Deregulation of microRNAs, as key elements in colorectal cancer (CRC) pathogenesis, is correlated with various stages of this cancer. miR-196 is involved in the initiation and progression of a verity of malignances, especially CRC. miR-196 in CRC cells could target different types of genes with oncogenic and/or tumor suppressor function such as HOX genes, GATA6, SOCS1, SOCS3, ANXA1, DFFA, PDCD4, ZG16 and ING5. Therefore, these genes could be up or down-regulated in cells and subsequently change the capacity of CRC cells in terms of tumor development, progression and, response to therapy. Comprehension of miR-196-associated aberrations underlying the CRC pathogenesis might introduce promising targets for therapy. Additionally, it seems that miR-196 expression profiling, especially circulatory exosomal miR-196, might be useful for diagnosis and prognosis determination of the CRC patients. In this review, at first, we summarize the roles of miR-196 in different types of cancers. After that, a detailed discussion about this miRNA and also their targets in CRC pathogenesis, progression, and response to treatment are represented. Moreover, we highlight the potential utilization of miR-196 and its targets as therapeutic targets and novel biomarkers in early detection and prediction of prognosis in CRC patients.

MiR-196: emerging of a new potential therapeutic target and biomarker in colorectal cancer.

Breast cancer (BC) is the second most common solid malignant tumor that metastasizes to the brain. Despite emerging therapies such as immunotherapy, whether the tumor microenvironment (TME) in breast cancer brain metastasis (BCBM) has potential as a target of new treatments is unclear. Expression profiling of 770 genes in 12 pairs of primary BC and matched brain metastasis (BM) samples was performed using the NanoString nCounter PanCancer IO360TM Panel. Immune cell profiles were validated by immunohistochemistry (IHC) in samples from 50 patients with BCBM. Pathway analysis revealed that immune-related pathways were downregulated. Immune cell profiling showed that CD8+ T cells and M1 macrophages were significantly decreased, and M2 macrophages were significantly increased, in BM compared to primary BC samples (p = 0.001, p = 0.021 and p = 0.007, respectively). CCL19 and CCL21, the top differentially expressed genes, were decreased significantly in BM compared to primary BC (p < 0.001, both). IHC showed that the CD8+ count was significantly lower (p = 0.027), and the CD163+ and CD206+ counts were higher, in BM than primary BC (p < 0.001, both). A low CD8+ T cell count, low CD86+ M1 macrophage count, and high M2/M1 macrophage ratio were related to unfavorable clinical outcomes. BC exhibits an immunosuppressive characteristic after metastasis to the brain. These findings will facilitate establishment of a treatment strategy for BCBM based on the TME of metastatic cancer.

Evolution of the Tumor Microenvironment toward Immune-Suppressive Seclusion during Brain Metastasis of Breast Cancer: Implications for Targeted Therapy.

Glioma is one of the most common neurological malignancies worldwide. Delta-like ligand 3 (DLL3), an inhibitory ligand-driven activation of the Notch pathway, has been shown to be significantly associated with overall survival in patients with glioma. Therefore, the purpose of this study was to determine whether DLL3 as a biomarker in glioma is associated with patients' clinicopathological features and prognosis. We identified differences in transcriptome and promoter methylation in the Chinese Glioma Genome Atlas (CGGA) in patients with malignant glioma with shorter (less than 1 year) and longer (greater than 3 years) survival time. Further analysis of The Cancer Genome Atlas (TCGA) revealed that four genes (DLL3, TSPAN15, RTN1, PAK7) are highly associated with patient prognosis and play an indispensable role in evolution. We chose the expression level of DLL3 in glioma patients for our study. Patients were divided into groups with low and high expression of DLL3 according to the cutoff values obtained, and Kaplan–Meier and Cox analysis were used to examine the correlation between DLL3 gene expression and patient survival. We then performed a gene set enrichment analysis (GSEA) to identify significantly enriched signaling pathways. Our results confirmed that the overall survival of patients with low DLL3 expression was significantly shorter than that of patients with high DLL3 expression. GSEA showed that the signaling pathways of the immune process and immune response, among others, were enhanced with the DLL3 low-expression phenotype. Collectively, our findings signify that DLL3 is a potent prognostic factor for glioma, which can provide a viable approach for glioma prognostic assessment and valuable insights for anti-tumor immune-targeted therapies.

Integrated Gene Expression and Methylation Analyses Identify DLL3 as a Biomarker for Prognosis of Malignant Glioma

Aims: This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Methods: Based on the survival-related representation features yielded by BiDNNs through integrating transcriptomics and epigenomics data, K-means clustering analysis was performed to cluster tumor samples into different survival subgroups. The BiDNNs-based model was validated using tenfold cross-validation and in two independent confirmation cohorts. Results: Using the BiDNNs-based survival stratification model, patients were grouped into two survival subgroups with log-rank p-value = 9.05E-05. The subgroups classification was robustly validated in tenfold cross-validation (C-index = 0.65 ± 0.02) and in two confirmation cohorts (E-GEOD-26253, C-index = 0.609; E-GEOD-62254, C-index = 0.706). Conclusion: We propose and validate a robust and stable BiDNN-based survival stratification model in gastric cancer. 

Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer

Background: The mechanism of DNA damage repair plays an important role in many solid tumors represented by cervical cancer. Purpose: The purpose of this study was to explore the effect of DNA damage repair-related genes on immune function of patients with cervical cancer, and to establish and evaluate a prognosis model based on DNA damage repair-related genes. Methods: In the study, we analyzed the genes related to DNA damage and repair, and obtained two subtypes (F1 and F2). We selected two groups of samples for different selection, and studied which pathways were enriched expression. For different subtypes, the immune score was explored to explain immune infiltration. We got the key genes through screening, and established the prognosis model through the key genes. These 11 key genes were correlated with the expression of common Clusters of Differentiation (CD) genes in order to explore the effects of these genes on immunity. Results: Through the Least absolute shrinkage and selection operator (LASSO) method, we screened 11 genes from 232 candidate genes as the key genes for the prognosis score. Through the Kaplan-Meier method, four genes (HAP1, MCM5, RNASEH2A, CETN2) with significant prognostic significance were screened into the final model, forming a Nomogram with C-index of 0.716 (0.649–1.0). Conclusion: In cervical cancer, DNA damage repair related genes and immune cell infection characteristics have certain association, and DNA damage repair related genes and immune cell infection characteristics can effectively predict the prognosis.

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DNA Damage Repair-Related Genes Signature for Immune Infiltration and Outcome in Cervical Cancer

This study was intended to investigate the genomic landscape of the immune microenvironments of brain metastases in breast cancer. Three gene expression profile datasets (GSE76714, GSE125989 and GSE43837) of breast cancer with brain metastases were downloaded from Gene Expression Omnibus (GEO) database. After differential expression analysis, the tumor immune microenvironment and immune cell infiltration were analyzed. Then immune-related genes were identified, followed by function analysis, transcription factor (TF)-miRNA–mRNA co-regulatory network analysis, and survival analysis of metastatic recurrence. The present results showed that the tumor immune microenvironment in brain metastases was immunosuppressed compared with primary caner. Compared with primary cancer samples, the infiltration ratio of plasma cells in brain metastases samples was significantly higher, while the infiltration ratio of macrophages M2 cells in brain metastases samples was significantly lower. Total 42 immune-related genes were identified, such as THY1 and NEU2. CD1B, THY1 and DOCK2 were found to be implicated in the metastatic recurrence of breast cancer. Targeting macrophages or plasma cells may be new strategies for immunotherapy of breast cancer with brain metastases. THY1 and NEU2 may be potential therapeutic targets for breast cancer with brain metastases, and THY1, CD1B and DOCK2 may serve as potential prognostic markers for improvement of brain metastases survival.

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Genomic landscape of the immune microenvironments of brain metastases in breast cancer.

Glioblastoma (GBM) is a common and aggressive primary brain tumor, and the prognosis for GBM patients remains poor. This study aimed to identify the key genes associated with the development of GBM and provide new diagnostic and therapies for GBM. Three microarray datasets (GSE111260, GSE103227, and GSE104267) were selected from Gene Expression Omnibus (GEO) database for integrated analysis. The differential expressed genes (DEGs) between GBM and normal tissues were identified. Then, prognosis-related DEGs were screened by survival analysis, followed by functional enrichment analysis. The protein–protein interaction (PPI) network was constructed to explore the hub genes associated with GBM. The mRNA and protein expression levels of hub genes were respectively validated in silico using The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases. Subsequently, the small molecule drugs of GBM were predicted by using Connectivity Map (CMAP) database. A total of 78 prognosis-related DEGs were identified, of which10 hub genes with higher degree were obtained by PPI analysis. The mRNA expression and protein expression levels of CETN2, MKI67, ARL13B, and SETDB1 were overexpressed in GBM tissues, while the expression levels of CALN1, ELAVL3, ADCY3, SYN2, SLC12A5, and SOD1 were down-regulated in GBM tissues. Additionally, these genes were significantly associated with the prognosis of GBM. We eventually predicted the 10 most vital small molecule drugs, which potentially imitate or reverse GBM carcinogenic status. Cycloserine and 11-deoxy-16,16-dimethylprostaglandin E2 might be considered as potential therapeutic drugs of GBM. Our study provided 10 key genes for diagnosis, prognosis, and therapy for GBM. These findings might contribute to a better comprehension of molecular mechanisms of GBM development, and provide new perspective for further GBM research. However, specific regulatory mechanism of these genes needed further elaboration.

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Ce Yuan

Papers

Genomic landscape of the immune microenvironments of brain metastases in breast cancer.

Identification of potential biomarkers and candidate small molecule drugs in glioblastoma