Development and Validation of an Inflammatory Response-Related Gene Signature for Predicting the Prognosis of Pancreatic Adenocarcinoma

Deng, Zuliang; Zhou, Dingzhong; Cao, Sujuan; Li, Qing; Zhang, Jianfang; Xie, Hui

doi:10.1007/s10753-022-01657-6

Cited by 8 publications

(5 citation statements)

References 54 publications

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“…Next, considering the lack of data on long survival in PC, we compared our risk model with published models on ROC at 1 year, and our model achieved the largest AUC in the data set TCGA-PAAD ( Figure 4I ), achieved the fourth largest AUC in CPTAC ( Supplementary Figure S1A ), and the second in GEO57495 ( Supplementary Figure S1B ). The c-index of our model is 0.70, which is higher than the c-index values of Lin et al (2021) (0.66); Ma et al (2021) (0.63); Zhu et al (2021) (0.66); Xie et al 2022 (0.68); and Deng et al (2022) (0.64) models ( Figure 4J ). The c-index values of our model based on CPTAC and GEO57495 were 0.595 ( Supplementary Figure S1C ) and 0.596 ( Supplementary Figure S1D ), respectively.…”

Section: Resultscontrasting

confidence: 61%

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Prognostic utility of TME-associated genes in pancreatic cancer

Nie,

Xu,

Bai

et al. 2023

Front. Genet.

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Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC.Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy.Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model.Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

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Section: Resultscontrasting

confidence: 61%

“…(H) K-M curves of the survival probability in patients with stages 3–4 disease ( p < 0.05). (I) 1-year ROC curves of the risk score in Lin et al (2021) , Ma et al (2021) , Zhu et al (2021) , Xie et al 2022 , Deng et al (2022) , and our models. (J) C-index of different models.…”

Section: Resultsmentioning

confidence: 99%

Prognostic utility of TME-associated genes in pancreatic cancer

Nie,

Xu,

Bai

et al. 2023

Front. Genet.

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“…To our knowledge, inflammation is an important hallmark of cancer and plays an integral role in the development and progression of cancer. Previous studies have indicated that inflammatory-related gene signatures can predict the prognosis and impact the immune status of HCC[ 22 ], lung adenocarcinoma[ 39 ], head and neck squamous cell carcinoma[ 40 ], and pancreatic adenocarcinoma[ 41 ]. These findings suggest that inflammatory-related genes could be used as tumour prognostic markers and are closely related to tumorigenesis.…”

Section: Discussionmentioning

confidence: 99%

Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients

Hu,

Huang,

Halina

et al. 2024

World J Gastrointest Oncol

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BACKGROUND Gastric cancer (GC) is a highly aggressive malignancy with a heterogeneous nature, which makes prognosis prediction and treatment determination difficult. Inflammation is now recognized as one of the hallmarks of cancer and plays an important role in the aetiology and continued growth of tumours. Inflammation also affects the prognosis of GC patients. Recent reports suggest that a number of inflammatory-related biomarkers are useful for predicting tumour prognosis. However, the importance of inflammatory-related biomarkers in predicting the prognosis of GC patients is still unclear. AIM To investigate inflammatory-related biomarkers in predicting the prognosis of GC patients. METHODS In this study, the mRNA expression profiles and corresponding clinical information of GC patients were obtained from the Gene Expression Omnibus (GEO) database (GSE66229). An inflammatory-related gene prognostic signature model was constructed using the least absolute shrinkage and selection operator Cox regression model based on the GEO database. GC patients from the GSE26253 cohort were used for validation. Univariate and multivariate Cox analyses were used to determine the independent prognostic factors, and a prognostic nomogram was established. The calibration curve and the area under the curve based on receiver operating characteristic analysis were utilized to evaluate the predictive value of the nomogram. The decision curve analysis results were plotted to quantify and assess the clinical value of the nomogram. Gene set enrichment analysis was performed to explore the potential regulatory pathways involved. The relationship between tumour immune infiltration status and risk score was analysed via Tumour Immune Estimation Resource and CIBERSORT. Finally, we analysed the association between risk score and patient sensitivity to commonly used chemotherapy and targeted therapy agents. RESULTS A prognostic model consisting of three inflammatory-related genes (MRPS17, GUF1, and PDK4) was constructed. Independent prognostic analysis revealed that the risk score was a separate prognostic factor in GC patients. According to the risk score, GC patients were stratified into high- and low-risk groups, and patients in the high-risk group had significantly worse prognoses according to age, sex, TNM stage and Lauren type. Consensus clustering identified three subtypes of inflammation that could predict GC prognosis more accurately than traditional grading and staging. Finally, the study revealed that patients in the low-risk group were more sensitive to certain drugs than were those in the high-risk group, indicating a link between inflammation-related genes and drug sensitivity. CONCLUSION In conclusion, we established a novel three-gene prognostic signature that may be useful for predicting the prognosis and personalizing treatment decisions of GC patients.

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“…Compared to other prediction signatures of PAAD, such as research focused on necroptosis-related gene, [33] cuprotosis programmed-cell-death-related lncRNA, [34] extracellular matrix-related genes, [35] ferroposis-related genes, [36] anoikis-related long noncoding RNAs [37] as well as inflammatory response-related genes, [38] we constructed a signature with less genes but higher AUC. A more concise model means economic advantage in clinical application, and a model with superior AUC achieves better clinically meaningful prediction for PAAD.…”

Section: Discussionmentioning

confidence: 99%

Construction of prognostic markers for pancreatic adenocarcinoma based on mitochondrial fusion-related genes

Chen,

Zhang,

Jiang

et al. 2024

Medicine

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Early detection of pancreatic adenocarcinoma (PAAD) remains a pressing clinical problem. Information on the clinical prognostic value of mitochondrial fusion-related genes in PAAD remains limited. In this study, we investigated mitochondrial fusion-related genes of PAAD to establish an optimal signature plate for the early diagnosis and prognosis of PAAD. The cancer genome atlas database was used to integrate the Fragments Per Kilobase Million data and related clinical data for patients with PAAD. Least absolute shrinkage and selection operator regression, cox regression, operating characteristic curves, and cBioPortal database was used to evaluate model performance, assess the prognostic ability and sensitivity. The levels of immune infiltration were compared by CIBERSORT, QUANTISEQ, and EPIC. Chemotherapy sensitivity between the different risk groups was compared by the Genomics of Drug Sensitivity in Cancer database and the “pRRophetic” R package. At last, a total of 4 genes were enrolled in multivariate Cox regression analysis. The risk-predictive signature was constructed as: (0.5438 × BAK1) + (‐1.0259 × MIGA2) + (1.1140 × PARL) + (‐0.4300 × PLD6). The area under curve of these 4 genes was 0.89. Cox regression analyses indicates the signature was an independent prognostic indicator (P < .001, hazard ratio [HR] = 1.870, 95% CI = 1.568–2.232). Different levels of immune cell infiltration in the 2 risk groups were observed using the 3 algorithms, with tumor mutation load (P = .0063), tumor microenvironment score (P = .01), and Tumor Immune Dysfunction and Exclusion score (P = .0012). The chemotherapeutic sensitivity analysis also revealed that the half-maximal inhibitory concentration of 5-fluorouracil (P = .0127), cisplatin (P = .0099), docetaxel (P < .0001), gemcitabine (P = .0047), and pacilataxel (P < .0001) were lower in the high-risk groups, indicating that the high-risk group patients had a greater sensitivity to chemotherapy. In conclude, we established a gene signature plate comprised of 4 mitochondrial fusion related genes to facilitate early diagnosis and prognostic prediction of PAAD.

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Development and Validation of an Inflammatory Response-Related Gene Signature for Predicting the Prognosis of Pancreatic Adenocarcinoma

Cited by 8 publications

References 54 publications

Prognostic utility of TME-associated genes in pancreatic cancer

Prognostic utility of TME-associated genes in pancreatic cancer

Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients

Construction of prognostic markers for pancreatic adenocarcinoma based on mitochondrial fusion-related genes

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