| Literature DB >> 35725413 |
Liren Jiang1, Siteng Chen2, Qi Pan3, Jun Zheng1, Jin He1, Juanjuan Sun1, Yaqin Han1, Jiji Yang1, Ning Zhang4, Guohui Fu5,6, Feng Gao7.
Abstract
BACKGROUND: Bladder cancer (BCa) shows its potential immunogenity in current immune-checkpoint inhibitor related immunotherapies. However, its therapeutic effects are improvable and could be affected by tumor immune microenvironment. Hence it is interesting to find some more prognostic indicators for BCa patients concerning immunotherapies.Entities:
Keywords: Bladder cancer; Immune-related; PD-1; PD-L1; Prognostic signature
Mesh:
Substances:
Year: 2022 PMID: 35725413 PMCID: PMC9210750 DOI: 10.1186/s12885-022-09783-y
Source DB: PubMed Journal: BMC Cancer ISSN: 1471-2407 Impact factor: 4.638
The clinicopathological features in all cohorts
| Clinical characteristics | TCGA cohort ( | E-MTAB-4321 cohort ( | General cohort ( |
|---|---|---|---|
| Age | 69 (34 ~ 90) | 69 (24 ~ 96) | 67 (47 ~ 89) |
| Gender | |||
| Female | 106 | 109 | 20 |
| Male | 299 | 367 | 109 |
| Stage | |||
| I | 2 | 460 | 0 |
| II | 129 | 16 | 76 |
| III | 139 | 0 | 53 |
| IV | 133 | 0 | 0 |
| Unknown | 2 | 0 | 0 |
| T | |||
| Ta | 0 | 345 | 0 |
| Cis | 0 | 3 | 0 |
| T1 | 3 | 112 | 0 |
| T2 | 118 | 16 | 77 |
| T3 | 192 | 0 | 27 |
| T4 | 58 | 0 | 25 |
| Unknown | 34 | 0 | 0 |
| N | |||
| N0 | 235 | / | 122 |
| N1 | 46 | / | 5 |
| N2 | 75 | / | 1 |
| N3 | 7 | / | 1 |
| Unknown | 42 | / | 0 |
| M | |||
| M0 | 195 | / | 129 |
| M1 | 11 | / | 0 |
| Unknown | 199 | / | 0 |
Fig. 1Identification of immune-related genes with prognostic values. A The heatmap of LC–MS from 9 pairs of MIBC patients with all the differential expression proteins between two different prognosis groups. B A total of 13 out of 677 differentially expressed proteins were classified as immune-related proteins. C The Volcano plot result of all the 677 differential expression protein. D The LASSO analysis of the 13 immune-related genes. E The profile of coefficients of the 7 immune-related genes. F The illustration of expression levels of 7 immune-related proteins in General cohort. LC–MS: liquid chromatography-mass spectrometry. LASSO: least absolute shrinkage and selection operator
Fig. 2Kaplan–Meier survival analysis among 3 cohorts. A The OS of MIBC patients in TCGA cohort. B The DFS of MIBC patients in TCGA cohort. C The DFS of BCa patients in E-MTAB-4321 cohort. D The OS of MIBC patients in General cohort. E The DFS of MIBC patients in General cohort. OS: overall survival. DFS: disease-free survival
Fig. 3Correlation of IRPS score and clinicopathological features among 3 cohort. A Cox regression analysis of IRPS score and clinicopathologic features for patients’ OS in TCGA cohort. B The correlation of IRPS score and tumor grade in TCGA cohort. C The correlation of IRPS score and lymph node metastasis in TCGA cohort. D Cox regression analysis of IRPS score and clinicopathologic features for patients’ DFS in E-MTAB-4321 cohort. E The correlation of IRPS score and tumor grade in E-MTAB-4321 cohort. F Cox regression analysis of IRPS score and clinicopathologic features for patients’ OS in General cohort. G The correlation of IRPS score and tumor grade in General cohort. H The correlation of IRPS score and lymph node metastasis in General cohort. OS: overall survival. DFS: disease-free survival
The results of hazard ratio values for each protein in General cohort
| Protein | Hazard Ratio | 95% Confidence Interval | |
|---|---|---|---|
| NFKB1 | 0.69 | 0.58–0.82 | < 0.001 |
| STAT3 | 1.00 | 0.82–1.22 | 0.994 |
| CTSG | 1.47 | 1.26–1.71 | < 0.001 |
| TGFB1 | 1.49 | 1.23–1.81 | < 0.001 |
| SNRPD2 | 0.60 | 0.52–0.70 | < 0.001 |
| TAP1 | 0.64 | 0.55–0.74 | < 0.001 |
| PDCD1 | 0.61 | 0.51–0.72 | < 0.001 |
Fig. 4Correlation of IRPS score and the remodeling of the immune microenvironment. A Heatmap of IRPS score and the expression of effector molecules. B Evaluation of the correlation among IRPS score and Effector score. C Correlation of IRPS score and GZMB or IFN-γ expression. D Heatmap of IRPS score and the expression of ICK molecules. E Evaluation of the correlation among IRPS score and ICK score. F Correlation of IRPS score and PD-1 or PD-L1 expression. G Heatmap of IRPS score and the infiltration of 22 types of immune cells. H Evaluation of the correlation among IRPS score and lymphocyte infiltration signature score. I Correlation of IRPS score and M2 macrophage or resting mast cell infiltration