The proposed research will develop an innovative and clinically relevant class of nanomaterials—DNA-based “dendritic” (branched) nanostructures—as immunotherapeutics for treating melanoma. Melanoma immunotherapies, where one seeks to harness the body’s natural immune system and reprogram it to attack melanoma tumor cells, are currently ineffective in most patients. New approaches are urgently needed to improve response rates and deliver long-lasting remissions. One promising avenue lies in utilizing a cell’s natural “alarm system,” the cGAS–STING pathway. This pathway, activated when DNA binds to the cGAS enzyme, triggers a cascade of signals that stimulates both innate and adaptive immune defenses against cancer. Clinical efforts to exploit this pathway with small molecule STING agonists have not succeeded clinically because these drugs are rapidly cleared from the body, do not enter cells efficiently, and vary in potency across patient populations.

Adding to the challenge, immune activation through cGAS-STING also increases levels of a checkpoint “brake” protein PD-L1 on tumor and immune cells, which in turn dampens tumor killing and exhausts the immune system. To overcome these hurdles, we will develop a new class of programmable DNA-based nanostructures that can carry and precisely deliver orthogonally complementary therapies: DNA sequences to activate the cGAS–STING pathway and separate short DNA sequences that block the production of PD-L1 surface protein. This proposed research innovatively develops these nanostructures as molecular platforms to structure these immunotherapeutic cues and deliver them in optimized architectures to cells. Due to the modularity of our system, we propose to harness this feature to evaluate specific structural parameters that lead to effective delivery of immune-stimulating cues as well as appropriate timing of the anti-tumor-evasion cues. Our research is a paradigm shift in the way in which melanoma treatments are developed, as it harnesses advances in chemistry and nanotechnology to expand our capabilities in immunology. With our approach, we have the opportunity to develop robust and longer-lasting melanoma immunotherapies that are effective across a wide population of patients. By uniting precise immune activation with reduced “immune brake protein” expression in a single, modular platform, this research aims to produce a versatile, next-generation immunotherapy to treat patients with melanoma.  

Melanoma is one of the most serious forms of skin cancer, but when found early, it’s highly treatable. Unfortunately, many people who are most at risk do not have easy access to dermatologists or affordable sun protection, making prevention and early detection more difficult. Our project focuses on patients seen at the DAWN Dermatology Clinic, a free, student-run clinic in Denver that serves uninsured Aurora residents. We are studying how our patients learn about skin cancer and melanoma prevention, including which social media or online sources they use and how much they trust that information. We are also testing how well artificial intelligence tools, such as ChatGPT, answer common patient questions about moles, sunscreen, and melanoma warning signs.

Our dermatology team reviews these artificial intelligence-generated answers using a standardized rubric developed by board-certified dermatologists to assess accuracy and safety. To help reduce UV exposure, we plan to give each participant SPF-protective shirts and sunscreen, items that many cannot afford but that make a real difference in melanoma prevention. These products are especially valuable for patients who work outdoors and spend long hours in the sun, which is common among our clinic population. By combining education, sun-protective resources, and evaluation of digital information quality, our project aims to close the melanoma prevention gap for underserved communities. We hope this effort will help patients recognize the early signs of melanoma, practice better sun safety, and feel empowered to protect their skin health.

Skin cancer is one of the most common and preventable types of cancer. Sun exposure and tanning increase the risk, but using sunscreen and avoiding sunburns can help prevent it. Some people, such as those who take medicines that weaken their immune system or who have certain medical conditions, are at higher risk for skin cancer. We do not know as much about whether these adults protect themselves from the sun as much as others. This project will use data from the 2024 National Health Interview Survey (NHIS), which asks thousands of adults across the United States about their health and sun-protection habits. The study will compare people who are immunosuppressed with those who are not to see how their sun behaviors and skin-cancer rates differ. The results will help identify who is less likely to practice sun safety and how doctors and public health programs can better teach and assist with sun protection strategies. This research will provide important information to guide future efforts to prevent melanoma and other skin cancers in people most at risk. 

Melanoma and Parkinson’s disease may seem like completely unrelated conditions. One involves uncontrolled cell growth, while the other involves the degeneration of brain cells. However, research has shown a surprising connection between them: people with melanoma are more likely to develop Parkinson’s disease, and vice versa. This link suggests that both diseases may share biological processes that determine whether a cell survives or dies. A key molecule that may connect these two conditions is a protein called alpha-synuclein, best known for its role in Parkinson’s disease. In brain cells, this protein can clump together into a non-functional aggregate, impairing the cell’s ability to repair its DNA and eventually leading to cell death.

In melanoma, however, an overabundance of the same protein appears to help tumor cells repair DNA damage more efficiently, which promotes tumor progression and resistance to cancer treatments such as radiation or chemotherapy. This project will explore how alpha-synuclein influences DNA repair in melanoma cells and whether those same repair pathways can be targeted to make treatments more effective. To do this, we will compare melanoma cells that produce alpha-synuclein with those that do not, using advanced imaging, molecular, and single-cell techniques to track how cells respond to DNA damage. We will also test whether a drug called enoxacin, which strengthens the cell’s natural DNA repair machinery, can restore efficient repair in cells lacking alpha-synuclein. By uncovering how melanoma cells use these repair mechanisms to survive, this work could reveal new ways to increase the effectiveness of existing therapies and prevent treatment resistance. More broadly, it may explain how the same molecular pathways can cause degeneration in the brain but drive cancer growth in the skin, providing insight that could benefit patients with both melanoma and Parkinson’s disease. 

The morphologies of benign lesions are well-defined in the literature; however, most visual examples and training materials are selectively sampled from patients with lighter skin and in the most common anatomical areas, leaving important gaps in how common, harmless lesions appear in darker skin tones. As a result, both clinicians and AI tools can struggle to identify benign lesions accurately in all patients, leading to over-biopsying of patients with skin tones in the extremes of the spectrum or patients who present with benign lesions in uncommon anatomical areas.

Our project will create an inclusive, high-quality annotated image dataset of common benign skin lesions, such as seborrheic keratoses, angiomas, and dermatofibromas, captured across the full range of objectively measured skin tones and body sites. Using dermoscopic imaging and a color-measurement tool that quantifies skin tone precisely (via Individual Typology Angle, or ITA), we will document how these benign lesions vary in dermoscopic appearance. We will assess the innate skin tone of each patient by measuring the ITA value of the inner portion of the upper arm to avoid incorporating variations in skin tone due to UV exposure on different body sites. This dataset will improve the ability of clinicians to recognize benign skin lesions more accurately and reduce unnecessary biopsies. By capturing how benign lesions look across diverse innate skin tones, this work will improve clinical training and accuracy of melanoma diagnosis and help ensure that future AI tools are built on datasets that are representative of a more diverse population of patients. 

Cardiofaciocutaneous syndrome (CFC) is an inherited disorder. It can cause people to have more moles on their body. Having more moles increases your risk of developing melanoma, the deadliest form of skin cancer. We do not know if the risk is different in individuals with CFC syndrome, specifically. In this study, we aim to find patients with CFC who also have a history of melanoma. We will analyze the genetic makeup of these tumors and compare them to other melanomas and normal moles. We hypothesize that individuals with CFC will have a higher risk of melanoma compared to people without CFC. Research participants will be recruited through CFC support and research organizations. 

We will compare the DNA in the melanomas to DNA from a saliva sample and compare them. We will then create a cellular map of the melanoma, showing gene activity throughout the sample. We have already identified one patient with melanoma in situ, an early stage of disease. To our knowledge, this is the first case in an individual with CFC. Additionally, we have already completed the DNA comparison and cellular mapping in one mole from a person with CFC and two melanomas in people without CFC. In this study, we will investigate the genetic differences between melanomas in individuals with CFC, normal moles, and melanomas in people without CFC. This study will shed light on melanoma development and risk of disease in CFC patients. 

Melanoma is the 5th leading cause of cancer with 100,000 new cases annually in the United States. Though some melanomas carry mutations that can be targeted with drugs, these do not provide lasting remissions. Furthermore, a large number of T-regulatory cells, M2-like macrophages, and myeloid-derived suppressor cells infiltrate tumors and directly suppress tumor-targeting immune cells. We believe that the dendritic cell (DCs), a type of white blood cell, can overcome these immunosuppressive signals. DCs present pieces of cancer called antigens to train immune cells. By injecting large numbers of DCs directly into tumors, we have shown in clinical trials with aggressive HER2-positive breast cancer patients that, before chemotherapy and surgery, these injections can shrink multiple tumors throughout the body with few side effects. This response correlates with significant increases in immune cells and decreases in immunosuppressive cells in the tumor. We believe this DC therapy can work across all cancer types when paired with a lipid antigen called a-GalCer, which is recognized by invariant natural killer T cells (iNKTs). iNKT cells are universally present in all people. Although they have been shown to enhance immunosuppressive myeloid cells, preliminary work suggests that a-GalCer DCs can train iNKT cells to convert immunosuppressive cells into supportive cells. In mouse models of melanoma, blocking the interaction between DCs and iNKT cells prevents the DC immunotherapy from working as well. By using a series of direct coculture experiments, flow cytometry, and RNA-sequencing, we are seeking to understand how iNKT cells work with DCs to regress tumors, understand how iNKT cells subsequently change immunosuppressive cells into supportive cells, and test whether the combination of iNKT cells with DCs can create a therapy that can reduce or even replace the need for toxic chemotherapy. 

The Problem: New immune therapies have dramatically improved survival for melanoma patients, but they can sometimes make the immune system attack healthy skin, causing rashes and other side effects. These skin problems can be painful, disruptive, and even force patients to stop life-saving treatment. Studying them is very slow and hard because doctors would have to read through thousands of patient records by hand. Our Solution: We built a “smart AI team” that can read patient records like a group of expert assistants. Each AI has a job: one identifies the type of rash, another finds when it started, a third checks whether the therapy likely caused it, and a fourth grades how severe it is. A supervising AI double-checks all their work. The AI organizes the results into a standardized digital format, like putting together furniture by following a specific blueprint, so they can be used safely and consistently across hospitals. What We Did: We first tested the AI on 2,000 patient charts reviewed by real doctors to see how well it matches human judgment. We also tested it on 700 charts from another hospital to make sure it works in different settings. The system is designed to avoid mistakes, and to give reliable results every time. The Impact: This AI team can work more than 50 times faster than humans and still be accurate. It will create a large, clean dataset that links skin side effects to patient genetics, helping researchers discover who is most at risk. Ultimately, this could guide safer, more personalized treatment for melanoma patients. 

Even after successfully removing a cutaneous melanoma (CM) primary tumor, the cancer can sometimes return years or decades later in other parts of the body; the main reason this cancer can be fatal. This recurrence happens because a few cancer cells escape the original tumor early on and travel elsewhere in the body, where they lie dormant, or “asleep,” for an extended period of time before suddenly “waking up” to form a new tumor. A critical mystery is what causes these cells to wake up when they do. Our research tackles this problem based on two key ideas. First, we believe only a subset of cells within the original tumor are primed to spread, lie dormant, and later wake up. Second, we can calculate how long these cells were dormant by reading the genetic changes accumulated in their DNA, like reading a molecular clock. In our preliminary work, we found that tumors with specific, recurring errors in genes that control cell growth were more likely to spread.

These errors, which make the cancer cells’ chromosomes unstable, seem to give them a special ability to travel and survive in the body. We have gathered a unique collection of tissue samples from 80 melanoma patients, each including their original tumor and the later metastasis. This direct comparison is essential to see what changed in the cells’ DNA during this dormant “asleep” period. Our first goal is to compare the primary and metastatic tumors to identify the exact “founder” cells that started the metastasis and understand what makes these founder cells different from the others. Our second goal is to use the DNA changes as a timer to calculate the dormancy period and pinpoint the specific genetic features that cause some cells to wake up quickly while others stay asleep for years. By understanding the mechanisms that keep these dangerous cells asleep and what triggers them to wake up, we hope to identify new treatment targets that can extend dormancy and prevent the cancer from returning. 

Skin cancer is the most commonly diagnosed cancer in the US. Although melanoma accounts for only 1% of skin cancers, it causes the majority of deaths. 50% of melanoma tumors contain mutations in the BRAF protein, which causes cells to constantly grow and divide. Drugs that target this growth pathway are effective, but melanomas typically overcome these drugs within one year, often by using alternative pathways to cell growth. One such pathway is through a protein called phosphatidyl inositol 3-kinase (PI3K). Research targeting this pathway has shown variable success. This is in part because subclasses of PI3K, including PI3Ka,ß,d, and ?, have different roles, including in metabolic and immune functions, and inhibition of all PI3K subclasses can have serious side effects. Research by the Sheng Lab and others has demonstrated a key role of PI3Kß specifically in melanoma cells with the BRAF mutation.

As such, our overarching research question explores how targeting PI3Kß specifically will decrease melanoma cell growth in melanomas that have overcome existing drug therapies. The proposed research investigates how inhibiting PI3Kß will affect melanoma cells that are resistant to Dabrafenib/Trametinib, one of the existing melanoma treatment combinations. The Sheng Lab has designed a unique drug, Selective-9 (S9) that blocks PI3Kß only, without affecting other PI3K proteins. We hypothesize that therapy-resistant melanoma cells with high levels of PI3K will show less growth when treated with S9 compared to therapy-resistant melanoma cells with low levels of PI3K. Utilizing existing drug combinations with proven success in treating melanoma is resource-efficient and safe, while inhibiting specific tumor pathways will also create more individualized treatment solutions.