Research into the characteristic molecules significantly affecting liver cancer immunotherapy

Abstract

BackgroundThe past decade has witnessed unprecedented scientific breakthroughs, including immunotherapy, which has great potential in clinical applications for liver cancer.MethodsPublic data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases and analyzed with R software.ResultsThe LASSO and SVM-RFE machine learning algorithms identified 16 differentially expressed genes (DEGs) related to immunotherapy, namely, GNG8, MYH1, CHRNA3, DPEP1, PRSS35, CKMT1B, CNKSR1, C14orf180, POU3F1, SAG, POU2AF1, IGFBPL1, CDCA7, ZNF492, ZDHHC22, and SFRP2. Moreover, a logistic model (CombinedScore) was established based on these DEGs, showing an excellent prediction performance for liver cancer immunotherapy. Patients with a low CombinedScore might respond better to immunotherapy. Gene Set Enrichment Analysis showed that many metabolism pathways were activated in patients with a high CombinedScore, including butanoate metabolism, bile acid metabolism, fatty acid metabolism, glycine serine and threonine metabolism, and propanoate metabolism. Our comprehensive analysis showed that the CombinedScore was negatively correlated with the levels of most tumor-infiltrating immune cells and the activities of key steps of cancer immunity cycles. Continually, the CombinedScore was negatively associated with the expression of most immune checkpoints and immunotherapy response-related pathways. Moreover, patients with a high and a low CombinedScore exhibited diverse genomic features. Furthermore, we found that CDCA7 was significantly correlated with patient survival. Further analysis showed that CDCA7 was positively associated with M0 macrophages and negatively associated with M2 macrophages, suggesting that CDCA7 could influence the progression of liver cancer cells by affecting macrophage polarization. Next, single-cell analysis showed that CDCA7 was mainly expressed in prolif T cells. Immunohistochemical results confirmed that the staining intensity of CDCA7 was prominently increased in the nucleus in primary liver cancer tissues compared to adjacent non-tumor tissues.ConclusionsOur results provide novel insights into the DEGs and factors affecting liver cancer immunotherapy. Meanwhile, CDCA7 was identified as a potential therapeutic target in this patient population.

Identification of CNKSR1 as a biomarker for “cold” tumor microenvironment in lung adenocarcinoma: An integrative analysis based on a novel workflow

“…Additionally, CNKSR1 mediates the initiation of the c-Jun N-terminal kinase (JNK) pathway by binding to Rho guanine nucleotide exchange factors, the GTPase Rho, and downstream molecules of Rho [ 26 , 42 ]. CNKSR1 has been implicated as an oncogene in various cancers [ 41 , 43 , 44 ], and its potential role in immunotherapy for bladder and liver cancers has also been suggested [ 45 , 46 ]. However, there has been a lack of in-depth investigation into the role of CNKSR1 in tumor immunity.…”

Analysis and experimental validation of fatty acid metabolism-related genes prostacyclin synthase (PTGIS) in endometrial cancer

“…These results suggest that abnormal fatty acid metabolism in EC may further enhance tumor progression by inhibiting immune function and immune response. Previous studies have indicated that abnormal fatty acid metabolism may be associated with resistance to immunotherapy in liver cancer [ 30 ]. Additionally, FDX1, a gene related to fatty acid metabolism, has been shown to regulate the progression of clear-cell renal carcinoma by influencing the immune microenvironment of tumor cells [ 31 ].…”

A Novel Prognostic Model for Gastric Cancer with EP_Dis-Based Co-Expression Network Analysis

“…Studies have shown that PDK4 (Pyruvate Dehydrogenase Kinase 4) has been identified as a potential candidate diagnostic biomarker and therapeutic target for GC patients [41], TF (Transferrin) has been shown to be highly expressed in GC and associated with poor prognosis of GC patients [42], and TSC22D3 (TSC22 Domain Family Member 3) is considered to be involved in the GC iron death-related key competitive endogenous RNA network [43]. DPEP1 (Dipeptidase 1) has been shown to be an important regulator of single-pathway iron death and to cause kidney disease development by altering cellular iron transport [44], and it is also related to leukemia [45], hepatoblastoma [46], osteoarthritis [47] and colon cancer resistance [48]; however, DPEP1's relationship with GC patient prognosis is less studied. Based on this chapter's research, DPEP1 may be a new research direction for GC.…”