Impact statements

  • Real world data suggest that serum lipids could predict irAEs and antitumour effects in SCLC patients receiving PD-L1 inhibitors as first line treatment.

  • Clinicians and pharmacists can predict subgroups of SCLC patients who will most benefit from immunotherapy and who will suffer irAEs according to their serum lipid levels.

Introduction

Small cell lung cancer (SCLC) is an aggressive disease that is characterized by rapid growth, early metastasis, and recurrence after treatment [1]. Patients with SCLC are typically divided into those with limited-stage (LS) disease and those with extensive-stage (ES) disease by using the Veterans Administration Lung Study Group (VALG) staging system [2]. Most patients with ES-SCLC at presentation have a poor prognosis, and they have a low survival rate [3].

Immune checkpoint inhibitors (ICIs) have improved survival outcomes for many advanced cancer patients [4,5,6,7]. Recently, remarkable developments have been made in immunotherapy-based approaches for SCLC, such as programed death-ligand 1 (PD-L1) inhibitors in combination with chemotherapy for first-line treatment of ES-SCLC [8]. Immunotherapy provides new hope for SCLC patients, but a small subset of patients benefit from it, and it also has an unprecedented toxicity profile. The toxicities, broadly referred to as immune-related adverse events (irAEs), can affect any organ system [9]. These irAEs are generally mild and can be managed, but some irAEs may be severe and even life-threatening [10, 11]. Along with the increasing application of immunotherapy in clinical practice, irAEs should not be overlooked. Therefore, predicting biomarkers for irAEs and the anti-tumour effects of the drugs is crucial for SCLC patients receiving ICI treatment.

An unbalanced lipid profile is often associated with cardiovascular diseases. Moreover, it might promote tumorigenesis, metastasis, recurrence, and even drug resistance, impacting the overall survival of patients with cancer [12,13,14,15]. Recent studies have shown the prognostic impact of serum lipid levels on the outcome of patients undergoing immunotherapy [16,17,18]. Cholesterol and other components of the lipid profile could become new biomarkers to predict the efficacy of ICIs and may also become new biomarkers for irAEs. However, there has not been a definitive study on the relationship between serum lipids and the responses of SCLC patients to PD-L1 inhibitors.

Aim

Clinical and molecular markers that can predict responses to anti-PD-L1 therapy will help clinicians and pharmacists predict the occurrence of irAEs and the anti-tumour effects in cancer patients. We conducted a single centre observational study that aimed to determine whether these serum lipids could predict irAEs and the anti-tumour effects in SCLC patients who received PD-L1 inhibitors as first-line treatment.

Ethics approval

This study was approved by the Ethics Committee of Shanghai Pulmonary Hospital (Ethical approval number: K24-325).

Method

Study design and patient population

The study population consisted of 124 patients who were diagnosed with SCLC and who received first-line chemotherapy combined with PD-L1 inhibitors at Shanghai Pulmonary Hospital from August 2020 to December 2023. Eligible patients met the following criteria: (1) age ≥ 18 years; (2) histological confirmation of SCLC; (3) confirmed record of at least one cycle of PD-L1 inhibitors and etoposide with platinum administration as first-line treatment; (4) serum lipid levels assessed before immunotherapy.

Data extraction

The demographic and clinical characteristics, including age, sex, smoking history, tumour stage, Eastern Cooperative Oncology Group performance status (ECOG PS), diabetes status, cardiovascular disease status, hypertension status, body mass index (BMI) (kg/m2), total cholesterol (TC) (mmol/L), triglycerides (TG) (mmol/L), high-density lipoprotein cholesterol (HDL-C) (mmol/L), low-density lipoprotein cholesterol (LDL-C) (mmol/L), apolipoprotein A-1 (ApoA-1) (g/L), apolipoprotein B (ApoB) (g/L), lipoprotein (a) (Lp(a)) (mg/L), small-dense LDL-C (sdLDL-C) (mmol/L), and their six derivatives, non-high-density lipoprotein cholesterol (non-HDL-C) (mmol/L), TG/HDL-C, non-HDL-C/HDL-C, HDL-C/TC, LDL-C/TC and AopB/ApoA-1, were retrospectively extracted from institutional electronic medical records.

The response to immunotherapy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) Version 1.1. The objective response rate (ORR) was defined as the sum of complete response (CR) and partial response (PR). The disease control rate (DCR) was defined as the sum of CR, PR and stable disease (SD). Progression-free survival (PFS) was calculated as the time from the initiation of treatment to the occurrence of progressive disease (PD) or death. Data on the effectiveness and irAEs of PD-L1 inhibitors were collected from clinical notes, hospital records, and laboratory data.

Two authors used a standardized form to gather patient-related information, and the two result sets were checked against each other to ensure accuracy and reduce the risk of bias.

Statistical analysis

Continuous variables are expressed by the median and interquartile range (IQR; 25th-75th percentile), while categorical variables are presented as n (%). Student’s t-test and the chi-square test were used to compare continuous and categorical variables, respectively. Factors associated with clinical effects were detected by logistic regression. Survival and subgroup analyses were performed using the Kaplan–Meier method and log-rank test. The discriminative ability of serum lipids for clinical outcomes was evaluated as the areas under receiver operating characteristic (ROC) curves (AUC). Statistical processing was performed via IBM SPSS 23.0 (SPSS, Chicago, IL, USA) as well as GraphPad Prism 9.5 (GraphPad Software, La Jolla, CA, USA). When p value < 0.05, the difference is considered to be statistically significant.

Results

Baseline characteristics

A total of 124 patients were included in this study. Most were males (93.6%). The median age was 65 (IQR 59–70) years, and 53.2% of the patients were over 65. A smoking history was present in 71.0% of the patients. Most patients had ES-SCLC (82.3%). A total of 91.13% of the patients had an ECOG PS ≤ 1. The median BMI was 23.99 (IQR 21.13–25.96) kg/m2, and 39.5% of the patients had BMI ≥ 25 kg/m2.

Table 1 presents an overview of the clinical features of the enrolled patients, including their serum lipid levels (median and IQR). The median TG, TC, HDL-C, LDL-C, non-HDL-C, ApoA-1, ApoB, Lp(a) and sdLDL levels were 1.36 mmol/L, 4.22 mmol/L, 1.08 mmol/L, 2.79 mmol/L, 3.18 mmol/L, 1.39 g/L, 0.85 g/L, 182.75 mgl/L and 0.69 mmol/L, respectively. The median TG/HDL-C, non-HDL-C/HDL-C, HDL-C/TC, LDL-C/TC and ApoB/ApoA-1 ratios were 1.37, 3.09, 0.24, 0.66 and 0.63, respectively.

Table 1 Baseline characteristics
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Serum lipid levels can be influenced by various factors, such as lifestyle habits and genetics. The 124 patients in this study had wide ranges of serum lipid levels. We dichotomized the patients around the median of each serum lipid level, yielding low and high groups for each.

Associations between serum lipids and irAEs

A total of twenty patients (16.1%) in this study experienced any grade of irAE. Two patients discontinued treatment due to intolerant adverse reactions. No treatment-related deaths occurred. Through multivariate logistic analysis, we found that the TG/HDL-C ratio was an independent risk factor for irAEs (hazard ratio (HR): 16.894, 95% confidence interval (CI): 1.065–268.050, p = 0.045) (Table 2). The ROC analysis demonstrated a moderate ability of the TG/HDL-C ratio to predict irAEs (AUC: 0.6938, 95% CI: 0.557–0.831, p = 0.0062) (Fig. 1).

Table 2 Univariate and multivariate logistic regression for immune-related adverse events
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Fig. 1
figure 1

Predictive ability of TG/HDL ratio for irAEs in SCLC patients by ROC curve. ROC receiver operating characteristic, irAEs immune related adverse events, TG triglycerides, HDL-C high-density lipoprotein cholesterol

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Associations between serum lipids and anti-tumour effects of PD-L1 inhibitors

In patients with an evaluable response (122 patients of the study), tumour response analysis indicated that 53 (43.4%) patients achieved PR, and 44 (36.1%) patients achieved SD, yielding the ORR of 43.4% and the DCR of 79.5% (Table 1). Through logistic analyses, we found that the association between serum lipid levels and the ORR did not reach statistical significance (Supplementary Table 1), but we found that LDL-C and non-HDL-C were reliable predictors of the DCR (HR: 16.309, 95% CI:1.207–220.326, p = 0.036; HR:34.484, 95% CI: 1.840–646.378, p = 0.018) (Supplementary Table 2). The ROC curve analyses demonstrated a poor ability of LDL-C and non-HDL-C to predict the DCR (AUC: 0.5786, 95% CI: 0.4532–0.7039, p = 0.227; AUC: 0.5732, 95% CI: 0.4506–0.6958, p = 0.26) (Supplementary Fig. 1).

Seventy-seven patients (62.1%) experienced any PFS event, and the median PFS (mPFS) was 6.23 months. The 6-month and 1-year PFS rates were 58.4 and 14.3%, respectively. As shown in Fig. 2, LS-SCLC patients had longer mPFS than ES-SCLC patients (17.0 months vs. 6.67 months, Log Rank p = 0.0003) (Fig. 2A). Compared to the TG-high group (mPFS 6.67 months), the TG-low group had a significantly longer mPFS (9.17 months) (Log Rank p = 0.044) (Fig. 2B). The HDL-C-high group had a longer mPFS than the HDL-C-low group (10.03 months vs 6.67 months, Log Rank p = 0.043) (Fig. 2C). Notably, the TG/HDL-C-low group had longer mPFS than the TG/HDL-C-high group (9.17 months vs 6.33 months, Log Rank p = 0.023) (Fig. 2D). Through multivariate Cox regression analysis, we found that tumour stage and HDL-C level were reliable predictors of PFS (HR: 4.619, 95% CI: 1.860–11.467, p = 0.001; HR: 2.988, 95% CI: 1.500–5.950, p = 0.002) (Table 3).

Fig. 2
figure 2

Kaplan–Meier survival curves for PFS. (A) PFS for patients compared among the LS-SCLC group and ES-SCLC groups. (B) PFS for patients compared among the TG-high group and TG-low groups. (C) PFS for patients compared among the HDL-C-high group and HDL-C-low groups. (D) PFS for patients compared among the TG/HDL-C-high group and TG/HDL-C-low groups. PFS Progression-free survival, LS limited-stage, ES extensive-stage, TG triglycerides, HDL-C: high-density lipoprotein cholesterol

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Table 3 Univariate and multivariate Cox regression for progression-free survival
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Associations between irAEs and anti-tumour effects of PD-L1 inhibitors

After adjusting for potential confounding factors in logistic multivariate analysis, we further investigated the correlation between irAEs and anti-tumour effects of PD-L1 inhibitors. For patients of the high TG/HDL-C ratio, the ORR significantly differed between patients who experienced any irAEs and those who did not (p = 0.0139), but no significant difference was detected between the DCR and any irAEs (Table 4).

Table 4 Short-term effectiveness in the irAEs group and no irAEs group for patients of the high TG/HDL-C ratio
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Discussion

In the present study, we observed that the impact of the serum lipid profile on the clinical outcomes of patients with SCLC treated with ICIs may vary. Our results showed that the TG/HDL-C ratio had a moderate ability to predict irAEs. High HDL-C levels, low TG levels and low TG/HDL-C ratios at baseline were correlated with better outcomes, and HDL-C was a reliable predictor of PFS in SCLC patients received first-line chemotherapy combined PD-L1 inhibitors. In addition, for patients of the high TG/HDL-C ratio, the ORR significantly differed between patients who suffered from any irAEs and those who did not.

Lipoproteins and serum lipids have been reported to be associated with the morbidity and mortality of cardiovascular diseases and cancer [19, 20]. Lipids have been linked to the fundamental mechanisms underlying SCLC development [21,22,23]. In addition, the serum lipid profile is useful for predicting the prognosis of SCLC patients [24, 25]. Moreover, lipid metabolism signalling plays a key role in the tumour microenvironment and immunotherapy [26]. Cholesterol and other lipids are considered determinants of several alterations occurring in immune cells [27,28,29,30].

In terms of ICI therapeutic efficacy, the serum ApoA-1 and TG levels are remarkable independent prognostic factors for overall survival (OS) in advanced intrahepatic cholangiocarcinoma patients treated with anti-PD-1 therapy [18]. High HDL-C levels at baseline and early elevation of HDL-C levels are correlated with better outcomes in metastatic colorectal cancer patients treated with anti-PD-1 therapy [31]. Early elevated TC, LDL-C, ApoA-1, and ApoB levels were significantly associated with a better ORR in recurrent or metastatic nasopharyngeal carcinoma patients treated with anti-PD-1 therapy [32]. In a retrospective study, the favourable impact of passive cholesterol diffusion on clinical outcome might reflect its main conformation in mature HDL particles, which potentially shapes the inflammatory response, and ultimately promotes ICI efficacy [33]. A multicentre cohort study revealed that a lipid score that defined subgroups of patients with advanced solid tumours who benefit differently from ICIs, where the poor-risk profile (TC < 200 and TG ≥ 150 mg/dl) represented an independent poor prognostic factor for both PFS and OS [34].

In terms of irAEs, through non-targeted lipidomics and semi-targeted lipid quantification analysis, 9 lipids exhibited a good AUC according to the ROC curve for prediction and could be utilized to develop a rapid and effective prediction model for identifying irAEs in advanced non-small cell lung cancer patients treated with first-line chemotherapy combined with immunotherapy [35].

Serum lipid levels could be predictive markers for the response of cancer patients to ICI therapy and their prognosis. However, there has not been a definite study on the relationship between the serum lipid profile and the response of SCLC patients to PD-1 inhibitors. Our research indicated that the TG/HDL-C ratio could be an independent predictive marker for irAEs and that HDL-C was a reliable predictor of PFS in SCLC patients who were treated with first-line chemotherapy combined with anti-PD-L1 therapy.

We acknowledge some limitations of this study. The major limitation was that the study was a single centre observational study, and there may be selection bias in the absence of long-term serum lipid levels after immunotherapy. Additionally, it was a small study. Serum lipid levels can be influenced by various factors, such as lifestyle habits and genetics. Further studies are needed to establish more reliable and independent data, because predicting biomarkers for immunotherapy is crucial for cancer patients.

Conclusion

Serum lipids predicted anti-PD-L1 therapy response in a study including a total of 124 patients with SCLC, and the TG/HDL-C ratio and HDL-C level may be independent predictors of clinical outcomes. These findings can help clinicians and pharmacists predict the occurrence of irAEs and anti-tumour effects based on serum lipid levels.