Navigating between Scylla and Charybdis: A roadmap to do better than Pola-RCHP in DLBCL

Javier Munoz, Anagha Deshpande,Lisa Rimsza, Grzegorz S. Nowakowski,Razelle Kurzrock

CANCER TREATMENT REVIEWS(2024)

引用 0|浏览13
暂无评分
摘要
In treating diffuse large B-cell lymphoma (DLBCL), oncologists have traditionally relied on the chemotherapy backbone of R-CHOP as standard of care. The two dangers that the hematologist must navigate between are the aggressive disease (Charybdis that in the absence of therapy systematically destroys all the ships) and the toxicity of the therapies (Scylla with its six monstrous heads that devours six crew members at a time), and hematologists have to navigate very carefully between both. Therefore, three different strategies were employed with the goal of improving cure rates: de-escalating regimens, escalating regimens, and replacement strategies. With a replacement strategy, a breakthrough in treatment was identified with polatuzumab vedotin (anti-CD79B antibody/drug conjugate) plus R-CHP. However, this regimen still did not achieve the elusive universal cure rate. Fortunately, advances in genomic and molecular technologies have allowed for an improved understanding of the heterogenous molecular nature of the disease to help develop and guide more targeted, precise, and individualized therapies. Additionally, new pharmaceutical technologies have led to the development of novel cellular therapies, such as chimeric antigen receptor (CAR) T-cell therapy, that could be more effective, while maintaining an acceptable safety profile. Thus, we aim to highlight the challenges of DLBCL therapy as well as the need to address therapeutic regimens eventually no longer tethered to a chemotherapy backbone. In the intersection of artificial intelligence and multi-omics (genomics, epigenomics, transcriptomics, proteomics, metabolomics), we propose the need to analyze multidimensional biologic data to launch a decisive attack against DLBCL in a targeted and individualized fashion.
更多
查看译文
关键词
DLBCL,Polatuzumab vedotin,Targeted therapy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要