Assessment of Prostate and Bladder Cancer Genomic Biomarkers Using Artificial Intelligence: a Systematic Review

IF 2.5 2区医学 Q2 UROLOGY & NEPHROLOGY

Current Urology Reports Pub Date : 2023-12-15 DOI:10.1007/s11934-023-01193-2

Andrey Bazarkin, Andrey Morozov, Alexander Androsov, Harun Fajkovic, Juan Gomez Rivas, Nirmish Singla, Svetlana Koroleva, Jeremy Yuen-Chun Teoh, Andrei V. Zvyagin, Shahrokh François Shariat, Bhaskar Somani, Dmitry Enikeev

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Abstract

Purpose of Review

The aim of the systematic review is to assess AI’s capabilities in the genetics of prostate cancer (PCa) and bladder cancer (BCa) to evaluate target groups for such analysis as well as to assess its prospects in daily practice.

Recent Findings

In total, our analysis included 27 articles: 10 articles have reported on PCa and 17 on BCa, respectively. The AI algorithms added clinical value and demonstrated promising results in several fields, including cancer detection, assessment of cancer development risk, risk stratification in terms of survival and relapse, and prediction of response to a specific therapy. Besides clinical applications, genetic analysis aided by the AI shed light on the basic urologic cancer biology. We believe, our results of the AI application to the analysis of PCa, BCa data sets will help to identify new targets for urological cancer therapy.

Summary

The integration of AI in genomic research for screening and clinical applications will evolve with time to help personalizing chemotherapy, prediction of survival and relapse, aid treatment strategies such as reducing frequency of diagnostic cystoscopies, and clinical decision support, e.g., by predicting immunotherapy response. These factors will ultimately lead to personalized and precision medicine thereby improving patient outcomes.

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利用人工智能评估前列腺癌和膀胱癌基因组生物标记物：系统综述

综述目的本系统综述旨在评估人工智能在前列腺癌（PCa）和膀胱癌（BCa）遗传学方面的能力，以评估此类分析的目标群体，并评估其在日常实践中的前景：我们的分析共包括 27 篇文章：10 篇报道了 PCa，17 篇报道了 BCa。人工智能算法增加了临床价值，并在多个领域取得了可喜的成果，包括癌症检测、癌症发展风险评估、生存和复发风险分层以及对特定疗法的反应预测。除临床应用外，人工智能辅助下的基因分析还揭示了泌尿系统癌症的基本生物学原理。我们相信，我们将人工智能应用于 PCa、BCa 数据集分析的结果将有助于确定泌尿系统癌症治疗的新靶点。摘要随着时间的推移，人工智能在基因组研究筛查和临床应用中的整合将有助于个性化化疗、预测生存和复发、辅助治疗策略（如减少诊断性膀胱镜检查的频率）和临床决策支持（如通过预测免疫疗法反应）。这些因素将最终实现个性化和精准医疗，从而改善患者的治疗效果。

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来源期刊

Current Urology Reports UROLOGY & NEPHROLOGY-

CiteScore

4.60

自引率

3.80%

发文量

期刊介绍： This journal intends to review the most important, recently published findings in the field of urology. By providing clear, insightful, balanced contributions by international experts, the journal elucidates current and emerging approaches to the care and prevention of urologic diseases and conditions. We accomplish this aim by appointing international authorities to serve as Section Editors in key subject areas, such as benign prostatic hyperplasia, erectile dysfunction, female urology, and kidney disease. Section Editors, in turn, select topics for which leading experts contribute comprehensive review articles that emphasize new developments and recently published papers of major importance, highlighted by annotated reference lists. An international Editorial Board reviews the annual table of contents, suggests articles of special interest to their country/region, and ensures that topics are current and include emerging research. Commentaries from well-known figures in the field are also provided.