Biology subjects

Goldszmid, R. S.

Publications and source records attributed to Goldszmid, R. S..

5 recordsLinked to original sources

bioRxiv2024

BRAIN-METASTATIC MELANOMA MODELS UNCOVER IMMUNE AND MOLECULAR CORRELATES OF RESPONSE TO IMMUNOTHERAPY

Despite the promising results of immune checkpoint blockade (ICB) therapy, outcomes for patients with brain metastasis (BrM) remain poor. Identifying resistance mechanisms has been hindered by limited access to patient samples and relevant preclinical models. Here, we developed two mouse melanoma BrM models that recapitulate the disparate responses to ICB seen in patients. We demonstrate that these models capture the cellular and molecular complexity of human disease and reveal key factors shaping the tumor microenvironment and influencing ICB response. BR1-responsive tumor cells express inflammatory programs that polarize microglia into reactive states, eliciting robust T cell recruitment. In contrast, BR3-resistant melanoma cells are enriched in neurological programs and exploit tolerance mechanisms to maintain microglia homeostasis and limit T cell infiltration. In humans, BR1 and BR3 expression signatures correlate positively or negatively with T cell infiltration and BrM patient outcomes, respectively. Our study provides clinically relevant models and uncovers mechanistic insights into BrM ICB responses, offering potential biomarkers and therapeutic targets to improve therapy efficacy.

immunology↗

bioRxiv2024

Development of an optimized machine learning approach to enhance brain metastatic burden assessment in preclinical models.

Brain metastases (BrM) occur when malignant cells spread from a primary tumor located in other parts of the body to the brain. BrM is a deadly complication for cancer patients and currently lacks effective therapies. Due to the limited access to patient samples, preclinical models remain a valuable tool for studying metastasis development, progression, and response to therapy. Thus, reliable methods for quantifying metastatic burden in these models are crucial. Here, we describe step by step a new semi-automatic machine-learning approach to quantify metastatic burden on mouse whole-brain stereomicroscope images while preserving tissue integrity. This protocol utilizes the open-source, user-friendly image analysis software QuPath. The method is fast, reproducible, unbiased, and provides access to data points not always obtainable with other existing strategies.

cancer biology↗

bioRxiv2024

Use of optimized single-cell RNA flow cytometry protocol identifies monocytes as main producers of type I interferon in mouse syngeneic tumors

The tumor microenvironment (TME) consists of complex interactions between cellular and extracellular components, among which the immune system is known to play an integral role in disease progression and response to therapy. Cytokines and chemokines are cell signaling proteins used by immune cells to communicate with each other as well as with other cell types in the body. These proteins control systemic and local immune responses and levels of cytokines/chemokines in the TME have been associated with tumor outcomes. However, cytokines and chemokines have varied expression across cell types, tumors, and host conditions. Therefore, approaches to effectively study the production of these proteins at the single-cell level in the TME are needed to fully elucidate the mechanisms governing the anti-cancer immune response. Here, we detail a protocol to assess the production of cytokines/chemokines across leukocyte populations in mouse tumors using RNA flow cytometry. Importantly, this method can be adapted with minimal changes to study various mouse and human tumors, other RNA analytes, and non-tumor tissues. With this approach, we characterize single-cell production of Ifnb1, Xcl1 and Ccl5 in mouse tumors and identify monocytes and monocyte-derived macrophages as the main producers of type I interferon transcript Ifnb1 consistent across 4 different syngeneic tumor models.

immunology↗

bioRxiv2024

Loss of NAT10 disrupts enhancer organization via p300 mislocalization and suppresses transcription of genes necessary for metastasis progression.

Acetylation of protein and RNA represent a critical event for development and cancer progression. NAT10 is the only known RNA acetylase that catalyzes the N4-actylcytidine (ac4C) modification of RNAs. Here, we show that the loss of NAT10 significantly decreases lung metastasis in allograft and genetically engineered mouse models of breast cancer. NAT10 interacts with a mechanosensitive, metastasis susceptibility protein complex at the nuclear pore. In addition to its canonical role in RNA acetylation, we find that NAT10 interacts with p300 at gene enhancers. NAT10 loss is associated with p300 mislocalization into heterochromatin regions. NAT10 depletion disrupts enhancer organization, leading to alteration of gene transcription necessary for metastatic progression, including reduced myeloid cell-recruiting chemokines that results in a less metastasis-prone tumor microenvironment. Our study uncovers a distinct role of NAT10 in enhancer organization of metastatic tumor cells and suggests its involvement in the tumor-immune crosstalk dictating metastatic outcomes.

cancer biology↗

bioRxiv2019

Multi-model preclinical platform predicts clinical response of melanoma to immunotherapy

Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrates durable clinical benefit. Definitive predictive biomarkers and targets to overcome resistance remain unidentified, underscoring the urgency to develop reliable immunocompetent models for mechanistic assessment. Here we characterize a panel of syngeneic mouse models representing the main molecular and phenotypic subtypes of human melanomas and exhibiting their range of responses to immune checkpoint blockade (ICB). Comparative analysis of genomic, transcriptomic and tumor-infiltrating immune cell profiles demonstrated alignment with clinical observations and validated the correlation of T cell dysfunction and exclusion programs with resistance. Notably, genome-wide expression analysis uncovered a melanocytic plasticity signature predictive of patient outcome in response to ICB, suggesting that the multipotency and differentiation status of melanoma can determine ICB benefit. Our comparative preclinical platform recapitulates melanoma clinical behavior and can be employed to identify new mechanisms and treatment strategies to improve patient care.

cancer biology↗