Identification and characterization of essential genes in the human genome

CRISPR-Cas9 applications in T cells and adoptive T cell therapies

T cell immunity is central to contemporary cancer and autoimmune therapies, encompassing immune checkpoint blockade and adoptive T cell therapies. Their diverse characteristics can be reprogrammed by different immune challenges dependent on antigen stimulation levels, metabolic conditions, and the degree of inflammation. T cell-based therapeutic strategies are gaining widespread adoption in oncology and treating inflammatory conditions. Emerging researches reveal that clustered regularly interspaced palindromic repeats-associated protein 9 (CRISPR-Cas9) genome editing has enabled T cells to be more adaptable to specific microenvironments, opening the door to advanced T cell therapies in preclinical and clinical trials. CRISPR-Cas9 can edit both primary T cells and engineered T cells, including CAR-T and TCR-T, in vivo and in vitro to regulate T cell differentiation and activation states. This review first provides a comprehensive summary of the role of CRISPR-Cas9 in T cells and its applications in preclinical and clinical studies for T cell-based therapies. We also explore the application of CRISPR screen high-throughput technology in editing T cells and anticipate the current limitations of CRISPR-Cas9, including off-target effects and delivery challenges, and envisioned improvements in related technologies for disease screening, diagnosis, and treatment.

Ancestry-specific high-risk gene variant profiling unmasks diabetes-associated genes

How ancestry-associated genetic variance affects disparities in the risk of polygenic diseases and influences the identification of disease-associated genes warrants a deeper understanding. We hypothesized that the discovery of genes associated with polygenic diseases may be limited by the overreliance on single-nucleotide polymorphism (SNP)-based genomic investigation, as most significant variants identified in genome-wide SNP association studies map to introns and intergenic regions of the genome. To overcome such potential limitations, we developed a gene-constrained, function-based analytical method centered on high-risk variants (hrV) that encode frameshifts, stopgains or splice site disruption. We analyzed the total number of hrV per gene in populations of different ancestry, representing a total of 185 934 subjects. Using this analysis, we developed a quantitative index of hrV (hrVI) across 20 428 genes within each population. We then applied hrVI analysis to the discovery of genes associated with type 2 diabetes mellitus (T2DM), a polygenic disease with ancestry-related disparity. HrVI profiling and gene-to-gene comparisons of ancestry-specific hrV between the case (20 781 subjects) and control (24 440 subjects) populations in the T2DM national repository identified 57 genes associated with T2DM, 40 of which were discoverable only by ancestry-specific analysis. These results illustrate how a function-based, ancestry-specific analysis of genetic variations can accelerate the identification of genes associated with polygenic diseases. Besides T2DM, such analysis may facilitate our understanding of the genetic basis for other polygenic diseases that are also greatly influenced by environmental and behavioral factors, such as obesity, hypertension and Alzheimer's disease.

Tumor immune evasion: insights from CRISPR screens and future directions

Despite the clinical success of cancer immunotherapies including immune checkpoint blockade and adoptive cellular therapies across a variety of cancer types, many patients do not respond or ultimately relapse; however, the molecular underpinnings of this are not fully understood. Thus, a system-level understating of the routes to tumor immune evasion is required to inform the design of the next generation of immunotherapy approaches. CRISPR screening approaches have proved extremely powerful in identifying genes that promote tumor immune evasion or sensitize tumor cells to destruction by the immune system. These large-scale efforts have brought to light decades worth of fundamental immunology and have uncovered the key immune-evasion pathways subverted in cancers in an acquired manner in patients receiving immune-modulatory therapies. The comprehensive discovery of the main pathways involved in immune evasion has spurred the development and application of novel immune therapies to target this process. Although successful, conventional CRISPR screening approaches are hampered by a number of limitations, which obfuscate a complete understanding of the precise molecular regulation of immune evasion in cancer. Here, we provide a perspective on screening approaches to interrogate tumor-lymphocyte interactions and their limitations, and discuss further development of technologies to improve such approaches and discovery capability.

Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning

Transcriptome engineering applications in living cells with RNA-targeting CRISPR effectors depend on accurate prediction of on-target activity and off-target avoidance. Here we design and test ~200,000 RfxCas13d guide RNAs targeting essential genes in human cells with systematically designed mismatches and insertions and deletions (indels). We find that mismatches and indels have a position- and context-dependent impact on Cas13d activity, and mismatches that result in G-U wobble pairings are better tolerated than other single-base mismatches. Using this large-scale dataset, we train a convolutional neural network that we term targeted inhibition of gene expression via gRNA design (TIGER) to predict efficacy from guide sequence and context. TIGER outperforms the existing models at predicting on-target and off-target activity on our dataset and published datasets. We show that TIGER scoring combined with specific mismatches yields the first general framework to modulate transcript expression, enabling the use of RNA-targeting CRISPRs to precisely control gene dosage.

Genome-scale pan-cancer interrogation of lncRNA dependencies using CasRx

Although long noncoding RNAs (lncRNAs) dominate the transcriptome, their functions are largely unexplored. The extensive overlap of lncRNAs with coding and regulatory sequences restricts their systematic interrogation by DNA-directed perturbation. Here we developed genome-scale lncRNA transcriptome screening using Cas13d/CasRx. We show that RNA targeting overcomes limitations inherent to other screening methods, thereby considerably expanding the explorable space of the lncRNAome. By evolving the screening system toward pan-cancer applicability, it supports molecular and phenotypic data integration to contextualize screening hits or infer lncRNA function. We thereby addressed challenges posed by the enormous transcriptome size and tissue specificity through a size-reduced multiplexed gRNA library termed Albarossa, targeting 24,171 lncRNA genes. Its rational design incorporates target prioritization based on expression, evolutionary conservation and tissue specificity, thereby reconciling high discovery power and pan-cancer representation with scalable experimental throughput. Applied across entities, the screening platform identified numerous context-specific and common essential lncRNAs. Our work sets the stage for systematic exploration of lncRNA biology in health and disease.

Neutrophils actively swell to potentiate rapid migration

While the involvement of actin polymerization in cell migration is well-established, much less is known about the role of transmembrane water flow in cell motility. Here, we investigate the role of water influx in a prototypical migrating cell, the neutrophil, which undergoes rapid, directed movement to sites of injury and infection. Chemoattractant exposure both increases cell volume and potentiates migration, but the causal link between these processes is not known. We combine single cell volume measurements and a genome-wide CRISPR screen to identify the regulators of chemoattractant-induced neutrophil swelling, including NHE1, AE2, PI3K-gamma, and CA2. Through NHE1 inhibition in primary human neutrophils, we show that cell swelling is both necessary and sufficient for the potentiation of migration following chemoattractant stimulation. Our data demonstrate that chemoattractant-driven cell swelling complements cytoskeletal rearrangements to enhance migration speed.

Precise prediction of phase-separation key residues by machine learning

Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme. In vivo and in vitro validations demonstrate that truncating just 6 key residues in GATA3 disrupts phase separation, enhancing tumor cell migration and inhibiting growth. Glycine and its motifs are enriched in spacer and key residues, as revealed by our comprehensive analysis. PSPHunter identifies nearly 80% of disease-associated phase-separating proteins, with frequent mutated pathological residues like glycine and proline often residing in these key residues. PSPHunter thus emerges as a crucial tool to uncover key residues, facilitating insights into phase separation mechanisms governing transcriptional control, cell fate transitions, and disease development.

Precise large-fragment deletions in mammalian cells and mice generated by dCas9-controlled CRISPR/Cas3

Currently, the Cas9 and Cas12a systems are widely used for genome editing, but their ability to precisely generate large chromosome fragment deletions is limited. Type I-E CRISPR mediates broad and unidirectional DNA degradation, but controlling the size of Cas3-mediated DNA deletions has proven elusive thus far. Here, we demonstrate that the endonuclease deactivation of Cas9 (dCas9) can precisely control Cas3-mediated large-fragment deletions in mammalian cells. In addition, we report the elimination of the Y chromosome and precise retention of the Sry gene in mice using CRISPR/Cas3 and dCas9-controlled CRISPR/Cas3, respectively. In conclusion, dCas9-controlled CRISPR/Cas3-mediated precise large-fragment deletion provides an approach for establishing animal models by chromosome elimination. This method also holds promise as a potential therapeutic strategy for treating fragment mutations or human aneuploidy diseases that involve additional chromosomes.

Discovery, structure, mechanisms, and evolution of protein-only RNase P enzymes

The endoribonuclease RNase P is responsible for tRNA 5' maturation in all domains of life. A unique feature of RNase P is the variety of enzyme architectures, ranging from dual- to multi-subunit ribonucleoprotein forms with catalytic RNA subunits to protein-only enzymes, the latter occurring as single- or multi-subunit forms or homo-oligomeric assemblies. The protein-only enzymes evolved twice: a eukaryal protein-only RNase P termed PRORP and a bacterial/archaeal variant termed homolog of Aquifex RNase P (HARP); the latter replaced the RNA-based enzyme in a small group of thermophilic bacteria but otherwise coexists with the ribonucleoprotein enzyme in a few other bacteria as well as in those archaea that also encode a HARP. Here we summarize the history of the discovery of protein-only RNase P enzymes and review the state of knowledge on structure and function of bacterial HARPs and eukaryal PRORPs, including human mitochondrial RNase P as a paradigm of multi-subunit PRORPs. We also describe the phylogenetic distribution and evolution of PRORPs, as well as possible reasons for the spread of PRORPs in the eukaryal tree and for the recruitment of two additional protein subunits to metazoan mitochondrial PRORP. We outline potential applications of PRORPs in plant biotechnology and address diseases associated with mutations in human mitochondrial RNase P genes. Finally, we consider possible causes underlying the displacement of the ancient RNA enzyme by a protein-only enzyme in a small group of bacteria.

Recent advances in genome-scale engineering in Escherichia coli and their applications

Owing to the rapid advancement of genome engineering technologies, the scale of genome engineering has expanded dramatically. Genome editing has progressed from one genomic alteration at a time that could only be employed in few species, to the simultaneous generation of multiple modifications across many genomic loci in numerous species. The development and recent advances in multiplex automated genome engineering (MAGE)-associated technologies and clustered regularly interspaced short palindromic repeats and their associated protein (CRISPR-Cas)-based approaches, together with genome-scale synthesis technologies offer unprecedented opportunities for advancing genome-scale engineering in a broader range. These approaches provide new tools to generate strains with desired phenotypes, understand the complexity of biological systems, and directly evolve a genome with novel features. Here, we review the recent major advances in genome-scale engineering tools developed for Escherichia coli, focusing on their applications in identifying essential genes, genome reduction, recoding, and beyond.

INPP5A phosphatase is a synthetic lethal target in GNAQ and GNA11-mutant melanomas

Activating mutations in GNAQ/GNA11 occur in over 90% of uveal melanomas (UMs), the most lethal melanoma subtype; however, targeting these oncogenes has proven challenging and inhibiting their downstream effectors show limited clinical efficacy. Here, we performed genome-scale CRISPR screens along with computational analyses of cancer dependency and gene expression datasets to identify the inositol-metabolizing phosphatase INPP5A as a selective dependency in GNAQ/11-mutant UM cells in vitro and in vivo. Mutant cells intrinsically produce high levels of the second messenger inositol 1,4,5 trisphosphate (IP3) that accumulate upon suppression of INPP5A, resulting in hyperactivation of IP3-receptor signaling, increased cytosolic calcium and p53-dependent apoptosis. Finally, we show that GNAQ/11-mutant UM cells and patients' tumors exhibit elevated levels of IP4, a biomarker of enhanced IP3 production; these high levels are abolished by GNAQ/11 inhibition and correlate with sensitivity to INPP5A depletion. Our findings uncover INPP5A as a synthetic lethal vulnerability and a potential therapeutic target for GNAQ/11-mutant-driven cancers.

Past, present, and future of CRISPR genome editing technologies

Genome editing has been a transformative force in the life sciences and human medicine, offering unprecedented opportunities to dissect complex biological processes and treat the underlying causes of many genetic diseases. CRISPR-based technologies, with their remarkable efficiency and easy programmability, stand at the forefront of this revolution. In this Review, we discuss the current state of CRISPR gene editing technologies in both research and therapy, highlighting limitations that constrain them and the technological innovations that have been developed in recent years to address them. Additionally, we examine and summarize the current landscape of gene editing applications in the context of human health and therapeutics. Finally, we outline potential future developments that could shape gene editing technologies and their applications in the coming years.

Massively parallel disruption of enhancers active in human neural stem cells

Changes in gene regulation have been linked to the expansion of the human cerebral cortex and to neurodevelopmental disorders, potentially by altering neural progenitor proliferation. However, the effects of genetic variation within regulatory elements on neural progenitors remain obscure. We use sgRNA-Cas9 screens in human neural stem cells (hNSCs) to disrupt 10,674 genes and 26,385 conserved regions in 2,227 enhancers active in the developing human cortex and determine effects on proliferation. Genes with proliferation phenotypes are associated with neurodevelopmental disorders and show biased expression in specific fetal human brain neural progenitor populations. Although enhancer disruptions overall have weaker effects than gene disruptions, we identify enhancer disruptions that severely alter hNSC self-renewal. Disruptions in human accelerated regions, implicated in human brain evolution, also alter proliferation. Integrating proliferation phenotypes with chromatin interactions reveals regulatory relationships between enhancers and their target genes contributing to neurogenesis and potentially to human cortical evolution.

A Potent SOS1 PROTAC Degrader with Synergistic Efficacy in Combination with KRASG12C Inhibitor

AMG510, as the first approved inhibitor for KRASG12C mutation, has shown promising efficacy in nonsmall-cell lung cancer and colorectal cancer harboring KRASG12C mutation. However, the moderate response rate and the rapid emergence of acquired resistance limit the therapeutic potential of AMG510, highlighting the need for the development of combination strategies. Here, we observed the suppression of RAS-MAPK signaling induced by AMG510 was prolonged and enhanced by SOS1 knockdown. Thus, we design, synthesize, and characterize a potent and specific SOS1 degrader 23. Compound 23 showed efficient SOS1 degradation in KRAS-driven cancer cells and achieved significant antiproliferative potency. Importantly, the combination of 23 with AMG510 suppressed RAS signaling feedback activation, showing synergistic effects against KRASG12C mutant cells in vitro and in vivo. Our findings demonstrated that KRASG12C inhibition plus SOS1 degradation as a potential therapeutic strategy to improve antitumor response and overcome acquired resistance to KRASG12C inhibitor.

A Genome Wide CRISPR Proling Approach Identies Mechanisms of Cisplatin Resistance in Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is a lethal disease with poor survival rates, especially for cancers arising in the oral cavity or larynx. Cisplatin is a key chemotherapeutic for HNSCC; however poor survival rates may be partially due to cisplatin resistance observed in some HNSCCs. Here, we examined the utility of genome-wide CRISPR knockout profiling for nominating pivotal mechanisms of cisplatin resistance in HNSCC models.

Methods

We characterized the cisplatin sensitivity of 18 HNSCC cell lines. Next, we used a genome-wide CRISPR/Cas9 library to identify genes involved in cisplatin resistance. We next performed validation assays in the UM-SCC-49 cell line model.

Results

Our data prioritized 207 genes as pivotal for cisplatin resistance in HNSCC, including novel genes VGLL3, CIRHA1, NCOR1, SPANXA1, MAP2K7, ULK1, and CDK16. Gene set enrichment analysis identified several NOTCH family genes comprising the top pathway driving cisplatin resistance, which we then validated using a targeted NOTCH1 knockout model. Interestingly, we noted that HNSCC models with natural NOTCH pathway alterations including single allele mutations and/or frameshift alterations had diverse responses to cisplatin treatment suggesting that complex and multi-faceted mechanisms contribute to cisplatin resistance in HNSCC.

Conclusions

Collectively, our study validates a genome-wide CRISPR/Cas9 approach for the discovery of resistance mechanisms in HNSCC, adds to the growing evidence that NOTCH1 status should be evaluated as a biomarker of cisplatin response and provides a framework for future work aimed at overcoming cisplatin resistance.

Oncoprotein SET-associated transcription factor ZBTB11 triggers lung cancer metastasis

Metastasis is the major cause of lung cancer-related death, but the mechanisms governing lung tumor metastasis remain incompletely elucidated. SE translocation (SET) is overexpressed in lung tumors and correlates with unfavorable prognosis. Here we uncover SET-associated transcription factor, zinc finger and BTB domain-containing protein 11 (ZBTB11), as a prometastatic regulator in lung tumors. SET interacts and collaborates with ZBTB11 to promote lung cancer cell migration and invasion, primarily through SET-ZBTB11 complex-mediated transcriptional activation of matrix metalloproteinase-9 (MMP9). Additionally, by transcriptional repression of proline-rich Gla protein 2 (PRRG2), ZBTB11 links Yes-associated protein 1 (YAP1) activation to drive lung tumor metastasis independently of SET-ZBTB11 complex. Loss of ZBTB11 suppresses distal metastasis in a lung tumor mouse model. Overexpression of ZBTB11 is recapitulated in human metastatic lung tumors and correlates with diminished survival. Our study demonstrates ZBTB11 as a key metastatic regulator and reveals diverse mechanisms by which ZBTB11 modulates lung tumor metastasis.

Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy

Chemical genetic screens are a powerful tool for exploring how cancer cells' response to drugs is shaped by their mutations, yet they lack a molecular view of the contribution of individual genes to the response to exposure. Here, we present sci-Plex-Gene-by-Environment (sci-Plex-GxE), a platform for combined single-cell genetic and chemical screening at scale. We highlight the advantages of large-scale, unbiased screening by defining the contribution of each of 522 human kinases to the response of glioblastoma to different drugs designed to abrogate signaling from the receptor tyrosine kinase pathway. In total, we probed 14,121 gene-by-environment combinations across 1,052,205 single-cell transcriptomes. We identify an expression signature characteristic of compensatory adaptive signaling regulated in a MEK/MAPK-dependent manner. Further analyses aimed at preventing adaptation revealed promising combination therapies, including dual MEK and CDC7/CDK9 or nuclear factor κB (NF-κB) inhibitors, as potent means of preventing transcriptional adaptation of glioblastoma to targeted therapy.

Compromised transcription-mRNA export factor THOC2 causes R-loop accumulation, DNA damage and adverse neurodevelopment

We implicated the X-chromosome THOC2 gene, which encodes the largest subunit of the highly-conserved TREX (Transcription-Export) complex, in a clinically complex neurodevelopmental disorder with intellectual disability as the core phenotype. To study the molecular pathology of this essential eukaryotic gene, we generated a mouse model based on a hypomorphic Thoc2 exon 37-38 deletion variant of a patient with ID, speech delay, hypotonia, and microcephaly. The Thoc2 exon 37-38 deletion male (Thoc2Δ/Y) mice recapitulate the core phenotypes of THOC2 syndrome including smaller size and weight, and significant deficits in spatial learning, working memory and sensorimotor functions. The Thoc2Δ/Y mouse brain development is significantly impacted by compromised THOC2/TREX function resulting in R-loop accumulation, DNA damage and consequent cell death. Overall, we suggest that perturbed R-loop homeostasis, in stem cells and/or differentiated cells in mice and the patient, and DNA damage-associated functional alterations are at the root of THOC2 syndrome.

Multiple Genes Core to ERAD, Macroautophagy and Lysosomal Degradation Pathways Participate in the Proteostasis Response in α1-Antitrypsin Deficiency

BACKGROUND & AIMS

In the classic form of α1-antitrypsin deficiency (ATD), the misfolded α1-antitrypsin Z (ATZ) variant accumulates in the endoplasmic reticulum (ER) of liver cells. A gain-of-function proteotoxic mechanism is responsible for chronic liver disease in a subgroup of homozygotes. Proteostatic response pathways, including conventional endoplasmic reticulum-associated degradation and autophagy, have been proposed as the mechanisms that allow cellular adaptation and presumably protection from the liver disease phenotype. Recent studies have concluded that a distinct lysosomal pathway called endoplasmic reticulum-to-lysosome completely supplants the role of the conventional macroautophagy pathway in degradation of ATZ. Here, we used several state-of-the-art approaches to characterize the proteostatic responses more fully in cellular systems that model ATD.

METHODS

We used clustered regularly interspaced short palindromic repeats (CRISPR)-mediated genome editing coupled to a cell selection step by fluorescence-activated cell sorter to perform screening for proteostasis genes that regulate ATZ accumulation and combined that with selective genome editing in 2 other model systems.

RESULTS

Endoplasmic reticulum-associated degradation genes are key early regulators and multiple autophagy genes, from classic as well as from ER-to-lysosome and other newly described ER-phagy pathways, participate in degradation of ATZ in a manner that is temporally regulated and evolves as ATZ accumulation persists. Time-dependent changes in gene expression are accompanied by specific ultrastructural changes including dilation of the ER, formation of globular inclusions, budding of autophagic vesicles, and alterations in the overall shape and component parts of mitochondria.

CONCLUSIONS

Macroautophagy is a critical component of the proteostasis response to cellular ATZ accumulation and it becomes more important over time as ATZ synthesis continues unabated. Multiple subtypes of macroautophagy and nonautophagic lysosomal degradative pathways are needed to respond to the high concentrations of misfolded protein that characterizes ATD and these pathways are attractive candidates for genetic variants that predispose to the hepatic phenotype.

A review of computational methods for predicting cancer drug response at the single-cell level through integration with bulk RNAseq data

Cancer treatment failure is often attributed to tumor heterogeneity, where diverse malignant cell clones exist within a patient. Despite a growing understanding of heterogeneous tumor cells depicted by single-cell RNA sequencing (scRNA-seq), there is still a gap in the translation of such knowledge into treatment strategies tackling the pervasive issue of therapy resistance. In this review, we survey methods leveraging large-scale drug screens to generate cellular sensitivities to various therapeutics. These methods enable efficient drug screens in scRNA-seq data and serve as the bedrock of drug discovery for specific cancer cell groups. We envision that they will become an indispensable tool for tailoring patient care in the era of heterogeneity-aware precision medicine.

Inhibition of the glutamate-cysteine ligase catalytic subunit with buthionine sulfoximine enhances the cytotoxic effect of doxorubicin and cyclophosphamide in Burkitt lymphoma cells

Burkitt lymphoma (BL) is a highly aggressive lymphoma that mainly affects children and young adults. Chemotherapy is effective in young BL patients but the outcome in adults is less satisfactory. Therefore, there is a need to enhance the cytotoxic effect of drugs used in BL treatment. Glutathione (GSH) is an important antioxidant involved in processes such as regulation of oxidative stress and drug detoxification. Elevated GSH levels have been observed in many cancers and were associated with chemoresistance. We previously identified GCLC, encoding an enzyme involved in GSH biosynthesis, as an essential gene in BL. We now confirm that knockout of GCLC decreases viability of BL cells and that the GCLC protein is overexpressed in BL tissues. Moreover, we demonstrate that buthionine sulfoximine (BSO), a known inhibitor of GCLC, decreases growth of BL cells but does not affect control B cells. Furthermore, we show for the first time that BSO enhances the cytotoxicity of compounds commonly used in BL treatment, doxorubicin, and cyclophosphamide. Given the fact that BSO itself was not toxic to control cells and well-tolerated in clinical trials, combination of chemotherapy with BSO may allow reduction of the doses of cytotoxic drugs required to obtain effective responses in BL patients.

Overlapping characteristics of weak interactions of two transcriptional regulators with WDR5

The WD40 repeat protein 5 (WDR5) is a nuclear hub that critically influences gene expression by interacting with transcriptional regulators. Utilizing the WDR5 binding motif (WBM) site, WDR5 interacts with the myelocytomatosis (MYC), an oncoprotein transcription factor, and the retinoblastoma-binding protein 5 (RbBP5), a scaffolding element of an epigenetic complex. Given the clinical significance of these protein-protein interactions (PPIs), there is a pressing necessity for a quantitative assessment of these processes. Here, we use biolayer interferometry (BLI) to examine interactions of WDR5 with consensus peptide ligands of MYC and RbBP5. We found that both interactions exhibit relatively weak affinities arising from a fast dissociation process. Remarkably, live-cell imaging identified distinctive WDR5 localizations in the absence and presence of full-length binding partners. Although WDR5 tends to accumulate within nucleoli, WBM-mediated interactions with MYC and RbBP5 require their localization outside nucleoli. We utilize fluorescence resonance energy transfer (FRET) microscopy to confirm these weak interactions through a low FRET efficiency of the MYC-WDR5 and RbBP5-WDR5 complexes in living cells. In addition, we evaluate the impact of peptide and small-molecule inhibitors on these interactions. These outcomes form a fundamental basis for further developments to clarify the multitasking role of the WBM binding site of WDR5.

Shared structural features of Miro binding control mitochondrial homeostasis

Miro proteins are universally conserved mitochondrial calcium-binding GTPases that regulate a multitude of mitochondrial processes, including transport, clearance, and lipid trafficking. The exact role of Miro in these functions is unclear but involves binding to a variety of client proteins. How this binding is operated at the molecular level and whether and how it is important for mitochondrial health, however, remains unknown. Here, we show that known Miro interactors-namely, CENPF, Trak, and MYO19-all use a similar short motif to bind the same structural element: a highly conserved hydrophobic pocket in the first calcium-binding domain of Miro. Using these Miro-binding motifs, we identified direct interactors de novo, including MTFR1/2/1L, the lipid transporters Mdm34 and VPS13D, and the ubiquitin E3-ligase Parkin. Given the shared binding mechanism of these functionally diverse clients and its conservation across eukaryotes, we propose that Miro is a universal mitochondrial adaptor coordinating mitochondrial health.

Recent advances in targeted protein degraders as potential therapeutic agents

Targeted protein degradation (TPD) technology has gradually become widespread in the past 20 years, which greatly boosts the development of disease treatment. Contrary to small inhibitors that act on protein kinases, transcription factors, ion channels, and other targets they can bind to, targeted protein degraders could target "undruggable targets" and overcome drug resistance through ubiquitin-proteasome pathway (UPP) and lysosome pathway. Nowadays, some bivalent degraders such as proteolysis-targeting chimeras (PROTACs) have aroused great interest in drug discovery, and some of them have successfully advanced into clinical trials. In this review, to better understand the mechanism of degraders, we elucidate the targeted protein degraders according to their action process, relying on the ubiquitin-proteasome system or lysosome pathway. Then, we briefly summarize the study of PROTACs employing different E3 ligases. Subsequently, the effect of protein of interest (POI) ligands, linker, and E3 ligands on PROTAC degradation activity is also discussed in detail. Other novel technologies based on UPP and lysosome pathway have been discussed in this paper such as in-cell click-formed proteolysis-targeting chimeras (CLIPTACs), molecular glues, Antibody-PROTACs (Ab-PROTACs), autophagy-targeting chimeras, and lysosome-targeting chimeras. Based on the introduction of these degradation technologies, we can clearly understand the action process and degradation mechanism of these approaches. From this perspective, it will be convenient to obtain the development status of these drugs, choose appropriate degradation methods to achieve better disease treatment and provide basis for future research and simultaneously distinguish the direction of future research efforts.

Recent advances in the characterization of essential genes and development of a database of essential genes

Over the past few decades, there has been a significant interest in the study of essential genes, which are crucial for the survival of an organism under specific environmental conditions and thus have practical applications in the fields of synthetic biology and medicine. An increasing amount of experimental data on essential genes has been obtained with the continuous development of technological methods. Meanwhile, various computational prediction methods, related databases and web servers have emerged accordingly. To facilitate the study of essential genes, we have established a database of essential genes (DEG), which has become popular with continuous updates to facilitate essential gene feature analysis and prediction, drug and vaccine development, as well as artificial genome design and construction. In this article, we summarized the studies of essential genes, overviewed the relevant databases, and discussed their practical applications. Furthermore, we provided an overview of the main applications of DEG and conducted comprehensive analyses based on its latest version. However, it should be noted that the essential gene is a dynamic concept instead of a binary one, which presents both opportunities and challenges for their future development.

An Update on the Application of CRISPR Technology in Clinical Practice

The CRISPR/Cas system, an innovative gene-editing tool, is emerging as a promising technique for genome modifications. This straightforward technique was created based on the prokaryotic adaptive immune defense mechanism and employed in the studies on human diseases that proved enormous therapeutic potential. A genetically unique patient mutation in the process of gene therapy can be corrected by the CRISPR method to treat diseases that traditional methods were unable to cure. However, introduction of CRISPR/Cas9 into the clinic will be challenging because we still need to improve the technology's effectiveness, precision, and applications. In this review, we first describe the function and applications of the CRISPR-Cas9 system. We next delineate how this technology could be utilized for gene therapy of various human disorders, including cancer and infectious diseases and highlight the promising examples in the field. Finally, we document current challenges and the potential solutions to overcome these obstacles for the effective use of CRISPR-Cas9 in clinical practice.

Understanding species-specific and conserved RNA-protein interactions in vivo and in vitro

While evolution is often considered from a DNA- and protein-centric view, RNA-based regulation can also impact gene expression and protein sequences. Here we examined interspecies differences in RNA-protein interactions using the conserved neuronal RNA binding protein, Unkempt (UNK) as model. We find that roughly half of mRNAs bound in human are also bound in mouse. Unexpectedly, even when transcript-level binding was conserved across species differential motif usage was prevalent. To understand the biochemical basis of UNK-RNA interactions, we reconstituted the human and mouse UNK-RNA interactomes using a high-throughput biochemical assay. We uncover detailed features driving binding, show that in vivo patterns are captured in vitro, find that highly conserved sites are the strongest bound, and associate binding strength with downstream regulation. Furthermore, subtle sequence differences surrounding motifs are key determinants of species-specific binding. We highlight the complex features driving protein-RNA interactions and how these evolve to confer species-specific regulation.

A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds

Current approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screening platform by generating a DNA damage response (DDR)-focused custom sgRNA library targeting 1011 genes with 3033 sgRNAs. We performed five proof-of-principle compound screens and found that the compounds' known modes-of-action (MoA) were enriched among the compounds' CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale with 20-fold fewer resources than commonly used genome-wide libraries and produce biologically informative CGI profiles.

Evaluating possible maternal effect lethality and genetic background effects in Naa10 knockout mice

Amino-terminal (Nt-) acetylation (NTA) is a common protein modification, affecting approximately 80% of all human proteins. The human essential X-linked gene, NAA10, encodes for the enzyme NAA10, which is the catalytic subunit in the N-terminal acetyltransferase A (NatA) complex. There is extensive genetic variation in humans with missense, splice-site, and C-terminal frameshift variants in NAA10. In mice, Naa10 is not an essential gene, as there exists a paralogous gene, Naa12, that substantially rescues Naa10 knockout mice from embryonic lethality, whereas double knockouts (Naa10-/Y Naa12-/-) are embryonic lethal. However, the phenotypic variability in the mice is nonetheless quite extensive, including piebaldism, skeletal defects, small size, hydrocephaly, hydronephrosis, and neonatal lethality. Here we replicate these phenotypes with new genetic alleles in mice, but we demonstrate their modulation by genetic background and environmental effects. We cannot replicate a prior report of "maternal effect lethality" for heterozygous Naa10-/X female mice, but we do observe a small amount of embryonic lethality in the Naa10-/Y male mice on the inbred genetic background in this different animal facility.

RNA methyltransferase SPOUT1/CENP-32 links mitotic spindle organization with the neurodevelopmental disorder SpADMiSS

SPOUT1/CENP-32 encodes a putative SPOUT RNA methyltransferase previously identified as a mitotic chromosome associated protein. SPOUT1/CENP-32 depletion leads to centrosome detachment from the spindle poles and chromosome misalignment. Aided by gene matching platforms, we identified 24 individuals with neurodevelopmental delays from 18 families with bi-allelic variants in SPOUT1/CENP-32 detected by exome/genome sequencing. Zebrafish spout1/cenp-32 mutants showed reduction in larval head size with concomitant apoptosis likely associated with altered cell cycle progression. In vivo complementation assays in zebrafish indicated that SPOUT1/CENP-32 missense variants identified in humans are pathogenic. Crystal structure analysis of SPOUT1/CENP-32 revealed that most disease-associated missense variants mapped to the catalytic domain. Additionally, SPOUT1/CENP-32 recurrent missense variants had reduced methyltransferase activity in vitro and compromised centrosome tethering to the spindle poles in human cells. Thus, SPOUT1/CENP-32 pathogenic variants cause an autosomal recessive neurodevelopmental disorder: SpADMiSS ( SPOUT1 Associated Development delay Microcephaly Seizures Short stature) underpinned by mitotic spindle organization defects and consequent chromosome segregation errors.

Meta-analysis of dispensable essential genes and their interactions with bypass suppressors

Genes have been historically classified as essential or non-essential based on their requirement for viability. However, genomic mutations can sometimes bypass the requirement for an essential gene, challenging the binary classification of gene essentiality. Such dispensable essential genes represent a valuable model for understanding the incomplete penetrance of loss-of-function mutations often observed in natural populations. Here, we compiled data from multiple studies on essential gene dispensability in Saccharomyces cerevisiae to comprehensively characterize these genes. In analyses spanning different evolutionary timescales, dispensable essential genes exhibited distinct phylogenetic properties compared with other essential and non-essential genes. Integration of interactions with suppressor genes that can bypass the gene essentiality revealed the high functional modularity of the bypass suppression network. Furthermore, dispensable essential and bypass suppressor gene pairs reflected simultaneous changes in the mutational landscape of S. cerevisiae strains. Importantly, species in which dispensable essential genes were non-essential tended to carry bypass suppressor mutations in their genomes. Overall, our study offers a comprehensive view of dispensable essential genes and illustrates how their interactions with bypass suppressors reflect evolutionary outcomes.

Functional genomics and small molecules in mitochondrial neurodevelopmental disorders

Mitochondria are critical for brain development and homeostasis. Therefore, pathogenic variation in the mitochondrial or nuclear genome which disrupts mitochondrial function frequently results in developmental disorders and neurodegeneration at the organismal level. Large-scale application of genome-wide technologies to individuals with mitochondrial diseases has dramatically accelerated identification of mitochondrial disease-gene associations in humans. Multi-omic and high-throughput studies involving transcriptomics, proteomics, metabolomics, and saturation genome editing are providing deeper insights into the functional consequence of mitochondrial genomic variation. Integration of deep phenotypic and genomic data through allelic series continues to uncover novel mitochondrial functions and permit mitochondrial gene function dissection on an unprecedented scale. Finally, mitochondrial disease-gene associations illuminate disease mechanisms and thereby direct therapeutic strategies involving small molecules and RNA-DNA therapeutics. This review summarizes progress in functional genomics and small molecule therapeutics in mitochondrial neurodevelopmental disorders.

Computational prediction and experimental validation identify functionally conserved lncRNAs from zebrafish to human

Functional studies of long noncoding RNAs (lncRNAs) have been hindered by the lack of methods to assess their evolution. Here we present lncRNA Homology Explorer (lncHOME), a computational pipeline that identifies a unique class of long noncoding RNAs (lncRNAs) with conserved genomic locations and patterns of RNA-binding protein (RBP) binding sites (coPARSE-lncRNAs). Remarkably, several hundred human coPARSE-lncRNAs can be evolutionarily traced to zebrafish. Using CRISPR-Cas12a knockout and rescue assays, we found that knocking out many human coPARSE-lncRNAs led to cell proliferation defects, which were subsequently rescued by predicted zebrafish homologs. Knocking down coPARSE-lncRNAs in zebrafish embryos caused severe developmental delays that were rescued by human homologs. Furthermore, we verified that human, mouse and zebrafish coPARSE-lncRNA homologs tend to bind similar RBPs with their conserved functions relying on specific RBP-binding sites. Overall, our study demonstrates a comprehensive approach for studying the functional conservation of lncRNAs and implicates numerous lncRNAs in regulating vertebrate physiology.

Higher-order protein assembly controls kinetochore formation

To faithfully segregate chromosomes during vertebrate mitosis, kinetochore-microtubule interactions must be restricted to a single site on each chromosome. Prior work on pair-wise kinetochore protein interactions has been unable to identify the mechanisms that prevent outer kinetochore formation in regions with a low density of CENP-A nucleosomes. To investigate the impact of higher-order assembly on kinetochore formation, we generated oligomers of the inner kinetochore protein CENP-T using two distinct, genetically engineered systems in human cells. Although individual CENP-T molecules interact poorly with outer kinetochore proteins, oligomers that mimic centromeric CENP-T density trigger the robust formation of functional, cytoplasmic kinetochore-like particles. Both in cells and in vitro, each molecule of oligomerized CENP-T recruits substantially higher levels of outer kinetochore components than monomeric CENP-T molecules. Our work suggests that the density dependence of CENP-T restricts outer kinetochore recruitment to centromeres, where densely packed CENP-A recruits a high local concentration of inner kinetochore proteins.

Rewriting regulatory DNA to dissect and reprogram gene expression

Regulatory DNA sequences within enhancers and promoters bind transcription factors to encode cell type-specific patterns of gene expression. However, the regulatory effects and programmability of such DNA sequences remain difficult to map or predict because we have lacked scalable methods to precisely edit regulatory DNA and quantify the effects in an endogenous genomic context. Here we present an approach to measure the quantitative effects of hundreds of designed DNA sequence variants on gene expression, by combining pooled CRISPR prime editing with RNA fluorescence in situ hybridization and cell sorting (Variant-FlowFISH). We apply this method to mutagenize and rewrite regulatory DNA sequences in an enhancer and the promoter of PPIF in two immune cell lines. Of 672 variant-cell type pairs, we identify 497 that affect PPIF expression. These variants appear to act through a variety of mechanisms including disruption or optimization of existing transcription factor binding sites, as well as creation of de novo sites. Disrupting a single endogenous transcription factor binding site often led to large changes in expression (up to -40% in the enhancer, and -50% in the promoter). The same variant often had different effects across cell types and states, demonstrating a highly tunable regulatory landscape. We use these data to benchmark performance of sequence-based predictive models of gene regulation, and find that certain types of variants are not accurately predicted by existing models. Finally, we computationally design 185 small sequence variants (≤10 bp) and optimize them for specific effects on expression in silico. 84% of these rationally designed edits showed the intended direction of effect, and some had dramatic effects on expression (-100% to +202%). Variant-FlowFISH thus provides a powerful tool to map the effects of variants and transcription factor binding sites on gene expression, test and improve computational models of gene regulation, and reprogram regulatory DNA.

Rational design of a SOCS1-edited tumor-infiltrating lymphocyte therapy using CRISPR/Cas9 screens

Cell therapies such as tumor-infiltrating lymphocyte (TIL) therapy have shown promise in the treatment of patients with refractory solid tumors, with improvement in response rates and durability of responses nevertheless sought. To identify targets capable of enhancing the antitumor activity of T cell therapies, large-scale in vitro and in vivo clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 screens were performed, with the SOCS1 gene identified as a top T cell-enhancing target. In murine CD8+ T cell-therapy models, SOCS1 served as a critical checkpoint in restraining the accumulation of central memory T cells in lymphoid organs as well as intermediate (Texint) and effector (Texeff) exhausted T cell subsets derived from progenitor exhausted T cells (Texprog) in tumors. A comprehensive CRISPR tiling screen of the SOCS1-coding region identified sgRNAs targeting the SH2 domain of SOCS1 as the most potent, with an sgRNA with minimal off-target cut sites used to manufacture KSQ-001, an engineered TIL therapy with SOCS1 inactivated by CRISPR/Cas9. KSQ-001 possessed increased responsiveness to cytokine signals and enhanced in vivo antitumor function in mouse models. These data demonstrate the use of CRISPR/Cas9 screens in the rational design of T cell therapies.

Joint semiparametric kernel network regression

Variable selection and graphical modeling play essential roles in highly correlated and high-dimensional (HCHD) data analysis. Variable selection methods have been developed under both parametric and nonparametric model settings. However, variable selection for nonadditive, nonparametric regression with high-dimensional variables is challenging due to complications in modeling unknown dependence structures among HCHD variables. Gaussian graphical models are a popular and useful tool for investigating the conditional dependence between variables via estimating sparse precision matrices. For a given class of interest, the estimated precision matrices can be mapped onto networks for visualization. However, the limitation of Gaussian graphical models is that they are only applicable to discretized response variables and for the case whenp log ( p ) ≪ n $$ p\log (p)\ll n $$ , wherep $$ p $$ is the number of variables andn $$ n $$ is the sample size. They are necessary to develop a joint method for variable selection and graphical modeling. To the best of our knowledge, the methods for simultaneously selecting variable selection and estimating networks among variables in the semiparametric regression settings are quite limited. Hence, in this paper, we develop a joint semiparametric kernel network regression method to solve this limitation and to provide a connection between them. Our approach is a unified and integrated method that can simultaneously identify important variables and build a network among those variables. We developed our approach under a semiparametric kernel machine regression framework, which can allow for nonlinear or nonadditive associations and complicated interactions among the variables. The advantages of our approach are that it can (1) simultaneously select variables and build a network among HCHD variables under a regression setting; (2) model unknown and complicated interactions among the variables and estimate the network among these variables; (3) allow for any form of semiparametric model, including non-additive, nonparametric model; and (4) provide an interpretable network that considers important variables and a response variable. We demonstrate our approach using a simulation study and real application on genetic pathway-based analysis.

Applications of Innovation Technologies for Personalized Cancer Medicine: Stem Cells and Gene-Editing Tools

Personalized medicine is a new approach toward safer and even cheaper treatments with minimal side effects and toxicity. Planning a therapy based on individual properties causes an effective result in a patient's treatment, especially in a complex disease such as cancer. The benefits of personalized medicine include not only early diagnosis with high accuracy but also a more appropriate and effective therapeutic approach based on the unique clinical, genetic, and epigenetic features and biomarker profiles of a specific patient's disease. In order to achieve personalized cancer therapy, understanding cancer biology plays an important role. One of the crucial applications of personalized medicine that has gained consideration more recently due to its capability in developing disease therapy is related to the field of stem cells. We review various applications of pluripotent, somatic, and cancer stem cells in personalized medicine, including targeted cancer therapy, cancer modeling, diagnostics, and drug screening. CRISPR-Cas gene-editing technology is then discussed as a state-of-the-art biotechnological advance with substantial impacts on medical and therapeutic applications. As part of this section, the role of CRISPR-Cas genome editing in recent cancer studies is reviewed as a further example of personalized medicine application.

Paralog dispensability shapes homozygous deletion patterns in tumor genomes

Genomic instability is a hallmark of cancer, resulting in tumor genomes having large numbers of genetic aberrations, including homozygous deletions of protein coding genes. That tumor cells remain viable in the presence of such gene loss suggests high robustness to genetic perturbation. In model organisms and cancer cell lines, paralogs have been shown to contribute substantially to genetic robustness-they are generally more dispensable for growth than singletons. Here, by analyzing copy number profiles of > 10,000 tumors, we test the hypothesis that the increased dispensability of paralogs shapes tumor genome evolution. We find that genes with paralogs are more likely to be homozygously deleted and that this cannot be explained by other factors known to influence copy number variation. Furthermore, features that influence paralog dispensability in cancer cell lines correlate with paralog deletion frequency in tumors. Finally, paralogs that are broadly essential in cancer cell lines are less frequently deleted in tumors than non-essential paralogs. Overall, our results suggest that homozygous deletions of paralogs are more frequently observed in tumor genomes because paralogs are more dispensable.

Gene essentiality in cancer is better predicted by mRNA abundance than by gene regulatory network-inferred activity

Gene regulatory networks (GRNs) are often deregulated in tumor cells, resulting in altered transcriptional programs that facilitate tumor growth. These altered networks may make tumor cells vulnerable to the inhibition of specific regulatory proteins. Consequently, the reconstruction of GRNs in tumors is often proposed as a means to identify therapeutic targets. While there are examples of individual targets identified using GRNs, the extent to which GRNs can be used to predict sensitivity to targeted intervention in general remains unknown. Here we use the results of genome-wide CRISPR screens to systematically assess the ability of GRNs to predict sensitivity to gene inhibition in cancer cell lines. Using GRNs derived from multiple sources, including GRNs reconstructed from tumor transcriptomes and from curated databases, we infer regulatory gene activity in cancer cell lines from ten cancer types. We then ask, in each cancer type, if the inferred regulatory activity of each gene is predictive of sensitivity to CRISPR perturbation of that gene. We observe slight variation in the correlation between gene regulatory activity and gene sensitivity depending on the source of the GRN and the activity estimation method used. However, we find that there is consistently a stronger relationship between mRNA abundance and gene sensitivity than there is between regulatory gene activity and gene sensitivity. This is true both when gene sensitivity is treated as a binary and a quantitative property. Overall, our results suggest that gene sensitivity is better predicted by measured expression than by GRN-inferred activity.

Clonal dynamics limits detection of selection in tumour xenograft CRISPR/Cas9 screens

Transplantable in vivo CRISPR/Cas9 knockout screens, in which cells are edited in vitro and inoculated into mice to form tumours, allow evaluation of gene function in a cancer model that incorporates the multicellular interactions of the tumour microenvironment. To improve our understanding of the key parameters for success with this method, we investigated the choice of cell line, mouse host, tumour harvesting timepoint and guide RNA (gRNA) library size. We found that high gRNA (80-95%) representation was maintained in a HCT116 subline transduced with the GeCKOv2 whole-genome gRNA library and transplanted into NSG mice when tumours were harvested at early (14 d) but not late time points (38-43 d). The decreased representation in older tumours was accompanied by large increases in variance in gRNA read counts, with notable expansion of a small number of random clones in each sample. The variable clonal dynamics resulted in a high level of 'noise' that limited the detection of gRNA-based selection. Using simulated datasets derived from our experimental data, we show that considerable reductions in count variance would be achieved with smaller library sizes. Based on our findings, we suggest a pathway to rationally design adequately powered in vivo CRISPR screens for successful evaluation of gene function.

Targeted CRISPR activation and knockout screenings identify novel doxorubicin transporters

PURPOSE

Tissue-specific drug uptake has not been well studied, compared to the deeper understanding of drug resistance mediated by the cellular efflux system such as MDR1 proteins. It has been suggested that many drugs need active or defined transporters to pass the cell membrane. In contrast to efflux components induced after anti-cancer drugs reach the intracellular compartment, drug importers are required for initial drug responses. Furthermore, tissue-specific uptake of anti-cancer drugs may directly impact the side effects of many drugs when they accumulate in healthy tissues. Therefore, linking anti-cancer drugs to their respective drug import transporters would directly help to predict drug responses, whilst minimizing side effects.

METHODS

To identify drug transporters of the commonly used anti-cancer drug doxorubicin, we performed focused CRISPR activation and knockout genetic screens targeting all potential membrane-associated transporters and proteins. We monitored the direct uptake of doxorubicin by fluorescence-activated cell sorting (FACS) as the screening readout for identifying transporters/proteins directly involved in doxorubicin uptake.

RESULTS

Integrating the data from these comprehensive CRISPR screenings, we confirmed previously indicated doxorubicin exporters such as ABCB1 and ABCG2 genes, and identified novel doxorubicin importer gene SLC2A3 (GLUT3). Upregulation of SLC2A3 led to higher doxorubicin uptake and better cell killing, indicating SLC2A3 could be a new marker to predict doxorubicin drug response and minimize side effects for the personalized application of this conventional chemotherapeutic drug.

CONCLUSIONS

Our study provides a comprehensive way for identifying drug transporters, as exemplified by the commonly used anti-cancer drug doxorubicin. The newly identified importers may have direct clinical implications for the personalized application of doxorubicin in treating distinct tumors. Our results also highlight the necessity of combining both CRISPR knockout and CRISPR activation genetic screens to identify drug transporters.

Exportin 1-mediated nuclear/cytoplasmic trafficking controls drug sensitivity of classical Hodgkin's lymphoma

Exportin 1 (XPO1) is the main nuclear export receptor that controls the subcellular trafficking and the functions of major regulatory proteins. XPO1 is overexpressed in various cancers and small inhibitors of nuclear export (SINEs) have been developed to inhibit XPO1. In primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin's lymphoma (cHL), the XPO1 gene may be mutated on one nucleotide and encodes the mutant XPO1E571K . To understand the impact of mutation on protein function, we studied the response of PMBL and cHL cells to selinexor, a SINE, and ibrutinib, an inhibitor of Bruton tyrosine kinase. XPO1 mutation renders lymphoma cells more sensitive to selinexor due to a faster degradation of mutant XPO1 compared to the wild-type. We further showed that a mistrafficking of p65 (RELA) and p52 (NFκB2) transcription factors between the nuclear and cytoplasmic compartments accounts for the response toward ibrutinib. XPO1 mutation may be envisaged as a biomarker of the response of PMBL and cHL cells and other B-cell hemopathies to SINEs and drugs that target even indirectly the NFκB signaling pathway.

Targeting the non-coding genome and temozolomide signature enables CRISPR-mediated glioma oncolysis

Glioblastoma (GBM) is the most common lethal primary brain cancer in adults. Despite treatment regimens including surgical resection, radiotherapy, and temozolomide (TMZ) chemotherapy, growth of residual tumor leads to therapy resistance and death. At recurrence, a quarter to a third of all gliomas have hypermutated genomes, with mutational burdens orders of magnitude greater than in normal tissue. Here, we quantified the mutational landscape progression in a patient's primary and recurrent GBM, and we uncovered Cas9-targetable repeat elements. We show that CRISPR-mediated targeting of highly repetitive loci enables rapid elimination of GBM cells, an approach we term "genome shredding." Importantly, in the patient's recurrent GBM, we identified unique repeat sequences with TMZ mutational signature and demonstrated that their CRISPR targeting enables cancer-specific cell ablation. "Cancer shredding" leverages the non-coding genome and therapy-induced mutational signatures for targeted GBM cell depletion and provides an innovative paradigm to develop treatments for hypermutated glioma.

Evidence for widespread existence of functional novel and non-canonical human transcripts

BACKGROUND

Fraction of functional sequence in the human genome remains a key unresolved question in Biology and the subject of vigorous debate. While a plethora of studies have connected a significant fraction of human DNA to various biochemical processes, the classical definition of function requires evidence of effects on cellular or organismal fitness that such studies do not provide. Although multiple high-throughput reverse genetics screens have been developed to address this issue, they are limited to annotated genomic elements and suffer from non-specific effects, arguing for a strong need to develop additional functional genomics approaches.

RESULTS

In this work, we established a high-throughput lentivirus-based insertional mutagenesis strategy as a forward genetics screen tool in aneuploid cells. Application of this approach to human cell lines in multiple phenotypic screens suggested the presence of many yet uncharacterized functional elements in the human genome, represented at least in part by novel exons of known and novel genes. The novel transcripts containing these exons can be massively, up to thousands-fold, induced by specific stresses, and at least some can represent bi-cistronic protein-coding mRNAs.

CONCLUSIONS

Altogether, these results argue that many unannotated and non-canonical human transcripts, including those that appear as aberrant splice products, have biological relevance under specific biological conditions.

HDAC3 and HDAC8 PROTAC dual degrader reveals roles of histone acetylation in gene regulation

HDAC3 and HDAC8 have critical biological functions and represent highly sought-after therapeutic targets. Because histone deacetylases (HDACs) have a very conserved catalytic domain, developing isozyme-selective inhibitors remains challenging. HDAC3/8 also have deacetylase-independent activity, which cannot be blocked by conventional enzymatic inhibitors. Proteolysis-targeting chimeras (PROTACs) can selectively degrade a target enzyme, abolishing both enzymatic and scaffolding function. Here, we report a novel HDAC3/8 dual degrader YX968 that induces highly potent, rapid, and selective degradation of both HDAC3/8 without triggering pan-HDAC inhibitory effects. Unbiased quantitative proteomic experiments confirmed its high selectivity. HDAC3/8 degradation by YX968 does not induce histone hyperacetylation and broad transcriptomic perturbation. Thus, histone hyperacetylation may be a major factor for altering transcription. YX968 promotes apoptosis and kills cancer cells with a high potency in vitro. YX968 thus represents a new probe for dissecting the complex biological functions of HDAC3/8.

Liquid-liquid phase separation in DNA double-strand breaks repair

DNA double-strand breaks (DSBs) are the fatal type of DNA damage mostly induced by exposure genome to ionizing radiation or genotoxic chemicals. DSBs are mainly repaired by homologous recombination (HR) and nonhomologous end joining (NHEJ). To repair DSBs, a large amount of DNA repair factors was observed to be concentrated at the end of DSBs in a specific spatiotemporal manner to form a repair center. Recently, this repair center was characterized as a condensate derived from liquid-liquid phase separation (LLPS) of key DSBs repair factors. LLPS has been found to be the mechanism of membraneless organelles formation and plays key roles in a variety of biological processes. In this review, the recent advances and mechanisms of LLPS in the formation of DSBs repair-related condensates are summarized.

A deep catalog of protein-coding variation in 985,830 individuals

Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in the population. Identifying and ascertaining the frequency of such rare variants requires very large sample sizes. Here, we present the largest catalog of human protein-coding variation to date, derived from exome sequencing of 985,830 individuals of diverse ancestry to serve as a rich resource for studying rare coding variants. Individuals of African, Admixed American, East Asian, Middle Eastern, and South Asian ancestry account for 20% of this Exome dataset. Our catalog of variants includes approximately 10.5 million missense (54% novel) and 1.1 million predicted loss-of-function (pLOF) variants (65% novel, 53% observed only once). We identified individuals with rare homozygous pLOF variants in 4,874 genes, and for 1,838 of these this work is the first to document at least one pLOF homozygote. Additional insights from the RGC-ME dataset include 1) improved estimates of selection against heterozygous loss-of-function and identification of 3,459 genes intolerant to loss-of-function, 83 of which were previously assessed as tolerant to loss-of-function and 1,241 that lack disease annotations; 2) identification of regions depleted of missense variation in 457 genes that are tolerant to loss-of-function; 3) functional interpretation for 10,708 variants of unknown or conflicting significance reported in ClinVar as cryptic splice sites using splicing score thresholds based on empirical variant deleteriousness scores derived from RGC-ME; and 4) an observation that approximately 3% of sequenced individuals carry a clinically actionable genetic variant in the ACMG SF 3.1 list of genes. We make this important resource of coding variation available to the public through a variant allele frequency browser. We anticipate that this report and the RGC-ME dataset will serve as a valuable reference for understanding rare coding variation and help advance precision medicine efforts.

Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles

Single-cell RNA sequencing greatly advanced our understanding of intratumoral heterogeneity through identifying tumor subpopulations with distinct biologies. However, translating biological differences into treatment strategies is challenging, as we still lack tools to facilitate efficient drug discovery that tackles heterogeneous tumors. One key component of such approaches tackles accurate prediction of drug response at the single-cell level to offer therapeutic options to specific cell subpopulations. Here, we present a transparent computational framework (nicknamed scIDUC) to predict therapeutic efficacies on an individual-cell basis by integrating single-cell transcriptomic profiles with large, data-rich pan-cancer cell line screening datasets. Our method achieves high accuracy, with predicted sensitivities easily able to separate cells into their true cellular drug resistance status as measured by effect size (Cohen's d > 1.0). More importantly, we examine our method's utility with three distinct prospective tests covering different diseases (rhabdomyosarcoma, pancreatic ductal adenocarcinoma, and castration-resistant prostate cancer), and in each our predicted results are accurate and mirrored biological expectations. In the first two, we identified drugs for cell subpopulations that are resistant to standard-of-care (SOC) therapies due to intrinsic resistance or effects of tumor microenvironments. Our results showed high consistency with experimental findings from the original studies. In the third test, we generated SOC therapy resistant cell lines, used scIDUC to identify efficacious drugs for the resistant line, and validated the predictions with in-vitro experiments. Together, scIDUC quickly translates scRNA-seq data into drug response for individual cells, displaying the potential as a first-line tool for nuanced and heterogeneity-aware drug discovery.

Noncoding RNA mutations in cancer

Cancer is driven by both germline and somatic genetic changes. Efforts have been devoted to characterizing essential genetic variations in cancer initiation and development. Most attention has been given to mutations in protein-coding genes and associated regulatory elements such as promoters and enhancers. The development of sequencing technologies and in silico and experimental methods has allowed further exploration of cancer predisposition variants and important somatic mutations in noncoding RNAs, mainly for long noncoding RNAs and microRNAs. Association studies including GWAS have revealed hereditary variations including SNPs and indels in lncRNA or miRNA genes and regulatory regions. These mutations altered RNA secondary structures, expression levels, and target recognition and then conferred cancer predisposition to carriers. Whole-exome/genome sequencing comparing cancer and normal tissues has revealed important somatic mutations in noncoding RNA genes. Mutation hotspots and somatic copy number alterations have been identified in various tumor-associated noncoding RNAs. Increasing focus and effort have been devoted to studying the noncoding region of the genome. The complex genetic network of cancer initiation is being unveiled. This article is categorized under: RNA in Disease and Development > RNA in Disease.