Dr. Yi Li (MS’18), now an assistant professor of bioengineering, said the funding is “transformative” as he builds his lab and accelerates research into cancers powered by fusion genes. His efforts extend work initiated during his postdoctoral years in the lab of Dr. Leonidas Bleris at UT Dallas.

SFT develops when the NAB2 and STAT6 genes fuse, producing aberrant signaling that triggers cancer-cell growth. Although the underlying cause of the fusion remains unknown, the fusion itself offers a direct molecular handle. Current clinical management typically relies on surgery to remove tumors and/or radiation, because no drug is specifically tailored to SFT.

Li’s team previously collaborated with Dr. Heather Hayenga, an associate professor of bioengineering at UT Dallas, whose leadership helped establish local SFT research. Hayenga died on April 5, and the CPRIT-funded projects are intended to continue that scientific legacy while expanding toward new therapeutic strategies.

In recent years, the research community—supported by UT Dallas efforts—has used gene-editing tools to create experimental models that clarify how the NAB2–STAT6 fusion sustains disease. Those models have also supported an interdisciplinary pipeline for therapy development.

CPRIT support includes two major awards for Li. In May, he received a $249,000 high impact/high risk grant (RP260816) aimed at developing a potential immunotherapy for SFT. Last fall, he obtained an $899,216 individual investigator award (RP260461) to pursue a fusion-silencing approach using antisense oligonucleotides.

Antisense oligonucleotides are short strands of synthetic genetic material designed to block the activity of cancer-driving gene fusions. In laboratory-grown tumor cells and in animal models, the team has shown that these strategies can reduce fusion-gene activity and weaken oncogenic signaling.

A practical challenge is delivery: dense tumor tissue can limit how therapeutic molecules penetrate the tumor interior. Li is collaborating with Dr. Jeremiah Gassensmith in chemistry and biochemistry to design an effective delivery route through outer tissue barriers.

Overall, the work could generate a framework not only for SFT but also for other fusion-driven cancers that share similar vulnerabilities in gene-fusion signaling.

Subject of Research: Solitary fibrous tumor (SFT) driven by NAB2–STAT6 gene fusions
Article Title: (Not provided in the provided content)
News Publication Date: (Not provided in the provided content)
Web References: https://www.cprit.texas.gov/grants-funded/grants/rp260816 ; https://www.cprit.texas.gov/grants-funded/grants/rp260461
References: (No full reference list provided beyond the grant links)
Image Credits: The University of Texas at Dallas

Keywords: solitary fibrous tumor, SFT, NAB2–STAT6, gene fusion, antisense oligonucleotides, immunotherapy, cancer immunology, translational research, targeted therapy, drug delivery

Historically, cancer has been understood primarily through the lens of dysregulated cell growth fueled by genetic mutations in oncogenes and tumor suppressor genes. The p53 protein, in particular, is critical in sensing DNA damage and either repairing the cell or directing it toward apoptosis. However, the OdH suggests that what has been identified as “uncontrolled” cellular proliferation may instead reflect a higher-order immunological strategy—a biological creativity rather than mere fatalism. This paradigm shift invites researchers to decipher cancer’s “source code,” seeking pathways to reprogram malignant cells, thereby transforming treatments from suppression to adaptive modulation.

At the forefront of this innovative framework is the proposition to design and construct synthetic p53 superproteins using cutting-edge AI tools such as AlphaFold 3 for protein structure prediction, integrated with molecular design platforms like MoluCAD and Blender for 3D modeling and printing. These engineered superproteins are envisioned to function as wireless molecular biochips, capable of interfacing with AI algorithms (exemplified by models like ChatGPT) to dynamically regulate tumor suppression pathways. This represents a fusion of synthetic biology, computational modeling, and evolutionary medicine, delivering a potential leap toward precision immunotherapy.

Another transformative aspect of the hypothesis involves redefining the immunological role of cancer at two levels: micro-immunology and macro-immunology. Micro-immunology focuses on how tumor cells evade immune detection and destruction in the immediate environment, a well-studied phenomenon. In contrast, macro-immunology posits that cancer exists on an evolutionary timescale as an ongoing, non-pathological, self-learning immune response. The AI-integrated p53 superproteins could potentially accelerate this macro-immunoadaptive process, empowering the immune system to engage with tumor cells in a more nuanced and evolutionarily informed manner.

Technological advances in AI-driven protein design, especially tools like AlphaFold 3 and RoseTTAFold, have revolutionized the ability to predict and manipulate protein folding and function with unprecedented accuracy. Coupling these capabilities with 3D bioprinting offers the exciting prospect of fabricating complex protein-based devices that can be delivered efficiently to target sites. The OdH outlines a delivery mechanism leveraging attenuated Salmonella bacteria as vectors, capable of ferrying viral genomes and synthetic p53 constructs directly into the tumor microenvironment—an innovative platform termed CAPPSID reflecting combined cellular and molecular precision intervention.

While the theoretical scaffold of the Oncodarwinian Hypothesis is compelling, its clinical translation remains speculative and fraught with challenges. The author emphasizes the need for rigorous experimental validation to guard against confirmation bias, advocating for robust statistical methodologies (with significance thresholds such as α=0.05) to establish tumor inhibition capabilities. The analogy is drawn to Einstein’s photon hypothesis, which also met initial skepticism but was eventually confirmed through meticulous experimentation, underscoring the importance of perseverance in overturning scientific dogma.

This hypothesis not only reframes cancer biology but also presages a future where interdisciplinary partnerships among molecular biologists, AI specialists, synthetic biologists, and clinical oncologists become indispensable. The development of viability tests to ascertain the electrochemical functionality of p53 as a biochip and the refinement of bacterial delivery systems will be paramount steps. By harnessing AI and 3D printed biomolecular devices, researchers could unlock new frontiers in personalized medicine and immunotherapy.

By challenging the prevailing view of cancer as merely runaway cellular division and genetic chaos, the OdH offers a glimpse beyond conventional treatments toward decoding and reprogramming cancer’s underlying “algorithm.” This shift could transform the therapeutic landscape from blunt-force eradication to elegant immunoadaptive engagement, equipping the immune system to evolve and learn alongside the disease it battles. The integration of AI-designed p53 superproteins embodies a futuristic merging of computational intelligence with biological complexity, potentially ushering in an era where medicine acts like software engineers debugging and updating living systems.

Critically, the success of the Oncodarwinian Hypothesis hinges on experimental and clinical data in future research, from in vitro viability assays to in vivo delivery efficacy and safety studies. Establishing reproducible outcomes and clear mechanisms will be key to gaining acceptance in the broader scientific community and driving translational breakthroughs. If confirmed, the implications for oncology could be profound, shifting paradigms from destruction towards co-evolutionary harmony with cancer cells.

Ultimately, the power of OdH lies in its imaginative yet scientifically grounded vision—using AI and biofabrication to craft molecular sentinels capable of intelligently guiding the immune response. The hypothesis predicts a dynamic interplay where cancer is not an adversary to be obliterated indiscriminately but a complex biological narrative to be interpreted and directed. Such innovative thinking underscores the transformative potential of integrating technology, biology, and evolutionary medicine to confront one of humanity’s toughest medical challenges.

The Oncodarwinian Hypothesis thus marks an ambitious step toward decoding the genetics, immunology, and evolutionary biology of cancer through sophisticated, AI-driven biomolecular engineering. Whether future empirical findings validate this bold vision remains an open question, but the conceptual framework inaugurates new scientific dialogues and inspires novel lines of inquiry that may reshape how we understand and ultimately treat cancer.

Subject of Research: Cancer biology, synthetic biology, AI-driven protein design, immunology, evolutionary medicine

Article Title: The Oncodarwinian Hypothesis: Cancer as a Potential Immunoadaptive Response and Artificial Intelligence-based 3D Printed p53 Superproteins

News Publication Date: 22-Jan-2026

Web References:
https://dx.doi.org/10.14218/ERHM.2025.00041
https://www.xiahepublishing.com/journal/erhm