Evolution of Metabolic and Immune Dysfunction in In-transit Melanoma
- Registration Number
- NCT04658303
- Lead Sponsor
- Yana Najjar
- Brief Summary
Melanoma in-transit metastases (ITMs) continue to represent a therapeutic dilemma, in that no standard method of treatment has been uniformly adopted. The complexity and heterogeneity of patient and disease characteristics, including the location and number of ITMs presents a barrier to a one size fits all treatment approach. Treatment of patients with limited regional disease remains challenging. Patients are typically treated with a combination of surgery, regional therapy, systemic therapy. Data on the management of ITMs is limited, even with the availability of immunotherapy (IMT). This study will use the unique etiology of ITMs to facilitate the understanding of how individual lesions metabolically and immunologically evolve as they move away from the primary tumor site. It is hypothesize that as ITMs move away from the primary melanoma site each will harbor progressively hypermetabolic tumor cells and a harsher microenvironment.
- Detailed Description
This study will use a novel platform to profile patient biopsies, including microscopic analysis, flow cytometry for phenotyping, metabolic, and functional analyses, and metabolic profiling by Seahorse analysis to understand the unique etiology of ITMs to understand how individual melanoma lesions metabolically and immunologically evolve as they move away from the primary tumor site. A large amount of translational data is able to be derived from from an individual tissue biopsies. This study will utilize this platform to extensively evaluate 2-5 (melanoma) in-transit metastases (ITMs) per patient. It is hypothesized that as ITMs move away from the primary melanoma site each will harbor progressively hypermetabolic tumor cells and a harsher microenvironment. Each ITM station will be deeply profiled using metabolic assays, flow cytometry, and highly multiplexed immunofluorescent microscopy including, to interrogate the metabolic profiles of tumor and immune system in individual melanoma ITMs, and, to Determine tumor:immune interaction in the context of hypoxia using high-dimensional imaging. Using high throughput sequencing technologies, it will determined how tumor and immune cells interact and evolve during the course of transit in ITMs (as these cells become more metabolically and immunologically suppressive as they migrate further from the primary site). The clonal evolution analysis of tumor cells through and pimonidazole-enabled single cell RNA-sequencing will be used to identify transcriptomic changes in tumor, immune, and stromal cells correlated with hypoxia exposure.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 20
- Be willing and able to provide written informed consent for the trial.
- Be ≥ 18 years of age on day of signing informed consent.
- A histological diagnosis of melanoma and at least two in-transit lesions at distinct distances from the primary site. Patients may be enrolled on the basis of a diagnosis of in-transit disease by a treating melanoma oncologist.
- Cutaneous, mucosal or uveal melanoma are permitted.
- Patients may be on treatment or treatment naïve.
- Female patients of childbearing potential must have a negative urine or serum pregnancy test within 7 days from the time of pimonidazole administration.
- Subjects with in-transit disease that is not amenable to biopsy per the treating physician are excluded.
- Subjects with known chronic immunosuppression (such as biologic agents like remicade, mycophenolate, methotrexate, prednisone >20 mg daily).
- Subjects who are known to be HIV+, Hep B or Hep C positive.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Pimonidazole Pimonidazole Single dose of 0.5 gm/m\^2 of pimonidazole (approximately 13 mg/kg)
- Primary Outcome Measures
Name Time Method Immunometabolic profiling At baseline Immunometabolic profiling of individual microenvironments in ITMs (in-transit metastases) using flow cytometry via T cell subsets, markers of activation/exhaustion, and metabolic insufficiency (mitochondrial mass, glucose uptake capacity, and hypoxia by pimonidazole staining.
Tumor cell metabolism At baseline Tumor cells metabolism of ITMs (in-transit metastases) will be profiled using the Seahorse flux analyzer to measure oxygen consumption rate (OCR) and extracellular acidification rate (ECAR).
hypoxia exposure analyses At baseline Akoya Biosciences' CODEX analysis suite and custom ImageJ plugins will be used to determine proximity of cells to one another, coincidence with hypoxic areas, and accumulation of regulatory/dysfunctional populations.
Imaging of individual ITM stations At baseline CODEX imaging will be conducted on sections from each station using extensive phenotyping panels.
- Secondary Outcome Measures
Name Time Method TCR clonotype and trajectory analysis At baseline 5' scRNAseq will be used for identification of TCR sequences to identify individual T cell clones. Clonotypes will be revealed in each lesion, and diffusion pseudotime analyses will be employed within each ITM and between ITMs to determine differentiation states of various T cell subsets. It is thought that distant lesions will harbor more terminally differentiated T cells.
Tumor transcriptomic states At baseline Analysis of hypoxia exposure for each cell using unique pimonidazole CITE-seq strategy also allows for the a. As hypoxia promotes the terminal differentiation of T cells, it is expected that distant ITMs will harbor more hypoxic cells and that terminally differentiated T cells will experience higher levels of hypoxia.
Clonal evolution analysis of individual ITMs At baseline Mutations will be used to construct trees revealing clonal representation and diversity at each station. The goal is to determine how migration away from the primary site affects a tumor's heterogeneity in terms of tumor cells.
Whole exome sequencing of tumor cells At baseline Whole exome sequencing will be performed to identify mutations in tumor cells isolated from each lesion. Analysis will be in an 'intrapatient' manner as a function of distance from the primary site.
Cellular heterogeneity and transcriptomic state At baseline The composition of each ITM tumor microenvironment will be analyzed using dimension reduction strategies, in collaboration with a bioinformatics core. Each biopsy sample will be sequenced simultaneously but hashed separately, allowing all ITMs to be compared in one run. Clusters will be identified using lineage-defining genes and then transcriptomic states identified within each cluster.
Trial Locations
- Locations (1)
UPMC Hillman Cancer Center
🇺🇸Pittsburgh, Pennsylvania, United States