When to consider logistic LASSO regression in multivariate analysis?

Machine learning identifies characteristics molecules of cancer associated fibroblasts significantly correlated with the prognosis, immunotherapy response and immune microenvironment in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly lethal disease with a dramatic pro-fibrocytic response. Cancer-associated fibroblasts (CAFs) have been reported to play a key role in lung adenocarcinoma.

METHODS

Marker genes of CAFs were obtained from the Cell Marker website. Single sample gene set enrichment analysis (ssGSEA) was used for CAFs quantification. R and GraphPad Prism software were utilized for all analysis. Quantitative real-time PCR (qRT-PCR) was utilized to detect the RNA level of specific molecules.

RESULTS

Based on the ssGSEA algorithm and obtained CAFs markers, the LUAD patients with low- and high-CAFs infiltration were successfully identified, which had different response patterns to immunotherapy. Through the machine learning algorithm - LASSO logistic regression, we identified 44 characteristic molecules of CAFs. Furthermore, a prognosis signature consisting of seven characteristic genes was established, which showed great prognosis prediction ability. Additionally, we found that patients in the low-risk group might have better outcomes when receiving immunotherapy of PD-1, but not CTLA4. Also, the biological enrichment analysis revealed that immune response-related pathways were significantly associated with CAFs infiltration. Meanwhile, we investigated the underlying biological and microenvironment difference in patients with high- and low-risk groups. Finally, we identified that AMPD1 might be a novel target for LUAD immunotherapy. Patients with a high level of AMPD1 were correlated with worse responses to immunotherapy. Moreover, immunohistochemistry showed that the protein level of AMPD1 was higher in lung cancer. Results of qRT-PCR demonstrated that AMPD1 was upregulated in A549 cells compared with BEAS-2B. Meanwhile, we found that the knockdown of AMPD4 can significantly reduce the expression of CTLA4 and PDCD1, but not CD274 and PDCD1LG2.

CONCLUSION

We comprehensively explored the role of CAFs and its characteristics molecules in LUAD immunotherapy and developed an effective signature to indicate patients prognosis and immunotherapy response. Moreover, AMPD1 was identified as a novel target for lung cancer immunotherapy.

An Analysis Regarding the Association Between Connexins and Colorectal Cancer (CRC) Tumor Microenvironment

Background

Gap junctions, as one of the major ways to maintain social connections between cells, are now considered as one of the potential regulators of tumor metastasis. However, to date, studies on the relationship between gap junctions and colorectal cancer (CRC) are limited.

Methods

We synthesized connexins-coding gene expression data from public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatics analysis was performed using R software and several database resources such as MEXPRESS database, Gene Set Cancer Analysis (GSCA) database, Human Protein Atlas (HPA) database, Tumor Immune Single Cell Hub (TISCH) database, Search Tool for Retrieval of Gene Interaction Relationships (STRING), and Cytoscape software, etc., to investigate the biological mechanisms that may be involved in connexins. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of GJA4.

Results

We found that CRC patients can be divided into two connexin clusters and that patients in cluster C1 had shorter survival than in cluster C2. The infiltration of M1 macrophages and NK cells was lower in cluster C1, while the levels of M2 macrophages and immune checkpoints were higher, indicating an immunosuppressed state in cluster C1. In addition, the epithelial–mesenchymal transition (EMT) phenotype was significantly activated in cluster C1. We observed that GJA4 was up-regulated in colorectal cancer tissues, which was related to poor prognosis. It was mainly expressed in fibroblasts, but the expression levels in normal intestinal epithelial cells were low. Finally, we found that GJA4 was associated with M2 macrophages and may be a potential immunosuppressive factor.

Conclusion

We found that there is a significant correlation between abnormal connexins expression and patients’ prognosis, and connexins play an important role in stromal-tumor interactions. Connexins, especially GJA4, can help enhance our understanding of tumor microenvironment (TME) and may guide more effective immunotherapeutic strategies.