NYU ABL Publications Dashboard 2016

Highlighted Work

Selected publications showcasing ABL collaborative research impact

Nature · 2026 PMID: 41708864 Papagiannakopoulos lab

The Integrated Stress Response Promotes Immune Evasion Through Lipocalin 2

Bossowski et al. · The integrated stress response promotes immune evasion through lipocalin 2. Nature 2026

⚠️The Problem

The ISR–ATF4 axis is known to aid tumor survival, but its role in modulating anti-tumor immunity was largely unknown.
Many cancers fail to respond to immunotherapy due to poorly understood immune evasion mechanisms.

🔍Why It Matters

Identifying immune evasion pathways is critical to improve immunotherapy response rates.
LCN2 could represent a new and targetable node in the ISR-immune crosstalk.

💡Key Results

The ISR–ATF4 axis promotes immune evasion by upregulating LCN2.
LCN2 drives accumulation of immunosuppressive interstitial macrophages and Tregs.
LCN2 levels correlate with patient survival and T cell infiltration in tumors.

Figure Highlights

Yuan
Hao

Nature

Nature Portfolio

PubMed ID

41708864

Lab

Papag. lab

Cell · 2026 PMID: 41702399 Simeone lab (w/ Kimmelman lab)

Heterogeneity of Autophagic Flux in Pancreatic Ductal Adenocarcinoma

Assi et al. · Extracellular matrix sensing regulates intratumoral heterogeneity of autophagic flux

⚠️The Problem

Cancer cells can modulate their level of autophagic flux depending on their microenvironment
Growth and progression of PDA are highly dependent on autophagy regulation

🔍Why It Matters

PDA heterogeneity — enabled by adaptation to environmental cues — is a key factor in stress survival
Uncovering autophagy regulatory pathways may reveal new therapeutic targets

💡Key Results

PDA cells with a disrupted Hippo-YAP1 axis lose autophagic flux & heterogeneity
YAP1 and autophagy signatures are inversely proportional in PDA patients
High-YAP/low-autophagy PDA populations show higher proliferative potential

Figure Highlights

Emily
Kawaler

Cell

A Cell Press journal

PubMed ID

41702399

Lab

Simeone lab

Science · 2025 PMID: 41678619 Reizis lab

Sc-MultiOme (snRNA+ATAC) Analysis of Migratory DCs in Autoimmunity

Adams et al. · Transcription factor Etv3 controls the tolerogenic function of dendritic cells

⚠️The Problem

What molecular program allows steady-state migDCs to maintain peripheral immune tolerance instead of provoking T cell activation?
ETV3 may be critical for this tolerogenic function but its mechanisms were unknown.

🔍Why It Matters

Dendritic cells sit at the boundary between tolerance and immunity — disruption tips the balance toward autoimmunity.
ETV3 disruption may be clinically relevant in human autoimmunity, particularly SLE.

💡Key Results

Etv3 is preferentially expressed in mature migDCs and required for homeostatic maturation and CCR7-dependent migration.
Etv3-deficient migDCs up-regulate costimulatory molecules, especially OX40L/TNFSF4.
Loss of Etv3 worsens TLR7-driven SLE-like disease.

Figure Highlights

Eduardo
Esteva

Science

AAAS Journal

PubMed ID

41678619

Lab

Reizis lab

Nature Medicine · 2018 PMID: 30224757 Razavian & Tsirigos labs

Deep Learning for Lung Cancer Subtyping and Mutation Prediction from Histopathology

Coudray et al. · Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning

⚠️The Problem

Distinguishing LUAD vs. LUSC on whole-slide histopathology is difficult, time-consuming, and sometimes ambiguous for pathologists.
Determining mutation status usually requires additional molecular tests, adding cost, time, and tissue.

🔍Why It Matters

LUAD and LUSC have different treatment guidelines and targeted therapy options — misclassification directly impacts patient care.
Rapid, accurate subtype and mutation assessment is critical for precision oncology.

💡Key Results

A deep CNN trained on lung histopathology tiles classifies normal, LUAD, and LUSC with high accuracy.
Key LUAD gene mutations (EGFR, STK11, KRAS, TP53) are predicted directly from H&E images.
Models are validated on independent biopsy cohorts.

Figure Highlights

Nicolas
Coudray

Nature Medicine

Nature Portfolio

PubMed ID

30224757

Lab

Tsirigos lab

Nature · 2026 PMID: 41535459 Littman lab

Microbiota-Induced T Cell Plasticity Enables Immune-Mediated Tumour Control

Najar et al. · Microbiota-induced T cell plasticity enables immune-mediated tumour control. Nature 2026

⚠️The Problem

The gut microbiota is known to influence response to immune checkpoint blockade, but the underlying mechanisms remain poorly defined.
There is no clear causal pathway linking gut microbes to immune-mediated control of distal tumors.

🔍Why It Matters

Understanding this mechanism could explain variable patient responses to checkpoint immunotherapy.
Microbiome engineering offers a non-invasive opportunity to develop novel microbiota-based immunotherapies.

💡Key Results

SFB colonization enables effective anti-PD-1-mediated tumor suppression in mice.
Gut TH17 cells migrate to distal tumors and reprogram into TH1-like effector cells.
TH1-like cells promote cytotoxic T cell infiltration and enhance anti-PD-1 immunotherapy.

Figure Highlights

Yuan
Hao

Nature

Nature Portfolio

PubMed ID

41535459

Lab

Littman lab

Cancer Cell · 2022 PMID: 35660135 Bar-Sagi lab

KNetL Map: An Adjustable Dimensionality Reduction Tool

Kurz et al. · Exercise-induced engagement of the IL-15/IL-15Rα axis promotes anti-tumor immunity in pancreatic cancer

⚠️The Problem

Standard tools (tSNE, UMAP) fail to clearly separate closely related cell communities
Changing clustering resolution alters cluster count but not the visual representation

🔍Why It Matters

Subtle differences between cell sub-populations remain hidden, complicating downstream analyses
Communities with similar trajectories cluster too closely, obscuring distinct sub-populations

💡Key Results

Build a K-nearest-neighbor graph and apply force-directed graph drawing
Organize cells into a force-compacted network layout
Extract node coordinates and "unpack" into a KNetL map

Figure Highlights

Alireza
Khodadadi-Jamayran

Cancer Cell

A Cell Press journal

PubMed ID

35660135

Lab

Bar-Sagi lab

Nat Med · 2025 PMID: 40473950 Kirchhoff lab

Inherited Mitochondrial Genetics as a Predictor of Immune Checkpoint Inhibition Efficacy in Melanoma

Monson et al. · Inherited mitochondrial genetics as a predictor of immune checkpoint inhibition efficacy in melanoma. Nat Med 31, 2385–2396 (2025)

⚠️The Problem

Existing tumor-based biomarkers are insufficient to predict which melanoma patients will respond to immune checkpoint inhibitors (ICIs).
The role of mitochondrial genetics in shaping peripheral T cell differentiation and ICI responsiveness is unclear.

🔍Why It Matters

Without reliable pretreatment biomarkers, clinicians cannot rationally select between ICI regimens.
If MT-HGs drive differential ROS tolerance and T cell differentiation states, this reveals a new biological axis connecting germline mitochondrial genetics to antitumor immunity.

💡Key Results

Mitochondrial haplogroup T (HG-T) is robustly and independently associated with resistance to nivolumab (anti-PD-1).
HG-T patients show a distinct baseline peripheral CD8+ T cell phenotype which upregulates ROS detoxification pathways.
This establishes a mechanistic link between mitochondrial genetics and impaired T cell effector differentiation.

Figure Highlights

Chaitra
Sreenivasaiah

Nature Medicine

Nature Portfolio

PubMed ID

40473950

Lab

Kirchhoff lab

Molecular Cell · 2025 PMID: 39719705 Aifantis / Tsirigos lab

Integrative Analysis of 3D Chromatin Organization and Accessibility in Acute Leukemia

Gambi, Boccalatte, Rodriguez Hernaez, Lin et al. · 3D chromatin hubs as regulatory units of identity and survival in human acute leukemia

⚠️The Problem

3D chromatin organization plays a key role in regulating gene expression in leukemia, but its functional interpretation remains incompletely understood.
The role of chromatin hubs in linking regulatory elements to target gene expression is not fully defined.

🔍Why It Matters

Understanding 3D chromatin organization is critical for defining gene regulatory programs controlling leukemia cell identity and survival.
Integrating chromatin accessibility enables functional interpretation of regulatory elements within 3D chromatin structures.

💡Key Results

Integrated 3D chromatin interaction and accessibility data to map regulatory hubs in acute leukemia.
Characterized chromatin accessibility landscapes using scATAC-seq across leukemia subtypes.
Identified regulatory elements controlling leukemia cell identity and survival.

Figure Highlights

Ziyan
Lin

Molecular Cell

Cell Press

PubMed ID

39719705

Lab

Aifantis / Tsirigos

Circulation · 2023 PMID: 37772400 Park lab

Integrative Multi-Omics Analysis of Gene Regulatory Programs in Cardiac Outflow Tract Development

Yamaguchi, Chang, Lin et al. · An anterior second heart field enhancer regulates the gene regulatory network of the cardiac outflow tract

⚠️The Problem

Regulatory mechanisms controlling cardiac outflow tract development remain incompletely understood.
Integration of transcriptional and chromatin data is required to define gene regulatory programs in this context.

🔍Why It Matters

Understanding gene regulatory networks is critical for elucidating mechanisms of congenital heart defects.
Multi-omics integration enables comprehensive characterization of developmental programs.

💡Key Results

Integrated RNA-seq, ATAC-seq, ChIP-seq, and scRNA-seq to define cardiac outflow tract regulatory programs.
Characterized gene regulatory programs underlying cardiac outflow tract development.
Identified key regulatory elements and transcriptional networks in cardiac development.

Figure Highlights

Ziyan
Lin

Circulation

AHA Journal

PubMed ID

37772400

Lab

Park lab

Nature · 2021 PMID: 33658712 Schwab lab

Monocyte-Derived S1P in the Lymph Node Regulates Immune Responses

Baeyens, Bracero, Chaluvadi, Khodadadi-Jamayran et al. · Nature 592, 290–295 (2021)

⚠️The Problem

How S1P is regulated in lymph nodes during immune responses is not well understood.
The source of increased S1P in inflamed lymph nodes was unclear.

🔍Why It Matters

S1P controls immune cell movement and can shape the strength of immune responses.
Understanding this pathway may help explain and treat inflammatory and autoimmune disease.

💡Key Results

S1P levels rise in lymph nodes during immune responses, with inflammatory monocytes serving as a key source.
CD69 helps monocytes maintain this S1P signal, which prolongs T cell retention and worsens autoimmune inflammation in mice.

Figure Highlights

Alireza
Khodadadi-
Jamayran

Nature

Nature Portfolio

PubMed ID

33658712

Lab

Schwab lab

Cancer Discovery · 2022 PMID: 34911733 Neel lab

Ontogeny and Vulnerabilities of Drug-Tolerant Persisters in HER2+ Breast Cancer

Chang, Jen, Jiang, Sayad, Khodadadi-Jamayran, Neel et al. · Cancer Discov 12, 1022–1045 (2022)

⚠️The Problem

Resistance to HER2-targeted therapy remains a major challenge in HER2+ breast cancer.
Drug-tolerant persister (DTP) cells can survive treatment through reversible, non-genetic mechanisms, but their origins in HER2+ breast cancer were not well defined.

🔍Why It Matters

DTPs can seed relapse and contribute to long-term therapeutic resistance.
Understanding how these cells arise and survive may reveal vulnerabilities that improve responses to HER2 inhibitors.

💡Key Results

HER2 TKIs induce two DTP states — luminal-like or mesenchymal-like — with distinct transcriptional programs.
Single-cell and lineage-tracing analyses identified a stochastic "pre-DTP" state that preferentially gives rise to DTPs after treatment.
Luminal-like DTPs depend on ER–SGK3 signaling, revealing a therapeutic vulnerability via AKT-independent mTORC1 activation.

Figure Highlights

Alireza
Khodadadi-
Jamayran

Cancer Discovery

AACR Journal

PubMed ID

34911733

Lab

Neel lab

Molecular Cell · 2019 PMID: 31522988 Reinberg / Skok labs

RNA Interactions Are Essential for CTCF-Mediated Genome Organization

Saldaña-Meyer, Rodriguez-Hernaez, Escobar et al. · Mol Cell 76, 412–422 (2019)

⚠️The Problem

While CTCF is known to organize the 3D genome into loops and domains, the mechanisms stabilizing these dynamic structures are not fully understood.
The loop extrusion model fails to account for how CTCF self-associates to maintain stable insulation at chromatin boundaries.

🔍Why It Matters

CTCF is essential for life — homozygous deletion is embryonic lethal and its disruption is a hallmark of cancer.
Identifying non-DNA-binding requirements for CTCF activity is vital to understanding how cells maintain identity and regulate tumor suppressor genes.

💡Key Results

Identified specific RNA-binding regions (RBRs) in CTCF (ZF1 and ZF10) and generated mutants deficient only in RNA interaction.
Combined PAR-CLIP, scRNA-seq, and Hi-C to demonstrate that RNA molecules act as structural cross-linkers for CTCF–CTCF loop formation.

Figure Highlights

Javier
Rodriguez-
Hernaez

Molecular Cell

Cell Press

PubMed ID

31522988

Lab

Reinberg / Skok

Molecular Cell · 2025 PMID: 39719705 Tsirigos / Aifantis labs

3D Chromatin Hubs as Regulatory Units of Identity and Survival in Human Acute Leukemia

Gambi, Boccalatte, Rodriguez Hernaez, Lin et al. · Mol Cell 85, 42–60 (2025)

⚠️The Problem

Genetic studies alone have failed to define robust risk stratification or effective targeted therapies for pediatric T-ALL and ETP-ALL.
Current induction regimens often fail to eradicate primitive leukemic subpopulations, leading to a 20% relapse rate with poor prognosis.

🔍Why It Matters

3D chromatin organization acts as a non-genetic regulatory layer that stabilizes oncogenic programs and reflects tumor heterogeneity.
Identifying the "regulatory headquarters" of these programs is essential to predict disease risk and discover novel therapeutic vulnerabilities.

💡Key Results

Combined H3K27ac HiChIP, RNA-seq, and scATAC-seq to define genome-wide 3D hubs and super-hubs (SHs) in acute leukemia.
Used CRISPRi screening and in-silico perturbation to identify essential hubs (e.g., MYB, KRR1) coordinating leukemia identity and survival.

Figure Highlights

Javier
Rodriguez-
Hernaez

Molecular Cell

Cell Press

PubMed ID

39719705

Lab

Tsirigos / Aifantis

Clin Cancer Res · 2023 PMID: 37449980 Morgan lab

Uncovering Clinical Implications of Different 1q Gain Genotypes in Multiple Myeloma

Boyle, Blaney, Stoeckle et al. · Multiomic mapping of acquired chromosome 1 copy-number and structural variants to identify therapeutic vulnerabilities in multiple myeloma. Clin Cancer Res 29, 3901–3913 (2023)

⚠️The Problem

Myeloma frequently acquires chromosome 1q copy number gains, but clinical consequences are heterogeneous.
Lack of resolution on specific 1q+ genotypes and their link to clinical phenotype limits precise risk stratification and understanding of disease progression.

🔍Why It Matters

Chromosome 1q alterations drive aggressive myeloma — understanding the underlying genomics could improve prognosis and treatment selection.
Identifying specific genotypes may provide biomarkers of aggressive clinical behavior.

💡Key Results

Whole-arm 1q copy number gains are associated with significantly worse clinical outcomes.
Copy number gain events target super-enhancers with accessible chromatin.
Simultaneous dysregulation of multiple driver genes including MCL1, SLAMF7, and POU2F1.

Figure Highlights

Patrick
Blaney

Clin Cancer Res

AACR Journal

PubMed ID

37449980

Lab

Morgan lab

✚

More highlighted works coming soon — submit a slide to have your paper featured here

ABL Repository Initiative

Centralizing curated datasets, analysis outputs, and metadata from ABL collaborations to support reproducibility, reuse, and discovery

Curate

Standardized metadata & QC records

Preserve

Local ABL repository & linked archives

Controlled access for collaborators

Reuse

Secondary analysis & grant support

Overview

The ABL Repository Initiative expands NYU Langone’s local ABL data repository into a structured resource for high-throughput genomic, multi-omic, imaging, and clinical datasets processed through the Applied Bioinformatics Laboratories. Working closely with the Genome Technology Center (GTC), investigator laboratories, and DART teams, ABL curates project data so results remain findable, well-documented, and reusable across the research lifecycle.

The initiative supports every stage of collaborative research — from experimental design and QC through analysis, publication, and secondary reuse — while aligning with NYU Langone data governance, security classification, and sharing policies.

Access on UltraViolet

The ABL data repository can be accessed on UltraViolet under: /gpfs/data/abl

In the main directory, you will find a README.md outlining how to access and request access to the various repositories.

ABL data sharing guidelines are designed to ensure consistency and organization in managing datasets for dealing with private or public datasets.

Initiative Goals

Capture ABL outputs — align raw data, processed matrices, pipeline versions, and analysis reports with project identifiers and investigator context.

Improve reproducibility — document workflows, reference genomes, software versions, and QC decisions alongside each dataset.

Enable discovery — make curated ABL datasets easier to locate for follow-up studies, meta-analyses, and training.

Support compliance — integrate NYU data classification, retention, and publication requirements into repository workflows.

Data Sources Integrated

Local ABL repository

Curated project folders, analysis outputs, and pipeline artifacts from ABL collaborations

Investigator & DART laboratories

Linked sequencing, imaging, and clinical datasets generated with ABL support

Public repositories

GEO, SRA, dbGaP, and other external archives referenced in ABL project records

NYU Data Catalog

Discovery layer for datasets approved for broader institutional visibility

Repository Workflow

How ABL moves collaborative data from generation through long-term stewardship

📥

Ingest

Receive data from GTC, labs, and external sources

✅

QC & Process

Run standardized and custom ABL pipelines

🏷️

Catalog

Attach metadata, PI, assay, and project tags

🔒

Govern

Apply NYU security tiers and access controls

♻️

Reuse

Support publications, grants, and follow-on analysis

Data Types & Modalities

RNA-Seq / scRNA-Seq ATAC-Seq / scATAC-Seq ChIP-Seq / CUT&RUN WGS / WES / Targeted panels Spatial transcriptomics Long-read / PacBio / ONT Methylation & multi-omics Digital pathology & imaging Clinical & EHR-linked cohorts

Mirrored public data sources

Data from the cancer genomics resources represented in the ABL repository · click to visit

Governance & Access

Repository contents follow NYU Langone data security classification (low, moderate, high risk).
Access is granted to project PIs, designated lab members, and ABL analysts with documented approval.
Restricted datasets remain in secure storage; only approved metadata may be published to discovery indexes.
Retention and sharing align with sponsor, journal, and institutional policy requirements.
ABL acknowledges use of core services in publications and grant submissions per NYU guidelines.

Related Resources

NYU Data Catalog →

Institutional discovery index for NYU Langone datasets and external resources

Data Sharing Guide →

NYU Health Sciences Library workflows, policies, and contacts

ABL Core Services →

Official NYU Langone ABL facility page and service requests via iLab

Repository inquiries

Contact the ABL team for dataset access, deposition, or collaboration planning through your existing ABL project channel.

About the Applied Bioinformatics Laboratories

Who We Are

The Applied Bioinformatics Laboratories (ABL) provide computational analysis and support services for high-throughput genomic data at NYU Langone Health. Our mission is to accelerate scientific discoveries by guiding experimental design, performing robust data quality assessment, and carrying out comprehensive computational analyses.

In close collaboration with the NYU Genome Technology Center (GTC), we deliver results to the scientific community of the NYU Medical Center as well as external academic and non-academic collaborators — both as standardized core services and in the context of long-term collaborations.

By developing computational pipelines, methods, and analysis tools, our goal is to ensure the validity of experimental data and generate reliable, reproducible, and insightful computational results.

Vision & Mission

🔬

Guiding experimental design

✅

Robust QC, standardized and customized analyses

💻

Build software tools and analysis pipelines

🧬

Expertise in sequencing, imaging, and clinical data

📄

Contribute to publications and grant support

🎓

Educating and training

Director

Aristotelis Tsirigos, Ph.D.

Professor, Department of Medicine
Professor, Department of Pathology
Co-Director, Precision Medicine
Director, Applied Bioinformatics Laboratories

NYU Grossman School of Medicine
Division of Precision Medicine
Translational Research Building
227 East 30th Street, RM #824
NYC, NY 10016

Contribution to Research Cycle

ABL supports every stage — from first ideas through publication and back again

ABL Services — Technology Coverage

All sequencing technologies and analytical services offered by ABL

ABL Repository Initiative

The ABL data repository can be accessed on UltraViolet under: /gpfs/data/abl. In the main directory, you will find a README.md outlining how to access and request access to the various repositories.

ABL data sharing guidelines are designed to ensure consistency and organization in managing datasets for dealing with private or public datasets.

Mirrored public data sources

Data from the cancer genomics resources represented in the ABL repository · click to visit

Purpose of ABL data repository:

ABL Data Repository

🔥

Drive potential scientific collaboration

🔥

Ease the burden of finding data

🔥

Save space by storing the data at one place

Contact & Access

Director: aristotelis.tsirigos@nyulangone.org

Asst. Director: alireza.khodadadi-jamayran@nyulangone.org

Phone: (646) 501-2693

Location: NYU Langone Health
550 First Avenue, New York, NY 10016

Services offered to external collaborators. Consulting for internal NYU researchers only.

Citation & RRID

Please cite ABL using the RRID in all publications, grants, and media releases:

RRID:SCR_019178

🌐 Official ABL Website ↗

Publications 2016–2025

Full curated list of all ABL-affiliated publications from 2016 to 2025, sorted by date, on PubMed Collections.

📚

PubMed Collection

487

papers · 2016–2025

View Full Publication List ↗

ABL Team

Current and recent members · alphabetical order

Patrick
Blaney

Daniel
Cameron

Romane
Cathelin

Nicolas
Coudray

Igor
Dolgalev

Eduardo
Esteva

Yuan
Hao

Ai
Ra Idrous

Emily
Kawaler

Alireza
Khodadadi-Jamayran

Ziyan
Li

Suyash
Maji

Tamara
Mestvirishvili

Javier
Rodriguez-Hernaez

Jonathan
Serrano

Chaitra
Sreenivasaiah

Varshini
Vasudavaraja

Summer
Yang

Hua
Zhou