Biomedical subjects

Razelle Kurzrock

Publications and source records attributed to Razelle Kurzrock.

7 recordsLinked to original sources

PubMed2026

Worldwide Innovative Network Consortium: Building a Common Global Cancer Database.

This review shares the ongoing work of the global Worldwide Innovative Network (WIN) Consortium for Precision Medicine to synthesize emerging cancer treatment data and to define the requirements for a common global cancer database that can truly support precision oncology. We performed a narrative review of emerging cancer treatment data, molecular profiling technologies, and existing clinicogenomic databases, focusing on how tumors are characterized, how subgroups are defined, and how demographic, lifestyle, and environmental factors are captured. The growth in molecular profiling technologies and the development of new targeted therapies are transforming cancer care. Tumors, regardless of tissue origin, are increasingly defined as composites of multiple, often rare, subgroups, each with distinct biology and likely response to specific therapies, based on multidimensional profiling of the tumor and its microenvironment. The solution lies in building vast databases that capture racial and ethnic diversity, reflected in genomic data, as well as diet and lifestyle factors that may have epigenetic impact on gene expression and post-translational modifications. A truly inclusive and informative data set must reflect global diversity, and there are multiple examples of demography-dependent differences in genomic signals. With members caring for and studying patients with cancer across five continents, WIN is actively exploring pathways to create a global cancer database, rich in clinical and molecular detail, granular enough for precise analysis, and large enough to power artificial intelligence-driven insights, provided appropriate data quality, validation, and governance frameworks are in place. This review surveys the current landscape and outlines practical paths forward to achieve this goal.

Humans↗

PubMed2026

MEK inhibitor-based genomically matched combinatorial targeted therapies in metastatic pancreatic adenocarcinoma with KRAS alterations.

INTRODUCTION: Pancreatic Ductal Adenocarcinoma (PDAC) is often caused by mutations in multiple genes including KRAS (activating the Ras-Raf-MEK-ERK pathway). This study evaluated the role of MEK inhibitor (MEKi)-based combinatorial targeted therapies in patients with PDAC. Methods. This is a retrospective/prospective observational, single institution study, including 29 patients with metastatic PDAC with KRAS alterations, treated with MEKi therapies between 2022-2024. RESULTS: Ten patients had KRAS G12R (34.5%), ten G12D (34.5%), and nine G12V (31%). Majority of patients received MEKi therapy as third-line and beyond (KRAS G12R/G12D/G12V 60%/50%/78%, respectively). Median overall survival from MEKi initiation for KRAS G12R/G12D/G12V was 8.2/5.1/4.7 months (P = 0.5), respectively, and median progression-free survival was 4.4/2.3/1.4 months (P = 0.11). Six (21%) patients discontinued at least one drug in the treatment combination due to toxicity. CONCLUSIONS: MEKi-based combinatorial therapies had modest disease control in patients with KRAS G12R, and minimal disease control in patients with KRAS G12D/V in the late-line setting.

KRAS↗

PubMed2026

Evolution of Precision Oncology, Personalized Medicine, and Molecular Tumor Boards.

With multiple molecular targeted therapies available for patients with cancer that correspond to a specific genetic alteration, the selection of the best treatment is essential to ensure therapeutic efficacy. Molecular tumor boards (MTBs) play a key role in this process to deliver personalized medicine to patients with cancer in a multidisciplinary manner. Historically, personalized medicine has been offered to patients with advanced cancer, but the incorporation of molecular targeted therapies and immunotherapy into the perioperative setting requires clinicians to understand the role of the MTB. Evidence is accumulating to support feasibility and survival benefit in patients treated with matched therapy.

Humans↗

PubMed2025

CD40 transcriptomic expression patterns across malignancies: implications for clinical trials of CD40 agonists.

BACKGROUND: CD40 is a T-cell co-stimulatory receptor targeted by next-generation immunotherapies. We conducted a pan-cancer transcriptome analysis of CD40, its ligand, and related immune markers to evaluate co-expression patterns and clinical outcomes. METHODS: We analyzed transcriptome data for CD40, its ligand, and other common checkpoints and co-stimulators (PD-1, PD-L1, PD-L2, CTLA-4, LAG-3, ICOS, CD27, CD28, OX40, and GITR). RNA expression was classified as high (75-100th percentile), moderate (25-74th), or low (0-24th) against a reference population of 735 previously tested solid tumors. RESULTS: Of 514 patients, 114 (22%) showed high, 247 (48%) moderate, and 153 (30%) low CD40 RNA expression. High CD40 expression was most frequent in liver and bile duct (42%), pancreatic (42%), and ovarian (40%) cancers. Both high CD40 and low-moderate CD40 ligand expression-potentially conducive to CD40 agonist therapy-was most frequent in ovarian (33%) and pancreatic (24%) cancer. In both UCSD (N = 514) and TCGA (N = 10,953) cohorts, high CD40 expression significantly correlated with high CD28 and GITR. High CD40 RNA levels were not prognostic for overall survival (OS) from metastatic disease (P = 0.2) (n = 272 immune checkpoint inhibitor (ICI)-naïve patients). High CD40 expression correlated with longer OS from immunotherapy initiation (n = 217 ICI-treated patients; P = 0.04, univariable analysis), but not multivariable analysis, suggesting it may not be an independent predictive biomarker. CONCLUSION: High CD40 expression correlated with liver and bile duct, pancreatic, and ovarian cancers, as well as with CD28 and GITR transcripts. Immune marker co-expression in individual patients merits further exploration for the development of CD40-based and other immunotherapy interventions.

Humans↗

PubMed2025

Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine: Bringing next-generation precision oncology to patients.

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.

Humans↗

PubMed2025

PD-1 transcriptomic landscape across cancers and implications for immune checkpoint blockade outcome.

Programmed cell death protein 1 (PD-1) is a critical immune checkpoint receptor and a target for cancer immune checkpoint inhibitors (ICI). We investigated PD-1 transcript expression across cancer types and its correlations to clinical outcomes. Using a reference population, PD-1 expression was calculated as percentiles in 489 of 514 patients (31 cancer types) with advanced/metastatic disease. PD-1 RNA expression varied across and within cancer types; pancreatic and liver/bile duct malignancies displayed the highest rates of high PD-1 (21.82% and 21.05%, respectively). Elevated CTLA-4, LAG-3, and TIGIT RNA expression were independently correlated with high PD-1. Although high PD-1 was not associated with outcome in immunotherapy-naïve patients (n = 272), in patients who received ICIs (n = 217), high PD-1 transcript expression was independently correlated with prolonged survival (hazard ratio 0.40; 95%CI, 0.18-0.92). This study identifies PD-1 as an important biomarker in predicting ICI outcomes, and advocates for comprehensive immunogenomic profiling in cancer management.

Journal Article↗

PubMed2022

High tumor amplification burden is associated with TP53 mutations in the pan-cancer setting.

Next-generation sequencing data is fundamentally changing the clinical management of patients with cancer. The most frequent genomic alterations in malignancy are mutations and amplifications, with a subset of tumors having multiple amplifications - "amplificators". We sought to understand the molecular correlates of high tumor amplification burden in a pan-cancer context. Using both national registries and a single-institution dataset, our results demonstrate that cancers with TP53 mutations (as compared to those with wild-type TP53) exhibited significantly higher tumor amplification burden across all datasets. Amplifications, generally associated with overexpression, may be potentially actionable secondary consequences of TP53 mutations.

Biomarkers, Tumor↗