A novel prognostic model of gastric cancer patients based on cachexia status by using plasma exosome-derived miRNAs

Abstract

Abstract Background:Emerging evidence shows that serum biomarkers are closely associated with the prognosis of gastric cancer. Cachexia represents systemic nutritional and metabolic statuses. This study aimed to clinically validate the predictive value of serum biomarkers and cachexia, and to identify a potential biomarker for the early diagnosis of cachexia. Methods: This study included patients with gastric cancer who received curative treatment with no other nonneoplastic cachexia. The eligible population was randomized into training (70%) and test (30%) cohorts.A univariate and multivariate Cox proportional-hazards regression model was used to construct a gastric cancer prognosis model. The predictive and discriminative abilities of the model were evaluated using Kaplan–Meier (K–M) and receiver operating characteristic (ROC) curves. A nomogram was constructed based on the factors identified using the prognostic model, and the corresponding calibration curve was used to validate the accuracy of the nomogram. Exosomal microRNAs (miRNAs) were screened for the early diagnosis of cachexia via whole-genome sequencing, and the clinical samples were used for verification. Results: This study included 1101 eligible patients with gastric cancer. There were 330 (29.97%) patients with cachexia and 771 (70.03%) without cachexia. Univariate Cox regression analysis identified the following prognostic factors: body mass index; cachexia; nutritional risk screening scale-2002 (NRS2002) score; serum albumin, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9(CA19-9), and carbohydrate antigen 125 (CA125) levels, and red blood cell count. Multivariate Cox regression analysis identified cachexia and CEA, CA19-9, and serum albumin levels as the independent risk factors for overall survival (OS;p < 0.05). The K–M curve indicated that the OS of high-risk patients was significantly lower than that of low-risk patients. The areas under the curve of the 1-, 2-, and 3-year prognostic models were 81.13%, 78.49%, and 76.23%, respectively (79.01%, 78.61%, and 75.34% for the test cohort, respectively). Finally, the corresponding nomogram was used to predict the OS of patients with gastric cancer. The calibration curve showed the best agreement between predictions and actual observations. Furthermore, plasma exosomal miR-432-5p was identified as a biomarker for the early diagnosis of cachexia via whole-gene sequencing to make up for the lack of methods for the early diagnosis of cachexia. Conclusions: Serum biomarker levels and cachexia status are clinically significant in patients with gastric cancer. We constructed a novel prognostic model based on serum biomarker levels and cachexia. A novel nomogram constructed using this model may predict OS in patients with gastric cancer alone. Furthermore, we identified a novel plasma exosomal biomarker, miR-432-5p, for the early diagnosis of cachexia.