Simon Schallenberg

An ultrasensitive spatial tissue proteomics workflow exceeding 100 proteomes per day

The paper develops an ultrasensitive spatial tissue proteomics workflow capable of processing over 100 proteomes per day, demonstrating its utility in analyzing rare cancers.

Unravelling drug resistant proteotypes through phenotype-resolved proteomics of single-cell derived colonies

This paper introduces PhenoSCoP, a framework that uses single-cell proteomics and microscopy to identify drug-resistant proteotypes in cancer cells and their progression in patient tissues.

OpenDVP: An experimental and computational framework for community-empowered deep visual proteomics

The paper introduces openDVP, a framework for deep visual proteomics, demonstrating its application in three tissue studies to integrate spatial single-cell phenotypes with proteomic data.

A quantitative tumor-wide analysis of morphological heterogeneity of colorectal adenocarcinoma

The paper quantitatively analyzes morphological heterogeneity in colorectal adenocarcinoma, finding that specific morphotypes correlate with clinical outcomes.

nanoPhos enables ultra-sensitive and cell-type resolved spatial phosphoproteomics

nanoPhos improves phosphoproteomics sensitivity and enables cell-type resolved spatial analysis of mouse brain tissue.

Open-ST: High-resolution spatial transcriptomics in 3D

Open-ST provides a high-resolution, 3D spatial transcriptomics method to study tissue molecular organization, revealing spatially contiguous structures and biomarkers in tumors and lymph nodes.

High-resolution molecular atlas of a lung tumor in 3D

This paper presents a 3D spatial atlas of a human lung carcinoma, revealing tumor microenvironment niches and their associated immune interactions and survival outcomes.