Biology subjects

Coukos, G.

Publications and source records attributed to Coukos, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Actionable spatial prostanoid barriers constrain BiTE-driven adoptive T cell immunity in intact human tumors

Adoptive cell therapy (ACT) in solid tumors is limited by tumor microenvironment (TME)-imposed resistance mechanisms that are inadequately addressed by conventional systems. We developed tissue-preserving patient-derived explants (PDEs) from lung and ovarian cancer to interrogate redirected T cell immunity in intact human tissue. Using mesothelin-targeting bispecific T cell engager (BiTE(R), Amgen trademark)-secreting T cells, we observed antigen-dependent but heterogeneous responses across lesions. An integrated ex vivo response score stratified responder and non-responder TMEs, revealing that resistance associates with reduced antigen density, stromal dominance, and limited myeloid licensing rather than baseline lymphocyte abundance. Elevated prostaglandin E2 (PGE2) inversely correlated with BiTE-induced T cell activation, identifying the COX/PGE2 axis as a tissue-imposed constraint. COX inhibition amplified interferon-driven immune programs enhanced intratumoral CD8 infiltration, and increased tumor-restricted apoptosis. Spatial transcriptomics localized these effects to tumor-proximal immune hubs in responders, whereas non-responders remained stromally insulated. These findings position PDEs as human-based new approach methodologies enabling combinatorial ACT pharmacodynamics and stratification. Statement of significancePatient-derived explants provide a human-based new approach methodology to interrogate adoptive immunotherapy pharmacodynamics within intact tumor microenvironments in NSCLC and HGSOC. We uncover a COX/PGE2-mediated tissue ceiling that limits BiTE-driven T cell function and demonstrate that COX inhibition reactivates tumor-proximal immune hubs to enhance intratumoral CD8 infiltration and tumor-restricted apoptosis, informing patient stratification and rational combinations.

systems biology↗

bioRxiv2026

Applications of T-cell receptor specificity annotation models for quality control and immunomonitoring in adoptive T-cell therapies

Adoptive cell therapy (ACT) with tumor-infiltrating lymphocytes (TIL) is a powerful candidate immunotherapy. However, the personalized production process that underlies its potential also introduces an element of stochasticity, where the actual target of the TILs is variable across patients and protocols, and remains largely unknown. In this letter, we describe the application of T-cell receptor (TCR) sequencing in combination with computational tools for annotating epitope-specificity of the TCR repertoire of TIL products as a potent quality control. We highlight the potential of this approach by demonstrating the tumor antigen-specificity of TCR clusters within the TIL product in silico, and validating these responses in vitro. We also demonstrate screening for off-cancer reactivity against viral antigens, and immune monitoring of identified TCR clones. HighlightsO_LIT-cell receptor sequencing combined with epitope annotation tools are viable for quality control of TIL products by identifying tumor-specific clones. C_LIO_LIWe showed the additional utility of screening for off-cancer reactivity, such as viral antigens. C_LIO_LIThe identified tumor-specific TCR clones can be tracked in vivo providing a means of immune monitoring. C_LI

bioinformatics↗

bioRxiv2025

Computational Inference of Metabolic Programs: A Case Study Analyzing the Effect of BRCA1 Loss

Metabolic reprogramming is a hallmark of cancer, yet how oncogenic drivers shape tumor metabolism across disease progression remains incompletely understood. In this study, we present iMSEA (in silico Metabolic State and Enrichment Analysis), a computational framework that infers flux-based metabolic states from omics profiles. Applying iMSEA to isogenic BRCA1-mutant and BRCA1-wild-type ovarian cancer cells, we identified a shift toward glycolysis, nucleotide biosynthesis, and redox imbalance, coupled with impaired oxidative phosphorylation. These predictions were validated with metabolomics, Seahorse, and SCENITH assays, demonstrating the accuracy of our approach. Extending the analysis to homologous recombination deficient patient tumors at single-cell resolution, we found that BRCA1-deficient cancers display heightened metabolic activity and site-specific adaptations, including altered central carbon fluxes, mitochondrial function, nucleotide biosynthesis, and lipid metabolism. By linking transcriptional programs to functional metabolic states, iMSEA reveals hidden metabolic liabilities in BRCA1-deficient ovarian cancer and provides a broadly applicable strategy for dissecting metabolic heterogeneity and therapeutic vulnerabilities in cancer.

systems biology↗

bioRxiv2025

Multi-modal image analysis for large scale cancer tissue studies within IMMUcan

MotivationMultiplexed imaging is increasingly used to study tissue architecture in health and disease. To investigate the cancer tumor microenvironment, typically either tissue micro-arrays or small patient cohorts are used to collect and process data. However, studies performed over the course of years, collecting data from thousands of samples are rare and require specialized workflows to ensure sample throughput and reproducibility for data production and processing. Here, we present two such workflows for multiplexed immunofluorescence and imaging mass cytometry of cancer tissues which are applied to a total of roughly 10000 samples from 2500 patients over six years. SummaryIn cancer research, multiplexed imaging allows detailed characterization of the tumor microenvironment (TME) and its link to patient prognosis. The IMMUcan consortium collects multi-modal imaging data from thousands of cancer patients to perform broad molecular and cellular spatial profiling across five cancer indications. Here, we describe two workflows for multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) developed within IMMUcan to enable analysis of thousands of cancer tissues. IFQuant supports web-based, user-friendly, and reproducible analysis of mIF data. High sample throughput for IMC is achieved by optimizing experimental protocols and developing a robotic arm for automated slide loading. We provide a resource of 350000 manually labelled cells across 180 cancer samples to accurately annotate cell phenotypes in IMC. All major cell phenotypes and tissue structures correlate well between mIF and IMC. These pipelines form the basis for multiplexed image analysis within IMMUcan and provide computational tools for the larger community.

cancer biology↗

bioRxiv2024

Transcriptome Analysis of Archived Tumor Tissues by Visium, GeoMx DSP, and Chromium Methods Reveals Inter- and Intra-Patient Heterogeneity

Recent advancements in probe-based, full-transcriptome, high-resolution technologies for Formalin-Fixed Paraffin-Embedded (FFPE) tissues, such as Visium CytAssist, Chromium Flex (10X Genomics), and GeoMx DSP (Nanostring), have opened new opportunities for studying decades-old archival samples in biobanks, facilitating the generation of data from extensive cohorts. However, the experimental protocols can be labor-intensive and costly; therefore, it is thus essential for researchers to carefully evaluate the strengths and limitations of each technology in relation to their specific research objectives. Here, we report the results of a comparative analysis of the three methods mentioned above on FFPE archival tumor samples from four non-small cell lung cancer, four breast cancer and six diffuse large B-cell lymphoma. We highlight some relative advantages and disadvantages of each method in the context of operational challenges, bioinformatic analysis and biological discovery. Our results show that: 1) all three methods yielded good-quality, highly reproducible transcriptomic data from serial sections of the same FFPE block; 2) GeoMx data contained mixtures of cell types, even when pre-selecting areas with cell type-specific markers; 3) high-throughput spot-level (Visium) or cell-level (Chromium) data enabled the identification of tumor heterogeneity within and between patients, which could be used to identify targeted therapies. Our data support the use of Visium and Chromium for high-throughput and discovery-driven projects, while the GeoMx platform could be suited for addressing specialized questions on targeted regions. All data generated from this study, including GeoMx, Visium, Chromium, H&E, and expert annotations are publicly available.

bioinformatics↗

bioRxiv2024

DNA-Dependent Protein Kinase Inhibitors PI-103 and Samotolisib Augment CRISPR/Cas9 Knockin Efficiency in Human T Cells

1.The adoptive cell transfer of ex vivo expanded tumor infiltrating lymphocytes (i.e., TIL therapy) is a promising clinical strategy and recently FDA approved for melanoma but has major limitations including that not all tumors are inflamed. Moreover, tumor-specific clones can be rare and in an exhausted state due to the suppressive tumor microenvironment. These obstacles can be overcome by engineering autologous peripheral blood T cells with pre-selected T cell receptors (TCRs) by viral vector-mediated gene insertion. While viral transduction is highly efficient, the insertional site is not specific and persistence of the T cells is oftentimes limited. In contrast, site-specific integration of the TCR into the TCR chain (TRAC) locus by CRISPR/Cas9 has been shown to enable more consistent and physiological levels of exogenous TCR expression coupled with superior persistence and tumor control in preclinical studies. Here, we sought to improve the efficiency of CRISPR/Cas9 mediated TCR knockin (KI) into the TRAC locus of primary human T cells. In addition to the previously reported DNA-dependent protein kinase inhibitor M3814, we demonstrate that PI-103 and samotolisib markedly increase KI efficiency in a process that is GMP-compatible, while CC-115 had a variable effect. Importantly, PI-103 and samotolisib do not negatively impact cell viability, fold-expansion nor T cell phenotype and we conclude that they are suitable for the generation of gene-modified T cells for clinical use.

bioengineering↗

bioRxiv2024

Myeloid cell networks determine reinstatement of original immune environments in recurrent ovarian cancer

Immunotherapy has produced disappointing results in recurrent ovarian cancer (OC). However, the prognostic value of tumour-infiltrating lymphocytes (TILs) is largely based on the analysis of treatment-naive tumours. To understand the immunobiology of recurrent cancers, and their evolution, we profiled 170 patient-matched primary-recurrent OC samples from 69 patients of two independent cohorts. By capturing heterogeneous TIL distributions, we identified four immune phenotypes associated with differential prognosis, TILs states and TILs:myeloid networks, which dictate malignant evolution after chemotherapy and recurrence. Notably, recurrent tumours recapitulate the immunogenic patterns of original cancers. Mirroring inflamed human OC, preclinical recurrent Brca1mut tumours maintained activated TILs:dendritic cells (DCs) niches and immunostimulatory tumour-associated macrophages (TAMs). Conversely, recurrent Brca1wt tumours displayed loss of TILs:DCs niches and accumulated immunosuppressive myeloid networks featuring Trem2/ApoEhigh TAMs and Nduf4l2high/Galectin3high malignant states. Our study highlights that persistent immunogenicity in recurrent OC is governed by the crosstalk between dissimilar myeloid cells and TILs, which is BRCA-dependent.

immunology↗

bioRxiv2023

Acidity-induced dysfunction of CD8+ T cells is characterized by impaired IL-2 responsiveness and perturbations to mTORC1 signaling and c-Myc levels

CD8+ T cells play a critical role in cancer control but a range of barriers in the tumor microenvironment, including low pH, can impair their function. Here, we demonstrate that acidity dampens T-cell expansion mainly due to impaired IL-2 responsiveness, blunts cytokine secretion upon re-activation, and lowers the cytolytic capacity of CD8+ T cells expressing weak affinity TCR. We further reveal and dissect defects in both mTORC1 activity and c-Myc accumulation at low pH, the latter of which is largely due to proteasome-mediated degradation. In addition, lower intracellular levels of glutamine, glutamate and aspartate as well as elevated proline were noted, with no apparent impact on mTORC1 or c-Myc. Overall, low pH disrupts diverse intracellular signaling pathways as well as nutrient uptake/processing by T cells and we conclude that unless intracellular pH can be restored, multiple interventions will be required to overcome acidity-induced dysfunction.

cell biology↗

bioRxiv2023

Dissection and reconstruction of the colorectal cancer tumor microenvironment

Patient-derived organoids (PDOs) are the reference in vitro human disease models. However, the utility of colorectal cancer (CRC) PDOs is hindered by the lack of a tumor microenvironment (TME). To address this limitation, we built a living biobank of CRC PDOs with autologous stromal and immune TME. We characterized the original tumors and traditional monocultures using single-cell RNA-seq (scRNA-seq) and whole exome sequencing (WES) to obtain insights into cell type selection and phenotypic drift in culture. Subsequently, we developed culture conditions supporting all cell types to recapitulate the CRC-TME around PDOs. From the transcriptomes of >180k cells obtained from 260 such co-cultures, we illuminated the mutual influence of cells within CRC tumors. Based on original tumor data, atlases of predicted interactions and transcriptional networks elucidated why monocultures were altered and suggested that TME reconstruction more accurately reflected original tumor behavior. We found that inflammatory signals were absent in vitro and recovered upon co-culture with tumor-infiltrating lymphocytes (TILs). We also functionally confirmed that stromal, not cancer cells, mediated immune evasion. Additionally, stroma induced an invasive phenotype in cancer cells. From this deep dive into CRC-TME interactions, we built the human CRC-TME atlas (https://crc-tme.com/), an online portal for interactive exploration of gene expression data, prediction of cell-cell interactions at the pathway and receptor/ligand levels, transcriptional networks, and more. We anticipate PDO cultures with reconstructed TMEs will be valuable for discovery efforts, preclinical studies, and personalized medicine, with the atlas as a framework and inspiration for future CRC-TME studies.

cancer biology↗

bioRxiv2023

Tumor-reactive clonotype dynamics underlying clinical response to TIL therapy in melanoma

The profiles, specificity and dynamics of tumor-specific clonotypes that are associated with clinical response to adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TILs) remain unclear. Using single-cell RNA/TCR-sequencing, we tracked TIL clonotypes from baseline tumors to ACT products and post-ACT blood and tumor samples in melanoma patients treated with TIL-ACT. Patients with clinical responses had baseline tumors enriched in tumor-reactive TILs, which were more effectively mobilized upon in vitro expansion, yielding products with higher numbers of tumor-specific CD8+ cells, which also preferentially infiltrated tumors post-ACT. Conversely, lack of clinical responses was associated with tumors devoid of tumor-reactive resident clonotypes, and with cell products mostly composed of blood-borne clonotypes mainly persisting in blood but not in tumors post-ACT. Upon expansion, tumor-specific TILs lost the specific signatures of states originally exhibited in tumors, including exhaustion, and in responders acquired an intermediate exhausted effector state after tumor engraftment, revealing important functional cell reinvigoration.

cancer biology↗

bioRxiv2023

Combination of NY-ESO-1-TCR-T-cells coengineered to secrete SiRPalpha decoys with anti-tumor antibodies to augment macrophage phagocytosis

The adoptive transfer of T cell receptor (TCR)-engineered T cells (ACT) targeting the HLA-A2 restricted cancer-testis epitope NY-ESO-1157-165 (A2/NY) has yielded favorable clinical responses against a variety of cancers. Two promising approaches to improve ACT efficacy are TCR affinity-optimization and combinatorial treatment strategies to reprogram the tumor microenvironment (TME). By computational design, we previously developed a panel of affinity-enhanced A2/NY-TCRs. Here, we have demonstrated improved tumor control and engraftment by T cells gene-modified to express one such TCR comprising a single amino acid replacement in CDR3{beta} (A97L). To harness macrophages in the TME, we coengineered TCR-T cells to constitutively or inducibly secrete a high-affinity signal regulatory protein alpha (SiRP) decoy (CV1) to block the CD47 dont eat me signal. We demonstrated better control of tumor outgrowth by CV1-Fc coengineered TCR-T cells but in subcutaneous xenograft tumor models we observed depletion of both CV1-Fc and CV1 coengineered T cells. Importantly, CV1 coengineered T cells were not depleted by human macrophages in vitro. Moreover, Avelumab and Cetuximab enhanced macrophage-mediated phagocytosis in vitro in the presence of CV1, and augmented tumor control upon ACT. Taken together, our study indicates important clinical promise for harnessing macrophages by combining CV1 coengineered TCR-T cells with tumor-targeting monoclonal antibodies.

bioengineering↗

bioRxiv2023

TCRpcDist: Estimating TCR physico-chemical similarity to analyze repertoires and predict specificities

Approaches to analyse and cluster TCR repertoires to reflect antigen specificity are critical for the diagnosis and prognosis of immune-related diseases and the development of personalized therapies. Sequence-based approaches showed success but remain restrictive, especially when the amount of experimental data used for the training is scarce. Structure-based approaches which represent powerful alternatives, notably to optimize TCRs affinity towards specific epitopes, show limitations for large scale predictions. To handle these challenges, we present TCRpcDist, a 3D-based approach that calculates similarities between TCRs using a metric related to the physico-chemical properties of the loop residues predicted to interact with the epitope. By exploiting private and public datasets and comparing TCRpcDist with competing approaches, we demonstrate that TCRpcDist can accurately identify groups of TCRs that are likely to bind the same or similar epitopes. Additionally, we experimentally validated the ability of TCRpcDist to predict antigen-specificities of tumor-infiltrating lymphocytes orphan TCRs obtained from four cancer patients. TCRpcDist is a promising approach to support TCR repertoire analysis and cancer immunotherapies. One Sentence SummaryWe present a new approach for TCR clustering which allows TCR deorphanization for the first time.

immunology↗

bioRxiv2023

Transcriptional reprogramming by IL-2 variant generates metabolically active stem-like T cells

Interleukin-2 receptor (IL-2R)-mediated intracellular signaling is a key regulator of T-cell fate decisions. While the potent signals generated by IL-2 engagement execute effector differentiation, elevated metabolic activities and rapid cellular expansion, IL-15 binding induces a stemness/memory phenotype and a quiescent metabolic state. Here, we demonstrate that weak but sustained signaling generated by a non-IL-2R-binding variant of IL-2 (IL-2v) drive proliferation/metabolic and stemness transcriptional programs, thereby reprogramming CD8+ T cells into a hybrid metabolically active stem-like state. We further show that IL-2v-induced T cells are capable of superior engraftment, persistence, and tumor control when utilized in adoptive cell therapy. Taken together, our study highlights the ability to fine-tune cytokine engagement of cognate receptors in order to generate therapeutically relevant T-cell states and further reveals the metabolic plasticity of the T-cell memory program.

systems biology↗

bioRxiv2022

Tumor Microenvironment Cellular Crosstalk Predicts Response to Adoptive TIL Therapy in Melanoma

Adoptive cell therapy (ACT) using ex vivo expanded tumor-infiltrating T lymphocytes (TILs) can mediate responses in metastatic melanoma, but long-term efficacy remains limited to a fraction of patients. Here we interrogated tumor-microenvironment (TME) cellular states and interactions of longitudinal samples from 13 metastatic melanoma patients treated with TIL-ACT in our clinical study (NCT03475134). We performed single-cell RNA-seq and spatial proteomic analyses in pre- and post-ACT tumor tissues and showed that responders exhibited higher tumor cell-intrinsic immunogenicity. Also, endogenous CD8+ TILs and myeloid cells of responders were characterized by increased cytotoxicity, exhaustion and costimulation and type-I IFN signaling, respectively. Cell-cell interaction prediction analyses corroborated by spatial neighborhood analyses revealed that responders have rich baseline intratumoral and stromal tumor-reactive T-cell networks with activated myeloid populations. Successful TIL-ACT therapy further reprogrammed the myeloid compartment and increased TIL-myeloid networks. Our systematic target discovery study reveals CD8+ T-cell network-based biomarkers that could improve patient selection and guide the design of ACT clinical trials. One-Sentence SummaryResponse to adoptive TIL therapy in melanoma is determined by CD8+ TIL-myeloid cell networks

immunology↗

bioRxiv2022

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes

CD4+ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on MHC-II molecules. The high polymorphism of MHC-II genes represents an important hurdle towards accurate prediction and identification of CD4+ T-cell epitopes in different individuals and different species. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across human, mouse, cattle and chicken. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse binding mode in MHC-II ligands. We then developed a machine learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T-cell epitopes, and enabled us to discover and characterize several viral and bacterial epitopes following the aforementioned reverse binding mode.

immunology↗

bioRxiv2022

Orthogonal Gene Engineering Enables CD8+ T Cells to Control Tumors through a Novel PD-1+ TOX-indifferent Synthetic Effector State

Adoptive immunotherapy offers opportunities to reprogram T cells and the tumor microenvironment. Orthogonal engineering of adoptively transferred T cells with an IL-2R{beta}{gamma}-binding IL-2 variant, PD1-decoy and IL-33 led to cell-autonomous T-cell expansion, T-cell engraftment and tumor control in immunocompetent hosts through reprogramming of both transferred and endogenous CD8+ cells. Tumor-infiltrating lymphocytes adopted a novel effector state characterized by TOX suppression and specific expression of multiple effector molecules, most prominently granzyme C. While the IL-2 variant promoted CD8+ T-cell stemness and persistence, and was associated with downregulation of TOX, the combination with IL-33 was necessary to trigger the novel polyfunctional effector state. Rational T-cell engineering without host lymphodepletion enables optimal reprogramming of adoptively transferred T cells as well as mobilization of endogenous immunity into new functional CD8+ states mediating tumor control.

immunology↗

bioRxiv2021

High-throughput single-cell TCR - pMHC dissociation rate measurements performed by an autonomous microfluidic cellular processing unit

We developed an integrated microfluidic cellular processing unit (mCPU) capable of autonomously isolating single cells, perform, measure, and on-the-fly analyze cell-surface dissociation rates, followed by recovery of selected cells. We performed proof-of-concept, high-throughput single-cell experiments characterizing pMHC-TCR interactions on live CD8+ T cells. The mCPU platform analyzed TCR-pMHC dissociation rates with a throughput of 50 cells per hour and hundreds of cells per run, and we demonstrate that cells can be selected, enriched, and easily recovered from the device.

bioengineering↗

bioRxiv2021

Deciphering the landscape of phosphorylated HLA-II ligands

CD4+ T-cell activation in infectious diseases and cancer is governed by the recognition of peptides presented on class II human leukocyte antigen (HLA-II) molecules. Therefore, HLA-II ligands represent promising targets for vaccine design and personalized cancer immunotherapy. Much work has been done to identify and predict unmodified peptides presented on HLA-II molecules. However, little is known about the presentation of phosphorylated HLA-II ligands. Here, we analyzed Mass Spectrometry HLA-II peptidomics data and identified 1,113 unique phosphorylated HLA-II ligands. This enabled us to precisely define phosphorylated binding motifs for more than 30 common HLA-II alleles and to explore various molecular properties of phosphorylated peptides. Our data were further used to develop the first predictor of phosphorylated peptide presentation on HLA-II molecules.

immunology↗