Evaluating the efficacy of immunotherapy in gastric cancer: Insights from immune checkpoint inhibitors

Abstract

The emergence of immunotherapy, particularly immune checkpoint inhibitors (ICIs), represents a groundbreaking approach to treating gastric cancer (GC). However, the prognosis of GC patients receiving ICI treatment is influenced by various factors. This manuscript identified sarcopenia and myosteatosis as inde-pendent prognostic factors impacting the outcomes of GC patients treated with ICIs. Additionally, this study introduced a visual predictive model to estimate the prognosis of GC patients. If confirmed by further studies, this observation could provide valuable insights to propel the advancement of personalized clinical medicine and the integration of precision medicine practices.

Key Words: Gastric cancer; Immune checkpoint inhibitors; Sarcopenia; Myosteatosis; Prediction model

Core Tip: This study delved into the determinants influencing the efficacy of immune checkpoint inhibitor (ICI) therapy in gastric cancer. Employing COX regression analysis, it crafted a prediction model aimed at enhancing the efficiency and simplicity of evaluating the suitability of immunotherapy. These findings offer novel perspectives for the judicious utilization of ICIs, contributing to improved treatment decision-making and patient care.

INTRODUCTION

In this issue of the World Journal of Gastroenterology, Deng et al[1] highlighted sarcopenia and myosteatosis as autonomous prognostic indicators impacting the effectiveness of immune checkpoint inhibitors (ICIs) in gastric cancer (GC) treatment. They also devised a visual predictive model to evaluate progression-free survival (PFS) and overall survival (OS) among GC patients.

GC

GC stands as one of the most prevalent malignancies globally, ranking as the third leading cause of cancer-related deaths. With a median OS of less than one year for metastatic GC. Globally, the incidence of GC is highest in East Asia, followed by Eastern and Central Europe[2]. Its high morbidity, mortality, and propensity for metastasis pose substantial threats to human health and life and burdens to global public health[3]. The primary risk factors for GC encompass Helicobacter pylori infection, dietary habits, smoking, suboptimal lifestyle behaviors, and exposure to radiation[4]. Presently, endoscopic resection constitutes the cornerstone of treatment for early-stage GC, while surgical intervention is employed for non-early-stage GC, and sequential chemotherapy is administered for advanced GC[5]. In the era of precision medicine, immunotherapy emerges as a promising therapeutic avenue, marking transformative phase in cancer tr-eatment. Central to this approach is the modulation of immune checkpoints, where CTLA-4 plays a pivotal role in suppressing T cell activation and proliferation, while the interaction between PD-1 and PD-L1 inhibits T cell function within the tumor microenvironment[6]. Immunotherapy agents such as Pembrolizumab, Nivolumab, Avelumab, Durvalumab, Ipilimumab, and Tremelimumab, targeting these checkpoints, have shown some efficacy in GC treatment[7]. Despite promising outcomes, the effectiveness of ICIs in GC treatment remains modest, with only approximately 15% of patients demonstrating response rates[8]. The heterogeneous nature of the tumor microenvironment contributes to resistance against immunotherapy through mechanisms of immune evasion[9]. Moreover, the activation of immune cells as a result of checkpoint inhibition can precipitate adverse inflammatory responses. These responses may manifest as dermatologic reactions, colitis, myocarditis, and autoimmune disorders[10]. A retrospective study encompassing 115 patients diagnosed with GC who underwent ICI therapy, including PD-1 blocking antibodies (both anti-PD-1 and anti-PD-L1 antibodies), either as monotherapy or in combination, was conducted[1]. Given the significant heterogeneity observed in GC and the challenges in predicting therapeutic responses to ICIs, there is an urgent need for simple and efficient predictive models to identify suitable candidates for immunotherapy. Such models would facilitate personalized treatment approaches, optimizing the utilization of ICIs and improving patient outcomes. This study evaluates the influence of ICIs on the efficacy and prognosis of GC from the standpoint of sarcopenia and myosteatosis. The findings contribute to the advancement of personalized immunotherapy for GC. Additionally, the novel predictive model developed, which incorporates key influencing factors, enhances the accuracy and convenience of selecting clinical immunotherapy to a certain degree[1].

In recent years, there has been a notable rise in the prevalence of GC cases accompanied by sarcopenia or myosteatosis. In the research, the authors identified sarcopenia and myosteatosis as critical prognostic factors affecting GC patients undergoing ICI treatment[1]. Sarcopenia, characterized by a gradual and generalized decline in skeletal muscle mass and function, poses significant risks, including increased susceptibility to falls, functional impairment, muscle weakness, and mortality[11]. Myosteatosis primarily characterized as the infiltration of skeletal muscle tissue by ectopic adipose deposits[12]. The study presented demographic profiles, clinical features, tumor characteristics (including tumor size and stage), and laboratory findings, along with measurements of the L3 skeletal muscle area and mean computed tomography (CT) radiodensity. The assessment of sarcopenia and myosteatosis was conducted based on the skeletal muscle area and mean density at the L3 level, with PFS and OS serving as the primary endpoints[1]. Both sarcopenia and myosteatosis were found to adversely affect the prognosis of GC by altering the body's metabolic state and immune function. A meta-analysis indicates that sarcopenia correlates with adverse outcomes across various tumor types and increases the risk of postoperative complications in patients with digestive system malignancies[13]. Muscle steatosis correlates with an increased risk of mortality related to GC[14]. Insufficient nutrition, particularly low protein intake, constitutes a risk factor for both sarcopenia and frailty[15]. The quantity of protein consumed in the diet directly impacts protein synthesis and subsequently influences muscle mass[16]. A meta-analysis involving 1424 older adults revealed that dairy protein intake was significantly associated with increased appendicular muscle mass[15]. Diminished nutritional intake and metabolic alterations observed in patients with GC can contribute to the development of sarcopenia. Malignant tumors, particularly GC, are among the primary factors precipitating sarcopenia[17,18]. The results of this study showed that GC patients with sarcopenia tended to be older, had lower BMI and creatinine levels, and were predominantly male. Conversely, GC patients with myosteatosis exhibited differences from those without myosteatosis in terms of age and various biochemical parameters, including concentrations of globulin, lactate dehydrogenase activity, d-dimer, and prealbumin. Subsequently, the authors employed COX regression analysis to identify potential prognostic factors, with sarcopenia and myosteatosis emerging as independent prognostic factors for PFS and OS in GC patients treated with ICIs. Survival curve analysis demonstrated that both sarcopenia and myosteatosis detrimentally affected PFS and OS in these patients[10].

Amid the advancement of precision medicine, researchers are increasingly focusing on crafting disease prediction models. Tailoring treatment plans to individual needs and devising personalized precision therapies hold promise for enhancing clinical efficacy and extending patient survival. The authors developed an optimized prediction model for PFS and OS using multivariate COX regression analysis, confirming its accuracy and clinical utility through evaluation metrics such as the C-index, area under the curve analysis, and decision curve analysis[10]. The progression of precision medicine necessitates assessment aided by parameters such as biomarkers. Currently, biomarkers such as PD-L1 expression, tumor mutational burden, mismatch repair status, Epstein-Barr virus infection, circulating tumor DNA, and tumor-infiltrating lymphocytes have demonstrated utility in assessing the efficacy of immunotherapy for GC. However, these assays are costly and possess inherent limitations[19]. This study identified easily detectable sarcopenia/myosteatosis, assessed through CT imaging, as a critical predictor for ICI efficacy in GC. Utilizing biosignal analysis, the study established a predictive model, markedly enhancing the affordability and simplicity of evaluating immunotherapy outcomes. If validated, these findings present a novel avenue for the judicious utilization of ICIs in clinical practice.

Nevertheless, this study has several limitations. Firstly, the sample size was limited, and the research was conducted as a single-center study. There could be inherent selection biases, particularly considering the older age demographic observed among patients with GC combined with sarcopenia or myosteatosis. Secondly, the assessment of sarcopenia or myosteatosis relied solely on single and unspecified time CT data. This may potentially overlooked variations in CT conditions across different stages of disease progression, which could impact the study outcomes. Thirdly, to elucidate the efficacy of ICIs in GC patients with sarcopenia or myosteatosis, experiments should compare the patients treated and untreated with ICIs that exhibited similar sarcopenia/myosteatosis, as well as without sarcopenia/myosteatosis. Lastly, a rigorous prospective controlled studies would made a significant advancement if the proposed model from this retrospective observation is confirmed.

CONCLUSION

The emergence of ICIs has introduced a novel therapeutic avenue for GC, holding significant potential. However, the efficacy of ICIs therapy in GC is influenced by multiple factors. Besides, the available indices for predicting efficacy are often limited and costly. Sarcopenia and myosteatosis, common comorbidities of GC, play crucial roles in shaping GC prognosis. In this study, sarcopenia and myosteatosis were identified as independent prognostic factors impacting GC patients treated with ICIs. Building on these findings, a prediction model was introduced. If confirmed by further studies, this model will facilitate the assessment of ICIs efficacy and offer valuable guidance for selecting ICIs treatment in GC patients. It will also advance the precision medicine in GC management. Therefore, it is recommended that the government enhance funding for ICIs in the context of GC and support both basic and clinical research to elucidate the impact of sarcopenia and myosteatosis on the efficacy of immunotherapy for GC. The prevalence of sarcopenia and myosteatosis as comorbidities in GC is increasing, significantly influencing the prognosis of GC. Consequently, there is an urgent need for the development of appropriate immunosuppressive agents for targeted treatment. Additionally, researchers should intensify efforts in the development and application of novel ICIs.