Discovery of synthetic lethal and tumor suppressive paralog pairs in the human genome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA737515 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14810500.fastq.gz | Fastqsanger.gz | |||
| SRR14810501.fastq.gz | Fastqsanger.gz | |||
| SRR14810502.fastq.gz | Fastqsanger.gz | |||
| SRR14810503.fastq.gz | Fastqsanger.gz | |||
| SRR14810504.fastq.gz | Fastqsanger.gz |
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Project description:CRISPR knockout screens have accelerated the discovery of important cancer genetic dependencies. However, traditional CRISPR-Cas9 screens are limited in their ability to assay the function of redundant or duplicated genes. Paralogs in multi-gene families constitute two-thirds of the protein-coding genome, so this blind spot is the rule, not the exception. To overcome the limitations of single gene CRISPR knockout screens, we developed paired guide RNAs for Paralog gENetic interaction mapping (pgPEN), a pooled CRISPR/Cas9 approach which targets over a thousand duplicated human paralogs in single knockout and double knockout configurations. We applied pgPEN to two cell lineages and discovered that over 10% of human paralogs exhibit synthetic lethality in at least one cellular context. We recovered known synthetic lethal paralogs such as MAP2K1/MAP2K2, important drug targets such as CDK4/CDK6, and numerous other synthetic lethal pairs such as CCNL1/CCNL2. In addition, we identified ten tumor suppressive paralog pairs whose compound loss promotes cell growth. These findings identify a large number of previously unidentified essential gene families and nominate new druggable targets for oncology drug discovery.
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Project description:CRISPR screens have accelerated the discovery of important cancer vulnerabilities. However, single-gene knockout phenotypes can be masked by redundancy among related genes. Paralogs constitute two-thirds of the human protein-coding genome, so existing methods are likely inadequate for assaying a large portion of gene function. Here, we develop paired guide RNAs for paralog genetic interaction mapping (pgPEN), a pooled CRISPR-Cas9 single- and double-knockout approach targeting more than 2,000 human paralogs. We apply pgPEN to two cell types and discover that 12% of human paralogs exhibit synthetic lethality in at least one context. We recover known synthetic lethal paralogs MEK1/MEK2, important drug targets CDK4/CDK6, and other synthetic lethal pairs including CCNL1/CCNL2. Additionally, we identify ten tumor suppressor paralog pairs whose compound loss promotes cell proliferation. These findings nominate drug targets and suggest that paralog genetic interactions could shape the landscape of positive and negative selection in cancer.
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Project description:Studying the evolution of binding preferences for 30 paralog TF pairs in S.cerevisiae
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Project description:Paralogs often exhibit functional redundancy, allowing them to effectively compensate for each other's loss. However, this buffering mechanism is frequently disrupted in cancer, exposing unique paralog-specific vulnerabilities. Here, we identify a selective dependency on the splicing factor TRA2A. We find that TRA2A and its paralog TRA2B are synthetic lethal partners that function as widespread and largely redundant activators of both alternative and constitutive splicing. While loss of TRA2A alone is typically neutral due to compensation by TRA2B, we discover that a subset of cancer cell lines are highly TRA2A-dependent. Upon TRA2A depletion, these cell lines exhibit a lack of paralog buffering specifically on shared splicing targets, leading to defects in mitosis and cell death. Notably, TRA2B overexpression rescues both the aberrant splicing and lethality associated with TRA2A loss, indicating that paralog compensation is dosage-sensitive. Together, these findings reveal a complex dosage-dependent relationship between paralogous splicing factors, and highlight how dysfunctional paralog buffering can create a selective dependency in cancer.
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Project description:This project aimed to identify a specific target for chromosome 8p deletions. Using large-scale functional-genomic screening data of over 527 well-characterized cancer cell lines. We were able to identify the dependency of SLC25A28 (Mitoferrin-2, MFRN2), a mitochondrial iron transporter, in chromosome 8p deleted cancer cell lines. Interestingly, we found that SLC25A37 (Mitoferrin-1, MFRN1), the paralog of MFRN2, resides on chromosome 8p and is frequently deleted in liver cancer. We found a strong correlation between the cellular dependency on MFRN2 and the MFRN1 expression levels, possibly explaining why MFRN2 is a synthetic lethal target for 8p deletions. Our study discovered MFRN2 as a target for a therapeutic strategy in chromosome 8p deleted cancer specimens. Further, it revealed MFRN1 as a biomarker that predicts the response to MFRN2-directed therapy.
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Project description:Emerging immunotherapies such as immune checkpoint blockade (ICB) and chimeric antigen receptor T-cell (CAR-T) therapy have revolutionized cancer treatment and have improved the survival of patients with multiple cancer types. Despite this success many patients are unresponsive to these treatments or relapse following treatment. CRISPR activation and knockout (KO) screens have been used to identify novel single gene targets that can enhance effector T cell function and promote immune cell targeting and eradication of tumors. However, cancer cells often employ multiple genes to promote an immunosuppressive pathway and thus modulating individual genes often has a limited effect. Paralogs are genes that originate from common ancestors and retain similar functions. They often have complex effects on a particular phenotype depending on factors like gene family similarity, each individual gene's expression and the physiological or pathological context. Some paralogs exhibit synthetic lethal interactions in cancer cell survival; however, a thorough investigation of paralog pairs that could enhance the efficacy of cancer immunotherapy is lacking. Here we introduce a sensitive computational approach that uses sgRNA sets enrichment analysis to identify cancer-intrinsic paralog pairs which have the potential to synergistically enhance T cell-mediated tumor destruction. We have further developed an ensemble learning model that uses an XGBoost classifier and incorporates features such as gene characteristics, sequence and structural similarities, protein-protein interaction (PPI) networks, and gene coevolution data to predict paralog pairs that are likely to enhance immunotherapy efficacy. We experimentally validated the functional significance of these predicted paralog pairs using double knockout (DKO) of identified paralog gene pairs as compared to single gene knockouts (SKOs). These data and analyses collectively provide a sensitive approach to identify previously undetected paralog pairs that can enhance cancer immunotherapy even when individual genes within the pair has a limited effect.
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Project description:Gene duplication enables the emergence of new functions by lowering the general evolutionary pressure. Previous studies have highlighted the role of specific paralog genes during cell differentiation, e.g., in chromatin remodeling complexes. It remains unexplored whether similar mechanisms extend to other biological functions and whether the regulation of paralog genes is conserved across species. Here, we analyze the expression of paralogs across human tissues, during development and neuronal differentiation in fish, rodents and humans. While ~80% of paralog genes are co-regulated, a subset of paralogs shows divergent expression profiles, contributing to variability of protein complexes. We identify 78 substitutions of paralog pairs that occur during neuronal differentiation and are conserved across species. Among these, we highlight a substitution between the paralogs Sec23a and Sec23b subunits of the COPII complex. Altering the ratio between these two genes via RNAi-mediated knockdown is sufficient to influence the differentiation of immature neuron. We propose that remodeling of the vesicular transport system via paralog substitutions is an evolutionary conserved mechanism enabling neuronal differentiation.
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Project description:Gene duplication enables the emergence of new functions by lowering the general evolutionary pressure. Previous studies have highlighted the role of specific paralog genes during cell differentiation, e.g., in chromatin remodeling complexes. It remains unexplored whether similar mechanisms extend to other biological functions and whether the regulation of paralog genes is conserved across species. Here, we analyze the expression of paralogs across human tissues, during development and neuronal differentiation in fish, rodents and humans. While ~80% of paralog genes are co-regulated, a subset of paralogs shows divergent expression profiles, contributing to variability of protein complexes. We identify 78 substitutions of paralog eggNOG pairs that occur during neuronal differentiation and are conserved across species. Among these, we highlight a substitution between the paralogs Sec23a and Sec23b subunits of the COPII complex. Altering the ratio between these two genes via silencing-RNA knockdown was able to influence neuronal differentiation in different ways. We propose that remodeling of the vesicular transport system via paralog substitutions is an evolutionary conserved mechanism enabling neuronal differentiation.
2022-03-07 | PXD027195 | Pride