PYCR1的泛癌分析及其对膀胱癌化疗和免疫治疗应答的潜在预测价值

doi:10.12122/j.issn.1673-4254.2025.04.24

摘要/Abstract

摘要：

目的基于生物信息学分析探究吡咯啉-5-羧酸还原酶-1（PYCR1）作为泛癌生物标志物的潜力，并探究其在膀胱癌（BLCA）中的表达、功能及临床意义。方法通过生物信息学分析PYCR1与泛癌患者预后、免疫微环境重塑、肿瘤突变负荷及微卫星不稳定性的关联。在TCGA-BLCA数据集中通过单因素和多因素回归分析PYCR1作为BLCA患者独立预后风险因素的潜力，并构建临床决策模型。利用IMvigor210中的BLCA队列鉴定PYCR1作为免疫治疗效果评估独立因子的潜力。基于pRRophetic药物库筛选PYCR1高表达时BLCA治疗耐受的潜在化疗药物。CMap-XSum算法和分子对接技术用于筛选并验证小分子PYCR1抑制剂。结果 PYCR1高表达与多种肿瘤不良预后、免疫细胞浸润、肿瘤突变负荷及微卫星不稳定性显著相关（r>0.3）。PYCR1在BLCA中过表达，PYCR1高表达与BLCA预后差密切相关（HR：1.14，95% CI： 1.02-1.68，P=0.006）。PYCR1高表达时西妥昔单抗、5-氟尿嘧啶、多柔比星等抗肿瘤药物IC₅₀提高（P<0.0001）。结论 PYCR1是癌症潜在的预后生物标志物和治疗靶点，PYCR1高表达是BLCA患者不良预后的独立危险因素，其具有良好的临床决策能力，是预测化疗药物敏感性和免疫治疗效果的指标。

关键词: 膀胱癌, 吡咯啉-5-羧酸还原酶-1, 免疫治疗, 化疗药物敏感性, 小分子PYCR1抑制剂

Abstract:

Objective To explore the potential of pyrroline-5-carboxylate reductase 1 (PYCR1) as a pan-cancer biomarker and investigate its expression, function, and clinical significance in bladder cancer (BLCA). Methods Bioinformatics analysis was conducted to evaluate the associations of PYCR1 with prognosis, immune microenvironment remodeling, tumor mutation burden (TMB), and microsatellite instability (MSI) in cancer patients. Using the TCGA-BLCA dataset, univariate and multivariate regression analyses were performed to assess the potential of PYCR1 as an independent prognostic risk factor for BLCA, and a clinical decision model was constructed. The IMvigor210 cohort was utilized to evaluate the potential of PYCR1 for independently predicting the efficacy of immunotherapy. The pRRophetic was employed to screen candidate chemotherapeutic agents for treating BLCA with high PYCR1 expression. The CMap-XSum algorithm and molecular docking techniques were used to explore and validate small molecule inhibitors of PYCR1. Results A high expression of PYCR1 was significantly associated with poor prognosis, immune cell infiltration, TMB and MSI in various tumors (r>0.3). PYCR1 was overexpressed in BLCA, and high PYCR1 expression was closely related to poor prognosis in BLCA patients (HR: 1.14, 95% CI: 1.02-1.68, P=0.006). The IC₅₀ of the anti-cancer drugs cetuximab, 5-fluorouracil, and doxorubicin increased significantly in BLCA cell lines with high PYCR1 expressions (P<0.0001). Conclusion High PYCR1 expression is an independent risk factor for poor prognosis in BLCA patients and can serve as a significant indicator for clinical decision-making as well as a marker for predicting sensitivity to chemotherapeutic agents and the efficacy of immunotherapy.

Key words: bladder cancer, pyrroline-5-carboxylate reductase 1, immunotherapy, chemotherapy drug sensitivity, small molecule PYCR1 inhibitors

李煜桐, 宋杏钰, 孙蕊旭, 董璇, 刘宏伟. PYCR1的泛癌分析及其对膀胱癌化疗和免疫治疗应答的潜在预测价值[J]. 南方医科大学学报, 2025, 45(4): 880-892.

Yutong LI, Xingyu SONG, Ruixu SUN, Xuan DONG, Hongwei LIU. A pan-cancer analysis of PYCR1 and its predictive value for chemotherapy and immunotherapy responses in bladder cancer[J]. Journal of Southern Medical University, 2025, 45(4): 880-892.

图/表 18

图1 泛癌中PYCR1的表达

Fig.1 Expression of PYCR1 in pan-cancer. A, B: mRNA and protein expression levels of PYCR1 in UCSC Xena and GTEx pan-cancer data. C, D: Differences in mRNA and protein expression levels of PYCR1 between cancer and adjacent tissues in 33 cancers. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001 vs control group.

表1 泛癌中PYCR1的预后意义

Tab.1 Prognostic significance of PYCR1 in pan-cancer

Index	Cancers	HR	95% CI	P
OS	SARC KIRP KIRC ESCA ACC LGG	1.29 2.01 1.59 1.22 1.68 0.78	1.13-1.47 1.58-2.54 1.40-1.80 0.94-1.59 1.28-2.21 0.60-1.00 0.96-3.35 0.67-1.01 1.37-2.09 1.44-1.87 1.18-4.23 1.25-1.92 1.12-2.47 0.74-4.82 1.27-2.24 1.59-2.15 0.90-1.65 1.09-1.45 2.92-1003.87 2.27-4.20	<0.001 <0.01 <0.01 0.022 0.022 0.017
PFS	UVM LGG KIRP KIRC KICH ACC	1.79 0.82 1.69 1.64 2.24 1.54		0.032 0.013 <0.01 <0.01 0.020 <0.01
DFS	ACC	1.66		0.024
DSS	PCPG ACC KIRC ESCA SARC PRAD KIRP	1.88 1.69 1.85 1.22 1.26 54.17 3.09		0.022 0.028 <0.01 0.043 0.047 0.030 <0.01

表2 泛癌中PYCR1调控的分子功能（前3）

Tab.2 Top 3 molecular functions regulated by PYCR1 in pan-cancer

Cancers	Description
CESC	Maturity-onset diabetes of the young, Glutathione metabolism, Melanoma Olfactory Transduction, Maturity-onset diabetes of the young, Ascorbic Acid Metabolism Taurine and Hypotaurine Metabolism, Taste transduction, Hedgehog signaling pathway Ascorbic Acid Metabolism, Autophagy, Pentose and Glucuronate Interconversions Lysine Degradation, Arginine and Proline Metabolism, Basal Cell Carcinoma Folate biosynthesis, Autophagy, Cytosolic DNA sensing by cGAS Other glycan degradation, Autophagy, Butanoate Metabolism Primary immunodeficiency, Viral myocarditis, Graft-Versus-Host Disease Viral myocarditis, Maturity-onset diabetes of the young, Glutathione metabolism
LUSC
LIHC
THYM
LAML
CHOL
UCS
THCA
KICH
HNSC	Ascorbic Acid Metabolism, Porphyrin and Chlorophyll Metabolism, Metabolism of xenobiotics by cytochrome P450
UCEC	Olfactory Transduction, Autophagy, Autoimmune thyroid disorders
STAD	Dilated cardiomyopathy, Arrhythmogenic Right Ventricular Cardiomyopathy, Hypertrophic cardiomyopathy
ACC	Glycosaminoglycan degradation, Hedgehog signaling pathway, Olfactory Transduction
SKCM	Primary immunodeficiency, Linoleic acid metabolism, Graft-Versus-Host Disease
LUAD	Olfactory Transduction, Autophagy, RIG-I-like Receptor signaling pathway
TGCT	Allograft rejection, Graft-Versus-Host Disease, Primary immunodeficiency
READ	Cytosolic DNA sensing by cGAS, Autoimmune thyroid disorders, Autophagy
LGG	Pentose and Glucuronate Interconversions, Ascorbic Acid Metabolism, Porphyrin and Chlorophyll Metabolism
BRCA	Olfactory Transduction, Cytosolic DNA sensing by cGAS, Autoimmune thyroid disorders
COAD	Taste transduction, Olfactory Transduction, Cytosolic DNA sensing by cGAS
BLCA	Maturity-onset diabetes of the young, Valine, Leucine, and Isoleucine Degradation, Graft-Versus-Host Disease

表2 泛癌中PYCR1调控的分子功能（前3）

Tab.2 Top 3 molecular functions regulated by PYCR1 in pan-cancer

Cancers	Description
CESC	Maturity-onset diabetes of the young, Glutathione metabolism, Melanoma Olfactory Transduction, Maturity-onset diabetes of the young, Ascorbic Acid Metabolism Taurine and Hypotaurine Metabolism, Taste transduction, Hedgehog signaling pathway Ascorbic Acid Metabolism, Autophagy, Pentose and Glucuronate Interconversions Lysine Degradation, Arginine and Proline Metabolism, Basal Cell Carcinoma Folate biosynthesis, Autophagy, Cytosolic DNA sensing by cGAS Other glycan degradation, Autophagy, Butanoate Metabolism Primary immunodeficiency, Viral myocarditis, Graft-Versus-Host Disease Viral myocarditis, Maturity-onset diabetes of the young, Glutathione metabolism
LUSC
LIHC
THYM
LAML
CHOL
UCS
THCA
KICH
HNSC	Ascorbic Acid Metabolism, Porphyrin and Chlorophyll Metabolism, Metabolism of xenobiotics by cytochrome P450
UCEC	Olfactory Transduction, Autophagy, Autoimmune thyroid disorders
STAD	Dilated cardiomyopathy, Arrhythmogenic Right Ventricular Cardiomyopathy, Hypertrophic cardiomyopathy
ACC	Glycosaminoglycan degradation, Hedgehog signaling pathway, Olfactory Transduction
SKCM	Primary immunodeficiency, Linoleic acid metabolism, Graft-Versus-Host Disease
LUAD	Olfactory Transduction, Autophagy, RIG-I-like Receptor signaling pathway
TGCT	Allograft rejection, Graft-Versus-Host Disease, Primary immunodeficiency
READ	Cytosolic DNA sensing by cGAS, Autoimmune thyroid disorders, Autophagy
LGG	Pentose and Glucuronate Interconversions, Ascorbic Acid Metabolism, Porphyrin and Chlorophyll Metabolism
BRCA	Olfactory Transduction, Cytosolic DNA sensing by cGAS, Autoimmune thyroid disorders
COAD	Taste transduction, Olfactory Transduction, Cytosolic DNA sensing by cGAS
BLCA	Maturity-onset diabetes of the young, Valine, Leucine, and Isoleucine Degradation, Graft-Versus-Host Disease

图2 泛癌中PYCR1与肿瘤免疫评分的关联分析

Fig.2 Correlation analysis between PYCR1 and tumor immunity score in pan-cancer.

图3 泛癌中PYCR1调节免疫细胞浸润水平

Fig.3 PYCR1 regulates the level of immune cell infiltration in pan-cancer.

图4 泛癌中PYCR1评估TMB、MSI以及免疫治疗获益的潜力

Fig.4 Potential of PYCR1 for assessing tumor mutation burden (TMB), microsatellite instability (MSI) and immune therapy benefits in pan-cancer. A: Correlation of PYCR1 with TMB and MSI. B: Correlation of PYCR1 with benefits of anti-PD-1 immunotherapy in SKCM patients in the SKCM immunotherapy cohort. C: Correlation of PYCR1 with benefits of anti-PD-L1 immunotherapy in RCC patients in the metastatic RCC immunotherapy cohort. D: Correlation of PYCR1 with immune checkpoint inhibitor therapy benefit in patients with BLCA in the IMvigor210 cohort.

图5 在BLCA中PYCR1的mRNA和蛋白质表达水平

图6 PYCR1高表达和低表达的BLCA组织学特征

Fig.6 Histological features of BLCA with high and low PYCR1 expressions. A: HE staining profile of BLCA tissue with high PYCR1 expression level (Original magnification: ×1000). B: HE staining profile of BLCA tissue with low PYCR1 expression level (×1000).

图7 沉默PYCR1对BLCA细胞系增殖能力的影响

Fig.7 Effect of PYCR1 silencing on proliferative capacity of BLCA cell lines. A: mRNA expression levels of PYCR1 in BLCA cell lines and SV-HUC-1. **P<0.01 vs SV-HUC-1. B: Verification of PYCR1 silencing efficiency. C: Effect of PYCR1 silencing on proliferation of T24 and UM-UC-3 cells. *P<0.05, **P<0.01, ***P<0.001 vs si-NC.

图8 高PYCR1表达水平对BLCA患者预后的影响

Fig.8 Effect of high PYCR1 expression level on prognosis of BLCA patients.

表3 单因素回归分析识别BLCA危险因素

Tab.3 Univariate analysis for identifying prognostic risk factors for BLCA

Characteristics	HR	95% CI	P
Age (year)	1.05	1.02-1.07	<0.001
Tumor classification	1.25	1.04-1.49	0.016
Copy number variation	0.97	0.79-1.19	0.764
Gender	0.95	0.55-1.65	0.858
Grade	2.02	0.49-8.29	0.327
Hypermethylation	0.93	0.79-1.09	0.377
Hypomethylation	0.92	0.78-1.08	0.044
Tumor mutation burden	1.10	0.85-1.44	0.457
PYCR1	1.23	0.99-1.87	0.032
Race	0.91	0.67-1.24	0.544
Single nucleotide variation	1.00	0.99-1.01	0.027
Stage	1.60	1.19-2.15	0.002

表4 多因素回归分析识别BLCA独立预后风险因素

Tab.4 Multivariate analysis for identifying independent prognostic risk factors for BLCA

Characteristics	HR	95% CI	Assignment and Attributes	P
Age (year)	1.04	1.02-1.07	Continuous variable	0.001
Tumor classification	1.16	0.95-1.41	0= LumP,1= LumNS,2= LumU,3= Stroma-rich,4= Ba/Sq,5= NE-like	0.135
Hypomethylation	0.89	0.75-1.05	Continuous variable	0.162
PYCR1	1.14	1.02-1.68	Continuous variable	0.006
Single nucleotide variation	1.00	0.99-1.01	Continuous variable	0.019
Stage	1.49	1.10-2.04	0= I-II,1= III-IV	0.011

图9 基于临床性状和PYCR1构建BLCA临床DCA模型

Fig.9 Construction of BLCA clinical DCA model based on clinical traits and PYCR1 expression levels.

图10 PYCR1促进BLCA进展调控的分子机制

Fig.10 Molecular mechanism of PYCR1 for promoting BLCA progression. A, B: GO and KEGG signaling pathway enrichment analysis circle diagram of PYCR1 co-expressed genes.

图11 基于PYCR1高表达的BLCA药物敏感性分析

Fig.11 Drug sensitivity analysis of BLCA with high PYCR1 expressions.

图12 基于PYCR1表达谱的小分子药物虚拟筛选

Fig.12 Virtual screening of small molecule drugs based on PYCR1 expression profiling. A: Screening for small molecule drugs in BLCA patients based on PYCR1 expression profile using XSum algorithm. B: Likely compound structures of candidate small molecule inhibitors of PYCR1. C: Known PYCR1 inhibitor Pycr1-IN-1 is used as the positive control.

表5 小分子抑制剂-PYCR1蛋白复合物构象结合能（前3）

Tab.5 Conformational binding energies of small molecule inhibitor-PYCR1 protein complexes （Top 3）

Ligands	ID	Cavity volume (Å³)	Vina score (kcal/mol)	Center (x, y, z)
Pycr1-IN-1	C1	436	-5.2	34, 58, 14
	C2	377	-4.5	31, 63, 1
	C3	316	-4.7	9, 60, -6
Exisulind	C2	377	-7.1	31, 63, 1
	C4	232	-7.1	1, 66, -5
	C3	316	-6.8	9, 60, -6
Fasudil	C1	436	-7	34, 58, 14
	C4	232	-6.5	1, 66, -5
	C5	142	-6.4	40, 83, -2
Butein	C4	232	-6.6	1, 66, -5
	C2	377	-6.5	31, 63, 1
	C1	436	-6.3	34, 58, 14
Iloprost	C1	436	-6.3	34, 58, 14
	C2	377	-6.2	31, 63, 1
	C4	232	-6.1	1, 66, -5
W-13	C1	436	-6.2	34, 58, 14
	C2	377	-6	31, 63, 1
	C4	232	-5.9	1, 66, -5

图13 候选化合物与蛋白受体互作模式图

Fig.13 Interaction pattern of candidate compounds with protein receptors. A-F: 3D interaction pattern diagram between candidate small molecule inhibitors and receptor protein PYCR1. Gray stick model represents subsequent small molecule inhibitors, the blue stick model represents PYCR1 side chain amino acid residues, the pink dashed line represents hydrophobic interactions, the green dashed line represents hydrogen bonding interactions, and the yellow dashed line represents alkyl interactions.

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