Fast Screening Method of Biological Samples Based on Needle Stochastic Sensors for Early Detection of Gastric Cancer

Early detection of cancer is essential for saving the life of patients. Needle stochastic sensors were proposed as new tools for the fast screening of biological samples. The design of the stochastic sensors was based on the immobilization of protoporphyrin IX in pastes of S-doped graphene. The selected biomarkers were CEA and CA19-9. High sensitivities, and wide linear concentration ranges as well as low limits of quantification were achieved. The proposed sensors were validated; student t-test shown that the proposed needle stochastic sensors can be reliably used for the pattern recognition and quantification of CEA and CA19-9 in whole blood, gastric tumor tissue, saliva, and urine.

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The Fast Screening Method of Biological Samples for Early Diagnosis of Gastric Cancer

Multidisciplinary Cancer Investigation ◽

10.30699/mci.4.3.25 ◽

2020 ◽

Vol 4 (3) ◽

pp. 25-30

Author(s):

Raluca Ioana Stefan-van Staden ◽

Ruxandra Maria Ilie-Mihai ◽

Simona Gurzu ◽

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...

Keyword(s):

Gastric Cancer ◽

Early Diagnosis ◽

Biological Samples ◽

Screening Method ◽

Fast Screening

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Validation of a Screening Method Based on a Needle Stochastic Sensor for the Determination of Interleukins 1β, 6, and 12 in Biological Samples

Proceedings ◽

10.3390/proceedings2020055014 ◽

2020 ◽

Vol 55 (1) ◽

pp. 14

Author(s):

Sorin Sebastian Gheorghe ◽

Ruxandra Maria Ilie-Mihai ◽

Raluca-Ioana Stefan-van Staden ◽

Alexandru Bratei

Keyword(s):

Brain Cancer ◽

Biological Samples ◽

Whole Blood ◽

Screening Method ◽

Protoporphyrin Ix ◽

Tissue Samples ◽

Fast Screening ◽

Relative Standard ◽

Diamond Paste

Interleukins proved to be valuable biomarkers for different diseases. Interleukins 1β, 6, and 12 can be used as biomarkers for brain cancer diagnosis, and therefore this paper proposed a needle stochastic sensor based on protoporphyrin IX immobilized in nano-diamond paste for fast screening of biological samples, such as whole blood, urine and brain tumoral tissue, for these interleukins. The results obtained using this needle stochastic sensor proved that the interleukins 1β, 6, and 12 can be reliably determined from whole blood, urine and brain tumoral tissue, with recoveries higher than 96.00% and with relative standard deviations lower than 1.00%. The validation of the method was performed using whole blood and tissue samples collected from the patients confirmed with brain tumor.

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(Invited) Fast Screening Tests for Early Diagnosis of Gastric Cancer, Based on Molecular Recognition and Assay of Maspin in Biological Samples

ECS Meeting Abstracts ◽

10.1149/ma2021-02561655mtgabs ◽

2021 ◽

Vol MA2021-02 (56) ◽

pp. 1655-1655

Author(s):

Raluca Van Staden ◽

Ruxandra Maria Ilie-Mihai ◽

Damaris Cristina Ghrorghe ◽

Iuliana Mihaela Bogea

Keyword(s):

Gastric Cancer ◽

Molecular Recognition ◽

Early Diagnosis ◽

Biological Samples ◽

Screening Tests ◽

Fast Screening

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Screening for Early Gastric Cancer Using a Noninvasive Urine Metabolomics Approach

Cancers ◽

10.3390/cancers12102904 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2904

Author(s):

Hyuk Nam Kwon ◽

Hyuk Lee ◽

Ji Won Park ◽

Young-Ho Kim ◽

Sunghyouk Park ◽

...

Keyword(s):

Gastric Cancer ◽

Early Detection ◽

Performance Test ◽

Screening Method ◽

Endoscopic Examination ◽

Multivariate Statistical ◽

Metabolic Markers ◽

Intramucosal Cancer ◽

Incidence And Mortality ◽

Urine Metabolomics

The early detection of gastric cancer (GC) could decrease its incidence and mortality. However, there are currently no accurate noninvasive markers for GC screening. Therefore, we developed a noninvasive diagnostic approach, employing urine nuclear magnetic resonance (NMR) metabolomics, to discover putative metabolic markers associated with GC. Changes in urine metabolite levels during oncogenesis were evaluated using samples from 103 patients with GC and 100 age- and sex-matched healthy controls. Approximately 70% of the patients with GC (n = 69) had stage I GC, with the majority (n = 56) having intramucosal cancer. A multivariate statistical analysis of the urine NMR data well discriminated between the patient and control groups and revealed nine metabolites, including alanine, citrate, creatine, creatinine, glycerol, hippurate, phenylalanine, taurine, and 3-hydroxybutyrate, that contributed to the difference. A diagnostic performance test with a separate validation set exhibited a sensitivity and specificity of more than 90%, even with the intramucosal cancer samples only. In conclusion, the NMR-based urine metabolomics approach may have potential as a convenient screening method for the early detection of GC and may facilitate consequent endoscopic examination through risk stratification.

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Development of an Efficient Immunosensing Platform by Exploring Single-Walled Carbon Nanohorns (SWCNHs) and Nitrogen Doped Graphene Quantum Dot (N-GQD) Nanocomposite for Early Detection of Cancer Biomarker

ACS Biomaterials Science & Engineering ◽

10.1021/acsbiomaterials.1c00753 ◽

2021 ◽

Author(s):

Koushik Dutta ◽

Sriparna De ◽

Beauty Das ◽

Suman Bera ◽

Biswanath Guria ◽

...

Keyword(s):

Early Detection ◽

Quantum Dot ◽

Early Detection Of Cancer ◽

Cancer Biomarker ◽

Graphene Quantum Dot ◽

Carbon Nanohorns ◽

Nitrogen Doped ◽

Single Walled Carbon ◽

Nitrogen Doped Graphene ◽

Doped Graphene

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Graphene-based stochastic sensors for pattern recognition of gastric cancer biomarkers in biological fluids

Journal of Porphyrins and Phthalocyanines ◽

10.1142/s1088424619501293 ◽

2019 ◽

Vol 23 (11n12) ◽

pp. 1365-1370 ◽

Cited By ~ 3

Author(s):

Raluca-Ioana Stefan-van Staden ◽

Ruxandra-Maria Ilie-Mihai ◽

Florina Pogacean ◽

Stela Pruneanu

Keyword(s):

Gastric Cancer ◽

Pattern Recognition ◽

Biological Samples ◽

Whole Blood ◽

Biological Fluids ◽

Protoporphyrin Ix ◽

Cancer Biomarkers ◽

Exfoliated Graphene ◽

Blood And Urine Samples

This paper proposes pattern recognition of gastric cancer biomarkers CEA, CA19-9 and p53 in whole blood and urine samples using a stochastic sensor based on exfoliated graphene (E-NGr) paste modified with protoporphyrin IX. The proposed sensor covered large ranges of concentrations: 1 × 10[Formula: see text]–1 × 10[Formula: see text]g/mL for CEA, 1 × 10[Formula: see text]–1 × 102 U/mL for CA19-9, and 0.2–5.0 [Formula: see text]g/mL for p53. These ranges allowed the determination of the three biomarkers from early to latest stages of gastric cancer. Validation of the pattern recognition of gastric cancer biomarkers was accomplished using biological samples: whole blood and urine.

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Stochastic biosensors based on N- and S-doped graphene for the enantioanalysis of aspartic acid in biological samples

RSC Advances ◽

10.1039/d1ra02066h ◽

2021 ◽

Vol 11 (38) ◽

pp. 23301-23309

Author(s):

Raluca-Ioana Stefan-van Staden ◽

Damaris-Cristina Gheorghe ◽

Ruxandra-Maria Ilie-Mihai ◽

Lucian-Barbu Tudoran ◽

Stela Maria Pruneanu

Keyword(s):

Gastric Cancer ◽

Aspartic Acid ◽

Biological Samples ◽

Doped Graphene

Stochastic biosensors based on N- and S-doped graphene modified with hemin or α-hemolysin contributed to establishing the metabolomics of gastric cancer by performing the enantioanalysis of aspartic acid in different biological samples.

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