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Young age at diagnosis is associated with better prognosis in stage IV breast cancer.

ABSTRACT: Numerous studies have shown that young age is a risk factor in early breast cancer. But for stage IV breast cancer, it is unclear whether age has a similar effect on patient survival. We collected and analyzed data from patients with stage IV breast cancer between January 2010 and December 2015 in SEER database. Multivariate Cox proportional hazard model was used in this study. 13,069 patients with stage IV breast cancer were included in the analysis, of which 1,135 were young breast cancer patients (?40 years old). In a multivariate analysis that adjusted for sociodemographic factors, clinical-pathological characteristics and therapeutic methods, the risk of death in patients with stage IV ?40 years was significantly reduced (hazard ratio [HR], 0.72; 95% CI, 0.65-0.79). Subgroup analyses showed that, with the same adjustment of all factors, young age only significantly reduced the risk of death in patients with luminal A (HR, 0.78; 95% CI, 0.68-0.89) and luminal B (HR 0.46; 95% CI, 0.35-0.60) subtypes. Young age at diagnosis is associated with better survival in patients with stage IV breast cancer. The effect of young age at diagnosis on the survival outcome of stage IV breast cancer varies by subtypes.

SUBMITTER: Liu W

PROVIDER: S-EPMC6932875 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Young age at diagnosis is associated with better prognosis in stage IV breast cancer.

Liu Wei W Xiong Xi-Feng XF Mo Yu-Zhen YZ Chen Wei-Guang WG Li Mei M Liang Rong R Zhang Zhi-Biao ZB Zhang Zhi Z

Aging 20191211 23

Numerous studies have shown that young age is a risk factor in early breast cancer. But for stage IV breast cancer, it is unclear whether age has a similar effect on patient survival. We collected and analyzed data from patients with stage IV breast cancer between January 2010 and December 2015 in SEER database. Multivariate Cox proportional hazard model was used in this study. 13,069 patients with stage IV breast cancer were included in the analysis, of which 1,135 were young breast cancer pati ...[more]

PMID: 31829978

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Project description:IntroductionDetection of serum biomarkers for early diagnosis of breast cancer remains an important goal. Changes in the structure of O-linked glycans occur in all breast cancers resulting in the expression of glycoproteins that are antigenically distinct. Indeed, the serum assay widely used for monitoring disease progression in breast cancer (CA15.3), detects a glycoprotein (MUC1), but elevated levels of the antigen cannot be detected in early stage patients. However, since the immune system acts to amplify the antigenic signal, antibodies can be detected in sera long before the antigen. We have exploited the change in O-glycosylation to measure autoantibody responses to cancer-associated glycoforms of MUC1 in sera from early stage breast cancer patients.MethodsWe used a microarray platform of 60mer MUC1 glycopeptides, to confirm the presence of autoantibodies to cancer associated glycoforms of MUC1 in a proportion of early breast cancer patients (54/198). Five positive sera were selected for detailed definition of the reactive epitopes using on chip glycosylation technology and a panel of glycopeptides based on a single MUC1 tandem repeat carrying specific glycans at specific sites. Based on these results, larger amounts of an extended repertoire of defined MUC1 glycopeptides were synthesised, printed on microarrays, and screened with sera from a large cohort of breast cancer patients (n = 395), patients with benign breast disease (n = 108) and healthy controls (n = 99). All sera were collected in the 1970s and 1980s and complete clinical follow-up of breast cancer patients is available.ResultsThe presence and level of autoantibodies was significantly higher in the sera from cancer patients compared with the controls, and a highly significant correlation with age was observed. High levels of a subset of autoantibodies to the core3MUC1 (GlcNAc?1-3GalNAc-MUC1) and STnMUC1 (NeuAc?2,6GalNAc-MUC1) glycoforms were significantly associated with reduced incidence and increased time to metastasis.ConclusionsAutoantibodies to specific cancer associated glycoforms of MUC1 are found more frequently and at higher levels in early stage breast cancer patients than in women with benign breast disease or healthy women. Association of strong antibody response with reduced rate and delay in metastases suggests that autoantibodies can affect disease progression.

Project description:This study analyzes the expression and clinical significance of long non-coding RNA (lncRNA) BM466146 in breast cancer, and explores the role of BM466146 in immune regulation. The expression of BM466146 in 89 cases of breast cancer and their corresponding non-cancerous breast tissues was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Kaplan-Meier survival analysis was applied to evaluate patient survival. EDU and CCK-8 experiments on breast cancer cells were performed to verify the function of BM466146 in vitro. The target genes of BM466146 were screened by informatics analysis to predict associated miRNAs and their corresponding mRNAs, immune genes associated with lncRNAs and chemokines associated with CD8. Immunohistochemistry was used to detect the expression of CD8, Ki-67, and CXCL-13 in the 89 breast cancer tissues. It was found that the expression of lncRNA BM466146 in breast cancer tissues was significantly lower than that in normal breast tissues (P < 0.001). In breast cancer, tissues that overexpressed BM466146 exhibited a lower Ki-67 index compared with that of low BM466146 expression (P = 0.048). Kaplan-Meier survival analysis showed that breast cancer patients with overexpression of BM466146 had longer overall survival. EDU and CCK8 experiments showed that overexpression of BM466146 inhibited the proliferation of breast cancer cells. The hsa-miR-224-3p is associated with BM466146, and its target gene might be CXCL-13. The positive CD8 cells in the BM466146 overexpression group was higher than that in the low BM466146 expression group (P=0.027), and the positive CD8 cells in the CXCL-13 positive group was higher (P=0.023) than that of the negative group. Our results indicate that the lncRNA BM466146 has the function of tumor suppressor gene. Overexpression of BM466146 is associated with better prognosis. BM466146 could regulate CXCL-13 by adsorbing hsa-miR-224-3p and inducing CD8+ T cells to accumulate in the tumor area which regulate immune response. Therefore, BM466146 could be a prognostic biomarker and a molecular immune target of breast cancer.

Project description:BACKGROUND The early death of patients is a global cancer issue. We aimed to identify the risk factors for early death in stage IV breast cancer. Predictive nomograms for early death evaluation were generated based on the risk factors. MATERIAL AND METHODS Based on the Surveillance, Epidemiology, and End Results (SEER) database, patients diagnosed with IV breast cancer were selected. The risk factors for early death (survival time ?1 year) were identified using logistic regression model analysis. Predictive nomograms were constructed and internal validation was performed. RESULTS A total of 5998 (32.6%) breast cancer patients were diagnosed as early death in the construction cohort. Age older than 50 years, unmarried status, black race, uninsured status, triple-negative type, grade (II and III), tumor size >5 cm, and metastasis to lung, liver, and brain were risk factors for total early death, while Luminal B subtype, N1 stage, and surgical interventions were associated with lower risk of early death. As for cancer-specific and non-cancer-specific early death, several factors were not consistent between the 2 groups. Nomograms for all-cause, cancer-specific, and non-cancer-specific early death were constructed. The calibration curve showed satisfactory agreement. The areas under the ROC curve (AUC) were 78.3% (95% CI: 77.7-78.9%), 75.8% (75.1-76.4%), and 72.3% (71.6-72.9%), respectively. In the validation cohort, a total of 689 (19.3%) patients were diagnosed as early death and the calibration curve showed satisfactory agreement. The AUCs of the all-cause, cancer-specific, and non-cancer-specific early death prediction were 74.0% (95% CI: 72.5-75.4%), 73.5% (72.0-74.9%), and 68.6% (67.0-70.1%), respectively. CONCLUSIONS Nomograms were generated to predict early death, with good calibration and discrimination. The predictive model can provide a reference for identifying cases with high risk of early death among stage IV breast cancer patients and play an auxiliary role in guiding individual treatment.

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Young age at diagnosis is associated with better prognosis in stage IV breast cancer.

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Young age at diagnosis is associated with better prognosis in stage IV breast cancer.

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