• BMB Reports
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• v.57 no.3
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• pp.155-160
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• 2024

Lung cancer carries one of the highest mortality rates among all cancers. It is often diagnosed at more advanced stages with limited treatment options compared to other malignancies. This study focuses on calnexin as a potential biomarker for diagnosis and treatment of lung cancer. Calnexin, a molecular chaperone integral to N-linked glycoprotein synthesis, has shown some associations with cancer. However, targeted therapeutic or diagnostic methods using calnexin have been proposed. Through 1D-LCMSMS, we identified calnexin as a biomarker for lung cancer and substantiated its expression in human lung cancer cell membranes using Western blotting, flow cytometry, and immunocytochemistry. Anti-calnexin antibodies exhibited complement-dependent cytotoxicity to lung cancer cell lines, resulting in a notable reduction in tumor growth in a subcutaneous xenograft model. Additionally, we verified the feasibility of labeling tumors through in vivo imaging using antibodies against calnexin. Furthermore, exosomal detection of calnexin suggested the potential utility of liquid biopsy for diagnostic purposes. In conclusion, this study establishes calnexin as a promising target for antibody-based lung cancer diagnosis and therapy, unlocking novel avenues for early detection and treatment.

• BMB Reports
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• v.41 no.9
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• pp.615-625
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• 2008

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.

• Biomedical Science Letters
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• v.29 no.4
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• pp.336-343
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• 2023

Lung cancer is one of the cancers with high mortality and incidence rates worldwide. Although, various anticancer research efforts are underway to completely treat cancer, the challenge against it remains in the inability to eliminate cancer stem cells (CSCs), leading to difficulties in curing the cancer and resulting in recurrence. As a result, there is a growing interest in the discovery of new biomarkers and therapeutic molecules that can simultaneously target both cancer cells and CSCs. From this point of view, we focused on fibronectin leucine rich transmembrane protein 3 (FLRT3), one of the genes known to be present in human lung cells and the discovery from our previous cancer proteomic analysis study. This study aimed to evaluate the potential of FLRT3 as a specific therapeutic biomarker for lung cancer and Lung Cancer-derived-Stem Cells (LCSC). Also, to estimate the biological function of FLRT3 in cancer and LCSC, short hairpin RNA (shRNA) was generated and showed the ability of the decreased-cell migration and cell proliferation of lung cancer through ERK signaling pathway when FLRT3 was knock-downed. In conclusion, our study is the first to report that FLRT3 has the potential as therapeutic biomarker for the treatment of lung cancer and LCSC.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2167-2172
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• 2013

Lung cancer remains a major cause of morbidity and mortality worldwide, accounting for more deaths than any other cause. All the clinical practice guidelines recommended against routine screening for lung cancer have cited lack of robust evidence, at least until a few years back. However, the potential to screen lung cancers has received renewed interest due to superior performance of low dose CT (LD-CT) in detecting early stage cancers. The incremental costs and risks involved due to the invasive procedures in the screened population due to a high false positivity rate questions the use of LD-CT scan as a reliable community based screening tool. There is therefore an urgent need to find a less invasive and a more reliable biomarker that is crucial to increase the probability of early lung cancer detection. This can truly make a difference in lung cancer survival and at the same time be more cost and resource utilization effective. Sampling blood serum being minimally invasive, low risk and providing an easy to obtain biofluid, needs to be explored for potential biomarkers. This review discusses the use of circulatory miRNAs that have been able to discriminate lung cancer patients from disease free controls. Several studies conducted recently suggest that circulating miRNAs may have promising future applications for screening and early detection of lung cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2511-2515
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• 2014

Objective: Lung cancer is one of the malignant tumors with greatest morbidity and mortality around the world. The keys to targeted therapy are discovery of lung cancer biomarkers to facilitate improvement of survival and quality of life for the patients with lung cancer. Translationally controlled tumor protein (TCTP) is one of the most overexpressed proteins in human lung cancer cells by comparison to the normal cells, suggesting that it might be a good biomarker for lung cancer. Materials and Methods: In the present study, the targeted efficacy of dihydroartemisinin (DHA) on TCTP expression in the A549 lung cancer cell model was explored. Results and Conclusions: DHA could inhibit A549 lung cancer cell proliferation, and simultaneously up-regulate the expression of TCTP mRNA, but down-regulate its protein expression in A549 cells. In addition, it promoted TCTP protein secretion. Therefore, TCTP might be used as a potential biomarker and therapeutic target for non-small cell lung cancers.

• Journal of Sensor Science and Technology
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• v.22 no.2
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• pp.144-149
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• 2013

In this research, we developed a biosensor to detect lung cancer-specific biomarker using Anodic Aluminum Oxide (AAO) chip based on interference and nano surface plasmon resonance (nanoSPR). The nano-porous AAO chip was fabricated $2{\mu}m$ of pore-depth by two-step anodizing method for surface uniformity. NanoSPR has sensitivity to the refractive index (RI) of the surrounding medium and also provides simple and label-free detection when specific antibodies are immobilized to the Au-deposited surface of nano-porous AAO chip. To detect the lung cancer-specific biomarker, antibodies were immobilized on the surface of the chip by Self Assembled Monolayer (SAM) method. Since then lung cancer-specific biomarker was applied atop the antibodies immobilized layer. The specific reaction of the antigen-antibody contributed to the change in the refractive index that cause shift of resonance spectrum in the interference pattern. The Limit of Detection (LOD) was 1 fg/ml by using our nano-porous AAO biosensor chip.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2273-2276
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• 2013

Objectives: This study employed proteomic profiling to identify specific tumor markers that might improve early diagnosis of lung squamous cell carcinoma. Methods: Serum samples were isolated from 30 patients with stage I lung squamous cell carcinoma and 30 age-and gender-matched healthy controls, and proteomic profiles were obtained by matrix-assisted laser desorption ionization time of flight mass spectrometry. Results: Three highly expressed potential tumor markers were identified in the sera of stage I lung squamous cell carcinoma patients, with molecular weights of 3261.69, 3192.07, and 2556.92 Da. One protein peak with molecular weight 3261.69 Da was chosen as the candidate biomarker and identified as a fibrinogen alpha chain through a search of the IPI, NCBI or SWISS-PROT protein databases. Conclusion: As a potential tumor biomarker, fibrinogen alpha chain may be applicable for the early diagnosis and prognosis of lung squamous cell carcinoma patients.

• Biomedical Science Letters
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• v.28 no.1
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• pp.9-24
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• 2022

The aim of this study was to identify the expression of zinc finger E-box binding homeobox 1 (ZEB1), its prognostic significance, and correlation between ZEB1 and infiltrating immune cells in lung cancer. Correlation between ZEB1 and telomerase was also analyzed in different types of cancers. RNA sequencing analysis and survival rates of patients were confirmed by Gene Expression Profiling Interactive Analysis (GEPIA). The Kaplan-Meier plotter and PrognoScan databases were used to analyze the prognostic value of ZEB1 in various cancers. The Tumor IMmune Estimation Resource (TIMER) was used to determine the correlation between ZEB1 and infiltrating immune cells. Lower ZEB1 expression was lower in lung cancer and was related to poor prognosis in lung adenocarcinoma (LUAD). ZEB1 expression exhibited a significantly positive correlation with infiltration levels of immune cells in LUAD and lung squamous cell carcinoma. Furthermore, we found that the ZEB1 expression correlated with subunits of telomerase. Our findings suggest ZEB1 as a potential biomarker to be used for prognostic significance and tumor immunology in lung cancer. The correlation between the expression of ZEB1 and telomere-related gene will help in understand the cancer-promoting mechanisms.

• Journal of Korean Medical Science
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• v.33 no.53
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• pp.342.1-342.6
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• 2018

We validated the diagnostic performance of a previously developed blood-based 7-protein biomarker panel, $AptoDetect^{TM}$-Lung (Aptamer Sciences Inc., Pohang, Korea) using modified aptamer-based proteomic technology for lung cancer detection. Non-small cell lung cancer (NSCLC), 200 patients and benign nodule controls, 200 participants were enrolled. In a high-risk population corresponding to ${\geq}55years$ of age and ${\geq}30pack-years$, the diagnostic performance was improved, showing 73.3% sensitivity and 90.5% specificity with an area under the curve of 0.88. $AptoDetect^{TM}$-Lung (Aptamer Sciences Inc.) offers the best validated performance to discriminate NSCLC from benign nodule controls in a high-risk population and could play a complementary role in lung cancer screening.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9367-9373
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• 2014

In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool - gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are requentlyused lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer.