Identification of Neural Crest and Neural Crest-Derived Cancer Cell Invasion and Migration Genes Using High-throughput Screening and Deep Attention Networks

利用高通量筛选和深度注意力网络鉴定神经嵴及神经嵴衍生的癌细胞侵袭和迁移基因

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Abstract

BACKGROUND: Cell migration and invasion are well-coordinated processes in development and disease but remain poorly understood. We previously showed that highly migratory neural crest (NC) cells share a 45-gene panel with other cell invasion phenomena, including cancer. To identify critical genes of the 45-gene panel, we performed a high-throughput siRNA screen and used statistical and deep learning methods to compare NC- versus non-NC-derived human cell lines. RESULTS: We find 14 out of 45 genes significantly reduces c8161 melanoma cell migration; only 4 are shared with HT1080 fibrosarcoma cells (BMP4, ITGB1, KCNE3, RASGRP1). Deep learning attention network analysis identified distinct cell-cell interaction patterns and significant alterations after BMP4 or RASGRP1 knockdown in c8161 cells. Addition of recombinant proteins to the culture media identified 5 out of the 10 known secreted molecules stimulate c8161 cell migration, including BMP4. BMP4 siRNA knockdown inhibited c8161 cell invasion in vivo and in vitro ; however, its addition to the culture media rescued c8161 cell invasion. CONCLUSION: A high-throughput screen and deep learning rapidly distilled a 45-gene panel to a small subset of genes that appear critical to melanoma cell invasion and warrant deeper in vivo functional analysis for their role in driving the neural crest.

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