Tumor characteristics and recurrence patterns in triple negative breast cancer: a comparison between younger (<65) and elderly (≥65) patients

miRNA signatures affecting the survival outcome in distant metastasis of triple-negative breast cancer

Triple-negative breast cancer (TNBC) constitutes for 10-15% of all breast cancer cases. Tumor heterogeneity, high invasiveness, distant metastasis, lack of estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2 expression contribute to TNBC associated with poor overall survival outcomes amongst diseased individuals. The disparity in clinico-pathological and metastatic patterns to distant sites has substantially enhanced the incidences of tumor recurrence. Survival outcomes amongst metastatic TNBC patients are worse in comparison to non-metastatic TNBC counterparts. MicroRNAs (miRNAs) have emerged as significant drivers to function either as oncogene or tumor suppressors by exerting modulating effects on the expression of target genes in the TNBC tumor microenvironment. The pleiotropic nature of miRNAs expands their preclinical and clinical utility in combating both metastatic and non-metastatic TNBC cases and thereby improves their survival outcomes. The present review article aims to highlight the varying survival outcomes in metastatic and non-metastatic TNBC cases. The present review article emphasizes the therapeutic and prognostic potential of miRNAs in TNBC to improve survival outcomes by retarding distant metastasis to lung, bone, brain, and lymph nodes.

Metastatic recurrence in women diagnosed with non-metastatic breast cancer: a systematic review and meta-analysis

BACKGROUND

To assess proportions of metastatic recurrence in women initially diagnosed with non-metastatic breast cancer by stage at diagnosis, breast cancer subtype, calendar period and age.

METHODS

A systematic search of MEDLINE and Web of Science databases (January 2010-12 May 2022) was conducted. Studies reporting the proportion of distant metastatic recurrence in women with non-metastatic breast cancer were identified and outcomes and characteristics were extracted. Risk of bias was assessed independently by two reviewers. Random-effects meta-analyses of proportions were used to calculate pooled estimates and 95% confidence intervals (CIs).

RESULTS

193 studies covering over 280,000 patients were included in the main analysis. Pooled proportions of metastatic recurrence increased with longer median follow-up time from 12.2% (95% CI 10.5-14.0%) at 1-4 years post diagnosis, 14.3% (95% CI 12.9-15.7%) at 5-9 years to 23.3% (95% CI 20.1-26.8) at 10 years or more. Regional variation was observed with pooled estimates ranging from 11.0% (95% CI 8.5-13.7%) in Europe to 26.4% (95% CI 16.7-37.4%) in Africa (1-4 years follow-up). Proportions of recurrence were higher in studies with diagnosis before 2000 (22.2%, 95% CI 15.1-30.3) compared to studies with diagnosis from 2000 onwards (12.8%, 95% CI 11.7-14.0). At 1-4 years median follow-up, pooled proportions of metastatic recurrence were higher in women with hormone receptor negative (15.2%, 95% CI 12.0-18.7%) compared with receptor positive disease (9.6%, 95% CI 6.2-13.6%) and in women with locally advanced (33.2%, 95% CI 24.7-42.3%) relative to early disease at initial diagnosis (4.8%, 95% CI 2.5-7.8%). Proportions were higher in those under 50 years compared with 70+ years, 18.6% (95% CI 15.9-21.4%) versus 13.3% (95% CI 9.2, 18.0%), respectively. Heterogeneity was high in all meta-analyses and results should be interpreted with caution.

CONCLUSIONS

Higher proportions of metastatic recurrence in patients initially diagnosed at an advanced stage and in earlier calendar period emphasises the importance of early detection and treatment advancements. As the global number of breast cancer survivors increases, research and health policy efforts should be directed towards timely diagnosis and access to effective treatments and care.

STUDY REGISTRATION

PROSPERO CRD42022314500.

Establishment of prognostic model for invasive ductal carcinoma with distant metastasis within the triple-negative breast cancer: a SEER population-based study

Triple-negative breast cancer (TNBC) is a complex and diverse group of malignancies. Invasive ductal carcinoma (IDC) is the predominant pathological subtype and is closely linked to the ominous potential for distant metastasis, a pivotal factor that significantly influences patient outcomes. In light of these considerations, the present study was conceived with the objective of developing a nomogram model. This model was designed to predict the prognosis observed in IDC with distant metastasis in TNBC. This was a retrospective study based on the SEER database. Data of 9739 IDC-TNBC patients diagnosed from 2010 to 2020 were included in our study. Independent risk factors were screened by univariate and multivariate Cox regression analyses successively, which were used to develop a nomogram model predicting for prognosis. Cox multivariable analysis showed statistical significance in bone metastasis, liver metastasis, surgery, and chemotherapy. Incorporating statistically significant variables, as well as clinically significant age, lung metastasis, and brain metastasis into the construction of the prediction model, the C-indexes of the training group and validation group were 0.702 (0.663-0.741) and 0.667 (0.600-0.734), respectively, while the calibration curves were all close to the ideal 45° reference line, and decision curve analysis curves show excellent net benefit in the predictive model. The prognostic prediction model developed in this study demonstrated enhanced predictive accuracy, enabling a more precise evaluation of mortality risks associated with IDC with distant metastasis in TNBC.

An enhanced and efficient approach for feature selection for chronic human disease prediction: A breast cancer study

Computer-aided diagnosis (CAD) systems play a vital role in modern research by effectively minimizing both time and costs. These systems support healthcare professionals like radiologists in their decision-making process by efficiently detecting abnormalities as well as offering accurate and dependable information. These systems heavily depend on the efficient selection of features to accurately categorize high-dimensional biological data. These features can subsequently assist in the diagnosis of related medical conditions. The task of identifying patterns in biomedical data can be quite challenging due to the presence of numerous irrelevant or redundant features. Therefore, it is crucial to propose and then utilize a feature selection (FS) process in order to eliminate these features. The primary goal of FS approaches is to improve the accuracy of classification by eliminating features that are irrelevant or less informative. The FS phase plays a critical role in attaining optimal results in machine learning (ML)-driven CAD systems. The effectiveness of ML models can be significantly enhanced by incorporating efficient features during the training phase. This empirical study presents a methodology for the classification of biomedical data using the FS technique. The proposed approach incorporates three soft computing-based optimization algorithms, namely Teaching Learning-Based Optimization (TLBO), Elephant Herding Optimization (EHO), and a proposed hybrid algorithm of these two. These algorithms were previously employed; however, their effectiveness in addressing FS issues in predicting human diseases has not been investigated. The following evaluation focuses on the categorization of benign and malignant tumours using the publicly available Wisconsin Diagnostic Breast Cancer (WDBC) benchmark dataset. The five-fold cross-validation technique is employed to mitigate the risk of over-fitting. The evaluation of the proposed approach's proficiency is determined based on several metrics, including sensitivity, specificity, precision, accuracy, area under the receiver-operating characteristic curve (AUC), and F1-score. The best value of accuracy computed through the suggested approach is 97.96%. The proposed clinical decision support system demonstrates a highly favourable classification performance outcome, making it a valuable tool for medical practitioners to utilize as a secondary opinion and reducing the overburden of expert medical practitioners.

Diagnostic and Prognostic Nomograms for Lung Metastasis in Triple-Negative Breast Cancer

Background

The lungs are one of the common sites of metastasis of triple-negative breast cancer (TNBC). Patients with lung metastases (LM) have a shorter duration of survival. This study is aimed at determining the prognostic factors of patients with TNBC with LM and constructing two nomograms to assess the risk of LM and the prognosis of patients with TNBC with LM.

Methods

Clinicopathological and follow-up data of patients with TNBC between 2010 and 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were used to screen for independent predictors of LM in patients with TNBC and identify the independent prognostic factors of patients with TNBC with LM. The two nomograms were appraised using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

Results

A total of 27,048 patients with TNBC were included in this study. Age, tumour size, T stage, and N stage were identified as independent risk factors for LM in patients with TNBC. Histological type, marital status, prior surgery, chemotherapy, bone metastases, brain metastases, and LM were confirmed as independent prognostic factors for patients with TNBC with LM. The area under the ROC curve (AUC) of the diagnostic nomogram was 0.838 (95% confidence interval 0.817-0.860) in the training cohort and 0.894 (95% confidence interval 0.875-0.917) in the verification cohort. The AUC values of the 6-, 12-, and 18-month prognostic nomograms in the training cohort were 0.809 (95% confidence interval 0.771-0.868), 0.779 (95% confidence interval 0.737-0.834), and 0.735 (95% confidence interval 0.699-0.811), respectively, and the corresponding AUC values in the validation cohort were 0.735(95% confidence interval 0.642-0.820), 0.672 (95% confidence interval 0.575-0.758), and 0.705 (95% confidence interval 0.598-0.782), respectively. According to the calibration curves and data analysis, both nomograms exhibited good performance.

Conclusion

We successfully constructed and verified two valuable nomograms for predicting the incidence of LM and prognosis of patients TNBC with LM.

Phytochemical-conjugated bio-safe gold nanoparticles in breast cancer: a comprehensive update

Breast cancer is the most common malignancy in women and is rated among one of the three common malignancies worldwide in combination with colon and lung cancer. The escalating mortality rate of breast cancer patients has captivated the attention of the present-day researchers to come up with new management options. According to WHO, early detection, timely diagnosis and comprehensive breast cancer management are the three cornerstones for controlling breast cancer incidences per year. Multidisciplinary theragnostic approaches for simultaneous diagnosis and treatment of breast cancer have further enriched the therapeutic arsenal. Imaging and biopsy play a significant role in the diagnosis of breast cancer. The treatment plan mostly initiates with general surgery or radiation therapy followed up with adjuvant and/or neoadjuvant therapy. Conventional chemotherapeutics in breast cancer suffer from toxicity and lack of site specificity. Bio-safe gold nanoparticles hold sufficient promise for bridging this gap. Diverse phytochemicals-based synthesis routes to arrive at nano-dimensional gold with spotlight on reaction mechanisms, reaction variables, specific advantages, toxicity and their influence in breast cancer conditions are the focus of this work. This review marks the first attempt to explore the potential of phytochemical-derived nano-gold in breast cancer treatment.

Addition of chemotherapy to local therapy in women aged 70 years or older with triple-negative breast cancer: a propensity-matched analysis

BACKGROUND

There is a scarcity of data exploring the benefits of adjuvant or neoadjuvant chemotherapy in the treatment of breast cancer in older women. We aimed to explore the effect of adding chemotherapy to local therapy on overall survival in older women with triple-negative breast cancer.

METHODS

For this propensity-matched analysis, we used data from the National Cancer Database, a joint project of the Commission on Cancer of the American College of Surgeons and the American Cancer Society. We included data from women aged 70 years or older with surgically treated, American Joint Committee on Cancer (AJCC) Stage I-III invasive triple-negative breast cancer diagnosed from 2004 to 2014. Patients with T1aN0M0 disease and those with incomplete data on oestrogen receptor status, progesterone receptor status, or HER2 status were excluded. To reduce bias, patients were subdivided into three groups: those who were recommended chemotherapy but did not receive it; those who received chemotherapy; and those for whom chemotherapy was not recommended and not given. The primary outcome was overall survival. Multivariate Cox regression analysis and propensity score matching were done to minimise bias.

FINDINGS

Between Jan 1, 2004, and Dec, 31, 2014, 16 062 women with triple-negative breast cancer in the database met the inclusion criteria for this analysis. Median follow-up was 38·3 months (IQR 20·7-46·1, range 0-138·0; 95% CI 37·8-38·7). Collectively, the 5-year overall survival estimate of the 16 062 patients in the study cohort was 62·3% (95% CI 59·7-64·4). 5-year estimated overall survival was 68·5% (95% CI 66·4-70·6) for patients receiving chemotherapy, 61·1% (59·0-63·2) for patients recommended but not given chemotherapy, and 53·7% (51·8-55·8) for patients not recommended chemotherapy and not given chemotherapy (pooled log rank p<0·0001). Multivariate Cox regression analysis of a propensity score-matched sample comparing those who received chemotherapy with those who were recommended but not given chemotherapy (n=1884 matched pairs) identified improved overall survival with chemotherapy (hazard ratio [HR] 0·69 [95% CI 0·60-0·80]; p<0·0001). After stratifying the propensity score matching sample, this benefit persisted for node-negative women (HR 0·80 [95% CI 0·66-0·97]; p=0·007), node-positive women (0·76 [0·64-0·91]; p=0·006), and those with a comorbidity score greater than 0 (HR 0·74 [95% CI 0·59-0·94]; p=0·013).

INTERPRETATION

These data support consideration of chemotherapy in the treatment of women aged 70 years or older with triple-negative breast cancer.

FUNDING

None.

Supervised Machine Learning Predictive Analytics For Triple-Negative Breast Cancer Death Outcomes

Objective

To use machine learning algorithms to predict the death outcomes of patients with triple-negative breast cancer, 5 years after discharge.

Methods

1570 stage I-III breast cancer patients receiving treatment from Sun Yat-sen Memorial Hospital were analyzed. Machine learning was used to predict the death outcomes of patients with triple-negative breast cancer, 5 years after discharge.

Results

The results showed that platelets, LMR (lymphocyte-to-monocyte ratio), age, PLR (the platelet-to-lymphocyte ratio) and white blood cell counts accounted for a significant weight in the 5-year prognosis of triple-negative breast cancer patients. The results of model prediction indicated that rankings for accuracy among the training group (from high to low) were forest, gbm, and DecisionTree (0.770335, 0.760766, 0.751994, 0.737640 and 0.734450, respectively). For AUC value (high to low), they were forest, Logistic and DecisionTree (0.896673, 0.895408, 0.776836, 0.722799 and 0.702804, respectively). The highest MSE value for DecisionTree was 0.2656, and the lowest MSE value for forest was 0.2297. In the test group, accuracy rankings (from high to low) were DecisionTree, and GradientBoosting (0.748408, 0.738854, 0.738854, 0.732484 and gbm, respectively). For AUC value (high to low), the rankings were GradientBoosting, gbm, and DecisionTree (0.731595, 0.715438, 0.712767, 0.708348 and 0.691960, respectively). The maximum MSE value for gbm was 0.2707, and the minimum MSE value for DecisionTree was 0.2516.

Conclusion

The machine learning algorithm can predict the death outcomes of patients with triple-negative breast cancer 5 years after discharge. This can be used to estimate individual outcomes for patients with triple-negative breast cancer.

Know your enemy: Genetics, aging, exposomic and inflammation in the war against triple negative breast cancer

Triple negative breast cancer (TNBC) is one of the most biologically aggressive and very often lethal breast disease. It is one of the most puzzling women malignancies, and it currently appears not to be a good candidate to a standardized, unanimously accepted and sufficiently active therapeutic strategy. Fast proliferating and poorly differentiated, it is histopathologically heterogeneous, and even more ambiguous at the molecular level, offering few recurrent actionable targets to the clinicians. It is a formidable and vicious enemy that requires a huge investigational effort to find its vital weak spots. Here, we provide a broad review of "old but gold" biological aspects that taken together may help in finding new TNBC management strategies. A better and updated knowledge of the origins, war-like tactics, refueling mechanisms and escape routes of TNBC, will help in moving the decisive steps towards its final defeat.

Risk factors for distant metastasis of patients with primary triple-negative breast cancer

Objective: Triple-negative breast cancer (TNBC) involves higher rates of recurrence and distant metastasis. The present study sought to characterize the risk factors for distant metastasis of TNBC.

Methods: The Surveillance, Epidemiology, and End Results (SEER) database was exploited to enroll patients diagnosed with TNBC from 2010 to 2015. The eligible patients were dichotomized into locoregional and distant metastasis at the time of diagnosis. Patients’ demographics and tumor features, and treatment were evaluated to identify the risk factors for distant metastasis of primary TNBC. The categorical variables were examined by chi-square tests. Univariate and multivariate logistic regression analyses were used to determine the risk factors for distant metastasis. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated by Kaplan–Meier plots with log-rank tests.

Results: We collected 26863 patients with primary TNBC, 1330 (5.0%) of them presented with distant metastasis. In the univariate analysis, all the variables indicated statistical significance. The significant variables were subsequently enlisted into the multivariate logistic regression analysis. Age > 50, higher clinical stage T and N, and tumor size > 5 cm were independent risk factors for distant metastasis of primary TNBC. Moreover, higher clinical stage T and stage N were independent risk factors for bone metastasis of the patients. TNBC patients with either bone or visceral metastasis have poor survival, with brain metastasis worst of all, though the OS difference was not statistically significant.

Conclusions: TNBC patients with larger age, higher clinical stage, larger tumor size were more predisposed to have distant metastasis. Great attention should be paid to the prognosis of these patients with distant metastasis.

Pharmacotherapeutic Management of Breast Cancer in Elderly Patients: The Promise of Novel Agents

As its incidence increases with age, breast cancer in elderly patients takes on a growing importance in clinical oncology practice. Management decisions are challenging because there is a lack of high-quality evidence in this heterogeneous population. Epidemiological studies have shown that breast cancer mortality does not decrease substantially in the older population compared with younger adults. Recent data suggest a phenotype somewhat different from that of younger patients, also confirmed at the molecular level. Breast cancer biology has been incompletely deciphered in this age group. New therapeutic agents continue to expand the available treatment options at every stage, and for each subtype of breast cancer. In the estrogen receptor-positive subtype, agents to overcome endocrine resistance have been introduced; CDK 4/6 and mTOR inhibitors have already been approved in this setting. In addition, more potent agents targeting the HER2 pathway are actively being trialed. Besides trastuzumab, pertuzumab, or lapatinib, new agents like neratinib or PI3K inhibitors are currently being tested in clinical trials. Finally, even though chemotherapy remains the cornerstone of the treatment of triple negative tumors, alternative promising approaches such as immunotherapy, notably antibodies against PD-1/PD-L1 or targeted therapies (PARP or androgen inhibitors), are currently being investigated in this specific subtype.

Alarming Burden of Triple-Negative Breast Cancer in India

Breast cancer is the most prevalent cancer among women worldwide. Among the different breast cancer subtypes, triple-negative breast cancer (TNBC), which is more prevalent among younger age women, is the most aggressive form. Numerous clinicopathologic studies performed throughout the world strongly support the utterly poor prognoses and high recurrence rate of TNBC. The present report details a thorough data survey from Google and PubMed on the burden of TNBC worldwide and other associated factors, with special emphasis on its ever increasing incidence among Indian women. Our analysis revealed that the proportion of TNBC ranges from 6.7% to 27.9% in different countries, with the highest reported percentage in India among all, followed by Indonesia, Algeria, and Pakistan. Most of the other countries (Netherlands, Italy, London, Germany) had a TNBC incidence less than the mean level (ie, 15%). The high incidence of TNBC in the Indian population is associated with vivid risk factors, which primarily include lifestyle, deprivation status, obesity, family history, high mitotic indexes, and BRCA1 mutations. The treatment of TNBC is greatly hampered due to the lack of targeted therapies. Hence, it requires earnest attention towards extensive research for the prevention and development of treatment modalities with high efficacy.

Triple-negative breast cancer in the elderly: Prognosis and treatment

Our objective is to characterize treatment of triple-negative breast cancer (TNBC) in older patients and measure mortality risk relative to younger women. We conducted a retrospective cohort study analysis of patients presenting with primary TNBC, age 25-93, stage I-III from 1990 to 2014, identified and tracked by our registry (n=771). Clinical characteristics were chart abstracted at diagnosis and follow-up. The Kaplan-Meier method was used to measure disease-specific survival (DSS) by age with Cox regression modeling for relative contribution of patient and clinical characteristics. Of patients, 80% were <65 years (n=612), 13% were 65-74 years (n=100), and 7% were 75 and older (n=59). Older women presented more often with lower stage BC (stage I: 31% age <65, 48% age 65-74, 39% age 75+; P=.014). All three age groups were equally likely to have radiation therapy (77%) but older patients were less often treated with adjuvant chemotherapy (<65=95%, 65-74=76%, 75+=39%; P<.001). Mean follow-up was 7.34 years and did not differ by age. Five-year DSS was equivalent across the three age groups (<65=85%, 65-74=90%, 75+=83%, P=.322). In Cox regression analysis controlling for stage, histologic and nuclear grade, diagnosis year, radiation and chemotherapy treatment, age was not significantly associated with disease-specific mortality. TNBC survival appears equivalent by age despite less aggressive treatment in patients 75 years and older. This may be a result of lower stage at diagnosis and decreased disease virulence resulting in comparative survival despite less treatment.

Operation with less adjuvant therapy for elderly breast cancer

BACKGROUND

The standard of care for elderly women with breast cancer remains controversial. The aim of this study was to clarify the management of elderly breast cancer patients who undergo surgery.

MATERIALS AND METHODS

This retrospective single-center cohort study included 2276 breast cancer patients who underwent surgery between 1993 and 2014. The patients were divided into three groups according to age: ≤64 y (young), 65-74 y (older), and ≥75 y (elderly).

RESULTS

The elderly had more advanced stage disease at diagnosis (stage III and IV, 16.2%, 17.5%, and 22.1% for the young, older, and elderly groups, respectively). The elderly were more likely to undergo mastectomy (43.3%, 41.4%, and 50.7%, respectively), omit axillary operation (0.6%, 1.1%, and 9.3%, respectively), and skip radiotherapy after breast-conserving surgery (93.1%, 86.8%, and 29.1%, respectively). Endocrine therapy was widely used in all the groups (94.4%, 93.8%, and 90.1%, respectively), but frequency of chemotherapy was lower in the elderly regardless of hormone receptor (HR) status (40.8%, 25.5%, and 9.3% in HR(+), 87.2%, 75.3%, and 39.5% in HR(-), respectively). Although the locoregional recurrence rate was higher in the elderly (4.2%, 3.4%, and 7.0% at 5 y, respectively; P = 0.028), there were no differences among groups in distant metastasis-free survival or breast cancer-specific survival.

CONCLUSIONS

Although elderly patients had more advanced stages of cancer and received less treatment, there were no differences in survival. Omission of axillary dissection, radiation, and chemotherapy after operation may be an option for breast cancer patients aged ≥75 y.

Prognostic impact of breast cancer subtypes in elderly patients

We aimed to analyse the impact of breast cancer (BC) subtypes on the clinical course of disease with special emphasis on the occurrence of brain metastases (BM) and outcome in an elderly BC population. A total number of 706 patients ≥65 years receiving treatment for BC from 2007 to 2011 were identified from a BC database. 62 patients diagnosed with DCIS and 73 patients with incomplete datasets were excluded, leaving 571 patients for this analysis. Patient characteristics, biological tumour subtypes, and clinical outcome including overall survival (OS) were obtained by retrospective chart review. 380/571 (66, 5 %) patients aged 65–74 years were grouped among the young-old, 182/571 (31.9 %) patients aged 75–84 years among the old–old, and 29/571 (5.1 %) patients aged ≥85 years among the oldest-old. 392/571 (68.8 %) patients presented with luminal BC, 119/571 (20.8 %) with HER2-positive, and 59/571 (10.3 %) with triple-negative BC (TNBC). At 38 months median follow-up, 115/571 (20.1 %) patients presented with distant recurrence. A higher recurrence rate was observed in the HER2-positive subtype (43/119 (36.1 %)), as compared to TNBC (15/59 (25.4 %)) and luminal BC (57/392 (14.5 %); p < 0.001). BM were detected at a significantly higher rate in HER2-positive BC patients (9/119 (7.6 %)), as compared to TNBC (2/59 (3.4 %)) and luminal BC patients (6/392 (1.5 %); p = 0.003). Diagnosis of metastatic disease (HR 7.7; 95 % CI 5.2–11.4; p < 0.001) as well as development of BM (HR 3.5; 95 % CI 1.9–6.4; p < 0.001) had a significantly negative impact on OS in a time-dependent covariate cox regression model. In contrast to younger BC patients, outcome in this large cohort of elderly patients suggests that HER2-positive disease—not TNBC—featured the most aggressive clinical course with the highest rates of metastatic spread and BM. In-depth analysis regarding a potentially distinct biology of TNBC in elderly is therefore warranted.

Breast and ovarian cancer in the older woman

Nearly half of all women diagnosed with breast or ovarian cancer are age 65 years or older with the number of women diagnosed expected to increase as the population ages and life expectancy improves. Older women are less likely to be offered standard cancer treatments, are more likely to develop higher toxicity, and have higher mortality. Chronologic age should not be the only factor used for making treatment decisions. Functional dependence, organ function, comorbidity, polypharmacy, social support, cognitive and/or psychosocial factors, overall life expectancy, and patient's goals of care are equally vital and should be assessed before and during treatment. In this review, current evidence and treatment guidelines for older women with breast or ovarian cancer are outlined.

Prognosis in very young women with triple-negative breast cancer: retrospective study of 216 cases

The aim of this investigation was to compare clinical pathological characteristics and prognosis of very young and older triple-negative breast cancer (TNBC) patients in order to assess their relevance to TNBC in an younger population. Data of TNBC patients diagnosed between 2002 and 2007 were retrospectively analyzed by computer based chart information. Baseline tumor characteristics, biological markers, and patients' prognosis were compared between very young (≤ 35 years) and older (>35 years) TNBC patients. In the 216 cases of operable TNBC patients, 48 (22.2%) were ≤ 35 years and 168 (77.8%) were >35 years. Very young TNBC patients had showed a high clinical stage, more positive lymph nodes, Ck5/6 and/or EGFR expression (P = 0.049, 0.006, and 0.011, respectively). Compared to older TNBC patients, very young TNBC patients have short disease-free survival (P = 0.031), while no significant difference was found in overall survival (OS) (P = 0.075). In multivariate analysis, lymph node metastatic status was a significant predictor of OS. TNBC of very young patients is an aggressive breast cancer subtype, but the overall survival of both young and older TNBC patients did not have significant differences.

The challenges of individualized care for older patients with localized breast cancer

Individualized care is achieved when the appropriate screening and/or evaluative tests are used, the treatment plan is driven by evidence-based data and the patient's functional ability, physical and mental health, preference and social situation are incorporated into treatment decisions. Breast cancer is a disease of aging; yet, the management of breast cancer in older women in most cases lacks evidence from prospective randomized clinical trials (i.e., level 1 evidence) to support treatment recommendations. Older women are underrepresented in therapeutic clinical studies, even though studies show that selected fit older women enrolled on clinical trials derive similar benefits as younger women. Very few studies have focused on the distribution and biological behavior of different molecular subtypes of breast cancer in older women making it difficult to conclude whether old age adds extra biological complexity. A comprehensive geriatric assessment that includes a multidimensional process designed to assess functional ability, physical health, cognitive and mental health, social issues and environmental situation of elderly person should be an integral part of individualized care for older patients with breast cancer. However, incorporation of this tool into standard oncology practice is very slow despite the expected steep increase in older individuals with cancer projected over the next 25 years. All of the factors mentioned above hinder progress in delivering individualized care to older patients with breast cancer. This article provides an overview on progress and challenges of individualized and personalized health care in older women with breast cancer.

Triple-negative breast cancer and the need for new therapeutic targets

Triple-negative breast cancers (TNBCs) are a diverse and heterogeneous group of tumors that by definition lack estrogen and progesterone receptors and amplification of the HER2 gene. The majority of the tumors classified as TNBCs are highly malignant, and only a subgroup responds to conventional chemotherapy with a favorable prognosis. Results from decades of research have identified important molecular characteristics that can subdivide this group of breast cancers further. High-throughput molecular analyses including sequencing, pathway analyses, and integrated analyses of alterations at the genomic and transcriptomic levels have improved our understanding of the molecular alterations involved in tumor development and progression. How this knowledge should be used for rational selection of therapy is a challenging task and the subject of numerous ongoing research programs. This review summarizes the current knowledge on the clinical characteristics and molecular alterations of TNBCs. Currently used conventional therapeutic strategies and targeted therapy studies are discussed, with references to recently published results on the molecular characterization of TNBCs.

Expression of Lewis X is associated with poor prognosis in triple-negative breast cancer

The Lewis X (Le(X)) antigen is a prognostic marker in certain solid tumors and has been proposed as a therapeutic target. Immunohistochemical analyses were performed to retrospectively examine the prognostic impact of Le(X) expression in 158 patients with triple-negative breast cancer (TNBC). Twenty-three (14.5%) patients were Le(X)-positive. Multivariate analysis showed that Le(X) positivity was an independent poor prognostic factor for recurrence-free survival (RFS) and overall survival (OS) (P = .037 and P = .024, respectively). Le(X) expression was a prognostic factor for survival in stage I/II and stage III TNBCs. Subgroup analysis according to age showed that Le(X) positivity was only associated with poor RFS and OS in younger patients with TNBC (age < 50 years) (P < .001 and P < .001, respectively). Our results suggest that Le(X) expression is an independent prognostic factor for RFS and OS in younger patients with TNBC.