Clinical significances of RPL15 gene expression in circulating tumor cells of patients with breast cancer
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- Published online on: March 11, 2025 https://doi.org/10.3892/br.2025.1960
- Article Number: 82
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Copyright: © Zhuang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
The incidence of breast cancer (BC) in women always is increasing and rank first according to statistics in China and other countries, worldwide (1,2). The mortality rate of patients with BC ranks second after lung cancer, which account for ~30% of cancers in women (3,4). According to the World Health Organization (WHO) report, ~2 million new patients with BC are diagnosed per year, and this has been attributed to the increased life span and improved medical care worldwide (5-7). Recently, the mortality rate of patients with BC has decreased because of early screening with mammography and advanced therapeutic methods, such as targeted and immune therapies (8-13) or the combination of ferroptosis with photodynamic therapy (14). However, for those patients with advanced BC, 5-year survival rate is only 5-10% (15); therefore, a sensitive and reliable biomarker is critical for predicting the outcomes of patients with BC.
Emerging evidence indicates that the detection of circulating tumor cells (CTCs) in peripheral blood are markedly related to the recurrence, metastasis and the outcomes of numerous cancers (16-18). CTCs originate from primary tumor or metastatic tumors and enter peripheral circulation, potentially giving rise to tumor cell proliferation in other parts of the body undergoing epithelial-mesenchymal transition (EMT) (16,19-21). CTCs can be divided into epithelial CTCs (eCTCs), mesenchymal CTCs (MCTCs) and hybrid CTCs (HCTCs), which express EpCAM and ck8/18/19 as epithelial marker and vimentin combined twist as mesenchymal marker, respectively (19,22). Initially, EpCAM was considered as a major marker for epithelial cell because it is a transmembrane glycoprotein and mediates cell-cell adhesion of epithelial tissues (23,24), but later cytokeratin 8/18/19CTCs combined EpCAM measurements to enhance epithelial cell specificity because cytokeratin 8/18/19 proteins are essential components of the cytoskeleton in epithelial cells (25,26). In addition, vimentin was identified as a mesenchymal cell marker and twist was a relevant transcription factor for mesenchymal cells (27). Therefore, EMT markers are more likely to reflect biological functions of CTCs. CTCs' detecting methods were varied dependent on available equipment and patients' status, including density-gradient centrifugation, filtration approaches, flow cytometry, immunohistochemistry (IHC), glycolysis-associated long non-coding RNAs (IncRNAs) (20), long non-coding RNA detection (28), and RNA in situ hybridization (RNA-ISH) (29-32). Among these techniques, RNA-ISH has numerous advantages over other methods, such as high sensitivity, less CTCs loss, detecting CTCs undergoing EMT (33).
The relationship between the numbers of CTCs and the prognosis of patients with cancer were extensively investigated (34-37). Recent studies have revealed that the overall survival (OS) of patients with higher CTCs number was significantly shorter than that of patients with low CTCs number (38,39). Therefore, measurement of the CTCs number is very helpful for predicting the outcomes of patients with cancer and guiding treatment decisions.
Recently, Ebright et al (40) identified a ribosomal submit, ribosomal protein L15 (RPL15) gene, that plays a role in BC metastasis during an in vivo genome-wide CRISPR screening of CTCs from patients with hormone receptor positive (HR+) BC. It was found that RPL15 overexpression was strongly associated with the metastatic growth of BC in numerous organs of patients and a poor prognosis. RPL15 gene encodes the 60S RPL15, which catalyzes protein synthesis (41). A previous study showed that RPL15 also enhances drug resistance to chemotherapy in patients with gastric cancer (42); however, the exact mechanism of RPL15 action in cancer development remains unclear. It was hypothesized that RPL15 overexpression in CTCs promotes recurrence and metastasis of BC. To address this hypothesis, the CanPatrol technique was used to detect RPL15 gene expression in CTCs of patients with BC and evaluate the relationship between RPL15 expression and patient outcomes. Therefore, patients with BC were recruited to measure their CTCs and RPL15 expression before treatment. The results provide insights into the metastatic mechanisms of BC and can be helpful for guiding clinical treatment decision.
Materials and methods
Study design and subjects
The present study recruited 170 patients with BC to evaluate the outcomes of patients with various CTCs levels. Female patients who were 27-83 years-old and admitted to the Hubei Cancer Hospital from November 2007 to July 2022 were included in the present study. The criteria for enrollment were as follows: i) age >18 years; ii) BC diagnosis confirmed by two independent clinical pathologists in tumor biopsy or fine-needle aspiration samples and combined computerized tomography (CT) scan images; iii) tumor-node-metastasis (TNM) stages I-III determined according to proposal criteria in AACR-8th edition (43); iv) with estrogen receptor (ER), progesterone receptor (PR) and epidermal growth factor receptor 2 (HER2) expression detected via IHC before surgery; and v) complete medical data and follow-up record. The following exclusion criteria were applied to the present study: i) incomplete clinical data; ii) lost to follow-up; and iii) no previous therapies, such as surgery, chemotherapy, or radiotherapy before the study. In addition, 10 patients with breast benign nodule were also recruited as a control. The present study was reviewed and approved (approval no. 2024-264) by the Ethical Committee of the Hubei Cancer Hospital (Wuhan, China). Written informed consent was obtained from all patients before the study. The present study was conducted in accordance with the principles of Declaration of Helsinki (2013 version).
CTCs enrichment and analysis
During EMT transition of CTCs, eCTCs, MCTCs and HCTCs subtypes can be differentiated using EpCAM and CK8/18/19 for eCTCs biomarker, Vimentin and Twist for mesenchymal biomarker measurement. In the present study, CanPatrol™ technology was utilized to detect these biomarker-branched DNA (bDNA) (24). Briefly, CTCs were enriched via a filter-based process, then different CTCs subtypes were identified using an RNA-ISH technique.
CTCs enrichment was performed as previously described (19), and none of the patients received any therapy before the present study. To enrich CTCs in the peripheral blood of patients with BC, 5 ml of whole blood was collected from enrolled patients and was transferred into an EDTA-coated tube one day just before treatment. Blood samples was immediately processed or stored at 4˚C for <4 h before the next step. To obtain white blood cells, erythrocytes were mixed with 15 ml red blood lysis buffer and incubated for 30 min at room temperature (RT). After centrifugation for 5 min with 300 x g at RT, the supernatant was discarded. The cells were then washed twice with phosphate-buffered saline (PBS). The collected cells were transferred into a filter tube with 8-µM pore size membrane and connected with the vacuum filtration system at 0.08 MPa. The filtered cells were fixed in 4% paraformaldehyde (PFA) for 1 h at RT.
CTCs and RPL15 gene detection using mRNA probes in RNA-ISH
To evaluate total CTCs and subtypes as well as RPL15 gene expression in the peripheral blood of patients with BC, the RNA-ISH technique was employed to detect specific genes based on the bDNA signal amplification technique because this technique is more powerful for rare gene expression. The bDNA signal amplification employs specific capture probes to bind the target gene sequences and combine bDNA signal amplification probes, including preamplifier sequence, the amplifier sequences and the label probes (24,44). The pre-amplifier sequence was designed to recognize the capture and bDNA amplifier sequences. The label probes were conjugated with fluorescent dye and counted under fluorescence scanning microscope (24). Briefly, previous fixed samples were digested with 0.1 mg/ml proteinase K for 30 min at 4˚C to enhance the cell membrane permeability. After rinsing twice with PBS solution, the following capture probes were added to the hybridization solution and incubated for 2 h at 40˚C: EpCAM and CK8/18/19 for epithelial biomarker; Vimentin and Twist for mesenchymal biomarker; RPL15 bDNA probes. These bDNA specific probes were custom-made and purchased from Invitrogen; Thermo Fisher Scientific; Inc. based on their gene sequences. To deduce background signals, the cells were washed twice with 0.1X SSC eluent (MilliporeSigma). Cells were then added pre-amplification and amplification solution and incubated at 40˚C for 90 min to obtain a strong signal after adding Alexa Fluor (AF) 594 conjugated EpCAM and CK8/18/19 detection probe, AF488 conjugated Vimentin and Twist probe, and AF750 conjugated RPL15 probe for 60 min incubation. Finally, DAPI was added into samples for cellular nucleus staining. Images were obtained using fluorescence scanning microscope at x100 magnification (Olympus BX53; Olympus Corporation).
Criteria for CTCs and RPL15 gene expression positivity
Positive eCTCs, MCTCs, HCTCs, and RPL15 cells were determined and counted under a fluorescence microscope, following the manufacturer's instructions (SurExam; http://www.surexam.com). Only red or green fluorescence signal spots on cell surface represent eCTCs and MCTCs, respectively. If there were both red and green spots on cell surface, these cells were classified as HCTCs. The purple fluorescence signal dots represent RPL15 gene on cellular surface. The positive RPL15 gene was counted with ≥1 purple dots/5 ml peripheral blood on CTC, MCTCs, or HCTCs. No any purple dots on CTCs were observed and defined as RPL15 negative. Images of 5 microscopy fields were randomly captured and average number of CTCs in each field was counted. These cell-specific images and characteristics are presented in Fig. 1 and Table I.
HR detection using IHC and fluorescence in-situ hybridization (FISH)
HR expression levels, including ER, PR and HER2, were detected via IHC for ER and PR or FISH for HER2. Tumor samples were prepared as 4-µM wide sections and mounted into slides. The primary antibodies at 1:1,000 dilution were incubated overnight at 4˚C and the secondary antibody at 1:1,000 dilution were incubated at RT for 1 h according to the manufacturer's instructions (Roche Diagnostics). ER- and PR-positive cells were identified by at least three certified pathologists. Positive HER2 cells were quantified using FISH method (Sinomdgene; https://www.sinogenepets.com). Briefly, the deparaffinized sections of formalin-fixed paraffin-embedded tumor tissue were incubated with a serial of reagents. HER2 specific DNA probe labeled with spectrum orange and chromosome enumeration probe (CEP17) labeled with spectrum green were added to slides for staining. The cells were observed and counted under a fluorescence microscope following the 2018 ASCO/CAP criteria (45).
Disease status follow-up
All patients were followed up to 24 months by visitor phone call by every three months in the first half year, then every six months thereafter. Follow-up data included disease symptoms, chest computed tomography (CT), skull magnetic resonance imaging, whole-body bone scan, abdominal color ultrasound, and positron emission tomography. Signs of recurrence and metastasis were determined by image data showing space-occupying lesions in the chest and other organs. Progression-free survival (PFS) was defined as time from treatment to recurrence.
Statistical analysis
All data analysis was performed using GraphPad Prism 9.0 version (Dotmatics). A comparison of the relationship between continuous or categorical variables and patient demographics was performed using the paired t-test and χ2 tests. Cox proportional hazard regression model were used to investigate the factors (age, MCTCs, HCTCs, RPL15, ER, PR and HER2) impacting patients' outcomes. In this model, age, MCTCs, HCTCs, RPL15, ER, PR and HER2 were as variables and PFS was as events at 24 months cut-off. Hazard ratio (HR), 95% confidence intervals (CI), and P-values were compared in varous groups. The assessment of Schoenfeld's residuals was used to ensure the assumptions have not been violated. The PFS curve of patients was plotted by the Kaplan-Meier method after the log-rank test. A power calculation was used to determine differences in PFS of the subgroups. P<0.05 was considered to indicate a statistically significant difference.
Results
Patient clinico-pathological charateristics
All patients were female, and ages ranged from 27-83 years-old (median, 59 years-old; mean ± SD, 50.95±10.76 years-old). A total of 29 patients were ≥65 years-old (range 61-63) (29/170, 17.1%) and 141 patients were <60 years-old (range 27-60, 141/170, 82.9%). A total of 152 patients had invasive ductal carcinoma (IDC) (89.4%), and the rest of the study cohort included 3 patients with invasive lobular carcinoma (ILC, 1.8%), 8 with ductal carcinoma in situ (DCIS, 4.8%), 2 with mucinous carcinoma (MC, 1.1%), 2 with metaplastic carcinoma (MeC, 1.1%) and 3 with papillary carcinoma (PC, 1.8%), r espectively. Regarding patient TNM stages, 70 were stage I (70/170, 41.2%), 72 were stage II (72/170, 42.3%), 20 were stage III (20/170, 11.7%), and 8 patients had DCIS (8/170,4.8%) based on criteria recommended by AACR-8th edition (43). ER, PR and HER2 were measured using IHC and FISH methods. Regarding HR+ status, 114 were ER+ (114/170, 67.1%), 105 were PR+ (105/170, 61.8%), 88 were HER2+ (88/170, 51.8%), and 12 triple-negative BC (TNBC, 25/170, 14.7%). All patients performed surgery, 162 cases (95.3%) of which added chemotherapy. Additionally, 90 patients (52.9%) experienced immunotherapy using anti-PD1 administration (Table II).
CTCs and RPL15 expression in patients with BC
CTCs and RPL15 gene expression are strongly associated with tumorigenesis and the outcome of patients with BC. CTCs, CTCs' subtypes and RPL15 expression level in patients with BC were detected in the present study using CanPatrol technology combined triple color in situ RNA hybridization (Table I and Fig. 1). These specific biomarkers possess unique cellular surface molecules that can be labeled with differentiated fluorochromes and counted under a fluorescence microscope. For positive RPL15 expression, CTC, MCTCs, or HCTCs were firstly counted, then RPL15 gene expression was calculated on these CTCs. As can be observed in Table III, no significant differences were found in total CTCs, eCTCs, MCTCs, HCTCs and RPL15 on TCTCs between patients aged ≥60 years and those <60 years. Furthermore, the CTCs in patients with different pathological subtypes, including IDC, ILC, DCIS, PC, MeC and MC, did not significantly differ. Interestingly, CTCs and RPL15 on the total CTCs of patients with BC were strongly associated with TNM stage (P=0.021) and HR levels (P=0.13). Positive CTCs and RPL15 on CTC rates were significantly increased in advanced TNM. Furthermore, patients with TNBC had significantly higher CTCs and PRL15 expression than those with other HR types. Recent data have shown that CTCs and RPL15 expression are significantly associated with TNM stages and HR expression levels in patients with BC.
The prediction of recurrence and metastaisis in patients with BCusing multivariate COX regression analysis
To further evaluate the outcomes of patients with different clinical characteristics, recurrence and metastasis in patients were predicted via multivariate COX proportional hazard regression analysis using age, MCTCs, HCTCs, RPL15 on TCTCs, ER, PR and HER2 as co-variates. The follow-up time was variable, and PFS as well as relapse were defined as events. Age, CTC cut-off values, RPL15, ER, PR, HER2 positive or negative expression were used as the other variable, and Graphpad Prism softare was used for statitical analysis. A total of 24 months follow-up was set as cut-off duration for recurrence,metastasis and PFS time (Table IV). These cut-off values of biomarker expressive levels in patients with BC were determined according to RPL15 CTCs and levels of 10 patients with breast benign nodule, which can distinguish benign and malignant breast mass with >80% sensitivity and specificity at these cut-off values. The patients with ≥/<60 years of age, ER+/- and PR+/- expression were not determining factors for recurrenece and metastasis. By contrast, high MCTCs, HCTCS, positive RPL15 on CTCs had 2.73, 2.38, 1.83 and 2.76 HR for recurrence and metastasis, which mean that relapse and metastasis chances of patients with high MCTCs (>2), HCTCs (>5), and positive RPL15 were 2.73,2.38 and 2,76-fold than that of patients with low MCTCs (≤2), HCTCs (≤5) and negative RPL15, respectively. The PFS of patients with low MCTCs, low HCTCs, negative RPL15 gene expression and negative HER2 expression was significantlylonger than that of the patients with positive expression levels, respectively (P<0.05).
 | Table IVMultivariate analysis of risk factors for recurrence and metastasis in patients with breast cancer. |
Survival comparison of patients with various CTCs, RPL15 and HR expression by Kaplan-Meier analysis
The multivariate COX regress analysis showed that MCTCs, HCTCs, RPL15 and positive HER2 were critical risk factors for recurrence and metastasis of patients with BC;a survival analysis of patient with different CTCs and RPL15 levels was further carried out via a Kaplan-Meier survival analysis (Fig. 2). Different cut-off values for total CTCs and subtypes were set to compare PFS duration. The results demonstrated that PFS of patients with >7/≤7 TCTCs (Fig. 2A), positive/negative eCTCs (Fig. 2B) did not significatly differ (P>0.05). By contrast, the PFS of patients with low MCTCs (Fig. 2C), HCTCs (Fig. 2D) and RPL15 on TCTCs (Fig. 2E) was significantly longer than that of patients with high MCTCs, HCTCs, and positive RPL15 expression. The associated HRs, 95% CIs, and P-value were: HR, 4.818; 95% CI, 3.053-7.604; P<0.0001 for MCTCs; HR, 2.928; 95% CI, 2-4.288; P<0.001 for HCTCs; HR, 2.134; 95% CI, 1.446-3.15; P<0.001 for RPL15 (Fig. 2 and Table V). These data revealed that high MCTCs, HCTCs, and positive RPL15 expression on CTCs were critical risk factors for prognosis of patients with BC.
The PFS durations of patients with different HR expression levels was also compared (Fig. 3 and Table VI). The results identified that PFS duration of patients with positive and negative ER (Fig. 3A) or PR (Fig. 3B) was not significant differences (P>0.05). By contrast, the PFS of patients with positive HER2 expression was significantly shorter than that of patients with negative HER2 (Fig. 3C; HR, 1.929; 95% CI, 1.33-2.797; P=0.0014). The PFS of patients with and without TNBC were also compared (Fig. 3D), and the following results were observed: HR, 3.734; 95% CI, 1.573-8.862; P<0.001 (Table VI).
Discussion
Numerous prior studies have indicated that CTCs are critical biomarkers for predicting tumor recurrence and metastasis. Notably, the results of the present study showed that patients with high MCTCs, HCTCs, RPL15 positivity, and HER2 positivity had significantly poorer survival times than those without. In addition, the PFS of patients with TNBC was significanlty shorter than that of patients without TNBC.
BC is an exceedingly prevalent disease in women and can frequently recur (46,47). Chemotherapy is a critical therapeutic option for patients with advanced-stage cancers; however, the pathologic types of BC are very heterogeneous and occur in various locations (48). Most patients eventually experience relapse owing to drug resistance; therefore, there is an urgent need to identify sensitive and reliable biomarkers for predicting patient prognosis. Recently, CTCs have received increasing attention because they have the same features at the primary and metastatic sites (49), and CTC detection has been extensively used to predict the outcomes of numerous types of cancers (19,22,49,50). CanPatrol combined with RNA-ISH has been utilized to detect CTCs levels in patients with non-small cell lung cancer (NSCLC) and achieved 81.6% sensitivity and 86.8% specificity at 0.5 CTCs/5 ml cut-off (19). This technique has also been used to determine CTCs and programmed cell death-ligand 1 (PD-L1) expression in patients with NSCLC (50). The results indicated high levels of TCTCs, MCTCs and PD-L1 (+) CTCs levels in patients correlate with poor survival. The present data are consistent with these findings and indicate that patients with high levels of MCTCs and HCTCs had a shorter PFS. Prior results also suggest that the EMT is really involved in BC tumorigenesis, because MCTCs exhibit greater invasive ability (51).
Prior studies revealed that CTCs levels were positively correlated with cancer stage. Dong et al (50) revealed that OS of patients with NSCLC at stage III was significantly shorter that those at stage I-II. Wang et al (52) indicated that positive CTCs' detection was most likely to occur in patients with NSCLC at stage IV. Actually, the Food and Drug Administration (FDA) approved CellSearch® system use in clinical practice in 2004, which measured expression of CTCs in patients with monitor metastatic BC based on the results of Cristofanilli et al (23). The present data showed that CTCs and positive RPL15 of patients at stage III were significantly higher than those at stage I-II, indicating that CTCs and RPL15 arereally associated with BC stage. It was also identified that PFS of patients with high MCTCs (>2) and HCTCs (>5) was significantly shorter than those with low MCTCs (≤2) and HCTCs (≤5) (P<0.001), suggesting that MCTCs may play more crucial roles in EMT transition in patients with BC. In addition, some positive CTCs and RPL15 were also found at early stage of BC, illustrating early CTCs and RPL15 detection have great clinical significances. These results drive physicians to measure CTCs and RPL15 expression and guide optimal treatments before BC treatments.
RPL15 is a subunit of the large ribosomal complex and is involved in rRNA processing (40). Previous studies showed that high RPL15 levels are associated with a poor prognosis in esophageal cancer (53), skin squamous cell carcinoma (54) and pancreatic cancer (55). Furthermore, Shi and Liu (56) reported that elevated RPL15 expression in patients with hepatocellular carcinoma was associated with shorter survival times. The present study showed that the PFS of patients with positive RPL15 on CTCs was shorter (2.134-fold) than that of patients with negative RPL15 expression on CTCs. This result further confirms that RPL15 expression in CTCs is also a key biomarker for predicting prognosis of patients with BC. Other studies also revealed that RPL15 is involved in antitumor immune activation (57,58), indicating that RPL15 plays crucial roles in occurrence, progression and prognosis of cancer. Therefore, RPL15 detection may have great benefits for guiding treatment of patients with BC, which encourages clinicians to routinely perform these tests to improve evaluation of the status of patients and predict their prognosis. If RPL15 of patients is positive on CTCs, chemotherapy, immune therapy and hormone therapy should be performed as soon as possible after surgery because these patients have high relapse chances.
The relationship between HR expression and outcome in patients with BC has been extensively investigated (49,59,60), and HR expression has been found to strongly associated with the therapeutic methods used by patients (61,62). For example, HER2+ patients with Enhertu treatment have significantly longer survival times than those treated with regular chemotherapy (61). The outcomes of BC with HER2+ are poor because HER2 amplification is closely associated with HER2 protein overexpression, indicating breast cancer with HER2+ had more invasive ability than those with HER2- (63). The present data indicate that HER2+ expression before treatment strongly associates with the prognosis of patients with BC, although ER+ and PR+ were not risk factors for recurrence and metastasis. The PFS of patients with HER2+ was significantly shorter than those with HER2-, indicating that targeting HER2 has significant benefits on the outcomes of patients with BC. Therefore, if HER2 in BC will be detected before treatment, immediate Enhertu administration may prolong survival time of patients. In the present study, HER2+ expression was detected before treatment, and targeting HER2+ therapy was not adjusted for survival analysis. This may give rise to bias based on targeting HER2+ treatment. Further analysis will compare patient survival rates in the patients with and without targeting HER2+ therapy.
The present findings are noteworthy; however, the following observations and limitations should be noted when interpreting our results: i) CTC number was found to drive BC tumorigenesis; ii) RPL15 expression was associated with the prognosis of patients with BC; iii) the sample size patient subtypes is small, which may have resulted in a selection bias; iv) the lack of validation of cellular or clinical samples; and v) sub-analysis of RPL15 on TCTC was unclear. To overcome these limitations, the authors plan to recruit more patients and perform additional biological, molecular biology and biochemical experiments to explore CTC biology in patients with BC. The prognosis of patients with RPL15-combined MCTCs or HCTCs will be explored in the future to further understand biological significance of RPL15. The clinical significances of sub-analysis of RPL15 on TCTC will undoubtfully have great benefits for BC survival.
In conclusion, the PFS of patients with >2 MCTC, >5HCTCs, and positive RPL15expression was shorter than that of those with ≤2 MCTCs, ≤5 HCTCs, and negative RPL15 expression, and the prognosis of BC patients with negative HER2 expression was favorable, compared with that of patients with positive HER2 expression.
Acknowledgements
Not applicable.
Funding
Funding: The present study was supported by the Health Commission of Hubei (grant no. WJ2019F190), the Beijing Kangmeng Charity Federation (grant no. TB212045) and the Administration of Traditional Chinese Medicine of Hubei (grant no. ZY2023F024).
Availability of data and materials
The data generated in the present study may be requested from the corresponding author.
Authors' contributions
YZ and WZ contributed to manuscript drafting and the design of the study. YZ, SSL and WF carried out experiments. YZ, KS, SSL and HL contributed to the acquisition and analysis of the data. KS and WF confirm the authenticity of all the raw data. All authors read and approved the final version of the manuscript.
Ethics approval and consent to participate
The present study was reviewed and approved (approval no. 2024-264) by the Ethical Committee of Hubei Cancer Hospital (Wuhan, China). Written informed consent was obtained from all patients before the study. The present study was conducted in accordance with the principles of Declaration of Helsinki (2013 version).
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
References
|
Chen W, Zheng R, Zhang S, Zeng H, Xia C, Zuo T, Yang Z, Zou X and He J: Cancer incidence and mortality in China, 2013. Cancer Lett. 401:63–71. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA and Jemal A: Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 68:394–424. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Balasubramanian R, Rolph R, Morgan C and Hamed H: Genetics of breast cancer: Management strategies and risk-reducing surgery. Br J Hosp Med (Lond). 80:720–725. 2019.PubMed/NCBI View Article : Google Scholar | |
|
Siegel RL, Miller KD and Jemal A: Cancer statistics, 2020. CA Cancer J Clin. 70:7–30. 2020.PubMed/NCBI View Article : Google Scholar | |
|
Bray F, Ferlay J, Laversanne M, Brewster DH, Gombe Mbalawa C, Kohler B, Piñeros M, Steliarova-Foucher E, Swaminathan R, Antoni S, et al: Cancer incidence in five continents: Inclusion criteria, highlights from volume X and the global status of cancer registration. Int J Cancer. 137:2060–2071. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Collaborative Group on Hormonal Factors in Breast Cancer. Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet. 360:187–195. 2002.PubMed/NCBI View Article : Google Scholar | |
|
Gage M, Wattendorf D and Henry LR: Translational advances regarding hereditary breast cancer syndromes. J Surg Oncol. 105:444–451. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Oeffinger KC, Fontham ET, Etzioni R, Herzig A, Michaelson JS, Shih YC, Walter LC, Church TR, Flowers CR, LaMonte SJ, et al: Breast cancer screening for women at average risk: 2015 Guideline update from the American cancer society. JAMA. 314:1599–1614. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Fleshner L, Lagree A, Shiner A, Alera MA, Bielecki M, Grant R, Kiss A, Krzyzanowska MK, Cheng I, Tran WT and Gandhi S: Drivers of emergency department use among oncology patients in the era of novel cancer therapeutics: A systematic review. Oncologist. 28:1020–1033. 2023.PubMed/NCBI View Article : Google Scholar | |
|
Egelston CA, Guo W, Yost SE, Ge X, Lee JS, Frankel PH, Cui Y, Ruel C, Schmolze D, Murga M, et al: Immunogenicity and efficacy of pembrolizumab and doxorubicin in a phase I trial for patients with metastatic triple-negative breast cancer. Cancer Immunol Immunother. 72:3013–3027. 2023.PubMed/NCBI View Article : Google Scholar | |
|
Zhao J, Li GY, Lu XY, Zhu LR and Gao Q: Landscape of m6A RNA methylation regulators in liver cancer and its therapeutic implications. Front Pharmacol. 15(1376005)2024.PubMed/NCBI View Article : Google Scholar | |
|
Du C, Wu X, He M, Zhang Y, Zhang R and Dong CM: Polymeric photothermal agents for cancer therapy: Recent progress and clinical potential. J Mater Chem B. 9:1478–1490. 2021.PubMed/NCBI View Article : Google Scholar | |
|
Kumar V, Garg V and Dureja H: Nanomedicine-based approaches for delivery of herbal compounds. Tradit Med Res. 7(48)2022. | |
|
Gao Z, Zheng S, Kamei K and Tian C: Recent progress in cancer therapy based on the combination of ferroptosis with photodynamic therapy. Acta Mater Med. 1:411–426. 2022. | |
|
Huober J and Thurlimann B: The role of combination chemotherapy in the treatment of patients with metastatic breast cancer. Breast Care (Basel). 4:367–372. 2009.PubMed/NCBI View Article : Google Scholar | |
|
Cohen EN, Jayachandran G, Moore RG, Cristofanilli M, Lang JE, Khoury JD, Press MF, Kim KK, Khazan N, Zhang Q, et al: A multi-center clinical study to harvest and characterize circulating tumor cells from patients with metastatic breast cancer using the Parsortix® PC1 system. Cancers (Basel). 14(5238)2022.PubMed/NCBI View Article : Google Scholar | |
|
Yu M, Bardia A, Wittner BS, Stott SL, Smas ME, Ting DT, Isakoff SJ, Ciciliano JC, Wells MN, Shah AM, et al: Circulating breast tumor cells exhibit dynamic changes in epithelial and mesenchymal composition. Science. 339:580–584. 2013.PubMed/NCBI View Article : Google Scholar | |
|
Fina E: Signatures of breast cancer progression in the blood: What could be learned from circulating tumor cell transcriptomes. Cancers (Basel). 14(5668)2022.PubMed/NCBI View Article : Google Scholar | |
|
Li J, Liao Y, Ran Y, Wang G, Wu W, Qiu Y, Liu J, Wen N, Jing T, Wang H and Zhang S: Evaluation of sensitivity and specificity of CanPatrol™ technology for detection of circulating tumor cells in patients with non-small cell lung cance. BMC Pulm Med. 20(274)2020.PubMed/NCBI View Article : Google Scholar | |
|
Ho KH, Huang TW, Shih CM, Lee YT, Liu AJ, Chen PH and Chen KC: Glycolysis-associated lncRNAs identify a subgroup of cancer patients with poor prognoses and a high-infiltration immune microenvironment. BMC Med. 19(59)2021.PubMed/NCBI View Article : Google Scholar | |
|
Lu H, Li Z, Liu L, Tao Y, Zhou Y, Mao X, Zhu A, Wu H and Zheng X: A pan-cancer analysis of the oncogenic roles of RAD51 in human tumors. Adv Gut Microbiome Res. 2022(1591377)2022. | |
|
Mäurer M, Schott D, Pizon M, Drozdz S, Wendt T, Wittig A and Pachmann K: Increased circulating epithelial tumor cells (CETC/CTC) over the course of adjuvant radiotherapy is a predictor of less favorable outcome in patients with early-stage breast cancer. Curr Oncol. 30:261–273. 2022.PubMed/NCBI View Article : Google Scholar | |
|
Cristofanilli M, Budd GT, Ellis MJ, Stopeck A, Matera J, Miller MC, Reuben JM, Doyle GV, Allard WJ, Terstappen LW and Hayes DF: Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 351:781–791. 2004.PubMed/NCBI View Article : Google Scholar | |
|
Wu S, Liu S, Liu Z, Huang J, Pu X, Li J, Yang D, Deng H, Yang N and Xu J: Classification of circulating tumor cells by epithelial-mesenchymal transition markers. PLoS One. 10(e0123976)2015.PubMed/NCBI View Article : Google Scholar | |
|
Jung R, Krüger W, Hosch S, Holweg M, Kröger N, Gutensohn K, Wagener C, Neumaier M and Zander AR: Specificity of reverse transcriptase polymerase chain reaction assays designed for the detection of circulating cancer cells is influenced by cytokines in vivo and in vitro. Br J Cancer. 78:1194–1198. 1998.PubMed/NCBI View Article : Google Scholar | |
|
Giuliano M, Giordano A, Jackson S, Hess KR, De Giorgi U, Mego M, Handy BC, Ueno NT, Alvarez RH, De Laurentiis M, et al: Circulating tumor cells as prognostic and predictive markers in metastatic breast cancer patients receiving first-line systemic treatment. Breast Cancer Res. 13(R67)2011.PubMed/NCBI View Article : Google Scholar | |
|
Mego M, Cierna Z, Janega P, Karaba M, Minarik G, Benca J, Sedlácková T, Sieberova G, Gronesova P, Manasova D, et al: Relationship between circulating tumor cells and epithelial to mesenchymal transition in early breast cancer. BMC Cancer. 15(533)2015.PubMed/NCBI View Article : Google Scholar | |
|
Mancheng AD and Ossas U: How does lncrna regulation impact cancer metastasis. Cancer Insight. 1(6)2022. | |
|
Riethdorf S, Fritsche H, Müller V, Rau T, Schindlbeck C, Rack B, Janni W, Coith C, Beck K, Jänicke F, et al: Detection of circulating tumor cells in peripheral blood of patients with metastatic breast cancer: A validation study of the CellSearch system. Clin Cancer Res. 13:920–928. 2007.PubMed/NCBI View Article : Google Scholar | |
|
Balic M, Dandachi N, Hofmann G, Samonigg H, Loibner H, Obwaller A, van der Kooi A, Tibbe AG, Doyle GV, Terstappen LW and Bauernhofer T: Comparison of two methods for enumerating circulating tumor cells in carcinoma patients. Cytometry B Clin Cytom. 68:25–30. 2005.PubMed/NCBI View Article : Google Scholar | |
|
Cruz I, Ciudad J, Cruz JJ, Ramos M, Gómez-Alonso A, Adansa JC, Rodríguez C and Orfao A: Evaluation of multiparameter flow cytometry for the detection of breast cancer tumor cells in blood samples. Am J Clin Pathol. 123:66–74. 2005.PubMed/NCBI View Article : Google Scholar | |
|
Meng S, Tripathy D, Frenkel EP, Shete S, Naftalis EZ, Huth JF, Beitsch PD, Leitch M, Hoover S, Euhus D, et al: Circulating tumor cells in patients with breast cancer dormancy. Clin Cancer Res. 10:8152–8162. 2004.PubMed/NCBI View Article : Google Scholar | |
|
Yang J, Ma J, Jin Y, Cheng S, Huang S, Zhang N and Wang Y: Development and validation for prognostic nomogram of epithelial ovarian cancer recurrence based on circulating tumor cells and epithelial-mesenchymal transition. Sci Rep. 11(6540)2021.PubMed/NCBI View Article : Google Scholar | |
|
Zhou H, Shen H, Xiang F, Yang X, Li R, Zeng Y and Liu Z: Correlation analysis of the expression of mesenchymal circulating tumor cells and CD133 with the prognosis of colorectal cancer. Am J Transl Res. 15:3489–3499. 2023.PubMed/NCBI | |
|
Rath B, Plangger A, Klameth L, Hochmair M, Ulsperger E, Boeckx B, Neumayer C and Hamilton G: Small cell lung cancer: Circulating tumor cell lines and expression of mediators of angiogenesis and coagulation. Explor Target Antitumor Ther. 4:355–365. 2023.PubMed/NCBI View Article : Google Scholar | |
|
Magri V, Marino L, Nicolazzo C, Gradilone A, De Renzi G, De Meo M, Gandini O, Sabatini A, Santini D, Cortesi E and Gazzaniga P: Prognostic role of circulating tumor cell trajectories in metastatic colorectal cancer. Cells. 12(1172)2023.PubMed/NCBI View Article : Google Scholar | |
|
Chen H, Li H, Shi W, Qin H and Zheng L: The roles of m6A RNA methylation modification in cancer stem cells: New opportunities for cancer suppression. Cancer Insight. 1(10)2022. | |
|
Gao T, Mao J, Huang J, Luo F, Lin L, Lian Y, Bin S, Zhao L and Li S: Prognostic significance of circulating tumor cell measurement in the peripheral blood of patients with nasopharyngeal carcinoma. Clinics (Sao Paulo). 78(100179)2023.PubMed/NCBI View Article : Google Scholar | |
|
Wang HT, Bai LY, Wang YT, Lin HJ, Yang HR, Hsueh PR and Cho DY: Circulating tumor cells positivity provides an early detection of recurrence of pancreatic cancer. J Formos Med Assoc. 122:653–655. 2023.PubMed/NCBI View Article : Google Scholar | |
|
Ebright RY, Lee S, Wittner BS, Niederhoffer KL, Nicholson BT, Bardia A, Truesdell S, Wiley DF, Wesley B, Li S, et al: Deregulation of ribosomal protein expression and translation promotes breast cancer metastasis. Science. 367:1468–1473. 2020.PubMed/NCBI View Article : Google Scholar | |
|
Kenmochi N, Kawaguchi T, Rozen S, Davis E, Goodman N, Hudson TJ, Tanaka T and Page DC: A map of 75 human ribosomal protein genes. Genome Res. 8:509–523. 1998.PubMed/NCBI View Article : Google Scholar | |
|
Ma Y, Xue H, Wang W, Yuan Y and Liang F: The miR-567/RPL15/TGF-β/Smad axis inhibits the stem-like properties and chemo-resistance of gastric cancer cells. Transl Cancer Res. 9:3539–3549. 2020.PubMed/NCBI View Article : Google Scholar | |
|
Amin MB, Edge SB, Greene FL and Brierley JD: AJCC cancer staging manual. 8th edition. New York: Springer, 2017. | |
|
Tsongalis GJ: Branched DNA technology in molecular diagnostics. Am J Clin Pathol. 126:448–453. 2006.PubMed/NCBI View Article : Google Scholar | |
|
Wolff AC, Hammond MEH, Allison KH, Harvey BE, Mangu PB, Bartlett JMS, Bilous M, Ellis IO, Fitzgibbons P, Hanna W, et al: Human epidermal growth factor receptor 2 testing in breast cancer: American society of clinical oncology/college of American pathologists clinical practice guideline focused update. J Clin Oncol. 36:2105–2122. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Joseph C, Papadaki A, Althobiti M, Alsaleem M, Aleskandarany MA and Rakha EA: Breast cancer intratumour heterogeneity: Current status and clinical implications. Histopathology. 73:717–731. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Ji X, Tian X, Feng S, Zhang L, Wang J, Guo R, Zhu Y, Yu X, Zhang Y, Du H, et al: Intermittent F-actin perturbations by magnetic fields inhibit breast cancer metastasis. Research (Wash DC). 6(0080)2023.PubMed/NCBI View Article : Google Scholar | |
|
Navin N, Krasnitz A, Rodgers L, Cook K, Meth J, Kendall J, Riggs M, Eberling Y, Troge J, Grubor V, et al: Inferring tumor progression from genomic heterogeneity. Genome Res. 20:68–80. 2010.PubMed/NCBI View Article : Google Scholar | |
|
Li Y, Jiang X, Zhong M, Yu B and Yuan H: Whole genome sequencing of single-circulating tumor cell ameliorates unraveling breast cancer heterogeneity. Breast Cancer (Dove Med Press). 14:505–513. 2022.PubMed/NCBI View Article : Google Scholar | |
|
Dong J, Zhu D, Tang X, Qiu X, Lu D, Li B, Lin D and Zhou Q: Detection of circulating tumor cell molecular subtype in pulmonary vein predicting prognosis of stage I-III non-small cell lung cancer patients. Front Oncol. 9(1139)2019.PubMed/NCBI View Article : Google Scholar | |
|
Polyak K and Weinberg RA: Transitions between epithelial and mesenchymal states: Acquisition of malignant and stem cell traits. Nat Rev Cancer. 9:265–273. 2009.PubMed/NCBI View Article : Google Scholar | |
|
Wang X, Ma K, Yang Z, Cui J, He H, Hoffman AR, Hu JF and Li W: Systematic correlation analyses of circulating tumor cells with clinical variables and tumor markers in lung cancer patients. J Cancer. 8:3099–3104. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Wang Q, Yang C, Zhou J, Wang X, Wu M and Liu Z: Cloning and characterization of full-length human ribosomal protein L15 cDNA which was overexpressed in esophageal cancer. Gene. 263:205–209. 2001.PubMed/NCBI View Article : Google Scholar | |
|
Nindl I, Dang C, Forschner T, Kuban RJ, Meyer T, Sterry W and Stockfleth E: Identification of differentially expressed genes in cutaneous squamous cell carcinoma by microarray expression profiling. Mol Cancer. 5(30)2006.PubMed/NCBI View Article : Google Scholar | |
|
Yan TT, Fu XL, Li J, Bian YN, Liu DJ, Hua R, Ren LL, Li CT, Sun YW, Chen HY, et al: Downregulation of RPL15 may predict poor survival and associate with tumor progression in pancreatic ductal adenocarcinoma. Oncotarget. 6:37028–37042. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Shi R and Liu Z: RPL15 promotes hepatocellular carcinoma progression via regulation of RPs-MDM2-p53 signaling pathway. Cancer Cell Int. 22(150)2022.PubMed/NCBI View Article : Google Scholar | |
|
Kitai Y: Elucidation of the mechanism of topotecan-induced antitumor immune activation. Yakugaku Zasshi. 142:911–916. 2022.PubMed/NCBI View Article : Google Scholar : (In Japanese). | |
|
Yamada S, Kitai Y, Tadokoro T, Takahashi R, Shoji H, Maemoto T, Ishiura M, Muromoto R, Kashiwakura JI, Ishii KJ, et al: Identification of RPL15 60S ribosomal protein as a novel topotecan target protein that correlates with DAMP secretion and antitumor immune activation. J Immunol. 209:171–179. 2022.PubMed/NCBI View Article : Google Scholar | |
|
Feng H, Liu H, Wang Q, Song M, Yang T, Zheng L, Wu D, Shao X and Shi G: Breast cancer diagnosis and prognosis using a high b-value non-Gaussian continuous-time random-walk model. Clin Radiol. 78:e660–e667. 2023.PubMed/NCBI View Article : Google Scholar | |
|
Mai N, Abuhadra N and Jhaveri K: Molecularly targeted therapies for triple negative breast cancer: History, advances, and future directions. Clin Breast Cancer. 23:784–799. 2023.PubMed/NCBI View Article : Google Scholar | |
|
Bartsch R and Bergen E: ASCO 2018: Highlights in HER2-positive metastatic breast cancer. Memo. 11:280–283. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Papadaki MA, Stoupis G, Theodoropoulos PA, Mavroudis D, Georgoulias V and Agelaki S: Circulating tumor cells with stemness and epithelial-to-mesenchymal transition features are chemoresistant and predictive of poor outcome in metastatic breast cancer. Mol Cancer Ther. 18:437–447. 2019.PubMed/NCBI View Article : Google Scholar | |
|
Ahn S, Woo JW, Lee K and Park SY: HER2 status in breast cancer: Changes in guidelines and complicating factors for interpretation. J Pathol Transl Med. 54:34–44. 2020.PubMed/NCBI View Article : Google Scholar |
