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A 13-Gene Metabolic Prognostic Signature Is Associated With Clinical and Immune Features in Stomach Adenocarcinoma.

ABSTRACT: Patients with advanced stomach adenocarcinoma (STAD) commonly show high mortality and poor prognosis. Increasing evidence has suggested that basic metabolic changes may promote the growth and aggressiveness of STAD; therefore, identification of metabolic prognostic signatures in STAD would be meaningful. An integrative analysis was performed with 407 samples from The Cancer Genome Atlas (TCGA) and 433 samples from Gene Expression Omnibus (GEO) to develop a metabolic prognostic signature associated with clinical and immune features in STAD using Cox regression analysis and least absolute shrinkage and selection operator (LASSO). The different proportions of immune cells and differentially expressed immune-related genes (DEIRGs) between high- and low-risk score groups based on the metabolic prognostic signature were evaluated to describe the association of cancer metabolism and immune response in STAD. A total of 883 metabolism-related genes in both TCGA and GEO databases were analyzed to obtain 184 differentially expressed metabolism-related genes (DEMRGs) between tumor and normal tissues. A 13-gene metabolic signature (GSTA2, POLD3, GLA, GGT5, DCK, CKMT2, ASAH1, OPLAH, ME1, ACYP1, NNMT, POLR1A, and RDH12) was constructed for prognostic prediction of STAD. Sixteen survival-related DEMRGs were significantly related to the overall survival of STAD and the immune landscape in the tumor microenvironment. Univariate and multiple Cox regression analyses and the nomogram proved that a metabolism-based prognostic risk score (MPRS) could be an independent risk factor. More importantly, the results were mutually verified using TCGA and GEO data. This study provided a metabolism-related gene signature for prognostic prediction of STAD and explored the association between metabolism and the immune microenvironment for future research, thereby furthering the understanding of the crosstalk between different molecular mechanisms in human STAD. Some prognosis-related metabolic pathways have been revealed, and the survival of STAD patients could be predicted by a risk model based on these pathways, which could serve as prognostic markers in clinical practice.

SUBMITTER: Ye Z

PROVIDER: S-EPMC8256842 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeHepatoid adenocarcinoma of the stomach (HAS) is a highly malignant and aggressive tumor. The purpose of this study was to describe the clinical, computed tomography (CT), and prognostic features of HAS to increase the awareness of this entity and determine its distinguishing features from non-HAS tumors.MethodsThe CT features and clinical data of 47 patients in our hospital with pathologically documented HAS were retrospectively analyzed, and the relevant differences between pure HAS (pHAS) and mixed HAS (mHAS) were determined. In addition, 141 patients with non-HAS tumors in the same T stage in the same period were selected as the control group. The data were compared between the two groups, and factors affecting the prognosis of HAS were analyzed. In addition, we included 9 patients with HAS and 27 patients with non-HAS tumors from another center for external validation.ResultsThe patients in the HAS group were predominantly men (n = 33), and the tumor location was mostly the cardia or fundus (n = 27). Between the HAS and non-HAS groups, there were observed differences in terms of: sex, serum alpha-fetoprotein (AFP), carbohydrate antigen (CA)-125, and CA-724 levels; longest tumor diameter; degree of differentiation; vascular invasion; N stage, M stage, and tumor-node-metastasis (TNM) stage; thickest tumor diameter; plain CT attenuation; arterial-phase CT attenuation; CT attenuation between the venous and arterial phases; enhancement modes; and degrees of enhancement (all P < 0.05). In the data from another center for external validation, there were observed differences in terms of: age, degree of differentiation, vascular invasion, thickest tumor diameter, the ratio of arterial CT attenuation to CT attenuation of the abdominal aorta at the same level (RA), CT attenuation difference between the venous phase and arterial phase (HUv-a) (all P < 0.05). The results of the multivariate analysis revealed that the independent factors for differentiation were serum AFP level (P = 0.001), M stage (P = 0.038), and tumor enhancement on CT (P = 0.014). Among patients in the HAS group, 72.34% had pHAS and 27.66% had mHAS. The thickest tumor diameter and the longest short diameter of the metastatic lymph nodes of the mHAS group were on average 6.39 cm and 1.45 cm, respectively, which were larger than those in the pHAS group. The median progression-free survival time was 18.25 months in the HAS group, which was shorter than that in the non-HAS group (72.96 months; P = 0.001). The median overall survival time in the HAS group was 24.80 months, which was shorter than that in the non-HAS group (67.96 months; P = 0.001). The factors affecting the prognosis of HAS were M stage (P = 0.001), overall TNM stage (P = 0.048), presence of vascular cancer emboli (P = 0.040), and pHAS type (P = 0.046). Multifactorial analysis revealed that M stage (P = 0.027) and pHAS type (P = 0.009) were independent risk factors affecting the prognosis of HAS.ConclusionAlthough HAS is a rare clinical entity, it should be considered in the differential diagnosis of gastric tumors. Patients with HAS often have advanced-stage disease at presentation and a worse prognosis than patients with non-HAS tumors. CT findings, combined with laboratory results, can support the diagnosis of HAS. However, the final diagnosis needs to be confirmed with a histopathologic examination. If the postoperative pathologic findings reveal the mHAS type, a rapid clinical intervention and a detailed follow-up with CT are essential.

Project description:BackgroundStomach adenocarcinoma (STAD) is the most common histological type of stomach cancer, which causes a considerable number of deaths worldwide. This study aimed to identify its potential biomarkers with the notion of revealing the underlying molecular mechanisms.MethodsGene expression profile microarray data were downloaded from the Gene Expression Omnibus (GEO) database. The "limma" R package was used to screen the differentially expressed genes (DEGs) between STAD and matched normal tissues. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for function enrichment analyses of DEGs. The STAD dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another STAD dataset from the GEO database. CIBERSORT algorithm was used to characterize the 22 human immune cell compositions. The expression of LRFN4 and CTHRC1 in tissues was determined by quantitative real-time PCR from the patients recruited to the present study.ResultsThree public datasets including 90 STAD patients and 43 healthy controls were analyzed, from which 44 genes were differentially expressed in all three datasets. These genes were implicated in biological processes including cell adhesion, wound healing, and extracellular matrix organization. Five out of 44 genes showed significant survival differences. Among them, CTHRC1 and LRFN4 were selected for construction of prognostic signature by univariate Cox regression and stepwise multivariate Cox regression in the TCGA-STAD dataset. The fidelity of the signature was evaluated in another independent dataset and showed a good classification effect. The infiltration levels of multiple immune cells between high-risk and low-risk groups had significant differences, as well as two immune checkpoints. TIM-3 and PD-L2 were highly correlated with the risk score. Multiple signaling pathways differed between the two groups of patients. At the same time, the expression level of LRFN4 and CTHRC1 in tissues analyzed by quantitative real-time PCR were consistent with the in silico findings.ConclusionThe present study constructed the prognostic signature by expression of CTHRC1 and LRFN4 for the first time via comprehensive bioinformatics analysis, which provided the potential therapeutic targets of STAD for clinical treatment.

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A 13-Gene Metabolic Prognostic Signature Is Associated With Clinical and Immune Features in Stomach Adenocarcinoma.

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