Determination of biomarker candidates with proteomics approach in small cell lung cancer: NCI-H209 cell line

Proteins, the primary building blocks of the cell membrane, play crucial roles in communication between cells as well as interactions with the extracellular matrix. They make for an excellent resource for disease identification due to their potential as biomarkers. In order to perform the study, HEL-299 (CCL-137™) and NCI-H209 lung cells were incubated at 37°C in a chamber that contained 5% CO2. Trypsinization was used to transfer the cells into Eppendorf tubes. Proteomics analyses were carried out using LC-QTOF equipment, and the corresponding procedures of denaturation, alkynylation, trypsinization, and purification were carried out by adding the required chemicals. The Searchquie and PeptideShacker software interfaces were used to assess the analysis findings. Proteins that differ across groups are displayed by classifying them based on their roles as cellular components, molecular activities, and biological processes. Proteomics data showed that the lung cancer cell line NCI-H209 lacked 14 proteins that were present in the healthy lung cell HEL-299. These are the proteins ANK3, PIK3R2, INPP5F, HSF1, VIM, NFAM1, SHROOM3, ETV4, RNF31, LMNA, BRD8, PRTN3, TERT, SMAD9. There were discovered to be 5 distinct proteins in the lung cancer group compared to healthy lung HEL-299 cells. These proteins are AHSG, NCOA6, VCP, DNAJC19, NCL. Given the heterogeneity of lung cancer, a thorough and in-depth investigation of lung cancer proteome profiling is necessary for effective target treatment. The examination of proteins as prospective lung cancer biomarker candidates shows that it will make up a viable source for clinical investigations. These proteins differ in the direction in this study. Potential clinical applications of the biomarkers identified in this study, such as early diagnosis, monitoring treatment response, and determining disease prognosis, may contribute to the development of personalized medicine approaches.

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Journal
Frontiers in Life Sciences and Related Technologies
Published
2024-11-05
DOI
https://doi.org/10.51753/flsrt.1511261
Citations
1
Primary Topic
Machine Learning in Bioinformatics
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article
Field-Weighted Citation Impact
0.23
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article

Determination of biomarker candidates with proteomics approach in small cell lung cancer: NCI-H209 cell line

Nebiye Pelin Türker, Saffet Çelìk
1 citations
Frontiers in Life Sciences and Related Technologies
Machine Learning in Bioinformatics
0.23
article

Determination of biomarker candidates with proteomics approach in small cell lung cancer: NCI-H209 cell line

Nebiye Pelin Türker, Saffet Çelìk
article en
1 citations

Abstract

Proteins, the primary building blocks of the cell membrane, play crucial roles in communication between cells as well as interactions with the extracellular matrix. They make for an excellent resource for disease identification due to their potential as biomarkers. In order to perform the study, HEL-299 (CCL-137™) and NCI-H209 lung cells were incubated at 37°C in a chamber that contained 5% CO2. Trypsinization was used to transfer the cells into Eppendorf tubes. Proteomics analyses were carried out using LC-QTOF equipment, and the corresponding procedures of denaturation, alkynylation, trypsinization, and purification were carried out by adding the required chemicals. The Searchquie and PeptideShacker software interfaces were used to assess the analysis findings. Proteins that differ across groups are displayed by classifying them based on their roles as cellular components, molecular activities, and biological processes. Proteomics data showed that the lung cancer cell line NCI-H209 lacked 14 proteins that were present in the healthy lung cell HEL-299. These are the proteins ANK3, PIK3R2, INPP5F, HSF1, VIM, NFAM1, SHROOM3, ETV4, RNF31, LMNA, BRD8, PRTN3, TERT, SMAD9. There were discovered to be 5 distinct proteins in the lung cancer group compared to healthy lung HEL-299 cells. These proteins are AHSG, NCOA6, VCP, DNAJC19, NCL. Given the heterogeneity of lung cancer, a thorough and in-depth investigation of lung cancer proteome profiling is necessary for effective target treatment. The examination of proteins as prospective lung cancer biomarker candidates shows that it will make up a viable source for clinical investigations. These proteins differ in the direction in this study. Potential clinical applications of the biomarkers identified in this study, such as early diagnosis, monitoring treatment response, and determining disease prognosis, may contribute to the development of personalized medicine approaches.

Frontiers in Life Sciences and Related TechnologiesVol. 5(3)
Trakya University (TR)
Good health and well-being
Openalex Percentile: Top 41%
Machine Learning in Bioinformatics
0.23
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