Proteomics

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Label-free based DIA quantification of a lung cancer cell line and its potential application in nanomedicine.


ABSTRACT: Lung cancer is the uncontrolled growth of abnormal cells in the lungs, which can form tumors and interfere with the functioning of the lung. This disease is registered worldwide as the most common type of cancer in men as well as the most common cause of death; besides lung cancer mortality in women has experienced a significant increase in recent years. In Mexico, lung cancer was recorded as the leading cause of death, representing 9.7% of the total annual cancer deaths. Small Cell Lung Cancer (SCLC) is a malignant epithelial tumor classified as a high-grade neuroendocrine carcinoma tumor that usually occurs in the central airways4 with high growth rate and early development of metastases. The classic treatments used to treat this type of pathologies are radiotherapies, chemotherapies, and surgeries that tend to be ineffective and with side effects that lead patients' quality of life to low levels. Due to this lack of effectiveness of classic therapies, we are looking for alternative therapies that may be more effective and hopeful for cancer patients; especially those treatments based on the use of nanomedicine. The objective of this work was to use Label-free based DIA approach to evaluate the differences in the proteome of enriched membranes between a SCLC cell line H69AR (ATCC® CRL-11351) and a non-tumoral lung cell line MRC5 (ATCC® CCL171), and additionally, compare which protein receptors are overexpressed in cancer vs normal cells, in this way we can select the best target for functionalization of core-shell nanoparticles (CSNPs) to improve the affinity of the therapy for the cancer cell instead of normal cell, this in order to decrease the negative effects of chemotherapeutic drugs in healthy cells.

INSTRUMENT(S): Synapt MS

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Epithelial Cell, Cell Culture, Fibroblast

SUBMITTER: Emmanuel Rios-Castro  

LAB HEAD: Jose Tapia-Ramirez

PROVIDER: PXD015405 | Pride | 2022-08-19

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
20190313_HDMSE_HAR.raw.zip Raw
20190313_HDMSE_MRC.raw.zip Raw
20190313_MSE_HAR.raw.zip Raw
20190313_MSE_MRC.raw.zip Raw
20190313_UDMSE_HAR_001.raw.zip Raw
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