Hypoxia-related bioinformatic signatures associated with prognosis and tumor microenvironment of pancreatic cancer: Current status, concerns, and future perspectives

Table 1 The main information and prognostic performance of hypoxia-related bioinformatic models in pancreatic cancer

Ref.	Data sources	Modeling methods	Biomarkers	Prognostic performance
Yang et al[9]	TCGA, GSE62452	Cox, LASSO	CAPN2, CCNA2, PLAU	1-, 3-, 5-year area under the curve (AUC) in the training set: 0.687, 0.749, and 0.796; 1-, 3-, 5-year AUC in the test set: 0.610, 0.849, and 0.765; Calibration curve: Moderate fit; Better predictor than other clinical variables
Ren et al[10]	TCGA, ICGC	Cox, LASSO	LY6D, PCAT2, RP11-80B9.1, RP3-525N10.2, TRIM67, UCA1	1-, 2-, 3-year AUC in the training set: 0.727, 0.911, and 0.93; 1-, 2-, 3-year AUC in test set 1: 0.635, 0.696 and 0.694; 1-, 2-, 3-year AUC in test set 2: 0.68, 0.756 and 0.689; Better predictor than other clinical variables; Independent prognostic factor
Huang et al[11]	TCGA, ICGC, ArrayExpress E-MTAB-6134	Cox, RSF	LDHA, POM121C	1-, 3-, 5-year AUC in the training set: 0.716, 0.676, and 0.696; 1-, 3-, 5-year AUC in test set 1: 0.582, 0.642 and 0.657; 1-, 3-, 5-year AUC in test set 2: 0.711, 0.623 and 0.606; Better predictor than other clinical variables; Independent prognostic factor
Li et al[12]	TCGA, GSE62452, GSE78229	Cox, LASSO	KIF23, KRT13, LRP3, LY6D, MMP3, SERPINB7, SEC31B	1-, 3-, 5-year AUC: 0.763, 0.832 and 0.814; Better predictor than other clinical variables; Independent prognostic factor
Ren et al[13]	TCGA, ICGC	Cox, LASSO	ARID5A, FAM19A2, ICOSLG, IGLV7-46, SPRN	1-, 2-, 3-year AUC in the training set: 0.77, 0.793, and 0.781; 1-, 2-, 3-year AUC in the test set: 0.675, 0.678 and 0.57; Better predictor than other clinical variables; Independent prognostic factor
Zhou et al[14]	TCGA, GSE102238, GSE62452, GSE85916	Cox, LASSO	BHLHE40, ENO1, SDC4, TGM2	Calibration curve: Moderate fit; Independent prognostic factor
Sun et al[15]	TCGA	Cox, LASSO	CCAT2, CEP83-DT, CYTOR, DANCR, GAS5, LINC01029, LINC01133, LINC01963, LINC02287, LINC-PINT, LNCSRLR, SH3PXD2A-AS1, TSPOAP1-AS1, UCA1	1-, 3-, 5-year AUC in the training set: 0.804, 0.89, and 0.915; 1-, 3-, 5-year AUC in the test set: 0.694, 0.769, and 0.866; Calibration curve: Moderate fit; Independent prognostic factor
Tian et al[16]	TCGA, GSE62452	Cox, LASSO	ANKZF1, CITED2, ENO3, JMJD6, LDHA, NDST1, SIAH2, TES	1-, 3-, 5-year AUC in the training set: 0.936, 0.836, and 0.840; 1-, 3-, 5-year AUC in the test set: 0.814, 0.784, and 0.714; Calibration curve: Moderate fit; Independent prognostic factor
Zhang et al[17]	TCGA, ICGC, GSE57495	Cox	ANXA2, LDHA, TES	1-, 3-, 5-year AUC in the training set: 0.683, 0.654, and 0.776; 1-, 3-, 5-year AUC in test set 1: 0.670, 0.628 and 0.761; 1-, 3-, 5-year AUC in test set 2: 0.684, 0.612 and 0.647; Independent prognostic factor
Chen et al[18]	TCGA, GSE28735, GSE62452, ICGC	Cox, LASSO	GDF11, IL18, NR0B1, PLAU, PPP3CA, S100A16, SEMA3C	1-, 3-, 5-year AUC in the training set: 0.76, 0.80, and 0.82; 1-, 3-, 5-year AUC in test set 1: 0.60, 0.83 and 0.79; 1-, 3-, 5-year AUC in test set 2: 0.75, 0.67 and 0.56; Calibration curve: Moderate fit; Better predictor than other clinical variables; Independent prognostic factor
Ding et al[19]	TCGA, GSE78229, GSE57495	Cox	ENO3, LDHA, PGK1, PGM1	1-, 3-, 5-year AUC in the training set: 0.701, 0.758, and 0.884; 1-, 3-, 5-year AUC in the test set: 0.602, 0.669, and 0.725; Independent prognostic factor

ANKZF1: Ankyrin repeat and zinc finger peptidyl tRNA hydrolase 1; ANXA2: Annexin A2; ARID5A: AT-rich interaction domain 5A; BHLHE40: Basic helix-loop-helix family member e40; CAPN2: Calpain 2; CCAT2: Colon cancer associated transcript 2; CCNA2: Cyclin A2; CEP83-DT: Centrosomal protein 83 divergent transcript; CITED2: Glutamic acid/aspartic acid-rich carboxyl-terminal domain 2; CYTOR: Cytoskeleton regulator RNA; DANCR: Differentiation antagonizing non-protein coding RNA; ENO1: Enolase 1; ENO3: Enolase 3; FAM19A2: Family with sequence similarity 19 member A2; GAS5: Growth arrest specific 5; GDF11: Growth differentiation factor 11; ICOSLG: Inducible T cell costimulator ligand; IGLV7-46: Immunoglobulin lambda variable 7-46; IL18: Interleukin 18; JMJD6: Jumonji domain containing 6; KIF23: Kinesin family member 23; KRT13: Keratin 13; LASSO: Least absolute shrinkage and selection operator; LDHA: Lactate dehydrogenase A; LINC01029/LINC01133/LINC01963/LINC02287/LINC-PINT: Long intergenic non-protein coding RNA 01029/01133/01963/02287/p53 induced transcript; LNCSRLR: Sorafenib resistance associated long non-coding RNA; LRP3: Low-density lipoprotein receptor-related protein 3; LY6D: Lymphocyte antigen 6 family member D; MMP3: Matrix metallopeptidase 3; NDST1: N-deacetylase and N-sulfotransferase 1; NR0B1: Nuclear receptor subfamily 0 group B member 1; PCAT2: Prostate cancer associated transcript 2; PGK1: Phosphoglycerate kinase 1; PGM1: Phosphoglucomutase 1; PLAU: Plasminogen activator urokinase; POM121C: Nuclear pore membrane protein 121 transmembrane nucleoporin C; PPP3CA: Protein phosphatase 3 catalytic subunit alpha; RSF: Random survival forests; S100A16: S100 calcium binding protein A16; SDC4: Syndecan 4; SEC31B: Secretory protein 31 homolog B; SEMA3C: Semaphorin 3C; SERPINB7: Serpin family B member 7; SH3PXD2A-AS1: SH3 and PX domains 2A antisense RNA 1; SIAH2: SIAH E3 ubiquitin protein ligase 2; SPRN: shadow of prion protein; TES: Testin LIM domain protein; TGM2: Transglutaminase 2; TRIM67: Tripartite motif containing 67; TSPOAP1-AS1: TSPO-associated protein 1 antisense RNA 1; UCA1: Urothelial cancer associated 1.