CRISPR Screens in Synthetic Lethality and Combinatorial Therapies for Cancer

Targeting p53 for immune modulation: Exploring its functions in tumor immunity and inflammation

p53, often referred to as the "guardian of the genome," is a critical regulator of cellular responses to stress. p53 plays a dual role in tumor suppression and immune regulation. In addition to its well-known functions of maintaining genomic stability and inducing apoptosis, p53 orchestrates a complex interaction between innate and adaptive immune responses. This involvement contributes to pathogen clearance, immune surveillance, and immunogenic cell death (ICD). This review explores the influence of p53 on immune dynamics, detailing its effects on macrophages, dendritic cells, natural killer cells (NK), T cells, and B cells. This review explains how mutations in p53 disrupt immune responses, promoting tumor immune evasion, and highlights its regulation of inflammatory cytokines and pattern recognition receptors. Furthermore, p53's role in ICD marks it as a key player in antitumor immunity, which has significant implications for cancer immunotherapy. The review also discusses the role of p53 in inflammation, autoimmune diseases, and chronic infections, revealing its dual function in promoting and suppressing inflammation through interactions with NF-κB signaling. Therapeutically, approaches that target p53, including wild-type p53 reactivation and combination therapies with immune checkpoint inhibitors, show considerable promise. Advances in high-throughput technologies, such as single-cell RNA sequencing and CRISPR screens, provide new insights into the immunological functions of p53, including its role in microbiome-immune interactions and immune senescence. This comprehensive review highlights the importance of incorporating immunological insights from p53 into innovative therapeutic strategies, addressing existing knowledge gaps, and paving the way for personalized medicine.

Genome-Wide Screening in Haploid Stem Cells Reveals Synthetic Lethality Targeting MLH1 and TP53 Deficient Tumours

Synthetic lethality is defined as a type of genetic interaction where the combination of two genetic events results in cell death, whereas each of them separately does not. Synthetic lethality can be a useful tool in personalised oncology. MLH1 is a cancer-related gene that has a central role in DNA mismatch-repair and TP53 is the most frequently mutated gene in cancer. To identify genetic events that can lead to tumour death once either MLH1 or TP53 is mutated, a genome-wide genetic screening was performed. Thus, mutations in all protein-coding genes were introduced into haploid human embryonic stem cells (hESCs) with and without loss-of-function mutations in the MLH1 or TP53 genes. These experiments uncovered a list of putative hits with EXO1, NR5A2, and PLK2 genes for MLH1, and MYH10 gene for TP53 emerging as the most promising candidates. Synthetic lethal interactions of these genes were validated genetically or chemically using small molecules that inhibit these genes. The specific effects of SR1848, which inhibits NR5A2, ON1231320 or BI2536, which inhibits PLK2, and blebbistatin, which inhibits MYH10, were further validated in cancer cell lines. Finally, animal studies with CCL xenografts showed the selective effect of the small molecule BI2536 on MLH1-null tumours and of blebbistatin on TP53-mutated tumours. Thus, demonstrating their potential for personalised medicine, and the robustness of genetic screening in haploid hESCs in the context of cancer therapeutics.

Harnessing the power of AI in precision medicine: NGS-based therapeutic insights for colorectal cancer cohort

Purpose

Developing innovative precision and personalized cancer therapeutics is essential to enhance cancer survivability, particularly for prevalent cancer types such as colorectal cancer. This study aims to demonstrate various approaches for discovering new targets for precision therapies using artificial intelligence (AI) on a Polish cohort of colorectal cancer patients.

Methods

We analyzed 71 patients with histopathologically confirmed advanced resectional colorectal adenocarcinoma. Whole exome sequencing was performed on tumor and peripheral blood samples, while RNA sequencing (RNAseq) was conducted on tumor samples. We employed three approaches to identify potential targets for personalized and precision therapies. First, using our in-house neoantigen calling pipeline, ARDentify, combined with an AI-based model trained on immunopeptidomics mass spectrometry data (ARDisplay), we identified neoepitopes in the cohort. Second, based on recurrent mutations found in our patient cohort, we selected corresponding cancer cell lines and utilized knock-out gene dependency scores to identify synthetic lethality genes. Third, an AI-based model trained on cancer cell line data was employed to identify cell lines with genomic profiles similar to selected patients. Copy number variants and recurrent single nucleotide variants in these cell lines, along with gene dependency data, were used to find personalized synthetic lethality pairs.

Results

We identified approximately 8,700 unique neoepitopes, but none were shared by more than two patients, indicating limited potential for shared neoantigenic targets across our cohort. Additionally, we identified three synthetic lethality pairs: the well-known APC-CTNNB1 and BRAF-DUSP4 pairs, along with the recently described APC-TCF7L2 pair, which could be significant for patients with APC and BRAF variants. Furthermore, by leveraging the identification of similar cancer cell lines, we uncovered a potential gene pair, VPS4A and VPS4B, with therapeutic implications.

Conclusion

Our study highlights three distinct approaches for identifying potential therapeutic targets in cancer patients. Each approach yielded valuable insights into our cohort, underscoring the relevance and utility of these methodologies in the development of precision and personalized cancer therapies. Importantly, we developed a novel AI model that aligns tumors with representative cell lines using RNAseq and methylation data. This model enables us to identify cell lines closely resembling patient tumors, facilitating accurate selection of models needed for in vitro validation.

Comprehensive review of CRISPR-based gene editing: mechanisms, challenges, and applications in cancer therapy

The CRISPR system is a revolutionary genome editing tool that has the potential to revolutionize the field of cancer research and therapy. The ability to precisely target and edit specific genetic mutations that drive the growth and spread of tumors has opened up new possibilities for the development of more effective and personalized cancer treatments. In this review, we will discuss the different CRISPR-based strategies that have been proposed for cancer therapy, including inactivating genes that drive tumor growth, enhancing the immune response to cancer cells, repairing genetic mutations that cause cancer, and delivering cancer-killing molecules directly to tumor cells. We will also summarize the current state of preclinical studies and clinical trials of CRISPR-based cancer therapy, highlighting the most promising results and the challenges that still need to be overcome. Safety and delivery are also important challenges for CRISPR-based cancer therapy to become a viable clinical option. We will discuss the challenges and limitations that need to be overcome, such as off-target effects, safety, and delivery to the tumor site. Finally, we will provide an overview of the current challenges and opportunities in the field of CRISPR-based cancer therapy and discuss future directions for research and development. The CRISPR system has the potential to change the landscape of cancer research, and this review aims to provide an overview of the current state of the field and the challenges that need to be overcome to realize this potential.

CRISPR-Based Therapies: Revolutionizing Drug Development and Precision Medicine

With the discovery of CRISPR-Cas9, drug development and precision medicine have undergone a major change. This review article looks at the new ways that CRISPR-based therapies are being used and how they are changing the way medicine is done. CRISPR technology's ability to precisely and flexibly edit genes has opened up new ways to find, validate, and develop drug targets. Also, it has made way for personalized gene therapies, precise gene editing, and advanced screening techniques, all of which hold great promise for treating a wide range of diseases. In this article, we look at the latest research and clinical trials that show how CRISPR could be used to treat genetic diseases, cancer, infectious diseases, and other hard-to-treat conditions. However, ethical issues and problems with regulations are also discussed in relation to CRISPR-based therapies, which shows how important it is to use them safely and responsibly. As CRISPR continues to change how drugs are made and used, this review shines a light on the amazing things that have been done and what the future might hold in this rapidly changing field.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and the emergence of drug resistance. Host-based antivirals are an alternative, but can cause nonspecific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR knockout (KO) screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting antiviral SL drug targets. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Our comparison of SARS-CoV-2 and influenza infection data revealed potential broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Single cell RNA sequencing – a valuable tool for cancer immunotherapy: a mini review

Single-cell RNA sequencing (scRNA-seq) technology has made great strides in research over the last decade. Data analysis has been aided by developments in bioinformatics tools and artificial intelligence, allowing biological and clinical researchers to get a deeper understanding of the different cell clusters and their dynamics within tumours. Combining conventional treatment modalities like chemotherapy and radiation with immunotherapy is a growing trend in cancer treatment. Hence, knowledge of the tumour microenvironment and the effect of each treatment modality on the TME, at a single cell level can provide treating clinicians with better clues for patient stratification and prognostication. With this knowledge, immunotherapy could become successful in treating a wide range of cancers, opening the path for the creation of even more effective treatment strategies. Despite the widespread availability of scRNA-seq technology, computational analysis and data interpretation are still challenges. Worldwide, such challenges are being addressed by various researchers, strengthening the contribution of this technology towards cancer elimination. In this mini-review, we primarily focus on the technique, its workflow, and the computational aspects of scRNA technology, along with an overview of the current challenges in the analysis and interpretation of the data generated.

CRISPR-Cas System Is an Effective Tool for Identifying Drug Combinations That Provide Synergistic Therapeutic Potential in Cancers

Despite numerous efforts, the therapeutic advancement for neuroblastoma and other cancer treatments is still ongoing due to multiple challenges, such as the increasing prevalence of cancers and therapy resistance development in tumors. To overcome such obstacles, drug combinations are one of the promising applications. However, identifying and implementing effective drug combinations are critical for achieving favorable treatment outcomes. Given the enormous possibilities of combinations, a rational approach is required to predict the impact of drug combinations. Thus, CRISPR-Cas-based and other approaches, such as high-throughput pharmacological and genetic screening approaches, have been used to identify possible drug combinations. In particular, the CRISPR-Cas system (Clustered Regularly Interspaced Short Palindromic Repeats) is a powerful tool that enables us to efficiently identify possible drug combinations that can improve treatment outcomes by reducing the total search space. In this review, we discuss the rational approaches to identifying, examining, and predicting drug combinations and their impact.

Theory for High-Throughput Genetic Interaction Screening

Systematic, genome-scale genetic screens have been instrumental for elucidating genotype-phenotype relationships, but approaches for probing genetic interactions have been limited to at most ∼100 pre-selected gene combinations in mammalian cells. Here, we introduce a theory for high-throughput genetic interaction screens. The theory extends our recently developed Multiplexing using Spectral Imaging and Combinatorics (MuSIC) approach to propose ∼105 spectrally unique, genetically encoded MuSIC barcodes from 18 currently available fluorescent proteins. Simulation studies based on constraints imposed by spectral flow cytometry equipment suggest that genetic interaction screens at the human genome-scale may be possible if MuSIC barcodes can be paired to guide RNAs. While experimental testing of this theory awaits, it offers transformative potential for genetic perturbation technology and knowledge of genetic function. More broadly, the availability of a genome-scale spectral barcode library for non-destructive identification of single cells could find more widespread applications such as traditional genetic screening and high-dimensional lineage tracing.

Genome-wide CRISPR Screen Reveals RAB10 as a Synthetic Lethal Gene in Colorectal and Pancreatic Cancers Carrying SMAD4 Loss

The TGFβ signaling mediator SMAD4 is frequently mutated or deleted in colorectal and pancreatic cancers. SMAD4 acts as a tumor suppressor and its loss is associated with poorer patient outcomes. The purpose of this study was to find synthetic lethal interactions with SMAD4 deficiency to find novel therapeutic strategies for the treatment of patients with SMAD4-deficient colorectal or pancreatic cancers. Using pooled lentiviral single-guide RNA libraries, we conducted genome-wide loss-of-function screens in Cas9-expressing colorectal and pancreatic cancer cells harboring altered or wild-type SMAD4. The small GTPase protein RAB10 was identified and validated as a susceptibility gene in SMAD4-altered colorectal and pancreatic cancer cells. Rescue assays showed that RAB10 reintroduction reversed the antiproliferative effects of RAB10 knockout in SMAD4-negative cell lines. Further investigation is necessary to shed light on the mechanism by which RAB10 inhibition decreases cell proliferation of SMAD4-negative cells.

Significance

This study identified and validated RAB10 as new synthetic lethal gene with SMAD4. This was achieved by conducting a whole-genome CRISPR screens in different colorectal and pancreatic cell lines. A future RAB10 inhibitors could correspond to a new therapeutic solution for patients with cancer with SMAD4 deletion.

Genetic screens reveal new targetable vulnerabilities in BAP1-deficient mesothelioma

More than half of patients with malignant mesothelioma show alterations in the BAP1 tumor-suppressor gene. Being a member of the Polycomb repressive deubiquitinating (PR-DUB) complex, BAP1 loss results in an altered epigenome, which may create new vulnerabilities that remain largely unknown. Here, we performed a CRISPR-Cas9 kinome screen in mesothelioma cells that identified two kinases in the mevalonate/cholesterol biosynthesis pathway. Furthermore, our analysis of chromatin, expression, and genetic perturbation data in mesothelioma cells suggests a dependency on PR complex 2 (PRC2)-mediated silencing. Pharmacological inhibition of PRC2 elevates the expression of cholesterol biosynthesis genes only in BAP1-deficient mesothelioma, thereby sensitizing these cells to the combined targeting of PRC2 and the mevalonate pathway. Finally, by subjecting autochthonous Bap1-deficient mesothelioma mice or xenografts to mevalonate pathway inhibition (zoledronic acid) and PRC2 inhibition (tazemetostat), we demonstrate a potent anti-tumor effect, suggesting a targeted combination therapy for Bap1-deficient mesothelioma.

A CRISPR Platform for Targeted In Vivo Screens

Large-scale genetic screens are becoming increasingly used as powerful tools to query the genome to identify therapeutic targets in cancer. The advent of the CRISPR technology has revolutionized the effectiveness of these screens and has made it possible to carry out loss-of-function screens to identify cancer-specific genetic interactions. Such loss-of-function screens can be performed in silico, in vitro, and in vivo, depending on the scale of the screen, as well as research questions to be answered. Performing screens in vivo has its challenges but also advantages, providing opportunities to study the tumor microenvironment and cancer immunity. In this chapter, we present a procedural framework and associated notes for conducting in vivo CRISPR knockout screens in cancer models to study cancer biology, anti-tumor immune responses, tumor microenvironment, and predicting treatment responses.

Synthetic lethal gene pairs: Experimental approaches and predictive models

Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.

A genetic map of the chromatin regulators to drug response in cancer cells

BACKGROUND

Diverse drug vulnerabilities owing to the Chromatin regulators (CRs) genetic interaction across various cancers, but the identification of CRs genetic interaction remains challenging.

METHODS

In order to provide a global view of the CRs genetic interaction in cancer cells, we developed a method to identify potential drug response-related CRs genetic interactions for specific cancer types by integrating the screen of CRISPR-Cas9 and pharmacogenomic response datasets.

RESULTS

Totally, 625 drug response-related CRs synthetic lethality (CSL) interactions and 288 CRs synthetic viability (CSV) interactions were detected. Systematically network analysis presented CRs genetic interactions have biological function relationship. Furthermore, we validated CRs genetic interactions induce multiple omics deregulation in The Cancer Genome Atlas. We revealed the colon adenocarcinoma patients (COAD) with mutations of a CRs set (EP300, MSH6, NSD2 and TRRAP) mediate a better survival with low expression of MAP2 and could benefit from taxnes. While the COAD patients carrying at least one of the CSV interactions in Vorinostat CSV module confer a poor prognosis and may be resistant to Vorinostat treatment.

CONCLUSIONS

The CRs genetic interaction map provides a rich resource to investigate cancer-associated CRs genetic interaction and proposes a powerful strategy of biomarker discovery to guide the rational use of agents in cancer therapy.

Long Non-Coding RNAs: Tools for Understanding and Targeting Cancer Pathways

The regulatory nature of long non-coding RNAs (lncRNAs) has been well established in various processes of cellular growth, development, and differentiation. Therefore, it is vital to examine their contribution to cancer development. There are ample examples of lncRNAs whose cellular levels are significantly associated with clinical outcomes. However, whether these non-coding molecules can work as either key drivers or barriers to cancer development remains unknown. The current review aims to discuss some well-characterised lncRNAs in the process of oncogenesis and extrapolate the extent of their decisive contribution to tumour development. We ask if these lncRNAs can independently initiate neoplastic lesions or they always need the modulation of well characterized oncogenes or tumour suppressors to exert their functional properties. Finally, we discuss the emerging genetic approaches and appropriate animal and humanised models that can significantly contribute to the functional dissection of lncRNAs in cancer development and progression.

Synthetic Vulnerabilities in the KRAS Pathway

Mutations in Kristen Rat Sarcoma viral oncogene (KRAS) are among the most frequent gain-of-function genetic alterations in human cancer. Most KRAS-driven cancers depend on its sustained expression and signaling. Despite spectacular recent success in the development of inhibitors targeting specific KRAS alleles, the discovery and utilization of effective directed therapies for KRAS-mutant cancers remains a major unmet need. One potential approach is the identification of KRAS-specific synthetic lethal vulnerabilities. For example, while KRAS-driven oncogenesis requires the activation of a number of signaling pathways, it also triggers stress response pathways in cancer cells that could potentially be targeted for therapeutic benefit. This review will discuss how the latest advances in functional genomics and the development of more refined models have demonstrated the existence of molecular pathways that can be exploited to uncover synthetic lethal interactions with a promising future as potential clinical treatments in KRAS-mutant cancers.

Validating Small Molecule Chemical Probes for Biological Discovery

Small molecule chemical probes are valuable tools for interrogating protein biological functions and relevance as a therapeutic target. Rigorous validation of chemical probe parameters such as cellular potency and selectivity is critical to unequivocally linking biological and phenotypic data resulting from treatment with a chemical probe to the function of a specific target protein. A variety of modern technologies are available to evaluate cellular potency and selectivity, target engagement, and functional response biomarkers of chemical probe compounds. Here, we review these technologies and the rationales behind using them for the characterization and validation of chemical probes. In addition, large-scale phenotypic characterization of chemical probes through chemical genetic screening is increasingly leading to a wealth of information on the cellular pharmacology and disease involvement of potential therapeutic targets. Extensive compound validation approaches and integration of phenotypic information will lay foundations for further use of chemical probes in biological discovery. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Malignant peripheral nerve sheath tumor: models, biology, and translation

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive, invasive cancer that comprise around 10% of all soft tissue sarcomas and develop in about 8-13% of patients with Neurofibromatosis Type 1. They are associated with poor prognosis and are the leading cause of mortality in NF1 patients. MPNSTs can also develop sporadically or following exposure to radiation. There is currently no effective targeted therapy to treat MPNSTs and surgical removal remains the mainstay treatment. Unfortunately, surgery is not always possible due to the size and location of the tumor, thus, a better understanding of MPNST initiation and development is required to design novel therapeutics. Here, we provide an overview of MPNST biology and genetics, discuss findings regarding the developmental origin of MPNST, and summarize the various model systems employed to study MPNST. Finally, we discuss current management strategies for MPNST, as well as recent developments in translating basic research findings into potential therapies.

CRISPR screening of E3 ubiquitin ligases reveals Ring Finger Protein 185 as a novel tumor suppressor in glioblastoma repressed by promoter hypermethylation and miR-587

Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor. E3 ligases play important functions in glioma pathogenesis. CRISPR system offers a powerful platform for genome manipulation, while the screen of E3 ligases in GBM still remains to be explored. Here, we first constructed an E3 ligase small guide RNA (sgRNAs) library for glioma cells growth screening. After four passages, 299 significantly enriched or lost genes (SELGs) were compared with the initial state. Then the clinical significance of SELGs were validated and analyzed with TCGA glioblastoma and CGGA datasets. As RNF185 showed lost signal, decreased expression and favorable prognostic significance, we chose RNF185 for functional analysis. In vitro overexpressed cellular phenotype showed that RNF185 was a tumor suppressor in two glioma cell lines. Finally, the molecular mechanism of decreased RNF185 expression was investigated and increased miR-587 expression and DNA hypermethylation was evaluated. This study would provide a link between the molecular basis and glioblastoma pathogenesis, and a novel perspective for glioblastoma treatment.

Functional Roles of Bromodomain Proteins in Cancer

Histone acetylation is generally associated with an open chromatin configuration that facilitates many cellular processes including gene transcription, DNA repair, and DNA replication. Aberrant levels of histone lysine acetylation are associated with the development of cancer. Bromodomains represent a family of structurally well-characterized effector domains that recognize acetylated lysines in chromatin. As part of their fundamental reader activity, bromodomain-containing proteins play versatile roles in epigenetic regulation, and additional functional modules are often present in the same protein, or through the assembly of larger enzymatic complexes. Dysregulated gene expression, chromosomal translocations, and/or mutations in bromodomain-containing proteins have been correlated with poor patient outcomes in cancer. Thus, bromodomains have emerged as a highly tractable class of epigenetic targets due to their well-defined structural domains, and the increasing ease of designing or screening for molecules that modulate the reading process. Recent developments in pharmacological agents that target specific bromodomains has helped to understand the diverse mechanisms that bromodomains play with their interaction partners in a variety of chromatin processes, and provide the promise of applying bromodomain inhibitors into the clinical field of cancer treatment. In this review, we explore the expression and protein interactome profiles of bromodomain-containing proteins and discuss them in terms of functional groups. Furthermore, we highlight our current understanding of the roles of bromodomain-containing proteins in cancer, as well as emerging strategies to specifically target bromodomains, including combination therapies using bromodomain inhibitors alongside traditional therapeutic approaches designed to re-program tumorigenesis and metastasis.

Exploiting DNA Endonucleases to Advance Mechanisms of DNA Repair

The earliest methods of genome editing, such as zinc-finger nucleases (ZFN) and transcription activator-like effector nucleases (TALENs), utilize customizable DNA-binding motifs to target the genome at specific loci. While these approaches provided sequence-specific gene-editing capacity, the laborious process of designing and synthesizing recombinant nucleases to recognize a specific target sequence, combined with limited target choices and poor editing efficiency, ultimately minimized the broad utility of these systems. The discovery of clustered regularly interspaced short palindromic repeat sequences (CRISPR) in Escherichia coli dates to 1987, yet it was another 20 years before CRISPR and the CRISPR-associated (Cas) proteins were identified as part of the microbial adaptive immune system, by targeting phage DNA, to fight bacteriophage reinfection. By 2013, CRISPR/Cas9 systems had been engineered to allow gene editing in mammalian cells. The ease of design, low cytotoxicity, and increased efficiency have made CRISPR/Cas9 and its related systems the designer nucleases of choice for many. In this review, we discuss the various CRISPR systems and their broad utility in genome manipulation. We will explore how CRISPR-controlled modifications have advanced our understanding of the mechanisms of genome stability, using the modulation of DNA repair genes as examples.