Proteomic-Based Approaches for the Study of Cytokines in Lung Cancer

Abstract

Proteomic techniques are currently used to understand the biology of different human diseases, including studies of the cell signaling pathways implicated in cancer progression, which is important in knowing the roles of different proteins in tumor development. Due to its poor prognosis, proteomic approaches are focused on the identification of new biomarkers for the early diagnosis, prognosis, and targeted treatment of lung cancer. Cytokines are proteins involved in inflammatory processes and have been proposed as lung cancer biomarkers and therapeutic targets because it has been reported that some cytokines play important roles in tumor development, invasion, and metastasis. In this review, we aim to summarize the different proteomic techniques used to discover new lung cancer biomarkers and therapeutic targets. Several cytokines have been identified as important players in lung cancer using these techniques. We underline the most important cytokines that are useful as biomarkers and therapeutic targets. We also summarize some of the therapeutic strategies targeted for these cytokines in lung cancer.

Estrogen‐related receptor alpha triggers the proliferation and migration of human non‐small cell lung cancer via interleukin‐6

“…25 More specifically, increased levels of IL-6, IL-8, IL-10, IL-22, VEGF, TGF-β, and TNF-α have been observed in serum of NSCLC patients and are correlated with poor therapy outcomes. 5 Our results revealed that knockdown of ERRα can significantly decrease the expression of IL-6, while not IL-8, IL-10, IL-22, VEGF, TGF-β, or TNF-α, in A549 cells ( Figure 4A).…”

“…It indicates that gender‐dependent factors may be involved in the incidence and progression of NSCLC . Increased levels of cytokines such as IL‐6, IL‐8, IL‐10, IL‐22, VEGF, TGF‐β, and TNF‐α have been observed in serum of NSCLC patients and are correlated with poor therapy outcomes . For example, IL‐6 secreted from cancer‐associated fibroblasts can trigger the chemoresistance in NSCLC by increasing epithelial‐mesenchymal transition (EMT) signalling .…”

“…4 Increased levels of cytokines such as IL-6, IL-8, IL-10, IL-22, VEGF, TGF-β, and TNF-α have been observed in serum of NSCLC patients and are correlated with poor therapy outcomes. 5 For example, IL-6 secreted from cancer-associated fibroblasts can trigger the chemoresistance in NSCLC by increasing epithelialmesenchymal transition (EMT) signalling. 6 The autocrine of IL-8 and VEGF can trigger the EMT and invasiveness via p38/JNK-ATF-2 signalling in A549 lung cancer cells.…”

Sparse Proteomics Analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

“…To test the algorithm's performance increasing amount of Gaussian noise n i ∼ N (0, σ 2 ) with σ = {0.1, 0.3} was added to DS1 and DS2. These corresponds to signal-to-noise (SNR) ratio of 10, 3.33 repectively 15 . The values of SNR are chosen to represent the behaviour of the algorithm up to the levels of noise that are normally found in MS data.…”

“…The bisection method was used until the optimal sparsity parameter was found or the difference between the two consecutive parameters became smaller than a preset tolerance. 15 Signal-to-noise ratio was calculated as SN R = power of signal power of noise . 16 Due to the redundancy of the peak-associated feature variables (cf.…”