Epigenetic abnormalities play important roles in nasopharyngeal cancer (NPC), however, the epigenetic changes associated with abnormal cell proliferation remain unclear.ZNF671 in NPC tissues and cell lines by bisulfite pyrosequencing. We evaluated zinc finger protein 671 (ZNF671) expression in NPC cell lines and clinical tissues using real-time PCR and western blotting. Then, we established NPC cell lines that stably overexpressed ZNF671 and knocked down ZNF671 expression to explore its function in NPC in vitro and in vivo. Additionally, we investigated the potential mechanism of ZNF671 by identifying the mitotic spindle and G2/M checkpoint pathways pathway downstream genes using gene set enrichment analysis, flow cytometry and western blotting.We detected epigenetic change of ZNF671 was hypermethylated in NPC tissues and cell lines. The mRNA and protein expression of ZNF671 was down-regulated in NPC tissues and cell lines and the mRNA expression could be upregulated after the demethylation agent 5-aza-2′-deoxycytidine treatment. Overexpression of ZNF671 suppressed NPC cell proliferation and colony formation in vitro; silencing ZNF671 using a siRNA had the opposite effects. Additionally, overexpression of ZNF671 reduced the tumorigenicity of NPC cells in xenograft model in vivo. The mechanism study determined that overexpressing ZNF671 induced S phase arrest in NPC cells by upregulating p21 and downregulating cyclin D1 and c-myc.Epigenetic mediated zinc finger protein 671 downregulation promotes cell proliferation and enhances tumorigenicity by inhibiting cell cycle arrest in NPC, which may represent a novel potential therapeutic target.The online version of this article (10.1186/s13046-017-0621-2) contains supplementary material, which is available to authorized users. Nasopharyngeal carcinoma (NPC) is the most common head and neck cancer in Southern China and Southeast Asia . AlthougUncontrolled proliferation is a pathological characteristic of cancer cells. Protein kinase complexes composed of cyclins and cyclin-dependent kinases (CDKs) determine the progression of cells through the cell cycle. Cyclins function as the regulatory subunit and CDKs function as the catalytic subunit of the activated heterodimer complexes, which orchestrate coordinated entry into the S phase of the cell cycle . DysreguZNF671), which contains C2H2-type zinc fingers (ZFs) and a Krüppel associated box (KRAB) domain, is a member of the KRAB-ZFP family of mammalian transcriptional repressors [ZNF671 is epigenetically silenced by DNA methylation and functions as a tumor suppressor in multiple carcinomas [ZNF671 in NPC.DNA methylation is a critical epigenetic modification involved in regulation of gene expression . Dysregupressors , 13 thatpressors , 15. Recrcinomas –18. HoweZNF671 is downregulated and the ZNF671 promoter is hypermethylated in NPC cell lines and tissues. Overexpression of ZNF671 suppressed, while silencing ZNF671 promoted, NPC cell proliferation and colony formation in vitro and tumorigenicity in vivo. Further studies demonstrated overexpression of ZNF671 inhibited NPC cell proliferation and tumorigenicity by inducing S phase cell cycle arrest.Here, we report that Human NPC cell lines  were cultured in RPMI-1640  supplemented with 5% fetal bovine serum (FBS) . Human immortalized nasopharyngeal epithelial cell line  were cultured in keratinocyte serum-free medium (Invitrogen) supplemented with bovine pituitary extract . 293 T cells were obtained from the ATCC  and maintained in DMEM (Invitrogen) supplemented with 10% FBS. Four freshly frozen NPC samples and four normal nasopharyngeal epithelium samples were collected from patients undergoing biopsy at Sun Yat-sen University Cancer Center.ZNF671 forward, 5′- GACTTAGACCTGGTTGTTGG -3′ and reverse, 5′- GTATTTAGCCAGGTGTAAGGT-3′. GAPDH was used as control for normalization.Total RNA was isolated from NPC cell lines using TRIzol Reagent (Invitrogen) following the manufacturer’s instructions, cDNA was synthesized using M-MLV reverse transcriptase  and amplified with Platinum SYBR Green qPCR SuperMix-UDG reagents (Invitrogen) using the CFX96 sequence detection system  with the following primers: ZNF671 , anti-cyclin D1 , anti-c-myc  or anti-p21  antibodies overnight at 4 °C, followed by species-matched secondary antibodies. Bands were detected using enhanced chemiluminescence.RIPA lysis buffer  was used to isolate proteins and the Bradford method, to determine protein concentrations. Proteins (20 μg) were separated by SDS-polyacrylamide gel electrophoresis , transferred onto PVDF membranes  and incubated with primary anti-NPC cell lines were treated with or without 10 μmol/L 5-aza-2′-deoxycytidine  for 72 h, with the drug/media replaced every 24 h. DNA was isolated using the EZ1 DNA Tissue Kit , then 1–2 μg DNA was treated with sodium bisulfite using the EpiTect Bisulfite kit (Qiagen) according to the manufacturer’s instructions. Bisulfite pyrosequencing primers were designed using PyroMark Assay Design Software 2.0 (Qiagen), and were: PCR forward primer: 5′-GAATTTAGGTTAGGGATAGTTTGAT-3′ (F); PCR reverse primer: 5′-CCAAAAAAAAAATATTTCAATACC-3′ (R); sequencing primer: 5′-GG ATAGTTTGA TAGAAATAAAATG-3′(S). The PyroMark Q96 System (Qiagen) was used for the sequencing reactions and to quantify methylation.ZNF671-HA or pSin-EF2-puro-vector plasmids were obtained from Land. Hua Gene Biosciences ; pSin-EF2-puro-Vector plasmid was used as a control. Stably transfected cells were selected using puromycin and confirmed using RT-PCR. SiRNAs targeting ZNF671 were obtained from GenePharma Co., Ltd. ; siRNA #1 targets ZNF671-Homo-626 cDNA  and siRNA #2 targets ZNF671-Homo-279 cDNA .The pSin-EF2-puro-3) were seeded into 96-well plates, incubated for 0–4 days, stained with CCK-8 , and absorbance values were determined at 450 nm using a spectrophotometer. For the colony formation assay, cells (0.3 × 103) were seeded into 6-well plates, cultured for 2 weeks and the colonies were fixed in methanol, stained with crystal violet and counted.For the CCK-8 assay, cells (1 × 105) were seeded into 6-well plates, cultured for 24 h, serum-starved for 24 h to synchronize cells at the G1/S checkpoint, trypsinized, washed with ice-cold PBS, fixed in 70% ethanol, and stored at −20 °C until analysis. Before staining, cells were gently resuspended in cold PBS and RNase A was added into cell suspension tube incubated at 37 °C for 30 min, followed by incubation with propidium iodide (PI) (Beyotime) for 20 min at room temperature. The fluorescence intensity of the cells was analyzed by flow cytometry .Cells (2 × 10ZNF671 cells (1 × 106) were subcutaneously inoculated into the dorsal flank. Tumor size was measured every 3 days and tumor volumes were calculated using the equation: volume = D × d2 × π/6, where D and d represent the longest and shortest diameters, respectively. All animal research was conducted in accordance with the detailed rules approved by the Animal Care and Use Ethnic Committee of Sun Yat-sen University Cancer Center and all efforts were made to minimize animal suffering.BALB/c-nu mice (4–6 weeks old) were purchased from Charles River Laboratories , and CNE2-vector or CNE2-www.broadinstitute.org/gsea/) was used to identify KEGG pathways  that show an overrepresentation of up- or downregulated genes between ZNF671 high expression (n = 15) and ZNF671 low expression (n = 16) in GSE12452. Briefly, an enrichment score was calculated for each gene set  by ranking each gene by their expression difference using Kolmogorov-Smirnov statistic, computing a cumulative sum of each ranked in each gene set, and recording the maximum deviation from zero as the enrichment score.The GSEA software tool .Statistical analyses were performed using SPSS 17.0 . All data shown are representative of at least three independent experiments, and values are expressed as the mean ± SD. Differences between two groups were analyzed using the two-tailed unpaired Student’s ZNF671 was detected by bisulfite pyrosequencing analysis in other NPC (n = 8) and normal tissues (n = 8). The CpG islands and region selected for bisulfite pyrosequencing in the ZNF671 promoter region are shown in Fig. ZNF671 (cg11977686) in NPC tissues were significantly increased compared with normal tissues  methylation levels in the NPC cell lines  were also increased compared with human immortalized normal nasopharyngeal epithelial cell line (NP69) . These results indicate that ZNF671 promoter is hypermethylated in NPC.To confirm our previous methylation data (GSE52068) . Furthermore, western blotting showed ZNF671 protein expression was downregulated in both the NPC cell lines and freshly frozen NPC tissues (n = 4) compared to normal samples (n = 4) . To determine whether the downregulation of ZNF671 results from its promoter hypermethylation, immortalized normal nasopharyngeal epithelial cell line and NPC cell lines were treated with or without the demethylation drug 5-aza-2′-deoxycytidine . The ZNF671 methylation level were substantially decreased , while the ZNF671 mRNA were significantly increased  in NPC cell lines compared with immortalized normal nasopharyngeal epithelial cell. The findings suggest that ZNF671 is downregulated in NPC and the downregulation of ZNF671 is associated with the hypermethylation of ZNF671 in NPC.To know the association between lls Fig. . AnalysiZNF671 on proliferation and metastasis in NPC, we subjected CNE2 and 5-8F cells stably overexpressing ZNF671 or the control vector to the CCK8, colony formation and Transwell migration and invasion assays. As shown in Fig. ZNF671 mRNA and protein level was obviously elevated after stably overexpressing ZNF671 in NPC cells. The CCK8 assay demonstrated that the cell viability of CNE2 and 5-8F cells stably overexpressing ZNF671 remarkably was much slower than that of cells expressing vector plasmid  in the GEO database to identify pathways potentially linked to ZNF671. As shown in Fig. ZNF671-high expressing tumors; conversely, these pathways were not enriched in ZNF671-low expressing tumors.To further investigate the mechanism by which ZNF671 significantly decreased the percentage of cells in the G2/M phase  and increased the proportion of cells in the S phase . Furthermore, bioinformatics analysis indicated that ZNF671 is involved in regulation of the cycle-related proteins cyclin D1 and p21. Overexpression of ZNF671 decreased the protein levels of cyclin D1 and c-myc, and increased p21  Methylation levels of ZNF671 in Normal (n = 24) and NPC (n = 24) tissues from the genome-wide methylation microarray data. Mean ± ± SD; Student’s t-tests. (B) Bisulfite pyrosequencing analysis of the ZNF671 promoter region in NP69 and NPC  cell lines. Red words: CG site of cg11977686. *P < 0.05, **P < 0.01 vs. control, Student’s t-test. (TIFF 831 kb)Additional file 2: Figure S2.ZNF671 is hypermethylated in NPC cells. Bisulfite pyrosequencing analysis of the ZNF671 promoter region in NP69 and NPC  cell lines following treatment with DAC. Red words: CG site of cg11977686. *P < 0.05, **P < 0.01 vs. control, Student’s t-test. (TIFF 861 kb)Additional file 3: Figure S3.ZNF671 has no effect on affect NPC migratory and invasive ability. (A) Migration ability was measured using a wound healing assay (200 ×) and (B) Transwell assay with Matrigel (200 ×) in CNE2 and SUNE1 cells with the vector or ZNF671 overexpression. Scale bar: 100 μm; data are mean ± SD. *P < 0.05, **P < 0.01 vs. control, Student’s t-test. (TIFF 1066 kb)


No standard of care is established for plasmablastic lymphoma (PBL) and prognosis remains extremely poor, given that patients relapse early after chemotherapy and display resistance to commonly applied cytostatic drugs.We report a case of nodal, HIV-unrelated PBL in a patient who achieved and maintained a very long lasting complete remission after an intensive therapy consisting consisting of thalidomide plus dexamethasone followed by a consolidation with double autologous stem cell transplantation. Our approach was based on the full application of a standard multiple myeloma treatment and, to the best of our knowledge, it represents the only reported experience so far. This treatment was overall well tolerated.Multiple myeloma-like treatment may represent a possible alternative to intensive lymphoma-directed therapies. Plasmablastic lymphoma (PBL) is a rare and highly aggressive subtype of diffuse large B-cell lymphoma, characterized by diffuse proliferation of large neoplastic cells which resemble B-cell immunoblasts but have a plasma cell immunophenotype . No stanA 46-year old Italian female presented in June 2007 with 3 enlarged lymph nodes in her left groin without any systemic symptoms. She had no significant comorbidities and no underlying immunosuppression. An excisional biopsy showed diffuse proliferation of large lymphoid cells with several interspersed macrophages, which imparted a “starry-sky” appearance to the infiltrate Fig. . ImmunohOn admission, laboratory data were the following: white blood cells 9500/μL, hemoglobin 12.5 g/dL, platelets 313,000/μL; lactate dehydrogenase, calcium, serum proteins and immunoglobulin levels were all within normal ranges; protein electrophoresis and immunofixation showed no monoclonal component. Serology for human immunodeficiency virus (HIV) was negative.From July to September 2007, the patient received 3 cycles of thalidomide and dexamethasone: thalidomide was given at the dose of 100 mg/day and dexamethasone at the dose of 40 mg/day on days 1–4 and 9–12 of each cycle. The rationale for the use of thalidomide in PBL relied upon the notion that increased angiogenesis plays a major role in aggressive lymphomas, as well as in MM [2) and granulocyte-colony stimulating factor (G-CSF): 7.2 × 106 CD34+/kg were harvested after a single apheresis. Following this procedure, the patient went back on thalidomide-dexamethasone for 3 more months, then she underwent an autologous stem cell transplantation (ASCT), conditioned with melphalan, 200 mg/m2. 2.5 × 106 CD34+/kg PBSC were reinfused. The PET scan performed one month after ASCT confirmed a CR. In light of the good response achieved so far, it was decided to proceed with a second ASCT. The patient again received thalidomide-dexamethasone for 3 months, then 2.5 × 106 CD34+/kg PBSC were reinfused 2 days after melphalan conditioning. A CR was clinically and metabolically confirmed by PET scan after the second ASCT. The patient is now healthy and in durable CR after at least 10 years.Afterwards, the patient received maintenance therapy with thalidomide for 2 months, followed by peripheral blood stem cell (PBSC) mobilization achieved by the administration of high dose cyclophosphamide  and has been performed in accordance with the ethical standards of the Declaration of Helsinki. Patient provided a written informed consent to publish her data.PBL is a highly aggressive lymphoma strongly associated with immunosuppression, in particular with HIV infection . NeverthMYC occur in up to 47% of HIV-related PBL cases and end up with overcoming the regulatory effects of its repressors Bcl-6 and BLIMP-1, thus allowing cells to proliferate without control. Moreover, MYC translocations are thought to contribute to the plasmablastic morphology and to a worse prognosis [The pathogenesis of PBL is currently unclear. The neoplastic cell derives from a post-germinal centre activated B-cell that has already undergone somatic hypermutation and class switching recombination and is in the process of becoming a plasma cell . Mutatiorognosis . The HIVMaking a diagnosis of PBL is always challenging: the immunophenotype resembles that of plasma cell neoplasms, as PBL cells typically lack expression of B-cell markers  and show little to no expression of leukocyte common antigen CD45, whereas the plasma cell markers CD79a, IRF4/MUM-1, BLIMP-1, CD38 and CD138 are usually highly expressed. The proliferation rate is generally high, with Ki-67 expression higher than 60% [Given its rarity and peculiar features, no standard of care can be established for PBL patients, whose prognosis remains very poor. Early relapses and subsequent chemotherapy resistance characterize the clinical course of the disease. A large literature review of 248 cases of PBL, 50% of which had received cyclophosphamide, doxorubicin, vincristine, prednisone (CHOP) or CHOP-like regimens, while 23% had been treated with more intensive regimens, such etoposide, vincristine, doxorubicin, cyclophosphamide, prednisone (EPOCH), hyperfractionated cyclophosphamide, vincristine, doxorubicin, dexamethasone (hyper-CVAD) and cyclophosphamide, vincristine, doxorubicin, methotrexate alternating with ifosfamide, etoposide, cytarabine (CODOX-M/IVAC), showed an overall response rate to chemotherapy of 77%, with 46% of patients achieving a CR and 31% a partial response [On the basis of the plasmacytic differentiation of this lymphoma, given that a plasmablast is an activated B-cell undergoing the process of becoming a plasma cell, PBL is ontogenetically collocated between an aggressive post-germinal centre B-cell non-Hodgkin lymphoma and MM. For this reason, the use of antimyeloma agents – like bortezomib, thalidomide or lenalidomide - may have a sound rationale, although the experience with these agents is rather limited. More specifically, they have been predominantly combined with more standard lymphoma-directed regimens, such as CHOP or EPOCH –15, rath


NF1 gene deficiency leads to Ras hyperactivation causing the subsequent activation of the AKT/mTOR and Raf/MEK/ERK pathways and inducing multiple cellular responses including cell proliferation. In this study, three NF1-null MPNST-derived cell lines , STS26T sporadic MPNST cell line and PNF-derived primary Schwann cells were used to test responses to AZD8055, an ATP-competitive “active-site” mTOR inhibitor. In contrast to rapamycin treatment which only partially affected mTORC1 signaling, AZD8055 induced a strong inhibition of mTORC1 and mTORC2 signaling in MPNST-derived cell lines and PNF-derived Schwann cells. AZD8055 induced full blockade of mTORC1 leading to an efficient decrease of global protein synthesis. A higher cytotoxic effect was observed with AZD8055 compared to rapamycin in the NF1-null MPNST-derived cell lines with IC50 ranging from 70 to 140 nM and antiproliferative effect was confirmed in PNF-derived Schwann cells. Cell migration was impaired by AZD8055 treatment and cell cycle analysis showed a G0/G1 arrest. Combined effects of AZD8055 and PD0325901 MEK inhibitor as well as BRD4 (BromoDomain-containing protein 4) inhibitors showed a synergistic antiproliferative effect. These data suggest that NF1-associated peripheral nerve sheath tumors are an ideal target for AZD8055 as a single molecule or in combined therapies.Approximately 30-50% of individuals with Neurofibromatosis type 1 develop benign peripheral nerve sheath tumors, called plexiform neurofibromas (PNFs). PNFs can undergo malignant transformation to highly metastatic malignant peripheral nerve sheath tumors (MPNSTs) in 5-10% of NF1 patients, with poor prognosis. No effective systemic therapy is currently available for unresectable tumors. In tumors, the  Neurofibromatosis type 1  is an autosomal disorder with a worldwide birth incidence of one in 2500. Approximately 30-50% of individuals with NF1 develop benign peripheral nerve sheath tumors, called plexiform neurofibromas (PNFs) that are usually congenital or appear in early childhood . PNFs caNeurofibromin 1 (NF1) encoding neurofibromin, a negative regulator of RAS (rat sarcoma) proteins. NF1 loss of heterozygosity was found in Schwann cells isolated from PNFs and MPNSTs .–18.NF1 lCDKN2A/B .NF1 locus were found in DNAs from 3/8 of the PNF-derived primary Schwann cells: PNF1, PNF2, and PNF8  or rapamycin (10nM) respectively in 90.8 cell lines, and a decrease of 82% vs 12% when using AZD8055 (100nM) or rapamycin (10nM) respectively in STS26T cell lines . This inhibition correlates to the concentration of AZD8055 required to fully inhibit the phosphorylation of 4E-BP1 on S65 in all cell lines tested . In contrast, cell cycle progression was impaired. After 24h of treatment, AZD8055 significantly inhibited MPNST-derived cell lines proliferation PD901 = 3.7±0.8μM and IC50PD901 = 6.8±2.3μM, respectively) whereas STS26T and 90-8 were not sensitive . To a lesser extent, 96-2 cell line was also sensitive to JQ1 (IC50JQ1 = 66±22μM). In contrast, 88-14 and STS26T cell lines were JQ1-resistant  and, to a lesser extent, 88-14 and 96-2 cell lines were also . In contrast, STS26T was OTX015-resistant  and, to a lesser extent, 96-2 and 88-14 cell lines were also (IC50I-BET-762 = 66±32μM and IC50I-BET-762 = 95±10μM respectively). In contrast, STS26T was I-BET-762-resistant . PNF3 derived primary Schwann cells did not response to JQ1 (not shown). Due to little or no response of PNF-derived primary Schwann cells to JQ1, IC50 were only assessed with JQ1 BET bromodomain inhibitor.Dose-response analyzes after 48 hours of continuous exposure of the three JQ1, OTX015, I-BET-762/GSK525762 BET bromodomain inhibitors were performed in STS26T, 90-8, 88-14, and 96-2 MPNST-derived cell lines. 90-8 cell line was sensitive to JQ1  supporting the relevance of combined mTOR kinase inhibitor AZD8055 and BET bromodomain inhibitors therapies. To a lesser extent, 96-2 cell line was also sensitive to BET bromodomain inhibitors and we confirmed the synergistic effect of AZD8055 combined to BET bromodomain inhibitors on this second cell line  showed antitumor activity on MPNST cell lines in vitro. mTOR inhibitors have been both characterized as leading to cell cycle arrest by suppressing cyclin D1 expression, inducing apoptosis, and inhibiting cell proliferation and angiogenesis, and shown to repress cell motility and invasion  Leucine assay. Cells were incubated for 2h at 105 cells/mL in a low leucine medium  then labelled for 1h with [3H] leucine . The amount of radioactivity incorporated into proteins was determined by trichloroacetic acid precipitation.The global protein synthesis was assessed by [Hp < 0.05, p < 0.01, p < 0.001 respectively.Data were expressed as mean values and SD. Statistical significance of differences observed between experimental groups was determined using Student's t test. *, **, *** mean


Plasmablastic lymphoma (PBL) is a rare, highly aggressive subtype of non-Hodgkin lymphoma with plasma-cell differentiation occurring typically in immune-suppressed patients such as those with AIDS. This study reports the establishment and characterization of a new cell line, PBL-1, derived from a patient with AIDS-associated PBL. Morphological assessment of PBL-1 indicated plasma-cell differentiation with a CD20(−) CD38(+) CD138(+) immunophenotype and IgH/c-myc translocation. The cell line harbours Epstein-Barr virus, but a 52.7-kbp length defect was identified in its genome, resulting in no expression of viral microRNAs encoded in the BamHI-A Rightward Transcript region. Importantly, supplementation of culture medium with >5 ng/mL of interleukin-6 (IL-6) was required for PBL-1 growth. Starvation of IL-6 or addition of tocilizumab, an inhibitory antibody for the IL-6 receptor, induced apoptosis of PBL-1. Transduction of IL-6 into PBL-1 by lentivirus vector induced autologous growth without IL-6 supplementation of culture medium. These data indicate the IL-6 dependency of PBL-1 for proliferation and survival. mTOR inhibitors induced cell death effectively, suggesting mTOR in the IL-6 signalling pathway is a potential therapeutic target for PBL. This established PBL cell line will be a useful tool to further understand the pathophysiology of PBL and aid the future development of PBL treatment. The incidence of PBL has been estimated as 2–8% of all cases of AIDS-related lymphomas4. Histologically, PBL cells have a large, round-to-irregular nucleus with a prominent nucleoli and perinuclear halo, as well as a variable amount of cytoplasm that is deeply basophilic2. PBL cells do not express an immunophenotype typical for B-cell  or T-cell  markers. Instead, several markers of lymphocyte activation  and plasma-cell differentiation  are usually detected.Plasmablastic lymphoma (PBL) is a rare distinct clinicopathological entity of large B-cell malignant lymphoma, occurring typically in HIV-1 infected or other immunodeficient patients and is generally associated with Epstein–Barr virus (EBV) infection6, suggesting it might play an important role in the tumorigenesis of PBL. EBV is a member of the oncogenic human gamma-herpesvirus family, and has been detected in Hodgkin lymphoma, Burkitt lymphoma, nasopharyngeal carcinoma, post-transplantation lymphoproliferative disorder, and gastric cancer. Approximately 40% of AIDS-related lymphoma cases are positive for EBV7. In PBL cases, EBV has been detected as Latency I, expressing EBV-encoded small RNAs (EBERs) and EBV-encoded nuclear antigen 1 (EBNA-1). Although integration of EBV in the host chromosome was observed in several cell lines established from EBV-associated lymphoma with persistent infection13, there has been no report of an EBV integrated case of PBL.EBV has been detected in 66–74% of PBL cases14. Currently, a combination of antiretroviral therapy16 with a CHOP -like regimen or more aggressive regimen including CODOX-M/IVAC , dose-adjusted EPOCH , or HyperCVAD  are considered first-line therapies18. Recently, cases treated with chemotherapy in combination with bortezomib, a proteasome inhibitor, have been reported24.The prognosis of PBL is very poor, and a standard therapy for PBL has not been establishedImmortalized cell lines are useful tools to investigate disease pathogenesis and to evaluate the effects of therapeutic agents. To the best of our knowledge, there has been no report describing a well-characterized PBL cell line established from typical PBL cases. In this study, we established a PBL cell line from a case of AIDS-associated PBL, and demonstrated its interleukin 6 (IL-6)-dependent growth. In addition, the treatment effect of therapeutic agents was investigated.2. After several passages, autologous growth was observed. However, when the ascites was removed from the culture medium, the cells did not grow and became apoptotic. Therefore, we speculated that certain growth factor(s) were required for cell growth. Cytokines in the patient’s ascites and the supplemented cultured medium were analysed by Luminex. A high amount of IL-6 was detected in the ascites , 10 ng/mL insulin, and 10 ng/mL of transferrin at 37 °C with 5% COIn situ hybridization demonstrated that PBL-1 were positive for EBER-1  with a triple colour-dual fusion probe of IgH and c-myc revealed that PBL-1 had an IgH/c-myc rearrangement , whereas there were no bcl-2 or bcl-6 gene splits (data not shown). PCR and sequence analysis identified a break point in the IgH/c-myc rearrangement that was upstream of exon 1 of c-myc and downstream of the IgH regulatory region , LMP-2A, and LMP-2B mRNA, indicating that the EBV status in PBL-1 was Latency I   3 pathway28. Flow cytometry analysis revealed the expression of gp80 and gp130 in PBL-1  Fig. . The XTTmL) Fig. . WesternmL) Fig. . Flow cymL) Fig. , and BrdmL) Fig. . IL-6 bi26. To verify the effect of IL-6 on STAT3 in PBL-1, we performed western blotting in the presence or absence of IL-6. While p-STAT3 was abundant in total cell lysates of PBL-1 in the presence of IL-6 (5 ng/mL), the dephosphorylation of p-STAT3 was induced within 1 h after the starvation of IL-6  and p70S6K and the dephosphorylation of 4E-BP-1, which are factors downstream of the mTOR pathway  inhibitors. The XTT assay showed that these drugs also inhibited the mitochondrial metabolic activity of PBL-1 in a dose-dependent manner  method. The combination of bortezomib and tocilizumab  MUM-1 (+) and CD20 (−), as reflected in PBL. The immunophenotype of PBL is similar to that of multiple myeloma except for those with EBV infection32. The established cell line, PBL-1, had an immunophenotype typical of plasmablasts, with morphological features that resembled plasmacytic tumours. To the best of our knowledge, there have been two previous reports of the establishment and characterization of cell lines from this distinct tumour34, and one report of a xenograft model of EBV-negative-PBL35. A study of two EBV-positive cell lines, SPIBL-II and III, established by Friis et al. did not report the immunophenotype or culture method used including IL-6-dependency33. The SPIBL-II and III cell lines were established from the pleural effusion of an HIV-positive case of plasmablastic lymphoma. Considering that PBL occurred in the ascites as an effusion lymphoma in our case, such an effusion form of PBL that is very rare might contribute to the establishment of a cell line. Another two PBL cell lines, KY-1 and KY-2, reported by Matsuki et al. were established from a immunocompetent patient without HIV infection, and were CD20 (−), CD138 (+), VS38c (+), EMA (+), but CD38 (−) and EBV (−)34. IL-6-dependency in the culture medium was not described for these reported cell lines, although IL-6 might be associated with the establishment of these cell lines in a xenograft model35.The cell origin of PBL is thought to be the plasmablast27. Starvation of IL-6 in PBL-1 led to the dephosphorylation of p-STAT3 and the phosphorylation of Akt, PDK1, and p70 within 1 h; however, p-Akt, p-PDK1, and p-p70 were dephosphorylated within 24 h  were effective at inducing apoptosis in PBL-1. Everolimus, an mTOR inhibitor, is an immunosuppressive drug used for the treatment of breast cancer, neuroendocrine tumours, and kidney cancer; however, there has been no report on the therapeutic use of everolimus for PBL. Inhibitors of the mTOR pathway such as everolimus or rapamycin were more effective on PBL-1 than inhibitors to other factors downstream of IL-6 signalling such as the Jak/Stat pathway. This suggests that mTOR-associated factors play an important role in the IL-6 signalling pathway in PBL-1, and that IL-6 signalling pathways, especially mTOR, are a potential therapeutic target for PBL. Furthermore, in this study, bortezomib, a proteasome inhibitor used for the therapy of multiple myeloma, also exhibited a cytotoxic effect on PBL-1. This finding may indicate that PBL-1 has similar pharmacological responses to multiple myeloma. A combination of HDAC and proteasome inhibitors enhanced apoptosis in some lymphomas, multiple myeloma, EBV-associated tumours and cell linesin situ hybridization. These results led to a diagnosis of AIDS-related PBL. Six courses of CHOP chemotherapy induced a remission, but the patient eventually succumbed to the recurrence of disease.A 60-year-old Japanese male patient with HIV-1 infection was admitted with fever, weight loss, and ascites. His blood CD4 (+) cell counts were 316/μL. Flow cytometry analysis indicated the presence of CD19 (−), CD20 (−), CD38 (+) cells in the ascites. Positron emission transfer imaging revealed a large tumour in the transversus colon, and its biopsied specimen showed the infiltration of tumour cells similar to those in the ascites. Tumour cells were CD19 (−), CD20 (−), CD79a (−), CD38 (+), CD138 (+), CD30 (−), EBV- LMP-1 (−), EBV-EBNA-2 (−), KSHV-latency-associated nuclear antigen 1 (−), CD3 (−) CD5 (−), CD10 (−), BCL6 (−), MUM1 (+), and >95% Ki67 (MIB-1) (+) by immunohistochemistry, and EBER-1 (+) by 2. Supplementation of insulin and transferrin was gradually reduced during passages. Finally, cells were grown in RPMI 1640 with 5 ng/mL of IL-6  and 10% FBS. Single cell cloning was performed using a limiting dilution method in IL-6 containing medium. For the IL-6 starvation study, cells were centrifuged, washed twice with phosphate buffered saline (PBS), and cultured in RPMI 1640 supplemented with 10% FBS without IL-6. EBV-positive human cell lines (Raji and LCL), B95.8, an EBV-positive marmoset cell line, and EBV-negative cell lines  were cultured in RPMI 1640 medium with 10% FBS. Cells were stained with trypan blue and cell viability was measured using a TC10 automated cell counter .To establish a new cell line, tumour cells were collected from the patient ascites and cultured in RPMI 1640 culture medium supplemented with 10% patient ascites, 10% FBS, 10 ng/mL of insulin , and 10 ng/mL of transferrin (Sigma-Aldrich) at 37 °C with 5% CO4 cells per spot. The samples were incubated with mouse monoclonal antibodies to CD20, CD38, CD138, and LMP-1 of EBV  diluted 1:100 with Block Ace  for 1 h at room temperature, followed by Alexa Fluor 488-conjugated goat anti-mouse IgG (H+L)  diluted 1:500 with PBS for 1 h at room temperature. Nuclear staining was performed with 1 μg/mL 4′,6-diamidino-2-phenylindole. Images were captured with a fluorescence microscope .Suspended cells were centrifuged onto glass slides via Cytospin  to form a single layer of 5 × 10PBL-1 cells were pelleted by centrifugation, fixed with 2.5% glutaraldehyde and 2% paraformaldehyde in 0.1 M phosphate buffer (pH 7.4) for 2 h at room temperature, post-fixed in 1% osmium tetroxide, and embedded in Epon. Ultrathin sections were stained with uranyl acetate and lead citrate, and observed under a transmission electron microscope  at 80 kV.54.RT-PCR to detect EBV latency–associated transcripts was performed as described previously5 cells/mL in RPMI 1640 medium containing 10% FBS in the presence or absence of 5 ng/mL IL-6 and/or applied drugs. After 48 h of culture, the XTT labelling mixture was added according to the manufacturer’s instructions. Colour development of formazan production was measured spectrophotometrically with Multiskan MS (LabSystems/Thermo Fisher Scientific) at 450 nm55. The cell proliferation ratio was calculated by the OD of a sample divided by the OD of the positive controls (IL-6-supplied PBL-1).The viability of PBL-1 cells was examined using a XTT (tetrazolium derivative) assay kit . Cells were cultured in 96-well plates in triplicate at a density of 2 × 1056. Briefly, 1 × 106 cells were lysed in 100 μL of M-PER lysis buffer containing Halt protease and phosphatase inhibitor cocktail . Cell lysates were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred onto a polyvinylidene fluoride microporous membrane  using the NuPAGE system . The membranes were blocked with Block Ace and probed with primary antibodies followed by horse radish peroxidase-conjugated anti-mouse or anti-rabbit antibodies  with an immunoreaction enhancer solution . Blots were visualized by Super-Signal West Femto Chemiluminescent Substrate (Thermo Fisher Scientific) and images were captured with a C-Digit Blot Scanner .Protein extraction and immunoblotting were performed as described previouslyAnti-IL6R antibody, tocilizumab (Actemra), was purchased from Chugai Pharmaceutical, Tokyo, Japan, and used at 48 ng–100 μg/mL. To identify drugs that inhibited PBL-1 cell proliferation, PBL-1 cells were cultured in RPMI 1640 with 10% FBS, 5 ng/mL of IL-6, and drugs from the InhibitorSelect 96-well Protein Kinase Inhibitor Library I, II, III  in a 96-well plate at two final concentrations (10 nM and 1 μM). We also added 7 HDAC inhibitors (HDAC inhibitor Set II: Sigma Aldrich) and other antitumour drugs to PBL-1 cells with 5 ng/mL of IL-6 and cultured them for 48 h.50. XTT assay was performed after 48 hr of culture. A constant combination ratio experiment for the 8 point assay was carried out, as the ratio of (IC50 of drug 1)/(IC50 of drug 2) was constant. The Chou–Talalay Combination index (CI) was calculated according to a study by Chou et al. using CompuSyn Version 1.0 software (http://www.combosyn.com/)57. A CI value of <1, = 1, or >1 indicates synergy, additivity, and antagonism, respectively.PBL-1 cells were cultured in RPMI 1640 with 10% FBS, 5 ng/mL of IL-6 and two drugs  each added as a 2-fold dilution series from 6.4 μg/mL (tocilizumab), 32 nM (bortezomib and panobinostat) or 1.6 nM (everolimus) to determine the ICAll results were expressed as the mean ± SD of data obtained in triplicate, from at least three individual experiments. All statistical analyses were performed with Excel software , and GraphPad Prism Version 6.0 software . P values < 0.05 were considered statistically significant.The study protocol was approved by the Institutional Review Board, National Institute of Infectious Diseases  and Tokyo Metropolitan Komagome Hospital . Informed consent was obtained from the patient with PBL. All methods were performed in accordance with the relevant guidelines and regulations.Further methods are provided in the supplemental Materials and Methods.The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.Supplementary information


Thevetia peruviana (Pers.) K. Schum or Cascabela peruviana (L.) Lippold , native to Mexico and Central America, is a medicinal plant used traditionally to cure diseases like ulcers, scabies, hemorrhoids and dissolve tumors. The purpose of this study was to evaluate the cytotoxic, antiproliferative and apoptotic activity of methanolic extract of T. peruviana fruits on human cancer cell lines.T. peruviana methanolic extract was carried out on human breast, colorectal, prostate and lung cancer cell lines and non-tumorigenic control cells (fibroblast and Vero), using the MTT assay. For proliferation and motility, clonogenic and wound-healing assays were performed. Morphological alterations were monitored by trypan blue exclusion, as well as DNA fragmentation and AO/EB double staining was performed to evaluate apoptosis. The extract was separated using flash chromatography, and the resulting fractions were evaluated on colorectal cancer cells for their cytotoxic activity. The active fractions were further analyzed through mass spectrometry.The cytotoxic activity of T. peruviana methanolic extract exhibited cytotoxic activity on four human cancer cell lines: prostate, breast, colorectal and lung, with values of IC50 1.91 ± 0.76, 5.78 ± 2.12, 6.30 ± 4.45 and 12.04 ± 3.43 μg/mL, respectively. The extract caused a significant reduction of cell motility and colony formation on all evaluated cancer cell lines. In addition, morphological examination displayed cell size reduction, membrane blebbing and detachment of cells, compared to non-treated cancer cell lines. The T. peruviana extract induced apoptotic cell death, which was confirmed by DNA fragmentation and AO/EB double staining. Fractions 4 and 5 showed the most effective cytotoxic activity and their MS analysis revealed the presence of the secondary metabolites: thevetiaflavone and cardiac glycosides.The T. peruviana extract has potential as natural anti-cancer product with critical effects in the proliferation, motility, and adhesion of human breast and colorectal cancer cells, and apoptosis induction in human prostate and lung cancer cell lines, with minimal effects on non-tumorigenic cell lines.The online version of this article (doi:10.1186/s12906-017-1727-y) contains supplementary material, which is available to authorized users. Cancer is one of the most important causes of death worldwide. In 2012, 8.2 million cancer-related deaths were reported and the number of new cases is expected to rise by about 70% over the next two decades . TherefoCatharanthus, Nerium, Strophanthus, Apocynum and Thevetia , and then, DNA was extracted. The nucleic acid concentration and purity were measured using a NanoDrop® ND-2000 spectrophotometer (Thermo Scientific). Equal amounts of DNA (10 μg/well) were electrophoresed in 1% agarose gel. DNA fragments were visualized using an UV transilluminator . Three independent experiments were performed.DNA fragmentation was carried out as described previously . Cells w5 cells were seeded in a 6-well plate. Cells were treated with T. peruviana fruit extract at the corresponding IC50 concentration for 4 h. Then cells were subjected to AO/EB staining as described previously [For the AO/EB method, 5 × 10eviously . Briefly18 column equilibrated at 40 °C and a flow rate set at 0.3 mL/min. The mobile phase consisted of 15% CH3CN–H2O (0.1% formic acid) for 0.5 min, and then a linear gradient from 15% CH3CN to 100% CH3CN over 6 min, and 1 min holding 100% CH3CN before returning to the starting conditions. Samples were dissolved in MS grade methanol and filtered through a 0.2 μm Acrodisc (Waters) filter. Tentative metabolite identification was performed by comparison of HRMS data, UV maxima and fragmentation patterns (MS/MS data) with those contained in the Dictionary of Natural Products [Thevetia plant metabolites.HRESIMS data were collected and in positive and negative ionization modes using a Thermo QExactive Plus mass spectrometer (ThermoFisher) equipped an electrospray ionization (ESI) source and via an Acquity UPLC system (Waters Corp). The higher-energy collisional dissociation (HCD) cell used a normalized collision energy of 30 eV for all the compounds to obtain MS/MS data. The UPLC separation was performed using an Acquity BEH CProducts  referencp-value was analyzed in comparison to the untreated samples using Student’s t-Test or using one-way analysis of variance (ANOVA) followed by a Tukey test for comparison between different treatment groups. Differences were considered statistically significant at p < 0.05. Results were expressed as mean ± SEM of data obtained from tripled or quintuplet, independent experiments. Multivariate analysis was performed using the R 3.2.5 environment. Three biological replicates for each cell line were evaluated, and the variables used were the IC50, the clonogenic assay (CL), the membrane permeability (MP) and the wound-healing assay (WH). A standardized principal component analysis (PCA) was performed with “ade4” package [Statistical analysis was performed using GraphPad Prism 7 software. The  package , followe package .T. peruviana methanol extract on breast (HTB-22), colorectal (HTB-38), prostate (HTB-81), and lung (HTB-177) cancer cell lines, a MTT assay was performed. IC50 values indicate the concentration of the extract that inhibits the growth of 50% of the cell population. The criteria of cytotoxicity established by the U.S. National Cancer Institute (NCI) considers a crude extract as active, moderately active, or inactive, when the IC50 values are lower than 20 μg/mL, from 20 to 100 μg/mL, or higher than 100 μg/mL, respectively [T. peruviana methanol fruit extract induced strong cytotoxicity in all four cancer cell lines (<20 μg/mL), but prostate cancer cells showed the lowest IC50 after treatment with T. peruviana extract  on different types of cancer cells whereas the normal fibroblast cells were not affected.To determine whether the viability of the human cancer cells is affected during treatment with 25% Fig. . Interes50 value, the clonogenic assay, the wound healing assay, and membrane permeability. PCA was applied to the whole dataset and the first 3 principal components (PC’s) accounted for 97.3% of the observed variability. Assuming that directions with the greatest variance are the most biologically relevant, these leading PC’s were selected as those with the major structure or variance, as a de-noising step enhancing ICA results. ICA obtained 3 independent components  with negative kurtosis . The employment of these components, plotting IC1 and IC2, allowed the effective separation of samples into their original groups . The IC1 clearly separates tumor cells from normal cells, mainly due to the effect of the extract on cell motility  and the membrane permeability, while the IC2 separates samples mainly on the basis of the IC50 observed for each cell line. The anti-proliferative (clonogenic assay) response of the cell lines to the extract is mainly represented by the IC3, which can be observed in the Additional file T. peruviana extract were cell motility and membrane permeability and, less significantly, the IC50 and anti-proliferative activity.Multivariate analysis was performed on the six cell lines , using as variables to be evaluated: the ICT. peruviana fruit extract could induce DNA fragmentation and thus whether apoptosis occurred, human cancer cells exposed to T. peruviana treatment were assessed for DNA laddering and visualized by agarose gel electrophoresis  fluorescent staining was used to identify apoptosis-associated changes in the cell membrane. AO is a membrane-permeable dye that binds to the nucleic acids of viable cells. EB is an impermeable dye, but readily penetrates the membrane of nonviable cells and binds to DNA. When AO/EB are used simultaneously, viable cells fluoresce green and nonviable cells fluoresce red under fluorescence microscopy. Lung and prostate cells were labeled by AO/EB after 4 h of treatment with the T. peruviana extract, and dual staining was examined under a fluorescent microscope. Early and late-stage apoptotic cells, marked by crescent-shaped or granular yellow-green AO nuclear staining (as indicated by condensed or fragmented chromatin) were detected in the treated group (with T. peruviana extract) and the positive control (doxorubicin treated)  Fig. . Also, ded) Fig. . Thus, iT. peruviana fruit was subjected to flash chromatography and six fractions were obtained. Because prostate cancer cells showed the lowest IC50 to T. peruviana crude extract compared to lung, breast, and colorectal cancer cells, every single fraction was analyzed on the prostate cancer cell line by MTT assay, fractions four and five being the most significantly cytotoxic . The results showed that these fractions contained the polyketide thevetiaflavone and the cardiac glycosides: peruvosidic acid, peruvoside, thevefoline, solanoside, neriifoside and neriifolin.Methanol extract of ic Table . Those fT. peruviana belongs to the Apocynaceae family, a plant which is native to central and southern Mexico, as well as Central America. It is a medicinal plant used to treat different diseases, including cancer [T. peruviana on different types of human cancer cell lines.g cancer . The leag cancer , 28–30. T. peruviana fruit extract exhibited strong cytotoxicity against four cancer cell lines. Among the cell lines examined, lung cells showed higher IC50 value (12.04 μg/mL) than prostate (1.91 μg/mL), breast (5.78 μg/mL), and colorectal (6.30 μg/mL) cells. Such variation among the cell lines might be attributed in part to the fact that cancer cells possess differences in their genetic make up, morphology and doubling time, resulting in differential susceptibility to the same cytotoxic agent [T. peruviana fruit methanol extract has an antiproliferative potential.Our experiments in vitro showed that ic agent . Our resT. peruviana fruit extract significantly reduced the cell viability and the ability of cells to form colonies in four different human cancer cell lines. The clonogenic assay has been used to detect cells that have retained their capacity to produce a large number of progeny after radiation and chemotherapy treatments [T. peruviana fruit extract has potential anticancer activity, limiting proliferation of cancer cells after treatment. Notably, normal cells (vero and fibroblast) treated with T. peruviana extract did not show any observable effect in clonogenic assay.Cancer is a complex disease characterized by proliferation of highly resistant cells to death. An increased rate of cellular proliferation is frequent, due to the fact that most cancer cells divide more often than normal cells. The goal of targeting cell proliferation is to arrest the cell cycle or induce cancer cell death using cytotoxic compounds. We show here, that eatments . It alsoeatments . Hence, T. peruviana fruit extract inhibited and delayed the cell migration of cancer cells, but not among normal cells. These results open the door to further studies that could confirm if the cytotoxic activity of T. peruviana fruit extract alters the regulation of the actin cytoskeleton, induces morphological changes and leads to detachment of cells, culminating in cell death. Moreover, motility and membrane permeability features were mainly affected by T. peruviana fruit extract, according with the multivariate analysis performed on the six cell lines and the four variables evaluated, suggesting a potential antimetastatic activity in the T. peruviana fruit extract.Migration is a critical step in initial progression of cancer that facilitates metastasis. Wound and healing assay is a classic and common method used for discovery and validation of molecules that affect cell migration , 34 and Cerbera manghas, a plant belonging to the Apocynaceae family, contains a cardiac glycoside (neriifolin), which induced DNA fragmentation on hepatocellular carcinoma 48 h after treatment [T. peruviana fruit showed death induction on cancer cell lines through early apoptosis mechanisms (AO/EB fluorescent staining) 4 h after treatment and late-stage apoptosis (DNA laddering assay) after 24 h of treatment. This result indicates that T. peruviana could have a higher level of apoptotic activity than other members of the Apocynaceae family. In addition, it will be important to determine whether the apoptotic activity is located in the compounds present in the flesh or seeds.One crucial and desirable mechanism by which chemotherapeutics destroy tumor cells is by inducing apoptosis. Cells undergoing apoptosis show morphological and biochemical modifications including chromatin segregation, nuclear condensation, DNA fragmentation, partition of the membrane, and vesicles formation , 37. Thereatment . Here, cT. peruviana fruit methanol extract indicated that one flavonoid and cardiac glycosides are secondary metabolites present in the fruit plant. Flavonoids, such as curcumin, quercentin and genistein, are known to have cell line-specific anti-proliferative and apoptosis inducing activity [T. peruviana on human cancer cell lines. Recent investigations of seeds from T. peruviana resulted in the isolation of cardiac glycosides that had inhibitory effects against human gastric and pancreatic cancer cell lines [T. peruviana due to the fact they can heal heart pathologies [T. peruviana fruit methanolic extract, mainly due to the effect of the extract on the motility and membrane permeability on human prostate, breast, colorectal and lung cancer cell lines. The cytotoxic activity of crude extract from T. peruviana fruit could be attributed to their phytochemical components such as thevetin A, thevetin B, peruvoside, thevenerin, and cerberin, which are toxins [T. peruviana fruit is currently being undertaken to investigate their cytotoxic, molecular and genetic action mechanisms, which could provide meaningful perspectives for biomedical and biotechnological research.Mass spectrometry analysis of active fractions from activity –42. It hactivity –46. Furtll lines . Cardiachologies , but arehologies  and hepahologies . Thevetihologies . One hune toxins , and alsT. peruviana fruit inhibits cell proliferation, has a time-dependent cytotoxic activity and induces apoptosis of human cancer cell lines, but has minimal or less pronounced effects on normal cells. The fruit extract displayed anticancer properties mainly through mechanisms that included membrane permeability, motility and DNA fragmentation. Maximum cytotoxic activity was observed in a fraction that contained one flavonoid and cardiac glycosides. Chemical analyses of the active fractions are currently in progress to perform a better evaluation of their biological significance. Additionally, further “in vivo” research is essential to show the full potential for the use of T. peruviana fruit extract in cancer therapy. In conclusion, these findings shows the importance of T. peruviana fruit as a source of bioactive compounds with anticancer potential.The current study presents evidence that the methanol extract of Additional file 1: Figure S1.Clonogenic assay of four human cancer cell lines treated with doxorubicin. Image showing colonies produced by human cancer lines and normal cell lines, following plating of 100 cells and 10–14 days incubation. Cells were treated with doxorubicin at 10 μg/mL. (PDF 1719 kb)Additional file 2: Figure S2.T. peruviana extract. Representative photographs of wounded cancer cells monolayer after 24 h of treatment with methanol T. peruviana fruit extract at IC50 value corresponding to each cell line. Vero and fibroblast cells were used as normal cell lines. A typical result from three independent experiments is shown. (PDF 2.74 mb)Wound and healing closure activity of four human cancer cell lines treated with methanol Additional file 3: Figure S3.Wound and healing closure activity of four human cancer cell lines treated with doxorubicin. Representative photographs of wounded cancer cells monolayer after 24 h of treatment with doxorubicin at 10 µg/mL. The result from three independent experiments is shown. (PDF 2.62 mb)Additional file 4: Figure S4.Morphological changes on four human cancer cell lines during treatment with doxorubicin. Human cancer cells were treated with doxorubicin at 10 µg/mL and monitored over a 24 h period. (PDF 1.88 mb)Additional file 5:Figure S5. Classification of normal and cancer cell lines exposed to T. peruviana fruit methanolic extract according to independent component analysis (ICA). The distribution of the cell lines  and variables  is shown in the space spanned by the independent components 1 and 3. The clear unsupervised discrimination among the six cell lines reflects the greater effect of T. peruviana extract on tumor cell lines , while normal cells are affected less . The independent component 1 is clearly separating cancer cells from normal cells, mainly due to the effect of the extract on the motility (WH) and membrane permeability (MP), while the independent component 3 is separating samples mainly by the anti-proliferative  observed for each cell line. (PDF 1121 kb)


Targeted therapies have shown significant patient benefit in about 5–10% of solid tumors that are addicted to a single oncogene. Here, we explore the idea of ligand addiction as a driver of tumor growth. High ligand levels in tumors have been shown to be associated with impaired patient survival, but targeted therapies have not yet shown great benefit in unselected patient populations. Using an approach of applying Bagged Decision Trees (BDT) to high-dimensional signaling features derived from a computational model, we can predict ligand dependent proliferation across a set of 58 cell lines. This mechanistic, multi-pathway model that features receptor heterodimerization, was trained on seven cancer cell lines and can predict signaling across two independent cell lines by adjusting only the receptor expression levels for each cell line. Interestingly, for patient samples the predicted tumor growth response correlates with high growth factor expression in the tumor microenvironment, which argues for a co-evolution of both factors in vivo. The prediction of growth factor induced cancer cell growth was improved significantly by combining a signaling model with machine learning. A team led by Andreas Raue at Merrimack Pharmaceuticals, attempted to better understand growth factor-dependent tumors and their potential treatment with receptor-targeting antibodies. Interestingly, prediction of tumor response improved significantly by adding prior knowledge from a mechanistic signaling model. This conceptually new approach relies solely on publicly available gene expression data and can be readily applied in drug development and development of clinical trials. In patient data, correlation between growth factor expression in the tumor microenvironment and its predicted response were identified. This consolidates the belief of an addiction of tumors to growth factors abundant in the tumor microenvironment, and might enable a more robust patient stratification in the future. We find that about half of the cell lines do not respond to any of the ligands whereas the other half of the cell lines respond to a least one ligand. We compare the observed ligand-induced proliferation with the response to treatment with antibodies targeting the ErbB receptor family members, a subfamily of four closely related receptor tyrosine kinases (RTKs): EGFR (ErbB1), HER2/c-neu (ErbB2), HER3 (ErbB3) and HER4 (ErbB4) as well as the insulin growth factor receptor (IGF-1R) and the hepatocyte growth factor receptor (Met). Not surprisingly, the antibodies targeting the respective RTK inhibit ligand-induced proliferation. The antibodies also inhibited basal proliferation in some cell lines that do not respond to exogenous ligand addition, which could be driven by autocrine signaling.17 Large collections of genetic and genomic data led to efforts to disentangle the complex mechanisms using machine-learning algorithms.21 It was previously shown that simulated patient-specific signaling responses derived from mechanistic signaling models using RNA sequencing data from patient biopsies can be robust biomarkers that are predictive of patient outcome.22 Here, we combined machine learning and mechanistic modeling to predict which cell lines proliferate in the presence of ligand. We used RNA sequencing data as inputs into a comprehensive mechanistic model capturing the ErbB, IGF-1R and Met signaling pathways. Our novel approach uses simulated signaling features and mutation status of a specific cell line as inputs into a Bagged Decision Tree, which predicts whether tumor cells proliferate in the presence of a growth factor. We achieved a substantial gain in accuracy compared to predictions based on RNA sequencing data alone by inclusion of simulated signaling features such as the area under curve of distinct heterodimers and phosphorylated S6 for in vitro models.The need has been recognized for computational approaches to deal with the complexity of signal transduction and its dysregulation in cancer to ultimately understand drug activity.Applying this approach to patient data, the prediction of ligand-dependent tumor samples based on mRNA data from The Cancer Genome Atlas (TCGA) revealed that colorectal and lung cancer are the two indications most responsive to EGF, which agrees with the approval of EGFR inhibitors in these indications. In addition, the prediction of responders in patient samples revealed a correlation between predicted tumor growth and measured ligand expression in the tumor microenvironment, which argues for a co-evolution of ligand production and the ability of the tumor cells to respond to stimulation.23 Seribantumab (MM-121), a monoclonal antibody targeting ErbB3;16 MM-131, a bispecific antibody co-targeting Met and EpCAM;24 and Istiratumab (MM-141), a bispecific antibody co-targeting IGF-1R and ErbB3.25 Fig. α = 0.05 . Per this screen approximately 45% of cell lines responded to EGF, 55% of cell lines responded to HRG, 33% of cell lines responded to HGF and 7% of cell lines responded to IGF-1. The low response rate to IGF-1 in this proliferation screen may reflect the presence of IGF-1 in the low-serum medium and the modest absolute inhibition point to the importance of IGF-1 mediated signaling for survival rather than for proliferation.26 We and others observed a generally weaker MAPK activation via IGF-1R  for response to the exogenously added ligands EGF, HRG, HGF, and IGF-1 . Bound receptors can form homo and heterodimers and subsequently undergo endocytosis. After internalization, the receptor dimers can get either dephosphorylated and recycled to the cell surface or they get degraded in the lysosomes.35 Downstream of the receptor, all homo- and heterodimers except the ErbB3-homodimer, which cannot trans-phosphorylate due to its lack of intrinsic kinase activity, can activate the MAP kinase cascade as well as the PI3K/AKT pathway. ERK and AKT phosphorylation converge in the phosphorylation of S6K1 and S6. Several known feedback mechanisms between the pathways 27 were implemented in the computational model. Mathematical details, executable code to simulate the model and instructions to replicate our findings are available in the biomodels.org.To construct a comprehensive signal transduction model that could be used to predict proliferation in response to growth factors for all 58 cell lines, we built on a previously published model of ErbB receptor signaling.Met Fig.  as well 37 Size and complexity of the computational model were chosen to reflect the available experimental data, and to facilitate efficient computation. This is particularly important during model parameter calibration, which uses parameter estimation algorithms to match the available experimental data as closely as possible (see Methods section for details). Mutations were not implemented in the computational signaling model as they appear to increase the signaling baseline but not necessarily the signaling dynamics.38 However, the mutation status for each cell line was used in the machine learning classification.The computational model is constructed with the aim to capture the signaling dynamics of key components of the signaling pathway including receptor homo- and heterodimerization. It is not intended to be a complete compendium of all the known molecular interactions.39 for the receptor phosphorylation as well as for phospho-MEK, phospho-ERK, phospho-AKT, and phospho-S6 across all seven cancer cell lines  were used. Only the two cell lines H322M and IGFROV-1 were included in the cell line proliferation screen in Fig. 40 In this case, it was possible to restrict all kinetic rate constants to the same value and to adjust only the receptor expression for individual cell lines. Due to the analytically calculated basal activation levels of all homo- and heterodimers as well as of the downstream components, which were derived from steady-state constraints,41 the receptor expression impact the signaling response throughout the model. Therefore, the individual receptor expression of each cell line enables distinct model responses upon ligand stimulation. The receptor expression was measured using quantitative flow-cytometry (qFACS) in combination with RNA sequencing data (see Methods section). The model can accurately describe the time course data of seven training cell lines, with 85.7% of the data points within two standard deviations of the model uncertainty  and compared to the experimental data. The goodness of the predictions for the validation cell lines was equivalent to the goodness of fit of the training cell lines . To this end, previously publishedFurther insights into growth factor signaling and signal processing by the cancer cells can be gained by analyzing the computational model and why it can capture the distinct signaling dynamics across cell lines. This analysis revealed the importance of different homo and heterodimers in encoding information as a function of the ligand(s) present. The largest effect of heterodimerization on signal output is seen within the ErbB family. The interplay between the receptors explains the slower, more sustained receptor activation in response to EGF in the BxPc-3 cells, which are characterized by a high ratio of EGFR to other receptors Fig. . In contIGF-1 is distinct from the other growth factors in our screen. IGF-1 displayed a much weaker ability to induce proliferation and similarly the effect of IGF-1 signaling in co-stimulation experiments is distinct to the HRG/EGF or HGF/EGF co-stimulation experiments. The time-course data for co-stimulation of IGF-1 with either EGF or HRG did not show deviations from the respective stimulation with IGF-1 alone , we trained bootstrap-aggregating (bagged) decision trees (BDTs). BDTs are highly efficient for multivariate analysis and allow for a comprehensive interpretation of the chosen features.48 The second feature set did not contain the receptor expression explicitly but only signaling features derived from the computational model based on the receptor expression and the ligand stimulation , we use our model to predict if an individual patient tumor would show a proliferation response if stimulated by the ligand of interest. The patient data set includes 2909 samples from patients with breast, colorectal, lung, and ovarian cancer. The input to our model is receptor RNA expression measured by RNA sequencing for each tumor sample. The measured RNA expressions between our in vitro cancer cell line data and the data from patient tumors were on different scales. Therefore, we normalized the expressions to their respective means. Subsequently, the expression of EGFR, Her2, ErbB3, Met, and IGF-1R were used to perform model simulations and to extract the signaling features needed to predict ligand-dependent tumors using the previously described BDT algorithm. The number of ligand-dependent tumors differed within indications and ligand . The number of predicted ligand responsive tumors was highest for HRG followed by EGF and lowest for HGF , a Met blocking antibody in a Phase 3 study in NSCLC.55 Similarly, EGFR inhibitors have not yet proven to result in clinical benefit in breast cancer,56 which is also in agreement with the predicted low EGF dependence of breast cancer. The predicted high responsiveness of breast cancer and lung cancer to HRG seems to agree with the retrospective analysis of two clinical studies with Seribantumab and the finding that HRG expression appears to be predictive of patients responding to therapy.57 Unfortunately, the precision of the predictions cannot be assessed as no outcome data to treatment with ligand blocking antibodies is available for the TCGA data set. The predicted ligand-dependence only considers the molecular makeup of individual tumors. However, a tumor that is predicted to be ligand-dependent would respond only if the respective ligands were also present in sufficient amounts in the tumor microenvironment. The local concentration of ligands, however, cannot be inferred from our analysis and it is difficult to match to the in vitro data that was used for model training. This impacts the predicted number of ligand-dependent tumors in this data set.In the previous section, we showed that a mechanistic computational model in combination with decision tree classification can predict in vitro proliferation. Next, we applied this novel approach to patient data. Using the data from the TCGA Research Network  amounts of the corresponding ligand compared to the predicted ligand independent tumors, if we compare the mean expression. This suggests that tumors that express ligands evolved to be sensitive to ligands, or vice versa. In our opinion, this is an indirect proof that the model predictions can be applied to data from patient tumors and that they could be clinically relevant.However, apart from the relative number of ligand-dependent tumors, we observed a significant correlation between ligand expression and the predicted response to ligands Fig. . The pre58 Targeted therapy and combinations thereof have become important areas of drug development with rising FDA approval rates in the last years.60 However, by studying cellular fate across multiple cell lines and indications, we and others have learned that complex interactions between receptors as well as positive and negative feedback regulation between signaling pathways can diminish drug efficacy. To obtain a deeper understanding of cell response to exogenous stimuli, phenotypic responses need to be studied in the context of multiple signaling pathways as well as mutation status. In this work, we developed a computational model describing multiple signaling pathways and show that a BDT algorithm using simulated signaling features can accurately predict ligand-dependent proliferation in vitro.The research to understand and therapeutically battle various cancer types has made significant progress over the last two decades, decreasing the overall mortality by roughly 2% per year since 2001.28 The fact that the developed computational model can accurately describe the signaling responses across multiple cell lines enables the prediction of signaling dynamics for cell lines of the proliferation screen that were not used to construct the computational signaling model.The signaling model incorporates the ErbB receptor family as well as the Met and IGF-1R receptors. Parameters of the model were estimated based on a variety of time-resolved data from seven different cell lines including a wide range of ligand concentrations with comprehensive single ligand and co-stimulations. The cell lines cover a broad range of ratios of receptor expression. The ligand concentrations used in the proliferation screen were in the range of concentrations used for the signaling experiments. While retaining a good fit to the experimental data, we could keep all kinetic parameters in the signaling model constant and just vary the receptor expression to describe the experimental signaling data for each cell line. It is important to note that this is not a direct proof that the reaction rate constants are identical between the cell lines. However, our model with all rate constants set to the same values, is in line with the receptor phosphorylation and downstream signaling data. We do not argue that the model presented here is correct in all of its aspect, but we could show that the signaling dynamics predicted by the model are useful for predicting the cellular responses to ligand stimulation and that this presents an approach that should be explored further by incorporating clinical patient response data. The computational model not only describes the data for the seven training cell lines but also predicts the signaling responses of two additional, independent validation cell lines. We showed that the goodness of fit is dependent on the absolute receptor expression and the formation of different homo- and heterodimers. The observed variability in model response was achieved by differences in internalization, degradation and recycling rates for different receptor homo- and heterodimers. Saturation of different downstream model components is sensitive to the receptor expression. The analytically solved steady states for all cell lines were important to implement the complex receptor dimerization properties in the signaling model. Thus, ligand stimulation results in a complex re-distribution of receptor homo- or heterodimerization and facilitated distinct downstream activation patterns. The calculated steady states, especially for the ErbB receptor family, were found in concordance with measured basal total and phosphorylation levels of 39 breast cancer cell lines utilized from.63 and carve out regions in feature space that best distinguish between different data classifications, here proliferation vs. stasis upon ligand stimulation. BDTs were trained on the in vitro proliferation screen across 58 cell lines. The algorithm was trained with either receptor expression and ligand stimulation conditions as Boolean columns or with signaling features extracted from the computational model. The signaling features included the integrated area under curve of all receptor complexes as well as the phosphorylation of AKT, ERK, and S6. Both feature sets lead to a better prediction of proliferation compared to control, where response was predicted based on random data. However, the signaling features allowed for a more robust and statistically improved prediction of proliferation. In addition, the computational model allows us to gain insights into the underlying processes driving ligand-dependent proliferation. In all cases homo or heterodimerization of the ErbB receptors was important. In the case of EGF, the PI3K mutation status mattered in addition. For HRG and HGF possible RAS mutations together with AKT and S6 phosphorylation were important features to predict cell proliferation. However, the importance of features in the tree-based approach is very sensitive to the utilized data, and additional measurements are needed to infer the role of MAPK and PI3K signaling in inducing growth.To predict proliferation in response to ligand stimulation, we linked simulated signaling features to the data of the cell proliferation screen using a supervised machine learning approach. Tree-based classification algorithms are widely used for machine learningSimulated signaling features are advantageous over using receptor expression directly as input features for two reasons: First, the dynamic range of receptor activation as well as of the downstream components is described quantitatively and renders the model outputs more robust to receptor expressions, which span multiple orders of magnitude. Second, the interplay between receptors and the included feedback mechanisms adds a source of information on top of the receptor expression and ligand information alone, resulting in a non-linear input transformation that improves the detection of regions governing proliferation.57To demonstrate the applicability of this novel approach to patient samples, data from 2909 patients with breast, colorectal, lung or ovarian cancer were analyzed. For these samples, model simulations were conducted to extract signaling features required for BDT prediction of ligand-dependence. Interestingly, we observed a significant correlation between the measured ligand expression and the predicted ligand-dependence for breast and colorectal cancer. This may be a consequence of evolutionary adaption of these tumor cells due to the growth advantage from ligand-mediated signaling. Therefore, the presence of ligands in the tumor micro-environment may be a favorable biomarker for RTK-directed drug treatment. This rationale together with possible mutations, which contributed substantially in the BDT training, are currently being explored in the clinic.64 with additional prior knowledge may allow us to better bridge between quantitative time-resolved data and large-scale genomic and phenotypic data. To understand ligand mixtures and pathway redundancy a greater variety of single ligands, e.g., FGF and PDGF, or stimulations with ligand mixtures might aid to more accurately determine model parameters for receptor dimerization, trafficking and downstream activation in the future. Further, or model is currently limited to MAPK and PI3K pathways. Future work, should expand on this approach by including other signaling pathways, e.g., data from the JAK-STAT signaling pathway. An expanded model may improve the accuracy of the predictions as well as additional perturbations like specific gene knockdown etc. would help to improve the signaling model.However, both the prediction of proliferation and the mechanistic computational model have limitations. For one, machine learning in feature-space regions that are not covered by many cell lines is not efficient as illustrated by IGF-1 in the proliferation screen data-set. The mechanistic model is limited in its ability to fully reproduce data in cases of either receptor overexpression  might prove to be far more prevalent than oncogene addiction given the high ligand prevalence in solid tumors and potentially as much more complex since multiple ligands are expressed in the tumor microenvironment. To successfully treat patients with ligand-dependent tumors with targeted inhibitors  or rational combinations of targeted inhibitors, a better understanding of ligand-dependence is crucial, especially given the redundancy of signaling pathways within a tumor cell and tumor heterogeneity. We argue that the mechanistic understanding of changes in receptor stoichiometry based on individual ligands or ligand mixtures result in non-obvious signaling responses that are relevant to the ultimate phenotypic response. The work presented here demonstrates that for targeted therapies to be successful in the clinic the ligand hierarchy as well as co-dependence need to be understood and most likely require the measurement of multiple ligands and respective receptor expression in tumor biopsies. New methodologies like single cell RNAseq67 Yet, significant improvement in predictions proved to be challenging across multiple approaches and data sets. With the presented approach, mechanistic knowledge can be easily combined with known datasets from RNA sequencing, copy-number alterations and mutation information to improve the prediction of patient-individual drug response and unravel the interplay between complex signaling and cellular fate.The presented novel approach of using BDTs in conjunction with simulated signaling features is the beginning of how complex mechanistic models and large data sets can be combined to understand cell-specific complexity but also heterogeneous tumors better. We demonstrated that mechanistic computational models of signaling pathways can help bridge between large scale in vitro observations and clinical hypotheses. In the future, selected in vivo studies should be used to validate rational combination regimens. Previous efforts predicting drug sensitivity based on large and diverse data sets found that gene expression data proved most valuable, together with exploiting non-linear relationships and addition of prior knowledge of biological pathways.® was obtained from Promega and reconstituted fresh for each experiment.All cell lines used in the viability screen were purchased from American Type Culture Collection. In brief, cells were cultured in RPMI 1640 medium (Life Technologies) supplemented with 10% fetal bovine serum  and 1% penicillin-streptomycin  at 37 °C and 5% CO2. Recombinant human heregulin1−β1 (NRG1b) EGF domain and HGF were obtained from PeproTech, and recombinant human IGF-1 and EGF were obtained from RD Systems. Seribantumab, MM-131, Istiratumab and MM-151 was manufactured in-house by the Merrimack Pharmaceuticals Protein Engineering Department and stored at 4 °C. CellTiter-GloTo measure cell viability in a three-dimensional spheroid culture, cells were seeded into 384-well low- binding multi-spheroid culture plates  in the relevant growth medium supplemented with 4% FBS and 1% pen/strep at a density of 1500 cells/well. To allow for spheroid formation, plates were incubated for 24 h, after which cells were treated with ligands  and/or inhibitors  in 4% FBS containing medium. Following 72 h of incubation, cell viability was determined by incubation with CellTiterGlo® reagent for 10 min and measuring well luminescence on an Envision (Perkin Elmer) plate reader.The available data consists of three different data sets, which include time-resolved concentration measurements of activated and total receptors as well as of various phosphorylated downstream targets. The largest data set comprises nine cell lines with measurements of the EGFR, HER2 and ErbB3 receptors of the ErbB family and the IGF1-receptor, together with the downstream targets ERK, AKT, S6K1 and S6. Four different ligand concentrations of EGF, HRG, and IGF-1 ranging from 0.156 to 10 nM are used and 12 measurement time points up to 240 min are taken. In addition, co-stimulations of the respective ligands are available for two of the nine cell lines. Out of the nine cell lines, six cell lines are used for model calibration, the remaining three to validate the model. Cell lines used for calibration include H322M , BxPc-3 (pancreatic cancer), A431 (epidermoid cancer), BT-20 (breast cancer), ADRr (ovarian cancer) and IGROV-1 (ovarian cancer). BT474 (breast cancer), MDA-MB-231 (breast cancer) and ACHN  are utilized to validate the model.Measurements after either EGF or BTC stimulation are available for one of the calibration cell lines, ADRr, with ligand concentrations between 0.11 and 9.26 nM, and 12 measurement time points up to 240 min. These include phosphorylation of EGFR, HER2, ErbB3, ERK, and AKT. Apart from that, measurements with HGF and EGF as well as their co-stimulation is available for ACHN, which is used for validation with respect to HRG and IGF-1, spanning the same concentrations and measurements up to 120 min. Therein, phosphorylated EGFR and Met phosphorylation as well as phospho-ERK and phospho-AKT are measured. The receptor concentrations in all experiments are measured by ELISA whereas the downstream components are measured by lysate microarray.Cells were trypsinized, washed, and stained using fluorescently labeled antibodies, see list below. Antibodies were labeled as previously described (16). Receptor numbers were determined by assessing the antibody-binding capacity of the fluorescently labeled antibody via quantitative fluorescence-activated cell sorting. Antibody-binding capacity was determined using Simply CellularQuantumBeads , per the manufacturer’s instructions. List of antibodies and target receptors used in qFACS method: Erbitux (EGFR), Trastuzumab (HER2), Anti-human HER3 Ab generated by Merrimack, A12 IgG (anti-human IGF1-R), Anti-human Met, Mouse Anti-Human EpCAM-APC .68Matching high density lysate matrices from nine cells lines  were generated for both the ELISA and lysate microarray studies. Lysate matrices were developed by treating each cell line with EGF, HRG1b1, IGF1, individually at four different doses , as well as in all two-way combinations of these three ligands at a single 2.5 nM dose of each ligand  in 96-well plates (Corning). Antibodies directed at pAKT (S473), pMEK (S217/S221), pERK (T202/Y204), p-S6K1 (T389), and pS6 (S235/S236) were obtained from Cell Signaling Technology. Cells were cultured using standard tissue culture techniques in RPMI supplemented with 10% FBS and penicillin/streptomycin. Cells were counted using a hemocytometer and seeded at 10,000 cells/well into 40x 96-well tissue culture plates (Corning). After 24–48 h, once cells had reached approximately 50% confluency, medium was aspirated and replaced with low- in medium (RPMI supplemented with 0.5% FBS and penicillin/streptomycin) (Gibco). 16–24 h later, 2x ligand solutions prepared in low-serum medium were added simultaneously to all 96 wells of each plate. Plates were returned to the incubator for the prescribed incubation times, then placed on ice to stop ligand stimulation. Medium was aspirated from all wells, cells were washed once with ice-cold PBS, and then lysed in 30 μL/well of lysis buffer. Twelve time points as well as an untreated time zero were collected for all conditions . Lysates were then collected and frozen. For ELISA lysates, M-PER buffer (ThermoFisher) was supplemented with protease and phosphatase inhibitors (Roche) and NaCl to a final concentration of 150 mM. For lysate microarrays, lysis buffer was prepared as previously described.69 Protein specific antibodies were used for capture in all cases, while an anti-phospho tyrosine antibody was used for detection in all phosphor assays  using the Aushon 2170 micro-arraying robot in 2x4 8-pin mode . Slides were washed in 100 mM Tris-HCl pH 9.0 at RT for several days, followed by 3x 5 min PBST, after which slides were spun dry. ProPlate 16-well slide modules (GraceBioLabs) were then attached. Arrays were blocked in Odyssey Blocking Buffer  at 4 °C for 1 h, after which blocking solution was replaced with 1:500 primary antibodies  mixed with 1:1000 anti-beta-actin antibody (mouse) (Sigma A1978) for 24 h at 4 °C with agitation. Slides were then washed 3x 5 min with PBST, then incubated in secondary antibodies (1:1000 anti-rabbit-800 and 1:1000 anti-mouse-680 (LiCor) in 5% BSA/PBST) at 4 °C for 5 h. Arrays were washed briefly in PBST, ProPlate modules were removed, and whole-slides were washed 3x 5 min in PBST. Slides were then spun dry at room temperature. Slides were scanned on the LiCor Odyssey scanner at 21 μm resolution and under the “highest” quality setting in both the 700 and 800 nm channels. Spot intensities were extracted using the LiCor ImageStudio software with manual spot alignment.Total and phospho ELISAs of EGFR, ErbB2, ErbB3, and IGF-1R were performed as previously described.x of the model has a biological counterpart. The time evolution x(t) of the model concentrations is obtained by integration of the corresponding system of ODEsθd. These are linked to measured concentrations of the involved constituents y(t) by an observational functionθo. Both observational and dynamic parameters are comprised in θ. To compare the model response to measured data at time points ti, the scaled log-likelihood is calculated viaχ2(θ).Mechanistic models based on ordinary differential equations (ODEs) are frequently used for the description of biochemical reaction networks. They are composed of kinetic rate equations and every component 71 Therein, an implicit BDF integration method72 with attached KLU sparse solver was chosen.73 The inner derivatives of the likelihood needed in gradient-based parameter estimation were computed via forward sensitivities supplied to the integration algorithm.74 Numerical optimization was conducted using a trust-region based, large scale nonlinear optimization algorithm implemented in the MATLAB function LSQNONLIN.75 For the mathematical modeling and visualization, the open-source and freely available d2d framework,76 based on MATLAB, was used.Since analytical solutions of non-linear ODE systems are in general not available, a numerical integration must be performed. In this work, the dynamical system and its sensitivities were integrated by the CVODES integrator of the SUNDIALS suite.77 A good correlation between mRNA and protein expression was previously shown in an independent study.78 By fitting a linear model  and receptor mRNA expression from the Cancer Cell Line Encyclopedia (CCLE) for 124 cancer cell lines.BioModels.org with the identifier MODEL1708210000. In addition, the computational model including all proteomic data, the phenotypic data from the in vitro viability screen together with the RNA sequencing data obtained from the CCLE 77 and the TCGA Research Network (http://cancergenome.nih.gov/), respectively, have been deposited within freely available modeling toolbox Data2Dynamics . It includes MATLAB code and documented script files to readily perform all analysis steps outlined in this publication. The code folder is also available in the Figshare repository (10.6084/m9.figshare.5331544). In addition, the mechanistic signaling model was also implemented in the open-source R package dMod 71 . The package contains the experimental data for all calibration cell lines and allows to simulate model trajectories.The signaling model and code for machine learning analysis from this publication have been deposited to Supplementary Figure and TextSources of cell lines


Drosophila induces cell migration, which is suppressed by the loss of JNK signaling and enhanced by the gain of JNK signaling. APLP1 activates JNK signaling through phosphorylation of JNK, which up-regulates the expression of matrix metalloproteinase MMP1 required for basement membranes degradation and promotes actin remodeling essential for cell migration. Our data thus provide the first in vivo evidence for a cell-autonomous role of APLP1 protein in migration.The amyloid precursor like protein-1 (APLP1) is a member of the amyloid precursor protein (APP) family in mammals. While many studies have been focused on the pathologic role of APP in Alzheimer's disease, the physiological functions of APLP1 have remained largely elusive. Here we report that ectopic expression of APLP1 in  Amyloid precursor-like protein 1 (APLP1) is a member of the highly conserved amyloid precursor protein family that includes amyloid precursor protein (APP) and amyloid precursor-like protein 2 (APLP2) in mammals . Membersin vivo and in vitro [APP family proteins have also been implicated in neuronal migration, yet this function has been controversial. It was originally reported that neurons in APP/APLP1/APLP2 triple knockout mice over-migrated and accumulated in the marginal zone , suggestin vitro , and dowin vitro . RNAi knin vitro , suggestin vitro . Furtherin vitro . TogetheThough APP family proteins have conserved structure and could compensate for each other to certain extent in double and triple knockout mice , APLP1 lDrosophila to human, and regulates a wide range of cellular activities including proliferation, differentiation, migration and apoptosis [Drosophila [The c-Jun N-terminal Kinase (JNK) pathway is evolutionarily conserved from poptosis . Recentlpoptosis  and Aβ iosophila , 36. HowDrosophila has been used as an animal model to study the in vivo function of APP, for the genetics of Drosophila is clear and Drosophila is easy to manipulate. In Drosophila, there is also an APP-like protein, APPL, indicating the role of APPL may be conserved from Drosophila to human. In this report, we investigate the function of APLP1 in Drosophila. We found that expression of APLP1 in Drosophila wing disc triggers cell migration, which is suppressed by the loss of JNK signaling and enhanced by the gain of JNK signaling. APLP1 activates JNK signaling through phosphorylation of JNK, which results in elevated expression of JNK target genes including puc and mmp1, and actin polymerization. Thus, this work provides the first evidence that APLP1 promotes JNK-dependent cell migration in vivo.Drosophila. Interestingly, expression of APLP1 along the anterior/posterior (A/P) compartment boundary in third-instar wing discs under the control of patched-Gal4  gene. puc encodes a JNK phosphatase that negatively regulates JNK activity [puc mutants  encoding the Drosophila JNK [DN , which was consistent with APLP1 in cell migration, indicating a universal role of APLPs in cell migration. To examine whether APLP1 induced JNK-mediated cell migration is conserved from  protein , in cellof BskDN  or Puc  triggered puc-LacZ expression  or in the salivary gland also activates JNK signaling, resembling that of Hep expression  and lung carcinoid tumor [https://www.oncomine.org/), many more cancers, including Esophageal cancer, Ovarian cancer, Sarcoma, and Kidney cancer, have a portion of samples showing significantly higher expression of APLP1 in multiple studies, suggesting APLP1 may play an important role in some subtypes of cancers during tumorigenesis. Finally, higher APLP1 expression was observed in more advanced stages in lung cancer [Consistent with our findings, APLP1 has been found to be significantly up-regulated in several types of human cancers including invasive ductal breast carcinoma (id tumor  (Figure g cancer  (Figure Drosophila media and crosses were performed at 25°C unless otherwise indicated. UAS-APLP1, UAS-APPLsd were kindly provided by Dr. Merdes [pucH246, UAS-mmp1-IR, UAS-mmp2-IR, UAS-TIMP1, UAS-RasV12, UAS-Rho1-IR, UAS-p35, UAs-P53DN were obtained from Bloomington Stock Center; sd-Gal4, UAS-BskDN, UAS-Puc, UAS-Egr, UAS-Hep [ptc-Gal4, en-Gal4, pucE69 34, UAS-LacZ [All stocks were raised on standard . Merdes ; pucH246 UAS-Hep ; ptc-GalUAS-LacZ  were prerd instar larvae were dissected for each genotype as described [For statistical analysis of cell migration, 20-30 3escribed . Discs wAntibody staining of the imaginal discs was performed as previously described . The folrd instar larvae wing discs were dissected in PBST and stained for β galactosidase activity as described [For X-gal staining, 3escribed .