Dataset Information

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker  for Lung Adenocarcinoma].

ABSTRACT:

Background

Transcription factor (TF) can bind specific sequences that either promotes or represses the transcription of target genes, and exerts important effects on tumorigenesis, migration, invasion. Staphylococcal nuclease-containing structural domain 1 (SND1), which is a transcriptional co-activator, is considered as a promising target for tumor therapy. However, its role in lung adenocarcinoma (LUAD) remains unclear. This study aims to explore the role of SND1 in LUAD.

Methods

Data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA) database was obtained to explore the association between SND1 and the prognosis, as well as the immune cell infiltration, and subcellular localization in LUAD tissues. Furthermore, the functional role of SND1 in LUAD was verified in vitro. EdU assay, CCK-8 assay, flow cytometry, scratch assay, Transwell assay and Western blot were performed.

Results

SND1 was found to be upregulated and high expression of SND1 is correlated with poor prognosis of LUAD patients. In addition, SND1 was predominantly present in the cytoplasm of LUAD cells. Enrichment analysis showed that SND1 was closely associated with the cell cycle, as well as DNA replication, and chromosome segregation. Immune infiltration analysis showed that SND1 was closely associated with various immune cell populations, including T cells, B cells, cytotoxic cells and dendritic cells. In vitro studies demonstrated that silencing of SND1 inhibited cell proliferation, invasion and migration of LUAD cells. Besides, cell cycle was blocked at G1 phase by down-regulating SND1.

Conclusions

SND1 might be an important prognostic biomarker of LUAD and may promote LUAD cells proliferation and migration.

SUBMITTER: Zhang R

PROVIDER: S-EPMC10895293 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker  for Lung Adenocarcinoma].

Zhang Ruihao R Huang Hua H Zhu Guangsheng G Wu Di D Chen Chen C Cao Peijun P Ding Chen C Liu Hongyu H Chen Jun J Li Yongwen Y

Zhongguo fei ai za zhi = Chinese journal of lung cancer 20240101 1

<h4>Background</h4>Transcription factor (TF) can bind specific sequences that either promotes or represses the transcription of target genes, and exerts important effects on tumorigenesis, migration, invasion. Staphylococcal nuclease-containing structural domain 1 (SND1), which is a transcriptional co-activator, is considered as a promising target for tumor therapy. However, its role in lung adenocarcinoma (LUAD) remains unclear. This study aims to explore the role of SND1 in LUAD.<h4>Methods</h ...[more]

PMID: 38296623

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Project description:Objectives: Lung adenocarcinoma (LUAD) accounts for a majority of cancer-related deaths worldwide annually. The identification of prognostic biomarkers and prediction of prognosis for LUAD patients is necessary. Materials and Methods: In this study, LUAD RNA-Seq data and clinical data from the Cancer Genome Atlas (TCGA) were divided into TCGA cohort I (n = 338) and II (n = 168). The cohort I was used for model construction, and the cohort II and data from Gene Expression Omnibus (GSE72094 cohort, n = 393; GSE11969 cohort, n = 149) were utilized for validation. First, the survival-related seed genes were selected from the cohort I using the machine learning model (random survival forest, RSF), and then in order to improve prediction accuracy, the forward selection model was utilized to identify the prognosis-related key genes among the seed genes using the clinically-integrated RNA-Seq data. Second, the survival risk score system was constructed by using these key genes in the cohort II, the GSE72094 cohort and the GSE11969 cohort, and the evaluation metrics such as HR, p value and C-index were calculated to validate the proposed method. Third, the developed approach was compared with the previous five prediction models. Finally, bioinformatics analyses (pathway, heatmap, protein-gene interaction network) have been applied to the identified seed genes and key genes. Results and Conclusion: Based on the RSF model and clinically-integrated RNA-Seq data, we identified sixteen key genes that formed the prognostic gene expression signature. These sixteen key genes could achieve a strong power for prognostic prediction of LUAD patients in cohort II (HR = 3.80, p = 1.63e-06, C-index = 0.656), and were further validated in the GSE72094 cohort (HR = 4.12, p = 1.34e-10, C-index = 0.672) and GSE11969 cohort (HR = 3.87, p = 6.81e-07, C-index = 0.670). The experimental results of three independent validation cohorts showed that compared with the traditional Cox model and the use of standalone RNA-Seq data, the machine-learning-based method effectively improved the prediction accuracy of LUAD prognosis, and the derived model was also superior to the other five existing prediction models. KEGG pathway analysis found eleven of the sixteen genes were associated with Nicotine addiction. Thirteen of the sixteen genes were reported for the first time as the LUAD prognosis-related key genes. In conclusion, we developed a sixteen-gene prognostic marker for LUAD, which may provide a powerful prognostic tool for precision oncology.

Project description:Lung cancer is one of the most common malignancy worldwide and causes estimated 1.6 million deaths each year. Cancer immunosurveillance has been found to play an important role in lung cancer and may be related with its prognosis. KLRK1, encoding NKG2D, is a homodimeric lectin-like receptor. However, there has not been one research of KLRK1 as a biomarker in lung cancer. Data including patients` clinical characteristics and RNAseq information of KLRK1 from TCGA were downloaded. A total of 1019 patients with lung cancer were included in this study, among which 407 patients were female and 611 patients were male. Evaluations of mRNA expression, diagnostic value by ROC (receiver operating characteristic) curves and prognostic value by survival curve, Cox model and subgroup analysis were performed. The level of KLRK1 expression in lung adenocarcinoma cancer tissues and normal lung tissues was detected by qRT-PCR. The CCK-8 assay investigated the proliferation rate and the wound healing assay assessed the migratory ability in vitro. The expression of KLRK1 in tumor was lower than that in normal tissue. KLRK1 expression was associated with gender, histologic grade, stage, T classification and vital status. Patients with high KLRK1 expression presented an improved overall survival (P = 0.0036) and relapse free survival (P = 0.0031). KLRK1 was found to have significant prognostic value in lung adenocarcinoma (P = 0.015), stage I/II (P = 0.03), older patients (P = 0.0052), and male (P = 0.0047) by subgroup overall survival analysis, and in lung adenocarcinoma (P = 0.0094), stage I/II (P = 0.0076), older patients (P = 0.0072), and male (P = 0.0033) by subgroup relapse free survival analysis. Lung adenocarcinoma cancer patients with high KLRK1 expression presented an improved overall survival (P = 0.015) and relapse free survival (P = 0.0094). In vitro studies indicated that KLRK1 inhibited tumor cell proliferation and migration. KLRK1 was an independent prognostic factor and high KLRK1 expression indicated a better overall and relapse free survival. KLRK1 may be a prognostic biomarker for lung adenocarcinoma cancer.

Project description:BackgroundLung cancer is the leading cause of cancer-related death, and adenocarcinoma is the most common type of lung cancer. Although emerging evidence implicates the role of several aldehyde dehydrogenases in cancer progression, the expression and clinical significance of aldehyde dehydrogenase 3B1 in lung adenocarcinoma has never been studied.MaterialsIn our study, the expression of aldehyde dehydrogenase 3B1 in 250 cases of lung adenocarcinoma was detected with immunohistochemistry, and the patients were further divided into subgroups with different aldehyde dehydrogenase 3B1 expression. Using real-time polymerase chain reaction, we investigated the aldehyde dehydrogenase 3B1 messenger RNA in 20 lung adenocarcinoma and paired normal lung tissues. With the χ2 test, we evaluated the clinical significance of aldehyde dehydrogenase 3B1 by analyzing its correlation with the clinicopathological factors. Propensity score matching was performed to balance the baseline of cohort. With univariate and multivariate analyses, we screened the prognostic factors of lung adenocarcinoma and identified the independent prognostic factors before and after the propensity score matching.ResultsAldehyde dehydrogenase 3B1 expression was significantly associated with the sex and age of patients, tumor size, and histological grade. High expression of aldehyde dehydrogenase 3B1 predicted the poor prognosis (P = .003). Moreover, male patients (P = .020), large tumor size (P = .009), advanced T stage (P = .001), positive lymphatic invasion (P < .001), and advanced tumor-node-metastasis stage (P < .001) were all the prognostic factors for unfavorable outcome. Aldehyde dehydrogenase 3B1 was an independent prognostic biomarker of lung adenocarcinoma, indicating the poor prognosis. In addition, after balancing the baseline characteristics by propensity score matching, we also demonstrated that aldehyde dehydrogenase 3B1 was an independent prognostic biomarker of lung adenocarcinoma (P = .007).ConclusionsAldehyde dehydrogenase 3B1 was an independent prognostic biomarker of lung adenocarcinoma, indicating the unfavorable prognosis. Postoperative detection of aldehyde dehydrogenase 3B1 would help stratify the high-risk patients with lung adenocarcinoma and guide individual treatment.

Project description:BackgroundLung adenocarcinoma (LUAD) is a highly prevalent and deadly form of lung cancer and is a significant health concern worldwide. Although the expression of serine protease 3 (PRSS3) is elevated in certain cancers, its function in LUAD is yet unclear. The aim of this study was to investigate the mechanism of PRSS3 in lung adenocarcinoma, and validate PRSS3 as a reliable prognostic biomarker in lung adenocarcinoma.MethodsThe Cancer Genome Atlas (TCGA) provides RNA expression data and patient medical information for LUAD patients. To determine which genes are expressed differently in LUAD and normal lung tissues, we carefully examined these data. We then used Cox regression analysis to examine the expression and survival data to pinpoint the genes that are strongly associated with patient survival. The PRSS3 gene affects patient prognosis. Afterward, we divided LUAD patients into low- and high-expression groups on the basis of the median PRSS3 expression to examine the relationship between immune cells and PRSS3. The results of the CIBERSORT and CIBERSORTx studies revealed correlations between PRSS3 and the degree of infiltration of several immune cell types. After the groups with low and high PRSS3 expressions were compared, PRSS3-related genes were identified, and functional enrichment analysis was performed. Furthermore, a model was developed to predict patient prognosis according to clinical characteristics and PRSS3 expression. After the bioinformatics analyses were completed, we validated the differential expression of PRSS3 in samples obtained from our center via Western blotting and immunohistochemistry (IHC).ResultsWe found that PRSS3 expression is highly upregulated in LUAD and that high PRSS3 expression is associated with a poorer prognosis in the TCGA database. Single-sample gene enrichment analysis revealed a strong correlation between PRSS3 and the immunological microenvironment. The clinical model developed on the basis of the PRSS3 showed great accuracy and can be used as a significant diagnostic indicator for LUAD. Western blotting and IHC confirmed a substantial increase in PRSS3 expression in LUAD. Herein, we analyzed an available dataset for a clinical cohort and revealed that elevated levels of PRSS3 are indicative of unfavorable outcomes in patients diagnosed with LUAD.ConclusionsPRSS3 is significantly upregulated in LUAD and can be used as a marker for LUAD diagnosis and prognosis assessment. Further study of PRSS3 could provide valuable insight into the mechanisms underlying the occurrence and progression of LUAD.

Dataset Information

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker  for Lung Adenocarcinoma].

Background

Methods

Results

Conclusions

Publications

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker  for Lung Adenocarcinoma].

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker for Lung Adenocarcinoma].

Background

Methods

Results

Conclusions

Publications

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker for Lung Adenocarcinoma].

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker  for Lung Adenocarcinoma].

[Identification and Analysis of SND1 as an Oncogene and Prognostic Biomarker  for Lung Adenocarcinoma].