Schneider Lab Research

The mission of the Schneider Lab is to advance therapies for lung cancer by uncovering and targeting metabolic rewiring that enables tumors to grow, adapt, and resist treatments.

Research Overview

The Schneider Lab focuses on how metabolic rewiring enables lung tumors to emerge, adapt, and persist. Although genotype-directed targeted therapies have reshaped the treatment landscape for patients with lung cancer, durable responses remain uncommon, and therapeutic resistance continues to limit patient outcomes. Our mission is twofold: (1) to identify metabolic vulnerabilities that drive tumor growth and drug resistance, and (2) to translate these insights into innovative therapeutic strategies.

We investigate metabolic vulnerabilities across three interconnected contexts:

• Oncogenotype-specific metabolic dependencies that create liabilities for selective therapeutic targeting
• Metabolic reprogramming during targeted therapy resistance, which sustains residual disease and drives relapse
• The impact of aging on tumor and microenvironmental metabolism, influencing lung tumor initiation and progression

To address these questions, we integrate complementary experimental approaches, including:

• CRISPR-based functional genomics to uncover metabolic genes essential for tumor survival
• pY-enriched proteomics to define signaling pathways driving adaptive metabolic states
• Steady-state and isotope tracing metabolomics in patient-derived cells and in vivo tumor models
• Metabolic inhibitor development to mechanistically inform therapeutic strategies
• Spatial metabolic imaging and multiplexed immunofluorescence to resolve metabolic programs within intact tumor ecosystems

Together, these approaches allow us to chart how tumors rewire their metabolic circuitry and leverage these discoveries towards next-generation therapies for patients with cancer. 

Research Areas

Our work seeks to understand how distinct oncogenotypes in lung cancer - including ALK, ROS1, RET, NTRK, MET, RAS, EGFR, HER2, STK11, KEAP1/NRF2, MTAP, amongst others - reprogram metabolic networks to support tumor growth, survival, and therapeutic resistance. Although these oncogenotypes activate overlapping signaling pathways, accumulating evidence suggests that they generate unique metabolic dependencies that may be selectively targetable. As one example, we identified guanylate kinase 1 (GUK1), a GDP-synthesizing enzyme, as a previously unrecognized metabolic target of oncogenic signaling in ALK+ lung cancers. We discovered that oncogenic fusion kinases directly phosphorylate and regulate GUK1, marking the first demonstration that an oncogenic fusion kinase can control a nucleotide synthesis enzyme via post-translational modification. Modulating GUK1 activity changes intracellular GTP pools and, in turn, alters MAPK pathway activation through Ras-GTP loading, positioning nucleotide metabolism upstream of Ras signaling, a paradigm-shifting insight into how metabolic flux shapes oncogenic output. These findings illustrate a broader principle central to our research program that oncogenic drivers do not merely activate signaling cascades, they also rewire metabolic circuitry to reinforce those signals. By identifying the metabolic nodes that sit at these signaling–metabolism intersections, we aim to develop therapeutic strategies that selectively disable the metabolic “engines” sustaining oncogene-driven tumors.

Lung cancers driven by oncogenic alterations are often exquisitely sensitive to small-molecule tyrosine kinase inhibitors (TKIs). However, drug resistance almost inevitably emerges, leading to disease relapse. Our lab works closely with Dana-Farber's Thoracic Oncology Program to uncover how resistance mechanisms arise in patients treated with targeted therapies. Our central research question centers around how how cancer cells adapt their metabolic circuitry to evade targeted therapies. We are particularly interested in understanding how alterations in metabolic enzyme regulation contribute to therapeutic resistance and tumor persistence. By integrating molecular, biochemical, and metabolic profiling approaches, our studies aim to uncover how signaling networks and metabolic pathways become rewired under drug pressure. These efforts seek to reveal new insights into the dynamic interplay between oncogenic signaling, nucleotide metabolism, and the broader metabolic landscape of therapy-resistant tumors. Ultimately, this work aspires to identify metabolic vulnerabilities that may guide the next generation of precision cancer therapies. In parallel, we are actively profiling metabolic signatures from tumors treated with different modalities to understand how metabolic remodeling of the tumor microenvironment differentiates responders from non-responders. Our goal is to translate these insights into rational therapeutic strategies that anticipate and overcome resistance, improving outcomes for patients with advanced lung cancer.

Have you ever wondered why does the risk and biology of cancer vary so strikingly with age? Or whether age-related differences in tumor behavior are dictated solely by mutational events or if the aging microenvironment shapes tumor evolution even in genetically similar contexts? We do! Our lab investigates how the biological processes of aging influence the initiation and progression of lung cancer through changes in cellular metabolism. As organisms age, their tissues experience cumulative shifts in nutrient utilization, redox balance, and energy homeostasis. These are conditions that may create distinct metabolic landscapes for tumor development. We are interested in understanding how these age-associated metabolic environments alter the evolutionary pressures faced by emerging cancer cells and, in turn, how they dictate patterns of tumor growth, heterogeneity, and therapeutic sensitivity. Our work is actively exploring the idea that metabolic preferences in tumors may be shaped not only by oncogenic mutations or tissue of origin but also by the age of the host. By integrating molecular, metabolic, and genomic profiling across diverse models and primary patient samples, we aim to uncover how aging reshapes the metabolic wiring of cancer cells and their surrounding microenvironment. These studies seek to reveal how age-dependent differences in metabolism influence cancer vulnerability and treatment response, with the broader goal of informing precision strategies that account for patient age as a fundamental biological variable in cancer therapy.

"Science is more than a body of knowledge. It is way of thinking…" – Carl Sagan