjuvant chemotherapy regimens in treatment of breast cancer: a systematic review and network meta-analysis protocol
Systematic Reviews, 7
F. Guo, Y. Kuo, Y. Shih, S. Giordano, A. Berenson (2018)Trends in breast cancer mortality by stage at diagnosis among young women in the United States
S. Assadian, W. El-Assaad, Xue Wang, Phillipe Gannon, V. Barrès, M. Latour, A. Mes-Masson, F. Saad, Y. Sado, J. Dostie, J. Teodoro (2012)p53 inhibits angiogenesis by inducing the production of Arresten.
Cancer research, 72 5
A. Waks, E. Winer (2019)Breast Cancer Treatment: A Review
C. Kemp, S. Sun, K. Gurley (2001)p53 induction and apoptosis in response to radio- and chemotherapy in vivo is tumor-type-dependent.
Cancer research, 61 1
R. Kalluri (2003)Basement membranes: structure, assembly and role in tumour angiogenesis
Nature Reviews Cancer, 3
K. Kühn (1995)Basement membrane (type IV) collagen.
Matrix biology : journal of the International Society for Matrix Biology, 14 6
A. Onitilo, J. Engel, R. Greenlee, B. Mukesh (2009)Breast Cancer Subtypes Based on ER/PR and Her2 Expression: Comparison of Clinicopathologic Features and Survival
Clinical Medicine & Research, 7
C. Selli, A. Sims (2019)Neoadjuvant Therapy for Breast Cancer as a Model for Translational Research
Breast Cancer : Basic and Clinical Research, 13
M. Athar, C. Elmets, L. Kopelovich (2011)Pharmacological activation of p53 in cancer cells.
Current pharmaceutical design, 17 6
M. Duffy, N. Synnott, J. Crown (2018)Mutant p53 in breast cancer: potential as a therapeutic target and biomarker
Breast Cancer Research and Treatment, 170
Zhen Wang, Yi Sun (2010)Targeting p53 for Novel Anticancer Therapy.
Translational oncology, 3 1
Justin Middleton, D. Stover, Tsonwin Hai (2018)Chemotherapy-Exacerbated Breast Cancer Metastasis: A Paradox Explainable by Dysregulated Adaptive-Response
International Journal of Molecular Sciences, 19
P. Bertheau, J. Lehmann-Che, M. Varna, A. Dumay, B. Poirot, R. Porcher, E. Turpin, L. Plassa, A. Roquancourt, E. Bourstyn, P. Crémoux, A. Janin, S. Giacchetti, M. Espié, H. Thé (2013)p53 in breast cancer subtypes and new insights into response to chemotherapy.
Breast, 22 Suppl 2
Yao‐Li Chen, Po-Ming Chen, P. Lin, Ya-Tze Hsiau, P. Chu (2016)ABCG2 Overexpression Confers Poor Outcomes in Hepatocellular Carcinoma of Elderly Patients.
Anticancer research, 36 6
G. Karagiannis, J. Pastoriza, Yarong Wang, A. Harney, D. Entenberg, Jeanine Pignatelli, Ved Sharma, Emily Xue, E. Cheng, Timothy D’alfonso, Joan Jones, J. Anampa, T. Rohan, J. Sparano, J. Condeelis, M. Oktay (2017)Neoadjuvant chemotherapy induces breast cancer metastasis through a TMEM-mediated mechanism
Science Translational Medicine, 9
M. Hou, Po-Ming Chen, P. Chu (2018)LGR5 overexpression confers poor relapse-free survival in breast cancer patients
BMC Cancer, 18
Hindawi Journal of Oncology Volume 2020, Article ID 5209695, 8 pages https://doi.org/10.1155/2020/5209695 Research Article Effect of COL4A1 Expression on the Survival of Neoadjuvant Chemotherapy Breast Cancer Patients 1 2,3 4 3 3 Shin-Mae Wang, Po-Ming Chen, Yu-Wen Sung, Wei-Chieh Huang, Hung-Sen Huang, 5,6,7 and Pei-Yi Chu Department of General Surgery, Show Chwan Memorial Hospital, Changhua 500, Taiwan Research Assistant Center, Show Chwan Memorial Hospital, Changhua 500, Taiwan Chinese Medical Research Center, China Medical University, Taichung 404, Taiwan Department of Obstetrics and Gynecologics, China Medical University Hospital, Taichung City, Taiwan School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei 242, Taiwan Department of Pathology, Show Chwan Memorial Hospital, Changhua 500, Taiwan Department of Health Food, Chung Chou University of Science and Technology, Changhua 510, Taiwan Correspondence should be addressed to Pei-Yi Chu; firstname.lastname@example.org Received 11 February 2020; Revised 7 April 2020; Accepted 29 April 2020; Published 15 May 2020 Academic Editor: Yongzhong Hou Copyright © 2020 Shin-Mae Wang et al. +is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Optimal therapy for each patient depends on their subtype, anatomic cancer stage, gene status, and preferences. Neoadjuvant chemotherapy-treated tumors have shown attenuated tumor growth, but the therapy cannot completely reduce tumor cell dissemination to blood stream and distant metastasis. +ough it has been indicated that the protein of the collagen type IV alpha 1 (COL4A1) gene is induced by p53 to inhibit angiogenesis and tumorigenic activity in cancer cells, its prognostic signiﬁcance in breast cancer (BC) patients has not yet been fully elucidated. We analysed 206 BC and fresh paired-match adjacent normal breast tissue from tissue microarrays (TMAs) and COL4A1-stained TMAs using immunohistochemistry. +ese were used to evaluate COL4A1 expression in BC and to analyse the relationship between this expression and clinicopathological factors and prognosis. +e expression of the COL4A1 protein was signiﬁcantly higher in normal adjacent tissue than in the tumor tissues of BC (P<0.0001). +e low COL4A1 expression of the BC patients had decreased metastasis incidence ratio than those exhibiting high COL4A1 expression (P � 0.034). Low COL4A1 expression in the tumor cells of BC patients was found to signiﬁcantly reduce the overall survival (OS) and relapse-free survival (RFS) rates of neoadjuvant chemotherapy patients (P � 0.047 and P � 0.025, respectively). We also validated the results to ensure their consistency with a web server program for survival analysis from the Cancer Genome Atlas (TCGA) database (P � 0.057). Additionally, COL4A1 expression was positively correlated with p53 expression (P � 0.00076). +us, we present clinical evidence that COL4A1 expression can be used as a biomarker of better prognosis of BC patients receiving neoadjuvant chemotherapy. similar longitudinal age-speciﬁc incidence probabilities 1. Introduction along with converging incidence rate ratios (IRRs) reveal Breast cancer (BC) is the most frequently diagnosed cancer that the age eﬀects are more similar among Asian and and the second leading cause of cancer-related mortality Western populations . Human mammary glands have a after lung cancer among women worldwide . Breast highly branched network of epithelial tubes, embedded cancer in Asian populations is characterized by an early- within the breast which undergoes changes in size, shape, onset and relatively younger median age upon diagnosis and function to puberty, pregnancy, and lactation, in re- than in Western populations . For invasive breast cancer, sponse to steroid hormone and growth factor receptor 2 Journal of Oncology signalling. However, the aberrant signalling pathways by primary surgery to the date of death. +e median overall which they contribute to breast carcinogenesis and breast survival of all breast cancer patients was 1485 days. During this survey, 25 patients died and 46 relapsed. On the basis of cancer type can be classiﬁed into various subtypes based on the expression of the estrogen receptor (ER), progesterone the follow-up data, 42 patients exhibited tumor metastasis, receptor (PR), and human epidermal growth factor 2 with the metastasis sites, including bone, lung, liver, chest (HER2) patterns, which implied signiﬁcant overall and wall, breast, and lymph node. +ere were 42 metastasis disease-free survival advantages [4–6]. TP53 (p53) is the cases: three in the lymph node, 19 in the breast, four in the most frequently mutated gene associated with greater dis- lung, one in the pleura, one in the liver, seven in the bone, ease aggression and worse overall survival . Although one in the chest wall, one in the chest skin, one in the breast mutated in 30–35% of all cases, p53 is mutated in ap- and lung, one in the liver and bone, one in the breast and proximately 80% of triple-negative (TN) tumors (i.e., tumors liver, one in multiple organs, and one in the bone and negative for ER, PR, and HER2) . So far, mutant p53 abdomen. +is project was approved by the Ethics Com- cannot be recommended as a prognostic or therapy pre- mittee of the Institutional Review Board of Show Chwan Memorial Hospital (IRB no. 1060407). dictive biomarker in BC, and some studies had until recently investigated it as a potential target for BC treatment [7, 8]. +e genetic and epigenetic changed in p53 have been 2.2. Immunohistochemistry and Scoring. identiﬁed in regulators of p53 activity as well as in some Immunohistochemistry (IHC) staining was used to evaluate downstream transcriptional targets of p53 in BC that express COL4A1 protein expression. +e COL4A1 antibody (NB120- wild-type p53 [7, 8]. 6586) was purchased from Novus Biologicals (Novus Biologi- p53 is not only a well-known activator of apoptosis or cals,Littleton,CO, USA).Please alsohavealook at https://www. cell cycle arrest in response to cellular stress or DNA novusbio.com/products/collagen-iv-alpha-1-antibody_nb120- damage stemming from protection of genomic stability, it 6586#PublicationSection. +e COL4A1 antibody (NB120-6586) also enhances antiangiogenic eﬀects, monitors tumor in- has been tested in human, mouse, rat, and bovine and ﬂammation and immune response, and inhibits metastases applied to immunocytochemistry (ICC), immunoﬂuores- [9, 10]. COL4A1 is a major antiangiogenic gene induced by cence (IF), immunohistochemistry (IHC-frozen sections p53 in human adenocarcinoma cells, and p53 directly and paraﬃn-embedded sections), enzyme-linked immu- activates the transcription of the COL4A1 gene by binding nosorbent assay (ELISA), and western blot (WB). Previously to an enhancer region 26 kbp downstream of its 3′ end . described IHC evaluation and protocol were used to obtain COL4A1, the collagen IV molecule, is 400nm long and score . +e mean signal scores were evaluated inde- involved in cell interactions with cells, possessing two pendently by the two pathologists who were blinded when speciﬁc recognition sites for the integrins alpha 1 beta 1 and assessing the samples. Immunostaining scores were deﬁned alpha 2 beta 1 . as the cell staining intensity (0 �nil; 1 �weak; 2 �moderate; We analysed 206 surgical specimens from patients with and 3 �strong) multiplied by the percentage of labeled cells breast cancer and adjacent normal tissue using IHC (0% to 100%), leading to scores from 0 to 300. +e mean of staining with a speciﬁc antibody against COL4A1 and score of signals was evaluated independently by the two evaluated the correlation between the clinical outcomes pathologists. +e median IHC staining score (75) was used and the IHC scores of COL4A1. We further investigated the as the cutoﬀ point for the dichotomization of COL4A1. A correlation between COL4A1 expression and long-term OS score greater than 75 was deﬁned as “high” immunostaining, and RFS in patients with breast cancer via Kaplan–Meier whereas a score of less than or equal to 75 was deﬁned as analysis. “low.” 2. Materials and Methods 2.3. Statistical Analysis. +e association between COL4A1 2.1. Patients. Contralateral primary breast tumor and ad- expression and the clinical and pathological parameters was jacent normal breast tissues were acquired from 206 BC calculated using chi-square and paired-sample t-tests, and patients receiving surgical resection at Changhua Show survival curves were plotted using the Kaplan–Meier Chwan Memorial Hospital from March 2011 to January method and compared using the log-rank test. Cox’s pro- 2017. Computed tomography (CT) was used for staging in portional hazard regression model was used to analyse the the breast cancer patients prior to surgery. +e diagnosis association between the variables and survival data. P<0.05 parameters and clinical outcomes were recruited until the was considered to indicate a statistically signiﬁcant diﬀer- patient’s death, censorship, or loss to follow-up. For each ence. SPSS 18.0 (SPSS, Inc., Chicago, IL, USA) was used for patient, representative tissue cores of the BC tumor section all statistical analyses. as well as the adjacent normal section were carefully col- lected and made into tissue microarray. +e age of all patients was between 30 and 95 years (mean±SD 2.4. Web Server Survival Analysis. +e survival analysis of 54.36± 11.62). Clinical parameters and overall survival COL4A1 expression of in this study was performed using the data were collected from a cancer registry system at the web server for the Kaplan–Meier plots from the Cancer Genome Atlas (TCGA) datasets by autoselecting the best Changhua Show Chwan Memorial Hospital. Survival time was deﬁned to be the period of time from the date of cutoﬀ values between the lower and upper quartiles into high Journal of Oncology 3 3.5. COL4A1 Expression as a Better Prognosis for Overall and low expression groups which are computed in all stages, gender, race, and mutation burden. Survival (OS) and Relapse-Free Survival (RFS) in BC Patients Who Received Neoadjuvant Chemotherapy. In BC patients Please have a look at https://kmplot.com/analysis/index. php?p�service&cancer�breast#. +e gene chip data sources who received neoadjuvant chemotherapy but not without for the databases include GEO, EGA, and TCGA. +e received neoadjuvant chemotherapy, we found that those primary purpose of the tool is the meta-analysis-based exhibiting a high expression of COL4A1 had longer OS discovery and validation of the survival biomarkers. All and RFS periods than those exhibiting a low expression as cutoﬀ values between the lower and upper quartiles, as well determined via Kaplan–Meier analysis (P � 0.047 and as the best performing threshold, were used as a cutoﬀ. P � 0.026, Figures 4(a) and 4(b)). As shown in Table 2, the low expression of COL4A1 was positively associated with the late-stage cancer (III and IV) (P � 0.046), but there was 3. Results no association between COL4A1 expression and age (P � 0.688). 42 patients with late-stage tumor had a lower 3.1. COL4A1 Expression Is Signiﬁcantly Higher in Normal overall survival and relapse-free survival rate compared Tissues. We enrolled 206 BC patients to estimate COL4A1 with early-stage cancer (P<0.0001, Figure 4). +e older protein detected using immunohistochemistry in 206 paired patients (≧65 years old) had a lower overall survival rate tumor and adjacent normal breast tissue. Representative than the younger patients (<65 y/o) (P �0.026, Figure 4), results are shown in Figures 1(a) and 1(b), and COL4A1 but there was no signiﬁcant in the relapse-free survival expression was observed in the cytoplasm of the tumor and rate. paired adjacent normal tissues. COL4A1 was expressed at higher levels in the breast cancer tissues compared to the 206 pairs of adjacent normal tissue (P<0.0001, Figure 1(c)). Of 3.6. COL4A1 mRNA Expression Is Positively Associated with the 206 pairs, the expression level of COL4A1 in the tumor p53 Expression and Identiﬁcation of COL4A1 mRNA Ex- tissue was higher than in the normal tissue from the 161 pairs pression in terms of Survival Rates of BC Patients Who Received (161/206, 78%). Neoadjuvant Chemotherapy in the Web Server. In terms of correlation, COL4A1 mRNA expression was positively associated with p53 mRNA expression (P � 0.00076, 3.2. COL4A1 Expression Is Positively Correlated with Tumor Figure 5(a)) as assessed via a web server program, an Metastasis. As shown in Table 1, low COL4A1 expression in enhanced web server for large-scale expression proﬁling tumors was signiﬁcantly associated with tumor metastasis and interactive analysis (http://gepia2.cancer-pku.cn/ (P � 0.034), but no signiﬁcant association was found in #correlation). +e breast cancer mRNA database was those over aged 65 (P � 0.421), with late-stage tumors searched to analyse the expression of COL4A1 mRNA in (P � 0.058), with positive ER expression (P � 0.092), with BC patients who received neoadjuvant chemotherapy and positive PR expression (P � 0.257), positive HER2 expres- the eﬀects on their overall survival. We found that low sion (P � 0.647), or who received neoadjuvant chemo- COL4A1 expression was associated with a poor prognosis therapy (P � 0.742). for overall survival (OS) for breast cancer patients who received neoadjuvant chemotherapy (P � 0.057, Figure 5(b)) (https://kmplot.com/analysis/index.php? 3.3. Age, Stage, ER, PR, Metastasis, and Neoadjuvant Che- p�service&cancer�breast). motherapy Characteristics Are Correlated with Overall Sur- vival (OS) in BC Patients. Kaplan–Meier survival curves further showed that late-stage tumors (P<0.001), ER-pos- 4. Discussion itive tumors (P � 0.0005), and PR-positive tumors Neoadjuvant chemotherapy is a standard of strategy that (P � 0.012) were associated with poor survival probability is widely used for locally advanced and early breast cancer (Figure 2). Furthermore, patients aged 65 and above patients . +e varying roles of the diﬀerent regimens (P<0.001), patients with metastasis (P<0.0001), and pa- used as neoadjuvant chemotherapy need to be investi- tients who received neoadjuvant chemotherapy (P<0.0001) exhibited poor survival probability (Figure 2). gated, as it is currently unclear which treatment regimen suits best . Prior to the surgical removal of the tumors, patients receive neoadjuvant chemotherapy and can 3.4. Age, Stage, Metastasis, and Neoadjuvant Chemotherapy downstage tumors allowing breast-conserving surgery, Characteristics as Independent Prognosis Factors in BC. rather than mastectomy and setting oﬀers a valuable We further examined whether the clinical parameters could opportunity to monitor individual tumor response . be the independent prognosis factors in BC patients. We Prior to the surgical removal of the tumors, patients re- performed Cox’s regression analysis with these factors in ceive neoadjuvant chemotherapy, can downstage tumors order to estimate the independent eﬀect of the OS of BC. In allowing breast-conserving surgery, rather than mastec- the multiple univariate analysis, age, stage, metastasis, and tomy and setting which oﬀers a valuable opportunity to neoadjuvant chemotherapy status were predictive of poor monitor individual tumor response . In 42 patients overall survival (P<0.001, 0.001, 0.001, and 0.002, respec- who received neoadjuvant chemotherapy, the expression tively; Figure 3). level of COL4A1 in the tumor, as assessed by 4 Journal of Oncology Normal_low COL4A1 Normal_high COL4A1 200 μm 200 μm (a) Tumor_low COL4A1 Tumor_high COL4A1 200 μm 200 μm (b) Tumor Normal (c) Figure 1: COL4A1 expression in adjacent normal and tumor breast tissue of BC patients. (a) Representative high COL4A1 immunostaining results in adjacent normal breast tissue. (b) Representative high COL4A1 immunostaining results in breast cancer tissue. (c) t-test for COL4A1 levels was compared in tumor and pair matched nontumor breast tissues of BC patients. Table 1: Relationship of clinical parameters with COL4A1 ex- immunohistochemistry, was not associated with age pression in 206 breast cancer. (Table 2), but was highly positively correlated with stage COL4A1 expression status (P � 0.046). Furthermore, the failure of neo- Characteristics No. P value adjuvant chemotherapy will make it more hospitable to Low (%) High (%) N �88 N �116 resisted cancer cells upon their arrival at the distant sites due to change in the nontumor tissue microenvironment Age <65 173 76 (44) 97 (56) 0.421 [16, 17]. ≥65 33 12 (36) 21 (64) +e clinical characteristics showed that the positive Stage expression of ER and PR tumors was associated with I, II 171 68 (40) 103 (60) 0.058 longer OS in BC patients (Figures 2(c) and 2(d)), but there III, IV 35 20 (57) 15 (43) was no signiﬁcant correlation on OS by the Cox regression ER model (Figure 3). Indeed, triple-negative breast cancers Negative 57 19 (33) 38 (67) 0.092 (TNBCs), which account for approximately 15% of all Positive 149 69 (46) 80 (54) breast cancer patients, are negative for ER, PR, and HER2 PR and exhibit poor prognosis and limited treatment options Negative 77 29 (38) 48 (62) 0.257 relative to other breast cancer subtypes . +e BC Positive 129 59 (46) 70 (54) patients who received neoadjuvant chemotherapy have HER2 Negative 33 13 (39) 20 (61) 0.647 poor prognosis by Kaplan–Meier analysis and Cox re- Positive 173 75 (43) 98 (57) gression that was because these patients had higher fre- Metastasis quency of the late tumor stage (17/42, 41%) (Figures 2(g) No 164 64 (39) 100 (61) 0.034 and 3; Table 2). Yes 42 24 (57) 18 (43) In this cohort, metastasis sites including bone, lung, Neoadjuvant chemotherapy liver, chest wall, breasts, and lymph nodes that shorten No 164 71 (43) 93 (57) 0.742 the survival rate of BC patients were correlated with low Yes 42 17 (40) 25 (60) COL4A1 IHC score Journal of Oncology 5 1.0 1.0 1.0 1.0 P = 0.004 P < 0.001 P = 0.006 P = 0.012 0.8 0.8 0.8 0.8 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 0.2 0.2 0.2 0.2 0.0 0.0 0.0 0.0 Days Days Days Days Age Stage ER PR > = 65 (N = 33) III, IV (N = 35) Negative (N = 57) Negative (N = 77) < 65 (N = 173) I, II (N = 171) Positive (N = 149) Positive (N = 129) (a) (b) (c) (d) 1.0 1.0 1.0 1.0 P = 0.381 P < 0.001 P < 0.001 P = 0.361 0.8 0.8 0.8 0.8 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 0.2 0.2 0.2 0.2 0.0 0.0 0.0 0.0 Days Days Days Days HER2 Metastasis Neoadjuvant chemotherapy COL4A1 Positive (N = 173) Yes (N = 42) Yes (N = 42) Low (N = 88) Negative (N = 33) No (N = 164) No (N = 164) High (N = 118) (e) (f) (g) (h) Figure 2: Kaplan–Meier analysis of diﬀerent characteristics for patients. (a) Overall survival estimates for age. (b) Overall survival estimates for tumor stage. (c) Overall survival estimates for ER. (d) Overall survival estimates for PR. (e) Overall survival estimates for HER2. (f) Overall survival estimates for tumor metastasis. (g) Overall survival estimates for neoadjuvant chemotherapy. (h) Overall survival estimates for COL4A1 expression. Cox regression analysis for the inﬂuence of stage and COL4A1 on overall survival in breast cancer patients. Characteristics HR Unfavourable/favourable P value 95% CI Age 20.395 ≥65/ <65 <0.001 Stage 6.205 III, IV/ I, II 0.001 ER 0.714 Negative/ positive 0.631 PR 0.884 Negative/ positive 0.868 HER2 1.173 Negative/ positive 0.853 Metastasis 8.882 Yes/ no 0.001 Chemotherapy 6.861 Yes/ no 0.002 COL4A1 1.664 High/ low 0.287 0.1 1 10 100 Figure 3: Cox regression analysis for the inﬂuence of parameters and COL4A1 on overall survival in all BC patients. Statistical tests were two sided. HR �hazard ratio and CI �conﬁdence interval. COL4A1 protein expression (Table 1). Tumor metastasis COL4A1 downregulation in infertile human endome- correlated with worse prognosis, and COL4A1 expres- trium reduces endometrial epithelial cell adhesive ca- sion in BC patients who received neoadjuvant chemo- pacity , which implied COL4A1 expression can therapy could predict favourable OS and RFS as assessed inhibit primary tumor segregation and result in via the Kaplan–Meier method (Figures 4(a) and 4(b)). metastasis. OS OS 0 0 1000 1000 2000 2000 3000 3000 4000 4000 5000 5000 6000 6000 OS OS 0 0 1000 1000 2000 2000 3000 3000 4000 4000 5000 5000 6000 6000 OS OS 0 0 1000 1000 2000 2000 3000 3000 4000 4000 5000 5000 6000 6000 OS OS 0 0 1000 1000 2000 2000 3000 3000 4000 4000 5000 5000 6000 6000 6 Journal of Oncology 1.0 1.0 1.0 P = 0.047 P < 0.0001 P = 0.026 0.8 0.8 0.8 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0.0 0.0 0.0 0 1000 2000 3000 4000 5000 6000 0 1000 2000 3000 4000 5000 6000 0 1000 2000 3000 4000 5000 6000 Days Days Days COL4A1 Stage Age Low (N = 17) III, IV (N = 17) >=65 (N = 4) High (N = 25) I, II (N = 25) <65 (N = 38) (a) (b) (c) 1.0 1.0 1.0 P = 0.025 P < 0.0001 P = 0.375 0.8 0.8 0.8 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0.0 0.0 0.0 0 1000 2000 3000 4000 5000 6000 0 1000 2000 3000 4000 5000 6000 0 1000 2000 3000 4000 5000 6000 Days Days Days COL4A1 Stage Age Low (N = 17) III, IV (N = 17) >=65 (N = 4) High (N = 25) I, II (N = 25) <65 (N = 3 8) (d) (e) (f) Figure 4: Kaplan–Meier analysis for the inﬂuence of COL4A1 expression, stage, and age on overall survival (OS) and relapse-free survival (RFS) in BC patients with neoadjuvant chemotherapy. (a) Overall survival estimates for COL4A1 expression. (b) Overall survival estimates for stage. (c) Overall survival estimates for age. (d) Relapse-free survival estimates for COL4A1 expression. (e) Relapse-free survival estimates for stage. (f) Relapse-free survival estimates for age. Table 2: Relationship of age, stage, and COL4A1 expression in 42 COL4A1 is a major transcriptional target of p53 . We breast cancer patients who received neoadjuvant chemotherapy. found COL4A1 expression contributed to the better prognosis in BC patients who received neoadjuvant COL4A1 expression chemotherapy. Characteristics No. P value Low (%) High (%) +e p53 protein rapidly accumulates in cells in response N �17 N �25 to chemotherapy, which is important for tumor suppres- Age sion by p53, and implicit in the p53 induction-apoptosis <65 38 15 (39) 23 (61) 0.683 pathway inhibiting tumor cells, especially in T-cell lym- ≥65 4 2 (50) 2 (50) phomas, intestinal adenomas, and mammary tumors Stage [20–24]. However, p53-induced COL4A1 function is still I, II 25 7 (28) 18 (72) 0.046 III, IV 17 10 (59) 7 (41) unknown in BC patients who received neoadjuvant che- motherapy. We further calculated the correlation between p53 and COL4A1 by GEPIA2 (P � 0.00076, R �0.1, Several types of collagen have been identiﬁed to Figure 5(a)) (http://gepia2.cancer-pku.cn/#correlation) process antiangiogenic domains that can be released by and investigated the COL4A1 prognostic impact on BC proteolysis of the basement membrane (BM), a special- patients who received neoadjuvant chemotherapy ized form of the extracellular matrix [19, 20], and (P � 0.057, Figure 5(b)) . RFS OS RFS OS RFS OS Journal of Oncology 7 Neoadjuvant chemotherapy breast cancer 1.0 HR = 0.47 (0.21 – 1.04) P value = 0.00076 Logrank P = 0.057 R = 0.1 0.8 0.6 0.4 0.2 0.0 34567 89 0 10 20 30 40 50 60 Time (months) Log2 (COL4A1 TPM) Number at risk Low 38 36 34 31 28 23 15 High 118 117 106 82 55 38 23 COL4A1 Expression Low High (a) (b) Figure 5: +e web server for the COL4A1 expression analysis. (a) Pearson’s correlation for p53 and COL4A1 expression. (b) Kaplan–Meier analysis of the inﬂuence of and COL4A1 expression on overall survival (OS) in BC patients with neoadjuvant chemotherapy. 5. Conclusion Ethical Approval In conclusion, we proposed for the ﬁrst time that COL4A1 could +is study was approved by the Ethics Committee of the act as a prognostic marker of survival for BC patients who Institutional Review Board of Show Chwan Memorial underwent neoadjuvant chemotherapy. Despite the modest Hospital (IRB 1060407). sample size of the analysed BC samples, this study successfully provided the prognosis marker and therapeutic targets for BC Disclosure patientswhoreceivedneoadjuvantchemotherapy.Ourresultsare helpfulintheevaluationofBCpatientswhoreceivedneoadjuvant Shin-Mae Wang and Po-Ming Chen are the co-ﬁrst authors. chemotherapy before the surgical removal of a tumor. Abbreviations Conflicts of Interest COL4A1: Collagen type IV alpha 1 +e authors conﬁrm that there are no conﬂicts of interest BC: Breast cancer associated with this publication. TMAs: Tissue microarrays OS: Overall survival RFS: Relapse-free survival Authors’ Contributions IRRs: Incidence rate ratios ER: Estrogen receptor Shin-Mae Wang and Po-Ming Chen contributed equally. PR: Progesterone receptor HER2: Human epidermal growth factor 2 IHC: Immunohistochemistry. Acknowledgments +is work was funded by grants RB 17004 and RD 1060407 Data Availability from Show Chwan Memorial Hospital, Taiwan and grants +e raw and derived data used to support the ﬁndings of this MOST103-2314-B-442-002-MY3 and MOST106-2314-442- 002-MY3 from the Ministry of Science and Technology, study are available from the corresponding author upon Taiwan. request. Log2 (p53 TPM) Probability 8 Journal of Oncology  M. Griﬃths, M. Van Sinderen, K. Rainczuk et al., “miR-29c References overexpression and COL4A1 downregulation in infertile  F. Guo, Y. F. Kuo, Y. C. T. Shih, S. H. Giordano, and human endometrium reduces endometrial epithelial cell A. B. Berenson, “Trends in breast cancer mortality by stage at adhesive capacity in vitro implying roles in receptivity,” diagnosis among young women in the United States,” Cancer, Scientiﬁc Reports, vol. 9, no. 1, p. 8644, 2019. vol. 124, no. 17, pp. 3500–3509, 2014.  R. Kalluri, “Basement membranes: structure, assembly and  N. Harbeck and M. Gnant, “Breast cancer,” :e Lancet, role in tumour angiogenesis,” Nature Reviews Cancer, vol. 3, vol. 389, no. 10074, pp. 1134–1150, 2017. no. 6, pp. 422–433, 2003.  H. Sung, P. S. Rosenberg, W. Q. Chen et al., “Female breast  V. A. Botchkarev, E. A. Komarova, F. Siebenhaar et al., “p53 is cancer incidence among Asian and Western populations: essential for chemotherapy-induced hair loss,” Cancer Re- more similar than expected,” JNCI: Journal of the National search, vol. 60, pp. 5002–5006, 2000. Cancer Institute, vol. 107, no. 7, 2015.  C. J. Kemp, S. Sun, K. E. Gurley et al., “p53 induction and  A. A. Onitilo, J. M. Engel, R. T. Greenlee, and B. N. Mukesh, apoptosis in response to radio- and chemotherapy in vivo is “Breast cancer subtypes based on ER/PR and Her2 expression: tumor-type-dependent,” Cancer Research, vol. 61, pp. 327– comparison of clinicopathologic features and survival,” 332, 2001. Clinical Medicine & Research, vol. 7, no. 1-2, pp. 4–13, 2009.  Z. Wang and Y. Sun, “Targeting p53 for novel anticancer  M. I. Nounou, F. ElAmrawy, N. Ahmed, K. Abdelraouf, therapy,” Translational Oncology, vol. 3, no. 1, pp. 1–12, 2010. S. Goda, and H. Syed-Sha-Qhattal, “Breast cancer: conven-  M. Athar, A. C. Elmets, L. Kopelovich et al., “Pharmacological tional diagnosis and treatment modalities and recent patents activation of p53 in cancer cells,” Current Pharmaceutical and technologies,” Breast Cancer: Basic and Clinical Research, Design, vol. 17, no. 6, pp. 631–639, 2011. vol. 9, no. 2, pp. 17–34, 2015.  D. Pan, P. Marcato, and D. G. Ahn, “Activation of p53 by  A. G. Waks and E. P. Winer, “Breast cancer treatment,” chemotherapeutic agents enhances reovirus oncolysis,” PLoS JAMA, vol. 321, no. 3, pp. 288–300, 2019. One, vol. 8, no. 1, Article ID e54006, 2013.  M. Gasco, V. Shami, and T. Crook, “+e p53 pathway in breast cancer,” Breast Cancer Research, vol. 4, no. 2, pp. 70–76, 2002.  M. J. Duﬀy, N. C. Synnott, J. Crown et al., “Mutant p53 in breast cancer: potential as a therapeutic target and bio- marker,” Breast Cancer Research and Treatment, vol. 170, no. 2, pp. 213–219, 2018.  Y. Feng, M. Spezia, S. Huang et al., “Breast cancer develop- ment and progression: risk factors, cancer stem cells, signaling pathways, genomics, and molecular pathogenesis,” Genes & Diseases, vol. 5, no. 2, pp. 77–106, 2018.  P. Bertheau, J. Lehmann-Che, M. Varna et al., “p53 in breast cancer subtypes and new insights into response to chemo- therapy,” :e Breast, vol. 22, no. 2, pp. S27–S29, 2013.  S. Assadian, W. El-Assaad, X. Q. D. Wang et al., “p53 inhibits angiogenesis by inducing the production of Arresten,” Cancer Research, vol. 72, no. 5, pp. 1270–1279, 2012.  K. Kuhn, ¨ “Basement membrane (type IV) collagen,” Matrix Biology, vol. 14, no. 6, pp. 439–445, 1995.  Y. L. Chen, P. M. Chen, P. Y. Lin, Y. T. Hsiau, and P. Y. Chu, “ABCG2 overexpression confers poor outcomes in hepato- cellular carcinoma of elderly patients,” Anticancer Research, vol. 36, no. 6, pp. 2983–2988, 2016.  M. Pathak, S. N. Dwivedi, and S. V. S. Deo, “Neoadjuvant chemotherapy regimens in treatment of breast cancer: a systematic review and network meta-analysis protocol,” Systematic Reviews, vol. 7, no. 1, p. 89, 2018.  C. Selli and A. H. Sims, “Neoadjuvant therapy for breast cancer as a model for translational research,” Breast Cancer: Basic and Clinical Research, vol. 13, 2019.  J. D. Middleton, D. G. Stover, and T. Hai, “Chemotherapy- exacerbated breast cancer metastasis: a paradox explainable by dysregulated adaptive-response,” International Journal of Molecular Sciences, vol. 19, no. 11, 2018.  G. S. Karagiannis, J. M. Pastoriza, Y. Wang et al., “Neo- adjuvant chemotherapy induces breast cancer metastasis through a TMEM-mediated mechanism,” Science Transla- tional Medicine, vol. 9, no. 397, 2017.  M.-F. Hou, P.-M. Chen, and P.-Y. Chu, “LGR5 over- expression confers poor relapse-free survival in breast cancer patients,” BMC Cancer, vol. 18, no. 1, p. 219, 2018.
Journal of Oncology – Hindawi Publishing Corporation
Published: May 15, 2020
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