Risk factors for central nervous system metastasis in patients with metastatic breast cancer

Predicting survival and prognosis of postoperative breast cancer brain metastasis: a population-based retrospective analysis

BACKGROUND

Breast cancer is one of the most common cancer in women and a proportion of patients experiences brain metastases with poor prognosis. The study aimed to construct a novel predictive clinical model to evaluate the overall survival (OS) of patients with postoperative brain metastasis of breast cancer (BCBM) and validate its effectiveness.

METHODS

From 2010 to 2020, a total of 310 female patients with BCBM were diagnosed in The Affiliated Cancer Hospital of Xinjiang Medical University, and they were randomly assigned to the training cohort and the validation cohort. Another 173 BCBM patients were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database as an external validation cohort. In the training cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression model was used to determine the fundamental clinical predictive indicators and the nomogram was constructed to predict OS. The model capability was assessed using receiver operating characteristic, C-index, and calibration curves. Kaplan-Meier survival analysis was performed to evaluate clinical effectiveness of the risk stratification system in the model. The accuracy and prediction capability of the model were verified using the validation and SEER cohorts.

RESULTS

LASSO Cox regression analysis revealed that lymph node metastasis, molecular subtype, tumor size, chemotherapy, radiotherapy, and lung metastasis were statistically correlated with BCBM. The C-indexes of the survival nomogram in the training, validation, and SEER cohorts were 0.714, 0.710, and 0.670, respectively, which showed good prediction capability. The calibration curves demonstrated that the nomogram had great forecast precision, and a dynamic diagram was drawn to increase the maneuverability of the results. The Risk Stratification System showed that the OS of low-risk patients was considerably better than that of high-risk patients (P <0.001).

CONCLUSION

The nomogram prediction model constructed in this study has a good predictive value, which can effectively evaluate the survival rate of patients with postoperative BCBM.

A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple-negative breast cancer

BACKGROUND

Patients with metastatic triple-negative breast cancer (mTNBC) frequently experience brain metastasis. This study aimed to identify prognostic factors and construct a nomogram for predicting brain metastasis possibility and brain screening benefit in mTNBC patients.

METHODS

Patients with mTNBC treated at our institution between January 2011 and December 2018 were retrospectively analyzed. Fine and Gray's competing risks model was used to identify independent prognostic factors. By integrating these prognostic factors, a competing risk nomogram and risk stratification model were developed and evaluated with concordance index (C-index) and calibration curves.

RESULTS

A total of 472 patients were retrospectively analyzed, including 305 patients in the training set, 78 patients in the validation set I and 89 patients in the validation set II. Four clinicopathological factors were identified as independent prognostic factors in the nomogram: lung metastasis, number of metastatic organ sites, hilar/mediastinal lymph node metastasis and KI-67 index. The C-indexes and calibration plots showed that the nomogram exhibited a sufficient level of discrimination. A risk stratification was further generated to divide all the patients into three prognostic groups. The cumulative incidence of brain metastasis at 18 months was 5.3% (95% confidence interval [CI], 2.5%-9.7%) for patients in the low-risk group, while 14.3% (95% CI, 9.3%-20.4%) for patients with intermediate risk and 34.3% (95% CI, 26.8%-41.9%) for patients with high risk. Routine brain MRI screening improved overall survival in high-risk group (HR 0.67, 95% CI 0.46-0.98, P = .039), but not in low-risk group (HR 0.93, 95% CI 0.57-1.49, P = .751) and intermediate-risk group (HR 0.83, 95% CI 0.55-1.27, P = .386).

CONCLUSIONS

We have developed a robust tool that is able to predict subsequent brain metastasis in mTNBC patients. Our model will allow selection of patients at high risk for brain metastasis who might benefit from routine bran MRI screening.

Biological subtypes and survival outcomes in breast cancer patients with brain metastases in the targeted therapy era

Background

There is recognition that breast cancer is a collection of heterogeneous diseases divided in subtypes based on combined molecular features such as hormonal receptors (HR) and human epidermal growth factor receptor 2 (HER2) status. We aimed to study clinical differences among biological subtypes in brain metastasis from breast cancer after targeted therapy introduction.

Methods

This was a retrospective study with 406 consecutive patients with brain metastasis from breast cancer treated at MD Anderson Cancer Center from 1998 to 2013. Overall, 315 of these patients met the study criteria and were analyzed. Subtypes were classified as HER2-/HR+ (96 patients), HER2+/HR+ (57 patients), HER2+/HR- (63 patients), and triple negative (HER2-/HR-) (99 patients). End points were time to development of brain metastasis (TDBM), brain metastasis-free survival (BMFS), and overall survival from start of treatment of brain metastasis (OSBM). Univariate and multivariate Cox proportional hazard regression models were used to analyze the data.

Results

TDBM was 41 months for HER2-/HR+; 58 months for HER2+/HR+; 30 months for HER2+/HR-; and 27 months for triple negative (P < .001). BMFS was 9 months for HER2-/HR+; 24 months for HER2+/HR+; 9 months for HER2+/HR-; and 7 months for triple negative (P = .06). OSBM was 20 months for HER2-/HR+; 22 months for HER2+/HR+; 24 months for HER2+/HR-; and 9 months for triple negative (P < .001). On multivariate analyses, triple negative showed lower OSBM compared with other subtypes, with a hazard ratio of 1.9 (P < .001).

Conclusion

Comparing all breast cancer subgroups we noticed that HR and HER2 are the most significant biomarkers in brain metastasis behavior. Patients who received targeted therapy had better outcomes, but not in the triple negative group. Prospective studies with different treatment modalities for each subgroup are recommended.

Developmental therapeutics for patients with breast cancer and central nervous system metastasis: current landscape and future perspectives

Breast cancer is the second-leading cause of metastatic disease in the central nervous system (CNS). Recent advances in the biological understanding of breast cancer have facilitated an unprecedented increase of survival in a subset of patients presenting with metastatic breast cancer. Patients with HER2 positive (HER2+) or triple negative breast cancer are at highest risk of developing CNS metastasis, and typically experience a poor prognosis despite treatment with local and systemic therapies. Among the obstacles ahead in the realm of developmental therapeutics for breast cancer CNS metastasis is the improvement of our knowledge on its biological nuances and on the interaction of the blood–brain barrier with new compounds. This article reviews recent discoveries related to the underlying biology of breast cancer brain metastases, clinical progress to date and suggests rational approaches for investigational therapies.

Pathogenesis of Breast Cancer Metastasis to Brain: a Comprehensive Approach to the Signaling Network

There is a general consensus that breast cancer is a rising trend disease in the world. It is one of the most common cancer types and is the leading cause of death among women's cancers. There are several reasons for this high rate of mortality including metastasis which is responsible for about 90 % of cancer-related mortality. Therefore, recognition and understanding of metastatic process is important, and by considering the key role of pathophysiological route in metastasis as a multistep cascade of "invasion-metastasis," it might modify and improve our insight toward this complex phenomenon. Moreover, it can provide novel approaches for designing advanced targeted therapies. The present work aimed to review the published papers regarding molecular basis of metastatic process of breast cancer to brain metastasis, especially related genes and signaling network. Furthermore, the use of molecular aspects of metastatic breast cancer to brain was discussed in horizon of future treatment of breast cancer.

Exploring factors related to metastasis free survival in breast cancer patients using Bayesian cure models

BACKGROUND

Breast cancer is a fatal disease and the most frequently diagnosed cancer in women with an increasing pattern worldwide. The burden is mostly attributed to metastatic cancers that occur in one-third of patients and the treatments are palliative. It is of great interest to determine factors affecting time from cancer diagnosis to secondary metastasis.

MATERIALS AND METHODS

Cure rate models assume a Poisson distribution for the number of unobservable metastatic-component cells that are completely deleted from the non-metastasis patient body but some may remain and result in metastasis. Time to metastasis is defined as a function of the number of these cells and the time for each cell to develop a detectable sign of metastasis. Covariates are introduced to the model via the rate of metastatic-component cells. We used non-mixture cure rate models with Weibull and log-logistic distributions in a Bayesian setting to assess the relationship between metastasis free survival and covariates.

RESULTS

The median of metastasis free survival was 76.9 months. Various models showed that from covariates in the study, lymph node involvement ratio and being progesterone receptor positive were significant, with an adverse and a beneficial effect on metastasis free survival, respectively. The estimated fraction of patients cured from metastasis was almost 48%. The Weibull model had a slightly better performance than log-logistic.

CONCLUSIONS

Cure rate models are popular in survival studies and outperform other models under certain conditions. We explored the prognostic factors of metastatic breast cancer from a different viewpoint. In this study, metastasis sites were analyzed all together. Conducting similar studies in a larger sample of cancer patients as well as evaluating the prognostic value of covariates in metastasis to each site separately are recommended.

Current approaches to the treatment of metastatic brain tumours

Metastatic tumours involving the brain overshadow primary brain neoplasms in frequency and are an important complication in the overall management of many cancers. Importantly, advances are being made in understanding the molecular biology underlying the initial development and eventual proliferation of brain metastases. Surgery and radiation remain the cornerstones of the therapy for symptomatic lesions; however, image-based guidance is improving surgical technique to maximize the preservation of normal tissue, while more sophisticated approaches to radiation therapy are being used to minimize the long-standing concerns over the toxicity of whole-brain radiation protocols used in the past. Furthermore, the burgeoning knowledge of tumour biology has facilitated the entry of systemically administered therapies into the clinic. Responses to these targeted interventions have ranged from substantial toxicity with no control of disease to periods of useful tumour control with no decrement in performance status of the treated individual. This experience enables recognition of the limits of targeted therapy, but has also informed methods to optimize this approach. This Review focuses on the clinically relevant molecular biology of brain metastases, and summarizes the current applications of these data to imaging, surgery, radiation therapy, cytotoxic chemotherapy and targeted therapy.

Translational research in brain metastasis is identifying molecular pathways that may lead to the development of new therapeutic strategies

Central nervous system (CNS) or brain metastasis is an emerging area of interest in organ-specific metastasis research. Lung and breast cancers are the most common types of primary tumors to develop brain metastases. This disease complication contributes significantly to the morbidity and mortality of both of these common cancers; as such, brain metastasis is designated an unmet medical need by the US Food and Drug Administration (FDA). Recently, an increase in incidence of CNS disease has been noted in the literature for breast cancer, while it has been an ongoing major complication from lung cancer. Progress in treating brain metastases has been hampered by a lack of model systems, a lack of human tissue samples, and the exclusion of brain metastatic patients from many clinical trials. While each of those is significant, the major impediment to effectively treating brain metastatic disease is the blood-brain barrier (BBB). This barrier excludes most chemotherapeutics from the brain and creates a sanctuary site for metastatic tumors. Recent findings on the biology of this disease and translational leads identified by molecular studies are discussed in this article.