Data-independent acquisition (DIA)-mass spectrometry (MS)-based proteome strategies are increasingly used for detecting and validating protein biomarkers and therapeutic targets. Here, based on an in-depth proteome analysis of seven pancreatic cancer cell lines, we built a pancreas-specific mass spectrum library containing 10633 protein groups and 184551 peptides. The proteome difference among the seven pancreatic cancer cells was significant, especially for the divergent expression of proteins related to epithelial-mesenchymal transition (EMT). The spectra library was applied to explore the proteome difference of PANC-1 and BxPC-3 cells upon gemcitabine (GEM) treatment, and potential GEM targets were identified. The cytotoxicity test and GEM target analysis found that HPAC, CFPAC-1, and BxPC-3 were sensitive to GEM treatment, whereas PANC-1 and AsPC-1 were resistant. Finally, we found EMT was significant for CFPAC-1, AsPC-1, and PANC-1 cells, whereas BxPC-3 and HPAC cells showed more typical epithelial features. This library provides a valuable resource for in-depth proteomic analysis on pancreatic cancer cell lines, meeting the urgent demands for cell line-dependent protein differences and targeted drug analysis.  Pancreatic ductal adenocarcinoma (PDAC) accounts for > 90% of all pancreatic malignancies3. Asymptomatic early stage and lack of reliable early diagnostic biomarkers hinder pancreatic cancer detection before it has spread to other organs, and the insensitivity of pancreatic cancer to chemotherapy and radiotherapy leads to a high mortality rate4. Therefore, understanding the biology and mechanism of PDAC progression and metastasis is essential to improve early detection and treatment. The rapid development of proteomics and chemical biology technologies has recently stimulated interest in elucidating the complex mechanisms underlying pancreatic cancer.The average 5-year survival rate of pancreatic cancer is 8%, rendering it the fourth leading cause of cancer-related deaths worldwide. It is expected to become the second leading cause of cancer-related deaths by 20306. However, these analyses failed to provide information regarding post-transcriptional regulation, post-translational modification, or protein localisation.The study of protein composition in pancreatic cancer is important for discovering new strategies for early diagnosis. The interaction between cancer cells and the host is reflected in the constantly changing protein composition during carcinogenesis and metastasis. Studies based on transcriptome and genome sequencing have identified four major driving genes in pancreatic cancer: the oncogene KRAS (mutation rate greater than 95%), tumour suppressor gene TP53 (50%–75%), CD-KN2A/p16, and SMAD4 (mutation rate > 90%)7. With a much lower level of missing values, DIA provides quantification accuracy and repeatability, achieving high stability and high-precision, rendering DIA-MS extremely suitable for proteome researchers with large sample sizes. DIA has been successfully applied in disease proteomic research such as Parkinson’s disease, Alzheimer’s disease, and liver cancer10.Data-independent acquisition (DIA), a label-free quantitative proteomics approach, is a new MS technology developed in recent years. The entire scanning range of the mass spectrometer was divided into several windows, and all precursor ions in each window were selected, fragmented, and detected cyclically at high speeds, and all the fragment information of all the precursor ions in the sample were recorded without any bias or omission14. However, after a few weeks of treatment, tumour cells originally sensitive to GEM develop drug resistance. GEM resistance is one of the most significant factors affecting the efficacy of chemotherapy, leading to poor prognosis16. GEM resistance is closely related to the tumour microenvironment, extracellular matrix, and intracellular signal molecule regulation, which are decisive factors affecting PDAC treatment. Activation of epithelial-mesenchymal transition (EMT) is associated with the invasion and metastasis of pancreatic cancer and resistance to GEM chemotherapy19. Although the transformation from epithelial to mesenchymal cells is achieved through TGF-β, HIF-1α, WNT, NF-κB, and other mediated signal pathway expressions, its downstream molecular signal has not been determined22.Presently, nucleoside analogue gemcitabine (GEM) monotherapy or combinational therapy has been the treatment of choice for advanced pancreatic cancer, doubling the 5-year survival rate of around 16%-21% of patientsIn this study, we first used the combination of peptide pre-fractionation with DDA tandem MS strategy to acquire MS2 spectra for seven pancreatic cancer cell lines. Which, together with the spiked indexed Retention Time (iRT) peptides information, were imported Spectronaut ™ (version 15.0) software to establish a pancreatic cancer cell-specific spectra library for DIA-based proteome application. Then, based on the established DIA pancreatic cancer cell spectrum library, we analysed the proteomics of PANC-1 and BxPC-3 cells before and after GEM treatment. In addition, the Cell Counting Kit-8 (CCK-8) kit was used to detect the half-maximal inhibition rate of pancreatic cancer cells. Finally, based on the known and potential targets of GEM- and EMT-related biomarkers, and the analysis of the relative expression levels of proteins in the seven pancreatic cancer cell lines, we determined the GEM-sensitive and EMT phenotypes of the cell lines. These data provide a supportive resource for in-depth proteomic analyses of pancreatic diseases.Seven commonly used human pancreatic cancer cell lines were selected to generate the spectral library: the pancreatic cancer cell lines AsPC-1, BxPC-3, CFPAC-1, HPAC, and PANC-1; human pancreatic stellate cells HPaSteC (HPSC); normal human pancreatic ductal epithelial cells HPDE6-C7 (H6C7). Eighty-four original MS data files were obtained from the pre-fractioned peptide by basic reversed-phase chromatography  in a 26-year-old white male25; PANC1, derived from the pancreatic ducts of patients with epithelioid carcinoma26; HPAC, a cell line established by xenotransplantation of primary human pancreatic ductal adenocarcinoma27; a pancreatic stellate cell line, HPSC, derived from pancreatic exocrine myofibroblasts, is responsible for synthesising and degrading extracellular matrix components and promoting tissue repair28; a normal human pancreatic duct epithelial cell line, H6C7, which can be used as a model for studying human pancreatic ductal cell carcinogenesis29. The basic characteristics of pancreatic cancer cell lines are shown in Fig. We selected seven commonly studied human pancreatic cancer cell lines grown under the same conditions: five pancreatic cancer cell lines, including AsPC-1, derived from cancerous ascites produced by xenotransplantation of human pancreatic cancer in nude mice and can express carcinoembryonic antigen, human pancreas-associated antigen, human pancreas-specific antigen, and mucin30.Pancreatic cancer cell samples were lysed with T-PER® and sonicated on ice . After incubating on ice and cracking for 10 min, the lysate was centrifuged at 14,000 × g for 15 min. The supernatant was recovered as an extract for subsequent analyses, and quantified using the Bradford assay. The protein was digested using the filter-aided sample preparation (FASP) methodFor each cell line, 50 ug of peptides were pre-fractionated in a tip filled with C18 media, by a sequential elution using 90 µL of solution containing 6%, 9%, 12%, 15%, 18%, 21%, 25%, 30%, 35%, and 50% acetonitrile in ammonia water at pH 10, respectively. The 7th, 8th and 9th fractions were merged into 1st, 2nd and 3rd respectively, and the 10th into 6th. Finally, the fractions were collected and combined into 6 fractions.LC-MS/MS identification of the peptide fractions was performed on an Easy-nLC 1000 System nanoflow high-performance liquid chromatograph (HPLC) coupled to a Q-Exactive HF mass spectrometer . A self-packed column of 30 cm length  was used. The chromatographic conditions were as follows: gradient elution at a flow rate of 350 nL/min , 135-min gradient elution: 0 min, 6% B; 0–13 min, 6%–10% B; 13–99 min, 10%–23% B; 99–120 min, 23%–33% B; 120–123 min, 33%–90% B; 123–135 min, 90% B. The ion scan range of the primary mass spectrometer was 375–1400 m/z with a resolution of 120,000.iRT  was added to all samples as an internal standard before MS injection according to the manufacturer’s instructions.Following the digestion of PANC-1 and BxPC-3 cells before and after GEM intervention, they were identified using LC-MS/MS. The scanning range of MS1 was 400–1200 m/z, followed by MS2, which cyclically selected, fragmented, and detected all ions in each window . All experiments were repeated twice, and the iRT-standardised peptide was added for calibration.CCK-8  was used to detect cell proliferation. The pancreatic cancer cell lines AsPC-1, BxPC-3, CFPAC-1, HPAC and PANC-1 were inoculated into the wells of a 96-well-plate at 5000 cells per well. After 24 h of incubation, different concentrations of GEM were added, and the cells were further incubated for 48 h. Then, 10 μL of CCK-8 was added to each well, incubated for 2 h, and the absorbance at 450 nm was measured using a microplate reader. Each concentration was repeated four times.31. We used MaxQuant software (version 1.6.2.3) based on the human Uniprot protein sequence database  containing iRT peptide sequences. The parameter settings of the MaxQuant software were: the restriction enzyme digestion method, trypsin; the missed cleavage site of the enzyme was set to 2, the false positive rate (FDR) of the peptide and protein was less than 1%, and the corrected precursor ion error was set to 5 ppm. The “msms.txt” file output by MaxQuant was imported into Spectronaut™ (version 15.0).Qualitative and quantitative proteomic analyses were performed on RAW files obtained by Q-Exactive HF mass spectrometer analysisBioinformatic analysis was performed on R (version 3.5.4). Different analysis methods and software may require different gene/protein identifiers. We used clusterProfiler and org.Hs.eg.db for conversions of identifiers. Use the official gene symbols approved by the HUGO Gene Nomenclature Committee and the protein identifier using UniProtKB accession number.33. After correction, most analyses require the log2 logarithmic transformation of the proteomic data for subsequent analysis and filling in the minimum value for the missing values that cannot be processed.Differentially expressed protein analyses were done using the “limma” software package (version 3.24.15), and the quantile normalisation method in the “limma” corrected the proteome datahttp://software.broadinstitute.org/gsea/msigdb/index.jsp), including 50 cancer hallmark gene sets, 186 Kyoto Encyclopaedia of Genes and Genomes (KEGG) signal pathways, and 7481 gene ontology (GO) biological process ontology’s signal pathways. Based on the above signal pathway entries, differentially expressed proteins were analysed for pathway enrichment. Only enriched signal pathways with false discovery rate-adjusted p-value (p.FDR) < 0.05 were considered.Gene set analysis was performed using the “GSEABase” and “enrichplot” R package. The biological signal pathways selected for analysis were downloaded from the MSigDB database  DDA files for library generation and the search results (pepXML) have been deposited to the ProteomeXchange Consortium via the PRIDE36. The spectral library was labelled as “PC library.xls”. The DIA data analysed in Spectronaut (xlsx) is available from ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD03226337.Besides, the raw MS DIA files of BxPC-3 and PANC-1 cell lines used to discover potential targets of GEM and the DIA spectral library have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD030948Seven common human pancreatic cancer cell lines that grew normally under the same conditions were selected to generate the DIA spectral library. A total of 42 peptide fractions was obtained by pre-separating the peptide mixtures, and 84 original MS data files were collected from 84 MS injections. iRT was added to each sample to ensure accurate retention time calibration for better quality control. To evaluate the reliability of the proteomics data, we checked the original MS/MS data and found that the average number of matched spectra for each peptide was 15, indicating that the proteomics data were highly reliable at the peptide level Fig. . In addiTM, included 10663 proteome groups, 184551 peptides, 283077 precursors, and 2013590 fragments. This resource supports the reliable detection and quantification of 52.28% of all human proteins annotated using UniProtKB, currently the most comprehensive pancreatic cancer-specific DIA spectral library. This method is expected to be widely used in basic research and large-scale proteomics of clinical samples. We then counted the number of peptides and protein groups for each of the seven cell lines and found 6668 proteins in all cell lines   Fig. .Fig. 3Biin vivo and in vitro tests has increased its complexity. Therefore, stratifying pancreatic cancer according to heterogeneity and developing a more accurate GEM sensitisation programme should be the focus of future research and development.We performed gene set enrichment analysis (GSEA) in each of these seven datasets to determine their biological functions. A total of 36, 55, 297, 126, 48, 83, 110 pathways were significantly enriched or depleted in the AsPC-1, BxPC-3, CFPAC-1, HPAC, PANC-1, HPSC, and H6C7 cell lines, respectively. The proteins specifically expressed by AsPC-1 mainly mediated regulation of histone modification, transmembrane transport, and cell adhesion Fig. . The enr2 FC = 2, p < 0.05)  Fig. . Subsequ05) Fig. . In PANC05) Fig. . In AsPC05) Fig. . In BxPC05) Fig. . In HPAC05) Fig. . In the 05) Fig. .Fig. 4GeFurthermore, the gene set analysis (GSA) of the hallmark gene set was used to analyse the molecular characteristics of each pancreatic cancer cell line Fig. . Gene seIn vitro cell line models have become one of the most important tools in pancreatic cancer research. Therefore, it is essential to investigate the sensitivity of GEM and the molecular biological mechanisms in different cell lines. In this study, a comprehensive proteomic analysis provided a valuable resource to study the GEM sensitivity of different pancreatic cancer cell lines. To investigate the effect of GEM on pancreatic cancer cell lines, we incubated the cell lines with different concentrations of GEM for 48 h and measured the cell growth using a CCK-8 kit. We observed that the cell growth in HPAC, CFPAC-1, BXPC-3, AsPC-1, and PANC-1 were dose-dependently inhibited, and the respective half-inhibitory concentration (IC50) was 13.57, 14.38, 19.56, 23.26, and 23.9 µM/L  tend to have a better overall survival rate as ERCC1 can repair GEM-induced chain breaks40. The induction of topoisomerase 1 (TOP-1)-mediated DNA breaks may contribute to GEM cytotoxicity42.Based on the known GEM target genes and their functions, we evaluated the sensitivity of several cell lines to GEM, providing a colour-coded indication of the standardised gene expression Fig. . Genes sTM with default settings. As a result, a total of 77928 unique peptides and 7089 corresponding proteins were identified, of which 712 were identified as differentially expressed proteins   Fig. . The pot05) Fig. . GO anal05) Fig. . Further05) Fig. . In addi45. Numerous studies have suggested that EMT contributes to chemotherapy resistance in cancer cells47. Downregulation of proteins involved in cell junctions (such as E-cadherin and cytokeratin) and upregulation of mesenchymal molecular markers  are hallmarks of the EMT phenotype49. Pathway enrichment analysis showed that the NF-κB, PI3K-Akt, VEGF, and ECM-receptor interaction pathways were significantly enriched in the AsPC-1, CFPAC-1, and PANC-1 cell lines. The epithelial cell marker CDH1 was significantly downregulated, whereas the mesenchymal cell markers VIM and ZEB1 were significantly upregulated . In conclusion, changes in the EMT status are closely related to GEM resistance. Different pancreatic cancer mesenchymal cell characteristics may lead to different results. Future research should focus on the stratification of pancreatic cancer according to heterogeneity and the development of more accurate GEM sensitisation programmes.Targeted inhibition of EMT has become a new strategy for overcoming GEM resistance in pancreatic cancer. The histone deacetylase (HDAC) inhibitor, mocetinostat, inhibits the expression of EMT-TF and ZEB1 by restoring miR-203, rendering pancreatic cancer cells with an EMT phenotype sensitive to chemotherapyPancreatic cancer cells spectral library by DIA-MS and the phenotype analysis of gemcitabine sensitivity


The synthesis of Ni(OH)2@Mn3O4 nanocomposite from chia-seed extract was mediated by sonication. The obtained materials were characterized by different spectroscopic techniques such as transmission electron microscopy (TEM), scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), ultraviolet-visible (UV-Vis), and Fourier transform infrared (FT-IR) spectroscopies. The results of XRD, SEM, EDS, TEM, FT-IR, and UV-Vis analysis indicate the successful manufacturing of a crystalline, cactus-type Ni(OH)2@Mn3O4 nanocomposite of 10.10 nm average particle size. XPS analysis confirms that the synthesized materials consist mainly of Ni2+, Mn2+, and Mn3+. The antitumor activity of the nanocomposite was tested against a breast cancer (MCF-7) cell line. The results showed Ni(OH)2@Mn3O4 nanocomposite possesses insignificant cytotoxicity. The cell-death percentage was 34% at a 100 ppm concentration of Ni(OH)2@Mn3O4 nanocomposite. The obtained results imply that the synthesized nanocomposite could be suitable and safe for drug delivery and water treatment.In the present work, the facile eco-friendly synthesis and evaluation of the anti-tumor activity of Ni(OH) Cancer is a disease caused by abnormal cell division and is considered one of the major worldwide health problems . The comMetal nanocomposites are multicomponent materials that consist of many phases; at least one has a nanoscale diameter . They shThere are several forms of metal nanocomposites, including metal–metal, metal–metal hydroxide, metal–metal oxide, metal oxide—metal oxide, and metal–organic polymer. It is necessary to develop new classes of nanomaterial—nanoparticles (NPs)—and improve functionalities to overcome the limitation of mono-nanoparticles and enhance their properties ,13.Metal nanocomposites can be synthesized through chemical and physical routes. However, these methods have adverse effects on the environment and are not economically viable ,19. HencMetal nanocomposites are amongst the nanomaterials that have been widely examined due to their wide-ranging availability in chemical sensors, microwave absorbers, permanent magnets, and in bio-medical applications like drug delivery and in cancer thermotherapy. They have shown significant pharmacokinetic advantages in cancer treatment; lately, they have been used as anticancer materials for different kinds of cancer cells such as (A549), HepG-2, and MCF-7 cell lines ,15,16.3O4 is a mixed oxide material, and one of the important nanoparticles, which encompasses many crystal forms. Because it is naturally abundant, inexpensive, and exhibits a variety of oxidation states, it has been used extensively in different fields, including catalysis, electrochemistry, and medicinal chemistry . T. T53]. T2@Mn3O4 nanocomposite toward the MCF-7 cell line was examined using MTT assay. It has been previously reported that Ni(OH)2 has a potential activity toward several cancer cell lines (83.2%) [3O4 nanoparticles have been less toxic to some kinds of cell lines such as HT29 cells [2@Mn3O4 nanocomposite has insignificant cytotoxic activity toward the examined cell line. The cell mortality was found to be 34% at 100 ppm concentration of Ni(OH)2@Mn3O4. The lower cytotoxic behavior of Ni(OH)2@Mn3O4 nanocomposite could be attributed to the presence of Mn3O4-NP in the produced nanocomposite. These results suggest that produced Ni(OH)2@Mn3O4 nanocomposites could be safe to use for water remediation and drug delivery [The antitumor efficiency of the produced Ni(OH) (83.2%) ; however29 cells  and L92929 cells . The resdelivery .2@Mn3O4 nanocomposite was successfully synthesized via an environmentally safe, easy, and cheap method using aqueous chia-seed extract. FT-IR confirmed the interaction between different function groups in the chia-seed extract and the synthesized nanocomposite. XRD analysis confirmed the crystalline structure of the nanocomposite and investigated the size in the range of 11 nm. SEM showed agglomerated cactus-type nanoparticle morphology. According to the XPS survey spectrum, the produced nanocomposite consists of the elements Ni, Mn, O, and C existing without any other contaminants, suggesting the successful synthesis of the nanocomposite. The antitumor activity of the manufactured nanocomposite was tested against a breast cancer (MCF-7) cell line. The results showed that the Ni(OH)2@Mn3O4 nanocomposite has insignificant cytotoxicity toward the cancer cells, with a cell mortality of 34% at 100 ppm concentration. Based on a literature review, Mn3O4 nanoparticles showed lower toxicity toward some cancer cell lines. Therefore, the lower cytotoxic activity of Ni(OH)2@Mn3O4-NC could be attributed to the presence of Mn3O4-NP.Ni(OH)


In the past 65 years, over 25 000 referenced articles have been published on graft-versus-host disease (GVHD). Although this included clinically orientated papers or publications on chronic GVHD, the conservative estimate of scientific publications still contains several thousands of documents on the pathophysiology of acute GVHD. Thus, summarizing what we believe are prominent publications that can be considered milestones in our knowledge of this disease is a challenging and inherently biased task. Here we review from a historical perspective what can be regarded as publications that have made the field move forward. We also included several references of reviews on aspects we could not cover in detail. It has been more than 65 years since the seminal description that mice exposed to lethal irradiation and received allogeneic splenocytes developed diarrhea and skin lesions and died , 2. InitThousands of patients have since been transplanted, and our understanding of the disease has improved. At the time of writing this perspective, we made a PubMed search on “GVHD included in the title or the abstract.” This resulted in over 25,000 referenced publications Figure 1the graft must contain immunologically competent cells; the recipient must express antigens that are not present in the transplant donor, and the recipient must be incapable of mounting an effective response to eliminating the transplanted cells” [summarized by Ferrara in  in mice that led to GVHD but was prevented by the removal of T-lymphocytes from the graft . It thenIn the past 60 years, our knowledge of acute GVHD has dramatically improved. Readers with interest might compare figures on the pathophysiology of acute GVHD published by Ferrara and Deeg in 1991  to thoseThe biology of acute GVHD has been classically described by successive steps from conditioning-induced tissue damage to the induction phase, donor T-cell expansion, and recruitment of neutrophils and macrophages, to the effector stage and tissue damages . HoweverIn the clinical setting, pre-transplant conditioning regimens has long been associated with GVHD’s incidence and severity. In experimental models, Ferrara’s group also demonstrated increased severity of GVHD with increasing dose of total body irradiation (TBI). Increased GVHD was mediated by systemic increases in TNFα. TBI-induced damages increased the translocation of LPS, and LPS triggered excess TNFα alpha from macrophages primed by the GVH reaction as first described by Nestel and coworkers  and lateThe first cytokines associated with GVHD-associated tissue lesions were TNFα and IL-1 , 35. Thein vivo was assessed by imaging technics using enhanced green fluorescence protein transgenic-, or luciferase-labeled, allogeneic T cells  showed that imprinting toward the GI tract is mediated by dendritic cells (DCs) from Peyer’s patches  only host-derived antigen-presenting cells (APCs) initiated graft versus host disease . SubsequT-cell activation needs costimulation that has also been extensively studied within the context of GVHD from a therapeutical perspective. In 1994, Blazar et al. reported that blockade of the CD28/CTLA4: CD80-CD86 interaction reduces lethal GVHD in a major mismatched mice model . This waLangerhans cells (LCs) act as network in the epidermis of the skin. Using an inducible depletion of host LCs experimental model, Bennet et al. found reduced GVHD when LCs were absent. However, LCs were not required either for CD8 T-cell activation or homing to the epidermis. However, LCs were necessary for licensing IFN-γ secreting donor CD8 cells in the epidermis to induce epithelial injury .In vivo analyses of the early event in murine models also support the leading role of naïve T-cells . The field of Treg has been initially the subject of controversies, as nicely reviewed by Sakagushi . In GVHDAlthough included in the classical Ferrara’s circled schema of GVHD’s pathogenesis , 80, it During the past ten years, more careful attention has been paid to IEC subsets  than on effectors . Somewhat arbitrary, we will first allude to IEC and second to microbiota, although, obviously, these aspects are interrelated.As already stated GI tract damages are critical for the amplification of GVHD . IntestiAnother cell subset, Paneth cells (PCs), was also studied, and it was demonstrated that GVHD disrupts the intestinal microbiome by inhibiting Paneth cell production of α-defensins  and restFinally, after ISCs, PCs, and L cells GI-cell subsets, the role of goblet cells was explored in GI GVHD. Intestinal goblet cells form the mucus layers, which serves as a barrier between the gut microbiota and the host tissues. Goblet cell loss is one of the histologic features of GVHD. This leads to a disruption of the mucus layer and increased bacterial translocation. Pretransplant administration of interleukin-25 (IL-25) protected goblet cells from GVHD, prevented bacterial translocation, reduced IFN-γ and IL-6 plasma levels, and ameliorated GVHD. The protective role of IL-25 depended on Lypd8, an enterocyte-derived antimicrobial molecule that suppresses the motility of flagellated bacteria .Mitigation of secondary disease of allogeneic mouse radiation chimeras by modification of the intestinal microflora” (via the expansion of Bacteroides thetaiotaomicron (BT) which can degrade dietary polysaccharides and host mucin glycans. BT in meropenem-treated mice upregulated enzymes involved in the degradation of glycans within the mucus leading to thinning of the colonic mucus layer and decreased levels of xylose in the lumen. Finally, oral xylose supplementation prevented thinning of the colonic mucus layer  with IL-17RA and IL-17R-deficient mice, they found increased GVHD severity in WT mice, and the gut microbiome of WT mice shifted toward that of the IL-17RA/C mice . From a From the above-summarized data, we would finally put into perspective other ways of thinking about GVHD pathophysiology.primarily tailored to fit the tissue in which the response occurs”. More recently, Wu and Reddy  impressive bloom of new technologies has emerged in the field of biology in the past few years, including single-cell technologies that allow studying pathophysiology at the genomic, epigenetic, transcriptomic, and protein levels. These have obvious consequences for deciphering in depth the pathophysiology mechanisms of GVHD. Most of the data described here come from experimental mice models of acute GVHD. We have already described elsewhere how important these models have been operative in deciphering the mechanisms of GVHD and have been able to set the stage for  successful clinical trials . As niceThe first study that opened the gate in human GVHD was that of Claude Perreault’s group in 2007 . In thisMost recently, 3 groups shed new light on T-resident memory (Trm) T-cells in NHP and humans. In the NHP study, authors analyzed the transcriptomic of circulating, emigrating or already existing tissue-resident T cells in aGVHD target organs. Combining intravascular staining technique with single-cell RNA sequencing they demonstrate that T cell infiltration of the GI by donor CD8+ T cells was associated with an activated/cytotoxic phenotype and provided a canonical Trm signature . In humaIt is our own bias to believe that modern tools, including single cell multi-omics, both in experimental transplantation and in the human setting open a new area in the study of the pathophysiology of acute GVHD. Furthermore, recent development in tissue imaging (including mass cytometry) and spatial transcriptomics will allow the target organ. We might thus be faced with new studies where in-depth description of affected organs in human can lead to mechanistic experiments in the mice system.All authors contributed to the article and approved the submitted version.I (GS) would like to sincerely thank my friends and worldwide recognized experts in the immune biology of GVHD. They kindly agreed to give me their own top 10 references which they believe to be the milestones in this topic: Bruce Blazar, Jamy Ferrara, Pavan Reddy, Jerry Ritz, Takanori Teshima, Marcel Van Den Brinck, Robert Zeiser. Special dedication also to Claude Perreault, whose work inspired me to study the immune biology of allogeneic transplantation in humans.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Nature Communications 10.1038/s41467-022-30342-3, published online 13 May 2022.Correction to: The original version of this Article contained an error in the ‘De novo proteome-based subtypes’ section of the Results, which incorrectly read ‘s3 and s11 cell lines had consistent negative correlations in contrast to the other subtypes . This observation indicated that s3 and s11 cell lines  tended to express essential genes highly .’ The correct version states ‘s10’ in place of ‘s11’.The legend of Figure 4 originally read, ‘c, Pearson correlation between differential protein expression patterns versus gene effect scores based on Cancer Dependency Map (DepMap) CRISPR assays , whereby s3 and s11 cell lines tend to have high expression of essential genes. e For s3 and s11 cell lines, associated patterns for the sets of genes having both high expression and low gene effect scores across cell lines .’ The correct version states ‘s10’ in place of ‘s11’.These errors have now been corrected in both the PDF and HTML versions of the Article.


GNAQ and GNA11 genes. These mutations activate downstream and targetable signaling pathways, including the protein kinase C (PKC) cascade. PKC inhibitors have been used in clinical trials for metastatic UM but have shown limited efficacy. In this study, we examined the signaling and functional effects of two PKC inhibitors (AEB071 and IDE196) in a panel of UM cell models. In response to PKC inhibition, all UM cell lines showed potent suppression of PKC activity, but this was not sufficient to predict PKC inhibitor sensitivity and only two UM cell lines showed substantial PKC inhibitor-induced cell death. The differences in UM cell responses to PKC inhibition were not attributable to the degree or timing of PKC suppression or inhibition of the downstream mitogen-activated protein kinase (MAPK) or phosphatidylinositol-3-kinase (PI3K) pathways. Instead, UM cell show complex, PKC-independent signaling pathways that contribute to their survival and resistance to targeted therapies.Uveal melanoma (UM) is a rare cancer arising from melanocytes in the uveal tract of the eye. Despite effective primary treatment, there is no approved therapy for metastatic UM and prognosis and survival remain poor. Over 90% of UM are driven by mutations affecting the Gα subunits encoded by the  Uveal melanoma (UM) is the most common primary ocular malignancy in adults, affecting 5–7 individuals per million per year , 2. UM aGNAQ or GNA11 with another 6–8% of UM carrying mutations in the CYSLTR2 or PLCB4 genes [q and G11 subunits encoded by GNAQ and GNA11, respectively. These GTPase subunits transmit signals between GPCRs and downstream molecules such as the canonical effector phospholipase C-β (PLC-β) (PLCB4). PLC-ß promotes the sequential activation of secondary signaling molecules that stimulate protein kinase C (PKC) activity [Over 95% of UM harbor mutually exclusive activating driver mutations in B4 genes –12. Thesactivity . The stiactivity . Importaactivity , 15.The activation of PKC by UM driver mutations highlighted PKC as a potential therapeutic target in UM. PKC is a family of isoforms that are subdivided into the classical PKCs , novel PKCs  and atypical PKCs (PKCζ and PKCι) . These iIn order to reconcile the central role of PKC in GNAQ/GNA11 signaling with the poor response rates observed in PKC inhibitor monotherapy UM trials, we evaluated the effects of PKC inhibitors IDE196 and AEB071 in a large panel of UM cell lines. Both PKC inhibitors effectively suppressed PKC activity in all UM cell lines. Nevertheless, PKC inhibition resulted in variable downstream signaling changes and the MAPK pathway was only inhibited in the GNAQ/GNA11-mutant UM cell models. Critically, PKC inhibition was not sufficient to predict the degree of MAPK suppression or the response of UM to PKC inhibition. In fact, the differences in UM cell responses to PKC inhibition were not attributable to the degree or timing of PKC or MAPK inhibition, or the transcriptional inhibition of additional signaling cascades. This work confirms that PKC is not a central effector of UM survival and highlights the need for combination therapies targeting multiple signaling pathways in UM.GNAQ and GNA11 genes (Table We examined the effects of PKC inhibitors (IDE196 and AEB071) on a panel of 11 UM cell lines. These models included nine cell lines with a GNAQ or GNA11 mutation and two wild-type UM cell lines with no alterations in the UM cells were treated with vehicle control or the PKC inhibitors IDE196 and AEB071 and protein changes were monitored 24 h post treatment by western immunoblotting. The selected doses of IDE196 and AEB071 were previously shown to induce UM cell cycle arrest and cell death . We examp-value (q) < 0.05) in response to PKC inhibition in the UM cell lines  did not correlate with the degree of MAPK inhibition, as measured by the PKC inhibitor changes in pERK, pS6, and DUSP6, in the 11 UM cell lines -adjusted es Figs.  and S1C.es Figs. , and whenes Fig. .Fig. 2ExFinally, PKC inhibitor treatment did not consistently affect the phosphorylation of AKT or YAP in these UM cell models Figs.  and S1C.Considering that MARCKS phosphorylation was potently and uniformly inhibited in response to PKC inhibition, we examined the functional consequences of this signaling change. The UM cell lines were exposed to two PKC inhibitor concentrations and cell cycle distribution and viability were analysed 72 h post treatment. In most cell lines the response of UM cell lines to intermediate (1 µM IDE196 or 2 µM AEB071) and high dose (5 µM each) PKC inhibitors was equivalent Table .Analysis of PKC inhibitor responses revealed three distinct UM response patterns – cytotoxic (defined as >25% in sub G1 content), cytostatic  and resistant (defined as minor/inconsistent changes in cell cycle distribution with no evidence of cell death in response to PKC inhibition). PKC inhibition was cytotoxic in only the GNAQ-mutant Mel270 and GNA11-mutant OMM1 cell lines. These two cell lines showed substantial cell death (defined as >25% in sub G1 content), particularly in response to IDE196  assays, with the two most sensitive UM cell lines, Mel270 and OMM1, displaying the lowest AUC values for both AEB071 and IDE196 Fig. .The number of PKC inhibitor resistant and sensitive UM cell lines were too small to allow for meaningful statistical comparisons between the resistant, cytostatic and cytotoxic UM PKC inhibitor response groups. It was evident, however, that the cytotoxic Mel270 and OMM1 cell lines did not show the most pronounced inhibition of pMARCKS, pS6, DUSP6, or pERK Figs.  and S1. These data indicate that PKC regulates MAPK activity in GNAQ/GNA11 mutant, but not wild type, UM cell lines, and that MAPK activity is strongly associated with UM cell proliferation, but not cell survival.To expand our analysis on PKC inhibitor-induced signaling changes in UM, we examined the transcriptome profiles of five uveal melanoma cell lines treated with vehicle control  or 5 µM IDE196 for 8 h, 16 h and 24 h. These UM cells included the Mel270 (cytotoxic response), three cell lines showing cytostatic responses  and the resistant Mel285 cell line.p-value < 0.05.Geneset enrichment analysis using GSEA in PreRanked mode and the Hallmark gene set with additional signatures indicative of MAPK and YAP activity, was used to identify gene signatures that were differentially expressed between control versus PKC inhibitor-treated uveal cell models. For each cell line the differentially expressed genes were ranked and selected based on an FDR-adjusted The cytotoxic Mel270 cell line showed consistent loss of several signatures indicative of cell cycle inhibition, including the Hallmark_E2F Targets and Hallmark MYC Targets_V1 & V2 gene sets Fig. . TemporassGSEA analysis confirmed that MAPK activity loss  was pronounced 8 h post PKC inhibitor treatment and plateaued by 16 h of treatment Fig. . In contThe three cytostatic UM cell models  also showed a consistent decrease in proliferative gene sets Fig. –S5. TempThere was no significantly differentially expressed gene signatures in the resistant Mel285 cell line (control vs PKC inhibitor treatment groups) even though the ranking used for selecting genes in this cell model was increased to an FDR-adjusted p value <0.2.It is also worth noting that few transcriptome gene signatures were upregulated in response to PKC inhibition, although the cholesterol homeostasis was increased in Mel270, OMM1.3 and MP46 cell models . Predictably there was substantial variation in the ssGSEA scores of signaling pathways across these UM cell models. For instance, the PKC inhibitor-resistant Mel285 UM had the highest ssGSEA scores for epithelial-mesenchymal transition, transforming growth factor ß (TGFß) signaling, tumor necrosis factor α (TNFα) signaling, and kirsten rat sarcoma virus (KRAS) signaling Fig. . These sThis study comprehensively examined the response of a large panel of UM cell lines to two clinically developed PKC inhibitors. We confirm that both AEB071 and IDE196 consistently inhibited the phosphorylation of MARCKS, an immediate downstream effector of PKC. Critically, the inhibition of MARCKS was not sufficient to predict the response of UM to PKC inhibition. This was particularly evident for the WT UM cell lines, Mel290 and Mel285. Both these UM cells responded to PKC inhibition with potent suppression of MARCKS phosphorylation, although this did not result in the downregulation of established UM oncogenic and PKC-regulated pathways, including MAPK , 24 and The nine GNAQ/GNA11-mutant UM cell lines also responded to PKC inhibition with potent downregulation of MARCKS phosphorylation. In these mutant UM cell lines suppression of MARCKS activity was associated with the downregulation of MAPK signaling at both transcript and protein levels. However, the degree of MARCKS inhibition did not reflect the level of MAPK suppression or cell responses to PKC inhibition. For instance, only the Mel270 and OMM1 UM cells showed cell death in response to PKC inhibitor monotherapy, but these two cell lines did not show the most potent suppression of MARCKS or MAPK signaling. In fact, the differences in UM cell responses to PKC inhibition were not attributable to the degree or timing of pMARCKS, pS6 or DUSP6 inhibition, or the transcriptional inhibition of additional signaling cascades. Instead, UM sensitivity to PKC inhibition is likely to reflect the activity of alternate survival and proliferation pathways, rather than efficacy of PKC inhibitors to downregulate MARCKS and MAPK signaling. This may include pathways that alter the differentiation status of UM cell models. For instance, the PKC inhibitor resistant Mel285 UM cells expressed elevated TGFß signaling and displayed features of treatment resistant undifferentiated melanoma .Our data are consistent with previous literature describing UM responses to PKC inhibition. In particular, AEB071 consistently inhibited the phosphorylation of MARCKS in six UM cell lines, regardless of the cell genotype. However only GNAQ/11-mutant UM cell lines responded to AEB071 by suppressing MAPK activity and undergoing dose-dependent proliferative inhibition .Our work is also consistent with clinical trial data showing limited anti-tumor effects of therapies targeting single oncogenic pathways in UM. For instance, phase I clinical trial with MEK inhibitors TAK-733 and trametinib have shown that UM are poorly responsive , 28. TheOur data confirm that PKC activity is potently suppressed in UM by the clinically available AEB071 and IDE196 PKC inhibitors. PKC inhibition does not inhibit multiple activated Gα downstream pathways however, and the suppression of MAPK activity was not sufficient to promote robust cell death in most UM cell models. Instead, novel combination therapies targeting multiple upstream and downstream signaling nodes will be required to inhibit the complex signaling pathways that contribute to the proliferation and survival of UM.A total of 11 cell lines, Mel285, Mel290, 92.1, Mel202, Mel270, OMM1.3, OMM1.5, MP38, MP46, OMM1, and MP41 were included in this study , 4 mM glutamine , and 10 mM HEPES (Gibco) and were maintained at 37 °C in 5% COAEB071 was purchased from Selleckchem (S2791) and prepared as a 10 mM stock solution in DMSO. IDE196 was purchased from Chemgoods (C-1368) and prepared as a 10 mM stock solution in DMSO. All stocks were stored in aliquots at −20 °C. For western blot analysis, 5μM was used for AEB071 and IDE196. For cell cycle analysis, 1 μM and 5 μM for AEB071 and 2 μM and 5 μM for IDE196 were used. For cell viability assay, doses ranging from 0.001 μM to 10 μM for AEB071 and 0.1 μM to 10 μM for IDE196 were used. Transcriptome analysis was performed after treating cells for 24 h with 5 µM IDE196.2 transformed (multiplied by a factor of 1000) and independent experiments averaged.UM cell lines were treated with 5μM AEB071 or 5μM IDE196 or 0.1% DMSO for 24 h. Total cellular proteins were extracted at 4 °C using RIPA lysis buffer containing protease inhibitors and phosphatase inhibitors . Total proteins (20 µg) were resolved on 10% SDS-PAGE and transferred to Immobilon-P membranes (Millipore). Western blots were probed with the following antibodies: total ERK , phosphorylated ERK , total AKT , phosphorylated AKT , DUSP6 , total YAP , phosphorylated YAP , total MARCKS , phosphorylated MARCKS , total ribosomal S6 , phosphorylated ribosomal S6  overnight at 4 °C. Membranes were washed with tris-buffered saline with 0.05% Tween-20 and then incubated with secondary antibodies IRDye® 800CW Donkey anti-Mouse, IRDye® 800CW Donkey anti-Rabbit, IRDye® 680LT Donkey anti-Mouse, IRDye® 680LT Donkey anti-Rabbit . Membranes were detected on the Odyssey imaging system. pERK, pYAP, pAKT, pMARCKS, pS6 were normalized relative to their respective total protein levels and DUSP6 was normalized to the REVERT total protein stain (LI-COR). Normalized protein data were logUM cells were treated with various inhibitors for 72 h and floating and adhered cells collected for cell cycle and apoptosis analysis as previously described . DNA con3 cells per well and incubated overnight in RPMI-1640. Cells were allowed to adhere for 24 h before treatment. Media was then removed and UM cells were exposed to increasing concentrations of PKC inhibitor for 72 h; AEB071  and IDE196 . Cell viability was measured using the Cell titre 96 Aqueous One Solution Cell Proliferation Assay . The absorbance density was acquired on a PHERASTAR F5 microplate reader  at a wavelength of 490 nm. Cell viability was calculated as a percentage normalized to controls after background subtraction. A minimum of three independent viability assays, each conducted in triplicate was performed for each cell line. We report area under the does response curve (AUC) for these analyses as the UM cell models showed variable maximal growth inhibition [50 values did not accurately discriminate between these response curves. Cell viability measurements were fitted using GraphPad Prism software version 9.0 .UM cells were seeded in 96-well plates at 2.0 × 10hibition  and IC50Total RNA was isolated from uveal melanoma cell lines using the RNeasy Kit . cDNA synthesis and library construction were performed using the TruSeq RNA Library Prep Kit  and paired-end 150 bp sequencing, with each sample yielding 40–50 million reads. Sequencing was performed on the Illumina NovaSeq platform at the Australian Genome Research Facility.RNA-sequence data processing was kindly performed by Dr Dario Strebnac, University of Sydney. Trimming of Illumina TruSeq paired-end sequencing adapter sequences and bases with a quality of <20 from each end was done using cutadapt . Reads <RNA count data were normalized using trimmed mean of M-values (TMM) and transformed with voom to log2-counts per million with associated precision weights . To obta2 counts [q < 0.05 was used to generate the ranked gene list for each cell line. Enrichment scores were calculated from the ranked lists using gene set enrichment analysis in pre-ranked mode (GSEA pre-ranked version 7.2.4) [https://cloud.genepattern.org/) [Differentially expressed genes between control and PKC inhibitor treatment groups were determined using TMM-voom normalized log2 counts  and the 2 counts . The conn 7.2.4)  providedrn.org/) . Two estrn.org/) , MAPK Sirn.org/) ) and thehttps://cloud.genepattern.org/) [Transcriptome analysis of log2 (FPKM + 1) count data was performed using single-sample gene set enrichment analysis (ssGSEA version 10.09)  providedrn.org/) .https://software.Broadinstitute.org/morpheus/). ClustVis was used for principal component analysis [Analysis was performed using the GraphPad Prism software version 9.0 . was used. Figure legends specify the statistical analysis used and define error bars. If the assumption of normality distribution was not met, nonparametric tests were used. Equality of variances across unpaired samples was confirmed using an F-test as part of unpaired t-test analyses. Comparisons between control and PKC inhibitor treated UM cell lines were calculated using the Marker Selection tool, the Pearson’s correlation coefficient in the nearest neighbor and Similarity Matrix algorithms within the Morpheus web-based tool (analysis .Supplementary TablesSupplementary Figures


For the MDA-MB-231 cell line, oxadiazole 2l demonstrated the lowest IC50 value, with 22.73 μM. For PC-3, hydrazone 1d showed the lowest C50 value of 9.38 μM. The three most promising compounds were determined as compounds 1e, 1d, and 2a based on their minimum IC50 values, and an additional scratch assay was performed for A-549 and MDA-MB-231 cells, which have high migration capacity, for the three most potent molecules; it was determined that these molecules did not show a significant antimetastatic effect.To understand whether previously synthesized novel hydrazone and oxadiazole derivatives have promising anticancer effects, docking studies and in vitro toxicity assays were performed on A-549, MDA-MB-231, and PC-3 cell lines. The antiproliferative properties of the compounds were investigated using molecular docking experiments. Each compound’s best-docked poses, binding affinity, and receptor-ligand interaction were evaluated. Compounds’ molecular weights, logPs, TPSAs, abilities to pass the blood-brain barrier, GI absorption qualities, and CYPP450 inhibition have been given. When the activities of these molecules were examined in vitro, for the A-549 cell line, hydrazone  Cancer is one of the most difficult diseases to which humans are exposed, as well as one of the leading causes of mortality around the world. Lung, breast, and prostate cancer are the most frequently seen cancer types . Althoug2 group replaces the oxygen in aldehydes or ketones. Hydrazone derivatives have a broad range of pharmaceutical activities and are already being used in the market as anticancer, antiproliferative, antimicrobial, anti-inflammatory, and antiviral agents [Hydrazones are chemical compounds with a structure similar to aldehydes and ketones. They can be formed when the NNHl agents ,9,10,11.Oxadiazoles are aromatic, heterocyclic chemical compounds. They have four isomers: 1,2,3 oxadiazoles, 1,2,4 oxadiazoles, 1,2,5 oxadiazoles, and 1,3,4 oxadiazoles. In particular, 1,3,4 oxadiazoles possess antibacterial, anti-inflammatory antioxidant, anticancer, analgesic, and antiviral properties, and they have a broad range of applications ,18,19,20As an important class of medicinal chemistry, many of the differently substituted acyl hydrazones ,24,25,26N-acyl hydrazones 1a-o, and 2,5-substituted 1,3,4-oxadiazoles 2a-d, 2f-i, and 2k-n, encouraged by the great pharmaceutical potentials of acyl hydrazones and 1,3,4-oxadiazoles. The synthesis route is shown in In our previous study , we syntIn this study, cell lines representing lung, breast, and prostate cancers, which are among the most common cancer types, were selected to determine the anticancer activities of the N-acyl hydrazones and 1,3,4-oxadiazoles shown in According to the results obtained, an additional scratch assay was performed for the three molecules that were found to have the most effect, and whether they were effective against metastasis was also investigated.When biological activity analyses and docking studies are evaluated together, further studies can be carried out based on molecules that will be determined to be effective against cancer. In addition, other molecules can be designed and synthesized based on these molecules, and improvements can be made based on the results obtained.To determine the effect of N-acyl hydrazones and 2,5 substituted 1,3,4-oxadiazole derivatives, a dose-response curve was produced for each and every molecule based on the viability of A549 (lung carcinoma), PC-3 (prostate adenocarcinoma), and MDA-MB-231(breast adenocarcinoma) cancerous cell lines by using the Cell Titer Glo assay. The MRC-5 (lung fibroblast) cell line was used as the non-cancerous control group. For 48 h, the cytotoxic effects of novel derivatives on all of the cell lines were investigated in a dose-dependent manner.50 values in The results are shown as IC50 values in each cell line. Hydrazone 1e showed the best activity for the A-549 cell line, with an IC50 value of 13.39 µM. The molecule with the best activity for the MDA-MB-231 cell line was oxadiazole 2l, with an IC50 value of 22.73 µM. For the PC-3 cell line, the most effective molecule was hydrazone 1d, with an IC50 value of 9.389 µM.As can be seen in 1e, which is effective on lung cancer, has an IC50 of 18.09 µM in the PC-3 cell line and 108.3 µM in the MDA-MB-231 cell line. Another active molecule, hydrazone 1d, has an IC50 of 49.79 µM in the A549 cell line and 31.49 µM in the MDA-MB-231 cell line. Finally, oxadiazole 2l, which is the most effective among 27 molecules on breast cancer, has an IC50 of 38.42 µM on the PC-3 cell line and 36.26 µM on the A549 cell line. The concentrations of these substances on the MRC-5 fibroblast cells used in this study as a control group were found to be 44.66 µM for 1d, 86.96 µM for 1e, and 51.87 µM for 2l.When the activities of these molecules on other lines are examined, it is seen that hydrazone 1a, 1b, 1d, 1f, 1g, 1h, and 1m) on A549 appear to have lower IC50 values than their respective 1,3,4,-oxadiazoles. Based on cell viability results, it is possible to say that hydrazone derivatives are more effective on A549 cell lines than oxadiazole derivatives. Contrary to A549, oxadiazoles were found to be more effective on the MDA-MB-231 cell line than their respective N-acyl hydrazones. Only four N-acyl hydrazones  were able to act at lower concentrations than their respective 1,3,4-oxadiazoles in the MDA-MB-231 cell line. Finally, in the PC-3 cell line, similar to the A549 cell line, N-acyl hydrazones are more effective than 1,3,4-oxadiazoles. Only four oxadiazoles  managed to have lower IC50 values than their respective hydrazones. When the effects of synthesized compounds on the non-cancerous MRC-5 cell line were examined, it was determined that seven oxadiazoles  caused a more destructive effect than their respective hydrazones. When all lines and molecules are considered, 2k and 2n oxadiazoles are found to be more active than hydrazones in all cancerous cell lines and also in the control group. For the remaining molecules, it is not possible to generalize the results that are valid for all of the cell lines since activities vary based on the lines.When N-acyl hydrazones and 2,5-substituted 1,3,4-oxadiazoles are compared based on their activity on cell lines specifically, seven N-acyl hydrazones  had any antimetastatic effect on these lines.Because A-549 and MDA-MB-231 are two of the most metastatic cell lines tested in this study, a scratch assay was performed to see if the three most active compounds . Structural defects in the target proteins were eliminated with the Autodock Vina suite software. Default parameters were used while docking calculations were in progress . The final molecular docking score results were calculated using the average score of the top 10 final docking postures determined by the binding minimum energy  for each chemical [The target proteins’ X-ray crystal structures as three-dimensional coordinates were retrieved from the Protein Data Bank of the Research Collaboratory for Structural Bioinformatics (RCSB) , MDA-MB-231 (human breast carcinoma), and PC-3 (human prostatic carcinoma) cell lines.1d and 1e and oxadiazole 2a. While making this evaluation, the effects of the molecules on all the cancerous cell lines and their toxicity on normal cells were taken into consideration.The cytotoxic activities of the synthesized compounds were studied at concentrations of 300 µM, 200 µM, 100 µM, 50 µM, and 25 µM. When all the data obtained during the study were reviewed together, the most potent compounds among the twenty-seven molecules tested were determined to be hydrazones A scratch assay was performed for the three most promising compounds, 1d, 1e, and 2a, based on the data obtained from these scans. In this way, it was anticipated to see if these molecules have an antimetastatic effect.It was discovered throughout the study that the hydrazones used in the production of oxadiazoles did not exhibit a consistent difference in biological activity when compared to their counterparts in any of the cell lines. According to research, molecules respond differently in different types of cancer. As a result, it is not possible to draw a firm assumption that applies to all cell lines.If some modifications are made to the chemical structures of potent compounds to reduce their toxicity and boost their activity against cancer, it may be possible to re-evaluate selected candidate compounds as more promising anticancer agents.1e, demonstrated a particularly selective effect in PC-3 and A-549 cell lines. This molecule also has a low toxicity level on the MRC-5 cell line. This hydrazone’s structure includes a thiadiazol heterocyclic aromatic ring. Thiadiazols are frequently studied structures by medicinal chemists. This heterocyclic ring has a mesoionic character, which allows candidate molecules with this ring in their structures to permeate the cell membrane more effectively and have a stronger connection with biological targets. Therefore, it would be wise to investigate this thoroughly in other cancer cell lines and further study the mechanism of action in biological systems.The most potent molecule, hydrazone 1e has a lower impact on them than A-549 and PC-3 cells since the possible target might be missing. Hence, it is believed that the heterocyclic structure of thiadiazol in the molecule structure might influence receptor binding capacity and lower the effectiveness of the molecule. In a study conducted by Du et al., activities of 1,3,4-oxadiazole-thioether derivatives on various cancer lines were examined. Based on the obtained results, it was reported that the activity of their most effective derivative (compound 3) against breast cancer-representing cell line MCF-7 (18.3 µM) was less than that of the liver cancer-representing cell line HepG2 (0.7 µM) [MDA-MB-231 cells are triple-negative cells that do not express some hormone receptors for HER2, estrogen, and progesterone on their surfaces, so this might be a reason why (0.7 µM) .In almost all of the 1,3,4 oxadiazole derivatives included in another study conducted by Ashok and Vanaja, the activities on the lung cancer-representing cell line A549 were better than MCF-7, similar to our study . AnotherMore active molecules might be generated by synthesizing and analyzing the new derivatives of this compound in the future.In this study, four adherent cell lines were used: three from different cancer types and one from a regular fibroblast. The cancerous cells were human breast carcinoma , human prostatic carcinoma , and human lung cancer epithelial cells , while the fibroblasts in the control group were human fetal lung  cells. All cells were checked every few weeks for various sources of contamination.l-glutamine (Gibco) at 37 °C with 5% CO2. All the cells were removed from the flask with Trypsin/EDTA 0.25% (Gibco) when they reached 80% density.MDA-MB-213, MRC-5, and PC-3 cell lines were cultured in T75 flasks with high glucose DMEM medium , and A549 cells were cultured with RPMI-1640 (Pan Biotech) containing 10% fetal bovine serum , 1% penicillin-streptomycin (Gibco), and 1% 2 for 25 h. After 24 h in the incubator, the medium on top of each well was discharged. All of the cells were treated with 25, 50, 100, 200, or 300 µM of fifteen N-acyl hydrazones and twelve 2,5-substituted 1,3,4-oxadiazole in a dose-increasing manner. Molecules were studied in triplicate for each concentration. To assess the viability of non-treated cells, a control group was placed in the setup with only cells and DMSO control treatments without any candidate molecules introduced. Plates were incubated for 48 h, and Cell Titer Glo reagent (Promega) was added on top of each well. Cells were then evaluated in terms of viability with the Cell Titer-Glo Luminescent Cell Viability Assay. Luminescence signals were detected with the SpectraMax i3x Multimode Detection Platform to obtain the cell viability percentages.To test the effect of different doses on cells, all types of cells were seeded into 96-well plates at a density of eight thousand cells in 100 µL volume per well. Cells were incubated at 37 °C with 5% CO1d, 1e, and 2a.MDA-MB-231 and A-549 cells were seeded for the scratch assay. A total of 100.000 cells were cultured in 1.5 mL complete medium per well on a 6-well plate, as detailed above. The 6-well plates were then incubated for 24 h at 37 °C. After 24 h, accumulated cells were scraped out with the tip of a 200 µL pipette. After discarding the media on top of the cells, the cells were treated for 48 h with three molecules: 1d, 120 µM for 1e, and 30 µM for 2a. The dosages for the A-549 cell line were 55 µM for 1d, 15 µM for 1e, and 15 µM for 2a.The dosages for the MDA-MB-231 cell line were 40 µM for The cell states were evaluated under the microscope, and markings were made to obtain photos from the same location during the follow-up. Images of the determined reference points were captured under the microscope immediately after treatment, 24 h later, and 48 h later.t-test, which claims equal variance. At p < 0.05, the differences were accepted as statistically significant. The data were presented as a standard error of the mean (SEM).Experiments were carried out in three separate sets, each with its own set of results, and the findings were represented as mean standard errors. Statistical comparisons were made using Student’s 1a–1o and oxadiazole compounds of 2a–2n and related target proteins. Theoretical binding affinities were determined by using energy minimization from docking calculation outcomes. The Autodock Vina software suite was used to perform molecular docking computations, energy minimization, and molecular visualization of docking data. The Chem Draw sketch program was used to prepare 1a–1o and 2a–2n series and model inhibitor compounds for molecular docking. The Chem 3D suit program was used to draw and edit the unique 1a–1o and 2a–2n series chemicals in the SD file format before the docking process. These conformations were protonated and polarized, and conformation minimization was performed using the root-mean-square gradient.Molecular docking analyses were implemented to offer a theoretical perspective on potential molecular encounters between hydrazone compounds of The X-ray crystal structures of the target proteins were obtained as three-dimensional coordinates from the Protein Data Bank of the Research Collaboratory for Structural Bioinformatics (RCSB). A structure with the PDB ID of 1Z5M for PC-3, 2XP2 for A-549, and 3KRR for MDA-MB-231 were selected as the crystal structure model corresponding to this target protein for use in docking calculations. The Autodock Vina suite program was used to remove structural flaws in these target proteins. Default parameters were used while docking calculations were in progress . The average score of the top ten final docking postures defined by the binding minimum energy  for each molecule was used to generate the final molecular docking score values ,38. In order to gain a better understanding of compound structure-activity connections, drug-likeness rankings were determined using the Swiss ADME Calculation program.1d and 1e contain hydrazone moieties, and 2a, which contains a 1,3,4-oxadiazole moiety, yielded the most promising findings among all molecules. Molecular modeling investigations on the synthesized compounds revealed further structural and dynamic information about their possible target proteins. The activities of the compounds synthesized in this study are not a better alternative than other available molecules on the market.In this study, previously synthesized novel 2-arenoxybenzaldehyde N-acyl Hydrazone and 1,3,4-Oxadiazole derivatives were evaluated for their anticancer activities in different cancer cells. Compounds However, the findings suggest that it is possible to synthesize several derivatives that might be employed in future research to examine different cancer pathways. More research into these novel derivatives and their anticancer effects may offer more insights into potential therapeutic applications.


Among reproductive cancers, ovarian cancer leads to the highest female mortality rate. Fisetin, a natural flavonoid, exerts pharmacological effects, inhibiting cancer growth with various origins. Although multiple mechanisms are involved in regulating cell death, it is still unclear whether and how fisetin exhibits anticancer effects on ovarian cancer. The present study aimed to evaluate cell apoptotic and necroptotic processes occurring in ovarian carcinoma (OC) cell lines induced by fisetin.Cell growth was evaluated by MTT assay in OC cell lines treated with or without fisetin. Annexin V/propidium iodide staining followed by flow cytometry was used to characterize fisetin-induced cell death. The apoptotic process was suppressed by z-VAD intervention, and cell necroptosis was assessed by introducing ZBP1-knockdown OC cell lines coupled with fisetin intervention. The expression of necroptosis-related mediators and the migration capability of the respective cells were evaluated by Western blotting and in vitro cell invasion assay.Fisetin successfully reduced cell growth in both OC cell lines in a dose-dependent manner. Both apoptosis and necroptosis were induced by fisetin. Suppression of the cell apoptotic process failed to enhance the proliferation of fisetin-treated cells. The induced cell death and robust expression of the necroptotic markers RIP3 and MLKL were alleviated by knocking down the expression of the ZBP1 protein in both OC cell lines.The present study provided in vitro evidence supporting the involvement of both apoptosis and necroptosis in fisetin-induced OC cell death, while ZBP1 regulates the necroptotic process via the RIP3/MLKL pathway. Ovarian cancer (OC) ranks as the second most common gynecological malignancy and is also one of the leading causes of cancer-related mortality in women . AlthougFisetin  is a flavonoid substance that can be extracted from a variety of plants, such as cucumbers, onions, apples and strawberries . FisetinSimilar to those in other solid malignant cancers, various types of cell death processes have been discovered in OC over the past decade. Apoptosis occurs via two main mechanisms: a receptor-dependent extrinsic pathway and a mitochondrion-dependent intrinsic pathway . Both paIn this study, we focused on necroptosis of OC via fisetin intervention. Recent studies have identified ZBP1 as a potential mediator in the regulation of cell death, including that in various types of cancer . HoweverFisetin and z-VAD were purchased from Sigma, USA. The primary antibodies used in this study for Western blotting were as follows: anti-HMGB1 , 1:1000 dilution; anti-ZBP1 , 1:1000 dilution; anti-RIP3 , 1:1000 dilution; anti-RIP1 , 1:1000 dilution; anti-MLKL , 1:1000 dilution; and anti-GAPDH , 1:5000 dilution.2 atmosphere. Fisetin was dissolved in dimethyl sulfoxide (DMSO) to a series of concentrations of 0, 25, 50 or 100 µmol/L and then added to the culture medium to treat both cell lines for 72 h. v-ZAD (dissolved at a concentration of 30 μmol/L) was added to 100 µmol/L fisetin-treated cells for 72 h to inhibit the apoptotic process.Human ovarian carcinoma (OC) cell lines were obtained from Procell  and cultured in DMEM  supplemented with 10% fetal bovine serum  and 1% penicillin–streptomycin . Both cell lines were cultured in a 37% with 5% COThe effect of fisetin on cell proliferation was examined by 3--2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. Briefly, A2780 and VOCAR-3 cells in both the treated and control groups were seeded in 96-well plates at a concentration of 75 µmol/L cells per well. Cells were then incubated for 12 h following fisetin treatment at the series of concentrations mentioned above. After incubation for 72 h, MTT was added to each well, followed by 4 h of incubation. The medium was then washed 3 times to remove MTT. After stabilizing the blue formazan crystals by adding 150 µL of DMSO, the absorbance at 570 nm was detected with a microplate reader  to determine the concentration of blue crystals.An Annexin V-FITC apoptosis detection kit (Sigma–Aldrich) was used for the detection of apoptotic cells. Cells were double-stained with PI and Annexin-V with binding buffer for 30 min at room temperature (RT). Apoptotic and necroptotic cells were analyzed with flow cytometry.ZBP1 siRNAs  were introduced to block endogenous ZBP1 gene expression. Briefly, ZBP1 siRNA  was transfected into A2780 cells using an siRNA transfection kit  following the manufacturer’s instructions. After 24 h of transfection, fisetin + z-VAD treatment was followed. The levels of ZBP1 protein in both cell lines were analyzed by Western blotting.An in vitro cell invasion assay was performed to measure the migration ability of both ZBP-knockdown (ZBP1-/-) and control cells after fisetin + z-VAD treatment using a Matrigel-coated Transwell chamber . Briefly, both types of cells at a density of 24 cells/well were seeded into the upper chambers in serum-free medium with fisetin + z-VAD, while DMEM containing 10% FBS and 1% penicillin–streptomycin was added to the lower chamber. After incubation for 24 h, the cells on the top surface were removed, while the cells on the lower surface of the membranes were fixed with 4% paraformaldehyde for 10 min and stained using 0.25% crystal violet for 15 min. The invaded cells were subjected to an MTT assay.Cell mitochondrion isolation was performed using a Cell Mitochondria Isolation Kit  according to the manufacturer’s instructions. Briefly, the cells were washed with PBS and digested with trypsin, and then the cells were centrifuged at a speed of 100–200 × g for 5 min to collect alkalotic cells. We then transferred the cells to clean tubes and homogenized the cells 10–30 times. The cell homogenate was centrifuged at a speed of 600 g at 4 °C for 10 min. We transferred the supernatant to another clean tube and centrifuged it at a speed of 11,000 rpm at 4 °C for 10 min. The supernatant was cytosol, and the deposit was mitochondria.RNA was extracted from isolated mitochondria by the PureLink RNA mini kit . The quantity and quality of extracted RNA were analyzed by using a NanoDrop 2000 spectrophotometer. Extracted RNA was prepared to synthesize cDNA according to the QuantiNova Reverse Transcription Kit. The QuantiNova SYBR Green PCR Kit was used to determine mRNA expression on an Applied Biosystems PCR machine . The sequences of the primers used in the qRT–PCR experiment were as follows:Cyt-c forward primer, 5’-CTG GGTGACGAGTGAAACTG-3’; reverse primer, 5’-TGAGCACAACAGGAACTGGA-3’; primer length in bp, 104 bp;GAPDH forward primer, 5’-GAAATCCCATCACCATCTTCCAGG-3’; reverse primer, 5’-GAGCCCCAGCCTTCTCCATG-3’; primer length in bp, 120 bp.Cells were cultured in the absence or presence of the respective intervention and then harvested and lysed in RIPA buffer to collect total protein. After ice incubation for 30 min, lysates were centrifuged at 12,000 × g for 5 min to separate the supernatants. The concentration of protein contained in the supernatants was measured by a BCA kit according to the manufacturer’s instructions. Next, 30 µg denatured protein samples were separated on SDS–PAGE gels and then transferred to PVDF membranes (Bio–Rad). After incubation of the membranes with primary antibodies at 4 °C overnight, the samples were incubated with the secondary antibodies conjugated with horseradish peroxidase for 1 h at room temperature. The blots were visualized using a Leica Imaging System.Statistical analysis was completed with SPSS 23.0  and GraphPad Prism 6  software. Data are presented as the mean ± standard deviation. Student’s t test was used to compare the means of groups, and P values ≤ 0.05 were considered significant.Fisetin suppressed cell proliferation in human ovarian cancer cell lines in vitro.To assess the cytotoxicity of fisetin  staining followed by flow cytometry analysis. Fisetin-treated A2780 cells showed a lower percentage of vital cells, as indicated by AV(-)/PI(-) /PI( +) signal. Thus, we hypothesized that the cell necroptotic process and related signaling pathway regulate fisetin-induced OC cell death.Z-DNA-binding protein 1 (ZBP1) functions as a central regulator of cell necroptosis under diverse conditions , 35, 36.To the best of our knowledge, the data presented in this study provide the first in vitro evidence that both cell apoptosis and necroptosis play important roles in the process of fisetin-initiated OC cell death. ZBP1 mediated fisetin-induced cell necroptosis in OC cell lines via the RIP3/MLKL pathway. However, the contribution of each mentioned mechanism to the cell death process by fisetin needs to be further quantified.


Children with T-cell leukemia (T-ALL) who experience relapse have a low chance of a cure with current therapy; so, new medicines are needed. MERTK and BCL-2 are proteins that may be therapeutic targets in children with T-ALL. In this research we tested whether treatments targeting MERTK and BCL-2 are effective in experimental models of T-ALL. We found that MERTK and BCL-2 are present in some T-ALL cells and showed that a new drug called MRX-2843, which blocks MERTK function, can kill T-ALL cells. In mice with T-ALL, treatment with MRX-2843 reduced the presence of leukemia cells and prolonged survival. We also found that MRX-2843 provided more effective T-ALL cell killing when it was combined with another drug called venetoclax, which blocks BCL-2 function. These studies provide good evidence that MRX-2843 could be effective for treatment of T-ALL, especially when combined with venetoclax.T-cell acute lymphoblastic leukemia (T-ALL) accounts for 15% of childhood ALL. The early T-precursor (ETP-ALL) subset is characterized by an immature T-cell phenotype, chemoresistance, and high rates of induction failure. MERTK receptor tyrosine kinase is ectopically expressed in half of T-ALLs, particularly those with an immature T-cell phenotype, suggesting a role in ETP-ALL. The anti-apoptotic protein B-cell lymphoma-2 (BCL-2) is essential for ETP-ALL cell survival. Here, we show that MERTK and BCL-2 mRNA and protein are preferentially expressed in ETP-ALL patient samples. The dual MERTK/FLT3 inhibitor MRX-2843 decreased MERTK activation and downstream signaling, inhibited cell expansion, and induced cell death in ETP-ALL cell lines. Further, 54% (21/39) of primary T-ALL patient samples were sensitive to MERTK inhibition. Treatment with MRX-2843 significantly reduced leukemia burden and prolonged survival in cell-line-derived T-ALL and ETP-ALL xenograft models. In a patient-derived ETP-ALL xenograft model, treatment with MRX-2843 markedly reduced peripheral blood leukemia and spleen weight compared to vehicle-treated mice and prolonged survival. MRX-2843 also synergized with venetoclax to provide enhanced anti-leukemia activity in ETP-ALL cell cultures, with a dose ratio of 1:20 MRX-2843:venetoclax providing optimal synergy. These data demonstrate the therapeutic potential of MRX-2843 in patients with T-ALL and provide rationale for clinical development. MRX-2843 monotherapy is currently being tested in patients with relapsed leukemia (NCT04872478). Further, our data indicate that combined MERTK and BCL-2 inhibition may be particularly effective for treatment of ETP-ALL. Acute lymphoblastic leukemia (ALL) is the most common form of childhood cancer. T-cell ALL (T-ALL) accounts for approximately 15% of ALL cases in children ,3,4,5,6.Early T-precursor ALL (ETP-ALL) comprises 10–15% of pediatric T-ALL, has stem cell and myeloid features, and is difficult to treat, with high rates of remission failure and relapse in children ,4,5. ETPMERTK is a member of the TAM  family of receptor tyrosine kinases. The TAM receptors are ectopically or aberrantly expressed and contribute to oncogenesis in a wide range of human malignancies ,9,10,11.Numerous studies have demonstrated the dependence of hematopoietic malignancies, including T-ALL, on the anti-apoptotic protein B-cell lymphoma 2 (BCL-2) and its family members ,20,21. BIn this report, we expand on our prior work identifying MERTK as a therapeutic target in T-ALL  and demoMRX-2843 and UNC2025 were synthesized as previously described . Venetochttps://ocg.cancer.gov/programs/target (accessed on 23 October 2019). The TARGET data used for this analysis are available at https://portal.gdc.cancer.gov/projects (accessed on 23 October 2019).Publicly available RNA expression data were queried for MERTK and BCL-2 expression. Read counts for MERTK and BCL-2 expression were normalized to the mean read count of non-ETP patient samples. Data were derived from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative, phs000464  supplemented with 10–20% fetal bovine serum (FBS) and 1% penicillin–streptomycin (complete RPMI (cRPMI)).The cell lines CEM, HPB-ALL, HSB2, Jurkat, MOLT4, Loucy, and PEER were obtained from either the American Type Culture Collection  or the DSMZ . The Jurkat-luciferase cell line has been previously described . The LouPatient samples (blood or bone marrow) were obtained from the Aflac Leukemia and Lymphoma Biorepository at Children’s Healthcare of Atlanta (samples designated CHOA), Children’s Oncology Group , and the Therapeutic Advances in Childhood Leukemia & Lymphoma Consortium (TACL0274). Other investigators may have received specimens from the same subjects. Samples ETP-0068TJ and ETP-0065FN were injected into immune-compromised mice and serially passaged to generate murine xenograft models as described below. Additional xenograft-passaged patient samples  were generously provided by Dr. David Teachey .Cell lysates were prepared as previously described . Where iAnalysis of phosphorylated MERTK was conducted as described in . The fol®  cell viability reagents. Fluorescence (PrestoBlue) or luminescence (CellTiter-Glo) was measured using a plate reader. Data shown are representative of at least 3 independent experiments.Cells were plated in triplicate at 20,000 cells/well and cultured in cRPMI. After 24 h, cells were treated with vehicle, MRX-2843, venetoclax, or a combination of MRX-2843 and venetoclax for an additional 48 h and then stained with PrestoBlue™ (Invitrogen) or CellTiter-GloCells were plated at 300,000 cells/well and cultured in cRPMI for 24 h and treated with vehicle or MRX-2843 for an additional 48 h. Treated cells were then harvested and resuspended in PBS with 1 μM PO-PRO™-1 iodide (Invitrogen) and 1.5 μM propidium iodide (Invitrogen) for 15–30 min prior to assessment of dye uptake by flow cytometry using a Cytoflex flow cytometer  and FlowJo v10.8.0 analysis software .Blood and bone marrow samples were obtained after receiving informed consent with IRB approval at Oregon Health & Science University , Stanford University , University of Utah , University of Texas Southwestern , and University of Colorado-Denver . Mononuclear cells were cultured for 72 h in 384-well plates with graded concentrations of UNC2025 or vehicle, and relative numbers of viable cells were determined as previously described .scidIl2rgtm1Wjl/PrkdcSzJ (NSG) and NOD.Cg-scidIl2rgtm1WjlPrkdcTg 1Eav/MloySzJ (NSGS) mice were purchased from The Jackson Laboratory  or bred in-house. Established leukemia cell lines or a xenograft-passaged patient sample were suspended in PBS and injected into the tail vein in NSG or NSGS mice (1 × 106 cells/mouse), respectively, to establish xenografts. Male and female mice were equally represented in all experiments. Lymphoblasts were detected in peripheral blood, spleen, and bone marrow samples after staining with an FITC-conjugated anti-human CD45 Ab . Samples were analyzed using a Cytoflex flow cytometer (Beckman Coulter) and FlowJo v10.8.0 analysis software (Becton Dickinson). For luciferase-expressing cell lines, bioluminescence images were captured and quantitated at intervals as previously described [NOD.Cg-escribed . The higv/v. Cell plates were incubated for 72 h prior to measuring cell viability with the CellTiter-Glo 2.0 Assay (Promega). Relative growth inhibition was calculated by subtracting background luminescence and normalizing to vehicle controls. Synergy was calculated using a response additivity model with the Explicit Mean Equation, as previously described [ETP-ALL cells (Loucy and PEER) were cultured in cRPMI with 10% FBS. Cells were plated  on white polystyrene 384-well microplates  using a Multidrop Combi Reagent Dispenser  and then treated with combinations of MRX-2843 (0–800 nM) and venetoclax (0–400 nM)  using high-throughput liquid transfer robotics . Prior to liquid transfer, drugs were stored in checkerboard arrays of anhydrous DMSO (Thermo Fisher) on polypropylene microwell plates  such that pairwise drug combinations were tested in quadruplicate at a final DMSO concentration of 0.5% escribed , where vt-test, one-way ANOVA with Dunnett’s test for multiple comparisons, or Mann–Whitney-U test as appropriate and are presented as mean ± SEM. p values of <0.05 were considered significant. IC50 values were determined by nonlinear best-fit regression analysis with upper and lower values constrained to 1 and 0, respectively. Kaplan–Meier survival curves were compared using the log-rank test. Synergy was calculated using the fractional product method [Data were analyzed by paired or unpaired t method  or a rest method . All staAll animal experiments were conducted in accordance with the relevant regulatory standards and were approved by the Institutional Animal Care and Use Committee of Emory University.To evaluate MERTK and BCL-2 mRNA expression in patients with ETP-ALL and non-ETP T-ALL, publicly available gene expression data from the TARGET program were analyzed. MERTK A and BCL50 values of 9.5 nM  6.2–14.6) in the Loucy cell line (p = 0.0093) in the presence of FBS, which contains the MERTK ligands GAS6 and PROS1, and by 38% (p = 0.0465) when additional GAS6 was added to the culture to provide an acute stimulus  in Loucy cultures and 86 nM (95% CI 64–118) in PEER cultures. Furthermore, treatment with MRX-2843 resulted in a significant dose-dependent increase in cell death in Loucy , there was no significant difference between mice treated with MRX-2843 compared with vehicle-treated controls  have been reported to occur at a higher frequency in patients with ETP-ALL, though the frequency appears to be lower in pediatric patients with ETP-ALL as compared to adults [Mutations in FMS-like tyrosine kinase 3 .While MRX-2843 was effective in mice with T-ALL/ETP-ALL, mice treated with the monotherapy were not cured. Thus, we explored the potential to combine MRX-2843 with other therapies to enhance therapeutic efficacy. Indeed, MRX-2843 synergized with the BCL-2 inhibitor venetoclax in two ETP-ALL cell lines and provided increased anti-leukemia activity against ETP-ALL cells compared with either of the drugs alone. Given the biologic rationale for targeting BCL-2 in T-ALL and ETP-ALL, and the robust clinical experience with venetoclax, this combination is particularly promising. Using a high-throughput screen, we also identified an optimal synergistic ratio of 1:20 MRX-2843:venetoclax. These data will inform upcoming in vivo studies combining MRX-2843 and venetoclax in T-ALL and ETP-ALL mouse models. The recent finding that ETP-ALL cells may find sanctuary from venetoclax monotherapy in the spleen , coupledAlthough PEER cells did not express detectable BCL-2 protein in our assays, they retained limited sensitivity to BCL-2 monotherapy at high concentrations. This may reflect an off-target effect. Alternatively, BCL-2 protein expression may not correlate with sensitivity to BCL-2 inhibition, a finding that has been demonstrated in T-ALL cell lines . The devActivation of the JAK/STAT signaling pathway—in particular, activation of STAT5—is also important for ETP-ALL cell survival . We prevIn this study, we have demonstrated that MERTK inhibition mediates direct anti-leukemia effects in MERTK-expressing T-ALL and ETP-ALL models. Using Mertk −/− mouse models, our group has previously demonstrated that MERTK deficiency also promotes immune-mediated clearance of ALL . FurtherOur findings support the ongoing clinical development of MRX-2843 for treatment of T-ALL. Additionally, they provide a rationale for further preclinical investigation of combined MERTK and BCL-2 inhibition in ETP-ALL and T-ALL models. Based on these and other data, MRX-2843 monotherapy is being tested in patients with relapsed acute leukemia (NCT04872478).


Circulating tumour cells (CTCs) are a rare cell subpopulation regulated by the tumour microenvironment. In hypoxic conditions, CTCs are able to invade the lymphatic and circulatory systems leading to metastasis at distant sites.To mimic in vivo oxygen variations and effects on CTCs, we have cultured five non-small cell lung cancer (NSCLC) cell lines under normoxic and hypoxic conditions, followed by a pulse of reoxygenation for 4 h.2 levels were investigated. Proliferation rate was not altered when cells were cultured in 2D models under hypoxic conditions. However, we observed that hypoxia enhanced in vitro formation of tumour-spheres and accelerated clonogenicity of NSCLC cell lines. In addition, cells exposed to hypoxia and reoxygenation conditions showed altered expression of epithelial-mesenchymal transition (EMT) related genes in NSCLC cell lines both at mRNA  and protein levels .Proliferation, spheroid-formation and colony formation ability under varying OOur data suggest that when investigating CTCs as a prognostic biomarker in NSCLC, it is also essential to take into consideration EMT status to obtain a comprehensive overview of CTCs in circulation. Metastasis is an extremely complex, multistep process   or in a hypoxic chamber at 1–2% O2, 5% CO2, (94% N2). To avoid the influence of culture media, all culture media conditions were standardised to RPMI-1640-Glutamax  supplemented with 10% foetal bovine serum (FBS)  and 1% Penicillin–Streptomycin .We have used the following NSCLC cell lines, NCI-H460, HCC827, NCI-H1299, NCI-H1703 and SK-MES-1, which were gifted by Professor Derek Richard . All of the NSCLC cell lines were STR profiled and authenticated. This gave us the confidence that our cell lines are correctly identified, and not cross contaminated with other cells. Cells were cultured under standard conditions in humidified incubators at 37 °C, 20% O2) for 14 days to capture in-vivo conditions of CTCs as they enter circulation. In addition, cells maintained in hypoxia were further exposed to a pulse of reoxygenation (normoxia) for 4 h prior to collection. This is to model exposure of CTCs to relatively high O2 levels while in circulation  or hypoxia 1% O% O2 for ® 10 System  according to the manufacturer’s instructions at the Genomics Research Centre . The NSCLC cell lines were processed using the Applied Biosystems® 3500 Genetic Analyzer. Data were analysed using GeneMapper® v5.0 software (Applied Biosystems). Appropriate positive and negative controls were run and confirmed for each sample. Furthermore, mycoplasma testing was also performed in all NSCLC cell lines using the MycoAlert Mycoplasma detection system  at the Genomics Research Centre . All cell lines were negative for mycoplasma.To detect cross-contamination in NSCLC cell lines, we used a short tandem repeat (STR) profiling technique on the GenePrint®). Cells were left to settle overnight in a standard incubator at 37 °C, 20% O2, 5% CO2 for normoxic conditions and 1–2% O2, 5% CO2, (94% N2) for hypoxic conditions. At 24, 48 and 72 h time points, cells were incubated with 3--2,5-diphenyltetrazolium bromide  at a final concentration of 0.5 mg/ml for 4 h as per manufacturer’s instructions. Absorbance was measured using a CLARIOstar Plus microplate reader  at 490 nm absorbance used as the reference wavelength. The assay was performed in three biological replicates.To determine cell proliferation, NSCLC cell lines were seeded in 24 replicates at 2500cells/well in 96-well flat-bottomed plates  diluted with RPMI-1640-Glutamax supplemented with FBS, and Pen Strep described above. Seeding density was optimised to 0.5 × 106/well for each cell line and plated in 96 well Ultra-Low Attachment plates (Corning). Cells were incubated for 72 h in normoxia and hypoxia (1% O2) and visualised with a Nikon Eclipse TS2 microscope.Post trypsinisation, cells were spun down at 10006 cells) was extracted using the RNeasy Mini Kit following the manufacturer’s protocol. RNA extraction procedure comprised of an on-column DNase treatment using RNase-free DNase , as described by the manufacturer. Total RNA was eluted in 25 μL nuclease-free water. The RNA concentration and quality were assessed using the NanoDrop ND-1000 spectrophotometer . Purity of samples was estimated by measuring A260/280 and A260/230 ratios of spectrophotometric absorbance to check for copurified contaminants during RNA isolation. cDNA synthesis and genomic DNA elimination were conducted using the RT2 First Strand Kit  according to the manufacturer’s instructions, using 400 ng total RNA for each sample. Negative reverse transcription (without the reverse transcriptase enzyme) was conducted to prove that the samples are devoid of genomic DNA.For quantitative mRNA analysis, total RNA  was used to investigate the expression of multiple EMT-related genes in NSCLC cell lines under normoxia and hypoxic conditions. The epithelial to mesenchymal transition RT2 Profiler PCR Array includes cell surface receptor, extracellular matrix and cytoskeletal genes mediating cell adhesion, migration, motility, and morphogenesis. The array also includes genes controlling cell differentiation, development, growth, proliferation and signal transduction and transcription factor associated with the process of EMT. The expression of 84 genes was quantified by qPCR in cells grown in normoxia and hypoxia for 14 days and compared to the same cell types subjected to a pulse of reoxygenation for 4 h. All analyses were performed using the web-based PCR Array Data Analysis Software tool provided on the Gene Globe Data Portal  RT™ SYBR® Green Master Mix . qPCR conditions were as follows: 50 °C for 2 min; 95 °C for 10 min; 40 cycles at 95 °C for 15 s and 60 °C for 1 min; and a final melting curve analysis with the following conditions: 95 °C for 15 s, 60 °C for 1 min, and 95 °C for 15 s. qPCR reaction per NSCLC cell line under a condition was run in duplicate using the QuantStudio™ 7 Flex Real-Time PCR System (Applied Biosystems™).HIF-1α expression levels were tested using primers  obtained from the literature . Equal amounts of proteins (25 µg) were loaded into 10% SDS-PAGE gels and run at 100 V for 90 min. Proteins were transferred onto a polyvinylidene difluoride (PVDF) membrane at 100 V for 90 min at 4 °C. The membrane was blocked for 1 h at room temperature (RT) using 5% bovine serum albumin (BSA). Membranes were incubated overnight at 4 °C with the following primary antibodies: EGFR , HIF-1α (Sigma-Aldrich- # HPA000907), AKT , p-AKT , Vimentin—(Santa Cruz—-#sc32322), Pan-Cytokeratin (Thermo Fisher—#ma513203), 4EBP1—, p4EBP1—. Following primary antibody incubation, membranes were incubated with anti-rabbit IgG-HRP secondary antibody  or anti-mouse IgG-HRP secondary antibody  for 1 h at RT. The membranes were incubated with Pierce ECL Western Blotting substrate (Thermo Fisher Scientific) and imaged using ChemiDoc XRS + System (Bio-Rad Laboratories).t test was performed. For analysing the EMT array and qPCR, a One-Way Analysis of Variance (ANOVA) with Multiple Comparisons was performed. Data are shown as mean ± standard deviation unless otherwise specified.All statistical analyses were performed using GraphPad Prism 8 software version 8.43 . For cell proliferation assay and colony-forming assay, an unpaired two-tailed Student’s Cell proliferation is a hallmark of cancer and is considered as an important cellular process leading to tumour development  difference observed for NCI-H1299  in Happy Cell299 Fig. b.Fig. 3Tp < 0.05) decrease in the expression of HIF-1α after reoxygenation in comparison to hypoxia.To investigate the influence of hypoxia on the expression of genes associated with EMT, we have used a commercially available EMT array, and the mRNA expression changes were verified at the protein level using western blotting. We compared the mRNA expression changes of 84 EMT genes in five NSCLC cell lines under normoxia, hypoxia and reoxygenation. We found that the mRNA expression levels of seven EMT-related genes  were significantly altered across the different oxygen conditions  were differentially expressed across varying oxygen conditions. Except for HIF1α, the rest of the genes were significantly upregulated in reoxygenation compared to hypoxia. Over-expressed mesenchymal genes  in NSCLC show the invasiveness in the reoxygenation cell subpopulation compared to the hypoxic condition. It has been shown that cells in reoxygenation showed overexpression of cell–cell and cell-ECM adhesion genes compared to hypoxic  and transcriptional factors  initiate and orchestrate the process of EMT. We saw a lower expression of ZEB1 mRNA in NSCLC cell lines under hypoxia compared to normoxia and reoxygenation. In contrast, exposing cells to hypoxia has been shown to increase EMT-promoting transcription factors such as ZEB1 (Foster et al. The findings of this pilot study have some limitations. It is nearly impossible to establish the time that CTCs in circulation have been subjected to hypoxic conditions prior to release into the bloodstream from primary or metastatic sites. Furthermore, tumour microenvironment conditions are difficult to mimic and make the current study an approximation in identifying oxygenation effects on proliferation, colony and sphere formation, as well as the impact on EMT. Other cultural conditions should also be accounted for, such as pH changes. Additional evaluation of other phenotypic assays are needed, including migration and invasion assays and further exploring proliferation rates and cell cycle. Future studies with patient samples could utilise this model to understand better the effects of oxygenation on tumour cells and their ability to survive and extravasate.Our data suggest that when investigating CTCs as a prognostic biomarker in NSCLC, it is also important to take into consideration mesenchymal markers to obtain a comprehensive overview of the status of CTC in circulation. We also suggest that reoxygenation increases the expression of a number of EMT markers, leading to a more mesenchymal phenotype.