The Worldwide Innovative Networking (WIN) Consortium in personalized cancer medicine was initiated in 2010 with leadership from leading cancer centers worldwide. WIN is a non-profit, non-governmental organization headquartered in Paris.

WIN was created to accelerate the pace and reduce the cost of translating novel cancer treatments to the bedside by developing and applying, through worldwide clinical trials and research projects, the most promising advances in genomic-based cancer research. WIN aims to initiate research projects each year in a global consortium guided by an independent scientific advisory board.

WIN now includes 34 institutional members. These stakeholders have come together from all parts of the world to address the challenge of increasing the efficacy of cancer diagnostics and therapeutics by understanding the genetics and biology of each individual’s tumor and accounting for genetic differences across diverse populations—from North and South America, Europe, Asia, Middle East and Australia.

Our goal is to significantly improve outcomes for patients around the globe. We aim to increase the number of patients worldwide that have access to innovative, global clinical trials in the area of genomic-based cancer therapeutics. Global diversity and inclusion of all stakeholders is WIN’s most important and differentiating asset.

WIN enables cross-sector collaborations designed to accelerate the speed and efficacy with which breakthroughs in personalized cancer medicine can be realized and brought to patients worldwide.

Our members include leading academic, life science, not-for-profit, health, patient advocacy and IT organizations.

The response to a genetically-targeted therapy can vary due to differences in ethnicity and environment. WIN's global studies are designed to identify and account for this variability, enhancing the speed and efficacy with which novel discoveries can be made and brought to patients around the world.

WIN Symposia, held annually, brings together hundreds of leaders representing all stakeholders from around the world in a forum designed to promote the exchange of ideas and information.

October 19, 2024
Published by Therapeutic Advances in Medical Oncology

Abstract
Background: Dysregulated pathways in cancer may be hub addicted. Identifying these dysregulated networks for targeting might lead to novel therapeutic options.

Objective: Considering the hypothesis that central hubs are associated with increased
lethality, identifying key hub targets within central networks could lead to the development of novel drugs with improved efficacy in advanced metastatic solid tumors.

Design: Exploring transcriptomic data (22,000 gene products) from the WINTHER trial (N = 101 patients with various metastatic cancers), in which both tumor and normal organ-matched tissue were available.

Methods: A retrospective in silico analysis of all genes in the transcriptome was conducted to identify genes different in expression between tumor and normal tissues (paired t-test) and to determine their association with survival outcomes using survival analysis (Cox proportional
hazard regression algorithm). Based on the biological relevance of the identified genes, hub targets of interest within central networks were then pinpointed. Patients were grouped based on the expression level of these genes (K-mean clustering), and the association of these
groups with survival was examined (Cox proportional hazard regression algorithm, Forest plot, and Kaplan–Meier plot).

Results: We identified four key central hub genes—PLOD3, ARHGAP11A, RNF216, and CDCA8, for which high expression in tumor tissue compared to analogous normal tissue had the most significant correlation with worse outcomes. The correlation was independent of tumor or treatment type. The combination of the four genes showed the highest significance and correlation with the poorer outcome: overall survival (hazard ratio (95% confidence interval
(CI)) = 10.5 (3.43–31.9) p = 9.12E−07 log-rank test in a Cox proportional hazard regression model). Findings were validated in independent cohorts.

Conclusion: The expression of PLOD3, ARHGAP11A, RNF216, and CDCA8 constitute, when combined, a prognostic tool, agnostic of tumor type and previous treatments. These genes represent potential targets for intercepting central hub networks in various cancers, offering
avenues for novel therapeutic interventions.

Keywords: cancer, genes, prognostic markers, RNA, transcriptomic

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WIN's article “Digital Display Precision Predictor: the prototype of a global biomarker model to guide treatments with targeted therapy and predict progression-free survival” published by NPJ Precision Oncology, a Nature Research journal.

The WIN SPRING trial was conducted in the USA, France, Spain, Luxembourg and Israel in the following cancer centers: University of California - San Diego's Moores Cancer Center, Avera Cancer Center (Sioux Falls, Arizona), Institut Curie (Paris), Centre Léon Bérard (Lyon), Vall d'Hebron Institute of Oncology (Barcelona), Centre Hospitalier de Luxembourg (Luxembourg), and Chaim Sheba Medical Center (Israel).

The trial was sponsored by the WIN Consortium and funded by ARC Fondation for cancer research (France). The drugs were donated by Pfizer Inc.

Published in Nature Medicine, results of WINTHER, the first study pioneered by the WIN Consortium.

Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial - shows that RNA profiling together with DNA testing matches more patients with advanced cancer to personalized therapies than DNA profiling for tumor mutations alone.

August 13, 2025
Frontiers in Pharmacology
DATA REPORT article: Sec. Pharmacology of Anti-Cancer Drugs
Volume 16 - 2025 | https://doi.org/10.3389/fphar.2025.1588191

INTRODUCTION

The rapid evolution of targeted therapies in oncology has revolutionized cancer treatment, offering new hope to patients through precision medicine. These therapies are designed to specifically inhibit molecular targets that drive tumor growth and progression. By focusing on the unique genetic and molecular characteristics of individual tumors, targeted therapies enable more effective and personalized treatment strategies, thereby improving patient outcomes and minimizing adverse effects (Choi and Chang, 2023).

In recent years, the U.S. Food and Drug Administration (FDA) has approved a growing number of targeted therapies, reflecting the increasing understanding of the molecular underpinnings of various cancers. As of 2024, over 150 targeted agents have received FDA approval (Zhong et al., 2021), each associated with specific molecular targets and indications. These therapies encompass a range of mechanisms, including small molecule inhibitors that disrupt intracellular signaling pathways and monoclonal antibodies that block the interaction between cancer cells and their environment (Zhong et al., 2021; FDA Approved Targeted Drug List, 2024). For instance, agents targeting the epidermal growth factor receptor (EGFR), such as erlotinib and gefitinib, have demonstrated significant efficacy in non-small cell lung cancer (NSCLC) (Maemondo et al., 2010; Toschi et al., 2017), while BRAF inhibitors have transformed the treatment landscape for melanoma (Ribas and Flaherty, 2011; Patel et al., 2020).

To effectively track the landscape of these targeted therapies, comprehensive databases serve as invaluable resources for clinicians and researchers alike. Amid the ongoing artificial intelligent (AI) revolution, such databases hold immense significance for precision oncology algorithms and clinical pharmacology applications, enabling clinicians and researchers to leverage accessible knowledge and tools to make personalized, evidence-based decisions in cancer treatment (Alowais et al., 2023). Comprehensive databases, like PHARMGKB (Whirl-Carrillo et al., 2021), DrugBank (Knox et al., 2024) and Therapeutic Target Database (TTD) (Zhou et al., 2024; Liu et al., 2020; Yang et al., 2024), offer detailed molecular characterization of drugs, pharmacogenomic insights and clinical annotations across numerous therapeutic areas. Clinicians and researchers can use such databases to delve into treatment responses and explore repurposing possibilities. Recently, datasets specifically focusing on anti-cancer drugs (Pantziarka et al., 2021) have been introduced, offering enhanced data availability for machine learning applications and drug repurposing in precision oncology. These resources, though extensive, merely scratch the surface of potential oncology data. The vast possibilities and the comprehensiveness of such databases also introduce challenges, particularly for clinicians who often face time constraints, specifically, when patients fail to respond to guideline-recommended treatments. In such cases oncologists must consider alternative therapeutic approaches by integrating clinical guidelines with available data (Otte et al., 2017; Glatzer et al., 2020).

This report presents the OncoAID database, a specialized and dynamic resource meticulously developed by integration of existing datasets as well as newly curated, up-to-date information. The database is comprehensive, practical, relevant and features an interactive, user-friendly interface that enables clinicians and researchers to quickly and effectively search, filter, and explore information of interest, whether within the database or through navigation to linked external resources.

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July 4, 2025 - WIN Consortium is supporting the activation of the Tempus GEMINI-NSCLC study at member institutions in the USA, Canada, Europe, and the Middle East.

The GEMINI-NSCLC study generates a robust, multi-omic dataset for research in biomarker discovery. The study includes two patient cohorts:
- Patients diagnosed with Stage IV NSCLC receiving standard-of-care first-line checkpoint inhibitor therapy
- Patients with early-stage NSCLC who are candidates for surgery and perioperative treatment

Tempus deploys its comprehensive molecular profiling platform—including solid tumor (xT/xR) and liquid biopsy (xF)—to analyze tumor biology longitudinally in the study. The study focuses on understanding disease progression and treatment response, with emphasis on identifying novel biomarkers and the use of circulating tumor DNA (ctDNA) to monitor MRD.

June 17, 2025
Oncotarget, 2025, Vol.16, pp: 456-466
Precision Oncology

ABSTRACT
Heavily pretreated metastatic colorectal cancer (mCRC) poses significant therapeutic challenges. Advances in molecular profiling enables personalized strategies. We present a 62-year-old male with mCRC harboring BRAF, MET, APC, TP53 and NRAS alterations, following FOLFOX and FOLFIRI, dabrafenib plus panitumumab, and a BRAF inhibitor clinical trial, each leading to initial responses followed by disease progression.

WIN Consortium International Molecular Tumor Board (MTB), included experts from institutions across 13 countries. Enrollment in suitable clinical trials was explored but limited by availability. Personalized combinations suggested included amivantamab-vmjw (anti-MET/EGFR antibody) (one-third standard dose) (for MET amplification and due to prior response to anti-EGFR antibody), trametinib, 1 mg po daily (MEK inhibitor for BRAF V600E mutation), and regorafenib (may have WNT inhibitor activity relevant to APC mutation; VEGFR activity relevant since TP53 alterations upregulate EGF/VEGFR axis) starting at 40 mg po daily three weeks on, one week off. Another option was trametinib at 1 mg daily, cetuximab (EGFR antibody), 250 mg/m² IV every two-weeks, and cabozantinib (MET and VEGFR inhibitor), 40 mg po daily. FOLFOXFIRI combined with bevacizumab, or liver-directed therapies for hepatic metastases, or regorafenib with 5FU, or crizotinib (MET inhibitor) combined with regorafenib or dabrafenib, was also suggested.

This case emphasizes the critical role of comprehensive molecular profiling and personalized therapeutic approaches in managing complex mCRC. The WIN International MTB aims to provide treatment and biomarker analysis discussion with the ultimate goal of optimizing treatment efficacy by targeting specific molecular alterations, though final treatment decisions remain at the discretion of the treating physician.

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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.

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