Breast cancer remains a leading cause of cancer-related mortality in women, driven in large part by its cellular heterogeneity. 1 Breast cancer stem cells play a crucial role in tumor initiation, metastasis, therapeutic resistance, and recurrence, yet their dynamic behavior remains poorly understood. Conventional omics approaches have advanced our knowledge but are limited in capturing rapid, transient cellular processes that underlie functional heterogeneity. To overcome these limitations, ESPRESSO 2 (a novel spatiotemporal omics platform) enables high-dimensional, single-cell analyses by mapping organelle landscapes rather than static gene or protein expression. Despite its promise, current implementations face critical barriers, including low throughput and optical constraints, which limit its applicability in complex biological and clinical contexts. This project proposes a super-resolution strategy based on structured illumination to achieve rapid, aberration-free, 3 and volumetric imaging. Integrated hyperspectral encoding 4,5 allows simultaneous detection of multiple labeled organelles, generating high-content data sets for ESPRESSO analyses. This integration represents a major technological advancement, enabling unprecedented single-cell, spatiotemporal resolution of multiplexed organelle function. Beyond its immediate biological applications, this project delivers a broadly accessible toolkit comprising high-resolution instrumentation and computational pipelines for single-cell analysis targeting the functional heterogeneity that drives cancer progression and dynamically evolving cellular processes (metabolic plasticity, stress response, among others). 1 Pasha et al., (2021). Nat. Cancer . 2 Scipioni et al., (2025). Nat. Methods . 3 Fersini et al., (2025). Biomed. Opt. Express . 4 Scipioni et al., (2021). Nat. Methods . 5 Scipioni et al., (2025). BioRxiv .
Francesco Fersini (Sun,) studied this question.