IRAK3 is a critical modulator of inflammation in innate immunity. IRAK3 is associated with many inflammatory diseases, including sepsis, and is required in endotoxin tolerance to maintain homeostasis of inflammation. The impact of IRAK3 on inflammatory markers such as nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), tumour necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in cell culture models remains controversial.To analyse temporal effects of IRAK3 on inflammatory markers after one- or two-challenge interventions in cell culture models.in vitro cell studies reporting outcome measures of expression of IRAK3 and inflammatory markers. Meta-analyses were performed where sufficient data were available. Comparisons of outcome measures were performed between different cell lines and human and mouse primary cells.A systematic search was performed to identify The literature search identified 7766 studies for screening. After screening titles, abstracts and full-texts, a total of 89 studies were included in the systematic review.The review identifies significant effects of IRAK3 on decreasing NF-κB DNA binding activity in cell lines, TNF-α protein level at intermediate time intervals (4h–15h) in cell lines or at long term intervals (16h–48h) in mouse primary cells following one-challenge. The patterns of TNF-α protein expression in human cell lines and human primary cells in response to one-challenge are more similar than in mouse primary cells. Meta-analyses confirm a negative correlation between IRAK3 and inflammatory cytokine (IL-6 and TNF-α) expression after two-challenges. Inflammation is primarily initiated by the innate immune system as the first line of defence in response to infection or tissue injury. Infectious microbes express molecules with specific structural patterns that are known as pathogen-associated molecular patterns (PAMPs) and are recognized by pattern recognition receptors of the innate immune system, including Toll-like receptors (TLRs) . While TIRAK3, another member of the IRAK family, inhibits the dissociation of IRAK1 or IRAK2 from myddosome complexes and therefore the interaction of IRAK1 or IRAK2 with TRAF6, required for NF-κB activation . Thus, Iin vivo rat model [Importantly, IRAK3 is involved in regulation of endotoxin tolerance , 16, 17.in vivo models [et al. [et al. [et al. [et al. [IRAK3 mRNA and protein expression and its effects on inflammation have been studied widely using various experimental models including cell lines , 21–24, o models –31, and  [et al.  reported [et al. , 10. In  [et al. . Kim et  [et al.  reported [et al.  found IR [et al. . Additio [et al.  suggeste [et al. . Further [et al. . The var [et al. , or cell [et al. .Considering the multiple pathways implicated in IRAK3 action, the research questions of this review are to identify to what extent IRAK3 has inhibitory effects on inflammation, and how the actions of IRAK3 are temporally regulated. The function of IRAK3 in inflammation has been the subject of a number of research studies , 10, 13 Six databases  were searched systematically from the earliest date available until 16 July 2020. The search keywords were conducted using three concepts: IRAK, endotoxin tolerance, and sepsis. Synonyms within each concept were combined using the OR Boolean operator .Titles and abstracts were screened initially by one reviewer (T.N.) using selection criteria described in The included studies were restricted to animal or human cell culture studies. Cell culture models used in the studies are cell lines, human primary cells and mouse primary cells.Mycobacterium tuberculosis, Escherichia coli, Streptococcus pneumoniae, Haemophilus influenzae, Lactobacillus acidophilus), protozoa (Leishmania donovani promastigotes) or inflammation-modulating chemicals , lipoteichoic acid, peptidoglycan, IL-1, S-nitrosoglutathione, transforming growth factor beta (TGF-β), paramethoxyamphetamine, vitamin D3, 6-methylprednisolone, surfactant protein A, titanium particles/bone cement, granulocyte-macrophage colony-stimulating factor (GM-CSF)/ interferon gamma (IFN-ϒ), IL-13, hyperoxia (95% O2), TLR7 agonist , IL-1β, TNF-α). Descriptions of the intervention chemicals can be found in S1 Table  protein production and NF-κB activity were included.in vivo studies were excluded.The articles must be research studies containing cell culture models. Review articles and Data including cell type, study design, description of intervention, intervention duration and outcome measure were extracted from each included study  in one group, and other challenge chemicals are in separate groups. RevMan 5.3 software was used to perform the meta-analyses. Standardized mean difference (SMD) and 95% confidence intervals (CIs) were calculated for outcome measures of interest to indicate the effect size. The I2 statistic was used for assessing heterogeneity [The studies are grouped for meta-analyses based on population, intervention and outcome measures of interest, which can be found in esponses . Interveogeneity . A valueogeneity .A total of 16,302 studies were identified through database searches, and 8,549 duplicate studies were removed . Citatio1, 28 used human primary cells2, 25 used mouse primary cells3, two used cell lines and mouse primary cells [E. coli and Porphyromonas gingivalis LPS, one study used E. coli and Salmonella minnesota LPS, 33 studies used LPS from E. coli, two used LPS from P. gingivalis, five studies used Salmonella abortus LPS, one used Klebsiella LPS, one used Aggregatibacter actinomucetencomit LPS, two used LPS from S. minnesota, one used Salmonella enteritidis LPS, 16 studies did not mention the bacterial origin of LPS); three studies used Pam3CSK4; three studies used TLR7 ligand; three studies used IL-1β; eight studies used bacteria; one study used protozoa; two studies used TNF-α; several single studies used challenges with one of these chemicals .Of the 89 included studies, 31 used cell linesry cells , 44, onery cells , one usery cells , and onery cells . Most st1 References [ferences , 48–70.2 References [ferences , 71–92.3 References [ferences , 93–111.Most studies (89 studies) performed one-challenge and measured outcomes of interest from 30min to 48h post-treatment; one study involved five days (5d); one study used 6d; one study reported data from 3d and 4d post-treatment; and three studies involved less than 30min (5 to 15min). The interval of less than 3h is for measuring outcomes involving nuclear translocation and DNA binding of transcription factors such as NF-κB. In time intervals less than 3h, there is no significant increase of IRAK3 mRNA and protein expression , 50, 55.E. coli pathogen-associated molecular patterns, Pam3CSK4, lipoteichoic acid, H. pylori antigen and peptidoglycan) included in one group, and other inflammation-modulating chemicals in separate groups. Changes in NF-κB activity, IRAK3 and cytokine expression levels are analysed by comparing control cells as described above with cells receiving one-challenge. The impact of IRAK3 at ST, IT or LT temporal periods on cytokine expressions is examined by comparing wildtype cells and cells with IRAK3 silenced or knocked out.This review analyses IRAK3 mRNA and protein expression, NF-κB activity, TNF-α and IL-6 protein levels in cell lines, human or mouse primary cells at ST, IT and LT after intervention of one-challenge with microbes or inflammation-modulating chemicals. As mentioned above, interventions are grouped for meta-analyses, with challenges by microbes (bacteria or protozoa) and bacteria-derived compounds  to 3h (ITN) after challenge with hyperoxia (95% O2) but significant elevation after IL-1β challenge in a lung epithelial cell line. Tiwari et al. [N) in monocytic cell lines when challenged with paramethoxyamphetamine. Harada et al. [N) post-treatment with LPS or Pam3CSK4. NF-κB reporter gene expression was found to increase markedly at 6h (LTN) after LPS challenge in bone marrow-derived macrophages [N) after lipoteichoic acid challenge in human periodontal ligament cells [N) after challenge with TLR7 ligand in single study involving a macrophage cell line [Two cell line studies reported significant increase of DNA binding activity of NF-κB at LTPam3CSK4 , 22. Metn et al.  reportedi et al.  reporteda et al.  reportedrophages , or at 2nt cells , or at 1ell line .L. donovani or H. pylori antigen indicate that TNF-α protein expression is highly increased at IT and LT  after LPS challenge. In two studies using human cell lines, IRAK3 was reported to have an inhibitory effect on NF-κB DNA binding activity at 6h and 9h (LTN) upon LPS stimulation [N) after IL-1β challenge [et al. [N) after challenge with LPS in mouse Kupffer cells .Gene silencing and knockout approaches are important genetic tools to analyse effects of proteins such as IRAK3 on inflammation and thus outcomes from these approaches are examined in this review. Two studies using human  or mousemulation , 22. In hallenge , 10. A s [et al.  showed nL. donovani [H. pylori antigen or LPS , cells were challenged first with a TLR or IL-1R ligand and then challenged with the same or a different ligand at a later period. In these 32 studies, the outcomes of interest were measured after durations of 1h–48h following the second challenge. In this section the effect of two-challenges on IRAK3 mRNA and protein expression, NF-κB activity and cytokine protein production are examined by comparing cells receiving one-challenge with cells challenged twice.E. coli pathogen-associated molecular patterns compared to IRAK3 expression between 1h and 18h after one-challenge with LPS or heat-stable enterotoxigenic E. coli pathogen-associated molecular patterns  cells . Two celet al.  reportedet al. . Two stuet al. , whereaset al. . A singlet al. .N (6h–24h) in cell lines [This review provides better understanding of the role of IRAK3 and its upstream and downstream factors in regulating inflammation following one-challenge and two-challenge interventions, and potential involvement in sepsis. The meta-analyses identified IRAK3 mRNA expression increase at ST (5min– 3h) and IT 4h–15h) periods, and IRAK3 protein expression increase at LT 16h–48h) after one-challenge in human primary cells and cell lines  in a human monocytic cell line rather than the earlier induction by P. gingivalis LPS at 0.5h (ST) [P. gingivalis LPS than E. coli LPS in monocytic cell lines [E. coli Ultrapure LPS (Invivogen), which is extracted by successive enzymatic hydrolysis steps and purified by phenol-triethylamine-deoxycholate extraction to remove bacterial lipoproteins that act as TLR2 ligands, specifically activates TLR4, while E. coli LPS purified simply by ion-exchange chromatography activates both TLR4 and TLR2 [E. coli LPS or E. coli Ultrapure LPS resulted in differences in time-course and strength of NF-κB dynamic responses [LPS is a prototypical PAMP and was the most widely used receptor ligand in the included studies. The bacterial origin, source and concentration of LPS can influence cell signalling , 35, 114gnalling . Most stfindings  correlat.5h (ST) . Bacterill lines . Moreoveesponses  or Ultraesponses . Sub-nanIRAK3 mRNA expression is induced from ST, and precedes IRAK3 protein expression at LT after one-challenge in human primary cells and cell lines Figs . It is nN respectively, in both human and mouse cell lines . TNF-α protein expression reaches peak levels at IT in human primary cells and human cell lines, but at LT in mouse primary cells , 35, 53.in vivo mice and human studies [In vitro cell models also demonstrated cytokine storm upon endotoxin stimulation, as confirmed for TNF-α and IL-6 at IT and LT in this review  [in vivo study where human subjects were administered LPS for five consecutive days reported the peak level of TNF-α at 1.5h (ST) on day 1 followed by peak level of IL-6 at 2h–3h (ST) [in vivo models injected with LPS also show significant increases in IRAK3 mRNA levels from ST to LT and protein levels at LT [in vivo models than in vitro cell models. Differences in inflammatory responses between in vitro and in vivo models can be due to the involvement of other regulators such as glucocorticoids or neuroprotective peptides present in vivo model [One-challenge intervention model mimics the initial hyper-inflammatory phase of sepsis. The hyper-inflammatory phase presents with dramatic increases of various potent cytokines  including TNF-α and IL-6 in patients with sepsis, and in  studies , 119. IL studies . TNF-α l studies . Moreove studies . In vitrs review . A human.5h (ST) . Another–3h (ST) . Mice inls at LT , 125, wils at LT , 126 andls at LT , 127. Thvo model .et al. [The effect of IRAK3 on NF-κB activity differs when challenged with IL-1β or LPS , 12, 22,et al.  and thenet al. , 96, 105et al. . Howeveret al. . It is aet al. . TherefoH. influenzae infection in cell lines and mouse primary cells, thereby decreasing H. influenzae–induced expression of inflammatory cytokines including TNF-α and IL-6 at 24h (LT) in wildtype mice, but this suppressive effect is disabled in IRAK3 knockout mice [Glucocorticoids are potent anti-inflammatory agents with evidence for beneficial effects in severe sepsis treatment. Long-course administration of low-doses of corticosteroid reduced mortality of patients with sepsis and the length of stay in the intensive care unit , 132. Onout mice . Anotherout mice . Treatmeout mice . Thus, bout mice , 134.ex vivo treated with endotoxin and in vivo mouse or human models similarly reported profound reduction of TNF-α and IL-6 [in vivo human study performing LPS administration for five consecutive days showed a significant attenuation of TNF-α and IL-6 on the fifth compared to levels on the first day [This review indicates significant increases in IRAK3 mRNA and protein expression, and reductions in TNF-α and IL-6 protein level between 1h and 24h following the second challenge Figs  and 8. Tand IL-6 , 123. Foirst day , 21, 44.irst day .ex vivo LPS challenge [et al. [ex vivo LPS challenge than in samples of healthy controls, which reflects a hyper-inflammatory response phase of sepsis similar to the meta-analysis of one-challenge (In vitro models of human cell lines and primary cell cultures at 4h (IT) after one-challenge or two-challenges with LPS or bacteria showed significant effects of interventions on IRAK3, TNF-α and IL-6 protein expression which are comparable to outcomes reflecting the two phases of sepsis in patients. Thus, in vitro cell culture models challenged with bacteria or LPS can mimic sepsis conditions and are useful to study the molecular functions of IRAK3 in endotoxin tolerance and sepsis. However, blood samples from sepsis patients need to be tested for IRAK3, TNF-α and IL-6 protein levels at more time intervals after endotoxin challenge to clarify whether the patterns of temporal expression of these molecules reflect in vitro human cell culture models. Such studies also need to consider the phase at which the blood is collected from the sepsis patients.Identifying the time frames of these events in different cell models is relevant, as IRAK3 is involved in sepsis pathophysiology , 135. Thhallenge  or decrehallenge , whereashallenge . PotentiTo our knowledge, no review involving meta-analyses aimed at elucidating how IRAK3 impacts inflammation through modulation of inflammatory markers has been conducted to date. The systematic search conducted reduced the likelihood of missing relevant studies. Meta-analyses are carried out to consolidate varied results from different studies. The consistency of meta-analyses can be influenced by the large values of heterogeneity across the included studies. While low levels of heterogeneity were observed between cell line studies, higher levels of heterogeneity were observed across both mouse and human primary cell studies. These high levels of heterogeneity could be influenced by diverse behaviours of different cell sources or donors, whereas cell lines are stably-established. Where high levels of heterogeneity occurred between studies, this was considered while interpreting results. Several studies from the final library could not be included in meta-analyses; for instance, they differed in intervention chemicals, or the format of reported data was inappropriate for meta-analysis. In order to perform meta-analyses for each outcome, data must be in the similar measurement unit and format , and arranged in appropriate comparison groups . Moreover, study data should indicate mean values, precise number of samples (n), and standard deviation or standard error. Another limitation arises from the number studies employing specific techniques on the cell types examined identified in this review. For example, only one study used human primary cells in which IRAK3 was silenced .in vivo studies may lead to further understanding of IRAK3 action on inflammation and identify possible differences between in vitro and in vivo models.This systematic review and meta-analyses reveals temporal patterns of IRAK3 mRNA and protein expression, NF-κB activity and TNF-α and IL-6 protein expression following one- or two-challenge interventions in cell lines, human and mouse primary cells . In cellS1 Checklist(DOC)Click here for additional data file.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.


Due to higher precision and consequent sparing of normal tissue, pancreatic cancer patients might profit from proton beam radiotherapy, a treatment modality increasingly used. Since molecular data upon proton irradiation in comparison to standard photon radiotherapy are limited in pancreatic cancer, the aims of our study were to unravel differences in the effectiveness of photon versus proton irradiation and to exploit radiation type-specific molecular changes for radiosensitizing 3D PDAC cell cultures. Although protons showed a slightly higher effectiveness and a stronger induction of molecular alterations than photons, our results revealed a radiation-type independent sensitization of molecular-targeted agents selected according to the discovered molecular, radiation-induced alterations.Pancreatic ductal adenocarcinoma (PDAC) is a highly therapy-resistant tumor entity of unmet needs. Over the last decades, radiotherapy has been considered as an additional treatment modality to surgery and chemotherapy. Owing to radiosensitive abdominal organs, high-precision proton beam radiotherapy has been regarded as superior to photon radiotherapy. To further elucidate the potential of combination therapies, we employed a more physiological 3D, matrix-based cell culture model to assess tumoroid formation capacity after photon and proton irradiation. Additionally, we investigated proton- and photon-irradiation-induced phosphoproteomic changes for identifying clinically exploitable targets. Here, we show that proton irradiation elicits a higher efficacy to reduce 3D PDAC tumoroid formation and a greater extent of phosphoproteome alterations compared with photon irradiation. The targeting of proteins identified in the phosphoproteome that were uniquely altered by protons or photons failed to cause radiation-type-specific radiosensitization. Targeting DNA repair proteins associated with non-homologous endjoining, however, revealed a strong radiosensitizing potential independent of the radiation type. In conclusion, our findings suggest proton irradiation to be potentially more effective in PDAC than photons without additional efficacy when combined with DNA repair inhibitors. Pancreatic cancer, with pancreatic ductal adenocarcinoma (PDAC) being the most common subtype, presents one of the top tumor types with unmet needs and only minimal advances in treatment outcome in recent years ,2. PDAC Due to the delicate localization of the pancreas close to the gastrointestinal tract, radiotherapy with photons is frequently used for metastatic PDAC or palliatively . With grDespite the first promising clinical results obtained for proton beam therapy of other tumor entities, little is known for PDAC. It further remains open whether proton irradiation induces similar or different modifications to the DNA and to signal transduction events and whether such differences might be exploitable for combinatorial therapies with biologicals ,8. In geTo comparatively elucidate the efficacy of proton versus photon irradiation and to identify novel potential therapeutic targets for these two radiation types in PDAC, we cultured PDAC cell lines under more physiological three-dimensional (3D), matrix-based conditions and examined their tumoroid formation capacity and phosphoproteome modifications. Our results indicate a cell-line-dependent higher efficacy for protons over photons regarding 3D PDAC tumoroid growth. Combination treatments with RTK, cytoplasmic protein kinase and DNA repair inhibitors showed an inhibitor- and cell-line-specific cytotoxic and radiosensitizing potential, which presented as equipotent for photons and protons and with a strong non-homologous endjoining (NHEJ) dependency in our PDAC cell line panel.We commenced our study by a comparative tumoroid growth analysis upon photon and proton irradiation in a panel of five human PDAC cell lines grown in physiological laminin-rich extracellular matrix (lrECM) A. While We next sought to unravel potential differences in the molecular mechanisms causing the observed differential effectiveness between proton and photon irradiation in PDAC cell cultures. Hence, we performed a screening in form of a broad-spectrum phosphoproteome analysis A. 3D lrEA more rigorous analysis focused on phosphorylation sites with an increase of 50% or higher, aiming to identify potential radiosensitizing targets specific to protons, photons or both. For photons, Merlin (p-Ser10) was the only shared unique candidate among 39 phospho-sites in 3D Colo357 and MiaPaCa-2 cell cultures . Upon prIn summary, proton irradiation led to greater changes in phosphorylation events than photon irradiation in 3D PDAC cell cultures, and our analysis revealed a strikingly different pattern of phosphorylation events for proton and photon irradiation.®, MSD SHARP & DOHME GMBH, Haar, Germany) and the small molecule inhibitor lapatinib were applied for HER2 and prexasertib, a small molecule inhibitor, for Chk1.The list of all proteins showing a ≥50% increase in phosphorylation that entailed enhanced enzymatic activity prompted us to search for both radiation-type-specific and non-specific targets F. Out ofConcerning basal tumoroid growth after treatment, we found only moderate effects in both analyzed cell lines, Colo357 and MiaPaCa-2 B. In comTaken together, despite detectable changes in protein phosphorylation in the phosphoproteome analysis, we were unable to therapeutically exploit these differences uniquely for PDAC cell sensitization to either photon or proton irradiation.We subsequently conducted a screen with inhibitors deactivating either RTK signal transduction  or DNA repair processes , PARPi, Rad51i). While 3D tumoroid growth of Colo357 cells was diminished upon EGFRi, VEGFRi and Rad51i, MiaPaCa-2 tumoroid growth remained unaffected A. Cell-lIn conclusion, we found effective signal transduction inhibitors such as PI3Ki and DNA repair inhibitors as radiation type-independent radiosensitizers. Notably, the screen pointed at specific DNA repair inhibitors associated with NHEJ.The DNA damage response, in general, plays a pivotal role in tumor cell survival and the associated DNA repair enzymes are considered as ideal therapeutic targets. We next sought to confirm the different DNA repair inhibitor efficacies for radiosensitization in our larger PDAC cell line panel. Single pharmacological inhibition of Rad51, PARP, DNA-PK and ATM indeed echoed the results observed in the Colo357/MiaPaCa-2 cell model screen A. OveralConclusively, the data generated in our PDAC cell line panel revealed the classical and alternative NHEJ DNA repair pathways as candidate targets for sensitization to proton- and photon-based radiotherapy.Given the higher precision accompanied by optimized sparing of normal tissue, proton beam irradiation is considered more favorable for PDAC patients than photon irradiation. However, supportive large clinical datasets, as well as systematic preclinical insights, are lacking. To address this point, we conducted a preclinical study in a panel of PDAC cell lines grown in 3D extracellular matrix with and without molecular-targeted pretreatments. Our study revealed an equal or higher efficacy of low-LET protons over photons in terms of reducing PDAC tumoroid formation. Moreover, we showed a greater extent of phosphoproteome alterations upon proton irradiation compared with photon irradiation. The targeting of proteins identified in the phosphoproteome uniquely altered by protons or photons failed to mediate marked radiation type-specific radiosensitization. Instead, inhibition of DNA repair proteins acting in NHEJ revealed a strong radiosensitizing potential independent of the radiation type.These observations are in line with comparative survival analysis of proton versus photon irradiation in other tumor entities such as glioma stem cells ,10 or luTaking into consideration the therapeutic exploitability of the hallmarks of cancer represented by altered prosurvival signal transduction and the associated opportunities for treatment personalization ,17, we uNevertheless, we were able to discover three druggable targets from the array. Targeting the ER-α, unique for photon irradiation, and Chk1, for both photon and proton irradiation, resulted in moderate but significant radiosensitization irrespective of the radiation type. The ineffectiveness of trastuzumab-mediated HER2 deactivation in PDAC cell models observed in our study is in line with both preclinical and clinical findings but has not been addressed in combination with radiotherapy to date ,19. As tAs alternative approach, we widened the inhibitor spectrum, including candidates that are either validated molecular targets for other cancer types or are considered as potential cancer targets . Beyond Intriguingly, our conducted experiments revealed the efficacy of the selected inhibitors to be independent from the radiation type in 3D lrECM PDACcultures. Our data pinpoint two aspects: (i) the radiation type-unrelated strong dependence of PDAC cell survival on DNA repair; (ii) the great similarity in dependence on the same DNA repair machinery upon photon and proton irradiation. DNA double-strand breaks are repaired by two main DNA repair pathways, i.e., homologous recombination (HR) and NHEJ ,8. Our 3Concerning HR targeting, Colo357 cells were the only cell line strongly and marginally radiosensitized by Rad51 inhibition to photon and proton irradiation, respectively. Importantly, we were unable to confirm the reported greater cellular sensitivity towards protons under HR-deficiency in the here-presented 3D lrECM PDAC cell cultures ,36,37.All used primary antibodies for Chk1, phospho-Chk1 S345, Estrogen Receptor-α, phospho-Estrogen Receptor-α S118, HER2/ErbB2 and phospho-HER2/ErbB2 Y1248 were purchased from Cell Signaling . Secondary antibodies anti-mouse IgG, HRP conjugated and anti-rabbit IgG, HRP conjugated, were purchased from Pierce .2 at pH 7.4. In all experiments, asynchronously growing cells were used. All cells tested negative for Mycoplasma by using the mycoplasma detection kit Venor®GeM OneStep .Human pancreatic ductal adenocarcinoma (PDAC) cell lines BxPC3, MiaPaCa2, Panc-1, and Patu8902 were purchased from the American Type Culture Collection (ATCC). Colo357 cell lines were a kind gift from Chr. Pilarsky . The origin and stability of the cells were routinely monitored by short-tandem repeat analysis (microsatellites). All cell lines were cultured in Dulbecco’s modified Eagle medium  with 10% fetal calf serum  and 1% non-essential amino acids  at 37 °C with 8.5% COPDAC cells were seeded for 3D tumoroid formation assay, as published . In brieCells were irradiated at room temperature using 2, 4, or 6 Gy single doses of 200-kVp X-rays  filtered with 0.5-mm Cu, as published . The abs2 proton field and a SOBP of 26.3 mm (90% dose plateau) in water. Cells in tissue culture plates were irradiated at room temperature using two different setting to assure mid-SOBP position. For tumoroid formation assays 96-well plates were placed perpendicular to beam axis (90°), whereas for whole-cell lysates 24-well plates were positioned at 42° relative to beam axis to avoid destruction of 3D structure [Proton irradiation (low-LET of 3.7 keV/µm) was performed at the horizontal fixed-beam beam line in the experimental hall of the University Proton Therapy Dresden (UPTD). For 150 MeV protons, a dedicated beam shaping system consisting of a double-scattering device and a ridge filter provides a laterally extended 10 × 10 cmtructure . For abstructure .The RBE values were calculated as follows (1): The doses (D) were calculated as follows: data points were fitted in the linear-quadratic formula and the values for α and β were taken from the fitted curve. D was then solved at a SF of 50% from the following Formula (2): g for 20 min to remove debris. The chemiluminescent detection was performed using ECL™ Prime Western Blotting System (Sigma-Aldrich). Densitometric analysis was carried out with ImageJ. In Whole-cell lysates, SDS-PAGE and Western blotting were performed as previously described in . In brie®, Roche, Basel, Switzerland; 10 µM), ER-α , HER2 , MAPK , MDM2 , MEK , MRNcomplex , PI3K , PARP , Rad51  and VEGFR  with the indicated concentrations. Ethanol (for Hydroxy-Tamoxifen), IgG (for Ontruzant) and DMSO  were used as controls.Cells were treated with pharmacological inhibitors for ATM  Chk1 , DNA-PK , EGFR  and a p value of less than 0.05 was considered statistically significant.Means ± standard deviation (SD) of at least three independent experiments were calculated. For statistical significance analysis of tumoroid formation capacity, two-sided Student’s In summary, our comparative study unravels a cell-line-dependent higher efficacy of proton over photon irradiation. Phosphoproteome analysis revealed different phosphorylation patterns induced by photon and proton irradiation, the latter leading to more critical changes 1 h post-irradiation. Contrary to our hypothesis, we could not find any radiation-type-specific targets in this dataset that can be used for a clear radiosensitization in a cell line-dependent manner. Instead, we discovered that a radiosensitization mediated by the inhibition of specific kinases occurs to a similar extent for protons and for photons in a panel of PDAC cell line cultures under more physiological 3D, matrix-based conditions. Considering the translation of these results to the treatment of patients suffering from PDAC, further insights are required to better discriminate the differences in sensitivity towards proton versus photon irradiation. Despite the great benefit of higher precision, and sparing of normal tissue, our data fail to clearly document a benefit of the co-application of biologicals to proton beam irradiation over photon irradiation.


CHEK1, PIK3CA, and PIK3CD was significantly upregulated in OSCC. The antitumor efficacy of CHK1 inhibitors  and PI3K inhibitors  was investigated in OSCC cell lines and PDX models. Targeting either CHK1 or PI3K effectively inhibited cell proliferation and colony formation by inducing cell cycle arrest and apoptosis in in vitro cell-based assays. Cisplatin-based chemotherapy combined with CHK1 inhibitor treatment synergistically inhibited cell proliferation by suppressing CHK1 phosphorylation and inducing PARP cleavage. Furthermore, compared with monotherapy, cotreatment with CHK1 and PI3K inhibitors exerted synergistic anticancer effects by suppressing CHK1, AKT, and 4E-BP1 phosphorylation. In summary, our study identified CHK1 and PI3K as promising targets, especially in a dual treatment strategy combining a CHK1 inhibitor with cisplatin or a PI3K inhibitor as a novel therapeutic approach for OSCC patients with aberrant cell cycle regulation and PI3K signaling activation.Oral cavity squamous cell carcinomas (OSCCs) are aggressive tumors, and their recurrence leads to poor prognosis and reduced survival rates. This study aimed to identify therapeutic targets and to evaluate the efficacy of targeted inhibitors in OSCC patient-derived xenograft (PDX) models. Herein, we reported that OSCC PDXs recapitulated the genomic signatures of their paired primary tumors and the expression of  Oral cavity squamous cell carcinoma (OSCC) is an aggressive tumor and is the most common malignancy of the oral cavity, accounting for up to 90% of all malignant neoplasms of the oral cavity ,2,3. TheDysregulation of the cell cycle, apoptosis, and/or DNA damage response pathways is a common cause for the development of cancers, including oral cancer . TherefoCHEK1, PIK3CA, and PIK3CD are significantly upregulated in OSCC and provide evidence that a dual treatment strategy that combine a CHK1 inhibitor with a PI3K inhibitor or cisplatin is a potential therapeutic option for patients.Cancer cell lines derived from tumor tissues have been widely used for the development of cancer treatment approaches. However, because of the genetic variations and lack of tumor microenvironment in vitro, cell lines may not be fully useful for establishment of treatment methods. PDX models are recognized as accurate and clinically relevant models and are used as powerful tools for characterizing tumor biology and screening drugs ,20,21. HTP53, FAT1, NOTCH, PIK3CA, and CDKN2A [TP53 and CDKN2A mutations; Patient #2 harbored TP53, FAT1, and PIK3CA mutations; and Patient #3 harbored a TP53 mutation  in the 39 paired OSCC transcriptome datasets were analyzed with the DAVID and GSEA bioinformatics tools. The significantly enriched cancer-associated pathways included the cell cycle, PI3K-AKT signaling pathway, focal adhesion, and ECM-receptor interaction (We cross referenced these data with our previously published OSCC transcriptome datasets containing 39 paired samples (uploaded to the NCBI Sequence Read Archive (SRA) database under accession code SRP078156). The upregulated genes , is a critical regulator of the DNA damage response (DDR) [CHEK1 in OSCC tumors was further validated by quantitative real-time PCR and immunohistochemical (IHC) staining in 25 paired samples from OSCC patients . Cervical lymph nodes are a common site of regional metastasis in OSCC, and cervical lymph node metastasis suggests an increased risk of local or regional recurrence.We then examined promising drug targets in the cell cycle and PI3K-AKT pathways and further evaluated drug efficacy in the SAS, OC3, and OEC-M1 cell lines, as well as in CDXs and PDXs. One of the druggable targets, checkpoint kinase 1 (se (DDR) , and waspatients b,c. The  samples . CHEK1 oPIK3CA and PIK3CD, which are involved in ECM-receptor interaction and PI3K signaling, was also significantly increased in the 39 paired OSCC transcriptome datasets and in the TCGA datasets, as shown by RNA-seq  for PF477736 in SAS and OC3 cells ranged from 120 to 320 nM, whereas the IC50 concentration in OEC-M1 cells was 10 μM , suggesting that the low susceptibility of OEC-M1 cells to the inhibitors may result from the dysregulation of genes involved in multidrug resistance mechanisms.To evaluate the antitumor effect of the small molecule inhibitors that targeted the two potential proteins, CHK1 and PI3K, we first assessed cell proliferation after CHK1 inhibitor  or PI3K inhibitor  treatment in OSCC cell lines . In OSCC cell lines, compared with the vehicle control treatment, the PF477736 treatment decreased cell proliferation, as assessed by MTT assays a. The haas 10 μM a. The ICThe colony-forming abilities of SAS and OEC-M1 cells were significantly decreased after PF477736 treatment b. Simila50 for cisplatin in the SAS, OC3, and OEC-M1 cell lines ranged from 5 to 10 μM. To evaluate the antitumor effects of combining cisplatin-based chemotherapy with CHK1 inhibitor treatment, we then assessed cell proliferation in OSCC cell lines treated with combinations of cisplatin and PF477736. Interestingly, compared with control and single-agent treatment, combination treatment with cisplatin and PF477736 significantly decreased the proliferation of the OSCC cells  targeting the PI3K pathway were also evaluated in this study. The PI3K inhibitor BYL719 significantly decreased cell proliferation, as shown by MTT assays a and colto 20 μM a. Furtheto 20 μM c. All thto 20 μM . To evalto 20 μM d. Combinto 20 μM . These f3, the mice were divided into different experimental groups. At concentrations of 10 or 20 mg/kg, the CHK1 inhibitor PF477736 partially but not significantly inhibited tumor growth compared with that in the control group  and sensitivity to Chk1 inhibition was reported in HNSCC cell lines [CDKN2A mutation or CDKN2A deletion was detected in OSCC Patients #1 and #3 but not in Patient #2. The therapeutic response to combination therapy with cisplatin and the CHK1 inhibitor was significantly stronger than that to monotherapy in Patient #2, suggesting that CHK1 targeting combined with cisplatin treatment may also be beneficial in patients with wild-type CDKN2A. Moreover, other molecules involved in cell cycle regulation may have been altered, and more models with/without mutation of only CDKN2A must be tested.CHK1, a serine/threonine-specific protein kinase, regulates the DDR, cell cycle checkpoints, and DNA repair mechanisms ,27. CHK1blastoma ,31,32,33ll lines . We firsn cancer ,35. Addik cancer . Additioplatform . In the ll lines . The p.RPIK3CA and PIK3CD were overexpressed in OSCC clinical specimens. Additionally, the PI3K inhibitors  can inhibit cell proliferation and induce cell death in OSCC cell lines. Alpelisib (BYL719) is a PI3K alpha-specific inhibitor with antitumor activity in vitro and in vivo [The PI3K-AKT signaling pathway is another pathway dysregulated in head and neck cancer, leading to growth factor-independent cell proliferation in tumors . In this in vivo ,41. PI3KKinase inhibitors may produce off-target effects by inducing changes in molecules other than the specifically targeted molecule. For instance, PF477736, one of the CHK1 inhibitors used here, can target VEGFR2, Aurora A, and CHK2 ; howeverCHEK1, PIK3CA, or PIK3CD, combination therapy with a CHK1 inhibitor and a PI3K inhibitor could be suggested for consideration.Clinically, if OSCC patients undergo genetic testing to identify increased expression of CHEK1 qRT-PCR analysis and univariable analysis , Taiwan. Prior to sample collection, written informed consent was obtained from all participants. Primary tumors from three late-stage OSCC patients were successfully transplanted and expanded into immunodeficient mice . Tumor aanalysis .2.SAS cells were maintained in Dulbecco’s modified Eagle’s medium  containing 100 U/mL penicillin and 100 μg/mL streptomycin and supplemented with 10% fetal bovine serum . OEC-M1 cells were maintained in Roswell Park Memorial Institute (RPMI) 1640 medium , and OC3 cells were maintained in DMEM supplemented with keratinocyte serum-free medium  and containing antibiotics and 10% FBS. All cell lines were cultured at 37°C in a humidified atmosphere containing 5% COThe CHK1 inhibitors PF477736 , AZD7762 , and LY2606368 ; as well as the PI3K inhibitors GDC0941  and GSK1059615  were used. The PI3K inhibitor BYL719 was kindly provided by Novartis Pharma AG . Cisplatin was purchased from Sigma-Aldrich. Antibodies against the following molecules were used for immunoblotting: CHK1, p-CHK1-Ser296, AKT, p-AKT-Ser473 , and GAPDH .http://www.broadinstitute.org/gsea/msigdb) database; the hallmarks were screened to include only those highly linked to cancer according to Drake et al [p values  returned by the DoGsea function.Total RNA from the paired tumor tissues and xenografts was extracted using TRIzol Reagent (Gibco BRL), and the RNA quality and quantity were confirmed using an Agilent 2100 Bioanalyzer . For RNA-seq, libraries were prepared using the TruSeq Stranded mRNA Sample Preparation Guide  according to the manufacturer’s instructions. Sequencing was conducted in an Illumina NextSeq 500 instrument. Transcriptome and pathway analyses were performed as previously described . Cancer ke et al . Enrichmke et al . HallmarGenomic DNA was extracted from tumor and normal tissues using the QIAamp DNA Mini Kit (Qiagen) in accordance with the manufacturer’s protocols. The quality and DNA concentrations of the samples were assessed with a Qubit fluorometer (Thermo Fisher Scientific) and 0.8% agarose gel electrophoresis. For whole-exome sequencing and bioinformatic analysis, high-quality genomic DNA was captured using a SureSelect Human All Exon V6 + COSMIC Kit according to the manufacturer’s protocol (Agilent Technologies) and analyzed as previously reported .For quantitative PCR, first-strand complementary DNA was synthesized from 1 μg of total RNA using random hexamer primers  and SuperScript III RT . The sequences of the primers were as follows: CHEK1-F (5’-TCGGTATAATAATCGTGAGCG-3’), CHEK1-R (5’-ACAGGACCAAACATCAACTG-3’), PIK3CA-F (5’-ACGATGGACAACTGTTTCA-3’), PIK3CA-R (5’-GTCTTTGTGCATTCTTGGG-3’), PIK3CD-F (5’-GACATCCAGTATCTCAAGGAC-3’), PIK3CD-R (5’-AGCCAGTTCACTTTGGTT-3’), TBP-F849 (5’-TGCTCACCCCACCAACAATTTAG-3’), and TBP-R969 (5’-CTGGGTTTGATCATTCTGTAGATTAA-3’).For cell cycle analysis, cells were treated as indicated for 24 h. Cells were fixed with 70% ethanol, stained with 50 µg/mL propidium iodide  and analyzed by flow cytometry. For the cell viability assay, cells were treated for 48 h. MTT (5 mg/mL) was then added to each well for the MTT cell viability assay. After incubation for 1 h, the supernatant was discarded, DMSO (100 μL) was added, and the absorbance was measured at 540 nm in a spectrophotometer . For the apoptosis assay, cells were treated at the indicated concentrations for 48 h and were then stained with a FITC-conjugated Annexin V antibody  and propidium iodide . Cells were evaluated by flow cytometry , and the data were analyzed with FlowJo software .3VO4, 5 mM EDTA, 10% glycerol, PMSF, and 0.2% protease inhibitor). Equal amounts of protein were separated by SDS-PAGE and transferred to a PVDF membrane, which was incubated with the appropriate primary antibodies. Immunoreactions were detected with HP-conjugated secondary antibodies and ECL substrate .Total protein was extracted with RIPA lysis buffer  and stained with antibodies against CHK1 (Abcam), phosphorylated AKT (Abcam), and Ki67 . The remaining steps were performed in accordance with standard procedures.scid Il2rgtm1Wjl/SzJ (NSG) mice (obtained from The Jackson Laboratory) were housed in a specific-pathogen-free animal room. All animal experiments were approved by the Institutional Animal Care and Use Committee of Chang Gung University (Protocol Nos: CGU106-114 and CGU107-074). For PDX establishment, patient tumor explants were obtained from surgical specimens and engrafted in NSG mice within 2 h. In brief, fresh tumor tissues were rinsed in PBS containing an antibiotic-antimycotic solution  and cut into small pieces (~1 mm3). Each NSG mouse was subcutaneously inoculated with a tumor fragment weighing 50–100 mg in the left flank to establish the first-generation (P1) PDX. When the tumors attained an average volume of 1000 mm3, they were excised and were then transplanted and expanded to establish the next generation (P2). When the tumors attained an average volume of 300–500 mm3, the mice were assigned randomly to the control and various experimental groups. For drug tests in the PDX models, 20 mg/kg PF477736 was administered by intraperitoneal injection (4 days in the first week). BYL719 (50 mg/kg) was administered by oral gavage (5 days/week for two weeks). Cisplatin (5 mg/kg) was administered by intraperitoneal injection (2 days in the first week). To establish the SAS cell line-derived xenografts, 100 µL of a SAS cell suspension (5 × 106 cells per ml) was injected subcutaneously into NOD/SCID mice, and tumors were established after 3–4 weeks. When the xenografts attained a volume of 300–500 mm3, the mice were randomly divided into the experimental and control groups. PF477736  was administered by intraperitoneal injection (4 days in the first week). BYL719 (25 or 50 mg/kg) was administered by oral gavage (5 days/week for two weeks). Cisplatin (5 or 10 mg/kg) was administered by intraperitoneal injection (2 days in the first week). Tumors were measured with calipers, and the volume was calculated as follows: volume = 1/2 × length × width2.NOD/SCID mice  and NOD.Cg-Prkdct-tests or the Mann–Whitney U tests. All statistical tests were performed with SPSS software version 12.0  or Prism. A p value of < 0.05 was considered to indicate a statistically significant difference.The Wilcoxon test was used to analyze the qRT-PCR results for OSCC and normal counterpart tissues. Between-group comparisons were performed with Student’s CHEK1, PIK3CA, and PIK3CD were significantly increased in both the primary tumor tissues and xenografts. The antitumor efficacy of CHK1 inhibitors and PI3K inhibitors was validated in vitro and in vivo. Targeting either CHK1 or PI3K effectively induced cell cycle arrest and apoptosis in OSCC cells. Combination therapy with cisplatin-based chemotherapy and a CHK1 inhibitor exhibited a synergistic antitumor effect. Furthermore, combination therapy with CHK1 and PI3K inhibitors resulted in greater therapeutic efficacy than treatment with either agent as monotherapy via suppression of CHK1, AKT, and 4E-BP1 phosphorylation. Overall, our results provide proof of principle for CHK1 inhibition in combination with either PI3K inhibition or cisplatin treatment as a novel therapeutic strategy for OSCC (In this study, OSCC PDX preclinical models were established, and their therapeutic implications were explored. Notably, the expression levels of for OSCC f.


High-content screening is an important tool in drug discovery and characterization. Often, high-content drug screens are performed on one single-cell line. Yet, a single-cell line cannot be thought of as a perfect disease model. Many diseases feature an important molecular heterogeneity. Consequently, a drug may be effective against one molecular subtype of a disease, but less so against another. To characterize drugs with respect to their effect not only on one cell line but on a panel of cell lines is therefore a promising strategy to streamline the drug discovery process.The contribution of this article is 2-fold. First, we investigate whether we can predict drug mechanism of action (MOA) at the molecular level without optimization of the MOA classes to the screen specificities. To this end, we benchmark a set of algorithms within a conventional pipeline, and evaluate their MOA prediction performance according to a statistically rigorous framework. Second, we extend this conventional pipeline to the simultaneous analysis of multiple cell lines, each manifesting potentially different morphological baselines. For this, we propose multi-task autoencoders, including a domain-adaptive model used to construct domain-invariant feature representations across cell lines. We apply these methods to a pilot screen of two triple negative breast cancer cell lines as models for two different molecular subtypes of the disease.https://github.com/jcboyd/multi-cell-line or https://zenodo.org/record/2677923.Bioinformatics online. A high-content drug screen corresponds to a series of imaging experiments under controlled conditions, where a cell line representative of some disease is exposed to a large panel of drugs. For each drug, one obtains a set of images informative of its phenotypic effect and hence on the biological pathways undergoing perturbation. Various advances in microscopy automation and image analysis have pushed HCS to the early The discovery of new drugs may be guided by a reference set of drugs of known mechanism of action (MOA). The MOA of a drug is the particular cellular pathway it perturbs to achieve its effect. Through application of image analysis, one may attempt to infer the MOA of an unknown drug from HCS image data. Note that MOA can be defined at different levels and with different degrees of specificity: MOA might concern the exact protein that is targeted (e.g. AURKA inhibition), or a specific effect on cellular components (e.g. stabilization of microtubuli) or perturbation of a more general cellular pathway (e.g. DNA repair). HCS is usually optimized with respect to particular pathways by the choice of the fluorescent markers and readouts . ConsequA second difficulty concerns the cellular model that is used. As a proxy for diseased cells, a cell line cannot be thought of as a perfect model. Many diseases feature a significant molecular heterogeneity. Consequently, a drug may be effective against one molecular subtype of a disease, but less so against another. Furthermore, immortalized cell lines may diverge over time due to genetic drift. For example, HeLa, the quintessential cell line, is famously the cause of great scientific confusion due to difficulties in cell line identification  and signThe contribution of this article is 2-fold. First, we investigate whether we can predict MOA at the molecular level without optimization of the MOA classes to the screen specificities. To this end, we benchmark a set of algorithms within a conventional pipeline, and evaluate their MOA prediction performance according to a statistically rigorous framework.Second, we extend this conventional pipeline to the simultaneous analysis of multiple cell lines, each with potentially different morphological baselines. For this, we propose multi-task autoencoders, including an adaptive model used to construct domain-invariant feature representations across cell lines. We apply these methods to a pilot screen of two triple negative breast cancer (TNBC) cell lines as models for two different molecular subtypes of the disease.In Section 2, we describe our dataset. In Section 3, we formalize a range of profiling approaches from the literature according to four key properties, and extend this to a multi-cell-line analysis. In Section 4, we illustrate the benefit of multi-task models for our dataset through extensive cross-validation and provide an exploratory analysis of differential drug effects between the two cell lines. In Section 5, we discuss our methods and the obtained results.https://zenodo.org/record/2677923). MDA231  and MDA468 (TP53-PTEN) were both established from a pleural effusion of two different patients with triple negative metastatic breast carcinoma. Using transcriptomic and genomic data, we have recently shown that MDA468 clustered in a breast cancer specific subgroup but MDA231, one of the most used breast cancer cell lines, clustered in a mixed subgroup with cancer cell lines of very different origins, such as ovarian, urinary and kidney , thus constituting a multi-cell-line drug screen (the full image set for this study is available at γH2AX to mark DNA double-strand breaks) and (iii) Cyanine 5 . Together, these fluorescent channels paint a rich, composite picture of the cell populations.Both of our cell lines were subjected to the same inventory of drugs on separate 384-well microtiter plates (microplates): 36 wells contained the negative control dimethyl sulfoxide (DMSO); two the positive controls ; 166 the test compounds; and 184 empty. For each well of our two microplates, images were taken in four non-overlapping fields of view (fields), with three multiplexed fluorescent channels: (i) DAPI (cell nuclei) (ii) Cyanine 3 , PKC inhibitors, protein tyrosine phosphatase inhibitors and tyrosine kinase inhibitors.In comparison with other datasets, This section describes the approaches for phenotypic profiling we have benchmarked. We embed these descriptions in a formalized overview of phenotypic profiling strategies to motivate the different setups. In Section 3.3, we describe methods for a joint analysis of multiple cell lines.MOA, the cellular pathway perturbed by the drug, as depicted in leave-one-compound-out cross-validation (LOCOCV) scheme. At each fold of the cross-validation, we hold out a drug and predict its MOA class using a classifier trained on the remaining ‘reference’ drugs. The prediction is made as the nearest neighbor (1-NN) in cosine distance between drug profiles, Drugs are assigned a class based on their D and is constructed according to four ordered methodological stages: measurement unit, feature representation, dimensionality reduction and aggregation strategy . We segmented cell nuclei on the DAPI channel by subtracting a background image formed with a mean filter, before clipping to zero. Touching nuclei were further separated by applying the watershed transform on the inverse distance map of the foreground image. The cytoplasm was segmented from the microtubule channel (Cy5) following The most common measurement unit is the cell itself, constituting a per-image analysis, such as in segmentation-free, as they obviate the segmentation phase of the conventional pipeline. In this study, we deliberately choose to focus on the cell as unit of measurement.Alternatively, one might analyze the image field directly in a 3.2.2N is the number of samples for that well and D is the number of features measured. For each segmented cell we extracted a previously published set of features  following the design of 3.2.3M < D. The objective is to capture the essential information in lower dimension or to cast the high-dimensional feature vector to an interpretable representation. Supervised classification of individual cells  (M =  8). Necessarily, we partition wells into separate train and test sets, where the test data alone is used to build profiles for the MOA prediction downstream.Dimensionality reduction requires some function M  =  80 and  100 clusters, respectively . K-means is fast to fit approximately, in particular using mini-batch training. On the other hand, even using optimized software —on handcrafted features. We also train deep CAEs directly on image pixels, as described in Section 3.2.2. Note that such models perform both feature extraction and dimensionality reduction simultaneously. Here, the encoder consists of 5 × 5 and 3 × 3 convolutional layers, with 16 and 8 kernels, respectively, and a fully connected layer (M = 128), each alternating with max pooling layers. The decoder mirrors this, albeit replacing pooling with upsampling.Autoencoders, as used by 3.2.4p. A variable number of cells per well requires an aggregation strategy yielding a profile of fixed size. The most straightforward approach is an element-wise averaging as in Once all cells are endowed with a representation, one needs some means of reducing the population to a single profile, Alternatively, One can extend the above MOA prediction framework for multiple cell lines either by pooling data or by ensembling models. In a pooling analysis such as We adopted a pooling approach to predict MOA from multiple cell lines. The challenge of this approach is to reconcile the inherent differences between the cell lines in feature space, which derives from the fundamental morphological differences of the cell lines. For this purpose, we tested multi-task autoencoders , extensi3.3.1Multi-task models learn to predict multiple targets simultaneously and multi-task neural nets often build more generalized internal representations . We propid identifies the cell line of One obvious design is to have separate decoders for each cell line with a shared encoder. During training, minibatches can be split after the shared layers with samples routed to the decoder corresponding to their cell line. We thus minimize,x. That is, given source and target domains, and given a hypothesis class domain-invariant features in the earlier, shared layers of the network.The fundamental morphological differences between the cell lines can be quantified in feature space by a increase the reconstruction error of the autoencoder. However, we hypothesize that the domain-invariant features learned will be more useful to the downstream MOA prediction when combining heterogeneous cell line data. For example, with a single additional affine layer, ω is a modulating hyperparameter. However, now the parameters of maximize minimize gradient reversal pseudo-layer , to promote domain-invariant representations between the cell lines. This consists of attaching a domain discriminator We test multi-task versions of both our affine and CAEs, and compare them directly in Section 4.2. The domain discriminator of our DAAs is linear in terms of the encoding (domain-invariant features) and the weight of the log loss was tuned to lgorithm . For thelization , which wWe compared different profiling settings by evaluating performance on a MOA prediction task. For this, we balanced our datasets by randomly sampling 5 drugs from each of the 8 classes specified in Section 2, analyzing 40 drugs at a time. Applying the LOCOCV scheme described in Section 3.1, we note that random accuracy is 12.5%. To account for random variability, we repeated LOCOCV 60 times with different sets of randomly sampled drugs and in Section 4 report average top-1 accuracy and standard deviation as the percentage of MOAs correctly predicted by the 1-NN classifier. We consider this to be a more rigorous approach in a comparative study, as while a given method often fit one drug set well, it was harder to find hyperparameter choices that worked well across all sets. We used a Wilcoxon signed-rank test to establish significance against baselines over the 60 rounds.We use Cell Cognition (scikit-learn (Keras (https://keras.io) https://github.com/jcboyd/multi-cell-line). Basic image processing was performed with scikit-image  on Euclidean distance in 4.2.3We ran a separate experiment controlling for the aforementioned bias to attempt to measure the effective power of heterogeneous cell line data. To do this we created equally sized samples: 10 000 randomly subsampled cells from the MDA231 cell line; 10 000 randomly subsampled cells from the MDA468 cell line; and 5000 cells sampled from each cell line and pooled into a multi-cell-line dataset. We did this for the handcrafted features of segmented cells, averaged element-wise, again repeated over the 60 experimental folds. We found the pooled samples yielded an average accuracy of 20.89, significantly improving over the pure MDA231 sample at 14.94 4.2.4K cell lines with K > 2, the log loss in ith sample, and all other terms are defined as before. We found that this simple modification sufficed to train effectively on the new dataset, provided ω was reduced as the number of cell lines increased. In To test how our model behaves with increasing numbers of cell lines, we acquired image data without drug perturbation of a third TNBC cell line (MDA-MB-157) under the same protocol as the pilot screen. In order to apply domain adaptation to As stated earlier, this new dataset was not a drug screen and therefore we could not evaluate our model in the same way as before. We were, however, able to pre-train our model on this morphological screen and transfer it to our drug screen to be used as a feature encoder directly. When compared with an equivalent vanilla autoencoder our model performed marginally better for three cell lines (32.08 compared with 31.17)  pairs. This is one of the most important use cases if the cell lines represent different molecular subtypes of a disease. Importantly, it allows one to identify highly specific drugs that only act on one particular subtype—the paradigm of precision medicine—and to distinguish them from drugs that are generally effective across different subtypes, as well as from drugs that lead to different phenotypic effects, which in turn suggest a target of different pathways depending on the transcriptional program.Although these approaches have only been applied to a small-scale pilot study, they provide an interesting starting point for larger multi-cell-line screens.J.C.B. has a PhD fellowship granted by PSL Research University.Conflict of Interest: none declared.btz774_Supplementary_DataClick here for additional data file.


TP53 mutations indicate YM155 resistance. Here, the investigation of 10 additional YM155-adapted UKF-NB-3 sublines only confirmed the roles of ABCB1 and SLC35F2. However, cellular ABCB1 and SLC35F2 levels did not indicate YM155 sensitivity in YM155-naïve cells, as indicated by drug response data derived from the Cancer Therapeutics Response Portal (CTRP) and the Genomics of Drug Sensitivity in Cancer (GDSC) databases. Moreover, the resistant sublines were characterized by a remarkable heterogeneity. Only seven sublines developed on-target resistance as indicated by resistance to RNAi-mediated survivin depletion. The sublines also varied in their response to other anti-cancer drugs. In conclusion, cancer cell populations of limited intrinsic heterogeneity can develop various resistance phenotypes in response to treatment. Therefore, individualized therapies will require monitoring of cancer cell evolution in response to treatment. Moreover, biomarkers can indicate resistance formation in the acquired resistance setting, even when they are not predictive in the intrinsic resistance setting.Survivin is a drug target and its suppressant YM155 a drug candidate mainly investigated for high-risk neuroblastoma. Findings from one YM155-adapted subline of the neuroblastoma cell line UKF-NB-3 had suggested that increased ABCB1 (mediates YM155 efflux) levels, decreased SLC35F2 (mediates YM155 uptake) levels, decreased survivin levels, and  BIRC5 gene, which encodes the protein survivin [Sepantronium bromide YM155) was introduced as an anti-cancer drug candidate that inhibits expression of the 55 was insurvivin ,11,12,13A number of studies have investigated the potential of YM155 against neuroblastoma cells ,15,16,17The formation of acquired resistance is a central problem in (metastasized) cancer diseases that need to be treated by systemic drug therapy. Although many cancers initially respond well to therapy, resistance formation is common, and cures are rare . Hence, Most studies focus on biomarkers that indicate whether a certain cancer cell (population) is likely to respond to a certain treatment but not on biomarkers that indicate early that a current therapy has stopped working. This also applies to the previous studies that investigated the efficacy of YM155 in neuroblastoma ,15,17. HTP53 status do not reliably indicate resistance formation.To test this hypothesis, we here established and characterized 10 further YM155-adapted UKF-NB-3 neuroblastoma cell lines. Moreover, acquired resistance models may provide information that cannot be gained from the comparison of non-adapted cell lines with a varying resistance status. To investigate whether this is the case, the findings from the YM155-adapted UKF-NB-3 sublines were compared to data from the two large pharmacogenomics screens Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutic Response Portal (CTRP), which use non-adapted cancer cell lines ,30, whetAll YM155-adapted UKF-NB-3 sublines displayed pronounced YM155 resistance . The YM1TP53 status was described to not directly influence the anticancer action of YM155 [TP53 status (wild-type or mutant)  .TP53 mutation [TP53 as indicated by TP53 next-generation sequencing. The cellular p53 levels also did not differ consistently between UKF-NB-3 and its YM155-resistant sublines  (SLC35F2 expression was most strongly inversely correlated to the YM155 AUC (Increased cellular ABCB1 (mediates YM155 efflux) levels and decreased SLC35F2 (mediates cellular YM155 uptake) levels have previously been identified as important YM155 resistance mechanisms ,16,17,35pression  and low pression  were assesponse)  in the GM155 AUC  in both M155 AUC . HoweverM155 AUC .All YM155-adapted UKF-NB-3 sublines displayed increased ABCB1 levels relative to UKF-NB-3 . AcquireYM155 has been proposed to exert its anticancer effects via the induction of DNA damage in some experimental systems ,5,35,36.50s were detected  and the subline with the highest IC50  was 5.4-fold. This heterogeneity is in agreement with the up to 29-fold difference observed in the cell viability in response to BIRC5/survivin depletion between the most sensitive (IV) and the most resistant (VII) subline (50: 714 ng/mL) and subline IX (vincristine IC50: 5.6 ng/mL)  .TP53 mutation [TP53 status as potential biomarkers of YM155 resistance formation in the intrinsic resistance setting, using data derived from the GDSC and CTRP databases [In a previous study, a YM155-adapted subline of the neuroblastoma cell line UKF-NB-3 was characterized by increased cellular ABCB1 levels, decreased SLC35F2 and survivin levels, and a mutation . Here, watabases ,30, and Increased ABCB1 expression (mediates YM155 efflux) and decreased SLC35F2 expression (mediates cellular YM155 uptake) were identified as YM155 resistance mechanisms in panels of YM155-naïve cell lines that displayed varying levels of these proteins and in functional studies ,16,17,37TP53 status was reported not to influence the anticancer effects of YM155 [TP53 mutation [TP53. Thus, the role of p53 seems to depend on the individual cellular context. Neither the cellular TP53 status nor the formation of TP53 mutations can currently be considered as valid biomarkers for YM155 therapies.Initially, the of YM155 , which wmutation . Here, aThe relevance of cellular survivin levels for cancer cell sensitivity to YM155 is not clear ,33,34,35The YM155-adapted UKF-NB-3 sublines displayed various survivin levels, demonstrating that resistance formation to YM155 is also not associated with a consistent change in cellular survivin levels. Seven of the YM155-adapted cell lines displayed on-target resistance as indicated by reduced sensitivity to RNAi-mediated BIRC5/survivin depletion relative to parental UKF-NB-3 cells, further confirming that survivin is a target of YM155 in neuroblastoma cells. However, cellular survivin levels do not represent a reliable biomarker of resistance formation to YM155.While YM155 was described to act via the induction of DNA damage in some cancer types ,5,35,36,TP53 status and survivin levels indicate resistance formation [In this study, the use of multiple models of acquired resistance enabled insights that could not be gained from just one drug-adapted subline. The previous investigation of one YM155-resistant UKF-NB-3 subline had suggested that changes in the cellular ormation , which whttps://research.kent.ac.uk/industrial-biotechnology-centre/the-resistant-cancer-cell-line-rccl-collection/). They were established by adaptation of UKF-NB-3 cells (passage 87) to growth in the presence of YM155 20nM by previously described methods [rYM15520nMI to UKF-NB-3rYM15520nMX. All cells were propagated in IMDM supplemented with 10 % FBS, 100 IU/mL penicillin, and 100 µg/mL streptomycin at 37 °C. Cells were routinely tested for mycoplasma contamination  and authenticated by short tandem repeat profiling.The MYCN-amplified neuroblastoma cell line UKF-NB-3 was established from a bone marrow metastasis of a stage IV neuroblastoma patient . Ten YM1 methods  and desi4 cells per well were plated into 6-well plates, incubated at 37 °C and 5% CO2, and counted after 1, 2, 3, 5, and 7 days using a Neubauer chamber. Doubling times were then calculated using http://www.doubling-time.com/compute.php, which uses the equation:To determine doubling times, 2 × 10Doubling time = duration × log(2)/log − log.4/100 µL per well in 96-well plates) were incubated in the presence or absence of drug for 120 h. Then, 25 µL of MTT solution (2 mg/mL (w/v) in PBS) were added per well, and the plates were incubated at 37 °C for an additional 4 h. After this, the cells were lysed using 100 µL of a buffer containing 20% (w/v) sodium dodecylsulfate and 50% (v/v) N,N-dimethylformamide with the pH adjusted to 4.7 at 37 °C for 4 h. Absorbance was determined at 570 nm for each well using a 96-well multiscanner. After subtraction of the background absorption, the results were expressed as the percentage viability relative to control cultures that received no drug. Drug concentrations that inhibited cell viability by 50% (IC50) or 90% (IC90) were determined using CalcuSyn .Cell viability was tested by the 3--2,5-diphenyltetrazolium bromide (MTT) dye reduction assay after 120 h of incubation modified as described previously . Cells (TP53 next-generation sequencing was performed as previously described [TP53 gene were amplified from genomic DNA with Platinum™ Taq DNA polymerase (Life Technologies) by multiplex PCR using two primer pools with 12 non-overlapping primer pairs each, yielding approximately 180 bp amplicons. Each sample was tagged with a unique 8-nucleotide barcode combination using 12 differently barcoded forward and eight differently barcoded reverse primer pools. Barcoded PCR products from up to 96 samples were pooled, purified, and an indexed sequencing library was prepared using the NEBNext® ChIP-Seq Library Prep Master Mix Set for Illumina in combination with NEBNext® Multiplex Oligos for Illumina (New England Biolabs). The quality of sequencing libraries was verified on a Bioanalyzer DNA High Sensitivity chip (Agilent) and quantified by digital PCR. 2 × 250 bp paired-end sequencing was carried out on an Illumina MiSeq (Illumina) according to the manufacturer’s recommendations at a mean coverage of 300×.escribed . All codTP53 (R17) database to check for known p53 cancer mutations.Read pairs were demultiplexed according to the forward and reverse primers and subsequently aligned using the Burrows-Wheeler Aligner against the Homo sapiens Ensembl reference (rev. 79). Overlapping mate pairs where combined and trimmed to the amplified region. Coverage for each amplicon was calculated via SAMtools (v1.1) . To iden® 800CW Goat anti-Mouse IgG, dilution 1:25,000, Li-Cor Biosciences, Lincoln, NE, USA), SLC35F2 , GAPDH , ABCB1 , p53 , and survivin . Protein bands were visualized by laser-induced fluorescence using infrared scanner for protein quantification  and Image Studio Ver. 5.2 software (Li-Cor Biosciences) for densitometric analyses.Cells were lysed using Triton-X-100 sample buffer, and proteins were separated by SDS-PAGE. Detection occurred by using specific antibodies against β-actin  (Transient depletion of BIRC5/survivin was achieved using synthetic siRNA oligonucleotides (ON-TARGETplus SMARTpool) from Dharmacon . Non-targeting siRNA (ON-TARGETplus SMARTpool) was used as negative control. Cells were transfected by electroporation using the NEON Transfection System  according to the manufacturer protocol. Cells were grown to 60–80% confluence, trypsinised, and 1.2 × 10AACAUUU) .4 cells per well were irradiated at room temperature  with single doses of X-rays ranging from 1 to 5 Gy using a linear accelerator  with 6 MeV photons/100 cm focus–surface distance with a dose rate of 4.0 Gy/min. Sham-irradiated cultures were kept at room temperature in the X-ray control room while the other samples were irradiated.In 96-well cell culture plates, 102) data portal . The Genomics of Drug Sensitivity in Cancer (GDSC) data were obtained from www.cancerrxgene.org [All data (including drug response area under curve (AUC) data for YM-155-treated cancer cell lines, basal gene-expression for ABCB1, BIRC5 (the gene that encodes survivin), and SLC35F2, and genomic alterations of p53) in this study were obtained from two online resources: Version 2 of the Cancer Therapeutics Response Portal (CTRP v2) data ,42 were gene.org ,44.The CTRP contains ABCB1, BIRC5, and SLC35F2 expression data for 823 cell lines and YM-155 AUC data for 715 cell lines. For 703 cell lines (including 12 neuroblastoma cell lines), gene expression data and YM155 AUC values were available. Whole exome sequencing (WES) data was available for 546 of the cell lines for which YM-155 sensitivity data was also available (including 11 neuroblastoma cell lines).The GDSC contains ABCB1, BIRC5, and SLC35F2 expression data for 1019 cell lines and YM155 AUC data for 945 cell lines. Expression data and WES data were available for all 945 cell lines with YM-155 sensitivity data (including 30 neuroblastoma cell lines).TP53 were produced using the ggplot2 package [Data processing was performed using Perl version 5.26.0, and R statistical packages version 3.3.2. Cell lines were determined to display either high or low expression for each gene using the median gene expression as a threshold . Box plots indicating the YM-155 sensitivity in cell lines that display low or high expression of a certain gene or wild-type or mutant  package  in R.Statistical tests were carried out in R and included Wilcoxon rank-sum test  and Peart-test. The means of three or more sample groups were compared by one-way ANOVA followed by the Student–Newman–Keuls test. P values lower than 0.05 were considered to be significant.Results are expressed as mean ± S.D. of at least three experiments. Comparisons between the means of two sample groups were performed using Student’s Our data revealed a high phenotypic heterogeneity among a panel of 10 YM155-resistant sublines of the neuroblastoma cell line UKF-NB-3. This heterogeneity is of conceptual importance, because it shows that even a defined cancer cell population of limited intrinsic heterogeneity can develop various resistance mechanisms and phenotypes in response to treatment. From a clinical perspective, this means that the close monitoring of cancer cell evolution in response to therapy will have to become an essential part of the design of individualized therapies. Notably, such insights can only be gained from preclinical model systems, such as drug-adapted cancer cell lines, which enable the repeated adaptation of a given cancer cell population to the same treatment but not from clinical material as every patient can only be treated once.Our findings also demonstrate that biomarkers can indicate resistance formation, even when they do not enable the prediction of drug sensitivity in therapy-naïve cancer cells. Hence, the use of biomarkers differs between the intrinsic and the acquired resistance setting, and pre-clinical models of acquired drug resistance are needed for the identification of such biomarkers that herald resistance development.


We write to inform the readership of the beneficial role of interventional radiology (IR) in providing an urgent central venous access service to patients in the intensive care units (ICU) of our hospital during the peak surge of the current Covid-19 pandemic.The World Health Organisation declared the Covid-19 outbreak a global pandemic on March 11th, 2020. Among several measures that were taken by the United Kingdom’s National Health Service was a significant increase in ICU capacity. Our own institution increased ICU beds from 65 to 155. As was the case in many IR departments : guidance and support, To audit our practice, data was collected retrospectively between April 1st-24th 2020 using the Integrated Clinical Information Programme and Picture Archiving and Communication system. All lines inserted by IR were included. Data collected included line type, insertion site, technical success, and immediate complications . When applicable, post-procedural chest radiographs were reviewed for adequate positioning, pneumothorax and haemothorax.Approximately 120 lines were inserted on Covid ICUs during the audit period, of which, IR inserted 45 lines during 35 patient encounters. Vascular surgery would have inserted a proportion of the remaining lines, however, their data is not presented here. Line type and location were: 29 quad-lumen central venous lines ; 13 non-tunnelled dialysis catheters ; and 3 radial arterial lines. Peak referrals reached 6 patients/7 lines in 24 h. No immediate complications were reported (0%). Post-procedural radiographs revealed no instance of pneumothorax/haemothorax (0%). One left-sided central venous line tip was malpositioned in the left brachiocephalic vein (2.5%). Reported complication rates for line insertion in the literature are, 3–32% tip malposition without imaging guidance and 0–4% with imaging guidance (McBride et al., In summary, implementation of the ‘lines team’ was a successful and well utilised resource during the peak of the Covid-19 outbreak. This illustrates the versatile nature of IR, which in crisis situations can play a significant role in the delivery of aspects of critical care.


Signal transducer and activator of transcription 3 (STAT3) is a transcriptional regulator of a number of biological processes including cell differentiation, proliferation, survival, and angiogenesis, while cyclin-dependent kinases (CDKs) are a critical regulator of cell cycle progression. These proteins appear to play central roles in angiogenesis and cell survival and are widely implicated in tumor progression. In this study, we used the well-characterized US National Cancer Institute 60 (NCI60) human tumor cell lines to screen the in vitro anti-cancer activities of our novel small molecule derivatives (NSC765690 and NSC765599) of salicylanilide. Furthermore, we used the DTP-COMPARE algorithm and in silico drug target prediction to identify the potential molecular targets, and finally, we used molecular docking to assess the interaction between the compounds and prominent potential targets. We found that NSC765690 and NSC765599 exhibited an anti-proliferative effect against the 60 panels of NCI human cancer cell lines, and dose-dependent cytotoxic preference for NSCLC, melanoma, renal, and breast cancer cell lines. Protein–ligand interactions studies revealed that NSC765690 and NSC765599 were favored ligands for STAT3/CDK2/4/6. Moreover, cyclization of the salicylanilide core scaffold of NSC765690 mediated its higher anti-cancer activities and had greater potential to interact with STAT3/CDK2/4/6 than did NSC765599 with an open-ring structure. NSC765690 and NSC765599 met the required safety and criteria of a good drug candidate, and are thus worthy of further in-vitro and in-vivo investigations in tumor-bearing mice to assess their full therapeutic efficacy. The eansition . Under pansition ,11. CDKsansition . Thus, tansition .A number of key oncogenic abnormalities, including amplification of cyclin D; inactivation of CDKN2A p16); and deletions/mutations upstream of cyclin D, such as activating mutations of phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA)/the B-raf proto-oncogene, serine/threonine kinase (BRAF), and phosphatase and tensin homolog (PTEN) deletion ,14, were; and delSTAT3 is a cytoplasmic transcription factor involved in a number of biological processes including cell differentiation, proliferation, survival, and angiogenesis . OverexpThe translational value of knowledge of cancer biology into developing effective prognostic/diagnostic and therapeutic strategies for clinical practice remains disappointing . HoweverNSC765599 and NSC765690 are small molecule derivatives of salicylanilides , which were previously synthesized and evaluated for biological activities in our Lab . We had 2 for 48 h. Cells were fixed with a sulforhodamine B (SRB) solution [50 (concentration needed to kill 50% of cells by cytotoxic activity) for each cell line tested, and GI50 (concentration needed to inhibit 50% of cancer cell growth) [NSC765690 and NSC765599  were subsolution  followed growth) . Results50, TGI and LC50 were set as the endpoints.NSC765599 and NSC765690 were screened for potential drug target using SwissTarget prediction algorithm, which predicts potential drug target based on the principle of similarity . In addiThe three-dimensional 3D) structure of palbociclib (CID: 5330286) and SH-4-54 (CID: 72188643) were retrieved in SDF file format from the PubChem database, while the 3D structures of NSC765690 and NSC765599 were drawn out in sybyl mol2 format using the Avogadro molecular builder and visualization tool vers. 1.XX  and wereD structu50) in rats and environmental toxicity were predicted using GUSAR software [The drug-likeness, medicinal chemistry, and pharmacokinetics, including the adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of NSC765690 and NSC765599 were analyzed using SwissADME software developed by the Swiss Institute of Bioinformatics . The drusoftware .Spearman’s rank correlation was used to assess the correlations of NSC765599 and NSC765690 fingerprints with NCI synthetic compounds, standard agents, and molecular targets. The COMPARE correlation threshold was set to ≥45 common cell lines, ≥0.1 correlation coefficient, and ≥0.05 standard deviation. The growth inhibition by NSC765690 and NSC765599 in single-dose assay was obtained by subtracting the positive value on the plot from 100, i.e., a value of 40 would mean 60% growth inhibition.Both NSC765690 and NSC765599 exhibited anti-proliferative effect against all the 60 panels of NCI human cancer cell lines . Further50 values ranged from 0.14~2.79 μM in NSC76569-treated cell lines and 0.219~5.55 μM in NSC765599-treated cell lines. Consistent with the activities demonstrated in single-dose treatments, the NSCLC, melanoma, renal, and breast cancer cell lines were most sensitive to NSC765690 treatment, while leukemia, CNS, ovarian, and colon cancer cell lines were the least sensitive to NSC765690 , NSCLC , CNS , renal , leukemia , and breast  cancer cell lines . The GI5SC765690 . Analysit active .p values in the range of 0.44~0.62. In addition, NSC765690  and NSC765599  shared anticancer mechanism with a number of standardized drugs in the NCI database (p = 0.1~0.3) with the expression of multiple genes, most of which are proteins involved in cell cycle progressions , with database . The molressions .Using NSC765690 and NSC765599 as query molecules on the SwissTargetPrediction algorithm, a computer-based drug target prediction tool that identifies the most probable macromolecular targets of a small molecule, on the basis of similarity with a known actives compound in the library , we idenUsing molecular docking studies, we found that both NSC765690 and NSC765599 exhibited strong interactions with the crystal structure of apo CDK2 , CDK4/cyclin D3 , CDK6/cyclin , and STAT3 . The observed interactions and binding affinities indicated that CDK2 is the most favored receptor for both compounds , while NOur careful analysis of the interactions between NSC765690 and the receptors revealed a higher number of conventional H-bonding, pi interactions, and Van der Waal forces created on the ligand backbone with a higher number of amino acids residues than does NSC765599 and palbociclib, in the CDK2/4/6 binding cavities . NSC765650) according to OECD classification  = 0~6) and lipophilicity (XlogP3 = −0.7~5) having slight outlying values of −5.71 and 5.47 respectively. Both compounds demonstrated good synthetic accessibilities, highly probable GIA absorption, and bioavailability, but poor BBB permeation , Table 7Despite advances in treatment modalities, cancer survival ratios are still disappointing; thus, developing a novel chemotherapeutic strategy may improve the prognosis of the cancer patient . At presp = 0.15~0.36) antitumor mechanistic fingerprints with known inhibitors of growth factor receptor and cell cycle transition, and DNA damage inducer. However, the modest correlation with NCI-standard agents suggests that NSC765599 may have a unique mechanism of action not common to standard agent database. The strong antitumor pattern correlation (p = 0.44~0.6) between NSC765690 and NSC765599 fingerprint with NCI synthetic compounds suggests a mechanism of action similar to that of the seed compounds. Unfortunately, the top-ranked correlated compounds antineoplastic-643812 (p = 0.61) and N-(3-chloro-2-methylphenyl)-2-hydroxy-3-nitrobenzamide (p = 0.62) are yet to be mechanistically investigated, while combretastatin A-4 with p-value 0.58 (NSC765690) and p-value 0.53 (NSC765599) have been reported for the mechanism of action, indicating cell cycle arrest and inhibition of tubulin [p = 0.1~0.3) were low, indicating the possibility of a new mechanism not captured by COMPARE.The NCI60 cell lines have been well-characterized for genetic and protein expression patterns, and, a computational tool, the DTP-COMPARE algorithm, has been developed to identify the molecular targets and mechanism(s) of action for the unknown compound from known drugs as well as the known molecular targets in the NCI databases . Interes tubulin , hence pThe COMPARE prediction, together with in-silico SwissTarget and PASS prediction collectively identified STAT3/CDK2/4/6 as the most probable target for NSC765690 and NSC765599, and thus were further studied for ligand–receptor interactions. Interestingly, we found that NSC765690 and NSC765599 docked well into the receptor cavities of STAT3, CDK2, CDK4, and CDK6, with CDK2 being the most favored receptor while CDK4 appeared to be the least favored. Comparatively, the higher binding affinities and closer proximity of NSC765690 to the receptors suggested that NSC765690 is a better ligand for CDK2, CDK4, and CDK6 than is NSC765599.NSC765690 and NSC765599 are both derivatives of NDMC101. A close look at the structure-related activities of NSC765690 and NSC765599 revealed that cyclization of salicylanilide core scaffold  was the The unique stability of NSC765690 in the binding sites of CDK2, CDK4, and CDK6 could be attributed to the larger number of H-bond and pi interactions including pi–cation, pi–anion, pi–alkyl, pi–pi stack, and pi–pi T-shaped interactions between NSC765690 and the receptors. The large numbers of pi interactions, which mostly involve charge transfer, help in intercalating the NSC765690 in the receptors’ binding cavities. The higher affinity of NSC765690 was also associated with the presence of a larger number of Van der Waal forces created on its backbone with respective amino acids Phe82, Leu83, Asp145, Ala144, Asn132, Gln131, Thr14, Thr158, Glu12, Gly13, Gly11, Asp86, Gln85 and His84 of CDK2; Leu64, Arg60, Leu113, Ala63, Leu31, Phe163, Phe160, Leu161, Glu76 and Arg114 of CDK4; and Phe71, Ser296, Leu295, Phe127, and His73 of CDK6, which undoubtedly created a strong cohesive environment, thereby stabilizing the complex formed . Althoug50), an adverse effect that follows a single dose exposure to a substance, is an important task in drug design and risk assessment of chemicals [50 values predicted for oral, intravenous, intraperitoneal, and subcutaneous administration indicated that both NSC765690 and NSC765599 were non-toxic and will be well-tolerated by the experimental animals. In addition, NSC765690 and NSC765599 met the criteria of a good drug candidate (The concept of drug-likeness gives useful guidelines for identifying potential drug candidates during the early stage of drug discovery and development . Estimathemicals ,61,62. Tandidate , suggestIn conclusion, this study demonstrated the anti-proliferative effect of NSC765690 and NSC765599 against the 60 panels of NCI human cancer cell lines, and dose-dependent cytotoxic preference for NSCLC, melanoma, renal, and breast cancer cell lines. STAT3/CDK2/4/6 signatures appear to be potential druggable candidates for the small molecules and interacted with high binding affinity, indicating the potential of NSC765690 and NSC765599 to dysregulate expressions of STAT3/CDK2/4/6 signature and, consequently, compromised cell survival. Further in-vitro and in-vivo confirmation studies are ongoing in our lab.


As the prognosis for patients with ATL remains extremely poor due to resistance to conventional chemotherapy regimens, introduction of novel therapeutic agents is needed. Previous studies have reported that nucleosides 2′-deoxy-2′-methylidenecytidine (DMDC) and its derivative 2′-deoxy-2′-methylidene-5-fluorocytidine (FDMDC) exhibit antitumor activities in T-cell acute lymphoblastic leukemia (T-ALL) and solid tumor cell lines. Another nucleoside, 1-(2-azido-2-deoxy-β-D-arabinofuranosyl)cytosine (cytarazid), is considered a therapeutic drug with antitumor activity in human solid tumors. In this study, we investigated the effects of these nucleosides on cell growth in vitro and in vivo using relevant leukemia cell lines and NOD/Shi-scid, nullIL-2Rg (NOG) mice, respectively. The nucleosides demonstrated significant cytotoxic effects in ATL and T-ALL cell lines. Intraperitoneal administration of FDMDC and DMDC into tumor-bearing NOG mice resulted in significant suppression of tumor growth without lethal side effects. Our findings support a therapeutic application of these nucleosides against tumor progression by targeting DNA polymerase-dependent DNA synthesis in patients with ATL.Adult T-cell leukemia (ATL) is a CD4 Aggressor cells . Neverthor cells . Dependior cells . While mRecently, a variety of chemical compounds and pharmacological inhibitors targeting the tumor itself based on different molecular mechanisms have been evaluated in clinical trials, including enhancer of zeste homolog 2, histone deacetylase, and checkpoint inhibitors . Among tscid, nullIL-2Rg (NOG) mice, which are widely utilized for evaluating drug efficacy in ATL and other human malignant tumors. Treatment of ATL tumor-bearing NOG mice with DMDC and FDMDC resulted in significant inhibition of tumor growth in vivo. Notably, this is the first report of the antitumor activity of FDMDC in a human tumor xenograft model in vivo. Overall, our results support the potential use of nucleosides as a therapeutic strategy for patients with ATL.In this study, we examined the antitumor effects of DMDC, its derivative FDMDC, and cytarazid on the growth of ATL cells. All nucleosides induced significant cytotoxic effects in ATL cell lines in a dose-dependent manner in vitro. We further examined the antitumor effects of DMDC and FDMDC using NOD/Shi-The HTLV-I-transformed T cell lines C5/MJ, HUT-102, MT-2, MT-4, and SLB-1; ATL-derived (HTLV-I-positive) cell lines KOB, MT-1, ST1, and TL-OmI; and T-ALL (HTLV-I-negative) cell lines CCRF-CEM and MOLT-4 were grown in Roswell Park Memorial Institute (RPMI)-1640 medium supplemented with 10% heat-inactivated fetal bovine serum (FBS), penicillin (100 units/mL), and streptomycin (100 µm/mL). Recombinant human interleukin (IL)-2 (0.5 nM)  was added to the culture of KOB and ST1. The Burkitt lymphoma cell lines BJAB and Raji were grown in RPMI-1640 medium supplemented with 20% FBS, penicillin, and streptomycin. The colon adenocarcinoma cell line SW480 was grown in Dulbecco’s modified Eagle’s medium (D-MEM) supplemented with 10% FBS, penicillin, and streptomycin.DMDC, FDMDC, and cytarazid A–C were 4 cells in the presence of various concentrations of nucleosides for 72 h at 37 °C. DMSO was used as the control vehicle. The cells were further incubated with the Cell Proliferation Reagent WST-1  for 2–4 h at 37 °C. Absorbance of the samples was measured at 450 and 550 nm (reference wavelength) using an EnSpire microplate reader .Cells were seeded at a density of 2 × 10NOG mice were obtained from the Central Institute for Experimental Animals . All mice were maintained under specific-pathogen-free conditions in the Laboratory of Animal Experiments, Hokkaido University.7 cells per mouse. For therapeutic experiments, 50 or 100 mg/kg of FDMDC, DMDC, or DMSO as a control vehicle, resuspended in phosphate-buffered saline (−), was intraperitoneally injected into NOG mice once a day for 5 days when tumors reached approximately 150–250 mm3 after cell inoculation. Tumor size was measured daily and determined using the formula (L × W2)/2 . Body weight was measured daily. All experiments were approved and performed in accordance with the guidelines of the Committee of Ethics on Animal Experiments at Hokkaido University.TL-OmI cells were washed twice with serum-free RPMI-1640 medium. The cells were resuspended in serum-free RPMI-1640 medium and inoculated subcutaneously into NOG mice at a density of 3 × 10t-test and are indicated as p values. Differences of p < 0.05 were considered statistically significant .Statistically significant differences between nucleoside- and DMSO-treated mice were calculated using Student’s Previous studies have reported the effects of DMDC and its derivative FDMDC A,B on le50) values of DMDC, FDMDC, and cytarazid in tested cell lines are summarized in 50 of ~0.6 µM for both) and colon adenocarcinoma cell line SW480 (IC50 of 10.1 µM) as control cell lines, in agreement with previous results [50 of 2.01 to 4.88 µM) and HTLV-I-transformed cell lines (IC50 of 1.49 to 2.36 μM). Similar to DMDC, FDMDC exhibited cytotoxic effects on the growth of ATL cell lines (IC50 of 1.53 to 3.86 µM) and HTLV-I-transformed cell lines (IC50 of 1.62 to 4.49 µM). We also tested two Burkitt lymphoma cell lines, BJAB and Raji; BJAB cells were highly sensitive to both DMDC and FDMDC (IC50 of ~0.05 µM for both). Finally, we tested the antitumor effect of cytarazid  were much higher than those of DMDC or FDMDC, with the exception for MT-4 cells (IC50 of 0.353 µM).The half-maximal inhibitory concentration . Miwa et al. reported the relationship between antitumor effects and cytidine deaminase (CDA) activity in solid tumor cell lines ; since DIn our in vivo study, we found significant antitumor activities of DMDC and FDMDC in suppressing ATL tumor growth in NOG mice. Administration of DMDC at a dose of 100 mg/kg resulted in a slight body weight loss in tumor-bearing mice B, sugges2/day [50 of DMDC and FDMDC in ATL cell lines and HTLV-I-transformed cell lines had the same or greater level of cytotoxic effect as that in SW480 cells (Phase I clinical trials demonstrated that the maximum tolerated dose of DMDC and the recommended dose for phase II clinical trials were both 18 mg/m2/day . Althoug80 cells , indicatIn conclusion, our results demonstrated the antitumor effects of nucleosides DMDC, FDMDC, and cytarazid on ATL tumor growth in vitro and in vivo. The clinical efficacy of these nucleosides on primary ATL cells should be explored in future studies. This work may lead to a promising therapeutic strategy for eradicating tumors in patients with ATL.