4.8 Article

In-depth proteomic analysis reveals unique subtype-specific signatures in human small-cell lung cancer

Journal

CLINICAL AND TRANSLATIONAL MEDICINE
Volume 12, Issue 9, Pages -

Publisher

JOHN WILEY & SONS LTD
DOI: 10.1002/ctm2.1060

Keywords

diagnostic biomarkers; molecular targets; proteomics; secretome; small-cell lung cancer; subtype; transcriptomics

Funding

  1. Semmelweis 250+ Excellence PhD Scholarship [EFOP-3.6.3-VEKOP-16-2017-00009]
  2. Hungarian National Research, Development and Innovation Office [KH130356, KKP126790, KNN121510, 2020-1.1.6-JOVO, TKP2021-EGA-33]
  3. Austrian Science Fund [T 1062-B33, FWF I3522, FWF I3977, I4677]
  4. New National Excellence Program of the Ministry for Innovation and Technology of Hungary [UNKP-20-3, UNKP-21-3, UNKP-19-4]
  5. Hungarian Respiratory Society
  6. Netherlands X-omics Initiative (NWO) [184.034.019]
  7. Bolyai Research Scholarship of the Hungarian Academy of Sciences
  8. City of Vienna Fund for Innovative Interdisciplinary Cancer Research
  9. Mrs. Berta Kampradts Cancer Foundation [FBKS-2020-22-(291)]

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This study reveals the protein expression differences among subtypes of small-cell lung cancer (SCLC) and identifies potential subtype-specific therapeutic vulnerabilities and diagnostic biomarkers.
Background: Small-cell lung cancer (SCLC) molecular subtypes have been primarily characterized based on the expression pattern of the following key transcription regulators: ASCL1 (SCLC-A), NEUROD1 (SCLC-N), POU2F3 (SCLC-P) and YAP1 (SCLC-Y). Here, we investigated the proteomic landscape of these molecular subsets with the aim to identify novel subtype-specific proteins of diagnostic and therapeutic relevance. Methods: Pellets and cell media of 26 human SCLC cell lines were subjected to label-free shotgun proteomics for large-scale protein identification and quantitation, followed by in-depth bioinformatic analyses. Proteomic data were correlated with the cell lines' phenotypic characteristics and with public transcriptomic data of SCLC cell lines and tissues. Results: Our quantitative proteomic data highlighted that four molecular sub-types are clearly distinguishable at the protein level. The cell lines exhibited diverse neuroendocrine and epithelial-mesenchymal characteristics that varied by subtype. A total of 367 proteins were identified in the cell pellet and 34 in the culture media that showed significant up- or downregulation in one subtype, including known druggable proteins and potential blood-based markers. Pathway enrichment analysis and parallel investigation of transcriptomics from SCLC cell lines outlined unique signatures for each subtype, such as upregulated oxidative phosphorylation in SCLC-A, DNA replication in SCL-CN, neurotrophin signalling in SCLC-P and epithelial-mesenchymal transition in SCLC-Y. Importantly, we identified the YAM-driven subtype as the most distinct SCLC subgroup. Using sparse partial least squares discriminant analysis, we identified proteins that clearly distinguish four SCLC subtypes based on their expression pattern, including potential diagnostic markers for SCLC-Y (e.g. GPX8, PKD2 and UFO). Conclusions: We report for the first time, the protein expression differences among SCLC subtypes. By shedding light on potential subtype-specific therapeutic vulnerabilities and diagnostic biomarkers, our results may contribute to a better understanding of SCLC biology and the development of novel therapies.

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