scholarly journals Study on PI3k gene expression in breast cancer samples and its association with clinical factors and patient survival

2022 ◽  
Vol 67 (4) ◽  
pp. 321-327
Author(s):  
Jiang Lin ◽  
Qi Ding ◽  
Guoying Zhang ◽  
Xiling Yin
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Rna Extraction ◽  
Tumor Grade ◽  
P Value ◽  
Clinical Factors ◽  
Phosphatidylinositol 3 Kinase ◽  
Tumor Tissues ◽  
Pcr Method ◽  
Control Study

Breast cancer is the most common cancer among women in the world. The phosphatidylinositol 3-Kinase (PI3k), which regulates various cellular signaling pathways, is often elevated in human cancers. This study aimed to evaluate the expression of the PI3k gene in breast cancer. In this case-control study, 40 paraffin-embedded tissues of breast cancer and 40 adjacent non-tumor tissues were examined. After total RNA extraction and cDNA synthesis, the relative expression of the gene was obtained using the real-time-PCR method and evaluated by the 2-ΔΔCT method. Also, the association of gene expression with clinical factors and survival rate was investigated. Data analysis was performed by SPSS statistical software (version 22), t-test, and ANOVA. A p-value of less than 0.05 was considered significant. The results showed that PI3k expression was significantly increased in breast tumor tissues compared to non-tumor tissues (p = 0001). Consistent with these results, PI3k expression was associated with metastasis (p = 0.008) and high tumor grade (p = 0.01). In addition, increasing PI3k expression decreased overall survival compared to its low expression (p = 0.03). In general, PI3k plays a tumor-enhancing role in the progression of breast cancer. In addition, increased PI3k expression is associated with metastasis and poor prognosis of cancer, so that PI3k may be useful in the diagnosis, treatment, and prognosis of people with the disease. However, further investigation is needed to substantiate this claim.

scholarly journals The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Michal Marczyk ◽  
Chunxiao Fu ◽  
Rosanna Lau ◽  
Lili Du ◽  
Alexander J. Trevarton ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Rna Sequencing ◽  
Rna Extraction ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
The Impact ◽  
Formalin Fixed

Abstract Background Utilization of RNA sequencing methods to measure gene expression from archival formalin-fixed paraffin-embedded (FFPE) tumor samples in translational research and clinical trials requires reliable interpretation of the impact of pre-analytical variables on the data obtained, particularly the methods used to preserve samples and to purify RNA. Methods Matched tissue samples from 12 breast cancers were fresh frozen (FF) and preserved in RNAlater or fixed in formalin and processed as FFPE tissue. Total RNA was extracted and purified from FF samples using the Qiagen RNeasy kit, and in duplicate from FFPE tissue sections using three different kits (Norgen, Qiagen and Roche). All RNA samples underwent whole transcriptome RNA sequencing (wtRNAseq) and targeted RNA sequencing for 31 transcripts included in a signature of sensitivity to endocrine therapy. We assessed the effect of RNA extraction kit on the reliability of gene expression levels using linear mixed-effects model analysis, concordance correlation coefficient (CCC) and differential analysis. All protein-coding genes in the wtRNAseq and three gene expression signatures for breast cancer were assessed for concordance. Results Despite variable quality of the RNA extracted from FFPE samples by different kits, all had similar concordance of overall gene expression from wtRNAseq between matched FF and FFPE samples (median CCC 0.63–0.66) and between technical replicates (median expression difference 0.13–0.22). More than half of genes were differentially expressed between FF and FFPE, but with low fold change (median |LFC| 0.31–0.34). Two out of three breast cancer signatures studied were highly robust in all samples using any kit, whereas the third signature was similarly discordant irrespective of the kit used. The targeted RNAseq assay was concordant between FFPE and FF samples using any of the kits (CCC 0.91–0.96). Conclusions The selection of kit to purify RNA from FFPE did not influence the overall quality of results from wtRNAseq, thus variable reproducibility of gene signatures probably relates to the reliability of individual gene selected and possibly to the algorithm. Targeted RNAseq showed promising performance for clinical deployment of quantitative assays in breast cancer from FFPE samples, although numerical scores were not identical to those from wtRNAseq and would require calibration.

scholarly journals The Expression of miR-513c and miR-3163 was Downregulated in Tumor Tissues Compared with Margin Tissues of Patients With Breast Cancer

2020 ◽  
Author(s):  
Soheila Delgir ◽  
Khandan Ilkhani ◽  
Asma Safi ◽  
Farhad Seif ◽  
Milad Bastami ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
In Silico ◽  
In Silico Analysis ◽  
Glutamine Metabolism ◽  
Expression Level ◽  
P Value ◽  
Biological Processes ◽  
Tumor Tissues ◽  
Silico Analysis

Abstract Background Breast cancer (BC) is the most common invasive cancer with different subtypes that its metabolism is unique compared with normal cells. Glutamine is considered a critical nutrition for tumor cell growth and therefore, targeting glutamine metabolism, especially Glutaminase, which catalyzed the conversion of glutamine to glutamate can be beneficial to design anti-cancer agents. Recently, evidence has shown that miRNAs with short length and single strand properties play a significant role in regulating the genes related to glutamine metabolism and may control the development of cancer.Methods Since, in-silico analysis confirmed that miR-513c and miR-3163 might be involved in glutamine metabolism, the expression level of these two miRNAs was evaluated in eighty BC tissues and margin tissues. The data were analyzed to evaluate the correlation between expression level of these miRNAs and patient’s characteristics such as abortion history, family history, and age. Furthermore, in-silico analysis was applied to predict the potential biological processes and molecular pathways of miR-513c and miR-3163 based on its gene targets.Results In-silico studies revealed the top categories of biological processes and pathways that play a critical role in cancer development were target genes for miR-513c and miR-3163. The current study showed that miR-513c (P-value = 0.02062 and fold change= -2.3801) and miR-3163 (P-value = 0.02034 and fold change= -2.3792) were downregulated in tumor tissues compared to margin tissues. Furthermore, the subgroup studies did not show any substantial relationship between expression levels of these two miRNAs and factors such as age, family history cancer, and abortion.Conclusion Based on our data, miR-513c and miR-3163 may be offered as a potential diagnosis and therapeutic targets for patients with BC.

scholarly journals Expression of Intratumoral IGF-II Is Regulated by the Gene Imprinting Status in Triple Negative Breast Cancer from Vietnamese Patients

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Vinodh Kumar Radhakrishnan ◽  
Lorraine Christine Hernandez ◽  
Kendra Anderson ◽  
Qianwei Tan ◽  
Marino De León ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
African American Women ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Gene Imprinting ◽  
Vietnamese Women ◽  
Tumor Tissues ◽  
Incidence And Mortality ◽  
Caucasian Women

African American women suffer higher incidence and mortality of triple negative breast cancer (TNBC) than Caucasian women. TNBC is very aggressive, causing the worst clinical outcome. We previously demonstrated that tumors from these patients express high IGF-II and exhibit high activation of the IGF signaling pathways. IGF-II gene expression is imprinted (monoallelic), promotes tumor progression, and metastasis and regulates Survivin, a TNBC prognostic marker. Since BC mortality has increased among young Vietnamese women, we analyzed 48 (paired) TNBC samples from Vietnamese patients to assess IGF-II expression. We analyzed all samples by qrtPCR for identification of IGF-II heterozygosity and to determine allelic expression of the IGF-II gene. We also analyzed the tissues for proIGF-II and Survivin by RT-PCR and Western blotting. A total of 28 samples displayed IGF-II heterozygosity of which 78% were biallelic. Tumors with biallelic IGF-II gene expression exhibited the highest levels of proIGF-II and Survivin. Although 100% of these tissues corresponding normal samples were biallelic, they expressed significantly lower levels of or no proIGF-II and Survivin. Thus, IGF-II biallelic gene expression is differentially regulated in normal versus tumor tissues. We propose that intratumoral proIGF-II is dependent on the IGF-II gene imprinting status and it will promote a more aggressive TNBC.

scholarly journals A signature predictive of early versus late recurrence after radiation (RT) for breast cancer that may inform the biology of early, aggressive recurrences.

2019 ◽  
Vol 5 (suppl) ◽  
pp. 112-112
Author(s):  
Corey Wayne Speers ◽  
S. Laura Chang ◽  
Benjamin Chandler ◽  
Andrea Pesch ◽  
Anna Michmerhuizen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cox Regression ◽  
External Validation ◽  
Rank Correlation ◽  
Local Therapy ◽  
Feature Reduction ◽  
Recurrence Time ◽  
P Value ◽  
Treatment Intensification

112 Background: Unmet clinical needs in breast cancer (BC) management include the identification of patients at high risk to fail locally despite standard local therapy and an understanding of the biology of these recurrences. We previously reported a radiation response signature and here extend those studies to identify a signature predictive of timing of recurrence after RT. Methods: 2 independent patient cohorts were used for training (119 pts) and validation (112 pts). All patients received RT after BCS and systemic therapy as appropriate. Spearman’s rank correlation to correlate gene expression to recurrence time was used for feature selection. Significant genes were used to train a linear model which was locked before validation. Cox regression was used for both UVA and MVA. Results: Spearman’s correlation identified 485 genes whose expression was significantly associated with recurrence time (+/-3 yrs). Feature reduction refined the list to 41 genes retained within the signature. In training, the correlation of score to recurrence time was 0.85, p-value < 1.3x10-31; AUC of 0.91. External validation in an independent BC validation set accurately identified patients with early vs. late recurrences (correlation= 0.75, p-value = 0.001, AUC = 0.92, sens.=0.75, spec.= 1.0, PPV = 1.0, NPV = 0.8). Unique associations of breast cancer intrinsic subtype to timing of local recurrence were found. In UVA and MVA the signature remained the most significant factor associated with recurrence. GSEA analysis of the 41 genes retained within the signature identified proliferation and EGFR concepts associated with early recurrences and luminal and ER-signaling pathways associated with late recurrences. Knockdown of genes associated with the early and late recurrences demonstrated novel effects on proliferation and clonogenic survival, respectively. Conclusions: We report a BC gene expression signatures that may be useful in identifying patients unlikely to respond to adjuvant RT and may be used to predict timing of recurrences, with implications for potential treatment intensification and duration of follow-up for women with breast cancer treated with RT.

scholarly journals Association Analysis of Deep Genomic Features Extracted by Denoising Autoencoders in Breast Cancer

Cancers ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 494 ◽  
Author(s):  
Qian Liu ◽  
Pingzhao Hu
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Characteristics ◽  
Genomic Data ◽  
Risk Scores ◽  
P Value ◽  
Positive Regulation ◽  
Genomic Features ◽  
Survival Differences ◽  
Breast Cancer Gene

Artificial intelligence-based unsupervised deep learning (DL) is widely used to mine multimodal big data. However, there are few applications of this technology to cancer genomics. We aim to develop DL models to extract deep features from the breast cancer gene expression data and copy number alteration (CNA) data separately and jointly. We hypothesize that the deep features are associated with patients’ clinical characteristics and outcomes. Two unsupervised denoising autoencoders (DAs) were developed to extract deep features from TCGA (The Cancer Genome Atlas) breast cancer gene expression and CNA data separately and jointly. A heat map was used to view and cluster patients into subgroups based on these DL features. Fisher’s exact test and Pearson’ Chi-square test were applied to test the associations of patients’ groups and clinical information. Survival differences between the groups were evaluated by Kaplan–Meier (KM) curves. Associations between each of the features and patient’s overall survival were assessed using Cox’s proportional hazards (COX-PH) model and a risk score for each feature set from the different omics data sets was generated from the survival regression coefficients. The risk scores for each feature set were binarized into high- and low-risk patient groups to evaluate survival differences using KM curves. Furthermore, the risk scores were traced back to their gene level DAs weights so that the three gene lists for each of the genomic data points were generated to perform gene set enrichment analysis. Patients were clustered into two groups based on concatenated features from the gene expression and CNA data and these two groups showed different overall survival rates (p-value = 0.049) and different ER (Estrogen receptor) statuses (p-value = 0.002, OR (odds ratio) = 0.626). All the risk scores from the gene expression and CNA data and their concatenated one were significantly associated with breast cancer survival. The patients with the high-risk group were significantly associated with patients’ worse outcomes (p-values ≤ 0.0023). The concatenated risk score was enriched by the AMP-activated protein kinase (AMPK) signaling pathway, the regulation of DNA-templated transcription, the regulation of nucleic acid-templated transcription, the regulation of apoptotic process, the positive regulation of gene expression, the positive regulation of cell proliferation, heart morphogenesis, the regulation of cellular macromolecule biosynthetic process, with FDR (false discovery rate) less than 0.05. We confirmed DAs can effectively extract meaningful genomic features from genomic data and concatenating multiple data sources can improve the significance of the features associated with breast cancer patients’ clinical characteristics and outcomes.

scholarly journals Study of KMT2B (MLL2) gene expression changes in patients with breast cancer

2019 ◽  
Vol 8 (2) ◽  
pp. BMT24
Author(s):  
Mohammad Ghanbari ◽  
Mohammadali Hosseinpour-Feizi ◽  
Reza Safaralizadeh ◽  
Aida Aghazadeh ◽  
Vahid Montazeri
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Tumor Tissue ◽  
Rna Extraction ◽  
Cancer Tissue ◽  
Cdna Synthesis ◽  
Tissue Samples ◽  
Spss Software ◽  
Analyze Data ◽  
Mll2 Gene

Aim: This study aimed to demonstrate misregulation of KMT2B gene expression in breast cancer tissue. Materials & methods: Cancerous and marginal tissue samples were collected from 43 female patients. After RNA extraction and cDNA synthesis, quantitative-PCR was used to evaluate the expression level of the KMT2B gene. REST, Sigma plot and SPSS software were used to analyze data. Results: KMT2B gene expression was significantly decreased in tumor tissue compared with marginal tissue (p = 0.02). No significant correlation was found between expression levels of KMT2B and clinical parameters of patients (p > 0.05) Conclusion: Our study demonstrated that downregulation of KMT2B is associated with breast cancer and its misregulation may play an important role in tumorigenesis.

scholarly journals Clinical Evaluation of the Diagnostic Role of MicroRNA-155 in Breast Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Fatemeh Hosseini Mojahed ◽  
Amir Hossein Aalami ◽  
Vahid Pouresmaeil ◽  
Amir Amirabadi ◽  
Mahdi Qasemi Rad ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Rna Extraction ◽  
Tumor Grade ◽  
Breast Cancer Diagnosis ◽  
Tumor Stage ◽  
Lymph Node Involvement ◽  
Youden Index ◽  
Control Group ◽  
Roc Curve Analysis ◽  
Ki 67

Aim. Biochemical markers, including microRNAs (miRs), may facilitate the diagnosis and prognosis of breast cancer. This study was aimed at assessing serum miR-155 expression in patients with breast cancer and receptors. Methods. This case-control study was conducted on 36 patients with breast cancer and 36 healthy individuals. After RNA extraction from the patient’s serum, cDNA was synthesized. The expression of miR-155 was measured using RT-qPCR. Demographic and histochemical data were extracted from patient documents. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) software. Results. The mean age of subjects in breast cancer and control groups was 47.64±8.19 and 47.36±7.52 years, respectively. The serum miR-155 expression was higher in the cancer group (1.68±0.66) compared to the control group (p<0.0001). There was a significant relationship between serum miR-155 expression and the tumor grade (p<0.001), tumor stage (p<0.001), and tumor size (p<0.001) of the patients. However, no relationship between miR-155 expression and the presence of lymph node involvement (p=0.15), HER2 (p=0.79), Ki-67 (p=0.9), progesterone receptor (p=0.54), and estrogen receptors (p=0.84) was found. The ROC curve analysis showed that the AUC was 0.89 (77.78% sensitivity and 88.89% specificity), and the cutoff was 1.4 (Youden index: 0.6667) for detecting breast cancer. Conclusion. The findings of this study revealed that serum miR-155 may serve as a potential noninvasive molecular biomarker for breast cancer diagnosis and can help predict the grade of the disease.

The influence of efaproxiral on breast cancer xenograft hypoxia and HIF-1-alpha expression

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 10102-10102
Author(s):  
B. D. Kavanagh ◽  
R. P. Steffen ◽  
B. Frederick ◽  
B. Solomon ◽  
D. Chan
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Rna Extraction ◽  
Tumor Oxygenation ◽  
Human Breast ◽  
Clinical Safety ◽  
Early Effect ◽  
Breast Cancer Xenograft ◽  
Oxygen Breathing

10102 Background: Efaproxiral (E), a synthetic allosteric modifier of hemoglobin, has demonstrated clinical safety and efficacy as a radiosensitizer in patients with brain metastases from breast cancer. Although shown to enhance oxygenation in a murine mammary tumor, efaproxiral has not previously been tested in a human breast cancer xenograft. We studied changes in tumor oxygenation in a human xenograft and evaluated whether efaproxiral induces cell signaling events of potential therapeutic value. Methods: MDA-MB-468 breast cancer cells in matrigel were injected into the flank of nude mice. After tumors grew to 1–1.5 cm, animals were subjected to 1 of 3 treatments: ip saline +room air breathing (RA), ip saline + 50% oxygen breathing (O2), or ip efaproxiral (300 mg/kg) + 50% oxygen breathing (E+O2). Twenty minutes later the hypoxia marker, pimonidazole (pimo), was given, and 70 minutes later tumors were harvested for immunohistochemical study of hypoxia and hypoxia-inducible factor 1-alpha (HIF1-α) and RNA extraction to identify early changes in gene expression. Image analysis software was used to quantify observations. Results: Tumor hypoxia and HIF1-α staining were significantly decreased by efaproxiral (Table). HIF1-α staining did not entirely colocalize with pimo, implying different oxygen tension levels for HIF1-α ubiquitination and pimo reduction. Gene arrays indicated that after E+O2, expression of the hypoxia-induced DR1 transcription repressor was reduced compared with O2. Conclusions: The combination of E+O2 reduced hypoxia and HIF1-α expression in MDA-MB-468 human breast tumors in vivo, and an early effect on gene expression was reduced DR1. The results demonstrate an efaproxiral-mediated enhanced oxygenation of human hypoxic breast cancer. Furthermore, the efaproxiral-mediated down-regulation of HIF1-α suggests possible new opportunities in the clinical application of efaproxiral, notably as an adjuvant to systemic agents for which HIF1-α-mediated resistance limits efficacy. [Table: see text] [Table: see text]

High level analysis of genomic data reveals complex predictors of response to trastuzumab (T) and chemotherapy for early stage breast cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 544-544
Author(s):  
L. N. Harris ◽  
S. Carter ◽  
F. You ◽  
A. Eklund ◽  
S. Hilsenbeck ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Expression Patterns ◽  
Rna Extraction ◽  
Pathologic Complete Response ◽  
Gene Expression Signature ◽  
Response To Therapy ◽  
Snp Analysis ◽  
Predictors Of Response ◽  
High Level

544 Background: Trastuzumab (T) with chemotherapy has been shown to improve survival in breast cancer patients but de novo resistance is common. Identifying predictors of response to T in primary cancers may lead to an understanding of mechanisms of resistance. We investigated whether combined microarray datasets from patients with early breast cancer treated with preoperative T and chemotherapy could predict for response to therapy. Methods: Two cohorts of patients with HER2 3+/FISH+, stage II-III breast cancer were included in this analysis: trial 1- T and docetaxel (n=38), trial 2 -T and vinorelbine (n=48), both for 12 weeks. Frozen tissue core biopsies were available and successfully amplified in 41 patients (trial 1: 20, trial 2: 21 patients), with standard sample processing, RNA extraction, amplification and hybridization to Affymetrix U133 chips. Differential expression of genes and chromosomal regions, (defined as >10 genes in a given chromosomal cytoband), between patients with pathologic complete response (pCR) vs. those with residual invasive disease were examined. A measure of total functional aneuploidy (tFA) was calculated by summing net deviation in expression of all chromosomal regions and a gene expression signature of genomic instability (CIN) was derived by the identification of genes showing a high level of correlation with tFA . Results: By unsupervised hierarchical analysis, both datasets interdigitated suggesting no inherent bias. Gene expression patterns of individual genes showed weak associations with pCR. However, distinct statistically significant chromosomal regions, Chr2p23 Chr6q24 Chr7q33 Chr2p2 Chr12q21.31 Chr14q32.2 Chr1p34.2 Chr8q21.3, were associated with pCR to T therapy (p<0.005), and were confirmed in more than 50% samples by SNP analysis. In addition, resistant tumors showed higher levels of the CIN signature (p<0.005). Conclusions: We have shown that gene expression data can be merged and used for discovery predictive chromosomal regions associated T response. In addition, chromosomal instability was associated with T resistance. If validated, these distinct dysregulated chromosomal regions may serve as predictive markers of response to trastuzumab therapy. [Table: see text]

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