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LncRNAs associated with vascular mimicry establish a novel molecular subtype and prognostic model for pancreatic cancer

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Da Li
Da Li
Da Li
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Qiang Zhang
Qiang Zhang
Qiang Zhang
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Yubao Tang
Yubao Tang
Yubao Tang
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Feiyu Mao
Feiyu Mao
Feiyu Mao
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Abstract and Figures

Background: Vascular mimicry (VM) epitomizes an innovative tumor angiogenesis pathway, potentially serving as an alternate conduit under the assumption of traditional tumor angiogenesis pathway inhibition. The role of VM in pancreatic cancer (PC), however, remains unexplored. Methods: Using differential analysis and Spearman correlation, we identified key long non-coding RNAs (lncRNAs) signatures in PC from the collected set of VM-associated genes in the literature. We identified optimal clusters using the non-negative matrix decomposition (NMF) algorithm, and then compared clinicopathological features and prognostic differences between clusters. We also assessed tumor microenvironmental (TME) differences between clusters using multiple algorithms. Using univariate Cox regression analyses as well as lasso regression, we constructed and validated new lncRNA prognostic risk models for PC. We used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to analyze model-enriched functions and pathways. Nomograms were then developed to predict patient survival in association with clinicopathological factors. In addition, single-cell RNA-sequencing (scRNA-seq) analysis was used to analyze the expression patterns of VM-related genes and lncRNAs in the PC of TME. Finally, we used the Connectivity Map (cMap) database to predict local anaesthetics that could modify the VM of PC. Results: In this study, we developed a novel three-cluster molecular subtype using the identified VM-associated lncRNA signatures of PC. The different subtypes have significantly different clinical characteristics and prognostic value, and also show differential treatment response and TME. Following an in-depth analysis, we constructed and validated a novel prognostic risk model for PC based on the VM-associated lncRNA signatures. Enrichment analysis suggested that high riskscores were significantly associated with functions and pathways, including extracellular matrix remodeling, et al. In addition, we predicted eight local anaesthetics that could modulate VM in PC. Finally, we discovered differential expression of VM-related genes and lncRNAs across various cell types within pancreatic cancer. Conclusion: VM has a critical role in PC. This study pioneers the development of a VM-based molecular subtype that demonstrates substantial differentiation in PC populations. Furthermore, we highlighted the significance of VM within the immune microenvironment of PC. Moreover, VM might contribute to PC tumorigenesis through its mediation of mesenchymal remodeling and endothelial transdifferentiation-related pathways, which offers a new perspective on its role in PC.
Flowchart of the study
Flowchart of the study
… 
Screening of vascular mimicry (VM) gene signatures and VM-related lncRNA signatures in pancreatic cancer. A The heatmap displays the results of differential analysis, with six genes downregulated and nine genes upregulated in pancreatic cancer. B Univariate Cox analysis shows that six VM gene signatures have significant prognostic value in pancreatic cancer in the training cohort (Tain_PAAD). C The volcano plot shows the differential expression analysis results of lncRNAs between tumor tissue and normal tissue in pancreatic cancer, with 4015 upregulated and 273 downregulated. D Intersection of 652 lncRNAs significantly positively correlated with VM gene signatures and 4015 significantly upregulated lncRNAs yield 568 lncRNAs
Screening of vascular mimicry (VM) gene signatures and VM-related lncRNA signatures in pancreatic cancer. A The heatmap displays the results of differential analysis, with six genes downregulated and nine genes upregulated in pancreatic cancer. B Univariate Cox analysis shows that six VM gene signatures have significant prognostic value in pancreatic cancer in the training cohort (Tain_PAAD). C The volcano plot shows the differential expression analysis results of lncRNAs between tumor tissue and normal tissue in pancreatic cancer, with 4015 upregulated and 273 downregulated. D Intersection of 652 lncRNAs significantly positively correlated with VM gene signatures and 4015 significantly upregulated lncRNAs yield 568 lncRNAs
… 
The creation of novel molecular subtypes in pancreatic cancer based on 568-VMGs. A Unsupervised clustering analysis via non-negative matrix factorization (NMF), with similarity coefficient and heatmap, points to rank = 3 as the optimal cluster. B Significant disparities in tumor differentiation and therapy response among clusters are apparent (Stage1: IA + IB + IIA, Stage2: IIB + III, Stage3: IV; G1: well differentiated, G2: moderately differentiated, G3: poorly differentiated, G4: undifferentiated; CR complete response, PR partial remission, SD stable disease, PD progressive disease). C, D The overall survival (OS) and progression-free interval (PFI) were notably extended for Cluster3 (C3) when compared to the other two clusters (P < 0.05)
The creation of novel molecular subtypes in pancreatic cancer based on 568-VMGs. A Unsupervised clustering analysis via non-negative matrix factorization (NMF), with similarity coefficient and heatmap, points to rank = 3 as the optimal cluster. B Significant disparities in tumor differentiation and therapy response among clusters are apparent (Stage1: IA + IB + IIA, Stage2: IIB + III, Stage3: IV; G1: well differentiated, G2: moderately differentiated, G3: poorly differentiated, G4: undifferentiated; CR complete response, PR partial remission, SD stable disease, PD progressive disease). C, D The overall survival (OS) and progression-free interval (PFI) were notably extended for Cluster3 (C3) when compared to the other two clusters (P < 0.05)
… 
Disparities in the tumor microenvironment among the novel molecular subtypes. A C3 exhibits significantly elevated stromal, immune, and ESTIMATE scores relative to the other two clusters (P < 0.05). B The majority of the 22 types of immune cell infiltrations demonstrated significant variations in their abundance across the different clusters (p < 0.05). C C3 manifested significantly elevated expression levels for most stimulatory immune checkpoints (p < 0.05). D The expression levels of the primary suppressive immune checkpoints are significantly amplified in C3 (P < 0.05). E Immune checkpoint blockade response analysis indicates Cluster1 (C1) possesses a superior TIDE score, followed by C3, with Cluster2 (C2) showing the least (P < 0.05) (*P < 0.05; **P < 0.01, ***P < 0.001, ****P < 0.0001)
Disparities in the tumor microenvironment among the novel molecular subtypes. A C3 exhibits significantly elevated stromal, immune, and ESTIMATE scores relative to the other two clusters (P < 0.05). B The majority of the 22 types of immune cell infiltrations demonstrated significant variations in their abundance across the different clusters (p < 0.05). C C3 manifested significantly elevated expression levels for most stimulatory immune checkpoints (p < 0.05). D The expression levels of the primary suppressive immune checkpoints are significantly amplified in C3 (P < 0.05). E Immune checkpoint blockade response analysis indicates Cluster1 (C1) possesses a superior TIDE score, followed by C3, with Cluster2 (C2) showing the least (P < 0.05) (*P < 0.05; **P < 0.01, ***P < 0.001, ****P < 0.0001)
… 
The novel developed lncRNA prognostic risk model for pancreatic cancer, based on VM. A Univariate Cox analysis shows that only 16 VM-related lncRNA signatures still have significant prognostic value in the test cohort. B The model was constructed using the Lasso-Cox method, with a tenfold cross-validation to select the optimal model. A minimum Lambda value of 0.04 was obtained, resulting in the selection of five lncRNAs for constructing the model. C and D In both the training and test sets, the high-risk group had a poorer survival rate than the low-risk group (P < 0.05). E The G3 + G4 group had a significantly higher risk score compared to the G2 + G1 group (P < 0.05), where G1 refers to well differentiation, G2 to moderate differentiation, G3 to poor differentiation, and G4 to undifferentiation
+4
The novel developed lncRNA prognostic risk model for pancreatic cancer, based on VM. A Univariate Cox analysis shows that only 16 VM-related lncRNA signatures still have significant prognostic value in the test cohort. B The model was constructed using the Lasso-Cox method, with a tenfold cross-validation to select the optimal model. A minimum Lambda value of 0.04 was obtained, resulting in the selection of five lncRNAs for constructing the model. C and D In both the training and test sets, the high-risk group had a poorer survival rate than the low-risk group (P < 0.05). E The G3 + G4 group had a significantly higher risk score compared to the G2 + G1 group (P < 0.05), where G1 refers to well differentiation, G2 to moderate differentiation, G3 to poor differentiation, and G4 to undifferentiation
… 
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Vol.:(0123456789)
1 3
Journal of Cancer Research and Clinical Oncology (2023) 149:11571–11584
https://doi.org/10.1007/s00432-023-05015-3
RESEARCH
LncRNAs associated withvascular mimicry establish anovel molecular
subtype andprognostic model forpancreatic cancer
DaLi1· QiangZhang2· YubaoTang2· FeiyuMao1· JiaZeng1· AnlaiJi1
Received: 13 June 2023 / Accepted: 19 June 2023 / Published online: 4 July 2023
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023
Abstract
Background Vascular mimicry (VM) epitomizes an innovative tumor angiogenesis pathway, potentially serving as an alter-
nate conduit under the assumption of traditional tumor angiogenesis pathway inhibition. The role of VM in pancreatic cancer
(PC), however, remains unexplored.
Methods Using differential analysis and Spearman correlation, we identified key long non-coding RNAs (lncRNAs) sig-
natures in PC from the collected set of VM-associated genes in the literature. We identified optimal clusters using the
non-negative matrix decomposition (NMF) algorithm, and then compared clinicopathological features and prognostic dif-
ferences between clusters. We also assessed tumor microenvironmental (TME) differences between clusters using multiple
algorithms. Using univariate Cox regression analyses as well as lasso regression, we constructed and validated new lncRNA
prognostic risk models for PC. We used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to
analyze model-enriched functions and pathways. Nomograms were then developed to predict patient survival in association
with clinicopathological factors. In addition, single-cell RNA-sequencing (scRNA-seq) analysis was used to analyze the
expression patterns of VM-related genes and lncRNAs in the PC of TME. Finally, we used the Connectivity Map (cMap)
database to predict local anaesthetics that could modify the VM of PC.
Results In this study, we developed a novel three-cluster molecular subtype using the identified VM-associated lncRNA sig-
natures of PC. The different subtypes have significantly different clinical characteristics and prognostic value, and also show
differential treatment response and TME. Following an in-depth analysis, we constructed and validated a novel prognostic
risk model for PC based on the VM-associated lncRNA signatures. Enrichment analysis suggested that high riskscores were
significantly associated with functions and pathways, including extracellular matrix remodeling, etal. In addition, we pre-
dicted eight local anaesthetics that could modulate VM in PC. Finally, we discovered differential expression of VM-related
genes and lncRNAs across various cell types within pancreatic cancer.
Conclusion VM has a critical role in PC. This study pioneers the development of a VM-based molecular subtype that
demonstrates substantial differentiation in PC populations. Furthermore, we highlighted the significance of VM within the
immune microenvironment of PC. Moreover, VM might contribute to PC tumorigenesis through its mediation of mesen-
chymal remodeling and endothelial transdifferentiation-related pathways, which offers a new perspective on its role in PC.
Keywords Vascular mimicry· Pancreatic cancer· Prognosis· Molecular subtype· Competitive endogenous RNA
Introduction
Pancreatic cancer (PC) is a formidable disease with an esca-
lating global incidence rate. According to the World Health
Organization, PC has ascended to the twelfth most prevalent
cancer worldwide, with projections indicating that by 2030,
it will become the second leading cause of cancer-related
fatalities (Sung etal. 2020). Contemporary treatments for PC
encompass radical resection surgery and chemotherapy (Miz-
rahi etal. 2020). However, despite these therapeutic modali-
ties, the 5-year survival rate for PC remains dismally low, with
fewer than 10% of patients enduring beyond 5years post-
diagnosis, and a heightened probability of recurrence (Huang
etal. 2019). This is principally attributed to the exceptional
drug resistance frequently demonstrated by PC, alongside the
challenges of eradicating all tumor cells via surgery (Jiang
Qiang Zhang and Yubao Tang contributed equally to this work.
Extended author information available on the last page of the article
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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