Massively parallel phenotyping of coding variants in cancer with Perturb-seq

Ursu, Oana; Neal, James T.; Shea, Emily; Thakore, Pratiksha I.; Jerby‐Arnon, Livnat; Nguyễn, Lan; Diaz, Celeste; Bauman, Julia; Mosaad, Mariam Mounir; Fagre, Christian; Lo, April; McSharry, Maria; Giacomelli, Andrew O.; Ly, Seav Huong; Rozenblatt-Rosen, Orit; Hahn, William C.; Aguirre, Andrew J.; Berger, Alice H.; Regev, Aviv; Boehm, Jesse S.

doi:10.1038/s41587-021-01160-7

Cited by 66 publications

(68 citation statements)

References 82 publications

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“…, 2021 ). While this has been explored at the bulk level, our results and previous work based on scRNAseq ( Ursu et al. , 2022 ) indicate that this type of analysis could be extended to understand multiomics connections at the single-cell level.…”

Section: Discussionmentioning

confidence: 86%

“…Image-based profiling inherently offers single-cell resolution while being the lowest cost even among bulk profiling methods. We investigated whether single-cell morphological profiling might provide insights into the heterogeneity of allele subpopulations or other phenotypic mechanisms that cannot be observed using bulk-level data ( Ursu et al. , 2022 ).…”

Section: Resultsmentioning

confidence: 99%

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Cell Painting predicts impact of lung cancer variants

Caicedo

Arevalo

Piccioni

et al. 2022

MBoC

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Most variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding gene is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance (VUS) as impactful vs. neutral in an approach called expression-based variant-impact phenotyping (eVIP). We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cell's image, we found that cell morphological profiling (cmVIP) can predict variants’ functional impact and, particularly at the single-cell level, reveals biological insights into variants which can be explored in our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene-specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.

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Section: Discussionmentioning

confidence: 86%

Section: Resultsmentioning

confidence: 99%

Cell Painting predicts impact of lung cancer variants

Caicedo

Arevalo

Piccioni

et al. 2022

MBoC

Self Cite

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“…These initial studies screened tens of genes and assessed their trans-effect on the transcriptome of thousands of cells in a single experiment. Since these pioneering demonstrations, the technology has been optimised and adapted, for example, to improve the efficiency, 142 to study the effect of upregulation using CRISPR-activation, 143 to read out the effect of perturbations on the epigenome 144 or proteome 145 to dissect the function of protein domains (sc-Tiling), 146 as well as to elucidate gene functions 147 and gene regulatory networks related to development, diseases 148 or DNA-chromatin structure. 149 Xie et al demonstrated that this approach can be used to measure the function of enhancers (figure 4D,E).…”

Section: Reviewmentioning

confidence: 99%

“…However, early demonstrations to profile single nucleotide variants do look promising 152. Transduction-based overexpression instead of gene-editing has also been used as a method to overcome the limitations for functional annotation of variants 147. As the gene-editing technologies improve in efficiency, resolution, accuracy and specificity,153 154 it is increasingly likely that such technologies currently restricted to research will find direct applications in Personal Genomics for high-throughput experimental screening of variants identified in an individual.…”

Section: What Can We Do With Sc-seq Technologies In Human Genetics?mentioning

confidence: 99%

The role of single-cell genomics in human genetics

2022

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Single-cell sequencing is a powerful approach that can detect genetic alterations and their phenotypic consequences in the context of human development, with cellular resolution. Humans start out as single-cell zygotes and undergo fission and differentiation to develop into multicellular organisms. Before fertilisation and during development, the cellular genome acquires hundreds of mutations that propagate down the cell lineage. Whether germline or somatic in nature, some of these mutations may have significant genotypic impact and lead to diseased cellular phenotypes, either systemically or confined to a tissue. Single-cell sequencing enables the detection and monitoring of the genotype and the consequent molecular phenotypes at a cellular resolution. It offers powerful tools to compare the cellular lineage between ‘normal’ and ‘diseased’ conditions and to establish genotype-phenotype relationships. By preserving cellular heterogeneity, single-cell sequencing, unlike bulk-sequencing, allows the detection of even small, diseased subpopulations of cells within an otherwise normal tissue. Indeed, the characterisation of biopsies with cellular resolution can provide a mechanistic view of the disease. While single-cell approaches are currently used mainly in basic research, it can be expected that applications of these technologies in the clinic may aid the detection, diagnosis and eventually the treatment of rare genetic diseases as well as cancer. This review article provides an overview of the single-cell sequencing technologies in the context of human genetics, with an aim to empower clinicians to understand and interpret the single-cell sequencing data and analyses. We discuss the state-of-the-art experimental and analytical workflows and highlight current challenges/limitations. Notably, we focus on two prospective applications of the technology in human genetics, namely the annotation of the non-coding genome using single-cell functional genomics and the use of single-cell sequencing data for in silico variant prioritisation.

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“…A recent effort has expanded Perturb-seq to the genome-wide level for the first time [ 84 ]. Besides CRISPR-based gene perturbations, scRNA-seq can also be combined with the pooled ORF overexpression to enable screening for cell reprogramming [ 85 , 86 ] or coding variants of oncogenes [ 87 ]. Compound perturbation experiments, on the other hand, would require cells to be treated in the arrayed format rather than the pooled one.…”

Section: Emerging Single-cell Technologies and Future Perspectivesmentioning

confidence: 99%

Transcriptional Regulation of the Hippo Pathway: Current Understanding and Insights from Single-Cell Technologies

Paul¹,

Xie²,

Yao³

et al. 2022

Cells

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The Hippo pathway regulates tissue homeostasis in normal development and drives oncogenic processes. In this review, we extensively discuss how YAP/TAZ/TEAD cooperate with other master transcription factors and epigenetic cofactors to orchestrate a broad spectrum of transcriptional responses. Even though these responses are often context- and lineage-specific, we do not have a good understanding of how such precise and specific transcriptional control is achieved—whether they are driven by differences in TEAD paralogs, or recruitment of cofactors to tissue-specific enhancers. We believe that emerging single-cell technologies would enable a granular understanding of how the Hippo pathway influences cell fate and drives oncogenic processes, ultimately allowing us to design better pharmacological agents against TEADs and identify robust pharmacodynamics markers of Hippo pathway inhibition.

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Massively parallel phenotyping of coding variants in cancer with Perturb-seq

Cited by 66 publications

References 82 publications

Cell Painting predicts impact of lung cancer variants

Cell Painting predicts impact of lung cancer variants

The role of single-cell genomics in human genetics

Transcriptional Regulation of the Hippo Pathway: Current Understanding and Insights from Single-Cell Technologies

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