Investigation of blood-based biomarkers as prognostic and predictive factors in patients with neuroendocrine neoplasms
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Abstract
The current study is being conducted to determine whether plasma cfDNA, cfDNA
hypomethylation, cfDNA integrity index or quantitative concentrations of ALU 115-, ALU 260-,
LINE-1 97-, LINE-1 266-bp fragments can be robust biomarkers for the diagnosis and
prognosis of NENs. The aim is to establish a new biomarker for the diagnosis and follow-up
of NEN patients on a molecular basis. This study evaluates the efficiency of these suggested
biomarkers in different phases of NEN cancer and the association between each biomarker
and clinicopathological tumor characteristics.
Methods: The cfDNA plasma samples originated from 62 patients, aged (33-87), with
pathologically confirmed NEN, and 29 control, aged (24-77) years, from neuroendocrine
patients without neoplastic diseases were evaluated. Depending on the disease, the patients
were categorized into different groups to 47 patients with the metastatic NET disease
(mNET), 8 nonmetastatic NET disease (non-mNET), and 7 NEC disease. Here, we examined
the cfDNA plasma concentration, concentration of long and short cfDNA fragments measured
via ALU and LINE-1 repetitive DNA elements, cfDNA integrity, and cfDNA hypomethylation.
The integrity index was calculated using: the ALU 266/115 ratio and the LINE-1 266/97 ratio,
based on the data obtained by real-time PCR. The cfDNA hypomethylation was assessed
based on the methylation status of ALU and was considered representative of the global
hypomethylation status. The discriminatory power of each logistic model was investigated
using the area under the ROC curve (AUC).
Results: cfDNA biomarker: NEN Patients, showed a higher, but not significant increase of
cfDNA concentration in comparison to healthy controls. Dividing the study patients’ group to
non-metastatic NET (none- mNET), metastatic NET (mNET) and NEC patients, a significant
increase for mNET could be detected. Further analysis revealed, the more advanced the
NEN disease, the higher the cfDNA level, leading to significant differences for controls to
patients with a G3 tumor or a significant increase for patients with a moderate or high tumor
burden. ROC curve for discriminating patients with grade 3(G3) NENs from healthy subjects
had an AUC of 0.80 (at 50% sensitivity and 100% specificity). The ROC curve for
discriminating patients with moderate and high tumor burden displayed an AUC of 0.77 and
for patients with high tumor burdens an AUC of 0.84 (at 75% sensitivity and 97.4%
specificity). The analysis confirmed higher cfDNA levels in patients were associated with an
increased risk of death. The patients with lung tumor origin had a higher quantity of cfDNA
than patients with a primary tumor of the ileum. Fragment sizes biomarker: No significant
difference was observed in levels of short and langer fragments between groups, but a
significant decrease in ALU 260-bp fragment level was detected in samples with no tumor
compared to large tumor burdens. ROC curve analysis showed a good distinguish accuracy
between these two groups (AUC: 0.81, 100% sensitivity, and 52.6% specificity). cfDNA
integrity index (cfDII) biomarker: We did not find any significant differences regarding ALU
cfDII between the groups. In contrast, the LINE-1 cfDII was significantly decreased in plasma
of NEN patients compared to healthy control, but it showed a low accuracy in ROC analysis
(AUC=0.67). For LINE-1 cfDII, we could see in the more advanced the NEN disease, the
lower the LINE-1 cfDII, leading to a good discriminatory AUC of 0.80 (at 90% sensitivity and
69% specificity) for G3 classified tumors or an AUC of 0.83 (at 87.5% sensitivity and 71%
Summary
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specificity) for patients with a high tumor burden to healthy controls. In addition, a lower
LINE-1 cfDII was observed in patients with primary tumors in the small intestine than in
patients with the primary tumor in the ileum. ALU hypomethylation biomarker: Significant
higher hypomethylation was observed in patients with mNETs than patients with non mNETs, with a sensitivity of 87.5% at 79.6%% specificity and an AUC of 0.87. Regarding
tumor grade and tumor burden, the more advanced the disease, the higher was the
measured hypomethylation level. A great discriminatory accuracy was calculated between
patients with a high tumor burden and healthy or cured patients (AUC: 0.96; at 100%
sensitivity and 86.8% specificity). A positive correlation between hypomethylation and CgA
levels was detected. Combined biomarkers: With the multiparametric ROC curve analysis
including cfDNA, hypomethylation, and CgA level as a biomarker, a great diagnostic
accuracy between patients with mNET and NEC to patients with non-mNET could be
calculated with 66.67% positive predictive and 90.91% negative predictive values
(AUC:0.91).
Conclusion: Current findings support the role of the tested biomarkers for prognosis,
progressive and predictive, but not a diagnostic. The combination of tested biomarkers
contributes to better efficiency relative to the single-use them. The novel biomarkers can be
valuable biomarkers for the management of patients, optimal treatment, and open new
therapy views correlated with sickness course. ALU hypomethylation was the most promising
molecular marker that would be useful in monitoring patients for disease progression.
However, these potential molecular biomarkers need clinical confirmation and more
validation to use as a non-invasive tool for routine monitoring in a clinical setting.