RESUMO
Copper, an indispensable trace element for the human body, serves not only as a crucial auxiliary factor in redox reactions within the organism but also as a significant constituent of numerous key metabolic enzymes. The COMMD family plays a vital role in regulating copper at both the cellular and systemic levels, particularly in the realm of tumor research, an area notably deficient in gastric cancer investigations. With the advancement of precision medical techniques, individualized and precise screening and treatment have become paramount considerations in the contemporary medical landscape for gastric cancer therapy. In light of this, we meticulously scrutinized existing transcriptomic datasets for gastric cancer, validating the expression levels and prognostic value of COMMD family genes. Simultaneously, employing the ssGSEA algorithm, we devised the COMMDs score. Enrichment analysis, gene mutations, and clinical features were incorporated into the assessment of this score. Furthermore, we contextualized the COMMDs score within the framework of the immune microenvironment, evaluating the relationship between the COMMDs family and immune factors as well as immune cells. The results suggest a correlation between the COMMDs score and various immune-related features. Based on this foundation, multiple machine learning approaches indicated Logistic Regression, with a remarkable ROC of 0.972, as the optimal diagnostic model. To accentuate the translational medical value of the COMMDs family, we selected COMMD10 as a differential gene in gastric cancer for further validation. Functional experiments revealed a decline in the proliferative and migratory capabilities of gastric cancer cells upon silencing COMMD10. Additionally, through pathway intervention, we unveiled the PI3K-AKT pathway as a potential mechanism through which COMMD10 influences gastric cancer activity. In summary, our study affirms the prospective role of the COMMDs family as potential markers for the diagnosis and treatment of gastric cancer in the future.
RESUMO
Several studies have shown significant involvement of tumor-associated macrophages (TAMs) in the tumor microenvironment and cancer progression. However, no data on reliable TAM-related biomarkers are available for predicting the prognosis of patients with colorectal cancer (CRC). We analyzed the clinical data and gene expression profiles of patients with CRC from databases. The single-cell transcriptomic data was applied to identify M2-like TAM-related differentially expressed genes. Univariate Cox and least absolute shrinkage and selection operator regression analyses were used to determine the prognostic signature genes. Then, seven key genes were screened to develop the prognostic signature. In the training and external validation cohorts, the overall survival (OS) of patients in the high-risk group was significantly shorter compared to the low-risk group. Consequently, we created a nomogram that could accurately and reliably predict the prognosis of patient with CRC. A significant correlation was observed between the patient's prognosis, clinical features, sensitivity to anticancer drugs, TME, and risk scores. Moreover, risk score was strongly related to the response to immunotherapy in patients from GSE91061, GSE78220, and GSE60331 cohorts. Finally, high expression of HSPA1A, SERPINA1, CXCL1, and low expression of DNASE1L3 were found in human CRC tissue and normal tissue by using qRT-PCR. In conclusion, the M2-like TAM-related prognostic signature could predict the survival, prognosis, and response of patients with CRC to immunotherapy, which sheds light on the role of TAMs in CRCs and enhances our understanding of TAMs.
