β-glucan combined with Envafolimab and Endostar as immune rechallenge for metastatic non-small cell lung cancer

Abstract

Background

Immune checkpoint inhibitor rechallenge has emerged as a prominent study area in non-small cell lung cancer (NSCLC). β-glucan was reported to reverse resistance to anti-PD-1/PD-L1 inhibitors by regulating the tumor microenvironment. In this self-initiated clinical trial (ChiCTR2100054796), NSCLC participants who have previously failed anti-PD-1 therapy received β-glucan (500 mg, bid, d1-21), Envafolimab (300 mg, d1) and Endostar (210 mg, civ72h) every 3 weeks until disease progression or unacceptable toxicity. The clinical efficacy and adverse events were observed, while serum samples were collected for proteomic analysis.

Results

Twenty Three patients were enrolled from January 2022 to March 2023 (median age, 65 years; male, n = 18 [78.3%]; squamous NSCLC, n = 9 [39.1%]; mutant type, n = 13 [56.5%]). The overall response rate (ORR) was 21.7% and disease control rate (DCR) was 73.9%. Median progression-free survival (mPFS) and median overall survival (mOS) was 4.3 months [95% CI: 2.0–6.6] and 9.8 months [95% CI: 7.2–12.4], respectively. The mPFS between PD-L1 positive and negative subgroup has significant difference (6.3 months vs. 2.3 months, p = 0.002). Treatment-related adverse events (TRAEs) occurred in 52.2% of patients. The most common TRAEs were hypothyroidism (26.1%) and fatigue (26.1%). 2 (8.7%) grade 3 adverse events were reported. No adverse reaction related deaths have been observed. Proteomic analysis revealed that the levels of CASP-8, ARG1, MMP12, CD28 and CXCL5 correlated with resistance to the treatment while the levels of CD40-L and EGF related to the favorable response.

Conclusion

β-glucan combined with Envafolimab and Endostar has considerable efficacy and safety for immune rechallenge in metastatic NSCLC patients who failed of anti-PD-1 treatment previously, especially for PD-L1 positive patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12865-024-00651-x.

Introduction

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer [1]. With the development of immunotherapy, immune checkpoint inhibitors (ICIs) typified by anti-programmed cell death-1 (PD-1) /anti-programmed cell death ligand-1 (PD-L1) inhibitors have become the main treatment option for advanced NSCLC due to their sustaining anti-tumor efficacy and tolerable safety profile [2]. However, ICIs only benefits a small number of patients and a significant proportion of patients could develop primary or acquired drug resistance to ICIs [3], which has become an important issue that cannot be ignored. At present, there is a lack of consistent guidelines or consensus on the evaluation criteria for immunotherapy resistance and the choice of intensive treatment after immune resistance. To solve this dilemma, multiple combination therapies have been explored, including ICIs combined with chemotherapy or targeted drugs, dual immunotherapy, systemic immunotherapy in conjunction with local radiotherapy, exploration of other immune checkpoints and tumor vaccines [4–6]. However, the outcomes of current clinical trials regarding immune rechallenge were less than satisfactory. The reason was most likely that they ignored the important role played by the regulation of the tumor immune microenvironment (TME) in anti-tumor treatment.

β-glucan, the main component of microbial cell walls, is a linear polysaccharide linked by β-glucoside bond of D-glucose monomeris [7]. As an immune adjuvant, β-glucan has been used in clinical practice alongside other anti-tumor medications for tumor treatment [8]. Following oral administration of β-glucan, there was an increase in dendritic cells (DCs) within the TME of wild-type mice with colitis-associated colorectal cancer (CAC), resulting in enhanced production of CD8⁺T cells and related cytokines, ultimately leading to a delay in CAC development [9]. β-glucan could also enhance the efficacy of immunotherapy by regulating the composition of intestinal microbiota and adjusting the intestinal microenvironment [10]. Furthermore, for patients with advanced tumors resistant to anti-PD-1 inhibitors, 69.2% obtained stable disease (SD) when added with β-glucan on the basis of maintaining the original treatmennt regimen in our previous study, suggesting that β-glucan had the potential to reverse immune resistance [11].

Envafolimab is a single domain anti-PD-L1 inhibitor administered subcutaneously, which can block the PD-1/PD-L1 pathway, reactivate the suppressed T cells to induce anti-tumor immune response and recover the antigen presentation function of DCs [12–14]. Envafolimab monotherapy has been proved the anti-tumor activity and safety in the second and above line treatment for a variety of MSI-H/dMMR advanced solid tumors in phase II clinical studies [15, 16]. Nowadays, the conversion of anti-PD-1 /PD-L1 antibodies as immune rechallenge is also a treatment option for some patients with NSCLC [17, 18].

Anti-angiogenic drugs play a very important role in the treatment of advanced NSCLC, especially in lung adenocarcinoma [19]. Previous studies have shown that the abnormal blood vessels in the TME were associated with drug resistance [20]. As a novel recombinant human endostatin, Endostar can strongly inhibit VEGF expression and angiogenesis while also inducing vascular normalization [21]. By inducing vascular normalization of tumor blood vessels, it can promote the infiltration of T cells into the tumor, thereby transforming the tumor microenvironment into "hot tumor". The combination of anti-PD-1 inhibitors and Endostar exhibited a significant synergistic effect in suppressing tumor growth in preclinical lung tumor models as well as NSCLC patients [22–24].

Totally, our study aims to evaluate the efficacy and safety of β-glucan combined with Envafolimab (an anti-PD-L1 antibody) and Endostar (an angiogenesis inhibitor) in the treatment of metastatic NSCLC patients who have previously failed anti-PD-1 therapy, while also investigating potential biomarkers associated with treatment response and resistance.

Materials and methods

Study design and ethics

This is a single-arm, Phase II clincal trial (ChiCTR2100054796, Registration Date: 2021–12-27) performed at the Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou city, to evaluate the efficacy and safety of β-glucan combined with Envafolimab and Endostar in mNSCLC patients failed of anti-PD-1 therapy previously. Participants received β-glucan (500 mg, bid, d1-21), Envafolimab (300 mg, d1) and Endostar (210 mg, civ72h) every 3 weeks until disease progression or unacceptable toxicity. Tumor imaging and objective response assessment were performed every 2 cycles according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Patients were followed up for safety 30 days after the last cycle and followed for survival every 12 weeks after disease progression or the last cycle. The study was approved by the Ethics Committee of Changzhou No.2 People’s Hospital (Approval number: [2021YLJSD002]) and conducted in accordance with the principles of the Declaration of Helsinki. All registered patients have signed informed consent forms to participate.

Inclusion and exclusion criteria for participants

All enrolled patients were in line with the following conditions: (1) aged from 18 to 80 years old; (2) confirmed as stage IV NSCLC histologically or cytologically; (3) Eastern Cooperative Oncology Group Performance Status (ECOG PS) 0 or 1; (4) with at least one measurable target lesion; (5) failed of anti-PD-1 therapy and never treated with PD-L1 inhibitors; (6) with sufficient organ and bone marrow function; (7) with an expected survival of at least 3 months or the ability to tolerate a minimum of 2 treatment cycles.

Patients with any of the following conditions were excluded: (1) participating in other clinical studies; (2) with invasion of large blood vessels confirmed by imaging; (3) with symptoms of central nervous system metastases; (4) with grade III-IV (New York Heart Association classification) congestive heart failure; (5) allergic to the drugs used in this trial; (6) requiring long-term systemic application of corticosteroids.

Characteristics of all enrolled patients were collected at baseline, including age, sex, pathology, driver gene mutation, ECOG PS score, number of treatment lines and expression of PD-L1. Clinical data were collected from patients receiving treatment until disease progression or death. Enrolled patients provided serum samples at baseline, when achieved best response and after disease progression. The samples were centrifuged at 2000 rpm for 10 min and stored at -80 °C for proteomic analysis.

Clinical outcomes

The primary endpoints were objective response rate (ORR) and safety. The secondary endpoints included disease control rate (DCR), progression-free survival (PFS) and overall survival (OS). The best response (BOR) is evaluated by RECIST version 1.1, classified as complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). ORR is defined as the percentage of all patients who achieved CR and PR. DCR is defined as the percentage of all patients who achieved CR, PR and SD. The NCI Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 was used to evaluate the rating of adverse events. SPSS 25.0 and Graphpad Prism 9.0.0 were used for statistical analysis and image drawing of the data. Chi-square test, Fisher’s exact test and rank sum test were used to compare the differences in efficacy and survival outcomes between subgroups. Kaplan–Meier curves were drawn. The log-rank test was used to for the significance of survival curves in subgroups. p < 0.05 indicated that the difference was statistically significant. The safety-related results were summarized by descriptive statistics.

Proteomic analysis

Each protein was quantified by using multiple proximity extension assays. A double-recognition immunoassay mechanism was applied in which two pairs of antibodies (each with a unique DNA oligonucleotide marker) simultaneously bind to a target protein in a liquid medium, bringing the two antibodies in close proximity, allowing hybridization and serving as a template for DNA polymerase-dependent extension steps. Double-stranded DNA was unique to a particular antigen and was amplified using primers in quantities proportional to the sample concentration of the target protein. The target of amplification was quantified by RT-PCR. Protein abundance was reported as normalized protein expression (NPX), which was on the Log2 scale. In order to convert several correlated proteins into a number of uncorrelated variables and visualize the dataset, PCA for K-means clustering was performed. Double-tailed Welcht-test was performed to identify proteins which were significantly enriched or consumed in serum samples. The immune cytokines of different response groups were compared by Mann–Whitney U test and evaluated by log-rank test. R statistical program (version 3.6.3) was used for data analysis. Graphpad Prism 9.0.0 was used for further data visualization. p < 0.05 was considered statistically significant.

Results

Clinical baseline characteristics of patients

From January 2022 to March 2023, 23 patients were enrolled in this study with median age of 65 years. Among the recruited patients, 18 (78.3%) were male, 14 (60.9%) patients were adenocarcinoma, 5 (21.7%) were with ECOG PS 0. PD-L1 expression was found to be positive in 15 (65.2%) patients. Patients received β-glucan combined with Envafolimab and Endostar as 2 (10/23, 43.5%), 3 (6/23, 26.1%) or > 3 (7/23, 30.4%) lines of therapy (Table 1).

Table 1.

Baseline clinical characteristics of patients

Characteristics	n = 23
Age, median (range)	65 (55, 80)
Gender, n (%)
Male	18 (78.3)
Female	5 (21.7)
Histopathology, n (%)
Adenocarcinoma	14 (60.9)
Squamous cell carcinoma	9 (39.1)
Gene mutation status, n (%)
Mutant-type	13 (56.5)
Wild-type	10 (43.5)
ECOG PS, n (%)
0	5 (21.7)
1	18 (78.3)
Lines of therapy, n (%)
2	10 (43.5)
3	6 (26.1)
> 3	7 (30.4)
PD-L1 expression, n (%)
Positive	15 (65.2)
Negative	8 (34.8)

ECOG PS Eastern Cooperative Oncology Group performance status, PD-L1 Programmed cell death ligand-1

Efficacy evaluation

As of the data cutoff date (April 1, 2024), 5 patients achieved PR, 12 patients achieved SD and 6 patients were evaluated as PD (Fig. 1). No patients achieved CR. The overall ORR was 21.7% and DCR was 73.9% (Table 2). The median PFS was 4.3 months [95% CI: 2.0–6.6] (Fig. 2A) and the median OS was 9.8 months [95% CI: 7.2–12.4] (Fig. 2D).

Fig. 1.

Waterfall plot of all patients (n = 23). As of the data cutoff date (April 1, 2024), 5 patients achieved PR, 12 achieved SD and 6 patients were evaluated as PD. PR, partial response; SD, stable disease; PD, progressive disease

Table 2.

Best response of all patients and subgroups

Response	All patients (n = 23)	LUAD (n = 14)	LUSC (n = 9)	χ2 value	P value	PD-L1 positive (n = 15)	PD-L1 negative (n = 8)	χ2 value	P value
BOR, n (%)
CR	0	0	0			0	0
PR	5 (21.7)	5 (35.7)	0			4 (26.7)	1 (12.5)
SD	12 (52.2)	7 (50.0)	5 (55.6)			9 (60.0)	3 (37.5)
PD	6 (26.1)	2 (21.3)	4 (44.4)			2 (13.3)	4 (50.0)
ORR (%)	21.7	35.7	0	-	0.116	26.7	12.5	-	0.621
DCR (%)	73.9	85.7	55.6	-	0.162	86.7	50.0	-	0.131

BOR Best overall response, CR Complete response, PR Partial response, SD Stable disease, PD Progression of disease, ORR Objective response rate, DCR Disease control rate, PD-L1 Programmed cell death-ligand 1, LUAD Lung adenocarcinoma, LUSC Lung squamous cell carcinoma

Fig. 2.

Kaplan–Meier curves of progression-free survival (PFS) and overall survival (OS). A PFS of all patients (n = 23). B PFS of LUAD (n = 14) and LUSC (n = 9) subgroups. C PFS of PD-L1 positive (n = 15) and PD-L1negative (n = 8) subgroups. D OS of all patients (n = 23). E OS of LUAD (n = 14) and LUSC (n = 9) subgroups. F OS of PD-L1 positive (n = 15) and PD-L1 negative (n = 8) subgroups. Use log-rank test to compare survival curves of subgroups. p < 0.05 is considered to be statistically significant. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; PD-L1, programmed cell death ligand-1

According to pathology and expression of PD-L1, 23 patients were categorized into different subgroups for analysis. The results showed that the ORR of patients in adenocarcinoma group and squamous cell carcinoma group were 35.7% and 0% (p = 0.116). The DCR of adenocarcinoma group was significantly higher than that of squamous cell carcinoma group (85.7% vs. 55.6%, p = 0.162). Additionally, the ORR of PD-L1 positive and negative groups were 26.7% and 12.5% (p = 0.621) and the DCR were 86.7% and 50.0%, respectively (p = 0.131) (Table 2).

Patients with adenocarcinoma tended to have better mPFS compared to those with squamous cell carcinoma, but the difference was not statistically significant (5.8 months [95% CI: 2.9–7.7] vs. 3.0 months [95% CI: 0.4–5.6], p = 0.223) (Fig. 2B). However, there was no significant difference in mOS between the two subgroups (8.2 months [95% CI: 7.0–9.0] vs. 12.3 months [95% CI: 1.6–23.0], p = 0.724) (Fig. 2E). Apart from this, the mPFS was significantly improved in PD-L1 positive patients than PD-L1 negative patients (6.3 months [95% CI: 4.7–7.9] vs. 2.3 months [95% CI: 0.3–2.9], p = 0.002) (Fig. 2C). The mOS had the same trend (9.9 months [95% CI: 3.8–16.0] vs. 8.1 months [95% CI: 5.0–10.6], p = 0.398) (Fig. 2F) between the two subgroups, though the difference was not statistically significant.

Safety

In safety analysis, 12/23 (52.2%) patients experienced treatment-related adverse events (TRAEs) during treatment. The most common TRAEs were hypothyroidism (26.1%) and fatigue (26.1%), followed with anemia (13.0%), rash (13.0%) and fever (9.7%). 2/23 (8.7%) grade 3 adverse events were reported. Up to April 2024, no immune-associated pneumonia or adverse reaction related deaths have been observed (Table 3).

Table 3.

Profiles of adverse events

TRAEs, n (%)	Grade
	1	2	3	4
Fatigue	4 (17.4)	1 (4.3)	1 (4.3)	0
Hypothyroidism	6 (26.1)	0	0	0
Rash	3 (13.0)	0	0	0
Anemia	1 (4.3)	1 (4.3)	1 (4.3)	0
Fever	2 (8.7)	0	0	0

TRAE Treatment-related adverse events

Protemic expression and analysis

Serum samples were collected at baseline, when achieved response and/or disease progression. Proteomic tests were performed on serum samples of 9 patients ultimately (Fig. 3A, B). A total of 5 cytokines were found to be significantly different before and after tumor progression, including CASP-8, ARG1, MMP12, CD28 and CXCL5 (Fig. 3C, D, Figure S2A).

Fig. 3.

Data preprocessing for DEGs and protemic analysis results of 9 patients. A A Boxplot of data preprocessing for different expressed proteins (DEPs). B Heat map of DEPs in all patients (n = 9). Red or blue represents high or low expression. C Volcano plot of DEPs before and after progression in all patients (n = 9). Red dots represent significantly associated proteins at FDR ≤ 5%. D Boxplot of significantly different DEPs in plasma of all patients (n = 9) before and after progression. E Volcano plot of DEPs of RG (n = 6) and NRG (n = 3) at baseline. Red dots represent significantly associated proteins at FDR ≤ 5%. F Boxplot of significantly different DEPs in RG and NRG at baseline. G Volcano plot of DEPs in RG (n = 6) before and after response. Red dots represent significantly associated proteins at FDR ≤ 5%. H Boxplot of significantly different DEPs in plasma of RG before and after response. The DEPs were compared by Mann–Whitney U test and evaluated by Log-rank test. *p < 0.05, **p < 0.01. RG, response group. NRG, non-response group. DEPs, different expressed proteins. NPX, normalized protein expression

Nine patients were divided into a response group (n = 6, PR + SD) and a non-response group (n = 3, PD) according to the best response. The results showed that IL-6, CD83 and ICOSLG had significant differences at baseline between response group and non-response group (Fig. 3E, F, Figure S1A, Figure S2B).

In response group, 2 patients achieved PR and 4 patients achieved SD. We then compared the cytokines of patients in response group at baseline and after response to the treatment and found that the levels of CD40-L and EGF relate to the favorable response (Fig. 3G, H, Figure S1B, Figure S2C). Univariate and multivariate cox regression analysis was used to explore the correlation between cytokines with PFS or OS at baseline in the two groups, but the results showed no significant differences.

Discussion

Recently, there has been a growing body of research dedicated to the investigation of immune rechallenge [25]. For NSCLC, several studies with small samples of immune rechallenge were reported while the efficacy varied widely. The ORR ranged from 5.9% to 14.3%, and DCR ranged from 45.8% to 85.7% for single immunotherapy [17, 18, 26]. Dual immunotherapy achieved an ORR of 47.3% and a DCR of up to 81.5% [27]. A comprehensive meta-analysis encompassing 49 studies was conducted to access the efficacy and safety of immune rechallenge in patients with solid tumors. The findings revealed an ORR rate of 21.8%, a mPFS of 4.9 months and a mOS of 15.6 months while the incidence of adverse events was 52.2%, including 21.5% for grade 3 and above [28]. For our study, the ORR rate, mPFS was 21.7%, 4.3 months, which is similar to the above study. However, the mOS was 9.8 months, which is significantly lower than the above study. This may be attributed to the preponderance of patients with 3 lines or above in our study. Meanwhile, the incidence of adverse events in our study was 52.2%, with no grade 4 adverse events or new specific immune-related adverse events occurred, indicating that this treatment regimen (β-glucan combined with Envafolimab and Endostar) is feasible and safe as immune rechallenge for mNSCLC patients.

Modulating TME from an immunosuppressive environment to an inflammatory environment holds great promise for achieving immune rechallenge [29]. In this process, β-glucan offers a new treatment perspective. Previous studies have demonstrated that β-glucan can activate DCs and macrophages, inhibit MDSCs and TEDCs, thereby eliminating tumor-induced immunosuppression [30, 31]. It also regulates nature killer (NK) cell function by altering macrophage phenotype, enhancing antigen presentation, promoting initiation and differentiation of cytotoxic T lymphocytes [32–35]. The addition of β-glucan is of great value in improving the immunosuppressive TME, especially in combination with ICIs. For example, Hu et al. discovered that β-glucan can enhance the antitumor effects of anti-PD-L1 inhibitors in melanoma models [36]. Wang et al. developed an antibody-β-glucan conjugate (AGC) by linking β-glucan with anti-PD-L1 inhibitors, the AGC-mediated bridging effect enhanced the interaction between tumor cells and DCs. Compared to anti-PD-L1 inhibitors monotherapy, AGC induced the infiltration of DCs and the activation of T cells in TME, resulting in an earlier immune response [37].

Anti-PD-1 inhibitors and anti-PD-L1 inhibitors have been regarded as the same drug for a long time. Typically, anti-PD-L1 inhibitors are usually not applied after resistance to anti-PD-1 inhibitors. As research progresses, many studies indicated mechanistic differences between anti-PD-L1 and anti-PD-1 inhibitors. In addition to inhibiting the PD-1/PD-L1 pathway, anti-PD-L1 inhibitors can also inhibit the overexpression of PD-L1 on the surface of DCs in the TME, thus activating the antigen presentation function of DCs and recruiting T cells for the unique killing of tumor cells [38–40]. In the past few years, many studies found that after the progress of anti-PD-1 treatment, the usage of anti-PD-L1 antibody could also obtain a fairly controllable therapeutic efficacy [41–43]. Therefore, conversion of anti-PD-1/PD-L1 antibody is also an emerging therapeutic regimen as immune rechallenge strategy.

In the subgroup analysis, there were no significant differences observed in ORR between adenocarcinoma and squamous cell carcinoma subgroups or between PD-L1 positive and negative subgroups. Patients with adenocarcinoma tended to have better mPFS compared to those with squamous cell carcinoma, but the difference was not statistically significant. This may be attributed to the limited sample size. At the same time, there was no difference in mOS. It is important to note that PFS reflects short-term treatment effects, whereas OS can be influenced by various factors such as ECOG PS status, site of metastasis, lines of treatment, etc. Therefore, it was not uncommon to see differences in PFS but often no differences in OS in clinical studies. The high expression of PD-L1 at baseline has been associated with enhanced efficacy of anti-PD-1/PD-L1 therapy in advanced NSCLC [44, 45]. However, it is not clear whether PD-L1 levels change during the previous immunotherapy. At present, the redetection of PD-L1 expression before immune rechallenge is still rare. Whether PD-L1 can be used as a therapeutic marker for immune rechallenge is controversial [46, 47]. In our study, the PFS of PD-L1 positive subgroup was significantly better than that of PD-L1 negative subgroup. The OS data showed the same trend with no significant difference, which we thought was also related to the small sample size. These results indicated that the expression of PD-L1 at baseline might also serve as a prognostic biomarker for immune rechallenge.

Admittedly, effective biomarkers for immune rechallenge are currently lacking. Therefore, we collected peripheral blood samples from patients at different treatment time points and conducted proteomic analysis in an attempt to identify potential markers for therapeutic efficacy and prognosis. A total of 5 cytokines, including CASP-8, ARG1, MMP12, CD28 and CXCL5, were found to be significantly different before and after tumor progression and we considered this might be related to the treatment resistance. Among the cytokines, previous studies have shown that MMP12 and ARG1 were associated with poor prognosis in various tumors [48, 49] and CASP-8 promoted melanoma progression [50]. The increase of CD8⁺CD28⁺ T cells in advanced NSCLC patients who received chemo (radio) therapy predicted treatment efficacy and prognosis [51, 52]. However, the results of CXCL5 in our study could not be confirmed by current studies, as CXCL5 tended to be associated with poor prognosis in many solid tumors [53].

Comparing between response and non-response groups, mNSCLC patients with lower ICOSLG and CD83 at baseline responded better to the treatment, but the specific thresholds remains unknown [54, 55]. However, high expression of IL-6 associated with poor efficacy with immunosuppression in many tumors [56], which differed from our results. Furthermore, CD40-L can activate NK cells, CD4⁺ and CD8⁺ T cells and inhibit tumor progression [57]. EGF signaling is the core in regulating tumor cell proliferation [58]. The levels of CD40-L and EGF might relate to the favorable response. However, due to the limited number of patients enrolled in proteomic analysis, the results should be interpreted with caution. Further investigation is required in a larger cohort to validate these proteins’ association with resistance or response to immune rechallenge, thus providing more reliable predictive biomarkers for guiding clinical work.

The main limitation of this study was that the patients enrolled in the study were not enough, leading to insufficient statistical power in the analysis. Enrollment should be expanded or a multi-center clinical study could be conducted in the follow-up studies. Secondly, as a single-arm study, it was difficult to accurately compare the efficacy and side effects with other treatment regimens in immune rechallenge studies. Despite these limitations, this study was the first attempt to demonstrate that β-glucan combined with Envafolimab and Endostar has considerable efficacy in patients who have failed previous anti-PD-1 treatment. As a “chemo-free” treatment regimen, attempting to regulate the TME for the purpose of immune rechallenge, this is more acceptable for cancer patients.

Conclusion

In summary, β-glucan combined with Envafolimab and Endostar has considerable efficacy and safety for immune rechallenge in metastatic NSCLC patients who failed of anti-PD-1 treatment previously. Especially, PD-L1 positive patients can benefit more from immune rechallenge than PD-L1 negative patients.

Abbreviations

AGC

Antibody-β-glucan conjugate

BOR

Best overall response

CAC

Colitis associated colorectal cancer

CR

Complete response

CTCAE

Common Terminology Criteria for Adverse Events

DC

Dendritic cell

DCR

Disease control rate

DEP

Different expressed proteins

ECOG PS

Eastern Cooperative Oncology Group performance status

ICI

Immune checkpoint inhibitor

irAE

Immune-related Adverse Event

LUAD

Lung adenocarcinoma

LUSC

Lung squamous cell carcinoma

MDSC

Myeloid-derived suppressor cell

mNSCLC

Metastatic non-small cell lung cancer

mPFS

Median progression-free survival

mOS

Median overall survival

NK

Natural killer

NPX

Normalized protein expression

NRG

Non-response group

NSCLC

Non-small-cell lung cancer

ORR

Objective response rate

OS

Overall survival

PCA

Principal components analysis

PD

Progression of disease

PD-1

Programmed cell death-1

PD-L1

Programmed cell death ligand-1

PFS

Progression-free survival

PR

Partial response

RECIST

Response Evaluation Criteria in Solid Tumors

RG

Response group

SD

Stable disease

TEDC

Tumor-educated dendritic cell

TME

Tumor microenvironment

TRAE

Treatment-related adverse events

Authors’ contributions

QG, HJ, DL and CQ, conceptualization. XP, YZ, YZ, QZ, and GW, investigation. YL, LQ, original draft writing and formal analysis. QG, HJ, DL, review and editing. All authors contributed to the article and approved the submitted version.

Funding

This study was supported by the 2022 Clinical Research project of Changzhou Medical Center, Nanjing Medical University (CMCC202201), the 2021 Science and Technology Project of Changzhou Health Commission (Major Science and Technology Project) (ZD202113), 2021 Science and Technology Project of Changzhou Health Commission (Young Talent Science and Technology Project) (QN202116), 2022 Changzhou 8th Batch of Science and Technology Project (Applied Basic Research) (CJ20220086). The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or decision to submit the manuscript for publication.

Availability of data and materials

The datasets generated and analyzed during the current study are not publicly available due to limitations of ethical approval involving the patient data but are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was approved by the Ethics Committee of Changzhou No.2 People’s Hospital (Approval number: [2021YLJSD002]) and conducted in accordance with the principles of the Declaration of Helsinki. All registered patients have signed informed consent forms to participate.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.