Editorial
Copyright ©The Author(s) 2024.
World J Gastroenterol. Nov 28, 2024; 30(44): 4689-4696
Published online Nov 28, 2024. doi: 10.3748/wjg.v30.i44.4689
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, GSE62452Cox, LASSOCAPN2, CCNA2, PLAU1-, 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, ICGCCox, LASSOLY6D, PCAT2, RP11-80B9.1, RP3-525N10.2, TRIM67, UCA11-, 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-6134Cox, RSFLDHA, POM121C1-, 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, GSE78229Cox, LASSOKIF23, KRT13, LRP3, LY6D, MMP3, SERPINB7, SEC31B1-, 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, ICGCCox, LASSOARID5A, FAM19A2, ICOSLG, IGLV7-46, SPRN1-, 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, GSE85916Cox, LASSOBHLHE40, ENO1, SDC4, TGM2Calibration curve: Moderate fit; Independent prognostic factor
Sun et al[15]TCGACox, LASSOCCAT2, CEP83-DT, CYTOR, DANCR, GAS5, LINC01029, LINC01133, LINC01963, LINC02287, LINC-PINT, LNCSRLR, SH3PXD2A-AS1, TSPOAP1-AS1, UCA11-, 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, GSE62452Cox, LASSOANKZF1, CITED2, ENO3, JMJD6, LDHA, NDST1, SIAH2, TES1-, 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, GSE57495CoxANXA2, LDHA, TES1-, 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, ICGCCox, LASSOGDF11, IL18, NR0B1, PLAU, PPP3CA, S100A16, SEMA3C1-, 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, GSE57495CoxENO3, LDHA, PGK1, PGM11-, 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
Table 2 The role of hypoxic-related prognostic models in the tumor microenvironment and antitumor therapy and their experimental validation and underlying mechanisms
Ref.
TME changes in a high-risk group
Therapeutic significance
Experimental validation
Mechanism
Yang et al[9]CD8+ T cells, T cells, B cells, plasmacytoid dendritic cells, immature dendritic cells, and cytotoxic cellsHigher sensitivity to cisplatin and paclitaxel in the high-risk groupqPCR: MRNA expressionNone
Ren et al[10]CD8+ T cells, CD4+ T cells, and endothelial cells; Macrophages and fibroblastsHigher sensitivity to paclitaxel, erlotinib, and cisplatin in the high-risk group; No significant difference in TMB, PD1, PD-L1, CTLA4 and IPS scoreNoneNone
Huang et al[11]NoneKRAS mutations are more frequent in the hypoxic subtypeqPCR: MRNA expressionNone
Li et al[12]T cell exclusion scoresLower PD1 expression in the high-risk subgroupNoneNone
Ren et al[13]CD8+ T cells, B cells, macrophage, eosinophil, and monocyte; Immune activation scoreHigher sensitivity to paclitaxel and erlotinib in the high-risk group; No significant difference in TMB, MSI, and IPS scoreNoneNone
Zhou et al[14]CD8+ T cells, activated CD4+ memory T cells, naïve B cells, and plasma cells; M0 macrophages; Scores in CD4+ T cell recruiting, Th17 cell recruiting, dendritic cell recruiting, macrophage recruiting, and killing of cancer cellsNoneqPCR: MRNA expression; Wound-healing assay: Migration; Transwell assay: InvasionChIP assay: BHLHE40/TLR3 axis
Sun et al[15]CD8+ T cells and B cellsNoneqPCR: MRNA expression; MTT assay: Proliferation; Transwell assay: InvasionChIP assay and luciferase reporter assay: HIF-1α/ TSPOAP1-AS1 axis
Tian et al[16]CD8+ T cells and regulatory T cellLower PD1 and CTLA4 expression in a high-risk groupqPCR: MRNA expressionNone
Zhang et al[17]T cells; M0 macrophagesHigher LDHA methylation in pancreatic cancer tissuesNoneNone
Chen et al[18]CD8+ T cells, follicular helper T cells, memory B cells, monocytes, M1 macrophages, M2 macrophages, resting mast cells, and eosinophils; Immune score and stromal scoreHigher TMB in the high-risk groupsNoneNone
Ding et al[19]CD8+ T cells, plasma cells, and naïve B cells; M2 macrophages, resting memory CD4+ T cells, and resting natural killer cellsNoneNoneNone