Liquid Biopsy and Artificial Intelligence as Tools to Detect Signatures of Colorectal Malignancies: A Modern Approach in Patient’s Stratification

Жидкостная биопсия и искусственный интеллект как инструменты для выявления сигнатур колоректальных злокачественных образований: современный подход к стратификации пациентов
Marieta Costache, Octav Ginghină, Ariana Hudiță, Marius Zamfir, Andrada Spânu, Mara Mardare, Irina Bondoc, Laura Buburuzan, Sergiu Emil Georgescu, Marieta Costache, Carolina Negrei, Cornelia Niţipir, Bianca Gălățeanu, Laura Buburuzan
2022-03-08

artificial intelligence (AI)cell-free nucleic acids (cfNA)circulating tumor cells (CTCs)extracellular vesicles (EVs)liquid biopsy
Colorectal cancer (CRC) is the second most frequently diagnosed type of cancer and a major worldwide public health concern. Despite the global efforts in the development of modern therapeutic strategies, CRC prognosis is strongly correlated with the stage of the disease at diagnosis. Early detection of CRC has a huge impact in decreasing mortality while pre-lesion detection significantly reduces the incidence of the pathology. Even though the management of CRC patients is based on robust diagnostic methods such as serum tumor markers analysis, colonoscopy, histopathological analysis of tumor tissue, and imaging methods (computer tomography or magnetic resonance), these strategies still have many limitations and do not fully satisfy clinical needs due to their lack of sensitivity and/or specificity. Therefore, improvements of the current practice would substantially impact the management of CRC patients. In this view, liquid biopsy is a promising approach that could help clinicians screen for disease, stratify patients to the best treatment, and monitor treatment response and resistance mechanisms in the tumor in a regular and minimally invasive manner. Liquid biopsies allow the detection and analysis of different tumor-derived circulating markers such as cell-free nucleic acids (cfNA), circulating tumor cells (CTCs), and extracellular vesicles (EVs) in the bloodstream. The major advantage of this approach is its ability to trace and monitor the molecular profile of the patient's tumor and to predict personalized treatment in real-time. On the other hand, the prospective use of artificial intelligence (AI) in medicine holds great promise in oncology, for the diagnosis, treatment, and prognosis prediction of disease. AI has two main branches in the medical field: (i) a virtual branch that includes medical imaging, clinical assisted diagnosis, and treatment, as well as drug research, and (ii) a physical branch that includes surgical robots. This review summarizes findings relevant to liquid biopsy and AI in CRC for better management and stratification of CRC patients.
1
Artificial intelligence (AI) offers promising tools in oncology for diagnosis, treatment planning, and prognosis prediction, with virtual (imaging, clinical decision support, drug research) and physical (surgical robots) branches.
2
Combining liquid biopsy and AI has potential to improve CRC patient stratification, management, and monitoring of treatment response and resistance mechanisms.
3
Current CRC diagnostic methods (serum tumor markers, colonoscopy, histopathology, CT/MRI) have limitations in sensitivity and/or specificity.
4
Early detection and pre-lesion detection of colorectal cancer (CRC) greatly reduce mortality and incidence, making improved diagnostics clinically impactful.
5
Liquid biopsy can detect circulating tumor-derived markers (cfNA, CTCs, EVs) enabling minimally invasive screening, monitoring, and real-time molecular tumor profiling for personalized treatment.

Liquid biopsy analytes and artificial intelligence applications in colorectal cancer patient management

Use of liquid biopsy-derived circulating tumor markers (cfNA, CTCs, EVs) combined with AI methods to detect signatures of colorectal malignancies for screening, patient stratification, treatment selection, and monitoring response/resistance

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2022-03-08
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Marieta Costache
Octav Ginghină
Ariana Hudiță
Marius Zamfir
Andrada Spânu
Mara Mardare
Irina Bondoc
Laura Buburuzan
Sergiu Emil Georgescu
Marieta Costache
Carolina Negrei
Cornelia Niţipir
Bianca Gălățeanu
Laura Buburuzan
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