Multi-model preclinical platform predicts clinical response of melanoma to immunotherapy
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA605423 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11040700.fastq.gz | Fastqsanger.gz | |||
| SRR11040700_1.fastq.gz | Fastqsanger.gz | |||
| SRR11040700_2.fastq.gz | Fastqsanger.gz | |||
| SRR11040701.fastq.gz | Fastqsanger.gz | |||
| SRR11040701_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 154 |
Similar Datasets
Project description: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 a variety of molecular and phenotypic subtypes of human melanomas and exhibiting their diverse 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 (MPS) 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.
2020-06-01 | GSE144946 | GEO
Project description:Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrate 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 a variety of molecular and phenotypic subtypes of human melanomas and exhibiting their diverse 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 mechanisms and treatment strategies to improve patient care.
| S-EPMC8482620 | biostudies-literature
Project description:Despite the remarkable success of immunotherapy, only ~20-30% of cancer patients display an extended durable response. Pre-existing biomarkers for immunotherapy outcome are significantly limited in their predictive power. While mice are the most widely used and cost-effective model to study human disease, translating preclinical biomarkers into clinical practice faces significant obstacles – in part due to the lack of diverse or appropriate models. Here, to improve translatability and identify novel biomarkers, we showcase an approach encompassing several pre-clinical models - each capturing one possible mechanistic aspect of immunotherapy response, such as tumor- and host-dependency, in order to reflect the variability seen in human cancers. Using this approach, we identify interferon-stimulated, Ly6Ehi neutrophils as a pre-treatment, blood-borne biomarker for anti-PD1 response in mice. We subsequently validate this result in cohorts of immunotherapy-treated non-small cell lung cancer (NSCLC) and melanoma patients, where the abundance of Ly6Ehi neutrophils predicts anti-PD1 response and further validated these results using available datasets for other cancers. Moreover, we demonstrate that these cells sensitize otherwise resistant tumors to anti-PD1 therapy, in part by directly activating cytotoxic T cells and contributing to tumor cell killing, while operate upstream of T cells in the immunotherapy response. Collectively, our study identifies a new and functionally active biomarker to predict immunotherapy outcome with potential clinical relevance.
2024-01-05 | GSE226962 | GEO
Project description:Immune checkpoint inhibitors (ICI) produce durable responses in some melanoma patients, but many patients derive no clinical benefit, and the molecular underpinnings of such resistance remain elusive. Here, we leveraged single-cell RNA-seq (scRNA-seq) from 31 melanoma tumors and novel computational methods to interrogate malignant cell states that promote immune evasion. We identified a resistance program expressed by malignant cells that is associated with T cell exclusion and immune evasion. The program is present prior to immunotherapy, characterizes cold niches, and predicts clinical responses to anti-PD-1 therapy in an independent cohort of 112 melanoma patients. CDK4/6-inhibition represses this program in individual malignant cells, induces senescence, and reduces melanoma tumor outgrowth in a mouse model when given in combination with immunotherapy. Our study provides a high-resolution landscape of ICI resistant cell states, identifies clinically predictive signatures, and forms a basis for the development of novel therapeutic strategies that could overcome immunotherapy resistance.
2018-11-01 | GSE115978 | GEO
Project description:A Syngeneic ErbB2 Mammary Cancer Model for Preclinical Immunotherapy Trials
| PRJNA450984 | ENA
Project description:A Syngeneic ErbB2 Mammary Cancer Model for Preclinical Immunotherapy Trials [microarray]
| PRJNA448828 | ENA
Project description:Cance vaccines have become a milestone in immunotherapy, but inadequate activation rate of antigen presenting cells (APCs) and low delivery efficiency of specific antigen have widely limited their clinical application. Here we design an engineered vaccine platform based on targeted delivery of specific antigens to activated APCs. This vaccine platform is implemented by loading stimulator of interferon genes agonist and tumor lysate protein with calcium phosphate as adjuvants, and coating the surface with mannose-modified liposomes. By loading different types of tumor antigen proteins, this nanovaccine platform successfully achieves tumor immunotherapy in breast and colon cancer bearing mice. In addition, personalized nanovaccine prepared from surgically removed tumor lysate proteins also significantly suppresses postsurgical distant tumor. Through the design of nanovaccine platform, we provide an efficient multi-adjuvant delivery platform for multiple types of tumor antigens, and also offer more ideas for personalized vaccine immunization. This nanovaccine platform has great prospects for transformation due to the designability and simplicity for the preparation.
2024-05-14 | GSE267162 | GEO
Project description:Rheumatoid arthritis is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis. A total of 559 human sera were profiled using a custom made panel of putative rheumatoid arthritis associated autoantigens. The cohort was comprised of 79 patients with clinical RA for whom stored serum was available from 1-10 years prior to disease onset and 80 control subjects without RA that were matched to cases based on age, gender, race, region of assignment, and time of serum sampling.
2011-09-09 | E-GEOD-32016 | biostudies-arrayexpress
Project description:A Syngeneic ErbB2 Mammary Cancer Model for Preclinical Immunotherapy Trials [RNA-seq]
| PRJNA450988 | ENA
Project description:Rheumatoid arthritis is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-?, IL-6, IL-12p70, and IFN-?. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis. A total of 556 human sera were profiled using multiplex cytokine and chemokine assays. The cohort was comprised of 80 patients with clinical RA for whom stored serum was available from 1-10 years prior to disease onset and 78 control subjects without RA matched to cases based on age, gender, race, region of assignment, and time of serum sampling.
2011-09-09 | E-GEOD-32019 | biostudies-arrayexpress