Abstract
Background
Bladder cancer has the characteristics of high morbidity and mortality, and the prevalence of bladder cancer has been increasing in recent years. Immune and autophagy related genes play important roles in cancer, but there are few studies on their effects on the prognosis of bladder cancer patients.
Methods
Using gene expression data from the TCGA-BLCA database, we clustered bladder cancer samples into 6 immune-related and autophagy-related molecular subtypes with different prognostic outcomes based on 2208 immune-related and autophagy-related genes. Six subtypes were divided into two groups which had significantly different prognosis. Differential expression analysis was used to explore genes closely related to the progression of bladder cancer. Then we used Cox stepwise regression to define a combination of gene expression levels and immune infiltration indexes to construct the risk model. Finally, we built a Nomogram which consist of risk score and several other prognosis-related clinical indicators.
Results
The risk model suggested that high expression of C5AR2, CSF3R, FBXW10, FCAR, GHR, OLR1, PGLYRP3, RASGRP4, S100A12 was associated with poor prognosis, while high expression level of CD96, IL10, MEFV pointed to a better prognosis. Validation by internal and external dataset suggested that our risk model had a high ability to discriminate between the outcomes of patients with bladder cancer. The immunohistochemical results basically confirmed our results. The C-Index value and Calibration curves verified the robustness of Nomogram.
Conclusions
Our study constructed a model that included a risk score for patients with bladder cancer, which provided a lot of helps to predict the prognosis of patients with bladder cancer.
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Introduction
Bladder cancer (BLCA) is a high-incidence tumor which has high morbidity and mortality. According to statistics, BLCA ranks ninth in the prevalence of malignant diseases and 13th among the most common causes of cancer death [1].
For the past decades, BLCA has made many advances in clinical treatment. Gene sequencing technology has identified the most mutated genes in BLCA. Many studies have researched the treatment of BLCA at the level of cells and molecular mechanism [37]. Meanwhile, the upregulation of LOX-1 was associated with the occurrence, development and metastasis of various tumors [38]. In the present study, overexpression of OLR1 led to a higher risk score and a poorer prognosis, which was also consistent with the findings above.
At present, there are relatively few studies on PGLYRP3. According to research, PGLYRP3 acted a pivotal part in antibacterial immunity and inflammatory responses [39, 40]. In our research, PGLYRP3 A was highly expressed in BLCA and was associated with poor prognosis.
According to research, RASGRP4 was significantly overxpressed in diffuse large B cell lymphoma. Meanwhile, knockdown of RASGRP4 significantly inhibited tumor formation [41]. Studies on bladder urothelial carcinoma have found that overexpression of RASGRP4 was significantly related to shorter survival of bladder urothelial carcinoma [42]. Our study confirmed this.
S100A12 was proved to be a useful biomarker in inflammatory conditions. And some studies suggest that it might also take part in cardiovascular disease [43]. In cancer, S100A12 also played a regulatory role. For example, the expression of S100A12 was significantly upregulated in human papillary thyroid cancer, and knockdown of S100A12 significantly inhibited propagation, transfer, invasion, and cell cycle progression of cancer cells [44]. This study showed that high expression of S100A12 led to worse prognosis in BLCA patients.
Immunity and autophagy play important roles in tumors. Our study identified twelve genes associated with immunity and autophagy and three Cibersort immune infiltration scores that were significantly associated with bladder cancer prognosis. On this basis, we established a model to predict survival in patients with BLCA. There are some limitations to our study. First, the genes we defined were validated only by immunohistochemistry in the HPA database. Although the immunohistochemical data in the HPA database and the gene expression data in the TCGA are of relatively high quality, the data we used were from urothelial carcinoma and were not 100% representative of bladder cancer. Second, immunohistochemical information of FBXW10, MEFV, OLR1 and RASGRP4 were missing in HPA. The high expression of IL10 was detrimental to prognosis, which was inconsistent with our findings. Besides, the functions of these genes in bladder cancer need to be further explored. For BLCA patients with T1G3 stage, Bacillus Calmette-Guerin (BCG) treatment and response to BCG have important influence on the prognosis of patients. Unfortunately, our study did not have enough data at this point to make a credible statistical analysis, which was one of the limitations of this study. At the same time, genetic mutations may also have a significant impact on the prognosis of patients with bladder cancer. In many tumors, mutations in one or more genes have been shown to be significantly associated with prognosis. Unfortunately, we did not explore the genetic mutations in high-risk and low-risk patients.
Availability of data and materials
The original contributions presented in the study are publicly available. These data can be found here: (https://www.ncbi.nlm.nih.gov/geo/), (https://portal.gdc.cancer.gov/), (https://reactome.org/).
Abbreviations
- TCGA:
-
The Cancer Genome Atlas
- BLCA:
-
Bladder cancer
- DEG:
-
Differentially expressed gene
- GEO:
-
Gene Expression Omnibus
- HPA:
-
Human Protein Atlas
- NMF:
-
Non-negative matrix factorization
- GO:
-
Gene Ontology
- KEGG:
-
Kyoto Encyclopedia of Genes and Genomes
- KM:
-
Kaplan-Meier
- MF:
-
Molecular function
- BP:
-
Biological process
- CC:
-
Cellular component
- BCG:
-
Bacillus Calmette-Guerin
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Acknowledgments
We acknowledge TCGA and GEO database for providing their platforms and contributors for uploading their meaningful datasets.
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Contributions
Quanfeng Zhu: study conception, study design, data collection and analysis, results interpretation, visualization, and manuscript writing and revision. Lingdi Zhang: data collection and analysis. Ya** Deng: manuscript writing and revision. Leilei Tang: manuscript writing and revision. The author(s) read approved the final manuscript.
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TCGA and GEO belong to public databases. The patients involved in the databases have obtained ethical approval. Users can download relevant data for free for research and publish relevant articles. Our study was based on open source data, so there are no ethical issues and other conflicts of interest. All methods of our research were carried out in accordance with relevant guidelines and regulations, and were in accordance to guidelines of Declaration of Helsinki.
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Supplementary Information
Additional file 1: Table S1.
The difference of pTNM staging between high-risk group and low-risk group was significant.
Additional file 2: Table S2.
The difference of immune infiltration index between high-risk group and low-risk group was significant.
Additional file 3: Table S3.
2208 immune-related and autophagy-related genes.
Additional file 4: Table S4.
Differentially expressed genes.
Additional file 5: Table S5.
GSEA KEGG enrichment.
Additional file 6: Table S6.
Risk score of each sample from the training cohort.
Additional file 7: Table S7.
Regression coefficient for each variable.
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Zhu, Q., Zhang, L., Deng, Y. et al. Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer. BMC Genom Data 23, 60 (2022). https://doi.org/10.1186/s12863-022-01073-7
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DOI: https://doi.org/10.1186/s12863-022-01073-7