scholarly journals Serum Long Non-Coding RNAs PVT1, HOTAIR, and NEAT1 as Potential Biomarkers in Egyptian Women with Breast Cancer

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 301
Author(s):  
Amal Ahmed Abd El-Fattah ◽  
Nermin Abdel Hamid Sadik ◽  
Olfat Gamil Shaker ◽  
Amal Mohamed Kamal ◽  
Nancy Nabil Shahin
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Cancer Patients ◽  
Breast Cancer Diagnosis ◽  
Serum Levels ◽  
Breast Cancer Patients ◽  
Multivariate Logistic Regression ◽  
Expression Levels ◽  
Non Coding Rnas ◽  
Pai 1

Long non-coding RNAs play an important role in tumor growth, angiogenesis, and metastasis in several types of cancer. However, the clinical significance of using lncRNAs as biomarkers for breast cancer diagnosis and prognosis is still poorly investigated. In this study, we analyzed the serum expression levels of lncRNAs PVT1, HOTAIR, NEAT1, and MALAT1, and their associated proteins, PAI-1, and OPN, in breast cancer patients compared to fibroadenoma patients and healthy subjects. Using quantitative real-time PCR (qRT-PCR), we compared the serum expression levels of the four circulating lncRNAs in patients with breast cancer (n = 50), fibroadenoma (n = 25), and healthy controls (n = 25). The serum levels of PAI-1 and OPN were measured using ELISA. Receiveroperating-characteristic (ROC) analysis and multivariate logistic regression were used to evaluate the diagnostic value of the selected parameters. The serum levels of HOTAIR, PAI-1, and OPN were significantly higher in breast cancer patients compared to controls and fibroadenoma patients. The serum level of PVT1 was significantly higher in breast cancer patients than in the controls, while that of NEAT1 was significantly lower in breast cancer patients compared to controls and fibroadenoma patients. Both ROC and multivariate logistic regression analyses revealed that PAI-1 has the greatest power in discriminating breast cancer from the control, whereas HOTAIR, PAI-1, and OPN have the greatest power in discriminating breast cancer from fibroadenoma patients. In conclusion, our data suggest that the serum levels of PVT1, HOTAIR, NEAT1, PAI-1, and OPN could serve as promising diagnostic biomarkers for breast cancer.

scholarly journals Study of Gene Expression of Programmed Cell Death Ligand 1 (PD-L1) in Breast Cancer Patients

2021 ◽  
Vol 107 (1_suppl) ◽  
pp. 2-2
Author(s):  
H Gadelrab ◽  
M Mokhtar ◽  
H Morsy ◽  
M Elnaggar
Keyword(s):  
Breast Cancer ◽  
Cell Death ◽  
Programmed Cell Death ◽  
Cancer Patients ◽  
Therapeutic Response ◽  
Female Breast Cancer ◽  
Clinicopathological Parameters ◽  
Breast Cancer Patients ◽  
Expression Levels ◽  
Female Breast

Introduction: Breast cancer is the most frequently occurring cancer among females and the second most common cancer overall. Programmed Cell Death Ligand 1 (PD-L1) plays an important role in blocking ‘cancer-immunity cycle’ and is considered as a major inhibitory pathway. The aim of the present study was to clarify the alterations of expression of PD-L1 in peripheral blood mononuclear cytes (PBMCs) of female breast cancer patients and analyze its association with clinico-pathological criteria as well as therapeutic response. Materials and Methods: The study was conducted on 45 female breast cancer patients and 45 female controls. Blood samples were collected followed by PBMCs isolation, total RNA extraction, reverse transcription and finally, quantitative polymerase chain reaction (qPCR) using SYBR Green DNA binding dye. Expression levels of PD-L1 were calculated and then compared with clinicopathological parameters of the patients in addition to initial therapeutic response. Results: A significant difference was detected for PD-L1 expression levels in breast cancer patients compared to controls. A significant association with age, metastatic breast cancer, estrogen receptor (ER) negative status as well as high concentrations of cancer antigen 15-3 (CA15-3) was detected. On the other hand, no significant association was recognized with tumor size, lymph nodal status, histopathological type, grade, progesterone receptor (PR) status, human epidermal growth factor receptor 2 (HER-2) status, triple negative, among de novo and recurrent metastatic patients and for the number of metastatic sites as well as the therapeutic response. Conclusions: This study paves the way of the use of PD-L1 as a noninvasive prognostic and diagnostic biomarker for poor prognosis of breast cancer.

scholarly journals Abnormal Long Non-Coding RNAs Expression Patterns Have the Potential Ability for Predicting Survival and Treatment Response in Breast Cancer

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 996
Author(s):  
Ana Carolina Pavanelli ◽  
Flavia Rotea Mangone ◽  
Luciana R. C. Barros ◽  
Juliana Machado-Rugolo ◽  
Vera L. Capelozzi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Predictive Value ◽  
Expression Patterns ◽  
Survival Rates ◽  
In Silico Analysis ◽  
Cancer Prognosis ◽  
Response To Treatment ◽  
Breast Cancer Patients ◽  
Non Coding Rnas

Abnormal long non-coding RNAs (lncRNAs) expression has been documented to have oncogene or tumor suppressor functions in the development and progression of cancer, emerging as promising independent biomarkers for molecular cancer stratification and patients’ prognosis. Examining the relationship between lncRNAs and the survival rates in malignancies creates new scenarios for precision medicine and targeted therapy. Breast cancer (BRCA) is a heterogeneous malignancy. Despite advances in its molecular classification, there are still gaps to explain in its multifaceted presentations and a substantial lack of biomarkers that can better predict patients’ prognosis in response to different therapeutic strategies. Here, we performed a re-analysis of gene expression data generated using cDNA microarrays in a previous study of our group, aiming to identify differentially expressed lncRNAs (DELncRNAs) with a potential predictive value for response to treatment with taxanes in breast cancer patients. Results revealed 157 DELncRNAs (90 up- and 67 down-regulated). We validated these new biomarkers as having prognostic and predictive value for breast cancer using in silico analysis in public databases. Data from TCGA showed that compared to normal tissue, MIAT was up-regulated, while KCNQ1OT1, LOC100270804, and FLJ10038 were down-regulated in breast tumor tissues. KCNQ1OT1, LOC100270804, and FLJ10038 median levels were found to be significantly higher in the luminal subtype. The ROC plotter platform results showed that reduced expression of these three DElncRNAs was associated with breast cancer patients who did not respond to taxane treatment. Kaplan–Meier survival analysis revealed that a lower expression of the selected lncRNAs was significantly associated with worse relapse-free survival (RFS) in breast cancer patients. Further validation of the expression of these DELncRNAs might be helpful to better tailor breast cancer prognosis and treatment.

scholarly journals What mediates the racial/ethnic disparity in psychosocial stress among breast cancer patients?

2021 ◽  
Author(s):  
C. T. Sánchez-Díaz ◽  
S. Strayhorn ◽  
S. Tejeda ◽  
G. Vijayasiri ◽  
G. H. Rauscher ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Social Support ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Psychosocial Stress ◽  
Breast Cancer Diagnosis ◽  
Support Needs ◽  
Breast Cancer Patients ◽  
Hispanic Patients ◽  
Racial Ethnic

Abstract Background Prior studies have observed greater levels of psychosocial stress (PSS) among non-Hispanic (nH) African American and Hispanic women when compared to nH White patients after a breast cancer diagnosis. We aimed to determine the independent and interdependent roles of socioeconomic position (SEP) and unmet support in the racial disparity in PSS among breast cancer patients. Methods Participants were recruited from the Breast Cancer Care in Chicago study (n = 989). For all recently diagnosed breast cancer patients, aged 25–79, income, education, and tract-level disadvantage and affluence were summed to create a standardized socioeconomic position (SEP) score. Three measures of PSS related to loneliness, perceived stress, and psychological consequences of a breast cancer diagnosis were defined based on previously validated scales. Five domains of unmet social support needs (emotional, spiritual, informational, financial, and practical) were defined from interviews. We conducted path models in MPlus to estimate the extent to which PSS disparities were mediated by SEP and unmet social support needs. Results Black and Hispanic patients reported greater PSS compared to white patients and greater unmet social support needs (p = 0.001 for all domains). Virtually all of the disparity in PSS could be explained by SEP. A substantial portion of the mediating influence of SEP was further transmitted by unmet financial and practical needs among Black patients and by unmet emotional needs for Hispanic patients. Conclusions SEP appeared to be a root cause of the racial/ethnic disparities in PSS within our sample. Our findings further suggest that different interventions may be necessary to alleviate the burden of SEP for nH AA (i.e., more financial support) and Hispanic patients (i.e., more emotional support).

Exploring The Clinical Significance of Serum Angiopoietin-2 In Breast Cancer Patients

QJM ◽  
2021 ◽  
Vol 114 (Supplement_1) ◽  
Author(s):  
Abeer I Abd Elmagid ◽  
Hala Abdel Al ◽  
Wessam El Sayed Saad ◽  
Seham Kamal Mohamed
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Serum Levels ◽  
Tnm Staging ◽  
Control Group ◽  
Healthy Controls ◽  
Breast Cancer Patients ◽  
Female Patients ◽  
Significant Difference ◽  
Angiopoietin 2

Abstract Background Breast cancer is the most common cancer among women and one of the most important causes of death among them.Angiogenesis is an important step for primary tumor growth, invasiveness, and metastases. Angiopoietins are well-recognized endothelial growth factors that are involved in angiogenesis associated with tumors. Aim To explore the diagnostic significance of serum angiopoietin-2 (Ang-2) in breast cancer and to evaluate its prognostic efficacy through studying the degree of its association with the TNM staging of the disease. Patients and Methods This study was conducted on (35) Egyptian female patients who were diagnosed as breast cancer according to histopathological examination of breast biopsy (Group 1, Breast Cancer Patients) and (25) female patients with benign breast diseases (Group II, Pathological Control Patients), in addition to (20) age - matched apparently healthy, free mammogram, females serving as healthy controls (Group III, Healthy Controls). For all participants, measurement of serum Ang-2 was done using enzyme linked immunosorbent assay (ELISA) technique. Results A highly significant increased levels of Ang-2 was observed in breast cancer patients when compared to healthy control group (Z = 4.95, p < 0.01). However, no significant difference was observed in Ang-2 levels between breast cancer patients group and pathological control group (Z = 3.37, p > 0.05). No significant difference was detected in Ang-2 levels in relation to TNM stage and histological grade. No significant correlation was found between Ang-2 levels and serum levels of CA15-3, hormone receptors, HER2/new receptor status (p > 0.05, respectively). Conclusion This study revealed that Ang-2 serum levels were significantly increased in patient with breast cancer compared with healthy controls, indicating that high Ang-2 level is a promising non invasive biomarker for breast cancer diagnosis. However, no significant difference of Ang-2 levels was detected in relation of breast TNM staging in the population studied.

scholarly journals Serum levels of oxidative stress marker malondialdehyde in breast cancer patients in relation to pathohistological factors, estrogen receptors, menopausal status, and age

2018 ◽  
Vol 8 (3) ◽  
pp. 154-161
Author(s):  
Jasmina Gubaljevic ◽  
Nahida Srabović ◽  
Adlija Jevrić-Čaušević ◽  
Adaleta Softić ◽  
Adi Rifatbegović ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Benign Breast Disease ◽  
Menopausal Status ◽  
Serum Levels ◽  
Breast Disease ◽  
Breast Cancer Patients ◽  
Node Metastases

Introduction: The aim of this study was to determine the serum levels of malondialdehyde (MDA) in patients with invasive breast cancer in relation to its serum levels in patients with benign breast disease, and to investigate correlation between MDA serum levels with pathohistological prognostic factors (tumor size, lymph node involvement, and histologic grade [HG]), estrogen receptor (ER) status, and with breast cancer patient’s age and menopausal status. Methods: A total of 43 with well-documented invasive breast cancer were included in this study: 27 with positive axillary’s lymph nodes, and 16 with negative axillary’s lymph nodes, and 39 patients with findings of benign breast diseases. MDA determination in serum of breast cancer and benign breast disease patients was performed by the fluorimetric method, immunohistochemical staining was performed for ER, and routine pathohistological examination was conducted for pathohistological factors. Results: MDA serum levels in breast cancer patients were significantly higher than MDA serum levels in benign breast disease patients (p = 0.042). No statistically significant difference between MDA serum levels in breast cancer patients with and without lymph node metastases was found (p = 0.238). No statistically significant correlations between MDA serum levels and tumor size (p = 0.256), HG (p = 0.124), or number of positive lymph nodes (0.113) were found. A statistically significant correlation between serum MDA levels and ages of breast cancer patients with lymph node metastases was found (p = 0.006). Conclusion: Obtained results support the importance of MDA in the carcinogenesis of breast cancer. According to our findings, serum level of MDA could not be a useful prognostic factor in breast cancer.

scholarly journals Predicting the Level of Tumor-Infiltrating Lymphocytes in Patients With Breast Cancer: Usefulness of Mammographic Radiomics Features

2021 ◽  
Vol 11 ◽  
Author(s):  
Hongwei Yu ◽  
Xianqi Meng ◽  
Huang Chen ◽  
Jian Liu ◽  
Wenwen Gao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Feature Selection ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Training Dataset ◽  
Validation Dataset ◽  
Gray Level ◽  
Breast Cancer Patients ◽  
Short Run

ObjectivesThis study aimed to investigate whether radiomics classifiers from mammography can help predict tumor-infiltrating lymphocyte (TIL) levels in breast cancer.MethodsData from 121 consecutive patients with pathologically-proven breast cancer who underwent preoperative mammography from February 2018 to May 2019 were retrospectively analyzed. Patients were randomly divided into a training dataset (n = 85) and a validation dataset (n = 36). A total of 612 quantitative radiomics features were extracted from mammograms using the Pyradiomics software. Radiomics feature selection and radiomics classifier were generated through recursive feature elimination and logistic regression analysis model. The relationship between radiomics features and TIL levels in breast cancer patients was explored. The predictive capacity of the radiomics classifiers for the TIL levels was investigated through receiver operating characteristic curves in the training and validation groups. A radiomics score (Rad score) was generated using a logistic regression analysis method to compute the training and validation datasets, and combining the Mann–Whitney U test to evaluate the level of TILs in the low and high groups.ResultsAmong the 121 patients, 32 (26.44%) exhibited high TIL levels, and 89 (73.56%) showed low TIL levels. The ER negativity (p = 0.01) and the Ki-67 negative threshold level (p = 0.03) in the low TIL group was higher than that in the high TIL group. Through the radiomics feature selection, six top-class features [Wavelet GLDM low gray-level emphasis (mediolateral oblique, MLO), GLRLM short-run low gray-level emphasis (craniocaudal, CC), LBP2D GLRLM short-run high gray-level emphasis (CC), LBP2D GLDM dependence entropy (MLO), wavelet interquartile range (MLO), and LBP2D median (MLO)] were selected to constitute the radiomics classifiers. The radiomics classifier had an excellent predictive performance for TIL levels both in the training and validation sets [area under the curve (AUC): 0.83, 95% confidence interval (CI), 0.738–0.917, with positive predictive value (PPV) of 0.913; AUC: 0.79, 95% CI, 0.615–0.964, with PPV of 0.889, respectively]. Moreover, the Rad score in the training dataset was higher than that in the validation dataset (p = 0.007 and p = 0.001, respectively).ConclusionRadiomics from digital mammograms not only predicts the TIL levels in breast cancer patients, but can also serve as non-invasive biomarkers in precision medicine, allowing for the development of treatment plans.

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