Dataset Information

Serum protein fingerprinting by PEA immunoassay coupled with a pattern-recognition algorithms distinguishes MGUS and multiple myeloma.

ABSTRACT: Serum protein fingerprints associated with MGUS and MM and their changes in MM after autologous stem cell transplantation (MM-ASCT, day 100) remain unexplored. Using highly-sensitive Proximity Extension ImmunoAssay on 92 cancer biomarkers (Proseek Multiplex, Olink), enhanced serum levels of Adrenomedullin (ADM, P_corr= .0004), Growth differentiation factor 15 (GDF15, P_corr= .003), and soluble Major histocompatibility complex class I-related chain A (sMICA, P_corr= .023), all prosurvival and chemoprotective factors for myeloma cells, were detected in MM comparing to MGUS. Comparison of MGUS and healthy subjects revealed elevation of angiogenic and antia-poptotic midkine (P_corr= .0007) and downregulation of Transforming growth factor beta 1 (TGFB1, P_corr= .005) in MGUS. Importantly, altered serum pattern was associated with MM-ASCT compared to paired MM at the diagnosis as well as to healthy controls, namely by upregulated B-Cell Activating Factor (sBAFF) (P_corr< .006) and sustained elevation of other pro-tumorigenic factors. In conclusion, the serum fingerprints of MM and MM-ASCT were characteristic by elevated levels of prosurvival and chemoprotective factors for myeloma cells.

SUBMITTER: Schneiderova P

PROVIDER: S-EPMC5642488 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Serum protein fingerprinting by PEA immunoassay coupled with a pattern-recognition algorithms distinguishes MGUS and multiple myeloma.

Schneiderova Petra P Pika Tomas T Gajdos Petr P Fillerova Regina R Kromer Pavel P Kudelka Milos M Minarik Jiri J Papajik Tomas T Scudla Vlastimil V Kriegova Eva E

Oncotarget 20160812 41

Serum protein fingerprints associated with MGUS and MM and their changes in MM after autologous stem cell transplantation (MM-ASCT, day 100) remain unexplored. Using highly-sensitive Proximity Extension ImmunoAssay on 92 cancer biomarkers (Proseek Multiplex, Olink), enhanced serum levels of Adrenomedullin (ADM, Pcorr= .0004), Growth differentiation factor 15 (GDF15, Pcorr= .003), and soluble Major histocompatibility complex class I-related chain A (sMICA, P ...[more]

PMID: 29050213

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Project description:ImportanceObesity is a risk factor associated with multiple myeloma (MM) and its precursor, monoclonal gammopathy of unknown significance (MGUS). However, it is unclear how cumulative exposure to obesity affects the risk of MGUS progression to MM.ObjectiveTo determine the association of cumulative exposure to excess body mass index (EBMI), defined as BMI (calculated as weight in kilograms divided by height in meters squared) greater than 25, with risk of MGUS progression to MM.Design, setting, and participantsThis cohort study included patients with MGUS, including immunoglobin G, immunoglobin A, or light chain MGUS, from the nationwide US Veterans Health Administration database from October 1, 1999, to December 31, 2021. A published natural language processing-assisted model was used to confirm diagnoses of MGUS and progression to MM. Data were analyzed from February 12 to November 4, 2024.ExposuresCumulative EBMI was calculated by area under the curve of measured BMI subtracting the reference BMI at 25 during the first 3 years after MGUS diagnosis.Main outcomes and measuresThe main outcome was progression from MGUS to MM. Multivariable Fine-Gray time-to-competing-event analyses, with death as the competing event, were used to determine associations.ResultsThe cohort included 22 429 patients with MGUS (median [IQR] age, 70.5 [63.5-77.9] years; 21 613 [96.4%] male), with 8329 Black patients (37.1%) and 14 100 White patients (62.9%). There were 4862 patients (21.7%) with reference range BMI (18.5 to <25), 7619 patients (34.0%) with BMI 25 to less than 30, and 8513 patients (38.0%) with BMI 30 or greater at the time of MGUS diagnosis. Compared with reference range BMI at MGUS diagnosis, patients with BMI 25 to less than 30 (adjusted hazard ratio [aHR], 1.17; 95% CI, 1.03-1.34) or 30 or greater (aHR, 1.27; 95% CI, 1.09-1.47) at MGUS diagnosis had higher risk of progression to MM. In patients with reference range BMI at MGUS diagnosis, each 1-unit increase of EBMI per year was associated with a 21% increase in progression risk (aHR, 1.21; 95% CI, 1.04-1.40). However, for patients with BMI 25 or greater at MGUS diagnosis, the incremental risk associated with cumulative EBMI exposure was not statistically significant.Conclusions and relevanceThis cohort study found that, for patients with BMI 18.5 to less than 25 at the time of MGUS diagnosis, cumulative exposure to BMI 25 or greater was associated with an increased risk of progression. These findings suggest that for these patients, maintaining a healthy and stable weight following MGUS diagnosis may prevent progression to MM.

Project description:Seahorse is a valuable marine-animal drug widely used in traditional Chinese medicine (TCM), and which was first documented in the "Ben Cao Jing Ji Zhu" during the Liang Dynasty. Hippocampus kelloggi (HK) is the most common seahorse species in the medicinal material market and is one of the genuine sources of medicinal seahorse documented in the Chinese pharmacopeia. It is mainly cultivated in the Shandong, Fujian, and Guangxi Provinces in China. However, pseudo-HK, represented by Hippocampus ingens (HI) due to its similar appearance and traits, is often found in the market, compromising the safety and efficacy of clinical use. Currently, there is a lack of reliable methods for identifying these species based on their chemical composition. In this study, we employed, for the first time, a strategy combining gas chromatography-mass spectrometry (GC-MS) fingerprints and chemical patterns in order to identify HK and HI; it is also the first metabolomic study to date of HI as to chemical components. The obtained results revealed remarkable similarities in the chemical fingerprints, while significant differences were also observed. By employing hierarchical cluster analysis (HCA) and principal component analysis (PCA), based on the relative contents of their characteristic peaks, all 34 samples were successfully differentiated according to their species of origin, with samples from the same species forming distinct clusters. Moreover, nonadecanoic acid and behenic acid were exclusively detected in HK samples, further distinguishing them from HI samples. Additionally, the relative contents of lauric acid, tetradecanoic acid, pentadecanoic acid, n-hexadecanoic acid, palmitoleic acid, margaric acid, oleic acid, fenozan acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) exhibited significant differences between HK and HI (p < 0.0001), as determined by an unpaired t-test. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified seven components (DHA, EPA, n-hexadecanoic acid, tetradecanoic acid, palmitoleic acid, octadecanoic acid, and margaric acid) with high discriminatory value (VIP value > 1). Thus, nonadecanoic acid, behenic acid, and these seven compounds can be utilized as chemical markers for distinguishing HK from HI. In conclusion, our study successfully developed a combined strategy of GC-MS fingerprinting and chemical pattern recognition for the identification of HK and HI, and we also discovered chemical markers that can directly differentiate between the two species. This study can provide a foundation for the authentication of Hippocampus and holds significant importance for the conservation of wild seahorse resources.

Dataset Information

Serum protein fingerprinting by PEA immunoassay coupled with a pattern-recognition algorithms distinguishes MGUS and multiple myeloma.

Publications

Serum protein fingerprinting by PEA immunoassay coupled with a pattern-recognition algorithms distinguishes MGUS and multiple myeloma.

Similar Datasets

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