INVESTIGATING THE RELATIONSHIPS BETWEEN EXPRESSED CANCER RELATED GENES AND SURVIVAL OF PATIENTS WITH BREAST CANCER

2021 ◽  
Vol 5 (2) ◽  
pp. 327-333
Author(s):  
Chinenye Nworah ◽  
Bashir Sule
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Dynamic Range ◽  
Pearson Correlation ◽  
Expression Patterns ◽  
Parametric Models ◽  
Normal Model ◽  
Breast Cancer Patients ◽  
Expression Levels ◽  
Log Normal

Cancer stem cells are regulated by complex interactions with the components of the tumor microenvironment through networks of Cytokins and growth factors. These interactions are mediated by group of proteins and microRNAs (miRs), which are expressed or repressed. These expression levels are critical for cancer stem cell formation and expansion, enabling the promotion of tumor cell proliferation and migration, as well as for the survival of cancer recurrence and patient survival. Micro array and RNA deep sequencing (RNA-seq) provide tools with ability to generate transcriptome information, deciphering global gene expression patterns and quantifying a large dynamic range of expression levels. In this study 94 breast cancer patients were investigated based on miR and mRNA expression levels in which WDR1, APC and AKAP13 genes were identified as genes that play important role in the survival of patients and these genes differed significantly with respect to survival of patients. We used the Pearson correlation to identify the over-expressed and under-expressed genes. We demonstrated that parametric survival models can be used to model outcomes for breast cancer, and for our dataset the log-normal model demonstrated the best fit compared to other parametric models. Through the use of log-normal model, we examined how each of the identified genes influence the survival of breast cancer patients.

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 HUBUNGAN ANTARA NAFSU MAKAN DENGAN ASUPAN ENERGI DAN PROTEIN PADA PASIEN KANKER PAYUDARA POST KEMOTERAPI[Correlation between Appetite with Energy and Protein Intake of Post Chemotherapy Breast Cancer Patients]

2019 ◽  
Vol 14 (2) ◽  
pp. 170
Author(s):  
Silviana Putri ◽  
Merryana Adriani ◽  
Yayuk Estuningsih
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Side Effect ◽  
Protein Intake ◽  
Pearson Correlation ◽  
Observational Research ◽  
Breast Cancer Patients ◽  
Cross Sectional ◽  
Chemotherapy Drugs ◽  
Pearson Correlation Test

Chemotherapy drugs used to kill or inhibit proliferation of cancer cell that are cytotoxic and causing side effect for breast cancer patients. The side effect of chemotherapy drugs is decreasing the appetite which causing decrease in energy and protein intake, and could affect nutritional status. This study aim to determine the relationship between appetite with energy and protein intake of post chemotherapy breast cancer patients. This research was an analytic observational research using cross sectional design and purposive sampling conducted at Dr. Ramelan Navy Hospital Surabaya with a sample size of 50 patients. Correlation between appetite with energy and protein intake were analyzed using Pearson correlation. The average of energy and protein intake were 976.3±304.2 kcal and 29.4±12.9 g. Pearson correlation test showed signifi cant correlation between appetite as chemoteraphy side effect with energy intake (p=0.000; r=-0.558) and protein intake (p=0.000; r=-0.504). Decreasing of appetite due to chemoterapy reduce the energy and protein intake of breast cancer patient. Patient are suggest to consume foods in small portion but often to maintain adequate energy and protein intake.

scholarly journals The expression and clinical significance of GADD45A in breast cancer patients

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5344 ◽  
Author(s):  
Junnan Wang ◽  
Yiran Wang ◽  
Fei Long ◽  
Fengshang Yan ◽  
Ning Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Cancer Patients ◽  
Clinical Significance ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Cancer Patients ◽  
Ki 67 ◽  
Expression Levels ◽  
Cancer Tissues

BackgroundGrowth arrest and DNA-damage-inducible protein 45 alpha (GADD45A) was previously found to be associated with risk of several kinds of human tumors. Here, we studied the expression and clinical significance of GADD45A in breast cancer.MethodsWe performed an immunohistochemical study of GADD45A protein from 419 breast cancer tissues and 116 adjacent non-neoplastic tissues.ResultsSignificantly high GADD45A expression were observed in breast cancer tissues compared with adjacent non-neoplastic tissues (P < 0.001) and were independently correlative with estrogen receptor negative (P = 0.028) and high Ki-67 index (P < 0.001). Kaplan–Meier survival analysis revealed that patients with high GADD45A expression levels had a worse long-term prognosis in triple negative breast cancer (P = 0.041), but it was not an independent prognostic factor in multivariate analysis (P = 0.058).ConclusionsGADD45A expression levels are significantly correlative with estrogen receptor status and Ki-67 index in human breast cancer. Patients with triple negative breast cancer might be stratified into high risk and low risk groups based on the GADD45A expression levels.

scholarly journals Multilectin Affinity Chromatography for Characterization of Multiple Glycoprotein Biomarker Candidates in Serum from Breast Cancer Patients

2006 ◽  
Vol 52 (10) ◽  
pp. 1897-1905 ◽  
Author(s):  
Ziping Yang ◽  
Lyndsay E Harris ◽  
Darryl E Palmer-Toy ◽  
William S Hancock
Keyword(s):  
Breast Cancer ◽  
Gene Ontology ◽  
Affinity Chromatography ◽  
Cancer Patients ◽  
Dynamic Range ◽  
Ion Homeostasis ◽  
Internal Standard ◽  
Breast Cancer Patients ◽  
Protease Inhibition ◽  
Large Panels

Abstract Background: Glycoproteins are often associated with cancer and are important in serum studies, for which glycosylation is a common posttranslational modification. Methods: We used multilectin affinity chromatography (M-LAC) to isolate glycoproteins from the sera of breast cancer patients and controls. The proteins were identified by HPLC–tandem mass spectrometry (MS/MS) analysis of the corresponding tryptic digests. We used the FuncAssociate Gene Ontology program for association analysis of the identified proteins. Biomarker candidates in these groups were comparatively quantitated by use of peak area measurements, with inclusion of an internal standard. We analyzed data for concordance within the ontology association groups for vector of change with the development of breast cancer. Results: Detection of the known low-concentration biomarker HER-2 (8–24 μg/L) enabled us to establish a dynamic range of 106, relative to the amount of albumin, for the depletion step. We then used ELISA to confirm this range. Proteins associated with lipid transport and metabolism, cell growth and maintenance, ion homeostasis, and protease inhibition were found to be differentially regulated in serum from women with breast cancer compared with serum from women without breast cancer. Conclusions: M-LAC for isolation of the serum glycoproteome, coupled with liquid chromatography–MS/MS and the use of gene ontology associations, can be used to characterize large panels of candidate markers, which can then be evaluated in a particular patient population.

scholarly journals High ERK Protein Expression Levels Correlate with Shorter Survival in Triple‐Negative Breast Cancer Patients

2012 ◽  
Vol 17 (6) ◽  
pp. 766-774 ◽  
Author(s):  
Chandra Bartholomeusz ◽  
Ana M. Gonzalez‐Angulo ◽  
Ping Liu ◽  
Naoki Hayashi ◽  
Ana Lluch ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Protein Expression ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Cancer Patients ◽  
Expression Levels

scholarly journals Expression of MTDH and IL-10 Is an Independent Predictor of Worse Prognosis in ER-Negative or PR-Negative Breast Cancer Patients

2020 ◽  
Vol 9 (10) ◽  
pp. 3153
Author(s):  
Pei-Yi Chu ◽  
Shin-Mae Wang ◽  
Po-Ming Chen ◽  
Feng-Yao Tang ◽  
En-Pei Isabel Chiang
Keyword(s):  
Breast Cancer ◽  
Protein Expression ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Expression Patterns ◽  
Hypoxia Inducible Factor ◽  
Tumor Hypoxia ◽  
Tissue Microarrays ◽  
Breast Cancer Patients ◽  
Worse Prognosis

(1) Background: Tumor hypoxia leads to metastasis and certain immune responses, and interferes with normal biological functions. It also affects glucose intake, down-regulates oxidative phosphorylation, and inhibits fatty-acid desaturation regulated by hypoxia-inducible factor 1α (HIF-1α). Although tumor hypoxia has been found to promote tumor metastasis, the roles of HIF-1α-regulated genes and their application are not completely integrated in clinical practice. (2) Methods: We examined the correlation between HIF-1α, metadherin (MTDH), and interleukin (IL)-10 mRNA expression, as well as their expression patterns in the prognosis of breast cancer using the Gene Expression Profiling Interactive Analysis (GEPIA) databases via a web interface; tissue microarrays (TMAs) were stained for MTDH and IL-10 protein expression using immunohistochemistry. (3) Results: HIF-1α, MTDH, and IL-10 mRNA expression are highly correlated and strongly associated with poor prognosis. MTDH and IL-10 protein expression of breast cancer patients usually harbored negative estrogen receptor (ER) or progesterone receptor (PR) status, and late-stage tumors have higher IL-10 expression. With regard to MTDH and IL-10 protein expression status for using univariate and multivariate analysis, the results showed that the protein expression of MTDH and IL-10 in ER-negative or PR-negative breast cancer patients have the worse prognosis. (4) Conclusions: we propose a new insight into hypoxia tumors in the metabolism and immune evidence for breast cancer therapy.

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