Tumor-Immune Partitioning and Clustering (TIPC): an algorithm for identifying tumor-immune cell spatial interaction signatures within the tumor microenvironment

2021 ◽  
Author(s):  
Jonathan Nowak ◽  
Mai Chan Lau ◽  
Jennifer Borowsky ◽  
Juha Väyrynen ◽  
Koichiro Haruki ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Spatial Heterogeneity ◽  
Nearest Neighbor ◽  
Immune Cell ◽  
Spatial Interaction ◽  
Prognostic Significance ◽  
Cell Types ◽  
Supervised Machine Learning ◽  
Tumor Subtypes ◽  
Molecular Features

Abstract Growing evidence supports the importance of quantifying tumor-immune cell interactions in the tumor microenvironment to enable precision cancer therapy. However, most existing methods rely solely upon immune cell density or nearest neighbor-type analyses and fail to fully characterize spatial heterogeneity. Herein, we describe a computational algorithm, termed Tumor-Immune Partitioning and Clustering (TIPC), that jointly measures immune cell partitioning between tumor epithelial and stromal areas and immune cell clustering versus dispersion. As proof of principle, we apply TIPC to two large colorectal cancer cohorts. TIPC identifies tumor subtypes with unique interaction signatures between tumor cells and T cells that harbor prognostic significance and are associated with distinct tumor molecular features. We extend our findings by applying TIPC to additional immune cell types identified using morphology and supervised machine learning. Spatial heterogeneity quantification and novel tumor subtype identification by TIPC may inform precision cancer immunotherapy and deepen our understanding of tumor immunobiology.

scholarly journals Tumor-Immune Partitioning and Clustering (TIPC) algorithm reveals distinct signatures of tumor-immune cell interactions within the tumor microenvironment

2020 ◽  
Author(s):  
Mai Chan Lau ◽  
Jennifer Borowsky ◽  
Juha P. Väyrynen ◽  
Koichiro Haruki ◽  
Melissa Zhao ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Spatial Patterns ◽  
Immune Cell ◽  
Spatial Relationship ◽  
Cell Types ◽  
Tumor Subtypes ◽  
Molecular Features ◽  
Cell Clustering ◽  
Spatial Composition ◽  
Cell Partitioning

AbstractGrowing evidence supports the importance of understanding tumor-immune spatial relationship in the tumor microenvironment in order to achieve precision cancer therapy. However, existing methods, based on oversimplistic cell-to-cell proximity, are largely confounded by immune cell density and are ineffective in capturing tumor-immune spatial patterns. Here we developed a novel computational algorithm, termed Tumor-Immune Partitioning and Clustering (TIPC), to offer an effective solution for spatially informed tumor subtyping. Our method could measure the extent of immune cell partitioning between tumor epithelial and stromal areas as well as the degree of immune cell clustering. Using a U.S. nation-wide colorectal cancer database, we showed that TIPC could determine tumor subtypes with unique tumor-immune spatial patterns that were significantly associated with patient survival and key tumor molecular features. We also demonstrated that TIPC was robust to parameter settings and readily applicable to different immune cell types. The capability of TIPC in delineating clinically relevant patient subtypes that encapsulate tumor-immune spatial relationship, immune density, and tumor morphology is expected to shed light on underlying immune mechanisms. Hence, TIPC can be a useful bioinformatics tool for effective characterization of the spatial composition of the tumor-immune microenvironment to inform precision immunotherapy.

scholarly journals MIXTURE: an improved algorithm for immune tumor microenvironment estimation based on gene expression data

2019 ◽  
Author(s):  
Elmer A. Fernández ◽  
Yamil D. Mahmoud ◽  
Florencia Veigas ◽  
Darío Rocha ◽  
Mónica Balzarini ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cell ◽  
Therapy Response ◽  
Cell Types ◽  
Gene Signature ◽  
Response To Therapy ◽  
Support Vector ◽  
Data Sets ◽  
Cell Type ◽  
Before And After

AbstractRNA sequencing has proved to be an efficient high-throughput technique to robustly characterize the presence and quantity of RNA in tumor biopsies at a given time. Importantly, it can be used to computationally estimate the composition of the tumor immune infiltrate and to infer the immunological phenotypes of those cells. Given the significant impact of anti-cancer immunotherapies and the role of the associated immune tumor microenvironment (ITME) on its prognosis and therapy response, the estimation of the immune cell-type content in the tumor is crucial for designing effective strategies to understand and treat cancer. Current digital estimation of the ITME cell mixture content can be performed using different analytical tools. However, current methods tend to over-estimate the number of cell-types present in the sample, thus under-estimating true proportions, biasing the results. We developed MIXTURE, a noise-constrained recursive feature selection for support vector regression that overcomes such limitations. MIXTURE deconvolutes cell-type proportions of bulk tumor samples for both RNA microarray or RNA-Seq platforms from a leukocyte validated gene signature. We evaluated MIXTURE over simulated and benchmark data sets. It overcomes competitive methods in terms of accuracy on the true number of present cell-types and proportions estimates with increased robustness to estimation bias. It also shows superior robustness to collinearity problems. Finally, we investigated the human immune microenvironment of breast cancer, head and neck squamous cell carcinoma, and melanoma biopsies before and after anti-PD-1 immunotherapy treatment revealing associations to response to therapy which have not seen by previous methods.

Patient-derived micro-organospheres recapitulate tumor microenvironment and heterogeneity for precision oncology.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3076-3076
Author(s):  
Shengli Ding ◽  
Zhaohui Wang ◽  
Marcos Negrete Obando ◽  
Grecia rivera Palomino ◽  
Tomer Rotstein ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Stromal Cells ◽  
Mononuclear Cells ◽  
Immune Cell ◽  
Tumor Biology ◽  
Cell Types ◽  
Precision Oncology ◽  
Original Tumor

3076 Background: Preclinical models that can recapitulate patients’ intra-tumoral heterogeneity and microenvironment are crucial for tumor biology research and drug discovery. In particular, the ability to retain immune and other stromal cells in the microenvironment is vital for the development of immuno-oncology assays. However, current patient-derived organoid (PDO) models are largely devoid of immune components. Methods: We first developed an automated microfluidic and membrane platform that can generate tens of thousands of micro-organospheres from resected or biopsied clinical tumor specimens within an hour. We next characterized growth rate and drug response of micro-organospheres. Finally, extensive single-cell RNA-seq profiling were performed on both micro-organospheres and original tumor samples from lung, ovarian, kidney, and breast cancer patients. Results: Micro-organospheres derived from clinical tumor samples preserved all original tumor and stromal cells, including fibroblasts and all immune cell types. Single-cell analysis revealed that unsupervised clustering of tumor and non-tumor cells were identical between original tumors and the derived micro-organospheres. Quantification showed similar cell composition and percentages for all cell types and also preserved functional intra-tumoral heterogeneity.. An automated, end-to-end, high-throughput drug screening pipeline demonstrated that matched peripheral blood mononuclear cells (PBMCs) from the same patient added to micro-organospheres can be used to assess the efficacy of immunotherapy moieties. Conclusions: Micro-organospheres are a rapid and scalable platform to preserve patient tumor microenvironment and heterogeneity. This platform will be useful for precision oncology, drug discovery, and immunotherapy development. Funding sources: NIH U01 CA217514, U01 CA214300, Duke Woo Center for Big Data and Precision Health

scholarly journals Applications of Single-Cell Omics to Dissect Tumor Microenvironment

2020 ◽  
Vol 11 ◽  
Author(s):  
Tingting Guo ◽  
Weimin Li ◽  
Xuyu Cai
Keyword(s):  
Tumor Microenvironment ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Immune Checkpoint Blockade ◽  
Lineage Tracing ◽  
Great Success ◽  
Novel Technologies ◽  
Single Cell Sequencing

The recent technical and computational advances in single-cell sequencing technologies have significantly broaden our toolkit to study tumor microenvironment (TME) directly from human specimens. The TME is the complex and dynamic ecosystem composed of multiple cell types, including tumor cells, immune cells, stromal cells, endothelial cells, and other non-cellular components such as the extracellular matrix and secreted signaling molecules. The great success on immune checkpoint blockade therapy has highlighted the importance of TME on anti-tumor immunity and has made it a prime target for further immunotherapy strategies. Applications of single-cell transcriptomics on studying TME has yielded unprecedented resolution of the cellular and molecular complexity of the TME, accelerating our understanding of the heterogeneity, plasticity, and complex cross-interaction between different cell types within the TME. In this review, we discuss the recent advances by single-cell sequencing on understanding the diversity of TME and its functional impact on tumor progression and immunotherapy response driven by single-cell sequencing. We primarily focus on the major immune cell types infiltrated in the human TME, including T cells, dendritic cells, and macrophages. We further discuss the limitations of the existing methodologies and the prospects on future studies utilizing single-cell multi-omics technologies. Since immune cells undergo continuous activation and differentiation within the TME in response to various environmental cues, we highlight the importance of integrating multimodal datasets to enable retrospective lineage tracing and epigenetic profiling of the tumor infiltrating immune cells. These novel technologies enable better characterization of the developmental lineages and differentiation states that are critical for the understanding of the underlying mechanisms driving the functional diversity of immune cells within the TME. We envision that with the continued accumulation of single-cell omics datasets, single-cell sequencing will become an indispensable aspect of the immune-oncology experimental toolkit. It will continue to drive the scientific innovations in precision immunotherapy and will be ultimately adopted by routine clinical practice in the foreseeable future.

scholarly journals IMMU-08. MICROENVIRONMENT MODULATION BY TIM-3 BLOCKADE IMPROVES THE OUTCOME OF PRECLINICAL DIPG MODELS

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i28-i28
Author(s):  
Iker Ausejo-Mauleon ◽  
Sara Labiano ◽  
Virginia Laspidea ◽  
Marc Garcia-Moure ◽  
Daniel de la Nava ◽  
...  
Keyword(s):  
T Cell ◽  
Tumor Microenvironment ◽  
Nk Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Pediatric Brain Tumors ◽  
Immune Memory ◽  
Cd8 Cells ◽  
Functional Studies

Abstract Diffuse Midline Gliomas (DMGs), encompassing Diffuse Intrinsic Pontine Gliomas (DIPGs), are the most aggressive pediatric brain tumors. Their meagre survival has not changed despite the combination of radiotherapy with targeted therapies emphasizing the urgent need for effective treatments. Recent research suggested that the DIPG tumor microenvironment is neither highly immunosuppressive nor inflammatory. These analyses showed the lack of infiltrating lymphocytes and the abundance of CD11b+ cells. TIM-3 (HAVCR2) is a member of the T-cell immunoglobulin and mucin domain protein family which is expressed on multiple immune cell types including T cells, Tregs, NK cells, monocytes, dendritic cells and microglia, where it potently regulates not only adaptive immunity but also innate immunity. Therefore, the central hypothesis of this study is that TIM-3 inhibitors could stimulate a cytotoxic immune effect and challenge several components in the tumor microenvironment including microglia, thereby providing a potential effective treatment for DMGs. In silico assessment of TIM-3 expression in a DIPG datasets showed a robust expression of this gene. Moreover, single-cell sequencing analyses of DIPG biopsies uncover its expression on tumor cells, especially in the OPCs compartment. In vivo efficacy studies showed that treatment with anti-TIM-3 antibody significantly increase the overall survival in two DIPG immunocompetent orthotopic animal models (doubling the median), lead to long-term survivors (50%) and showed immune memory. Analyses of CD45+ populations in the tumor microenvironment showed a significant increase in B, NK and CD8+ cells corresponding with a T-cell activate phenotype in treated-mice. The potential therapeutic involvement of NK cells was certified using nude mice and functional studies. Involvement of microglia in currently being analysed. In summary, these data underscore TIM-3 as a potential target DIPGs and uncover the potential involvement of NKs and other immune mechanisms in the efficacy of anti-TIM-3 therapy.

scholarly journals Comprehensive Analysis of Immune Cell Enrichment In The Tumor Microenvironment of Head And Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Ikko Mito ◽  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Immune Cell ◽  
Cell Types ◽  
Gene Set Enrichment Analysis ◽  
Rna Seq ◽  
Immune Microenvironment ◽  
Immune Signatures ◽  
Cancer Tissues

Abstract Background: Head and neck squamous carcinoma (HNSCC) is highly infiltrated by immune cells, including tumor-infiltrating lymphocytes and myeloid lineage cells. In the tumor microenvironment, tumor cells orchestrate a highly immunosuppressive microenvironment by secreting immunosuppressive mediators, expressing immune checkpoint ligands, and downregulating human leukocyte antigen expression. In the present study, we aimed to comprehensively profile the immune microenvironment of HNSCC using RNA-sequencing (RNA-seq) data obtained from The Cancer Genome Atlas (TCGA) database.Methods: We calculated enrichment scores of 33 immune cell types based on RNA-seq data of HNSCC tissues and adjacent non-cancer tissues. Based on these scores, we performed non-supervised clustering and identified three immune signatures, i.e., cold, lymphocyte, and myeloid/dendritic cell (DC), using clustering results. We then compared the clinical and biological features of the three signatures.Results: Among HNSCC and non-cancer tissues, human papillomavirus (HPV)-positive HNSCCs exhibited the highest scores in various immune cell types, including CD4+ T cells, CD8+ T cells, B cells, plasma cells, basophils, and their subpopulations. Among the three immune signatures, the proportions of HPV-positive tumors, oropharyngeal cancers, early T tumors, and N factor positive cases were significantly higher in the lymphocyte signature than in other signatures. Among the three signatures, the lymphocyte signature showed the longest overall survival (OS), especially in HPV-positive patients, whereas the myeloid/DC signature demonstrated the shortest OS in these patients. Gene set enrichment analysis revealed the upregulation of several pathways related to inflammatory and proinflammatory responses in the lymphocyte signature. The expression of PRF1, IFNG, GZMB, PDCD1, LAG3, CTLA4, HAVCR2, and TIGIT was the highest in the lymphocyte signature. Meanwhile, the expression of PD-1 ligand genes CD274 and PDCD1LG2 was highest in the myeloid/DC signature. Conclusions: Herein, our findings revealed the transcriptomic landscape of the immune microenvironment that closely reflects the clinical and biological significance of HNSCC, indicating that molecular profiling of the immune microenvironment can be employed to develop novel biomarkers and precision immunotherapies for HNSCC.

scholarly journals Exploring DNA Methylation for Prognosis and Analyzing the Tumor Microenvironment in Pleomorphic Xanthoastrocytoma

2020 ◽  
Vol 79 (8) ◽  
pp. 880-890
Author(s):  
Karen Tang ◽  
David Kurland ◽  
Varshini Vasudevaraja ◽  
Jonathan Serrano ◽  
Michael Delorenzo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Overall Survival ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Progression Free Survival ◽  
Cell Types ◽  
Homozygous Deletion ◽  
Pleomorphic Xanthoastrocytoma ◽  
Braf V600e ◽  
Rare Type

Abstract Pleomorphic xanthoastrocytoma (PXA) is a rare type of brain tumor that affects children and young adults. Molecular prognostic markers of PXAs remain poorly established. Similar to gangliogliomas, PXAs show prominent immune cell infiltrate, but its composition also remains unknown. In this study, we correlated DNA methylation and BRAF status with clinical outcome and explored the tumor microenvironment. We performed DNA methylation in 21 tumor samples from 18 subjects with a histological diagnosis of PXA. MethylCIBERSORT was used to deconvolute the PXA microenvironment by analyzing the associated immune cell-types. Median age at diagnosis was 16 years (range 7–32). At median follow-up of 30 months, 3-year and 5-year overall survival was 73% and 71%, respectively. Overall survival ranged from 1 to 139 months. Eleven out of 18 subjects (61%) showed disease progression. Progression-free survival ranged from 1 to 89 months. Trisomy 7 and CDKN2A/B (p16) homozygous deletion did not show any association with overall survival (p = 0.67 and p = 0.74, respectively). Decreased overall survival was observed for subjects with tumors lacking the BRAF V600E mutation (p = 0.02). PXAs had significantly increased CD8 T-cell epigenetic signatures compared with previously profiled gangliogliomas (p = 0.0019). The characterization of immune cell-types in PXAs may have implications for future development of immunotherapy.

scholarly journals Tumor-Associated Macrophages in Tumor Immunity

2020 ◽  
Vol 11 ◽  
Author(s):  
Yueyun Pan ◽  
Yinda Yu ◽  
Xiaojian Wang ◽  
Ting Zhang
Keyword(s):  
Tumor Microenvironment ◽  
Tumor Cells ◽  
Immune Cell ◽  
Malignant Tumors ◽  
Treatment Strategies ◽  
Cell Types ◽  
Therapeutic Interventions ◽  
M2 Macrophages ◽  
Tumor Associated Macrophages ◽  
Mediate Cytotoxicity

Tumor-associated macrophages (TAMs) represent one of the main tumor-infiltrating immune cell types and are generally categorized into either of two functionally contrasting subtypes, namely classical activated M1 macrophages and alternatively activated M2 macrophages. The former typically exerts anti-tumor functions, including directly mediate cytotoxicity and antibody-dependent cell-mediated cytotoxicity (ADCC) to kill tumor cells; the latter can promote the occurrence and metastasis of tumor cells, inhibit T cell-mediated anti-tumor immune response, promote tumor angiogenesis, and lead to tumor progression. Both M1 and M2 macrophages have high degree of plasticity and thus can be converted into each other upon tumor microenvironment changes or therapeutic interventions. As the relationship between TAMs and malignant tumors becoming clearer, TAMs have become a promising target for developing new cancer treatment. In this review, we summarize the origin and types of TAMs, TAMs interaction with tumors and tumor microenvironment, and up-to-date treatment strategies targeting TAMs.

scholarly journals Comprehensive analysis of immune cell enrichment in the tumor microenvironment of head and neck squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ikko Mito ◽  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Cell Types ◽  
Expression Data ◽  
Immune Microenvironment ◽  
Cancer Tissues

AbstractHead and neck squamous carcinoma (HNSCC) is highly infiltrated by immune cells, including tumor-infiltrating lymphocytes and myeloid lineage cells. In the tumor microenvironment, tumor cells orchestrate a highly immunosuppressive microenvironment by secreting immunosuppressive mediators, expressing immune checkpoint ligands, and downregulating human leukocyte antigen expression. In the present study, we aimed to comprehensively profile the immune microenvironment of HNSCC using gene expression data obtained from public database. We calculated enrichment scores of 33 immune cell types based on gene expression data of HNSCC tissues and adjacent non-cancer tissues. Based on these scores, we performed non-supervised clustering and identified three immune signatures—cold, lymphocyte, and myeloid/dendritic cell (DC)—based on the clustering results. We then compared the clinical and biological features of the three signatures. Among HNSCC and non-cancer tissues, human papillomavirus (HPV)-positive HNSCCs exhibited the highest scores in various immune cell types, including CD4+ T cells, CD8+ T cells, B cells, plasma cells, basophils, and their subpopulations. Among the three immune signatures, the proportions of HPV-positive tumors, oropharyngeal cancers, early T tumors, and N factor positive cases were significantly higher in the lymphocyte signature than in other signatures. Among the three signatures, the lymphocyte signature showed the longest overall survival (OS), especially in HPV-positive patients, whereas the myeloid/DC signature demonstrated the shortest OS in these patients. Gene set enrichment analysis revealed the upregulation of several pathways related to inflammatory and proinflammatory responses in the lymphocyte signature. The expression of PRF1, IFNG, GZMB, CXCL9, CXCL10, PDCD1, LAG3, CTLA4, HAVCR2, and TIGIT was the highest in the lymphocyte signature. Meanwhile, the expression of PD-1 ligand genes CD274 and PDCD1LG2 was highest in the myeloid/DC signature. Herein, our findings revealed the transcriptomic landscape of the immune microenvironment that closely reflects the clinical and biological significance of HNSCC, indicating that molecular profiling of the immune microenvironment can be employed to develop novel biomarkers and precision immunotherapies for HNSCC.

scholarly journals Pan-cancer analysis identified inflamed microenvironment associated multi-omics signatures

2020 ◽  
Author(s):  
Ben Wang ◽  
Mengmeng Liu ◽  
Zhujie Ran ◽  
Xin Li ◽  
Jie Li ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Single Cell ◽  
Histone Deacetylase Inhibitors ◽  
Immune Cell ◽  
Cell Interaction ◽  
Molecular Characteristics ◽  
Molecular Features ◽  
Phenotype Transformation ◽  
Multiple Drugs ◽  
Pan Cancer

AbstractBackgroundImmunotherapy has revolutionized cancer therapy. However, responses are not universal. The inflamed tumor microenvironment has been reported to correlate with response in tumor patients. However, how different tumors shape their tumor microenvironment remains a critical unsolved problem. A deeper insight into the molecular characteristics of inflamed tumor microenvironment may be needed.Materials and methodsHere, based on single-cell RNA sequencing technology and TCGA pan-cancer cohort, we investigated multi-omics molecular features of tumor microenvironment phenotypes. Based on single-cell RNA-seq analysis, we classified pan-cancer tumor samples into inflamed or non-inflamed tumor and identified molecular features of these tumors. Analysis of integrating identified gene signatures with a drug-genomic perturbation database identified multiple drugs which may be helpful for converting non-inflamed tumors to inflamed tumors.ResultsOur results revealed several inflamed/non-inflamed tumor microenvironments-specific molecular characteristics. For example, inflamed tumors highly expressed miR-650 and lncRNA including MIR155HG and LINC00426, these tumors showed activated cytokines-related signaling pathways. Interestingly, non-inflamed tumors tended to express several genes related to neurogenesis. Multi-omics analysis demonstrated the neuro phenotype transformation may be induced by hypomethylated promoters of these genes and down-regulated miR-650. Drug discovery analysis revealed histone deacetylase inhibitors may be a potential choice for helping favorable tumor microenvironment phenotype transformation and aiding current immunotherapy.ConclusionOur results provide a comprehensive molecular-level understanding of tumor cell-immune cell interaction and may have profound clinical implications.

Sign in / Sign up

Export Citation Format

Share Document