Identification of neural crest and melanoma cancer cell invasion and migration genes using high-throughput screening and deep attention networks

Journal article

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.

Authors: Kasemeier-Kulesa, J; Martina Perez, S; Baker, R; Kulesa, P

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Developmental Dynamics
• Publication date: 2025-07-10
• Acceptance date: 2025-05-25
• DOI: 10.1002/dvdy.70059
• EISSN: 1097-0177
• ISSN: 1058-8388
• Language: English
• Keywords: neural crest; melanoma; cell invasion; migration; high-throughput; siRNA screen; deep learning; attention networks