Aims: Colorectal cancer (CRC) has high mortality and morbidity rates; however, the mechanism of CRC cells uncontrolled proliferation is unclarified, E3 ligases are widely reported to have crucial functions in cancers. HERC3 was once recognized as an important role in CRC, however its effects on CRC cell proliferation and cell cycle are blank.

The tumor microenvironment (TME) plays a crucial role in tumor progression and metastasis. However, the immune phenotypes of colorectal cancer (CRC) and the underlying immune escape mechanism have not been studied sufficiently. A total of 1802 and 619 CRC samples from the microarray and TCGA cohorts were enrolled, respectively. The ssGSEA algorithm and unsupervised clustering were used for TME cell infiltration speculation and immune phenotype recognition in the above cohorts. A total of 447 samples from Zhongshan Hospital were collected for validation. Immunohistochemistry was performed in this cohort to quantify TME cell infiltration. The single-cell RNA-seq (scRNA-seq) data of 252,940 cells from 60 CRC samples was analyzed for further mechanistic exploration. CRC samples can be classified into three distinct immune phenotypes. Subtype 1, the immune-active subtype, was characterized by high infiltration of activated adaptive immune cells. Subtype 2, the immune-desert subtype, featured high tumor purity and low infiltration of immune and stromal cells. Subtype 3, the stroma-rich subtype, had high infiltration of stromal cells. The stroma-rich subtype conferred a significantly worse prognosis. The three subtypes had different immune escape mechanisms. The immune-active subtype has the highest immune checkpoint expression level. In comparison, the immune-desert subtype had the lowest immunogenicity and defective antigen presentation. The stroma-rich subtype lacked activated immune cells. In conclusion, distinct immune phenotypes and immune escape mechanisms may provide inspiration and direction for further research on CRC immunotherapy.

Background: Tumor-associated macrophages (TAMs) are pivotal mediators of the immunosuppressive tumor immune microenvironment (TIME) in colorectal cancer (CRC). However, genes of TAMs that potentiate immunotherapy remain to be explored.

We explored the infiltration and prognostic value of CXCR6+TAMs in all stages of colon cancer (CC) patients and assessed predictive ability as a biomarker for different ACT regimens among high-risk stage II and stage III patients in both primary and validation cohorts. Two independent cohorts of 360 and 126 consecutive colon cancer patients were enrolled from two medical centers of Zhongshan Hospital. Immunofluorescence and immunohistochemistry were performed to detect the density of CXCR6+TAMs and activated CD8+ T cells. The infiltration of CXCR6+TAMs was higher in tumor tissues and increased with advanced tumor stage. A high density of CXCR6+TAMs predicted worse overall survival (OS) in all CC patients (HR = 2.49, 95% CI = (1.68, 3.70), p < 0.001), and was an independent risk factor verified by Cox regression analysis (HR = 1.68, 95% CI = (1.09, 2.59), p = 0.019). For high-risk stage II and stage III patients with a high density of CXCR6+TAMs, better disease-free survival (DFS) (HR = 0.32, 95% CI = (0.11, 0.89), p = 0.003), and OS (HR = 0.28, 95% CI = (0.07, 1.11), p = 0.014) were observed in the 6-month treatment group. There was a negative relationship between the density of CXCR6+TAMs and CD8+ T cells (R = −0.51, p < 0.001) as well as activated CD8+ T cells (R = −0.54, p < 0.001). Higher levels of IL-6 and lower levels of IL-2R and TNF-α were expressed in high-CXCR6+ TAM-density patients, which indicates that CXCR6+TAMs contribute to an immunosuppressive microenvironment. CXCR6+TAMs predicted prognosis and response to different durations of ACT in CC patients. CXCR6+TAMs were associated with an immunosuppressive microenvironment and suppressed the activation of CD8+ T cells.

The ubiquitin (Ub)–proteasome system (UPS) is an important regulatory component in colorectal cancer (CRC), and the cell cycle is also characterized to play a significant role in CRC. In this present study, we firstly identified UPS-associated differentially expressed genes and all the differentially expressed protein-coding genes in CRC through three differential analyses. UPS-associated genes were also further analyzed via survival analysis. A weighted gene co-expression network analysis (WGCNA) was used to identify the cell cycle-associated genes. We used protein–protein interaction (PPI) network to comprehensively mine the potential mechanism of the UPS–cell cycle regulatory axis. Moreover, we constructed a signature based on UPS-associated genes to predict the overall survival of CRC patients. Our research provides a novel insight view of the UPS and cell cycle system in CRC.