Elevated serum neuron-specific enolase as an indicator of poor chemo-immunotherapy outcomes and reduced CD8-positive lymphocyte infiltration in small-cell lung cancer: a retrospective cohort study

Introduction

Immune checkpoint inhibitors (ICIs), adopted rapidly over the past decade, are now used in combination with chemotherapy (chemo-immunotherapy) as first-line treatment for extensive-disease small-cell lung cancer (ED-SCLC); however, their survival benefit is limited (1,2).

Unlike non-small cell lung cancer, clinically established biomarkers for identifying patients with SCLC who are most likely to benefit from ICIs remain limited (3). Although programmed death ligand-1 (PD-L1) expression, tumor mutational burden, molecular subtypes, and immune microenvironmental features have been investigated, none has been widely implemented as a routine clinical biomarker in ED-SCLC. Therefore, practical and accessible biomarkers that can help stratify the expected benefit of chemo-immunotherapy are needed.

Emerging evidence proposes molecular subtype classification for SCLC based on the expression of several transcriptional regulators. According to the expression of achaete-scute homolog 1 (ASCL1), neurogenic differentiation factor 1 (NEUROD1), and POU class 2 homeobox 3 (POU2F3), respectively, SCLC can be categorized into SCLC-A, SCLC-N, and SCLC-P; tumors lacking these transcription factors are classified as SCLC-I (4). A retrospective analysis of the IMpower133 trial suggested that ICIs may contribute to improved survival in the SCLC-I subtype, characterized by high expression of immune-related genes. These findings highlight the potential importance of tumor immune features in predicting the benefit of chemo-immunotherapy. Recent studies have further emphasized immune heterogeneity in SCLC and the need for clinically applicable biomarkers that can capture immune-enriched tumor states (5). However, molecular subtyping and detailed tumor microenvironmental assessment are not always feasible in routine practice because many patients with SCLC are diagnosed using small biopsy or cytological specimens.

In our previous study, we demonstrated the utility of immunohistochemistry-based subtyping, feasible in routine pathological practice, together with assessment of CD8-positive lymphocyte infiltration into tumor cells in predicting chemo-immunotherapy’s efficacy (6). Nevertheless, the practical application of tissue-based evaluation remains limited because biopsy specimens are frequently insufficient in quantity and/or quality. Thus, easily accessible biomarkers that can complement tissue-based evaluation are required.

Serum neuron-specific enolase (NSE) is a classical circulating biomarker for SCLC and is associated with tumor burden and poor prognosis. However, its clinical utility in the context of chemo-immunotherapy and its relationship with pathological features of the tumor immune microenvironment remain poorly defined (7). If serum NSE is associated with both clinical outcomes and intratumoral immune features, it may provide a practical marker for prognostic assessment and exploratory stratification of chemo-immunotherapy benefit, particularly when adequate tissue-based evaluation is difficult.

In this study, we evaluated the prognostic impact of pretreatment serum NSE levels by comparing clinical outcomes between high- and low-NSE groups of patients with ED-SCLC who received first-line chemo-immunotherapy. We also compared treatment outcomes between chemo-immunotherapy and chemotherapy cohorts stratified by pretreatment serum NSE levels to assess whether NSE status modifies the additional benefit conferred by immunotherapy over chemotherapy alone. Finally, we examined the association between serum NSE levels and intratumoral CD8-positive lymphocyte infiltration. We present this article in accordance with the STROBE and REMARK reporting checklists (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0275/rc).

Methods

Patients and clinical data

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Ethics Committee of Hakodate Goryokaku Hospital (Approval No. 2025-050). Informed consent was obtained from patients using an opt-out procedure via the hospital website. This retrospective analysis was performed using clinical data and biopsy specimens from 41 patients with ED-SCLC administered first-line chemo-immunotherapy at Hakodate Goryokaku Hospital (Hokkaido, Japan) between October 1, 2020, and October 31, 2022. In the historical chemotherapy cohort without ICI administration, we retrospectively analyzed clinical data and biopsy specimens from 38 patients with ED-SCLC who received first-line chemotherapy at the same institution between January 1, 2017, and September 30, 2020. Patients were eligible for NSE-based survival analyses if pretreatment serum NSE data and clinical outcome data were available. Patients without pretreatment serum NSE data were excluded from NSE-based analyses. Immunohistochemical analyses were restricted to patients with available formalin-fixed paraffin-embedded (FFPE) tumor specimens. Patients with unavailable or depleted tumor tissue were excluded from the immunohistochemical analyses. Pretreatment serum NSE was defined as the serum NSE value measured before initiation of first-line treatment. Serum NSE was measured as part of routine clinical practice at the institutional clinical laboratory using an electrochemiluminescence immunoassay (ECLIA).

Disease progression was retrospectively assessed by the treating physicians based on radiographic imaging and clinical information in routine clinical practice. Chest and abdominal computed tomography was generally performed every 2–3 months or as clinically indicated. Brain magnetic resonance imaging or computed tomography was performed at baseline and/or when clinically indicated.

Immunohistochemistry analysis and evaluation of tissue staining

Immunohistochemistry was performed as previously described (6). Human leukocyte antigen (HLA) class I expression was categorized into two patterns: high-expression, defined as HLA class I positivity in ≥80% of all tumor cells, and low-expression, defined as positivity in <80% of tumor cells. CD8-positive lymphocytes were evaluated in hotspot areas. Cases with ≥10 cells of CD8-positive lymphocytes infiltrating tumor cells per high-power field (approximately 0.24 mm²) were classified into the CD8-high group, whereas those with <10 cells per HPF were classified under the CD8-low group. Immunohistochemical staining was evaluated by two pathologist co-authors who were blinded to clinical information, including serum NSE status and survival outcomes. Final classifications were determined by consensus.

Statistical analysis

Progression-free survival (PFS) was defined as the time from initiation of first-line treatment to disease progression or the last follow-up, and overall survival (OS) was defined as the time from initiation of first-line treatment to death from any cause or the last follow-up. Survival data were collected through July 31, 2025. Continuous variables are presented as medians with ranges or 95% confidence intervals (CIs), as appropriate. Categorical variables are presented as numbers and percentages. The cutoff value for serum NSE was determined by receiver operating characteristic (ROC) curve analysis using 180-day PFS as the endpoint, and the Youden index was used to select the cutoff.

PFS and OS were estimated using the Kaplan-Meier method and compared using the log-rank test. Cox proportional hazards models were used for survival analyses, and results are reported as hazard ratios (HRs) with 95% CIs. Multivariable models were adjusted for clinically relevant covariates selected a priori, including performance status (PS), stage group, sex, liver metastasis, and brain metastasis. In analyses restricted to the chemo-immunotherapy cohort, models were adjusted for PS, stage group, liver metastasis, and brain metastasis to avoid overfitting.

To evaluate whether pretreatment NSE status modified the treatment effect of chemo-immunotherapy, formal interaction analyses were performed using Cox proportional hazards models including treatment group, NSE status, and a treatment-by-NSE interaction term. To address potential overfitting of the ROC-derived cutoff, pretreatment NSE was also analyzed as a log-transformed continuous variable. Additional sensitivity analyses were performed using the median NSE value as an alternative cutoff and by restricting the analysis to patients with PS 0–1.

Associations between categorical variables were assessed using Fisher’s exact test or the Chi-squared test, as appropriate. To evaluate factors associated with intratumoral CD8-positive lymphocyte infiltration, multivariable logistic regression analyses were performed using CD8 status as the dependent variable. The main model included serum NSE status, HLA class I expression, PS, liver metastasis, and brain metastasis. Sensitivity models additionally included stage group and treatment cohort.

All statistical tests were two-sided, and P<0.05 were considered statistically significant. Statistical analyses were performed using JMP software and R software. Cox proportional hazards models, including treatment-by-NSE interaction and sensitivity analyses, were fitted using the survival package in R.

Results

Patient characteristics and clinical variables

Forty-one patients were enrolled in the chemo-immunotherapy cohort (Figure 1A). In the historical chemotherapy cohort, 38 patients were initially identified. Of these, 30 patients had available pretreatment serum NSE data and were included in the NSE-based survival analyses, whereas eight patients were excluded because pretreatment serum NSE had not been measured (Figure 1B). Representative baseline patient characteristics are summarized in Table 1.

Figure 1 Study workflow and case selection for immunohistochemical analyses. (A) Chemoimmunotherapy (chemo + ICI) cohort. (B) Chemotherapy (chemo) cohort. ED-SCLC, extensive-disease small-cell lung cancer; HLA, human leukocyte antigen; ICI, immune checkpoint inhibitor; NSE, neuron-specific enolase; OS, overall survival; PFS, progression-free survival.

Serum NSE cutoff value determined by ROC analysis

ROC curve analysis yielded an area under the curve (AUC) of 0.751. The ROC-derived cutoff value was determined as 64.1 ng/mL based on the point maximizing the Youden index (Figure S1). Patients with serum NSE levels ≥64.1 ng/mL were classified into the high-NSE group, whereas those with levels <64.1 ng/mL were classified into the low-NSE group.

Survival outcomes according to serum NSE levels in patients treated with chemo-immunotherapy

Baseline patient characteristics of the low-NSE and high-NSE groups are summarized in Tables S1,S2 for the chemo-immunotherapy cohort (n=27 and 14, respectively) and the chemotherapy cohort (n=20 and 10, respectively). Most baseline clinical variables were comparable between the low- and high-NSE groups in both cohorts; however, liver metastasis was more frequent in the high-NSE group in the chemo-immunotherapy cohort.

In the chemo-immunotherapy cohort, the median PFS was 6.4 months (95% CI: 5.3–10.4) in the low-NSE group and 4.4 months (95% CI: 2.1–4.6) in the high-NSE group. PFS was significantly longer in the low-NSE group than in the high-NSE group (P<0.001; HR, 0.37; 95% CI: 0.20–0.71) (Figure 2A). Median OS was 17.2 months (95% CI: 13.9–not reached) in the low-NSE group and 7.9 months (95% CI: 5.2–12.3) in the high-NSE group, with significantly longer OS observed in the low-NSE group (P<0.001; HR, 0.31; 95% CI: 0.17–0.57) (Figure 2B).

Figure 2 Association of baseline serum NSE with survival in ED-SCLC. (A,B) Kaplan-Meier curves of PFS (A) and OS (B) in the chemo-immunotherapy cohort stratified by baseline serum NSE. Low NSE was associated with significantly longer PFS and OS. (C,D) Kaplan-Meier curves of PFS (C) and OS (D) in the chemotherapy-alone cohort stratified by baseline serum NSE. PFS did not differ significantly between low- and high-NSE groups, whereas OS was significantly longer in the low-NSE group. CI, confidence interval; ED-SCLC, extensive-disease small-cell lung cancer; HR, hazard ratio; ICI, immune checkpoint inhibitor; NR, not reached; NSE, neuron-specific enolase; OS, overall survival; PFS, progression-free survival.

In the chemotherapy cohort, median PFS was 5.5 months (95% CI: 2.4–7.0) in the low-NSE group and 2.6 months (95% CI: 1.9–6.8) in the high-NSE group, showing no significant difference (P=0.39; HR, 0.70; 95% CI: 0.31–1.57) (Figure 2C). In contrast, median OS was 14.2 months (95% CI: 7.6–19.0) in the low-NSE group and 3.3 months (95% CI: 1.2–9.5) in the high-NSE group, with significantly longer OS observed in the low-NSE group (P=0.001; HR, 0.23; 95% CI: 0.09–0.60) (Figure 2D).

Univariable and multivariable Cox regression analyses for PFS

Univariable Cox proportional hazards regression analyses were performed to identify factors associated with PFS in the chemo-immunotherapy cohort (Table S3). Four variables were significantly associated with shorter PFS: PS ≥1 (HR, 4.60; 95% CI: 2.11–10.0; P<0.001), stage IVB disease (HR, 2.54; 95% CI: 1.04–6.19; P=0.04), use of the IMpower133 regimen (HR, 2.07; 95% CI: 1.04–4.13; P=0.04), and high serum NSE levels (≥64.1 ng/mL) (HR, 3.22; 95% CI: 1.57–6.58; P=0.001). In multivariable analysis, PS ≥1 (HR, 4.04; 95% CI: 1.74–9.42; P=0.001) and high NSE levels (HR, 3.68; 95% CI: 1.39–9.76; P=0.009) remained independently associated with shorter PFS (Table S4).

Comparison of PFS between chemo-immunotherapy and chemotherapy according to serum NSE levels

We examined whether survival outcomes differed according to pretreatment serum NSE levels. Patients in the chemo-immunotherapy and chemotherapy cohorts were stratified into high- and low-NSE groups. Baseline clinical characteristics did not differ between the chemo-immunotherapy and chemotherapy cohorts within each group (Tables S5,S6). In both NSE subgroups, the frequencies of liver metastasis and brain metastasis were not significantly different between the treatment cohorts. Although PS tended to be more favorable in the chemo-immunotherapy cohort, especially in the low-NSE subgroup, metastatic site distribution was comparable between treatment cohorts. Outcomes were compared between the chemo-immunotherapy and chemotherapy groups within the high and low NSE groups. In the high-NSE group, survival did not differ between the two treatment cohorts (Figure 3A). In contrast, in the low-NSE group, chemo-immunotherapy was associated with significantly longer PFS than chemotherapy (6.3 vs. 5.5 months; HR, 0.47; 95% CI: 0.24–0.92; P=0.02) (Figure 3B).

Figure 3 PFS according to treatment regimen and baseline serum NSE levels. (A) Kaplan-Meier curves of PFS in serum NSE high population comparing first-line chemo-immunotherapy with chemotherapy alone in the entire ED-SCLC cohort. No significant differences in PFS were observed between the two treatment groups. (B) Kaplan-Meier curves of PFS in serum NSE low population comparing first-line chemo-immunotherapy with chemotherapy alone in the entire ED-SCLC cohort. In the low baseline serum NSE group, the addition of an ICI to chemotherapy was associated with longer PFS compared with chemotherapy alone. CI, confidence interval; ED-SCLC, extensive-disease small-cell lung cancer; HR, hazard ratio; ICI, immune checkpoint inhibitor; NSE, neuron-specific enolase; PFS, progression-free survival.

Assessment of HLA class I expression and CD8-positive lymphocyte infiltration in SCLC

Immunohistochemical analyses were performed to investigate tumor microenvironmental features associated with serum NSE levels. Among the 71 patients included in the survival analyses (41 in the chemo-immunotherapy cohort and 30 in the chemotherapy cohort), six from the chemo-immunotherapy cohort (five in the low-NSE group and one in the high-NSE group) were excluded because FFPE specimens were depleted. Thus, 65 patients were evaluated. HLA class I expression (Figure 4A) and intratumoral infiltration of CD8-positive lymphocytes (Figure 4B) were assessed along with hematoxylin and eosin staining quantification.

Figure 4 Immunohistochemical analysis of lung biopsy specimens. (A) HLA class I expression was categorized into two patterns. High expression was defined as HLA class I positivity in ≥80% of tumor cells, whereas low expression was defined as <80%. Scale bar =20 µm. Original magnification: ×200. (B) Positive and negative cases were defined based on the number of CD8-positive cells per high-power field (0.24 mm²) in hotspot areas, with cutoffs of ≥10 and <10 cells, respectively. Scale bar =20 µm. Original magnification: ×200. HE, hematoxylin and eosin; HLA, human leukocyte antigen.

Tumor cell HLA class I expression was observed in 35.7% (15/42) of cases in the low-NSE group and 39.1% (9/23) in the high-NSE group, with no significant difference (P=0.79). In contrast, 64.3% (27/42) of cases in the low-NSE group were classified as CD8-high, whereas 82.7% (19/23) of cases in the high-NSE group were classified as CD8-low, with a significant difference between the groups (P<0.001; Table S7). Logistic regression analysis using CD8 status as the dependent variable identified low serum NSE levels [odds ratio (OR), 11.68; 95% CI: 3.01–61.32; P=0.001] and tumor cell HLA class I expression (OR, 4.52; 95% CI: 1.29–19.16; P=0.03) as independent factors associated with CD8-positive lymphocyte infiltration (Table 2 and Table S8).

A formal treatment-by-NSE interaction analysis was performed to evaluate whether pretreatment NSE status modified the treatment effect of chemo-immunotherapy. In the multivariable model adjusted for PS, stage group, sex, liver metastasis, and brain metastasis, the treatment-by-NSE interaction was significant for PFS (HR, 4.52; 95% CI: 1.27–16.10; P=0.02), whereas the corresponding interaction for OS was not statistically significant (HR, 1.95; 95% CI: 0.48–7.90; P=0.35; Table S9).

To address potential overfitting of the ROC-derived cutoff, pretreatment NSE was also analyzed as a log-transformed continuous variable. Higher log-transformed NSE remained significantly associated with shorter PFS (HR, 1.39; 95% CI: 1.01–1.91; P=0.04) and OS (HR, 1.67; 95% CI: 1.19–2.33; P=0.003) after adjustment for treatment group, PS, stage group, sex, liver metastasis, and brain metastasis (Table S10). In sensitivity analyses restricted to patients with PS 0–1, log-transformed NSE also remained significantly associated with shorter PFS and OS (Table S11).

Discussion

In this study of patients with ED-SCLC, pretreatment serum NSE was associated with both clinical outcomes and tumor immune features. In the chemo-immunotherapy cohort, high serum NSE remained independently associated with shorter PFS after adjustment for PS, stage group, liver metastasis, and brain metastasis. Furthermore, formal interaction analysis demonstrated a significant treatment-by-NSE interaction for PFS, suggesting that pretreatment NSE status may modify the PFS benefit associated with the addition of ICIs to chemotherapy. However, the corresponding interaction for OS was not statistically significant. Therefore, these findings should be interpreted as supporting the prognostic value and exploratory stratification relevance of serum NSE, rather than establishing NSE as a definitive predictive biomarker.

A key issue is whether elevated serum NSE simply reflects aggressive metastatic disease burden. In our cohort, liver metastasis was more frequent in the high-NSE group than in the low-NSE group, whereas brain metastasis was not clearly associated with NSE status. This observation is clinically plausible, given that serum NSE has been associated with tumor burden and poor prognosis in SCLC and that liver metastasis has recently been reported as a clinically relevant adverse prognostic factor in patients with ED-SCLC receiving chemo-immunotherapy (8,9). Nevertheless, high serum NSE remained independently associated with shorter PFS in the chemo-immunotherapy cohort after adjustment for liver and brain metastases. In addition, when NSE was analyzed as a log-transformed continuous variable to address potential overfitting of the ROC-derived cutoff, higher NSE remained significantly associated with shorter PFS and OS after adjustment for treatment group, PS, stage group, sex, liver metastasis, and brain metastasis. Sensitivity analyses restricted to patients with PS 0–1 showed similar associations. These results suggest that the prognostic association of NSE was not fully explained by PS or metastatic sites alone.

The translational analyses provide further support for a link between serum NSE and the tumor immune microenvironment. Low serum NSE was strongly associated with intratumoral CD8-positive lymphocyte infiltration. In multivariable logistic regression analysis, low serum NSE remained independently associated with CD8-positive lymphocyte infiltration after adjustment for tumor cell HLA class I expression, PS, liver metastasis, and brain metastasis. Tumor cell HLA class I expression was also independently associated with CD8-positive lymphocyte infiltration. These findings suggest that low-NSE tumors may be enriched for an immune-infiltrated tumor microenvironment, whereas high-NSE tumors may more frequently exhibit immune-cold features. Intratumoral CD8-positive lymphocyte infiltration is associated with the therapeutic efficacy of ICI-based combination therapy for ED-SCLC (6). Thus, in low-NSE tumors, pre-existing intratumoral CD8-positive lymphocytes may be functionally engaged by ICIs to elicit an anti-tumor immune response (10). Because NSE/ENO2 is a glycolytic enzyme as well as a neuroendocrine marker, elevated serum NSE may reflect tumor-intrinsic metabolic and neuroendocrine programs that contribute to immune exclusion. However, these pathways were not directly examined in the present study; therefore, the observed association between serum NSE levels and immune-cell infiltration should be interpreted with caution, and further mechanistic studies are warranted.

In routine clinical practice, detailed tissue-based evaluation of SCLC remains challenging. Previous studies have shown that IHC-based molecular subtyping of SCLC is associated with neuroendocrine and therapeutic markers, including immune-cell infiltration (11). However, many patients are diagnosed using small biopsy or cytological specimens, and available tissue is often insufficient for comprehensive immunohistochemical or molecular assessment. We previously reported that immunohistochemistry-based SCLC subtyping and intratumoral CD8-positive lymphocyte infiltration may be useful for evaluating chemo-immunotherapy efficacy (6). In this context, serum NSE may serve as an easily accessible biomarker that complements, rather than replaces, tissue-based immune assessment. Because serum NSE is widely measured in routine care, it may be useful for prognostic assessment and exploratory stratification in future clinical studies.

This study has several limitations. First, this was a retrospective single-institution study with a limited sample size. Second, the chemo-immunotherapy and chemotherapy cohorts were non-contemporaneous, which may have introduced historical bias related to staging, supportive care, follow-up, and subsequent treatments. Third, baseline characteristics were not fully balanced between treatment cohorts, particularly with respect to PS. Although we performed multivariable adjustment and sensitivity analyses restricted to patients with PS 0–1, residual confounding cannot be excluded. Fourth, although liver and brain metastases were incorporated into the revised analyses, other aspects of disease burden and metastatic distribution may have influenced outcomes. Fifth, the NSE cutoff was derived from the same dataset using ROC analysis and may therefore be subject to overfitting. To address this concern, we performed sensitivity analyses using log-transformed NSE as a continuous variable, but external validation is required. Sixth, immunohistochemical analyses were limited by the availability and quality of biopsy specimens, potential sampling bias, and binary classification of CD8 infiltration and HLA class I expression. Finally, only baseline serum NSE levels were evaluated, and longitudinal changes in NSE during treatment were not assessed.

Conclusions

Pretreatment serum NSE was associated with both survival outcomes and intratumoral CD8-positive lymphocyte infiltration in patients with ED-SCLC. Although the present findings do not establish NSE as a definitive predictive biomarker, serum NSE may serve as a clinically accessible prognostic marker and exploratory stratification biomarker for chemo-immunotherapy benefit, particularly for PFS. Prospective validation in larger multicenter cohorts, ideally incorporating metastatic site information, molecular subtyping, and detailed immune profiling, is warranted before serum NSE can be used to guide treatment selection in clinical practice.

Acknowledgments

The authors would like to thank Drs. Michitoshi Kimura and Mami Yamaguchi for technical assistance, and Editage (www.editage.com) for English language editing.

Footnote

Reporting Checklist: The authors have completed the STROBE and REMARK reporting checklists. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0275/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0275/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0275/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0275/coif). N.S. reports speaking fees from AstraZeneca K.K. and Nippon Boehringer Ingelheim Co., Ltd. T.S. reports speaking fees from AstraZeneca K.K., Eli Lilly Japan K.K., Chugai Pharmaceutical Co., Nippon Boehringer Ingelheim Co., Ltd., Merck Biopharma Co., Ltd., Takeda Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Nippon Kayaku Co., Ltd., Kyowa Kirin Co., Ltd., MSD K.K., GlaxoSmithKline K.K. (GSK), Sanofi K.K., Regeneron Pharmaceuticals Inc., AMCO Inc., Olympus Marketing Corp., Ono Pharmaceutical Co., Novartis Pharma K.K., and Amgen K.K. H.C. reports speaking fees from Nippon Boehringer Ingelheim Co., Ltd. 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 conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Ethics Committee of Hakodate Goryokaku Hospital (Approval No. 2025-050). Informed consent was obtained from patients using an opt-out procedure via the hospital website.

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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