Identification of a Novel Chemokine-Related Long Noncoding RNA Risk Model Via Comprehensive Prognostic and Immune...

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Pancreatic cancer (PC) has a poor prognosis and low 5-year survival rate.
• Chemokines and long non-coding RNAs (lncRNAs) are implicated in PC progression.
• The role of chemokine-related lncRNAs in PC requires further investigation.

Purpose of the Study:

• To explore the involvement of chemokine-related lncRNAs in pancreatic cancer.
• To establish a risk prediction model for PC prognosis based on these lncRNAs.
• To assess the relationship between risk groups and clinicopathological features, immune microenvironment, and drug sensitivity.

Main Methods:

• Utilized The Cancer Genome Atlas (TCGA) database to identify prognostic chemokine-related lncRNAs.
• Constructed a risk prediction model using six identified lncRNAs.
• Analyzed clinicopathological features, immune microenvironment, tumor mutation burden, and drug sensitivity.
• Performed in vitro experiments to validate the function of a selected lncRNA (SOCS2-AS1).

Main Results:

• A risk model comprising six chemokine-related lncRNAs (AC025162.2, SOCS2-AS1, AC025181.2, LINC00909, AC004825.2, AC068620.2) was established.
• High-risk patients exhibited significantly shorter overall survival (HR=3.08, P<0.001) compared to low-risk patients.
• Significant differences were observed in clinicopathological characteristics and immune treatment responses between risk groups.
• In vitro experiments confirmed SOCS2-AS1 inhibits PC cell proliferation and metastasis.

Conclusions:

• The developed chemokine-related lncRNAs risk model demonstrates significant prognostic value for pancreatic cancer.
• This model offers potential new insights for developing future therapeutic strategies in PC.
• Targeting specific lncRNAs like SOCS2-AS1 may represent a novel therapeutic approach.