Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma

Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies (Couturier et al., 2020; Neftel et al., 2019; Richards et al., 2021). The source of the dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas in-depth by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapt to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with re..., The dataset was collected using: 1) 10X Visium spatila gene expression kit: And all the instructions for Tissue Optimization and Library preparation were followed according to manufacturer’s protocol. Data were analyzed and quality controlled by the cell ranger pipeline provided by 10X. For further analysis we developed a framework for spatial data analysis. The cell ranger output can be imported into SPATA by either a direct import function (SPATA:: initiateSpataObject_10X) or manually imported using count matrix and barcode-coordinate matrix as well the H&E staining.2) MALDI-FTICR-MSI: Tissue preparation steps for MALDI imaging mass spectrometry (MALDI-MSI) analysis was performed as previously described (Aichler et al., 2017; Sun et al., 2018). We imported the files into R using the readImzML function from the cardinal package(Bemis et al., 2015). We reshaped the pixel data matrix into an intensity matrix and a matrix of coordinates for each tumor separately. We fil..., , # Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma

#### Author Information

* **Name**: Dr. Vidhya M. Ravi\
**Institution**: University Clinic of Freiburg\
**Email**: [[e-mail]](mailto:[e-mail])
* **Name**: PD. Dr. Dieter Henrik Heiland\
**Institution**: University Clinic of Freiburg\
**Email**: [[e-mail]](mailto:[e-mail])

#### Date of Data Collection

2020–2021

#### Geographic Location of Data Collection

Freiburg, Germany

#### Recommended Citation for This Dataset

Ravi, Vidhya; Will, Paulina; Kueckelhaus, Jan et al. (2022). Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma [Dataset]. Dryad. [https://doi.org/10.5061/dryad.h70rxwdmj](https://doi.org/10.5061/dryad.h70rxwdmj)

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## 1. Spatial Transcriptomics (10X Visium)

**File/folder name**: `10XVISIUM.zip`
...,