Visium spatial transcriptomics, single-nucleus RNA sequencing and co-detection by indexing are used to identify distinct spatial microregions in tumours and their microenvironment across six diverse solid cancer types.

Using a multipurpose, single-cell CRISPR platform, we demonstrate precise timing of tissue-specific cell expansion during mouse embryonic development, unconventional developmental relationships between cell types, new epithelial progenitor states and insights into precancer initiation by leveraging genetic histories.

Colorectal cancer metastasis involves dramatic plasticity and loss of PROX1-mediated repression of non-intestinal lineages.

Single-nucleus and single-cell RNA sequencing plus spatial profiling with four methods of core biopsies from 60 patients with metastatic breast cancer reveal patient-specific gene expression programs of breast cancer metastases that are maintained across time, site of metastasis and spatial profiling method, with spatial phenotypes correlating with microenvironmental features.

Ding and colleagues use bulk, single-cell and single-nucleus multi-omics together with spatial transcriptomics and multiplex imaging of clinical tumor samples to characterize gene expression and chromatin accessibility of breast cancer lineages.

In this work, we demonstrate the transcriptional networks that link breast cancer subtypes and their cells of origin, and how transcriptional signatures differ between benign cells and cancer.

Snyder and colleagues show global loss of promoter–enhancer connectivity during early colorectal carcinogenesis and the dependency of gene dysregulation during this process on the baseline of promoter–enhancer interaction in normal colonic epithelium.

The early molecular events driving cancer initiation remain elusive, hampering prognostic accuracy. A comparative analysis of 3D genomics data from all stages of colon malignant transformation now reveals that altered connectivity of gene promoters with cognate enhancers is both predictive of and rate-limiting in neoplasia.

Snyder and colleagues present a comprehensive multiomic atlas of normal mucosal, benign polyps and dysplastic polyps from six persons with familial adenomatous polyposis, comprising transcriptomic, proteomic, metabolomic and lipidomic datasets.

The current wave of papers from the Human Tumor Atlas Network represents a concerted effort to create multimodal atlases of tumours and their microenvironments, in various sites of origin. As well as the atlases, the initiative has generated a wealth of fresh insights into tumour biology, along with innovative tools to analyse these atlases in depth.

This work presents CalicoST for inferring allele-specific copy numbers and reconstructing spatial tumor evolution by using spatial transcriptomics data.

Microscopy artifacts and tissue imperfections interfere with single-cell analysis. CyLinter software offers quality control for high-plex tissue profiling by removing artifactual cells, thereby facilitating accuracy of biological interpretation.

CelloType is an end-to-end method for spatial omics data analysis that uses a transformer-based deep neural network for concurrent object detection, segmentation and classification and performs with high accuracy on diverse datasets.

This study proposes a computational panel reduction method for CyCIF, leveraging 9 markers to impute information from 25, enhancing speed, content, and reducing costs.

MILWRM is a Python package that can perform tissue domain detection on spatial transcriptomics (ST) and multiplex immunofluorescence (mIF) data across multiple specimens.