Neuroblastoma is the most common extracranial solid tumor during infancy and childhood.Outcome of high-risk and late-stage disease remains poor despite intensive treatment regimens.Suppressing inhibitor of apoptosis proteins (IAPs) using Smac mimetics (SM) significantly sensitizes neuroblastoma (NB) cells for chemotherapy, however strongly dependent on the cytotoxic drug combined with SM.de novo NB cell lines (n=8).Therefore, a systematic analysis of the impact of SM in combination with different classes of chemotherapeutics was of crucial importance. Treatment of NB cell lines with SM LCL161 and vinca alkaloids revealed a strong synergistic inhibition of proliferation and significant induction of apoptosis in virtually all established and In contrast, combination of anthracyclines or topoisomerase inhibitors with LCL161 showed a synergism for single drugs and/or cell lines only.Furthermore, we could show that insensibility to LCL161-mediated sensitization for chemotherapeutics is associated with aberrant activation of anaplastic lymphoma kinase (ALK) by common mutation F1174L. Inhibition of ALK using TAE684 is able to overcome this resistance in a synergistic fashion, a finding that could be highly relevant for improvement of neuroblastoma therapy. Neuroblastoma is a malignant disease of the sympathetic nervous system and the most prevalent solid extracranial tumor during infancy and childhood. Prognosis for non-high risk disease is good with 5-year survival > 90%, at the same time more than 50% of patients suffer from metastatic disease at time of diagnosis , 2. OutcApoptosis is a form of programmed cell death that is necessary to eradicate impaired cells and to enable realization of developmental programs. Deregulated apoptotic machinery is one of the hallmarks of cancer contributing to development and expansion of diverse malignancies .The family of inhibitor of apoptosis proteins (IAP) are essential regulators of apoptosis. X-linked IAP (XIAP), the most prominent and best-analyzed IAP, is increased in different cancers including neuroblastoma contributing to chemotherapy resistance and unfavorable outcome -10. Caspin vitro and in a syngeneic mouse model using SM LBW242 and LCL161 [Smac mimetics (SM) were able to induce apoptosis and to significantly increase efficacy of classic treatment in several experimental cancer models , 13. In d LCL161 . LBW242 d LCL161 . Severald LCL161 .Sensitization of neuroblastoma cells for chemotherapy using SM was highly synergistic for vincristine, in part synergistic for doxorubicin and antagonistic for etoposide .If the synergistic interaction of SM is drug-dependent or related to the molecular background of the neuroblastoma cells is still unanswered.Therefore, a systematic effect analysis of different classes of antineoplastic drugs in combination with SM was the logical next step to shed light on this relevant issue. In the current study, we could show that in all except one of the tested neuroblastoma cell lines vinca alkaloids  with SM LCL161 displayed a strong synergistic effect on proliferation and a significant apoptosis induction in line with the results obtained before. Using anthracyclines  or topoisomerase inhibitors  in contrast a synergism with LCL161 was detectable for single drugs and/or cell lines only.in vivo as well [www.clinicaltrials.gov).Smac mimetic LBW242 displayed a synergistic gain of chemotherapy on neuroblastoma cell lines in a drug-dependent manner . Differe as well . Furthern = 6) using Western blot analysis  in the presence of SM LCL161 monotherapy. Significant inhibition of proliferation was detected using high micromolar concentrations with IC50 of 49.4-77.9 μM  and vincristine (IC50 24.5-117 nM). Combined treatment of LCL161 with each of the vinca alkaloids enhanced the antiproliferative potential of the drugs in a synergistic manner in all cell lines except SK-N-BE(2)-M17  showed a concentration-dependent inhibition of proliferation Figure . Vinblas7 Figure +1B. In t50 of 42-223 nM. The IC50 of the other two anthracyclines were 0.35-1.58 μM for daunorubicin and 0.12-2.58 μM for doxorubicin. Addition of LCL161 enhanced the negative effect on proliferation of daunorubicin and doxorubicin in all cell lines, except Kelly, synergistically  were unresponsive against etoposide with IC50 of 4.6-29.1 μM  and topotecan (IC50 0.08-1.17 μM) was inhibited to a similar degree -M17 Figures . In fourNeuroblastoma cell lines were treated with LCL161 in combination with anthracyclines to evaluate the effects on apoptosis induction Figures . In all 50) 0.63) inhibition of proliferation in the combination treatment. Add-on of LCL161 to idarubicin had no significant effect in the cell lines Kelly, SK-N-BE(2)-M17 and SK-N-SH and only a low increase in apoptosis was seen in the cell line SH-EP TET21N -M17 that displayed a synergistic  or mutations in p53 or anaplastic lymphoma kinase (ALK) are commonly found in advanced stage or relapsed tumors and are associated with an adverse outcome -25. TherFor this reason, genetic features of NB cell lines were correlated to combination index (CI) scores reflecting synergistic (CI < 1) or additive/antagonistic (CI ≥ 1) interaction of chemotherapeutic drugs with LCL161 Tables  and 2.U test it became evident that status of MYCN, deletion of chromosome arm 1p or mutated p53 could not account for significant differences between groups (data not shown). In contrast, in cell lines with activating mutation of ALK (ALKF1174L) a significantly higher CI than in ALKwt cells was observed for LCL161 and its combination with idarubicin (CI(IC50) 1.1 vs. 0.76, p = 0.05) or SN-38 (CI(IC50) 0.94 vs. 0.8, p = 0.05)  was detectable for doxorubicin and LCL161 (CI(IC50) 0.8 vs. 0.46, p = 0.127).Using the Mann-Whitney ) Figure . The larn = 6) was efficiently inhibited using a low micromolar range of TAE684  to the synergistic range  were observed  and late apoptotic (Annexin V and propidium iodide positive) cells  in neuroblastoma not only is effective to increase the effect of chemo drugs but also is able to synergistically interact with Smac mimetic LCL161. The latter is highly relevant for cells that are resistant for combination of either TAE684 or LCL161 with chemotherapy.These findings show that TAE684-induced inhibition of activated ALK  and 3 drugs of each class of chemotherapeutics it became apparent that vinca alkaloids generally showed a synergism and significant increase in apoptosis induction with SM LCL161  of almost all (7 of 8) tested NB cell lines were much higher as the achievable plasma steady-state concentration of ~12 μM (7 μg/ml) as only one cell line was established before therapy [With this in mind it is not surprising that the IC therapy .50 13 nM-1.56 μM vs. Cmax of 56 nM (22 ng/ml)) [50 80 nM-1.17 μM vs. Cmax of 209 nM (88 ng/ml)) [A comparable pattern of resistance was seen for SN-38 (IC ng/ml))  and topo ng/ml)) . Cross-r ng/ml)) .50 26.7 μM), SN-38 (IC50 0.53 μM) and topotecan (IC50 0.78 μM) but all drugs showed a synergism with LCL161. This synergism lowered the IC50 to 20.4 μM for etoposide, to 0.38 μM for SN-38 and to 0.22 μM for topotecan. As these concentrations are only clinically achievable for topotecan, it would however have relevant clinical implications to find molecular markers that are causal for these findings.The use of Smac mimetics in contrast could nevertheless be a promising strategy to overcome topoisomerase inhibitor resistance in some cases. The cell line SK-N-AS disclosed triple resistance against etoposide (ICF1174L). Interestingly, other molecular aberrations like MYCN status did not influence impact of LCL161. Point mutations activating the ALK tyrosine kinase domain were found in familial and sporadic neuroblastomas with high frequency [Systematical analysis of susceptibility of different drug classes for LCL161 revealed a so far unknown association with mutation of ALK  is necessary for cellular proliferation and survival [F1174L targeted expression has been demonstrated to be tumorigenic in mice inducing neuroblastomas that resemble the human disease [F1174L mice were dependent on ALKF1174L activity as treatment with ALK inhibitor TAE684 induced a complete tumor regression.In neuroblastoma the most common and aggressive modified ALK variant  [2-atmosphere and a relative humidity of 95%.Neuroblastoma cell lines Kelly, NB1691luc, SH-EP TET21N, SK-N-AS, SK-N-BE(2)-M17 and SK-N-SH as well as recently established ifswald)  were useifswald) . NB1691lifswald) . Neurobl2O to designated concentrations.Novartis Pharma generously provided Smac mimetic LCL161. Cytostatic drugs daunorubicin, doxorubicin, etoposide, idarubicin, topotecan, SN-38 (active metabolite of irinotecan), vinblastine, vincristine and vindesine were obtained from Sigma-Aldrich . NVP-TAE684 was purchased from Selleckchem . Working solutions were prepared by dilution of drugs with medium or ddHβ-actin . Specific protein bands were visualized using IRDye 680RD or 800CW secondary antibodies (LI-COR) and LI-COR Odyssey infrared imaging system.Cell lysates were prepared with radioimmunoprecipitation assay (RIPA) buffer (Sigma-Aldrich) supplemented with Complete protease inhibitor cocktail and PhosSTOP - Phosphatase Inhibitor Cocktail (Roche). Standard procedures for Western blotting were followed using the following primary antibodies: cIAP-1 , XIAP  and ® Total ALK and Phospho-ALK (Tyr1604) Chemiluminescent Sandwich ELISA Kits  according to the manufacturer's protocols. Protein concentrations of lysates were determined using Bio-Rad Protein Assay and bovine serum abumin as protein standard.Expression of total ALK and phospho-ALK was quantified using PathScan50 values were determined using in-house software (Microsoft Excel).Proliferation assays were performed with Cell Proliferation Reagent WST-1  according to the manufacturer's protocol. Cells were seeded in culture medium in 96-well plates to adhere overnight. Cytostatic drugs and LCL161 were added to the cells for an incubation period of 48 hours. Following incubation with WST-1 for 2 hours, absorbance was measured with an ELISA reader. IC2). Apoptosis was detected by Annexin V-FITC  and propidium-iodide (PI)  staining and flow cytometry.Cells were seeded in cell culture medium in 24-well plates to adhere overnight. Cells were treated with the indicated reagents for 48 h. Cells were harvested, washed twice with PBS and resuspended in Annexin V binding buffer  + (d2/D2), where D1 and D2 represent the required doses of drug 1 and 2 to produce x% effect and d1 and d2 the required doses of drug 1 and 2 to produce the same effect if used in combination. Statistical significance of differences between experimental groups was determined using the Student t-test or the Mann-Whitney U test. A two tailed p-value ≤ 0.05 was regarded as significant.Combination indices (CI) for cellular proliferation assays were calculated using the Chou-Talay method to determine synergism (CI ≤ 0.9), additivity (CI > 0.9-1.1), or antagonism (CI > 1.1), if combining LCL161 with cytostatic drugs . The CI


SRC proto-oncogene is commonly overexpressed or activated during cancer development. Src family kinase inhibitors are approved for the treatment of certain leukemias, and are in clinical trials for the treatment of solid tumors. Src signaling is activated in endometriosis, a precursor of clear cell and endometrioid subtypes of epithelial ovarian cancers (OCs). We examined the expression of phosphorylated Src (Src-pY416) in 381 primary OC tissues. Thirty-six percent of OCs expressed Src-pY416. Src-pY416 expression was most common in endometriosis-associated OCs (EAOCs) (P=0.011), particularly in clear cell OCs where 58.5% of cases expressed Src-pY416. Src-pY416 expression was associated with shorter overall survival (log rank P=0.002). In vitro inhibition of Src signaling using 4-amino-5-(4-chlorophenyl)-7-(dimethylethyl)pyrazolopyrimidine (PP2) resulted in reduced anchorage-independent and -dependent growth, and in three-dimensional cell culture models PP2 disrupted aggregate formation in Src-pY416-positive but not in Src-pY416-negative cell lines. These data suggest that targeting active Src signaling could be a novel therapeutic opportunity for EAOCs, and support the further pre-clinical investigation of Src family kinase inhibitors for treating OCs expressing Src-pY416.The  SRC was the first oncogene to be described over 40 years ago. Since then, dysregulation of SRC and the other eight SRC family kinase (SFK) members has been shown to be important in the development of many solid tumor types.1 In normal tissues, Src is typically found in an inactive form, but during cancer development Src can become overexpressed or activated by mutations that increase its enzymatic activity. Src is a serine/threonine kinase and, when active, transduces signaling cascades through the STAT3/MYC, MAPK and PI3K pathways. Consequently, overexpression or mutation of Src is associated with a variety of tumorigenic phenotypes including angiogenesis, proliferation, invasion, motility and chemoresistance.23 OCs are the eighth most common cancer among women in developing countries, but the fourth most common cause of cancer death. OCs are particularly lethal, with 5-year survival rates of ~45%.3 There are four main histological subtypes of invasive epithelial OC—high-grade serous, endometrioid, clear cell and mucinous —with each histotype characterized by specific somatic alterations and biomarker expression.4 While histologically distinct, clear cell and endometrioid OCs share some common molecular and epidemiological features. Both commonly exhibit mutation or loss of the ARID1A tumor suppressor gene;6 and endometriosis represents a defined precursor for these subtypes but not for the most common subtype, high-grade serous OC.11 Thus, collectively clear cell and endometrioid OCs are referred to as ‘endometriosis-associated ovarian cancers' (EAOCs). It has been shown that Src signaling is common in mucinous OC,13 but the importance of Src in other OC subtypes is currently unknown. We have previously shown that Src signaling is active in in vitro models of endometriosis, as well as in the eutopic endometrium of endometriosis patients.14 This led us to hypothesize that Src may also be activated in EAOCs. In the current study, we investigated this hypothesis by first evaluating expression of active Src in primary OCs representing the main histological subtypes, and then using in vitro models of different OC subtypes to establish the effects of inhibiting Src. Our results indicate that Src inhibition may represent a novel therapeutic target for EAOC.It is estimated that over 21 000 women in the United States will be diagnosed with epithelial ovarian cancer (OC) in 2015.P=0.012) but not with the serous subtype (P=0.139). Src-pY416 positivity was the most common in clear cell OCs, where 24/41 cases (58.5%) were positive. In this study, Src-pY416 was only detected in 4/21 mucinous OCs.We examined the expression of Src by immunohistochemical staining in 381 primary epithelial OC tissues representing the major histological subtypes, using an antibody that specifically recognizes the Src protein when phosphorylated at tyrosine 416 (Src-pY416)  Supplem. This moP=0.018), but was not significantly associated with survival based on the percentage of stained cells (log rank P=0.14), although the trend was the same (P=0.002)  . Median 15 However, the majority of OC cell lines show poorly differentiated histologies when cultured in 3D, despite having originated from differentiated tumor specimens.15 In the present study, we included additional 35 cell lines to identify other good models of the main OC histotypes. In this panel of cell lines, we found that only 28.6% (2/7) of serous cell lines resembled human serous OCs when grown in 3D, but 76.5% of clear cell OC cell lines (13/17) showed clear cell differentiation when grown as 3D spheroids. These results indicate that OV-177 and SHIN-3 are good models of serous OC, and that HCH-1, JHOC-5, JHOC-7, JHOC-9, KOC-7c, OV207, OVAS, OVISE, OVMANA, OVTOKO, RMG-II, SMOV-2 and TU-OC-1 are good models of clear cell OC. These results can be found in full in We have previously described the histology of 31 OC cell lines grown as two-dimensional (2D) monolayers and as three-dimensional (3D) spheroid cultures, and found that 3D cultures more closely mimic the histological differentiation and marker expression of human primary tumors than their 2D counterparts.R2=0.52), indicating that Src signaling is not altered by culture conditions.We proceeded by evaluating Src-pY416 expression in epithelial OC cell lines grown in 2D and 3D. Of 64 OC cell lines evaluated, 34 OC (53%) exhibited Src-pY416 positivity in 2D and/or 3D cultures. Cell lines with strong Src-pY416 staining included Hey.A8, HEY-C2, TYK-nu, HAC-2, SMOV-2 and OVISE (of which the latter three are derived from clear cell tumors) . The remd]pyrimidine (PP2) to inhibit Src in OC cell lines expressing Src-pY416. Addition of PP2 to the cell culture medium inhibits expression of Src-pY416 in OC cells in a dose-dependent manner (m PP2 dose (P<0.05), while Hey.A8 also exhibited a dose-dependent sensitivity  -7-(dimethylethyl)pyrazolo[3,4-t manner . We firs R2=0.8) . A Src-p numbers  and a trony size .Anchorage-dependent growth assays were also performed to test the sensitivity of OC cells to PP2 treatment when cultured on plastic in the presence of PP2 for 7 days. Cell lines positive for Src-pY416  were more sensitive than the Src-pY416-negative TOV21G line .In vitro 3D multicellular aggregates (MCAs) mimic the OC aggregates found in the ascitic fluid of OC patients and so we tested whether inhibiting Src can impair the formation of 3D MCAs in Src-pY416-positive and -negative cell lines. Cell line models expressing high levels of active Src were Hey.A8 and HEY-C2 (high-grade OC models but subtype unknown), and SMOV-2 (clear cell OC) (cell OC) . TOV21G cell OC) . MCAs wecell OC) .BRCA1 and BRCA2. Novel targeted therapies are needed for non-BRCA1/2-associated OCs and particularly for the non-serous histological subtypes, in which BRCA1/2 mutations are rare. We previously reported Src activation in endometriosis epithelial cells in in vitro models of endometriosis and in endometriosis tissues.14 It follows therefore that in the current study Src-pY416 positivity is also common in EAOCs. These data suggest a role for Src activation in the development of EAOCs. Src activation has not yet been studied in EAOC but has been studied in depth in mucinous OC, where inhibition of Src reduces cell viability, sensitizes cells to platinum chemotherapy and inhibits cell growth in vivo.13 Our data suggest that patients with EAOCs could benefit from therapeutic targeting of Src, in particular clear cell OCs that most frequently exhibit Src activation, but also perhaps a subset of serous OCs, one-third of which expresses active Src. Although endometrioid OCs are associated with endometriosis,10 activation of Src was not strongly associated with this subtype, suggesting that activation of this pathway may be more commonly involved in the progression of endometriosis to tumors of clear cell histology. Further in vitro and in vivo modeling will be required to investigate this hypothesis.Targeted therapies that exploit specific pathways active in a patients' tumor have significantly improved patient outcomes for many cancers. Therapies such as Trastuzumab for HER2-positive breast cancer, and Imatinib for leukemias driven by the BCR-ABL fusion are now widely used in clinical practice. There are currently no targeted therapies routinely used for the treatment of OC, with the exception of olaparib (a PARP1 inhibitor), which recently been approved specifically for the small subset of pre-treated OCs caused by germline mutations in in vitro assays that aim to mimic the progression of OC in vivo. Anchorage-independent growth assays, which mimic dissemination of single tumor cells, showed that treatment of Src-pY416-positive cell lines with a Src inhibitor significantly impeded colony seeding and/or proliferation. In 3D cultures, which are similar to tumor cell aggregates found in ascitic fluid, high-dose Src (50 μm) inhibition impaired or even abolished MCA formation. Qualitative assessment of MCAs suggests that cell–cell adhesion as well as cell survival was impaired by inhibition of Src. This is consistent with the known functions of Src, which operates upstream of many pathways involved in these cellular processes. MCAs in ascitic fluid are responsible for the widespread dissemination of disease throughout the peritoneal cavity, which results in high tumor burden for patients with advanced disease, making treatment of OC particularly challenging. Our data suggest that targeting the Src pathway could be a way to impede the spread of advanced OC, though in vivo pre-clinical testing will be required to test the efficacy of such an approach.To examine the effects of inhibiting Src, we selected in vitro and impair the growth of colon, ovarian, liver and breast cancer cells in vitro and/or in vivo.17 However, one caveat of using PP2 is that it can also have activity against other SFK members, and we also observed some off-target effects at high doses.18 Our approach is consistent with recent clinical trials in which SFK rather than Src-specific inhibitors have been favored, including dasatinib (BMS354825) and saracatinib (AZD0530),21 perhaps because in some instances activity against other SFK members may be advantageous.In this study, we used PP2 to inhibit Src signaling, as PP2 can inhibit Src activity 21 Future trials involving only patients with tumors exhibiting active Src signaling will be required to fully evaluate whether inhibiting Src can offer a survival benefit for OC patients with Src-driven cancers. Src activity can be reliably assayed using immunohistochemistry, which could be performed rapidly on tumor biopsies to identify the patients most likely to benefit from Src-targeted therapy. Preliminary data from other tumor types support this approach: in a phase I study exploring the use of dasatinib for chemo-naive metastatic colorectal cancer, 75% of tumors expressing active Src responded to dasatinib, whereas tumors without active Src showed no response.22 The timing of SFK inhibition also appears to be important, as data from trials for castration-resistant metastatic prostate cancer suggest that dasatinib may impair bone metastasis in patients who have received no prior chemotherapy.24 It appears unlikely that SFK inhibitors will be effective as single agent treatment for recurrent disease;21 but data from in vitro and in vivo models as well as some promising early results from a phase I trial suggest that the combination of a dasatinib plus chemotherapy could improve outcomes for OC patients.25Cell lines negative for Src-pY416 were not sensitive to PP2 in MCA assays, reinforcing the idea that targeted therapies are of little or no benefit in the absence of pathway activation. Clinical trials targeting Src in OC have not found an improvement in patient outcome; but the OC trials reported to date did not select patients based on Src expression.In summary, the current study represents, to our knowledge, the largest study to evaluate Src-pY416 protein expression in OCs of all the major histologies, and the first to specifically implicate Src in the development of EAOCs. These results support the continued investigation of Src and SFK inhibitors as novel therapeutic agents for OC.All patient samples used in this study were collected with informed patient consent and all protocols were performed with approval from the institutional review boards at the University of Southern California, University College London or Oregon Health and Science University.29 The patient characteristics of the population can be found in 2O2 for 10 min. A serum-free protein block  was applied for 30 min before sections were treated with an EDTA buffer saline solution, microwaved (20 min) and then incubated with an anti-phospho Src (Tyr416) monoclonal antibody  for 1 h at room temperature. The diaminobenzidine complex was used as a chromagen. Two pathologists (PMF and EP) scored staining intensity and percentage of expressing cells in each sample.The tumor tissue microarrays (TMAs) used in this study have been previously described.P-values less than 0.05 was considered as statistically significant.Tabulated data were analyzed in SAS version 9.2  using simple linear regression. For survival analyses, Kaplein–Meier survival estimates with log-rank testing were determined using SPSS . in vitro assays and all lines were confirmed to be free of Mycoplasma infection.Cell cultures were maintained following standard protocols. Cell culture media used are listed in et al.15 was stained for phospho-Src, and we generated a second cell line TMA containing additional 38 cell lines. A list of all cell lines included in this study, and culture media used for each, can be found in 15 Cell culture TMAs were stained and scored for Src-pY416 positivity as described above for primary tumors. To grow 3D spheroids, cell culture dishes were coated twice with 1.5% polyhydroxoethylamethacrylate (polyHEMA) dissolved in 95% ethanol. Cells were trypsinized, resuspended in appropriate growth media and inoculated onto dry polyHEMA-coated plates to induce spheroid formation. PP2 was added to the cultures as required and spheroids were refed every 3–4 days. 3D cultures were harvested after 14 days by centrifugation at 200 g for 5 min to sediment the spheroids. Spheroids were washed with phosphate-buffered saline (PBS) and fixed in neutral buffered formalin  for 30 min before processing into paraffin. Images of spheroids were obtained using a Nikon Eclipse Ts100 microscope  and NIS Elements D 3.2 software (Nikon).For analysis of Src activation in OC cell lines, the cell line TMA from Lee In all, 50 000 SMOV-2 and Hey.A8 cells were plated onto glass coverslips in 6-well plates. After 24 h, PP2 was added, and the cell incubated for a further 48 h. Cells were then fixed with 4% paraformaldehyde  in PBS and permeabilized in 0.5% Triton-X in PBS. Cells were blocked in DMEM containing 10% fetal bovine serum (VWR) before adding an anti-phospho Src (Tyr416) monoclonal antibody  for 1 h. Coverslips were washed before adding an anti-Rabbit Alexa Fluor coupled secondary antibody . Coverslips were washed, stained with Hoechst , rewashed and mounted using Mowiol . Stained cells were imaged using a Zeiss Axio Imager Z1 fluorescent microscope . For western blot analyses, cells were treated with PP2 for 48 h, lysed with RIPA buffer (Sigma) containing protease and phosphatase inhibitor cocktails . Insoluble proteins were cleared by centrifugation and protein concentrations determined using a BCA Protein Assay (Thermo Fisher Scientific). In all, 30 μg protein was loaded onto a gradient gel, and transfers performed by semi-dry blotting. Membranes were blocked in Odyssey blocking buffer and incubated with primary antibodies. We used the same anti-phospho Src (Tyr416) monoclonal antibody as above, plus a non-phospho Src (Tyr416) , both used at a 1:1000 dilution and incubated overnight. Infra-red coupled secondary antibodies were applied for 1 h  and the membranes scanned using the Odyssey Imaging System (Licor Biosciences). Quantification was performed using Image Studio Lite software , with background normalization. Immunostaining and blots were performed at least twice. Raw quantification data for western blots after PP2 treatment can be found in 4 cells per well in 3.3% Noble agar (Sigma) top layer on top of a 6% agar base layer. Assays were incubated for 4 weeks and then stained with 1% p-iodonitrotetrazolium violet (Sigma) dissolved in methanol, to fix and stain cells to enable enumeration of the colonies. Colonies were counted and imaged using a Nikon Eclipse TS100 microscope and NIS Element D 3.2 software. Two-tailed paired Student's T-tests were used to test for phenotypic differences in PP2-treated and untreated cells. Assays were performed three times, with triplicate wells plated for each dose of drug.Assays were performed with PP2  at doses of 50 μm, 5 μm, 500 nm and 5 nm. Control cells received vehicle  alone. Anchorage-independent growth assays were performed in 6-well plates by plating 2 × 10In all, 1500 HEY-C2, 3000 SMOV-2, 5000 OVISE or 1500 TOV21G cells were plated per well, in 24-well plates. After 24 h, seven doses of PP2 were added, and the cells were incubated for 7 days. Control cells received vehicle (0.1% DMSO) alone. Media (containing PP2 or vehicle) was replenished on day 3 or 4. After 7 days, 100 μl of 3--2,5-diphenyltetrazolium bromide (MTT) solution (10 mg/ml in PBS) was applied to each well and incubated for 2 h. Cells were washed with PBS and lysed in DMSO (Sigma). Absorbance was read using a Mikrowin platereader . Data were analyzed in GraphPad Prism . Treatment doses were log transformed, and the non-linear curve of best fit was calculated.For PP2 treatment of 3D cultures, cells were grown in 3D as described above and, at the time of seeding, culture media supplemented with PP2 at the specified doses, or vehicle (0.1% DMSO). Cells were treated for 7 days before harvesting. Samples were processed in paraffin blocks and hematoxylin and eosin-stained sections made by the USC Pathology Core facility.


The ability to inhibit cancer is inherent in organotin materials yet the structural relationships that regulate/direct this activity remains unknown. We measured antitumor activity using a matched pair of cell lines MDA-MB-231 cells that are estrogen-independent, estrogen receptor negative and MCF-7 cells, a cell line that is estrogen receptor (ER) positive. Those polyethers that contained a O-phenyl unit were able to significantly inhibit the non-estrogen sensitive cell line but were much less effective against the estrogen sensitive cell line; that is, the human breast cancer cell line MDA-MB-231 showed better test results for polymers derived from diols containing the O-phenyl moiety than the breast cancer cell line MCF-7, a well-characterized estrogen receptor positive control cell line. Those polyethers that did not contain the O-phenyl unit inhibited both cell lines approximately the same. The differential activity of the O-phenyl-containing polyethers is likely due to the estrogen-sensitive cells combining with some of the organotin polyethers minimizing their ability to inhibit cell growth. The ability to inhibit cancer by organotin materials has been known for about 80 years . Even soin vitro model of breast cancer to study the role of estrogen in breast cancer. Here, we describe some of these results.We have noticed in our general testing of the ability of various organotin polyethers to inhibit different cancer cell lines that in certain cases the human breast cancer cell line MDA-MB-231, that is estrogen-independent, estrogen receptor negative, showed better test results than the breast cancer cell line MCF-7, a well-characterized estrogen receptor positive control cell line (cells are positive for cytoplasmic estrogen receptors) and therefore are a useful 50, is reported. The second value is the chemotherapeutic index (CI) value. The CI is employed to compare the toxicity of a drug on normal cell lines (or other “base-line” cell line) to its toxicity to a cancer (or second) cell line. The CI50 is the GI50 drug concentration for the normal (or base line) cell line divided by the GI50 drug concentration for the cancer cell line. Values in excess of two are generally considered significant.Two types of measurements are generally employed to report the ability of materials to inhibit cell growth. The first is the growth inhibition, GI, value. Generally the concentration at which 50% growth inhibition occurs, GI50 values, a column noting the ratio of the GI50 for the MDA cell line divided by the GI50 for the MCF-7 cell line, MDA/MCF-7, has been added. Here, values greater than one are consistent with lower concentrations of drug inhibiting the growth of the MCF-7 cells compared to the MDA cells. Values less than one are consistent with inhibition of the MDA cells occurring at lower concentrations than for the MCF-7 cells. When describing the CI some researchers employ the similar terms ED or effective dose in place of the GI value for the cancer cells and LD or lethal dose in place of GI for the healthy cell line, here the WI-38 cell line (strain line ATCC CCL-75). Thus, CI50 = LD50/ED50. For the CI50 values the added column contains the CI50 for the MDA cell line divided by the CI50 for the MCF-7 cell line, CI-MDA/CI-MCF-7. Here, values greater than one are consistent with inhibition of the MDA cells occurring at lower concentrations than for the MCF-7 cells. And, values less than one are consistent with lower concentrations of drug inhibiting the growth of the MCF-7 cells compared to the MDA cells. The values contained in the added columns should be related since the CI values are “normalized” with the same WI-38 cell line values.To gain a better picture of the relationship between polymer and possible preference for one cell line over the other one additional column have been added to each table. For the GI50 MDA/ GI50 MCF-7 as well as the corresponding CI50 MDA/ CI50 MCF-7 values are around one consistent with the organotin polyethers not having a marked preference for either cell line. The aliphatic diols themselves do not exhibit cancer cell inhibition. The values of GI50 MDA/ GI50 MCF-7 are about one (average = 0.95) and are consistent with the organotin polyethers not having a preference for either cell line. The corresponding CI50 MDA/ CI50 MCF-7 values are around two (average = 2.0) consistent with the organotin polyethers having some preference for inhibiting the non-estrogen MDA cell line at lower concentration of drug than the estrogen-sensitive MCF-7 cells.Characterization of these materials has been described ,33. The 50 and CI50 data for organotin polyethers derived from hydroquinone and hydroquinone derivatives  while the CI50 MDA/ CI50 MCF-7 values are much greater than one (average = 20). These are markedly different than for the organotin polyethers derived from aliphatic diols. Here, inhibition occurs at a much lower concentration for the MDA cell line in comparison to the MCF-7 cell line. The diols in this study showed little or no inhibition of the cancer cell lines.The GIIn our study of a variety of organotin polyethers we included the study of two related hormone-containing products. Characterization of these products has been reported ,35,36.The first is diethylstilbestrol (DES). Diethylstilbestrol -1,2-ethenediyl]bisphenol), is a synthetic estrogen that mimics estrogen, one of the primary ovarian hormones. It is known by a number of common names including stilbesterol and stilboestrol and sold under a number of names including Apstil, cyren A, distilbene, and stilbetin.DES was first used in 1938 for women in an effort to prevent miscarriage or premature deliveries. In 1953, a double-blind study showed that DES did little to improve premature deliveries or miscarriage. Even so, it was still widely marketed until the early 1970s for this use. By 1971 it was estimated that 5 to 10 million people were exposed to DES. In 1971 the Food and Drug Administration issued a Drug Bulletin advising physicians to halt prescribing DES. DES was linked to a rare vaginal cancer in female offspring. Further research has shown that DES is a teratogen that can cause malformation of an embryo or fetus.DES is currently used with animals. Its primary use is to treat urinary incontinence in spayed female cats and dogs. It has also been used to prevent unwanted pregnancy in dogs and cats. DES has been used to treat breast and prostate cancer but its use is limited because of relatively poor water solubility and a wide range of dose-related toxicities that includes nausea and vomiting, venous and arterial thrombosis, and fluid retention. The use of estrogens as potent antiandrogens in hormonal therapy of metastatic prostate cancer has also been described. Thus, there exist several studies that indicate the potential usefulness of DES as a positive drug in the treatment of specific cancers.The second hormone was dienestrol. Dienestrol,(4-phenol, is one of the most widely used sex hormones. It was initially synthesized by Dodd and others in 1938 and initially patented by both Boots and Hoffman-La Roche in 1949. In the popular literature it is often confused with DES, diethylstilbestrol, but it is a distinct hormone with its own chemical and biological properties. It is sold under a variety of trade names including Farmacyrol, Lipamone, and Retalon-Oral.Dienestrol is widely used in hormone therapy, mainly hormone replace therapy or more precisely, estrogen replacement therapy.50 MDA/ GI50 MCF-7 are generally much smaller than one (average = 0.30 for DES and 0.22 for dienestrol) while the CI50 MDA/ CI50 MCF-7 values are generally much larger than one (average = 4.0 for DES and 8.5 for dienestrol). The values are consistent with these organotin polyethers preferentially inhibiting the MDA non-estrogen sensitive cancer cell line. Further, the values for DES and dienestrol themselves are consistent with a preferential inhibition of the MDA non-estrogen cancer cell line. DES is effective against estrogen receptor positive (ER+) tumors such as the MCF-7 cell line [Here, the GIell line ,44,45,46Thus, the results for the two hormones are similar to those found for the hydroquinone and hydroquinone-derived products described in 50 and CI50 results for the organotin monomers. The GI50 MDA/ GI50 MCF-7 values are about one (average = 1.07) as are the CI50 MDA/ CI50 MCF-7 values (average = 1.06). Thus, the results are similar to those found for the aliphatic-derived diols given in Reactions were carried out using the interfacial polycondensation technique. Briefly, an aqueous solution (30 mL) containing the diol (0.00300 mol) and sodium hydroxide (0.0060 mol) was transferred to a one quart Kimax emulsifying jar fitted on top of a Waring Blender . Stirring was begun and a hexane solution (30 mL) containing the diorganotin dichloride (0.00300 mol) was rapidly added about 3-4 seconds) through a hole in the jar lid using a powder funnel. The resulting solution was blended for 15 seconds. The precipitate was recovered using vacuum filtration and washed several times with deionized water and hexane to remove unreacted materials and unwanted by-products. The solid was washed onto a glass petri dish and allowed to dry at room temperature. Chain length was determined employing light scattering photometry using a Brice-Phoenix BP 3000 Universal Light Scattering Photometer. Refractive indices were obtained using a Bauch & Lomb Model 3-L refractometer. Additional analysis was carried out including Mössbauer spectroscopy, infrared spectroscopy, NMR spectroscopy, and MALDI MS  seconds ,34,35,36in vitro model of breast cancer to study the role of estrogen in breast cancer. Cells are also positive for cytokeratin and negative for desmin, endothelin, GFAP, neurofilament, vimentin. Both cell lines were obtained from NCI and maintained in MEM supplemented with 10% fetal bovine serum at 37 °C in a 5% carbon dioxide atmosphere.The cell lines MDA-MB-231, that is estrogen-independent, estrogen receptor negative, and the breast cancer cell line MCF-7 a cell line isolated in 1970 from a 69-year-old Caucasian woman. MCF-7 is the acronym of Michigan Cancer Foundation. MCF-7 cells are a well-characterized estrogen receptor (ER) positive control cell line (cells are positive for cytoplasmic estrogen receptors) and therefore are a useful 4 cells per well in MEM supplemented with 10% fetal bovine serum, and incubated for 24 hours at 37 °C in a 5% carbon dioxide atmosphere. A stock solution of the compound was prepared in DMSO at a known concentration. On day two the cell media was removed and replaced with RPMI-1640 supplemented with 10% fetal bovine serum and the indicated drug concentrations. Seventy-two hours later the cells were assayed for proliferation using the CellTiter 96® Aqueous One Solution Cell Proliferation Assay by Promega Corporation. Assays are performed by adding a small amount of the CellTiter 96 Aqueous One Solution Reagent directly to culture wells, incubating for 1–4 hours and then recording absorbance at 490 nm with a 96-well plate reader. The quantity of formazan product as measured by the amount of 490 nm absorbance is directly proportional to the number of living cells in culture.For testing of the compounds, cells were harvested, counted, and plated into 96-well plates at 1 × 10All cytotoxicity values are calculated against a base-line value for each line that was generated from “mock-treatment” of the normal and tumor cells lines with media supplemented with all diluents used to prepare the chemotherapeutic compounds. For example, if the compounds were dissolved in DMSO and serial dilutions prepared in MEM to treat the cells, then the mock-treated cells were “treated” with the same serial dilutions of DMSO without added chemotherapeutic compound. This was done to ensure that any cytotoxicity observed was due to the activity of the compound and not the diluents. For the studies reported here, the mock-treatment never resulted in a loss of cell viability of more than one percent, demonstrating that the activity observed was not due to cytotoxicity of any of the diluents used, but was due to activity of the tested compounds.The results are consistent with the organotin polyethers derived from diols containing a O-phenyl moiety exhibiting a much lowered ability to inhibit the MCF-7 estrogen-sensitive cell line in comparison to the MDA non-estrogen cell line. By comparison, those organotin polyethers derived from simple aliphatic diols that do not contain an O-phenyl linkage to the tin exhibit little or no preference towards inhibition of either cell line.Recently, the ability of ionic tin to exert estrogen-like activity in MCF-7 breast cancer cells was reported . In thisThere are several possible consequences related to the difference in ability of different organotin polyethers to inhibit breast cancer cell lines based on the structure of the Lewis base moiety. First, other drugs incorporating known hormones may also demonstrate this preference for inhibiting the growth of non-estrogen sensitive breast cancer cells in comparison to estrogen sensitive breast cancer cells. Second, drugs containing related structures, specifically the O-phenylene or O-aromatic moiety, may also demonstrate a similar behavior. It is not known if this preference is operational when treating living breast cancer patients but it should be watched for, since a number of breast cancer treatments contain drugs that possess O-phenylene or O-aromatic moieties. These drugs include doxorubicin , epirubiMost of the hormones employed in drug replacement therapy, such as DES and dienestrol, also contain this structural moiety. Our bodies contain an abundance of cations such as magnesium, calcium, tin, and iron that chelate with carbonyls and aromatic hydroxyls present in the aforementioned drugs currently employed in the treatment of breast cancer. Each of these cations contain vacant d orbitals that could then form a complex similar to that present in the Sn-O-phenylene moiety that may provide differentiation between the estrogen and non-estrogen sensitive breast cancer cells. Thus, it might be prudent to employ drugs that do not contain the Sn-O-phenylene moiety in treating MCF-7 related breast cancer or at least test for this differentiation.in vitro cell studies reported on here. Much more must be done before more definite conclusions should be reached.The results are preliminary and must be viewed as such but do indicate that there exists a difference in the


Bone marrow transplantation (BMT) is the only therapeutic option for many hematological malignancies, but its applicability is limited by life-threatening complications, such as graft-versus-host disease (GvHD). The last decades have seen great advances in the understanding of BMT and its related complications; in particular GvHD. Animal models are beneficial to study complex diseases, as they allow dissecting the contribution of single components in the development of the disease. Most of the current knowledge on the therapeutic mechanisms of BMT derives from studies in animal models. Parallel to BMT, the understanding of the pathophysiology of GvHD, as well as the development of new treatment regimens, has also been supported by studies in animal models. Pre-clinical experimentation is the basis for deep understanding and successful improvements of clinical applications. In this review, we retrace the history of BMT and GvHD by describing how the studies in animal models have paved the way to the many advances in the field. We also describe how animal models contributed to the understanding of GvHD pathophysiology and how they are fundamental for the discovery of new treatments. The use of animal models to study human diseases is considered essential for understanding underlying pathophysiological and molecular mechanisms . Here, wThe advent of the atomic age in the early 1950s led to a strong interest in developing means to protect or cure the potentially lethal effects of radiation. Exposure to high doses of radiation was recognized to have deleterious effects on hematopoiesis and immune cell functions. By using different animal models including mice, rats, and guinea pigs, researchers soon discovered that injection of bone marrow or fetal spleen cells into lethally irradiated animals could reconstitute the hematopoietic system  . DespiteThe definition of GvHD is the result of a great number of accumulated observations since the 1940s. However, it was in particular the work of two independent researchers that elucidated the details of this phenomenon. Simonsen studied the acquisition of tolerance using chick embryos, and observed that injection of adult spleen or blood cells resulted in splenomegaly and severe hemolytic anemia in the recipient embryo. The rationale behind his experiments was that immunological competence is acquired after birth and, therefore, any immune effect in the adult to embryo transplantation setting is ascribable to the injected cells . During The nature of the GvHD reaction was ascribed to immunocompetent cells present in the bone marrow graft. Initial the first experiments showed that different hematopoietic cell populations could be fractionated by centrifugation on discontinuous albumin gradients . FactionThe success of allogeneic transplantation depends on the degree of histocompatibility match between donor and recipient. Research on outbred canine models has been vital to study genes involved in histocompatibility, and the importance of tissue typing and donor selection. In intial experiments, antisera were produced by cross immunization of dog littermates. These antisera were used in cytotoxicity tests in order to establish matched donor/recipient pairs that proved to be effective in reducing, but not eliminating, GvHD occurrence. The number and nature of the allo-determinants were still unknown; however, it was already clear that histocompatibility antigens were allocated to different loci and that the potential presence of different alleles would make the selection of donor–recipient pairs difficult, especially in unrelated animals –37. In tDifferences in the genes of the MHC region between donor and recipient are the major cause of T cell allo-activation and GvHD induction, but there are also other genes involved. The first observations of allo-antigens encoded outside the MHC complex came from the above-mentioned studies on BMT in dogs. In some instances, dogs developed GvHD when transplanted with MHC-matched bone marrow . SubsequGraft-versus-host disease can develop in two different forms that differ in pathogenesis, symptoms, and organ involvement. aGvHD affects up to 50% of the patients and accounts for 15% of post-transplantation mortality . ClassicUnderstanding the complexity of the process leading to aGvHD requires in-depth mechanistic studies to identify the involvement of the different components of the immune system. For this reason, a great deal of the knowledge on the pathophysiology of aGvHD is derived from animal models. In this section, we will review the seminal findings from animal models that have led to the current view of how aGvHD develops, which is acknowledged to progress through three phases: (i) activation of antigen-presenting cells (APCs), (ii) allo-activation of donor T cells, and (iii) tissue destruction by alloreactive T cells. A summary of these findings are found in Figure In the first phase, both the conditioning regimen and the underlying disease play central roles. Together, they create the tissue damage responsible for the production and the release of pro-inflammatory cytokines and chemokines that activate macrophages and APCs. Of particular importance is the damage to the intestinal epithelium caused by the conditioning regimens, and the subsequent release of microbial products, such as lipopolysaccharide (LPS) by the resident gut bacteria –84. AfteTotal body irradiation (TBI) was the standard immunoablative procedure in the first years of BMT, and it is a widely used pre-conditioning method in animal models of HSCT. TBI is a very harsh procedure and causes significant damage to the fast-replicating tissues, such as skin and intestinal mucosa. Through research in murine and canine models, it was shown that the conditioning intensity and GvHD severity were directly correlated , 87, 88.Enterobacteriales and Enterococcus order together with a loss in Clostridiales bacteria can promote aGvHD  proliferation and activity  cells can differentiate into diverse subsets depending on the cytokines and microenvironment they are exposed to, and different Th subsets may be involved in aGvHD pathogenesis in distinct organs  is an immunosuppressive drug that targets the production of folic acid, which is essential for the synthesis of nucleic acids and proteins. MTX was first tested in dogs and proved to be effective at reducing GvHD occurrence , 119. A TNF-α is one of the most important cytokines involved in the pathogenesis of aGvHD, implicated in many steps during the disease progression. The importance of this cytokine in aGvHD was first described in a mouse model . Since tIL-6 has a broad effect, activating many different immune cells. It has been associated with various inflammatory diseases, and has a predominant role in the early phases of aGvHD. Mouse studies have shown that IL-6 and its receptor (IL-6R) are upregulated during aGvHD , and thaThe classical role attributed to IL-2 is to stimulate T cell proliferation. After many years of both experimental and clinical research, it is now clear that IL-2 has a more broad effect, including the maintenance of Treg homeostasis. Due to its effect on this regulatory population, IL-2 has been investigated as a therapeutic agent for treatment or prophylaxis of aGvHD. Administration of low doses of IL-2 alone has produced contrasting results in mouse models showing either beneficial  or no efThe role of IL-18 and IL-22 in aGvHD pathogenesis is more controversial. ILC3 is a subset of innate lymphoid cells involved in maintaining gut homeostasis by producing IL-22, and is suggested to play a role in aGvHD pathogenesis. IL-22 is a cytokine with both protective and inflammatory functions, most likely depending on the microenvironment and the cell types involved . IL-22 p3CL1  observed in target tissues during disease. By injecting CXCR3-transfected Tregs, Hasegawa and colleagues showed specific migration of these cells to the target organs and subsequent reduction in aGvHD severity . DespiteEngagement of co-stimulatory molecules is necessary for full activation of T cells, and blocking these molecules has interesting potentials. Studies in animal models showed that anti-CD80 and anti-CD86 inhibited T cell expansion, and that mice treated with these antibodies experienced milder symptoms of aGvHD. Moreover, T cells isolated from CD28-deficient mice caused less severe GvHD , 145. Otex vivo, have made them promising candidates for immunotherapy for aGvHD [reviewed in Ref.  and Tregs . MSCs ar in Ref. ]. Despit in Ref. , 161, MS in Ref. , 162–167 in Ref. . The pre in Ref. , 170. A  rodents –173. Tre rodents . The fun rodents . Moreove rodents , 176. Inal aGvHD , 178.in vitro from conventional T cells  that develop in the thymus and induced Treg (iTreg) that differentiate from conventional T cells in response to TGF-β and IL-2. The second group is therapeutically interesting because iTreg can be generated  T cells , and theactivity , 181. Onactivity , 183. ThNatural killer cells are another therapeutically interesting cell population in context of aGvHD and GvL. Earlier studies in rodent models demonstrated that NK cells are important for successful engraftment after BMT. NK cells are particularly radioresistant and can mediate rejection of allogeneic cells –186. TheChronic GvHD in the clinic was initially defined as any symptoms of GvHD that occurred more than 100 days after transplantation, but it became increasingly clear that this definition was inadequate. Due to the heterogeneity of the clinical manifestations of cGvHD, cGvHD was only properly defined a decade ago with the NIH Consensus Project on cGvHD, and cGvHD is now classified as a disease distinct from aGvHD , 192. BoTherapies directed at ameliorating cGvHD have improved little over the past decades. The reason is incomplete knowledge of the underlying mechanisms that drive the disease. This has been mainly due to lack of animal models that completely recapitulate the full clinical heterogeneity of cGvHD. For more than three decades after cGvHD was acknowledged in the clinic, the best described and most utilized animal models for cGvHD addressed only one or a few of the many clinical manifestations of cGvHD, principally autoantibody generation or sclerodermatous disease  Table 22. The clChronic GvHD as a complication after allo-HSCT in the clinic was first acknowledged during the 1970s, with reports on autoimmune-like symptoms developing in patients several months after BMT. An autoimmune form of GvHD was described more than a decade earlier in experimental mouse and rat models. In 1961, Oliner, Schwartz, and Dameshek reported a form of GvHD (“runt disease”) in a parent to F1 hybrid transplantation model with autoimmune characteristics similar to systemic lupus erythematosus (SLE) . These wThroughout the 1970s and 1980s, the SLE-like and the scleroderma-like mouse models of cGvHD were the dominant animal models for cGvHD. These models were also extensively used for studies of autoimmune diseases. The SLE-like models generally involved transfers of lymphoid cells from a parental strain into non-irradiated F1 hybrids , and the allogeneic transplanted mice developed clinical and histological symptoms associated with GvHD, such as apoptosis and T cell infiltration into the target organs (b) – C57BL/6 (H2b)]. This model was developed to more closely mimic the clinical situation, where patients usually are MHC matched. With this model, similar T cell infiltration, GvHD-specific damage, and systemic inflammation were observed in the mice as reported in humans  between species can influence pathophysiology of GvHD (Another important consideration is the fact that the immune cell compositions vary between species. In murine models, mice receive bone marrow and T cells from an allogeneic counterpart to induce severe aGvHD. The T cell expansion is mainly homogeneous in the inbred recipients, in contrast to the heterogeneous T cell response in humans . Further of GvHD . In addi of GvHD . By cont of GvHD . In anot of GvHD . However of GvHD , 279.An important difference between mouse and rat animal models and humans is the homogenous genetic composition of inbred rodents, in contrast to the heterogeneous humans . FurtherMoreover, there are important species differences that need to be taken into consideration when extrapolating results found in animal models to humans . Differein vivo mechanisms and pathology of human GvHD (in vitro studies can provide hypotheses and models for research, there is a strong need for testing and validation in an in vivo animal model. The important pathophysiological conditions and symptoms of GvHD have been successfully reproduced in a number of animal models (An alternative to study GVHR is the use of the skin explant model. The skin explant model can closely mimic the man GvHD , 285. Thman GvHD , and we man GvHD . Althougl models , and anil models . Till dal models . IdentifOverall, substantial progress has been made using animal models to understand GvHD. However, major clinically relevant questions still remain unanswered. It is important to understand the mechanisms involved in the effect of RIC on late-onset aGvHD, for instance, or the mechanisms involved in steroid-resistant disease . In spitMB, PS, and MI wrote the manuscript; MB, PS, RD, and MI planned the contents; RD and MI reviewed the contents.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The throughput of spontaneous Raman spectroscopy for cell identification applications is limited to the range of one cell per second because of the relatively low sensitivity. Surface-enhanced Raman scattering (SERS) is a widespread way to amplify the intensity of Raman signals by several orders of magnitude and, consequently, to improve the sensitivity and throughput. SERS protocols using immuno-functionalized nanoparticles turned out to be challenging for cell identification because they require complex preparation procedures. Here, a new SERS strategy is presented for cell classification using non-functionalized silver nanoparticles and potassium chloride to induce aggregation. To demonstrate the principle, cell lysates were prepared by ultrasonication that disrupts the cell membrane and enables interaction of released cellular biomolecules to nanoparticles. This approach was applied to distinguish four cell lines – Capan-1, HepG2, Sk-Hep1 and MCF-7 – using SERS at 785 nm excitation. Six independent batches were prepared per cell line to check the reproducibility. Principal component analysis was applied for data reduction and assessment of spectral variations that were assigned to proteins, nucleotides and carbohydrates. Four principal components were selected as input for classification models based on support vector machines. Leave-three-batches-out cross validation recognized four cell lines with sensitivities, specificities and accuracies above 96%. We conclude that this reproducible and specific SERS approach offers prospects for cell identification using easily preparable silver nanoparticles. Cytopathology is the histopathologic inspection of cells. Dyes, such as hematoxylin for cell nuclei or eosin for cytoplasm, are commonly used to stain cells with subsequent microscopic assessment by pathologists. Complementary tools are immunocytochemistry, which uses fluorescence-labeled antibodies against cellular antigens, and flow cytometry, which combines several detection channels based on light scattering, absorption and fluorescence with microfluidic flow systems.Raman spectroscopy has been proposed as promising technique for cell characterization and cell identification because of its high chemical specificity under label-free and non-destructive conditions –2. RamanSERS was also suggested for cell identification –14. WhilThe current study transfers this SERS approach to distinguish four human cancer cell lines. These cell lines are two liver cancer cell lines , one breast cancer cell line  and one human pancreatic ductal adenocarcinoma cell line (Capan-1). A protocol was developed to disrupt the cell walls by sonication and to allow for the interaction of silver nanoparticles with the released cellular biomolecules. The measured SERS spectra from six different batches were subjected to a support vector machine (SVM) to train classification models. The sensitivities, specificities and accuracies of the SVM model were calculated by cross-validation schemes. This proof-of-principle demonstrates that non-functionalized, easy-to-prepare silver nanoparticles give reproducible SERS spectra that can be used for the identification of human cancer cells.The absorption band of silver (Ag) nanoparticles corresponds to the maximum of the plasmon resonance which is near 415 nm . ShiftinThe size and shape of Ag nanoparticles were also analyzed by electron microscopy. Transmission electron microscopy (TEM) images and scanning electron microscopy (SEM) images of silver nanoparticles are compared in −1 is assigned to carboxylate [−1 and can be assigned to adenine ring-breathing modes [−1. The bands at 800 and 960 cm−1 can be assigned to CN stretching vibrations. Carbohydrates are represented by bands in the spectral region of 1000–1100 cm−1. The bands at 1289 cm−1 and 1660 cm−1 can be assigned to the amide III and amide I vibrational modes of peptide bonds in proteins, respectively [−1 arises from CH2 deformation vibrations of all biomolecules. The bands at 2923 and 2952 cm−1 can be assigned to CH2 and CH3 stretching vibrations of all biomolecules [Cellular biomolecules including nucleic acids, proteins, carbohydrates and lipids are released after disruption of the cell membranes and can interact with nanoparticles. The spectral bands obtained from SERS measurements can then be assigned to biomolecules of cell nucleus and the cytoplasm. The raw spectra were baseline-subtracted and normalized. boxylate . Spectrang modes ,26–27. Pectively ,26,28. Tolecules ,26,28. T−1 and positive signals from 2800 to 3000 cm−1. The most pronounced spectral features were (i) positive bands near 660, 900 and 2900 cm−1 in PC2 loadings, (ii) a derivative-like feature at 660 cm−1 and negative bands near 723 and 1339 cm−1 in PC3 loadings, and (iii) negative band near 660 and derivative-like feature near 900 cm−1 in PC4 loadings. In general, we did not notice a significant difference in the amide content inside the four cell lines. The main differences were assigned to vibrations of nucleic acids, CH2/3 from the whole cell contents and the carboxylate moieties.It is evident from The score values of the first four PCs are plotted in The first four PCs were used as input for classification based on support vector machines (SVM). The SVM model was trained with three batches of cell lines and then tested with three different batches of the same cell lines. This allowed for 20 different batch permutations for validation and gave a reliable unbiased classification model. The test was run 20 times and the sensitivity, specificity and accuracy of the SVM model in each run were calculated. Four different human tumor cell lines, Capan-1, HepG2, Sk-Hep1 and MCF-7, were lysed using ultrasonication and then mixed with aggregated silver nanoparticles. The reproducibility of SERS spectra was demonstrated by preparing six batches and measuring them under the same conditions. The values of standard deviation, calculated for different batches, were small. PCA was performed to reduce the size of the data and assess variations between the four cell lines. Four PCs were used as input to a SVM model to classify these cell lines. Leave-three-batches-out cross validation was performed to test the stability of the SVM model. The SVM model was able to identify the different cell lines from each other with very high accuracy, sensitivity and specificity. The accuracy values were 96.7%, 97.1%, 99.1% and 98.8% for identification of Capan-1, HepG2, MCF-7 and Sk-Hep1, respectively. These values agree with classification results based on Raman spectra . CompareThe presented approach is a rapid, easy, efficient, highly reliable and specific strategy to identify and classify different human cancer cell lines without need for complex sample preparation procedures. To reduce the sample volume and measurement time towards few milliseconds, and automate mixing of solvents and acquisition of SERS spectra, this approach will be transferred to a droplet-based microfluidic lab-on-chip device . After dSilver nitrate , sodium hydroxide, hydroxylamine hydrochloride  and potassium chloride were purchased from Sigma–Aldrich. Distilled water was used for all preparations. The silver nanoparticle colloids were synthesized according to the protocol described by Leopold and Lendl . BrieflyTransmission electron microscopy (TEM): 5 µL of the particle dispersion were deposited on a carbon-coated 400 mesh copper grid. After 1 min of adsorption the excess liquid was blotted off with filter paper. Dried samples were then examined by a JEM 1400  transmission electron microscope.Scanning electron microscopy (SEM): Measurements were performed by a field emission microscope JSM-6300F . The energy of the exciting electrons was 5 keV. Beside the detector for secondary electrons (SEI) the system is equipped with different detector types (semiconductor and YAG) for backscattered electrons.Spectrophotometry: The UV–vis spectra of silver nanoparticles and KCl-aggregated silver nanoparticles were measured in the spectral range of 200–800 nm with a Jasco V-670 diode UV–vis spectrophotometer  using plastic cuvettes (Brand GmbH Wertheim Germany) of 1 cm light path.®, Life Technologies GmbH, Germany). Cultivation of MCF-7 breast cancer cells was performed in RPMI 1640 with 2.0 g/L NaHCO3  and 40 mg/L folic acid  with the same amount of fetal bovine serum, penicillin and streptomycin as described above for liver cells. The pancreatic cancer cell line Capan-1 was cultured in IMDM medium  complemented with 20% fetal bovine serum , 100 units/mL of penicillin and 100 µg/mL of streptomycin . The cells were maintained in an incubator at 37 °C, 90% humidity and 5% carbon dioxide in air. 75 cm2 cell culture flasks  were used for cultivation of the cell lines. Every two or three days the medium was changed until approximately 100% confluence was reached. Cells were detached from the substrate by a 0.05% of trypsin–EDTA solution  and fast frozen at −20 °C. The final number of cells in each flask was around 107 cells/mL, which was confirmed by cell counting, using Neubauer Chamber . In order to prove the reproducibility of our experiments six batches of each of the four cell lines were prepared. The optical density of different cell lines were measured using Eppendorf Biophotometer plus. The optical density of 0.25 was correlated to an averaged cell number of 107 cells/mL.Liver cancer cell lines (HepG2 and SK-Hep1) were cultivated in RPMI 1640 liquid medium with 20 mM HEPES, stable glutamine , 10% fetal bovine serum  together with 100 units/mL of penicillin and 100 µg/mL of streptomycin  with a maximum output power of 70 W. This sonication technique helps disrupting the cell membranes and allows for an interaction of released cell components with the silver nanoparticles. The probe was inserted inside an Eppendorf tube containing 1 mL of the cells in PBS solution. The sonication was applied in 3 cycles of 15 s each and 5 s break in between with a power set to 20%. The cell lysate was then transferred to a new tube and stored until further processing in a freezer.f/1.8 spectrograph with a holographic transmission grating , and a Peltier-cooled back-illuminated deep-depletion CCD detector . The microscope was coupled to the Raman system with fibers of 65 µm core diameter. A 10×/0.25 objective lens  was used for all SERS measurements. The laser wavelength was calibrated using cyclohexane. The system was intensity calibrated using a white light source. The laser power was fixed at 50 mW with an acquisition time of 5 s. Each batch was lysed and divided into eight to ten samples. 100 µL of the silver nanoparticles were mixed with 100 µL KCl as aggregating agent, and then 100 µL of cell lysate were added to the mixture with a final ratio of 1:1:1. 200 µL solution was filled in vials that were cut from 0.2 mL 96-well thin wall thermal cycler plates, and the laser beam was focused on the surface of the mixture. One spectrum was collected from each sample. The experiments were repeated using six batches for each cell line and the reproducibility was tested by calculating the standard deviation from the mean spectra.SERS measurements were performed on a commercial Raman microscopy system . This system consists of a multi-mode diode laser with 785 nm excitation wavelength (Invictus NIR laser), an −1 and a high-wavenumber region between 2828 and 3028 cm−1. Both regions were combined and area-normalized relative to the spectral wavenumber region. Spectral classification was performed by support vector machines (SVM) with a linear kernel, using the libSVM Matlab library by Chang [The intensity-corrected SERS spectra were exported to Matlab  and pre-processed before the evaluation of the spectral classification models. The imported spectra were corrected for the dark current and the constant voltage bias by subtracting a smoothed dark spectrum. The resulting spectra were corrected for the polynomial background arising from residual excitation light using the penalized least squares-based Whittaker smoother algorithm outlined by Eilers . The bacby Chang . The cla


RAS wild-type tumours. Novel drug targets, or drug combinations that induce a synergistic response, would be of great benefit to patients. The identification of genes that are essential for cell survival can be undertaken using functional genomics screens. Furthermore, performing such screens in the presence of a targeted agent would allow the identification of combinations that result in a synthetic lethal interaction. Here, we present a dataset containing the results of a large scale RNAi screen (815 genes) to detect essential genes as well as synergistic combinations with targeted therapeutic agents using a panel of 27 colorectal cancer cell lines. These data identify genes that are essential for colorectal cancer cell survival as well as synthetic lethal treatment combinations using novel computational approaches. Moreover, this dataset could be utilised in combination with genomic profiling to identify predictive biomarkers of response.Metastatic colorectal cancer is a leading cause of cancer death. However, current therapy options are limited to chemotherapy, with the addition of anti-EGFR antibodies for patients with  While early diagnosis leads to significantly higher survival, the prognosis for advanced stage disease remains poor. Therapeutic options for advanced colorectal cancer are currently limited to chemotherapy regimens (FOLFOX or FOLFIRI), and the anti-EGFR antibodies cetuximab or panitumumab4. While anti-EGFR therapy is beneficial in a subset of patients, tumours with activating KRAS, NRAS or BRAF mutations are intrinsically resistant, and exhibit constitutive activation of the MEK/ERK and/or PI3K/AKT signalling pathways6.Colorectal cancer is a leading cause of cancer mortality in the UK7–10.Despite the development of targeted agents over the last few decades, effective strategies to treat late-stage colorectal cancer have not emerged. While the concept of inhibiting a single signalling molecule remains attractive, in practice the inhibition of multiple targets often results in a more durable response. Furthermore, through the simultaneous inhibition of multiple signalling pathways, combination therapy may allow synthetic lethal interactions to be harnessed, and overcome intrinsic resistance to targeted agents11–14. Further, both chemical and genomic screens for synthetic lethal combinations have successfully identified targetable cancer-specific sensitivities15–19. However, it is important to note that in order to properly address the genomic heterogeneity of cancer, multiple cell lines are required. As is commonly seen, failure to do so results in a dataset that fails to capture the genetic diversity observed in the clinic, and identifies hits that are relevant only to the one cell line used.Several recent studies have successfully utilised high-throughput RNAi screening for profiling the essential gene landscape, and the identification of novel drug targets for cancer therapyIn this study, high-throughput functional genomics screens were used to identify and validate synthetic lethal combinations in a panel of colorectal cancer cell lines. An overview of the experimental design is shown in 20–23 (Data records 1 and 3). A total of 37 genes were identified that scored <−3 across three or more different cell lines.The primary siRNA screen hits were binned according to the screen arm: DMSO arm hits were binned as ‘Essential’ using a z-score cut-off of <−3, while ‘plus-drug’ arm hits were ranked according to their synergy score, and the number of cell lines that showed a synergistic response (Data records 1 and 3). Essential genes identified in the primary screen were enriched for genes connected to the cell cycle, and contained many known pan-cancer single gene vulnerabilitiesPLK1 and SF3B1 were also included. Deconvoluted siRNAs targeting 40 genes were rescreened as previously against the DMSO arm and three ‘plus-drug’ arms (The top 38 drug/gene synergistic combinations were selected for confirmation in a secondary deconvolution screen (4 siRNA sequences per gene) (Data records 2 and 3). siRNAs targeting the ‘Essential’ genes ug’ arms . This se25 were grown in either RPMI or DMEM/F12 medium, supplemented with 10% fetal calf serum and 1% penicillin/streptavidin, and maintained at 37 °C in a humidified atmosphere at 5% CO2. Cell lines used in these screens, and the number of cells seeded per well, are listed in A panel of commercially available colorectal cancer cell linesPrior to screening we performed optimisation of assay conditions using a subset of 11 colorectal cancer cell lines. The type and concentration of transfection reagent was established by transfecting cells with Non-targeting siRNA pool #2 or si_PLK1 using six different transfection reagents , Lipofectamine RNAiMAX, and Lipofectamine 2,000 (both from Invitrogen)) at 4 different concentrations, with 4 different siRNA concentrations. The optimal transfection score was calculated for each cell line as follows:This score takes into account any negative effect on cell viability that the transfection reagent may have, as well as rewarding conditions where the positive control siRNA (si_PLK1) is best at reducing cell viability compared to the control. The conditions with the best average OTS across all 11 lines were selected for screening.The concentration of anchor drugs was selected by performing dose response curves for each drug against 16 colorectal cancer cell lines. As the aim was to identify synergistic drug/siRNA combinations, it was important to select an anchor drug concentration that had a minimal effect on cell viability alone. A dose of the cetuximab and BYL719 compounds was therefore selected that inhibited cell viability by less than 20% in more than 75% of cell lines. Colorectal cancer is often driven by activation of the MEK/ERK pathway, and many of the lines on which trametinib was tested showed sensitivity to MEK inhibition. The dose of trametinib was therefore selected to 1) demonstrate effective inhibition of MEK phosphorylation and 2) inhibit cell viability by <30% in more than 50% of the cell lines.26, and is described below in detail. The primary siRNA screen was performed with biological replicates ; known to be important for cell cycle, and a propriety cell death siRNA control (siTOX) . The broad kinase inhibitor staurosporine (2 uM) was also added to select wells of each plate as a positive control for treatment by the anchor compounds. Non-targeting siRNA pool #2 was utilised as a negative control for siRNA transfection . Mock transfected (lipid only) wells were also added as a reference. Other controls that were included, but not used were siRNA SMARTpool targeting KIF11 , Non-targeting siRNA sequence #2  and siGENOME RISC-Free Control siRNA .The protocol developed for this screen was adapted from previously published methodsThe custom SMARTpool siRNA library was designed to target 95 genes commonly mutated in colorectal cancer (Data Record 3). Of these 95 genes, 15 were already present in the kinome library, resulting in 15 duplicates, and overall 794 unique siRNAs . Note that duplicate wells are not able to be reported in Pubchem (Data Record 1), but are included in the raw data files (Data Record 3).The siRNA transfer and addition of each anchor drug were performed using an Echo 555 acoustic dispenser (Labcyte Inc.). An XRD-384 (FluidX) automated reagent dispenser was used for all other liquid handling steps.Specialised consumable reagents that were required to perform the siRNA screens:Primary screen: Dharmacon Human siGENOME SMARTpool siRNA Library—Protein Kinases , and a Dharmacon Human siGENOME Custom SMARTpool siRNA Library (see Data Record 3)Secondary screen: Dharmacon Human siGENOME Custom siRNA Library—Set of 4 siRNA duplexes per gene1,536-well plates, polystyrene, tissue-culture treated, clear flat bottom wells, sterile, with lid, black Lipofectamine RNAiMAX Transfection Reagent OPTI-MEM CellTiter-Glo Luminescent Cell Viability Assay siRNA library and control plates were thawed at room temperature 1 h prior to use. Cells were incubated in TrypLE (Life Technologies) until detached, then washed in growth media, counted and diluted to the desired concentration in antibiotic-free DMEM/F12 or RPMI media .For the siRNA transfection, 70 nl of the siRNA library (2.5 μM stock) was dispensed into each well of 1,536-well plates  (using an Echo 555 acoustic dispenser). Lipofectamine RNAiMAX transfection reagent was diluted in OPTI-MEM media (1:50) and incubated for 5 min, before dispensing 1.5 μl into each well of each plate.Plates were then incubated for 20 min at room temperature, before dispensing 6 μl cells to each well (FluidX XRD-384 multiwell dispenser) . The final siRNA concentration was 23.9 nM.Column 1 of each plate received media only (no cells) for background luminescence readings. The plate layout was designed so that edge wells were not used, and control wells (positive and negative) were spread across the plate .2 in a Cytomat 24C rotating incubator (Thermo Fisher Scientific) to minimise temperature gradients.Plates were incubated at 37 °C in a humidified atmosphere at 5% CO−1 (32.9 μM) cetuximab , 10 nM trametinib (Selleckchem), or 1 μM BYL719 (Selleckchem). Vehicle treated wells received an equivalent volume of DMSO.After 24 h incubation, 7.5 nl of anchor drug or vehicle (DMSO) alone was added to each well as appropriate. Cells were treated to achieve a final concentration of 5 μg mlTo measure cellular ATP levels, the CellTiterGlo assay (Promega) was used. 2.5 μl of CellTiterGlo reagent was added to each well and incubated for 10 min. Luminescence was then measured using a Molecular Devices Paradigm plate reader. Changes in ATP levels were used as an indicator of overall cell viability.28. This method was chosen as it performed better than the B-score method29, which we found to overfit the data and significantly increased the kurtosis of the dataset. Note that no correction method was required for the secondary screen data.The analysis of screen data entailed background correction, normalisation and scoring steps. Analysis was performed using custom R scripts, and is detailed below. Preliminary analysis of the raw data (Data Record 3) uncovered a relatively consistent diagonal viability gradient across each plate. The raw luminescence intensity readings for each plate of the primary screen were corrected for these position bias effects using a loess normalization approachFor each plate the luminescence intensity readings were background corrected by subtracting the mean value of blank wells. This removes any background noise that may result from the cell medium. Each well was then normalized to the mean of DMSO treated Non-targeting siRNA pool #2 negative control wells (24 wells) on that plate to obtain a relative viability score (Data records 1 and 3). Note that viability values were capped at a maximum of 1 in order to obtain meaningful Bliss additivity score values (below).30–32 values for each plate, using the two positive siRNA controls (siPLK1 and siTOX), and passed plates if either SSMD value was greater than 330. Using plates that passed the SSMD threshold, the biological replicate plates for each cell line were then averaged.For quality control purposes, we calculated two Strictly Standardized Mean Difference (SSMD)29. Z-score normalisation is used to scale the results to a standard normal distribution, using the mean and standard deviation of the experimental wells. This approach ensured that variation in siRNA transfection efficiency across the panel did not affect our ability to select important viability genes in each cell line.In order to identify hits in the DMSO anchor arm  z-scores were calculated on a per-cell line basis33 for each drug/siRNA combination across each cell line as following (where V is the observed relative viability):To identify synergistic drug/siRNA combination hits, we calculated the Bliss additivity scoreWe then calculated the synergy score for each combination, by computing the difference between the expected Bliss additivity and the observed viability of the combination as following:Each drug/siRNA combination was then ranked according to the number of cell lines where Synergy score > 0.15. We selected 38 top drug/siRNA combinations that showed strong synergy scores (Synergy score > 0.15), across three or more cell lines. We prioritised combinations that also resulted in lower overall viability. Many siRNAs that ranked highly with one anchor drug were also synergy hits with a second anchor, and so we designed the secondary screen so that all 38 siRNAs were rescreened against all three ‘plus-drug’ arms. The secondary screen utilised four siRNA sequences per gene, assayed separately . The secondary screen data was then analysed using the same synergy score metric as previously, so that a synergy score was calculated for each individual siRNA duplex (Data records 2 and 3). For each siRNA duplex we determined whether the drug/siRNA combination reproduced a synergistic phenotype. The following threshold was used:The number of siRNA duplex per cell line that scored as reproduced was then tallied for each combination.Primary siRNA screen data for all 27 cell lines are available at PubChem (Data Citation 1 to Data Citation 27). Assay ID accession numbers are provided in Secondary deconvolution siRNA screen data for 23 cell lines are available at PubChem (Data Citation 28 to Data Citation 50). Assay ID accession numbers are provided in Raw data for both the Primary siRNA screen and the Secondary deconvolution screen are available at Figshare (Data Citation 51). Data for all assay plates are provided, including those with SSMD<3 that failed our QC threshold. Details of genes targeted by the custom siRNA library used in the Primary siRNA screen are also included, as are details of the siRNA/drug combinations selected for rescreening in the secondary deconvolution screen.30–32 , compared with the negative control Non-targeting siRNA pool #2 (NTPool#2). While most cell lines responded equally well to both siTOX and siPLK1, there were some cell lines that did not respond to siTOX while siPLK1 had a large viability effect, and vice versa. Therefore, for each assay plate the higher of the two SSMD scores was used to pass or fail the plate. Plates that passed the quality control criteria had an average NTPool#2/siPLK1 SSMD of 4.23 and median of 4.09, and an average NTPool#2/siTOX SSMD of 4.12 and median of 4.16 (27.The performance of positive and negative siRNA controls was quantified using the Strictly Standardised Mean Difference (SSMD)30–32 ; a stati of 4.16 , Fig. 2 Assay plates for four cell lines consistently failed , and couTo assess the biological replicate plate reproducibility, the Pearson correlation coefficient was calculated for each set of duplicate plates per cell line . All cell lines were highly reproducible with an overall median correlation between biological replicates of 0.77 (standard deviation: 0.13) .PLK1 (polo like kinase 1) was identified as essential (z-score<−3) in 24 of the 27 cell lines, with a further 2 lines scoring<−2.9. Other genes that were scored as essential in many of the cell lines include the cell cycle kinases AURKA (aurora kinase A) and WEE1, and SF3B1 (mRNA splicing factor 3b subunit 1) (The primary siRNA screen data (DMSO arm) returned a list of genes scored as essential (z-score<−3) for each cell line (Data record 1). Summarising this gene list showed that, as expected, bunit 1) .KRAS gene are expected to be highly dependent on KRAS expression compared to KRAS wild-type lines. siRNA-mediated knockdown of KRAS was found to be lethal (z-score<−3) for 7 of 14 KRAS mutant lines compared to 1 of 13 KRAS wild-type cell lines  (FGFR2 (z-score=−4.31). Medico et al.34 recently reported that NCI-H716 has an amplification of FGFR2 and is sensitive to an FGFR inhibitor as a result.Cancer cells that harbour mutations in the =0.0002) . While wPIK3CA with the anchor drug trametinib was identified as having a synergistic phenotype (Synergy score>0.15) in 7 cell lines (Data record 1), in keeping with the role of PI3K signalling in resistance to MEK1/2 (MAP2K1/2) inhibition35. While the reverse combination (BYL719 anchor drug with siRNA targeting MAP2K1) was not identified as synergistic, this is likely due to redundancy between MAP2K1 and MAP2K2. These results confirmed the ability of the screening methodology to identify known genes involved in colorectal cancer cell viability, and examples of synergistic drug/siRNA phenotypes.The analysis of the primary screen (synergy arms) synergy scores showed that the combination of siRNA targeting PLK1 and SF3B1. The results showed that individual siRNAs often produced stronger viability phenotypes than that observed using siRNA SMARTpools in the primary screen (Data record 2). In the Primary screen the effective concentration of each siRNA sequence in a SMARTpool is ~6 nM. However in the Secondary screen each individual siRNA sequence was 23.9 nM (4× higher concentration). While this may contribute to stronger viability phenotypes in the Secondary screen, part of the rationale for using siRNA SMARTpools is that by combining different siRNA sequences together the effective concentration of each siRNA sequence can be lower as the different siRNAs can act in concert.The deconvolution screen was designed to primarily confirm the top synergistic combinations. We did however also deconvolute siRNAs targeting the top essential genes SF3B1  as essential genes in colorectal cancer. Of note is the fact that several genes  that were ranked high in the primary screen (DMSO arm) list of essential genes were included in the secondary screen due to their role in synergistic combinations. Neither of these two genes were convincingly validated as single gene vulnerabilities  (Data record 2), despite a recent report which also identified these genes as essential genes in a pan-cancer siRNA screen11. This highlights the importance of a secondary deconvolution stage in any siRNA screening campaign.The results of deconvoluted siRNAs validated the role of PLK1  and PIK3CA in combination with the anchor drug trametinib. Overall, the average synergy score for each combination across all cell lines in the secondary screen was well correlated with the average synergy score for that combination in the primary screen  are provided so that users are able to investigate changes in viability and synergistic phenotypes by applying their own normalisation strategies and thresholds. This study focussed on identifying essential genes, across a heterogeneous panel of colorectal cancer cell lines. Genes that were scored as ‘Essential’ by siRNA knockdown alone (DMSO arm) can be investigated for their role in cell survival, with proof of principle being the lethality of In addition, we investigated and validated a number of novel synergistic drug/gene combinations using multiple siRNAs and multiple colorectal cancer cell lines. Only a subset of candidate combinations from the primary screen (synergy arms) were rescreened, and as the dataset contains the overall viability and synergy scores for each siRNA pool, further instances of synthetic lethal combinations may be uncovered. While the aim of this study was to identify drug/siRNA combinations that showed a synergistic response, investigators may also want to analyse the overall cell viability measurements in order to identify effective combinations that yield high cell death. In the clinic these combinations could also have potential benefit for patients.How to cite this article: Williams, S. P. et al. High-throughput RNAi screen for essential genes and drug synergistic combinations in colorectal cancer. Sci. Data 4:170139 doi: 10.1038/sdata.2017.139 (2017).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.