Neurology India | 2019
Brain metastasis: Momentum towards understanding the molecular milieu
Abstract
Brain metastases are the most common and devastating neurologic complications of systemic cancer that occurs in approximately 20% of patients with cancer.[1,2] However, the incidence of brain metastases is increasing because of better detection from improved imaging techniques, a lower threshold of magnetic resonance imaging (MRI) for screening and follow-up, more effective loco-regional and systemic treatment regimens that can prolong life, as well as permitting the cancer to disseminate to the brain, a sanctuary site. The common sources of primary cancers that result in brain metastases include lung, breast, an unknown primary, colorectal, melanoma, and renal cell carcinoma. Until the recent past, outcomes in patients with brain metastases were universally dismal with considerable nihilism in the management recommendations, and the patients were treated with palliative intent only. More definitive treatments, such as surgical resection and stereotactic radiosurgery, were used occasionally till reports of much better outcomes for select populations were noted. The number of brain metastasis, the source of the primary tumor, the volume and stage of the extracranial disease, the timing of brain metastasis with respect to the diagnosis of the primary lesion, the disease free interval, the patient’s age, the performance status and the type of treatment received have been some of the important predictors for outcome. Data-driven prognostication tools for patients with brain metastases, including the recursive partitioning analysis (RPA) score,[3] have been used to prognosticate and select patients suitable for aggressive treatments such as surgery and/or radiosurgery. Most of these traditional tools have been dependent on clinical parameters rather than biological factors. Although these are reasonably robust, we now know that there are inherent biological factors at play. Graded Prognostic Assessment (GPA), which includes histology‐specific information and driver mutation status, is already being used in the assessment of lung and breast cancer.[4,5] The molecular signature of the tumour, especially the status driver mutations, have been increasingly recognized to impact the outcome of these patients. For example, in patients with non-small-cell lung carcinoma (NSCLC) brain metastases, the presence or absence of mutations in epidermal growth factor receptor (EGFR) and translocations of anaplastic lymphoma kinase positive (ALK) gene can influence survival.[4] The tumour subtype can also substantially affect the prognosis for patients with breast cancer who have brain metastases.[5]