Genevieve Marie Boland

This study identifies genomic subtypes and immune features of mucosal melanoma, linking CD163+ macrophages to immune resistance and suggesting TIM-3 blockade as a therapeutic target.

This study identifies CD8+TOX+ T-cells as a specific marker for autoimmune hepatitis using single-nucleus RNA sequencing.

The paper introduces DIGEST, an ultrasensitive digital immunoassay for quantifying host proteins in fecal samples, demonstrating its utility in tracking immune dynamics and predicting disease outcomes.

This study identifies distinct malignant cell states and myeloid glutamate signaling in aggressive pancreatic neuroendocrine tumors, linking them to poor clinical outcomes and therapeutic vulnerabilities.

This study shows that breast tumors impair antigen presentation in local lymph nodes, which can be overcome by delivering IL1β or adjuvants to distant lymph nodes, improving anti-cancer immune responses.

This study identifies a novel CD8+ TIL subset that uses lymphotoxin and IFN pathways to kill cancer cells, linking LTB expression to clinical response in melanoma.

The paper identifies melanoma differentiation and immune exhaustion as predictors of tumor progression and therapy response in in-transit melanoma patients through multiomic profiling.

This paper describes a designed IL-21 mimic, 21h10, which shows potent antitumor activity in multiple models and reduces toxicity through TNF blockade.

This paper shows YAP1 promotes therapy resistance in melanoma by altering chromatin structure and immune evasion programs, and suggests TEAD inhibitors could overcome resistance and boost immune response.

The paper identifies a mature dendritic cell subtype associated with improved immune response and prognosis in melanoma patients treated with anti-PD-1 checkpoint inhibitors.

This study develops a zebrafish model of mucosal melanoma by activating an oncogene and inactivating tumor suppressors, revealing that internal melanocytes give rise to tumors with distinct transcriptional and chromatin features.

This study shows that targeting CD38 improves T cell function and restores response to immunotherapy in melanoma models.

The paper analyzes multiomic data from primary and metastatic esophageal adenocarcinoma tumors to identify cell states and their spatial interactions, linking them to clinical outcomes.

The paper identifies CREB5 as a driver of immunotherapy resistance in melanoma by promoting collagen matrix deposition, which activates LAIR1 signaling on immune cells.

The paper identifies HIF-2α as a therapeutic target for immune-infiltrated melanomas through stratified analysis of clinical and molecular data.

DeepVul predicts gene essentiality and drug response using a multi-task transformer model trained on cancer transcriptome data, improving precision oncology by identifying treatment vulnerabilities.

The paper uses buoyant mass to identify distinct T cell states that predict response to immune checkpoint therapy in melanoma patients.

This study examines the evolutionary dynamics of peritoneal metastases in colorectal cancer, finding they are more heterogeneous than liver metastases but less diverse than locoregional metastases.

This study identifies molecular mechanisms of resistance to immune checkpoint blockade in metastatic melanoma using proteogenomic and spatial analyses of tumor and immune microenvironment data.

This paper introduces MRD-EDGE, a machine learning platform for ultrasensitive ctDNA detection in plasma WGS, showing improved sensitivity and broader applicability for MRD monitoring.

DrugMap quantitatively analyzes cysteine ligandability across 416 cancer cell lines, revealing redox state, conformational changes, and mutations as drivers of variability, and identifies covalent inhibitors targeting NFκB1 and SOX10.

This paper introduces MAS-ISO-seq, a method to boost throughput of long-read RNA sequencing for isoform discovery, showing improved detection of differentially spliced genes and cell clustering in T cells.

This study applies low-cost whole genome sequencing to detect circulating tumor DNA at high sensitivity in plasma samples, achieving error rates as low as 10^-7 and enabling cancer monitoring without matched tumor sequencing.

The paper develops DNA- and RNA-based models combining immune and tumor features to predict outcomes of checkpoint inhibition in melanoma.

The paper profiles the enteric nervous system of human and mouse colon at single-cell resolution, revealing diverse neuron subsets and shared transcriptional programs between species.