Abstract
Introduction
Neuroendocrine tumors (NETs) are rare neoplasms that occur in various locations throughout the body. Despite their usually benign character, they might manifest with distant metastases. N-terminal prohormone of brain natriuretic peptide (NT-proBNP) has previously been described as a useful biomarker in diagnosing carcinoid heart disease (CHD), a common advanced NETs manifestation. We observed plasma concentrations of NT-proBNP in metastatic midgut NETs over a 4-year period.
Objectives
We aimed to explore NT-proBNP concentrations in states of varying levels of cell proliferation and disease status. Our goal was to investigate NT-proBNP’s role in predicting disease progression in relation to previous research and up-to-date scientific guidelines.
Patients and methods
We performed a retrospective multivariate analysis of NT-proBNP concentrations in 41 midgut NETs patients treated with somatostatin analogs, all with liver metastases. NT-proBNP concentrations were measured in every patient across 16 evenly distanced time points over a 48-month period and were compared to variables such as sex, age, grading, Ki-67, primary tumor location, and CT findings.
Results
NT-proBNP concentrations correlated positively with higher liver tumor burden, higher grading, high Ki-67 levels, and with progressive disease in CT. There were no differences in NT-proBNP levels with regard to primary location (ileum vs jejunum), sex, and age.
Conclusion
We conclude that NT-proBNP is a useful analyte for monitoring NETs progression, due to its increased concentration in scenarios implying increased cellular proliferation. These long-term follow-up results align with previous findings and suggest an additional role for NT-proBNP in diagnostic algorithms, beyond a CHD biomarker.
Introduction
Neuroendocrine tumors (NETs) make up a heterogeneous group of neoplasms stemming from the diffuse endocrine system (DES) (1). Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) represent a subdivision, most commonly originating in the jejunum and ileum, accounting for up to 70% of all NETs (2, 3). Partly due to their embryonic origin, GEP-NETs differ in genomic structure as well as in clinical presentation and applicable biomarkers (4). Another factor by which NETs can be described is their ability to produce and secrete hormones (functional NETs possess this ability, while nonfunctional NETs do not). Due to this characteristic, numerous researchers over the years explored the use of specific and nonspecific biomarkers for both prognostic and diagnostic purposes (e.g. 5-hydroxyindoleacetic acid, neuron-specific enolase, chromogranin A (CgA), and beta subunit of human chorionic gonadotropin) (5, 6, 7, 8). Identification of an optimal biomarker for a given type of tumor is important for early disease diagnosis, monitoring, and long-term patient care. However, due to the subpar diagnostic properties of currently used biomarkers, ongoing research focuses on the search for new analytes (9). Despite the usually benign character of NETs, metastases (most often to the liver) are a relatively common occurrence, with a lifetime prevalence of 28–77%. Their presence is associated with worse prognosis and decreased quality of life (10, 11, 12, 13, 14).
Carcinoid syndrome (CS) is characterized by increased secretion of serotonin, and other biogenic amines and peptides. It manifests as a set of symptoms including diarrhea, skin flushing, and abdominal pain (15). Patients with liver metastases frequently suffer from CS, as vasoactive substances easily reach systemic circulation through the hepatic vein. Additionally, the presence of metastases affects liver metabolism, leading to the accumulation of substances causing CS (16). Despite being usually associated with advanced-stage NET, patients with locoregional disease also present a high incidence of CS. As observed by Leong et al., CS is a major risk factor for reduced overall survival (OS) in NETs (17). A major cause of morbidity and mortality in CS is carcinoid heart disease (CHD) (18). CHD is one of the most common and most severe complications of CS patients, with a prevalence of 20–50% among CS patients and 3-year survival of around 31% (15). It is considered to be caused by excessive hormone secretion (predominantly serotonin), which leads to the formation of fibrous, plaque-like deposits on the patient’s endocardium and heart valves. Progressive deformation of the valves results in heart failure, usually right-sided (19).
N-terminal pro-B-type natriuretic peptide (NT-proBNP), is a biologically inactive, 76-amino acid-long prohormone used as a diagnostic biomarker for heart failure (20). Its use as a diagnostic and prognostic biomarker has also been described in CS and CHD by a number of researchers and is considered a part of the diagnostic algorithm for these conditions (15, 21, 22, 23, 24, 25).
Despite thorough research on NT-proBNP as a CHD biomarker, its potential role in monitoring tumor progression and its predictive value remain poorly understood. This study aims to investigate the utility of NT-proBNP as a monitoring tool in midgut NETs. We monitored serum NT-proBNP concentrations over a 4-year period and examined, whether elevated levels can serve as indicators of the disease status. Additionally, we explored the relationship between NT-proBNP levels and other variables, such as patient demographics and hallmarks of cell proliferation. Finally, we give our opinion on the prospect of its use as biomarker in NETs.
Patients and methods
Patients, inclusion and exclusion criteria
We have retrospectively analyzed an institutional database of patients diagnosed with midgut NET and treated with long-acting somatostatin analogs (octreotide, intramuscular injection, Sandostatin LAR 30 mg once every 4 weeks, Novartis, Basel, Switzerland; lanreotide, Somatuline Autogel 120 mg once every 4 weeks, Ipsen, Paris, France).
Patients were evaluated based on the following variables: sex, age, disease status according to RECIST 1.1, liver tumor burden (LTB), Ki-67 proliferation index, grading, and primary location of the tumor. A detailed description of the study group is presented in Table 1, and a visual presentation of the patients’ demographics is shown in Fig. 1.
Visual presentation of study subjects’ demographics.
Citation: Endocrine Connections 12, 10; 10.1530/EC-23-0249
Study group structure.
| Variable | All patients (n = 41) |
|---|---|
| Demographics | |
| Age, years | 63 (9)* |
| Sex | |
| Male | 12 (29%) |
| Female | 29 (71%) |
| Clinical characteristics | |
| Primary tumor location | |
| Jejunum | 18 (44%) |
| Ileum | 23 (56%) |
| Liver tumor burden | |
| 10% | 23 (56%) |
| 25% | 18 (44%) |
| Grading | |
| G1 | 19 (46%) |
| G2 | 22 (54%) |
| Treatment response | |
| sd | 20 (49%) |
| pd | 21 (51%) |
| Ki 67 | |
| 1% | 2 (5%) |
| 2% | 17 (41%) |
| 4% | 2 (5%) |
| 5% | 8 (20%) |
| 10% | 12 (29%) |
*Mean (s.d.).
LTB was defined as the amount of tumor growth in the liver (in this case metastatic NET lesions), measured as a percentage of total liver volume on a CT scan. LTB was evaluated based on the patient’s most recent CT scan, performed up to 6 months prior to the final NT-proBNP sampling. Subjects were divided into two groups: less than 10% and up to 25% LTB. The same CT scan was used to evaluate disease status. Disease status was distinguished, according to RECIST 1.1, into stable disease (SD) and progressive disease (PD). There were no patients fitting into any other RECIST 1.1 subgroup.
Ki-67 was based on histopathological evaluation upon diagnosis and was analyzed as a continuous variable. Grading was divided into G1 and G2 groups using the 2022 WHO criteria (26). Primary tumor location included NET of midgut origin: ileum and jejunum. Other primary locations were excluded due to potential differences in the characteristics of NET based on embryonic origin. Patients with neuroendocrine cancer (NEC) were also excluded following the same principle. To eliminate possible interference regarding NT-proBNP concentrations, patients with a history of heart failure preceding NET diagnosis were excluded. All patients were treated with long-acting somatostatin analogs (SSA) administered via intramuscular injection every 4 weeks. Patients who were not undergoing treatment with SSA or were administered SSA in different intervals were excluded from the study, due to possible influence on NT-proBNP concentrations.
Biological material sampling protocol
On the day of the SSA injection, patients were admitted to the outpatient clinic at the Department of Endocrinology for a routine follow-up visit, during which medication was administered and diagnostic procedures were performed. A venous blood sample was taken prior to the injection and transferred to a laboratory unit at the hospital, where plasma was obtained by centrifugation. Plasma samples were analyzed within 12 h of collection. NT-proBNP concentrations were measured at 3-month intervals for a period of 48 months, resulting in 16 measurements for each patient and 656 measurements in total across the study group. Results were included in the patient database and subject to statistical analysis.
Biochemical assay
NT-proBNP in the blood samples collected from the study participants was measured using Roche Elecsys NT-proBNP test (Roche Diagnostics GmbH). The assay has an analytical measuring range of 10–35,000 pg/mL. There were no results outside of the test measuring range in our analysis.
Statistical analyses
Median, mean, minimum, maximum, 25th percentile, and 75th percentile values for each patient’s NT-proBNP concentrations were calculated. Normality of distribution was checked by employing the Shapiro–Wilk test. In normally distributed variables with unequal variances, Cochrane–Cox test was used, while the Mann–Whitney U test was employed for non-normally distributed variables. Spearman’s rank correlation coefficient was used to examine the relationship between continuous variables while the chi-squared test was employed to investigate the relationship between categorical variables. The level of statistical significance was set at α = 0.05. The result was considered statistically significant when two-tailed P < α. Statistical analysis was performed using Statistica 13 (TIBCO Software Inc., Palo Alto, CA, USA).
Bioethical issues
The study was approved by the Regional Bioethical Committee at the Poznan University of Medical Sciences.
Results
LTB showed a strong positive correlation with NT-proBNP. Level of statistical significance was <0.001 across all performed descriptive statistics. Mean, maximum, and 75th percentile in the group of SD patients showed normal distribution, as opposed to the median, minimum and 25th percentile in the SD group, and all descriptive statistics in PD group. Further statistical analysis was adjusted for the discrepancy, using Cochrane–Cox test and Mann–Whitney U test accordingly. Regardless of the applied test, patients in the PD group showed higher NT-proBNP values than those within SD group. We found positive correlation between NT-proBNP concentrations and histopathological indicators of cellular proliferation (i.e. Ki-67 values, grading). In LTB and disease status, P-value was below .001.
The graphic presentation of descriptive statistics of median NT-proBNP concentrations across the test group in variables that showed statistical significance (grading, LTB, treatment response) is depicted in Fig. 2. Comparative analysis of mean NT-proBNP concentration and Ki-67 is shown in Fig. 3. Finally, we established that grading correlates positively with both, PD versus SD according to RECIST 1.1, and with higher LTB as presented in Table 2. Full statistical analysis results, including underlying data and statistically insignificant findings, are uploaded separately as Supplementary Material (Supplementary Tables 1.1–8.4, see section on supplementary materials given at the end of this article).
Relationship between NT-proBNP and selected variables. (A) Box and whiskers plot showing the distribution of median NT-proBNP concentrations grouped by liver tumor burden (LTB). NT-proBNP levels (pg/mL) are plotted on the y-axis. The inside square indicates the median NT-proBNP value (LTB 10% median = 532.87 pg/mL, LTB up to 25% median = 8413.54 pg/mL). The box edges display the 25th and 75th percentiles, while the whiskers indicate minimum and maximum values. Patients with higher LTB have increased NT-proBNP levels. (B) Box and whiskers plot displaying the distribution of median NT-proBNP concentrations grouped by tumor grading. NT-proBNP levels (pg/mL) are plotted on the y-axis. The inside square indicates the median NT-proBNP value for each tumor grade (G1 median = 522.49 pg/mL, G2 median = 6888.11 pg/mL). The box edges display the 25th and 75th percentiles, while the whiskers indicate minimum and maximum values. Patients with G2 grade tumors have higher NT-proBNP levels compared to those with G1 tumors. (C) Box and whiskers plot showing distribution of median NT-proBNP concentrations grouped by treatment response status. NT-proBNP levels (pg/mL) are plotted on the y-axis. The inside square indicates the median NT-proBNP value for patients with stable disease (SD median = 522.99 pg/mL) and progressive disease (PD median = 7266.49 pg/mL). The box edges display the 25th and 75th percentiles, while the whiskers indicate minimum and maximum values. Patients with progressive disease have increased NT-proBNP levels compared to those with stable disease.
Citation: Endocrine Connections 12, 10; 10.1530/EC-23-0249
Scatter plot displaying the distribution of mean NT-proBNP concentrations based on tumor Ki-67 value in patients with metastatic NETs. Ki-67 percentage is plotted on the x-axis and mean NT-proBNP level (pg/mL) is plotted on the y-axis. Each data point represents an individual patient's Ki-67 and mean NT-proBNP values. Patients with higher Ki-67 values have increased NT-proBNP levels.
Citation: Endocrine Connections 12, 10; 10.1530/EC-23-0249
Relationship between grading and liver tumor burden and between grading and treatment response according to RECIST 1.1.
| Variable | Grading | P-value for the Pearson’s chi-square test | ||
|---|---|---|---|---|
| G1 | G2 | Total | ||
| Liver tumor burden, n (%) | ||||
| 10% | 18 (78.26%) | 5 (21.74%) | 23 | <0.001 |
| 25% | 1 (5.56%) | 17 (94.44%) | 18 | |
| Treatment response, n (%) | ||||
| sd | 17 (85%) | 3 (15%) | 20 | <0.001 |
| pd | 2 (9.52%) | 19 (90.48%) | 21 | |
Discussion
NT-proBNP proved to be an important NET biomarker in a number of studies, specifically in a group of CS and CHD patients (23, 24). Its persistent monitoring allows to detect individuals most likely to develop CHD and to adjust diagnostic process according to their needs while improving patient outcomes (27). Levy et al. suggest intensifying the screening in cases where NT-proBNP concentrations rise above 55.1 pg/mL (6.5 pmol/L), by performing transthoracic echocardiography (TTE) every 1–2 years and retorting to just monitoring of NT-proBNP without echocardiography below said cutoff level (23). A more lenient approach is recommended by the Polish Network of Neuroendocrine Tumours and the European Neuroendocrine Tumor Society. According to the most recent guidelines, NT-proBNP concentration above 260 pg/mL (31 pmol/L) is indicative of CHD and TTE is considered a gold standard in CHD diagnosis for patients with elevated NT-proBNP (15, 20, 21, 26, 28).
Although the consideration of NT-proBNP as a diagnostic biomarker in CS and CHD is based on prospective cohort studies and uniform expert agreement, there is no such consensus for its use as a prognostic tool (15, 21). The lack of suitable biomarkers remains one of the crucial unmet needs in the world of NETs. The experts tend to agree that single biomarkers are unlikely to fill the void in a disease as complex and diverse as NET. This led to a rise in popularity of researching multianalyte assays and the use of algorithmic analysis (e.g. NETest). Algorithms can be modified and expanded as more data become available, and it is possible that NT-proBNP could be incorporated into such a script (29).
We observed that a large volume of liver metastases results in increased NT-proBNP concentrations, probably due to the larger mass of the tumor contributing to the increased hormone secretion and impaired liver function (i.e. failure to break down substances contributing to the rise of NT-proBNP) (30). As noted by Dobson et al., liver metastases are present in 97% of the CHD patients, compared to 79% of patients without CHD, in agreement with our observations. Following the same rationale, we have seen greater NT-proBNP concentrations in the group of G2, rather than G1 tumors, and in patients with higher Ki-67 values. However, Bhattacharyya et al. found no correlation between CHD diagnosis and tumor grade (24). In comparing the two studies, we need to keep in mind the limited sample sizes and the fact that CHD diagnosis and elevated NT-proBNP are not equal. NT-proBNP is typically considered a screening tool, whereas diagnosis of CHD is usually confirmed after performing morphological assessment of heart tissue by using heart echocardiography (15).
An important aspect of this research is NT-proBNP’s potential value as a prognostic biomarker. Patients with PD on the most recent CT scan showed higher NT-proBNP concentrations across all statistical parameters made throughout the observation period (minimum, maximum, mean, median, 25th, and 75th percentile). Our study offers a different perspective than that of Dobson et al., in which death and CHD progression (diagnosed using TTE) were treated as research endpoints, while NT-proBNP and radiological progression were used as variables and were not compared to each other. Therein, a higher baseline median NT-proBNP value was an independent predictor of CHD progression. Meanwhile, the rise of NT-proBNP by 100 ng/L during the observation period increased the risk of death by 11%, however, with no effect on CHD progression (31). Further confirmation of its potential use can be found in a study by Korse et al., where NT-proBNP concentrations were found to be a negative predictor of a 5-year survival rate in NETs, both independently and in a multivariate model together with CgA concentrations (32).
It seems that CHD and elevated NT-proBNP concentrations are not linked to sex, age, and primary tumor site, as neither our study nor previous publications found any correlation between these variables (30).
When discussing the results of the present study, several limitations should be considered. NETs are a rare disease with the incidence rate ranging from around 2 to 5 cases per 100,000; therefore, most of the studies will focus on a limited number of patients (as it is the case in this and other studies quoted in the present paper) (33, 34, 35). However, despite the small sample size, each patient’s NT-proBNP concentrations were observed over a long period of time and in multiple samples for each subject. Comparing not only the mean and median values of each patient’s NT-proBNP levels but also their borderline concentrations highlights significant differences in the group of patients with progressive disease in relation to outcomes from various statistical perspectives. Finally, our study was restricted to the use of NT-proBNP in late-stage disease, as all study subjects were metastatic and treated with SSA at the time of the inclusion. Exploring the use of NT-proBNP as an early detection biomarker was beyond the scope of this study, which presents a limitation.
NT-proBNP’s role as a neoplasm predictor has been discussed previously in conditions other than NET. For instance, small-cell lung cancer has also been found able to produce natriuretic peptides (36). In patients with no prior history of cardiac diseases or cardiotoxic medication intake, NT-proBNP has been described as a predictor of neoplastic process (37, 38). Natriuretic peptides have also been found to diminish cancerous cell numbers through inhibition of cGMP-mediated DNA synthesis, however, this has not been proven for NT-proBNP itself (39). These findings suggest that the exact mechanism of elevation in NT-proBNP concentration is more complex than previously theorized.
In our opinion, NT-proBNP can be an important prognostic NET biomarker. Despite showing little use as a screening tool in early-stage NET without distant metastases, its wide availability, reliability, and repeatability of different laboratory assays make it a useful analyte in monitoring of the disease. In this study, we highlight several potential clinical applications of NT-proBNP measurement. Aside from its use as a diagnostic biomarker in CHD, we think it offers additional value in the assessment of the metastatic process. In order to accurately describe its place (or the lack thereof) in the theranostic process of NET, further large-scale studies are needed to counteract the major flaw of researching rare diseases. Furthermore, we suggest that physicians should pay close attention to patients with elevated levels of NT-proBNP.
NETs are a complex group of tumors, and we are still yet to understand the full extent of this disease. Even though NT-proBNP is unlikely to be the one and only solution to the problem of NET biomarkers, it is beneficial to use it as a sort of magnifying glass to select individuals at risk of developing CHD or showing signs of disease progression.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/EC-23-0249.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding
This research did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector.
Author contribution statement
PK – study design, statistical analysis, data interpretation, writing and final revision of the manuscript; graphic design; PG – study design, statistical analysis, data interpretation, writing and final revision of the manuscript, consultations for intellectual content; JM – statistical analysis, data interpretation, writing the manuscript and final revision of the manuscript; MC – statistical analysis, data interpretation, writing and final revision of the manuscript; AM – data interpretation, writing and final revision of the manuscript; PP – data interpretation, writing and final revision of the manuscript, proofreading; GM – data interpretation, writing and final revision of the manuscript, consultations for intellectual content; MR – data interpretation, writing and final revision of the manuscript, consultations for intellectual content.
Acknowledgements
PK is a participant of STER Internationalisation of Doctoral Schools Programme from NAWA Polish National Agency for Academic Exchange No. PPI/STE/2020/1/00014/DEC/02. The authors would like to thank Izabela Miechowicz for performing descriptive statistics and for her technical support throughout the manuscript preparation process.
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