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

Direct detection of microRNA in liquid biopsies from single cancer spheroids

Exploring cancer heterogeneity is crucial for both understanding cancer and developing prognostic tools to monitor cancer progression during treatment through the liquid biopsy concept. Herein, a nanoparticle-based "dispersible electrodes" biosensor was used to detect ultra-low concentrations of microRNA-155 (miRNA-155) from a single breast cancer spheroid for the first time. The results from the sensor were comparable to the standard real-time polymerase chain reaction analysis, but in a much shorter detection time and without any sample purification or amplification. Owing to the unique ability of the sensor to measure biomarker expression from unaltered and undiluted cancer liquid biopsy from a single cancer spheroid, we then tracked dynamic changes in miRNA-155 expression in a single spheroid treated with the anti-cancer drug doxorubicin. The ability to track dynamic biomarker changes in a single cancer spheroid opens the door to understanding key biological processes such as response to treatment on the cellular and molecular levels, paving the way for adapting liquid biopsy insights to guide oncologists and more personalised treatment strategies.

Risk factors and prognostic factors of brain metastasis of triple-negative breast cancer: A single-center retrospective study

OBJECTIVE

This retrospective study is to explore the risk factors and prognostic factors of brain metastases of triple-negative breast cancer (TNBC) in a single center.

METHODS

Clinical data of patients with stages I-III TNBC were collected. The Kaplan-Meier method, log-rank test, and stepwise COX regression were performed.

RESULTS

The 437 patients with stages I-III TNBC were followed up for five years. Among them, 89 cases (20.4%) developed brain metastases, and they were followed up for 2 years after brain metastasis. The cumulative brain metastasis rates of TNBC patients at six months, one year, two years, three years, and five years were 1.38%, 5.75%, 12.94%, 17.63%, and 21.26%, respectively. Multivariate analysis suggested that the first diagnosis age ≤35 years old, advanced pathological stage, lymph node metastasis, and Ki-67 ≥30% represented the risk factors for brain metastasis. In contrast, the surgical method was a protective factor for brain metastasis. The median survival time after brain metastasis was 4.87 months. The survival rates at one, three, six, 12, and 24 months were 84.27%, 60.67%, 34.83%, 15.69%, and 6.64%, respectively. The age >60 years at first diagnosis, Ki-67 ≥30%, local recurrence, and distant metastasis were closely related to the poor prognosis of TNBC patients with brain metastases, while radiotherapy alone, systemic therapy, and combined chemotherapy and radiotherapy represented the prognostic protective factors.

CONCLUSIONS

Patient age, Ki-67 level, metastasis, and treatment methods are the risk factors and prognostic factors for brain metastasis of TNBC. Surgical resection of the primary lesion during the first treatment is essential to reduce the incidence of brain metastases. Close postoperative follow-up (such as brain magnetic resonance imaging [MRI]) within 2-3 years after surgery is recommended to improve the prognosis.

Association of cyclooxygenase-2 expression with endoplasmic reticulum stress and autophagy in triple-negative breast cancer

Cyclooxygenase-2 plays a role in oncogenesis and its overexpression is associated with triple-negative breast cancer. However, the mechanisms whereby cyclooxygenase-2 contribute to breast cancer are complex and not well understood. Cyclooxygenase-2 overexpression causes hypoxia, oxidative stress, and endoplasmic reticulum stress. The aim of this study is to investigate the correlations among cyclooxygenase-2 expression, endoplasmic reticulum stress-associated molecules, and autophagy-associated molecules in triple-negative breast cancer. Surgical specimens from two cohorts of triple-negative breast cancer patients without neoadjuvant systemic therapy were analyzed: cohorts 1 and 2 consisted of 218 cases from 2004 to 2006 and 221 cases from 2007 to 2009, respectively. Specimens were evaluated by immunohistochemical examination of cyclooxygenase-2, endoplasmic reticulum stress markers, and autophagy markers expression using tissue microarrays. Cyclooxygenase-2 was overexpressed in 29.8% and 23.9% of cases in cohorts 1 and 2, respectively; and it was positively correlated with two out of three endoplasmic reticulum stress-associated molecules (XBP1, p = 0.025 and p = 0.003 in cohort 1 and cohort 2, respectively; PERK, p < 0.001 in both cohorts). Cyclooxygenase-2 was also positively correlated with two out of three autophagy markers (p62, p = 0.002 and p = 0.003 in cohort 1 and cohort 2, respectively; beclin1, p < 0.001 in both cohorts). Although cyclooxygenase-2 was not an independent prognostic factor for distant metastasis free survival and overall survival, its expression was associated with the expression of endoplasmic reticulum stress and autophagy molecules in triple-negative breast cancer.

The Association between Early-Onset Diagnosis and Clinical Outcomes in Triple-Negative Breast Cancer: A Systematic Review and Meta-Analysis

Early-onset diagnosis, defined by age <40 years, has historically been associated with inferior outcomes in breast cancer. Recent evidence suggests that this association is modified by molecular subtype. We performed a systematic review and meta-analysis of the literature to synthesize evidence on the association between early-onset diagnosis and clinical outcomes in triple-negative breast cancer (TNBC). Studies comparing the risk of clinical outcomes in non-metastatic TNBC between early-onset patients and later-onset patients (≥40 years) were queried in Medline and EMBASE from inception to February 2023. Separate meta-analyses were performed for breast cancer specific survival (BCSS), overall survival (OS), and disease-free survival (DFS), locoregional recurrence-free survival (LRRFS), distant recurrence-free survival (DRFS), and pathological complete response (pCR). In total, 7581 unique records were identified, and 36 studies satisfied inclusion criteria. The pooled risk of any recurrence was significantly greater in early-onset patients compared to later-onset patients. Better BCSS and OS were observed in early-onset patients relative to later-onset patients aged >60 years. The pooled odds of achieving pCR were significantly higher in early-onset patients. Future studies should evaluate the role of locoregional management of TNBC and the implementation of novel therapies such as PARP inhibitors in real-world settings, and whether they improve outcomes.

A Novel lncRNA Panel for Risk Stratification and Immune Landscape in Breast Cancer Patients

Purpose

In recent years, breast cancer (BC) has been a primary cause of mortality in women. However, the underlying mechanisms remain to be elucidated. Accumulating evidence has supported the hypothesis that long noncoding RNAs (lncRNAs) play central roles in the progression of cancer. We aimed to construct an immune-related lncRNA panel to predict the prognosis of patients with BC and evaluate the immune features.

Methods

The expression profiles of patients with BC were obtained from The Cancer Genome Atlas (TCGA) database to screen the differentially expressed lncRNAs (DELs). Pearson’s correlation analysis was employed to filter the DELs related to the immune-associated genes. Univariate Cox regression, the LASSO algorithm, and multivariate Cox regression analyses were conducted to establish the model. Functional enrichment analyses and biological experiments were performed to explore the immune activity of the lncRNA panel.

Results

A four-immune-related lncRNA panel (IRLP) composed of AC022196.1, ARHGAP26-AS1, DPYD-AS1 and PURPL was established in TCGA training cohort. The prognostic accuracy of the predictive model was confirmed in TCGA internal validation cohort, TCGA entire cohort and Qilu external validation cohort. Bioinformatics analyses indicated that the IRLP had a close relationship with tumour infiltrating immune cells and immunomodulatory biomarkers. The biological functions of the four immune-related lncRNAs in BC were first investigated in vitro and in vivo. PURPL was indicated to play a central role in the regulation of macrophage recruitment and polarization via CCL2.

Conclusion

Our study identified IRLP as a reliable prognostic indicator with great potential for clinical application in personalized immunotherapy.

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.

Unveiling Novel Therapeutic Drug Targets and Prognostic Markers of Triple Negative Breast Cancer

Triple negative breast cancer represents multiple genomic and transcriptomic heterogeneities. Genetic and epigenetic changes emerging in TNBC help it in acquiring resistance against immunological response. Distant metastasis, lack of clinically targeted therapies and prognostic markers make it the most aggressive form of breast cancer. In this review, we showed that driver alterations in targeted genes AR, ERR, TIL, TAM, miRNA, mTOR and immunosuppressive cytokines are predominantly involved in complicating TNBC by inducing cell proliferation, invasion and metastasis, and by inhibiting apoptosis. The role of node status, cathepsin-D, Ki-67 index, CD3+TIL, BRCA1 promoter methylation value and p53 as an efficient prognostic factor have also been studied to predict the disease free and overall survival rate in TNBC patients. The present review article is an attempt to gain an insight with a new vision on the etiology of TNBC, its treatment strategies and prognostic marker to identify the outcome of standard therapies and to re-design future treatment strategies to provide maximum benefit to patients.

Clinicopathologic features and prognosis of triple-negative breast cancer in China: a retrospective cohort study of patients under 35 years old

AIM

To analyze factors that affect the prognosis of triple-negative breast cancer patients under 35 years old.

MATERIAL AND METHODS

We retrospectively analyzed confirmed triple-negative breast cancer cases from 2000 to 2016 in multiple institutions. A total of 105 patients were included in the study, Nineteen of them were diagnosed with age ≤ 25, and 86 of them were aged between 26 to 35.

RESULT

There were no statistically significant differences in clinicopathologic features and treatment choices between patients aged ≤ 25 years and those aged 26-35 years (P > 0.05). Survival analysis showed no statistically significant differences in DFS and OS between the two groups (P > 0.05). Multiple factor analysis showed that age of menarche (HR 0.697, 95% CI [0.5634, 0.8631]), pregnancy correlation (HR 2.673, 95% CI [1.1581, 6.1741]), and lymph node positivity (HR 4.915, 95% CI [2.3774, 10.1627]) were independent prognostic factors that affected patients' DFS. Independent prognostic factors that influenced OS were age of menarche (HR 0.598, 95% CI [0.462 6, 0.775]) and lymph node positivity (HR 7.751, 95% CI [2.923, 20.559]).

CONCLUSION

There was no difference in the clinicopathological features and prognosis between women ≤ 25 and women aged 26-35 years with triple-negative breast cancer. Age of menarche, pregnancy correlation, and positive lymph nodes were independent factors affecting prognosis. The relationship between reproductive factors and prognosis in young patients with triple-negative breast cancer needs further discussion.

Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging

Identification of tumor antigens that induce cytotoxic T lymphocytes (CTLs) is crucial for cancer-vaccine development. Despite their predictive ability, current algorithmic approaches and human leukocyte antigen (HLA)-peptidomic analysis allow limited selectivity. Here, we optimized a method to rapidly screen and identify highly immunogenic epitopes that trigger CTL responses. We used a combined application of this method involving immune-specific signature analysis and HLA-associated peptidomics using samples from six patients with triple-negative breast cancer (TNBC) in order to select immunogenic HLA epitopes for in vitro testing. Additionally, we applied high-throughput imaging at the single-cell level in order to confirm the immunoreactivity of the selected peptides. The results indicated that this method enabled identification of promising CTL peptides capable of inducing antitumor immunity. This platform combining high-resolution computational analysis, HLA-peptidomics, and high-throughput immunogenicity testing allowed rapid and robust identification of highly immunogenic epitopes and represents a powerful technique for cancer-vaccine development.

[Breast cancer in young women. Histological and prognostic specificities: how are they different from older women?]

Early-onset of breast cancer (under the age of 40) represents only 7% of all breast cancers, but is the most common cancer in this age group in women. It is also known to be of worse prognosis, with a more aggressive tumoral behavior. The interaction of different prognostic factors contributes to the complexity of this population: tumor burden and biological features (using classical histopronostic features and genomic data) show differences from older women. Nevertheless, the prognostic impact of age varies according to the histological subtypes and seems pejorative mainly for the luminal subtype, probably with a crucial role of the hormonal environment and the treatments targeting the endocrine sensitivity of these tumors. In other subtypes, the influence of young age appears to be less significant, especially in HER2+ breast cancers.

Clinical features and their effect on outcomes of patients with triple negative breast cancer with or without lymph node involvement

Objective

Clinical and pathological characteristics of triple negative breast cancer (TNBC) treatment are required for escalation or de-escalation of treatment because of a lack of druggable targets. This study aimed to identify the factors affecting the risk of disease recurrence and disease-related death in patients with TNBC.

Methods

Patients with TNBC who were treated at the University Medical Centre Maribor between January 2010 and December 2017 were studied. Clinical and pathological data were analyzed using multivariate analysis and non-parametric tests. Subgroup analysis was performed to examine additional factors that affect 5-year overall survival (OS) and recurrence-free survival.

Results

Multivariate analysis showed that tumor size and the lymph node ratio (LNR) were significant risks in our population. Better discrimination of patients at risk of a shorter recurrence-free survival and OS was achieved by using the LNR. Only lymphovascular invasion was significant for predicting 5-year OS.

Conclusion

For risk-based decision-making systems, the LNR is useful for discriminating between high- and low-risk patients with TNBC.

Matrix stiffness modulates ILK-mediated YAP activation to control the drug resistance of breast cancer cells

One of the hallmarks of cancer progression is strong drug resistance during clinical treatments. The tumor microenvironment is closely associated with multidrug resistance, the optimization of tumor microenvironments may have a strong therapeutic effect. In this study, we configured polyacrylamide hydrogels of varying stiffness [low (10 kPa), intermediate (38 kPa) and high (57 kPa)] to simulate tissue physical matrix stiffness across different stages of breast cancer. After treatment with doxorubicin, cell survival rates on intermediate stiffness substrate are significantly higher. We find that high expression of ILK and YAP reduces the survival rates of breast cancer patients. Drug resistance is closely associated with the inactivation of the hippo pathway protein Merlin/MST/LATS and the activation of YAP. These results not only highlight the understanding of drug resistance mechanisms but also serve as a new basis for developing breast cancer treatment delivery systems.

Prognostic Value of Ki-67 in Patients With Resected Triple-Negative Breast Cancer: A Meta-Analysis

Background: Ki-67 is a widely used marker of tumor proliferation, but the prognostic value of ki-67 in triple-negative breast cancer (TNBC) has not been comprehensively reviewed. This meta-analysis was conducted to evaluate the association between ki-67 expression and survival of patients with resected TNBC.

Materials and Methods: Relevant studies, evaluating the prognostic impact of pretreatment ki-67 in resected TNBC patients, were identified from PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Cochrane Library until March 14, 2019. Hazard ratios (HRs) with 95% confidence intervals (CI) were calculated as effect values for disease-free survival (DFS) and overall survival (OS).

Results: In present meta-analysis, 35 studies with 7,716 enrolled patients were eligible for inclusion. Pooled results showed that a high ki-67 expression was significantly associated with poor DFS (HR = 1.73, 95% CI: 1.45–2.07, p < 0.001) and poor OS (HR = 1.65, 95% CI: 1.27–2.14, p < 0.001) in resected TNBC. In the subgroup analysis, when a cutoff of Ki-67 staining ≥40% was applied, the pooled HR for DFS and OS was 2.30 (95% CI 1.54–3.44, p < 0.001) and 2.95 (95% CI 1.67–5.19, p < 0.001), respectively.

Conclusion: A high Ki-67 expression is a poor prognostic factor of resected TNBC. The cut-off of ki-67 ≥40% is associated with a greater risk of recurrence and death compared with lower expression rates, despite the Ki-67 threshold with the greatest prognostic significance is as yet unknown.

Integrated network analysis identifies hsa-miR-4756-3p as a regulator of FOXM1 in Triple Negative Breast Cancer

Both aberrantly expressed mRNAs and micro(mi)RNAs play important roles in cancer cell function, which makes integration analysis difficult. In this study, we first applied master regulator analysisalgorithm and confirmed hsa-miR-4756-3p as a candidate miRNA in triple negative breast cancer (TNBC) patients; hsa-miR-4756-3p could regulate TNBC cell line apoptosis, proliferation, migration, and cell cycle as well as suppress TGF-β1 signalling andtumour growth. In TNBC, forkhead box protein M1 (FOXM1)was found to be an hsa-miR-4756-3p target gene, and FOXM1 knockout completely inhibited hsa-miR-4756-3p-induced cell migration and metastasis, TGF-β1 signalling, and epithelial mesenchymal signal activation, which indicated that hsa-miR-4756-3p functions via the FOXM1-TGFβ1-EMT axis.

Panoptic View of Prognostic Models for Personalized Breast Cancer Management

The efforts to personalize treatment for patients with breast cancer have led to a focus on the deeper characterization of genotypic and phenotypic heterogeneity among breast cancers. Traditional pathology utilizes microscopy to profile the morphologic features and organizational architecture of tumor tissue for predicting the course of disease, and is the first-line set of guiding tools for customizing treatment decision-making. Currently, clinicians use this information, combined with the disease stage, to predict patient prognosis to some extent. However, tumoral heterogeneity stubbornly persists among patient subgroups delineated by these clinicopathologic characteristics, as currently used methodologies in diagnostic pathology lack the capability to discern deeper genotypic and subtler phenotypic differences among individual patients. Recent advancements in molecular pathology, however, are poised to change this by joining forces with multiple-omics technologies (genomics, transcriptomics, epigenomics, proteomics, and metabolomics) that provide a wealth of data about the precise molecular complement of each patient's tumor. In addition, these technologies inform the drivers of disease aggressiveness, the determinants of therapeutic response, and new treatment targets in the individual patient. The tumor architecture information can be integrated with the knowledge of the detailed mutational, transcriptional, and proteomic phenotypes of cancer cells within individual tumors to derive a new level of biologic insight that enables powerful, data-driven patient stratification and customization of treatment for each patient, at each stage of the disease. This review summarizes the prognostic and predictive insights provided by commercially available gene expression-based tests and other multivariate or clinical -omics-based prognostic/predictive models currently under development, and proposes a more inclusive multiplatform approach to tackling the challenging heterogeneity of breast cancer to individualize its management. "The future is already here-it's just not very evenly distributed."-William Ford Gibson.

PTHrP, A Biomarker for CNS Metastasis in Triple-Negative Breast Cancer and Selection for Adjuvant Chemotherapy in Node-Negative Disease

Background

Triple-negative breast cancer (TNBC) is characterized by poor prognosis and lack of targeted therapies and biomarkers to guide decisions on adjuvant chemotherapy. Parathyroid hormone-related protein (PTHrP) is frequently overexpressed in breast cancer and involved in proliferation and metastasis, two hallmarks of poor prognosis for node-negative breast cancer. We investigated the prognostic value of PTHrP with respect to organ-specific metastasis and nodal status in TNBC.

Methods

We assessed PTHrP expression using immunohistochemistry in a clinically annotated tissue microarray for a population-based study of 314 patients newly diagnosed with TNBC, then analyzed its correlation to progression and survival using Kaplan-Meier and Cox regression analyses. The Cancer Genome Atlas (TCGA) validation analysis was performed through Bioconductor. All statistical tests were two-sided.

Results

PTHrP overexpression (160 of 290 scorable cases, 55.2%) was statistically significantly associated in univariate analysis with decreased overall survival (OS) in our cohort (P = .0055) and The Cancer Genome Atlas (P = .0018) and decreased central nervous system (CNS)-progression-free survival (P = .0029). In multivariate analysis, PTHrP was a statistically significant independent prognostic factor for CNS-progression-free survival in TNBC (hazard ratio [HR] = 5.014, 95% confidence interval [CI] = 1.421 to 17.692, P = .0122) and for OS selectively in node-negative TNBC (HR = 2.423, 95% CI = 1.129 to 5.197, P = .0231). Strikingly, PTHrP emerged as the only statistically significant prognostic factor (HR = 2.576, 95% CI = 1.019 to 6.513, P = .0456) for OS of low-clinical risk node-negative patients who did not receive adjuvant chemotherapy.

Conclusions

PTHrP is a novel independent prognostic factor for CNS metastasis and adjuvant chemotherapy selection of low-clinical risk node-negative TNBC. Its predictive value needs to be prospectively assessed in clinical trials.

Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm

Breast cancer is the most common cancer among women and is considered a major public health concern worldwide. Biogeography-based optimization (BBO) is a novel metaheuristic algorithm. This study analyzed the relationship between the clinicopathologic variables of breast cancer using Cox proportional hazard (PH) regression on the basis of the BBO algorithm. The dataset is prospectively maintained by the Division of Breast Surgery at Kaohsiung Medical University Hospital. A total of 1896 patients with breast cancer were included and tracked from 2005 to 2017. Fifteen general breast cancer clinicopathologic variables were collected. We used the BBO algorithm to select the clinicopathologic variables that could potentially contribute to predicting breast cancer prognosis. Subsequently, Cox PH regression analysis was used to demonstrate the association between overall survival and the selected clinicopathologic variables. C-statistics were used to test predictive accuracy and the concordance of various survival models. The BBO-selected clinicopathologic variables model obtained the highest C-statistic value (80%) for predicting the overall survival of patients with breast cancer. The selected clinicopathologic variables included tumor size (hazard ratio [HR] 2.372, p = 0.006), lymph node metastasis (HR 1.301, p = 0.038), lymphovascular invasion (HR 1.606, p = 0.096), perineural invasion (HR 1.546, p = 0.168), dermal invasion (HR 1.548, p = 0.028), total mastectomy (HR 1.633, p = 0.092), without hormone therapy (HR 2.178, p = 0.003), and without chemotherapy (HR 1.234, p = 0.491). This number was the minimum number of discriminators required for optimal discrimination in the breast cancer overall survival model with acceptable prediction ability. Therefore, on the basis of the clinicopathologic variables, the survival prediction model in this study could contribute to breast cancer follow-up and management.

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.

Effects of adjuvant chemotherapy in T1N0M0 triple-negative breast cancer

OBJECTIVES

Patients with T1N0M0 breast cancers are considered to have an excellent prognosis, even in triple-negative breast cancer (TNBC), which is often associated with diminished recurrence-free survival (RFS) and overall survival. Chemotherapy remains the only adjuvant treatment for TNBC, but evidence that adjuvant chemotherapy is beneficial for stage T1N0M0 TNBC patients is limited. In this study, we aimed to evaluate the effect of adjuvant chemotherapy and the benefit of taxanes in T1N0M0 TNBC patients.

MATERIAL AND METHODS

A cohort of 354 consecutive patients with newly diagnosed T1N0M0 TNBC between January 2008 and December 2015 were included from the Fudan University Shanghai Cancer Center. Univariate and multivariate survival analyses were performed to compare patients treated with adjuvant chemotherapy with/without taxane addition.

RESULTS

Median follow-up was 45 months. Chemotherapy was used in 92.4% of patients. The 5-year estimated RFS rates of patients with and without adjuvant chemotherapy were 94.5% and 83.6%, respectively. In multivariate analysis, adjuvant chemotherapy and a lack of lymphovascular invasion were associated with a significant benefit for RFS. A significant RFS benefit from adjuvant chemotherapy was observed in T1c (hazard ratio, HR = 0.24, 95% CI [0.08-0.76], P = 0.014) but not in T1b (HR = 0.32, 95% CI [0.03-3.18], P = 0.330) subgroups. Addition of taxane to an anthracycline-based regimen was not significantly associated with improved RFS in T1N0M0 TNBC patients.

CONCLUSION

Adjuvant chemotherapy improves recurrence-free survival in T1c TNBC patients but not in T1b. Anthracycline-based taxane-free regimens might be sufficient to achieve RFS benefits in T1N0M0 TNBC patients.

Clinical and pathological factors influencing survival in a large cohort of triple-negative breast cancer patients

BACKGROUND

To provide further information on the clinical and pathological prognostic factors in triple-negative breast cancer (TNBC), for which limited and inconsistent data are available.

METHODS

Pathological characteristics and clinical records of 841 TNBCs diagnosed between 1994 and 2015 in four major oncologic centers from Sardinia, Italy, were reviewed. Multivariate hazard ratios (HRs) for mortality and recurrence according to various clinicopathological factors were estimated using Cox proportional hazards models.

RESULTS

After a mean follow-up of 4.3 years, 275 (33.3%) TNBC patients had a progression of the disease and 170 (20.2%) died. After allowance for study center, age at diagnosis, and various clinicopathological factors, all components of the TNM staging system were identified as significant independent prognostic factors for TNBC mortality. The HRs were 3.13, 9.65, and 29.0, for stage II, III and IV, respectively, vs stage I. Necrosis and Ki-67 > 16% were also associated with increased mortality (HR: 1.61 and 1.99, respectively). Patients with tumor histotypes other than ductal invasive/lobular carcinomas had a more favorable prognosis (HR: 0.40 vs ductal invasive carcinoma). No significant associations with mortality were found for histologic grade, tumor infiltrating lymphocytes, and lymphovascular invasion. Among lymph node positive TNBCs, lymph node ratio appeared to be a stronger predictor of mortality than pathological lymph nodes stage (HR: 0.80 for pN3 vs pN1, and 3.05 for >0.65 vs <0.21 lymph node ratio), respectively. Consistent results were observed for cancer recurrence, except for Ki-67 and necrosis that were not found to be significant predictors for recurrence.

CONCLUSIONS

This uniquely large study of TNBC patients provides further evidence that, besides tumor stage at diagnosis, lymph node ratio among lymph node positive tumors is an additional relevant predictor of survival and tumor recurrence, while Ki-67 seems to be predictive of mortality, but not of recurrence.

Gene expression profiling of brain metastatic cell from triple negative breast cancer: Understanding the molecular events

Brain metastatic triple negative breast cancer (BM-TNBC) is afflicted with unfavorable prognosis. However, the molecular events underlying BM-TNBC remain largely unknown. In the present study, we conducted gene expression microarray analysis using the triple negative breast cancer cell line MDA-MB-231 and its brain metastatic derivative (MDA-MB-231Brm). Results of microarray analysis showed that a total of 4296 genes were differentially expressed, of which 2433 genes were up-regulated and 1863 genes were down-regulated. Gene Ontology (GO), KEGG pathway and protein-protein interaction (PPI) analyses indicated differentially expressed genes functionally categorized as genes of signal transduction, multicellular organismal development, ion transport, nervous system development, plasma membrane, extracellular region, calcium ion binding, GTP binding neuroactive ligand-receptor interaction. The validity of the microarray results was verified by quantitative real-time PCR analysis of twelve representative genes. The present findings revealed molecular basis and events associated with brain metastasis in TNBC, which will potentially contribute to the understanding of underlying mechanism and develop therapeutic targets.