Biology subjects

Lee, M. P.

Publications and source records attributed to Lee, M. P..

16 recordsLinked to original sources

bioRxiv2025

Hyper-responsiveness of cancer stem cells to microenvironmental cues controls metastasis and therapy response through YAP/TAZ/TEAD

Cancer stem cells (CSCs) are key drivers of metastasis and therapy resistance but have been challenging to visualize and study in situ. Using a fluorescent CSC reporter, we observed very different population dynamics for CSCs and nonCSCs during metastatic lung colonization in breast cancer models. CSC expansive self-renewal drives early lesion formation before switching to a maintenance mode of balanced self-renewal and differentiation, whereupon nonCSC proliferation takes over as the main driver of metastatic expansion. Mechanistic analyses showed that CSCs are hyper-responsive to microenvironmental cues such as cell crowding and nutrient availability, suggesting a novel role for CSCs as sensors and early responders to fluctuating local conditions in the tumor. Incoming signals converge on YAP/TAZ/TEAD, with heightened CSC sensitivity and response supported by elevated receptor expression and increased chromatin accessibility around enhancers with TEAD binding sites. Targeting inputs to the YAP/TAZ/TEAD node reversed chemotherapy-induced enrichment of CSCs in lung metastases. HighlightsO_LIDifferent population dynamics for breast cancer stem cells (CSCs) and their differentiated progeny in early metastatic colonization C_LIO_LICSCs are hyper-responsive to microenvironmental cues and serve as sensors of local conditions for the tumor C_LIO_LIMany microenvironmental inputs converge on YAP/TAZ to regulate self-renewal vs differentiation fate decisions in the CSC C_LIO_LITargeting YAP/TAZ input pathways blocks chemotherapy-induced enrichment of CSCs C_LI

cancer biology↗

bioRxiv2025

Pericyte-tumor crosstalk facilitates metastatic tumor cell latency through PIEZO1-activated lysophospholipid transfer.

Tumor dissemination is increasingly recognized to begin early in tumor development. Although most of these early disseminated cells are cleared, some survive and persist below clinical detection, acting as reservoirs for metastatic relapse. Metastatic tumor cells often rely on interactions with local stromal cells to support their colonization. In this study, we propose that pericyte-tumor cell interactions promote dormancy induction in the early metastatic lung, enhancing disseminated tumor cell (DTC) persistence. Extravital imaging demonstrated that DTCs interact with pericytes upon extravasation into the lung. Co-culture experiments were used to assess DTC fate after pericyte contact and revealed that transient contact with pericytes reduced the proliferation of metastatic 4T1 breast cancer cells but had no effect on non-metastatic 67NR cells. In vivo, transient pericyte contact resulted in higher lung metastatic burden, driven by small, non-proliferative lesions (<6 cells), 10 days after intracardiac injection. These lesions exhibited reduced KI67 staining and EdU incorporation compared to those from monocultured cells. We further observed that primary lung pericytes transferred lyso-phospholipids (lyso-PLs) specifically to metastatic 4T1 cells through direct contact. Gene expression analysis indicated that transient pericyte contact activated pathways related to syncytium formation in metastatic cells. In normal physiology, pericytes act in a syncytium to regulate blood flow via mechanosensitive channels in response to blood pressure changes. We hypothesize that tumor cells exploit these mechanosensitive responses to trigger lyso-PL transfer from pericytes. Supporting this, calcium imaging showed higher calcium activity in pericytes co-cultured with 4T1 cells, and calcium channel inhibitors significantly reduced lyso-PL transfer. Pharmacological activation of pericyte calcium channels induced lyso-PL release, which was subsequently taken up by tumor cells. Conditioned medium from activated pericytes, containing free lyso-PLs, recapitulated the reduced proliferation observed in transient co-culture. Finally, we found our pericyte-induced dormancy signature to be associated with tumor dormancy and distant metastasis free survival latency in breast cancer patients. Together, these findings suggest that early DTCs may exploit pericyte signaling mechanisms to enter dormancy, facilitating their persistence at metastatic sites and contributing to future relapse.

cancer biology↗

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

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↗

bioRxiv2023

The combination of topological data analysis and mathematical modeling improves sleep stage prediction from consumer-grade wearables

Wearable devices have become commonplace tools for tracking behavioral and physiological parameters in real-world settings. Nonetheless, the practical utility of these data for clinical and research applications, such as sleep analysis, is hindered by their noisy, large-scale, and multidimensional characteristics. Here, we develop a neural network algorithm that predicts sleep stages by tracking topological features (TFs) of wearable data and model-driven clock proxies reflecting the circadian propensity for sleep. To evaluate its accuracy, we apply it to motion and heart rate data from the Apple Watch worn by subjects undergoing polysomnography (PSG) and compare the predicted sleep stages with the corresponding ground truth PSG records. We find that TFs and clock proxies can improve the overall performance of wake/REM/NREM sleep classification, particularly in identifying REM and NREM sleep (AUROC/AUPRC improvements > 9% and REM/NREM accuracy improvement " 12%). We find that this improvement is mainly attributed to the heart rate TFs. To confirm this, we compare the heart rate TFs between two groups, expected to have different cardiovascular conditions: younger, healthy subjects from the Apple Watch cohort and elderly subjects from the Multi-ethnic Study of Atherosclerosis cohort. Indeed, TFs largely vary across REM and NREM sleep in younger individuals while the variations disappear in elderly individuals, explaining the enhanced improvements in REM or NREM sleep classification problems only in the younger individuals. This study demonstrates the benefits of combining topological data analysis and mathematical modeling to extract hidden inputs of neural networks from puzzling wearable data.

bioinformatics↗

bioRxiv2023

Melanoma clonal subline analysis uncovers heterogeneity-driven immunotherapy resistance mechanisms

Intratumoral heterogeneity (ITH) can promote cancer progression and treatment failure, but the complexity of the regulatory programs and contextual factors involved complicates its study. To understand the specific contribution of ITH to immune checkpoint blockade (ICB) response, we generated single cell-derived clonal sublines from an ICB-sensitive and genetically and phenotypically heterogeneous mouse melanoma model, M4. Genomic and single cell transcriptomic analyses uncovered the diversity of the sublines and evidenced their plasticity. Moreover, a wide range of tumor growth kinetics were observed in vivo, in part associated with mutational profiles and dependent on T cell-response. Further inquiry into melanoma differentiation states and tumor microenvironment (TME) subtypes of untreated tumors from the clonal sublines demonstrated correlations between highly inflamed and differentiated phenotypes with the response to anti-CTLA-4 treatment. Our results demonstrate that M4 sublines generate intratumoral heterogeneity at both levels of intrinsic differentiation status and extrinsic TME profiles, thereby impacting tumor evolution during therapeutic treatment. These clonal sublines proved to be a valuable resource to study the complex determinants of response to ICB, and specifically the role of melanoma plasticity in immune evasion mechanisms.

cancer biology↗

bioRxiv2022

Comprehensive single-cell transcriptomic analysis of embryonic melanoblasts uncovers lineage-specific mechanisms of melanoma metastasis and therapy resistance

Melanoma plasticity, driven by phenotype state switching, underlies clinically relevant traits such as metastasis and therapy resistance. As melanoma progression is thought to recapitulate aspects of neural crest cell (NCC) development, understanding embryonic melanocyte specification and lineage fate decisions of closely related NCCs may illuminate the pathways co-opted during disease evolution. Here, we use a mouse model to isolate and sequence Dopachrome tautomerase (Dct) expressing NCCs, the precursors of melanocytes, at two key developmental stages. We classify these lineages and devise a Developmental Gene Module (DGM) scoring system to interrogate lineage state switching in melanoma samples. In bulk transcriptomes, activation of DGMs representing embryonic Schwann Cell Precursors (SCPs)--multipotent stem cells--in patient tumors predicts poor response to immune checkpoint inhibitors (ICI). Co-activation of SCP and Mesenchymal-like (Mes.) modules further correlates with resistance to MAPK inhibitors. Notably, single-cell analyses reveal that melanoma cells can simultaneously express multiple DGMs, forming "hybrid" states. Cells in a hybrid Neural/SCP state are enriched in early metastasis and ICI-resistant tumors and are insensitive to inflammatory stimuli. We demonstrate that targeting Hdac2, a histone deacetylase associated with this Neural/SCP hybrid state, promotes a mesenchymal-like state switch, remodels the tumor microenvironment, and sensitizes melanoma cells to TNF and tumors to ICI therapy. Our methodology thus reveals dynamic patterns of lineage state switching correlated with melanoma tumor evolution to drive insight into new therapeutic targets. TeaserNewly identified melanoblast cell states are reawakened in metastasizing and therapy-resistant melanomas.

cancer biology↗

bioRxiv2021

Profiles of expressed mutations in single cells reveal patterns of tumor evolution and therapeutic impact of intratumor heterogeneity

Advances in single-cell RNA sequencing (scRNAseq) technologies uncovered an unexpected complexity in tumors, underlining the relevance of intratumor heterogeneity to cancer progression and therapeutic resistance. Heterogeneity in the mutational composition of cancer cells is a result of distinct (sub)clonal expansions, each with a distinct metastatic potential and resistance to specific treatments. Unfortunately, due to their low read coverage per cell, scRNAseq datasets are too sparse and noisy to be used for detecting expressed mutations in single cells. Additionally, the large number of cells and mutations present in typical scRNAseq datasets are too large for available computational tools to, e.g., infer distinct subclones, lineages or trajectories in a tumor. Finally, there are no principled methods to assess distinct subclones inferred through single-cell sequencing data and the genomic alterations that seed and potentially cause them. Here we present Trisicell, a computational toolkit for scalable mutational intratumor heterogeneity inference and assessment from scRNAseq as well as single-cell genome or exome sequencing data. Trisicell allows reliable identification of distinct clonal lineages of a tumor, offering the ability to focus on the most important subclones and the genomic alterations that are associated with tumor proliferation. We comprehensively assessed Trisicell on a melanoma model by comparing distinct lineages and subclones it identifies on scRNAseq data, to those inferred using matching bulk whole exome (bWES) and transcriptome (bWTS) sequencing data from clonal sublines derived from single cells. Our results demonstrate that distinct lineages and subclones of a tumor can be reliably inferred and evaluated based on mutation calls from scRNAseq data through the use of Trisicell. Additionally, they reveal a strong correlation between aggressiveness and mutational composition, both across the inferred subclones, and among human melanomas. We also applied Trisicell to infer and evaluate distinct subclonal expansion patterns of the same mouse melanoma model after treatment with immune checkpoint blockade (ICB). After integratively analyzing our cell-specific mutation calls with their expression profiles, we observed that each subclone with a distinct set of novel somatic mutations is strongly associated with a specific developmental status. Moreover, each subclone had developed a unique ICB-resistance mechanism. These results demonstrate that Trisicell can robustly utilize scRNAseq data to delineate intratumor heterogeneity and help understand biological mechanisms underlying tumor progression and resistance to therapy.

bioinformatics↗

bioRxiv2020

Analyses of Biomarker Traits in Diverse UK Biobank Participants Identify Associations Missed by European-centric Analysis Strategies

Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n=9354), East Asian (n=2559) and South Asian (n=9823) UK Biobank participants ancestry. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in European ancestry UK Biobank participants alone. We identify 12 novel signals in African ancestry and 3 novel signals in South Asian participants (p<1.61 x 10-10). Many of these signals are highly plausible and rare in Europeans (1% or lower minor allele frequency), including cis pQTLs for the genes encoding serum biomarkers like gamma-glutamyl transferase and apolipoprotein A, PIEZ01 and G6PD variants with impacts on HbA1c through likely erythocytic mechanisms, and a coding variant in GPLD1, a gene which cleaves GPI-anchors, associated with normally GPI-anchored protein alkaline phosphatase in serum. This work illustrates the importance of using the genetic data we already have in diverse populations, with many novel discoveries possible in even modest sample sizes.

genetics↗

bioRxiv2020

PhISCS-BnB: A Fast Branch and Bound Algorithm for the Perfect Tumor Phylogeny Reconstruction Problem

MotivationRecent advances in single cell sequencing (SCS) offer an unprecedented insight into tumor emergence and evolution. Principled approaches to tumor phylogeny reconstruction via SCS data are typically based on general computational methods for solving an integer linear program (ILP), or a constraint satisfaction program (CSP), which, although guaranteeing convergence to the most likely solution, are very slow. Others based on Monte Carlo Markov Chain (MCMC) or alternative heuristics not only offer no such guarantee, but also are not faster in practice. As a result, novel methods that can scale up to handle the size and noise characteristics of emerging SCS data are highly desirable to fully utilize this technology. ResultsWe introduce PhISCS-BnB, a Branch and Bound algorithm to compute the most likely perfect phylogeny (PP) on an input genotype matrix extracted from a SCS data set. PhISCS-BnB not only offers an optimality guarantee, but is also 10 to 100 times faster than the best available methods on simulated tumor SCS data. We also applied PhISCS-BnB on a large melanoma data set derived from the sub-lineages of a cell line involving 24 clones with 3574 mutations, which returned the optimal tumor phylogeny in less than 2 hours. The resulting phylogeny also agrees with bulk exome sequencing data obtained from in vivo tumors growing out from the same cell line. Availabilityhttps://github.com/algo-cancer/PhISCS-BnB

bioinformatics↗

bioRxiv2020

Targeting nuclear pore protein, NUP210, reduces metastasis through heterochromatin-mediated silencing of mechanosensitive genes

Mechanical signals from the extracellular microenvironment have been implicated in tumor and metastatic progression. Here, we identified nucleoporin NUP210 as a metastasis susceptibility gene for human estrogen receptor positive (ER+) breast cancer and a cellular mechanosensor. Nup210 depletion suppresses lung metastasis in mouse models of breast cancer. Mechanistically, NUP210 interacts with LINC complex protein SUN2 which connects the nucleus to the cytoskeleton. In addition, the NUP210/SUN2 complex interacts with chromatin via the short isoform of BRD4 and histone H3.1/H3.2 at the nuclear periphery. In Nup210 knockout cells, mechanosensitive genes accumulate H3K27me3 heterochromatin modification, mediated by the polycomb repressive complex 2 and differentially reposition within the nucleus. Transcriptional repression in Nup210 knockout cells results in defective mechanotransduction and focal adhesion necessary for their metastatic capacity. Our study provides a new insight into the role of nuclear pore protein in cellular mechanosensation and metastasis.

cancer biology↗

bioRxiv2019

Metastasis-specific gene expression in autochthonous and allograft mouse mammary tumor models: stratificationand identification of targetable signatures

Breast cancer is a leading cause of cancer-related death of women in the U.S., which is ultimately due to metastasis rather than primary tumor burden. Therefore, increased understanding of metastasis to develop novel therapies is critical in reducing breast cancer-related mortality. Indeed, a major hurdle in advancing metastasis-targeted intervention is the genotypic and phenotypic heterogeneity that exists between primary and secondary lesions. To identify targetable metastasis-specific gene expression profiles we performed RNA sequencing of breast cancer metastasis mouse models. We analyzed metastases from models of various oncogenic drivers and routes, including orthotopic injection, tail vein injection, intracardiac injection, and genetically engineered mouse models (GEMMs). Herein, we analyzed samples from 176 mice and tissue culture samples, resulting in 338 samples total. Using these data, we contrasted the different breast cancer metastasis models, and also identified common, targetable metastasis specific gene expression signatures. Principal component analysis revealed that mouse model (Allograft v. GEMM) rather than tissue source (PT v metastatic nodule) shaped the transcriptomes of our samples. Allograft models exhibited more mesenchymal-like gene expression than GEMM models, and primary culturing of GEMM-derived metastatic tissue induced more mesenchymal-like gene expression. Furthermore, metastasis-specific gene expression differed between tail vein and orthotopic injection models of the same cell line, the degree of which was cell line dependent. Finally, we examined metastasis-specific gene expression common to models of spontaneous metastasis (orthotopic injection and GEMMs). Pathway analysis identified upregulation of the sildenafil response, and nicotine degradation pathways. The influence of these pathways on metastatic spread was assessed by treatment of allograft models with clinically relevant dosing of sildenafil or nicotine. Sildenafil significantly reduced pulmonary metastasis while nicotine administration significantly increased metastasis, and neither regimen altered primary tumor mass. Taken together our data reveals critical differences between pre-clinical models of metastatic breast cancer. Additionally, this strategy has identified clinically targetable metastasis-specific pathways integral to metastatic spread.

cancer biology↗

bioRxiv2019

Melanoblast transcriptome analysis reveals novel pathways promoting melanoma metastasis

Cutaneous malignant melanoma is an aggressive cancer of melanocytes with a strong propensity to metastasize. We posited that melanoma cells acquire metastatic capability by adopting an embryonic-like phenotype, and that a lineage approach would uncover novel metastatic melanoma biology. We used a genetically engineered mouse model to generate a rich melanoblast transcriptome dataset, identified melanoblast-specific genes whose expression contributed to metastatic competence, and derived a 43-gene signature that predicted patient survival. We identified a melanoblast gene, KDELR3, whose loss impaired experimental metastasis. In contrast, KDELR1 deficiency enhanced metastasis, providing the first example of different disease etiologies within the KDELR-family of retrograde transporters. We show that KDELR3 regulates the metastasis suppressor, KAI1, and report an interaction with the E3 ubiquitin-protein ligase gp78, a regulator of KAI1 degradation. Our work demonstrates that the melanoblast transcriptome can be mined to uncover novel targetable pathways for melanoma therapy.

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↗

bioRxiv2019

Aicardi-Goutieres Syndrome gene Rnaseh2c is a metastasis susceptibility gene in breast cancer

Breast cancer is the second leading cause of cancer-related deaths in the United States, with the majority of these deaths due to metastatic lesions rather than the primary tumor. Thus, a better understanding of the etiology of metastatic disease is crucial for improving survival. Using a haplotype mapping strategy in mouse and shRNA-mediated gene knockdown, we identified Rnaseh2c, a scaffolding protein of the heterotrimeric RNase H2 endoribonuclease complex, as a novel metastasis susceptibility factor. We found that the role of Rnaseh2c in metastatic disease is independent of RNase H2 enzymatic activity, and immunophenotyping and RNA-sequencing analysis revealed engagement of the T cell-mediated adaptive immune response. Furthermore, the cGAS-Sting pathway was not activated in the metastatic cancer cells used in this study, suggesting that the mechanism of immune response in breast cancer is different from the mechanism proposed for Aicardi-Goutieres Syndrome, a rare interferonopathy caused by RNase H2 mutation. These results suggest an important novel, non-enzymatic role for RNASEH2C during breast cancer progression and add Rnaseh2c to a panel of genes we have identified that together could determine patients with high risk for metastasis. These results also highlight a potential new target for combination with immunotherapies and may contribute to a better understanding of the etiology of Aicardi-Goutieres Syndrome autoimmunity. Author SummaryThe majority of breast cancer-associated deaths are due to metastatic disease, the process where cancerous cells leave the primary tumor in the breast and spread to a new location in the body. To better understand the etiology of this process, we investigate the effects of gene expression changes in the primary tumor. In this study, we found that changing the expression of the gene Rnaseh2c changed the number of metastases that developed in the lungs of tumor-bearing mice. By investigating the enzyme complex Rnaseh2c is part of, RNase H2, we determined that Rnaseh2cs effects may be independent of RNase H2 enzyme activity. Because Rnaseh2c is known to cause the autoimmune disease Aicardi-Goutieres Syndrome (AGS), we tested whether the immune system is involved in the metastatic effect. Indeed, we found that the cytotoxic T cell response is important for mediating the effect that Rnaseh2c has on metastasis. Together these data indicate that Rnaseh2c expression contributes to a patients susceptibility to developing breast cancer metastasis and demonstrate that the immune system is involved in this outcome. The implications of this study suggest immunotherapy could be a viable treatment for breast cancer metastasis and may help inform the understanding of AGS and RNase H2 in cancer.

cancer biology↗

bioRxiv2018

BAP1 deubiquitinase is a potent repressor of fetal hemoglobin biosynthesis

Human globin gene production transcriptionally \"switches\" from fetal to adult synthesis shortly after birth, and is controlled by macromolecular complexes that enhance or suppress transcription by cis-elements scattered throughout the locus. The DRED repressor is recruited to the {varepsilon}- and {gamma}-globin promoters by the orphan nuclear receptors TR2 (NR2C1) and TR4 (NR2C2) to engender their silencing in adult erythroid cells. Here we found that nuclear receptor corepressor-1 (NCoR1) is a critical component of DRED that acts as a scaffold to unite the DNA binding and epigenetic enzyme components (e.g. DNMT1 and LSD1) that elicit DRED function. We also describe a potent new regulator of {gamma}-globin repression: the deubiquitinase BAP1 is a component of the repressor complex whose activity maintains NCoR1 at sites in the {beta}-globin locus, and BAP1 inhibition in erythroid cells massively induces {gamma}-globin synthesis. These data provide new mechanistic insights through the discovery of novel epigenetic enzymes that mediate {gamma}-globin gene repression.

developmental biology↗