In addition, many active compounds identified, including the non-anticancer drugs and other compounds, diversely inhibited the growth of three gynecologic cancer cell groups and individual cancer cell lines. These newly identified compounds are valuable for further studies of new therapeutics development, synergistic drug combinations, and new target identification for gynecologic cancers. The results also provide a rationale for the personalized chemotherapeutic testing of anticancer drugs in treatment of gynecologic cancer.Heterogeneous response to chemotherapy is a major issue for the treatment of cancer. For most gynecologic cancers including ovarian, cervical, and placental, the list of available small molecule therapies is relatively small compared to options for other cancers. While overall cancer mortality rates have decreased in the United States as early diagnoses and cancer therapies have become more effective, ovarian cancer still has low survival rates due to the lack of effective treatment options, drug resistance, and late diagnosis. To understand chemotherapeutic diversity in gynecologic cancers, we have screened 7914 approved drugs and bioactive compounds in 11 gynecologic cancer cell lines to profile their chemotherapeutic sensitivity. We identified two HDAC inhibitors, mocetinostat and entinostat, as pan-gynecologic cancer suppressors with IC The five main gynecologic cancers, including ovarian, cervical, uterine, vaginal, and vulvar, correspond to 12%  of new female cancer diagnoses annually in the United States While ovarian cancer is usually diagnosed at later stages of disease, resulting in a low 5-year survival of 29% for distant-stage disease, cervical cancer is typically diagnosed at early stages and thus has more favorable outcomes Placental cancers, or gestational trophoblastic disease (GTD) choriocarcinomas, are another type of gynecologic cancer. Gestational carcinomas arise from the fetal-derived layer of cells called the trophoblast that surrounds an embryo There is currently a set of standard anticancer drugs used in the clinic to treat gynecologic cancers. For ovarian and cervical cancer, these include chemotherapy agents gemcitabine, cisplatin, and doxorubicin as well as targeted therapeutics such as topotecan, a topoisomerase inhibitor, and bevacizumab, a monoclonal antibody directed against vascular endothelial growth factor To understand the diversity in compound efficacy across gynecologic cancers within individual cancer groups and identify new active compounds, we have screened 7914 compounds consisting of approved drugs and bioactive compounds using a quantitative high-throughput screening (qHTS) method against 11 unique gynecologic cancer cell lines derived from ovarian, cervical, and placental cancers. The results were analyzed to profile the chemotherapeutic activities of compounds against these gynecologic cancer cell lines. Our data demonstrate the commonality and diversity in responses of gynecologic cancers to the anticancer agents. We have also identified a group of non-anticancer compounds with antigynecologic cancer activities that can be further studied for target identification and drug development.A, B and Supplementary Figure 2A-C) and CAOV-3  cell lines. Based on the assay optimization results, we used 1000 cells per well plated in 1536-well plates and a 48-hour incubation with compounds. The control compound activities (IC50) of adriamycin and curcubitacin B reached the steady state at this assay condition. Other standard-of-care (SOC) anticancer drugs examined during optimization included paclitaxel and topotecan A-F). Adriamycin and curcubitacin B were designated as the positive control compounds in the subsequent screens .To determine the inhibitory effects of approved drugs and bioactive compounds on the common gynecologic cancer cell lines, 11 cell lines including 7 ovarian cancer lines , 3 cervical cancer lines , and 2 placental cancer lines  were used in the drug repurposing screen with HEK 293T cells as a control line to determine selectivity index of anticancer compounds (SI) Figure 150 less than 10 μM, efficacy greater than 50%, and three-fold greater selectivity over the HEK 293T cells. From the primary screen, the signal-to-basal ratio was 9.30, coefficient of variation was 13.2% and Z' factor was 0.69 in the PA-1 cell line. For the CAOV-3 cell line, the signal-to-basal ratio was 9.86, coefficient of variation was 11.3%, and Z' factor was 0.71.Following optimization, we next screened a collection of 7914 compounds including the FDA-approved drugs and bioactive compounds in 11 cancer cell lines shown in 50 less than 30 μM, efficacy greater than 70%, and five-fold greater selectivity over HEK cells. A group of hits that were toxic to both cancer cells and HEK 293T cells was designated as the pan-toxic compounds  and givinostat , two HDAC inhibitors, are used as examples to illustrate the toxicity .Among the primary hits tested in a follow-up screen (Pubchem AID 1345085), 205 compounds were confirmed using criteria of IC50 = 2.76 ± 1.98 μM; SI >100) and entinostat 50 = 7.11 ± 6.62 μM; SI >100), both class I HDAC inhibitors and in clinical trials, as pan-killers of all three cancer cell groups , a DNA intercalator and common drug for GTD, and fedratinib 50 = 13.1 ± 7.51 μM; SI >100), a JAK2 inhibitor , a JAK2 inhibitor, and CCT137690 50 = 20.0 ± 7.02 μM; SI >100), an Aurora kinase inhibitor , a Syk kinase inhibitor , an anti-parasitic alkaloid targeting Complex I of the mitochondrial respiratory chain and AP-1 machinery  in each group. Interestingly, while there were only 2 placental lines included in the study, 13 compounds reached an SI of 5 or greater in this group. Four compounds killed all three cervical cancer lines selectively, and only one compound, fedratinib, selectivity killed all six ovarian cancer lines. Fedratinib, one of the ovarian and cervical CCL selective inhibitors, has completed two Phase I clinical trials for solid tumors  but is not an FDA-approved drug. The heat maps for each cancer tissue group provided a high-level view of the SI for each compound that fulfilled the criteria (C-E). These maps reveal that PA-1, TOV-21-G, and HeLa cells, the faster growing lines . Neratinib 50 = 0.619 μM; SI >100), an FDA-approved epidermal growth factor receptor (EGFR) inhibitor, and milciclib 50 = 0.0897 μM (SI = 50.1), a CDK inhibitor, were the two most potent TOV-21-G inhibitors. The top HeLa suppressor was LY2874455 50 = 0.240; SI = 38.8) μM, a pan-FGFR inhibitor.In addition to finding compounds with general antineoplastic activity, the selective inhibitory activities of compounds to individual cell lines were evaluated. We identified five compounds with selective inhibitory activities for PA-1, two compounds for TOV-21-G, and four compounds for HeLa . As mentA). We arranged the data to reflect how many cell lines have a number of compounds with a potency less than 1 μM. These data show that only one compound, the multitargeted HDAC inhibitor panobinostat , exhibited sub-μM potency in every cancer cell line among 11 cancer cell lines tested .The results from our qHTS gynecologic cancer profiling revealed a diverse set of compounds with potencies ranging from the nanomolar to micromolar and different selectivity among three types of cancer tissues. We wanted to highlight these nanomolar compounds which may be useful to researchers and clinicians alike as these are the ones with anticancer activity to likely be far below their blood plasma concentrations, Cmax, in patients. We analyzed our data to uncover the number of compounds with less than 1 μM potency and greater than 70% efficacy regardless of selectivity. The data correspond with the similar trend for cytotoxic susceptibility in PA-1 (43 compounds), TOV-21-G (19 compounds), and HeLa (33 compounds) cells  2 resulted in a Cmax of 0.107 to 2.24 μM 50 of panobinostat for the ovarian, cervical, and placental lines in our study is 0.343, 0.224, and 0.516 μM, respectively. The IC90 average for all cell lines is 0.719 μM, within the range of the intravenous, but not oral, Cmax values.To provide useful information with clinical relevance, we have analyzed the IC50 of 0.150 μM with good efficacy in 8 of the 11 cancer cell lines excluding SKOV-3, HeLa, and JAR. Its average IC90 was 0.218 μM, well within the intravenous dose Cmax of 580 nM 50 of 0.173 μM and an IC90 of 0.283 μM. The Cmax of elesclomol in a clinical trial ranged from 1.32 to 12.84 μM with doses of 44 to 438 mg/m290 for Actinomycin D in our study against ES-2, CAOV3, PA-1, TOV-21-G, SK-OV-3, and Ca Ski was 512 nM, while the Cmax in a pediatric population can range from 4 to 97.2 nM after 15 minutes of exposure to the drug 90 identified in our study is several-fold above what can be achieved in human blood plasma 90 to Cmax values for the most promising clinical candidates from Supplementary Figure 9 is presented in Bortezomib, a 20S proteasome inhibitor, exhibited an average ICHeterogeneous responses in gynecologic cancers to chemotherapeutic drugs make it challenging to predict the drug's clinical effectiveness. This heterogeneity arises from differences in patient genetic background, patient age, tumor microenvironment, treatment regimen, and intrinsic resistance to drug therapy. In general, overall cancer incidence and death rates for women have been falling since the 1930s We assessed the cytotoxicity of 7914 compounds consisting of approved drugs, drug candidates tested in clinical trials, and bioactive compounds in six ovarian, three cervical, and two placental cancer cell lines. Two Class I HDACIs, mocetinostat and entinostat, were identified and confirmed as pan-gynecologic cancer inhibitors with high degrees of efficacy and selectivity (SI >100) in all three cancer groups. Interestingly, we did not find other HDACIs to be as selective except for these two. Indeed, panobinostat, givinostat, and vorinostat, three other HDAC inhibitors, were found to be equally toxic to HEK 293T cells in our screens in addition to suppressing the 11 gynecologic cancer cell lines. HDACIs prevent the removal of acetyl groups on histone lysines and, in effect, open chromatin structure to modulate gene expression 50 value or similar to or below its IC90 value in the cells of the newly identified indication. We researched the human Cmax values of our most broadly potent compounds and compared them to the experimental IC90 values in this study. In most cases, our experimental IC90 is at or below the human plasma concentration, indicating that the effective drug concentration against the new indication is achievable in patients. Mocetinostat has a Cmax of approximately 21.4 μM at 10 mg/kg and 75.7 μM at 40 mg/kg in humans 50 in our work was found to be 2.76 ± 1.98 μM, this indicates that the Cmax is well above its anticancer activity. For entinostat, however, although the patient Cmax is significantly lower than the average IC50 achieved in our study (7.11 ± 6.62 μM) for gynecologic cancers, its in vivo activity could possibly be achieved in higher doses or with compound structure-activity optimization. It is possible that the low toxicity of mocetinostat and entinostat is due to their specific HDAC isotype selectivity for certain HDACs. Both are class I HDAC inhibitors but exhibit varying IC50s for specific HDACs. For example, mocetinostat was found to inhibit only HDAC 1/2/3/11 at low micromolar potency or below in vitro effects against gynecologic cancers in our study. This HDAC isotype selectivity may be related to the drugs' activity against the gynecologic cancer cell lines as HDAC 1/2/3 have been implicated in ovarian tumor malignancy and growth In order to advance the compounds identified from a drug repurposing screen to potential clinical trials, the blood plasma concentration of the drug should be a few-fold higher than its ICi.e., G0 to G1We also identified single cell line selective compounds with submicromolar potency and high selectivity for PA-1 (ovarian), TOV-21-G (ovarian), and HeLa , which could be due to their faster growth rates compared to other cancer cell lines and the cell cycle–interrupting nature of many compounds. Empirically, cells which cycle faster are more susceptible to interruptions of cell growth at different cycle stages in vivo toxicity of compounds may also be different from the in vitro SI data. The selectivity reported here is for reference, and it should be noted that it cannot replace the data obtained from in vivo drug safety experiments and in clinical trials. We acknowledge the unequal numbers of lines for each cancer group . Having fewer lines in one group will potentially increase the number of compounds that are pan-killers for that particular group. This is evident in the larger number of compounds that killed both placental lines as compared to the number of compounds that killed all six ovarian lines.The control cell line in this study, HEK 293T, is a normal human cell line originating from human embryonic kidney cells that is typically used as control cell line. The selectivity values determined in this study were relevant to the cytotoxicity of the compounds in HEK 293T cells. Given a different control line, the resulting selectivity may be different. The in vivo against adenocarcinomic human alveolar basal epithelial (A549 cells) and colorectal carcinoma (HCT116 cells) xenografts in combination with chlorpromazine in vivo xenograft models that could provide more physiologically relevant data on tumor killing.The results of this study warrant further investigation into the different responses cancers have to similar classes of compounds. Here, different HDAC inhibitors exhibit differential selectivity. This could possibly be due to differences in HDAC class specificity, with some inhibitors targeting class I HDACs preferentially to class II HDACs, for example Drug resistance to chemotherapy is a common cause for relapse and recurrence of many different types of cancers bona fide gynecologic cancer therapeutics. Indeed, entinostat in combination with avelumab is already in Phase I/II clinical trials for epithelial ovarian cancer, peritoneal cancer, and fallopian tube cancer . Likewise, despite its toxicity to HEK 293T cells, panobinostat may be further studied in in vivo experiments due to its extremely high potency in gynecologic cancers. In conclusion, the chemotherapeutic profiling in individual cancer cells is an effective method to reveal the best anticancer therapeutics that might be particularly useful for those cancers with multidrug resistance, poor prognosis, and survival rates.In conclusion, the compounds identified and confirmed in this drug repurposing screen and profiling can be used to further investigate their utility in the treatment of gynecological cancer, especially for multidrug-resistant cancer patients. We demonstrate here the variability and heterogeneous responses of gynecologic cancer cells to anticancer drugs that may be related to patient genetic background, age, intrinsic drug resistance, and cancer aggressiveness. Two HDAC inhibitors identified in this study, mocetinostat and entinostat, may have high clinical relevance and can be moved to clinical trials as DMEM (11965092), penicillin/streptomycin (15140163), and TrypLE (12605010) were purchased from Life Technologies. FBS (SH30071.03) was purchased from HyClone (SH30071.03). ATPlite (6016739) was purchased from Perkin Elmer.The following cell lines were purchased from ATCC: CAOV-3 , SK-OV-3 , SW 626 , ES-2 , PA-1 , TOV-21G , HeLa , Ca ski , C-33 A , JAR , JEG-3 , and HEK 293T .Cells were kept in cryovials frozen at −150°C and thawed quickly in a 37°C water bath. A total of 1.5 million cells were seeded into T-225 flasks and subcultured once using TrypLE before freezing down for future experiments. For all assays, cells were seeded at 1000 cells per well into white, solid-bottom 1536-well plates using a Thermo Fisher Multidrop Combi reagent dispenser.2 in assay plates, followed by the addition of DMSO or 16 SOC chemotherapeutic compounds dissolved in DMSO. SOC compounds were dosed at 11 concentrations (1:3 dilution) in quadruplicate from 57.5 μM to 0.977 nM using the automated Wako 1536 Pin Tool workstation and incubated at 37°C with 5% CO2 for 24, 48, or 72 hours. Four microliters of ATPlite, the ATP monitoring reagent, was then added to each well of the assay plates using the Multidrop Combi reagent dispenser followed by incubation for 15 minutes at room temperature. The resulting luminescence was measured using the ViewLux plate reader. Data were normalized for each drug using the largest luminescence value as 100% full cell viability (0% cell killing) and to the smallest luminescence value 0% viability (100% cell killing).The ATPlite luminescence assay system assay kit was used to determine cell viability. The reagent was reconstituted and prepared as described by the manufacturer. To measure the cell death caused by the compounds, cells were cultured in 4 μl of media for 16 hours at 37°C with 5% CO50 values for each compound was conducted as described above. Plates were processed on the fully integrated Kalypsys robotic system. Hits were selected from the primary screen for follow-up confirmation, dosed in triplicate at 11 concentrations (1:3 dilution) from 57.5 μM to 0.977 nM, and incubated for 48 hours, and the ATPlite assay was used to determine the IC50 values.A qHTS Data analysis was performed using Microsoft Excel, and figures were generated using Prism Graphpad 7.0. In-house qHTS data normalization, correction, curve fitting, and classification were performed using custom programs developed at NCATS Data have been submitted to Pubchem. Primary Screen AID: 1345084. Confirmatory Screen AID: 1345085.


XPO1 mRNA expression in 741 pancreatic samples, including 95 normal, 73 metastatic and 573 primary cancers samples, and searched for correlations with clinicopathological and molecular data, including overall survival. XPO1 expression was heterogeneous across the samples, higher in metastatic samples than in the primary tumors, and higher in primaries than in the normal samples. “XPO1-high” tumors were associated with positive pathological lymph node status and aggressive molecular subtypes. They were also associated with shorter overall survival in both uni- and multivariate analyses. Supervised analysis between the “XPO1-high” and “XPO1-low” tumors identified a robust 268-gene signature, whereby ontology analysis suggested increased XPO1 activity in the “XPO1-high” tumors. XPO1 expression refines the prognostication in PAC and higher expression exists in secondary versus primary tumors, which supports the development of XPO1 inhibitors in this so-lethal disease.Pancreatic adenocarcinoma (PAC) is one of the most aggressive human cancers and new systemic therapies are urgently needed. Exportin-1 (XPO1), which is a member of the importin-β superfamily of karyopherins, is the major exporter of many tumor suppressor proteins that are involved in the progression of PAC. Promising pre-clinical data using XPO1 inhibitors have been reported in PAC, but very few data are available regarding XPO1 expression in clinical samples. Retrospectively, we analyzed  KRAS, TP53, SMAD4, CDKN2A, BRCA2, and ARID1A mutations and GATA6 amplification have been identified in PAC [Pancreatic adenocarcinoma (PAC) is a major public health problem worldwide with the highest mortality rate of all human cancers and a rising incidence ,2. Compld in PAC ,10,11,12The active transport of macromolecules between the nucleus and the cytoplasm controls the localization and functions of many proteins and RNAs. Exportin-1, which is also called chromosome region maintenance 1 (CRM1/XPO1), is a member of the importin-β superfamily of karyopherins; it is the major exporter of the majority of proteins, some mRNAs, rRNAs, and snRNAs , from thXPO1 inhibition can inhibit several critical pathways that promote cancer progression and therapy resistance, and became a potential therapeutic strategy. This has led to the development of XPO1 inhibitors, initially including natural products, such as leptomycin B ,29, plumIn PAC, preclinical data support the development of XPO1 inhibitors ,49,50,51XPO1 mRNA expression in a clinical series of 741 pancreatic samples, including 95 normal samples, 73 metastatic samples of PAC, and 573 primary PAC, and searched for correlations with clinicopathological and molecular data, including overall survival.However, there is a paucity of data regarding the prevalence of XPO1 expression in clinical samples of pancreatic cancer, with only three studies ,52,53, oXPO1  and EntrezGene , ftp://ftp.ncbi.nlm.nih.gov/gene/) to retrieve and update the Agilent annotations, and NetAffx Annotation files  for the Affymetrix annotations. The probes were then mapped according to their EntrezGeneID and, when multiple probes represented the same GeneID, we retained the one with the highest variance in a particular dataset. For the RNA-seq data, we used the available normalized RNASeq data that we log2-transformed. Subsequently, we corrected the ten studies for batch effects using z-score normalization. Briefly, for each separate XPO1 expression value in each study, subtracting the mean of the gene in that dataset divided by its standard deviation, mean, and standard deviation only being measured on primary cancer samples transformed the value. XPO1 expression in tumors was measured as discrete value after comparison with mean expression in the 573 primary tumors: high expression was defined by value > mean and low expression by value ≤ mean.Data analysis required pre-analytic processing. First, we separately normalized each DNA microarray-based data set by using quantile normalization for the available processed Agilent data, and Robust Multichip Average (RMA) with the non-parametric quantile algorithm for the raw Affymetrix data sets. Normalization was done in R using Bioconductor and the associated packages. Subsequently, we mapped hybridization probes across the different technological platforms present. We used SOURCE  as a learning set, and the other data sets as independent validation sets (423 samples). In the learning set, we compared the whole-genome expression profiles between tumors with (N = 76) versus without (N = 74) high XPO1 expression using a moderated t-test with an empirical Bayes statistic [p < 1.0 × 10−5 and q < 1.0 × 10−5 defined significant genes. Ontology analysis of the resulting gene list was based on the GO biological processes of the Database for Annotation, Visualization and Integrated Discovery . We verified the robustness of the resulting gene list in the validation set (295 tumors with and 283 without high XPO1 expression) by computing a metagene-based prediction score defined by the difference between the “metagene XPO1-high”  and the “metagene XPO1-low”  for each tumor. This score was then compared between the “XPO1-high” and “XPO1-low” samples.We separately applied different multigene classifiers to each sample in each data set: the subtype classifiers that were reported by Bailey , Collisstatistic  being intatistic  was applt-test or the Fisher’s exact test, when appropriate, were used to analyze the correlations between XPO1-based tumor classes and clinicopathological features. Overall survival (OS) was calculated from the date of diagnosis to the date of death from pancreatic cancer. Follow-up was measured from the date of diagnosis to the date of last news for event-free patients. The survivals were calculated using the Kaplan–Meier method and the curves were compared with the log-rank test. Univariate and multivariate survival analyses were done using Cox regression analysis . The variables tested in univariate analyses included patients’ age at time of diagnosis , sex, American Joint Committee on Cancer (AJCC) stage , pathological features including pathological type, tumor grade , tumor size , regional lymph node status (positive vs. negative), and XPO1 expression (“high” vs. “low”). Variables with a p-value < 0.05 were tested in multivariate analysis. All of the statistical tests were two-sided at the 5% level of significance. Statistical analysis was done using the survival package (version 2.30) in the R software . We followed the reporting REcommendations for tumor MARKer prognostic studies (REMARK criteria) [The riteria) .XPO1 mRNA expression in 573 clinical primary PAC samples. Their clinicopathological characteristics are summarized. Briefly, most of patients were more than 60 year-old and 53% were male. Most of the tumors were ductal type (93%), grade 2 (57%), and they were classified as AJCC stage II (85%); most of them were pT3 tumors (78%) and most had at least one lymph node involved (70%). All but one had been initially treated by surgery. None of them had received neoadjuvant chemotherapy or radiotherapy. All of the molecular subtypes were represented with more frequent squamous Bailey’s subtype (36%), more frequent classical Collisson’s subtype (45%), more frequent classical Moffitt’s tumor subtype (60%), and more frequent activated Moffitt’s stroma subtype (59%).XPO1 expression was variable and different between the normal tissue samples, the primary tumors, and the metastatic samples , and from primary cancer samples to metastatic samples . We defined two classes of primary cancer samples that were based upon XPO1 expression in tumors when compared with mean expression in normal pancreatic samples: the “XPO1-high” class  and the “XPO-low” class . We then searched for correlations between these two classes and the clinicopathological and molecular features (XPO1-high” tumors were enriched in pN-positive tumors (p = 1.97 × 10−2) and in squamous Bailey’s subtype (p = 3.20 × 10−5), in classical and quasi-mesenchymal Collisson’s subtypes (p = 9.07 × 10−4), in basal-like Moffitt’s tumor subtype (p = 4.55 × 10−4), and in activated Moffitt’s stroma subtype (p = 4.69 × 10−4).The  samples A, with afeatures . There wfeatures B–E. The p = 4.19 × 10−5, log-rank test). The respective median OS were 16 months (range: 1 to 126) versus 23 months (range: 1 to 156), and the hazard ratio (HR) for death was 1.56  in the “XPO1-high” class when compared with the “XPO1-low” class .Overall survival data were available for 573 patients. With a median follow-up of 16 months , 351 patients (61%) died, the two-year OS was 39% , 35–44; p = 3.98 × 10−3), the pathological lymph node involvement (p = 3.80 × 10−5), the Collisson’s classification (p = 7.62 × 10−3), the Moffitt’s tumor classification (p = 1.69 × 10−5), the Moffitt’s stroma classification (p = 4.33 × 10−4), and the Bailey’s classification (p = 1.26 × 10−6). Patients’ age and sex, and pathological tumor size and grade were not significantly associated with OS. In multivariate analysis, XPO1 expression remained significant when confronted with the significant clinicopathological variables  in the “XPO1-high” class when compared with the “XPO1-low” class  and when confronted with the molecular subtypes  in the “XPO1-high” class when compared with the “XPO1-low” class , suggesting an independent prognostic value. Due to the correlation between the four different molecular subtype classifications, we repeated the multivariate analyses by including XPO1 expression and each of the four classifications separately. As shown in −4 and 1.13 × 10−4).In univariate analysis , the othXPO1 expression status, we applied supervised analysis to the TCGA data set (N = 150). We identified 268 genes that were differentially expressed between the tumors with (N = 76) versus without (N = 74) XPO1 upregulation, including 191 genes that were upregulated and 77 genes that were downregulated in the “XPO1-high” samples  and aggressive molecular subtypes, squamous Bailey’s subtype, quasi-mesenchymal Collisson’s subtype, basal-like Moffitt’s tumor subtype, and activated Moffitt’s stroma subtype. Such an association with adverse prognostic features was confirmed in univariate analysis with shorter metastasis-free survival (MFS) in the “XPO1-high” class. However, interestingly, such unfavorable prognostic value remained significant in multivariate analysis, suggesting independence. Our analysis was based on discrete values while using the mean expression level in normal tissues as cut-off, but a similar correlation was found when XPO1 expression was analyzed as continuous values.Our analysis was based on mRNA expression rather than protein expression as measured using immunohistochemistry (IHC) for several reasons: i) avoiding the limitations of IHC with different non-standardized protocols for XPO1; ii) working on an available large series of clinical samples; and, iii) searching for associations with expression of other genes on a whole-genome scale. When compared to normal pancreatic tissue, It is not surprising to find frequent high expression in PAC and association with poor prognosis given the XPO1 function of inactivation of TSPs. This has already been reported in several cancers ,27,68,69XPO1-high tumors identified several ontologies that were related to cell proliferation, such as cell cycle, nuclear division, chromosome segregation, and DNA replication; other ontologies, such as DNA repair, signal transduction, or RNA processing also agreed with the multiple protein targets of XPO1 exported from the cell nucleus to the cytoplasm in eukaryotic cells [XPO1 expression in PAC is likely associated with an increase in its biological activity.Our analysis of genes upregulated in ic cells ,16, and ic cells , and shoic cells . These cXPO1 mRNA expression is heterogeneous in PAC and is associated with progression stage and shorter survival independently from the other prognostic features. The strength of our study lies in the size of the series , the biological and clinical relevance of XPO1 expression, and its independent prognostic value. The limitations include its retrospective nature and associated biases, such as the lack of available information regarding the delivery or not of adjuvant chemotherapy for most of cases. No patient had received neoadjuvant chemotherapy, impeding the search for an eventual correlation of XPO1 expression with response to chemotherapy. Obviously, an analysis of larger series, retrospective, then prospective, is warranted to confirm our observation. Functional studies need to be conducted with fresh patient samples as well as retroactive meta-data analysis to link mRNA levels to actual protein expression and patient outcomes. If such a prognostic value is confirmed, XPO1 expression might refine the prognostication and improve our ability to tailor adjuvant chemotherapy. However, more importantly, and given this unfavorable prognostic value and the likely association with increased XPO1 biological activity, patients with high level of XPO1 expression would warrant a more aggressive treatment plan, which should include SINE compounds that are associated with classical drugs, notably the DNA-damaging agents. In the metastatic setting, clinical trials are ongoing, and it will be important to test whether XPO1 mRNA expression can predict the clinical response to SINE compounds.In conclusion, we showed that


Central obesity was assessed with the Waist Hip Ratio (WHR) and abdominal visceral and subcutaneous fat area fractions , and systemic inflammation with blood plasma concentrations of leptin, adiponectin, C-reactive protein and interleukin 8. Men were significantly more centrally obese and had higher VFF than women. Individual differences in WHR and in VFF were negatively correlated with differences in fornix MPF and kf, but not with any differences in neurite microstructure. In women, age mediated the effects of VFF on fornix MPF and kf, whilst in men differences in the leptin and adiponectin ratio fully mediated the effect of WHR on fornix MPF. These results suggest that visceral fat related systemic inflammation may damage myelin-related properties of the fornix, a key limbic structure known to be involved in LOAD.Midlife obesity is a risk factor of late onset Alzheimer's disease (LOAD) but why this is the case remains unknown. As systemic inflammation is involved in both conditions, obesity-related neuroinflammation may contribute to damage in limbic structures important in LOAD. Here, we investigated the hypothesis that systemic inflammation would mediate central obesity related effects on limbic tissue microstructure in 166 asymptomatic individuals (38–71 years old). We employed MRI indices sensitive to myelin and neuroinflammation [macromolecular proton fraction (MPF) and  •Central adiposity is linked to apparent myelin/inflammatory damage in the fornix.•Central adiposity is not linked to differences in apparent neurite microstructure.•Men were more centrally obese and had higher visceral fat fractions than women.•In women, age mediated the correlation between visceral fat and fornix myelin.•In men, adipokines mediated the correlation between WHR and fornix myelin. Western-style diet and sedentary lifestyles contribute to obesity risk and its related diseases including metabolic syndrome, type 2 diabetes, and cardiovascular disease  (38–71 years old) . Going bkf was found to be sensitive to acute neuroinflammation in response to typhoid vaccination in the insular cortex, an area which also exhibited vaccination-induced increases in fluorodeoxyglucose positron emission tomography metabolism that correlated with inflammation-induce fatigue  between free and macromolecular bound protons. In white matter, MT is dominated by myelin , and is  fatigue . Similarfunction  that mayfunction .Fig. 1A)These qMT measurements were contrasted with MRI estimates of neurite microstructure from NODDI  yieldingvia limbic white matter pathways such as the fornix  and interleukin-8 (IL-8) , as wellAPOE genotype and family history of dementia were also collected and included in the analysis    in limbikf) . We alsokf) . In addikf)  one mighkf) . The app22.1via internet and poster advertisements. The study was approved by the School of Psychology Research Ethics Committee at Cardiff University (EC.14.09.09.3843R2) and all participants gave written informed consent in accordance with the Declaration of Helsinki. Exclusion criteria were a history of neurological disease , psychiatric disease , moderate to severe head injury with loss of consciousness, drug or alcohol dependency, high risk cardio-embolic source , known significant large-vessel disease  and MRI contraindications . Demographic and health information including information about genetic and lifestyle risk factors of dementia was collected for all 211 volunteers. Here we report data from n = 166 participants who also underwent MRI scanning at CUBRIC. Over a period of three years (2014–2017), n = 211 community-dwelling individuals between 35 and 75 years of age were recruited for CARDS from local Cardiff University databases and 2.22, overweight as BMI of 25–29.9 kg/m2 and obese as BMI >30 kg/m2. Abdominal subcutaneous and visceral fat area fractions were obtained from MRI segmentation as described below.Abdominal adiposity was assessed by measuring participants' waist and hip circumferences to calculate WHR following the World Health Organisation's recommended protocol . AbdominSystolic and diastolic blood pressure (BP) was measured with a digital blood pressure monitor  whilst participants were comfortably seated with their arm supported on a pillow. The average of three BP readings was taken and hypertension was defined as systolic BP ≥ 140 mm Hg. Other cardio-vascular risk factors of diabetes mellitus, high levels of blood cholesterol controlled with statin medication, history of smoking and weekly alcohol intake were self-reported by participants in a medical history questionnaire . Informa2.3g within 60 min from blood collection. Plasma samples were transferred into 0.5 ml polypropylene microtubes and stored in a freezer at −80 °C.Venous fasting blood samples were drawn into 9 ml heparin coated plasma tubes after 12 h overnight fasting and were centrifuged for 10 min at 2,000×Circulating levels of high-sensitivity CRP in mg/dL were assayed using a human CRP Quantikine enzyme-linked immunosorbent assay (ELISA) kit (R & D Systems) and IL-8 levels in pg/mL were determined using a high sensitivity CXCL8/INTERLEUKIN-8 Quantikine ELISA kit (R & D Systems). Leptin concentrations in pg/ml were determined with the DRP300 Quantikine ELISA kit (R & D Systems) and adiponectin in ng/ml with the human total adiponectin/Acrp30 Quantitkine ELISA kit (R & D Systems) and leptin/adiponectin ratios for each participant were calculated . Determi2.4Participants provided a saliva sample using the self-collection kit “Oragene-DNA (OG-500) (Genotek) for DNA extraction and APOE genotyping. APOE genotypes ε2, ε3 and ε4 were determined by TaqMan genotyping of single nucleotide polymorphism (SNP) rs7412 and KASP genotyping of SNP rs429358. Genotyping was successful in a total of 207 participants including 165 out of the 166 individuals that had undergone an MRI scan. The genotypic distribution of those successfully genotyped was reported in 2.5MRI data were acquired on a 3T MAGNETOM Prisma clinical scanner  equipped with a 32-channels receive-only head coil at CUBRIC.2.5.11-weighted anatomical images were acquired with a three-dimension (3D) magnetization-prepared rapid gradient-echo (MP-RAGE) sequence with the following parameters: 256× 256 acquisition matrix, TR = 2300 ms, TE = 3.06 ms, TI = 850 ms, flip angle θ = 9°, 176 slices, 1 mm slice thickness, FOV = 256 mm and acquisition time of ∼6 min.T2.5.22 and 60 directions at b-value = 2400 s/mm2) and six non-diffusion weighted scans with dynamic field correction and the following parameters: TR = 9400 ms, TE = 67 ms, 80 slices, 2 mm slice thickness, FOV = 256 × 256 × 160 mm, GRAPPA acceleration factor = 2 and acquisition time of ∼15 min.Diffusion data (2 × 2 × 2 mm voxel) were collected with a spin-echo echo-planar dual shell HARDI  sequence2.5.33 resolution. The following off-resonance irradiation frequencies (Θ) and their corresponding saturation pulse nominal flip angles (ΔSAT) for the 11 MT-weighted images were optimized using Cramer-Rao lower bound optimization: Θ =  and their corresponding ΔSAT values = . The longitudinal relaxation time, T1, of the system was estimated by acquiring three 3D gradient recalled echo sequence (GRE) volumes with three different flip angles  using the same acquisition parameters as used in the MT-weighted sequence . Data for computing the static magnetic field (B0) were collected using two 3D GRE volumes with different echo-times   .2.5.41 = 1910 ms, TR2 = 5.9 ms, TI = 1200 ms, flip angle θ = 20°, Field of View = 480 × 390 mm; acquisition matrix = 256 × 166; 10 mm slice thickness, 3.4 s acquisition time) was acquired. The echo times were set such that one image was acquired with water and fat signals in-phase (TE = 2.34 ms), and one with them out of phase (TE = 3.4 msec). Participants were instructed to hold their breath during the brief image acquisition to minimise movement artefacts.The Dixon technique  was used2.62 data were corrected separately for distortions induced by the diffusion-weighted gradients and artifacts due to head motion with appropriate reorientation of the encoding vectors  registration to correct for inter-scan motion using Elastix . Data fr1-weighted anatomical volume as reference image with linear affine registration (12 degrees of freedom) using FMRIB's Linear Image Registration Tool (FLIRT).All image modality maps and region of interest masks were spatially aligned to the T2.72 HARDI data for each dataset in single-subject native space using in house software , which is documented online (https://surfer.nmr.mgh.harvard.edu/). The hippocampal regions included areas of the presubiculum, subiculum, cornu ammonis subfields 1–4, dentate gyrus, hippocampal tail and fissure but excluded cortical regions such as the entorhinal cortex  and correlation coefficients are reported as indices of effect sizes.Statistical analyses were conducted in SPSS version 24  and the APOE genotype, FH). Post-hoc group comparisons were conducted with independent t-tests and were 5% FDR corrected.Omnibus multivariate regression analysis was conducted to test for the relationships between the body composition/adiposity metrics and demographic variables , health-related variables  and genetic risk of LOAD  = 0.4, p < 0.001], and with differences in WHR  but not with differences in VFF (p = 0.29). Differences in WHR correlated positively with differences in VFF  but not with SFF (p = 0.7). There was a negative correlation between differences in VFF and SFF .3.3APOE genotype, FH) on the body composition/adiposity metrics .Multivariate regression analysis was employed to test for any potential effects of demographic variables , health-related variables , and genetic risk of LOAD  = 2.8, p = 0.03; ηp2 = 0.12], leptin-adiponectin ratio  and CRP  on the four adiposity metrics.There were significant omnibus effects of sex  and VFF  than women . Older i3.4kf, the third on MPF, and the fourth on ICSF in all white matter regions. The fifth component had loadings from ISOSF, MPF and kf, of the fornix only.kf from left and right hippocampi  = −0.28, p < 0.001] (kf   = −0.24, p = 0.008] and hippocampal ISOSF component  remained significant when age was partialled out. Women showed significant negative correlations between VFF and fornix MPF  (kf   or women .As age and sex had significant effects on WHR and VFF, we assessed their respective effects on the observed adiposity-brain correlations by firstly partialling out age, and secondly, by calculating Pearson correlations coefficients for men and women separately. After 5% FDR correction, the correlations between WHR and fornix MPF , fornix  = 0.01] A and for< 0.001] B, and me< 0.001] C. No cor3.7kf , and alcohol had no overall effect on adiposity metrics in the multivariate analysis. Thus, we would argue that shifts in the leptin/adiponectin ratio in men were primarily due to their central obesity.kf, the apparent correlations with fornix and hippocampal ISOSF metrics were solely driven by sex differences in central obesity and ISOSF measures, i.e. men showed higher fornix and hippocampal ISOSF than women , whilst the majority of middle-aged participants in this study were overweight (MeanBMI = 27) with 20% falling within the obese category. As we proposed in the previous paper, the observed relationship between BMI and fornix microstructure may not relate to mechanisms underpinning obesity but may rather reflect some functional properties of the fornix within hippocampal-hypothalamic-prefrontal food control networks . However, we did not specifically investigate insulin resistance and glucose metabolism in the present study, and our sample size may not have been sufficiently large to detect any interactive effects between APOE genotype and obesity-related mechanisms in men.The relationship between obesity and genetic risk of dementia, notably n in men , other sOAD risk . Here weIn our study we also did not observe specific effects on hippocampal microstructure. However, for the reasons outlined above, one may expect qMT metrics to be more sensitive to myelin damage in white rather than in grey matter, especially as we were studying a sample of asymptomatic individuals. Our results are also consistent with a previous study that used multi-parameter mapping and reported BMI-related differences in MRI metrics consistent with reduced myelin, increased water and changes in tissue iron content in tracts connecting limbic structures with the prefrontal cortex .kf. However, the Ramani approximation provides a robust estimate of MPF, as noted by A few methodological limitations of our study need to be recognised. Firstly, although the Ramani 'Continuous Wave Power Equivalent' approximation for pulsed MT experiments reduces the complexity in modelling the data, it does introduce a bias into the fitted parameters. Most relevant for the data presented here, it can lead to a consistent underestimation in the exchange rate, Secondly, we were not able to acquire maps of the B1 transmit field as part of the study. Variations in the B1 transmit field generated by the RF coil will introduce a spatial variation in the effective MT pulse amplitude. Thus, the effective MT weighting for each MT acquisition will vary across the brain. This can be corrected by measuring this B1 transmit inhomogeneity by using, for example, the Bloch-Siegert method . It has Although we observed an omnibus effect of CRP on all body adiposity measures consistent with previous evidence , differeTo summarise, the present study showed that central obesity, notably abdominal visceral fat accumulation, was associated with differences in qMT indices of apparent myelin and neuroinflammation in the fornix in a sample of asymptomatic individuals at midlife and early older age. In men, who had larger VFF than women, these correlations were mediated by shifts in the leptin/adiponection ratio, suggesting that visceral fat related inflammatory states contribute to myelin-related damage in the fornix. As the fornix is a key limbic structure involved in LOAD, these results are consistent with the view that obesity-related changes in immune responses and associated white matter glia changes may contribute to the link between midlife obesity and LOAD.5APOE genotyping. FF and JE have prepared the qMT and diffusion MRI protocols and have helped with MRI data processing. AKM and FG carried out the manual segmentations of the abdominal fat area regions. RJB was involved in the conceptualisation and has advised on statistical data analysis. EK and BE were responsible for the ELISA serum analyses. DKJ provided feedback on the study design and manuscript.CMB is the PI of the study and is responsible for the conceptualisation and data acquisition and analyses of the study. CMB has also written the manuscript. JPM and EL were responsible for participant recruitment, data acquisition and MRI data processing. RS was responsible for the


Diverse properties of graphenic materials have been extensively explored to determine properties that make good electrochemical nanomaterial-based biosensors. These are reviewed by critically examining the influence of graphene nano-morphology, lattice defects and conductivity. Stability, reproducibility and fabrication are discussed together with sensitivity and selectivity. We provide an outlook on future directions for building efficient electrochemical biosensors. Fabrication of electrochemical biosensorsInfluence of nano-morphology, lattice defects and conductivityConcepts and parameters governing electrochemical biosensor sensitivity, selectivity, stability and reproducibilityBiosensors, broadly applicable to biology and biomedicine, can transform healthcare with innovative precise detection of scarce analytes via a biorecognition element and a transducer , 2. SpecHere, we introduce concepts for the main techniques used in electrochemical biosensing, highlighting the distinguishing qualities of advanced nanomaterials used for electrochemical biosensor elaboration. For graphenic sensors in particular, we focus on three key parameters: morphology, electrical conductivity and the influence of lattice defects.Electrochemical sensors represent promising and robust analytical tools, increasingly used in many fields, including analytical chemistry, molecular biology, healthcare diagnostics, environmental monitoring and security . ElectroDifferent electrochemical sensing technique nomenclature reflects what is measured: (1) Amperometric, current at a fixed potential; Voltammetric, current at a varying potential. (2) Potentiometric, potential or charge accumulation at constant current. (3) Conductometric, WE conductivity at varying frequencies. (4) Impedimetric, impedance (both resistance and reactance) at varying AC  potential frequencies. (5) Field-effect, current generated by a potentiometric effect at the gate electrode using a transistor . TypicalIn amperometry, the current (I) is recorded as a function of time (t) and various amperometric based sensors have been designed to measure the current continuouly from the oxidation or reduction of an electroactive species in an electrochemical reaction. The defining Clark experiment introduced the simplest form of amperometric biosensor, whereby currents produced by consumption of oxygen or production of hydrogen peroxide by oxydoreduction activities of glucose oxidase (GOx) permitted measurement of glucose concentration. Nowadays, amperometric biosensors are commercially available and widely used for glucose monitoring, reflecting the pioneering design’s effectiveness. Exemplifying current design progress, a miniaturised screen printed biosensor (100–400 microns), using a water-based ink containing cobalt phthalocyanine, detected glucose by chronoamperometry (CA) in the linear range from 0.5 to 2.5 mM , appropr6]3−/4− is a standard electrolyte for electrochemical biosensing, because of higher surface sensitivity in comparison to other redox systems such as [Ru(NH3)6]3+/2+ 3+/2+ . In cyclquations , 17; andequation . Those p−6 to 1 × 10−4 M ET and a detection limit of 8.7 × 10−7 M was achieved 3+/2+, the HET for both planes is similar, whereas for [Fe(CN)6]3−/4− it is dramatically different since the edge-plane activity is faster [3)6]3+/2+ redox system with an outer-sphere electron transfer mechanism, the charge transfer rate is mostly affected by the electronic properties of the electrode, in particular its DOS near the Fermi potential. In contrast, [Fe(CN)6]3−/4− represents an inner-sphere redox probe, thus its electron transfer kinetics is dependent on both surface microstructure and DOS.The electrochemical electrode response to reactants is mainly dependent on electron transfer kinetics and available surface area. The rate of heterogeneous electron transfer (HET), i.e. the transfer of electrons from/to electrode to/from molecules, is also correlated to the electrodes’s density of electronic states (DOS) and surface chemistry . Introducing disorder/defects and roughness achieves a higher DOS, improving the HET of an electrode. It is established that the existence of edge plane sites/defects on graphitic materials improves the electron transfer processes  Fig. 2aa2a, occue planes . Faster e planes , 57 withs faster . For theAlthough single-layer pristine graphene of perfect 2D crystal structure has promising applications, its electrochemical activity suffers from an “Achilles’ heel” lack of an edge-plane band or significant surface defect densities . Nonethe−1 and G peak at circa 1580 cm−1 3−/4− and [Ru(NH3)6]3+/2+ redox probes) and quantitative analysis (reversible process through Randles–Sevcik and Nicholson equations). An ability to controllably change the anodization time, served to accurately tune the graphene defect density. It was clearly shown that anodized EG at 200 s had a slower HET rate constant than the one anodized at 500 s. The latter had more defective sites, a sharper redox [Fe(CN)6]3−/4− peak separation and, higher capacitance in potassium chloride (KCl) at 0.025 V.Applying a CV potential of up to 2.0 V for 500 s to oxygenated epitaxial graphene in PBS (anodization process), a mixture of DNA bases could be detected simultaneously, without a pre-hydrolysis step. dsDNA was discriminated from ssDNA with better sensitivity than when using GCE and boron doped diamond. Moreover, mixtures of biomolecules  were treated as individual peaks . This wa2), lower charge transfer resistance (160.8 Ω), antifouling properties and a higher density of edge-plane defect sites (I(D)/I(G) ~ 1.38). Edge-plane defects provided numerous active sites valuable for accelerating electron transfer between the electrode and species in solution. However, it was clear from an I(D)/I(G) of graphite/GCE close to 0 [Zhou et al. compared the electrochemical sensing ability of CR-GO/GCE  with graphite/GCE and GCE with a different morphology Fig. a 106]. . 106]. Tose to 0 , that deOne of the most informative direct comparisons was undertaken by Báez et al., who compared the electrochemical performance of graphene oxide reduced by chemical (CRGO), thermal (TRGO), hydrothermal (HRGO), and electrochemical (ERGO) methods taken from a similar GO source . The red13 and 3.76 × 1013 molecules cm−2 for GO and CRGO-COOH, respectively. Interestingly, COOH groups on CRGO did not change its electrochemical response significantly (CV and EIS curves) meaning no significant damage was introduced during grafting. This seemed in good agreement with the fact that the grafted COOH groups did not introduced many defects in the structure as indicated by Raman measurements sistance . Nonethesistance .3−/4− by the negatively charged phosphate backbone of the hybrdized DNA probe NA probe . This imUbiquitous development of electrochemical biosensors for healthcare and biomedicine has yet to produce fully integrated functional devices approved for real clinical evaluation. Nonetheless, the growing portfolio of biosensors using unique versatile 2D nanomaterials and their hybrid composites as a thin surface veil imparting transformative properties has encouraging potential for the biomedical field. Manufacturing graphene sheets to perfection need not be essential, so long as measurement conditions and quality control can maintain a satisfactory consistency and reproducibility. Although defects are often considered detrimental to material properties, if engineered to tailor the surface in a controlled manner, they can introduce properties that enhance function for a wide range of new electrochemical biosensors.Research into innovative 2D material-based sensors beyond the first application of graphene in 2008, has provided useful experimental examples, yet for commercialization the technology is still in its infancy, facing challenging fabrication procedures and poor control of uniformity and reproducibility for reaching the desired properties . There i


Bruton’s tyrosine kinase (BTK) is a key component of B cell receptor signalling. Because of this, BTK plays an important role in cell proliferation and survival in various B cell malignancies. However, in certain contexts, BTK can also have tumour suppressor functions. We have previously shown that BTK activates the p53 transcriptional activity by binding to and phosphorylating p53, as well as acting on MDM2 to reduce its inhibitory effects. This results in increased p53 functions, including enhanced cell death. Here, we report that BTK can also induce cell death and increase responses to DNA damage independently of p53. This is concomitant to the induction of p21, PUMA and MDM2, which are classic target genes of the p53 family of proteins. Our results show that these p53-independent effects of BTK are mediated through p73. Similar to what we observed in the p53 pathway, BTK can upregulate p73 after DNA damage and induce expression of its target genes, suggesting that BTK is a modulator of p73 functions and in the absence of p53. This effect allows BTK to have pro-apoptotic functions independently of its effects on the p53 pathway and thus play an important role in the DNA damage-related induction of apoptosis in the absence of p53. This provides a novel role of BTK in tumour suppression and contributes to the understanding of its complex pleiotropic functions BTK is a fundamental component of the B cell receptor signalling, through which it regulates many cellular processes, including differentiation and signalling2. Various types of leukaemia and lymphoma express abundant levels of active BTK4. Because of this, Ibrutinib, a small-molecule inhibitor of BTK that forms a covalent bond with BTK near the ATP binding site at cysteine 481 and blocks autophosphorylation5, has shown clinical efficiency against B cell malignancies4.Bruton’s tyrosine kinase (BTK) is a cytoplasmic kinase that belongs to Tec family and is able to phosphorylate both serines and tyrosines6. Also, BTK can induce cell death in several models12. The mechanisms by which BTK expression increases the percentage of cells undergoing apoptosis have not been completely elucidated. We showed that it could be mediated by its enhancing role on p53 activity, by binding to and phosphorylating both p53 and MDM2, and thus disrupting the negative feedback loop that leads to the proteasomal degradation of p5313. These novel roles of BTK suggest that it could contribute to the activation of other tumour suppressor pathways as well.Despite its well-studied oncogenic role, it has been reported that BTK can also have tumour suppressor activity. For instance, we identified BTK in a screen of proteins selectively upregulated in senescence15. TAp73 is a bona fide tumour suppressor; conversely, ΔNp73 shows oncogenic properties, inhibiting TAp73 and p53 functions16. TAp73 induces target genes that have a key role in cell cycle arrest and apoptosis, including p53 targets such as p21, Puma17, and MDM219. MDM2 suppresses p73 activity, establishing a negative feedback loop similar to the one observed with p5320.The p73 transcription factor belongs to the p53 family of proteins and has many splice variants, including transcriptional domain-containing p73 (TAp73) and amino deleted p73 (ΔNp73)In order to better understand the tumour suppressor effects of BTK, we studied the mechanisms involved in the BTK-mediated induction of apoptosis. Here, we report that BTK can trigger cell death and enhance it after damage, independently of its effects on the p53 pathway. We show this is mediated by p73, the protein levels of are also regulated by BTK. We propose that BTK has a simultaneous impact on several pro-apoptotic pathways, among them p53 and p73, and that it is therefore an important component of tumour suppressor pathways.−/−). As shown in Fig. 12 and in the absence of p53. These results together indicate that BTK has pro-apoptotic effects and can enhance cell death responses triggered by DNA damage, even when p53 is not present.To study the p53-independent tumour suppressor functions of BTK, we expressed it in H1299, a p53 null non-small-cell lung carcinoma cell line, and a HCT116 colon cancer cell line with a p53 deletion  was added for 24 h to induce DNA damage.Cells were cultured in DMEM and incubated at 37 °C with 5% COpGL3-p21, pGL3-PUMA, pGL3-MDM2 , pSV-β-Galactosidase, pCDNA3, pCDNA3-FLAG-MDM2, pCDNA3-GFP-BTK , pGEX-MDM2, pGEX-UBC9, shBTK (Santa Cruz sc-29841-sh), and shRNA against luciferase  were used in this study.−/− using Turbofect, following manufacturer’s protocols. The medium in the plates was changed after an overnight incubation and 2 μg/ml puromycin added to each plate to select for transfected cells. Cells were kept under selection for 2 weeks.To generate cells with a stable downregulation of BTK, a shRNA against BTK was used. A shRNA against luciferase was used as a control. The shRNA was transfected into HCT116p53−/− were transfected with siRNA  using Lipofectamine 2000, following manufacturer’s protocols. A scrambled siRNA was used as control.Small interfering RNA (siRNA) against p73 was used to transiently downregulate p73 expression. HCT116p53A total of 100,000 cells per well were seeded in 24-well plates one day before transfection. Furthermore, 1.0 μg of total plasmid DNA per well was used, 24 h after transfection, media was replaced by fresh growth media and samples was treated with 1.0 μM Doxorubicin. Furthermore, 20 h later, lysates were collected in lysis buffer and stored at −80 °C overnight. One quarter of the 80 μl cell lysate was then analysed with a luciferase assay kit  using Victor X3 Multilabel Plate Reader  and following manufacturer’s instructions.13. Primary antibodies used: β-actin , p73 , p21 , PUMA , BTK , MDM2 , and PARP .Lysates were extracted as previously described24. The following primers were used: (MDM2) GTTCTTTTTTATCTTGCCCAGTATATT (FWD), GTGCTCTTTCACAGAGAAGCTTG (REV); (p21) CACCGAGACACCACTGGAGG (FWD), GAGAAGATCAGCCGGCGTTT (REV), (p73) AGCAGCCCATCAAGGAGGAGTT (FWD), TCCTGAGGCAGTTTTGGACACA (REV); (PUMA) GACCTCAACGCACAGTACGA (FWD), CACCTAATTGGGCTCCATCT (REV); (GAPDH) GGGAAGGTGAAGGTCGGAGT (FWD), TTGAGGTCAATGAAGGGGTCA (REV).Expression of MDM2, p21, p73 and Puma genes was analysed by RT-PCR as previously described13. Flow cytometry analysis was performed using Becton Dickinson FACSanto II FACSDiva 6.0 software (Becton Dickinson)Cell death was measured using PI as previously described12.The colony formation assay was performed as previously describedSupplementary FiguresAuthor contribution form


Blood-derived autologous products are frequently used in both human and equine medicine to treat musculoskeletal disorders. These products, especially the platelet-rich plasma (PRP), may contain high concentrations of growth factors (GFs), and thus improve healing in several tissues. Nevertheless, the procedures for preparation of PRP are currently non-standardized. Several protocols, which are based on distinct centrifugation patterns (rotation speed and time), result in PRPs with different characteristics, concerning platelet and GFs concentrations, as well as platelet activation. The aim of the present study was to compare two different protocols for PRP preparation: protocol (A) that is based on a single-centrifugation step; protocol (B), which included two sequential centrifugation steps (double-centrifugation). The results here reported show that the double-centrifugation protocol resulted in higher platelet concentration, while leukocytes were not concentrated by this procedure. Although platelet activation and aggregation were increased in this protocol in comparison to the single-centrifugation one, the TGF-β1 concentration was also higher. Pearson’s correlation coefficients gave a significant, positive correlation between the platelet counts and TGF-β1 concentration. In conclusion, although the double-centrifugation protocol caused premature platelet aggregation, it seems to be an effective method for preparation of PRP with high platelet and TGF-β1 concentrations.  In the last decade, hemoderivative therapeutics has become a suitable alternative to treat musculoskeletal disorders in both human and veterinary medicine. Particularly, the platelet-rich plasma (PRP) has shown beneficial effects on several joint diseases, which help to relieve pain and improve the articular structures .A systematic review on the efficacy of PRP in equine and human orthopedic therapeutics  concludeCampbell et al.  have demOn the other hand, PRP is an accessible and inexpensive source of growth factors , especiaDifferent authors have used distinct centrifugation patterns  to prepare PRP, possibly resulting in different final products . Some prAlthough TGF-β1 is not the only growth factor present in PRP, it plays a significant role in musculoskeletal disorders, and it will be emphasized here. TGF-β is a multifunctional cytokine that belongs to the TGF superfamily, which includes three different mammalian isoforms (TGF-β 1 to 3) and bone morphogenetic protein (BMP). The isoform TGF-β1 was first identified in human platelets as a protein of 25 kDa, with a potential role in wound healing. Most of the immune cells secrete TGF-β1 .In vitro and in vivo studies revealed that TGF-β ameliorates the deleterious effects of IL-1 on the cartilage matrix, counteracting both the IL-1 induced proteoglycan degradation and the suppression of synthesis . AdditioHowever, the role of TGF-β in joints remains controversial . While TThese controversial results emphasize the need to standardize PRP preparation and to characterize the products, aiming at high platelet counts and high TGF-β1 concentrations. This is usually achieved by increasing centrifugal force, and/or time, but a limiting point is that platelet activation and aggregation also increases by increasing these centrifugal patterns. Platelet activation leads to TGF-β1 release, and the resulting preparation could be rich in platelets, but poor in TGF-β1. Thus, careful characterization of PRP is necessary, especially when intended for intra-articular administration, concerning the TGF-β1 concentration, to minimize the adverse effects .The platelet-poor plasma (PPP) is the supernatant, which is usually discharged during PRP preparation. This fraction can be considered to be a byproduct and it has demonstrated positive effects when used in subcutaneous tissue during orthopedic surgery ,21 and aTherefore, the aim of the present study was to compare PRP that was prepared by two different protocols: a “single-centrifugation protocol”, based on one centrifugation step, and a “double-centrifugation protocol”, based on two centrifugation steps, in sequence. The PRP and PPP preparations were analyzed for platelet counts, platelet activation, and TGF-β1 concentration.http://ec.europa.eu/environment/chemicals/lab_animals/legislation_en.htm. Twelve gelding male horses, aged between three and five years, which were clinically healthy and free of any drugs for 15 days prior to the study, were included in the present study.The present study was approved by the Faculdade de Medicina Veterinária e Zootecnia of the Universidade de São Paulo’s Ethics Committee on Animal Use , and it was carried out in accordance with EC Directive 86/609/EEC for animal experiments The sample size calculation was determined to provide an 80% statistical power mainly for TGF-β1, and platelet concentration to detect a difference of 30% between the groups, with a two-sided alpha level of 0.025 and β = 0.20 based on two-way analysis of variance.Blood was collected from jugular vein following aseptic preparation of the site. For the single centrifugation protocol (see below), blood was collected while using a 21-gauge needle and a 10 mL syringe, and transferred to a Falcon tube (15 mL) containing 1 mL of 3.8% sodium citrate as anticoagulant. For the double centrifugation protocol, a 21-gauge needle and seven vacutainer tubes containing 3.8% sodium citrate were used . After harvesting and homogenization of the blood, the final volume was aliquoted and transferred to three Falcon tubes (15 mL), 10.5 mL each.Two different protocols were used for PRP preparation: a single and a double centrifugation procedure, as schematized in g for 12 min. (room temperature), and the supernatant was collected was named “PRP-0”.The single centrifugation protocol that was used here was adapted from Ottaiano et al. , in whicg for 5 min., followed by another 25 min. “rest period”. It was empirically observed that less platelet activation occurred when these “rest period” were included. The supernatants were collected, and one of them was reserved and named “PPP-1”, while the other two were submitted to a second 700× g, 15 min. centrifugation, followed by another “rest period” of 45 min. The supernatant from the second tube was collected, reserved, and named “PPP-2”. The pellet and remaining volume were gently homogenized using a pipette and named “PRP-1”. The supernatant of the third tube, named “PPP-0”, was collected and cleared by centrifugation at 1000× g for 10 min., to assure minimal platelet counting in the supernatant. This was use as a sample with 100% light transmission in aggregometry testing, as described below.For the double centrifugation protocol , three 1A complete blood count was performed on each blood sample. Leukocyte (WBC) counts were completed in the PRP-0, PRP-1, and PPP-1 sample while using a flow cytometry hematology system .Platelet counts were performed in whole blood  samples and in the PRP-0, PRP-1, PPP-1, and PPP-2 samples while using a Neubauer chamber. Platelet concentrations were described as a ratio between platelet count for each sample and the platelet count for the whole blood sample.Platelet aggregation responses were evaluated while using an aggregometer  and monitored by the turbidimetric method developed by Born and Cross  using AgThis test was performed in all samples, except PPP-2, because, due to its low platelet counts, PPP-2 did not gave reliable results. The agonist alone was added as a control. All of the samples were stored at −80 °C until further analysis and TGF-β1 determination.TGF-β1 concentrations were quantified in all samples by ELISA, while using a commercially available human TGF-β1 kit , previously validated for use in equine samples ,27, in aAfter thawing and homogenization, TGF-β1 of each sample was activated: aliquots (20 µL) were placed in microcentrifuge tubes (200 μL), and 10 µL of 1 M HCl were added, which were then homogenized and incubated at room temperature. After 10 min., 10 µL of 1.2 M NaOH and 160 µL of RD5-53 diluent  were added to each sample. RD5-53 diluent (50 µL) was added to all the wells of a 96-well anti-TGF-β1 antibody coated plate (TGF-β1 plate). Standards or samples (50 µL) were then added to the appropriate wells and then incubated for 2 h at room temperature with gentle agitation. The solution was discarded and the plate was washed four times with wash buffer solution . Next, 100 µL of anti-TGF-β1 polyclonal antibody conjugated with HRP  were added to each well, which were then covered by a film and then incubated again for 2 h at room temperature. The washing procedure was repeated, as previously described, and then 100 µL of substrate solution were added to each well. The plate was then covered with aluminum foil and incubated for 30 min. at room temperature. Finally, 100 µL of stop solution was added to each well. The wells were homogenized and absorbances were read while using a microplate reader at 450 nm.p < 0.05 and confidence interval (CI) of 95%.The data were analyzed for normality while using Kolmogorov–Smirnov tests. Afterwards, an analysis of variance (ANOVA), followed by Tukey-Kramer or Bonferroni tests, were used to compare parametric data. Non-parametric data were analyzed via the Friedman test. Correlation analyses were performed while using coefficients of determination and Pearson’s correlation coefficients. Statistical analyses were performed using GraphPad Instat 3 . Statistical significance was set to 3/μL. p = 0.0001). For PRP-0, the mean platelet count was 494 ± 157 × 103/μL (2.7 times the baseline), while for PPP-1 and PRP-1, the platelet counts were 756 ± 228 × 103/μL (4.2 times) and 1371 ± 423 × 103/μL (7.6 times), respectively. These data show that higher platelet counts were obtained in the products that were prepared by the double-centrifugation protocol (PPP-1 and PRP-1), as compared to the lower values that were obtained by the single centrifugation procedure (PRP-0). As expected, the platelet counts in PPP-2 (supernatant of the second centrifugation step) was lower than the baseline.The baseline platelet counts for the horses that were used in the present study was 180 × 10In contrast, the leukocyte counts decreased in all analyzed products  relative to the baseline , which ip = 0.0001) in the samples that were prepared by the double-centrifugation protocol: PPP-1 = 90.9% and PRP-1 = 66.8%. This indicates that a certain degree of platelet activation/aggregation had already occurred during the experimental procedure.Aggregometry tests revealed significant differences among the groups . PRP-0 hp = 0.0001). The mean TGF-β1 concentrations in PRP-0 (5537 pg/mL) and PPP-1 (5539 pg/mL) were similar to each other, while PPP-2 presented the lowest concentrations (mean 2942 pg/mL) (2 pg/mL) A.2 = 0.74; Pearson’s correlation coefficient = 0.86).The aim of the present study was to establish a protocol to prepare PRP with high platelet counts, as well as high TGF-β1 concentration. PRPs with such characteristics are supposed to be more useful for intra-articular administration in treating joint diseases.Two different protocols were tested, and the products thus obtained were characterized, concerning platelet counts, TGF-β1 concentrations, and premature platelet activation/aggregation.Our results have shown that the first protocol, based on a single centrifugation step, avoided premature platelet activation/aggregation, but resulted in a preparation with relatively low platelet and TGF-β1 concentrations (PRP-0).In contrast, the final product that was obtained by the double-centrifugation protocol—PRP-1—presented high platelet counts and high TGF-β1 concentration, but some degree of premature platelet activation occurred. Leukocyte counts were not concentrated.PPP-1, the product of the first centrifugation step in the double centrifugation protocol, was similar to PRP-0. This product could be considered to be a “PRP”, since it presents the minimum platelet concentration required to be considered a “PRP” by Fortier et al.  , and only 66.8% responded after the second centrifugation step (PRP-1). These results suggest that increased centrifugation speed and time could lead to platelet activation, which is in agreement with other authors . ArgüeleIn the present study, collagen was used as exogenous agonist. Reversible responses are obtained , althougThe TGF-β1 concentrations were similar in PRP-0 (single-centrifugation) and PPP-1 (first centrifugation step in the double-centrifugation protocol), despite their differences in platelet counts. This could be due to the premature platelet activation and partial TGF-β1 release in the preparation of PPP-1.The highest TGF-β1 concentrations were found in PRP-1 (double-centrifugation procedure), again demonstrating a correlation between platelet counts and TGF-β1 concentration. This result agrees with other studies on PRP in equines ,33,34,36Pereira et al.  comparedAs platelet activation is necessary to release growth factors, the avoidance of premature activation guarantees the presence of growth factors at the time of PRP use. Most of the growth factors have short half-lives after release (minutes to a few hours). If activated platelets are not used in an adequate timeframe, the growth factors become inactivated before application to the target tissue . ConsequIt should be emphasized that the procedures described here permit the preparation of PRPs with different characteristics, which could be useful in treating different clinical joint conditions. For example, PRP-0 may be useful to treat large joints, in which the injection volume is not an issue, while PRP-1, whereas more laborious and time-consuming, may be appropriate to treat small joints.The present study has compared two procedures for preparation of PRP, one that is based on a single-centrifugation step and one based on double-centrifugation. In the single-centrifugation procedure, no premature platelet activation occurred, but platelets and TGF-β1 were less concentrated. The double-centrifugation protocol resulted in high platelet and TGF-β1 concentrations, but a certain degree of activation occurred, which was evidenced by both aggregometry tests and the presence of TGF-β1 in supernatant. All of our preparations were platelet-rich but not leukocyte-rich. Taken together, these results emphasize the need to carefully characterize the PRP obtained by any procedure, to produce reliable and reproducible results.


Pisum sativum L.), the allelic state of Sym2 gene has long been reported to regulate the symbiotic specificity: for infection to be successful, plants with the Sym2A allele  require an additional acetylation of the Nod factor which is irrelevant for genotypes with the Sym2E allele (for “Sym2 European”). Despite being described about 90 years ago, Sym2 has not yet been cloned, though phenotypic analysis suggests it probably encodes a receptor for the Nod factor. Recently, we described a novel pea gene LykX (PsLykX) from the LysM-RLK gene family that demonstrates a perfect correlation between its allelic state and the symbiotic specificity of the Sym2A-type. Here we report on a series of Middle-Eastern pea genotypes exhibiting the phenotype of narrow symbiotic specificity discovered in the VIR plant genetic resources gene bank . These genotypes are new sources of Sym2A, as has been confirmed by an allelism test with Sym2A pea cv. Afghanistan. Within these genotypes, LykX is present either in the allelic state characteristic for cv. Afghanistan, or in another, minor allelic state found in two genotypes from Tajikistan and Turkmenistan. Plants carrying the second allele demonstrate the same block of rhizobial infection as cv. Afghanistan when inoculated with an incompatible strain. Intriguingly, this “Tajik” allele of LykX differs from the “European” one by a single nucleotide polymorphism leading to an R75P change in the receptor part of the putative protein. Thus, our new data are in agreement with the hypothesis concerning the identity of LykX and the elusive Sym2 gene.At the onset of legume-rhizobial symbiosis, the mutual recognition of partners occurs based on a complicated interaction between signal molecules and receptors. Bacterial signal molecules named Nod factors (“nodulation factors”) are perceived by the plant LysM-containing receptor-like kinases (LysM-RLKs) that recognize details of its structure , thus providing the conditions particular to symbiosis. In the garden pea ( Fabaceae) and nodule bacteria  is an example of a highly specific interaction of symbiotic partners. Communication between plant and bacteria relies on an exchange of signal molecules, a process known as “molecular cross-talk”  specimens originating from Afghanistan as incapable of forming nodules in European soils , and Sym2E, or Sym2C   . In conta genome . Since rpecific) , althougLotus japonicus (Regel) Larsen (NFR1 and NFR5) and Medicago truncatula Gaertn. (LYK3) (Sym2-orthologous region of the M. truncatula genome and described one of them (LYK3) as the best candidate for encoding the Nod factor receptor. In 2008, Zhukov and colleagues discovered two pea homologs of L. japonicus NFR1, namely Sym37 and K1, located in linkage group I, just where Sym2 is located  located in the same region of linkage group I was described. When analyzing the polymorphism of its first exon, a minor haplotype was found which is unique for lines with the “Afghan” phenotype. Thus, LykX has become a new candidate for the Sym2.In 2003, genes encoding LysM-domain receptor-like kinases (LysM-RLKs) that probably perceive the Nod factor were described in the model legumes . (LYK3) . Interes located . Unfortuous work , a new pSym2 gene has been the use of a limited number of “Afghan” lines with high genetic uniformity; for example, they all possessed the same alleles of the Sym37 and K1 genes. This may be due to the fact that these lines are close relatives, or even descendants of the same original genetic line. More than 30 years ago, the study of wild varieties of pea from Afghanistan, Iran, Tibet and Turkey revealed seven varieties with the “Afghan” specificity, but no molecular-genetic analysis had been performed , St. Petersburg, Russia), kindly provided by Prof. M. A. Vishnyakova, head of Department of genetic resources of leguminous crops, and E. V. Semenova, curator of the pea collection. The choice of material was determined by the geographical origin of samples (the Middle East). The whole sample contained 122 pea lines see .Pisum fulvum Sibth. & Smith  was kindly provided by Sc.D. O.E. Kosterin .Additionally, a number of pea cultivars and genetic lines with the confirmed “Afghan” phenotype from the collection of the laboratory of genetics of plant-microbial interactions of the All-Russia Research Institute for Agricultural Microbiology  were used as control . The linDuring the summer season of 2011, plants were grown in vegetation houses in conditions corresponding to the region’s climate . When necessary for control, plants were grown in Vötsch Industrietechnik VB 1014 growth chambers  under the following conditions: •day/night: 16/8 hours; •temperature: 21 °C; •relative air humidity: 75%; illumination: 38000 lux.2SO4 for between 10 and 15 minutes and then washed five times with distilled water. Sterilized seeds were germinated in Petri dishes filled with sterile vermiculite for 3 days at 27 °C, then seedlings were planted in pots. For large-scale experiments in vegetation houses, sterilization and preliminary germination of seeds was omitted.The seeds were pre-sterilized with concentrated HPlants were grown in the 2 l pots filled with sand. When sterility was necessary, pots together with sand were heated in a dry-heat cabinet for 2 h at 200 °C. Mineral nutrition  was addeRhizobium leguminosarum bv. viciae were used:In experiments involving analysis of nodulation, two contrast strains of R. leguminosarum bv. viciae RCAM1026 (= CIAM1026), used in ARRIAM as a model strain (nodX gene (nodX− strain).Strain l strain . This stR. leguminosarum bv. viciae A1, first isolated in the Leningrad Oblast from nodules of the “Afghan” pea line (nodX gene (nodX+ strain).Strain pea line , thus pogusA-marked derivative of RCAM1026 (RCAM1026 gusA) with constitutive expression of gusA gene was used  and the resulting solution was added to the substrate while planting the seedlings, 100 ml per pot.The strains were cultivated on solid medium No. 79  in a theDNA was extracted from young leaves (top or second-from-top node). Extraction was conducted according to the previously described CTAB protocol .LykX, primers were used as described in MN187362 –MN187364, MN200353 –MN200358.To amplify the first exons of https://www.ebi.ac.uk/Tools/msa/clustalo/).Analysis of sequences was conducted by means of MEGA7 software . A Minim2 sample obtained from the cross between lines K-3821 and NGB2150 carrying different alleles of LykX, the CAPS (cleaved amplified polymorphic sequence) marker was designed using the dCAPS Finder 2.0 online service (st exon. The digestion of SNP (single nucleotide polymorphism) site was performed by the Hpy188III restriction enzyme .To analyze the F service . The prigusA culture. Four weeks after inoculation, 5 segments of roots 2–2.5 cm long were collected from each plant, leaving approximately two cm from the base of the root and two cm from the tips (if possible). Root segments were stained for 18 h in a solution of 50 mM Na-phosphate buffer (pH 7.0) containing 0.1% Triton, 5 mM K3Fe(CN6) , 5 mM K4Fe(CN6)  and 0.02 % 5-bromo-4-chloro-3-indolyl-bD-glucuronic acid (X-glc). For storage, stained segments were fixated with 4% paraformaldehyde in a TBS buffer  with the addition of 0.1% Tween-20 and 0.1% Triton X-100 under a vacuum  using a VacuuBrand ME 1C vacuum pump  and then dehydrated in graded ethanol series (from 10% to 70%). For observation, fixated samples were treated with the same ethanol series in reverted order and then with TBS buffer. Microscopic analysis was conducted using Zeiss Axiovert 35 inverted phase contrast microscope  by 100-fold magnification. The photos were taken on the Canon EOS 4000D camera .For detailed phenotype analysis, plants were grown in sand, as described above, while inoculated with suspension of RCAM1026 nodX+ or nodX− strains. Five lines were discovered which did not form nodules when inoculated with nodX− strain RCAM1026, but demonstrated normal nodulation with strain A1  as well) (nodX−) strain or A1 (nodX+) strain, but these were not included in subsequent analysis.To increase the amount of the available “Afghan” lines, a sample of 122 pea lines originating from various regions of the Middle East  was obtaas well) . From amSym2 gene), an allelism test was conducted. F1 seeds obtained from the cross of previously reported “Afghan” lines NGB2150, K-6883 and K-6047-2 with lines selected from VIR gene bank, along with seeds of parental lines, were planted in pots with sterile sand and inoculated with the nodX− rhizobia strain RCAM1026 . Additionally, two seeds of cv. Finale (characterized by the broad “European” symbiotic specificity and thus able to interact with the nodX− strain RCAM1026) were planted in each pot to confirm the success of the inoculation.In order to determine whether the symbiotic phenotype of selected pea accessions was caused by the same gene as in the previously known “Afghan” lines  was identified as a promising candidate for the elusive gene Sym2, as it demonstrated the unique allelic state found only in two pea lines with the “Afghan” phenotype which leads to substitution of three amino acids in its corresponding protein: Q44R, N45Y, and A76D, all in the first LysM module of the receptor part. Here we sequenced the first exon of LykX (corresponding to the receptor domain of the putative protein) in the newly selected “Afghan” lines from the VIR gene bank, several lines with “European” phenotype from our laboratory collection, cv. Iran characterized by the leaky temperature-dependent “Afghan” phenotype , while control plants of cv. Finale formed, on average, 65.3 ± 20  nodules per plant , which corresponds with the idea that their phenotype is determined by the same gene  nodules, while NGB2150 and K-3821 formed 0.2 ± 0.6 and 0.6 ± 1.3 nodules, respectively. Thus, we confirmed that “Afghan” and “Tajik” pea lines have an identical symbiotic phenotype, which is consistent with the alterations in the first exon sequences of LykX gene as compared to the “European” variant.According to previous descriptions , “Afghanof roots , 2C. Conof roots . AccordiLegume-rhizobial symbiosis relies on proper mutual recognition of partners, a process involving signal molecules and receptors that have been evolving step-by-step in a fashion similar to an “arms race”. Indeed, a plant needs to limit the set of bacteria penetrating its tissues as part of its defenses from pathogens and/or incompatible symbionts. On the other hand, bacteria may benefit when they broaden the range of possible hosts. Consequently, plants have evolved highly specific receptors that allow for discrimination of compatible and incompatible bacteria; in turn, rhizobia develop more and more variants of signal molecules  that maySym2A allele conferring “resistance” to nodulation with rhizobia strains producing the Nod factor without the required decoration. According to genotyping data   as well, but is somewhat masked by the native genetic background  . Using Sckground . Our finSym2 and LykX. Accordingly, it seems appropriate to name the newly discovered allele of LykX Sym2T (for “Tajik”). However, genetic transformation experiments are still necessary to conclusively confirm or reject this hypothesis. It would also be essential to study the interaction of “Tajik” lines with rhizobial strains producing fucosylated Nod factor due to the presence of the nodZ gene, as their range of specificity may differ from that of the “typical Afghan” lines.Thus, our data are in agreement with the hypothesis of the identity of Pisum sativum L.) with the narrow symbiotic specificity similar to that of cv. Afghanistan, and confirmed that their phenotype is prompted by the same genetic determinant Sym2. It is highly likely that the recently discovered gene LykX is in fact the elusive Sym2 gene. Indeed, we found that within our sample, LykX demonstrates two allelic states (“Tajik” and “Afghan”) different from those found in forms with normal symbiotic receptivity (“European”). Both allelic states lead to different amino acid substitutions in their corresponding proteins, as compared to the more common “European” state. In neither K1 nor Sym37 –the previous candidate genes for Sym2 – were observed such correlations between allelic states and the “Afghan” phenotype. The results of our work also highlight the importance of the strict specificity of symbiosis for the pea, since, according to our data, it appeared independently at least twice during the evolution of Pisum sativum species.In this work we identified a series of naturally-occurred forms of pea  sample is shown. Parental lines are marked as 3821 and 2150.Part of the the F Click here for additional data file.10.7717/peerj.8070/supp-2Table S1Assessment of nodule formation has been performed qualitatively: 0 = “–”; <10 = “–/+”; 10-30 = “+/–”; 40–60 = “+”; 70–90 = “++”; >100 = “+++”. For all lines, the number of plants per pot has been 5. *: In , the linClick here for additional data file.10.7717/peerj.8070/supp-3Table S2Click here for additional data file.10.7717/peerj.8070/supp-4Table S34 * 7H 2O, (2) K 2HPO 4, Ca 3(PO 4) 2, (3) NH 4NO 3, (4) NaFe-EDTA and (5) microelements, and then diluted to the required concentration. Stock solutions for (1), (2), (3), (4) are 100×. Stock solution for (5) is 1,000×. NH 4NO 3 is not to be added to the solution when analyzing the nodulation capability.Concentrations are given for 1×working solution. Stock solutions are prepared separately for (1) MgSO Click here for additional data file.10.7717/peerj.8070/supp-5Table S4pH = 7.0–7.2Click here for additional data file.10.7717/peerj.8070/supp-6Table S5C1,2, control plants of cultivar Finale (“European” phenotype); M, mean; MC, mean for control plants.Click here for additional data file.10.7717/peerj.8070/supp-7Table S6LykX . The “nn” columns indicate the number of nodules formed by nodX− strain RCAM1026. One seed of cv. Finale was planted in each pot with four F 2 plants to ensure successful nodulation; number of nodules formed by cv. Finale is listed in “cv.Finale” column. The alleles frequency corresponds to 1:2:1 for monogenic segregation (chi-square = 0.025 (P = 0.99)).The “allele” columns indicate the allelic state of Click here for additional data file.