Cell line authentication: a necessity for reproducible biomedical research.

Immortalized or continuous cell lines are invaluable tools in basic and preclinical research. However, the widespread use of misidentified cell lines is a serious threat to scientific reproducibility. Based on the experiences of mandatory cell line authentication at the International Journal of Cancer (IJC), we provide an overview of the issues pertinent to misidentified cell lines and discuss available solutions. We also summarize the lessons learned, revealing that at least 5% of the human cell lines used in manuscripts considered for peer review are misidentified. About 4% of the considered manuscripts are rejected for severe cell line problems, and most are subsequently published in other journals. In order to diminish such malpractice and its consequences for the scientific record, we postulate that strict multi-layered quality control is essential. Besides journals and publishers, we encourage scientists, research institutions, and funders to take action on the matter and revise their respective policies. Hence, we provide concrete recommendations on introducing regular authentication schemes and staff training, and discuss future steps for enhancing good cell culture practices.

(Sialyl)Lewis Antigen Expression on Glycosphingolipids, N-, and O-Glycans in Colorectal Cancer Cell Lines is Linked to a Colon-Like Differentiation Program.

Alterations in the glycomic profile are a hallmark of cancer, including colorectal cancer (CRC). While, the glycosylation of glycoproteins and glycolipids has been widely studied for CRC cell lines and tissues, a comprehensive overview of CRC glycomics is still lacking due to the usage of different samples and analytical methods. In this study, we compared glycosylation features of N-, O-glycans, and glycosphingolipid glycans for a set of 22 CRC cell lines, all measured by porous graphitized carbon nano-liquid chromatography-tandem mass spectrometry. An overall, high abundance of (sialyl)Lewis antigens for colon-like cell lines was found, while undifferentiated cell lines showed high expression of H blood group antigens and α2-3/6 sialylation. Moreover, significant associations of glycosylation features were found between the three classes of glycans, such as (sialyl)Lewis and H blood group antigens. Integration of the datasets with transcriptomics data revealed positive correlations between (sialyl)Lewis antigens, the corresponding glycosyltransferase FUT3 and transcription factors CDX1, ETS, HNF1/4A, MECOM, and MYB. This indicates a possible role of these transcription factors in the upregulation of (sialyl)Lewis antigens, particularly on glycosphingolipid glycans, via FUT3/4 expression in colon-like cell lines. In conclusion, our study provides insights into the possible regulation of glycans in CRC and can serve as a guide for the development of diagnostic and therapeutic biomarkers.

The small molecule activator S3969 stimulates the epithelial sodium channel by interacting with a specific binding pocket in the channel's ß-subunit.

The epithelial sodium channel (ENaC) is essential for mediating sodium absorption in several epithelia. Its impaired function leads to severe disorders, including pseudohypoaldosteronism type 1 and respiratory distress. Therefore, pharmacological ENaC activators have potential therapeutic implications. Previously, a small molecule ENaC activator (S3969) was developed. So far, little is known about molecular mechanisms involved in S3969-mediated ENaC stimulation. Here, we identified an S3969-binding site in human ENaC by combining structure-based simulations with molecular biological methods and electrophysiological measurements of ENaC heterologously expressed in Xenopus laevis oocytes. We confirmed a previous observation that the extracellular loop of ß-ENaC is essential for ENaC stimulation by S3969. Molecular dynamics simulations predicted critical residues in the thumb domain of ß-ENaC (Arg388, Phe391, and Tyr406) that coordinate S3969 within a binding site localized at the ß-γ-subunit interface. Importantly, mutating each of these residues reduced (R388H; R388A) or nearly abolished (F391G; Y406A) the S3969-mediated ENaC activation. Molecular dynamics simulations also suggested that S3969-mediated ENaC stimulation involved a movement of the α5 helix of the thumb domain of ß-ENaC away from the palm domain of γ-ENaC. Consistent with this, the introduction of two cysteine residues (ßR437C - γS298C) to form a disulfide bridge connecting these two domains prevented ENaC stimulation by S3969 unless the disulfide bond was reduced by DTT. Finally, we demonstrated that S3969 stimulated ENaC endogenously expressed in cultured human airway epithelial cells (H441). These new findings may lead to novel (patho-)physiological and therapeutic concepts for disorders associated with altered ENaC function.

Metastatic potentials classified with hypoxia-inducible factor 1 downstream genes in pan-cancer cell lines.

Hypoxia-inducible factor 1 (HIF1) is a transcription factor that is stabilized under hypoxia conditions via post-translational modifications. HIF1 regulates tumor malignancy and metastasis by gene transcriptions, such as Warburg effect and angiogenesis-related genes, in cancer cells. However, the HIF1 downstream genes show varied expressional patterns in different cancer types. Herein, we performed the hierarchical clustering based on the HIF1 downstream gene expression patterns using 1406 cancer cell lines crossing 30 types of cancer to understand the relationship between HIF1 downstream genes and the metastatic potential of cancer cell lines. Two types of cancers, including bone and breast cancers, were classified based on HIF1 downstream genes with significantly altered metastatic potentials. Furthermore, different HIF1 downstream gene subsets were extracted to discriminate each subtype for these cancer types. HIF1 downstream subtyping classification will help to understand the novel insight into tumor malignancy and metastasis in each cancer type.

Analysis of the responsiveness to antiandrogens in multiple breast cancer cell lines.

Antiandrogens were originally developed as therapeutic agents for prostate cancer but are also expected to be effective for breast cancer. However, the role of androgen signaling in breast cancer has long been controversial due to the limited number of experimental models. Our study aimed to comprehensively investigate the efficacy of antiandrogens on breast cancer. In the present study, a total of 18 breast cancer cell lines were treated with the agonist or antagonists of the androgen receptor (AR). Among the 18 cell lines tested, only T-47D cells proliferated in an androgen-dependent manner, while the other cell lines were almost irresponsive to AR stimulation. On the other hand, treatment with AR antagonists at relatively high doses suppressed the proliferation of not only T-47D cells but also some other cell lines including AR-low/negative cells. In addition, expression of the full-length AR and constitutively active AR splice variants, AR-V7 and ARV567es, was not correlated with sensitivity to AR antagonists. These data suggest that the antiproliferative effect of AR antagonists is AR-independent in some cases. Consistently, proliferation of AR-knockout BT-549 cells was inhibited by AR antagonists. Identification of biomarkers would be necessary to determine which breast cancer patients will benefit from these drugs.

SNRMPACDC: computational model focused on Siamese network and random matrix projection for anticancer synergistic drug combination prediction.

Synergistic drug combinations can improve the therapeutic effect and reduce the drug dosage to avoid toxicity. In previous years, an in vitro approach was utilized to screen synergistic drug combinations. However, the in vitro method is time-consuming and expensive. With the rapid growth of high-throughput data, computational methods are becoming efficient tools to predict potential synergistic drug combinations. Considering the limitations of the previous computational methods, we developed a new model named Siamese Network and Random Matrix Projection for AntiCancer Drug Combination prediction (SNRMPACDC). Firstly, the Siamese convolutional network and random matrix projection were used to process the features of the two drugs into drug combination features. Then, the features of the cancer cell line were processed through the convolutional network. Finally, the processed features were integrated and input into the multi-layer perceptron network to get the predicted score. Compared with the traditional method of splicing drug features into drug combination features, SNRMPACDC improved the interpretability of drug combination features to a certain extent. In addition, the introduction of convolutional networks can better extract the potential information in the features. SNRMPACDC achieved the root mean-squared error of 15.01 and the Pearson correlation coefficient of 0.75 in 5-fold cross-validation of regression prediction for response data. In addition, SNRMPACDC achieved the AUC of 0.91 ± 0.03 and the AUPR of 0.62 ± 0.05 in 5-fold cross-validation of classification prediction of synergistic or not. These results are almost better than all the previous models. SNRMPACDC would be an effective approach to infer potential anticancer synergistic drug combinations.

NMRK2 is an efficient diagnostic indicator for Xp11.2 translocation renal cell carcinoma.

Xp11.2 translocation renal cell carcinomas (tRCC) are a rare and highly malignant type of renal cancer, lacking efficient diagnostic indicators and therapeutic targets. Through the analysis of public databases and our cohort, we identified NMRK2 as a potential diagnostic marker for distinguishing Xp11.2 tRCC from kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) due to its specific upregulation in Xp11.2 tRCC tissues. Mechanistically, we discovered that TFE3 fusion protein binds to the promoter of the NMRK2 gene, leading to its upregulation. Importantly, we established RNA- and protein-based diagnostic methods for identifying Xp11.2 tRCC based on NMRK2 expression levels, and the diagnostic performance of our methods was comparable to a dual-color break-apart fluorescence in situ hybridization assay. Moreover, we successfully identified fresh Xp11.2 tRCC tissues after surgical excision using our diagnostic methods and established an immortalized Xp11.2 tRCC cell line for further research purposes. Functional studies revealed that NMRK2 promotes the progression of Xp11.2 tRCC by upregulating the NAD+/NADH ratio, and supplementation with ß-nicotinamide mononucleotide (NMN) or nicotinamide riboside chloride (NR), effectively rescued the phenotypes induced by the knockdown of NMRK2 in Xp11.2 tRCC. Taken together, these data introduce a new diagnostic indicator capable of accurately distinguishing Xp11.2 tRCC and highlight the possibility of developing novel targeted therapeutics. © 2024 The Pathological Society of Great Britain and Ireland.

Thyroid cancer cell metabolism: A glance into cell culture system-based metabolomics approaches.

Thyroid cancer is the most common malignancy of the endocrine system and the seventh most prevalent cancer in women worldwide. It is a complex and diverse disease characterized by heterogeneity, underscoring the importance of understanding the underlying metabolic alterations within tumor cells. Metabolomics technologies offer a powerful toolset to explore and identify endogenous and exogenous biochemical reaction products, providing crucial insights into the intricate metabolic pathways and processes within living cells. Metabolism plays a central role in cell function, making metabolomics a valuable reflection of a cell's phenotype. In the OMICs era, metabolomics analysis of cells brings numerous advantages over existing methods, propelling cell metabolomics as an emerging field with vast potential for investigating metabolic pathways and their perturbation in pathophysiological conditions. This review article aims to look into recent developments in applying metabolomics for characterizing and interpreting the cellular metabolome in thyroid cancer cell lines, exploring their unique metabolic characteristics. Understanding the metabolic alterations in tumor cells can lead to the identification of critical nodes in the metabolic network that could be targeted for therapeutic intervention.

Generation of a stably transfected mouse embryonic stem cell line for inducible differentiation to excitatory neurons.

In vitro differentiation of stem cells into various cell lineages is valuable in developmental studies and an important source of cells for modelling physiology and pathology, particularly for complex tissues such as the brain. Conventional protocols for in vitro neuronal differentiation often suffer from complicated procedures, high variability and low reproducibility. Over the last decade, the identification of cell fate-determining transcription factors has provided new tools for cellular studies in neuroscience and enabled rapid differentiation driven by ectopic transcription factor expression. As a proneural transcription factor, Neurogenin 2 (Ngn2) expression alone is sufficient to trigger rapid and robust neurogenesis from pluripotent cells. Here, we established a stable cell line, by piggyBac (PB) transposition, that conditionally expresses Ngn2 for generation of excitatory neurons from mouse embryonic stem cells (ESCs) using an all-in-one PB construct. Our results indicate that Ngn2-induced excitatory neurons have mature and functional characteristics consistent with previous studies using conventional differentiation methods. This approach provides an all-in-one PB construct for rapid and high copy number gene delivery of dox-inducible transcription factors to induce differentiation. This approach is a valuable in vitro cell model for disease modeling, drug screening and cell therapy.

The impact of an additional copy of chromosome 21 in B-cell precursor acute lymphoblastic leukemia.

A common finding in pediatric B-cell precursor acute lymphoblastic leukemia (BCPALL) is that chromosome 21 is never lost and an extra chromosome 21 is often gained. This implies an important role for chromosome 21 in the pathobiology of BCPALL, emphasized by the increased risk of BCPALL in children with Down syndrome. However, model systems of chromosome 21 gain are lacking. We therefore developed a BCPALL cell line (Nalm-6, DUX4-rearranged) with an additional chromosome 21 by means of microcell-mediated chromosome transfer. FISH, PCR, multiplex ligation-dependent probe amplification, and whole exome sequencing showed that an additional chromosome 21 was successfully transferred to the recipient cells. Transcription of some but not all genes on chromosome 21 was increased, indicating tight transcriptional regulation. Nalm-6 cells with an additional chromosome 21 proliferated slightly slower compared with parental Nalm-6 and sensitivity to induction chemotherapeutics was mildly increased. The extra copy of chromosome 21 did not confer sensitivity to targeted signaling inhibitors. In conclusion, a BCPALL cell line with an additional human chromosome 21 was developed, validated, and subjected to functional studies, which showed a minor but potentially relevant effect in vitro. This cell line offers the possibility to study further the role of chromosome 21 in ALL.

Evidence of steady-state fibroblast subtypes in the normal human breast as cells-of-origin for perturbed-state fibroblasts in breast cancer.

BACKGROUND: Human breast cancer most frequently originates within a well-defined anatomical structure referred to as the terminal duct lobular unit (TDLU). This structure is endowed with its very own lobular fibroblasts representing one out of two steady-state fibroblast subtypes-the other being interlobular fibroblasts. While cancer-associated fibroblasts (CAFs) are increasingly appreciated as covering a spectrum of perturbed states, we lack a coherent understanding of their relationship-if any-with the steady-state fibroblast subtypes. To address this, we here established two autologous CAF lines representing inflammatory CAFs (iCAFs) and myofibroblast CAFs (myCAFs) and compared them with already established interlobular- and lobular fibroblasts with respect to their origin and impact on tumor formation. METHODS: Primary breast tumor-derived CAFs were transduced to express human telomerase reverse transcriptase (hTERT) and sorted into CD105low and CD105high populations using fluorescence-activated cell sorting (FACS). The two populations were tested for differentiation similarities to iCAF and myCAF states through transcriptome-wide RNA-Sequencing (RNA-Seq) including comparison to an available iCAF-myCAF cell state atlas. Inference of origin in interlobular and lobular fibroblasts relied on RNA-Seq profiles, immunocytochemistry and growth characteristics. Osteogenic differentiation and bone formation assays in culture and in vivo were employed to gauge for origin in bone marrow-derived mesenchymal stem cells (bMSCs). Functional characteristics were assessed with respect to contractility in culture and interaction with tumor cells in mouse xenografts. The cells' gene expression signatures were tested for association with clinical outcome of breast cancer patients using survival data from The Cancer Genome Atlas database. RESULTS: We demonstrate that iCAFs have properties in common with interlobular fibroblasts while myCAFs and lobular fibroblasts are related. None of the CAFs qualify as bMSCs as revealed by lack of critical performance in bone formation assays. Functionally, myCAFs and lobular fibroblasts are almost equally tumor promoting as opposed to iCAFs and interlobular fibroblasts. A myCAF gene signature is found to associate with poor breast cancer-specific survival. CONCLUSIONS: We propose that iCAFs and myCAFs originate in interlobular and lobular fibroblasts, respectively, and more importantly, that the tumor-promoting properties of lobular fibroblasts render the TDLU an epicenter for breast cancer evolution.

Recent advances in breast cancer cell line research.

Breast cancer, a formidable global health challenge, needs continuous translational research to understand the complexity of mechanisms and improve therapeutic and diagnostic strategies. Breast cancer cell lines are of paramount importance as they significantly contribute to the initial stage of research to understand cancer biology. This review provides insights into targeted therapies and immunotherapies that have emerged using in vitro models and microbiome analysis. It focuses on therapeutic development using cell lines and the limitations of tumor heterogeneity and microenvironment. We explore the evolving landscape of breast cancer cell lines from two-dimensional (2-D) cultures to patient-derived xenograft (PDX) models advancing both fundamental and translational research. Patient-derived xenografts, cell line-derived xenografts (CDX), three-dimensional (3-D) cultures, organoids, and circulating tumor cells (CTC) models provide promising alternatives that capture the intricacies of the tumor microenvironment. This review bridges the gap between traditional cell lines and newer developments exploring the therapeutic and diagnostic advancements and needs for cell lines to expedite the progress in breast cancer research and treatment.

Phytocannabinoids CBD, CBG, and their Derivatives CBD-HQ and CBG-A Induced In Vitro Cytotoxicity in 2D and 3D Colon Cancer Cell Models.

Phytocannabinoids, compounds found in Cannabis sativa L., are used in oncology and palliative care to reduce the adverse reactions of standard therapies. Cancer patients use formulations of Cannabis sativa L. to manage the anxiety, pain, and nausea associated with cancer treatment, and there is growing evidence that some of them may exhibit anticancer properties. In this study, we tested the anticancer potential of selected cannabinoids CBD (cannabidiol) and its quinone derivative CBD-HQ (cannabidiol hydroquinone), CBG (cannabigerol) and its acid derivative CBG-A (cannabigerolic acid), as well as a combination of CBD+CBG on the colon cancer cell line SW-620. The MTT assay was used to determine the cannabinoids' ability to induce colon cancer cell death. All cannabinoids were cytotoxic at the lowest concentration (3 µg/mL). The half maximal inhibitory concentration (IC50) ranged from 3.90 to 8.24 µg/mL, depending on the substance. Cytotoxicity was confirmed in a 3D spheroidal cell culture with calcein and propidium iodide staining. The amount of intracellular reactive oxygen species (ROS) was examined using a DCF-DA assay. CBG showed the lowest antioxidant activity of all the cannabinoids tested. The level of intracellular ROS decreased only by 0.7-18%. However, CBG-A induced the strongest reduction in ROS level by 31-39%. Our results suggest that cannabinoids represent an interesting research direction with great implementation potential. These preliminary results represent the beginning of research into the potential of these substances for anticancer treatment and underscore the potential for further research.

Broad Chain-Length Specificity of the Alkane-Forming Enzymes NoCER1A and NoCER3A/B in Nymphaea odorata.

Many terrestrial plants produce large quantities of alkanes for use in epicuticular wax and the pollen coat. However, their carbon chains must be long to be useful as fuel or as a petrochemical feedstock. Here, we focus on Nymphaea odorata, which produces relatively short alkanes in its anthers. We identified orthologs of the Arabidopsis alkane biosynthesis genes AtCER1 and AtCER3 in N. odorata and designated them NoCER1A, NoCER3A and NoCER3B. Expression analysis of NoCER1A and NoCER3A/B in Arabidopsis cer mutants revealed that the N. odorata enzymes cooperated with the Arabidopsis enzymes and that the NoCER1A produced shorter alkanes than AtCER1, regardless of which CER3 protein it interacted with. These results indicate that AtCER1 frequently uses a C30 substrate, whereas NoCER1A, NoCER3A/B and AtCER3 react with a broad range of substrate chain lengths. The incorporation of shorter alkanes disturbed the formation of wax crystals required for water-repellent activity in stems, suggesting that chain-length specificity is important for surface cleaning. Moreover, cultured tobacco cells expressing NoCER1A and NoCER3A/B effectively produced C19-C23 alkanes, indicating that the introduction of the two enzymes is sufficient to produce alkanes. Taken together, our findings suggest that these N. odorata enzymes may be useful for the biological production of alkanes of specific lengths. 3D modeling revealed that CER1s and CER3s share a similar structure that consists of N- and C-terminal domains, in which their predicted active sites are respectively located. We predicted the complex structure of both enzymes and found a cavity that connects their active sites.

Synthesis of novel hydrophilic celastrol nanoformulation by entrapment within calcium phosphate nanoparticle and study of its antioxidant activity against neurotoxin-induced damage in human neuroblastoma cells.

Celastrol, a pentacyclic triterpenoid found in Chinese herb Tripterygium wilfordii, is considered as one of the top-five natural medicinal compounds with high antioxidant property. However, celastrol has poor aqueous solubility and thereby low bioavailability, restricting its clinical application as drug. To overcome this problem, we nanonized celastrol by entrapping it within hydrophilic nanocarrier - calcium phosphate nanoparticle. The synthesized calcium phosphate celastrol nanoparticle (CPCN) had average size of 35 nm, spherical shape, significant stability with (-) 37 mV zeta potential, celastrol entrapment efficiency around 75 % and low celastrol release kinetics spanning over 7 days, as measured by different techniques like FESEM, AFM, DLS, and spectrophotometry. Studies on the antioxidant potency of CPCN by flow cytometry and fluorescence microscopy depicted that the toxicity developed in human neuroblastoma cells SH-SY5Y by treatment with the selective neurotoxin MPP+ iodide (N-Methyl-4-phenylpyridinium iodide) got reduced by pretreatment of the cells with CPCN. Determination of cellular ROS content, depolarization level of mitochondrial membrane potential, cell cycle analysis and nuclear damage in MPP+-exposed cells demonstrated that CPCN had about 65 % more antioxidant efficacy over that of bulk celastrol. Thus, the nanonization process transformed hydrophobic celastrol into hydrophilic CPCN, having high potentiality to be developed as an effective antioxidant drug.

Blockade of the TIGIT-CD155/CD112 axis enhances functionality of NK-92 but not cytokine-induced memory-like NK cells toward CD155-expressing acute myeloid leukemia.

TIGIT is an alternative checkpoint receptor (CR) whose inhibition promotes Graft-versus-Leukemia effects of NK cells. Given the significant immune-permissiveness of NK cells circulating in acute myeloid leukemia (AML) patients, we asked whether adoptive transfer of activated NK cells would benefit from additional TIGIT-blockade. Hence, we characterized cytokine-induced memory-like (CIML)-NK cells and NK cell lines for the expression of inhibitory CRs. In addition, we analyzed the transcription of CR ligands in AML patients (CCLE and Beat AML 2.0 cohort) in silico and evaluated the efficacy of CR blockade using in vitro cytotoxicity assays, CD69, CD107a and IFN-γ expression. Alternative but not classical CRs were abundantly expressed on healthy donor NK cells and even further upregulated on CIML-NK cells. In line with our finding that CD155, one important TIGIT-ligand, is reliably expressed on AMLs, we show improved killing of CD155+-AML blasts by NK-92 but interestingly not CIML-NK cells in the presence of TIGIT-blockade. Additionally, our in silico data (n = 671) show that poor prognosis AML patients rather displayed a CD86low CD112/CD155high phenotype, whereas patients with a better outcome rather exhibited a CD86high CD112/CD155low phenotype. Collectively, our data evidence that the complex CR ligand expression profile on AML blasts may be one explanation for the intrinsic NK cell exhaustion observed in AML patients which might be overcome with adoptive NK-92 transfer in combination with TIGIT-blockade.

Pediatric Glioma Models Provide Insights into Tumor Development and Future Therapeutic Strategies.

In depth study of pediatric gliomas has been hampered due to difficulties in accessing patient tissue and a lack of clinically representative tumor models. Over the last decade, however, profiling of carefully curated cohorts of pediatric tumors has identified genetic drivers that molecularly segregate pediatric gliomas from adult gliomas. This information has inspired the development of a new set of powerful in vitro and in vivo tumor models that can aid in identifying pediatric-specific oncogenic mechanisms and tumor microenvironment interactions. Single-cell analyses of both human tumors and these newly developed models have revealed that pediatric gliomas arise from spatiotemporally discrete neural progenitor populations in which developmental programs have become dysregulated. Pediatric high-grade gliomas also harbor distinct sets of co-segregating genetic and epigenetic alterations, often accompanied by unique features within the tumor microenvironment. The development of these novel tools and data resources has led to insights into the biology and heterogeneity of these tumors, including identification of distinctive sets of driver mutations, developmentally restricted cells of origin, recognizable patterns of tumor progression, characteristic immune environments, and tumor hijacking of normal microenvironmental and neural programs. As concerted efforts have broadened our understanding of these tumors, new therapeutic vulnerabilities have been identified, and for the first time, promising new strategies are being evaluated in the preclinical and clinical settings. Even so, dedicated and sustained collaborative efforts are necessary to refine our knowledge and bring these new strategies into general clinical use. In this review, we will discuss the range of currently available glioma models, the way in which they have each contributed to recent developments in the field, their benefits and drawbacks for addressing specific research questions, and their future utility in advancing biological understanding and treatment of pediatric glioma.

Glutamic Acid Modified Gold Nanorod Sensor for the Detection of Calcium ions in Neuronal Cells.

Calcium (Ca2+) ions play a crucial role in the functioning of neurons, governing various aspects of neuronal activity such as rapid modulation and alterations in gene expression. Ca2+ signaling has a significant impact on the development of diseases and the impairment of neuronal functions. Herein, the study reports a Ca2+ ion sensor in neuronal cells using a gold nanorod. The gold nanorod (GA-GNR) conjugated glutamic acid developed in the study was used as a nano-bio probe for the experimental and in vitro detection of calcium. The nanosensor is colloidally stable, preserves plasmonic properties, and shows good viability in neuronal cells, as well as promoting neuron cell line growth. The cytotoxicity and cell penetration of the nanosensor are studied using Raman spectroscopy, brightfield and darkfield microscopy imaging, and MTT assays. The quantification of Ca2+ ions in neuronal cells is determined by monitoring the surface plasmon resonance (SPR) of the GA-GNR. The change in the intensity profile in the presence of Ca2+ incubated neurons was effectively used to develop a portable prototype of an optical Ca2+ sensor, proposing it as a tool for neurodegenerative disease diagnosis and neuromodulation evaluation.

High dimensionality reduction by matrix factorization for systems pharmacology.

The extraction of predictive features from the complex high-dimensional multi-omic data is necessary for decoding and overcoming the therapeutic responses in systems pharmacology. Developing computational methods to reduce high-dimensional space of features in in vitro, in vivo and clinical data is essential to discover the evolution and mechanisms of the drug responses and drug resistance. In this paper, we have utilized the matrix factorization (MF) as a modality for high dimensionality reduction in systems pharmacology. In this respect, we have proposed three novel feature selection methods using the mathematical conception of a basis for features. We have applied these techniques as well as three other MF methods to analyze eight different gene expression datasets to investigate and compare their performance for feature selection. Our results show that these methods are capable of reducing the feature spaces and find predictive features in terms of phenotype determination. The three proposed techniques outperform the other methods used and can extract a 2-gene signature predictive of a tyrosine kinase inhibitor treatment response in the Cancer Cell Line Encyclopedia.

DeepTTA: a transformer-based model for predicting cancer drug response.

Identifying new lead molecules to treat cancer requires more than a decade of dedicated effort. Before selected drug candidates are used in the clinic, their anti-cancer activity is generally validated by in vitro cellular experiments. Therefore, accurate prediction of cancer drug response is a critical and challenging task for anti-cancer drugs design and precision medicine. With the development of pharmacogenomics, the combination of efficient drug feature extraction methods and omics data has made it possible to use computational models to assist in drug response prediction. In this study, we propose DeepTTA, a novel end-to-end deep learning model that utilizes transformer for drug representation learning and a multilayer neural network for transcriptomic data prediction of the anti-cancer drug responses. Specifically, DeepTTA uses transcriptomic gene expression data and chemical substructures of drugs for drug response prediction. Compared to existing methods, DeepTTA achieved higher performance in terms of root mean square error, Pearson correlation coefficient and Spearman's rank correlation coefficient on multiple test sets. Moreover, we discovered that anti-cancer drugs bortezomib and dactinomycin provide a potential therapeutic option with multiple clinical indications. With its excellent performance, DeepTTA is expected to be an effective method in cancer drug design.