Abstract P6-10-02: Black race is associated with worse distant relapse-free survival in breast cancer patients treated with neoadjuvant compared to adjuvant systemic chemotherapy

Author(s):  
JM Pastoriza ◽  
GS Karagiannis ◽  
X Xue ◽  
J Lin ◽  
JS Condeelis ◽  
...  
2021 ◽  
Author(s):  
Yuhao Xu ◽  
Yaoqiang Du ◽  
Qinghui Zheng ◽  
Hongchao Tang ◽  
Yangyang Qian ◽  
...  

Abstract Background Recent years, the breast cancer became the most commonly diagnosed cancer. The use of neoadjuvant chemotherapy (NACT) makes a significant contribution to chemotherapy in breast cancer. We aimed to develop the novel model as a predictor of distant relapse-free survival (DRFS) in breast cancer patients receiving taxane and anthracycline-based NACT. Methods We collected the mRNA expression datasets of patients from GSE25055 and GSE25065 in Gene Expression Omnibus (GEO). Univariate and Multivariate Cox Regression Analyses were conducted to achieve the prognostic genes that associated with DRFS. Moreover, the E2F targets genes were obtained from GSEA. We obtained the intersection genes between the prognostic genes and E2F target genes, then validated in GSE32603 dataset. And we established a nomogram model based on PTTG1 expression level and several clinical characteristics. Results A novel nomogram was conducted. The receiver operating characteristic (AUC = 0.849), C-index (0.805) and calibration plots were applied to assess the effect of this model. Conclusion Our study found that the E2F target genes, such as the PTTG1 may serve as a potential biomarker in breast cancer, and provided superior estimation of DRFS, which can guide the clinical practice in NACT of breast cancer.


2021 ◽  
Author(s):  
Yu-hao Xu ◽  
Yao-qiang Du ◽  
Qing-hui Zheng ◽  
Qiu-ran Xu ◽  
Xuli Meng

Abstract Background: The breast cancer is the most commonly diagnosed cancer in recent years. The use of neoadjuvant chemotherapy (NACT) makes a significant contribution to chemotherapy in breast cancer. We aimed to develop the novel model as a predictor of distant relapse-free survival (DRFS) in breast cancer patients receiving taxane and anthracycline-based NACT.Methods: We collected the mRNA expression datasets of patients from GSE25055 and GSE25065 in Gene Expression Omnibus (GEO). Univariate and Multivariate Cox Regression Analyses were conducted to achieve the prognostic genes that associated with DRFS. Moreover, the E2F target genes were obtained from GSEA. We obtained the intersection genes between the prognostic genes and E2F target genes, then validated in GSE32603 dataset. And we established a nomogram model based on PTTG1 expression level and several clinical characteristics.Results: There were 95 genes confirmed to be associated with DRFS both in GSE25055 and GSE25065. And PTTG1 was validated as a gene related to DRFS and associated with E2F target hallmark using GSEA analysis and chosen as our target gene. The AUC of PTTG1 model was 0.682 indicating a relatively poor prediction performance. Then a novel nomogram was conducted, the receiver operating characteristic (AUC=0.849), C-index (0.805) and calibration plots were applied to assess the effect of this model.Conclusion: Our study found that the E2F target genes, such as the PTTG1 may serve as a potential biomarker in breast cancer, and provided superior estimation of DRFS, which can guide the clinical practice in NACT of breast cancer.


2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10565-10565
Author(s):  
Maria Libera Ascierto ◽  
Michael O Idowu ◽  
Yingdong Zhao ◽  
Davide Bedognetti ◽  
Paolo Antonio Ascierto ◽  
...  

10565 Background: Tumor cell recognition by NK cells is mediated by the interaction of activating and inhibitory NK cell receptors with their ligands expressed on tumor cells. In addition, NK cells express adhesion molecules that facilitate formation of the immunological synapse with the tumor targets. Here, we investigated whether the coordinate expression of NK activating receptors and adhesion molecules could provide a signature to segregate breast cancer patients into relapse and relapse-free outcomes. Methods: Gene expression profiling, RT-PCR screening and survival analysis were performed on RNA extracted from primary breast cancers. Tumors were obtained from patients experiencing either 5-8 years relapse-free survival or tumor relapse within 1-3 years following initial treatment. Results: Tumors from patients with a favorable prognosis were characterized by increased expression of genes involved in NK cell interaction with tumor cells and its activation signaling. In particular, up-regulation of Natural Cytotoxicity Receptors (NCRs), leukocyte function-associated antigen 1 (LFA-1), CD226 (DNAM-1) and CD96 was observed in relapse-free patients. Thus, the expression of the NK activating receptors and relevant adhesion molecules involved in NK cell:target interactions can predict relapse free survival in breast cancer patients. Conclusions: Results from the present study, highlighted the effector cooperation between the innate and adaptive immune components within the tumor microenvironment. The NK cells parameters identified in this study, together with the prognostic B and T cell signatures previously reported by us, represent a powerful tool for predicting breast cancer outcome which might be easily introduced in clinical practice.


2020 ◽  
Vol 9 (16) ◽  
pp. 5922-5931
Author(s):  
Jouni Kujala ◽  
Jaana M. Hartikainen ◽  
Maria Tengström ◽  
Reijo Sironen ◽  
Veli‐Matti Kosma ◽  
...  

Author(s):  
Paulina Karin Grillo ◽  
Balázs Győrffy ◽  
Martin Götte

Abstract Purpose Dysregulated expression of proteoglycans influences the outcome and progression of numerous cancers. Several studies have investigated the role of individual glypicans in cancer, however, the impact of the whole glypican family of heparan sulfate proteoglycans on prognosis of a large patient cohort of breast cancer patients has not yet been investigated. In the present study, our aim was to investigate the prognostic power of the glypicans in breast cancer patients. Methods We used a public database including both gene expression data and survival information for 3951 breast cancer patients to determine the prognostic value of glypicans on relapse-free survival using Cox regression analysis. Moreover, we performed quantitative Real-Time PCR to determine glypican gene expression levels in seven representative breast cancer cell lines. Results We found that high GPC3 levels were associated with a better prognosis in overall breast cancer patients. When stratified by hormone receptor status, we found that in worse prognosis subtypes low GPC1 levels correlate with a longer relapse-free survival, and in more favorable subtypes low GPC6 was associated with longer survival. Conclusion Our study concludes that glypicans could act as subtype-specific biomarkers for the prognosis of breast cancer patients and sparks hope for future research on glypicans possibly eventually providing targets for the treatment of the disease.


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