In the contemporary era of the development of precision medicine, tailoring a treatment plan for the clinicopathological and molecular characteristics of each patient's tumor is extremely important for the treatment of the patient. [6, 7].The doctor’s preoperative evaluation, postoperative prediction, and follow-up have a profound impact on the quality of life of cancer patients.[8, 9].
Doctors are exploring targeted precision therapies for specific histological subtypes and genetic mutations of each STS patient. There is an urgent need to link the patient's transcriptome information with the best treatment strategy.[10].Some recent studies have made the genomic characterization of subtypes of soft tissue sarcoma more precise and discovered some prognostic-related molecular markers.[11].
Long non-coding RNA (lncRNA) has multiple functions in regulating gene expression at both transcription and translation levels, and more and more studies have found that lncRNA is closely related to tumor immunity.[12]. With the development of bioinformatics, more and more immune-related lncRNAs have been mined to construct tumor prognosis models.[13].[14],[15].In this study, we constructed for the first time a lncRNA model including 8 immune-related lncRNAs, and verified the accuracy of this model as a marker for the survival status of soft tissue sarcoma. First, we analyzed the transcriptome data of TCGA SARC and obtained the lncRNA co-expressed with immune genes. After univariate and multivariate cox regression analysis, we finally determined 8 immune-related lncRNAs:C5orf56, LINC00294, LINC01023, PCOLCE-AS1, LINC00944, LINC01140, SERTAD4-AS1, THUMPD3-AS1.Next, by comparing with other clinical characteristics, the score determined by 8 DEIRLs has the largest ROC value, indicating that this model has an excellent prognostic predictive ability for STS patients. The risk score and clinical information are combined to construct a nomogram to predict the 1, 3, and 5-year survival rate of patients, and the corresponding calibration chart shows that this nomogram has relatively high accuracy. We used GSEA to explore the differences in gene function between high- and low-risk populations, and the results showed that high-risk patients had relatively low levels of immune gene enrichment .The ESTIMATE algorithm showed that there were significant differences in immuneScore, tumor purity, StromalScore, ESTIMATEScore, between high- and low-risk patients.And, this 8 DEIRLs model related to 3 immune cell subtypes: CD4 + cells, Macrophage cells, Neutrophil cells.
GSEA analysis showed that these lncRNAs were enriched in the pathways of " KEGG_SPLICEOSOME", " KEGG_RNA_POLYMERASE", "KEGG_PYRIMIDINE_METABOLISM", " KEGG_RNA_DEGRADATION" and " KEGG_CELL_CYCLE". Recent genome analysis has shown that many of the molecular changes observed in cancer result from mutations in the splicing process. Understanding the link between tumor cell biology and splicing regulation is essential for studying pathogenesis and treatment methods.[16].Mutations in RNA polymerase regulatory factors are one of the most important regulators of cell malignant differentiation.[17]. Xiuxing Wang er al have found that targeting pyrimidine synthesis pathway can improve the therapeutic effect of glioblastoma stem cells on molecular biology.[18]. RNA degradation plays an important role in tumor cells. For example, Jing-Ting Chiou et al found that degradation of HuR mRNA caused by autophagy induced down-regulation of survivin and MCL1 protein levels in leukemia cells that is treated with YM155.[19].The cell cycle of cancer cells is dysregulated, leading to uncontrolled growth of tumor cells.[20].ESTIMATE algorithm and TIMER database analysis show that this model is closely related to tumor immune infiltration and immune cell subtypes, which may provide potential targets for immunotherapy of soft tissue sarcoma.
There have been some studies on the role of these DEIRLs in tumor cells. Xiaokun Zhou et al. found that overexpression of LINC00294 inhibited the growth of glioma cells and induces apoptosis. [21].Linc01023 can inhibit the growth and metastasis of glioma cells by regulating the IGF1R/AKT pathway.[22]. Pamela R de Santiago et al. discovered that LINC00944 regulated the level of ADAR1 in breast cancer cells, and the expression of LINC00944 was positively correlated with T lymphocyte infiltration. [23].Knockdown of LINC01140 can inhibit the growth and metastasis of glioma cells through miR-199a-3p.[24].THUMPD3-AS1 affects the proliferation of NSCLC cells by regulating the level of ONECUT2, so it can be used as a prognostic-related marker and a potential therapeutic target.[25].
As we know, this is the first time that an immune-related lncRNA model has been constructed to predict the prognosis of patients with soft tissue sarcoma, and the immune infiltration related to the model has been explored. The GTEx database makes up for the shortcomings of the lack of normal samples in the TCGA database. However, this work has some limitations: First of all, some important clinical features of patients in the TCGA database are not sufficiently detailed, such as tumor stage information, which may affect the treatment and prognosis of STS patients. Second,it is necessary to further determine the functional correlation between the expression levels of these 8 DEIRLs and the immunophenotype in soft tissue sarcoma at the cellular level. Finally, in order to ensure the predictive performance of the nomogram, more independent external queues should be analyzed on the basis of our model construction method.