Dataset Information

Predicting Cancer Cell Line Dependencies From the Protein Expression Data of Reverse-Phase Protein Arrays.

ABSTRACT:

Purpose

Predicting cancer dependencies from molecular data can help stratify patients and identify novel therapeutic targets. Recently available data on large-scale cancer cell line dependency allow a systematic assessment of the predictive power of diverse molecular features; however, the protein expression data have not been rigorously evaluated. By using the protein expression data generated by reverse-phase protein arrays, we aimed to assess their predictive power in identifying cancer dependencies and to develop a related analytic tool for community use.

Materials and methods

By using a machine learning schema, we conducted an analysis of feature importance based on cancer dependency and multiomic data from the DepMap and Cancer Cell Line Encyclopedia projects. We assessed the consistency of cancer dependency data between CRISPR/Cas9 and short hairpin RNA-mediated perturbation platforms. For a fair comparison, we focused on a set of genes with robust dependency data and four available expression-related features (copy number alteration, DNA methylation, messenger RNA expression, and protein expression) and performed the same-gene predictions of the cancer dependency using different molecular features.

Results

For the genes surveyed, we observed that the protein expression data contained substantial predictive power for cancer dependencies, and they were the best predictive feature for the CRISPR/Cas9-based dependency data. We also developed a user-friendly protein-dependency analytic module and integrated it with The Cancer Proteome Atlas; this module allows researchers to explore and analyze our results intuitively.

Conclusion

This study provides a systematic assessment for predicting cancer dependencies of cell lines from different expression-related features of a gene. Our results suggest that protein expression data are a highly valuable information resource for understanding tumor vulnerabilities and identifying therapeutic opportunities.

SUBMITTER: Chen MM

PROVIDER: S-EPMC7259880 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundProtein expression profiles throughout 28 days of peripheral nerve regeneration were characterized using an established rat sciatic nerve transection injury model. Reverse phase protein microarrays were used to identify the spatial and temporal expression profile of multiple proteins implicated in peripheral nerve regeneration including growth factors, extracellular matrix proteins, and proteins involved in adhesion and migration. This high-throughput approach enabled the simultaneous analysis of 3,360 samples on a nitrocellulose-coated slide.ResultsThe extracellular matrix proteins collagen I and III, laminin gamma-1, fibronectin, nidogen and versican displayed an early increase in protein levels in the guide and proximal sections of the regenerating nerve with levels at or above the baseline expression of intact nerve by the end of the 28 day experimental course. The 28 day protein levels were also at or above baseline in the distal segment however an early increase was only noted for laminin, nidogen, and fibronectin. While the level of epidermal growth factor, ciliary neurotrophic factor and fibroblast growth factor-1 and -2 increased throughout the experimental course in the proximal and distal segments, nerve growth factor only increased in the distal segment and fibroblast growth factor-1 and -2 and nerve growth factor were the only proteins in that group to show an early increase in the guide contents. As expected, several proteins involved in cell adhesion and motility; namely focal adhesion kinase, N-cadherin and ?-catenin increased earlier in the proximal and distal segments than in the guide contents reflecting the relatively acellular matrix of the early regenerate.ConclusionsIn this study we identified changes in expression of multiple proteins over time linked to regeneration of the rat sciatic nerve both demonstrating the utility of reverse phase protein arrays in nerve regeneration research and revealing a detailed, composite spatiotemporal expression profile of peripheral nerve regeneration.