Skip to content
#protein folding Open access

Elucidating the In Vitro Adverse Effect of Functionalized Single-Walled Carbon Nanotubes Against Breast Cancer Cells at the Proteomics Level.

Sep 2026 · Journal of Applied Toxicology · 0 citations · 89 references
Medicine

Abstract

The tremendous therapeutic potential of carbon-based nanomaterials (CNMs) has been limited by inconsistent data regarding the nanotoxicity assessment. Although a bulk of studies have been performed to assess the in vitro cytotoxicity mechanism of CNMs, the exact factors responsible for the cytotoxicity of CNMs have not been fully understood. With the rapid advancement of mass spectrometry technologies, proteomics has emerged as a powerful strategy for systematically investigating the molecular and cellular mechanisms underlying toxicity induced by nanomaterials. This study examined the in vitro cytotoxicity of single-walled carbon nanotubes (SWCNTs) in human MCF-7 breast cancer cells by conducting a comparative proteome-level analysis using mass spectrometry. Initially, the characterized SWCNTs were incubated with MCF-7 cells for 3, 6, and 24 h. Proteins were subsequently extracted from each treatment group and subjected to nano-liquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. The relative abundance of the identified proteins was determined by comparison with the control group, and differential expression patterns, including upregulated and downregulated proteins, were assessed. A total of 3482 unique protein groups were identified across all exposure periods. Among these, 3466 protein groups were detected following 3 h of exposure, 3469 following 6 h of exposure, and 3480 following 24 h of exposure. Compared with the control group, the identified differentially expressed proteins exhibited fold changes ranging from 2-fold to 20-fold across the incubation periods. In total, 70 proteins were found to be significantly regulated following SWCNT exposure. Of the differentially expressed proteins, 45 were significantly upregulated, whereas 25 were significantly downregulated. Visualization of these regulations over time was shown in a heatmap of log2-transformed fold-change values to explore time-specific proteomic alterations. Functional enrichment analysis of these proteins also showed that the regulated proteins were significantly associated with Reactome pathways, including ER-to-Golgi anterograde transport, Golgi-to-ER retrograde transport, COPI-mediated vesicle trafficking, regulation of insulin-like growth factor transport and uptake by insulin-like growth factor-binding proteins, protein metabolism, and posttranslational protein modification. Furthermore, a systematic comparison of previous studies within the present findings was provided to situate our study within the broader context of understanding CNT-induced cellular toxicity. Collectively, these findings provided an important proteomic evidence of the adverse effects of SWCNTs on MCF-7 cells. Furthermore, this study showed a comprehensive proteomic landscape of cellular responses to SWCNT exposure, contributing to a better understanding of the molecular mechanisms underlying SWCNT-induced cytotoxicity and bridging the gap between protein regulation and the resulting cellular responses. In this study, we characterized the proteomic landscape of MCF-7 cells following SWCNT exposure, revealing molecular mechanisms associated with cellular responses and cytotoxicity. The identified differentially expressed proteins established a link between altered protein regulation and SWCNT-induced cellular effects. Moreover, these proteins need to be further validated in different cell models and would potentially represent promising candidates for the identification of novel molecular targets involved in SWCNT-induced cytotoxicity.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.