Protein co-expression network-based profiles revealed from laser-microdissected cancerous cells of lung squamous-cell carcinomas

Sci Rep. 2021 Oct 12;11(1):20209. doi: 10.1038/s41598-021-99695-x.

Abstract

No therapeutic targets have been identified for lung squamous cell cancer (SqCC) which is the second most prevalent lung cancer because its molecular profiles remain unclear. This study aimed to unveil disease-related protein networks by proteomic and bioinformatic assessment of laser-microdissected cancerous cells from seven SqCCs compared with eight representative lung adenocarcinomas. We identified three network modules significant to lung SqCC using weighted gene co-expression network analysis. One module was intrinsically annotated to keratinization and cell proliferation of SqCC, accompanied by hypoxia-induced aerobic glycolysis, in which key regulators were activated (HIF1A, ROCK2, EFNA1-5) and highly suppressed (KMT2D). The other two modules were significant for translational initiation, nonsense-mediated mRNA decay, inhibited cell death, and interestingly, eIF2 signaling, in which key regulators, MYC and MLXIPL, were highly activated. Another key regulator LARP1, the master regulator in cap-dependent translation, was highly suppressed although upregulations were observed for hub proteins including EIF3F and LARP1 targeted ribosomal proteins, among which PS25 is the key ribosomal protein in IRES-dependent translation. Our results suggest an underlying progression mechanism largely caused by switching to the cap-independent, IRES-dependent translation of mRNA subsets encoding oncogenic proteins. Our findings may help to develop therapeutic strategies to improve patient outcomes.

MeSH terms

  • Adenocarcinoma of Lung / metabolism*
  • Aged
  • Carcinoma, Squamous Cell / metabolism*
  • Cell Line, Tumor
  • Female
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Laser Capture Microdissection
  • Lung Neoplasms / metabolism*
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Protein Interaction Maps
  • Proteomics / methods*