Cross-sectional survey of patients, caregivers, and physicians on diagnosis and treatment of brain metastases.

BACKGROUND: The development of brain metastases (BM) is one of the most feared complications of cancer due to the substantial neurocognitive morbidity and a grim prognosis. In the past decade, targeted therapies and checkpoint inhibitors have demonstrated promising intracranial response rates for tumors of multiple histologies. As overall survival for these patients improves, there is a growing need to identify issues surrounding patient survivorship and to standardize physician practice patterns for these patients. To date, there has not been an adequate study to specifically explore these questions of survivorship and practice standardization for patients with advanced cancer and BM. METHODS: Here, we present results from a cross-sectional survey in which we analyze responses from 237 patients, 209 caregivers, and 239 physicians to identify areas of improvement in the clinical care of BM. RESULTS: In comparing physician and patient/caregiver responses, we found a disparity in the perceived discussion of topics pertaining to important aspects of BM clinical care. We identified variability in practice patterns for this patient population between private practice and academic physicians. Many physicians continue to have patients with BM excluded from clinical trials. Finally, we obtained patient/physician recommendations on high-yield areas for federal funding to improve patient quality of life. CONCLUSION: By identifying potential areas of unmet need, we anticipate this wealth of actionable information will translate into tangible benefits for both patients and caregivers. Future studies are needed to validate our findings.

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

Critical analysis of the potential for microRNA biomarkers in breast cancer management.

Breast cancer is a complex and heterogeneous disease. Signaling by estrogen receptor (ER), progesterone receptor (PR), and/or human EGF-like receptor 2 (HER2) is a main driver in the development and progression of a large majority of breast tumors. Molecular characterization of primary tumors has identified major subtypes that correlate with ER/PR/HER2 status, and also subgroup divisions that indicate other molecular and cellular features of the tumors. While some of these research findings have been incorporated into clinical practice, several challenges remain to improve breast cancer management and patient survival, for which the integration of novel biomarkers into current practice should be beneficial. microRNAs (miRNAs) are a class of short non-coding regulatory RNAs with an etiological contribution to breast carcinogenesis. miRNA-based diagnostic and therapeutic applications are rapidly emerging as novel potential approaches to manage and treat breast cancer. Rapid technological development enables specific and sensitive detection of individual miRNAs or the entire miRNome in tissues, blood, and other biological specimens from breast cancer patients. This review focuses on recent miRNA research and its potential to address unmet clinical needs and challenges. The four sections presented discuss miRNA findings in the context of the following clinical challenges: biomarkers for early detection; prognostic and predictive biomarkers for treatment decisions using targeted therapies against ER and HER2; diagnostic and prognostic biomarkers for subgrouping of triple-negative breast cancer, for which there are currently no targeted therapies; and biomarkers for monitoring and characterization of metastatic breast cancer. The review concludes with a critical analysis of the current state of miRNA breast cancer research and the need for further studies using large patient cohorts under well-controlled conditions before considering the clinical implementation of miRNA biomarkers.

Stromal expression of miR-21 identifies high-risk group in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype defined by the lack of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 expression. Expression of miR-21, an oncomiR, is frequently altered and may be distinctly expressed in the tumor stroma. Because tumor lesions are a complex mixture of cell types, we hypothesized that analysis of miR-21 expression at single-cell resolution could provide more accurate information to assess disease recurrence risk and BC-related death. We implemented a fully automated, tissue slide-based assay to detect miR-21 expression in 988 patients with BC. The miR-21(High) group exhibited shorter recurrence-free survival [hazard ratio (HR), 1.71; P < 0.001] and BC-specific survival (HR, 1.96; P < 0.001) in multivariate regression analyses. When tumor compartment and levels of miR-21 expression were considered, significant associations with poor clinical outcome were detected exclusively in tumor epithelia from estrogen receptor- and/or progesterone receptor-positive human epidermal growth factor receptor 2-negative cases [recurrence-free survival: HR, 3.67 (P = 0.006); BC-specific survival: HR, 5.13 (P = 0.002)] and in tumor stroma from TNBC cases [recurrence-free survival: HR, 2.59 (P = 0.013); BC-specific survival: HR, 3.37 (P = 0.003)]. These findings suggest that the context of altered miR-21 expression provides clinically relevant information. Importantly, miR-21 expression was predominantly up-regulated and potentially prognostic in the tumor stroma of TNBC.