scholarly journals Neutrophil-to-lymphocyte ratio as a predictor of early death in metastatic triple-negative breast cancer

2020 ◽  
Author(s):  
Gabriel De la Cruz-Ku ◽  
Diego Chambergo-Michilot ◽  
J. Smith Torres-Roman ◽  
Pamela Rebaza ◽  
Joseph Pinto ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Care Center ◽  
Tertiary Care ◽  
Metastatic Breast ◽  
Early Death ◽  
Sensitivity Analyses ◽  
Rank Test

Abstract Background The prediction of survival using the neutrophil-to-lymphocytes ratio (NLR) in metastatic breast cancer is still under debate. We aimed to determine the mortality prognostic value of the NLR in female patients with metastatic triple-negative breast cancer. Methods. We reviewed 118 medical records of patients diagnosed and treated in a tertiary-care center over a 14-year period. The cut-off value for the NLR (<2.5 and ≥2.5) was determined with receiver operating characteristic curves (area under the curve: 0.73; 95% CI: 0.615, 0.851). Survival curves were estimated using the Kaplan-Meier method and compared with the Log-rank test. Multivariate Cox regression was used to identify the risk of mortality at two years. We further performed sensitivity analyses with different cut-off values and subgroup analysis in patients that only received chemotherapy. Results. The median follow-up was 24 months. Patients with an NLR ≥2.5 had a worse overall survival compared to patients with a NLR <2.5 (6% vs. 28%, p<0.001) at two years. This outcome remained consistent when we stratified for patients that received chemotherapy (8% vs. 36%, p=0.001). Multivariate analysis identified the NLR (≥2.5 vs. <2.5) at diagnosis as a prognostic risk factor for mortality in the entire population (HR: 2.12, 95% CI: 1.32-3.39) and in patients that received chemotherapy (HR: 2.68, 95% CI: 1.46 – 4.92). Conclusions. The NLR is an accessible biomarker that predicts early mortality in patients with metastatic triple-negative breast cancer. Physicians can use these results to predict survival in these patients.

scholarly journals Neutrophil-to-lymphocyte ratio predicts early mortality in females with metastatic triple-negative breast cancer

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243447
Author(s):  
Gabriel de la Cruz-Ku ◽  
Diego Chambergo-Michilot ◽  
J. Smith Torres-Roman ◽  
Pamela Rebaza ◽  
Joseph Pinto ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Early Mortality ◽  
Neutrophil To Lymphocyte Ratio ◽  
Sensitivity Analyses ◽  
Rank Test ◽  
Poor Overall Survival ◽  
Lymphocyte Ratio

Background The aim of this study was to determine the utility of the neutrophil-to-lymphocyte ratio (NLR) as a biomarker for predicting early-mortality (<2 years) among females with metastatic triple-negative breast cancer (mTNBC). Methods We reviewed 118 medical records of females with mTNBC. The cut-off value for the NLR (<2.5 and ≥2.5) was determined with receiver operating characteristic curves (area under the curve: 0.73; 95% CI: 0.62–0.85). Survival curves were estimated using the Kaplan-Meier method and compared with the Log-rank test. Multivariate Cox regression was used to identify the risk of mortality at two years. Moreover, we performed sensitivity analyses with different cut-off values and a subgroup analysis in females that only received chemotherapy. Results The median follow-up was 24 months. Females with NLR ≥2.5 had a poor overall survival compared to females with NLR <2.5 (6% vs. 28%, p<0.001) at two years. This outcome remained when we stratified for females that only received chemotherapy (8% vs. 36%, p = 0.001). Multivariate analyses identified NLR ≥2.5 as a poor prognostic risk factor for mortality in the entire population (HR: 2.12, 95% CI: 1.32–3.39) and among females that received chemotherapy (HR: 2.68, 95% CI: 1.46–4.92). Conclusion The NLR is an accessible and reliable biomarker that predicts early mortality among females with mTNBC. Our results suggest that females with high NLR values have poor prognosis despite receiving standard chemotherapy. Health providers should evaluate the possibility to enroll these patients in novel immunotherapy trials.

scholarly journals Genome Instability-Derived Genes Are Novel Prognostic Biomarkers for Triple-Negative Breast Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Maoni Guo ◽  
San Ming Wang
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Genome Instability ◽  
Molecular Taxonomy ◽  
Gene Signature ◽  
Rank Test ◽  
Log Rank Test ◽  
A Genome

BackgroundTriple-negative breast cancer (TNBC) is an aggressive disease. Recent studies have identified genome instability-derived genes for patient outcomes. However, most of the studies mainly focused on only one or a few genome instability-related genes. Prognostic potential and clinical significance of genome instability-associated genes in TNBC have not been well explored.MethodsIn this study, we developed a computational approach to identify TNBC prognostic signature. It consisted of (1) using somatic mutations and copy number variations (CNVs) in TNBC to build a binary matrix and identifying the top and bottom 25% mutated samples, (2) comparing the gene expression between the top and bottom 25% samples to identify genome instability-related genes, and (3) performing univariate Cox proportional hazards regression analysis to identify survival-associated gene signature, and Kaplan–Meier, log-rank test, and multivariate Cox regression analyses to obtain overall survival (OS) information for TNBC outcome prediction.ResultsFrom the identified 111 genome instability-related genes, we extracted a genome instability-derived gene signature (GIGenSig) of 11 genes. Through survival analysis, we were able to classify TNBC cases into high- and low-risk groups by the signature in the training dataset (log-rank test p = 2.66e−04), validated its prognostic performance in the testing (log-rank test p = 2.45e−02) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (log-rank test p = 2.57e−05) datasets, and further validated the predictive power of the signature in five independent datasets.ConclusionThe identified novel signature provides a better understanding of genome instability in TNBC and can be applied as prognostic markers for clinical TNBC management.

Patterns of recurrence in triple negative breast cancer patients (automated IHC) : An Indian Tertiary Care Center data.

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. e13128-e13128
Author(s):  
Joydeep Ghosh ◽  
Sanjit Agarwal ◽  
Sandip Ganguly ◽  
Deepak Dabkara ◽  
Bivas Biswas ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Care Center ◽  
Tertiary Care ◽  
Tertiary Care Center ◽  
Breast Cancer Patients ◽  
Patterns Of Recurrence

Triple Negative Breast Cancer: Experience from a North Indian Tertiary Care Center

2017 ◽  
Vol 80 (5) ◽  
pp. 474-478 ◽  
Author(s):  
Rahul Khanna ◽  
Ram Niwas Meena ◽  
Akash Bansal ◽  
S. C. U. Patne ◽  
Shashi Prakash Mishra ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Care Center ◽  
Tertiary Care ◽  
Tertiary Care Center ◽  
Cancer Experience

A novel three-long noncoding RNA risk score system for the prognostic prediction of triple-negative breast cancer

2021 ◽  
Vol 15 (1) ◽  
pp. 43-55
Author(s):  
Chao Yuan ◽  
Hongjun Yuan ◽  
Li Chen ◽  
Miaomiao Sheng ◽  
Wenru Tang
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Triple Negative Breast Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Triple Negative ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Gene Expression Omnibus ◽  
Prognostic Prediction

Background: Triple-negative breast cancer (TNBC) is characterized by fast tumor increase, rapid recurrence and natural metastasis. We aimed to identify a genetic signature for predicting the prognosis of TNBC. Materials & methods: We conducted a weighted correlation network analysis of datasets from the Gene Expression Omnibus. Multivariate Cox regression was used to construct a risk score model. Results: The multi-factor risk scoring model was meaningfully associated with the prognosis of patients with TBNC. The predictive power of the model was demonstrated by the time-dependent receiver operating characteristic curve and Kaplan–Meier curve, and verified using a validation set. Conclusion: We established a long noncoding RNA-based model for the prognostic prediction of TNBC.

scholarly journals Selection of aptamers against triple negative breast cancer cells using high throughput sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Débora Ferreira ◽  
Joaquim Barbosa ◽  
Diana A. Sousa ◽  
Cátia Silva ◽  
Luís D. R. Melo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Throughput ◽  
Triple Negative Breast Cancer ◽  
High Throughput Sequencing ◽  
Triple Negative ◽  
Metastatic Breast ◽  
Target Cells ◽  
Cancer Tissue ◽  
Surface Receptors

AbstractTriple-negative breast cancer is the most aggressive subtype of invasive breast cancer with a poor prognosis and no approved targeted therapy. Hence, the identification of new and specific ligands is essential to develop novel targeted therapies. In this study, we aimed to identify new aptamers that bind to highly metastatic breast cancer MDA-MB-231 cells using the cell-SELEX technology aided by high throughput sequencing. After 8 cycles of selection, the aptamer pool was sequenced and the 25 most frequent sequences were aligned for homology within their variable core region, plotted according to their free energy and the key nucleotides possibly involved in the target binding site were analyzed. Two aptamer candidates, Apt1 and Apt2, binding specifically to the target cells with $$K_{d}$$ K d values of 44.3 ± 13.3 nM and 17.7 ± 2.7 nM, respectively, were further validated. The binding analysis clearly showed their specificity to MDA-MB-231 cells and suggested the targeting of cell surface receptors. Additionally, Apt2 revealed no toxicity in vitro and showed potential translational application due to its affinity to breast cancer tissue sections. Overall, the results suggest that Apt2 is a promising candidate to be used in triple-negative breast cancer treatment and/or diagnosis.

scholarly journals The extracellular-regulated protein kinase 5 (ERK5) enhances metastatic burden in triple-negative breast cancer through focal adhesion protein kinase (FAK)-mediated regulation of cell adhesion

Oncogene ◽  
2021 ◽  
Author(s):  
Qiuping Xu ◽  
Jingwei Zhang ◽  
Brian A. Telfer ◽  
Hao Zhang ◽  
Nisha Ali ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Protein Kinase ◽  
Tumor Growth ◽  
Focal Adhesion ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Metastatic Breast ◽  
Adhesion Protein ◽  
Focal Adhesion Protein

AbstractThere is overwhelming clinical evidence that the extracellular-regulated protein kinase 5 (ERK5) is significantly dysregulated in human breast cancer. However, there is no definite understanding of the requirement of ERK5 in tumor growth and metastasis due to very limited characterization of the pathway in disease models. In this study, we report that a high level of ERK5 is a predictive marker of metastatic breast cancer. Mechanistically, our in vitro data revealed that ERK5 was critical for maintaining the invasive capability of triple-negative breast cancer (TNBC) cells through focal adhesion protein kinase (FAK) activation. Specifically, we found that phosphorylation of FAK at Tyr397 was controlled by a kinase-independent function of ERK5. Accordingly, silencing ERK5 in mammary tumor grafts impaired FAK phosphorylation at Tyr397 and suppressed TNBC cell metastasis to the lung without preventing tumor growth. Collectively, these results establish a functional relationship between ERK5 and FAK signaling in promoting malignancy. Thus, targeting the oncogenic ERK5-FAK axis represents a promising therapeutic strategy for breast cancer exhibiting aggressive clinical behavior.

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