In this study, we analyzed the DEFAMGs between HCC patients and controls in the TCGA database. Then, the prognosis-related genes were screened and a novel prognostic signature for HCC patients was built. Next, we validated the model as an effective biomarker in the GEO database. Furthermore, we demonstrated that the risk score model could predict the OS, identify the response to immunotherapy, select the suited chemotherapy drugs, and provide the guideline for the clinical work.
In this study, a total of 12 genes (PON1, CYP2C9, ACACA, ACADS, ME1, ACAT1, ELOVL1, SMS, UGDH, ADSL, HSP90AA1, S100A10) were used to construct the prognostic signature. PON1 involved in maintaining the function of endothelial cells, inhibiting the adhesion of leukocytes, reducing the chronic inflammation, and suppressing the tumor invasion or metastasis. ACADS was reported to participate in the proliferation and metastasis of HCC. SMS could influence the metabolism process and involved in oncogenesis and drug resistance. Overexpression of ACACA, ME1, ADSL or S100A10 promoted HCC growth, migration or invasion, and was associated with the poor prognosis[17–19]. As for the ACAT1 and CYP2C9, overexpression suppressed the proliferation and migration of tumor cells[20, 21]. As regards the ELOVL1, UGDH and HSP90AA1, studies only showed the correlation with cancer and needed further exploration to elucidate the underlying mechanisms[22–25]. As in our study, the level of PON1, CYP2C9 ACADS, ACAT1 decreased in the HCC and was positively associated with the OS of HCC patients. The expression of SMS, HSP90AA1, ADSL, UGDH, ACACA, ME1, ELOVL1, S100A10 was increased in the tumor tissues and was negatively associated with the OS.
In recent years, concerns have been raised in HCC because of the increasing incidence and mortality. However, the diagnosis and prognosis analysis of HCC patients are main on the basis of the conventional staging, which is not sensitive enough. Therefore, it is necessary to identify reliable prognostic markers to improve the clinical outcomes of HCC. Recently, abnormal metabolism was reported to be closely related to the course of tumorigenesis and metastasis, and the altered fatty acid metabolism in cancer drew the renewed interest in particular. Some studies have revealed that orchestrating fatty acid metabolism can regulate the occurrence and development of HCC[28–30]. Notably, many metabolism-related genes have been revealed to be valuable prognostic biomarkers and metabolism-related risk signatures was built to predict the OS of HCC[12, 31]. However, little study concerning fatty acid metabolism-related gene risk model has been done. Only one study selected 6 fatty acid metabolism-related genes to build a prognostic model of HCC without further drug exploration. Therefore, we screened the fatty acid metabolism-related genes again and finally identified 12 genes to construct the prognostic signature more accurately. We evaluated the predictive capacity of the model and revealed that it may be used as an independent prediction factor in HCC patients. In addition, the prognostic signature showed a higher AUC value and indicated a better predictive power than other clinical characteristics.
Immune system is considered to play an essential role in preventing people from cancer. In recent years, tumor immunotherapy is considered to be the promising adjuvant therapy for HCC. Tumor immunotherapy aimed at strengthening or weakening the abnormal immune state to control tumor growth or kill tumor cells. However, only part of HCC patients was reported to be sensitive to the tumor immunotherapy. Wu et al. found that fatty acid metabolism could regulate the phenotype and function of immune cells, and thus affect the effect of immunotherapy. In this study, according to the fatty acid metabolism-related genes model, high-risk patients responded better to immunotherapy than low-risk patients, which can guide the patient selection for immunotherapy. Besides, tumor mutational burden was regarded as a promising novel biomarker to select patients for the tumor immunotherapy in recent years. TP53 mutation is the most common mutation in HCC, and it influences the progression and prognosis of HCC. Long developed a TP53-associated immune prognostic model for HCC and found the model may have important implications for prediction of OS. In this study, TP53 mutation also showed higher risk scores in HCC patients. Collectively, the fatty acid metabolism-related genes model may provide the valuable information to select the HCC patients fit for immunotherapy.
It is reported that different patients respond inconsistently to chemotherapy drugs. Although sorafenib is the important first-line chemotherapeutic therapy, some HCC patients showed the sorafenib resistance and therapeutic efficacy was unsatisfying. Meanwhile, the same phenomenon has been seen in other chemotherapeutic drugs[39, 40], which really deteriorated the prognosis of patients. Therefore, the individualized treatment has received great interest and may be an important approach to improve the clinical effect. Ding et al. constructed the fatty acid metabolism-related risk signatures for predicting the effect of 5-Fluorouracil in colorectal cancer and revealed patients in low-risk score group were more sensitive to 5-FU. In our study, we demonstrated that HCC patients from the high-risk scores group were more suitable for sorafenib, gemcitabine, 5-Fluorouracil, and paclitaxel, while Lapatinib was more sensitive to the low-risk groups. Therefore, according to the risk score, appropriate chemotherapy drug can be chosen for the HCC patients in the future.
Study strengths and limitations
The main strength of this study is the construction and validation of a novel prognostic signature based on fatty acid metabolism-related genes, which has good performance in prognostic prediction and provides guidance for clinical medication. However, this study also has limitation without the experimental validation in vivo and vitro. Therefore, further exploration showed be carried out to evaluate the functions of fatty-acid metabolism-related genes in patients of HCC in the future.