A novel signature incorporating lipid metabolism- and immune-related genes to predict the prognosis and immune landscape in hepatocellular carcinoma

Background

Liver hepatocellular carcinoma (LIHC) is a highly malignant tumor with high metastasis and recurrence rates. Due to the relation between lipid metabolism and the tumor immune microenvironment is constantly being elucidated, this work is carried out to produce a new prognostic gene signature that incorporates immune profiles and lipid metabolism of LIHC patients.

Methods

We used the "DEseq2" R package and the "Venn" R package to identify differentially expressed genes related to lipid metabolism (LRDGs) in LIHC. Additionally, we performed unsupervised clustering of LIHC patients based on LRDGs to identify their subgroups and immuno-infiltration and Gene Ontology (GO) enrichment analysis on the subgroups. Next, we employed multivariate, LASSO and univariate Cox regression analyses to determine variables and to create a prognostic profile on the basis of immune- and lipid metabolism-related differential genes (IRDGs and LRDGs). We separated patients into low- and high-risk groups in accordance with the best cut-off value of risk score. We conducted Decision Curve Analysis (DCA), Receiver Operating Characteristic curve analysis as a function of time as well as Survival Analysis to evaluate this signature's prognostic value. We incorporated the clinical characteristics of patients into the risk model to obtain a nomogram prognostic model. GEO14520 and ICGC-LIRI JP datasets were employed to externally confirm the accuracy and robustness of signature. The gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were applied for investigating the underlying mechanisms. Immune infiltration analysis was implemented to examine the differences in immune between both risk groups. Single-cell RNA sequencing (scRNA-SEQ) was utilized to characterize the genes that were involved in the distribution of signature and expression characteristics of different LIHC cell types. The patients' sensitivity in both risk groups to commonly used chemotherapeutic agents and semi-inhibitory concentrations (IC50) of the drugs was assessed using the GDSC database. On the basis of the differentially expressed genes (DEGs) in the two groups, the CMAP database was adopted for the prediction of potential small-molecule compounds. Small-molecule compounds were molecularly docked with prognostic markers. Lastly, we investigated the prognostic gene expression levels in normal and LIHC tissues with immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction(qRT-PCR).

Results

We built and verified a prognostic signature with seven genes that incorporated immune profiles and lipid metabolism. Patients were classified as low- and high-risk groups depending on their prognostic profiles. The overall survival (OS) was markedly lower in the high-risk group as compared to low-risk group. Time-dependent ROC curves more precisely predicted patients' survival at 1, 3 and 5 years; the area under the ROC curve was 0.81 (1 year), 0.75 (3 years) and 0.77 (5 years). The DCA curves showed the value of the prognostic genes in this signature for clinical applications. We included the patients' clinical characteristics in the risk model for both multivariate and univariate Cox regression analyses, and the findings revealed that the risk model represents an independent factor that influences OS in LIHC patients. With immune analysis, GSVA and GSEA, we identified that there are remarkable differences between the two risk groups in immune pathways, lipid metabolism, tumor development, immune cell infiltration and immune microenvironment, response to immunotherapy, and sensitivity to chemotherapy. Moreover, those with higher risk scores presented greater sensitivity to the chemotherapeutic agents. Experiments in vitro further elucidated the roles of SPP1 and FLT3 in the LIHC immune microenvironment. Furthermore, four small-molecule drugs that could target LIHC were screened. In vitro qRT-PCR , IHC revealed that the SPP1,KIF18A expressions were raised in LIHC in tumor samples, whereas FLT3,SOCS2 showed the opposite trend.

Conclusions

We developed and verified a new signature comprising immune- and lipid metabolism-associated markers and to assess the prognosis and the immune status of LIHC patients. This signature can be applied to survival prediction, individualized chemotherapy, and immunotherapeutic guidance for patients with liver cancer. This study also provides potential targeted therapeutics and novel ideas for the immune evasion and progression of LIHC.

Personalized Prescription of Chemotherapy Based on Assessment of mRNA Expression of BRCA1, RRM1, ERCC1, TOP1, TOP2α, TUBβ3, TYMS, and GSTP1 Genes in Tumors Compared to Standard Chemotherapy in the Treatment of Non-Small-Cell Lung Cancer

Objectives: A growing body of evidence suggests the important role of chemosensitive gene expression in the prognosis of patients with lung cancer. However, studies on combined gene expression assessments for personalized prescriptions of chemotherapy regimens in patients have not yet been conducted. The aim of this work was to conduct a prospective study on the appointment of personalized chemotherapy in patients with non-small-cell lung cancer. Materials and methods: The present study analyzed 85 patients with lung cancer (stage IIB-IIIB). Within this group, 48 patients received individualized chemotherapy, and 37 patients received classical chemotherapy. In the individualized chemotherapy group, the mRNA expression levels of ERCC1, RRM1, TUBB3, TYMS, TOP1, TOP2α, BRCA1, and GSTP1 in lung tissues were measured by quantitative real-time PCR (qPCR), and an individual chemotherapy regimen was developed for each patient according to the results. Patients in the classical chemotherapy group received the vinorelbine/carboplatin regimen. Survival analyses were performed using the Kaplan−Meier method. Prognostic factors of metastasis-free survival (MFS) and overall survival (OS) of patients were identified via Cox’s proportional hazards regression model. Results: MFS and OS were significantly better in the personalized chemotherapy group compared to the classic chemotherapy group (MFS, 46.22 vs. 22.9 months, p = 0.05; OS, 58.6 vs. 26.9 months, p < 0.0001). Importantly, the best metastasis-free survival rates in the group with personalized ACT were achieved in patients treated with the paclitaxel/carboplatin regimen. Based on an assessment of chemosensitivity gene expression in the tumors, the classical chemotherapy strategy also increased the risk of death (HR = 14.82; 95% CI: 3.33−65.86; p < 0.000) but not metastasis (HR = 1.95; 95% CI: 0.96−3.98; p = 0.06) compared to the group of patients with chemotherapy. Conclusions: The use of combined ERCC1, RRM1, TUBB3, TYMS, TOP1, TOP2α, BRCA1, and GSTP1 gene expression results for personalized chemotherapy can improve treatment efficacy and reduce unnecessary toxicity.

Extensive analysis of the molecular biomarkers excision repair cross complementing 1, ribonucleotide reductase M1, β-tubulin III, thymidylate synthetase, and topoisomerase IIα in breast cancer: Association with clinicopathological characteristics

Excision repair cross complementing 1 (ERCC1), ribonucleotide reductase M1 (RRM1), β-tubulin III (TUBB3), thymidylate synthetase (TYMS), and topoisomerase IIα (TOP2A) genes have been shown to be associated with the pathogenesis and prognosis of various types of carcinomas; however, their roles in breast cancer have not been fully validated. In this study, we evaluated the correlations among these biomarkers and the associations between their expression intensity and the clinicopathological characteristics to investigate whether the above genes are underlying biomarkers for patients with breast cancer.Ninety-seven tissue specimens collected from breast cancer patients. The expression levels of these biomarkers were measured by the multiplex branched DNA liquidchip (MBL) technology and clinicopathological characteristics were collected simultaneously.The expression levels of ERCC1, TUBB3, TYMS, and TOP2A were significantly associated with the characteristics of menopausal status, tumor size, lymph node metastasis, hormone receptor status, triple-negative status, Ki-67 index, and epidermal growth factor receptor. The expression intensity of ERCC1 negatively associated with that of TUBB3 and TYMS, and positively associated with that of RRM1. The expression intensity of TOP2A positively associated with that of TYMS. Hierarchical clustering analysis and difference test indicated that breast cancer with higher levels of TUBB3, TYMS, and TOP2A, as well as lower levels of ERCC1 and RRM1 tended to have higher histological grade and Ki-67 index.Our studies showed that ERCC1, TYMS, TUBB3, and TOP2A may be potential biomarkers for prognosis and individualized chemotherapy guidance, while there may be interactions between ERCC1 and RRM1, or TUBB3, or TYMS, as well as between TOP2A and TYMS in pathogenesis and development of breast cancer.

Individualized chemotherapy guided by the expression of ERCC1, RRM1, TUBB3, TYMS and TOP2A genes versus classic chemotherapy in the treatment of breast cancer: A comparative effectiveness study

ERCC1, RRM1, TUBB3, TYMS and TOP2A genes have been shown to be associated with drug resistance in various types of tumors; however, their roles in breast cancer chemotherapy have not been fully validated. In the present study, 140 well-matched patients with breast cancer, comprising 70 patients receiving individualized chemotherapy and 70 receiving classic chemotherapy, were analyzed. In the individualized chemotherapy group, the mRNA expression levels of ERCC1, RRM1, TUBB3, TYMS and TOP2A in breast cancer tissues were measured using multiplex branched DNA liquidchip technology prior to chemotherapy; an individualized chemotherapy regimen was developed for each patient according to the results. As a control, patients in the classic chemotherapy group received a docetaxel + epirubicin + cyclophosphamide regimen. Survival analyses were performed using the Kaplan-Meier method. The prognostic factors for disease-free survival (DFS) and overall survival (OS) in the patients were identified via Cox's proportional hazards regression model. Adverse reactions were evaluated according to the National Cancer Institute Common Toxicity Criteria 4. Compared with the classic chemotherapy group, the DFS and OS of the individualized chemotherapy group were significantly longer (DFS, 77.4 vs. 67.1 months, P=0.039; OS, 81.4 vs. 75.4 months, P=0.031), and the incidence of grade 2 or 3 palpitations and chest tightness was lower (12.9 vs. 27.1%, P=0.035). The chemotherapy strategy guided by genetic detection was an independent protection factor for DFS [hazard ratio (HR)=0.389, 95% confidence interval (CI): 0.153, 0.989, P=0.047], but not an independent protection factor for OS (HR=0.340, 95% CI: 0.107, 1.078, P=0.067). The results indicate that the combined detection of ERCC1, RRM1, TUBB3, TYMS and TOP2A gene expression and use of the results to guide individualized chemotherapy can improve treatment efficacy and reduce unnecessary toxicity.

Chemosensitivity-directed therapy compared to dacarbazine in chemo-naive advanced metastatic melanoma: a multicenter randomized phase-3 DeCOG trial

Chemotherapy still plays an important role in metastatic melanoma, particularly for patients who are not suitable or have no access to highly efficacious new therapies. Pre-therapeutic chemosensitivity testing might be useful to identify optimal chemotherapy regimens for individual patients. This multicenter randomized phase-3 trial was aimed to test for superiority of chemosensitivity-directed combination chemotherapy compared to standard dacarbazine monochemotherapy, and to demonstrate the chemosensitivity test result as prognostic in metastatic melanoma. Chemo-naive patients with advanced melanoma were biopsied from metastatic lesions. Tumor cells were isolated and tested ex-vivo for sensitivity to chemotherapeutic agents using an ATP-based viability assay. Patients with evaluable test results were randomly assigned to receive either chemosensitivity-directed combination chemotherapy (paclitaxel+cisplatin, treosulfan+gemcitabine, treosulfan+cytarabine), or dacarbazine. The primary study endpoint was overall survival (OS). After inclusion of 287 patients and a median follow-up of 26 months, the per-protocol population (n=244) showed no difference in OS between chemosensitivity-directed therapy and dacarbazine (median 9.2 vs 9.0 months, HR=1.08, p=0.64). The disease control rate (CR+PR+SD) tended to be higher in patients treated with chemosensitivity-directed therapy (32.8% vs 23.0%, p=0.088); objective response rates (CR+PR) showed no difference between groups (10.7% vs 12.3%, p=0.90). Patients whose tumors were tested chemosensitive showed no better OS or response rate than patients with chemoresistant tumors. Severe toxicities (CTC grade 3-4) were significantly more frequently observed with chemosensitivity-directed combination chemotherapy than with dacarbazine (40.2% vs 12.3%, p<0.0001). These results indicate, that chemosensitivity-directed combination chemotherapy is not superior to dacarbazine, but leads to significantly more severe toxicities.

Lauren classification and individualized chemotherapy in gastric cancer

Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.