Urinary biomarkers for monitoring treatment response in neuroblastoma patients.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e22008-e22008
Author(s):  
Hizuru Amano ◽  
Akinari Hinoki ◽  
Hiroo Uchida ◽  
Kazuki Yokota ◽  
Takashi Ishigaki ◽  
...  
Keyword(s):  
Treatment Response ◽  
Urinary Metabolites ◽  
Response To Therapy ◽  
Urinary Biomarkers ◽  
Urine Samples ◽  
Vanillylmandelic Acid ◽  
Urinary Biomarker ◽  
Resistant Group ◽  
Monitoring Treatment ◽  
Monitoring Treatment Response

e22008 Background: Neuroblastoma is the most common extracranial solid tumor in children. Its heterogeneity may account for the non-uniform response to therapy; thus, accurate predictive biomarkers are required. We focused on urinary biomarkers since urine contains numerous low molecular weight metabolites that can be used as reliable and non-invasive biomarkers. We detected more than 2,000 metabolites by liquid chromatography-mass spectrometry (LC-MS) through a comprehensive analysis of metabolites in urine samples of patients with neuroblastoma and identified potential urinary biomarker candidates using the Wilcoxon rank-sum test and random forest. In this study, the levels of urinary biomarker candidates were compared between the responder and resistant groups to identify urinary biomarkers for monitoring treatment response. Furthermore, their effectiveness was compared with minimal residual disease (MRD) markers, which are currently considered to predict tumor relapse. Methods: Thirty-two patients with neuroblastoma were divided into two groups according to their responsiveness to therapy: the responder group, in which patients had no recurrence (60 urine samples from 24 patients) and the resistant group in which patients had a recurrence or died (18 urine samples from 8 patients). Levels of urinary metabolites (homovanillic acid [HVA], vanillylmandelic acid [VMA], 3-methoxytyramine sulfate [3-MTS], vanillactic acid [VLA], 3-methoxytyrosine [3-MTR]), and MRD markers (TH, PHOX2B, MK) were compared between the two groups during treatment. Results: The levels of five urinary metabolites (HVA, VMA, VLA, 3-MTR, 3-MTS) were significantly increased in the resistant group compared to that in the responder group. Conclusions: This study shows that three novel urinary metabolites (VLA, 3-MTR, 3-MTS) are significantly associated with the recurrence or death from neuroblastoma.

Expression Proteomics As Surrogate Biomarkers For Early Treatment Response In Chronic Myeloid Leukemia (CML) Patients

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4016-4016
Author(s):  
Ayodele Alaiya ◽  
Naeem Chaudhri ◽  
Tarek Owaidah ◽  
Jonathan Fox ◽  
Zakia Shinwari ◽  
...  
Keyword(s):  
Chronic Myeloid Leukemia ◽  
Treatment Response ◽  
Early Treatment ◽  
Myeloid Leukemia ◽  
Response To Therapy ◽  
Molecular Response ◽  
Major Molecular Response ◽  
Early Treatment Response ◽  
Monitoring Treatment ◽  
Monitoring Treatment Response

Abstract Purpose Despite advancements in diagnosis and treatment modalities for hematological malignancies, presently, there are no reliable blood tests for disease prognosis or prediction of patient’s response to particular treatments. Identification of such biomarkers for diagnostic or therapeutic response in clinical monitoring of hematologic diseases such as Chronic Myeloid Leukemia (CML) would be very useful. Experimental Design The ability to identify biomarkers in body fluids (i.e., plasma or serum) will not only involve minimally invasive procedures, but also more importantly, the potential for monitoring disease progression and effective response to therapy in relatively early stages. In this study, global proteome analysis of serum, plasma, and bone marrow samples from 28 patients with newly diagnosed chronic–phase CML were analyzed by using expression proteomics technology (label free quantitative liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). The goal was to evaluate for early treatment response and discovery disease–specific /disease-associated proteins for prognostic monitoring and patient’s response to therapy at protein level. Results We identified a panel of 15 differentially expressed proteins (> 2- °- fold change, p< 0.001) to accurately discriminate between CML patients that achieved Major Molecular Response (MMR) vs. No-Major Molecular Response (NoMMR) at 6 months (Figure 1 & Table 1). Six (6) of the 15 identified proteins were filtered and mapped as potential biomarkers using Ingenuity Pathway Analysis. Among the identified proteins implicated in hematological diseases include Group-specific component (vitamin D binding protein), haptoglobin and vitronectin. Others were inter-alpha-trypsin inhibitor heavy chain 1, leucine-rich alpha-2-glycoprotein 1 and metallophosphoesterase 1. We also observed most of these proteins to be located in extracellular space, acts as transporters and have been implicated as markers of hematological disease and inflammatory response. Our data indicates that multivariate analysis of quantitative proteome data can potentially be useful as a means of unsupervised artificial intelligence algorithm for classification and stratification of clinical CML patients. Conclusion Our results highlight the power of proteomics in the discovery of biomarkers for more accurate prediction of prognosis and monitoring treatment response in CML patients. These proteins might be valuable, once validated, to complement the currently existing parameters for reliable and objective prediction of disease progression, monitoring treatment response and clinical outcome of CML patients. Disclosures: No relevant conflicts of interest to declare.

Molecular imaging for monitoring treatment response in breast cancer patients

2013 ◽  
Vol 717 (1-3) ◽  
pp. 2-11 ◽  
Author(s):  
Frederike Bensch ◽  
Michel van Kruchten ◽  
Laetitia E. Lamberts ◽  
Carolien P. Schröder ◽  
Geke A.P. Hospers ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Imaging ◽  
Treatment Response ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Monitoring Treatment ◽  
Monitoring Treatment Response

The potential of monitoring treatment response in non-small cell lung cancer using circulating tumour cells

2019 ◽  
Vol 19 (8) ◽  
pp. 683-694 ◽  
Author(s):  
Marianna Gallo ◽  
Antonella De Luca ◽  
Daniela Frezzetti ◽  
Valeria Passaro ◽  
Monica R. Maiello ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Treatment Response ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Tumour Cells ◽  
Circulating Tumour Cells ◽  
Small Cell Lung ◽  
Monitoring Treatment ◽  
Monitoring Treatment Response

scholarly journals Efficacy of BAFF in Monitoring Treatment Response in Early Vietnamese Systemic Sclerosis Patients

2019 ◽  
Vol 7 (2) ◽  
pp. 264-268
Author(s):  
Vu Nguyen Minh ◽  
Khang Tran Hau ◽  
Matushita Takashi ◽  
Vinh Nguyen Ha ◽  
Long Hoang Bao ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Serum Level ◽  
Response To Therapy ◽  
B Cell Activating Factor ◽  
Monitoring Treatment ◽  
Monitoring Treatment Response ◽  
Baff Level

BACKGROUND: B-cell activating factor (BAFF) is considered to have a role in the pathogenesis of systemic sclerosis (SSc). AIM: We conducted a longitudinal study on early SSc patients to determine the change in BAFF serum level after treatment and its association with organ involvements. METHODS: A total of 46 patients (32 diffuse, 14 limited) were recruited, among which 35 patients (24 diffuse, 11 limited) completed 12-month follow-up. RESULTS: Higher pretreatment BAFF levels were observed in patients with positive anti-topoisomerase antibody (ATA) (2252.1 ± 899.7 pg/ml versus 1475.5 ± 697.6 pg/ml in ATA-negative patients; p = 0.01) and muscular involvement (2741.9 ± 1039.9 pg/ml versus 1897.2 ± 762.9 pg/ml in patients without muscular involvement; p = 0.005). Lower levels were observed in patients with interstitial lung disease (ILD) (1926.7 ± 757.9 pg/ml versus 2721.6 ± 1131.4 pg/ml in non-ILD patients; p = 0.01). After treatment, BAFF level reduced significantly in diffuse SSc patients (1652.2 ± 892.7 pg/ml versus 2147.6 ± 945.5 pg/ml before treatment; p = 0.03). CONCLUSION: Patients with worsening outcome had the highest pretreatment BAFF level and was associated with increased BAFF level after treatment. BAFF can be used to predict and monitor patients’ response to therapy.

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