Ovarian cancer has the highest mortality rate of gynecological cancer, surpassing cervical cancer [28]. Heterogeneity and difficulty in early diagnosis of ovarian cancer also lead to the uncertainty of prognosis for OC patients, which brings significant challenges to the accurate treatment of OC [2]. At present, the internationally commonly used ovarian cancer malignancy scoring systems for the diagnosis of OC include the Malignancy Risk Index (RMI) [29] and the Ovarian Cancer Risk Algorithm (ROCA) [30]. Still, these evaluation systems are suitable for a disease with many subtypes such as OC. In addition, these algorithms are mainly based on the clinical manifestations of OC and cannot accurately identify the molecular mechanism of the disease. Therefore, a newer, more applicable, and accurate OC risk scoring system is needed.
Nowadays, with the deepening of the research on the tumor process, tumor cell metabolic reprogramming was considered a crucial part of tumor process regulation [31, 32]. Interestingly, recent extensive anthropological studies have shown that high absorbance of lipids is related to an increasing incidence in OC [33, 34]; this also reflects from the side that lipid metabolism may be closely related to the progression of OC. The overall lipid metabolism process includes fatty acid oxidation and synthesis. Previous studies have demonstrated that fatty acid synthase (FASN or FAS) and the de novo synthesis of fatty acids are hyperactivated in OC [35]. The up-regulated levels of FASN or FAS are thought to be closely associated with poor prognosis and clinical grading of OC patients [35, 36], and also mediates the resistance of OC cells to the first-line therapy cisplatin [37]. In addition to the changes to the tumor cells themselves, changes in the lipid metabolism level of adipocytes in the tumor microenvironment can also cause dramatic changes in the activity of immune infiltrating cells in the TME and tumor cells themselves, ultimately leading to changes in tumor progression [38–40]. In addition, many recent studies have confirmed that lncRNA, a post-transcriptional modifier, can be cross-linked with the reprogramming of fatty acid metabolism in tumor cells [41–43]. Therefore, based on the above evidence, we established a novel OC predictive risk model from fatty acid metabolism-related lncRNAs and explored how these lncRNAs affect OC progression.
In our study, eight key fatty acid metabolism-related lncRNAs were screened. Except for AL021707.1, AC145343.1, and LINC00861, other lncRNAs are rarely studied. In the study by Miaolong Lu et al., AL021707.1 was considered involved in the N6-methyladenosin process and a potential therapeutic target for bladder cancer[44].AC145343.1 was deemed associated with genomic instability mutations in liver cancer in the studies of Jianhua Wu and Dan-Ping Huang, and both studies considered AC145343.1 a risk factor for liver cancer progression[45, 46]. Paradoxically, combined with the poor prognosis of the high-risk group, we also believe this lncRNA as a risk factor for OC. It is worth noting that the above two lncRNAs have not been studied in OC. For LINC00861, there are more related studies. The study by Hui Liu et al. suggested that LINC00861 is down-regulated in OC tissues, resulting in decreased activity of the PTEN/AKT/mTOR pathway, which leads to the progression of OC and the poor prognosis of patients with advanced OC[47]. In addition, a recent blockbuster study on eczema identified TRIB1/LINC00861 as one of the crucial variants, and this change is closely related to immune cell function [48].
Looking back on our analysis of the immune characteristics of OC, it is not difficult to find that the infiltration degree of various tumor- permeating immune cells as well as activity of different immune responses have changed, and there are significant differences between high and low-risk groups. For example, compared with the low-risk group, the infiltration of Tfh (Follicular B helper T cells) in the samples of the high-risk group was significantly decreased. The cells can be generated during the differentiation of Th cells to Th1 or Th2 cells [49] and participate in the production and maintenance of B cell germinal centers by secreting cytokines, which play an essential role in the humoral immune process of organisms [50] [51]. This is consistent with our results in the GO enrichment analysis that humoral immunity is enriched at the very top. This has been shown to be a key regulator of tumor immune responses in various tumors [52] [53]. The latest findings point out that the transfer of Tfh cells can inhibit the growth of OC cells [54], while previous studies by Li Li et al. observed that Tfh can reduce the activation of co-cultured CD8 + T cells by affecting IL-10, thereby making the body decreased tumor clearance [55]. From this point of view, The may be a potential OC immunotherapy target.
Admittedly, this study still has the following shortcomings. First of all, this research is according to analysis in bioinformatics technology, and results obtained need to be supplemented with corresponding animal or cell experiments to verify. In addition, the data in this study came from sample information in public databases, which may lead to bias in the analysis results.
This is the first comprehensive study of fatty acid metabolism-related lncrnas in OC patients. The expression profiles of lncRNAs and heavy acid metabolism genes were programmed, and a risk score model and a nomogram were built based on eight fatty acid metabolism-related lncRNAs. This risk model has been proved to have good reliability and validity of OC prognosis prediction and can be used as a signature to describe the immune characteristics and chemotherapeutic drug resistance of OC. The above research aims to offer novel ideas and viewpoints of precise therapy of OC.