Personalized medicine: Present and future of breast cancer management

Genomic signatures in breast cancer in a real-world setting: Experience in a Brazilian Northeastern Center

OBJECTIVE

We aim to evaluate the indication and use of genomic signatures in breast cancer patients and outcomes who in patients undergoing adjuvant chemotherapy or not.

METHODS

This is a retrospective study of breast cancer patients managed in a private oncology clinic in Teresina, from November 2014 to February 2021. All patients with an indication of genomic signature were included. Clinical and pathological variables, use of genomic signatures, treatment and follow-up were obtained. The nomogram to predict Oncotype DX results (University of Tennessee Medical Center) was also calculated. Clinical risk calculation was based on MINDACT, using the modified version of Adjuvant Online. The genetic signatures performed were: the Oncotype, MammaPrint and EndoPredict.

RESULTS

Fifty (50) female patients were included in the study. The mean age of the participants was 57.1 years. Among the patients receiving a genomic signature (26-52.0%), there was a change in treatment in 8 (30.7%) cases. Chemotherapy was indicated in four patients, It was contraindicated in another four patients. Treatment changed in 30.7% of the tested patients. Chemotherapy was indicated for those who would not receive it before. It was contraindicated in patients who would previously undergo chemotherapy.

Implications of Agile Values in Software Engineering for Agility in Breast Cancer Treatment: Protocol for a Comparative Study

BACKGROUND

Breast cancer treatment has been described as a dynamic and patient-centered approach that emphasizes adaptability and flexibility throughout the treatment process. Breast cancer is complex, with varying subtypes and stages, making it important to tailor treatment plans to each patient's unique circumstances. Breast cancer treatment delivery relies on a multidisciplinary team of health care professionals who collaborate to provide personalized care and quick adaptation to changing conditions to optimize outcomes while minimizing side effects and maintaining the patient's quality of life. However, agility in breast cancer treatment has not been defined according to common agile values and described in language comprehensible to breast cancer professionals. In the rapidly evolving landscape of breast cancer treatment, the incorporation of agile values from software engineering promises to enhance patient care.

OBJECTIVE

Our objective is to propose agile values for breast cancer treatment adopted and adapted from software engineering. We also aim to validate how these values conform to the concept of agility in the breast cancer context through referencing past work.

METHODS

We applied a structured research methodology to identify and validate 4 agile values for breast cancer treatment. In the elicitation phase, through 2 interviews, we identified 4 agile values and described them in language that resonates with breast cancer treatment professionals. The values were then validated by a domain expert and discussed in the context of supporting work from the literature. Final validation entailed a domain expert conducting a walkthrough of the 4 identified agile values to adjust them as per the reported literature.

RESULTS

Four agile values were identified for breast cancer treatment, and among them, we validated 3 that conformed to the concept of agility. The fourth value, documentation and the quality of documentation, is vital for breast cancer treatment planning and management. This does not conform to agility. However, its nonagility is vital for the agility of the other values. None of the identified agile values were validated as partially conforming to the concept of agility.

CONCLUSIONS

This work makes a novel contribution to knowledge in identifying the first set of agile values in breast cancer treatment through multidisciplinary research. Three of these values were evaluated as conforming to the concept of agility, and although 1 value did not meet the concept of agility, it enhanced the agility of the other values. It is anticipated that these 4 agile values can drive oncology practice, strategies, policies, protocols, and procedures to enhance delivery of care. Moreover, the identified values contribute to identifying quality assurance and control practices to assess the concept of agility in oncology practice and breast cancer treatment and adjust corresponding actions. We conclude that breast cancer treatment agile values are not limited to 4.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/53124.

The potential roles of lncRNA TINCR in triple negative breast cancer

Triple negative breast cancer (TNBC) is the most aggressive intrinsic breast cancer subtype characterized by the lack of estrogen receptor (ER), progesterone receptor (PR), and low levels of human epidermal growth factor receptor 2 (HER2). The complex nature of TNBC has resulted in little therapeutic progress for the past several decades. The standard of care remains the FEC cocktail (5-fluorouracil (5-FU), epirubicin and cyclophosphamide). However, early relapse and metastasis in TNBC patients persists in causing dismal clinical outcomes. Due to complex heterogeneity features of TNBC, identifying the biomarker associated to the chemoresistance remains a challenge. The emergence of the long non-coding RNA (lncRNA) as a potential signature may have proven to be a new deterrent to diagnostic and treatment options. Previous studies unveiled the associations of lncRNA in the development of TNBCs whereby the aggressiveness and response to therapies may be associated by the abrogation of the molecular mechanism lncRNA. Terminal differentiation induced ncRNA (TINCR) is a lncRNA which have been linked with many cancers including TNBC. The expression and behavior of TINCR may exert unfavorable outcome in TNBCs. Nevertheless, the underlying molecular mechanism of TINCR in driving chemoresistance in TNBC is not well understood. This review will highlight the potential molecular mechanisms of TINCR in TNBC chemoresistance and how it can serve as a future potential prognostic and therapeutic target for a better treatment intervention.

Single-tablet-scale direct-compression: An on-demand manufacturing route for personalized tablets

Today's pharmaceutical industry is facing various challenges. Two of them are issues with supply chain security and the increasing demand for personalized medicine. Both can be addressed by increasing flexibility and a more decentralized approach to pharmaceutical manufacturing. In this study, we present a setup that provides flexibility in terms of supplied raw materials and the product, i.e., a direct-compression setup for personalized tablets operating at a single-tablet-scale. The performance of the implemented single-tablet-scale technology for dosing and mixing was investigated. In addition, an analysis of the critical quality attributes (CQAs) of immediate release ibuprofen and loratadine tablets was performed. The developed dosing device achieved acceptance rates of > 90 % for doses ≥ 20 mg for various pharmaceutical powders. Regarding the vibratory mixing process, a dependency of the performance on the applied frequencies and acceleration was observed, with 100 Hz and ∼ 90 G performing best, yet still exhibiting varying mixing efficacies depending on the granular system. The tablets produced met U.S. Pharmacopeia requirements regarding mechanical stability and dissolution characteristics. Given these results, we consider the developed setup a proof of concept of a tool to provide personalized tablets to patients while minimizing the dependency on complex supply chains.

Identification of Prognostic Biomarkers for Breast Cancer Metastasis Using Penalized Additive Hazards Regression Model

Background:

Breast cancer (BC) has been reported as one of the most common cancers diagnosed in females throughout the world. Survival rate of BC patients is affected by metastasis. So, exploring its underlying mechanisms and identifying related biomarkers to monitor BC relapse/recurrence using new statistical methods is essential. This study investigated the high-dimensional gene-expression profiles of BC patients using penalized additive hazards regression models.

Methods:

A publicly available dataset related to the time to metastasis in BC patients (GSE2034) was used. There was information of 22 283 genes expression profiles related to 286 BC patients. Penalized additive hazards regression models with different penalties, including LASSO, SCAD, SICA, MCP and Elastic net were used to identify metastasis related genes.

Results:

Five regression models with penalties were applied in the additive hazards model and jointly found 9 genes including SNU13, CLINT1, MAPK9, ABCC5, NKX3-1, NCOR2, COL2A1, and ZNF219. According the median of the prognostic index calculated using the regression coefficients of the penalized additive hazards model, the patients were labeled as high/low risk groups. A significant difference was detected in the survival curves of the identified groups. The selected genes were examined using validation data and were significantly associated with the hazard of metastasis.

Conclusion:

This study showed that MAPK9, NKX3-1, NCOR1, ABCC5, and CD44 are the potential recurrence and metastatic predictors in breast cancer and can be taken into account as candidates for further research in tumorigenesis, invasion, metastasis, and epithelial-mesenchymal transition of breast cancer.

An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients' Age: A Retrospective Cohort Study

Characterization of breast cancer into intrinsic molecular profiles has allowed women to live longer, undergoing personalized treatments. With the aim of investigating the relation between different values of ki67 and the predisposition to develop a breast cancer-related IDE at different ages, we enrolled 900 patients with a first diagnosis of invasive breast cancer, and we partitioned the dataset into two sub-samples with respect to an age value equal to 50 years. For each sample, we performed a Kaplan−Meier analysis to compare the IDE-free survival curves obtained with reference to different ki67 values. The analysis on patients under 50 years old resulted in a p-value < 0.001, highlighting how the behaviors of patients characterized by a ki67 ranging from 10% to 20% and greater than 20% were statistically significantly similar. Conversely, patients over 50 years old characterized by a ki67 ranging from 10% to 20% showed an IDE-free survival probability significantly greater than patients with a ki67 greater than 20%, with a p-value of 0.01. Our work shows that the adoption of two different ki67 values, namely, 10% and 20%, might be discriminant in designing personalized treatments for patients under 50 years old and over 50 years old, respectively.

‘Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics’

In recent times, enormous progress has been made in improving the diagnosis and therapeutic strategies for breast carcinoma, yet it remains the most prevalent cancer and second highest contributor to cancer-related deaths in women. Breast cancer (BC) affects one in eight females globally. In 2018 alone, 1.4 million cases were identified worldwide in postmenopausal women and 645,000 cases in premenopausal females, and this burden is constantly increasing. This shows that still a lot of efforts are required to discover therapeutic remedies for this disease. One of the major clinical complications associated with the treatment of breast carcinoma is the development of therapeutic resistance. Multidrug resistance (MDR) and consequent relapse on therapy are prevalent issues related to breast carcinoma; it is due to our incomplete understanding of the molecular mechanisms of breast carcinoma disease. Therefore, elucidating the molecular mechanisms involved in drug resistance is critical. For management of breast carcinoma, the treatment decision not only depends on the assessment of prognosis factors but also on the evaluation of pathological and clinical factors. Integrated data assessments of these multiple factors of breast carcinoma through multiomics can provide significant insight and hope for making therapeutic decisions. This omics approach is particularly helpful since it identifies the biomarkers of disease progression and treatment progress by collective characterization and quantification of pools of biological molecules within and among the cancerous cells. The scrupulous understanding of cancer and its treatment at the molecular level led to the concept of a personalized approach, which is one of the most significant advancements in modern oncology. Likewise, there are certain genetic and non-genetic tests available for BC which can help in personalized therapy. Genetically inherited risks can be screened for personal predisposition to BC, and genetic changes or variations (mutations) can also be identified to decide on the best treatment. Ultimately, further understanding of BC at the molecular level (multiomics) will define more precise choices in personalized medicine. In this review, we have summarized therapeutic resistance associated with BC and the techniques used for its management.

Extracellular vesicles extracted from bone marrow mesenchymal stem cells carrying MicroRNA-342-3p inhibit the INHBA/IL13Rα2 axis to suppress the growth and metastasis of breast cancer

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BMSC-EVs carrying miR-342-3p could prevent breast cancer growth and metastasis by downregulating the INHBA/IL13Rα2 axis, highlighting a potential target for anti-cancer treatment for breast cancer.

Increasing focus has come to the role of extracellular vesicles (EVs) in various cancers. Hence, we designed this study to explore the mechanism whereby microRNA-342-3p (miR-342-3p)-containing EVs derived from BMSCs might affect breast cancer. MCF-7 breast cancer cell line was co-incubated with the EVs isolated from rat BMSCs, followed by alteration of miR-342-3p and INHBA expression. Microarray-based analyses predicted a possible regulatory mechanism involving miR-342-3p, INHBA, and IL13Rα2 in breast cancer, which was verified by luciferase reporter, RNA pull-down, and RIP assays. Besides, in order to evaluate the effects of miR-342-3p on the biological features of breast cancer cells in vitro and in vivo, we employed the scratch assay, Transwell assay, CCK-8 assay, and nude mouse tumorigenicity assay. miR-342-3p carried by BMSC-EVs was transferred into breast cancer cells through co-culture, which inhibited the proliferation and metastasis of breast cancer cells in vitro. miR-342-3p downregulated the expression of INHBA, which further repressed the expression of IL13Rα2. Finally, the in vivo experimental results revealed the inhibitory role of miR-342-3p in tumor growth and metastasis in nude mice. To sum up, BMSC-EVs carrying miR-342-3p could prevent breast cancer growth and metastasis by downregulating the INHBA/IL13Rα2 axis, highlighting a potential target for anti-cancer treatment for breast cancer.

Illness Perception and Quality of Life in Patients with Breast Cancer

Simple Summary

The declining average age of cancer patients may become a serious problem for health care systems and societies in general in the near future. For this reason, there is a need to fully understand the factors determining health-related quality of life in breast cancer patients, beyond clinical characteristics and sociodemographic factors. In our study, we aimed to demonstrate the relationship between illness perception and quality of life in breast cancer patients. The results of our study confirm the beneficial effect of positive illness perception on the intensity of symptoms related to cancer and treatment, as well as functional domains of EORTC QLQ-C30.

Abstract

Introduction. In 2020, breast cancer was the most frequently diagnosed malignancy worldwide. The QoL level plays a role in assessing the effectiveness of the diagnosis and therapy and is a significant prognostic factor. The subject that is relatively less often addressed in the literature is the impact of psycho-social factors and health-related beliefs on QoL in breast cancer patients. The aim of the study was to assess the association of illness perception, the sense of coherence, and illness acceptance with QoL in breast cancer patients. Methods. The study included 202 women (mean age 53.0 ± 10.3) treated surgically for breast cancer at the Lower Silesian Oncology Centre. The following standardized questionnaires were used: Acceptance of Illness Scale (AIS), Mental Adjustment to Cancer (Mini-MAC), Quality of Life Questionnaires (EORTC QLQ-C30 and QLQ-BR23), The Multidimensional Essence of Disease and Illness Scale (MEDIS), and Life Orientation Test (LOT-R). Results. There is a statistically significant association between illness acceptance and QoL. There is a statistically significant association between the sense of coherence (life optimism—LOT-R) and QoL among breast cancer patients. There is a statistically significant association between illness perception and QoL. There was a statistically significant correlation between the increasing importance of illness as a dysfunction, decreasing QoL, and increasing intensity of symptoms and complaints. Conclusions. Patients with a high level of illness acceptance, with an optimistic disposition, and with a positive illness perception have better QoL within all the functional domains and experience lower intensity of cancer- and treatment-related symptoms as compared to those with low level of illness acceptance, with moderate optimism or a pessimistic disposition, and with neutral or negative illness perception.

DNMT1 facilitates growth of breast cancer by inducing MEG3 hyper-methylation

Background

To understand the effect of DNMT1-mediated MEG3 promoter methylation on breast cancer progression.

Methods

Expression of DNMT1, MEG3 and miR-494-3p was assayed by qRT-PCR and western blot. Methylation-specific PCR was used to examine MEG3 promoter methylation level. ChIP, RNA binding protein immunoprecipitation assay and dual-luciferase reporter gene assay were applied to verify interaction between DNMT1 and MEG3, miR-494-3p and MEG3 and OTUD4. CCK-8, wound healing and Transwell assays were used to detect biological functions of breast cancer cells. Tumor growth was observed by tumor xenograft model.

Results

DNMT1 and miR-494-3p were highly expressed while MEG3 and OTUD4 were lowly expressed in breast cancer cells. Knockdown of DNMT1 inhibited progression of breast cancer cells by enhance MEG3 expression through demethylation. MEG3 could downregulate miR-494-3p expression, and OTUD4 was a target of miR-494-3p. Upregulation of MEG3 and downregulation of miR-494-3p both inhibited malignant behavior of cells in vitro. In addition, high MEG3 expression restrained growth of breast cancer in vivo.

Conclusion

Briefly, our results demonstrated that, DNMT1 induced methylation of MEG3 promoter, and played a key role in breast cancer growth throughmiR-494-3p/OTUD4 axis. These findings provide new insights into molecular therapeutic targets for breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02463-8.

Data-Driven Modeling of Breast Cancer Tumors Using Boolean Networks

Cancer is a genomic disease involving various intertwined pathways with complex cross-communication links. Conceptually, this complex interconnected system forms a network, which allows one to model the dynamic behavior of the elements that characterize it to describe the entire system’s development in its various evolutionary stages of carcinogenesis. Knowing the activation or inhibition status of the genes that make up the network during its temporal evolution is necessary for the rational intervention on the critical factors for controlling the system’s dynamic evolution. In this report, we proposed a methodology for building data-driven boolean networks that model breast cancer tumors. We defined the network components and topology based on gene expression data from RNA-seq of breast cancer cell lines. We used a Boolean logic formalism to describe the network dynamics. The combination of single-cell RNA-seq and interactome data enabled us to study the dynamics of malignant subnetworks of up-regulated genes. First, we used the same Boolean function construction scheme for each network node, based on canalyzing functions. Using single-cell breast cancer datasets from The Cancer Genome Atlas, we applied a binarization algorithm. The binarized version of scRNA-seq data allowed identifying attractors specific to patients and critical genes related to each breast cancer subtype. The model proposed in this report may serve as a basis for a methodology to detect critical genes involved in malignant attractor stability, whose inhibition could have potential applications in cancer theranostics.

The CINSARC signature predicts the clinical outcome in patients with Luminal B breast cancer

CINSARC, a multigene expression signature originally developed in sarcomas, was shown to have prognostic impact in various cancers. We tested the prognostic value for disease-free survival (DFS) of CINSARC in a series of 6035 early-stage invasive primary breast cancers. CINSARC had independent prognostic value in the Luminal B subtype and not in the other subtypes. In Luminal B patients receiving adjuvant endocrine therapy but no chemotherapy, CINSARC identified patients with different 5-year DFS (90% [95%CI 86-95] in low-risk vs. 79% [95%CI 75-84] in high-risk, p = 1.04E-02). Luminal B CINSARC high-risk tumors were predicted to be less sensitive to endocrine therapy and CDK4/6 inhibitors, but more vulnerable to homologous recombination targeting and immunotherapy. We concluded that CINSARC adds prognostic information to that of clinicopathological features in Luminal B breast cancers, which might improve patients' stratification and better orient adjuvant treatment. Moreover, it identifies potential therapeutic avenues in this aggressive molecular subtype.

Starvation stress attenuates the miRNA-target interaction in suppressing breast cancer cell proliferation

Background

Emerging evidence has demonstrated the limited access to metabolic substrates as an effective approach to block cancer cell growth. The mechanisms remain unclear. Our previous work has revealed that miR-221/222 plays important role in regulating breast cancer development and progression through interaction with target gene p27.

Results

Herein, we determined the miRNA-mRNA interaction in breast cancer cells under induced stress status of starvation. Starvation stimulation attenuated the miR-221/222-p27 interaction in MDA-MB-231 cells, thereby increased p27 expression and suppressed cell proliferation. Through overexpression or knockdown of miR-221/222, we found that starvation-induced stress attenuated the negative regulation of p27 expression by miR-221/222. Similar patterns for miRNA-target mRNA interaction were observed between miR-17-5p and CyclinD1, and between mR-155 and Socs1. Expression of Ago2, one of the key components of RNA-induced silencing complex (RISC), was decreased under starvation-induced stress status, which took responsibility for the impaired miRNA-target interaction since addition of exogenous Ago2 into MDA-MB-231 cells restored the miR-221/222-p27 interaction in starvation condition.

Conclusions

We demonstrated the attenuated interaction between miR-221/222 and p27 by starvation-induced stress in MDA-MB-231 breast cancer cells. The findings add a new page to the general knowledge of negative regulation of gene expression by miRNAs, also demonstrate a novel mechanism through which limited access to nutrients suppresses cancer cell proliferation. These insights provide a basis for development of novel therapeutic options for breast cancer.

Performance evaluation of texture analysis based on kinetic parametric maps from breast DCE-MRI in classifying benign from malignant lesions

BACKGROUND AND OBJECTIVES

To investigate the performance of texture analysis based on enhancement kinetic parametric maps derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in discriminating benign from malignant tumors.

METHODS

A total of 192 cases confirmed by histopathology were retrospectively selected from our Picture Archiving and Communication System, including 93 benign and 99 malignant tumors. Lesion areas were delineated semi-automatically, and six kinetic parametric maps reflecting the perfusion information were generated, namely the maximum slope of increase (MSI), slope of signal intensity (SI_slope ), initial percentage of peak enhancement (E_initial ), percentage of peak enhancement (E_peak ), early signal enhancement ratio (ESER), and second enhancement percentage (SEP) maps. A total of 286 texture features were extracted from those quantitative parametric maps. The Student t test or Mann-Whitney U test was used to select features that were statistically significantly different between the benign and malignant groups. A support vector machine was employed with a leave-one-out cross-validation method to establish the classification model. Classification performance was evaluated according to the receiver operating characteristic (ROC) theory.

RESULTS

The areas under ROC curves (AUCs) indicating the diagnostic performance were 0.925 for MSI, 0.854 for SI_slope , 0.756 for E_initial , 0.923 for E_peak , 0.871 for ESER and 0.881 for SEP. Significant differences in AUCs were found between E_initial vs MSI, E_initial vs E_peak and E_initial vs SEP (P < .05). There were no significant differences in other pairwise comparisons.

CONCLUSION

Texture analysis of the kinetic parametric maps derived from breast DCE-MRI can contribute to the discrimination between malignant and benign lesions. It can be considered as a supplementary tool for breast diagnosis.

Application of St Gallen Categories in Predicting Survival for Patients With Breast Cancer in Vietnam

Breast cancer is a heterogeneous disease with different tumor subtypes. Identifying risk categories will help make better treatment decisions. Hence, this study aimed to predict the survival outcomes of invasive breast cancer in Vietnam, using St Gallen 2007 classification. This study was conducted on 501 patients with breast cancer who had surgical operations, but had not received neoadjuvant chemotherapy, from 2011 to 2013. The clinicopathological characteristics were recorded. Immunohistochemistry staining was performed on ER, PR, HER2/neu, and Ki67 markers. For HER2/neu(2+), fluorescence in situ hybridization was used as the test. All patients with breast cancer were stratified according to 2007 St Gallen categories. Kaplan-Meier and log-rank models were used to analyze survival rates. There were 3.8% cases classified as low risk (LR), 72.1% as intermediate risk (IR1: 60.1% and IR2: 12.0%), and 24.1% as high risk (HR1: 11.8% and HR2: 12.3%). Patients who were LR had the best prognosis, with a 5-year overall survival (OS) rate of 100%. Intermediate-risk patients were at 92.3%. High-risk patients had the worst prognosis, with a 5-year OS proportion of 69.3% (P < .05). For disease-free survival (DFS), risk categories were categorized as LR: 100%, IR: 90.3%, and HR: 69.3% (P < .05). Three main risk categories of breast cancer had a distinct OS and DFS. These findings suggest that the 2007 St Gallen risk category could be used to stratify patients with breast cancer into different risk groups in Vietnam.

Influence of E-cadherin genetic variation in canine mammary tumour risk, clinicopathological features and prognosis

E-cadherin is a cell adhesion molecule that participates in several cellular processes that guarantee the maintenance of structural and functional integrity of epithelial tissues. E-cadherin plays an important role in mammary carcinogenesis, and various studies have demonstrated the effect of CDH1 genetic variation in risk, progression and biological behaviour of human breast cancer. Although there are some recognized genetic variations in canine CDH1 gene, their influence in canine mammary tumour development and progression has not been previously evaluated. In this study, we aim to assess the influence of CDH1 SNPs rs850805755, rs852280880 and rs852639930 in the risk, clinicopathological features and clinical outcome of canine mammary tumours. A case-control study was conducted involving 206 bitches with mammary tumours and 161 bitches free of mammary neoplasia. CDH1 SNPs rs850805755 and rs852280880 were associated with a decreased risk and a later onset of mammary tumour development. Furthermore, these SNPs were related to the development of small size carcinomas, of low histological grade and low nuclear pleomorphism. SNP rs852639930 was associated with the development of small size tumours with a non-infiltrative, non-invasive growth pattern. Data from the present investigation demonstrate that these CDH1 genetic variants could have a protective role in canine mammary tumours, by being associated with low risk of tumour development, delayed onset of the disease and less aggressive clinicopathological features.

Impact of 21-Gene Recurrence Score on Chemotherapy Decision in Invasive Ductal Carcinoma of Breast with Nodal Micrometastases

Purpose

The purpose of this study was to investigate the effect of 21-gene recurrence score (RS) on predicting prognosis and chemotherapy decision in node micrometastases (N1mi) breast invasive ductal carcinoma (IDC).

Methods

Patients with stage T1-2N1mi and estrogen receptor-positive IDC diagnosed between 2004 and 2015 were included. The associations of 21-gene RS with breast cancer-specific survival (BCSS), chemotherapy decision, and benefit of chemotherapy were analyzed.

Results

We identified 4,758 patients including 1,403 patients (29.5%) treated with adjuvant chemotherapy. In the traditional RS cutoffs, 2,831 (59.5%), 1,634 (34.3%), and 293 (6.2%) patients were in the low-, intermediate-, and high-risk RS groups, respectively. In 3,853 patients with human epidermal growth factor receptor-2 (HER2) status available, most patients were HER2-negative disease (98.3%). A higher RS was independently related to chemotherapy receipt, and 14.0%, 47.7%, and 77.8% of patients in the low-, intermediate-, and high-risk RS groups received chemotherapy, respectively. The multivariate analysis indicated that a higher RS was related to worse BCSS (p < 0.001). The 5-year BCSS rates were 99.3%, 97.4%, and 91.9% in patients with low-, intermediate-, and high-risk RS groups, respectively (p < 0.001). However, chemotherapy receipt did not correlate with better BCSS in low-, intermediate-, or high-risk RS groups. There were similar trends using Trial Assigning Individualized Options for Treatment RS cutoffs.

Conclusion

The 21-gene RS does predict outcome and impact on chemotherapy decision of N1mi breast IDC. Large cohort and long-term outcomes studies are needed to identify the effects of chemotherapy in N1mi patients by different 21-gene RS groups.

Role of texture analysis in breast MRI as a cancer biomarker: A review

Breast cancer is a known heterogeneous disease. Current clinically utilized histopathologic biomarkers may undersample tumor heterogeneity, resulting in higher rates of misdiagnosis for breast cancer. MRI can provide a whole-tumor sampling of disease burden and is widely utilized in clinical care. Texture analysis can provide a localized description of breast cancer, with particular emphasis on quantifying breast lesion heterogeneity. The object of this review is to provide an overview of texture analysis applications towards breast cancer diagnosis, prognosis, and treatment response evaluation and review the role of image-based texture features as noninvasive prognostic and predictive biomarkers. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:927-938.

The immunologic constant of rejection classification refines the prognostic value of conventional prognostic signatures in breast cancer

Background

The immunologic constant of rejection (ICR) is a broad phenomenon of Th-1 immunity-mediated, tissue-specific destruction.

Methods

We tested the prognostic value of a 20-gene ICR expression signature in 8766 early breast cancers.

Results

Thirty-three percent of tumours were ICR1, 29% ICR2, 23% ICR3, and 15% ICR4. In univariate analysis, ICR4 was associated with a 36% reduction in risk of metastatic relapse when compared with ICR1-3 (p = 2.30E–03). In multivariate analysis including notably the three major prognostic signatures (Recurrence score, 70-gene signature, ROR-P), ICR was the strongest predictive variable (p = 9.80E–04). ICR showed no prognostic value in the HR+/HER2− subtype, but prognostic value in the HER2+ and TN subtypes. Furthermore, in each molecular subtype and among the tumours defined as high risk by the three prognostic signatures, ICR4 patients had a 41–75% reduction in risk of relapse as compared with ICR1-3 patients. ICR added significant prognostic information to that provided by the clinico-genomic models in the overall population and in each molecular subtype. ICR4 was independently associated with achievement of pathological complete response to neoadjuvant chemotherapy (p = 2.97E–04).

Conclusion

ICR signature adds prognostic information to that of current proliferation-based signatures, with which it could be integrated to improve patients’ stratification and guide adjuvant treatment.

Predicting efficacy of epirubicin by a multigene assay in advanced breast cancer within a Danish Breast Cancer Cooperative Group (DBCG) cohort: a retrospective-prospective blinded study

Purpose

Anthracyclines remain a cornerstone in the treatment of primary and advanced breast cancer (BC). This study has evaluated the predictive value of a multigene mRNA-based drug response predictor (DRP) in the treatment of advanced BC with epirubicin. The DRP is a mathematical method combining in vitro sensitivity and gene expression with clinical genetic information from > 3000 clinical tumor samples.

Methods

From a DBCG cohort, 140 consecutive patients were treated with epirubicin between May 1997 and November 2016. After patient informed consent, mRNA was isolated from archival formalin-fixed paraffin-embedded primary breast tumor tissue and analyzed using Affymetrix arrays. Using time to progression (TTP) as primary endpoint, the efficacy of epirubicin was analyzed according to DRP combined with clinicopathological data collected retrospectively from patients’ medical records. Statistical analysis was done using Cox proportional hazards model stratified by treatment line.

Results

Median TTP was 9.3 months. The DRP was significantly associated to TTP (P = 0.03). The hazard ratio for DRP scores differing by 50 percentage points was 0.55 (95% CI –0.93, one-sided). A 75% DRP was associated with a median TTP of 13 months compared to 7 months following a 25% DRP. Multivariate analysis showed that DRP was independent of age and number of metastases.

Conclusion

The current study prospectively validates the predictive capability of DRP regarding epirubicin previously shown retrospectively allowing the patients predicted to be poor responders to choose more effective alternatives. Randomized prospective studies are needed to demonstrate if such an approach will lead to increased overall survival.

Budget impact analysis of gene expression tests to aid therapy decisions for breast cancer patients in Germany

OBJECTIVES

Many women with early-stage, hormone receptor-positive breast cancer may not benefit from adjuvant chemotherapy. Gene expression tests can reduce chemotherapy over- and undertreatment by providing prognostic information on the likelihood of recurrence and, with Oncotype DX, predictive information on chemotherapy benefit. These tests are currently not reimbursed by German healthcare payers. An analysis was conducted to evaluate the budget impact of gene expression tests in Germany.

MATERIALS AND METHODS

Costs of gene expression tests and medical and non-medical costs associated with treatment were assessed from healthcare payer and societal perspectives. Costs were estimated from data collected at a university hospital and were combined with decision impact data for Oncotype DX, MammaPrint, Prosigna and EndoPredict (EPclin). Changes in chemotherapy use and budget impact were evaluated over 1 year for 20,000 women.

RESULTS

Chemotherapy was associated with substantial annual costs of EUR 19,003 and EUR 84,412 per therapy from the healthcare payer and societal perspective, respectively. Compared with standard care, only Oncotype DX was associated with cost savings to healthcare payers and society (EUR 5.9 million and EUR 253 million, respectively). Scenario analysis showed that both women at high clinical but low genomic risk and low clinical but high genomic risk were important contributors to costs.

CONCLUSIONS

Oncotype DX was the only gene expression test that was estimated to reduce costs versus standard care in Germany. The reimbursement of Oncotype DX testing in standard clinical practice in Germany should be considered.

Mammalian sterile 20-like kinase 1 expression and its prognostic significance in patients with breast cancer

Mammalian sterile 20-like kinase 1 (Mst1) is a major inhibitor of cell proliferation, and is involved in apoptosis, oncogenesis and organ growth via its ubiquitously encoded serine threonine kinase. Previous studies have demonstrated that Mst1 has a tumor suppressor function in human breast cancer. Mst1 deletion or mutation is associated with tumorigenesis, whereas Mst1 overexpression leads to tumor cell apoptosis and decreases proliferation of tumor cells. Our previous study reported the tumor suppressive function of Mst1, and debated Mst1 as a prognostic factor in human breast cancer. In the present study, Mst1 levels were measured in the plasma of patients in order to elucidate their association with overall and disease-free survival. The results of the present study indicated that Mst1 is a strong prognostic and predictive factor in human breast cancer and a promising anticancer target.

The NuRD complex-mediated p21 suppression facilitates chemoresistance in BRCA-proficient breast cancer

The Mi-2/nucleosome remodeling and deacetylase (NuRD) complex play a role in silencing gene expression. CHD4, the core component of the NuRD complex, which cooperates with histone deacetylase in reducing tumor suppressor genes (TSGs). To dissect the mechanisms underlying cancer promotion, we clarify the role of CHD4 in cyclin-dependent kinase inhibitor protein p21. Here, our data indicates that CHD4 deficiency impairs the recruitments of HDAC1 to the p21 promoter. ~ 300bp proximal promoter region is responsible for CHD4-HDAC1 axis-mediated p21 transcriptional activity. For identifying the role of anti-cancer drug response, knockdown of p21 overcomes cisplatin and poly-(ADP-ribose) polymerase (PARP) inhibitor-mediated growth suppression in CHD4-depleted cells. Consistent with in vitro data, tissue of patients and bioinformatics approach also showed positive correlation between CHD4 and p21. Overall, our findings not only identify that CHD4 deficiency preferentially impairs cell survival via increasing the level of p21, but also establishes targeting CHD4 as a potential therapeutic implication in BRCA-proficient breast cancer treatment.

Impact of Oncotype DX breast Recurrence Score testing on adjuvant chemotherapy use in early breast cancer: Real world experience in Greater Manchester, UK

BACKGROUND

The National Institute for Health and Clinical Excellence (NICE) recommended the Oncotype DX^® Breast Recurrence Score^® (RS) assay as an option for informing adjuvant chemotherapy decisions in node-negative, oestrogen receptor (ER)+, human epidermal growth factor receptor 2 (HER2)-negative early breast cancer assessed to be at intermediate risk of recurrence based on clinicopathological factors. We evaluated the impact of RS testing on adjuvant chemotherapy decision-making in routine clinical practice in a UK Cancer Network.

METHODS

RS testing was performed in 201 females with newly diagnosed, ER+, HER2-negative, invasive breast cancer who underwent breast surgery with curative intent, were calculated to have a >3% overall survival benefit at 10 years from adjuvant chemotherapy based on PREDICT, and were considered for adjuvant chemotherapy. The impact of RS testing on adjuvant treatment decisions/associated cost was assessed.

RESULTS

In all patients, the multi-disciplinary team recommended chemotherapy but the RS result allowed 127/201 patients (63.2%) to avoid unnecessary adjuvant chemotherapy. Amongst ER+, HER2-negative, node-negative patients (eligible for Oncotype DX testing in UK guidelines), 60.3% were spared chemotherapy. In node-positive patients, the assay reduced the use of chemotherapy by 69.2%. The use of RS testing to guide treatment in these 201 patients was associated with significant cost saving (when considering the cost of RS testing for all patients plus chemotherapy and its associated cost for 74 patients).

CONCLUSIONS

Incorporating RS testing into routine clinical practice for selected node-negative and node-positive breast cancer patients significantly reduces the use of chemotherapy (p < 0.001) with its associated morbidity and costs.

An integrative transcriptomics approach identifies miR-503 as a candidate master regulator of the estrogen response in MCF-7 breast cancer cells

Estrogen receptor α (ERα) is an important biomarker of breast cancer severity and a common therapeutic target. In response to estrogen, ERα stimulates a dynamic transcriptional program including both coding and noncoding RNAs. We generate a fine-scale map of expression dynamics by performing a temporal profiling of both messenger RNAs (mRNAs) and microRNAs (miRNAs) in MCF-7 cells (an ER+ model cell line for breast cancer) in response to estrogen stimulation. We identified three primary expression trends-transient, induced, and repressed-that were each enriched for genes with distinct cellular functions. Integrative analysis of mRNA and miRNA temporal expression profiles identified miR-503 as the strongest candidate master regulator of the estrogen response, in part through suppression of ZNF217-an oncogene that is frequently amplified in cancer. We confirmed experimentally that miR-503 directly targets ZNF217 and that overexpression of miR-503 suppresses MCF-7 cell proliferation. Moreover, the levels of ZNF217 and miR-503 are associated with opposite outcomes in breast cancer patient cohorts, with high expression of ZNF217 associated with poor survival and high expression of miR-503 associated with improved survival. Overall, these data indicate that miR-503 acts as a potent estrogen-induced candidate tumor suppressor miRNA that opposes cellular proliferation and has promise as a novel therapeutic for breast cancer. More generally, our work provides a systems-level framework for identifying functional interactions that shape the temporal dynamics of gene expression.

A novel technology for multiplex gene expression analysis directly from whole blood samples stabilized at ambient temperature using an RNA-stabilizing buffer

We describe a novel method, based on target-dependent chemical ligation of probes, which simplifies the multiplexed quantitation of gene expression from blood samples by eliminating the RNA purification step. Gene expression from seven genes was evaluated over a range of sample inputs (16.7 to 0.25 μL of whole blood in serial dilutions) from three healthy donors. Mean CVs were ≤11% for five technical replicates for whole blood inputs ≥2.1 μL. The method showed a limit of detection of 300 copies of RNA by using titration of in vitro transcripts for four genes. Gene expression measured on stabilized blood samples was highly correlated (Spearman rank correlation method, ρ = 0.80) to gene expression results obtained with RNA isolated from matched samples (three donors, five technical replicates). Gene expression changes determined with seven radiation-responsive genes on six healthy donor blood samples before and after ex vivo irradiation were highly correlated (ρ = 0.93) to those measured with a TaqMan quantitative real-time RT-PCR assay on RNA purified from matched samples. Thus, this method is reproducible, sensitive, and correlated to quantitative real-time RT-PCR and may be used to streamline the multiplex gene expression analysis of large numbers of stabilized blood samples without RNA purification.

Somatic microsatellite variability as a predictive marker for colorectal cancer and liver cancer progression

Microsatellites (MSTs) are short tandem repeated genetic motifs that comprise ~3% of the genome. MST instability (MSI), defined as acquired/lost primary alleles at a small subset of microsatellite loci (e.g. Bethesda markers), is a clinically relevant marker for colorectal cancer. However, these markers are not applicable to other types of cancers, specifically, for liver cancer which has a high mortality rate. Here we show that somatic MST variability (SMV), defined as the presence of additional, non-primary (aka minor) alleles at MST loci, is a complementary measure of MSI, and a genetic marker for colorectal and liver cancer. Re-analysis of Illumina sequenced exomes from The Cancer Genome Atlas indicates that SMV may distinguish a subpopulation of African American patients with colorectal cancer, which represents ~33% of the population in this study. Further, for liver cancer, a higher rate of SMV may be indicative of an earlier age of onset. The work presented here suggests that classical MSI should be expanded to include SMV, going beyond alterations of the primary alleles at a small number of microsatellite loci. This measure of SMV may represent a potential new diagnostic for a variety of cancers and may provide new information for colorectal cancer patients.

Transcriptomics in cancer diagnostics: developments in technology, clinical research and commercialization

Transcriptomic technologies are evolving to diagnose cancer earlier and more accurately to provide greater predictive and prognostic utility to oncologists and patients. Digital techniques such as RNA sequencing are replacing still-imaging techniques to provide more detailed analysis of the transcriptome and aberrant expression that causes oncogenesis, while companion diagnostics are developing to determine the likely effectiveness of targeted treatments. This article examines recent advancements in molecular profiling research and technology as applied to cancer diagnosis, clinical applications and predictions for the future of personalized medicine in oncology.

Discovery of New Acid Ceramidase-Targeted Acyclic 5-Alkynyl and 5-Heteroaryl Uracil Nucleosides

A series of novel N-acyclic uracil analogs with linear, branched, aromatic, and cyclopropyl-alkynyl as well as heteroaryl moieties at C-5 were prepared using palladium catalyzed Sonogashira and Stille cross-coupling and evaluated against malignant tumor cell lines. C-5-Furan-2-yl uracil derivative 6 was shown to be more potent against MCF-7 than the reference drug 5-fluorouracil (5-FU), while C-5-alkynyl uracil derivatives 9c and 9e exhibited antibreast cancer activities comparable to 5-FU. Selected compounds induced cell death, partially due to apoptosis, of MCF-7 breast cancer cells. Abrogation of acid ceramidase (ASAH1) expression of 9c and 9e indicated that these compounds could perturb ASAH1-mediated sphingolipid signaling. The selective activity of 9c and 9e against breast cancer cells via the ASAH1-mediated signaling, as a molecular target, might have a great advantage for potential future therapeutic use.

Addressing challenges of heterogeneous tumor treatment through bispecific protein-mediated pretargeted drug delivery

Tumors are frequently characterized by genomically and phenotypically distinct cancer cell subpopulations within the same tumor or between tumor lesions, a phenomenon termed tumor heterogeneity. These diverse cancer cell populations pose a major challenge to targeted delivery of diagnostic and/or therapeutic agents, as the conventional approach of conjugating individual ligands to nanoparticles is often unable to facilitate intracellular delivery to the full spectrum of cancer cells present in a given tumor lesion or patient. As a result, many cancers are only partially suppressed, leading to eventual tumor regrowth and/or the development of drug-resistant tumors. Pretargeting (multistep targeting) approaches involving the administration of 1) a cocktail of bispecific proteins that can collectively bind to the entirety of a mixed tumor population followed by 2) nanoparticles containing therapeutic and/or diagnostic agents that can bind to the bispecific proteins accumulated on the surface of target cells offer the potential to overcome many of the challenges associated with drug delivery to heterogeneous tumors. Despite its considerable success in improving the efficacy of radioimmunotherapy, the pretargeting strategy remains underexplored for a majority of nanoparticle therapeutic applications, especially for targeted delivery to heterogeneous tumors. In this review, we will present concepts in tumor heterogeneity, the shortcomings of conventional targeted systems, lessons learned from pretargeted radioimmunotherapy, and important considerations for harnessing the pretargeting strategy to improve nanoparticle delivery to heterogeneous tumors.

Aberrant RNA homeostasis in amyotrophic lateral sclerosis: potential for new therapeutic targets?

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive motor neuron degeneration. The disease pathogenesis is multifaceted in that multiple cellular and molecular pathways have been identified as contributors to the disease progression. Consequently, numerous therapeutic targets have been pursued for clinical development, unfortunately with little success. The recent discovery of mutations in RNA modulating genes such as TARDBP/TDP-43, FUS/TLS or C9ORF72 changed our understanding of neurodegenerative mechanisms in ALS and introduced the role of dysfunctional RNA processing as a significant contributor to disease pathogenesis. This article discusses the latest findings on such RNA toxicity pathways in ALS and potential novel therapeutic approaches.

Analysis of the intricate relationship between chronic inflammation and cancer

Deregulated inflammatory response plays a pivotal role in the initiation, development and progression of tumours. Potential molecular mechanism(s) that drive the establishment of an inflammatory-tumour microenvironment is not entirely understood owing to the complex cross-talk between pro-inflammatory and tumorigenic mediators such as cytokines, chemokines, oncogenes, enzymes, transcription factors and immune cells. These molecular mediators are critical linchpins between inflammation and cancer, and their activation and/or deactivation are influenced by both extrinsic (i.e. environmental and lifestyle) and intrinsic (i.e. hereditary) factors. At present, the research pertaining to inflammation-associated cancers is accumulating at an exponential rate. Interest stems from hope that new therapeutic strategies against molecular mediators can be identified to assist in cancer treatment and patient management. The present review outlines the various molecular and cellular inflammatory mediators responsible for tumour initiation, progression and development, and discusses the critical role of chronic inflammation in tumorigenesis.

[Trends and evolutions of French breast cancer research: a bibliometric study]

This article presents a bibliometric study carried out in order to describe the trends and evolutions of French breast cancer research from 2003 to 2013. The results show an increase in the number of publications, especially international publications coordinated by non-French institutions. The most visible topics, in terms of number of publications by keywords, are related to biology, clinical trials and genetics. Most publications are written by authors affiliated to comprehensive cancer centres, followed by universities, research centres, university hospitals and governmental agencies. The importance of publications by topic varies throughout the years: there has been an increase of the number of publications related to targeted therapies or genomics. The importance of institutions or country affiliation of authors varies with the topics. This study, especially the analysis by keywords, enables the coordinators of research programs to identify the predominant actors and themes.

Dual specificity phosphatase 4 gene expression in association with triple-negative breast cancer outcome

Triple-negative breast cancer (TNBC) is an aggressive cancer with limited treatment options. Dual specificity phosphatase 4 (DUSP4) has recently been suggested as a potential marker of chemotherapy resistance for TNBC. DUSP4 gene expression levels were measured in breast cancer tissue from 469 TNBC patients aged 20-75 years who participated in the Shanghai Breast Cancer Survival Study, and their association with recurrence/breast cancer mortality and total mortality was evaluated. Information on breast cancer diagnosis, treatment, and disease progression was collected via medical chart review and multiple in-person follow-up surveys. A Cox regression model was applied in the data analyses. Over a median follow-up of 5.3 years (range: 0.7-8.9 years), 100 deaths and 92 recurrences/breast cancer deaths were documented. Expression levels of transcript variant 1 (NM_001394) and transcript variant 2 (NM_057158) of the DUSP4 gene were studied and were highly correlated (r = 0.76). Low DUSP4 expression levels, particularly of variant 1, were associated with both increased recurrence/breast cancer mortality and increased overall mortality. Hazard ratios with adjustment for age at diagnosis and TNM stage associated with below versus above the median expression level were 1.97 (95 % confidence interval (CI): 1.27-3.05) for recurrence/breast cancer mortality and 2.09 (95 % CI: 1.38-3.17) for overall mortality. Additional adjustment for expression levels of MKI67 and TP53, common treatment types, breast cancer subtype, and grade did not materially alter the observed associations. Low DUSP4 expression levels predict recurrence and mortality in TNBC patients independently from known clinical and molecular predictors.

EndoPredict predicts for the response to neoadjuvant chemotherapy in ER-positive, HER2-negative breast cancer

The EndoPredict (EP) signature is a prognostic 11-gene expression signature specifically developed in ER+/HER2- node-negative/positive breast cancer. It is associated with relapse-free survival in patients treated with adjuvant hormone therapy, suggesting that EP low-risk patients could be treated with adjuvant hormone therapy alone whereas high-risk patients would deserve addition of adjuvant chemotherapy. Thus, it is important to determine whether EP high-risk patients are or are not more sensitive to chemotherapy than low-risk patients. Here, we have assessed the EP predictive value for pathological complete response to neoadjuvant chemotherapy in ER+/HER2- breast cancer. We gathered gene expression and histoclinical data of 553 pre-treatment ER+/HER2- breast carcinomas treated with anthracycline-based neoadjuvant chemotherapy. We searched for correlation between the pathological complete response (pCR) and the EP score-based classification. The overall pCR rate was 12%. Fifty-one percent of samples were classified as low-risk according to the EP score and 49% as high-risk. EP classification was associated with a pCR rate of 7% in the low-risk group and 17% in the high-risk group (p < 0.001). In multivariate analysis, the EP score remained significantly associated with pCR. Many genes upregulated in the high-risk tumours were involved in cell proliferation, whereas many genes upregulated in the low-risk tumours were involved in ER-signalling and stroma. Despite higher chemosensitivity, the high-risk group was associated with worse disease-free survival. In conclusion, EP high-risk ER+/HER2- breast cancers are more likely to respond to anthracycline-based chemotherapy.

Tissue slide-based microRNA characterization of tumors: how detailed could diagnosis become for cancer medicine?

miRNAs are short, non-coding, regulatory RNAs that exert cell type-dependent, context-dependent, transcriptome-wide gene expression control under physiological and pathological conditions. Tissue slide-based assays provide qualitative (tumor compartment) and semi-quantitative (expression levels) information about altered miRNA expression at single-cell resolution in clinical tumor specimens. Reviewed here are key technological advances in the last 5 years that have led to implementation of fully automated, robust and reproducible tissue slide-based assays for in situ miRNA detection on US FDA-approved instruments; recent tissue slide-based discovery studies that suggest potential clinical applications of specific miRNAs in cancer medicine are highlighted; and the challenges in bringing tissue slide-based miRNA assays into the clinic are discussed, including clinical validation, biomarker performance, biomarker space and integration with other biomarkers.