Background COVID‐19 has become a pandemic, but its reported characteristics and outcomes vary greatly amongst studies. Objectives We determined pooled estimates for clinical characteristics and outcomes in COVID‐19 patients including subgroups by disease severity (based on WHO Interim Guidance Report or IDSA/ATS criteria) and by country/region. Methods We searched Pubmed, Embase, Scopus, Cochrane, Chinese Medical Journal, and preprint databases from January 1, 2020 to April 6, 2020. Studies of laboratory confirmed COVID‐19 patients with relevant data were included. Two reviewers independently performed study selection and data extraction. Results From 6,007 articles, 212 studies from 11 countries/regions involving 281,461 individuals were analyzed. Overall, mean age was 46 . 7 years, 51.8% were male, 22.9% had severe disease, and mortality was 5.6%. Underlying immunosuppression, diabetes, and malignancy were most strongly associated with severe COVID‐19 (coefficient=53.9, 23.4, 23.4, respectively, all p<0.0007), while older age, male gender, diabetes, and hypertension were also associated with higher mortality (coefficient=0.05 per year, 5.1, 8.2, 6.99, respectively, p=0.006 to 0.0002). Gastrointestinal (nausea, vomiting, abdominal pain) and respiratory symptoms (shortness of breath, chest pain) were associated with severe COVID‐19, while pneumonia and end organ failure were associated with mortality. Conclusion COVID‐19 is associated with a severe disease course in about 23% and mortality in about 6% of infected persons. Individuals with comorbidities and clinical features associated with severity should be monitored closely, and preventive efforts should especially target those with diabetes, malignancy and immunosuppression. This article is protected by copyright. All rights reserved.

Conventional immunohistochemistry (IHC) is a widely used diagnostic technique in tissue pathology. However, this technique is associated with a number of limitations, including high inter-observer variability and the capacity to label only one marker per tissue section. This review details various highly multiplexed techniques that have emerged to circumvent these constraints, allowing simultaneous detection of multiple markers on a single tissue section and the comprehensive study of cell composition, cellular functional and cell-cell interactions. Among these techniques, multiplex Immunohistochemistry/Immunofluorescence (mIHC/IF) has emerged to be particularly promising. mIHC/IF provides high-throughput multiplex staining and standardized quantitative analysis for highly reproducible, efficient and cost-effective tissue studies. This technique has immediate potential for translational research and clinical practice, particularly in the era of cancer immunotherapy.

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Intratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can confer a high success rate, selective pressures coupled with dynamic evolution within a tumour can drive the emergence of drug-resistant clones that allow tumours to persist in certain patients. To improve immunotherapy efficacy, researchers have used transcriptional spatial profiling techniques to identify and subsequently block the source of tumour heterogeneity. In this review, we describe and assess the different technologies available for such profiling within a cancer tissue. We first outline two well-known approaches, in situ hybridization and digital spatial profiling. Then, we highlight the features of an emerging technology known as Visium Spatial Gene Expression Solution. Visium generates quantitative gene expression data and maps them to the tissue architecture. By retaining spatial information, we are well positioned to identify novel biomarkers and perform computational analyses that might inform on novel combinatorial immunotherapies.