Fc Receptor Expression as a Prognostic Factor in Patients With Non-small-cell Lung Cancer

Kim, Min Hye; Lee, Jeong-Hee; Lee, Jong Sil; Kim, Dong Chul; Yang, Jung Wook; An, Hyo Jung; Na, Ji Min; Shin, Meong Cheol; Song, Dae Hyun

doi:10.21873/invivo.13006

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…In the non-small cell lung cancer study, it was elucidated that higher levels of FCGRT mRNA expression in both cancerous and noncancerous tissues are associated with a favorable prognosis [19]. Kim et al also reported that FCGRT level may play a role in favorable outcomes in the lung cancer population [32]. However, in our study, we observed more frequent expression of FcRn in patients with high-staged EC.…”

Section: Discussioncontrasting

confidence: 72%

“…Not only in cancer therapeutics but also as a cancer prognostic factor, FcRn has been studied extensively. In 2022, Kim et al reported that the negative expression of FcRn in non-small cell lung cancer cells is associated with significantly lower disease-free survival and decreased disease-specific survival in patients with TNM stage I disease [32]. Jensen et al observed the downregulation of FCGRT, encoding FcRn, in progressive breast cancer patients [33].…”

Section: Discussionmentioning

confidence: 99%

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FcRn Expression in Endometrial Cancer and Its Association with Clinicopathologic Features

Song,

Yang,

Kim

et al. 2023

Diagnostics

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Background: Endometrial cancer (EC) has robust molecular diagnostic evidence that correlates well with prognosis. In various types of cancers, FcRn has been identified as an early marker for prognosis. This study aims to assess FcRn expression and its association with clinicopathological features in endometrial cancer. Materials and Methods: We employed a tissue microarray (TMA) from a retrospective cohort of 41 patients diagnosed with endometrioid endometrial cancer post hysterectomy between January 2002 and December 2009 at Gyeongsang National University Hospital. Relevant clinical data collection for the cohort involved reviewing patients’ electronic medical charts. FcRn expression in microarrays of patient EC tissue was examined in conjunction with clinicopathologic data. Experiments, including siRNA knock-down, PCR mRNA semiquantification, Western blot, and confluence change tests, were conducted on the Ishikawa cell line. Results: The overall FcRn expression rate in EC patients was 41.8%. FIGO stage showed a statistically significant relationship with FcRn expression, while age, lymphovascular invasion, myometrial invasion, and tumor size had no effect. In endometrioid cancer cells of FIGO stage IA, FcRn was less frequently expressed than in other high-staged EC patients (p = 0.021). In experiments on the Ishikawa cell line, the siRNA knock-down group exhibited quantitatively lower FCGRT mRNA expression and lower FcRn protein signal compared to the scrambled RNA control group. The change in confluence over time measured at three hotspots did not show a significant difference between groups. Conclusions: To the best of our knowledge, this study represents the initial assessment of FcRn expression in endometrioid EC samples. FcRn expression was significantly associated with the FIGO stage. Ishikawa cell line proliferation did not significantly change in response to decreased FcRn expression. Further studies are needed to elucidate FcRn expression in EC as a potential molecular parameter.

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Section: Discussioncontrasting

confidence: 72%

Section: Discussionmentioning

confidence: 99%

FcRn Expression in Endometrial Cancer and Its Association with Clinicopathologic Features

Song,

Yang,

Kim

et al. 2023

Diagnostics

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“…Additionally, several human malignant tumors, such as liposarcoma [10], breast cancer [11], and lung squamous cell carcinoma [12], exhibit abnormal expression of PLIN1, indicating a potential role for PLIN1 in the development and spread of various tumors. Qiaochu Zhang et al [13] demonstrated that PLIN1 can be used to distinguish liposarcoma from other soft tissue sarcomas.…”

Section: Introductionmentioning

confidence: 99%

Clinical Pathological Significance and Biological Function of PLIN1 in Hepatocellular Carcinoma: bioinformatics analysis and in vitro experiment

Huang,

Wei,

et al. 2024

Preprint

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Background & aims: Perilipin1 (PLIN1) is an essential lipid droplet surface protein that participates in cell life activities by regulating energy balance and lipid metabolism. PLIN1 has been shown to have a close relationship with the development of numerous tumor types. The purpose of this work is to elucidate the clinicopathologic significance of PLIN1 in hepatocellular carcinoma (HCC), as well as its impact on the biological functions of HCC cells, and investigate possible mechanisms. Methods: Public high-throughput RNA microarray and RNA sequencingwere collected to examine PLIN1 levels and clinical significance in HCC. Immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (RT-qPCR) were conducted to assess PLIN1 expression levels and clinicopathological relevance of PLIN1 in HCC. Then, SK and Huh7 cells were transfected with a lentivirus overexpressed PLIN1. CCK8 assay, wound healing assay, transwell assay, and flow cytometric analysis were conducted to explore the effects of PLIN1 overexpression on HCC cell proliferation, migration, invasion, and cell cycle distribution. Ultimately, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate the underlying mechanisms of PLIN1 in HCC base on HCC differentially expressed genes and PLIN1 co-expressed genes. Results: PLIN1 was markedly down-regulated in HCC tissues, which correlated with a noticeably worse prognosis for HCC patients. Additionally, PLIN1 overexpression inhibited the proliferation, migration, and invasion in SK and Huh7 cells in vitro, as well as arresting the HCC cell cycle at the G0/G1 phase. More significantly, energy conversion-related biological processes, lipid metabolism, and cell cycle signaling pathways were the three most concentrated molecular mechanisms. Conclusion: The current study found that down-regulated PLIN1 is associated with a poor prognosis in HCC patients and prevented HCC progression by inhibiting cellular proliferation, migration, and metastasis, as well as the mechanisms underlying the regulation of lipid metabolism-related pathways in HCC.

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Machine learning reveals CAT gene as a novel potential diagnostic and prognostic biomarker in non-small cell lung cancer

Tian,

Zhao,

Liu

et al. 2024

Discov Onc

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Background Non-small cell lung cancer (NSCLC) represents one of the most prevalent forms of lung cancer, with a five-year survival rate of 21.7%. There is an urgent need to identify pertinent biomarkers to inform the diagnosis and prognosis of tumors, particularly those that can be applied to different age groups. Herein, we would apply machine learning methods to specifically analyze the issue of biomarker applicability across different age groups in NSCLC. Methods Studies have shown a higher incidence of NSCLC in people over 40 years of age, and due to the limitations of data set, studies of individuals under 40 years of age were not included in this study. To simulate the human aging model as closely as possible, we gathered corresponding non-small cell lung cancer (NSCLC) samples from the UCSC Xena database based on patient age information. These samples were then categorized into three groups: 40–60, 60–80, and over 80 years old. Subsequently, we employed four machine learning methods—Random Forest, LASSO regression analysis, XGBoost, and GBM—to identify gene sets with significant diagnostic value for each age group. By taking the intersection of these sets, we identified the optimal gene and assessed its prognostic significance in NSCLC. Then, the diagnostic value of CAT gene was validated using global public databases, including the GSE32863, GSE43458, GSE68571, GSE10072, and GSE63459 datasets from the Americas, the GSE30219 and GSE102511 datasets from Europe, and the GSE31210 and GSE19804 datasets from Asia. Furthermore, immunohistochemical staining was performed in an independent cohort from a tissue microarray. Additionally, cell culture and RT-qPCR were employed for external validation. Results Through the implementation of machine learning methods, we successfully identified the catalase (CAT) gene. Our analysis revealed that individuals with high expression of the CAT gene experienced improved survival rates. Additionally, these individuals exhibited elevated immune scores. We further discovered that the CAT gene synergizes with multiple components of neutrophils, including TLRs, FcRn, and the selective GEF of Rho-family GTPases. In addition, we identified a potential immune checkpoint, TNFSF15, which is applicable to the human aging model. Finally, we validated the CAT gene's diagnostic value using databases encompassing the Americas, Europe, and Asia regions. Through external RT-qPCR validation, we verified that CAT expression in BEAS-2B was higher than that of A549. In an independent human cohort, we also verified that CAT is lowly expressed in lung cancer tissues. In addition, higher CAT levels were associated with improved survival in the 40–60 and 60–80 age groups. Conclusions In our analysis of the NSCLC database, we pinpointed the CAT gene, which holds promise for potential diagnostic and prognostic applications in the context of human aging. Furthermore, it may offer insights into address...

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Fc Receptor Expression as a Prognostic Factor in Patients With Non-small-cell Lung Cancer

Cited by 4 publications

References 27 publications

FcRn Expression in Endometrial Cancer and Its Association with Clinicopathologic Features

FcRn Expression in Endometrial Cancer and Its Association with Clinicopathologic Features

Clinical Pathological Significance and Biological Function of PLIN1 in Hepatocellular Carcinoma: bioinformatics analysis and in vitro experiment

Machine learning reveals CAT gene as a novel potential diagnostic and prognostic biomarker in non-small cell lung cancer

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