Diagnostic value of combining tumor and inflammatory biomarkers in detecting common cancers in Korea

Kim, Young Sun; Kang, Kyung Nam; Shin, Yong Sam; Lee, Ji Eun; Jang, Ji Young; Kim, Chul Woo

doi:10.1016/j.cca.2021.02.002

Cited by 5 publications

(6 citation statements)

References 22 publications

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“…The lack of correlation between each individual biomarker in serum and blood cells in our study population supports the idea that whole blood and serum can be considered independent measurement sources. Furthermore, the negative result of combining biomarkers to improve their predictive value supports the recent idea of configuring panels consisting of uncorrelated biomarkers to reveal maximum information about patients [ 61 ].…”

Section: Discussionmentioning

confidence: 81%

Circulating PTGS2, JAG1, GUCY2C and PGF mRNA in Peripheral Blood and Serum as Potential Biomarkers for Patients with Metastatic Colon Cancer

Jiménez-Luna

González-Flores

Ortíz

et al. 2021

JCM

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Genes involved in the angiogenic process have been proposed for the diagnosis and therapeutic response of metastatic colorectal cancer (CRC). This study aimed to investigate the value of PTGS2, JAG1, GUCY2C and PGF-circulating RNA as biomarkers in metastatic CRC. Blood cells and serum mRNA from 59 patients with metastatic CRC and 47 healthy controls were analyzed by digital PCR. The area under the receiver operating characteristic curve (AUC) was used to estimate the diagnostic value of each mRNA alone or mRNA combinations. A significant upregulation of the JAG1, PTGS2 and GUCY2C genes in blood cells and serum samples from metastatic CRC patients was detected. Circulating mRNA levels in the serum of all genes were significantly more abundant than in blood. The highest discrimination ability between metastatic CRC patients and healthy donors was obtained with PTGS2 (AUC of 0.984) and GUCY2C (AUC of 0.896) in serum samples. Biomarker combinations did not improve the discriminatory capacity of biomarkers separately. Analyzed biomarkers showed no correlation with overall survival or progression-free survival, but GUCY2C and GUCY2C/PTGS2 expression in serum correlated significantly with the response to antiangiogenic agents. These findings demonstrate that assessment of genes involved in the angiogenic process may be a potential non-invasive diagnostic tool for metastatic CRC and its response to antiangiogenic therapy.

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Section: Discussionmentioning

confidence: 81%

Circulating PTGS2, JAG1, GUCY2C and PGF mRNA in Peripheral Blood and Serum as Potential Biomarkers for Patients with Metastatic Colon Cancer

Jiménez-Luna

González-Flores

Ortíz

et al. 2021

JCM

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“…In as many as 1261 proteins, 9 protein biomarkers have been approved as “tumor-associated antigens” by the USFDA. Although these protein biomarkers have not yet been approved for MCED, in many Asian regions, such as China [ 35 ], Taiwan [ 33 ], the Republic of Korea [ 49 ], etc., the use of protein biomarkers for MCED has been put into practice for more than 10 years. The popularity of this approach lies in its convenience, as cancer screening for many different cancer types can be conducted with a simple blood test.…”

Section: Serum Biomarkers As Critical Indicatorsmentioning

confidence: 99%

“…Theoretically, biomarkers in presymptomatic or asymptomatic cancer cases would be closer to those of healthy controls than in the symptomatic cancer cases. On healthy cases: The number of healthy control cases in a case-control study is usually up to several hundred given the fact that the ratio of cancer versus control ratio is set around 1:1–1:4 [ 15 , 17 , 34 , 49 ]. The relatively small number cannot represent the large diversity in the healthy control cases.…”

Section: Training and Validation Of Ai Models For Mcedmentioning

confidence: 99%

“…On healthy cases: The number of healthy control cases in a case-control study is usually up to several hundred given the fact that the ratio of cancer versus control ratio is set around 1:1–1:4 [ 15 , 17 , 34 , 49 ]. The relatively small number cannot represent the large diversity in the healthy control cases.…”

Section: Training and Validation Of Ai Models For Mcedmentioning

confidence: 99%

“…Additionally, discrepancies in the biomarkers that are tested in the panel also pose computational challenges and interpretation issues for AI models. Taking the example of protein biomarkers, one MCED screening kit may assess seven protein targets [ 16 ], while another MCED AI examines twelve protein targets [ 49 ]. Yet another screening kit may include both protein and gene targets [ 15 ].…”

Section: Challenges and Opportunitiesmentioning

confidence: 99%

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Integrating Artificial Intelligence for Advancing Multiple-Cancer Early Detection via Serum Biomarkers: A Narrative Review

Wang,

Lin,

Zhou

et al. 2024

Cancers

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The concept and policies of multicancer early detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control studies or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation, are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumors, and addressing cancer-related information, such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarker detection, MCED AI training/validation, and the clinical application. This review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.

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Exploring potential anti-inflammatory effects of medicinal cannabis

Gurgenci,

Kijanka,

Greer

et al. 2023

Support Care Cancer

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Purpose Inflammation is thought to play a key role in malignant disease and may play a significant part in the expression of cancer-related symptoms. Cannabidiol (CBD) is a bioactive compound in cannabis and is reported to have significant anti-inflammatory properties. Method Serial C-reactive protein (CRP) levels were measured in all participants recruited to a randomised controlled trial of CBD versus placebo in patients with symptoms related to advanced cancer. A panel of inflammatory cytokines was measured over time in a subset of these patients. Results There was no difference between the two arms in the trajectory of CRP or cytokine levels from baseline to day 28. Conclusion We were unable to demonstrate an anti-inflammatory effect of CBD in cancer patients. Trial registration ANZCTR 26180001220257, registered 20/07/2018.

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Diagnostic value of combining tumor and inflammatory biomarkers in detecting common cancers in Korea

Cited by 5 publications

References 22 publications

Circulating PTGS2, JAG1, GUCY2C and PGF mRNA in Peripheral Blood and Serum as Potential Biomarkers for Patients with Metastatic Colon Cancer

Circulating PTGS2, JAG1, GUCY2C and PGF mRNA in Peripheral Blood and Serum as Potential Biomarkers for Patients with Metastatic Colon Cancer

Integrating Artificial Intelligence for Advancing Multiple-Cancer Early Detection via Serum Biomarkers: A Narrative Review

Exploring potential anti-inflammatory effects of medicinal cannabis

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