scholarly journals A Novel Systematic Oxidative Stress Score Predicts the Prognosis of Patients with Operable Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Kaiming Zhang ◽  
Liqin Ping ◽  
Tian Du ◽  
Yan Wang ◽  
Ya Sun ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Oxidative Stress ◽  
Cancer Patients ◽  
Operable Breast Cancer ◽  
Breast Cancer Patients ◽  
Training Set ◽  
Oxidative Stress Biomarkers ◽  
Stress Biomarkers ◽  
Validation Set ◽  
The Relationship

Background. Breast cancer was associated with imbalance between oxidation and antioxidation. Local oxidative stress in tumors is closely related to the occurrence and development of breast cancer. However, the relationship between systematic oxidative stress and breast cancer remains unclear. This study is aimed at exploring the prognostic value of systematic oxidative stress in patients with operable breast cancer. Methods. A total of 1583 operable female breast cancer patients were randomly assigned into the training set and validation set. The relationship between systematic oxidative stress biomarkers and prognosis were analyzed in the training and validation sets. Results. The systematic oxidative stress score (SOS) was established based on five systematic oxidative stress biomarkers including serum creatinine (CRE), serum albumin (ALB), total bilirubin (TBIL), lactate dehydrogenase (LDH), and blood urea nitrogen (BUN). SOS was an independent prognostic factor for operable breast cancer patients. A nomogram based on SOS and clinical characteristics could accurately predict the prognosis of operable breast cancer patients, and the area under the curve (AUC) of the nomogram was 0.823 in the training set and 0.872 in the validation set, which was much higher than the traditional prognostic indicators. Conclusions. SOS is an independent prognostic indicator for operable breast cancer patients. A prediction model based on SOS could accurately predict the outcome of operable breast cancer patients.

scholarly journals Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244693
Author(s):  
Lingchen Wang ◽  
Wenhua Wang ◽  
Shaopeng Zeng ◽  
Huilie Zheng ◽  
Quqin Lu
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Lung Metastasis ◽  
Cancer Metastasis ◽  
External Validation ◽  
Breast Cancer Patients ◽  
Training Set ◽  
Validation Set ◽  
Robust Likelihood ◽  
Six Genes

Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient prediction tool based on several genes that may affect lung metastasis-free survival (LMFS). We preliminarily identified 319 genes associated with lung metastasis in the training set GSE5327 (n = 58). Enrichment analysis of GO functions and KEGG pathways was conducted based on these genes. The best genes for modeling were selected using a robust likelihood-based survival modeling approach: GOLGB1, TMEM158, CXCL8, MCM5, HIF1AN, and TSPAN31. A prognostic nomogram for predicting lung metastasis in breast cancer was developed based on these six genes. The effectiveness of the nomogram was evaluated in the training set GSE5327 and the validation set GSE2603. Both the internal validation and the external validation manifested the effectiveness of our 6-gene prognostic nomogram in predicting the lung metastasis risk of breast cancer patients. On the other hand, in the validation set GSE2603, we found that neither the six genes in the nomogram nor the risk predicted by the nomogram were associated with bone metastasis of breast cancer, preliminarily suggesting that these genes and nomogram were specifically associated with lung metastasis of breast cancer. What’s more, five genes in the nomogram were significantly differentially expressed between breast cancer and normal breast tissues in the TIMER database. In conclusion, we constructed a new and convenient prediction model based on 6 genes that showed practical value in predicting the lung metastasis risk for clinical breast cancer patients. In addition, some of these genes could be treated as potential metastasis biomarkers for antimetastatic therapy in breast cancer. The evolution of this nomogram will provide a good reference for the prediction of tumor metastasis to other specific organs.

scholarly journals A prediction model using 2-propanol and 2-butanone in urine distinguishes breast cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shoko Kure ◽  
Sera Satoi ◽  
Toshihiko Kitayama ◽  
Yuta Nagase ◽  
Nobuo Nakano ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Volatile Organic Compounds ◽  
Cancer Patients ◽  
Organic Compounds ◽  
External Validation ◽  
Healthy Controls ◽  
Breast Cancer Patients ◽  
Training Set ◽  
Volatile Organic ◽  
Validation Set

AbstractSafe and noninvasive methods for breast cancer screening with improved accuracy are urgently needed. Volatile organic compounds (VOCs) in biological samples such as breath and blood have been investigated as noninvasive novel markers of cancer. We investigated volatile organic compounds in urine to assess their potential for the detection of breast cancer. One hundred and ten women with biopsy-proven breast cancer and 177 healthy volunteers were enrolled. The subjects were divided into two groups: a training set and an external validation set. Urine samples were collected and analyzed by gas chromatography and mass spectrometry. A predictive model was constructed by multivariate analysis, and the sensitivity and specificity of the model were confirmed using both a training set and an external set with reproducibility tests. The training set included 60 breast cancer patients (age 34–88 years, mean 60.3) and 60 healthy controls (age 34–81 years, mean 58.7). The external validation set included 50 breast cancer patients (age 35–85 years, mean 58.8) and 117 healthy controls (age 18–84 years, mean 51.2). One hundred and ninety-one compounds detected in at least 80% of the samples from the training set were used for further analysis. The predictive model that best-detected breast cancer at various clinical stages was constructed using a combination of two of the compounds, 2-propanol and 2-butanone. The sensitivity and specificity in the training set were 93.3% and 83.3%, respectively. Triplicated reproducibility tests were performed by randomly choosing ten samples from each group, and the results showed a matching rate of 100% for the breast cancer patient group and 90% for the healthy control group. Our prediction model using two VOCs is a useful complement to the current diagnostic tools. Further studies inclusive of benign tumors and non-breast malignancies are warranted.

scholarly journals Nonenzymatic Evaluation of Antioxidant and Lipid Peroxidation Level in Breast Cancer Patients Receiving Juice of Wheat Grass during Treatment

2016 ◽  
Vol 02 ◽  
pp. 1
Author(s):  
Pragati Singh ◽  
Brij Raj Shrivastav ◽  
Archana Shrivastav ◽  
◽  
◽  
...  
Keyword(s):  
Breast Cancer ◽  
Oxidative Stress ◽  
Lipid Peroxidation ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Breast Cancer Chemotherapy ◽  
Chemotherapeutic Approach ◽  
Age Range ◽  
The Relationship ◽  
Normal Controls

For breast cancer, chemotherapy is the most common treatment in the world. In breast cancer patients, oxidative stress leads to accumulation of free radicals, which generate more oxidative stress during chemotherapy. This chemotherapeutic approach also leads to enhanced generation of reactive oxygen species and increased oxidative stress as a result. Blood samples were collected from 30 subjects (15 patients who received wheat grass juice (WGJ) and 15 patients who were only on chemotherapy) in the age range 25-60. The goal of the present investigation was to study the relationship between oxidative stress and breast cancer by measuring the non-enzymatic antioxidant levels of Glutathione reductase (GSH) and Malondialdehyde (MDA), which are the markers of lipid peroxidation in breast cancer patients and effect of wheat grass juice on these markers. From the results obtained, it was clear that MDA levels were higher whereas GSH levels decreased in breast cancer patients compared with normal controls. Significant changes in the MDA and GSH values were observed between the group receiving WGJ and the group receiving only chemotherapy. The administration of WGJ along with the treatment reduces the extent of oxidative damage and related complications in breast cancer patients.

scholarly journals Identification of a 6-gene signature for the survival prediction of breast cancer patients based on integrated multi-omics data analysis

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241924
Author(s):  
Wenju Mo ◽  
Yuqin Ding ◽  
Shuai Zhao ◽  
Dehong Zou ◽  
Xiaowen Ding
Keyword(s):  
Breast Cancer ◽  
Feature Selection ◽  
Cancer Patients ◽  
Copy Number ◽  
Gene Signature ◽  
Breast Cancer Patients ◽  
Training Set ◽  
Test Set ◽  
Genomic Variants ◽  
Validation Set

Purpose To identify a gene signature for the prognosis of breast cancer using high-throughput analysis. Methods RNASeq, single nucleotide polymorphism (SNP), copy number variation (CNV) data and clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA), and randomly divided into training set or verification set. Genes related to breast cancer prognosis and differentially expressed genes (DEGs) with CNV or SNP were screened from training set, then integrated together for feature selection of identify robust biomarkers using RandomForest. Finally, a gene-related prognostic model was established and its performance was verified in TCGA test set, Gene Expression Omnibus (GEO) validation set and breast cancer subtypes. Results A total of 2287 prognosis-related genes, 131 genes with amplified copy numbers, 724 gens with copy number deletions, and 280 genes with significant mutations screened from Genomic Variants were closely correlated with the development of breast cancer. A total of 120 candidate genes were obtained by integrating genes from Genomic Variants and those related to prognosis, then 6 characteristic genes (CD24, PRRG1, IQSEC3, MRGPRX, RCC2, and CASP8) were top-ranked by RandomForest for feature selection, noticeably, several of these have been previously reported to be associated with the progression of breast cancer. Cox regression analysis was performed to establish a 6-gene signature, which can stratify the risk of samples from training set, test set and external validation set, moreover, the five-year survival AUC of the model in the training set and validation set was both higher than 0.65. Thus, the 6-gene signature developed in the current study could serve as an independent prognostic factor for breast cancer patients. Conclusion This study constructed a 6-gene signature as a novel prognostic marker for predicting the survival of breast cancer patients, providing new diagnostic/prognostic biomarkers and therapeutic targets for breast cancer patients.

The relationship of self-acceptance with decision making duration in cancer patient to perform mastectomy

2021 ◽  
pp. 1-5
Author(s):  
Ayu Ratuati Setiawan ◽  
Feny Tunjungsari ◽  
Mochamad Aleq Sander
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Cross Sectional ◽  
Abnormal Growth ◽  
Self Acceptance ◽  
Observation Method ◽  
Relationship Of ◽  
The Relationship

BACKGROUND: Cancer is a disease caused by abnormal growth of body cells that turn malignant and continue to grow uncontrollably. One of the treatments for breast cancer is mastectomy. The quickness of decision-making determines the survival rate of prognosis patients. OBJECTIVE: This study aimed to determine the relationship of self-acceptance with decision-making duration in cancer patients to perform a mastectomy. METHODS: An analytic observation method with cross-sectional design. The samples were taken by purposive sampling method with 50 samples of breast cancer patients. Data collected include age, last level of education, marital status, profession, stage of cancer during mastectomy, self-acceptance score, and decision-making duration to perform a mastectomy. RESULTS: The data analyzed with the Kruskal–Wallis test. The test showed the relationship of self-acceptance (p = 0.027) with decision-making duration in breast cancer patients to perform a mastectomy. CONCLUSION: In Conclusion, there is a relationship of self-acceptance with decision-making duration in breast cancer patients to perform a mastectomy.

scholarly journals Relationship Between Obesity and Pathologic Response to Neoadjuvant Chemotherapy Among Women With Operable Breast Cancer

2008 ◽  
Vol 26 (25) ◽  
pp. 4072-4077 ◽  
Author(s):  
Jennifer K. Litton ◽  
Ana M. Gonzalez-Angulo ◽  
Carla L. Warneke ◽  
Aman U. Buzdar ◽  
Shu-Wan Kau ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Pathologic Complete Response ◽  
Operable Breast Cancer ◽  
Obese Patients ◽  
Breast Cancer Patients ◽  
Significant Difference ◽  
Response To Neoadjuvant Chemotherapy

Purpose To understand the mechanism through which obesity in breast cancer patients is associated with poorer outcome, we evaluated body mass index (BMI) and response to neoadjuvant chemotherapy (NC) in women with operable breast cancer. Patients and Methods From May 1990 to July 2004, 1,169 patients were diagnosed with invasive breast cancer at M. D. Anderson Cancer Center and received NC before surgery. Patients were categorized as obese (BMI ≥ 30 kg/m2), overweight (BMI of 25 to < 30 kg/m2), or normal/underweight (BMI < 25 kg/m2). Logistic regression was used to examine associations between BMI and pathologic complete response (pCR). Breast cancer–specific, progression-free, and overall survival times were examined using the Kaplan-Meier method and Cox proportional hazards regression analysis. All statistical tests were two-sided. Results Median age was 50 years; 30% of patients were obese, 32% were overweight, and 38% were normal or underweight. In multivariate analysis, there was no significant difference in pCR for obese compared with normal weight patients (odds ratio [OR] = 0.78; 95% CI, 0.49 to 1.26). Overweight and the combination of overweight and obese patients were significantly less likely to have a pCR (OR = 0.59; 95% CI, 0.37 to 0.95; and OR = 0.67; 95% CI, 0.45 to 0.99, respectively). Obese patients were more likely to have hormone-negative tumors (P < .01), stage III tumors (P < .01), and worse overall survival (P = .006) at a median follow-up time of 4.1 years. Conclusion Higher BMI was associated with worse pCR to NC. In addition, its association with worse overall survival suggests that greater attention should be focused on this risk factor to optimize the care of breast cancer patients.

scholarly journals Roles of Superoxide dismutase(SOD) , Malondialdehyde (MDA), 8-iso-prostaglandinF2α ( 8-iso-PGF2α)as oxidative stress in development and progression of Brest cancer in Iraqi females patients

2020 ◽  
Vol 25 (1) ◽  
pp. 1-4
Author(s):  
Ferdous Abbas Jabir ◽  
Ahmed Sabah Shaker
Keyword(s):  
Breast Cancer ◽  
Oxidative Stress ◽  
Cancer Patients ◽  
Antioxidant Defenses ◽  
Blood Levels ◽  
P Value ◽  
Oxygen Species ◽  
Breast Cancer Patients ◽  
Markers Of Oxidative Stress ◽  
The Mean

               Oxidative stress occurs as a result of disturbance in the balance between the production of reactive oxygen species (free radicals) and antioxidant defenses. Markers of oxidative stress were measured the markers of oxidative stress in breast cancer patients after diagnosis of breast cancer and compared these plasma blood levels controls This study was conducted to three markers of oxidative stress ;these are (SOD) enzyme ,malondialdehyde (MDA)and8-iso-prostaglandinF2α plasma of patients with breast cancer and compare with controls .In this study ;  the mean MDA (ng/ml) levels for the breast cancer patients and the controls were55.91±3.31 and40.61±3.76  respectively, while the SOD (pg/ml) levels were1530.37±80.4 and1851.4 9±93.65  respectively and the 8-iso-PGF2α (ng/ml ) levels were 40.16±3.31 and 30.16±2.34  difference of the mean were statistically significant (p value <0.05).                                                                                                                       

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