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Processing and Analysis of Tissue Samples from Esophageal Cancer Patients in an African Setting

Updated: Sep 21, 2021

Lucien Ferndale, Mishalan Moodley, Wenlong C. Chen, Reubina Wadee, Colleen A. Wright, Mohamed Iqbal Parker, Pascale Willem, and Christopher G. Mathew

Although infectious diseases continue to present a major health care problem in Africa, the incidence of cancer is increasing rapidly on the African continent and this merits an increased investment in cancer research in low to medium resource settings. Esophageal squamous cell carcinoma (ESCC) has a high incidence in Eastern and Southern Africa, with late clinical presentation and a very poor prognosis. There is limited research on the

molecular pathology of this cancer in Africa, partly as a result of a lack of infrastructure for biobanking and sample processing in many African countries. The aim of this study was to establish a practical and robust workflow to collect, store, and process esophageal cancer samples such that both the tissue architecture and quality of the samples would be preserved and suitable for future genomic research. We developed a workflow

that allows storage of fresh biopsy tissue in sterile Eppendorf tubes containing RNAlater, an efficient RNAse inhibitor. We collected 142 ESCC biopsy samples and showed that storage in RNAlater for up to 18 months did not alter tissue morphology, thus allowing histologic assessment by experienced pathologists and determination of tumor content in each biopsied sample. DNA and RNA extracted from tissue samples was assessed for purity,

molecular size, and yield. The quantity and quality of nucleic acids obtained were suitable for genomic applications, and whole-exome sequencing of DNA from tumor tissues produced sequence data with a high proportion of both usable reads and correct base calling. We conclude that this workflow may be applicable to a wide range of malignancies for future genomic research in low-resource settings.

Keywords: esophageal, cancer, sample, processing, analysis

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