Lung adenocarcinoma is rising, especially in Asia. Lung cancer causes more deaths worldwide than any other cancer, and China accounts for nearly one-third of global cases. Lung adenocarcinoma - which makes up 40-50% of lung cancers in China - has shown the fastest increase in incidence, particularly among non-smokers and East Asian populations, suggesting that factors beyond smoking may be important drivers.
Metabolic health may influence cancer risk. With changing lifestyles and diets, metabolic syndrome - a cluster of conditions including obesity, high triglycerides, high blood sugar, and high blood pressure - is becoming increasingly common. Insulin resistance (IR), a state where the body's cells become less responsive to insulin, is central to metabolic syndrome and has been linked to the development of several cancers.
The biological case for a link. Insulin resistance promotes elevated levels of insulin and insulin-like growth factor 1 (IGF-1) in the bloodstream. IGF-1 is a growth signal that encourages cells to divide and inhibits cell death - exactly the conditions that favor cancer development. Insulin resistance also promotes chronic low-grade inflammation and oxidative stress, creating a pro-cancer environment in body tissues including the lungs.
A simpler way to measure insulin resistance. The gold standard for measuring insulin resistance (the hyperinsulinemic-euglycaemic clamp test) is complex, expensive, and impractical for routine screening. The triglyceride-glucose (TyG) index - calculated from a simple fasting blood test measuring triglycerides and glucose - offers a practical, low-cost alternative that can be calculated from routine blood work already collected in most clinical settings.
The TyG index: a formula from two blood tests. The TyG index is calculated as the natural log of (triglycerides in mg/dL multiplied by fasting plasma glucose in mg/dL, divided by 2). This simple formula captures the combined effect of elevated blood fats and blood sugar - both markers of impaired metabolic function and insulin resistance - in a single numerical value derived from two widely available lab tests.
TyG-BMI: adding body weight to the picture. The TyG-BMI index multiplies the TyG index by body mass index (BMI). This derivative accounts for the contribution of general obesity to insulin resistance and metabolic dysfunction, recognizing that excess body fat is independently associated with both insulin resistance and cancer risk.
TyG-WC: incorporating abdominal obesity. TyG-WC multiplies the TyG index by waist circumference. Abdominal (central) obesity - measured by waist circumference - is considered a stronger predictor of metabolic risk than BMI alone, because visceral fat deposited around the abdominal organs drives insulin resistance and inflammation more directly than subcutaneous fat.
TyG/HDL-C: the lipid balance approach. The TyG/HDL-C index divides the TyG value by high-density lipoprotein cholesterol (HDL-C, the 'good' cholesterol). Low HDL-C reflects impaired lipid metabolism and loss of the anti-inflammatory, antioxidant functions of HDL. Dividing by HDL-C therefore captures both the pro-cancer effect of high triglycerides and glucose and the loss of protective lipid functions simultaneously.
200 cancer patients and 500 matched controls. This case-control study enrolled 200 patients with histologically confirmed lung adenocarcinoma who underwent surgery at a thoracic surgery center in China, along with 500 age- and sex-matched healthy controls drawn from the same hospital's routine health examination program during the same time period (September 2023 to September 2024).
Comprehensive metabolic measurements. All participants had fasting blood tests measuring glucose, triglycerides, total cholesterol (TC), LDL-C, HDL-C, HbA1c (a measure of long-term blood sugar control), and C-peptide. Anthropometric measurements including height, weight, and waist circumference were taken by trained nurses following standardized protocols. Blood pressure was also recorded.
Statistical methods to control for confounders. Multivariable logistic regression was used to calculate the odds of lung adenocarcinoma associated with each TyG-related index, adjusting for age, BMI, smoking, alcohol use, blood pressure, HbA1c, LDL-C, and total cholesterol. Restricted cubic spline (RCS) analysis assessed whether associations were linear or followed a threshold pattern across the full range of TyG values.
Predictive accuracy tested with ROC analysis. Receiver operating characteristic (ROC) curves and area under the curve (AUC) values were calculated for each TyG-related index to evaluate how well each measure could discriminate between lung cancer cases and healthy controls. The Youden index was used to identify optimal cut-off values balancing sensitivity and specificity.
Groups were well matched for age and BMI. Cases and controls were similar in age (mean 66.8 versus 65.2 years), sex distribution (about 60% male in both groups), and BMI (25.1 versus 24.7 kg/m2). This matching confirms that observed differences in metabolic indices are not simply due to differences in age or body weight.
Significant metabolic differences in cancer patients. Compared to healthy controls, lung adenocarcinoma patients had significantly higher systolic blood pressure (134.8 versus 130.5 mmHg), HbA1c (5.8% versus 5.6%), LDL cholesterol, and total cholesterol. They also had higher rates of current smoking (26.0% versus 18.0%) and alcohol consumption (27.5% versus 20.0%).
All TyG-related indices were elevated in cancer patients. The TyG index was significantly higher in cancer patients (8.78 versus 8.65 in controls). All three derivative indices - TyG-BMI, TyG-WC, and TyG/HDL-C - were also significantly elevated in the lung adenocarcinoma group (all p less than 0.05), suggesting a broad pattern of metabolic dysfunction associated with the disease.
Strongest contrast seen in TyG/HDL-C. The TyG/HDL-C ratio showed the largest absolute difference between groups (8.12 in cancer cases versus 7.48 in controls) and had the widest spread of values in the cancer group, reflecting greater variability in combined triglyceride-glucose-HDL metabolic status among lung cancer patients compared to healthy individuals.
Robust associations survive adjustment for confounders. After adjusting for age, BMI, smoking, alcohol use, blood pressure, HbA1c, LDL-C, and total cholesterol, all four TyG-related indices remained independently and significantly associated with lung adenocarcinoma risk. This means the associations cannot be explained away by known risk factors.
TyG/HDL-C shows the strongest effect. The fully adjusted odds ratio for TyG/HDL-C was 2.15 per standard deviation increase (95% confidence interval 1.51-3.07, p less than 0.001). In practical terms, individuals with TyG/HDL-C values one standard deviation above average had more than twice the odds of lung adenocarcinoma compared to those at average levels, after controlling for all other measured risk factors.
TyG-WC also shows a strong association. TyG-WC had an adjusted odds ratio of 1.79, making it the second-strongest predictor. The combination of insulin resistance with central obesity captured by this index reflects the particular cancer-promoting role of abdominal fat accumulation in the metabolic landscape of lung adenocarcinoma.
Dose-response relationship: higher index, higher risk. Restricted cubic spline analysis showed that lung adenocarcinoma risk increased progressively as TyG values rose, with no clear threshold below which there was no risk elevation. The TyG/HDL-C curve showed the steepest rise, particularly above the 75th percentile, suggesting that the highest-risk individuals are those with the greatest combined metabolic dysregulation.
TyG/HDL-C achieves the best discrimination. Among all the indices tested, TyG/HDL-C achieved the highest area under the ROC curve (AUC of 0.851), meaning it correctly distinguished lung adenocarcinoma cases from healthy controls 85.1% of the time when used as a predictive test. An AUC of 0.851 represents good-to-excellent discriminatory power for a simple blood test marker.
TyG-WC is the second-best predictor. TyG-WC achieved an AUC of 0.827, reflecting the added value of incorporating waist circumference as a measure of abdominal obesity. TyG-BMI performed slightly less well (AUC 0.785), while the basic TyG index alone achieved an AUC of 0.775.
Comparison with existing screening tools. An AUC of 0.851 for TyG/HDL-C is clinically meaningful, particularly given that this measure can be derived entirely from standard fasting blood tests and a single waist or weight measurement. Many expensive or invasive cancer screening approaches achieve similar or even lower discrimination in practice, making TyG/HDL-C a potentially valuable low-cost addition to risk stratification in clinical settings.
Potential utility in resource-limited settings. Because the TyG index and its derivatives require only routine fasting blood tests, they could be particularly valuable in primary care settings or lower-resource environments where advanced imaging or molecular diagnostics are unavailable. A high TyG/HDL-C value could prompt clinicians to offer enhanced lung cancer surveillance to at-risk patients who might otherwise not be identified.
IGF-1 as a cancer growth signal. One of the main proposed mechanisms linking insulin resistance to cancer is hyperinsulinemia - chronically elevated blood insulin levels. High insulin stimulates the liver and other tissues to produce excess IGF-1, a powerful mitogen (growth promoter) that drives cell division and blocks apoptosis (programmed cell death). These effects can accelerate the growth of pre-malignant cells in the lung.
Inflammation and oxidative stress create a pro-cancer environment. Insulin resistance is associated with chronic low-grade systemic inflammation - elevated levels of inflammatory molecules like TNF-alpha, IL-6, and C-reactive protein. This inflammatory state damages DNA, promotes abnormal cell growth, and suppresses immune surveillance, all of which favor cancer initiation and progression in the lungs and other organs.
Dyslipidemia fuels cancer cell energy demands. Elevated triglycerides and altered lipoprotein metabolism in insulin-resistant individuals provide a ready supply of lipid molecules that rapidly dividing cancer cells can use for membrane production and energy. The loss of HDL's anti-inflammatory functions - captured in the TyG/HDL-C index - removes an additional layer of cancer protection.
Why adenocarcinoma may be particularly metabolically sensitive. Lung adenocarcinoma has a higher prevalence in non-smokers, women, and East Asian populations - groups with lower rates of smoking-associated mutations but potentially higher exposure to metabolic risk factors from lifestyle and diet. This subtype's biology may make it more vulnerable to the growth-promoting effects of insulin resistance than other lung cancer histological types.
A new use for routine blood test data. This study demonstrates that the TyG index and its derivatives - derived entirely from standard fasting blood work that is already collected in routine clinical care - are meaningfully associated with lung adenocarcinoma risk. This opens the possibility of using existing metabolic data more systematically to identify individuals who should be considered for enhanced lung cancer screening.
Complementing traditional risk factors. The associations remained significant after adjusting for smoking, the strongest established risk factor for lung cancer. This suggests TyG-related indices add independent value beyond what smoking history alone captures, which is particularly important for identifying at-risk non-smokers who currently fall outside most lung cancer screening eligibility criteria.
Limitations requiring caution. As a case-control study, this design cannot establish causality - it is possible that cancer itself causes metabolic changes rather than the reverse. The study was conducted at a single hospital in northeastern China, limiting generalization. Only one-time blood measurements were taken, which may not reflect long-term metabolic exposure. Dietary information was not collected, leaving an important potential confounder unaddressed.
The path forward. Prospective cohort studies that follow healthy individuals over time will be needed to confirm whether high TyG indices truly precede and predict lung cancer development. Mechanistic studies are also needed to directly test whether reducing insulin resistance through lifestyle change or pharmacological intervention lowers lung cancer risk. These next steps could establish the TyG index as both a practical risk stratification tool and a modifiable therapeutic target.