Development and validation of a nomogram to predict pathological complete response in patients with locally advanced gastric adenocarcinoma treated with neoadjuvant chemotherapy in combination with PD-1 antibodies

Abstract

Background Currently, the survival benefits of combining neoadjuvant chemotherapy with programmed death 1 (PD-1) antibody immunotherapy in advanced gastric adenocarcinoma remain controversial. Emerging evidence suggests that the survival benefits of neoadjuvant therapy in advanced gastric adenocarcinoma hinge upon the attainment of pathological complete response (pCR). Therefore, the prediction of pCR in patients undergoing neoadjuvant chemotherapy combined with PD-1 antibody immunotherapy holds significant importance and is beneficial for the individualized treatment of gastric cancer (GC) patients. Methods Clinical and pathological characteristics of patients with GC who received neoadjuvant chemotherapy combined with PD-1 inhibitor (camrelizumab) therapy and radical gastrectomy between January 2019 and December 2020 at the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital were retrospectively analyzed. A total of 52 patients were enrolled in the study, with all subjects assigned to the training set. The neoadjuvant regimen consisted of a combination of PD-1 inhibitor and fluorouracil analogues plus oxaliplatin, comprising two drugs. The patients were divided into a pCR group and a non-pCR group according to pCR occurrence. Multifactor logistic regression analysis was applied to determine the correlation between each factor and pCR. A prediction model was developed based on the results of the logistic regression analysis. The predictive performance of the model was evaluated using the receiver operating characteristic curves. Internal verification was completed via the bootstrapping method. Results The pCR was observed in 10 out of 52 patients (19.2%). The results of binary logistic regression multivariate analysis showed that cN stage [odds ratio (OR): 0.215; P=0.03], combined positive score (CPS) (OR: 6.364; P=0.026), and tumor diameter (OR: 0.112; P=0.026) were independent predictors of pCR. The nomogram prediction model for the pCR was plotted with a concordance index of 0.923 [95% confidence interval (CI): 0.8441–1]. Conclusions Neoadjuvant chemotherapy combined with PD-1 antibodies may be the preferred option for patients with advanced gastric adenocarcinoma who have a small tumor diameter, no or few lymph node metastases, and high CPS. The presented nomogram model exhibits the potential to predict pCR in advanced gastric adenocarcinoma patients, showcasing satisfactory predictive performance and potentially facilitating the implementation of personalized treatment strategies.

Predictive Factors of Immunotherapy in Gastric Cancer: A 2024 Update

“…In advanced gastric adenocarcinoma with a reduced tumor mass, absence or a small number of lymph node metastases, and a large combined positive score, neoadjuvant chemotherapy plus PD-1 antibodies may be the best course of action. In patients with AGC, a nomogram model may be able to predict pathological complete response (pCR), demonstrating acceptable predictive performance and thus easing the use of individualized treatment plans [ 13 ]. A decrease in cytotoxic T-cell (CD8+ T) and CD8+ T-cell memory (CD8+ Tm) PD-1 expression, as well as the PD-1+CD8+ T/PD-1+CD4+ T-cell ratio, was found to be an independent risk factor for PFS in AGC patients receiving immunotherapy plus chemotherapy according to univariate and multivariate Cox regression analyses.…”

“…disulfidptosis-related gene prognostic risk model [4] -M2 macrophages were strongly correlated with a high PANscore [5] predictive signature AC129926.1, AC023511.1, AP002954.1, LINC01537, and TMEM7 based on CRLs [6] -ARLSig has strong predictive value for the survival of GC patients [7] -PRS was created using the TCGA, GSE15459, GSE26253, GSE62254, and GSE84437 datasets [8] -PI3K pathway linked to PD-L1 positivity is linked to increased immunotherapy efficacy [9] potentially valid serum predictive markers for identifying individuals who might profit from PD-1 inhibitors paired with chemotherapy include IL-6, IL-2, IL-17A, and NLR [10] -PD-L1+CD68+ macrophages may be a viable prognostic indicator in primary GC patients [11] -ITGB1 may be an effective prognostic biomarker and a useful predictor of outcome for GC patients receiving anti-PD-1 medication [12] a reduced tumor mass, absence or small number of lymph node metastases, and a large combined positive score; neoadjuvant chemotherapy plus PD-1 antibodies for the prediction of pCR in AGC patients undergoing neoadjuvant chemotherapy combined with PD-1 antibody immunotherapy [13] memory PD-1+CD8+ T cells and the ratio of PD-1+CD8+ T cells to PD-1+CD4+ T cells may be useful for identifying individuals who would benefit from immunotherapy among AGC patients [14] the CD4+/CD8+ ratio may be a potential predictive indicator for patients under PD-1 inhibitor-based combination therapy for advanced gastric and esophageal cancer, and it can independently predict dermatological damage [15] -MFSD2A may function as a prognostic biomarker for the response to anti-PD-1 immunotherapy in AGC patients [16] the peripheral CD4+ T-cell subset has shown significant predictive value for therapeutic response and longer survival in AGC patients [17] patients with GC receiving combination immunotherapy are predicted to respond better when HSPA4 is upregulated [18] the combination of Tregs, Ki-67, and age (65 years or older) can more accurately predict the likelihood of unfavorable responses [19] the incidence of irAEs could serve as a stand-in marker for ICIs [20] utilizing biomarkers based on the numbers of various lymphocyte subpopulations, it is possible to predict the clinical prognosis and efficacy of immunotherapy in patients with AGC [21] a negative correlation between CRABP2 and the immune checkpoint markers PD-1, PD-L1, and CTLA-4 was observed [22] Table 2. Major developments in genetic predictive factors research.…”