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Integration of CRISPR/Cas9 with artificial intelligence for improved cancer therapeutics.

ABSTRACT: Gene editing has great potential in treating diseases caused by well-characterized molecular alterations. The introduction of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-based gene-editing tools has substantially improved the precision and efficiency of gene editing. The CRISPR/Cas9 system offers several advantages over the existing gene-editing approaches, such as its ability to target practically any genomic sequence, enabling the rapid development and deployment of novel CRISPR-mediated knock-out/knock-in methods. CRISPR/Cas9 has been widely used to develop cancer models, validate essential genes as druggable targets, study drug-resistance mechanisms, explore gene non-coding areas, and develop biomarkers. CRISPR gene editing can create more-effective chimeric antigen receptor (CAR)-T cells that are durable, cost-effective, and more readily available. However, further research is needed to define the CRISPR/Cas9 system's pros and cons, establish best practices, and determine social and ethical implications. This review summarizes recent CRISPR/Cas9 developments, particularly in cancer research and immunotherapy, and the potential of CRISPR/Cas9-based screening in developing cancer precision medicine and engineering models for targeted cancer therapy, highlighting the existing challenges and future directions. Lastly, we highlight the role of artificial intelligence in refining the CRISPR system's on-target and off-target effects, a critical factor for the broader application in cancer therapeutics.

SUBMITTER: Bhat AA

PROVIDER: S-EPMC9673220 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Integration of CRISPR/Cas9 with artificial intelligence for improved cancer therapeutics.

Bhat Ajaz A AA Nisar Sabah S Mukherjee Soumi S Saha Nirmalya N Yarravarapu Nageswari N Lone Saife N SN Masoodi Tariq T Chauhan Ravi R Maacha Selma S Bagga Puneet P Dhawan Punita P Akil Ammira Al-Shabeeb AA El-Rifai Wael W Uddin Shahab S Reddy Ravinder R Singh Mayank M Macha Muzafar A MA Haris Mohammad M

Journal of translational medicine 20221118 1

Gene editing has great potential in treating diseases caused by well-characterized molecular alterations. The introduction of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-based gene-editing tools has substantially improved the precision and efficiency of gene editing. The CRISPR/Cas9 system offers several advantages over the existing gene-editing approaches, such as its ability to target practically any genomic sequence, enabling the rapid ...[more]

PMID: 36401282

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Project description:BackgroundRisk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to ECG images as a surrogate for imaging risk biomarkers and its association with early CTRCD.MethodsAcross a US-based health system (2013-2023), we identified 1550 patients (aged, 60 [interquartile range, 51-69] years, 1223 [78.9%] women) without cardiomyopathy who received anthracyclines or trastuzumab for breast cancer or non-Hodgkin lymphoma and had ECG performed ≤12 months before treatment. We deployed a validated AI model of left ventricular systolic dysfunction to baseline ECG images and defined low-, intermediate-, and high-risk groups based on AI-ECG left ventricular systolic dysfunction probabilities of <0.01, 0.01 to 0.1, and ≥0.1 (positive screen), respectively. We explored the association with early CTRCD (new cardiomyopathy, heart failure, or left ventricular ejection fraction <50%), or left ventricular ejection fraction <40%, up to 12 months after treatment. In a mechanistic analysis, we assessed the association between global longitudinal strain and AI-ECG left ventricular systolic dysfunction probabilities in studies performed within 15 days of each other.ResultsAmong 1550 patients without known cardiomyopathy (median follow-up, 14.1 [interquartile range, 13.4-17.1] months), 83 (5.4%), 562 (36.3%), and 905 (58.4%) were classified as high, intermediate, and low risk, respectively, by baseline AI-ECG. A high-risk versus low-risk AI-ECG screen (≥0.1 versus <0.01) was associated with a 3.4-fold and 13.5-fold higher incidence of CTRCD (adjusted hazard ratio, 3.35 [95% CI, 2.25-4.99]) and left ventricular ejection fraction <40% (adjusted hazard ratio, 13.52 [95% CI, 5.06-36.10]), respectively. Post hoc analyses supported longitudinal increases in AI-ECG probabilities within 6 to 12 months of a CTRCD event. Among 1428 temporally linked echocardiograms and ECGs, AI-ECG left ventricular systolic dysfunction probabilities were associated with worse global longitudinal strain (global longitudinal strain, -19% [interquartile range, -21% to -17%] for probabilities <0.1, to -15% [interquartile range, -15% to -9%] for ≥0.5 [P<0.001]).ConclusionsAI applied to baseline ECG images can stratify the risk of early CTRCD associated with anthracycline or trastuzumab exposure in the setting of breast cancer and non-Hodgkin lymphoma therapy.

Project description:BackgroundPichia pastoris (syn. Komagataella phaffii) is a widely used generally recognized as safe host for heterologous expression of proteins in both industry and academia. Recently, it has been shown to be a potentially good chassis host for the production of high-value pharmaceuticals and chemicals. Nevertheless, limited availability of selective markers and low efficiency of homologous recombination make this process difficult and time-consuming, particularly in the case of multistep biosynthetic pathways. Therefore, it is crucial to develop an efficient and marker-free multiloci gene knock-in method in P. pastoris.ResultsA non-homologous-end-joining defective strain (Δku70) was first constructed using the CRISPR-Cas9 based gene deficiency approach. It was then used as a parent strain for multiloci gene integration. Ten guide RNA (gRNA) targets were designed within 100 bp upstream of the promoters or downstream of terminator, and then tested using an eGFP reporter and confirmed as suitable single-locus integration sites. Three high-efficiency gRNA targets (PAOX1UP-g2, PTEF1UP-g1, and PFLD1UP-g1) were selected for double- and triple-locus co-integration. The integration efficiency ranged from 57.7 to 70% and 12.5 to 32.1% for double-locus and triple-locus integration, respectively. In addition, biosynthetic pathways of 6-methylsalicylic acid and 3-methylcatechol were successfully assembled using the developed method by one-step integration of functional genes. The desired products were obtained, which further established the effectiveness and applicability of the developed CRISPR-Cas9-mediated gene co-integration method in P. pastoris.ConclusionsA CRISPR-Cas9-mediated multiloci gene integration method was developed with efficient gRNA targets in P. pastoris. Using this method, multiple gene cassettes can be simultaneously integrated into the genome without employing selective markers. The multiloci integration strategy is beneficial for pathway assembly of complicated pharmaceuticals and chemicals expressed in P. pastoris.

Dataset Information

Integration of CRISPR/Cas9 with artificial intelligence for improved cancer therapeutics.

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Integration of CRISPR/Cas9 with artificial intelligence for improved cancer therapeutics.

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