Target Genetic Abnormalities for the Treatment of Colon Cancer and Its Progression to Metastasis

Cafestol inhibits colon cancer cell proliferation and tumor growth in xenograft mice by activating LKB1/AMPK/ULK1-dependent autophagy

Chemotherapy failure in colorectal cancer patients is the major cause of recurrence and poor prognosis. As a result, there is an urgent need to develop drugs that have a good chemotherapy effect while also being extremely safe. In this study, we found cafestol inhibited colon cancer growth and HCT116 proliferation in vivo and in vitro, and improved the composition of intestinal flora. Further metabolomic data showed that autophagy and AMPK pathways were involved in the process of cafestol's anti-colon cancer effects. The functional validation studies revealed that cafestol increased autophagy vesicles and LC3B-II levels. The autophagic flux induced by cafestol was prevented by using BafA1. The autophagy inhibitor 3-MA blocked the cafestol-induced increase in LC3B-II and cell proliferation inhibition. Then we found that cafestol induced the increased expressions of LKB1, AMPK, ULK1, p-LKB1, p-AMPK, and p-ULK1 proteins in vivo and in vitro. Using the siRNA targeted to the Lkb1 gene, the levels of AMPK, ULK1, and LC3B-II were suppressed under cafestol treatment. These results indicated that the effect of cafestol is through regulating LKB1/AMPK/ULK1 pathway-mediated autophagic death. Finally, a correlation matrix of the microbiome and autophagy-related proteins was conducted. We found that cafestol-induced autophagic protein expression was positively correlated with the beneficial intestinal bacteria (Muribaculaceae, Bacteroides, Prevotellacece, and Alloprevotella) and negatively correlated with the hazardous bacteria. Conclusions: This study found that cafestol inhibited colon cancer in vitro and in vivo by the mechanism that may be related to LKB1/AMPK/ULK1 pathway-mediated autophagic cell death and improved intestinal microenvironment.

ATF4 inhibits tumor development and mediates p-GCN2/ASNS upregulation in colon cancer

Colon cancer (CC) is a highly malignant tumor with a high incidence and poor prognosis. This study aimed to explore the function and molecular mechanisms of activating transcription factor 4 (ATF4) in CC. The expression levels of ATF4, GCN2, and ASNS in CC tissues were measured using immunohistochemistry (IHC) and reverse transcription quantitative PCR (RT-qPCR). Cell counting kit-8 (CCK-8), clone formation, transwell, and flow cytometry assays were conducted to assess cell viability, clonogenicity, migration, invasion, cell cycle, and apoptosis, respectively, in the ATF4 knockdown and overexpression SW480 cell lines. The effect of ATF4 on the expression of GCN2 and ASNS was detected using RT-qPCR, Chip-qPCR, and western blotting. ATF4, GCN2, and ASNS were expressed at low levels in CC tissues, and all had a significant negative correlation with tumor diameter. ATF4 knockdown promoted cell proliferation, invasion, and S-phase cell cycle and inhibited apoptosis in SW480 cells. In contrast, ATF4 overexpression had the opposite effect. Furthermore, ATF4 overexpression enhanced ATF4 binding to the ASNS promoter region. ATF4 knockdown significantly inhibited the expression of p-GCN2 and ASNS, whereas ATF4 overexpression significantly upregulated their expression. ATF4 inhibited CC cell viability, clone formation ability, migration, and invasion and promoted apoptosis, possibly by regulating the expression of p-GCN2 and ASNS. Our study provides a novel potential therapeutic target for the treatment of CC.

Construction of a Novel Immune-Related mRNA Signature to Predict the Prognosis and Immune Characteristics of Human Colorectal Cancer

Background: Anti-cancer immunotherapeutic approaches have gained significant efficacy in multiple cancer types. However, not all patients with colorectal cancer (CRC) could benefit from immunotherapy due to tumor heterogeneity. The purpose of this study was to construct an immune-related signature for predicting the immune characteristics and prognosis of CRC.

Methods: RNA-sequencing data and corresponding clinical information of patients with CRC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and immune-related genes (IRGs) were downloaded from the Immunology Database and Analysis Portal (ImmPort). Then, we utilized univariate, lasso regression, and multivariate cox regression to identify prognostic IRGs and develop the immune-related signature. Subsequently, a nomogram was established based on the signature and other prognostic factors, and its predictive capacity was assessed by receiver operating characteristic (ROC) and decision curve analysis (DCA). Finally, associations between the signature and the immune characteristics of CRC were assessed.

Results: In total, 472 samples downloaded from TCGA were divided into the training cohort (236 samples) and internal validation cohort (236 samples), and the GEO cohort was downloaded as an external validation cohort (122 samples). A total of 476 differently expressed IRGs were identified, 17 of which were significantly correlated to the prognosis of CRC patients. Finally, 10 IRGs were filtered out to construct the risk score signature, and patients were divided into low- and high-risk groups according to the median of risk scores in the training cohort. The high-risk score was significantly correlated with unfavorable survival outcomes and aggressive clinicopathological characteristics in CRC patients, and the results were further confirmed in the internal validation cohort, entire TCGA cohort, and external validation cohort. Immune infiltration analysis revealed that patients in the low-risk group infiltrated with high tumor-infiltrating immune cell (TIIC) abundances compared to the high-risk group. Moreover, we also found that the immune checkpoint biomarkers were significantly overexpressed in the low-risk group.

Conclusion: The prognostic signature established by IRGs showed a promising clinical value for predicting the prognosis and immune characteristics of human CRC, which contribute to individualized treatment decisions.