Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients

Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wei Li [verfasserIn] Tiandong Li [verfasserIn] Chenguang Sun [verfasserIn] Yimeng Du [verfasserIn] Linna Chen [verfasserIn] Chunyan Du [verfasserIn] Jianxiang Shi [verfasserIn] Weijie Wang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1

Übergeordnetes Werk:	In: Molecular Medicine - BMC, 2002, 28(2022), 1, Seite 16
Übergeordnetes Werk:	volume:28 ; year:2022 ; number:1 ; pages:16

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1186/s10020-022-00467-8

Katalog-ID:	DOAJ029796997

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520			\|a Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.
650		4	\|a Pancreatic cancer
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700	0		\|a Jianxiang Shi \|e verfasserin \|4 aut
700	0		\|a Weijie Wang \|e verfasserin \|4 aut
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allfields	10.1186/s10020-022-00467-8 doi (DE-627)DOAJ029796997 (DE-599)DOAJ91f97aa0f28e45e7946af0b4e1b3c053 DE-627 ger DE-627 rakwb eng RM1-950 QD415-436 Wei Li verfasserin aut Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs. Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1 Therapeutics. Pharmacology Biochemistry Tiandong Li verfasserin aut Chenguang Sun verfasserin aut Yimeng Du verfasserin aut Linna Chen verfasserin aut Chunyan Du verfasserin aut Jianxiang Shi verfasserin aut Weijie Wang verfasserin aut In Molecular Medicine BMC, 2002 28(2022), 1, Seite 16 (DE-627)269539611 (DE-600)1475577-4 15283658 nnns volume:28 year:2022 number:1 pages:16 https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/article/91f97aa0f28e45e7946af0b4e1b3c053 kostenfrei https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/toc/1076-1551 Journal toc kostenfrei https://doaj.org/toc/1528-3658 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022 1 16
spelling	10.1186/s10020-022-00467-8 doi (DE-627)DOAJ029796997 (DE-599)DOAJ91f97aa0f28e45e7946af0b4e1b3c053 DE-627 ger DE-627 rakwb eng RM1-950 QD415-436 Wei Li verfasserin aut Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs. Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1 Therapeutics. Pharmacology Biochemistry Tiandong Li verfasserin aut Chenguang Sun verfasserin aut Yimeng Du verfasserin aut Linna Chen verfasserin aut Chunyan Du verfasserin aut Jianxiang Shi verfasserin aut Weijie Wang verfasserin aut In Molecular Medicine BMC, 2002 28(2022), 1, Seite 16 (DE-627)269539611 (DE-600)1475577-4 15283658 nnns volume:28 year:2022 number:1 pages:16 https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/article/91f97aa0f28e45e7946af0b4e1b3c053 kostenfrei https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/toc/1076-1551 Journal toc kostenfrei https://doaj.org/toc/1528-3658 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022 1 16
allfields_unstemmed	10.1186/s10020-022-00467-8 doi (DE-627)DOAJ029796997 (DE-599)DOAJ91f97aa0f28e45e7946af0b4e1b3c053 DE-627 ger DE-627 rakwb eng RM1-950 QD415-436 Wei Li verfasserin aut Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs. Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1 Therapeutics. Pharmacology Biochemistry Tiandong Li verfasserin aut Chenguang Sun verfasserin aut Yimeng Du verfasserin aut Linna Chen verfasserin aut Chunyan Du verfasserin aut Jianxiang Shi verfasserin aut Weijie Wang verfasserin aut In Molecular Medicine BMC, 2002 28(2022), 1, Seite 16 (DE-627)269539611 (DE-600)1475577-4 15283658 nnns volume:28 year:2022 number:1 pages:16 https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/article/91f97aa0f28e45e7946af0b4e1b3c053 kostenfrei https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/toc/1076-1551 Journal toc kostenfrei https://doaj.org/toc/1528-3658 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022 1 16
allfieldsGer	10.1186/s10020-022-00467-8 doi (DE-627)DOAJ029796997 (DE-599)DOAJ91f97aa0f28e45e7946af0b4e1b3c053 DE-627 ger DE-627 rakwb eng RM1-950 QD415-436 Wei Li verfasserin aut Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs. Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1 Therapeutics. Pharmacology Biochemistry Tiandong Li verfasserin aut Chenguang Sun verfasserin aut Yimeng Du verfasserin aut Linna Chen verfasserin aut Chunyan Du verfasserin aut Jianxiang Shi verfasserin aut Weijie Wang verfasserin aut In Molecular Medicine BMC, 2002 28(2022), 1, Seite 16 (DE-627)269539611 (DE-600)1475577-4 15283658 nnns volume:28 year:2022 number:1 pages:16 https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/article/91f97aa0f28e45e7946af0b4e1b3c053 kostenfrei https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/toc/1076-1551 Journal toc kostenfrei https://doaj.org/toc/1528-3658 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022 1 16
allfieldsSound	10.1186/s10020-022-00467-8 doi (DE-627)DOAJ029796997 (DE-599)DOAJ91f97aa0f28e45e7946af0b4e1b3c053 DE-627 ger DE-627 rakwb eng RM1-950 QD415-436 Wei Li verfasserin aut Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs. Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1 Therapeutics. Pharmacology Biochemistry Tiandong Li verfasserin aut Chenguang Sun verfasserin aut Yimeng Du verfasserin aut Linna Chen verfasserin aut Chunyan Du verfasserin aut Jianxiang Shi verfasserin aut Weijie Wang verfasserin aut In Molecular Medicine BMC, 2002 28(2022), 1, Seite 16 (DE-627)269539611 (DE-600)1475577-4 15283658 nnns volume:28 year:2022 number:1 pages:16 https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/article/91f97aa0f28e45e7946af0b4e1b3c053 kostenfrei https://doi.org/10.1186/s10020-022-00467-8 kostenfrei https://doaj.org/toc/1076-1551 Journal toc kostenfrei https://doaj.org/toc/1528-3658 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022 1 16
language	English
source	In Molecular Medicine 28(2022), 1, Seite 16 volume:28 year:2022 number:1 pages:16
sourceStr	In Molecular Medicine 28(2022), 1, Seite 16 volume:28 year:2022 number:1 pages:16
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1 Therapeutics. Pharmacology Biochemistry
isfreeaccess_bool	true
container_title	Molecular Medicine
authorswithroles_txt_mv	Wei Li @@aut@@ Tiandong Li @@aut@@ Chenguang Sun @@aut@@ Yimeng Du @@aut@@ Linna Chen @@aut@@ Chunyan Du @@aut@@ Jianxiang Shi @@aut@@ Weijie Wang @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	269539611
id	DOAJ029796997
language_de	englisch
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Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. 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callnumber-first	R - Medicine
author	Wei Li
spellingShingle	Wei Li misc RM1-950 misc QD415-436 misc Pancreatic cancer misc Biomarkers misc LAMB3 misc FN1 misc KRT19 misc ANXA1 misc Therapeutics. Pharmacology misc Biochemistry Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients
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topic_title	RM1-950 QD415-436 Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients Pancreatic cancer Biomarkers LAMB3 FN1 KRT19 ANXA1
topic	misc RM1-950 misc QD415-436 misc Pancreatic cancer misc Biomarkers misc LAMB3 misc FN1 misc KRT19 misc ANXA1 misc Therapeutics. Pharmacology misc Biochemistry
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title	Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients
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title_full	Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients
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author_browse	Wei Li Tiandong Li Chenguang Sun Yimeng Du Linna Chen Chunyan Du Jianxiang Shi Weijie Wang
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title_sort	identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients
callnumber	RM1-950
title_auth	Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients
abstract	Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.
abstractGer	Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.
abstract_unstemmed	Abstract Background Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only “curative” treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC. Methods In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database. Results LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19. Conclusions In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.
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title_short	Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients
url	https://doi.org/10.1186/s10020-022-00467-8 https://doaj.org/article/91f97aa0f28e45e7946af0b4e1b3c053 https://doaj.org/toc/1076-1551 https://doaj.org/toc/1528-3658
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Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients

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