BackgroundA growing amount of evidence has indicated that PSAT1 is an oncogene that plays an important role in cancer progression and metastasis. In this study, we explored the expression and function of PSAT1 in estrogen receptor (ER)-negative breast cancer.MethodThe expression level of PSAT1 in breast cancer tissues and cells was analyzed using real-time-PCR (RT-PCR), TCGA datasets or immunohistochemistry (IHC). The overall survival of patients with ER-negative breast cancer stratified by the PSAT1 expression levels was evaluated using Kaplan-Meier analysis. The function of PSAT1 was analyzed using a series of in vitro assays. Moreover, a nude mouse model was used to evaluate the function of PSAT1 in vivo. qRT-PCR and western blot assays were used to evaluate gene and protein expression, respectively, in the indicated cells. In addition, we demonstrated that PSAT1 was activated by ATF4 by chromatin immunoprecipitation (ChIP) assays.ResultsmRNA expression of PSAT1 was up-regulated in ER-negative breast cancer. A tissue microarray that included 297 specimens of ER-negative breast cancer was subjected to an immunohistochemistry assay, which demonstrated that PSAT1 was overexpressed and predicted a poor clinical outcome of patients with this disease. Our data showed that PSAT1 promoted cell proliferation and tumorigenesis in vitro and in vivo. We further found that PSAT1 induced up-regulation of cyclin D1 via the GSK3β/β-catenin pathway, which eventually led to the acceleration of cell cycle progression. Furthermore, ATF4 was also overexpressed in ER-negative breast cancers, and a positive correlation between the ATF4 and PSAT1 mRNA levels was observed in ER-negative breast cancers. We further demonstrated that knockdown of ATF4 by siRNA reduced PSAT1 expression. Finally, chromatin immunoprecipitation (ChIP) assays showed that PSAT1 was a target of ATF4.ConclusionsPSAT1, which is overexpressed in ER-negative breast cancers, is activated by ATF4 and promotes cell cycle progression via regulation of the GSK3β/β-catenin/cyclin D1 pathway.Electronic supplementary materialThe online version of this article (doi: 10.1186/s13046-017-0648-4) contains supplementary material, which is available to authorized users.

EPB41L4A-AS2 is a novel long non-coding RNA of unknown function. In this study, we investigated the expression of EPB41L4A-AS2 in breast cancer tissues and evaluated its relationship with the clinicopathological features and prognosis of patients with breast cancer. This entailed conducting a meta-analysis and prognosis validation study using two cohorts from the Gene Expression Omnibus (GEO). In addition, we assessed EPB41L4A-AS2 expression and its relationship with the clinicopathological features of renal and lung cancers using the Cancer Genome Atlas cohort and a GEO dataset. We also clarified the role of EPB41L4A-AS2 expression in mediating cancer cell proliferation in breast, renal, and lung cancer cell lines transfected with an EPB41L4A-AS2 expression vector. We found that high EPB41L4A-AS2 expression is associated with favorable disease outcomes. Gene ontology enrichment analysis revealed that EPB41L4A-AS2 may be involved in processes associated with tumor biology. Finally, overexpression of EPB41L4A-AS2 inhibited tumor cell proliferation in breast, renal, and lung cancer cell lines. Our clinical and in vitro results suggest that EPB41L4A-AS2 inhibits solid tumor formation and that evaluation of this long non-coding RNA may have prognostic value in the clinical management of such malignancies.

Eosinophil granule ontogeny transcript (EGOT) is a long noncoding RNA involved in the regulation of eosinophil granule protein transcript expression. However, little is known about the role of EGOT in malignant disease. This study aimed to assess the potential role of EGOT in the pathogenesis of breast cancer. Quantitative real-time polymerase chain reaction was performed to detect the expression levels of EGOT in 250 breast cancerous tissues and 50 adjacent noncancerous tissues. The correlation of EGOT expression with clinicopathological features and prognosis was also analyzed. EGOT expression was lower in breast cancer compared with the adjacent noncancerous tissues (P < 0.001), and low levels of EGOT expression were significantly correlated with larger tumor size (P = 0.022), more lymph node metastasis (P = 0.020), and higher Ki-67 expression (P = 0.017). Moreover, patients with low levels of EGOT expression showed significantly worse prognosis for overall survival (P = 0.040), and this result was further validated in a larger cohort from a public database. Multivariate analysis suggested that low levels of EGOT were a poor independent prognostic predictor for breast cancer patients (HR = 1.857, 95 % CI = 1.032-3.340, P = 0.039). In conclusion, EGOT may play an important role in breast cancer progression and prognosis and may serve as a new potential prognostic target in breast cancer patients.

Purpose: Early detection and intervention can decrease the mortality of breast cancer significantly. Assessments of genetic/ genomic variants in circulating tumor DNA (ctDNA) have generated great enthusiasm for their potential application as clinically actionable biomarkers in the management of earlystage breast cancer.Experimental Design: In this study, 861 serial plasma and matched tissue specimens from 102 patients with early-stage breast cancer who need chemotherapy and 50 individuals with benign breast tumors were deeply sequenced via nextgeneration sequencing (NGS) techniques using large gene panels.Results: Cancer tissues in this cohort of patients showed profound intratumor heterogeneities (ITHGs) that were properly reflected by ctDNA testing. Integrating the ctDNA detection rate of 74.2% in this cohort with the corresponding predictive results based on Breast Imaging Reporting and Data System classification (BI-RADS) could increase the positive predictive value up to 92% and potentially dramatically reduce surgical overtreatment. Patients with positive ctDNA after surgery showed a higher percentage of lymph node metastasis, indicating potential recurrence and remote metastasis. The ctDNA-positive rates were significantly decreased after chemotherapy in basal-like and Her2 þ tumor subtypes, but were persistent despite chemotherapy in luminal type. The tumor mutation burden in blood (bTMB) assessed on the basis of ctDNA testing was positively correlated with the TMB in tumor tissues (tTMB), providing a candidate biomarker warranting further study of its potentials used for precise immunotherapy in cancer.Conclusions: These data showed that ctDNA evaluation is a feasible, sensitive, and specific biomarker for diagnosis and differential diagnosis of patients with early-stage breast cancer who need chemotherapy.

Fibroblast growth factor receptor 4 (FGFR4) belongs to the receptor tyrosine kinase (RTK) family, and FGFR4 polymorphisms have been implicated in both normal development and cancer, including breast cancer. In the present study, we investigated correlations between polymorphisms in FGFR4 and breast cancer prognosis. The FGFR4 SNPs rs1966265 and rs351855 were genotyped in 747 breast cancer patients using the SNaPshot method. FGFR4 protein expression was detected by immunohistochemistry in 339 samples. SNP rs351855 was correlated with FGFR4 protein expression under dominant and co-dominant models. Lymph node metastasis (LNM), ER (estrogen receptor) status, and molecular subtype were associated with high FGFR4 expression. Univariate analysis revealed rs351855 (CC/CT: P = 0.027, CC/TT: P < 0.001, CC/CT + TT: P = 0.005) to be a prognostic predictor, and multivariate analysis indicated rs351855 (CC/TT: P = 0.005) to be an independent prognostic factor. Kaplan-Meier survival analysis showed that high FGFR4 protein expression was associated with a poor prognosis. SNP rs351855 was correlated with worse outcomes, with a dose-dependent effect. The results of this study show that FGFR4 SNP rs351855 is associated with up-regulation of FGFR4 protein expression and a worse prognosis in breast cancer.

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Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54–99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56–100%), and AUPRC = 0.9220 (95% CI: 91.02–94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72–99.27%), and AUPRC = 0.9111 (95% CI: 88.45–93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07–98.91%), and AUPRC = 0.8640 (95% CI: 82.82–89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72–97.87%) and a specificity of 98.70% (95% CI: 86.36–100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75–99.55%), and AUPRC = 0.9800 (95% CI: 96.6–99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95–96.34%), and AUPRC = 0.9490 (95% CI: 91.7–98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p < 0.05). In conclusion, we developed and tested a cfDNA methylation model for BC diagnosis with better performance than mammography.

The function of Fer-1 like family member 4 (FER1L4) in human pan-cancer is unknown.Expression of FER1L4 in tumor tissues and nontumor tissues, upstream regulation of FER1L4, and the relationship between its expression with prognosis and chemoresistance were examined by The Cancer Genome Atlas and Gene Expression Omnibus databases.Next, these results were validated in breast tumor and paired nontumor tissues in our cohort. FER1L4 expression is higher in tumor tissues compared with the adjacent nontumor tissues. High FER1L4 expression is associated with worse disease outcomes.Hypomethylation and H3K4me3 accumulation in FER1L4 promoter locus activate its transcriptional expression. Moreover, FER1L4 may trigger chemoresistance in human cancer. Gene Ontology enrichment analysis revealed that FER1L4 may be involved in processes associated with tumorigenesis. These results indicated that FER1L4 may act as an oncogenic driver and it may be a potential therapy target in human cancer. K E Y W O R D SFER1L4, long noncoding RNA, methylation, pan-cancer, survival