Identification of Prognostic Genes in Lung Adenocarcinoma Immune Microenvironment

0
0
0

Identification of Prognostic Genes in Lung Adenocarcinoma Immune Microenvironment

Lung adenocarcinoma (LUAD) is the most common type of lung cancer—and the leading cause of cancer-related death worldwide. While treatments like surgery, chemotherapy, and immunotherapy have advanced, predicting how individual patients will fare remains a major challenge. Increasingly, researchers are turning to the tumor immune microenvironment—the complex mix of immune cells, stromal (support) cells, and molecular signals surrounding cancer cells—to find clues about prognosis. A 2021 study published in the Chinese Medical Journal aimed to uncover genes in this microenvironment that could help predict LUAD survival.

The Study: Using Data to Unlock Prognostic Clues

Led by researchers from the National Cancer Center/National Clinical Research Center for Cancer (Beijing), Guizhou Provincial People’s Hospital (Guiyang), and Zunyi Medical University (Zunyi), the study focused on two goals:

  1. Use the ESTIMATE algorithm—a tool that calculates immune and stromal cell levels in tumors using gene expression data—to score LUAD patients from The Cancer Genome Atlas (TCGA), a leading public cancer genomics repository.
  2. Identify differentially expressed genes (DEGs)—genes more or less active in patients with high vs. low immune/stromal scores—and test if these genes predict survival.

The team analyzed data from 522 LUAD patients (after excluding those with missing clinical information). The group included 280 women (53.6%) and 242 men (46.4), with an average age of 66. Most were in early stages (I or II) with no metastasis (M0).

Key Findings: Immune Scores and Survival

First, the researchers linked immune scores to survival:

  • Patients with low immune scores (fewer immune cells in their tumors) had significantly worse overall survival (P = 0.013).
  • Stromal scores (stromal cell levels) showed a weaker link to survival (P = 0.038).

Next, they compared gene expression in high vs. low immune/stromal score groups. They found 72 common DEGs: 64 genes that were more active and 8 that were less active. Using tools like the STRING database (to map protein interactions) and Cytoscape (to cluster genes), they narrowed these to 22 genes tied to LUAD prognosis (via log-rank test, P < 0.05).

To confirm their results, the team used two other resources:

  • The Gene Expression Omnibus (GEO): A public database of gene expression data.
  • The Kaplan-Meier (K-M) plotter: A tool that analyzes gene expression and survival.

Six of the 22 genes had prognostic value in GEO. Five of those—ABI3BP, CSF2RB (IL5RB), KBTBD8, PKHD1L1, and SCML4—were also verified in the K-M plotter. These five became the study’s “key genes.”

What Do These Genes Do?

Each key gene has a potential role in LUAD or cancer biology:

  • ABI3BP: A known lung cancer biomarker, it’s often suppressed in lung cancer cell lines. In gallbladder cancer, higher ABI3BP levels slow tumor growth by blocking EZH2, a protein that drives cancer.
  • CSF2RB: Triggers apoptosis (programmed cell death) in cancer cells—critical for stopping tumor growth.
  • PKHD1L1: Acts as a tumor suppressor in thyroid cancer, slowing cell growth and invasion.
  • KBTBD8 and SCML4: Less studied in cancer, but their link to LUAD prognosis makes them promising targets for future research.

Pathways Linked to Key Genes

The team used gene set enrichment analysis (GSEA) to see which biological pathways the five genes affect. High expression of the genes was tied to pathways like:

  • T-cell receptor (TCR) signaling (critical for immune responses to cancer).
  • CTLA4 signaling (a checkpoint pathway targeted by immunotherapies like ipilimumab).
  • IL12 signaling (a cytokine that boosts anti-tumor immunity).

While these pathways are known to impact cancer, the exact way the five genes interact with them needs more research—especially in human LUAD samples.

Limitations and Future Work

The study’s main limitation is that it used genomic data but didn’t test the genes in human LUAD tissues. The researchers note they plan to address this in future experiments.

Why This Matters

For LUAD patients, predicting prognosis is key to choosing the right treatment. The five key genes identified here may help doctors:

  • Better estimate survival.
  • Tailor treatments (like immunotherapy) to patients with specific gene profiles.

While more research is needed, this work highlights the importance of the tumor immune microenvironment in lung cancer—and how data science can unlock life-saving clues.

Study Details

Authors: Lian-Kui Han (Guizhou Provincial People’s Hospital), Qi-Lin Huai (Zunyi Medical University), Wei Guo, Peng Song, De-Miao Kong (Guizhou Provincial People’s Hospital), Shu-Geng Gao (National Cancer Center).
Funding: Institutional Fundamental Research Funds (2018PT32033), Ministry of Education Innovation Team Development Project (IRT-17R10), Beijing Hope Run Special Fund of Cancer Foundation of China (LC2019B15).
Published In: Chinese Medical Journal (2021).
DOI: doi.org/10.1097/CM9.0000000000001367

Was this helpful?

0 / 0