Increasing serum complement component 1q is associated with worse prognosis in advanced non-small cell lung cancer treated with immune checkpoint inhibitors: a single-center, retrospective study

Introduction

Lung cancer is one of the malignant tumors with the highest morbidity and mortality all over the world, of which about 85% are non-small cell lung cancer (NSCLC). Immune checkpoint inhibitors (ICIs), represented by programmed cell death protein-1 (PD-1)/programmed cell death ligand-1 (PD-L1) antibodies and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) antibodies, have become the first-line standard treatment for patients with advanced NSCLC and significantly improve survival (1). Unfortunately, most of the patients do not respond to the treatment and no accurate biomarkers able to identify these patients have been discovered yet. There are three main prognostic markers in NSCLC treated with ICIs, including clinical characteristics, blood-based biomarkers and genetic markers. Clinical characteristics such as Eastern Cooperative Oncology Group performance status (ECOG-PS) and age which predict efficacy have been extensively studied. Patients with ECOG-PS score ≥2 showed limited benefit from ICIs treatment, but the association between old age and efficacy of ICIs remains controversial (2-4). Studies investigating predictive blood-based biomarkers are insufficient (5,6). Moreover, blood-based biomarkers such as lactate dehydrogenase (LDH), C-reactive protein (CRP) and neutrophils to leukocytes ratio (NLR) are dynamic, the optimal time and frequency of measurements are also controversial (7-9). In terms of genetic markers, although markers represented by PD-L1 are effective in predicting the efficacy of ICIs, the detection method is difficult to be quantified and standardized (10). In addition, the detection is costly and some require tumor tissue, which is invasive (11). Therefore, a large number of clinical studies and transformational research are still needed to figure out easily accessible, cost-effective and standardized biomarkers (12,13).

Previous studies have shown that the function of anti-tumor immune cells [such as natural killer (NK) cells and CD8⁺ T cells] is significantly inhibited in advanced lung cancer patients because the tumor microenvironment (TME) contains a large number of immunosuppressive cells such as tumor-associated macrophages (TAMs) and regulatory T cells (Tregs) (14,15). Our former research revealed that TAMs in lung adenocarcinoma (LUAD) could secrete a large amount of complement component 1q (C1q) (16), a small protein involved in inflammatory and immunological responses, suggesting that a high levels of C1q may be related to worse prognosis of such patients. Besides, Iyer et al. (17) demonstrated that C1q has an association with the efficacy of immunotherapy in patients with advanced lung cancer. In addition, considering the easy availability of serum C1q in clinical practice, the use of serum C1q for the prediction of efficacy is a promising approach. In esophageal cancer, serum baseline and post-treatment C1q have been shown to be associated with the efficacy of combined immunotherapy (18). Nevertheless, there is still a lack of studies investigating the association between serum C1q and the prognosis of NSCLC immunotherapy. This present study discovered that increasing serum C1q may be related to a worse prognosis of ICIs treatment in advanced NSCLC. We present this article in accordance with the REMARK reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-304/rc).

Methods

Study design and eligibility criteria

A retrospective study of patients with advanced NSCLC in Renmin Hospital of Wuhan University, China was conducted from July 2018 to May 2023. The inclusion criteria included: (I) pathological diagnosis of NSCLC; (II) clinical staging of IIIb–IV; (III) patients treated with ICIs, such as anti-PD-1 or PD-L1 antibody, for at least two cycles; (IV) at least one measurable target lesion. The exclusion criteria were as follows: (I) concomitant with another cancer or serious disease; (II) data of efficacy assessment was not available; (III) mixed small cell lung cancer (SCLC) histology. This study was performed in accordance with the principle of the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of Renmin Hospital of Wuhan University dated on 2022-02-18. Individual consent for this retrospective analysis was waived.

Active and passive methods were used to collect follow-up data. The active method means that patients went to the outpatient clinic or hospitalization department for follow-up regularly, and the passive method means that we followed up patients by telephone, text message, etc. To maintain accurate surveillance information, data fields relating to patient vital status, date of last contact, treatment, and recurrence were updated. Patients were followed until the date of death or the last date of follow-up (May 31, 2023). Patients who were lost to follow-up were permitted for survival analysis. A flow chart of the present study is illustrated in Figure 1. Eventually, a total of 168 patients with advanced NSCLC were enrolled in this study.

Figure 1 Flow chart of immune checkpoint inhibitors in the treatment of patients with advanced NSCLC. NSCLC, non-small cell lung cancer; ICIs, immune checkpoint inhibitors.

Data collection and outcome

Baseline characteristics, including demographic characteristics (age and sex), smoking status, ECOG-PS, metastasis (brain, bone and liver), histology type, driver gene mutation, previous treatment, and immunotherapy regimen, were collected. Blood was drawn from the patient’s periphery vein and the blood samples were sent to the hospital laboratory for testing. The data of CRP, neutrophils, and lymphocytes were collected from routine blood tests. The whole blood was centrifuged to separate the serum for the detection of C1q, albumin, globulin, and LDH. Data of C1q at baseline and 3 weeks after ICIs treatment, baseline albumin to globulin ratio (AGR), NLR, LDH, and CRP were recorded and calculated. The primary outcome was overall survival (OS) (months from first dose of ICIs to death, censored at date of last follow-up). Secondary outcome was progression-free survival (PFS) [defined as months from first dose of ICIs to clinical or radiographic progression by Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) or death, censored at date of last follow-up] and objective response rate (ORR) which was defined as rate of complete response (CR) or partial response (PR) at best response by RECIST 1.1.

Response assessments

Tumor response efficacy was determined as CR, PR, stable disease (SD), or progressive disease (PD). The overall response rate (ORR) consisted of CR and PR. The disease control rate (DCR) was composed of CR, PR, and SD in 3 months after ICIs were administered. PFS was defined as the time from the first day of immunotherapy treatment to disease progression. The OS was the time from the date on which advanced NSCLC was confirmed and first-line treatment began to the date of death, or the date of death in line with the last follow-up by the families.

Clinical data during the immunotherapy were recorded to evaluate the efficacy. All ICIs and targeted regimens were administered in standard doses, based on Chinese Society of Clinical Oncology (CSCO) guidelines. The response was assessed according to RECIST 1.1. Before analysis, efficacy was evaluated by two oncologists according to RECIST 1.1 criteria based on chest computed tomography (CT) every 4–8 weeks, and positron emission tomography (PET)/CT was also referred to if existed during the evaluation.

Statistical analysis

The normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed continuous variables were presented as means ± standard deviations and analyzed using Student’s t-test. For non-normally distributed continuous variables, medians [interquartile ranges (IQRs)] were presented and analyzed using the Mann-Whitney U test. Categorical variables were expressed as frequency (percentage, %) and analyzed using Fisher’s exact test. OS and PFS were estimated based on Kaplan-Meier methods, and compared using log-rank test. Univariate and multivariate Cox regression models were performed to analyze the correlation between clinical factors and PFS and OS, through which hazard ratio (HR) and related 95% confidence intervals (CIs) were estimated. All statistical analyses were performed in SPSS version 25.0 (IBM Corp., Armonk, NY, USA). A two-sided P values <0.05 were considered statistically significant.

Data availability

The data generated in this study are not publicly available due to information that could compromise patient privacy but are available upon reasonable request from the corresponding author.

Results

Baseline characteristics

A total of 168 patients with advanced NSCLC were included in the study, including 127 males (75.60%) and 41 females (24.40%). Thirty-five (20.83%) were ≥75 years old at the beginning of the first ICIs treatment, 51 (30.36%) had a previous history of smoking, 109 (64.88%) had LUAD, 57 (33.93%) had lung squamous cell carcinoma (LUSC), and 2 (1.19%) had NSCLC not otherwise specified (NSCLC-NOS). The results of the driving gene test in 91 patients (54.17%) could be traced back, including 46 patients with driving gene mutation and 45 patients with wild type. The details of the baseline characteristics of the patients are shown in Table 1.

Response to immunotherapy treatment

The median follow-up period was 17.1 months (IQR, 7.7–21.2 months). A total of 168 patients were accessible to clinical and imaging data for efficacy evaluation. Thirty-nine patients (23.21%) achieved an objective response (2 cases of CR, 37 cases of PR), and 111 patients (66.07%) had SD as best response. DCR of 3 months was 89.28%. In addition, of 83 patients receiving first-line ICIs-based therapy, 23 patients (27.71%) achieved an objective response (1 cases of CR, 22 cases of PR), and 55 patients (66.27%) had the best efficacy of SD, thus DCR was 93.98%.

Association of serum C1q levels and patient survival

The patients were classified into the C1q increased group and the C1q decreased group according to the trend of serum C1q after ICIs treatment. Both median PFS (mPFS) (P=0.01) and median OS (mOS) (P=0.03) of patients in C1q increased group were significantly shorter compared with those in C1q decreased group (Figure 2). Taking the mOS 18.9 months as the cutoff of prognosis and the patients were divided into over mOS group and below mOS group, receiver operating characteristic (ROC) analysis showed that baseline serum C1q yielded an area under the ROC curve (AUC) of 0.785 (95% CI: 0.711–0.869) (Figure 3). The optimal serum baseline C1q cut-off point to predict immunotherapy prognosis was 216.2 mg/L, which gave a sensitivity of 66.7% and a specificity of 84.9% (P<0.001).

Figure 2 Correlation between serum C1q levels trends and survival of patients with advanced NSCLC treated with immunotherapy. (A) PFS of patients whose serum C1q decreased (mPFS =8.6 months, 95% CI: 7.8–9.4) or increased (mPFS =5.6 months, 95% CI: 4.6–6.6) after ICIs treatment. Patients whose serum C1q level increased after ICIs treatment showed shorter mPFS (HR =1.554, 95% CI: 1.07–2.10, P=0.01); (B) OS of patients whose serum C1q decreased (mOS =19.5 months, 95% CI: 17.7–21.3) or increased (mOS =16.5 months, 95% CI: 14.5–18.5) after ICIs treatment. Patients whose serum C1q level increased after ICIs treatment showed shorter mOS (HR =1.444, 95% CI: 1.01–1.98, P=0.03). PFS, progression-free survival; OS, overall survival; HR, hazard ratio; C1q, complement component 1q; NSCLC, non-small cell lung cancer; ICIs, immune checkpoint inhibitors; mPFS, median PFS; mOS, median OS.

Figure 3 Ability of baseline C1q level to predict OS of patients with advanced NSCLC to immunotherapy. The AUC is 0.785; the 95% CI is 0.711 to 0.869; and the difference is statistically significant (P<0.001). The cut-off value of baseline C1q is 216.2 mg/L; the corresponding sensitivity is 66.7%; and the specificity is 84.9%. C1q, complement component 1q; OS, overall survival; NSCLC, non-small cell lung cancer; AUC, area under the curve; CI, confidence interval.

The levels of baseline AGR, NLR, LDH, and CRP were compared in the above groups reflecting mPFS or mOS, respectively. The results of 158 samples for blood routine and biochemical examination were collected, among which 152, 152, 150, and 150 pieces of data were used for AGR, NLR, LDH, and CRP analysis respectively, and none of them was found to be correlated with prognosis (Figure S1).

Correlation between clinicopathological characteristics and survival

Until 3 May 2023, a total of 91 patients presented progression or death. Subgroup analysis based on clinical characteristics showed that the mPFS of patients whose age was <75 years (8.4±0.8 vs. 6.7±1.5 months, P=0.02) or ECOG-PS score 0–1 (8.5±0.7 vs. 4.8±2.2 months, P=0.001) was significantly longer than that of the corresponding control group. There was no significant difference in mPFS between patients with or without smoking history (P=0.39) or brain metastasis (P=0.89) (Table S1). The mOS of patients whose ECOG-PS 0–1 was significantly longer than those whose ECOG-PS ≥2 (P<0.001), the mOS of patients without brain metastasis was significantly longer than that of patients with brain metastasis (P=0.03). The mOS of patients whose age <75 years (P=0.09) tended to be prolonged. There was no significant difference in mOS among different sex groups (P=0.58) or bone metastasis (P=0.72) (Table S2).

Univariate and multivariate Cox proportional regression models were performed to analyze the PFS and OS. The multivariate Cox regression analyses showed that ECOG-PS ≥2 was significantly related to shorter PFS (P=0.001) (Table S3) and OS (P=0.001) (Table S4) of the patients with advanced NSCLC. Previous chemotherapy was an independent prognostic factor for OS of advanced NSCLC treated with ICIs (P=0.03).

Discussion

Our study focused on exploring C1q leading to diminished efficacy of ICIs in patients with advanced NSCLC. C1q in TME can act as a tumor promoter by promoting cancer cell adhesion, migration, and proliferation in NSCLC, melanoma, and colon cancer (19), and can influence the efficacy of ICIs in multiple ways. C1q can lead to immunotherapy resistance by enhancing signaling pathways. The overexpression of C1q in malignant pleural mesothelioma induces the production of immunosuppressive TME, leading to immunotherapy resistance (20). C1q enhances MAPKs, and PI3K/AKT signaling and makes hepatocellular carcinoma cells more aggressive (21). Our previous study suggests that overexpressed C1q in TAMs promotes macrophages M2 polarization and induces and maintains immunosuppressive TME by up-regulating nucleotide-binding leucine-rich repeat-containing receptor 12 (NLRP12) expression and activating nuclear transcription factor-kappa B (NF-κB) pathway (16). Meanwhile, a bioinformatics study explored common differentially expressed genes in NSCLC through multiple publicly available databases and showed that elevated C1q expression levels are associated with poorer prognosis in NSCLC patients (22). However, it is not clinically feasible to detect C1q in TME. Given the convenience of detecting peripheral blood, we endeavored to determine whether C1q in peripheral blood is as worthwhile as C1q in TME for predicting prognosis.

Our study found that serum C1q levels may be a useful predictor of the efficacy of ICIs. We retrospectively analyzed the efficacy of ICIs in 168 patients with advanced NSCLC, showing that ICIs showed a good clinical effect, with ORR of 23.21%, DCR of 89.28%, mPFS of 8.1 months, and mOS of 18.9 months. By comparing the relationship between serum C1q levels and survival in advanced NSCLC patients receiving ICIs treatment, the results revealed that patients with elevated serum C1q levels had poorer survival. In addition, baseline serum C1q levels showed the potential to predict NSCLC immunotherapy prognosis. Individual studies focused on the relationship between C1q and the prognosis of malignant tumor patients treated with ICIs successively emerged in recent years. This study aimed to explore the correlation between serum C1q levels and the efficacy of ICIs in real-world patients with advanced NSCLC. Our study concluded that the higher the C1q level was, the more limited the benefit of ICIs for NSCLC patients. Thus, we came up that monitoring the baseline and dynamic data of C1q during hospitalization and performing a comprehensive analysis of its changing trend may be helpful in judging the prognosis of patients.

Our study also discovered that age and ECOG-PS score also had a significant impact on the prognosis of NSCLC patients. The PFS of patients ≥75 years old was significantly shorter than that of those <75 years old. The PFS and OS of patients whose ECOG-PS 0–1 were significantly longer than those of patients whose ECOG-PS ≥2. Mezquita et al. (23) found that patients with advanced NSCLC with an ECOG-PS score of 0–1 had better survival outcomes. The age stratification results of the KEYNOTE-010 and KEYNOTE-042 studies showed that the benefit from ICIs treatment in NSCLC patients ≥75 years old was significantly lower than that in patients <75 years old (4). A retrospective study of higher age stratification showed that the OS of advanced NSCLC patients >80 years old after ICIs treatment was only 3.62 months, whereas that of people <80 years old was more than 12.92 months (2). Our study also found that there was a relationship between ECOG-PS and PFS/OS, however, the relationship between age and survival was not clear. In this study, age ≥75 years old was significantly related to shorter PFS, but was not related to OS. It might be because the sample was not large enough or the follow-up time was not long enough. Although many studies have implied the correlation between old age and shorter PFS/OS, it is still controversial whether patients with older age tend to achieve worse survival.

Conclusions

In summary, our research showed that a high level of serum C1q may be related to worse efficacy of NSCLC immunotherapy. This study presents several limitations, including the small sample size. Besides, our sample came from a single center, so the generalizability of our findings to other patient populations needs to be confirmed. In the future, prospective clinical studies of large scale are still needed to further verify the relationship between serum C1q level and survival of ICIs in patients with NSCLC.

Acknowledgments

Funding: This work was supported by the National Natural Science Foundation of China (No. 82272928); CSCO-BMS Cancer Immunotherapy Research Foundation (No. Y-BMS2019-003); Knowledge Innovation Program of Wuhan-Basic Research (No. 2022020801010475), and Medical Youth Outstanding Talents Project of Hubei Province (No. EWT2019-48).

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-304/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-304/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-304/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-304/coif). H.A. receives consulting fees from Astra Zeneca, payment for lectures from Takeda, gets support for attending meetings from MSD, Roche, Angelini Pharma, BMS, and takes charge of clinical trial coordination for Ferrer, outside this study. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was performed in accordance with the principle of the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of Renmin Hospital of Wuhan University dated on 2022-02-18. Individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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