Genetic Approach Research Articles

Genetic aspects of ataxias in a cohort of Turkish patients.

Ataxia is one of the clinical findings of the movement disorder disease group. Although there are many underlying etiological reasons, genetic etiology has an increasing significance thanks to the recently developing technology. The aim of this study is to present the variants detected in WES analysis excluding non-genetic causes, in patients with ataxia. Thirty-six patients who were referred to us with findings of ataxia and diagnosed through WES or other molecular genetic analysis methods were included in our study. At the same time, information such as the onset time of the complaints, consanguinity status between parents, and the presence of relatives with similar symptoms were evaluated. If available, the patient's biochemical and radiological test results were presented. Thirty-six patients were diagnosed through WES or CES. The rate of detected autosomal recessive inheritance disease was 80.5%, while that of autosomal dominant inheritance disease was 19.5%. Abnormal cerebellum was detected on brain MRI images in 26 patients, while polyneuropathy was detected on EMG in eleven of them. While the majority of the patients were compatible with similar cases reported in the literature, five patients had different/additional features (variants in MCM3AP, AGTPBP1, GDAP2, and SH3TC2 genes). The diagnosis of ataxia patients with unknown etiology is made possible thanks to these clues. Consideration of a genetic approach is recommended in patients with ataxia of unknown etiology.

A multi-objective genetic algorithm approach applied to compact meander branch line couplers design for 5G-enabled IoT applications

A multi-objective genetic algorithm approach applied to compact meander branch line couplers design for 5G-enabled IoT applications

Tracing the origin of alveolar stem cells in lung repair and regeneration

Alveolar type 2 (AT2) cells are stem cells of the alveolar epithelia. Previous genetic lineage tracing studies reported multiple cellular origins for AT2 cells after injury. However, conventional lineage tracing based on Cre-loxP has the limitation of non-specific labeling. Here, we introduced a dual recombinase-mediated intersectional genetic lineage tracing approach, enabling precise investigation of AT2 cellular origins during lung homeostasis, injury, and repair. We found AT1 cells, being terminally differentiated, did not contribute to AT2 cells after lung injury and repair. Distinctive yet simultaneous labeling of club cells, bronchioalveolar stem cells (BASCs), and existing AT2 cells revealed the exact contribution of each to AT2 cells post-injury. Mechanistically, Notch signaling inhibition promotes BASCs but impairs club cells' ability to generate AT2 cells during lung repair. This intersectional genetic lineage tracing strategy with enhanced precision allowed us to elucidate the physiological role of various epithelial cell types in alveolar regeneration following injury.

Circulating immune cell phenotyping is potentially relevant for diabetic retinopathy risk assessment

BackgroundInflammation is believed to play a central role in the development of diabetes mellitus and is a common feature of type 2 diabetes mellitus (T2DM). However, the association with diabetic retinopathy (DR) remains a topic of debate. MethodsThis study employed two-sample bidirectional Mendelian randomization (MR) analyses to establish causal associations between immune cell characteristics and DR. Using publicly available GWAS genetic data, we investigated the causal relationship between 731 immune cell characteristics and the risk of DR. A total of four types of immune features, including relative cell (RC), absolute cell (AC), median fluorescence intensities (MFI), and morphological parameters (MP), were included. Sensitivity analysis was conducted to assess the robustness, heterogeneity, and potential horizontal pleiotropy of the results. ResultsThirty-five immune cell phenotypes were correlated with the risk of developing DR among four immune traits (MFI, RC, AC, and MP), and DR resulted in altered expression of twenty-six immune cells. ConclusionWe have demonstrated a strong correlation between immune cell traits and DR using a genetic approach. This finding offers valuable insights for early DR prevention and future clinical research and treatment.

Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classification

Data-efficient image classification is a challenging task that aims to solve image classification using small training data. Neural network-based deep learning methods are effective for image classification, but they typically require large-scale training data and have major limitations such as requiring expertise to design network architectures and having poor interpretability. Evolutionary deep learning is a recent hot topic that combines evolutionary computation with deep learning. However, most evolutionary deep learning methods focus on evolving architectures of neural networks, which still suffer from limitations such as poor interpretability. To address this, this paper proposes a new genetic programming-based evolutionary deep learning approach to data-efficient image classification. The new approach can automatically evolve variable-length models using many important operators from both image and classification domains. It can learn different types of image features from colour or gray-scale images, and construct effective and diverse ensembles for image classification. A flexible multi-layer representation enables the new approach to automatically construct shallow or deep models/trees for different tasks and perform effective transformations on the input data via multiple internal nodes. The new approach is applied to solve five image classification tasks with different training set sizes. The results show that it achieves better performance in most cases than deep learning methods for data-efficient image classification. A deep analysis shows that the new approach has good convergence and evolves models with high interpretability, different lengths/sizes/shapes, and good transferability.

Expression, characterization and antivascular activity of amino acid sequence repeating collagen hexadecapeptide

Type V collagen is an essential component of the extracellular matrix (ECM), and its remodeling releases specific protein fragments that can specifically inhibit endothelial cell responses such as proliferation, migration, and invasion. In this study, we have successfully constructed two engineered strains of Pichia pastoris capable of producing recombinant collagen through a new genetic engineering approach. Through high-density fermentation, the expression of 1605 protein and 1610 protein could reach 2.72 g/L and 4.36 g/L. With the increase of repetition times, the yield also increased. Bioactivity analysis showed that recombinant collagen could block the angiogenic effect of FGF-2 on endothelial cells by eliminating FGF-2-induced endothelial cell migration and invasion. Collectively, the recombinant proteins we successfully expressed have a wide range of potential for inhibiting angiogenesis in the biomaterials and biomedical fields.

Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach

Antibiotics, as a class of environmental pollutants, pose a significant challenge due to their persistent nature and resistance to easy degradation. This study delves into modeling and optimizing conventional Fenton degradation of antibiotic sulfamethoxazole (SMX) and total organic carbon (TOC) under varying levels of H2O2, Fe2+ concentration, pH, and temperature removal using both statistical and artificial intelligence techniques including Multiple Regression Analysis (MRA), Support Vector Regression (SVR) and Artificial Neural Network (ANN). In statistical analysis, ANN model showcased an elevated predictive accuracy compared to its counterparts due to having lowest RMSE values of 0.986 and 1.173 for both SMX and TOC, respectively. Sensitivity showcased H2O2/Fe2+ ratio, time and pH as pivotal for SMX degradation, while in simultaneous SMX and TOC reduction, fine tuning the time, pH, and temperature was essential. Leveraging a Hybrid Genetic Algorithm-Desirability Optimization approach, the trained ANN model revealed an optimal desirability of 0.941 out of 1000 solutions which yielded a 91.18% SMX degradation and 87.90% TOC removal under following specific conditions: treatment time of 48.5 min, Fe2+: 7.05 mg L−1, H2O2: 128.82 mg L−1, pH: 5.1, initial SMX: 97.6 mg L−1, and a temperature: 29.8 °C. LC/MS analysis reveals multiple intermediates with higher m/z (242, 270 and 288) and lower m/z (98, 108, 156 and 173) values identified, however no aliphatic hydrocarbon was isolated, because of the low mineralization performance of Fenton process. Furthermore, some inorganic fragments like NH4+ and NO3− were also determined in solution. This comprehensive research enriches AI modeling for intricate Fenton-based contaminant degradation, advancing sustainable antibiotic removal strategies.

Transient Seizure Clusters and Epileptiform Activity Following Widespread Bilateral Hippocampal Interneuron Ablation.

Interneuron loss is a prominent feature of temporal lobe epilepsy in both animals and humans and is hypothesized to be critical for epileptogenesis. As loss occurs concurrently with numerous other potentially proepileptogenic changes, however, the impact of interneuron loss in isolation remains unclear. For the present study, we developed an intersectional genetic approach to induce bilateral diphtheria toxin-mediated deletion of Vgat-expressing interneurons from dorsal and ventral hippocampus. In a separate group of mice, the same population was targeted for transient neuronal silencing with DREADDs. Interneuron ablation produced dramatic seizure clusters and persistent epileptiform activity. Surprisingly, after 1 week seizure activity declined precipitously and persistent epileptiform activity disappeared. Occasional seizures (≈1/day) persisted to the end of the experiment at 4 weeks. In contrast to the dramatic impact of interneuron ablation, transient silencing produced large numbers of interictal spikes, a significant but modest increase in seizure occurrence and changes in EEG frequency band power. Taken together, findings suggest that the hippocampus regains relative homeostasis-with occasional breakthrough seizures-in the face of an extensive and abrupt loss of interneurons.

MULTI-OBJECTIVE GENETIC ALGORITHM FOR THE ASSEMBLY LINE WORKER ASSIGNMENT AND BALANCING PROBLEM: A CASE STUDY IN THE AUTOMOTIVE SUPPLY INDUSTRY

The primary challenge in assembly line design is the need for more appropriately allocating tasks and workers to workstations. This study addresses the problem of line balancing and worker assignments, considering the performance disparities among workers during the line balancing process. In the relevant literature, this problem is known as the Assembly Line Worker Assignment and Balancing (ALWAB) problem. This research examines a multi-objective ALWAB Type-2 problem, simultaneously evaluating cycle time and squared load assignment objectives. The study is conducted based on a real-life scenario in a sub-industry automotive industry that manufactures cable equipment. To solve this problem, a multi-objective genetic algorithm approach is proposed. Recognising that the selection of parameter values will influence the algorithm’s performance, parameter calibration has been performed. A full factorial experimental design and the irace method have been utilised for this purpose. The results are compared with those using parameter values utilised for similar problems in the literature. Furthermore, a sensitivity analysis has been carried out to examine the impact of various relative weight values of the objectives on the result. The results indicate that the experimental design generally yields superior results compared to other methods.

Insight into Insulin-like Growth Factor-1 Receptor (IGF-1R) gene mutations: Implications for growth disorders and treatment: A review of the literature and case report

Background: Insulin-like Growth Factor -1 Receptor (IGF-1R) and its ligand, IGF-1, are crucial for human tissue growth and development. Mutations in IGF-1R and, to a lesser extent, IGF-1 genes lead to diverse growth disorders, characterized by intrauterine growth retardation and postnatal growth challenges. Case report: We present a case of a 6-year-old girl with speech and mild cognitive delays, exhibiting normal motor skills, no neurological issues, and standard vital signs. Her growth parameters indicated significant retardation, with a height standard deviation score (Ht-SDS) of -2 and an IGF-1 level of +1.8 SDS, normal thyroid function and delayed bone age. Genetic analysis identified a 3335 mbp interstitial loss in 15q26.1, encompassing the IGF-1R gene, critical for growth and development. Literature review: Analysis of 34 papers provided insight into the genetic complexities of IGF-1R and IGF-1 mutations. Studies ranged from familial cases to cohort studies, uncovering mutations including missense mutations, deletions, and copy number variations (CNVs), each associated with unique growth disorder phenotypes. Advances in diagnostic techniques like multiplex ligation-dependent probe amplification (MLPA) and whole exome sequencing (WES) have been pivotal in identifying these mutations, facilitating more targeted management approaches. Conclusions: This case and review of literature underscore the importance of an integrated genetic, endocrine, and developmental approach in managing growth hormone deficiency (GHD) and IGF-1 resistance. The variability in growth disorders and response to therapy highlights the need for personalized treatment plans, informed by genetic insights, to optimize outcomes for patients with these complex conditions.

Integrative annotation scores of variants for impact on RNA binding protein activities.

The ENCODE project generated a large collection of eCLIP-seq RNA binding protein (RBP) profiling data with accompanying RNA-seq transcriptomes of shRNA knockdown of RBPs. These data could have utility in understanding the functional impact of genetic variants, however their potential has not been fully exploited. We implement INCA (Integrative annotation scores of variants for impact on RBP activities) as a multi-step genetic variant scoring approach that leverages the ENCODE RBP data together with ClinVar and integrates multiple computational approaches to aggregate evidence. INCA evaluates variant impacts on RBP activities by leveraging genotypic differences in cell lines used for eCLIP-seq. We show that INCA provides critical specificity, beyond generic scoring for RBP binding disruption, for candidate variants and their linkage-disequilibrium partners. As a result, it can, on average, augment scoring of 46.2% of the candidate variants beyond generic scoring for RBP binding disruption and aid in variant prioritization for follow-up analysis. INCA is implemented in R and is available at https://github.com/keleslab/INCA.

Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach.

The precise placement of antennas is essential to ensure effective coverage, service quality, and network capacity in wireless communications, particularly given the exponential growth of mobile connectivity. The antenna positioning problem (APP) has evolved from theoretical approaches to practical solutions employing advanced algorithms, such as evolutionary algorithms. This study focuses on developing innovative web tools harnessing genetic algorithms to optimize antenna positioning, starting from propagation loss calculations. To achieve this, seven empirical models were reviewed and integrated into an antenna positioning web tool. Results demonstrate that, with minimal configuration and careful model selection, a detailed analysis of antenna positioning in any area is feasible. The tool was developed using Java 17 and TypeScript 5.1.6, utilizing the JMetal framework to apply genetic algorithms, and features a React-based web interface facilitating application integration. For future research, consideration is given to implementing a server capable of analyzing the environment based on specific area selection, thereby enhancing the precision and objectivity of antenna positioning analysis.

Fecal genotyping to estimate small mammal population size, with a comparison to live mark-recapture estimates

Live capture-recapture is often considered the gold standard for estimating wildlife population size or density, but the approach can be limited by permitting requirements, required labor, welfare concerns, and biased estimates resulting from heterogeneity in individual behavior. Noninvasive genetic sampling (e.g., from fecal pellets) offers a powerful alternative approach, but this method’s success varies among taxa, with little research available on its use in rodents. Here, we addressed a series of questions to develop a noninvasive genetic sampling approach for the endangered giant kangaroo rat (Dipodomys ingens): (1) how quickly does DNA degrade in natural conditions, (2) how many pellets are required to recover a genotype, (3) how often do multiple individuals contaminate a pooled sample from a single sampling location, and (4) how do variable and parameter estimates from noninvasive genetic sampling compare to live-trapping mark-recapture estimates? We found that fecal pellets were successfully genotyped up to 9 days (estimated probability of recovery = 0.78) after exposure to hot, arid conditions, but that rate fell precipitously soon after. Although giant kangaroo rats are territorial, multiple individuals deposited fecal pellets at the same sampling locations; however, single pellets contained sufficient DNA to recover genotypes and to identify individuals, so contamination was not a problem for this approach. Capture probabilities were lower using noninvasive genetic sampling ( = 0.26, SE = 0.01) than live trapping ( = 0.40, SE = 0.06). Population estimates were generally similar using noninvasive genetic sampling, although they were quite a bit higher ( = 64 , = 38) on one grid. Noninvasive genetic sampling can overcome many of the limitations of live-trapping for small mammals, but the approach should be tested in additional taxa and systems to provide more generalizable recommendations for sampling schemes.

Review and meta-analysis of the genetic Minimal Cut Set approach for gene essentiality prediction in cancer metabolism.

Cancer metabolism is a marvellously complex topic, in part, due to the reprogramming of its pathways to self-sustain the malignant phenotype in the disease, to the detriment of its healthy counterpart. Understanding these adjustments can provide novel targeted therapies that could disrupt and impair proliferation of cancerous cells. For this very purpose, genome-scale metabolic models (GEMs) have been developed, with Human1 being the most recent reconstruction of the human metabolism. Based on GEMs, we introduced the genetic Minimal Cut Set (gMCS) approach, an uncontextualized methodology that exploits the concepts of synthetic lethality to predict metabolic vulnerabilities in cancer. gMCSs define a set of genes whose knockout would render the cell unviable by disrupting an essential metabolic task in GEMs, thus, making cellular proliferation impossible. Here, we summarize the gMCS approach and review the current state of the methodology by performing a systematic meta-analysis based on two datasets of gene essentiality in cancer. First, we assess several thresholds and distinct methodologies for discerning highly and lowly expressed genes. Then, we address the premise that gMCSs of distinct length should have the same predictive power. Finally, we question the importance of a gene partaking in multiple gMCSs and analyze the importance of all the essential metabolic tasks defined in Human1. Our meta-analysis resulted in parameter evaluation to increase the predictive power for the gMCS approach, as well as a significant reduction of computation times by only selecting the crucial gMCS lengths, proposing the pertinency of particular parameters for the peak processing of gMCS.

Expression of Multicopy Tandem Recombinant Ginseng Hexapeptide in Bacillus subtilis and the Evaluation of Antiaging Activity.

Ginseng oligopeptides are naturally occurring small-molecule peptides extracted from ginseng that exhibit positive effects on health and longevity. However, the current industrial production of ginseng oligopeptides primarily relies on plant extraction and chemical synthesis. In this study, we proposed a novel genetic engineering approach to produce active ginseng peptides through multicopy tandem insertion (5 and 15 times). The recombinant ginseng peptides were successfully produced from engineered Bacillus subtilis with an increasing yield from 356.55 to 2900 mg/L as the repeats multiple. Additionally, an oxidative stress-induced aging model caused by H2O2 was established to evaluate whether the recombinant ginseng peptides, without enzymatic hydrolysis into individual peptides, also have positive effects on antiaging. The results demonstrated that all two kinds of recombinant ginseng peptides could also delay cellular aging through various mechanisms, such as inhibiting cell cycle arrest, suppressing the expression of pro-inflammatory factors, and enhancing cellular antioxidant capacity.

CGS-Mask: Making Time Series Predictions Intuitive for All

Artificial intelligence (AI) has immense potential in time series prediction, but most explainable tools have limited capabilities in providing a systematic understanding of important features over time. These tools typically rely on evaluating a single time point, overlook the time ordering of inputs, and neglect the time-sensitive nature of time series applications. These factors make it difficult for users, particularly those without domain knowledge, to comprehend AI model decisions and obtain meaningful explanations. We propose CGS-Mask, a post-hoc and model-agnostic cellular genetic strip mask-based saliency approach to address these challenges. CGS-Mask uses consecutive time steps as a cohesive entity to evaluate the impact of features on the final prediction, providing binary and sustained feature importance scores over time. Our algorithm optimizes the mask population iteratively to obtain the optimal mask in a reasonable time. We evaluated CGS-Mask on synthetic and real-world datasets, and it outperformed state-of-the-art methods in elucidating the importance of features over time. According to our pilot user study via a questionnaire survey, CGS-Mask is the most effective approach in presenting easily understandable time series prediction results, enabling users to comprehend the decision-making process of AI models with ease.

Abstract 6595: HDAC8 targeting impairs Foxp3+Treg cell function and promotes anti-tumor immunity

Abstract HDAC8 is an evolutionarily distinct, X-linked, zinc-dependent class I histone/protein deacetylase implicated in developmental disorders, parasitic infections, myopathy, and cancers such as neuroblastoma, gastric cancer, hepatocellular carcinoma, oral squamous cell carcinoma, and childhood acute lymphoblastic leukemia. Here, we highlight a hitherto unknown role of HDAC8 in immune cells by presenting data on conditional targeting of HDAC8 in T cells and the effects of selective HDAC8 inhibitors (HDAC8i) on T cell-dependent immune responses. First, as a genetic approach, we produced C57BL/6 mice with floxed exon 3 of the HDAC8 gene suitable for targeted deletion of HDAC8 and, after crossing with syngeneic CD4cre mice, demonstrated conditional deletion of HDAC8 and enhanced acetylation of SMC3, a classic HDAC8 substrate, in their T-cells. Next, in a pharmacologic approach, we tested isoform-selective inhibitors of HDAC8 (OJ-1, PCI-34051) and assessed effects on Foxp3+ T-regulatory (Treg) cell suppressive function. Finally, we performed flow cytometry, RNAseq, CHIP-seq and mass spectrometry to investigate the underlying mechanisms by which HDAC8 knockout affected Treg function. Our data demonstrate that knocking down or inhibiting HDAC8: (i) impaired murine Treg suppressive function in vitro and in vivo, including inhibiting the ability of Tregs to promote mouse cardiac allograft survival (p<0.01); (ii) decreased Treg function in homeostatic proliferation assays (p<0.01), e.g., involving adoptive transfer of WT or HDAC8-/- Tregs plus WT conventional T cells into immunodeficient hosts; (iii) decreased intratumoral Tregs, increased CD4 and CD8 T cells, increased production of effectors such as IFN-g and granzyme-B, and limited growth of syngeneic mouse non-small cell lung cancer cell lines (p<0.01) (whereas no effect of Hdac8i on tumor growth was seen in immunodeficient hosts, indicating the key action was via immune cell targeting). Mechanistically, HDAC8 co-precipitated with Foxp3 and NFAT5 and promoted the deacetylation of Foxp3 and NFAT5, and knockout of HDAC8 enhanced the acetylation level of NFAT5 and promoted cytokine expression. Hence, our combined genetic and pharmacologic studies establish the importance of HDAC8 in Foxp3+ Treg cells and show that therapy with selective HDAC8 inhibitors can be a novel therapeutic approach in immuno-oncology. Citation Format: Fanhua Kong, Liqing Wang, Aaron Beeler, Wayne W. Hancock. HDAC8 targeting impairs Foxp3+Treg cell function and promotes anti-tumor immunity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6595.

No relationship between male pubertal timing and depression - new insights from epidemiology and Mendelian randomization.

In males, the relationship between pubertal timing and depression is understudied and less consistent than in females, likely for reasons of unmeasured confounding. To clarify this relationship, a combined epidemiological and genetic approach was chosen to exploit the methodological advantages of both approaches. Data from 2026 males from a nationwide, representative study were used to investigate the non-/linear relationship between pubertal timing defined by the age at voice break and depression, considering a multitude of potential confounders and their interactions with pubertal timing. This analysis was complemented by Mendelian randomization (MR), which is robust to inferential problems inherent to epidemiological studies. We used 71 single nucleotide polymorphisms related to pubertal timing in males as instrumental variable to clarify its causal relationship with depression based on data from 807 553 individuals (246 363 cases and 561 190 controls) by univariable and multivariable MR, including BMI as pleiotropic phenotype. Univariable MR indicated a causal effect of pubertal timing on depression risk (inverse-variance weighted: OR 0.93, 95%-CI [0.87-0.99)], p = 0.03). However, this was not confirmed by multivariable MR (inverse-variance weighted: OR 0.95, 95%-CI [0.88-1.02)], p = 0.13), consistent with the epidemiological approach (OR 1.01, 95%-CI [0.81-1.26], p = 0.93). Instead, the multivariable MR study indicated a causal relationship of BMI with depression by two of three methods. Pubertal timing is not related to MDD risk in males.

Abstract 6988: TP53RK regulates DNA replication by CDC7-mediated MCM helicase phosphorylation in colorectal cancer

Abstract Background: We identify TP53 regulating kinase (TP53RK), which showed the highest cell growth inhibition efficiency in six colon cancer cell lines. TP53RK is overexpressed in various cancer types, including multiple myeloma and skin cancer, but the mechanism for its tumorigenesis in colon cancer is unknown. Therefore, this study aims to reveal the tumorigenesis mechanism of TP53RK, which is overexpressed in Colorectal Cancer (CRC), through global and phospho-proteomics. Method: A total 5 CRC cell lines (HT29, SW480, HCT116, H508 and CaCO2), colon normal fibroblast CRL1459, HCT116 p53 null cell and patient-derived normal organoid were used. Immunoblotting, MTT assay, Colony formation assay, Annexin-V assay and cell cycle analysis were performed for evaluation of TP53RK loss-of-function. With kinase-substrate enrichment analysis with phospho-proteome analysis, MCM2 was found to be a substrate for the kinase regulated by TP53RK. Results: High-throughput genetic screening approach have been widely applied to the study the gene function and molecular mechanism associated with tumorigenesis. By using genome-wide CRISPR/Cas9 library screening, we identify TP53RK, the first committed negative-selected gene, as a tyrosine kinase in the colorectal cancer(CRC) specific biomarker. Through proteome analysis, we found that depletion of TP53RK can hypo-phosphorylate the DNA helicase complex, MCM2 (minichromosome maintenance protein2). According to previous studies, the phosphorylation of MCM2 is regulated by CDC7 (cell division cycle7), and the abnormal states of CDC7 and MCM2 cause DNA replication disorder. Our results show that TP53RK expression is upregulated in CRC and its depletion results in decreased CDC7 expression and hypo-phosphorylation of the MCM complex. Decreased CDC7 expression due to its instability after TP53RK depletion can lead to DNA replication errors. DNA replication errors can lead cancer cells to apoptosis, suggesting that they may be a strategy for cancer treatment. In summary, we provide TP53RK as a novel prognostic and therapeutic target in CRC. Conclusion: To recapitulate briefly, our findings suggest that the interaction of TP53RK with CDC7 can regulate CDC7 protein stability and stabilized CDC7 can phosphorylate MCM2 to initiate DNA replication. In other words, because overexpression of TP53RK acts as an oncogene that promotes tumor progression in CRC, depletion of TP53RK can degrade CDC7 and induce colon cancer cells to death or regression. Citation Format: Younghee Choi, Ji-won Park, Jun-kyu Kang, Eun-ju Kim, Sang-Hyun Song, Eugene C. Yi, Tae-You Kim. TP53RK regulates DNA replication by CDC7-mediated MCM helicase phosphorylation in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6988.

Abstract 5708: Silence exportin 7 sensitizes esophageal squamous cell cancer to CDK4/6 inhibition through block the cell cycle coresectory

Abstract Introduction: There is a lack of effective target therapies for esophageal squamous cell cancer. Our previous studies have demonstrated that CDK4/6 is a potency target for ESCC and combination with ERBB inhibitors is sufficient to achieve durable response. The aim of the current study is to prospectively map the landscape of sensitivity and resistance to CDK4/6 inhibition and develop novel combination therapies in ESCC. Experimental Procedures: We performed a genome-wide functional genetic screening and mini-pool designed CRISPR screen approaches to identify the modulators whose depletion sensitize CDK4/6 inhibition or confer resistance to the CDK4/6 inhibitor Palbociclib and elucidate new therapeutic strategies. Results: Our screen identified RB as the most enriched sgRNA, while guides targeting CCNE1 and CDK2 as the most depletion sgRNAs after CDK4/6 inhibition. These results validates our experimental approach as RB loss and CCNE1/CDK2 reactivation is the main mechanisms of CDK4/6 resistance. After gathering potential candidates from both screens, we found that genetically ablation of Exportin 7, a nuclear export factor, strongly sensitize CDK4/6 inhibition both in vitro and in vivo. RNAseq revealed a further repression of transcriptional activity of E2F and G2M by addition of XPO7depletion under CDK4/6 inhibitor treatment. To increase our insight in the molecular mechanism that could explain the synergy between XPO7 and CDK4/6, we further performed proteomics of nuclear and cytoplasm in ESCC lines with or without CDK4/6 inhibition. We found that silence XPO7 result in nuclear accumulation of mitosis-regulated genes such as CENPM, KIF4A and WEE1. Combined CDK4/6 inhibition with XPO7 depletion results in further downregulate of CENPM and KIF4A expression in nucleus, abrogating compensatory activation of cell cycle regulation and promote the cytostatic effect in ESCC. We further validated that CENPM and KIF4A depletion also sensitize CDK4/6 inhibition, and consequentially use WEE1 inhibitor after CDK4/6 inhibitor also effectively block the growth of ESCC lines. Conclusion: Overall, our comprehensive functional genetic screening approach revealed modulation of sensitive and resistance to the inhibition of CDK4/6 in ESCC. XPO7 was identified as a driver to change cell cycle landscape and merits as a therapeutic target combined with CDK4/6 inhibition in ESCC, which is beneficial to provide a novel treatment strategy. Citation Format: Zhong Wu, Lin Xu, Chuang Jiang, Adam Bass, Jin Zhou. Silence exportin 7 sensitizes esophageal squamous cell cancer to CDK4/6 inhibition through block the cell cycle coresectory [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5708.