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Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts
Published on: April 29, 2014
NK cell-associated long non-coding RNAs reveal heterogeneity of colorectal cancer immune microenvironment
Yuxuan Li1, Chuqi Xia1, Jinze Li1
1Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Introduction:
Individuals diagnosed with colorectal cancer (CRC) frequently confront a grave prognosis and exhibit poor responses to conventional treatment regimens. Immunotherapy, notably modalities centered on natural killer (NK) cells, represents a burgeoning frontier in the management of CRC. This study developed a validated prognostic model using NK-associated long non-coding RNAs (lncRNAs) to predict CRC outcomes.
Methods:
Integrating single-cell RNA-seq (GSE146771_Smartseq2) and TCGA-COAD/READ bulk transcriptomic data, we identified NK-specific genes and correlated lncRNAs. A multi-step analytical approach-including univariate Cox regression for preliminary screening, LASSO regression to minimize overfitting, and multivariate Cox regression for final model optimization-yielded a robust 16-lncRNA prognostic signature with high predictive accuracy.
Results:
This model demonstrated robust predictive performance across the training set, validation set, and 76 independent clinical samples. Mechanistic investigations revealed that AC010319.3 is highly expressed in NK cells, where it attenuates NK cell cytotoxicity by suppressing the expression of IFN-γ and granzyme B, thereby promoting the proliferation and invasion of CRC cells.
Discussion:
This study systematically delineates the regulatory role of NK-associated lncRNAs within the CRC immune microenvironment, offering novel molecular targets and stratification strategies for CRC immunotherapy.
Insights
This study developed a 16-long non-coding RNA (lncRNA) signature to predict colorectal cancer (CRC) outcomes. This prognostic model enhances NK cell-based immunotherapy strategies for CRC patients.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Colorectal cancer (CRC) poses significant challenges due to poor prognosis and limited response to conventional treatments.
- Natural killer (NK) cell-based immunotherapy is a promising avenue for CRC management.
- Identifying predictive biomarkers is crucial for optimizing CRC treatment strategies.
Purpose of the Study:
- To develop and validate a prognostic model for colorectal cancer (CRC) using NK-associated long non-coding RNAs (lncRNAs).
- To identify novel molecular targets for enhancing NK cell-based immunotherapy in CRC.
Main Methods:
- Integrated single-cell RNA sequencing and TCGA transcriptomic data to identify NK-specific lncRNAs.
- Employed univariate Cox, LASSO, and multivariate Cox regression analyses to build a 16-lncRNA prognostic signature.
- Validated the model's predictive accuracy using training, validation sets, and independent clinical samples.
Main Results:
- A robust 16-lncRNA prognostic signature demonstrated high predictive accuracy in CRC.
- The lncRNA AC010319.3 was identified to suppress NK cell cytotoxicity by downregulating IFN-γ and granzyme B.
- This suppression promotes CRC cell proliferation and invasion, highlighting a key mechanism in the tumor microenvironment.
Conclusions:
- NK-associated lncRNAs play a significant regulatory role in the CRC immune microenvironment.
- The developed prognostic signature offers a valuable tool for stratifying CRC patients for immunotherapy.
- These findings provide novel molecular targets for advancing CRC immunotherapy.
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