Triglyceride-glucose index as a prognostic indicator in advanced gastric cancer: Insights and future research

Abstract

Gastric cancer (GC), the fifth most common malignancy worldwide, poses a substantial challenge in clinical oncology, particularly in its advanced stages. Despite advancements in immunotherapy, patient prognosis remains poor, underscoring the need for reliable prognostic tools to refine treatment strategies. A study by Yao et al explores the role of the triglyceride-glucose (TyG) index as a prognostic marker for advanced GC patients receiving immunotherapy combined with chemotherapy. The results of the study demonstrate that the TyG index correlates with improved survival outcomes, including better progression-free survival and overall survival. This editorial critically evaluates the significance of these findings, discusses their implications for future research, and highlights innovative directions that could drive further breakthroughs in the application of the TyG index to cancer therapy. This editorial also highlights the potential of TyG in advancing precision oncology and advocates for global validation and mechanistic investigations to further solidify its clinical utility. Future research should focus on validating the TyG index across various malignancies, exploring its potential to influence immunotherapy through metabolic interventions, and developing multi-biomarker models that integrate TyG with immune and genomic profiles.

Key Words: Advanced gastric cancer; Triglyceride-glucose index; Prognostic indicator; Immunotherapy; Insulin resistance

Core Tip: Gastric cancer (GC) is one of the most prevalent and deadly cancers worldwide, with advanced stages associated with poor survival outcomes. The triglyceride-glucose (TyG) index is a comprehensive statistical measure that incorporates fasting triglyceride and fasting glucose levels. Yao et al reported the effect of the TyG index on the prognosis of advanced GC patients undergoing combination therapy with sintilimab (a programmed cell death protein 1 inhibitor) and chemotherapy. This editorial critically analyzes the study’s clinical significance, its potential for enhancing personalized treatment strategies, and the innovative future research directions that could solidify the role of the TyG index in clinical oncology.

INTRODUCTION

Gastric cancer (GC) is a significant global health burden, ranking as the fifth most common malignant cancer and the fourth leading cause of cancer-related mortality worldwide[1]. Although the incidence of GC has decreased in some parts of the world, it remains a prevalent and aggressive malignancy, particularly in Asia, where environmental factors, diet, and genetics contribute to its high incidence. Most GC patients are diagnosed at advanced stages, making the prognosis poor, with the majority of these patients unable to undergo curative surgical interventions.

Recent advances in immunotherapy have provided promising options for treating advanced GC, with immune checkpoint inhibitors such as programmed cell death protein 1 (PD-1) blockers (e.g., sintilimab) showing significant therapeutic potential. However, the efficacy of immunotherapy is often variable, and not all patients respond favorably. This underscores the necessity of identifying reliable biomarkers that can predict treatment outcomes and guide clinical decision-making.

One such promising biomarker is the triglyceride-glucose (TyG) index, a simple and cost-effective marker that reflects the metabolic state of a patient, specifically the level of insulin resistance[2-4]. Insulin resistance is recognized as a key player in the progression of many cancers, including GC, and can influence the tumor microenvironment, immune response, and response to treatment[5-7]. A previous study reported that the TyG index plays a mediating role in the relationship between circadian syndrome and cancer among middle-aged and elderly Chinese, and the higher the TyG index, the higher the possibility of developing cancer, showing a non-linear relationship[8]. This finding provides new evidence for the potential bridging role of circadian syndrome between metabolic dysfunction and cancer development[8]. It is worth noting that an elevated TyG index is significantly associated with gastric carcinogenesis, suggesting that the TyG index may serve as a novel predictive biomarker for the occurrence of GC[9]. The TyG index is significantly associated with visceral obesity, and when combined with body mass index, it has important predictive value for assessing visceral obesity in patients with GC[10]. Cai et al[11] reported that the TyG index is an independent protective factor for GC prognosis, and found that a higher TyG index indicated a better prognosis. A study by Yao et al[12], published in World Journal of Gastroenterology, investigates the role of the TyG index in predicting the prognosis of advanced GC patients treated with the combination of sintilimab and chemotherapy. The findings in the study suggest that the TyG index can be a useful prognostic marker for assessing the long-term survival of GC patients. This editorial will explore the significance of these findings, provide insights into their clinical applications, and propose innovative directions for future research on the TyG index in cancer therapy.

KEY FINDINGS OF THE STUDY

Yao et al[12] reports a novel exploration of the TyG index as a prognostic marker in GC. The study, which includes a cohort of 300 patients with advanced GC treated with sintilimab combined with chemotherapy, offers several key insights into the clinical utility of the TyG index.

The TyG index as a prognostic factor in GC

The study demonstrated that a higher TyG index was associated with significantly better outcomes, including longer overall survival (OS) and progression-free survival (PFS). Specifically, the high TyG index group had a median OS of 23.1 months compared to 16.5 months in the low TyG index group. Furthermore, patients in the high TyG index group had a median PFS of 9.8 months, whereas those in the low TyG index group had a median PFS of 8.0 months. These results suggest that the TyG index can serve as an independent prognostic factor, aiding in the prediction of survival outcomes for GC patients receiving combined immunotherapy and chemotherapy.

Exploring the relationship between TyG and immunotherapy response

The study also revealed that the objective response rate (ORR) and disease control rate (DCR) were higher in patients with a high TyG index. The high TyG index group had an ORR of 18.38% compared to 9.15% in the low TyG index group, and the DCR was 58.82% in the high TyG group vs 46.95% in the low TyG group. These findings suggest that a higher TyG index may enhance sensitivity to immunotherapy, making it a valuable marker for predicting which patients are more likely to benefit from immune checkpoint inhibitors. This insight may assist clinicians in identifying patients who are most likely to respond to treatment, potentially informing treatment decisions and improving outcomes.

Nomogram development and predictive models

The study also presented a nomogram model incorporating the TyG index, along with other prognostic factors such as the Eastern Cooperative Oncology Group performance status and programmed cell death ligand 1 (PD-L1) expression, to predict survival outcomes at 12, 15, and 18 months. The model demonstrated a high predictive accuracy, with a concordance index (c-index) of 0.779 in the validation set. This innovative approach integrates multiple clinical and metabolic factors to improve prognostication and guide therapeutic decisions, offering clinicians a practical tool for personalized treatment planning.

In future research, multi-center collaborative studies with other medical institutions are needed to further validate the predictive performance of the nomogram (such as C-index and calibration curve) in an independent cohort of advanced GC. If overfitting is found, regularization methods (such as least absolute shrinkage and selection operator regression) or machine learning algorithms (such as random forest) will be used to optimize variable selection and enhance the generalization ability of the model.

Mechanisms linking TyG to cancer progression and immune function

The study offers valuable insights into how the TyG index may be linked to cancer progression through metabolic pathways. Insulin resistance, as reflected by the TyG index, can foster a pro-inflammatory environment, impair immune function, and enhance the ability of tumor in proliferation and metastasis. A high TyG index (reflecting insulin resistance) may promote tumor cell proliferation and inhibit apoptosis by activating the phosphatidylinositol 3-kinase-protein kinase B-mammalian target of rapamycin pathway[13]. The overactivation of this pathway can lead to the enrichment of immunosuppressive cells (such as regulatory T cells and M2-type macrophages), thereby weakening the anti-tumor activity of cluster of differentiation 8 positive T cells[14,15]. Insulin resistance upregulates pro-inflammatory factors (such as interleukin-6 and tumor necrosis factor-α) through the nuclear factor kappa-B pathway, creating a chronic inflammatory microenvironment that promotes angiogenesis and inhibits the efficacy of immune checkpoint inhibitors (such as PD-1)[16-21]. An elevated TyG index may exacerbate this process, further reducing the response rate to immunotherapy. By monitoring the TyG index, clinicians can potentially assess the metabolic status of patients and predict how these factors may influence tumors with regard to growth and response to treatment. Moreover, improving the metabolic health of patients with high TyG indices could become a potential therapeutic strategy to enhance the efficacy of immunotherapy.

CLINICAL APPLICATION AND GUIDING EFFECT

The results from the study by Yao et al[12] present several key clinical implications. The incorporation of the TyG index into routine clinical practice may enable clinicians to refine their approach to the treatment of advanced GC. Key applications include the following.

Improved prognostic stratification

The ability to predict the prognosis of GC patients with greater accuracy allows for better patient stratification. The TyG index can assist in identifying patients who are more likely to experience favorable treatment outcomes, as well as those who may derive benefit from alternative therapies. For instance, patients with high TyG indices could be prioritized for more aggressive treatment regimens, while patients with low TyG indices may require closer monitoring or be considered for experimental therapies.

Personalized treatment planning

Personalized medicine is a cornerstone of modern oncology, and the TyG index offers a promising tool for tailoring treatment strategies. By using the TyG index in combination with other clinical parameters, clinicians can design individualized treatment regimens based on metabolic and immune status in patients. This approach not only optimizes therapeutic efficacy but also minimizes unnecessary treatments and side effects, leading to improved patient quality of life.

Monitoring metabolic health and immune function

The TyG index serves as a simple and cost-effective tool for monitoring both metabolic health and immune function. Insulin resistance is closely associated with immune dysfunction, thereby potentially diminishing the capacity of the body to mount an effective anti-tumor immune response. By regularly assessing the TyG index, clinicians can monitor changes in the metabolic profile in patients, adjusting treatment regimens as needed to ensure optimal outcomes. Furthermore, the TyG index could be used in combination with other immune-related biomarkers, such as PD-L1 expression, to further personalize immunotherapy strategies.

Guiding the use of immunotherapy

The TyG index could serve as a key marker for guiding decisions regarding the use of immunotherapy in advanced GC. By predicting which patients are more likely to respond to immune checkpoint inhibitors, clinicians can select patients who will derive the most benefit from these treatments. In contrast, patients with low TyG indices who may have a lower likelihood of benefiting from immunotherapy could be considered for alternative therapies to improve the efficiency and effectiveness of treatment plans.

Optimizing the use of combination therapies

The TyG index can further contribute to the optimization of combination therapies, in which multiple treatment modalities, such as immunotherapy and chemotherapy, are used concurrently. By predicting which patients are more likely to benefit from combination therapies, the TyG index may assist clinicians in designing treatment regimens that optimize therapeutic efficacy while minimizing potential adverse effects.

FUTURE RESEARCH DIRECTIONS

While the study by Yao et al[12] offers compelling evidence for the role of the TyG index in predicting the prognosis of advanced GC, several areas require further investigation. Future research should focus on innovative directions to fully explore the potential of the TyG index in cancer therapy. These innovative directions include the following.

Mechanistic research on TyG and cancer progression

The exact biological mechanisms by which the TyG index influences cancer progression and treatment response remain unclear. Future mechanism research can combine animal models with in vitro experiments, for instance, observing the changes in tumor growth and immune cell infiltration in insulin-resistant mouse models, or using single-cell sequencing technology to analyze the functional differences of immune cell subsets (such as T cells and macrophages) in the tumor microenvironment of patients with high/low TyG index. Additionally, metabolomics analysis can reveal the regulatory effects of TyG index-related metabolites (such as free fatty acids and inflammatory factors) on the expression of immune checkpoints. Investigating the role of metabolic pathways in cancer progression will provide valuable insights into how the TyG index can be leveraged for better patient management.

Exploring TyG in different cancer types

The TyG index has shown promise as a prognostic marker in GC, but its applicability across other malignancies remains to be explored. Future studies should examine the role of the TyG index across diverse types of cancer, including colorectal, lung, and breast cancers. If validated in multiple cancer types, the TyG index could serve as a universal biomarker for assessing treatment outcomes and guiding therapy selection across a broad range of cancers. Meanwhile, the association between the TyG index and tumor molecular subtypes (such as microsatellite instability and driver gene mutations) should be explored to determine its predictive efficacy in different subgroups.

Innovative multi-biomarker models

One of the most exciting research directions is the development of multi-biomarker models that combine the TyG index with other clinical, metabolic, and genomic markers. Integrating TyG with markers of immune function, such as PD-L1 expression, circulating tumor DNA (ctDNA), and tumor mutational burden (TMB), could enhance prognostication and improve the ability to predict treatment outcomes. These multi-biomarker models would allow for a more comprehensive approach to patient management, leading to more personalized and effective treatment strategies. The combination of TyG with PD-L1, ctDNA, and TMB to construct a dual biomarker model can better exert a synergistic effect, as shown in Table 1[22-24].

Table 1 Triglyceride-glucose index in combination with three other biomarkers[22-24].

Biomarker	Role in tumor immunity	Complementary role in combination with TyG	Ref.
TyG	Reflecting metabolism-immune interaction
TMB	Reflecting tumor antigen load	Predicting the sensitivity to immunotherapy	Cristescu et al[22]
PD-L1	Reflecting immune checkpoint status	Guiding the selection of immunotherapy	Le et al[23]
ctDNA	Reflecting real-time monitoring of tumor load	Dynamic assessment of treatment response	Tie et al[24]

TyG: Triglyceride-glucose; TMB: Tumor mutational burden; PD-L1: Programmed cell death ligand 1; ctDNA: Circulating tumor DNA.

Prospective and longitudinal studies

The current study was retrospective, and prospective studies are needed to confirm the findings. Future prospective studies should incorporate the design of dynamic monitoring of the TyG index, such as multiple measurements of this indicator before treatment, during treatment, and during follow-up, to assess its temporal association with survival outcomes. Longitudinal studies could contribute to validating the TyG index as a robust predictor of long-term survival and treatment response. Additionally, in combination with biobank resources, the interaction between the TyG index and the dynamic changes in metabolomics and the immune microenvironment should be explored.

Targeting insulin resistance for cancer therapy

A truly innovative direction for future research is exploring the possibility of targeting insulin resistance itself as a therapeutic strategy. If the TyG index proves to be a reliable indicator of treatment response, interventions aimed at improving insulin sensitivity and metabolic health could enhance the effectiveness of immunotherapy. This could involve lifestyle changes, pharmacological interventions, or a combination of both, with the goal of optimizing the metabolic profile to support a more robust immune response to cancer.

Future studies should design randomized controlled trial protocols to evaluate whether intervention measures to improve insulin sensitivity (such as metformin and lifestyle interventions) can enhance the efficacy of immunotherapy. In addition, the combination strategies of metabolic regulatory drugs (such as sodium-glucose co-transporter 2 inhibitors) and PD-1 inhibitors should be explored, and their synergistic effects on the TyG index and survival outcomes should be analyzed.

Examining the role of TyG in early-stage cancer

The current study primarily focuses on advanced GC, demonstrating that the TyG index serves as a long-term predictive marker for the efficacy of immunotherapy combined with chemotherapy, and patients with a high TyG index tend to exhibit a more favorable prognosis[12]. However, in a health checkup cohort study, the TyG index is considered to be a potential new predictive biomarker for GC, and its elevation is significantly associated with GC[9]. This may involve the “double-edged sword” characteristic of the TyG index, where metabolic stress in advanced patients may activate compensatory immune responses, while persistent insulin resistance in precancerous lesions directly promotes malignant transformation.

A high TyG index in advanced patients may reflect enhanced metabolic reserve, supporting more aggressive treatment tolerance rather than directly inhibiting tumor progression. However, this hypothesis needs to be verified through prospective studies. The role of the TyG index in early-stage cancer is also not to be ignored and may be groundbreaking. If insulin resistance plays a role in the early development of tumors, the TyG index can serve as an early biomarker to detect cancer risk and initiate preventive measures. This early identification can significantly improve survival outcomes through timely intervention, but its predictive role in early-stage cancer needs to be verified through more prospective studies.

Global validation of TyG as a standardized biomarker

Another critical area for future research is the global validation of the TyG index. As the study by Yao et al[12] used a cutoff value of 1.79 for the TyG index, future research should investigate whether this threshold is universally applicable across different populations and healthcare settings. This would contribute to establishing the TyG index as a globally recognized prognostic biomarker, thereby facilitating its routine clinical application.

Based on the heterogeneity of the population, future research should explore the impact of dietary habits in different geographical regions (such as Asia vs Europe and America) on the TyG index. For instance, a high-carbohydrate diet may be more likely to cause insulin resistance, while a high-fat diet may affect the clinical threshold of the TyG index. It is important to note that when applying the TyG index, local metabolic epidemiological data should be taken into account to avoid a one-size-fits-all clinical application. Moreover, it is necessary to verify whether the TyG threshold (such as 1.79) is applicable to populations with different dietary patterns or to explore the TyG threshold suitable for specific populations.

CONCLUSION

The study by Yao et al[12] highlights the TyG index as a promising prognostic marker for advanced GC patients undergoing immunotherapy combined with chemotherapy. Its ability to predict both PFS and OS presents an opportunity for more personalized and effective treatment strategies in clinical oncology. The TyG index, a simple and accessible marker of insulin resistance, could become a cornerstone in prognostic assessments, guiding clinicians in making more informed treatment decisions. However, further research is required to explore the underlying mechanisms, validate the findings in other cancers, and refine its clinical application. The potential of the TyG index in combination with other biomarkers offers exciting prospects for advancing cancer therapy and improving patient outcomes. Future studies should focus on addressing the gaps in knowledge, including the mechanisms linking insulin resistance to immune dysfunction, validating the TyG index across a range of cancer types, and exploring its integration into more comprehensive prognostic models. Ultimately, this research could pave the way for personalized treatment strategies that improve survival rates for GC patients and those with other malignancies. By continuing to optimize the use of biomarkers such as the TyG index, we move closer to achieving more individualized, effective cancer treatments that can revolutionize outcomes for patients worldwide. The innovative directions outlined for future research hold the potential to reshape cancer therapy, ushering in a new era of precision medicine that not only enhances survival rates but also improves quality of life for patients battling cancer.