Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine: Bringing next-generation precision oncology to patients
Posted: Thursday, March 13, 2025
Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine: Bringing next-generation precision oncology to patients
March 12, 2025
Oncotarget, 2025, Vol.16, pp: 140-162
Precision Oncology Special
ABSTRACT
The human genome project ushered in a genomic medicine era that was largely unimaginable three decades ago. Discoveries of druggable cancer drivers enabled biomarker-driven gene- and immune-targeted therapy and transformed cancer treatment. Minimizing treatment not expected to benefit, and toxicity—including financial and time—are important goals of modern oncology. The Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine founded by Drs. John Mendelsohn and Thomas Tursz provided a vision for innovation, collaboration and global impact in precision oncology. Through pursuit of transcriptomic signatures, artificial intelligence (AI) algorithms, global precision cancer medicine clinical trials and input from an international Molecular Tumor Board (MTB), WIN has led the way in demonstrating patient benefit from precision-therapeutics through N-of-1 molecularly-driven studies. WIN Next-Generation Precision Oncology (WINGPO) trials are being developed in the neoadjuvant, adjuvant or metastatic settings, incorporate real-world data, digital pathology, and advanced algorithms to guide MTB prioritization of therapy combinations for a diverse global population. WIN has pursued combinations that target multiple drivers/hallmarks of cancer in individual patients. WIN continues to be impactful through collaboration with industry, government, sponsors, funders, academic and community centers, patient advocates, and other stakeholders to tackle challenges including drug access, costs, regulatory barriers, and patient support. WIN’s collaborative next generation of precision oncology trials will guide treatment selection for patients with advanced cancers through MTB and AI algorithms based on serial liquid and tissue biopsies and exploratory omics including transcriptomics, proteomics, metabolomics and functional precision medicine. Our vision is to accelerate the future of precision oncology care.
INTRODUCTION
Cancer is a leading cause of morbidity and mortality worldwide, with rising incidence including among younger individuals [1]. In 2022, nearly 22 million new cases of cancer were reported, along with 9.7 million cancer-related deaths [2]. Despite significant advances in cancer diagnosis and treatment, the disease remains a major public health challenge around the world. One of the key factors contributing to the complexity of cancer is its diverse molecular landscape, which can vary not only between different types of cancer but also within cancer types and even within individual tumors [3]. As a result, personalized precision approaches to cancer diagnosis and treatment have become increasingly important in recent years [4–10]. While significant strides have been made in understanding cancer biology and developing treatments, there remains a substantial need for further advances in personalized and precise approaches to cancer diagnosis and treatment [11].
Traditional cancer treatment strategies often rely on histopathological assessments and clinical parameters to guide diagnosis and therapy selection.
However, the heterogeneity within and between tumors, especially those in the advanced/metastatic state, necessitates a more nuanced understanding of
each patient’s unique molecular profile to optimize treatment outcomes. Recent advances in molecular biology and high-throughput technologies have enabled
the generation of large-scale genomic, transcriptomic, proteomic, immunomic, and epigenomic data from cancer patients. These molecular profiling techniques have provided valuable insights into the underlying molecular mechanisms driving cancer development and progression, as well as potential therapeutic targets [12–16]. Despite the wealth of data generated by these techniques, translating this information into clinically actionable insights remains a significant challenge. This is due in part to the complexity and heterogeneity of cancer [17], as well as the limitations of existing methods for analyzing and interpreting large-scale molecular data which is usually available on a limited number of patients. There is a need for advanced computational tools and algorithms capable of integrating data from multiple sources, including omics and clinical data, as well as functional assays and response to treatment.
Effectively incorporating these data sources into clinical decision-making requires sophisticated data processing approaches [18]. Leveraging artificial intelligence (AI) algorithms to integrate and analyze these diverse datasets holds immense promise for advancing personalized cancer diagnosis and treatment [19]. Importantly, operationalizing a new generation of trials, with designs that are necessarily novel to address the wealth of new data revealed by advanced molecular technologies, is also critically important. The WIN global consortium is ready to take up the challenge by bringing the best possible Precision Oncology trial to patients.
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