PAC-5 Gene Expression Signature for Predicting Prognosis of Patients with Pancreatic Adenocarcinoma

Kim, Jieun; Jo, Yunhee; Jang, Miran; Nguyen, Ngoc Ngo Yen; Yun, Hyeong Rok; Ko, Seok Hoon; Shin, Yoonhwa; Lee, Ju Seog; Kang, In‐Cheol; Ha, Joohun; Choi, Tae Gyu; Kim, Sung Soo

doi:10.3390/cancers11111749

Cited by 15 publications

(16 citation statements)

References 67 publications

(86 reference statements)

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“…Establishing gene scoring models contribute to quantify the prognostic evaluation criteria and increasing studies have performed successful precedents in this regard. [ 12 , 15 , 16 ] Our current study established a six-gene prognosis predictive model in patients with PaCa and validated the prognostic value of this model in total PaCa patients and several subgroups, confirming that the six-gene prognosis model could exactly predict the OS of patients with PaCa.…”

Section: Discussionsupporting

confidence: 65%

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Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer

Yang¹,

Wei²,

Yang

2020

Medicine

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Section: Discussionsupporting

confidence: 65%

“…[ 9 – 11 ] Besides, investigators tend to utilized WGCNA to systematically analyze cancer patients’ phenotypes, especially for establishing potential prognostic gene signature. [ 12 , 13 ]…”

Section: Introductionmentioning

confidence: 99%

Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer

Yang¹,

Wei²,

Yang

2020

Medicine

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“…Leucine-rich repeats and immunoglobulin-like domains 1 (Lrig1) regulate cultured neural stem cell quiescence. The marker was identified in multiple organs in mice [224], but there is only a paper examining Lrig1 in pancreatic cancer [225].…”

Section: Favoring Quiescence (Cell Dormancy)-a Valid Therapeutic Stramentioning

confidence: 99%

CD36 and CD97 in Pancreatic Cancer versus Other Malignancies

Tănase

Gheorghișan-Gălățeanu

Popescu

et al. 2020

IJMS

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Starting from the recent identification of CD36 and CD97 as a novel marker combination of fibroblast quiescence in lung during fibrosis, we aimed to survey the literature in search for facts about the separate (or concomitant) expression of clusters of differentiation CD36 and CD97 in either tumor- or pancreatic-cancer-associated cells. Here, we provide an account of the current knowledge on the diversity of the cellular functions of CD36 and CD97 and explore their potential (common) contributions to key cellular events in oncogenesis or metastasis development. Emphasis is placed on quiescence as an underexplored mechanism and/or potential target in therapy. Furthermore, we discuss intricate signaling mechanisms and networks involving CD36 and CD97 that may regulate different subpopulations of tumor-associated cells, such as cancer-associated fibroblasts, adipocyte-associated fibroblasts, tumor-associated macrophages, or neutrophils, during aggressive pancreatic cancer. The coexistence of quiescence and activated states in cancer-associated cell subtypes during pancreatic cancer should be better documented, in different histological forms. Remodeling of the local microenvironment may also change the balance between growth and dormant state. Taking advantage of the reported data in different other tissue types, we explore the possibility to induce quiescence (similar to that observed in normal cells), as a therapeutic option to delay the currently observed clinical outcome.

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“…Nevertheless, a large percentage of patients with PAAD may benefit from immunotherapy in the future [14]. With remarkable progress in bioinformatics, prognostic gene expression characteristics have been extensively developed for PAAD [15]. The development of tumor molecular biology has further promoted tumor therapy based on immune-related genes.…”

Section: Introductionmentioning

confidence: 99%

Identification of Prognostic Immune-Related Genes in Pancreatic Adenocarcinoma and Establishment of a Prognostic Nomogram: A Bioinformatic Study

Deng

Jin

et al. 2020

BioMed Research International

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Background. The prognosis of pancreatic adenocarcinoma (PAAD) is extremely poor and has not been improved. Thus, an effective method to assess the prognosis of patients must be established to improve their survival rate. Method. This study investigated immune-related genes that could be used as potential therapeutic targets for PAAD. Level 3 gene expression data from the PAAD cohort and the relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. For validation, other PAAD datasets (DSE62452) were downloaded from the Gene Expression Omnibus (GEO) database. The PAAD datasets from TCGA and GEO were used to screen immune-related genes through the Molecular Signatures Database using gene set enrichment analysis. Then, the overlapping immune-related genes of the two datasets were identified. Coexpression networks of the immune-related genes were constructed. Results. A signature of three immune-related genes (CKLF, ERAP2, and EREG) was identified in patients with PAAD. The signature could be used to divide the patients with PAAD into high- and low-risk groups based on their median risk score. Multivariate Cox regression analysis was performed to determine the independent prognostic factors of PAAD. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to assess the prediction accuracy of the prognostic signature. Last, a nomogram was established to assess the individualized prognosis prediction model based on the clinical characteristics and risk score of the TCGA PAAD dataset. The accuracy of the prognostic signature was further evaluated through functional evaluation and principal component analysis. Conclusions. The results indicated that the signature of three immune-related genes had excellent predictive value for PAAD. These findings might help improve personalized treatment and medical decisions.

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PAC-5 Gene Expression Signature for Predicting Prognosis of Patients with Pancreatic Adenocarcinoma

Cited by 15 publications

References 67 publications

Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer

Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer

CD36 and CD97 in Pancreatic Cancer versus Other Malignancies

Identification of Prognostic Immune-Related Genes in Pancreatic Adenocarcinoma and Establishment of a Prognostic Nomogram: A Bioinformatic Study

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