P = 0.0303, OR = 3.45, 95% CI 1.05–11.35, chi-square test) and three HLA alleles  were identified in A(H7N9) infected volunteers. In an A549 cell line carrying the rs189256251 variant CT genotype, A(H7N9) infection incidence was elevated 6.665-fold over control cells carrying the CC genotype. Serum levels of interferon alpha were significantly lower in patients with the CT genotype compared to the CC genotype (P = 0.01). The study findings of genetic predisposition to A(H7N9) in the Chinese population may be valuable in systematic investigations of A(H7N9) disease etiology.The A(H7N9) virus strain that emerged in 2013 was associated with a high fatality rate and may become a long-term threat to public health. A(H7N9) disease incidence is disproportionate to viral exposure, suggesting that host genetic factors may significantly influence susceptibility to A(H7N9) infection. Human genome variation in conferring risk for A(H7N9) infection in Chinese populations was identified by a two-stage investigation involving 121 A(H7N9) patients and 187 healthy controls using next generation sequencing followed by functional analysis. As a result, a low frequency variant (rs189256251;  Multiple regionally distinct viral genotypes and expanded geographical range suggest that A(H7N9) virus may become a long-term threat to public health2.Since the first reported human infection by the novel avian influenza A virus H7N9 [A(H7N9)] in 2013 more than 1,564 laboratory-confirmed human cases were reported up to 27 May 2018, with a fatality rate of 39.25%. Five large epidemic waves of human infection have been reported3, hepatitis B virus4, hepatitis C virus5 and respiratory syncytial virus6. It is clear that the genetic make-up of the host has a major influence on the response to these pathogens7. In 2011 the World Health Organization (WHO) highlighted the importance of host genetic predisposition to infection with influenza virus8 and several host genetic variants have been reported to contribute to disease severity and the immune response following influenza virus infection10.The role of host genetic background in determining susceptibility to viral diseases has been studied intensively for several pathogens including human immunodeficiency virus14. Other investigations attempted to identify differential gene expression in case-controlled studies17. For studies involving small numbers of A(H7N9) patients and a possibility that a rare variant might have a moderate to large effect on susceptibility, a next generation sequencing (NGS) strategy might be superior to a genome wide association study (GWAS). Importantly, a stringent GWAS significance threshold and a modest genetic effect size might mask real associations. Therefore, comprehensive analysis using a high-throughput method is required to define additional genetic causes and risk variants for A(H7N9) infection in a relatively large cohort.Because A(H7N9) disease is contracted at rates disproportionate with virus load under circumstances of exposure, it has been suggested that host genetic effects have a major influence on susceptibility to A(H7N9) infection. Studies have investigated single nucleotide polymorphisms (SNPs) as risk factors for predisposition to infection with A(H7N9) virus in influenza patientsHere, we describe a two-stage study involving NGS of Chinese volunteers including 112 A(H7N9) patients and 167 healthy controls followed by functional validation of the effects of genetic variants. We also looked at which human leukocyte antigen (HLA) alleles closely associated with A(H7N9) infection, using HLA target sequencing in a cohort that included 117 A(H7N9) patients and 131 healthy controls. Altogether, our findings may aid systematic understanding of the role of host genetics in A(H7N9) infection.We conducted a two-stage study and the design is shown in Fig. P < 1 × 10–4) were defined as candidate SNPs for follow-up study (see Supplementary Table Genomic DNA was collected from 17 A(H7N9) patients. An average of ~ 110.5 million purity-filtered reads were generated for each of the 17 samples. 93% of the target bases in each individual were covered by at least 10 independent sequence reads, with an average sequence depth of 76.2× in each sample . Significant association of missense mutation rs189256251 in the UBX Domain Protein 11 (UBXN11) gene was still evident following logistic regression analysis  but none of the 6 known SNPs showed an association with A(H7N9) infection at this stage of analysis.The 140 candidate SNPs described above plus 6 previously reported SNPs . All patients or controls with the rs189256251 (C>T) mutation were detected again by Sanger sequencing and all results showed the mutation occurring in both alleles.Further validation of SNP rs189256251 in 112 A(H7N9) patients and 167 healthy controls continued to indicate significant association  were previously reported to be associated with influenza virus infection through modulation of related signaling pathways19. The Genecard database shows UBXN11 encoding a member of the ubiquitin binding factor X (UBX) family and having a divergent C-terminal UBX domain. The rs189256251 (a missense mutation NP_892120.2:p.Arg400His) SNP introduces a striking change in the 3-D structure of the C-terminal active domain of UBXN11  showed that UBXN11 with CT genotype and empty lentivirus vectors, respectively. The transcription level of UBXN11 (CT) in OE cells was 5.565 fold increased compared to OE-NC cells. As shown in Fig. The A549 OE and OE-NC cell lines harbor P = 0.01) and increased levels of interferon gamma  and IL-28B  were found in patients with the CT genotype compared to those of genotype CC  patients and controls: HLA-DQB1*06:01 , HLA-DQA1*05:05  and HLA-C*12:02 . These three HLA alleles also showed significant differences compared with 10,689 previously published control subjects with effects in the same direction  using a GWAS approach22. However, given the small number of A(H7N9) cases involved in the study, GWAS likely not the optimal approach21. A WES approach yielded 21 genes related to A(H7N9) infection13, but here again the sample size was relatively small.Multiple studies have demonstrated that host susceptibility to influenza virus is determined by host genetics23. UBXN11 therefore may modulate host susceptibility to the A(H7N9) virus through down regulation of innate immunity. Indeed, a previous study reported that UBXN1, another member of the UBX-domain containing family, strongly inhibited the RNA virus-induced type I interferon response20.In this study, we performed a two-stage study of host genetic predisposition using next generation sequencing based techniques to analyze a Chinese population that included 121 laboratory-confirmed A(H7N9) patients. We identified one low frequency SNP and three HLA alleles showing significant association with A(H7N9) infection. For all 112 patients, the allele frequency of the T allele of SNP rs18925625 was 4.02% (9/224), significantly higher than 0.5% (1/199) in the Southern Han Chinese population in the 1,000 Genomes phase 1 release, and significantly higher than 0.77%  in the East Asian population in the ExAC database. This was followed by functional verification of the SNP in an in vitro cell infection model. These studies showed that overexpression of UBXN11 (CT) rendered cells significantly more susceptible to A(H7N9) virus infection. The cells were also more susceptible to infection by A(H9N2), A(H5N6) and pandemic H1N1 2009 viruses. We also found reduced serum levels of interferon alpha in patients carrying the CT genotype compared to CC genotype patients. It is well known that interferon alpha is linked to innate immunity, which is critical for eliminating virus soon after infection24. Other studies have suggested that HLA-DR levels in CD14+ cells may be a biomarker predicting H7N9 disease progression25 and reported divergent differentiation pathways of CD38+ HLA-DR+ CD8+ T cells during fatal H7N9 disease26. These results support the argument that the HLA alleles identified in the current study may be useful markers for assessing risk of A(H7N9) infection.The HLA locus is involved in regulation of viral immunity. A previous study reported preferential binding of HLA alleles to conserved regions of viral proteomes and suggested that this preference may provide improved clearance of infection in different viral infectionsThere were also some limitations of this study. First, compared with the sequencing analysis of other diseases, our sample size is not large. But considering the overall number of A(H7N9) disease our sample is considered sufficient. Cytokines were measured in serum from only five patients with the CT genotype and 21 patients with the CC genotype. Future studies should explore in larger study populations that have a bigger sample size of cases. In addition, HLA gene alleles are highly polymorphic, and some alleles have low frequencies. Testing on a small sample size will cause some errors, which also needs to be verified on a larger sample size.In summary, we identified several genetic variants associated with A(H7N9) infection. The two-stage study design improved confidence in the results from a relatively small cohort, beneficial when the disease frequency is low. All of the identified variants are linked to antiviral immunity, highlighting the importance of innate immunity in genetic predisposition to A(H7N9) infection. Fine mapping and functional studies of the identified loci may provide further insights into the etiology of A(H7N9) disease.All subjects were recruited and anonymized by staff of the Shanghai Municipal Center for Disease Control and Prevention (SCDC) or the Chinese National Influenza Center (CNIC) in the course of an epidemiological survey. A total of 121 A(H7N9) patients and 187 healthy controls were recruited. A(H7N9) infection was in each case confirmed by real-time reverse-transcription polymerase chain reaction and/or virus culture. Heavily exposed poultry workers or close contacts were recruited as healthy controls. Venous blood samples and nasal swabs were collected from subjects. Genomic DNA was extracted from venous blood using a Qiagen Blood Kit  according to the manufacturer’s instructions.All procedures performed in studies involving human participants were in accordance with the ethical standards of Bio-X Institutes of Shanghai Jiao Tong University and National Institute for Viral Disease Control and Prevention  and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.27.17 A(H7N9) patients’ DNA exomes were ‘captured’ using Illumina TruSeq Exome enrichment technology . Libraries were indexed, pooled and sequenced on an Illumina HiSeq2000 platform . Raw sequencing reads were aligned to the reference genome hg19 using the Burrows-Wheeler Aligner . Duplicate reads and reads mapping to more than one location were excluded. The Genome Analysis Toolkit  was used for SNP calling. All SNPs were filtered using the GATK variant filtration module with a hard filter setting for initial filtering. Variants were annotated as a stop gain, stop loss, synonymous, nonsynonymous or splicing mutation using ANNOVAR28. Samples that failed to reach a genotype call rate of 95% and those with sex discrepancies were excluded. SNPs were excluded based on (i) not mapping on an autosomal chromosome, (ii) displaying a low call rate (< 90%) in all subjects and (iii) violating Hardy–Weinberg equilibrium (HWE) (P ≤ 0.00001) in the controls. We used two methods to select SNP sites for subsequent verification. One method was to identify novel, potentially harmful mutations that are not reported in the 1,000 Genomes database (novel SNPs) but were detected in at least 80% of patients. The other method was to compare allele frequencies between cases and controls and generate a P-value using the Pearson chi-squared test. Due to the relatively small sample size in the WES stage we set P < 1 × 10–4 as the significance threshold in order to select more SNPs. We then focused on nonsynonymous and LOF  mutations in the verification stage.A uniform quality control protocol was used to filter the samples and SNPs32 were evaluated. For quality control of genotyping, blinded duplicate samples from two subjects and two negative control (water) samples were included in each method. Samples that failed to reach a call rate of 90% and SNPs displaying a call rate below 95% or HWE P ≤ 0.00001 were excluded. Logistic regression was performed to subtract effects of age and sex on results. Lastly, the SNP with the most significant association with A(H7N9) disease was confirmed in a cohort including 112 A(H7N9) patients and 167 healthy controls. At this stage, our samples are completely covered the previous stage.In order to validate discoveries, candidate SNPs were detected by Agena iPLEX MassARRAY assay, multiplex SNaPshot genotyping or Sanger sequencing to achieve highest confidence results in a verification stage involving 24 A(H7N9) patients (including 17 of the same patients studied in the discovery stage and 7 new patients) and 103 healthy controls. Moreover, 6 known SNPs associated with influenza infection based on previous studiesUBXN11 gene and other genes were evaluated using commercial IPA software  based on pathways previously defined in the literature. The gene was characterized based on Genecard database (https://www.genecards.org/) and PubMed search results. Because UBXN11 encodes a 520 amino acid protein with a divergent C-terminal UBX domain we modeled the 3-D structure of the C-terminal active domain of UBXN11 with and without the rs189256251-T mutation using Swiss-Model online software (https://www.swissmodel.expasy.org/)33. Figures of the 3-D structure were generated by Swiss-PdbViewer software .Interactions between the UBXN11 in the OE and OE-NC cell lines were measured by real time PCR in triplicate assays and values calculated relative to a GAPDH internal control. Both OE and OE-NC cell lines also expressed EGFP.Adenocarcinoma derived human alveolar basal epithelial (A549) cells were used in functional validation assays of the CT genotype of rs189256251. A549 cells were purchased from the cell bank of the Chinese Academy of Science. Before assay, the genotype of rs189256251 in the original A549 cell were sequenced by Sanger sequencing and the result showed rs189256251 was the CC genotype. The stable A549 overexpression cell line (A549 OE) and negative control (OE-NC) were constructed using lentivirus vectors with or without the target CT genotype of rs189256251 (Shanghai Genechem Co. Ltd). The transcription levels of 50) for each virus type was determined using Madin-Darby canine kidney (MDCK) cells. A549, OE and OE-NC cells were inoculated with virus at a multiplicity of infection (M.O.I) of 1. The final concentration of TPCK-treated trypsin  used during infection was 0.5 g/ml. Cells were harvested 12 h post infection using 0.25% EDTA-trypsin. Cells were washed with PBS, fixed and permeabilized using Cytofix/Cytoperm solution . The mouse monoclonal antibody FR-1217 (WHO) against influenza A virus matrix protein was used to detect intracellular virus, followed by APC labeled goat anti-mouse IgG  secondary antibody. Infected cells were detected by flow cytometry . Infection assays for A(H7N9) and A(H5N6) viruses were performed three times in parallel, while those for A(H9N2) and pandemic H1N1 2009 viruses were performed twice. A549 cell line without influenza virus infection was included in each infection assay to establish baseline fluorescence levels in flow cytometry. The fold-increase in infection was calculated using the OE to OE-NC cell mean ratio of percent infection.Four types of influenza A viruses were included in assays: WHO recommended A(H7N9) avian influenza virus vaccine strain (NIBRG267), low pathogenicity A(H5N6) avian influenza virus (GDH5N6RETR), low pathogenicity A(H9N2) avian influenza virus (A/HK/2009(H9N2)) and pandemic H1N1 2009 influenza virus (A/Shanghai HP/SWL13439/2016(H1)). The tissue culture infective dose 50 . Data analysis was performed according to kit manufacturer’s instructions.For serum cytokine detection, sample acceptance criteria were first serum sample collected from A(H7N9) patient and interval between disease onset and sample collection of less than 12 days. Serum levels of IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12P70, IL-13, IL-17A, IL-21, IL-23, MIP-1a, MIP-1β, MCP-1, MIG, IP-10, RANTES, and IFN-γ were evaluated using the cytokine bead array (CBA) and the Human Th1/Th2 Cytokine CBA kit  in a flow cytometer  as previously describedHLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1 and HLA-DRB1) were chosen for targeted deep sequencing in a cohort that included 117 A(H7N9) patients and 131 healthy controls. HLA sequences were amplified by multiplex PCR and sequenced in PE 250 sequencing mode on the Illumina MiSeq sequencer according to manufacturer’s instructions. Low quality reads and those contaminated with adaptor sequences were filtered out to yield clean reads. HLA allele typing was performed using Omixon Target software (version 1.8.1). The HLA genotyping data from 117 A(H7N9) patients were also compared to previously published data from 10,689 Han Chinese control subjects35.Six classical HLA loci . Fisher's exact test was used to compare HLA frequency between infected and healthy controls. P < 0.05 was considered statistically significant.Plink software (version 1.9) was used to evaluate association between each variant and A(H7N9) infection risk. Male Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.Supplementary Table S6.Supplementary Figure S1.


The data in this article includes biotechnological joint patents as a proxy of technological alliances. Joint patents are not directly found in public or commercial databases. Each joint patent has their corresponding International Patent Classification codes, their forward citation measure as an indicator of innovation value, and the firms involved in the process. The data was collected during a time frame that ranges from 2006 to 2010. Data from the joint biotechnological patents was collected at first during the time window, and then filtered, cleaned, and sampled accordingly to obtain 340 joint patents between firms  in the industry. Then each of the joint patents was processed to find the forward citations they have. Data on joint patents of biotechnology industry can be reused in future studies related to technological alliances and patenting mechanisms and process. Specifications Table •The dataset provides information about joint patents which are not directly found in databases, specifically in the biotechnology sector. The data set can be used as a reference to the improve understanding about technological alliances or R&D collaboration and how partner technological attributes influence the value of the joint innovations.•Patent offices or patent organizations, firms from the biotechnology sector that have the will to develop potential strategic alliances, an managers and researchers will benefit from this data related to joint patents as a measure of firms collaborating in technological alliances.•Data can be used as a reference or baseline to develop comparative studies. Comparative studies should include analysis in terms of the value of the joint patent by means other than forward citations ; also, can be used as a reference to other databases different from the USPTO, such as the European Patent Office, or the Japan Patent Office to find differences and similitudes on the mechanisms used on those regions.1The dataset sample is composed of joint patents in the biotechnology industry. Patents in biotechnology industry are an indication of innovative success and the generation of new knowledge , 2. The Each joint patent or co-patent shown in the dataset is defined as the patent owned by two or more firms In general, there is a distinction between the private value and the social value of inventions or patents The dataset contains a sample of 340 joint patents  in the biotechnology industry with a total and average forward citation of 570 and 1.67 respectively, in a five-year window; the maximal forward citation made to a joint patent is 28 and the minimal forward citation for each year is cero. The Appendix A shows the complete dataset that includes the year of application, the application number, the 5-year forward citation, the International Patent Classification codes for the biotechnology industry, and the pair of firms that are assignees of each one of the joint patents. Appendix B shows the complete raw data from which the dataset was sampled.2The dataset is obtained from the joint patents in the biotechnological industry. The time frame used ranges from the years 2006 to 2010. Data were obtained from joint technological patents according to the International Patent Classification The data was first filtered by finding the joint patent applications found in the United States Patent and Trade Organization – USPTO- database. The USPTO has information on patent applications and all classes of patents such as utility, design, reissue, plant patents, and includes bibliographic data, full description of the invention and the claims. The USPTO was chosen because the United States is the country with the higher share in biotechnology patents filed under the Patent Cooperation Treaty -PCT_ with a 40.94% ((ic:(A01H1) OR ic:(A01H4) OR ic:(A61K38) OR ic:(A61K39) OR ic:(A61K48) OR ic:(C02F3/34) ORic:(C07G11) OR ic:(C07G13) OR ic:(C07G15) OR ic:(C07K4) OR ic:(C07K14) OR ic:(C07K16) ORic:(C07K17) OR ic:(C07K19) OR ic:(C12M*) OR ic:(C12N*) OR ic:(C12P*) OR ic:(C12Q*) OR ic:(C12S*)OR ic:(G01N27/327) OR ic:(G01N33/53) OR ic:(G01N33/531) OR ic:(G01N33/532) OR ic:(G01N33/533)OR ic:(G01N33/534) OR ic:(G01N33/535) OR ic:(G01N33/536) OR ic:(G01N33/537) OR ic:(G01N33/538)OR ic:(G01N33/539) OR ic:(G01N33/54) OR ic:(G01N33/541) OR ic:(G01N33/542) OR ic:(G01N33/543)OR ic:(G01N33/544) OR ic:(G01N33/545) OR ic:(G01N33/546) OR ic:(G01N33/547) OR ic:(G01N33/548)OR ic:(G01N33/549) OR ic:(G01N33/55) OR ic:(G01N33/551) OR ic:(G01N33/552) OR ic:(G01N33/553)OR ic:(G01N33/554) OR ic:(G01N33/555) OR ic:(G01N33/556) OR ic:(G01N33/557) OR ic:(G01N33/558)OR ic:(G01N33/559) OR ic:(G01N33/57) OR ic:(G01N33/571) OR ic:(G01N33/572) OR ic:(G01N33/573)OR ic:(G01N33/574) OR ic:(G01N33/575) OR ic:(G01N33/576) OR ic:(G01N33/577) OR ic:(G01N33/578)OR ic:(G01N33/579) OR ic:(G01N33/68) OR ic:(G01N33/74) OR ic:(G01N33/76) OR ic:(G01N33/78) ORic:(G01N33/88) OR ic:(G01N33/92))There is not direct way to obtain biotechnology joint patents from patent databases. To do so, the first step in this process was to obtain all the biotechnology patents no matter how many owners were assigned to them. This activity was made using the standalone software Matheo Patent XE® by means of a search equation based on the IPC codes assigned to the field. Matheo Patent XE® is a tool that search, analyses and make survey of patents. The search equation used in the analysis was the following:not APP/univ* and not APP/empty and not APP/colle* and not APP/inst* and not APP/center and not APP/hospital*In order to filter actors in the patents different from firms, the “inventor” filter was used, followed by the filter equation:The results from the software offered data that included joint and single owner patents. Therefore, the second step consisted on extracting only the joint biotechnological patents from this initial data. To do so, was necessary to filter the patents that had more than one applicant in the applicant field, this was done by the authors using a spreadsheet of Microsoft Excel®. The total number of joint patents in the biotechnological field was 1931 (Appendix B). This set of joint patents is the universe of the research. A simple random sampling method was used to select a subset to estimate characteristics of the whole population. The resulting sample size was 465 joint patents.The 465 joint patents were cleaned with high detail in order to overcome problems like incomplete or confused information or when they belonged to organizations or actors different from firms. The resulting sample of joint patents after cleaning was 340 patents which is the dataset used (Appendix A). In order to obtain a 5% of margin error, 95% of confidence level and a response distribution of 50%, the sample of joint patents would have been of 320. Once the 340 biotechnological joint patents were obtained, was necessary to find the forward citation to each one of them; in other words, the number of citations received by each joint patent application in the next five years from the application date. Consequently, the forward citations were collected from the years 2006 to 2014.The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.


Steroid 5α-reductase type I (SRD5A1) is a validated oncogene in many sex hormone-related cancers, but its role in multiple myeloma (MM) remains unknown. Based on gene expression profiling (GEP) of sequential MM samples during the disease course, we found that the aberrant expression of SRD5A1 was correlated with progression and poor prognosis in MM patients. In this study, the oncogenic roles of SRD5A1 were validated in human MM cell lines (ARP1 and H929) and the xenograft MM model as well as the 5TMM mouse model. MTT and flow cytometry were used to assess MM cell proliferation, cell cycle, and apoptosis post inducible knockdown SRD5A1 by lentivirus-mediated short-hairpin RNA (shRNA). Transcriptomic sequencing, immunofluorescence, and western blot were used to investigate the effects of SRD5A1 suppression on cell apoptosis and autophagy. Mechanistically, SRD5A1 downregulation simultaneously regulated both the Bcl-2 family protein-mediated apoptosis and the autophagic process via PI3K/Akt/mTOR signaling pathway in MM cells. Meanwhile, the autophagy inhibitor (3-methyladenine) and SRD5A1 inhibitor (Dutasteride) were utilized to evaluate their anti-myeloma effect. Thus, our results demonstrated that SRD5A1 downregulation simultaneously regulated both the apoptosis and the autophagic process in MM cells. The dual autophagy–apoptosis regulatory SRD5A1 may serve as a biomarker and potential target for MM progression and prognosis. It is estimated that the number of new cases is over 30,000 in 2019 in the United States2. The therapies for MM have undergone great progress over the past years, including allogeneic hematopoietic stem cell transplantation (ASCT) and novel chemotherapies, such as proteasome inhibitors and immunomodulatory drugs3. However, MM is still incurable for the majority of patients who become refractory to treatment and ultimately relapse, thus further development of new therapeutic agents is warranted, such as specific inhibitors targeting activated oncogenes.Multiple myeloma (MM) is the second most common hematologic malignancy worldwide. According to statistics collected in China, the incidence of MM in 2016 was 1.60 per 100,000 person-years, with 1.84 per 100,000 person-years for males and 1.30 for females, respectively6. SRD5A1 was mainly expressed in the skin, scalp, liver, and brain tissues, while SRD5A2 was predominantly found in androgen target organs such as the prostate and genital skin, but only SRD5A1 was upregulated in prostate cancers8. However, there is no report on the oncogenic role of SRD5A1 in MM progression, considering the unequal incidence rates between females and males of MM patients.SRD5A1, a member of the steroid 5α-reductase family  converting testosterone to dihydrotestosterone (DHT), was recently reported to be aberrantly expressed in several sex hormone-related cancers, such as breast cancer, endometrial cancer, and prostate cancerThis study aimed to investigate the potential involvement of SRD5A1 during MM pathogenesis, and the evidence from in vivo and in vitro data demonstrated that SRD5A1-mediated MM cell autophagy via PI3K/Akt/mTOR signaling pathway and induced MM cell apoptosis through Bcl-2 proteins family in MM. Furthermore, we validated that Dutasteride, an SRD5A1 inhibitor, induced myeloma cells apoptosis in human myeloma cells and xenograft mouse models. Thus, SRD5A1 might be a considerable therapeutic target in the development of MM therapy.2. HEK-293T and 5TMM3VT, which were donated by Dr. Wen Zhou , were cultured in DMEM medium  containing 10% FBS and 1% P/S solution in 5% CO2 at 37 °C.MM cell lines ARP1, OCI-MY5, and NCI-H929, which were kind gifts from Dr. Siegfried Janz , were cultured in RPMI 1640 medium  supplemented with 10% fetal bovine serum (FBS)  and 1% penicillin/streptomycin (P/S) solution  under the condition of 37 °C in a humidified atmosphere of 5% COCaspase-3 , Cleaved caspase-3 , PARP , Bcl-xl , Bcl-2 , Bad , Bax , ATG-5 , ATG-7 , LC3A/B , Akt , p-Akt (Thr308) , p-mTOR , p-p70S6K (Thr389)  and β-actin  antibodies were obtained from Cell Signaling Technology . SRD5A1  and p70S6K  were purchased from Proteintech . The p-PI3K (Tyr607)  and mTOR  antibody were purchased from Affinity . SQSTM1/p62  antibody was obtained from Sigma-Aldrich  and goat Anti-rabbit IgG/Alexa Fluor 647 antibody  was purchased from Bioss . LY2940002 (#9901) were obtained from Cell Signaling Technology. Dutasteride (#A1659), hydroxychloroquine (HCQ) (#B4874) and 3-methyladenine (3-MA) (#A8353) were purchased from APExBIO . Doxorubicin (#D1515) was purchased from Sigma-Aldrich.Briefly, whole proteins were extracted with RIPA Buffer  with protease inhibitor cocktail . The extracts were separated by SDS-PAGE and then transferred to 0.45-μm immobilon-P transfer membrane . Membranes were blocked with 5% skim milk for 1 h at room temperature followed by incubation with a primary antibody at 4 °C overnight. Then the blots were detected with HRP conjugated secondary antibody and visualized with the Super ECL Detection Reagent ECL .The shRNA sequence against SRD5A1, that is CTCGAGTGCTGTTGACAGTGAGCGACCTGTACCTGTTATCAATATATAGTGAAGCCACAGATGTATATATTGATAACAGGTACAGGCTGCCTACTGCCTCGGAGAATTC, was cloned into TRIPZ vector , which provides inducible shRNA expression in the presence of doxycycline (Dox). Recombinant lentivirus was produced using transient 293T cell transfection. Transfected efficiency was verified by western blotting.6 cells were fixed with 5 mL of cold ethanol at −20 °C overnight. After washed twice with cold PBS, the cells were suspended with 200 μl of PBS, and supplemented with 10 μl of RNase A stock  solution and incubated 60 min at room temperature. After incubation, cells were stained with propidium iodide  solution (40 μg/mL in PBS) for 15 min at room temperature and the cell cycle was analyzed using Flowsight flow cytometer . For the cell apoptosis experiment, the ARP1-SRD5A1-KD and H929-SRD5A1-KD cells post 2 μg/mL treatment for 48 h at a density of 2 × 105 cells were collected and stained using Annexin-V-Allophycocyanin (Annexin-V-APC)  and PI for 15 min in dark conditions, and the apoptosis of the cells was detected using flow cytometer.In total, 1 × 10Cells were enumerated by Trypan blue staining using a hemocytometer , then were seeded into 96-well plates at the density of 3000–4000 cells/well. After treatments, cells were incubated with MTT for 4 h, then the supernatant was removed, and the formazan crystals were dissolved in 200 μL dimethyl sulfoxide (DMSO), the optical density was measured at 570 nm.Cells were pelleted, and RNA samples were isolated and sent to the MicroAnaly  for constructing RNA-seq library. Briefly, total RNAs were isolated, and mRNA was enriched and then were pooled together for cDNA synthesis and sequencing. The transcriptomic RNA sequencing was performed on an Illumina NovaSeq 6000 platform, to create paired-end reads with a length of 150 bp (PE150). The differentially expressed genes (DEGs) were identified using edgeR (|logFC | >1 & FDR < 0.05), and these DEGs were undergone Gene ontology and KEGG pathway analysis. The original raw data and detailed processed data were submitted into Gene Expression Omnibus (GSE155858).Cells were harvested by scraping them from the plates. They were then washed twice with PBS and fixed with 2% paraformaldehyde/2% glutaraldehyde in 0.2 M sodium cacodylate buffer (pH 7.4). Cell pellets were postfixed with 1% (v/v) osmic acid in sodium cacodylate buffer and were then stained with 1% uranyl acetate. Following dehydration, pellets were embedded in Durcopan . Ultrathin sections were prepared using an ULTRACUT S ultramicrotome and were observed with a JEM 1010 transmission electron microscope.Cells were collected by cytospin on glass slides and fixed with 4% paraformaldehyde for 15 min. After washing in 10% PBS, the slides were permeabilized with 0.2% Triton X-100 in PBS and then were blocked with 4% bovine serum albumin  for 1 h at room temperature. After incubated with LC3A/B antibody  overnight at 4 °C, the slides were washed with PBS and then incubated with Alexa Fluor 647s antibody . The cells were stained with nuclear dye DAPI . All the images were captured with the fluorescence microscope, and representative images were shown.6) of OCI-MY5 and OCI-MY5-SRD5A1-OE were injected subcutaneously into the right and left flank of 6–8 weeks’ male/female NOD. Cg-Rag1 (NSG) mice  (n = 8), respectively. The tumor volume was measured with a caliper every 3 days to evaluate the tumor growth rate. Once tumors reached 15 mm in diameter, mice were sacrificed by CO2 asphyxiation.MM cells (1 × 106) were injected intravenously into the abdomen of 6-week-old male/female C57BL/KaLwrij mice  (n = 14). After 3 days, SRD5A1 inhibitor Dutasteride treatment used on seven mice and intraperitoneally injected at the dose of 25 mg/kg three times a week until all the mice were dead. The time of death caused by paralysis in the control group and the Dutasteride group was recorded in turn. All animal work was performed in accordance with the Guide for the Care and Use of Laboratory Animals  and approved by the Animal Ethical and Experimental Committee of Nanjing University of Chinese Medicine (ACU-15 & ACU170501).The 5TMM3VT murine myeloma cells  test. P < 0.05 was considered as significant.All data were shown as means ± SEM and performed using the GraphPad Prism program. Multiple groups were analyzed by one-way ANOVA, and paired groups were analyzed by Student’s 9. The Kaplan–Meier analysis demonstrated that high SRD5A1 level was associated with poor prognosis for multiple cancer patients, such as glioblastoma multiforme, acute myeloid leukemia, mesothelioma, pancreatic adenocarcinoma, etc.  using GEPIA online tool with customizable functional analysis, such as tumor/normal differential gene profiling and patient survival analysistc. Fig. , and SRDtc. Fig. . Moreove10. Taken together, we proposed that SRD5A1 might function as an oncogene in MM.Furthermore, high SRD5A1 expression was linked to shorter response duration of both event-free survival (EFS) and overall survival (OS) Fig. . As showTo determine whether SRD5A1 functions as an oncogene in MM, we functionally knocked down SRD5A1 in myeloma cells by expressing the lentivirus-mediated SRD5A1-shRNA which was under the control of a doxycycline (Dox)-inducible gene promoter thus avoiding the adverse effect of long-term knockdown. Western blotting verified a remarkable downregulation of SRD5A1 expression in both ARP1 and H929 human MM cells after Dox treatment compared with nontreated cells Fig. . Both ARTo elucidate the diminished cell viability of SRD5A1-KD cells, cells were stained with PI to detect cell cycle by flow cytometry. As shown in Fig. To further evaluate the impact of SRD5A1 on cell growth in vivo, we overexpressed SRD5A1 by lentivirus-mediated SRD5A1-cDNA transfection in the MM cell lines ARP1 and OCI-MY5. After assessing overexpression efficiency Fig. , we injehttp://www.autophagy.lu/index.html) with these above DEGs, we noticed that 21 (4 downregulated and 17 upregulated) could also be directly annotated as autophagy genes, indicating that SRD5A1 knockdown may be related to autophagic progress  to screen differentially expressed genes (DEGs) following the SRD5A1 knockdown. As shown in Fig. ess Fig. . Supportess Fig. . Thus, wTo verify these findings, scanning electron microscopy was firstly utilized to evaluate autophagosomes and autophagolysosomes, finding that the number of them was only slightly increased in SRD5A1-KD myeloma cells compared to control Fig. . Next, wThe aforementioned KEGG pathway analysis suggested that SRD5A1 knockdown influenced the PI3K/Akt and mTOR signaling pathways. To test whether SRD5A1-KD induced autophagy via the PI3K/Akt/mTOR pathway, we first detected marker proteins in potential autophagy-related pathways, such as Ras and PTEN, but there was no apparent variation Fig. . However11. To test this, we first compared the impact of three different autophagy inhibitors, LY294002, hydroxychloroquine (HCQ), and 3-methyladenine (3-MA) on MM cell viability in a dosage range of 0.1–105 nM. Results showed that 3-MA presented less inhibitory effect on cell viability compared to HCQ and LY294002  once the 5TMM3VT syngeneic MM-prone-model was established. Time-course analysis of tumor growth revealed that control MM mice rapidly deteriorated from day 22 until all mice were dead by day 32. However, Dutasteride-treated MM-prone mice exhibited prolonged survival rates up to 50 days  was discovered as an arbitrator in apoptosis14. The Bcl-2 family controls apoptosis-mediated mitochondrial outer membrane permeabilization (MOMP) and includes the anti-apoptotic proteins , pro-apoptotic effectors (Bak and Bax), and pro-apoptotic BH3-only proteins 16. The executor of apoptosis caspase activation results in MOMP, thereby releases apoptotic components, such as cytochrome c, Smac, and Omi. Nowadays targeting apoptosis has been increasingly recognized as a promising approach to kill cancer cells17. Our results detecting changed Bcl-2 family proteins in Figs. 19.Differing from necrosis, apoptosis is a highly programmed cell death process and is typically dysregulated in human cancers21). Recent reports indicate that autophagy plays a dichotomous role in tumorigenesis: extravagant autophagy triggers cancer cells to “autophagic cell death” (ACD) through excessive self-digestion and degradation of essential cellular constituents22, while more often, under normal physiological conditions, autophagy functions as a patron to counteract with cancer by eliminating damaged organelles and recycling degradation products23. Autophagy is observed at a higher frequency in cancer cells than in normal cells, and some cancers even count on autophagy for survival under external stresses such as starvation, hypoxia, growth factor withdrawal, chemotherapy, or radiotherapy25. In this study, SRD5A1 knockdown-induced autophagy existed merely in the beginning phase after treatment of Dox (before 24 h) and vanished at 48 h according to our observation , autophagy-related proteins (ATGs), caspases27. Targeting apoptosis has been the overwhelming focus of methods aimed at killing cancer cells, and experimental evidence shows that autophagy participates in resistance to chemotherapy-induced cell death28. In MM cells, the abnormal autophagy could regulate proliferation and apoptosis, which advances the progress of MM30. In this study, SRD5A1 suppression simultaneously induced apoptosis through Bcl-2 family proteins as well as autophagy via PI3K/Akt/mTOR signaling, meanwhile, the autophagy inhibition using 3-MA potentiated MM cell apoptosis. Consistent with our findings, one recent study report that silencing of the stress-related nuclear protein 1 (NUPR1) could suppress autophagy activities and induces autophagy-mediated apoptosis in two MM cell lines (U266 and RPMI 8226) through the PI3K/AKT/mTOR pathway31. In fact, the autophagy inhibitor drug chloroquine could also potentiate carfilzomib-induced apoptosis in myeloma cells in vitro and in vivo32. Therefore, the above findings support the therapeutic utilization of trials targeting both autophagy and autophagy-mediated apoptosis to improve anti-MM therapy33.However, the cross-talk between apoptosis and autophagy is complex and still vague, as synergistic, antagonistic, and interdependent effects have been observed35. Elevated levels of SRD5A1 have been reported to be correlated to the severity of multiple cancers with their nidus situated to the parts rich in sex hormone, including prostate cancer, breast cancer, endometrial cancer, or the like, and to facilitate cell proliferation32. Nonetheless, neither testosterone nor DHT has an impact on myeloma cell proliferation in this study (data not shown), but we did find that varying levels of SRD5A1 could alter the growth of myeloma cells. It may be mainly due to the oncogenic role of SRD5A1 in these tumor cells including MM and other prostate cancers . In fact, it is evidenced that tumor development is relevant to the metabolism of steroids within the local tumor and its adjacent host tissue which might create a microenvironment to promote the cancer37. Besides, the effects of testosterone can also be exerted through aromatization to estrogens, which could exert their carcinogenic effects through binding with estrogen receptors38. There are two 5α-reductase inhibitors tested clinically with Finasteride specifically inhibiting SRD5A2 and Dutasteride targeting both SRD5A1 and SRD5A240. We also presented the therapeutic effect of SRD5A1 inhibitor Dutasteride on MM , which was significantly overexpressed in newly diagnosed MM patients with a short survivalA3 ref. 3. In factTaken together, we discovered the previously unclear role of SRD5A1 in MM. SRD5A1 simultaneously regulates both apoptosis mediated by Bcl-2 proteins family and autophagic process via PI3K/Akt/mTOR signaling Fig. . On the Supplementary information


GDPD genotypes in infants with G6PDd detected by newborn screening and later studied in a single follow-up center. G6PDd newborns were categorized into three groups: group 1: hospitalized with or without neonatal jaundice (NNJ); group 2: non-hospitalized with NNJ; and group 3: asymptomatic. Frequencies of homozygous UGT1A1*28 (rs34983651) genotypes among G6PDd patients with or without NNJ were also explored.Glucose-6-phosphate dehydrogenase deficiency (G6PDd) newborn screening is still a matter of debate due to its highly heterogeneous birth prevalence and clinical expression, as well as, the lack of enough knowledge on its natural history. Herein, we describe the early natural clinical course and the underlying −202A/376G genotype was the most frequent (60.5%), followed by the G6PD A−376G/968C (22.2%) and the Union-Maewo  genotypes. These genotypes produce a wide range of clinical and biochemical phenotypes with significant overlapping residual enzymatic activity values among class I, II or III variants. Some G6PD A−202A/376G individuals had enzymatic values that were close to the cutoff value , while others showed extremely low enzymatic values . Homozygosity for UGT1A1*28 among G6PDd patients with  or without  NNJ did not shown significant statistical difference (p = 0.611).A total of 81 newborns  were included. Most individuals (46.9%) had NNJ without other symptoms, followed by asymptomatic (42.0%) and hospitalized (11.1%) patients, although the hospitalization of only 3 of these patients was related to G6PDd, including NNJ or acute hemolytic anemia (AHA). Nine different G6PDd genotypes were found; the G6PD A−376G/968C and G6PD A−202A/376G haplotypes.Wide variability in residual enzymatic activity was noted in G6PDd individuals with the same G6PD genotype. This feature, along with a documented heterogeneous mutational spectrum, makes it difficult to categorize G6PD variants according to current WHO classification and precludes the prediction of complications such as AHA, which can occur even with > 10% of residual enzymatic activity and/or be associated with the common and mild G6PD A G6PD gene  ), which was found in 7.4% of the deficient patients. The mean enzymatic activity of each variant and its geographical origin are shown in Table Across the studied population, we found 9 different ed Table . The mosys) rs39823546), wOf the 81 individuals, 9/81 (11.1%) patients, in accordance with the Luzzato 2016 classification [p = 0.376).The G6PD activity of the different clinical groups are shown in Table G6PD genotypes, enzymatic activity, and geographical origin of each of 81 patients are shown in Additional file In four families, one or more siblings were G6PDd, and their results are presented in Table G6PDd is widely heterogeneous in terms of biochemical, clinical, and molecular manifestations . In the G6PD variants. In class II newborns, the residual activity ranged from 0.56% to 12.36%, while in class III newborns, the residual activity ranged from 5.6 to 43.82%, and in a significant number of individuals, there was an overlap of the values , while other individuals showed extremely low enzymatic values . In fact, we identified four G6PDd families with more than one affected patient (Table −202A/376G genotype (class III)  and A(TA)7TAA allele, or for the “G71R” (rs4148323) variant highly prevalent in Asian-derived populations [p = 0.051). Nevertheless, one limitation of this study design is that it does not allow us to know the severe cases of kernicterus that could have occurred, which is to be expected in such patients that would be hospitalized or even deceased and not come to our newborn screening follow-up center.Several studies have revealed that the prevalence of G6PDd is higher in jaundiced newborns than in the control population, ranging from 8.9 to 28.1% –33. Badetability . Recentltability  describeG6PD spectrum, the most frequently identified hypomorphic variants come from Africa (82.7% comprised by G6PD A−202A/376G and G6PD A−376G/968C), followed by the class II Union-Maewo or p.(Arg454Cys) allele (7.4%)  Table , whose oectively –41. To tectively .G6PD variant can lead to highly variable enzymatic residual activity as well as a wide phenotypic spectrum in the first month of life, which is in accordance with previously reported results [In summary, the present work shows that the same  results . The abs results . Our worG6PD genotype. This feature, along with a documented heterogeneous mutational spectrum, hinders the categorization of G6PD variants according to the current WHO classification and, importantly, precludes the prediction of complications such as AHA, which can occur even with > 10% of residual G6PD activity and/or associated with the common and mild G6PD A−376G/968C and G6PD A−202A/376G variants.There is wide variability in the enzymatic activity in G6PDd individuals, even in those with the same Additional file 1: Table 1. Individual genotypes, geographic origin, residual enzymatic activity and concordance classification; Table 2. Proportion of patients with or without symptoms related to G6PDd, according to their genotype.


FLT3) internal tandem duplications (FLT3/ITDs) in their juxtamembrane domain (JMD). FLT3/ITDs range in size from three to hundreds of nucleotides, and confer an adverse prognosis. Studies on a possible relationship between of FLT3/ITDs length and clinical outcomes in those AML patients were inconclusive, yet.Approximately 30% of adult acute myeloid leukemia (AML) acquire within fms-like tyrosine kinase 3 gene (FLT3-ITD mutations in addition to NPM1 mutation. Cytogenetic approaches (banding cytogenetics) and fluorescence in situ hybridization (FISH) using specific probes to detect translocations t, t, t, t, and deletion del(13q)) were applied to exclude chromosomal abnormalities. Molecular genetic approaches (polymerase chain reaction (PCR) and the Sanger sequencing) identified a yet unreported combination of two new mutations in FLT3-ITDs. The first mutation induced a frameshift in JMD, and the second led to a homozygous substitution of c.1836T>A (p.F612L) also in JMD. Additionally a NPM1 type A mutation was detected. The first chemotherapeutic treatment was successful, but 1 month after the initial diagnosis, the patient experienced a relapse and unfortunately died.Here we report a 54-year-old Arab male diagnosed with AML who had two FLT3-ITD mutations in JMD together with an NPM1 type A mutation were not previously reported in adult AML. Further studies are necessary to prove or rule out whether the size of these FLT3-ITDs mutations and potential other double mutations in FLT3-ITD are correlated with the observed adverse outcome.To the best of our knowledge, a combination of two  In patients with acute myeloid leukemia (AML) genetic diagnostics were performed in the past mainly by cytogenetics and molecular cytogenetics. In recent years also tumor markers were added, which rely on molecular genetic methods .FLT3) gene encodes a class III tyrosine kinase receptor for the FLT3 ligand, which is normally expressed in CD34+ hematopoietic stem/progenitor cells, and plays a fundamental role in both normal and leukemic hematopoiesis [FLT3 gene (FLT3/ITDs) represent one of the most common molecular abnormalities in patients with AML. They are detectable in around 25–30% of all patients [FLT3/ITDs also protect leukemic cells from the damaging chemotherapeutic agents [The fms-like tyrosine kinase 3  lead progressively to increasing activation levels and (2) to worsen the overall survival (OS) in affected patients. Still, the results of studies which investigated the impact of ITD length on the clinical outcome are contradictory. Some studies confirming the aforementioned assumption –12, wherFLT3/ITDs has been associated with an increased initial peripheral white blood cell (WBC) count and percentage of blast cells in bone marrow, a reduced disease-free survival (DFS) and OS, and a high relapse rate with an overall adverse prognosis. However, the rate of complete remission (CR) was not significantly affected [FLT3/ITDs has been suggested [FLT3/ITD mutation have a poor prognosis.Presence of affected –17. Thusuggested . AccordiFLT3/ITD, mutations in nucleophosmin 1 (NPM1) gene represent the second most frequent molecular aberration in AML patients [NPM1 and the wild type FLT3 gene (NPM1+/FLT3−) is a well-established favorable risk factor in younger adult patients, with less probability of relapse and prolonged survival [FLT3/ITD and NPM1 mutations was suggested to partially improve response rates, DFS and OS outcomes compared to AML-patients having exclusively FLT3/ITD mutations. However, cases with mutations in FLT3/ITD and NPM1 have worse prognosis than those having (NPM1+/FLT3−) [Besides in patients . A combisurvival –21; thessurvival . Otherwi+/FLT3−) .FLT3-ITDs mutations in JMD and an NPM1 type A gene mutation associated with adverse outcome.Here, we present a unique case with two 9/l (10% were blasts). Pathologic examination of bone marrow (BM) aspirate characterized hybercellularity with 60% of blasts. Flow cytometric (FCM) analysis classified this case as AML-M2 according to world health organization (WHO) classification. The abnormal cell population (60%) was positive for CD45dim, CD34, HLADr, CD13, CD33 and expressed CD117 heterogeneously. Blasts cell population was negative for CD3, CD117, CD14, cCD3, cCD79a, CD14, CD11c, CD38, CD64, CD32, CD7, CD19, CD10, and CD5.In October 2019, a 54-year-old Arab male patient presented with 2 months history of fatigue, orthostatic hypotension followed by bruising on the lower right extremity, melena (present for one month only) and dyspnea II. Physical examination and computer tomographic scan showed hepatomegaly (4 cm). He had no familial history of malignancies and no social and environmental history of exposure to toxins or animals. Initial laboratory evaluation of peripheral blood (PB) revealed white blood cells count (WBC) of 26.3 × 102 for 3 days and cytarabine 200 mg/m2 for 7 days). One month later, under treatment with 3 + 7 protocol, the patient relapsed, i.e. his PB showed a WBC of 107 × 109/l, anemia (hemoglobin level (Hgb) = 8.8 g/dl) and thrombocytopenia (Plt 93 × 109/l). The patient was given re-induction with 3 + 7 chemotherapy protocol , FLT3-KTD and NPM1; using specific primers for each mutation previously reported [FLT3-ITD were identified in our patient  prior to chemotherapy treatment. Polymerase chain reaction (PCR) amplification of genomic DNA and Sanger sequencing were used to screen for the presence of mutations of the following genes: reported . ITDs weTD exons 1 and 12,mutation 1: c.1779-1780insTTTCAGAGAATATGAATATGATCTCAAATGGGAGTTTCCAAGAGAAAATTTAGAGTTAGG (p.D593-F594insREYEYDLKWEFPRENLEF).mutation 2: homozygous substitution c.1836T>A (p.F612L).FLT3-KTD test in our patient. However, he had also NPM1 type A mutation (data not shown).A D835 mutation was not detected by NPM1 type A and two frameshift FLT3-ITD mutations. The first frameshift FLT3-ITD was never reported before (COSMIC database for somatic samples from hematopoietic and lymphoid tissue), whereas the second mutation has already been observed, but as heterozygous variant (COSV54057677).Here we report the first case of an adult AML patient with normal karyotype, who had one The present case supports previous findings –12, whicOf special interest, is the suggestion that the complications of intense chemotherapy, as observed in our patient (see Table FLT3-ITDs mutation and the double mutations in FLT3-ITD are correlated with an adverse prognosis. Also, more research is needed to see if chemotherapy-complications as observed here can be omitted by the application of other treatment regimes.Further studies are needed to prove or rule out whether the size of the


NRXN1, a well-known neurodevelopmental disease-causing gene, from individuals with ASD and SCZ.Rare genetic variants contribute to the etiology of both autism spectrum disorder (ASD) and schizophrenia (SCZ). Most genetic studies limit their focus to likely gene-disrupting mutations because they are relatively easier to interpret their effects on the gene product. Interpretation of missense variants is also informative to some pathophysiological mechanisms of these neurodevelopmental disorders; however, their contribution has not been elucidated because of relatively small effects. Therefore, we characterized missense variants detected in NRXN1 coding exons with a sample comprising 562 Japanese ASD and SCZ patients, followed by a genetic association analysis in 4273 unrelated individuals. Impact of each missense variant detected here on cell surface expression, interaction with NLGN1, and synaptogenic activity was analyzed using an in vitro functional assay and in silico three-dimensional (3D) structural modeling.To discover rare variants with large effect size and to evaluate their role in the shared etiopathophysiology of ASD and SCZ, we sequenced NRXN1α isoform, as disease-associated variants. Diagnosis of individuals with T737M, D772G, and R856W was 1ASD and 1SCZ, 1ASD, and 1SCZ, respectively. We observed the following phenotypic and functional burden caused by each variant. (i) D772G and R856W carriers had more serious social disabilities than T737M carriers. (ii) In vitro assay showed reduced cell surface expression of NRXN1α by D772G and R856W mutations. In vitro functional analysis showed decreased NRXN1α-NLGN1 interaction of T737M and D772G mutants. (iii) In silico 3D structural modeling indicated that T737M and D772G mutations could destabilize the rod-shaped structure of LNS2-LNS5 domains, and D772G and R856W could disturb N-glycan conformations for the transport signal.Through mutation screening, we regarded three ultra-rare missense variants , all of which affected the LNS4 domain of NRXN1 could be associated with phenotypes of neurodevelopmental disorders beyond the diagnosis of ASD and/or SCZ.The combined data suggest that missense variants in  Autism spectrum disorder (ASD) and schizophrenia (SCZ), both of which are highly heritable heterogeneous collections of psychiatric and clinical diagnoses with neurodevelopmental origin –3, have NRXN1 (OMIM 600565), located on chromosome 2p16.3, is a well-established risk gene of broad neurodevelopmental disorders [NRXN1 were first identified in individuals with ASD [NRXN1 cause Pitt-Hopkins-like syndrome-2 (OMIM #614325), a rare autosomal recessive ID syndrome [NRXN1 deletions are estimated to contribute to approximately 0.2% of ASD, ID, and SCZ cases [NRXN1 disruption influences synapse function and neuronal connectivity [Nrxn1 knockout mouse models [NRXN1 have been also linked to broad neurodevelopmental disorders including ASD, SCZ, ID, and seizures [NRXN1. According to the Exome Aggregation Consortium (ExAC) [NRXN1 is defined as a constrained gene with an ExAC missense Z score of 3.02. A positive Z score, particularly a score > 3, indicates that the gene is very intolerant of missense variants.isorders –16. Rarewith ASD , 18 and with ASD . Subsequsyndrome , 21. GenCZ cases , 23. NRXCZ cases –29. Humaectivity , 31. SucOMIM #6145, a raree models . These mseizures –36; howem (ExAC) , NRXN1 iNRXN1 detected from individuals with ASD and/or SCZ from genes to functional levels to clinical features. Effects of SNVs are considered to be milder than those of intragenic deletions and may be obscured in complex animal models. For example, missense variants in SHANK3, the gene mutated in Phelan-McDermid syndrome (OMIM #606232), cause less severe phenotype than exonic SHANK3 deletion [NRXN1 in a cohort of 4835 unrelated individuals, followed by phenotypic evaluation of individuals with novel variants. We then performed in vitro functional assay for cell surface expression, NLGN1 binding and/or synaptogenic activity, and in silico three-dimensional (3D) structural modeling of NRXN1 with N-glycan and NLGN1 to determine the impact of the detected variants. Here, we highlight the functional characteristics of missense variants in NRXN1 on broad neurodevelopmental disorders.The purpose of the present study is to characterize rare missense variants in deletion –40. TherTwo independent sample sets were used in this study. The targeted-resequencing discovery cohort comprised 192 ASD  and 370 SCZ . For the genetic association analysis, the case-control sample set comprised 382 ASD , 1851 SCZ , and 2040 control subjects . All participants were unrelated, living on mainland Japan, and self-identified as Japanese. All ASD and SCZ cases fulfilled the criteria listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) for ASD or SCZ [NRXN1α  and NRXN1β  with Ion AmpliSeq Designer (Thermo Fisher Scientific). Sample amplification and equalization were achieved using Ion AmpliSeq Library Kit 2.0 and the Ion Library Equalizer Kit, respectively (Thermo Fisher Scientific). Amplified sequences were ligated with Ion Xpress Barcode Adapters (Thermo Fisher Scientific). Emulsion PCR and subsequent enrichment were performed using the Ion OneTouch Template Kit v2.0 on Ion OneTouch 2 and Ion OneTouch ES, respectively (Thermo Fisher Scientific). Sequence reads were run through a data analysis pipeline of the Ion Torrent platform-specific pipeline software, Torrent Suite version 4.4 (Thermo Fisher Scientific). Read assembly and variant identification were performed by the Ingenuity Variant Analysis software (Qiagen) using FASTQ files containing sequence reads and the Ion AmpliSeq Designer BED file software to map amplicons with default parameters: call quality > 20 and read depth > 10.Genomic DNA was extracted from peripheral blood or saliva samples using the QIAamp DNA Blood Kit or Tissue Kit  following the manufacturer’s protocol. The next-generation sequencing technology of the Ion Torrent PGM  was used for amplicon resequencing in accordance with the manufacturer’s protocol. We designed custom amplification primers to cover coding exons and flanking intron regions of both Candidate variants were defined as exonic or splice-site variants with allele frequencies of ≤ 1% in the following two public databases: dbSNP Build 151  and the The effective sample size and statistical power were computed using the web browser program, Genetic Power Calculator . An ABI NRXN1 [We scored the social function of patients with a variant that was possibly associated with ASD and SCZ phenotypes based on variation screening using the Global Assessment of Functioning (GAF). Patients are rated between 0 (most severe) and 90 (least severe) . ClinicaNRXN1 , 55, 56.NRXN1 .The coding sequence of mouse Nrxn1α lacking the signal peptide was cloned into pFLAG-CMV-1 vector  to yield pFLAG-NRXN1α. NRXN1α used in this study carried splice segments S1, S2, and S3 but lacked S4 and S5. T737M, D772G, R856W, N790Q, S792A, M735V, M756I, T779M, H845Y, L869M, S743Y, S763C, and R813H mutations were introduced into the pFLAG-NRXN1α vector by PCR-based mutagenesis for the cell surface-expression assay and cell surface-binding assay. Expression vectors for mutated forms of mouse NRXN1α-Fc were generated by PCR-based mutagenesis using pEB6-NRXN1α-ECD-Fc  as a temHEK293T cells were maintained in DMEM supplemented with 10% FCS. Expression vectors were transfected into HEK293T cells using PEI MAX . After 36 h of transfection, cells were incubated with mouse anti-FLAG antibody  for 1 h followed by fixation with 4% PFA for 20 min and blocking with 10% donkey serum for 1 h. Fixed cells were permeabilized with 0.25% Triton X-100 for 5 min and incubated with rabbit anti-FLAG antibody  for 1 h. Cell surface and total FLAG-NRXN1α proteins were visualized with Alexa Fluor 488-conjugated donkey anti-mouse IgG  and Alexa Fluor 555-conjugated donkey anti-rabbit IgG , respectively. Fluorescent images were taken using a confocal microscope  and fluorescence densities of cells were quantified using the ImageJ 1.37 software . Statistical significance was evaluated by one-way ANOVA followed by post hoc Tukey’s test.4 beads/cm2. After 24 h, cultures were fixed and immunostained with rabbit anti-Shank2 antibody  followed by Alexa555-conjugated donkey anti-rabbit IgG  for confocal microscopy. Quantification of immunostaining signals for Shank2 was performed essentially as previously described [Primary cerebral cortical neurons were prepared from mice at postnatal day 0 as described previously . Magnetiescribed . BrieflyExpression vectors for FLAG-tagged wild-type and mutated forms of NRXN1α were transfected into HEK293T cells. Transfected cells were then incubated with Fc and NLGN1-Fc  (0.1 μM HEK293T cells were transfected with expression vectors for FLAG-tagged wild-type and mutated forms of NRXN1α using Lipofectamine 2000 transfection reagent (Thermo Fisher Scientific). Two days after transfection, cells were lysed with RIPA buffer. Lysates containing 20 μg protein were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), transferred to polyvinylidene fluoride membranes, and probed with mouse anti-FLAG antibody  followed by horseradish-peroxidase-conjugated goat anti-mouse IgG antibody . Blots were then developed and imaged using a Luminescent Image Analyzer LAS-4000 mini .https://www.wwpdb.org) [The 3D atomic structure of NRXN1α determined by X-ray crystallography is available as entry 3r05  from thepdb.org) . Considepdb.org)  by compupdb.org)  and Modepdb.org) . Next, tpdb.org) , as showpdb.org) . The detNRXN1 coding regions in genomic DNA isolated from Japanese ASD and SCZ subjects (n = 562)  repeats, followed by an O-linked sugar modification sequence, a short cysteine-loop domain, a transmembrane region, and a cytoplasmic sequence of 55–56 residues. NRXN1β is composed of a unique N-terminal β-neurexin-specific sequence that splices into the NRXN1α sequence N-terminal of its LNS6 domain  and controls (n = 2040).We identified six rare missense SNVs within NRXN1 variants. Social impairments were more severe in individuals with D772G and R856W comparing to those with T737M . Three disease-associated variants were those registered in ClinVar, not in gnomAD (S743Y and S763C), and previously reported as de novo mutation in a case with ASD (R813H) [We summarize in vitro assay and features from 3D models of these variants in Table NRXN1α isoform, which were regarded as disease-associated variants based on their small fraction registered in public databases  and predicted to be protein-damaging by multiple prediction tools mentioned in the “Methods” section  within the LNS4 domain of NRXN1 [NRXN1 is one of highly dosage sensitive genes based on NCBI ClinGen Dosage Sensitivity Map [NRXN1 deletion. In combination with in silico 3D structural modeling, mutation of D772G and R856W, not T737M, might disturb the transport signal of N790 glycosylation for packaging NRXN1 into appropriate transport vesicles.Reduced cell surface expression of D772G and R856W mutants compared with wild-type and T737M mutant was observed using an in vitro assay. Interestingly, subjects carrying D772G and R856W exhibited severe functional impairments, which are linked to certain rare variants including those in NRXN1 –78. Becavity Map , our obsSubsequently, we showed increased excitatory synaptogenic activity with T737M mutant only and disturbed NRXN1α-NLGN1 interaction with T737M and D772G mutants. Impairments caused by mutations in the NRXN-NLGN complex have been implicated in the pathomechanisms of not only idiopathic ASD  and SCZ NRXN1, the involvement of other genetic factors cannot be ignored. A recent genome-wide study classified ASD and SCZ into different clusters based on over six million common variants [NRXN1-T737M, and the functional similarity of NRXN1-D772G with ASD and NRXN1-R856W with SCZ, beyond current diagnoses in psychiatry based on subjective reports and clinical observations [NRXN1 could contribute to risk for neurodevelopmental disorders. More extensive sequencing in the gene would be required rather than targeted sequencing in both cases and controls to determine which variants are relevant. Finally, we only demonstrated the impact of each variant detected on NRXN1 protein function through in vitro functional analysis and in silico 3D structural modeling. In fact, a reduced vesicle release capacity was observed in α-Nrxn 1, 2, and 3 triple knockout mice, whereas a limited reduction in vesicle release capacity was detected in the α-Nrxn2-only knockout mice [NRXN family genes, as well as the NLGN family genes, may be compensatory and suppress the effects of genomic mutations if the remaining genes are normal. With respect to the functional characterization, the spatio-temporal analysis of the effects of molecular network changes caused by NRXN1 SNVs during development using induced pluripotent stem cell models with knockdown of the variants of interest combined with phenotyping in neuronal cells, or generating conditional mutations in human neurons that are independent of the patients’ genetic background may also be potential avenues to explore.There are several limitations to this study. First, while there is a rationale for focusing on rare variants within variants . The joirvations  and Phelrvations –40, it iout mice . Mouse mout mice . NLGN1, out mice . TogetheNRXN1 SNVs might link to endophenotypes across neurodevelopmental disorders. As NRXN1 involves an overall transsynaptic signaling network, a more comprehensive approach to address the puzzling diversity of clinical manifestations associated with NRXN1 SNVs is required. Translation of rare missense variants of disease-causing genes into molecular risk mechanisms to clinical phenotypes is important to advance the clinical utility of human genome sequencing.Our data from human genetics, in vitro cell biological studies, and in silico informatics characterized Additional file 1 Supplementary Figures and Tables. Figure S1. Family-trio analysis with parental genotype data. Figure S2. Decreased NLGN1 binding activities of T737M and D772G variants. Figure S3. A modeled 3D complex structure of NLGN1 with NRXN1a. Figure S4. Six chosen model structures of LNS4 domain with the complex-type N-glycan among the 300 generated conformations. Figure S5. A schematic view of the complex-type N-glycan taken from PDB entry 4fqc. Figure S6. Locations of the LNS4 missense mutations in NRXN1a (PDB ID:3r05) with a modeled loop with N-glycan. Table S1. Overview of eight control SNVs in NRXN1-LNS4. Table S2. Overview of SNVs for in vitro functional assay and 3D models of structures. Table S3. Cross tabulation of variants for cell surface expression and N-glycan model. Table S4. Cross tabulation of variants for interaction with NLGN1 and stability change.


Importantly, sGRP78 overexpression inhibited DC activation and induced M2-like polarization in F4/80+ macrophages. Moreover, sGRP78 overexpression enhanced TGF-β production in the liver. In conclusion, sGRP78 promotes tumor cell colonization in the liver by remodeling the tumor microenvironment and promoting immune tolerance. The ability of sGRP78-targeting strategies to prevent or treat liver metastasis should be further examined.The liver is an immunologically tolerant organ and a common site of distant metastasis for various cancers. The expression levels of glucose-regulated protein 78 (GRP78) have been associated with tumor malignancy. Secretory GRP78 (sGRP78) released from tumor cells contributes to the establishment of an immunosuppressive tumor microenvironment by regulating cytokine production in macrophages and dendritic cells (DCs). However, the role of sGRP78 on tumor cell colonization and metastasis in the liver remains unclear. Herein, we found that GRP78 was expressed at higher levels in the liver compared to other tissues and organs. We performed intravital imaging using a sGRP78-overexpressing breast cancer cell line (E0771) and found that sGRP78 interacted with dendritic cells (DCs) and F4/80 Tumor metastasis remains the major cause of cancer-related deaths. The liver represents a common site of distant metastasis for various cancers, including melanoma, breast cancer, and colorectal cancer. The successful colonization of distant organs by circulating tumor cells (CTCs) is key for cancer metastasis , and thehi regulatory B cells (Glucose-regulated protein 78 (GRP78) belongs to a group of highly conserved heat shock proteins (HSP) with important stress response functions –5. GRP78 B cells  and dend B cells –11. More B cells –21. For  B cells . Further B cells . The ant B cells . Besides B cells .+ T cells. The crosstalk between DC and NK is mediated by the phosphorylation of the signal transducer and activator of transcription 3 (STAT3)  cells , which p (STAT3) . Zhou et (STAT3)  demonstr (STAT3) , 31. TGF (STAT3) , 33. NevHerein, we show that GRP78 is highly expressed in the liver of tumor-free mice. To elucidate the relevance of sGRP78 in the hepatic metastatic niche, we established a sGRP78-overexpressing cell line, which was used to establish an experimental liver metastasis mouse model. Using this mouse model, we found that sGRP78 mediates the formation of a pro-metastatic niche, supporting the rationale of sGRP78-targeting as a liver metastasis prevention strategy.Cx3cr1 locus. All experiments were performed with mice aged 6–8 weeks. Mice were bred and maintained in specific pathogen-free (SPF) conditions at the Animal Center of Wuhan National Laboratory for Optoelectronics. All procedures involving animals were conducted in compliance with protocols approved by the Hubei Provincial Animal Care and Use Committee of Huazhong University of Science and Technology.Female C57BL/6 mice were purchased from Hunan SJA Laboratory Animal Co., Ltd . CX3CR1-GFP mice in a C57BL/6 background were purchased from the Jackson Laboratory; in these mice, EGFP is expressed in monocytes, DCs, NK cells, and brain microglia, under the control of the endogenous CMV promoter-driven mCherry or mCherry-sGRP78 (GRP78 GeneBank No: NM_001163434.1) coding sequence, and named as E0771-mCherry/E0771-mCherry-sGRP78 cells. B16F10 cells were stably transfected with the PB transposon system, which contained the mCherry-sgGRP78, mCherry or mCherry-sGRP78 coding sequence . All cell lines were regularly tested for mycoplasma using the MycoProbe Mycoplasma Detection Kit . E0771 cells were cultured in DMEM containing 10% fetal bovine serum (FBS), 100 U/mL Sodium Pyruvate, 100 U/mL non-essential amino acids, and 100 U/mL penicillin-streptomycin. B16F10 cells were cultured in ROMI-1640 containing 10% FBS and 100 U/mL penicillin-streptomycin. Cells were maintained at 37°C in a 5% CO2 incubator .The E0771 cell line was kindly provided by Professor Rong Xiang  and was authenticated in Beijing Microread Genetics Co., Ltd. by STR analysis. The B16F10 cell line was purchased from the BO STER Company . E0771 cells were stably transfected with the PB transposon system  , which c6 cells were seeded in the plates and cultured in serum-free culture media for 24 h. Then supernatants and tissue samples were assayed by ELISA using the BiP (C50B12) Rabbit mAb (CST). The purified GRP78 protein was used as the standard sample. Data were analyzed by Welch’s ANOVA.Tissues and organs of C57BL/6 mice at 8 weeks were harvested and their mass was measured. Tissue samples with the same wet weight were lysed in NP-40 lysis buffer (5 μL/mg) containing a protease inhibitor cocktail (Sigma-Aldrich). Lysates were separated and stored at −80°C until further use. 1 × 104 E0771 tumor cells on day 0, and then the cells were counted for 7 consecutive days. Data were analyzed by Welch’s ANOVA (versus E0771 group).The 6-well plates were seeded with 105 E0771 tumor cells. After the cells adhere to the wall, the wound was scratched as the 0 h. And CCD photographs record the wound healing at 0 and 24 h.The 6-well plates were seeded with 4 × 106 E0771 or 5 × 105 B16F10 cells. Seven minutes later, half of the spleen containing the tumor cell injection site was resected. The hepatic metastatic burden was assessed on day 21 for E0771 and day 15 for B16F10 after tumor cell inoculation. Hematoxylin and eosin (H&E) stain was purchased from Servicebio Biotechnology  and slides were scanned using a Nikon Ni-E . Images were acquired using the NIS-Elements software and analyzed using ImageJ. The metastatic burden was calculated by dividing the area occupied by metastatic foci (mm2) by the total surface liver area (mm2).The mice were anesthetized by intraperitoneal (i.p.) injection of a mixture of 10 mg/kg xylazine and 100 mg/kg ketamine hydrochloride . During anesthesia, body temperature was maintained at 37°C using a warm plate . Mouse spleens were exposed by a small upper abdomen incision, followed by injection of 1 × 10g for 5 min. The resulting cell pellet was resuspended in 10 mL 35% Percoll containing 100 U/mL heparin and centrifuged at 700 × g for 15 min at room temperature. The cell pellet containing leukocytes was collected and resuspended in 3 mL red blood cell lysis solution . After incubation for 3 min at room temperature, cells were washed twice with RPMI 1640 containing 5% FBS.Female C57BL/6 mice (7–8 weeks old) were sacrificed by cervical dislocation. The liver was dissected into 1 mm pieces and digested using collagenase IV (Worthington) and DNAase II (Sigma) for 30 min at 37°C. The digested liver extracts were filtered through a 70 μm cell strainer and centrifuged at 500 × Antibodies against CD45 (104), CD3 (17A2), NK1.1 (PK136), CD19 (6D5), CD69 (H1.2F3), CD4 (RM4-4), CD8 (53-6.7), Ki-67 (11F6), CD146 (ME-9F1), Ly6G (1A8), CD11b (M1/70), F4/80 (BM8), CD11c (N418), MHC-II (M5/114.15.2), CD86 (GL-1), CD80 (16-10A1), PD-1 (RMP1-14), and FoxP3 (MF-14) were purchased from BioLegend. The fixable viability dye eFluor506 was purchased from eBioscience. Liver cell suspensions were subjected to surface staining with fluorescently labeled antibodies according to the manufacturer’s instructions. Cell viability was assessed using the fixable viability dye eFluor506 (eBioscience). Subsequently, cells were permeabilized using the Transcription Factor Buffer Set (Biolegend) and stained for Ki-67, FoxP3. Cells were analyzed on a CytoFLEX flow cytometer . Flow cytometry data were analyzed using FlowJo software .For the immunofluorescence analysis, liver tissues were fixed in 4% paraformaldehyde for 12 h at 4°C and then dehydrated in 30% sucrose solution. The tissues were then frozen in OCT  compound and sectioned into 20 μm slices using a freezing microtome . OCT was removed by washing three times in PBS, and the sections were immunostained with Alexa Fluor 647 anti-mouse F4/80 , Alexa Fluor 647 anti-mouse CD11c  or Alexa Fluor 647 anti-mouse NK1.1  at 1:200 dilution. All the sections were imaged with Olympus IX83 confocal microscope outfitted with an UltraVIEW VoX 3D live cell imaging system (PerkinElmer). Images were analyzed with Image J software .Livers were harvested and their mass was measured at days 4 and 7 after injection. Tissue samples were lysed in NP-40 lysis buffer (5 μL/mg) containing a protease inhibitor cocktail (Sigma-Aldrich). Lysates were separated and stored at −80°C until further use. Samples were assayed using the LEGENDplexTM Mouse Cytokine Panel array (BioLegend) according to the manufacturer’s instructions. Data were analyzed with Legendplex software (BioLegend). Mouse TGF-beta ELISA kit (DAKEWE) was used to detect TGF-β levels in the samples.6 E0771-mCherry or E0771-mCherry-sGRP78 cells (day 0). On days 4 and 7, mice were anesthetized by i.p. injection of a mixture of 10 mg/kg xylazine and 100 mg/kg ketamine hydrochloride . Mice were maintained anesthesia with isoflurane inhalation [1.5–2% (v/v) isoflurane in O2] and placed within a custom-designed imaging box. Throughout the imaging process, mice were placed on a heating pad to maintain a body temperature of 37°C . Intravital imaging was performed using an Olympus IX83 confocal microscope outfitted with an UltraVIEW VoX 3D live cell imaging system (PerkinElmer). Images were acquired using a 20 × /0.75 NA objective and Volocity 6.3 (PerkinElmer) software. Images were analyzed with Image J software .CX3CR1-GFP C57BL/6 mice (6–10 weeks old) were inoculated with 1 × 10RRID:SCR-007369) or Imaris 7.6  software. The mean velocity, mean displacement, arrest coefficient, and confinement ratio were determined. The mean velocity was used to determine the migratory speed in μm/min. Cells with a mean velocity of less than 2 μm/min were defined as immotile. The mean displacement was used to determine the initial displacement of the cells. The arrest coefficient was calculated as the percentage of time that the instantaneous velocity of each cell was less than 2 μm/min, as previously described  was used for comparisons of two groups. Survival data were analyzed using log-rank (Mantel-Cox) test. Values were expressed as mean ± standard error of the mean (SEM). Two-sided P < 0.05 was considered statistically significant . The numbers of animals used in each experiment were indicated in the figure legends.Statistical analysis was performed using GraphPad Prism 6 . A one-way ANOVA followed by a in vitro . Confocal microscopy showed that, although mCherry primarily localized in the cytoplasm in E0771-mCherry-sGRP78 cells, it was evenly distributed in E0771-mCherry cells . ELISA ain vitro . To invein vitro .in vivo, accelerating liver metastasis.We also found that the level of GRP78 in the supernatant (SN) of liver homogenate was two times higher than in the NS from spleen and lung . Flow cy+ macrophages and DCs in the liver differ significantly between the two groups , macrophages, and liver sinusoidal endothelial cells (LSECs) , 38. We + DCs . Compared to CX3CR1–F4/80+ cells, the numbers of mCherry-positive CX3CR1+F4/80– and CX3CR1+F4/80+ cells were 5 times and 3.5 times higher, respectively . However, in E0771-mCherry-bearing mice, CX3CR1+ cells migrated with a mean velocity of 2.899 ± 0.2512 μm/min (n = 95 cells). Moreover, in E0771-mCherry-sGRP78-bearing mice, the migration trajectories were more confined  and the arrest coefficient (percentage of cell resting time) was lower compared with the E0771-mCherry group  , followefication . Four da+ cell motility changed significantly. Although the number of moving CX3CR1+ cells was significantly lower in both groups compared with 4 days after cell inoculation, the velocity of movement was significantly increased in E0771-mCherry-sGRP78-bearing mice (102.9 ± 18.28 μm/min). In contrast, in E0771-mCherry-bearing mice, the velocity of movement did not differ significantly between 4 and 7 days after cell inoculation  and CD19+ B cells (P < 0.01) in E0771-mCherry-sGRP78-bearing mice 4 and 7 days after cell inoculation were lower than those in control mice, respectively  cells, B cells, CD4tastasis . The freectively . Four daectively , 42, was+ myeloid cells. sGRP78 inhibited DC activation by downregulating MHC-II, as well as induced F4/80+ M2-type polarization. Furthermore, sGRP78 affected NK cell infiltration and activation in hepatic metastatic lesions by regulating cytokine production (In this study, we demonstrated that high expression of sGRP78 in the liver promotes immune tolerance. To elucidate the role of sGRP78 in the hepatic pre-metastatic niche, we established an experimental liver metastasis model using sGRP78-overexpressing murine breast cancer cells. We found that tumor-secreted GRP78 reshaping the hepatic microenvironment by recruiting CX3CR1oduction .in vitro. In addition, sGRP78 overexpression enhanced the colonization and proliferation of metastatic cells in the liver, suggesting that sGRP78 expression in cancer cells promotes invasion and liver metastasis by modulating the hepatic microenvironment.GRP78 is expressed at higher levels in tumor tissues compared to adjacent healthy tissues, indicating that GRP78 has potential pro-tumorigenic functions –45. In o2+, leading to cytoskeleton remodeling. Our results supported the role of sGRP78 on the motility of CX3CR1+ cells in the liver, including DCs and macrophages, fostering liver metastasis. We believe that the increased infiltration of DCs and macrophages accompanied by the decreased recruitment and activation of NK cells contributed to the establishment of a microenvironment allowing for tumor cell survival and growth. Nevertheless, future studies are required to determine the mechanisms involved in the sGRP78-mediated NK cell inhibition.The establishment of a pre-metastatic niche is a prerequisite for tumor cell colonization and growth in secondary organs . In this+ macrophages, induction of TGF-β, and suppression of hepatic NK cells. Thus, sGRP78 promotes tumor growth and metastasis by remodeling the tumor microenvironment and promoting immune tolerance. The ability of GRP78-targeting agents to prevent liver metastasis should be further investigated.In conclusion, we have demonstrated that sGRP78 promotes tumor cell colonization in the liver. We also identified several mechanisms involved in this phenomenon, including the modulation of DCs and F4/80The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by the Animal Experimentation Ethics Committee of Huazhong University of Science and Technology.LC under the direction of ZZ and GS designed and performed the experiments, analyzed the data, and wrote the first version of the manuscript. XY and LL provided technical guidance. HZhe discussed the manuscript and provided feedback and suggestions. ZZ, PL, and GS designed the experiments, wrote the manuscript, and supervised the study. All authors contributed to the critical revision of the manuscript and approved the final version.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.


Novel and more broadly protective vaccines against influenza are needed to efficiently meet antigenic drift and shift. Relevant to this end, the stem domain of hemagglutinin (HA) is highly conserved, and antibodies specific for epitopes located to the stem have been demonstrated to be able to confer broad protection against various influenza subtypes. However, a remaining challenge is to induce antibodies against the poorly immunogenic stem by vaccination strategies that can be scaled up for prophylactic vaccination of the general population. Here, we have developed DNA vaccines where the conserved stem domain of HA from influenza A/PR/8/34 (H1N1) and A/Shanghai/2/2013 (H7N9) was targeted toward MHC class II molecules on antigen-presenting cells (APC) for increased immunogenicity. Each of these vaccines induced antibodies that cross-reacted with other subtypes in the corresponding phylogenetic influenza groups. Importantly, when mixing the MHCII-targeted stem domains from H1N1 and H7N9 influenza viruses into one vaccine bolus, we observed broad protection against candidate stains from both phylogenetic groups 1 and 2. Conventional influenza vaccines cannot provide protection against antigenically drifted or shifted strains of influenza viruses. Thus, novel vaccines that induce broadly protective immune responses are needed. Such vaccines will be of value both to rapidly counter an emerging pandemic strain, and during years where the conventional influenza vaccines fail to match circulating viruses .The most abundantly expressed surface protein on influenza is hemagglutinin (HA), and its globular head represents the prime target for neutralizing antibodies that confer sterilizing immunity against specific strains of influenza. However, the immunodominant head domain rapidly acquires expressed mutations (antigenic drift) that cause escape from pre-existing immunity. In contrast, the stem structure connecting the globular head with the viral membrane is highly conserved between different influenza subtypes , 3. In lThe broadly protective potential of stem-specific mAbs has instigated several attempts to induce similar polyclonal antibodies by vaccination. A headless HA stem domain was constructed already in 1983 , but theHere, we have taken a different approach. In order to enhance immunogenicity, the HA stem was inserted into a previously described vaccine format where antigens are targeted to antigen-presenting cells (APC) –21. The Six- to eight-week-old female BALB/c mice were purchased from Taconic  and housed under minimal disease conditions. All the experiments with BALB/c were approved by the Norwegian Animal Research Authority (NARA). F1 mice of BALB/c and knock-in CR9114 gH mice (C57BL/6 background) were bred and included in experiments from a minimal age of 8 weeks. All experiments with the F1 mice were approved by the Institutional Animal Care and Use Committee at The Scripps Research Institute, and were performed in accordance with relevant institutional and national guidelines. CR9114 gH mice will be described in detail elsewhere ; briefly, they were generated as previously described , except GGCCTCGGTGGCCTGGACACAATATGTATAGGCand TCCTCCTCCTCCACATAGTTTTCCGTTG; primer set 292–532: GGAGGAGGAGGATGTAACACGAAGTGand ACCGGCCCTGCAGGCCTCACGCCAGAATCTGATAGATCCCC. The fragments were joined by PCR SOEing with the linker: KLCGGGGCNTK(d) as targeting unit, or with the chemokine macrophage inflammatory protein 1 alpha (MIP1α) as targeting unit, a vaccine where the targeting unit had been replaced with a scFv specific for the hapten 4-hydroxy-3-iodo-5-nitrophenylacetic acid (NIP) (non-targeted control) (In order to construct vaccines encoding the HA stem domain from influenza A/PR/8/1934 (H1N1), primers were equipped with SfiI-sites (underlined) and designed to pick up amino acids 18–60 and 292–532 (numbering according to H0): primer set 18–60: CGGGGCNTK. In ordeCGGGGCNTK, 23, andCGGGGCNTK (kind gicontrol) , 23 was control) .H3 domain)  or NIP-BSA. Plates were blocked with 0.1% BSA in PBS, and supernatants from HEK293E cells were transiently transfected with 1 μg of vaccine plasmids, or purified vaccine proteins were added to wells in triplicates. Plates were now incubated with biotinylated mAb against IgG (Fc fragment)  or a C179 mAb specific for stem HA  followed by biotinylated anti mouse IgG2a . Next, plates were incubated with streptavidin alkaline phosphatase , developed with phosphatase substrate , and read at 405 nm with a Tecan reader using the Magellan v5.03 program.Ninety-six-well plates (Costar 3590) were coated with mouse anti-human IgG , or biotinylated anti-IgG2aa , and developed as above. For some ELISAs  were coated with inactivated A/PR/8/34 (H1N1) (PR8) virus (1:1600)  in PBS azide, or with recombinant HA protein (1 μg/ml) from one of the following viruses: PR8 , A/Hong Kong/1/1968 (H3N2) , A/Hong Kong/483/97 (H5N1) , A/Shanghai/1/2013 (H7N9) , or A/Hong Kong/1073/99 (H9N2) . Plates were blocked as above and incubated overnight at 4°C with diluted serum samples from individual mice. Next, plates were incubated with either alkaline phosphatase conjugated anti-mouse IgG , biotinylated anti-IgG1e ELISAs , the detThe influenza virus A/Puerto Rico/8/34 (mt.Sinai sub-strain) (H1N1) (PR8) was a kind gift from Dr. Anna Germundsson at the National Veterinary Institute, Norway. The influenza virus A/turkey/Italy/3889/1999 (H7N1) was a kind gift from Professor Rebecca Cox at the University of Bergen, Norway. Prior to use, the H7N1 virus was mouse adapted by several passages in BALB/c mice.Plasmids were purified by Endofree Qiagen kit  and dissolved in NaCl.BALB/c mice were anesthetized  by intraperitoneal (i.p.) injection and vaccinated by intramuscular (i.m.) injection with a total of 200 μg of plasmid DNA into the quadriceps muscles, immediately followed by electroporation (EP)  of the injection site. For viral challenge, BALB/c mice were anesthetized as above and given intranasal (i.n.) inoculations of virus in 10 μl per nostril. Mice were monitored for weight loss relative to the day of challenge (day 0), with an endpoint of a 20% weight reduction as required by NARA.F1 of BALB/c and knock-in CR9114 gH mice (C57BL/6 background) were anesthetized by isoflurane and vaccinated by i.m. injection with a total of 200 μg DNA into the quadriceps muscles immediately followed by EP . For viral challenge, the mice were anesthetized as above and given intratracheal (i.t.) inoculations of 2.5 × LD50 in 50 μl. Mice were monitored for weight loss relative to the day of challenge (day 0), with an endpoint of 25% weight loss.BALB/c mice were vaccinated as described above. Starting at day 12 after the second vaccination and until termination, mice that received αMHCII-H1stem were injected every other day i.p. with 200 μg of purified anti-CD4  and anti-CD8 , or control mAbs (SRF8-B6 and Y13-238). On day 14, mice were challenged with PR8 and monitored for weight loss. In order to assess the degree of depletion, spleens were harvested at termination and stained for FACS analysis with the following mAbs: Pacific Blue-conjugated rat anti-mouse CD8a , PE-conjugated rat anti-mouse CD3ε , and PerCP/Cy5.5-conjugated rat anti-mouse CD4 . In addition, the following isotype-matched control mAbs were used: Pacific Blue-conjugated rat IgG2aκ  and PerCP/Cy5.5-conjugated rat IgG2bκ .Splenocytes collected from vaccinated mice were fused with mouse plasmacytoma cells (OURI) using polyethylene glycol  as previously described . After fCells of 3-H7 see  and isotStatistical analyses of antibody responses in sera were performed using two-way ANOVA and Bonferroni's multiple comparison test. All other analyses were performed using the non-parametric Mann–Whitney test (GraphPad Software Inc.). The alpha level was set to 0.05 for all analyses.H3 exons of human IgG3, to a targeting unit consisting of a single-chain variable fragment (scFv) specific for mouse MHC class II molecules (I-Ed) (The stem regions of HA from influenza virus A/PuertoRico/8/1934 (H1N1) (PR8)  were joined by a linker that separated a conserved disulfide bridge in the stem region by four glycines (KLCGGGGCNTK), as previously described  Figure . Next, ts (I-Ed)  19, 20)H3 exons The constructs were inserted into pUMVC vectors , and theBALB/c mice were injected twice intramuscularly (i.m.) with vaccine plasmids encoding stem HA, or a positive control encoding full-length HA from influenza PR8 (αMHCII-HA) . ImmediaIn order to test the cross-reactive potentials of the vaccine-induced antibodies, sera were assayed against recombinant HA proteins from H3, H5, H7, and H9  influenzFollowing two immunizations with a 3 week interval, mice were challenged 4 weeks later with influenza PR8 virus. Disease progression was monitored by weight changes relative to the day of infection (day 0) . While aTo get a more clear picture of the protective mechanisms triggered by the different vaccines, sera were collected 4 days after viral challenge and analyzed for antibody responses against recombinant HA proteins from influenza H1, H3, H5, H7, and H9 . Results+ and CD8+ T cells or isotype-matched control antibodies, indicating a contribution of the vaccine induced antibodies to protection.In order to examine if the increased antibody responses observed after vaccination and viral challenge with αMHCII-H1stem could indeed contribute to the observed protection, experiments were set up to examine antibody functionality in the absence of T cell responses. In a first experiment, mice were vaccinated as above and then treated with T cell-depleting antibodies every second day from 2 days prior to a viral challenge with influenza PR8 . No signTo more directly test the influence of antibodies, B cell hybridomas were obtained from mice vaccinated twice with αMHCII-H1stem. The cell lines were screened for the presence of antibodies against HA from influenza viruses H1, H5, and H7, and also against the HA stem domain and ovalbumin . A candiWe have previously demonstrated that selective targeting of antigens to different receptors on APC can polarize immune responses to different types . As an eMice were immunized with DNA twice with a 4 week interval, and antibody responses were assayed againt influenza viruses H1, H5, H3, and H7 in ELISA . As expeAs described above, the immune responses and protection induced by vaccinations with either αMHCII-H1stem or MIP1α-H1stem were limited to efficacy against subtypes of group 1 influenza viruses. In order to develop a vaccine capable also of mediating protection against group 2 influenza viruses, fragments encoding the stem regions of HA from influenza A/Shanghai/2/2013 (H7N9) (aa 19–61 and 289–535) were inserted into the MHCII-targeted vaccine format (αMHCII-H7stem). Assessments of supernatants from 293E cells transiently transfected with the new vaccine construct demonstrated a secretion level similar to that of αMHCII-H1stem .Mice were immunized with a total of 200 μg of DNA plasmids encoding either αMHCII-H7stem, αMHCII-H1stem, or both (αMHCII-H1stem/H7stem), and antibody responses were assayed against recombinant HA proteins from H1, H3, H5, H7, and H9 influenza viruses . As expeMice were vaccinated twice with a 4 week interval and challenged with a lethal dose of influenza A/turkey/Italy/3889/1999 (H7N1). Weight was assessed as a marker of disease . As expeH1-69 . An analysis of antibody responses in sera against HA from H1, H3, H5, H7, and H9 influenza viruses demonstrated that while αMHCII-H1stem induced antibodies against the group 1 influenza subtypes H1, H5, and H9, αMHCII-H7stem induced antibodies against H3  and H7  and H7 . Vaccina) and H7 , as was ) and H7 .At week 4 after vaccination, mice were challenged with influenza PR8 virus and monitored for weight loss . ImportaFor the above experiments, we have used the stem-encoding DNA vaccines for both prime and boost vaccinations. Previously, we have demonstrated that vaccination with a mixture of full-length HAs from six different subtypes of influenza  could induce broadly reactive protective antibodies against HA from an influenza subtype that was not included in the vaccine mixture . Thus, wCR9114 knock-in mice were immunized either twice with αMHCII-H1stem/H7stem or αNIP-H1stem/H7stem or vaccinated once with the stem-encoding DNA vaccines followed by a boost with either αMHCII-MIX or αNIP-MIX. Interestingly, the antibody responses elicited by two deliveries of αMHCII-H1stem/H7stem were similar to the levels induced after a boost with αMHCII-MIX, and the only significant difference in antibody induction was the increased levels of IgG2a that were observed against HA from influenza H1 . While MAt day 70 after the boost, mice were challenged with influenza PR8 virus and monitored for weight  and survGiven the potential of stem-directed mAbs to mediate cross-protection against a multitude of influenza strains, such antibodies are currently popular for clinical applications . We haveWe here demonstrated that vaccination with αMHCII-H1stem significantly increased the induced levels of cross-reactive antibodies, as compared to the non-targeted control, αNIP-H1stem. These two constructs are similar in size, structure, and antigenic content. The observed difference in immunogenicity could thus be explained by the increased efficacy typically associated with APC targeting –38. HowePreviously, we demonstrated that a single DNA vaccination with MHCII-targeted HA could confer sterilizing immunity against a homologous strain of influenza virus . In the The first stem-specific antibody was isolated from BALB/c mice immunized with H2N2 influenza virus in 1993 . Since t+ helper T cells , and the Institutional Animal Care and Use Committee at The Scripps Research Institute.GG, BB, and DN conceived and designed experiments. GG, MB-H, JA, TB, and JT performed experiments. GG, MB-H, and BB analyzed the experiments and wrote the paper. All authors commented and edited on the paper.BB is an inventor on patent applications filed on the vaccine molecules by the TTO offices of the University of Oslo and Oslo University Hospital, according to institutional rules. BB is head of the Scientific panel of Vaccibody AS, and holds shares in the company. The remaining 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.