Prognostic Impact of Immunoglobulin Kappa C (IGKC) in Early Breast Cancer.
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ABSTRACT:
SUBMITTER: Schmidt M
PROVIDER: S-EPMC8304855 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The extent and composition of the immune response in a breast cancer is one important prognostic factor for the disease. The aim of the current work was to refine the analysis of the humoral component of an immune response in breast tumors by quantifying mRNA expression of different immunoglobulin classes and study their association with prognosis. We used RNA-Seq data from two local population-based breast cancer cohorts to determine the expression of IGJ and immunoglobulin heavy (IGH) chain-encoding RNAs. The association with prognosis was investigated and public data sets were used to corroborate the findings. Except for IGHE and IGHD, mRNAs encoding heavy chains were generally detected at substantial levels and correlated with other immune-related genes. High IGHG1 mRNA was associated with factors related to poor prognosis such as estrogen receptor negativity, HER2 amplification, and high grade, whereas high IGHA2 mRNA levels were primarily associated with lower age at diagnosis. High IGHA2 and IGJ mRNA levels were associated with a more favorable prognosis both in univariable and multivariable Cox models. When adjusting for other prognostic factors, high IGHG1 mRNA levels were positively associated with improved prognosis. To our knowledge, these results are the first to demonstrate that expression of individual Ig class types has prognostic implications in breast cancer.
| S-EPMC7338507 | biostudies-literature
Project description:Breast cancer progression is associated with dysregulated expression of the immunoglobulin superfamily (IgSF) genes that are involved in cell-cell recognition, binding and adhesion. Despite widespread evidence that many IgSF genes could serve as effective biomarkers, this potential has not been realized because the studies have focused mostly on individual genes and not the entire network. To gain a global perspective of the IgSF-related biomarkers, we constructed an IgSF-directed neighbor network (IDNN) and an IgSF-directed driver network (IDDN) by integrating multiple levels of data, including IgSF genes, breast cancer driver genes, protein-protein interaction (PPI) networks and gene expression profiling data. Our study shows that IgSF genes in the PPI network have important topological features related to cancer. Most IgSF genes are either cancer driver genes themselves or associated with them. We also identified a 21-gene IgSF network module with enriched mutations that are associated with overall survival based on 450 breast cancer patient samples extracted from The Cancer Genome Atlas (TCGA) and multiple independent microarray validation datasets. These results highlight the potential of IgSF genes as novel diagnostic, prognostic and therapeutic targets for breast cancer.
| S-EPMC5356814 | biostudies-literature
Project description:BackgroundRecent data suggest that human epidermal growth factor receptor 2 (HER2)-low breast cancer may represent a distinct entity. We aimed to compare disease characteristics and outcomes between HER2-low and HER2-0 in estrogen receptor (ER) positive, early-stage breast cancer.MethodsA single center retrospective study comprising all women with ER positive, HER2 negative early breast cancer, for whom an Oncotype DX test was performed between 2005 and 2012. Women were grouped to HER2-low (immunohistochemistry +1 or +2 and in situ hybridization not amplified) or HER2-0. Clinico-pathological features and Oncotype recurrence score (RS) were collected. Data on overall-survival (OS), disease-free survival (DFS) and distant disease-free survival (DDFS) were evaluated according to HER2 expression status.Results608 women were included, of which 304 women had HER2-0 and 304 had HER2-low disease. Lobular subtype was significantly more common in HER-0 compared to HER2-low disease (17% vs. 8%, p = 0.005). The prevalence of other clinic-pathological characteristics and long-term prognosis were comparable between both groups. For women with high genomic risk (RS > 25), HER2-low expression was associated with significantly favorable OS (HR = 0.31, 95% CI 0.11-0.78, p = 0.01), DFS (HR = 0.40, 95% CI 0.20-0.82, p = 0.01) and DDFS (HR = 0.26, 95% CI 0.11-0.63, P = 0.002) compared to women with HER2-0. For women with low genomic risk (RS ≤ 25), long-term prognosis was unrelated to HER2 expression.ConclusionThe prognostic impact of HER2-low expression in early-stage luminal disease varies across the genomic risk, with significant favorable outcomes of HER2-low expression compared to HER2-0 in women with high genomic risk.
| S-EPMC8414540 | biostudies-literature
Project description:Blood-based early detection of breast cancer has recently gained novel momentum, as liquid biopsy diagnostics is a fast emerging field. In this study, we aimed to identify secreted proteins which are up-regulated both in tumour tissue and serum samples of breast cancer patients compared to normal tissue and sera. Based on two independent tissue cohorts (n = 75 and n = 229) and one serum cohort (n = 80) of human breast cancer and healthy serum samples, we characterised AGR3 as a novel potential biomarker both for breast cancer prognosis and early breast cancer detection from blood. AGR3 expression in breast tumours is significantly associated with oestrogen receptor ? (P<0.001) and lower tumour grade (P<0.01). Interestingly, AGR3 protein expression correlates with unfavourable outcome in low (G1) and intermediate (G2) grade breast tumours (multivariate hazard ratio: 2.186, 95% CI: 1.008-4.740, P<0.05) indicating an independent prognostic impact. In sera analysed by ELISA technique, AGR3 protein concentration was significantly (P<0.001) elevated in samples from breast cancer patients (n = 40, mainly low stage tumours) compared to healthy controls (n = 40). To develop a suitable biomarker panel for early breast cancer detection, we measured AGR2 protein in human serum samples in parallel. The combined AGR3/AGR2 biomarker panel achieved a sensitivity of 64.5% and a specificity of 89.5% as shown by receiver operating characteristic (ROC) curve statistics. Thus our data clearly show the potential usability of AGR3 and AGR2 as biomarkers for blood-based early detection of human breast cancer.
| S-EPMC4398490 | biostudies-literature
Project description:BackgroundOverexpression of human epidermal growth factor receptor 2 (HER2) caused by HER2 gene amplification is a driver in breast cancer tumorigenesis. We aimed to investigate the prognostic significance of manual scoring and digital image analysis (DIA) algorithm assessment of HER2 copy numbers and HER2/CEP17 ratios, along with ERBB2 mRNA levels among early-stage HER2-positive breast cancer patients treated with trastuzumab.MethodsThis retrospective study comprised 371 early HER2-positive breast cancer patients treated with adjuvant trastuzumab, with HER2 re-testing performed on whole tumor sections. Digitized tumor tissue slides were manually scored and assessed with uPath HER2 Dual ISH image analysis, breast algorithm. Targeted ERBB2 mRNA levels were assessed by the Xpert® Breast Cancer STRAT4 Assay. HER2 copy number and HER2/CEP17 ratio from in situ hybridization assessment, along with ERBB2 mRNA levels, were explored in relation to recurrence-free survival (RFS).ResultsThe analysis showed that patients with tumors with the highest and lowest manually counted HER2 copy number levels had worse RFS than those with intermediate levels (HR = 2.7, CI 1.4-5.3, p = 0.003 and HR = 2.1, CI 1.1-3.9, p = 0.03, respectively). A similar trend was observed for HER2/CEP17 ratio, and the DIA algorithm confirmed the results. Moreover, patients with tumors with the highest and the lowest values of ERBB2 mRNA had a significantly worse prognosis (HR = 2.7, CI 1.4-5.1, p = 0.003 and HR = 2.8, CI 1.4-5.5, p = 0.004, respectively) compared to those with intermediate levels.ConclusionsOur findings suggest that the association between any of the three HER2 biomarkers and RFS was nonlinear. Patients with tumors with the highest levels of HER2 gene amplification or ERBB2 mRNA were associated with a worse prognosis than those with intermediate levels, which is of importance to investigate in future clinical trials studying HER2-targeted therapy.
| S-EPMC10848443 | biostudies-literature
Project description:Background:Immunoglobulin superfamily member 10 (IGSF10) is a member of the immunoglobulin superfamily that is expressed at high levels in both the gallbladder and ovary. Currently, the role and possible mechanism of IGSF10 in breast cancer remain unclear. Method:By applying real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC), the expression of IGSF10 in breast cancer cells and tissues was detected. We collected the clinical information from 700 patients with breast cancer in The Cancer Genome Atlas (TCGA), and analyzed the relationship between IGSF10 expression and the clinicopathological features and survival outcomes of these patients. The potential mechanisms and pathways associated with IGSF10 in breast cancer were explored by performing a gene set enrichment analysis (GSEA). Results:According to TCGA data, qRT-PCR and IHC experiments, levels of the IGSF10 mRNA and protein were significantly decreased in breast cancer tissues. IGSF10 expression was significantly correlated with age, tumor size, and tumor stage. Moreover, shorter overall survival (OS) and relapse-free survival (RFS) correlated with lower IGSF10 expression, according to the survival analysis. The multivariate analysis identified that IGSF10 as an independent prognostic factor for the OS (hazard ratio (HR) = 1.793, 95% confidence interval (CI) [1.141-2.815], P = 0.011) and RFS (HR = 2.298, 95% CI [1.317-4.010], P = 0.003) of patients with breast cancer. Based on the GSEA, IGSF10 was involved in DNA repair, cell cycle, and glycolysis. IGSF10 was also associated with the PI3K/Akt/mTOR and mTORC1 signaling pathways. Conclusions:This study revealed a clear relationship between IGSF10 expression and the tumorigenesis of breast cancer for the first time. Therefore, further studies are needed to understand the mechanism of IGSF10 in breast cancer.
| S-EPMC7585383 | biostudies-literature
Project description:Epidermal growth factor receptor (EGFR) and its ligands are involved in cancer pathogenesis. The emerging role of treatments co-targeting the EGFR system in breast cancer has increased the need to identify companion biomarkers. The aim of this study is to investigate whether pretreatment serum levels of EGFR and EGFR ligands in early-stage breast cancer patients might provide prognostic information as a stepping stone for further investigation. The study, which included 311 early-stage breast cancer patients, investigated associations between preoperative serum levels of EGFR and EGFR ligands (epidermal growth factor, heparin-binding epidermal growth factor (HBEGF), amphiregulin, transforming growth factor-α and betacellulin) and survival. Cutoffs were determined using Youden's method, and overall survival (OS) and invasive disease-free survival (IDFS) were evaluated using Cox regression. Preoperative S-EGFR < 60.3 ng/mL was associated with shorter OS and IDFS in both univariate analyses and when adjusting for standard prognostic factors (p < 0.05). Preoperative S-HBEGF < 21.4 pg/mL was associated with shorter OS in both univariate and multivariate analyses, whereas association with shorter IDFS could only be demonstrated in the univariate analysis. In conclusion, our study demonstrated shorter survival in early-stage breast cancer patients who had low pretreatment levels of either S-EGFR or S-HBEGF.
| S-EPMC7538553 | biostudies-literature
Project description:Although the prognosis for operable breast cancers is reportedly worse if serum carcinoembryonic antigen (CEA) and cancer antigen 15-3 (CA15-3) levels are above normal, the usefulness of this prognosis is limited due to the low sensitivity and specificity; in addition, the optimal cutoff levels remain unknown.A total of 1076 patients who were operated for breast cancers (test set = 608, validation set = 468) without evidence of metastasis were recruited, and their baseline and postoperative serum CEA and CA15-3 levels were analyzed. The optimal cutoff values of CEA and CA15-3 for disease-free survival (DFS) were 3.2 ng/mL and 13.3 U/mL, respectively, based on receiver operating characteristic curve and area under the curve analyses.The DFS of patients with high CEA levels (CEA-high: n?=?191, 5-year DFS 70.6%) was significantly worse (p?<?0.0001) than that of CEA-low patients (n?=?885, 5-year DFS 87.2%). There was a significant difference in DFS (p?<?0.0001) between CA15-3-high and CA15-3-low patients (n?=?314 and n?=?762, respectively; 5-year DFS 71.8 vs. 89.3%). Significant associations between DFS and CA15-3 levels were observed irrespective of the subtypes. Multivariable analysis indicated that tumor size, lymph node metastasis, tumor grade, and CEA (p?=?0.0474) and CA15-3 (p <?0.0001) levels were independent prognostic factors (hazard ratio [HR] 1.520, 95% confidence interval [CI] 1.005-2.245 for CEA; HR 2.088, 95% CI 1.457-2.901 for CA15-3).These findings suggest that CEA and CA15-3 levels might be useful for predicting the prognosis of patients with operable early breast cancer irrespective of the subtype. Serum levels at baseline may reflect tumor characteristics for metastatic potential even when these levels are within the normal ranges.
| S-EPMC5809836 | biostudies-other
Project description:BACKGROUND:Gene expression profiles from early-onset breast cancer and normal tissues were analyzed to explore the genes and prognostic factors associated with breast cancer. METHODS:GSE109169 and GSE89116 were obtained from the database of Gene Expression Omnibus. We firstly screened the differentially expressed genes between tumor samples and normal samples from patients with early-onset breast cancer. Based on database for annotation, visualization and intergrated discovery (DAVID) tool, functional analysis was calculated. Transcription factor-target regulation and microRNA-target gene network were constructed using the tool of transcriptional regulatory relatitionships unraveled by sentence-based text mining (TRRUST) and miRWalk2.0, respectively. The prognosis-related survival information was compiled based on The Cancer Genome Atlas breast cancer clinical data. RESULTS:A total of 708 differentially expressed genes from GSE109169 data sets and 358 differentially expressed genes from GSE89116 data sets were obtained, of which 122 common differentially expressed genes including 102 uniformly downregulated genes and 20 uniformly upregulated genes were screened. Protein-protein interaction network with a total of 83 nodes and 157 relationship pairs was obtained, and genes in protein-protein interaction, such as peroxisome proliferator-activated receptor γ, FGF2, adiponectin, and PCK1, were recognized as key nodes in protein-protein interaction. In total, 66 transcription factor-target relationship pairs were obtained, and peroxisome proliferator-activated receptor γ was the only one downregulated transcription factor. MicroRNA-target gene network contained 368 microRNA-target relationship pairs. Moreover, 16 differentially expressed genes, including 2 upregulations and 14 downregulations, were related to a significant correlation with the prognosis, including SQLE and peroxisome proliferator-activated receptor γ. CONCLUSIONS:SQLE and peroxisome proliferator-activated receptor γ might be important prognostic factors in breast cancers, and adiponectin might be important in breast cancer pathogenesis regulated by peroxisome proliferator-activated receptor γ.
| S-EPMC7011326 | biostudies-literature
Project description:PurposeIn addition to impacting incidence, risk factors for breast cancer may also influence recurrence and survival from the disease. However, it is unclear how these factors affect combinatorial biomarkers for aiding treatment decision-making in breast cancer.MethodsPatients were 8179 women with histologically confirmed invasive breast cancer, diagnosed and treated in a large cancer hospital in Beijing, China. Individual clinicopathological (tumor size, grade, lymph nodes) and immunohistochemical (IHC: ER, PR, HER2, KI67) markers were used to define clinically relevant combinatorial prognostic biomarkers, including the Nottingham Prognostic Index (NPI: combining size, grade, nodes) and IHC4 score (combining ER, PR, HER2, KI67). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between breast cancer risk factors and quartiles (Q1-Q4) of NPI and IHC4 were assessed in multivariable polytomous logistic regression models.ResultsOverall, increasing parity (ORtrend(95% CI) = 1.20(1.05-1.37);Ptrend = 0.007), overweight (OR(95% CI)vs normal = 1.60(1.29-1.98)), and obesity (OR(95% CI) vs normal = 2.12(1.43-3.14)) were associated with higher likelihood of developing tumors with high (Q4) versus low (Q1) NPI score. Conversely, increasing age (ORtrend(95% CI) = 0.75(0.66-0.84);Ptrend < 0.001) and positive family history of breast cancer (FHBC) (OR(95% CI) = 0.66(0.45-0.95)) were inversely associated with NPI. Only body mass index (BMI) was associated with IHC4, with overweight (OR(95% CI) vs normal = 0.82(0.66-1.02)) and obese (OR(95% CI) vs normal = 0.52(0.36-0.76)) women less likely to develop high IHC4 tumors. Notably, elevated BMI was associated with higher NPI irrespective of hormone receptor-expression status.ConclusionsOur findings indicate that factors affecting breast cancer incidence, particularly age, parity, FHBC, and BMI, may impact clinically relevant prognostic biomarkers with implications for surveillance, prognostication, and counseling.
| S-EPMC8357643 | biostudies-literature