scholarly journals CRISPR Screens in Synthetic Lethality and Combinatorial Therapies for Cancer

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1591
Author(s):  
Laia Castells-Roca ◽  
Eudald Tejero ◽  
Benjamín Rodríguez-Santiago ◽  
Jordi Surrallés
Keyword(s):  
Large Scale ◽  
Complex Disease ◽  
Synthetic Lethality ◽  
Clinical Success ◽  
Parp Inhibitors ◽  
Driver Mutations ◽  
Future Directions ◽  
Cancer Driver ◽  
Cancer Field ◽  
Crispr Screen

Cancer is a complex disease resulting from the accumulation of genetic dysfunctions. Tumor heterogeneity causes the molecular variety that divergently controls responses to chemotherapy, leading to the recurrent problem of cancer reappearance. For many decades, efforts have focused on identifying essential tumoral genes and cancer driver mutations. More recently, prompted by the clinical success of the synthetic lethality (SL)-based therapy of the PARP inhibitors in homologous recombinant deficient tumors, scientists have centered their novel research on SL interactions (SLI). The state of the art to find new genetic interactions are currently large-scale forward genetic CRISPR screens. CRISPR technology has rapidly evolved to be a common tool in the vast majority of laboratories, as tools to implement CRISPR screen protocols are available to all researchers. Taking advantage of SLI, combinatorial therapies have become the ultimate model to treat cancer with lower toxicity, and therefore better efficiency. This review explores the CRISPR screen methodology, integrates the up-to-date published findings on CRISPR screens in the cancer field and proposes future directions to uncover cancer regulation and individual responses to chemotherapy.

scholarly journals BET Proteins as Attractive Targets for Cancer Therapeutics

2021 ◽  
Vol 22 (20) ◽  
pp. 11102
Author(s):  
Joanna Sarnik ◽  
Tomasz Popławski ◽  
Paulina Tokarz
Keyword(s):  
Homologous Recombination ◽  
Transcriptional Control ◽  
Synthetic Lethality ◽  
Clinical Success ◽  
Predictive Biomarkers ◽  
Cancer Therapeutics ◽  
Parp Inhibitors ◽  
Novel Approach ◽  
Bet Inhibitors ◽  
Recombination Pathway

Transcriptional dysregulation is a hallmark of cancer and can be an essential driver of cancer initiation and progression. Loss of transcriptional control can cause cancer cells to become dependent on certain regulators of gene expression. Bromodomain and extraterminal domain (BET) proteins are epigenetic readers that regulate the expression of multiple genes involved in carcinogenesis. BET inhibitors (BETis) disrupt BET protein binding to acetylated lysine residues of chromatin and suppress the transcription of various genes, including oncogenic transcription factors. Phase I and II clinical trials demonstrated BETis’ potential as anticancer drugs against solid tumours and haematological malignancies; however, their clinical success was limited as monotherapies. Emerging treatment-associated toxicities, drug resistance and a lack of predictive biomarkers limited BETis’ clinical progress. The preclinical evaluation demonstrated that BETis synergised with different classes of compounds, including DNA repair inhibitors, thus supporting further clinical development of BETis. The combination of BET and PARP inhibitors triggered synthetic lethality in cells with proficient homologous recombination. Mechanistic studies revealed that BETis targeted multiple essential homologous recombination pathway proteins, including RAD51, BRCA1 and CtIP. The exact mechanism of BETis’ anticancer action remains poorly understood; nevertheless, these agents provide a novel approach to epigenome and transcriptome anticancer therapy.

In silico discovery of novel flavonoids as poly ADP ribose polymerase (PARP) inhibitors

2020 ◽  
Vol 16 ◽  
Author(s):  
Ashish Shah ◽  
Ghanshyam Parmar ◽  
Avinash Kumar Seth
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Synthetic Lethality ◽  
Parp Inhibitor ◽  
Parp Inhibitors ◽  
Docking Studies ◽  
Docking Score ◽  
Docking Method ◽  
Anti Cancer ◽  
In Silico Toxicity

Background: The concept of synthetic lethality is emerging field in the treatment of cancer and can be applied for new drug development of cancer as it has been already represented by Poly (ADP-ribose) polymerase (PARPs) inhibitors. Objectives: In this study we performed virtual screening of 329 flavonoids obtained from Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target (NPACT) database to identify novel PARP inhibitors. Materials and methods: Virtual screening carried out using different In Silico methods which includes molecular docking studies, prediction of druglikeness and In Silico toxicity studies. Results: Fifteen out of 329 flavonoids achieved better docking score as compared to rucaparib which is an FDA approved PARP inhibitor. These 15 hits were again rescored using accurate docking mode and drug-likeliness properties were evaluated. Accuracy of docking method was checked using re-docking. Finally NPACT00183 and NPACT00280 were identified as potential PARP inhibitors with docking score of -139.237 and -129.36 respectively. These two flavonoids were also showed no AMES toxicity and no carcinogenicity which was predicted using admetSAR. Conclusion: Our finding suggests that NPACT00183 and NPACT00280 have promising potential to be further explored as PARP inhibitors.

scholarly journals A Survey on Contrastive Self-Supervised Learning

Technologies ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 2
Author(s):  
Ashish Jaiswal ◽  
Ashwin Ramesh Babu ◽  
Mohammad Zaki Zadeh ◽  
Debapriya Banerjee ◽  
Fillia Makedon
Keyword(s):  
Computer Vision ◽  
Supervised Learning ◽  
Language Processing ◽  
Large Scale ◽  
Performance Comparison ◽  
Extensive Review ◽  
Future Directions ◽  
Dominant Component ◽  
Supervised Methods ◽  
The Cost

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudolabels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same sample close to each other while trying to push away embeddings from different samples. This paper provides an extensive review of self-supervised methods that follow the contrastive approach. The work explains commonly used pretext tasks in a contrastive learning setup, followed by different architectures that have been proposed so far. Next, we present a performance comparison of different methods for multiple downstream tasks such as image classification, object detection, and action recognition. Finally, we conclude with the limitations of the current methods and the need for further techniques and future directions to make meaningful progress.

scholarly journals Palliative treatment for malignant gastrointestinal obstruction with peritoneal carcinomatosis: enteral stenting versus surgery

2020 ◽  
Vol 08 (10) ◽  
pp. E1487-E1494
Author(s):  
Veeravich Jaruvongvanich ◽  
FNU Chesta ◽  
Anushka Baruah ◽  
Meher Oberoi ◽  
Daniel Adamo ◽  
...  
Keyword(s):  
Adverse Events ◽  
Hospital Stay ◽  
Peritoneal Carcinomatosis ◽  
Large Scale ◽  
Clinical Success ◽  
Eastern Cooperative Oncology Group ◽  
Length Of Hospital Stay ◽  
Palliative Surgery ◽  
Gastrointestinal Obstruction ◽  
Malignant Gastrointestinal Obstruction

Abstract Background and study aims Management of malignant gastrointestinal obstruction (MGIO) is more challenging in the presence of peritoneal carcinomatosis (PC). Outcomes data to guide the management of MGIO with PC are lacking. We aimed to compare the clinical outcomes and adverse events between endoscopic and surgical palliation and identify predictors of stent success in patients with MGIO with PC. Patients and methods Consecutive inpatients with MGIO with PC between 2000 and 2018 who underwent palliative surgery or enteral stenting were included. Clinical success was defined as relief of obstructive symptoms. Results Fifty-seven patients with enteral stenting and 40 with palliative surgery were compared. The two groups did not differ in rates of technical success, 30-day mortality, or recurrence. Clinical success from a single intervention (63.2 % versus 95 %), luminal patency duration (27 days vs. 145 days), and survival length (148 days vs. 336 days) favored palliative surgery (all P < 0.05) but the patients in the surgery group had a trend toward better Eastern Cooperative Oncology Group (ECOG) status. The rate of adverse events (AEs) (10.5 % vs. 50 %), the severity of AEs, and length of hospital stay (4.5 days vs. 9 days) favored enteral stenting (P < 0.05). The need for more than one stent was associated with a higher likelihood of stent failure. Conclusions Our study suggests that enteral stenting is safer and associated with a shorter hospital stay than palliative surgery, although unlike other MGIOs, clinical success is lower in MGIO with PC. Identification of the right candidates and potential predictors of clinical success in ECOG-matched large-scale studies is needed to validate these results.

scholarly journals Genetic and Transcriptomic Biomarkers in Neurodegenerative Diseases: Current Situation and the Road Ahead

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1030
Author(s):  
Julie Lake ◽  
Catherine S. Storm ◽  
Mary B. Makarious ◽  
Sara Bandres-Ciga
Keyword(s):  
Neurodegenerative Diseases ◽  
Large Scale ◽  
Disease Diagnosis ◽  
Open Science ◽  
Future Directions ◽  
The Road ◽  
Current State ◽  
Molecular Complexity ◽  
Science Framework ◽  
Lateral Sclerosis

Neurodegenerative diseases are etiologically and clinically heterogeneous conditions, often reflecting a spectrum of disease rather than well-defined disorders. The underlying molecular complexity of these diseases has made the discovery and validation of useful biomarkers challenging. The search of characteristic genetic and transcriptomic indicators for preclinical disease diagnosis, prognosis, or subtyping is an area of ongoing effort and interest. The next generation of biomarker studies holds promise by implementing meaningful longitudinal and multi-modal approaches in large scale biobank and healthcare system scale datasets. This work will only be possible in an open science framework. This review summarizes the current state of genetic and transcriptomic biomarkers in Parkinson’s disease, Alzheimer’s disease, and amyotrophic lateral sclerosis, providing a comprehensive landscape of recent literature and future directions.

scholarly journals Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma

2016 ◽  
Vol 113 (42) ◽  
pp. E6409-E6417 ◽  
Author(s):  
David G. McFadden ◽  
Katerina Politi ◽  
Arjun Bhutkar ◽  
Frances K. Chen ◽  
Xiaoling Song ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Mouse Models ◽  
Cancer Progression ◽  
Large Scale ◽  
Human Cancer ◽  
Genetically Engineered ◽  
Model Systems ◽  
Driver Mutations ◽  
Genetic Profile ◽  
Genetically Engineered Mouse Models

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity.

scholarly journals Adherence and competence assessment in studies of CBT for psychosis: current status and future directions

2011 ◽  
Vol 20 (2) ◽  
pp. 121-126 ◽  
Author(s):  
D. Fowler ◽  
R. Rollinson ◽  
P. French
Keyword(s):  
Cognitive Therapy ◽  
Large Scale ◽  
Rating Scale ◽  
Current Status ◽  
Behaviour Therapy ◽  
Future Directions ◽  
Making Sense ◽  
Cognitive Behaviour ◽  
The Uk ◽  
Careful Assessment

All good quality trials of psychological interventions need to check formally that therapists have used the techniques prescribed in the published therapy manuals, and that the therapy has been carried out competently. This paper reviews methods of assessing adherence and competence used in recent large-scale trials of Cognitive Behaviour Therapy (CBT) for psychosis in the UK carried out by our research groups. A combination of the Cognitive Therapy Rating Scale and specific versions of the Cognitive Therapy for Psychosis Adherence Scales provides an optimal assessment of adherence and competence. Careful assessment of the competence and adherence can help identify the procedures actually carried out with individuals within trials. The basic use of such assessments is to provide an external check on treatment fidelity on a sample of sessions. Such assessment can also provide the first step towards moving research towards making sense of CBT for psychosis as a complex intervention and identifying which techniques work for which problems of people with psychosis, at which stages of disorder?

Exploiting Synthetic Lethal Network for Precision Treatment of Clear Cell Renal Cell Carcinoma

2021 ◽  
Author(s):  
Zhicheng Liu ◽  
Dongxu Lin ◽  
Linmeng Zhang ◽  
Chen Yang ◽  
Bin Guo ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Large Scale ◽  
Target Genes ◽  
Clear Cell ◽  
Therapeutic Potential ◽  
Synthetic Lethality ◽  
Treatment Modalities ◽  
Cell Renal Cell Carcinoma

Abstract Background The emerging of targeted therapies has revolutionized the treatment modalities of advanced clear cell renal cell carcinoma (ccRCC) over the past fifteen years. However, lack of personalized treatment limits the development of effective clinical guidelines and improvement of patient prognosis. In this study, large-scale genomic profiles of ccRCC cohorts were exploited for conducting an integrative analysis. Method Based on synthetic lethality (SL), a concept that simultaneous losses of two genes cause cell death while a single loss does not, we sought to develop a computational pipeline to infer potential SL partners of ccRCC. Drug response prediction were received from three pharmacological databases to select agents which are likely to be effective in precisely treating patients with target gene mutation. Results We developed a credible method to identify SL pairs and determined a list of 72 candidate pairs which might be utilized to selectively eliminate tumors with genetic aberrations through SL partners of specific mutations. Further analysis identified BRD4 and PRKDC as novel medicine targets for patients with BAP1 mutations. After mapping these target genes to comprehensive drug datasets, two agents (BI-2536 and PI-103) were found to have considerable therapeutic potential in BAP1 mutant tumors. Conclusion Overall, our findings provide insight into the overview of ccRCC mutation patterns and offer novel opportunities for improving individualized cancer treatment.

scholarly journals Predictors and Modulators of Synthetic Lethality: An Update on PARP Inhibitors and Personalized Medicine

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Stephen Murata ◽  
Catherine Zhang ◽  
Nathan Finch ◽  
Kevin Zhang ◽  
Loredana Campo ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Parp Inhibitor ◽  
Advanced Ovarian Cancer ◽  
Parp Inhibitors ◽  
Damage Repair ◽  
Trial Testing ◽  
United States Food ◽  
States Food ◽  
And Personalized Medicine ◽  
Inhibitor Treatment

Poly(ADP-ribose) polymerase (PARP) inhibitors have proven to be successful agents in inducing synthetic lethality in several malignancies. Several PARP inhibitors have reached clinical trial testing for treatment in different cancers, and, recently, Olaparib (AZD2281) has gained both United States Food and Drug Administration (USFDA) and the European Commission (EC) approval for use inBRCA-mutated advanced ovarian cancer treatment. The need to identify biomarkers, their interactions in DNA damage repair pathways, and their potential utility in identifying patients who are candidates for PARP inhibitor treatment is well recognized. In this review, we detail many of the biomarkers that have been investigated for their ability to predict both PARP inhibitor sensitivity and resistance in preclinical studies as well as the results of several clinical trials that have tested the safety and efficacy of different PARP inhibitor agents inBRCAand non-BRCA-mutated cancers.

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