Distinct spatial landscapes in clear-cell renal cell carcinoma as revealed by whole transcriptome analysis.

Background: Clear-cell renal cell carcinoma (ccRCC) is the most common and aggressive form of renal cancer and a paradigm of inter- and intratumor heterogeneity. We carried out an exploratory digital spatial profiling of the tumor interior and periphery of two ccRCC tumor specimens and mapped spatially the molecular and cellular composition of their tumor microenvironment and ecosystem. Materials and methods: Digital spatial profiling of the whole transcriptome of 19 regions of interest (ROIs) was carried out from two selected highly immunogenic stage pT3a/grade 3 (G3) and stage pT3a/grade 4 (G4) ccRCC. A total of 9-10 ROIs were selected from distinct areas from each tumor, including tumor interior and tumor periphery, and differences in gene expression were analyzed by RNA sequencing, pathway enrichment analysis, and cell deconvolution. Results: The distinct areas from the two locally advanced tumors displayed unique gene expression spatial patterns defining distinct biological pathways. Dimensional reduction analysis showed that the G3 ccRCC, compared to the G4 ccRCC, correlated with more variability between regions from the tumor interior and tumor periphery. Cell deconvolution analysis illustrated higher abundance of immune cells, including macrophages, myeloid dendritic cells, and CD4 T cells, and lower abundance of regulatory T cells in the tumor periphery compared to the tumor interior. Conclusions: Transcriptome spatial profiling revealed high inter- and intratumor heterogeneity in the analyzed tumors and provided information with potential clinical utility. This included the finding of less intratumor heterogeneity and more tumor-infiltrated T cells in the ccRCC tumor specimen with a higher grade.

Managed public mental healthcare: issues, trends, and prospects.

OBJECTIVE: To describe the structure and status of public mental healthcare and the impact of managed behavioral healthcare on this system. STUDY DESIGN AND METHODS: The structure and financing of public mental health systems were reviewed. Because there are no controlled multisite studies of managed public sector behavioral healthcare, case examples were used to illustrate trends and issues. DISCUSSION: The methods, results, and impact of public managed behavioral healthcare are incomplete and uncertain. The complexity of the public sector system, the patients served in it, and the services provided are daunting. The variability of patient needs, the role of Medicaid versus state funding, and the variable governance structures of local systems in different states make managed care methods more complex than in private markets. CONCLUSIONS: The organization, structure, and financing of public mental health systems have developed rapidly in the past generation as care has been moved from hospital to community. Early efforts to apply managed behavioral healthcare methods used in the private, commercially paid sector have not been very successful, and most public sector managed care efforts have been limited to Medicaid-paid care. The trend in public mental health systems is to "unpack" managed care and use its tools selectively.

Normal housing: a key element of a supported housing approach for people with psychiatric disabilities.

This article summarizes current thinking in the field about the types of housing environments which are most relevant both to the overall goal of community integration, and to the variety of specific support needs of individuals with psychiatric disabilities. Within the context of a "supported housing" approach, which focuses on maximizing consumers choices and preferences, using integrated regular housing stock, and making a full array of community supports available, the authors propose a number of specific criteria which can be useful to community mental health organizations in planning for, or selecting housing.

Data and decisions: can mental health management be knowledge-based?

Three major factors suggest a healthy future for data-based decision making within mental health authorities: (1) the improved knowledge base related to the treatment and management of serious mental illness, (2) advances in data-processing technology and (3) conceptual advances in management information system design, most notably the National Institute of Mental Health (NIMH) Mental Health Statistics Improvement Package. This paper briefly outlines these three factors and goes on to examine information needed by state mental health authorities (SMHAs) to enhance decision making. The client-level data necessary for data-based policy decisions, while still scarce, are increasingly available and are increasingly finding homes within SMHA management information systems. As SMHAs improve their information systems to accommodate such data, they face substantial implementation challenges and substantial payoffs in terms of increased knowledge for decision making.