Identification Of Targets Research Articles

Regulation of seed dormancy by histone post-translational modifications in the model plant Arabidopsis thaliana.

Plants synchronize their growth and development with environmental changes, which is critical for their survival. Among their life cycle transitions, seed germination is key for ensuring the survival and optimal growth of the next generation. However, even under favorable conditions, oftentimes germination can be blocked by seed dormancy, a regulatory multilayered checkpoint integrating internal and external signals. Intricate genetic and epigenetic mechanisms underlie seed dormancy establishment, maintenance, and release. In this review, we focus on recent advances that shed light on the complex mechanisms associated with physiological dormancy, prevalent in seed plants, with Arabidopsis thaliana serving as a model. Here, we summarize the role of multiple epigenetic regulators, but with a focus on histone modifications like acetylation and methylation, that finely tune dormancy responses and influence dormancy-associated gene expression. Understanding these mechanisms can lead to a better understanding of seed biology in general, as well as result in the identification of possible targets for breeding climate-resilient plants.

Identification of ligand and receptor interactions in CKD and MASH through the integration of single cell and spatial transcriptomics.

Chronic Kidney Disease (CKD) and Metabolic dysfunction-associated steatohepatitis (MASH) are metabolic fibroinflammatory diseases. Combining single-cell (scRNAseq) and spatial transcriptomics (ST) could give unprecedented molecular disease understanding at single-cell resolution. A more comprehensive analysis of the cell-specific ligand-receptor (L-R) interactions could provide pivotal information about signaling pathways in CKD and MASH. To achieve this, we created an integrative analysis framework in CKD and MASH from two available human cohorts. The analytical framework identified L-R pairs involved in cellular crosstalk in CKD and MASH. Interactions between cell types identified using scRNAseq data were validated by checking the spatial co-presence using the ST data and the co-expression of the communicating targets. Multiple L-R protein pairs identified are known key players in CKD and MASH, while others are novel potential targets previously observed only in animal models. Our study highlights the importance of integrating different modalities of transcriptomic data for a better understanding of the molecular mechanisms. The combination of single-cell resolution from scRNAseq data, combined with tissue slide investigations and visualization of cell-cell interactions obtained through ST, paves the way for the identification of future potential therapeutic targets and developing effective therapies.

Assessment of TROP2, CEACAM5 and DLL3 in metastatic prostate cancer: Expression landscape and molecular correlates

Therapeutic approaches targeting proteins on the surface of cancer cells have emerged as an important strategy for precision oncology. To capitalize on the potential impact of drugs targeting surface proteins, detailed knowledge about the expression patterns of the target proteins in tumor tissues is required. In castration-resistant prostate cancer (CRPC), agents targeting prostate-specific membrane antigen (PSMA) have demonstrated clinical activity. However, PSMA expression is lost in a significant number of CRPC tumors. The identification of additional cell surface targets is necessary to develop new therapeutic approaches. Here, we performed a comprehensive analysis of the expression heterogeneity and co-expression patterns of trophoblast cell-surface antigen 2 (TROP2), delta-like ligand 3 (DLL3), and carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) in CRPC samples from a rapid autopsy cohort. We show that DLL3 and CEACAM5 exhibit the highest expression in neuroendocrine prostate cancer (NEPC), while TROP2 is expressed across different CRPC molecular subtypes, except for NEPC. We further demonstrated that AR alterations were associated with higher expression of PSMA and TROP2. Conversely, PSMA and TROP2 expression was lower in RB1-altered tumors. In addition to genomic alterations, we show a tight correlation between epigenetic states, particularly histone H3 lysine 27 methylation (H3K27me3) at the transcriptional start site and gene body of TACSTD2 (encoding TROP2), DLL3, and CEACAM5, and their respective protein expression in CRPC patient-derived xenografts. Collectively, these findings provide insights into patterns and determinants of expression of TROP2, DLL3, and CEACAM5 with implications for the clinical development of cell surface targeting agents in CRPC.

Identification of Population-Specific Novel Protein Biomarkers and Possible Therapeutic Targets in Gliomas by Proteomics Approach

Abstract Objective To analyze the differential proteomic profile of gliomas in patients from South India and to identify novel protein glioma biomarkers and possible therapeutic targets to tailor the treatment to individual patients. Material and Methods We have prospectively analyzed the differential proteomic profile of 34 patients with glioma imaging characteristics and compared them with that of normal brain tissue. This research was conducted at the Institute of Neurosurgery, Madras Medical College, in technical collaboration with the Indian Institute of Technology, Madras, over 1 year. Statistical Analysis Biological variate analysis (I-ANALYSIS OF VARIANCE (ANOVA)) was used, with p-value less than 0.05 being significant. Results Twenty proteins (10 upregulated and 10 downregulated) were differentially expressed in tumor tissue. The expression of three pro-apoptotic proteins was downregulated and the expression of three anti-apoptotic proteins was upregulated with statistical significance. The cellular functions of the 20 differentially regulated proteins were subjected to pathway analysis revealing significant alterations in heme biosynthesis, deoxyribonucleic acid (DNA) replication, fibroblast growth factor (FGF) signaling, and epidermal growth factor (EGF0 receptor signaling in glioma. Conclusion KRT18, PRS4, and EF1A2 are anti-apoptotic proteins and are significantly upregulated in gliomas. EARS2, COX5A, and LSM3 are pro-apoptotic proteins, and are significantly downregulated in gliomas. This subverts the apoptotic pathways resulting in prolonged cell survival. This study's statistically significant dysregulation of these six proteins was unique, suggesting that they might be considered population-specific biomarkers and possible therapeutic targets for patients from South India. Abnormalities of heme biosynthesis at the proteomic level were identified in this study, which has not been very well studied previously.

IGF2BP3 promotes glutamine metabolism of endometriosis by interacting with UCA1 to enhances the mRNA stability of GLS1

BackgroundInsulin like growth factor II mRNA binding protein 3 (IGF2BP3) has been implicated in numerous inflammatory and cancerous conditions. However, its precise molecular mechanisms in endometriosis (EMs) remains unclear. The aim of this study is to examine the influence of IGF2BP3 on the occurrence and progression of EMs and to elucidate its underlying molecular mechanism.MethodsEfects of IGF2BP3 on endometriosis were confrmed in vitro and in vivo. Based on bioinformatics analysis, RNA immunoprecipitation (RIP), RNA pull-down assays and Fluorescent in situ hybridization (FISH) were used to show the association between IGF2BP3 and UCA1. Single-cell spatial transcriptomics analysis shows the expression distribution of glutaminase 1 (GLS1) mRNA in EMs. Study the effect on glutamine metabolism after ectopic endometriotic stromal cells (eESCs) were transfected with Sh-IGF2BP3 and Sh-UCA1 lentivirus.ResultsImmunohistochemical staining have revealed that IGF2BP3 was upregulated in ectopic endometriotic lesions (EC) compared to normal endometrial tissues (EN). The proliferation and migration ability of eESCs were greatly reduced by downregulating IGF2BP3. Additionally, IGF2BP3 has been observed to interact with urothelial carcinoma associated 1 (UCA1), leading to increased stability of GLS1 mRNA and subsequently enhancing glutamine metabolism. Results also demonstrated that IGF2BP3 directly interacts with the 3’ UTR region of GLS1 mRNA, influencing its expression and stability. Furthermore, UCA1 was able to bind with c-MYC protein, stabilizing c-MYC mRNA and consequently enhancing GLS1 expression through transcriptional promotion.ConclusionThese discoveries underscored the critical involvement of IGF2BP3 in the elevation and stability of GLS1 mRNA in the context of glutamine metabolism by interacting with UCA1 in EMs. The implications of our study extended to the identification of possible therapeutic targets for individuals with EMs.

Lightweight-Improved YOLOv5s Model for Grape Fruit and Stem Recognition

Mechanized harvesting is the key technology to solving the high cost and low efficiency of manual harvesting, and the key to realizing mechanized harvesting lies in the accurate and fast identification and localization of targets. In this paper, a lightweight YOLOv5s model is improved for efficiently identifying grape fruits and stems. On the one hand, it improves the CSP module in YOLOv5s using the Ghost module, reducing model parameters through ghost feature maps and cost-effective linear operations. On the other hand, it replaces traditional convolutions with deep convolutions to further reduce the model’s computational load. The model is trained on datasets under different environments (normal light, low light, strong light, noise) to enhance the model’s generalization and robustness. The model is applied to the recognition of grape fruits and stems, and the experimental results show that the overall accuracy, recall rate, mAP, and F1 score of the model are 96.8%, 97.7%, 98.6%, and 97.2% respectively. The average detection time on a GPU is 4.5 ms, with a frame rate of 221 FPS, and the weight size generated during training is 5.8 MB. Compared to the original YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x models under the specific orchard environment of a grape greenhouse, the proposed model improves accuracy by 1%, decreases the recall rate by 0.2%, increases the F1 score by 0.4%, and maintains the same mAP. In terms of weight size, it is reduced by 61.1% compared to the original model, and is only 1.8% and 5.5% of the Faster-RCNN and SSD models, respectively. The FPS is increased by 43.5% compared to the original model, and is 11.05 times and 8.84 times that of the Faster-RCNN and SSD models, respectively. On a CPU, the average detection time is 23.9 ms, with a frame rate of 41.9 FPS, representing a 31% improvement over the original model. The test results demonstrate that the lightweight-improved YOLOv5s model proposed in the study, while maintaining accuracy, significantly reduces the model size, enhances recognition speed, and can provide fast and accurate identification and localization for robotic harvesting.

Subtractive Proteomics and Reverse-Vaccinology Approaches for Novel Drug Target Identification and Chimeric Vaccine Development against Bartonella henselae Strain Houston-1

Bartonella henselae is a Gram-negative bacterium causing a variety of clinical symptoms, ranging from cat-scratch disease to severe systemic infections, and it is primarily transmitted by infected fleas. Its status as an emerging zoonotic pathogen and its capacity to persist within host erythrocytes and endothelial cells emphasize its clinical significance. Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to the B. henselae strain Houston-1. Exploring these aspects is crucial for targeted therapeutic strategies against this versatile pathogen. Using reverse-vaccinology-based subtractive proteomics, this research aimed to identify the most antigenic proteins for formulating a multi-epitope vaccine against the B. henselae strain Houston-1. One crucial virulent and antigenic protein, the PAS domain-containing sensor histidine kinase protein, was identified. Subsequently, the identification of B-cell and T-cell epitopes for the specified protein was carried out and the evaluated epitopes were checked for their antigenicity, allergenicity, solubility, MHC binding capability, and toxicity. The filtered epitopes were merged using linkers and an adjuvant to create a multi-epitope vaccine construct. The structure was then refined, with 92.3% of amino acids falling within the allowed regions. Docking of the human receptor (TLR4) with the vaccine construct was performed and demonstrated a binding energy of −1047.2 Kcal/mol with more interactions. Molecular dynamic simulations confirmed the stability of this docked complex, emphasizing the conformation and interactions between the molecules. Further experimental validation is necessary to evaluate its effectiveness against B. henselae.

Efficient single-frequency millimeter-wave three-dimensional imaging for rapid target identification

Compared to broadband systems, single-frequency millimeter-wave (SFQ-MMW) imaging systems can significantly simplify system complexity, but can only obtain two-dimensional information of the target. Moreover, the position of the reference plane must be adjusted in real time during the imaging process to obtain a high-quality focusing effects. Therefore, this paper proposes a SFQ-MMW three-dimensional imaging algorithm. In the plane wave spectrum domain, the propagation operator is used as a focusing term to accurately locate the target focus. Only single-frequency echo data is required to retrieve information and reconstruct high-quality images. This method can significantly improve the efficiency of near-field millimeter wave measurement and imaging. This work facilitates applications in rapid target identification and characterization. The performance of this method was tested through numerical simulation. Finally, validation was performed on real data in an independently developed system. The results show that the test results are in line with expectations, and the imaging efficiency has been significantly improved.

CHUNAV: Analyzing Hindi Hate Speech and Targeted Groups in Indian Election Discourse

In the ever-evolving landscape of online discourse and political dialogue, the rise of hate speech poses a significant challenge to maintaining a respectful and inclusive digital environment. The context becomes particularly complex when considering the Hindi language—a low-resource language with limited available data. To address this pressing concern, we introduce the CHUNAV dataset—a collection of 11,457 Hindi tweets gathered during assembly elections in various states. CHUNAV is purpose-built for hate speech categorization and the identification of target groups. The dataset is a valuable resource for exploring hate speech within the distinctive socio-political context of Indian elections. The tweets within CHUNAV have been meticulously categorized into “Hate” and “Non-Hate” labels, and further subdivided to pinpoint the specific targets of hate speech, including “Individual”, “Organization”, and “Community” labels (as shown in Figure 1). Furthermore, this paper presents multiple benchmark models for hate speech detection, along with an innovative ensemble and oversampling-based method. The paper also delves into the results of topic modeling, all aimed at effectively addressing hate speech and target identification in the Hindi language. This contribution seeks to advance the field of hate speech analysis and foster a safer and more inclusive online space within the distinctive realm of Indian Assembly Elections.

Repositioning of Small Molecules through the Inverse Virtual Screening in silico Tool: Case of Benzothiazole-Based Inhibitors of Soluble Epoxide Hydrolase (sEH).

Computational techniques accelerate drug discovery by identifying bioactive compounds for specific targets, optimizing molecules with moderate activity, or facilitating the repositioning of inactive items onto new targets. Among them, the Inverse Virtual Screening (IVS) approach is aimed at the evaluation of one or a small set of molecules against a panel of targets for addressing target identification. In this work, a focused library of benzothiazole-based compounds was re-investigated by IVS. Four items, originally synthesized and tested on bromodomain-containing protein 9 (BRD9) but yielding poor results, were critically re-analyzed, disclosing only a partial fit with 3D structure-based pharmacophore models, which, in the meanwhile, were developed for this target. Afterwards, these compounds were re-evaluated through IVS on a panel of proteins involved in inflammation and cancer, identifying soluble epoxide hydrolase (sEH) as a putative interacting target. Three items were subsequently confirmed as able to inhibit sEH activity, spanning from 70% up to 30% when tested at 10 μM. Finally, one benzothiazole-based compound emerged as the most promising inhibitor featuring an IC50 in the low micromolar range (IC50 = 6.62 ± 0.13 μM). Our data confirm IVS as a predictive tool for accelerating the target identification and repositioning processes.

Identification of Curcumin Targets in the Brain of Epileptic Mice Using DARTS

Identification of Curcumin Targets in the Brain of Epileptic Mice Using DARTS

Identification of Genes Crucial for Biological Processes in Breast Cancer Liver Metastasis Relapse

Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, we aimed to shed light on the diversities of this process. This research investigated breast cancer liver metastasis relapse by employing a comprehensive approach that integrated data filtering, gene ontology and KEGG pathway analysis, overall survival analysis, identification of the alteration in the DEGs, visualization of the protein–protein interaction network, Signor 2.0, identification of positively correlated genes, immune cell infiltration analysis, genetic alternation analysis, copy number variant analysis, gene-to-mRNA interaction, transcription factor analysis, molecular docking, and identification of potential treatment targets. This study’s integrative approach unveiled metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.

Immune checkpoints: new insights into the pathogenesis of thyroid eye disease

Thyroid eye disease (TED) is a disfiguring autoimmune disease characterized by changes in the orbital tissues and is caused by abnormal thyroid function or thyroid-related antibodies. It is the ocular manifestation of Graves’ disease. The expression of thyroid-stimulating hormone receptor (TSHR) and the insulin-like growth factor-1 receptor (IGF-1 R) on the cell membrane of orbital fibroblasts (OFs) is responsible for TED pathology. Excessive inflammation is caused when these receptors in the orbit are stimulated by autoantibodies. CD34+ fibrocytes, found in the peripheral blood and orbital tissues of patients with TED, express immune checkpoints (ICs) like MHC II, B7, and PD-L1, indicating their potential role in presenting antigens and regulating the immune response in TED pathogenesis. Immune checkpoint inhibitors (ICIs) have significantly transformed cancer treatment. However, it can also lead to the occurrence of TED in some instances, suggesting the abnormality of ICs in TED. This review will examine the overall pathogenic mechanism linked to the immune cells of TED and then discuss the latest research findings on the immunomodulatory role of ICs in the development and pathogenesis of TED. This will offer fresh perspectives on the study of pathogenesis and the identification of potential therapeutic targets.

Altered Serum Proteins Suggest Inflammation, Fibrogenesis and Angiogenesis in Adult Patients with a Fontan Circulation

Previous omics research in patients with complex congenital heart disease and single-ventricle circulation (irrespective of the stage of palliative repair) revealed alterations in cardiac and systemic metabolism, inter alia abnormalities in energy metabolism, and inflammation, oxidative stress or endothelial dysfunction. We employed an affinity-proteomics approach focused on cell surface markers, cytokines, and chemokines in the serum of 20 adult Fontan patients with a good functioning systemic left ventricle, and we 20 matched controls to reveal any specific processes on a cellular level. Analysis of 349 proteins revealed 4 altered protein levels related to chronic inflammation, with elevated levels of syndecan-1 and glycophorin-A, as well as decreased levels of leukemia inhibitory factor and nerve growth factor-ß in Fontan patients compared to controls. All in all, this means that Fontan circulation carries specific physiological and metabolic instabilities, including chronic inflammation, oxidative stress imbalance, and consequently, possible damage to cell structure and alterations in translational pathways. A combination of proteomics-based biomarkers and the traditional biomarkers (uric acid, γGT, and cholesterol) performed best in classification (patient vs. control). A metabolism- and signaling-based approach may be helpful for a better understanding of Fontan (patho-)physiology. Syndecan-1, glycophorin-A, leukemia inhibitory factor, and nerve growth factor-ß, especially in combination with uric acid, γGT, and cholesterol, might be interesting candidate parameters to complement traditional diagnostic imaging tools and the determination of traditional biomarkers, yielding a better understanding of the development of comorbidities in Fontan patients, and they may play a future role in the identification of targets to mitigate inflammation and comorbidities in Fontan patients.

Combined transcriptome and proteome analysis reveals MSN and ARFIP2 as biomarkers for trastuzumab resistance of breast cancer.

HER2-positive breast cancer (BC) accounts for 20-30% of all BC subtypes and is linked to poor prognosis. Trastuzumab (Tz), a humanized anti-HER2 monoclonal antibody, is a first-line treatment for HER2-positive breast cancer which faces resistance challenges. This study aimed to identify the biomarkers driving trastuzumab resistance. Differential expression analysis of genes and proteins between trastuzumab-sensitive (TS) and trastuzumab-resistant (TR) cells was conducted using RNA-seq and iTRAQ. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used to study their functions. The prognostic significance and protein levels of ARFIP2 and MSN were evaluated using online tools and immunohistochemistry. Sensitivity of MSN and ARFIP2 to other therapies was assessed using public pharmacogenomics databases and the R language. Five genes were up-regulated, and nine genes were down-regulated in TR cells at both transcriptional and protein levels. Low ARFIP2 and high MSN expression linked to poor BC prognosis. MSN increased and ARFIP2 decreased in TR patients, correlating with shorter OS. MSN negatively impacted fulvestrant and immunotherapy sensitivity, while ARFIP2 had a positive impact. Our findings suggest that MSN and ARFIP2 could serve as promising biomarkers for predicting response to Tz, offering valuable insights for future research in the identification of diagnostic and therapeutic targets for BC patients with Tz resistance.

In Vitro Investigation of Therapy-Induced Senescence and Senescence Escape in Breast Cancer Cells Using Novel Flow Cytometry-Based Methods

Although cellular senescence was originally defined as an irreversible form of cell cycle arrest, in therapy-induced senescence models, the emergence of proliferative senescence-escaped cancer cells has been reported by several groups, challenging the definition of senescence. Indeed, senescence-escaped cancer cells may contribute to resistance to cancer treatment. Here, to study senescence escape and isolate senescence-escaped cells, we developed novel flow cytometry-based methods using the proliferation marker Ki-67 and CellTrace CFSE live-staining. We investigated the role of a novel senescence marker (DPP4/CD26) and a senolytic drug (azithromycin) on the senescence-escaping ability of MCF-7 and MDA-MB-231 breast cancer cells. Our results show that the expression of DPP4/CD26 is significantly increased in both senescent MCF-7 and MDA-MB-231 cells. While not essential for senescence induction, DPP4/CD26 contributed to promoting senescence escape in MCF-7 cells but not in MDA-MB-231 cells. Our results also confirmed the potential senolytic effect of azithromycin in senescent cancer cells. Importantly, the combination of azithromycin and a DPP4 inhibitor (sitagliptin) demonstrated a synergistic effect in senescent MCF-7 cells and reduced the number of senescence-escaped cells. Although further research is needed, our results and novel methods could contribute to the investigation of the mechanisms of senescence escape and the identification of potential therapeutic targets. Indeed, DPP4/CD26 could be a promising marker and a novel target to potentially decrease senescence escape in cancer.

Activity-based protein profiling of serine hydrolases and penicillin-binding proteins in Enterococcus faecium

Abstract Enterococcus faecium is a gut commensal bacterium that is gaining increasing relevance as an opportunistic, nosocomial pathogen. Its high level of intrinsic and acquired antimicrobial resistance is causing a lack of treatment options, particularly for infections with vancomycin-resistant strains, and prioritizes the identification and functional validation of novel druggable targets. Here, we use activity-based protein profiling (ABPP), a chemoproteomics approach using functionalized covalent inhibitors, to detect active serine hydrolases across 11 E. faecium and Enterococcus lactis strains. Serine hydrolases are a big and diverse enzyme family, that includes known drug targets such as penicillin-binding proteins (PBPs), whereas other subfamilies are underexplored. Comparative gel-based ABPP using Bocillin-FL revealed strain- and growth condition dependent variations in PBP activities. Profiling with the broadly serine hydrolase-reactive fluorescent probe fluorophosphonate-TMR showed a high similarity across E. faecium clade A1 strains, but higher variation across A2 and E. lactis strains. To identify these serine hydrolases, we used a biotinylated probe analog allowing for enrichment and identification via liquid chromatography-mass spectrometry. We identified 11 largely uncharacterized targets (α,β-hydrolases, SGNH-hydrolases, phospholipases, amidases, peptidases) that are druggable and accessible in live vancomycin-resistant E. faecium E745 and may possess vital functions that are to be characterized in future studies.

Multifunctional Supramolecular Hydrogel Modulated Heterojunction Interface Carrier Transport Engineering Facilitates Sensitive Photoelectrochemical Immunosensing.

Highly responsive interface of semiconductor nanophotoelectrochemical materials provides a broad development prospect for the identification of low-abundance cancer marker molecules. This work innovatively proposes an efficient blank WO3/SnIn4S8 heterojunction interface formed by self-assembly on the working electrode for interface regulation and photoregulation. Different from the traditional biomolecular layered interface, a hydrogel layer containing manganese dioxide with a wide light absorption range is formed at the interface after an accurate response to external immune recognition. The formation of the hydrogel layer hinders the effective contact between the heterojunction interface and the electrolyte solution, and manganese dioxide in the hydrogel layer forms a strong competition between the light source and the substrate photoelectric material. The process effectively improves the carrier recombination efficiency at the interface, reduces the interface reaction kinetics and photoelectric conversion efficiency, and thus provides strong support for target identification. Taking advantage of the process, the resulting biosensors are being explored for sensitive detection of human epidermal growth factor receptor 2, with a limit of detection as low as 0.037 pg/mL. Also, this study contributes to the advancement of photoelectrochemical biosensing technology and opens up new avenues for the development of sensitive and accurate analytical tools in the field of bioanalysis.

Clinical and Immunologic Characteristics of Colorectal Cancer Tumors Expressing LY6G6D

The identification of targets that are expressed on the cell membrane is a main goal in cancer research. The Lymphocyte Antigen 6 Family Member G6D (LY6G6D) gene codes for a protein that is mainly present on the surface of colorectal cancer (CRC) cells. Therapeutic strategies against this protein like the development of T cell engagers (TCE) are currently in the early clinical stage. In the present work, we interrogated public genomic datasets including TCGA to evaluate the genomic and immunologic cell profile present in tumors with high expression of LY6G6D. We used data from TCGA, among others, and the Tumor Immune Estimation Resource (TIMER2.0) platform for immune cell estimations and Spearman correlation tests. LY6G6D expression was exclusively present in CRC, particularly in the microsatellite stable (MSS) subtype, and was associated with left-side tumors and the canonical genomic subgroup. Tumors with mutations of APC and p53 expressed elevated levels of LY6G6D. This protein was expressed in tumors with an inert immune microenvironment with an absence of immune cells and co-inhibitory molecules. In conclusion, we described clinical, genomic and immune-pathologic characteristics that can be used to optimize the clinical development of agents against this target. Future studies should be performed to confirm these findings and potentially explore the suggested clinical development options.

MISP Is Overexpressed in Intestinal Metaplasia and Gastric Cancer

Gastric cancer is the fifth most common cancer and the fourth cause of global cancer mortality. The identification of new biomarkers and drug targets is crucial to allow the better prognosis and treatment of patients. The mitotic spindle positioning (MISP) protein has the function of correcting mitotic spindle positioning and centrosome clustering and has been implicated in the cytokinesis and migration of cancer cells. The goal of this work was to evaluate the expression and clinical relevance of MISP in gastric cancer. MISP expression was evaluated by immunohistochemistry in a single hospital series (n = 286) of gastric adenocarcinomas and compared with normal gastric mucosa and intestinal metaplasia, a preneoplastic lesion. MISP was detected on the membrane in 83% of the cases, being overexpressed in gastric cancer compared to normal gastric mucosa (n = 10). Its expression was negatively associated with diffuse and poorly cohesive types. On the other hand, it was strongly expressed in intestinal metaplasia where it was associated with MUC2 and CDX2 expression. Furthermore, when we silenced MISP in vitro, a significant decrease in the viability of gastric carcinoma cells was observed. In conclusion, MISP is overexpressed in gastric cancer, being associated with an intestinal phenotype in gastric carcinogenesis and having a role in cellular proliferation.