Methods for highly multiplexed RNA imaging are limited in spatial resolution, and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to mouse brain, yielding readout of thousands of genes, including splice variants and novel transcripts. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in neurons of the mouse hippocampus, revealing patterns across multiple cell types; layer-specific cell types across mouse visual cortex; and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus ExSeq enables highly multiplexed mapping of RNAs, from nanoscale to system scale.
Summary: In situ sequencing of physically expanded specimens enables multiplexed mapping of RNAs at nanoscale, subcellular resolution.
Discovery: The Rosetta team in Nature Genetics have demonstrated that the amino acid transporter SLC7A5 is required for efficient growth of KRAS-mutant colorectal cancer (CRC). SLC7A5 mediates the transmembrane trafficking of glutamine in exchange for essential amino acids that sustain cell growth, also referred to as an antiporter* in the paper, and has been shown to be critical for tumour development in early and late-stage mouse models of CRC.
Methods: This was achieved using a combination of approaches, including 3D cell culture (organoids), the generation of genetically engineered mouse models (GEMMs) [early and late stage carcinoma] and the analysis of human CRC samples.
*An antiporter (also called exchanger or counter-transporter) is a cotransporter and integral membrane protein involved in secondary active transport of two or more different molecules or ions across a phospholipid membrane such as the plasma membrane in opposite directions, one into the cell and one out of the cell.
We aimed to assess contralateral breast cancer (CBC) risk in patients with ductal carcinoma in situ (DCIS) compared with invasive breast cancer (BC). Women diagnosed with DCIS (N = 28,003) or stage I–III BC (N = 275,836) between 1989 and 2017 were identified from the nationwide Netherlands Cancer Registry. Cumulative incidences were estimated, accounting for competing risks, and hazard ratios (HRs) for metachronous invasive CBC. To evaluate effects of adjuvant systemic therapy and screening, separate analyses were performed for stage I BC without adjuvant systemic therapy and by mode of first BC detection. Multivariable models including clinico-pathological and treatment data were created to assess CBC risk prediction performance in DCIS patients. The 10-year cumulative incidence of invasive CBC was 4.8% for DCIS patients (CBC = 1334). Invasive CBC risk was higher in DCIS patients compared with invasive BC overall (HR = 1.10, 95% confidence interval (CI) = 1.04–1.17), and lower compared with stage I BC without adjuvant systemic therapy (HR = 0.87; 95% CI = 0.82–0.92). In patients diagnosed ≥2011, the HR for invasive CBC was 1.38 (95% CI = 1.35–1.68) after screen-detected DCIS compared with screen-detected invasive BC, and was 2.14 (95% CI = 1.46–3.13) when not screen-detected. The C-index was 0.52 (95% CI = 0.50–0.54) for invasive CBC prediction in DCIS patients. In conclusion, CBC risks are low overall. DCIS patients had a slightly higher risk of invasive CBC compared with invasive BC, likely explained by the risk-reducing effect of (neo)adjuvant systemic therapy among BC patients. For support of clinical decision making more information is needed to differentiate CBC risks among DCIS patients.
Cancer is driven by genomic mutations in ‘cancer driver’ genes, which have essential roles in tumor development. These mutations may be caused by exposure to mutagens in the environment or by endogenous DNA-replication errors in tissue stem cells. Recent observations of abundant mutations, including cancer driver mutations, in histologically normal human tissues suggest that mutations alone are not sufficient for tumor development, thus prompting the question of how single mutant cells give rise to neoplasia. In a concept supported by decades-old data from mouse tumor models, non-mutagenic tumor-promoting agents have been posited to activate the proliferation of dormant mutated cells, thus generating actively growing lesions, with the promotion stage as the rate-limiting step in tumor formation. Non-mutagenic promoting agents, either endogenous or environmental, may therefore have a more important role in human cancer etiology than previously thought.
Background: Performing a statistical test requires a null hypothesis. In cancer genomics, a key challenge is the fast generation of accurate somatic mutational landscapes that can be used as a realistic null hypothesis for making biological discoveries.
Results: Here we present SigProfilerSimulator, a powerful tool that is capable of simulating the mutational landscapes of thousands of cancer genomes at different resolutions within seconds. Applying SigProfilerSimulator to 2144 whole-genome sequenced cancers reveals: (i) that most doublet base substitutions are not due to two adjacent single base substitutions but likely occur as single genomic events; (ii) that an extended sequencing context of ± 2 bp is required to more completely capture the patterns of substitution mutational signatures in human cancer; (iii) information on false-positive discovery rate of commonly used bioinformatics tools for detecting driver genes.
Conclusions: SigProfilerSimulator’s breadth of features allows one to construct a tailored null hypothesis and use it for evaluating the accuracy of other bioinformatics tools or for downstream statistical analysis for biological discoveries.