Nottingham Prognostic Index in triple-negative breast cancer: a reliable prognostic tool?

Predicting the Survival Benefit of Radiotherapy in Elderly Breast Cancer Patients: A Population-Based Analysis

INTRODUCTION

This study aimed to establish two prediction tools predicting cancer-specific survival (CSS) and overall survival (OS) in elderly breast cancer patients with or without radiotherapy.

METHODS

Clinicopathological data of breast cancer patients aged more than 70 y from 2010 to 2018 were retrospectively collected from the Surveillance, Epidemiology, and End Results database. Patients were randomly divided into the training and validation cohorts at 7:3, and the Cox proportional risk model was used to construct the nomograms. The concordance index, the area under the receiver operating characteristic curve, and the calibration plot are used to evaluate the discrimination and accuracy of the nomograms.

RESULTS

One lakh twenty eight thousand two hundred twenty three elderly breast cancer patients were enrolled, including 57,915 who received radiotherapy. The Cox regression model was used to identify independent factors. These independent influencing factors are used to construct the prediction models. The calibration plots reflect the excellent consistency between the predicted and actual survival rates. The concordance index of nomograms for CSS and OS was more than 0.7 in both the radiotherapy group and the nonradiotherapy group, and similar results are also shown in area under the receiver operating characteristic curve. Decision curve analysis showed that the prognostication accuracy of the model was much higher than that of the traditional tumor, node, metastasis staging.

CONCLUSIONS

Radiotherapy can benefit elderly breast cancer patients significantly. The two prediction tools provide a personalized survival scale for evaluating the CSS and OS of elderly breast cancer patients, which can better provide clinicians with better-individualized management for these patients.

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists' proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists' capabilities and ameliorating patient outcomes in the realm of breast cancer management.

CRISPR/Cas9 mediated knocking out of OPN gene enhances radiosensitivity in MDA-MB-231 breast cancer cell line

PURPOSE

Although chemotherapy and radiotherapy in conjunction with surgery have been known as the standard methods for patients with breast cancer, they frequently face resistance due to the failure of cells to death. Accordingly, improving the results requires discovering novel therapeutic approaches based on the changes in the molecular biology of cancer cells. Osteopontin (OPN) is a secreted protein that previous studies have shown to be associated with progression, poor prognosis, and metastasis in breast cancer. The current study examined the synergistic effects of radiotherapy and knocking out of OPN gene, utilizing CRISPR/Cas9 technique in MDA-MB-231 breast cancer cells.

METHODS

We used to knock out the OPN gene by the two different gRNAs. The cells irradiated 24 h after transfection. The mRNA expression, tumor cell proliferation, cell cycle distribution, growth, and apoptosis were measured. Moreover, activation of Chk1 and AKT were measured via western blot.

RESULTS

We demonstrated the OPN knocking out along with radiation led to the promotion of apoptosis, suppression of downstream genes, reduction of cell viability, and inhibition of cell-cycle progression. The western blot analysis has indicated that the knocking out of the OPN gene along with radiotherapy changes DNA damage responses substantially.

CONCLUSIONS

The OPN gene knocking out with radiotherapy might be an efficient approach to overcome the radioresistance in breast cancer.

Advancement of prognostic models in breast cancer: a narrative review

Objective

To provide a reference for clinical work and guide the decision-making of healthcare providers and end-users, we systematically reviewed the development, validation and classification of classical prognostic models for breast cancer.

Background

Patients suffering from breast cancer have different prognosis for its high heterogeneity. Accurate prognosis prediction and risk stratification for breast cancer are crucial for individualized treatment. There is a lack of systematic summary of breast cancer prognostic models.

Methods

We conducted a PubMed search with keywords "breast neoplasm", "prognostic model", "recurrence" and "metastasis", and screened the retrieved publications at three levels: title, abstract and full text. We identified the articles presented the development and/or validation of models based on clinicopathological factors, genomics, and machine learning (ML) methods to predict survival and/or benefits of adjuvant therapy in female breast cancer patients.

Conclusions

Combining prognostic-related variables with long-term clinical outcomes, researchers have developed a series of prognostic models based on clinicopathological parameters, genomic assays, and medical figures. The discrimination, calibration, overall performance, and clinical usefulness were validated by internal and/or external verifications. Clinicopathological models integrated the clinical parameters, including tumor size, histological grade, lymph node status, hormone receptor status to provide prognostic information for patients and doctors. Gene-expression assays deeply revealed the molecular heterogeneity of breast cancer, some of which have been cited by AJCC and National Comprehensive Cancer Network (NCCN) guidelines. In addition, the models based on the ML methods provided more detailed information for prognosis prediction by increasing the data dimension. Combined models incorporating clinical variables and genomics information are still required to be developed as the focus of further researches.

Prediction of Late Recurrence and Distant Metastasis in Early-stage Breast Cancer: Overview of Current and Emerging Biomarkers

Recently, a significant number of breast cancer (BC) patients have been diagnosed at an early stage. It is therefore critical to accurately predict the risk of recurrence and distant metastasis for better management of BC in this setting. Clinicopathologic patterns, particularly lymph node status, tumor size, and hormonal receptor status are routinely used to identify women at increased risk of recurrence. However, these factors have limitations regarding their predictive ability for late metastasis risk in patients with early BC. Emerging molecular signatures using gene expression-based approaches have improved the prognostic and predictive accuracy for this indication. However, the use of their based-scores for risk assessment has provided contradictory findings. Therefore, developing and using newly emerged alternative predictive and prognostic biomarkers for identifying patients at high- and low-risk is of great importance. The present review discusses some serum biomarkers and multigene profiling scores for predicting late recurrence and distant metastasis in early-stage BC based on recently published studies and clinical trials.

A Bioinformatic Pipeline Places STAT5A as a miR-650 Target in Poorly Differentiated Aggressive Breast Cancer

Breast cancer (BRCA) is a leading cause of mortality among women. Tumors often acquire aggressive features through genomic aberrations affecting cellular programs, e.g., the epithelial to mesenchymal transition (EMT). EMT facilitates metastasis leading to poor prognosis. We previously observed a correlation between an amplification of miR-650 (Amp-650) and EMT features in BRCA samples isolated from Mexican patients. In this study, we explored the cBioportal database aiming to extend that observation and better understand the importance of Amp-650 for BRCA aggressiveness. We found that Amp-650 is more frequent in aggressive molecular subtypes of BRCA, as well as in high grade poorly differentiated tumors, which we confirmed in an external miRNA expression database. We performed differential expression analysis on samples harboring Amp-650, taking advantage of gene target prediction tools and tumor suppressor gene databases to mine several hundreds of differentially underexpressed genes. We observed STAT5A as a likely putative target gene for miR-650 in aggressive poorly differentiated BRCA. Samples with both Amp-650 and low expression of STAT5A had less overall survival than samples with either or none of the alterations. No target gene has been described for miR-650 in BRCA, thus, this bioinformatic study provides valuable information that should be corroborated experimentally.

Dynamic and subtype-specific interactions between tumour burden and prognosis in breast cancer

We investigated the relationship between the prognostic importance of anatomic tumour burden and subtypes of breast cancer using data from the Korean Breast Cancer Registry Database. In HR+/HER2+ and HR−/HER2−tumours, an increase in T stage profoundly increased the hazard of death, while the presence of lymph node metastasis was more important in HR+/HER2+ and HR−/HER2+ tumours among 131,178 patients with stage I–III breast cancer. The patterns of increasing mortality risk and tumour growth (per centimetre) and metastatic nodes (per node) were examined in 67,038 patients with a tumour diameter ≤ 7 cm and < 8 metastatic nodes. HR+/HER2− and HR−/HER2− tumours showed a persistent increase in mortality risk with an increase in tumour diameter, while the effect was modest in HER2+ tumours. Conversely, an increased number of metastatic nodes was accompanied by a persistently increased risk in HR−/HER2+ tumours, while the effect was minimal for HR−/HER2− tumours with > 3 or 4 nodes. The interactions between the prognostic significance of anatomic tumour burden and subtypes were significant. The prognostic relevance of the anatomic tumour burden was non-linear and highly dependent on the subtypes of breast cancer.

Comparison of Nottingham Prognostic Index, PREDICT and PrognosTILs in Triple Negative Breast Cancer -a Retrospective Cohort Study

Triple-negative breast cancer (TNBC) represents a heterogenous subtype of breast cancer with generally poor prognosis. The prediction of its prognosis remains essential to clinicians in their therapeutical decision-making process. The aim of our study was to compare the validity of three multivariable analysis derived prognostic systems, the Nottingham Prognostic Index (NPI), PREDICT and PrognosTILs (a prognosticator including tumor infiltrating lymphocytes, TILs) in a series of TNBCs. Patients operated on with TNBC at the Department of Surgery, Bács-Kiskun County Teaching Hospital, Kecskemét between 2005 and 2016 were included. Clinical and pathological parameters and follow-up data were collected from medical charts. TILs were assessed retrospectively, following international recommendations. Estimated survivals of PrognosTILs, PREDICT and NPI were recorded and compared with real outcomes. Altogether 136 patients were included in this retrospective study. In univariate Cox analysis, type of surgery, pT, pN, stage, NPI and type of adjuvant therapy were the significant prognostic variables. The multivariate Cox-regression strengthened that NPI is an independent predictor of overall and disease-free survivals in TNBCs. The NPI, PREDICT and PrognosTILs could be compared directly only in a ROC curve analysis: the sensitivities and specificities of these predicting systems are rather similar with area under the curve values falling between 0.7 and 0.8, and NPI having the highest values. Our findings reflect the diverse prognosis of TNBC and highlight the difficulties of predicting its outcome. None of the three multivariable prognosticators is inferior to the others, the NPI can reliably be used for TNBCs.

A prognostic model based on cell-cycle control predicts outcome of breast cancer patients

Background

A prognostic model combining biomarkers of metaphase-anaphase transition of the cell cycle was developed for invasive breast cancer. The prognostic value and clinical applicability of the model was evaluated in comparison with the routine prognosticators of invasive breast carcinoma.

Methods

The study comprised 1135 breast cancer patients with complete clinical data and up to 22-year follow-up. Regulators of metaphase-anaphase transition were detected immunohistochemically and the biomarkers with the strongest prognostic impacts were combined into a prognostic model. The prognostic value of the model was tested and evaluated in separate patient materials originating from two Finnish breast cancer centers.

Results

The designed model comprising immunoexpressions of Securin, Separase and Cdk1 identified 8.4-fold increased risk of breast cancer mortality (p < 0.0001). A survival difference exceeding 15 years was observed between the majority (> 75%) of patients resulting with favorable as opposed to unfavorable outcome of the model. Along with nodal status, the model showed independent prognostic impact for all breast carcinomas and for subgroups of luminal, N+ and N- disease.

Conclusions

The impact of the proposed prognostic model in predicting breast cancer survival was comparable to nodal status. However, the model provided additional information in N- breast carcinoma in identifying patients with aggressive course of disease, potentially in need of adjuvant treatments. Concerning N+, in turn, the model could provide evidence for withholding chemotherapy from patients with favorable outcome.

High WDR34 mRNA expression as a potential prognostic biomarker in patients with breast cancer as determined by integrated bioinformatics analysis

The WD-repeat domain (WDR) family is distributed in the majority of eukaryotes and has several unique biological functions. It serves important roles in signal transduction, cytoskeleton assembly, protein transport, RNA processing, chromatin modification and transcription mechanisms. WD repeat domain 34 (WDR34) has been recently identified as a member of the WDR family. Overexpression of WDR34 was accompanied by the presence of multiple centrioles in the cell, suggesting that it was associated with tumor occurrence. However, its association with breast cancer was unclear. To the best of our knowledge, it has not yet been confirmed whether WDR34 gene expression is associated with breast cancer. Therefore, the current study attempted to clarify this by performing a comprehensive study using multiple datasets in the Oncomine, Breast Cancer Gene-Expression Miner and Kaplan-Meier Plotter databases. The analysis indicated that the mRNA expression levels of WDR34 were increased in breast cancer tissues compared with normal tissues. Consistent with this result, the Broad-Novartis Cancer Cell Line Encyclopedia revealed that WDR34 mRNA expression levels were upregulated in breast cancer cell lines compared with other cancer cells. It was noted that high WDR34 mRNA expression was associated with forkhead box M1 and PTTG1 regulator of sister chromatid separation, securing in co-expression analysis. Expression profile characteristics of WDR34 mRNA were identified in different molecular subtypes of breast cancer. Furthermore, survival analysis revealed that increased expression levels of WDR34 mRNA were associated with poor overall survival in patients with breast cancer, particularly in luminal B, lymph node status-positive and estrogen receptor (ER)-negative subgroups. Additionally, Kaplan-Meier curves revealed that high WDR34 mRNA expression was associated with shorter relapse-free survival in patients with breast cancer, particularly in ER-positive, human epidermal growth factor receptor 2-negative and progesterone receptor-positive subgroups. These results suggested that WDR34 may be used as a prognosis predictor in breast cancer and may provide a novel target for the diagnosis and treatment of breast cancer.

Development and validation of nomograms predicting survival in Chinese patients with triple negative breast cancer

Background

Triple negative breast cancer (TNBC) is an aggressive and heterogeneous disease. Nomograms predicting outcomes of TNBC are needed for risk management.

Methods

Nomograms were based on an analysis of 296 non-metastatic TNBC patients treated at Sun Yat-sen Memorial Hospital from 2002 to 2014. The end points were disease-free survival (DFS) and overall survival (OS). Predictive accuracy and discriminative ability were evaluated by concordance index (C-index), area under the curve (AUC) and calibration curve, and compared with the American Joint Committee on Cancer (AJCC) staging system, PREDICT and CancerMath. Models were subjected to bootstrap internal validation and external validation using independent cohorts of 191 patients from the second Xiangya Hospital and Peking University Shenzhen Hospital between 2007 and 2012.

Results

On multivariable analysis of training cohort, independent prognostic factors were stromal tumor-infiltrating lymphocytes (TILs), tumor size, node status, and Ki67 index, which were then selected into the nomograms. The calibration curves for probability of DFS and OS showed optimal agreement between nomogram prediction and actual observation. The C-index of nomograms was significantly higher than that of the seventh and eighth AJCC staging system for predicting DFS (training: 0.743 vs 0.666 (P = 0.003) and 0.664 (P = 0.024); validation: 0.784 vs 0.632 (P = 0.02) and 0.607 (P = 0.002)) and OS (training: 0.791 vs 0.683 (P = 0.004) and 0.677 (P < 0.001); validation: 0.783 vs 0.656 (P = 0.006) and 0.606 (P = 0.001)). Our nomograms had larger AUCs compared with PREDICT and CancerMath. In addition, the nomograms showed good performance in stratifying different risk groups of patients both in the training and validation cohorts.

Conclusion

We have developed novel and practical nomograms that can provide individual prediction of DFS and OS for TNBC based on stromal TILs, tumor size, node status, and Ki67 index. Our nomograms may help clinicians in risk consulting and selection of long term survivors.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5703-4) contains supplementary material, which is available to authorized users.

Nanosized functional miRNA liposomes and application in the treatment of TNBC by silencing Slug gene

Background: Neo-adjuvant chemotherapy is an effective strategy for improving treatment of breast cancers. However, the efficacy of this treatment strategy is limited for treatment of triple negative breast cancer (TNBC). Gene therapy may be a more effective strategy for improving the prognosis of TNBC.

Methods: A novel 25 nucleotide sense strand of miRNA was designed to treat TNBC by silencing the Slug gene, and encapsulated into DSPE-PEG₂₀₀₀-tLyp-1 peptide-modified functional liposomes. The efficacy of miRNA liposomes was evaluated on invasive TNBC cells and TNBC cancer-bearing nude mice. Furthermore, functional vinorelbine liposomes were constructed to investigate the anticancer effects of combined treatment.

Results: The functional miRNA liposomes had a round shape and were nanosized (120 nm). Functional miRNA liposomes were effectively captured by TNBC cells in vitro and were target to mitochondria. Treatment with functional liposomes silenced the expression of Slug and Slug protein, inhibited the TGF-β1/Smad pathway, and inhibited invasiveness and growth of TNBC cells. In TNBC cancer-bearing mice, functional miRNA liposomes exerted a stronger anticancer effect than functional vinorelbine liposomes, and combination therapy with these two formulations resulted in nearly complete inhibition of tumor growth. Preliminary safety evaluations indicated that the functional miRNA liposomes did not affect body weight or cause damage to any major organs. Furthermore, the functional liposomes significantly increased the half-life of the drug in the blood of cancer-bearing nude mice, and increased drug accumulation in breast cancer tissues.

Conclusion: In this study, we constructed novel functional miRNA liposomes. These liposomes silenced Slug expression and inhibited the TGF-β1/Smad pathway in TNBC cells, and enhanced anticancer efficacy in mice using combined chemotherapy. Hence, the present study demonstrated a promising strategy for gene therapy of invasive breast cancer.

Prognostic models for breast cancer: a systematic review

BACKGROUND

Breast cancer is the most common cancer in women worldwide, with a great diversity in outcomes among individual patients. The ability to accurately predict a breast cancer outcome is important to patients, physicians, researchers, and policy makers. Many models have been developed and tested in different settings. We systematically reviewed the prognostic models developed and/or validated for patients with breast cancer.

METHODS

We conducted a systematic search in four electronic databases and some oncology websites, and a manual search in the bibliographies of the included studies. We identified original studies that were published prior to 1st January 2017, and presented the development and/or validation of models based mainly on clinico-pathological factors to predict mortality and/or recurrence in female breast cancer patients.

RESULTS

From the 96 articles selected from 4095 citations found, we identified 58 models, which predicted mortality (n = 28), recurrence (n = 23), or both (n = 7). The most frequently used predictors were nodal status (n = 49), tumour size (n = 42), tumour grade (n = 29), age at diagnosis (n = 24), and oestrogen receptor status (n = 21). Models were developed in Europe (n = 25), Asia (n = 13), North America (n = 12), and Australia (n = 1) between 1982 and 2016. Models were validated in the development cohorts (n = 43) and/or independent populations (n = 17), by comparing the predicted outcomes with the observed outcomes (n = 55) and/or with the outcomes estimated by other models (n = 32), or the outcomes estimated by individual prognostic factors (n = 8). The most commonly used methods were: Cox proportional hazards regression for model development (n = 32); the absolute differences between the predicted and observed outcomes (n = 30) for calibration; and C-index/AUC (n = 44) for discrimination. Overall, the models performed well in the development cohorts but less accurately in some independent populations, particularly in patients with high risk and young and elderly patients. An exception is the Nottingham Prognostic Index, which retains its predicting ability in most independent populations.

CONCLUSIONS

Many prognostic models have been developed for breast cancer, but only a few have been validated widely in different settings. Importantly, their performance was suboptimal in independent populations, particularly in patients with high risk and in young and elderly patients.

Importance of Copy Number Alterations of FGFR1 and C-MYC Genes in Triple Negative Breast Cancer

Background

Triple negative breast cancer (TNBC) is characterized by aggressive clinical course and is unresponsive to anti-HER2 and endocrine therapy. TNBC is difficult to treat and is often lethal. Given the need to find new targets for therapy we explored clinicopathological significance of copy number gain of FGFR1 and c-MYC. Our aim was to determine the impact of FGFR1 and c-MYC copy number gain on clinical course and outcome of TNBC.

Methods

FGFR1 and c-MYC gene copy number alterations were evaluated in 78 archive TNBC samples using TaqMan based quantitative real time PCR assays.

Results

50% of samples had increased c-MYC copy number. c-MYC copy number gain was associated with TNBC in contrast to ER positive cancers. Our results showed significant correlation between c-MYC copy number gain and high grade of TNBCs. This suggests that c-MYC copy number could be an useful prognostic marker for TNBC patients. c-MYC copy number gain was associated with high pTNM stage as well as lobular and medullary tumor subtypes. 43% of samples had increased FGFR1 copy number. No correlations between FGFR1 copy number gain and clinicopathological variables were observed.

Conclusions

We identified c-MYC copy number gain as a prognostic marker for TNBC. Our results indicate that c- MYC may contribute to TNBC progression. We observed no significant association between c-MYC and/or FGFR1 copy number status and patient survival.

Nottingham Prognostic Index is an Applicable Prognostic Tool in Non-Metastatic Triple-Negative Breast Cancer

Introduction:

Triple-negative breast cancer (TNBC) is characterized by a poor prognosis due to high mortality and early relapse, requiring the study of its prognostic factors. Tumor size, histological grade and lymph node status represent important parameters that are widely studied in breast cancer, and are retained as prognostic factors by several international guidelines. The Nottingham team combined these parameters into a prognostic score called the Nottingham prognostic index (NPI). In this study, we investigated the influence of NPI on outcomes in non metastatic TNBC.

Methodology:

This retrospective cohort study included all female patients with non metastatic TNBC who received treatment at the Regional Oncology Center Hassan II Oujda - Morocco, between January 2009 and December 2011. The prognostic impact of the NPI on the survival curves at 5 years was studied using multivariate Cox proportional hazards models.

Results:

The analysis of the data involved 98 patients, 39 patients (39.8%) were classed in the poor prognosis group with a NPI > 5.4. The Overall survival (OS) and Disease free survival (DFS) rates at 5 years, in this group, were 70 and 55.6 % respectively. After adjusting for clinic-pathological variables, a NPI > 5.4 was associated with mortality (HR: 2.598, 95% CI: 1.423 – 4.744, p = 0.002) and disease progression (HR: 2.512, CI to 95%: 1.496 – 4.219, p <0.001) in patients with non-metastatic TNBC.

Conclusion:

This retrospective cohort analysis showed that NPI was an independent prognostic factor for OS and DFS at 5 years in women with non metastatic TNBC. Once validated, the impact of this score on survival outcomes could be considered in the clinical management of TNBC.

Development of double strand RNA mPEI nanoparticles and application in treating invasive breast cancer

dsRNA mPEI nanoparticles entered cytoplasm and lysosomal escape occurred. dsRNA was released to form a dsRNA–RISC complex. Then, remaining sense strand bound to mRNA, forming a new structure. Thus, mRNA was cleared and translation was inhibited.

Identification of Key Genes and Pathways in Triple-Negative Breast Cancer by Integrated Bioinformatics Analysis

Purpose

Triple-negative breast cancer refers to breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (Her2). This study aimed to identify the key pathways and genes and find the potential initiation and progression mechanism of triple-negative breast cancer (TNBC).

Methods

We downloaded the gene expression profiles of GSE76275 from Gene Expression Omnibus (GEO) datasets. This microarray Super-Series sets are composed of gene expression data from 265 samples which included 67 non-TNBC and 198 TNBC. Next, all the differentially expressed genes (DEGs) with p<0.01 and fold change ≥1.5 or ≤-1.5 were identified.

Result

56 upregulated and 151 downregulated genes were listed and the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was performed. These significantly changed genes were mainly involved in the biological process termed prostate gland morphogenesis, inner ear morphogenesis, cell maturation, digestive tract morphogenesis, autonomic nervous system development, monovalent inorganic anion homeostasis, neural crest cell development, regulation of dendrite extension and glial cell proliferation, immune system process termed T cell differentiation, regulation of immune response, and macrophage activation. Genes are mainly involved in the KEGG pathway termed Oocyte meiosis. All DEGs underwent survival analysis using datasets from The Cancer Genome Atlas (TCGA) integrated by cBioPortal, of which amplification of SRY-related HMG-box 8 (SOX8), androgen receptor (AR), and Chromosome 9 Open Reading Frame 152 (C9orf152) were significantly negative while Nik Related Kinase (NRK) and RAS oncogene family 30 (RAB30) were positively correlated to the life expectancy (p<0.05).

Conclusions

In conclusion, these pathways and genes identified could help understanding the mechanism of development of TNBC. Besides, SOX8, AR, C9orf152, NRK and RAB30, and other key genes and pathways might be promising targets for the TNBC treatment.

Betulinic acid induces apoptosis and ultrastructural changes in MDA-MB-231 breast cancer cells

The aim of this study is to investigate the effects of betulinic acid (BA) on triple-negative breast cancer MDA-MB-231 cells and observe the ultrastructural changes. The concentration of BA required to induce apoptosis in MDA-MB-231 cells has been previously reported. In this study, a cell counting kit-8 proliferation assay was used to measure cell viability and the apoptosis rate. Western blotting was performed to observe the protein expression levels of Bcl-2. Cell morphology and changes in cell density were observed by microscopy. Electron microscopy revealed pyknotic nuclei as well as vacuoles. Collectively, our results showed the morphological mechanisms by which BA impairs the ultrastructure of MDA-MB-231 cells.

Statin Use and Breast Cancer Prognosis in Black and White Women

Studies show decreased risk of breast cancer recurrence and improved survival with statin use, but data on racial disparities regarding breast cancer prognosis and statin use are lacking. Our objective was to investigate if racial disparities in breast cancer prognosis can be partially explained by differences in pre-diagnosis statin use. Patients were identified from a prospective, multicenter study examining the effects of metabolic factors on breast cancer prognosis in Black and White women. Statin use, prognosis (as measured by Nottingham Prognostic Index), anthropometric, tumor, and socio-demographic characteristics were examined. Five hundred eighty-seven women (487 White, 100 Black) with newly diagnosed primary invasive breast cancer were recruited. Obesity was more prevalent in Black women than White women (47 vs 19%, p < 0.01); both groups had similar low-density lipoprotein (LDL) cholesterol levels (113 ± 41 vs 113 ± 36 mg/dl, p = 0.90). More Black women used statins than White women (18 vs 11%, p = 0.06). Black women had a worse prognosis in an adjusted model than White women (OR 2.13 95% CI 1.23-3.67). Statin use was not associated with prognosis in unadjusted (OR 1.03, 95% CI 0.53-2.0) and adjusted models (OR 1.14, 95% CI 0.56-2.31). In women with newly diagnosed breast cancer, Black women were more likely to be treated with statins than White women, contrary to previous studies. Black women had worse prognosis than White women, but this difference was not explained by differences in pre-diagnosis statin use. Our study suggests that differences in pre-diagnosis statin use do not contribute to racial disparities in breast cancer prognosis.

FANCM mutation c.5791C>T is a risk factor for triple-negative breast cancer in the Finnish population

PURPOSE

The FANCM c.5101C>T nonsense mutation was previously found to associate with breast cancer in the Finnish population, especially among triple-negative cases. Here, we studied the prevalence of three other FANCM variants: c.5791C>T, which has been reported to predispose to familial breast cancer, and the c.4025_4026delCT and c.5293dupA variants recently identified in Finnish cancer patients.

METHODS

We genotyped the FANCM c.5791C>T mutation in 4806 invasive breast cancer patients, including BRCA1/2 mutation negative familial cases and unselected cases, and in 2734 healthy population controls from four different geographical areas of Finland. The association of the mutation with breast cancer risk among patient subgroups was statistically evaluated. We further analyzed the combined risk associated with c.5101C>T and c.5791C>T mutations. We also genotyped 526 unselected ovarian cancer patients for the c.5791C>T mutation and 862 familial breast cancer patients for the c.4025_4026delCT and c.5293dupA variants.

RESULTS

The frequency of the FANCM c.5791C>T mutation was higher among breast cancer cases than in controls (OR 1.94, 95% CI 0.87-4.32, P = 0.11), with a statistically significant association with triple-negative breast cancer (OR 5.14, 95% CI 1.65-16.0, P = 0.005). The combined analysis for c.5101C>T and c.5791C>T carriers confirmed a strong association with breast cancer (OR 1.86, 95% CI 1.32-2.49, P = 0.0002), especially among the triple-negative patients (OR 3.08, 95% CI 1.77-5.35, P = 0.00007). For the other variants, only one additional c.4025_4026delCT carrier and no c.5293dupA carriers were observed.

CONCLUSIONS

These results support the role of FANCM as a breast cancer susceptibility gene, particularly for triple-negative breast cancer.

Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics

BACKGROUND

Triple-negative breast cancer (TNBC) accounts for 15-20% of all breast cancers and usually requires the administration of adjuvant chemotherapy after surgery but even with this treatment many patients still suffer from a relapse. The main objective of this study was to identify proteomics-based biomarkers that predict the response to standard adjuvant chemotherapy, so that patients at are not going to benefit from it can be offered therapeutic alternatives.

METHODS

We analyzed the proteome of a retrospective series of formalin-fixed, paraffin-embedded TNBC tissue applying high-throughput label-free quantitative proteomics. We identified several protein signatures with predictive value, which were validated with quantitative targeted proteomics in an independent cohort of patients and further evaluated in publicly available transcriptomics data.

RESULTS

Using univariate Cox analysis, a panel of 18 proteins was significantly associated with distant metastasis-free survival of patients (p<0.01). A reduced 5-protein profile with prognostic value was identified and its prediction performance was assessed in an independent targeted proteomics experiment and a publicly available transcriptomics dataset. Predictor P5 including peptides from proteins RAC2, RAB6A, BIEA and IPYR was the best performance protein combination in predicting relapse after adjuvant chemotherapy in TNBC patients.

CONCLUSIONS

This study identified a protein combination signature that complements histopathological prognostic factors in TNBC treated with adjuvant chemotherapy. The protein signature can be used in paraffin-embedded samples, and after a prospective validation in independent series, it could be used as predictive clinical test in order to recommend participation in clinical trials or a more exhaustive follow-up.

Correlation analysis between molecular subtypes and Nottingham Prognostic Index in breast cancer

Molecular subtypes and Nottingham Prognostic Index (NPI) are both prognostic models for breast cancer patients. We evaluated the association between molecular subtypes and NPI in 1042 breast cancer patients. The molecular subtypes indicating poorer prognosis were positively correlated to higher NPI (r = 0.138, P = 0.001). ER positive expression and PR high expression were positively correlated with NPI (r = 0.142, P = 0.001; r = 0.139, P = 0.001; respectively) and negatively correlated with histological grade (r = −0.233, P < 0.001; r = −0.176, P < 0.001; respectively). Ki67 status was negatively correlated with NPI and positively correlated with histological grade (r = −0.120, P =0.004; r = 0.197, P < 0.001; respectively). The percentages of cases with NPI score 2.00–3.40 were higher in the luminar A, ER+, PR high expression and Ki67 low expression group, and the percentages of cases with NPI > 5.40 were higher in the HER2 overexpression subtype, basal-like subtype, ER-, PR low/negative expression, and Ki67 high expression groups. The excellent consistence was observed between histological grade and molecular subtypes, ER, PR, Ki67. The difference of histological grade between the HER2 positive and negative group was statistically significant. In conclusion, there was closely association between molecular subtypes and NPI in breast cancer. For further comparing the prognostic significance of molecular subtypes and NPI, survival analyses should be performed on the same population in a large-scale prospective study.

A Prognostic Model for Patients with Triple-Negative Breast Cancer: Importance of the Modified Nottingham Prognostic Index and Age

Purpose

Considering the distinctive biology of triple-negative breast cancer (TNBC), this study aimed to identify TNBC-specific prognostic factors and determine the prognostic value of the Nottingham Prognostic Index (NPI) and its variant indices.

Methods

A total of 233 patients with newly diagnosed stage I to III TNBC from 2003 to 2012 were reviewed. We retrospectively analyzed the patients' demographics, clinicopathologic parameters, treatment, and survival outcomes. The NPI was calculated as follows: tumor size (cm)×0.2+node status+Scarff-Bloom-Richardson (SBR) grade. The modified NPI (MNPI) was obtained by adding the modified SBR grade rather than the SBR grade.

Results

The median follow-up was 67.8 months. Five-year disease-free survival (DFS) and overall survival (OS) were 81.4% and 89.9%, respectively. Multivariate analyses showed that the MNPI was the most significant and common prognostic factor of DFS (p=0.001) and OS (p=0.019). Young age (≤35 years) was also correlated with poor DFS (p=0.006). A recursive partitioning for establishing the prognostic model for DFS was performed based on the results of multivariate analysis. Patients with a low MNPI (≤6.5) were stratified into the low-risk group (p<0.001), and patients with a high MNPI (>6.5) were subdivided into the intermediate (>35 years) and high-risk (≤35 years) groups. Age was not a prognostic factor in patients with a low MNPI, whereas in patients with a high MNPI, it was the second key factor in subdividing patients according to prognosis (p=0.023).

Conclusion

The MNPI could be used to stratify patients with stage I to III TNBC according to prognosis. It was the most important prognosticator for both DFS and OS. The prognostic significance of young age for DFS differed by MNPI.

Metabolic syndrome and pre-diabetes contribute to racial disparities in breast cancer outcomes: hypothesis and proposed pathways

BACKGROUND

Women with obesity and type 2 diabetes (T2D) are at greater risk of dying from breast cancer than women without these conditions. Obesity and T2D are associated with insulin resistance and endogenous hyperinsulinemia and are more common in Black women. There is increasing disparity in breast cancer mortality between Black and White women in the USA. We hypothesize that insulin resistance and endogenous hyperinsulinemia in Black women with breast cancer contribute to their greater breast cancer mortality and are associated with increased insulin receptor signalling in tumours.

METHODS

We will recruit 350 Black women and 936 White women with newly diagnosed breast cancer. We will determine the presence or absence of the metabolic syndrome/pre-diabetes and insulin resistance by measuring body mass index, waist circumference, lipids, blood pressure, glucose, insulin-like growth factor binding protein 1 and insulin. Breast cancer prognosis will be determined by a Nottingham Prognostic Index (NPI), with poor prognosis being defined as NPI >4.4. Tumour insulin receptor signalling will be determined by immunohistochemistry. Insulin receptor subtype expression will be measured using Nanostring. Analysis of these factors will determine whether endogenous hyperinsulinemia is associated with a worse prognosis in Black women than White women and increased tumour insulin receptor signalling.

CONCLUSIONS

The results of this study will determine if the metabolic syndrome and pre-diabetes contribute to racial disparities in breast cancer mortality. It may provide the basis for targeting systemic insulin resistance and/or tumour insulin receptor signalling to reduce racial disparities in breast cancer mortality. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of Nottingham Prognostic Index and Adjuvant Online prognostic tools in young women with breast cancer: review of a single-institution experience

OBJECTIVE

Accurately predicting the prognosis of young patients with breast cancer (<40 years) is uncertain since the literature suggests they have a higher mortality and that age is an independent risk factor. In this cohort study we considered two prognostic tools; Nottingham Prognostic Index and Adjuvant Online (Adjuvant!), in a group of young patients, comparing their predicted prognosis with their actual survival.

SETTING

North East England

PARTICIPANTS

Data was prospectively collected from the breast unit at a Hospital in Grimsby between January 1998 and December 2007. A cohort of 102 young patients with primary breast cancer was identified and actual survival data was recorded. The Nottingham Prognostic Index and Adjuvant! scores were calculated and used to estimate 10-year survival probabilities. Pearson's correlation coefficient was used to demonstrate the association between the Nottingham Prognostic Index and Adjuvant! scores. A constant yearly hazard rate was assumed to generate 10-year cumulative survival curves using the Nottingham Prognostic Index and Adjuvant! predictions.

RESULTS

Actual 10-year survival for the 92 patients who underwent potentially curative surgery for invasive cancer was 77.2% (CI 68.6% to 85.8%). There was no significant difference between the actual survival and the Nottingham Prognostic Index and Adjuvant! 10-year estimated survival, which was 77.3% (CI 74.4% to 80.2%) and 82.1% (CI 79.1% to 85.1%), respectively. The Nottingham Prognostic Index and Adjuvant! results demonstrated strong correlation and both predicted cumulative survival curves accurately reflected the actual survival in young patients.

CONCLUSIONS

The Nottingham Prognostic Index and Adjuvant! are widely used to predict survival in patients with breast cancer. In this study no statistically significant difference was shown between the predicted prognosis and actual survival of a group of young patients with breast cancer.

OCT4 expression and vasculogenic mimicry formation positively correlate with poor prognosis in human breast cancer

To evaluate the prognostic value of OCT4 expression and vasculogenic mimicry (VM) in human breast cancer, we examined OCT4 expression and VM formation using immunohistochemistry and CD31/PAS (periodic acid-schiff) double staining on 90 breast cancer specimens. All patients were followed up for five-149 months following surgery. Survival curves were generated using Kaplan-Meier method. Multivariate analysis was performed using Cox regression model to assess the prognostic values. Results showed positive correlation between OCT4 expression and VM formation (p<0.05). Both OCT4 expression and VM were also positively correlated with lymph node metastasis, higher histological grade, and Nottingham prognostic index (p<0.05). Patients with OCT4 expression or VM formation exhibited poorer overall survival (OS) and disease-free survival (DFS) than OCT4-negative or VM-negative patients (p<0.05). OCT4-positive/VM-positive patients also had the worst OS and DFS (p<0.05). In multivariate survival analysis, VM, Nottingham prognostic index (NPI), and Her2 were independent prognostic factors related to OS and OCT4-positive/VM-positive patients, whereas NPI and Her2 were independent predictors of DFS. These results suggest that a combined OCT4 expression/VM could improve the prognostic judgment for breast cancer patients.

Can molecular subtyping replace axillary nodal status as prognostic marker in breast cancer?

Subtypes are an established prognostic factor of BC in western population but its significance in Indian BC patients has not been evaluated. Thus this study provides an insight into the prognostic significance of molecular classification and its effect on the survival of BC patients in Eastern India. In this hospital based study 242 BC patients attending a Comprehensive Breast Service Clinic of a reputed institute in Eastern India and having IDC were studied over a period of 7 years (January 2007 to October 2013). Nonluminal HER-2-positive and Triple negative tumors were associated with advanced stage of disease, metastatic lymph nodes and NPI ≥5.4, whereas Luminal 1 and Luminal 2 tumors were associated with early stage, uninvolved lymph nodes and NPI <5.4. Better survival was observed for the patients with Luminal 1 [OS = 57.1 % (n = 36)] and Luminal 2 [OS = 60.0 % (n = 6)], compared to Triple negative [OS = 33.6 % (n = 38)] and nonluminal HER-2-positive tumors [OS = 32.1 % (n = 18)]. This study provided some idea about the pattern of BC on the basis of classification by molecular profiling. Our study indicated that Triple negative and nonluminal HER-2-positive tumors have reduced DFS and OS compared with luminal 1 and 2 subtypes. In our patients, Triple negative and nonluminal HER-2-positive tumors were associated with established unfavorable prognostic indicators and this reflects the data in the western literature. The results suggest that the molecular subtypes are an independent prognostic and predictive marker in Indian BC patients. Whether or not molecular subtyping of breast cancer can replace axillary lymph nodes as the standard in prognosis remains to be seen, but if molecular subtyping can provide more information than the axilla about the prognosis and treatment option, it may well be the future of prognostication.

Lack of prognostic significance of adiponectin immunohistochemical expression in patients with triple-negative breast cancer

INTRODUCTION

Triple-negative breast cancers (TNBCs) - which lack the expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER-2) - have no established markers that can be used for prognostic stratification. As adiponectin has been previously implicated in a more aggressive phenotype of primary breast cancer, we explored the relation between adiponectin immunohistochemical expression and prognosis in TNBCs.

MATERIAL AND METHODS

Immunohistochemical staining for adiponectin was performed in 38 TNBC patients. Disease-free survival (DFS) and overall survival (OS) served as the main outcome measures.

RESULTS

Of the 38 TNBC patients, 18 (47%) had negative and 20 (53%) positive adiponectin immunohistochemical expression. We did not find any significant association between adiponectin immunohistochemical expression and the baseline characteristics. In addition, there were no associations between adiponectin immunohistochemical expression and prognosis.

CONCLUSIONS

Although our results suggest that adiponectin immunohistochemical expression is not of prognostic significance in TNBCs, further studies are warranted to determine the role of this adipokine in breast cancer biology.

Clinicopathological and prognostic characteristics of triple- negative breast cancer (TNBC) in Chinese patients: a retrospective study

AIMS

To determine the clinical, pathological and prognostic features associated with triple-negative breast cancer (TNBC).

METHODS

Clinical and histologic data of 21,749 breast cancer patients who were treated at Tianjin Medical University Cancer Institute and Hospital between July 2002 and December 2011 were collected. Patients were divided into two groups: those with TNBC and those with other types of breast cancer. Patients and tumor characteristics were compared between the two groups using the Chi-square test. The prognostic results of 9,823 patients in the study population were also analyzed to determine long-term survival rates in the two groups of breast cancer patients.

RESULTS

Among the breast cancer patients treated in our hospital between 2003 and 2011, 10.4%-13.5% of them had triple-negative breast cancers. Data analyses revealed significant differences in disease onset age, family history of breast cancer, tumor size, tumor histologic grade, lymph note positivity and metastatic status between TNBC and non-TNBC patients. There were also significant differences in 5-year, 7-year and 9-year disease-free and 7-year and 9-year overall survival probability between the groups.

CONCLUSIONS

TNBC are associated with younger disease onset age, larger tumor size, higher rate of axillary lymph node positivity, and higher tumor histologic grade. TNBC is also related to family history of breast cancer, increased metastatic risk and poor prognosis.

Role of Cyclooxygenase 2 (COX-2) in Prognosis of Breast Cancer

COX-2 regulates tumour growth, invasion and metastasis in breast cancer. This study investigated the association between COX-2 expression in human breast cancer versus the expression of ER, PR, HER-2/neu, as well as its association with other established prognostic indicators like age, menopausal status, tumour size, lymph nodal status, stage, grade, NPI and histological subtype, and aims to validate the role of overexpression of COX-2 as a prognostic marker in patients with breast cancer in Indian subcontinent. In this hospital based study of 123 breast cancer patients (Group-A) and 76 female patients with benign breast disease (Group-B) attending a Comprehensive Breast Clinic at a reputed institute in Eastern India, COX-2 protein expression was measured from breast tissue using the Western Blot Technique. COX-2 mRNA expression was measured by RT-PCR Technique. ER, PR and HER-2/neu status was measured by immunohistochemistry methods. COX-2 was not expressed in the control group. The proportion of COX-2 positive tumours was significantly higher in patients of age >50 years [52(91.2 %), p < 0.01], postmenopausal status [64(90.1 %), p < 0.01], advanced stage of disease (p < 0.01), higher grade (p < 0.01), larger tumors (p < 0.01), metastatic lymph nodes (p < 0.01) and NPI ≥ 5.4 (p < 0.01). COX-2 expression was seen in ER-negative [66(95.7 %), p < 0.01], PR-negative [76(92.7 %), p < 0.01], and HER-2/neu positive tumours [29(100.0 %), p < 0.01]. Risk of COX-2 positivity was found to be 2.74 times more for postmenopausal status, 6.90 times more for large size tumours (≥ 2.5), 34.37 times more for node positive tumours, 9.26 times more with ER negative patients and 5.88 times more for PR negative patients. COX-2 expression is associated with established indicators of poor prognosis such as postmenopausal status, age >50 year, advanced stage of disease, large tumour size, higher grade, lymph node metastasis, NPI ≥ 5.4, ER negativity, PR negativity and HER-2/neu positivity. Thus, COX-2 expression implies aggressive tumour biology, and may play an important role as a prognostic marker.

Predicting and communicating the risk of recurrence and death in women with early-stage breast cancer: a systematic review of risk prediction models

BACKGROUND

It is a challenge for oncologists to distinguish patients with breast cancer who can forego adjuvant systemic treatment without negatively affecting survival from those who cannot. Risk prediction models (RPMs) have been developed for this purpose. Oncologists seem to have embraced RPMs (particularly Adjuvant!) in clinical practice and often use them to communicate prognosis to patients. We performed a systematic review of published RPMs and provide an overview of the prognosticators incorporated and reported clinical validity. Subsequently, we selected the RPMs that are currently used in the clinic for a more in-depth assessment of clinical validity. Finally, we assessed lay comprehensibility of the reports generated by RPMs.

METHODS

Pubmed, EMBASE, and Web of Science were searched. Two reviewers independently selected relevant articles and extracted data. Agreement on article selection and data extraction was achieved in consensus meetings.

RESULTS

We identified RPMs based on clinical prognosticators (N = 6) and biomolecular features (N = 14). Generally predictions from RPMs seem to be accurate, except for patients ≤ 50 years or ≥ 75 years at diagnosis, in addition to Asian populations. RPM reports contain much medical jargon or technical details, which are seldom explained in lay terms.

CONCLUSION

The accuracy of RPMs' prognostic estimates is suboptimal in some patient subgroups. This urgently needs to be addressed. In their current format, RPM reports are not conducive to patient comprehension. Communicating survival probabilities using RPM might seem straightforward, but it is fraught with difficulties. If not done properly, it can backfire and confuse patients. Evidence to guide best communication practice is needed.

A prognostic model for triple-negative breast cancer patients based on node status, cathepsin-D and Ki-67 index

Objective

The aim of this study was to evaluate clinicopathologic factors that could possibly affect the outcome of patients with triple negative breast cancer and subsequently build a prognostic model to predict patients’ outcome.

Methods

We retrospectively analyzed clinicopathologic characteristics and outcome of 504 patients diagnosed with triple-negative invasive ductal breast cancer. 185 patients enrolled between 2000 and 2002 were designated to the training set. The variables that had statistically significant correlation with prognosis were combined to build a model. The prognostic value of the model was further validated in the separate validation set containing 319 patients enrolled between 2003 and 2006.

Results

The median follow-up duration was 66 months. 174 patients experienced recurrence, and 111 patients died. Positivity for ≥4 lymph nodes, Cathepsin-D positivity, and Ki-67 index ≥20% were independent factors for DFS, while the lymph nodes status and Ki-67 index were the prognostic factors for OS. The prognostic model was established based on the sum of all three factors, where positivity for ≥4 lymph nodes, Cathepsin-D and Ki-67 index ≥20% would individually contribute 1 point to the risk score. The patients in the validation set were assigned to a low-risk group (0 and 1 point) and a high-risk group (2 and 3 points). The external validation analysis also demonstrated that our prognostic model provided the independent high predictive accuracy of recurrence.

Conclusion

This model has a considerable clinical value in predicting recurrence, and will help clinicians to design an appropriate level of adjuvant treatment and schedule adequate appointments of surveillance visits.

Decision-making tools to assist prognosis and treatment choices in early breast cancer: a review

Breast cancer remains the most common type of cancer affecting women worldwide with an estimated lifetime risk of 1:8. With developments in adjuvant treatment and the identification of breast cancer subtypes, rising expectation of 'personalized' and 'targeted' therapy, decisions on systemic therapy have become increasingly more difficult. In a bid to assist clinicians in correctly selecting patients in whom systemic adjuvant therapy would be of most benefit, a number of decision-making tools have been developed. In this article, the authors will review some of these tools, explore how they were developed and assess the impact they have had on daily clinical practice.

Update on triple-negative breast cancer: prognosis and management strategies

Triple negative breast cancer (TNBC) is a heterogeneous disease comprehending different orphan breast cancers simply defined by the absence of ER/PR/HER-2. Approximately 15%-20% of all breast cancers belong to this phenotype that has distinct risk factors, distinct molecular features, and a particular clinical presentation and outcome. All these features will be discussed in this review. The risk of developing TNBC varies with age, race, genetics, breastfeeding patterns, and parity. Some TNBC are very chemo-sensitive and the majority of patients confronted with and treated for TNBC will never relapse. Some (histological) subgroups of TNBC may have good prognosis even in the absence of chemotherapy. Distinct molecular subgroups within TNBC have been defined now as well. In case metastatic relapse occurs, this is usually within 5 years following surgery, and survival following metastatic relapse is shorter compared to other breast cancer subtypes; treatment options are few and responses lack durability. Novel drug targets and new biomarkers are needed to improve breast cancer care for patients presenting with TNBC. Further molecular/biological unraveling of TNBC is needed.