Luminal (Her2 negative) prognostic index and survival of breast cancer patients

PurposeThe group of luminal (Her2 negative) is distinguished from other subtypes of breast cancer. We aimed to produce a prognostic index specific for luminal (Her2 negative) subtype breast cancer that could assist clinical treatment.MethodsThe test set comprised 406 consecutive luminal (Her2 negative) breast cancer patients. The relationship of 11 clinicopathologic factors including survivin with the 5-year disease-free survival was analyzed.ResultsIn univariate analysis, TNM stage, surgery, tumor size, lymph node involvement, and survivin expression were prognostic factors. In multivariate analysis, tumor size [HR (95% CI): 1.98 (1.12–3.49), p = 0.019], the number of lymph node metastasis [HR (95% CI): 1.75 (1.33–2.29), p < 0.0001] and the expression of progesterone receptor [HR (95% CI): 0.58 (0.36–0.95), p = 0.029] can independently predict prognosis. Prognostic index (PI) was calculated as 0.68 × tumor size + 0.56 × the number of lymph node metastasis − 0.54 × PR. According to the PI, patients were categorized into three groups: low, middle, and high risk group with the 5-year disease-free survival rates of 91.91%, 84.97% and 70.47%, respectively (P < 0.001). In the validation set, the luminal prognostic index (LPI) remained significant.ConclusionThe LPI may be a useful tool for evaluating the outcome of patients with luminal (Her-2 negative) breast cancer.     

Grade-specific diagnostic and prognostic biomarkers in breast cancer

An integrative approach is presented to identify grade-specific biomarkers for breast cancer. Grade-specific molecular interaction networks were constructed with differentially expressed genes (DEGs) of cancer grade 1, 2, and 3. We observed that the molecular network of grade3 is predominantly associated with cancer-specific processes. Among the top ten connected DEGs in the grade3, the increase in the expression of UBE2C and CCNB2 genes was statistically significant across different grades. Along with UBE2C and CCNB2 genes, the CDK1, KIF2C, NDC80, and CCNB2 genes are also profoundly expressed in different grades and reduce the patient's survival. Gene set enrichment analysis of these six genes reconfirms their role in metastatic phenotype. Moreover, the coexpression network shows a strong association of these six genes promotes cancer specific biological processes and possibly drives cancer from lower to a higher grade. Collectively the identified genes can act as potential biomarkers for breast cancer diagnosis and prognosis.     

Metallothionein as a prognostic biomarker in breast cancer

Breast cancer is the most common cancer in women, with a general upward trend in incidence. Basic and clinical breast cancer research has continued at a rapid pace, in the endeavor to understand the biology of the disease so as to improve management of patients. Besides traditional pathological indicators, expression of molecular markers in breast cancer has also been comprehensively investigated. This paper will focus on the prognostic utility of metallothioneins (MTs), a family of low molecular weight metal binding proteins encoded by at least 10 functional MT genes that are associated with cell proliferation in breast cancer. Evidence that MT is a potential prognostic biomarker for breast cancer is supported by many reports in the literature. Expression of the MT protein has been detected by immunohistochemistry in a significant portion of invasive ductal breast cancers. MT expression has also been well studied in association with traditional clinico-pathological parameters of breast cancers. Generally, higher MT expression in breast cancers is predictive of worse patient outcomes. The relationship of MT isoforms to histological grade, estrogen receptor (ER) status, and prognosis will also be discussed.     

Pre-treatment systemic immune-inflammation index is a useful prognostic indicator in patients with breast cancer undergoing neoadjuvant chemotherapy

The systemic immune-inflammation index (SII = N × P/L) based on neutrophil (N), platelet (P) and lymphocyte (L) counts is used to predict the survival of patients with malignant tumours and can fully reflect the balance between host inflammatory and immune status. This study is conducted to explore the potential prognostic significance of SII in patients with breast cancer undergoing neoadjuvant chemotherapy (NACT). A total of 262 patients with breast cancer received NACT were enrolled in this study. According to the receiver operating characteristic curve, the optimal cut-off value of SII was divided into two groups: low SII group (<602 × 10⁹/L) and high SII group (≥602 × 10⁹/L). The associations between breast cancer and clinicopathological variables by SII were determined by chi-squared test or Fisher's exact test. The Kaplan-Meier plots and log-rank test were used to determine clinical outcomes of disease-free survival (DFS) and overall survival (OS). The prognostic value of SII was analysed by univariate and multivariate Cox proportional hazards regression models. The toxicity of NACT was accessed by National Cancer Institute Common Toxicity Criteria (NCICTC). According to univariate and multivariate Cox regression survival analyses, the results showed that the value of SII had prognostic significance for DFS and OS. The patients with low SII value had longer DFS and OS than those with high SII value (31.11 vs 40.76 months, HR: 1.075, 95% CI: 0.718-1.610, P = .006; 44.47 vs 53.68 months, HR: 1.051, 95% CI: 0.707-1.564, P = .005, respectively). The incidence of DFS and OS in breast cancer patients with low SII value was higher than that in those patients with high SII value in 3-, 5- and 10-year rates. The common toxicities after NACT were haematological and gastrointestinal reaction, and there were no differences by SII for the assessment of side effects of neoadjuvant chemotherapy. Meanwhile, the results also proved that breast cancer patients with low SII value and high Miller and Payne grade (MPG) survived longer than those breast cancer with high SII value and low MPG grade. In patients without lymph vessel invasion, these breast cancer patients with low SII value had better prognosis and lower recurrence rates than those with high SII value. Pre-treatment SII with the advantage of reproducible, convenient and non-invasive was a useful prognostic indicator for breast cancer patients undergoing neoadjuvant chemotherapy and is a promising biomarker for breast cancer on treatment strategy decisions.     

Angiogenesis as an independent prognostic indicator in node-negative breast cancer

OBJECTIVE: To quantitate tumor angiogenesis in carcinoma of the breast (stage T2N0M0) by computerized image analysis of CD-31-stained histologic sections and, keeping in view the heterogeneity of tumors, to assess which areas of neovascularization provide the best prognostic indicator. STUDY DESIGN: Thirty-six cases of infiltrating duct carcinoma of the breast, stage T2N0M0, with follow-up of five years, were analyzed. All cases had received uniform initial treatment in the form of mastectomy with axillary clearance and radiotherapy. Intratumoral microvessel density (IMD) counts were done on "hot spots" and "non-hot spots" on CD-31-stained sections using computerized image analysis. Angiogenesis was correlated with other variables, such as age, menopausal status, histologic grade and proliferative activity by univariate and multivariate analyses. RESULTS: Hot-spot IMD counts were highly significant independent prognostic markers in univariate and multivariate analyses. Background vascularity of a tumor was of no value in prognosticating. CONCLUSION: In patients with node negative breast carcinoma, IMD counts in hot spots are an independent prognostic factor in disease-free and overall survival and can be used to separate out patients with T2N0M0 stage in need of systemic adjuvant therapy.     

Blood group as a prognostic indicator in breast cancer.

A retrospective analysis of 1001 patients with invasive breast cancer showed a difference in survival between patients with different blood groups. Analysis of time from operation to local recurrence and to general recurrence reinforced this finding. The difference between blood groups became increasingly significant after accepted prognostic factors were allowed for. Patients at particularly high risk of early death or general recurrence were those with blood groups B and AB, those with group AB having a greater relative local recurrence rate.     

Proteomic analysis of selected prognostic factors of breast cancer

The incidence of breast cancer is on the rise but as yet there is no guaranteed beneficial treatment for many of the sufferers. The treatments specific for breast and other hormone-sensitive cancers work well at times, however, the population of women that they will benefit is relatively small. Many are limited to surgical, chemotherapy, and radiotherapy options. Here, using two-dimensional electrophoresis (2-DE) in conjunction with a silver stain and Western blotting approach, we attempt to locate selected known prognostic markers for breast cancer. With these results, we can exclude these proteins from the future search for potential pharmaceutical targets, using the same techniques. The proteins that were located include the estrogen receptor-alpha, beta-casein, cytokeratin 7, calponin and bax. For each protein an estimated M(r) and pI was gained. Each protein was found in multiple variants. By locating these proteins the number of unknown proteins found on the 2-DE gel has been reduced, helping the future search for novel markers that are shown as being differentially expressed between healthy and cancerous tissue samples.     

T-cell receptors provide potential prognostic signatures for breast cancer

Although T-cell receptors (TCRs) are related to the progression of breast cancer (BC), their prognostic values remain unclear. We downloaded the messenger RNA (mRNA) profiles and corresponding clinical information of 1413 BC patients from the Cancer Genome Atlas and Gene Expression Omnibus database, respectively. The different expression analysis of 104 TCRs in BC samples was performed, and the consensus clustering based on 104 TCRs was performed by using the K-mean method of R language. Univariate cox regression analysis was used to screen TCRs significantly associated with the prognosis of BC, and LASSO Cox analysis was applied to optimize key TCRs. The risk score was calculated using the prognostic model constructed based on six optimal TCRs, and multivariate Cox regression analysis was used to determine whether it was an independent prognostic signature. Finally, the nomogram was constructed to predict the overall survival of BC patients. Six optimal TCRs (ZAP70, GRAP2, NFKBIE, IFNG, NFKBIA, and PAK5), which were favorable for the prognosis of BC patients, were screened. Risk score could reliably predict the prognosis of BC patients as an independent prognostic signature. In addition, when bringing into two independent prognostic signatures, age and risk score, the nomogram model could better predict the overall survival of BC patients. Our results suggested that the poor prognosis of BC patients with high risk might be due to an immunosuppressive microenvironment. In summary, a prognostic risk model based on six TCRs was established and could efficiently predict the prognosis of BC patients.     

Nuclear NHERF1 expression as a prognostic marker in breast cancer

Our purpose was to investigate whether Na⁺/H⁺ exchanger regulatory factor 1 (NHERF1) expression could be linked to prognosis in invasive breast carcinomas. NHERF1, an ezrin-radixin-moesin (ERM) binding phosphoprotein 50, is involved in the linkage of integral membrane proteins to the cytoskeleton. It is therefore believed to have an important role in cell signaling associated with changes in cell cytoarchitecture. NHERF1 expression is observed in various types of cancer and is related to tumor aggressiveness. To date the most extensive analyses of the influence of NHERF1 in cancer development have been performed on breast cancer. However, the underlying mechanism and its prognostic significance are still undefined. NHERF1 expression was studied by immunohistochemistry (IHC) in a cohort of 222 breast carcinoma patients. Association of cytoplasmic and nuclear NHERF1 expression with survival was analyzed. Disease-free survival (DFS) and overall survival (OS) were determined based on the Kaplan–Meier method. Cytoplasmic NHERF1 expression was associated with negative progesterone receptor (PgR) (P=0.017) and positive HER2 expression (P=0.023). NHERF1 also showed a nuclear localization and this correlated with small tumor size (P=0.026) and positive estrogen receptor (ER) expression (P=0.010). Multivariate analysis identified large tumor size (P=0.011) and nuclear NHERF1 expression (P=0.049) to be independent prognostic variables for DFS. Moreover, the nuclear NHERF1(−)/ER(−) immunophenotype (27%) was statistically associated with large tumor size (P=0.0276), high histological grade (P=0.0411), PgR-negative tumors (P<0.0001) and high proliferative activity (P=0.0027). These patients had worse DFS compared with patients with nuclear NHERF1(+)/ER(+) tumors (75.4% versus 92.6% P=0.010). These results show that the loss of nuclear NHERF1 expression is associated with reduced survival, and the link between nuclear NHERF1 and ER expression may serve as a prognostic marker for the routine clinical management of breast cancer patients.     

CA 15-3: a prognostic marker in breast cancer

CA 15-3 (also known as MUC1) is the most widely used serum marker in breast cancer. MUC1 is a large transmembrane glycoprotein which is frequently overexpressed and aberrantly glycosylated in cancer. Physiologically, MUC1 appears to play a role in cell adhesion and the high levels present in cancer may be causally involved in metastasis. At present the main uses of CA 15-3 are in preclinically detecting recurrent breast cancer and monitoring the treatment of patients with advanced breast cancer. In a prospective study of 368 patients we show that patients with high preoperative levels of CA 15-3 (>30.4 U/mL) had a worse outcome than patients with low levels of the marker. In multivariate analysis CA 15-3 as a prognostic marker was independent of both tumor size and nodal status. Furthermore, in multivariate analysis the prognostic impact of CA 15-3 was stronger than that of tumor size and at least as strong as nodal status. CA 15-3 may thus be the first independent prognostic serum marker in breast cancer.     

Immunocytochemical detection of prognostic markers in breast cancer; technical considerations

The purpose of this study was to establish a good technical procedure for immunocytochemical (IC) staining of prognostic markers in breast cancer specimens. The influence of various preparation, fixation and storage methods on ER, P53 and Ki-67 IC staining was assessed, using cells of two breast cancer cell lines T47D (ER/P53+) and ZR-75-ER (ER+, P53-). In addition we searched for a suitable transport medium. Depending on the technical procedure, great variations in expression of the tested antigens were found. Cytospins fixed and stored according to the Abbott method gave the best results. Histocon appeared to be the medium of choice. A good concordance of IC and immunohistochemical (IH) results was found when the adopted method was tested on material of 10 breast cancers. This study underlines the importance of quality controlled standardization of cell processing, fixation and storage of fine needle aspiration (FNA) aspirates in order to obtain reproducible and consistent IC results.     

A novel autophagy-related lncRNA prognostic risk model for breast cancer

Long non-coding RNAs (lncRNAs) are well known as crucial regulators to breast cancer development and are implicated in controlling autophagy. LncRNAs are also emerging as valuable prognostic factors for breast cancer patients. It is critical to identify autophagy-related lncRNAs with prognostic value in breast cancer. In this study, we identified autophagy-related lncRNAs in breast cancer by constructing a co-expression network of autophagy-related mRNAs-lncRNAs from The Cancer Genome Atlas (TCGA). We evaluated the prognostic value of these autophagy-related lncRNAs by univariate and multivariate Cox proportional hazards analyses and eventually obtained a prognostic risk model consisting of 11 autophagy-related lncRNAs (U62317.4, LINC01016, LINC02166, C6orf99, LINC00992, BAIAP2-DT, AC245297.3, AC090912.1, Z68871.1, LINC00578 and LINC01871). The risk model was further validated as a novel independent prognostic factor for breast cancer patients based on the calculated risk score by Kaplan-Meier analysis, univariate and multivariate Cox regression analyses and time-dependent receiver operating characteristic (ROC) curve analysis. Moreover, based on the risk model, the low-risk and high-risk groups displayed different autophagy and oncogenic statues by principal component analysis (PCA) and Gene Set Enrichment Analysis (GSEA) functional annotation. Taken together, these findings suggested that the risk model of the 11 autophagy-related lncRNAs has significant prognostic value for breast cancer and might be autophagy-related therapeutic targets in clinical practice.     

Comprehensive analysis of autophagy‐related prognostic genes in breast cancer

Accumulating evidence revealed that autophagy played vital roles in breast cancer (BC) progression. Thus, the aim of this study was to investigate the prognostic value of autophagy‐related genes (ARGs) and develop a ARG‐based model to evaluate 5‐year overall survival (OS) in BC patients. We acquired ARG expression profiling in a large BC cohort (N = 1007) from The Cancer Genome Atlas (TCGA) database. The correlation between ARGs and OS was confirmed by the LASSO and Cox regression analyses. A predictive model was established based on independent prognostic variables. Thus, time‐dependent receiver operating curve (ROC), calibration plot, decision curve and subgroup analysis were conducted to determine the predictive performance of ARG‐based model. Four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were identified using the LASSO and multivariate Cox regression analyses. A ARG‐based model was constructed based on the four ARGs and two clinicopathological risk factors (age and TNM stage), dividing patients into high‐risk and low‐risk groups. The 5‐year OS of patients in the low‐risk group was higher than that in the high‐risk group (P < 0.0001). Time‐dependent ROC at 5 years indicated that the four ARG–based tool had better prognostic accuracy than TNM stage in the training cohort (AUC: 0.731 vs 0.640, P < 0.01) and validation cohort (AUC: 0.804 vs 0.671, P < 0.01). The mutation frequencies of the four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were 0.9%, 2.8%, 8% and 1.3%, respectively. We built and verified a novel four ARG–based nomogram, a credible approach to predict 5‐year OS in BC, which can assist oncologists in determining effective therapeutic strategies.