Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests

Brito-Rocha, Tiago; Constâncio, Vera; Henrique, Rui; Jerónimo, Carmen

doi:10.3390/cells12060935

Cited by 37 publications

(26 citation statements)

References 195 publications

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“…The second approach involves machine learning algorithms, which are increasingly used for the automatic recognition of patients with various disorders, such as in diagnostics of cancer based on plasma denaturation profiles, or diagnostics of glaucoma by metabolomic changes in TF [ 16 , 27 ]. Indeed, machine learning is gaining popularity in the analysis of medical-related data for diagnostic purposes [ 41 ]. In our case, its application allows for the consideration of changes in profiles based on the complete set of data, without any preprocessing.…”

Section: Discussionmentioning

confidence: 99%

Tear nanoDSF Denaturation Profile Is Predictive of Glaucoma

Baksheeva

Tiuli

Iomdi

et al. 2023

IJMS

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Primary open-angle glaucoma (POAG) is a frequent blindness-causing neurodegenerative disorder characterized by optic nerve and retinal ganglion cell damage most commonly due to a chronic increase in intraocular pressure. The preservation of visual function in patients critically depends on the timeliness of detection and treatment of the disease, which is challenging due to its asymptomatic course at early stages and lack of objective diagnostic approaches. Recent studies revealed that the pathophysiology of glaucoma includes complex metabolomic and proteomic alterations in the eye liquids, including tear fluid (TF). Although TF can be collected by a non-invasive procedure and may serve as a source of the appropriate biomarkers, its multi-omics analysis is technically sophisticated and unsuitable for clinical practice. In this study, we tested a novel concept of glaucoma diagnostics based on the rapid high-performance analysis of the TF proteome by differential scanning fluorimetry (nanoDSF). An examination of the thermal denaturation of TF proteins in a cohort of 311 ophthalmic patients revealed typical profiles, with two peaks exhibiting characteristic shifts in POAG. Clustering of the profiles according to peaks maxima allowed us to identify glaucoma in 70% of cases, while the employment of artificial intelligence (machine learning) algorithms reduced the amount of false-positive diagnoses to 13.5%. The POAG-associated alterations in the core TF proteins included an increase in the concentration of serum albumin, accompanied by a decrease in lysozyme C, lipocalin-1, and lactotransferrin contents. Unexpectedly, these changes were not the only factor affecting the observed denaturation profile shifts, which considerably depended on the presence of low-molecular-weight ligands of tear proteins, such as fatty acids and iron. Overall, we recognized the TF denaturation profile as a novel biomarker of glaucoma, which integrates proteomic, lipidomic, and metallomic alterations in tears, and monitoring of which could be adapted for rapid non-invasive screening of the disease in a clinical setting.

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Section: Discussionmentioning

confidence: 99%

Tear nanoDSF Denaturation Profile Is Predictive of Glaucoma

Baksheeva

Tiuli

Iomdi

et al. 2023

IJMS

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“…Emerging multicancer detection tests mark a revolution in early screening, allowing multiple cancer types to be identified from a single blood sample 62 . These tests, based on sophisticated biomarker analysis, pave the way for routine, noninvasive cancer diagnosis akin to standard blood tests.…”

Section: Future Direction In Multifluid Biopsiesmentioning

confidence: 99%

Beyond blood: Advancing the frontiers of liquid biopsy in oncology and personalized medicine

Bao,

Zhang,

Guo

et al. 2024

Cancer Science

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Liquid biopsy is emerging as a pivotal tool in precision oncology, offering a noninvasive and comprehensive approach to cancer diagnostics and management. By harnessing biofluids such as blood, urine, saliva, cerebrospinal fluid, and pleural effusions, this technique profiles key biomarkers including circulating tumor DNA, circulating tumor cells, microRNAs, and extracellular vesicles. This review discusses the extended scope of liquid biopsy, highlighting its indispensable role in enhancing patient outcomes through early detection, continuous monitoring, and tailored therapy. While the advantages are notable, we also address the challenges, emphasizing the necessity for precision, cost‐effectiveness, and standardized methodologies in its broader application. The future trajectory of liquid biopsy is set to expand its reach in personalized medicine, fueled by technological advancements and collaborative research.

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“…In crafting AI models, different approaches are adopted, including the use of datasets from case-control studies or databases from real-life cancer screenings. 209 For validation, methods like cross-validation, 210 geographically-based validation, 211 and temporal validation 212 are utilized. Each of these elements plays a crucial role in determining the effectiveness of MECD AI tools in predicting cancer.…”

Section: Challenges and Future Perspectivesmentioning

confidence: 99%