Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The Spatial Heterogeneity in Multiple Myeloma - from the Subclonal Architecture to the Immune Microenvironment (partly hipo K08K)

ABSTRACT: Multiple myeloma (MM) cells show pronounced heterogeneity not only within a given patient but also between spatially separated tumor loci in the bone marrow. Understanding this spatial heterogeneity is emerging as a critical challenge for the successful treatment of the disease. Yet, our understanding of spatial differences in the subclonal architecture, molecular signatures and interactions with the tumor microenvironment remains very limited. To address this shortcoming, we performed bulk and single-cell multi-region sequencing, including random bone marrow samples from the iliac crest and paired imaging-guided focal lesion specimens from 15 newly diagnosed MM patients. We found a median of 5 subclones per patient and unique subclones in focal lesions. Central features of spatial heterogeneity included a consistent down-regulation of the chemoattractant cytokines CXCL7 and CXCL12 in focal lesion tumor cells as well as a significant depletion of macrophages in the focal lesion microenvironment. In contrast, a site-specific expansion of T-cell clones was not detected in focal lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity with potential implications for immunotherapies and molecular studies analyzing the role of gene signatures and MM-microenvironment interactions in disease progression.

PROVIDER: EGAS00001006090 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

Spatial Transcriptomic Analysis of Superficial Peritoneal Endometriotic Lesions

Project description:The mechanisms underlying the pathophysiology of endometriosis, characterized by the presence of endometrium-like tissue outside the uterus, remain poorly understood. This study aimed to identify cell type-specific gene expression changes in superficial peritoneal endometriotic lesions and elucidate the crosstalk among the stroma, epithelium, and macrophages compared to patient-matched eutopic endometrium. Surprisingly, comparison between lesions and eutopic endometrium revealed transcriptional similarities, indicating minimal alterations in the sub-epithelial stroma and epithelium of lesions. Spatial transcriptomics (NanoString GeoMx) highlighted increased signaling between the lesion epithelium and macrophages, emphasizing the role of the epithelium in driving lesion inflammation. We propose that the superficial endometriotic lesion epithelium orchestrates inflammatory signaling and promotes a pro-repair phenotype in macrophages, providing a new role for Complement 3 in lesion pathobiology. This study underscores the significance of considering spatial context and cellular interactions in uncovering mechanisms governing disease in endometriotic lesions.

2024-04-16 | GSE263897 | GEO

Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis

Project description:Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.

2023-08-01 | GSE235783 | GEO

Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces

Project description:Recent advances in spatial transcriptomics (ST) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor and its microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as occurs in tumor-immune interactions. We present SpaceMarkers, a novel bioinformatics algorithm to infer molecular changes from cell-cell interaction from latent space analysis of ST data. We apply this approach to infer molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantification of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.

2023-04-19 | GSE224411 | GEO

Spatial genomic heterogeneity in multiple myeloma revealed by multi- region sequencing

Project description:The bone-marrow (BM) containing skeletal system is the reservoir of Multiple Myeloma (MM), the malignant counterpart of antibody-secreting plasma cells. To gain insight into its spatial clonal architecture, we performed multi-region whole-exome sequencing of radiology-guided fine-needle aspirates from 51 MM patients. We found spatial genomic heterogeneity in a substantial proportion of cases including bi-allelic inactivation of tumor suppressors and mutations affecting cancer genes. The amount of heterogeneous mutations associated with the size of focal tumor lesions in whole body imaging consistent with focal outgrowth of highly advanced clones. In conclusion, our results support the regional initiation of transformation processes leading to high-risk disease as well as the pre-existence of key driver events in restricted areas. As such, our study does not only provide new insights in the underlying biology of MM progression but also has considerable implications for standard diagnostic approaches in the clinic.

| EGAS00001002111 | EGA

Spontaneous Endometritotic Lesions Compared to Eutopic Endometrium in the Baboon

Project description:The development and progression of endometriotic lesions are poorly understood, but immune cell dysfunction and inflammation are closely associated with the pathophysiology of endometriosis. A lack of suitable 3D in vitro models permitting the study of interactions between cell types and the microenvironment is a contributing factor. To address this limitation, we developed endometriotic organoids (EO) to explore the role of epithelial-stromal interactions and model peritoneal cell invasion associated with lesion development (GSE202661). These organoids were compared to spontaneous endometriotic lesions from baboons (Papio anubis).

2022-06-15 | GSE202729 | GEO

microRNA profiling of multiple myeloma bone marrow

Project description:Bone marrow microenvironment in MM contains a unique miR signature, which is partially present and detectable in the peripheral blood. A subset of miRs (let-7i, miR-106b, miR-15a, and miR16) shows aberrant expression in the precursor lesion of MGUS, while aberrant expression of other miRs (let-7a, miR-15a/b, miR-19b, miR-20a, miR-21, miR-223, and miR-361) is associated with cell proliferation and disease progression. miRNA profiling was performed using Agilent miRNA array platforms with RNAs isolated from the bone marrow supernatant of multiple myeloma.

2016-07-01 | E-GEOD-49261 | biostudies-arrayexpress

The gene expression profiles of human bone marrow stromal cells derived from multiple myeloma patients

Project description:Bone marrow stromal cells (BMSCs) and their exosomes are a promising area of cancer therapy. Multiple myeloma (MM) is refractory hematologic malignancy. Bone marrow stromal cells (BMSCs) interact with MM cells in the bone marrow (BM), and also create a permissive microenvironment for MM cell growth and survival. Recent evidence indicated that exosome-mediated MM cell-BMSC communication plays an important role in the MM microenvironment. In this study, we investigated the biological property of the exosomes and exosomal miRNAs derived from BMSCs, aiming to establish the emerging strategies to target MM microenvironment to prevent tumor growth and spread.

2018-07-14 | GSE108915 | GEO

Expression profiling in exosomal miRNAs of human bone marrow stromal cells derived from multiple myeloma patients

2018-06-08 | GSE110271 | GEO

Expression profiling in cellular miRNAs of human bone marrow stromal cells derived from multiple myeloma patients

Project description:Bone marrow stromal cells (BMSCs) and their exosomes are a promising area of cancer therapy. Multiple myeloma (MM) is a refractory hematologic malignancy. Bone marrow stromal cells (BMSCs) interact with MM cells in the bone marrow (BM), and also create a permissive microenvironment for MM cell growth and survival. Recent evidence indicated that exosome-mediated MM cell-BMSC communication plays an important role in the MM microenvironment. In this study, we investigated the biological property of the exosomes and exosomal miRNAs derived from BMSCs, aiming to establish the emerging strategies to target MM microenvironment to prevent tumor growth and spread.

2018-06-08 | GSE110238 | GEO

A window into disease: Protein signatures of remodeled airways in transplanted lungs with Bronchiolitis Obliterans Syndrome

Project description:Background: Bronchiolitis obliterans syndrome (BOS), the most common form of chronic lung allograft dysfunction (CLAD), is the major limitation to long-term survival after lung transplantation. The patho-anatomical correlate is progressive, fibrotic occlusion of the small airways, so-called obliterative bronchiolitis (OB) –lesions, ultimately leading to organ failure. The molecular composition of these lesions is unknown. Methods: By combining laser-capture microdissection (LCM) and optimized sample preparation protocols for mass spectrometry (MS) we analyzed end-stage OB-lesions identified in explanted lungs from four end-stage BOS patients. Immunohistochemistry and immunofluorescence were used to follow selected proteins of interest on the tissue level. Results: We established protein signatures for in total 15 OB-lesions. A set of 12 proteins identified in all lesions included both distinct structural proteins (collagen type IV and VI) and cellular components (actins, vimentin, tryptase). Each respective lesion exhibited a unique composition of proteins (on average n=66), thereby mirroring the histomorphological variation of the lesions. Conclusions: Even though being distinct and focal pathologic events, OB-lesions showed considerable variations in their protein content, most likely reflecting different disease pathways. Combining spatial information and advanced protein identification, this study provides molecular and morphological insights essential for a better understanding of the development of chronic rejection after lung transplantation.

2021-05-19 | PXD014171 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data