Biology subjects

Herlyn, M.

Publications and source records attributed to Herlyn, M..

At least 19 recordsLinked to original sources

bioRxiv2026

TFAP2A links drug resistance to antitumor immunity

Combination targeted therapy with BRAF/MEK inhibitors and immune therapy show promising therapeutic outcomes in melanoma; however, the development of drug resistance still represents a formidable challenge. Remaining unexplored is the possibility that BRAF/MEK inhibitors themselves inadvertently compromise the tumor immune microenvironment, limiting the efficacy of immunotherapy when it is used in combination with targeted inhibitors. Herein, we profiled the landscape of the BRAF regulatome identifying a novel transcription factor, TFAP2A, newly linking BRAF/MEK drug resistance to antitumor immunity. Specifically, we found that BRAF/MEK inhibitors significantly upregulate TFAP2A. Further, genetic disruption of TFAP2A overcomes BRAF/MEK-inhibitor resistance, promotes stromal enrichment, and enhances intratumoral infiltration of macrophages in an immune-compromised mouse model. In a syngeneic mouse model, TFAP2a knockout not only suppresses tumor growth but also induces potent anti-tumor tertiary lymphoid structures (TLSs). Single cell transcriptomics revealed that the absence of TFAP2A shapes the antitumor microenvironment with an influx of M1-like macrophages, CD8+ T cells and mature dendritic cells. By identifying TFAP2A as a shared driver of both targeted therapy resistance and immunosuppression, our work offers a one-stone-two-bird strategy to overcome drug resistance and elicit antitumor immunity.

cancer biology↗

bioRxiv2026

Single-cell lineage tracing maps clonal and transcriptional dynamics in melanoma metastasis

Melanoma metastasis is driven by extensive intratumoral heterogeneity and phenotypic plasticity, yet how clonal identity relates to transcriptional programs during metastasis remains unclear. Here, we applied MeRLin, a single-cell lineage tracing platform, to dissect the clonal and transcriptional heterogeneity of metastatic melanoma in a patient-derived spontaneous metastasis model. Clonal analyses revealed hierarchical structures during tumor progression, with a subset of lineages from primary tumors consistently enriched across metastatic sites, supporting a model of polyclonal seeding followed by selective expansion of pre-existing highly metastatic subpopulations. Single-cell transcriptomic profiling identified two major metastatic subpopulations of distinct transcriptional programs, characterized by neural crest stem cell-like and lipid metabolism signatures. Both programs were enriched for invasion-associated genes and maintained across organs through distinct regulatory networks. Spatial mapping by barcode RNA-FISH linked these transcriptional states to their tissue context and showed that OLFML3 expression partially co-localized with a dominant subpopulation at the tumor-liver interface, marking the invasive fronts of metastatic growth. Together, these findings establish a framework in which clonal identity, transcriptional state, and spatial organization jointly shape metastatic melanoma progression.

cancer biology↗

bioRxiv2026

MYC-ATF4-ASS1 axis governs intracellular arginine synthesis and dictates the immune microenvironment in melanoma

Drug resistance is a major challenge for both targeted therapies and immunotherapies in cancer. Arginine starvation has proven a promising strategy to overcome recurrent tumors. However, key molecules involved and how immune responses are elicited are not well understood. Here we identify in melanoma cells MYC-ATF4-ASS1 signaling as a pathway, which not only governs intracellular arginine synthesis but also modulates antitumor immunity. ATF4 knockout in melanoma cells phenocopied ASS1 knockout in the same cells, both showing greater sensitivity to arginine depletors such as ADI-PEG20. A combination strategy of BRAF/MEK inhibitors and an arginine depletor shows significant therapeutic effects in a immune-compromised mouse model. Both Atf4 and Ass1 knockout melanomas exhibited enhanced infiltration of Cd8+ T cells and significantly reduced tumor growth in a syngeneic mouse model. Single cell transcriptomics profiled the reshaped tumor microenvironment and revealed that a subset of resident macrophages were reprogrammed by endogenous arginine blockade. Overall, our findings reveal that the MYC-ATF4-ASS1 axis not only controls arginine vulnerability of melanomas but also shapes the immune microenvironment.

cancer biology↗

bioRxiv2025

Clonal dynamics shaped by diverse drug-tolerant persister states in melanoma resistance

Most advanced melanomas initially respond to targeted therapy but eventually relapse. Rather than acquiring new mutations, resistance is driven by drug-tolerant persister cells that enter a reversible drug-refractory state. We developed MeRLin, a high-resolution lineage tracing platform integrating cellular barcoding, single-cell transcriptomics, RNA fluorescence in situ hybridization (FISH), and computational analyses to track clonal and transcriptional dynamics in patient-derived melanoma models during prolonged therapy. Clonal dynamics revealed that persister subpopulations first responded to treatment but persisted and expanded during minimal residual disease, ultimately leading to tumor recurrence. Pre-treatment melanoma populations diversified into four conserved persister states characterized by stress-like, lipid metabolism, PI3K signaling, and extracellular matrix remodeling programs associated with adaptive resistance. Spatial transcriptomics showed the organization of these adaptive programs and a complex signaling network of autocrine and paracrine interactions among persister subpopulations. Barcoded RNA-FISH enabled spatial mapping of clonal identity and gene expression, revealing in situ co-localization of a dominant resistant clone with SLC2A1 expression. MeRLin provides a robust framework for dissecting cancer heterogeneity and identifying vulnerabilities in persister populations.

cancer biology↗

bioRxiv2025

DR5 CAR-T cells target solid tumors and suppress MDSCs with minimal toxicity

Chimeric antigen receptor (CAR) T cell therapies have poor efficacy in solid tumors due to limited target specificity and an immunosuppressive tumor microenvironment. We investigated death receptor 5 (DR5) as a CAR target based on its high expression in both solid tumors and myeloid- derived suppressor cells (MDSCs). We engineered agonistic DR5-specific CAR constructs and evaluated their activity in multiple models, demonstrating DR5-expression-dependent tumor killing, confirmed by knockout and overexpression experiments. DR5-targeting single-chain variable fragments retained their pro-apoptotic activity when expressed on non-effector cells or extracellular vesicles. Among multiple CAR designs, we identified a construct with optimized binding affinity that maintained T cell viability while preserving strong tumor and MDSC-killing potency. To assess safety and efficacy in an immunocompetent setting, we also developed a murine DR5-targeted CAR. In multiple xenograft and syngeneic mouse models, DR5 CAR-T cells reduced tumor growth, prolonged survival, and did not cause detectable toxicity. In patient- derived organoids and tissue slices, DR5 CAR-T cells infiltrated tumor tissues, reduced MDSCs, boosted CD8+ T cell activity, and inhibited tumor growth. These findings support DR5-targeted CAR-T therapy as a promising strategy for treating solid tumors, which combines direct tumor cytotoxicity with immune activation and minimizes off-target effects. TeaserDR5 CAR-T cells eliminate tumor cells and MDSCs and activate tumor-resident CD8+ T cells within the TME.

cancer biology↗

bioRxiv2025

Heterogeneous therapy-resistant cancer cells have distinct and exploitable drug sensitivity profiles

Resistance to targeted therapies is a significant clinical problem, but eliminating resistant cancer cells has proven difficult. One potential reason for this difficulty is heterogeneity in the resistant population: even genetically homogeneous cancer cell populations can give rise to many resistant subtypes, each potentially with specific second-line drug vulnerabilities. Using high-throughput drug screening of genetically-identical resistant clones with varying transcriptomes and morphologies, we show that each clone had a distinct drug sensitivity profile. These results suggested that there are drugs that are effective against only subsets of resistant populations but in combination eliminate a large proportion of the resistant population. Using the individual clone sensitivity profiles, we prospectively identified combinations that were highly effective at eliminating most of the resistant population. Our results demonstrate the effectiveness of "subpopulation-directed synergy", showing that considering population heterogeneity can reveal therapeutic opportunities otherwise masked by population averages, offering new strategies to combat therapy resistance.

systems biology↗

bioRxiv2025

SpaceBar enables clone tracing in spatial transcriptomic data

We report a cellular barcoding strategy, SpaceBar, that enables simultaneous clone tracing and spatial transcriptomics profiling. Our approach uses a library of 96 synthetic barcode sequences that can be robustly detected by imaging based spatial transcriptomics (seqFISH), delivered such that each cell is labeled with a combination of barcodes. We used these barcodes to label melanoma cells in a tumor xenograft model and profiled both clone identity and spatial gene expression in situ. We developed a gene scoring metric that quantifies how strongly gene expression is driven by intrinsic cellular cues or extrinsic environmental signals. Our framework distinguishes between clonal dynamics and environmentally-driven transcriptional regulation in complex tissue contexts.

genomics↗

bioRxiv2024

A Comprehensive Proteogenomic and Spatial Analysis of Innate and Acquired Resistance of Metastatic Melanoma to Immune Checkpoint Blockade Therapies

While a subset of patients with metastatic melanoma achieves durable responses to immune checkpoint blockade (ICB) therapies, the majority ultimately exhibit either innate or acquired resistance to these treatments. However, the molecular mechanisms underlying resistance to ICB therapies remain elusive and are warranted to elucidate. Here, we comprehensively investigated the tumor and tumor immune microenvironment (TIME) of paired pre- and post-treatment tumor specimens from metastatic melanoma patients who were primary or secondary resistance to anti-CTLA-4 and/or anti-PD-1/PD-L1 therapies. Differentially expressed gene (DEG) analysis and single-sample gene set enrichment analysis (ssGSEA) with transcriptomic data identified cell cycle and c-MYC signaling as pathway-based resistance signatures. And weighted gene co-expression network analysis (WGCNA) revealed the activation of a cross-resistance meta-program involving key signaling pathways related to tumor progression in ICB resistant melanoma. Moreover, spatially-resolved, image-based immune monitoring analysis by using NanoStrings digital spatial profiling (DSP) and Cyclic Immunofluorescence (CyCIF) showed infiltration of suppressive immune cells in the tumor microenvironment of melanoma with resistance to ICB therapies. Our study reveals the molecular mechanisms underlying resistance to ICB therapies in patients with metastatic melanoma by conducting such integrated analyses of multi-dimensional data, and provides rationale for salvage therapies that will potentially overcome resistance to ICB therapies. Statement of translational relevanceThis study paves the way for the creation of innovative therapeutic strategies, aimed at subverting resistance to immune checkpoint blockade (ICB) therapies in metastatic melanoma patients. By unraveling the specific molecular mechanisms underlying resistance, scientists can design effective alternative treatments that target pathways such as pathways associated with cell cycle dysregulation and c-MYC signaling. Furthermore, through the application of advanced immune monitoring techniques such as NanoString Digital Spatial Profiling (DSP) and Cyclic Immunofluorescence (CyCIF), this study has significantly enriched our understanding of the tumor microenvironment. This enhanced characterization facilitates the discovery of potential biomarkers that may forecast a patients response to ICB treatment. Ultimately, these advancements could potentially refine patient outcomes and foster the development of more personalized cancer treatments in the future.

genetics↗

bioRxiv2024

AP-1 Mediates Cellular Adaptation and Memory Formation During Therapy Resistance

Cellular responses to environmental stimuli are typically thought to be governed by genetically encoded programs. We demonstrate that melanoma cells can form and maintain cellular memories during the acquisition of therapy resistance that exhibit characteristics of cellular learning and are dependent on the transcription factor AP-1. We show that cells exposed to a low dose of therapy adapt to become resistant to a high dose, demonstrating that resistance was not purely selective. The application of therapy itself results in the encoding of transient gene expression into cellular memory and that this encoding occurs for both transiently induced and probabilistically arising expression. Chromatin accessibility showed concomitant persistence. A two-color AP-1 reporter system showed that these memories are encoded in cis, constituting an example of activating cis epigenetics. Our findings establish the formation and maintenance of cellular memories as a critical aspect of gene regulation during the development of therapy resistance.

systems biology↗

bioRxiv2024

Spatiotemporal profiling defines persistence and resistance dynamics during targeted treatment of melanoma

Resistance of BRAF-mutant melanomas to targeted therapy arises from the ability of cells to enter a persister state, evade treatment with relative dormancy, and repopulate the tumor when reactivated. Using spatial transcriptomics in patient derived xenograft models, we capture clonal lineage evolution during treatment, finding the persister state to show increased oxidative phosphorylation, decreased proliferation, and increased invasive capacity, with central-to-peripheral gradients. Phylogenetic tracing identifies intrinsic- and acquired-resistance mechanisms (e.g. dual specific phosphatases, Reticulon-4, CDK2) and suggests specific temporal windows of potential therapeutic efficacy. Using deep learning to analyze histopathological slides, we find morphological features of specific cell states, demonstrating that juxtaposition of transcriptomics and histology data enables identification of phenotypically-distinct populations using imaging data alone. In summary, we define state change and lineage selection during melanoma treatment with spatiotemporal resolution, elucidating how choice and timing of therapeutic agents will impact the ability to eradicate resistant clones. Statement of SignificanceTumor evolution is accelerated by application of anti-cancer therapy, resulting in clonal expansions leading to dormancy and subsequently resistance, but the dynamics of this process are incompletely understood. Tracking clonal progression during treatment, we identify conserved, global transcriptional changes and local clone-clone and spatial patterns underlying the emergence of resistance.

cancer biology↗

bioRxiv2023

Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples

HighlightsWe have developed an automated data processing pipeline to quantify mouse and human data from patient-derived xenograft samples assayed by Visium spatial transcriptomics with matched hematoxylin and eosin (H&E) stained image. We enable deconvolution of reads with Xenome, quantification of spatial gene expression from host and graft species with Space Ranger, extraction of B-allele frequencies, and splicing quantification with Velocyto. In the H&E image processing sub-workflow, we generate morphometric and deep learning-derived feature quantifications complementary to the Visium spots, enabling multi-modal H&E/expression comparisons. We have wrapped the pipeline into Nextflow DSL2 in a scalable, portable, and easy-to-use framework. SummaryWe designed a Nextflow DSL2-based pipeline, Spatial Transcriptomics Quantification (STQ), for simultaneous processing of 10x Genomics Visium spatial transcriptomics data and a matched hematoxylin and eosin (H&E)-stained whole slide image (WSI), optimized for Patient-Derived Xenograft (PDX) cancer specimens. Our pipeline enables the classification of sequenced transcripts for deconvolving the mouse and human species and mapping the transcripts to reference transcriptomes. We align the H&E WSI with the spatial layout of the Visium slide and generate imaging and quantitative morphology features for each Visium spot. The pipeline design enables multiple analysis workflows, including single or dual reference genomes input and stand-alone image analysis. We showed the utility of our pipeline on a dataset from Visium profiling of four melanoma PDX samples. The clustering of Visium spots and clustering of imaging features of H&E data reveal similar patterns arising from the two data modalities.

bioinformatics↗

bioRxiv2023

Dasatinib Resensitizes MAPK Inhibitor Efficacy in Standard-of-Care Relapsed Melanomas

Resistance to combination BRAF/MEK inhibitor (BRAFi/MEKi) therapy arises in nearly every patient with BRAFV600E/K melanoma, despite promising initial responses. Achieving cures in this expanding BRAFi/MEKi-resistant cohort represents one of the greatest challenges to the field; few experience additional durable benefit from immunotherapy and no alternative therapies exist. To better personalize therapy in cancer patients to address therapy relapse, umbrella trials have been initiated whereby genomic sequencing of a panel of potentially actionable targets guide therapy selection for patients; however, the superior efficacy of such approaches remains to be seen. We here test the robustness of the umbrella trial rationale by analyzing relationships between genomic status of a gene and the downstream consequences at the protein level of related pathway, which find poor relationships between mutations, copy number amplification, and protein level. To profile candidate therapeutic strategies that may offer clinical benefit in the context of acquired BRAFi/MEKi resistance, we established a repository of patient-derived xenograft models from heavily pretreated patients with resistance to BRAFi/MEKi and/or immunotherapy (R-PDX). With these R-PDXs, we executed in vivo compound repurposing screens using 11 FDA-approved agents from an NCI-portfolio with pan-RTK, non-RTK and/or PI3K-mTOR specificity. We identify dasatinib as capable of restoring BRAFi/MEKi antitumor efficacy in [~]70% of R-PDX tested. A systems-biology analysis indicates elevated baseline protein expression of canonical drivers of therapy resistance (e.g., AXL, YAP, HSP70, phospho-AKT) as predictive of MAPKi/dasatinib sensitivity. We therefore propose that dasatinib-based MAPKi therapy may restore antitumor efficacy in patients that have relapsed to standard-of-care therapy by broadly targeting proteins critical in melanoma therapy escape. Further, we submit that this experimental PDX paradigm could potentially improve preclinical evaluation of therapeutic modalities and augment our ability to identify biomarker-defined patient subsets that may respond to a given clinical trial. SINGLE SENTENCE SUMMARYBroad target inhibition effective as a salvage strategy in BRAF/MEK inhibitor-acquired resistance PDX

cancer biology↗

bioRxiv2022

Metastatic potential in clonal melanoma cells is driven by a rare, early-invading subpopulation

Metastasis occurs when tumor cells leave the primary tumor site and disseminate to distal organs. Even though most cells remain in the primary tumor, the circumstances by which a small fraction of them disseminate remain unclear. Here, we show that a rare, highly invasive subpopulation of melanoma cells can be detected within clonal cell lines due to non-genetic fluctuations in gene expression. The highly invasive phenotype was intrinsic to the cells, independent of their environment, and was marked by transiently high levels of SEMA3C expression, as revealed by RNA-sequencing analysis. Furthermore, the invasive subpopulation drove the bulk dissemination of tumor cells to distal locations in a mouse model of melanoma. The transcription factor NKX2.2 regulated the proportion of invasive cells in the melanoma 1205Lu cell line. Furthermore, an overall tradeoff between proliferation and invasion in single cells was observed. Our results suggest that phenotypes like metastasis may arise from intrinsic differences stemming from non-genetic fluctuations between single cells.

cancer biology↗

bioRxiv2022

clampFISH 2.0 enables rapid, scalable amplified RNA detection in situ

RNA labeling in situ has enormous potential to visualize transcripts and quantify their levels in single cells, but it remains challenging to produce high levels of signal while also enabling multiplexed detection of multiple RNA species simultaneously. Here, we describe clampFISH 2.0, a method that uses an inverted padlock design to efficiently detect and exponentially amplify signals from many RNA species at once, while also reducing time and cost compared to the prior clampFISH method. We leverage the increased throughput afforded by multiplexed signal amplification and sequential detection by demonstrating the ability to detect 10 different RNA species in over 1 million cells. We also show that clampFISH 2.0 works in tissue sections. We expect the advantages offered by clampFISH 2.0 will enable many applications in spatial transcriptomics.

bioengineering↗

bioRxiv2021

Pre-determined diversity in resistant fates emerges from homogenous cells after anti-cancer drug treatment

Even amongst genetically identical cancer cells, therapy resistance often only emerges from a very small subset of those cells. Much effort has gone into uncovering the molecular differences in rare individual cells in the initial population that may allow certain cells to become therapy resistant; however, comparatively little is known about variability in the resistant outcomes themselves. Here, we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically, and functionally distinct fate types. These different resistant types are largely predetermined by molecular differences between cells before addition of drug and not by extrinsic cell-specific microenvironmental factors. Changes in dose and kind of drug can, however, switch the resistant fate type of an initial cell, even resulting in the generation and elimination of certain fate types. Diversity in resistant fates was observed across several single-cell-derived cancer cell lines and types treated with a variety of drugs. Cell fate diversity as a result of variability in intrinsic cell states may be a generic feature of response to external cues.

systems biology↗

bioRxiv2021

PDXNet Portal: Patient-Derived Xenograft model, data, workflow, and tool discovery

We created the PDX Network (PDXNet) Portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources (i.e., PDX models, sequencing data, treatment response data, and bioinformatics workflows), to facilitate collaboration among researchers, and to make resources easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols, and training materials for processing PDX data. The initial portal release highlights PDXNet model and data resources, including 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCIs Patient-Derived Model Repository (PDMR) for public access. These models have 2,822 associated sequencing files from 873 samples across 307 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal also includes results from standardized analysis workflows on PDXNet sequencing files and PDMR data (2,594 samples from 463 patients across 78 disease types). These 15 analysis workflows for whole-exome and RNA-Seq data are freely available, robust, validated, and standardized. The model and data lists will grow substantially over the next two years and will be continuously updated as new data are available. PDXNet models support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials. The PDXNet portal is a centralized location for these data and resources, which we expect to be of significant utility for the cancer research community.

cancer biology↗

bioRxiv2020

Large-scale Characterization of Drug Responses of Clinically Relevant Proteins in Cancer Cell Lines

Perturbation biology is a powerful approach to developing quantitative models of cellular behaviors and gaining mechanistic insights into disease development. In recent years, large-scale resources for phenotypic and mRNA responses of cancer cell lines to perturbations have been generated. However, similar large-scale protein response resources are not available, resulting in a critical knowledge gap for elucidating oncogenic mechanisms and developing effective cancer therapies. Here we generated and compiled perturbed expression profiles of ~210 clinically relevant proteins in >12,000 cancer cell-line samples in response to >150 drug compounds using reverse-phase protein arrays. We show that integrating protein response signals substantially increases the predictive power for drug sensitivity and aids in gaining insights into mechanisms of drug resistance. We build a systematic map of protein-drug connectivity and develop an open-access, user-friendly data portal for community use. Our study provides a valuable information resource for a broad range of quantitative modeling and biomedical applications. HighlightsO_LIA large collection of cancer cell line protein responses to drug perturbations C_LIO_LIPerturbed protein responses greatly increase predictive power for drug sensitivity C_LIO_LIBuild a systematic map of protein-drug connectivity based on response profiles C_LIO_LIDevelop a user-friendly, interactive data portal for community use C_LI

systems biology↗

bioRxiv2020

The Janus-faced role of KDM5B heterogeneity in melanoma: differentiation as a situational driver of both growth arrest and drug-resistance

Melanoma is a highly plastic tumor characterized by dynamic interconversion of different cell identities depending on the biological context. For example, melanoma cells with high expression of the H3K4 demethylase KDM5B (JARID1B) rest in a slow-cycling, yet reversible persister state. Over time, KDM5Bhigh cells can promote rapid tumor repopulation with equilibrated KDM5B expression heterogeneity. The cellular identity of KDM5Bhigh persister cells has not been studied so far, missing an important cell state-directed treatment opportunity in melanoma. Here, we have established a doxycycline-titratable system for genetic induction of permanent intratumor expression of KDM5B and screened for chemical agents that phenocopy this effect. Transcriptional profiling and cell functional assays confirmed that the dihydropyridine phenoxyethyl 4-(2-fluorophenyl)-2,7,7-trimethyl-5-oxo-1,4,5,6,7,8-hexa-hydro-quinoline-3-carboxylate (termed Cpd1) supports high KDM5B expression and directs melanoma cells towards differentiation along the melanocytic lineage and to cell cycle-arrest. The high KDM5B state additionally prevents cell proliferation through negative regulation of cytokinetic abscission. Moreover, treatment with Cpd1 promoted the expression of the melanocyte-specific tyrosinase gene specifically sensitizing melanoma cells for the tyrosinase-processed antifolate prodrug 3-O-(3,4,5-trimethoxybenzoyl)-(-)-epicatechin (TMECG). In summary, our study provides proof-of-concept for a new dual hit strategy in melanoma, in which persister state-directed transitioning limits tumor growth and plasticity and primes melanoma cells towards lineage-specific elimination.

cancer biology↗