Perioperative blood transfusion and cancer prognosis. Different effects of blood transfusion on prognosis of colon and breast cancer patients

Cancer ◽  
1987 ◽  
Vol 59 (4) ◽  
pp. 836-843 ◽  
Author(s):  
Paul J. Voogt ◽  
Cornelis J. H. Van De Velde ◽  
Anneke Brand ◽  
Jo Hermans ◽  
Theo Stijnen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Blood Transfusion ◽  
Cancer Patients ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Perioperative Blood Transfusion

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 THE COMPLEX OF INFORMATIVE IMMUNOLOGICAL PARAMETERS FOR BREAST CANCER OUTCOME PROGNOSIS

2015 ◽  
Vol 14 (3) ◽  
pp. 30-34
Author(s):  
M. N. Stakheyeva ◽  
A. P. Serykh ◽  
S. I. Karas ◽  
E. A. Perina
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Immunological Parameters ◽  
Informative Parameters ◽  
Cell Immunity ◽  
Breast Cancer Outcome ◽  
Cancer Outcome

Prognosis of disease outcome is important procedure for cancer patients treatment. The article presents the problem of elicitation of breast cancer prognosis criteria from immunological data as parameters complex.The aim is to identify necessary and sufficient amount of immunological parameters for accurate classification of breast cancer patients with various outcomes – clinical remission and hematogenous metastases.Material and methods. 36 immunological parameters were studied in 197 breast cancer patients T1–4N0–3M0. The “next neighbor” algorithm was used for identification of informative parameters. Detection of informative parameters complex was carried out by using ADD and DEL methods.Results. Two sets of informative immunological parameters were detected. The ADD method elicited parameters related to T-cell immunity, DEL – to humoral response.Conclusions. The complex of 17–19 immunological parameters characterizing different elements of immune system is necessary for accurate classification of breast cancer patients with different outcomes (presence/absence of hematogenous metastases).

scholarly journals Correlation of Lymphocyte-Monocyte Ratio with Grading of Breast Cancer Malignancy

2020 ◽  
Vol 4 (3) ◽  
pp. 9-18
Author(s):  
Muhartono Muhartono ◽  
Rizki Hanriko ◽  
Suharyani
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Quantitative Research ◽  
Cancer Prognosis ◽  
Rank Test ◽  
P Value ◽  
Test Results ◽  
Breast Cancer Patients ◽  
Histological Grading ◽  
Laboratory Examination

Introduction: Breast cancer cases are increase and fast becoming the leading cause of oncologic mortality among women worldwide. Delay in management will worsen the prognosis of breast cancer patients. The poor prognosis is correlate with high grade of breast cancer malignancy. Histology can be used as an indicator to assess the grade of breast cancer malignancy. In addition, a high predictive value of lymphocyte-monocyte ratio (LMR) has been suggested to indicate favorable prognosis of various cancer, and used as parameters for assessing breast cancer prognosis. Method: This study is a quantitative research, using an observational approach. Laboratory examination results are collected from 43 breast cancer patients who will conduct treatment at Urip Sumoharjo Hospital from June to September 2019. Data are processed by the Spearman rank test using SPSS 22.0. Results: Correlation test results between lymphocyte-monocyte ratio with histological grading of breast cancer obtained a P value of 0.376. Conclusions: Lymphocytes to monocytes ratio (LMR) value cannot be utilize as a parameter for evaluating prognosis of breast cancer.

scholarly journals Association between SNPs within MicroRNA Binding Sites and the Prognosis of Breast Cancer

2020 ◽  
Author(s):  
Liwen Zhang ◽  
Lu Han ◽  
Yubei Huang ◽  
Ziwei Feng ◽  
Xin Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Binding Sites ◽  
Cox Regression ◽  
Breast Cancer Prognosis ◽  
Stage I ◽  
Cancer Prognosis ◽  
Stage Ii ◽  
Breast Cancer Patients ◽  
Survival Times

Abstract Background: Single nucleotide polymorphisms (SNPs) within microRNA binding sites can affect the binding of microRNA to mRNA and regulate gene expression, thereby contributing to the prognosis of cancer. We performed this study to explore the association between SNPs within microRNA binding sites and the prognosis of breast cancer.Methods: We carried out a two-stage study including 2647 breast cancer patients, with a median follow-up of 68 months (range 0-159). In stage I, we genotyped 192 SNPs within microRNA binding sites using the Illumina Goldengate platform. In stage II, we validated SNPs significantly associated with breast cancer prognosis in another dataset using the TaqMan platform. Survival times was calculated, and Kaplan-Meier curves and Cox regression model were used to analyze survival of breast cancer patients with different genotypes.Results: We identified 8 SNPs significantly associated with breast cancer prognosis in stage I (P<0.05), and only rs10878441 was statistically significant in stage II (AA vs CC: adjusted HR=2.21, 95% CI: 1.11-4.42, P=0.024). We combined the data from stage I and stage II, and found that, compared with rs10878441 AA genotype, CC genotype was significantly associated with poor survival of breast cancer (HR=1.69, 95% CI: 1.18-2.42, P=0.004; adjusted HR=2.19, 95% CI: 1.30-3.70, P=0.003). Stratified analyses demonstrated that rs10878441 was related to breast cancer prognosis in grade II patients and lymph node-negative patients (P<0.05).Conclusions: The LRKK2 rs10878441 CC genotype is associated with poor prognosis of breast cancer in a Chinese population, and it could be used as a potential prognostic biomarker for breast cancer. Further studies are warranted.

scholarly journals Identifies Immune-Related Gene Pair Signature Associated with Breast Cancer Prognosis

2021 ◽  
Author(s):  
Tianwei Sun ◽  
Qixing Tan ◽  
Changyuan Wei
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Gene Pair ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Future Research ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Immune Related Gene ◽  
Immune Related Genes

Abstract Background: Breast cancer (BC) is the cancer with the largest number of deaths in women. There is growing evidence that immunity plays an important role in the prognosis of breast cancer. Methods: In this study, we developed and validated an immune-related gene pair signature (IRGPs) to predict the survival of breast cancer patients. Screening immune-related genes from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database for the construction of IRGPs, and patients with breast cancer in these two cohorts were assigned to low- and high- risk subgroups. Additionally, we used Kaplan-Meier survival analysis, univariate and multivariate Cox analysis to investigate IRGPs and their individualized prognostic characteristics, and analysis of immune cell infiltration in breast cancer. Results: A 47-IRGP signature was constructed from 2498 immune genes, which could significantly predict the overall survival (OS) of breast cancer patients in the TCGA and GEO cohorts. Immune infiltration analysis showed that a variety of immune cells are significantly related to the prognostic effects of IRGP characteristics in breast cancer patients, especially CD8+ T cells and macrophages. Conclusions: The IRGP signature constructed in this study can help determine the prognosis of breast cancer and provide new ideas and basis for future research on the role of immune-related genes in breast cancer patients.

Exploratory Data Analysis on Breast Cancer Prognosis

2018 ◽  
pp. 1794-1805
Author(s):  
Mohammad Mehdi Owrang O. ◽  
Yasmine M. Kanaan ◽  
Robert L. Copeland Jr. ◽  
Melvin Gaskins ◽  
Robert L. DeWitty Jr.
Keyword(s):  
Breast Cancer ◽  
Marital Status ◽  
Cancer Patients ◽  
Proportional Hazards ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Howard University ◽  
Kaplan Meier ◽  
Seer Data

Breast cancer prognosis is a vital element of providing effective treatment for breast cancer patients. Breast cancer prediction survivability has mainly been studied based on pathological factors such as tumor size, tumor grade, number of positive lymph nodes, and hormone receptors among others. This chapter looks at the significance of the non-clinical prognostic factors of age, ethnicity, and marital status in finding the prognosis for breast cancer patients. The National Cancer Institute's SEER data and the Howard University Cancer Center Tumor Registry data are analyzed. Prognostic tool NPI (Nottingham Prognostic Index) and survival analysis tools of Cox proportional hazards and Kaplan-Meier survival curve are used in analyzing the experiments. The results suggest that age, ethnicity, and marital status have some influence on the survivability rate of breast cancer patients.

scholarly journals Selenium donors inhibits osteoclastogenesis through inhibiting IL-6 and plays a pivotal role in bone metastasis from breast cancer

2020 ◽  
Vol 9 (4) ◽  
pp. 544-551
Author(s):  
Luyan Zhang ◽  
Xifa Wu ◽  
Yong Feng ◽  
Linlin Zheng ◽  
Jinbo Jian
Keyword(s):  
Breast Cancer ◽  
Bone Metastasis ◽  
Bone Metastases ◽  
Cancer Cells ◽  
Cancer Patients ◽  
Cellular Level ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Dietary Selenium ◽  
Organic Selenium

Abstract Bone metastases are a frequent complication of breast cancer, and there has been little progress in the treatment of breast cancer patients with bone metastases. The cytotoxicity of selenium donors, including organic selenium and selenium nanoparticles (SeNPs), to cancer cells has been reported previously, but their relationship with bone metastases progression is not fully clear yet. In this study, multicenter clinical exploration was conducted to obtain dietary selenium intakes of breast cancer patients with or without bone metastasis, to study the relationship between selenium and breast cancer prognosis and bone metastasis. We found that dietary selenium intakes were significantly lower in breast cancer patients with bone metastasis, comparing with the non-bone metastasis cases. Selenium lower group of bone metastasis breast cancer patients had worse prognosis, whereas the daily selenium intakes could not predict the prognosis of breast cancer patients without bone metastasis. Subsequently, we study the regulatory role of selenium donors on bone metastasis at the cellular level, by challenging the cells with SeNPs. SeNPs showed potent cytotoxicity in breast cancer cells, no matter whether they were primary or bone-metastatic. SeNPs treated cancer cell inhibited the survival and differentiation of osteoclast progenitor cells. At the molecular level, we demonstrated that IL-6 partially mediated osteoclastogenesis suppression by SeNPs. These results provide a new way for biomarkers or drug development to treat and even prevent bone metastases of breast cancer by using selenium donors.

scholarly journals The tumor microbiome is implicated in breast cancer prognosis

2020 ◽  
Author(s):  
Jia Zhu ◽  
Jie Wu ◽  
Changgan Mo ◽  
Siyuan Liang ◽  
Tao Lian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Alpha Diversity ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Rrna Gene ◽  
Breast Cancer Patients ◽  
Immune Microenvironment ◽  
Tumor Tissues ◽  
Tumor Immune Microenvironment

Abstract Background: Some breast cancer patients are prone to recurrence and metastasis. Increasing evidence suggests that the breast tissue contains a diverse population of bacteria, which may be modulating the risk of breast cancer development or progression. However, the extent of microbial contribution to the tumor immune microenvironment in breast cancer remains unknown. Here, we explored the potential influence of the tumor microbiota on the local immune microenvironment and breast cancer prognosis.Methods: Using 16S rRNA gene sequencing, we analyzed the tumor microbiome composition and identified bacteria that were differentially abundant between breast cancer patients with recurrence or metastasis (R/M) and those without recurrence or metastasis (NRM). We performed total RNA sequencing in tumor tissues from patients in both groups to determine differentially expressed genes (DEGs). The landscape of tumor-infiltrating immune cells (TIICs) subtypes in the tumor immune microenvironment was analyzed using CIBERSORT, based on the gene expression profiling of tumor tissues. Differences in the tumor microbiomes were then correlated with DEGs and differences in TIICs, in order to determine how microbial abundance may contribute to cancer progression.Results: Microbial alpha-diversity was higher in NRM patients than in R/M patients. The composition and functions of the tumor microbiome communities differed between the two groups. We found higher alpha-diversity, higher abundance of Ruminococcus, Butyrivibrio, and Deinococcus, and lower abundance of Microbacterium could serve as a predictor of better prognosis in breast cancer patients. We also found that 16 genes, including CD36, showed differential expression in NRM compared to R/M, and differences in the composition of TIICs were observed between the two groups. In addition, we observed that the different tumor microbiome profiles were associated with DEGs and differences in TIICs between the two groups.Conclusions: The tumor microbiome may affect the prognosis of breast cancer patients by influencing the tumor immune microenvironment. Thus, the tumor microbiome may be a useful prognostic indicator.

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