TSC1 or TSC2 cause Tuberous Sclerosis Complex, an autosomal dominant disorder, characterized by multi-system tumor and hamartoma development. Mutation and loss of function of TSC1 and/or TSC2 also occur in a variety of sporadic cancers, and rapamycin and related drugs show highly variable treatment benefit in patients with such cancers. The TSC1 and TSC2 proteins function in a complex that inhibits mTORC1, a key regulator of cell growth, which acts to enhance anabolic biosynthetic pathways. In this study, we identified and validated five cancer cell lines with TSC1 or TSC2 mutations and performed a kinase inhibitor drug screen with 197 compounds. The five cell lines were sensitive to several mTOR inhibitors, and cell cycle kinase and HSP90 kinase inhibitors. The IC50 for Torin1 and INK128, both mTOR kinase inhibitors, was significantly increased in three TSC2 null cell lines in which TSC2 expression was restored. Rapamycin was significantly more effective than either INK128 or ganetespib (an HSP90 inhibitor) in reducing the growth of TSC2 null SNU-398 cells in a xenograft model. Combination ganetespib-rapamycin showed no significant enhancement of growth suppression over rapamycin. Hence, although HSP90 inhibitors show strong inhibition of TSC1/TSC2 null cell line growth in vitro, ganetespib showed little benefit at standard dosage in vivo. In contrast, rapamycin which showed very modest growth inhibition in vitro was the best agent for in vivo treatment, but did not cause tumor regression, only growth delay.Inactivating mutations in either  TSC1 or TSC2. Mutations in either gene cause the same phenotype, although mutations in TSC1 are associated with milder clinical severity in multiple respects [Tuberous sclerosis complex (TSC) is an autosomal dominant neurocutaneous disorder, which is caused by inactivating mutation either in respects . Althougrespects .TSC1 and TSC2 mutations also occur rarely in multiple cancer types. Cancers with higher rates of TSC1/TSC2 mutation include: urothelial carcinoma of the bladder and upper tract, with 6–10% incidence of TSC1 mutations [TSC2 and TSC1 mutations [Inactivating utations  and periThe mechanistic target of rapamycin (mTOR) is a large  protein kinase that occurs in cells in either of two complexes, mTOR complex 1 (mTORC1) and mTORC2, that have overlapping as well as distinct components. They have different roles, and mTORC1 regulates cell growth in part by enhancing anabolic biosynthetic pathways , 8.TSC1 encodes TSC1/hamartin, TSC2 encodes TSC2/tuberin, and with TBC1D7 the three proteins form the TSC protein complex [ complex . This TS complex . Loss of complex . mTORC1  complex , 12. Bot complex , 13.Rapamycin, also called Sirolimus, has antiproliferative and immunosuppressive activities. Rapamycin binds to FK-506-binding protein (FKBP12) with high affinity, and rapamycin-FKBP12 binds to mTORC1 to inhibit its kinase activity in an allosteric manner . RapamycClinically, rapamycin is FDA-approved for both prevention of allograft rejection, and for treatment of lymphangioleiomyomatosis, Drugs closely related to rapamycin are termed rapalogs, and include temsirolimus, everolimus, and deforolimus. Rapalogs have very similar if not identical activity in vivo .Heat shock protein 90 (HSP90) is an ATP-dependent molecular chaperone, which is highly expressed and helps to maintain proteostasis. HSP90 regulates the proper conformation, function and activity of multiple proteins (about 200 ‘client’ proteins) by protecting them from proteasome-mediated degradation. HSP90 expression is upregulated in many forms of cancer, and is thought to promote/enable malignant transformation, tumor progression, invasion, metastasis, and/or angiogenesis , 18.HSP90 inhibition results in proteasome-mediated degradation of protein substrates –22. Lumi2. For serum starvation, cells were incubated with standard medium without FBS for 24 hours. For serum stimulation, FBS was added back with a final concentration of 10% for 30 minutes.All cell lines were obtained from the Broad Institute of Harvard and MIT. PEER (T-cell acute lymphoblastic leukemia), SNU-878 (hepatocellular carcinoma), SNU-886 (hepatocellular carcinoma), CW-2 (large intestine adenocarcinoma), 23132/87 (stomach adenocarcinoma), MEF-319 (endometrium adenosquamous carcinoma), KM12 (large intestine adenocarcinoma), HEC-151 (endometrium adenocarcinoma), DV-90 (lung adenocarcinoma), OVK18 (ovarian endometrioid carcinoma) and HCC-95 (lung squamous cell carcinoma) were cultured in RPMI 1650 with 10% fetal bovine serum (FBS); CAL-72 (osteosarcoma) and NCI-H1651 (lung adenocarcinoma) in DMEM/F-12 with 10% FBS; MGH-U1 (urinary bladder carcinoma) and HEK-293 (embryonic kidney cells) in DMEM with 10% FBS; and SNU-398 (hepatocellular carcinoma) in RPMI 1650 GlutaMAX medium with 10% FBS. All media was supplemented with 1% penicillin- streptomycin-amphotericin B (Corning). All cell culture was done in a 37°C humidified incubator in 5% COTSC1 and TSC2 on the cell lines, where mutations were reported, were designed with Primer3 [For DNA purification Gentra Puregene Tissue Kit was used (Qiagen). Oligonucleotide primers for sequencing mutated regions of  Primer3 . FastStaLKB1, PTEN, CDKN2A, TSC1, and TSC2. 57 of 425 cancer cell lines showed some degree of reduction in signal for one more TSC1 or TSC2 probes, and were subject repeat analysis using probe sets specific for either TSC1 or TSC2, the SALSA MLPA probemix P124 TSC1, and the SALSA MLPA probemix P046-D1 TSC2, respectively. Amplification products were run on an ABI 3100Genetic Analyzer  and electrophoregrams were generated. Peak heights were loaded into a standard Excel file to determine copy number for each probe and sample pair.MLPA was performed by standard methods  using a probe set that covered five tumor suppressor genes: Cells were lysed in cell lysis buffer  with added protease and phosphatase inhibitor cocktails (Sigma-Aldrich). The protein concentration was determined using a Bradford assay (Boston BioProducts). For immunoblotting, proteins were loaded in 4–12% gradient NuPAGE bis-tris gels (Life Technologies) or home-made 15% polyacrylamide gels, separated by SDS–PAGE and transferred to PVDF membranes. For detection the following primary antibodies were used: mTOR , TSC2, C-20 , TSC1 , pAKT-Ser473 , AKT1, C-20 , pS6K-Thr389 , S6 kinase, C-18 , pS6-Ser235/236 , pS6-Ser240/244 , GAPDH , 4E-BP1 , p4E-BP1-Ser65, , p4E-BP1-Thr37/T46 , peIF2α-Ser51 , BiP , cleaved caspase-3  and β-Actin .Secondary antibodies were anti-mouse, anti-rabbit, and anti-goat (Santa Cruz Biotechnology) conjugated to horseradish peroxidase, and were used at 1:3000 dilution. Immunoreactive bands were detected by chemiluminescence  using the G:Box:iChemiXT imager (Syngene).50 values were calculated using Graphpad Prism as the drug concentration that reduced cell viability by 50% compared to untreated cells. Rapamycin was purchased from LC laboratories and ganetespib from Synta Pharmaceuticals.The cell lines SNU-878, SNU-886, SNU-398, CAL-72, and PEER were screened for kinase inhibitors using a kinase inhibitor-focused library (LINCS). The LINCS library contained 197 kinase inhibitors, from a diverse ATP competitive kinase inhibitor set. These kinase inhibitors were shown to be relatively potent and selective towards a narrow range of targets. 2000 adherent cells and 3000 suspension cells were plated with 50 μL medium in each well of a 384 microplate. Drugs with a concentration of 660 nM were added the same day. After 48 hours cellular proliferation was determined using CellTiter-Glo (Promega). Drugs identified as having a significant effect on this screen were tested in greater detail. 2000 adherent or 4000 suspension cells were plated on day 0 on a 96 well plate with 100 μL medium, except on the marginal wells. Drugs were added on day 1, which were serially diluted three-fold from 10 μM to 1.5 nM. Cell viability was determined after 72 hours of treatment by adding 20 μL CellTiter-Glo. Cell viability was determined using XLfit4.0 software. ICTo add back TSC2 to cells lacking a functional TSC2 expression , pMSCV and pMSCV-TSC2 (containing the TSC2 cDNA) plasmids were used. HEK293T cells were transfected with pCL Ampho retrovirus packaging vector (Imgenex) and pMSCV-EV (empty vector) or pMSCV-TSC2, with selection to generate retrovirus. Retrovirus was then added to each of the SNU cell lines. Neomycin was used as a selection antibiotic.All procedures were carried out according to the Guide for the Humane Use and Care of Laboratory Animals, and the experiments were approved by the Animal Care and Use Committee of the Children’s Hospital, Boston, MA, USA (protocol reference number: 1589).Igh-1b/IcrTac-Prkdcscid) mice were used to generate xenograft tumors. Mice were purchased at the age of 3–4 weeks from Taconic, Germantown, NY, USA. Mice were 6 to 8 weeks old and their weight was between 17 to 25 g when 3 x 106 tumor cells of the cancer cell line SNU-398 in 100 μL medium mixed with 100 μL matrigel were injected subcutaneously in both back flank regions.Immunodeficient strain CB17SC-M scid . For drug administration, INK128 powder was dissolved daily in vehicle ; and was administered by gavage 5 days/week at a dose of 1mg/kg and a volume of 100 μL. Rapamycin was prepared as a 20 mg/mL stock solution using 100% ethanol, and was mixed daily with sterile vehicle /80% dextrose (D5W). Ganetespib was administered by tail vein injection once/week in a dose of 50 mg/kg. Control mice received vehicle treatment for one of these three drugs.Xenograft tumor nodules were followed 3x weekly, and when they reached a minimum diameter of 4mm (14–30 days after injection), drug treatments were initiated. Mice were treated either with INK128 (Intellikine Inc.), rapamycin (LC laboratories), or ganetespib ; or vehicle; or a combination of ganetespib and INK128, or ganetespib and rapamycin. Bodyweight was measured at least 3 times a week. Tumor size was measured with an electronic digital caliper in 2 dimensions . For IHC tumors were fixed with 10% formalin overnight and stored in 70% ethanol solution until paraffin embedding. Paraffin-embedded sections, both unstained and stained (hematoxylin and eosin stain), were prepared by the Rodent Histopathology Core, Harvard Medical School.For IHC, slides were rinsed with a series of xylene, ethanol, 95% ethanol, 80% ethanol, and PBS. To unmask the epitopes slides were boiled in 10 mM sodium citrate for 60 minutes and cooled to room temperature. Slides were washed with PBS. Slides were put into peroxidase blocking reagent  for 10 minutes, and washed with PBS. Afterward, slides were washed with distilled water, sections were counterstained with hematoxylin and washed under running water.Cell proliferation was assessed using an antibody against PCNA and the HistoMouse kit- plus kit (Invitrogen/Thermo Fisher Scientific), using AEC single solution chromogen, and then counterstained with hematoxylin. Sections were mounted with cover glass and Fluoromount G media.For TSC2 and pS6 IHC primary antibodies against pS6 (Ser235/236)  at a dilution of 1:250 and TSC2  at a dilution of 1:100 were used and incubated at 4°C overnight, rinsed, and then treated with anti-rabbit-HRP secondary antibody at room temperature for 60 minutes, followed by rinsing and slide preparation as above.To identify apoptotic cells, ApopTag plus peroxidase in situ apoptosis detection kit (Merck Millipore) was used according to the manufacturer’s instructions.The quantitative data of the xenograft tumor experiments are reported as the mean ± standard deviation for at least 5 tumors. Tumor sizes for the different treatment groups were compared using the Wilcoxon Rank Sum test using GraphPad Prism software. P-values less than 0.05 were considered statistically significant.TSC1/TSC2 are known recessive oncogenes whose loss is known to activate mTORC1. Here we sought to identify and characterize cancer cell lines with complete loss of either TSC1 or TSC2, and then to examine their sensitivity to a broad panel of kinase inhibitors, with a goal to identify additional inhibitors beyond rapalogs.TSC1 or TSC2. Among 1457 cell lines, 49 were reported to have mutations in TSC1 and 111 to have mutations in TSC2. These mutations were reviewed to identify those with nonsense mutations, frameshift deletions or insertions, or in-frame deletions in either TSC1 or TSC2, yielding 4 cell lines with probable mutations in TSC1 and 10 with probable mutations in TSC2 (Data from the Broad Institute Cancer Cell Line Encyclopedia (CCLE)  was revi in TSC2 .S1 Fig inTSC1; SNU-878 and SNU-886 showed homozygous nonsense mutations in TSC2. All other cell lines had mutations with allele ratios around 0.5.All of these cell lines were obtained, and mutations were confirmed by Sanger sequencing  and pS6 (Ser240/244) expression in serum starvation, in PEER, MFE-319, OVK18, SNU-886, and SNU-887 cells. GAPDH was used as a loading control.TSC1 and TSC2 genes by the MLPA method , in serum absence and serum add back conditions . This haVariable 4E-BP1 expression was seen among these cell lines, but all TSC1 or TSC2 deficient cell lines showed similar levels of expression of p4E-BP1-Thr37/Thr46 in serum-deprived and serum add back conditions. Expression of p-eIF2α (Ser51) was also higher in TSC1 or TSC2 deficient cells in comparison to the control cell line .The cell lines SNU-878, SNU-886, SNU-398, CAL-72, and PEER were screened for sensitivity to kinase inhibition using a kinase inhibitor-focused library (LINCS), which contained 197 selective kinase inhibitors . This liA wide variety of inhibitors showed a positive signal in this initial assay, including multiple mTOR, CDK, PLK, CHK, Aurora, and HSP90 inhibitors .S2 Fig inS3-S7 Figs inS3-S7 Figs inCandidate inhibitors were studied against most or all of the TSC1/TSC2-deficient cell lines in standard 96 well plate growth assays over a dose range of 1 nM to 10μM . We focu50 values ranging from 68 to 179 nM  levels were decreased in the absence of serum conditions in the TSC2 add back cells, indicating return to normal regulation of mTORC1. pAKT (Ser473) expression was quite low in the TSC2 add back cells, but increased significantly in response to serum stimulation in the cell lines SNU-886 and SNU-878, compared to the levels of native or empty vector-transfected cells. SNU-398 did not show a pAKT (Ser473) expression increase in TSC2 add back cells .S5 and S7 Figs inS3, S4 and S6 Figs inS2, S8-S12, S15 and S17-S21 Figs inThese three TSC2 add back cell lines were used in drug testing experiments similar to what was done above. Interestingly, TSC2 add back cells had a 3 to 6-fold higher IC50 for both Torin1 and INK 128 than their empty vector controls or original unmanipulated cells  and pS6 S240/244) to a major degree in the absence of serum, as well as with serum stimulation . These f to a majGanetespib at lower doses, up to 10 nM, had little or no effect on expression of key mTOR signaling proteins, or activation of mTORC1, as assessed by pS6 (Ser240/244) levels . At 100 We also examined the effects of ganetespib on phosphorylation of 4E-BP1 and induction of apoptosis as assessed by cleaved caspase 3 levels  Fig 7)..Fig 7). The observation that there was little effect on mTORC1 signaling or protein expression in any of the cell lines near the IC50 dose of ganetespib (3 to 35nM) suggests that the growth inhibition effects were being mediated by other client proteins of HSP90 whose expression was likely reduced to some extent at doses near 10nM, and likely a collective effect on multiple HSP90 client proteins.6 SNU-398 cells were injected subcutaneously into the flank region of immunodeficient CB17SC-M (C.B-Igh-1b/IcrTac-Prkdcscid) mice. After approximately 10 days palpable and measurable tumors with a diameter of 3–5 mm were noted. Mice were treated with rapamycin, INK 128, or ganetespib, using doses described previously as being the maximal tolerated dose, in studies by ourselves and others [Given the evidence of some synergy in the growth inhibition of the TSC1/TSC2 null cell lines in response to combined mTOR and HSP90 inhibition, and evidence that they were impacting growth through different mechanisms, we explored the potential synergistic effect of treatment with these compounds in vivo using a subcutaneous xenograft tumor model with SNU-398 cells. 3.0x10d others , 46.3, after a mean (SD) of 18 (4.8) days after tumor cell injection. Treatment with the individual drugs was assigned randomly.Mice were treated when tumors had a mean (SD) diameter of 7.8 (1.7) mm and a mean (SD) volume of 186 (110) mmS22a-S22d Fig inGrowth of xenograft tumor nodules was reduced by each of the three drugs, with ganetespib, 50 mg/kg by tail vein injection 1 time/week, having the least effect; and rapamycin, 3mg/kg given intra-peritoneally 3 days per week, having the greatest effect; and INK 128, 1 mg/kg by gavage 5 days/week, being intermediate , and immunoblotting of tumor lysates. Histologically, the tumors were not homogeneous, with necrotic areas centrally and high proliferation in the periphery of nodules, regardless of treatment, as is commonly seen in xenograft models.IHC against proliferating cell nuclear antigen (PCNA) was used to assess proliferation , and theIHC showed no TSC2 expression in the tumors. Vehicle and ganetespib-treated tumors were pS6 (Ser235/236)+. In contrast rapamycin-treated tumors had much reduced pS6 (Ser235/236) expression, and this was also lower in INK 128-treated tumors, in comparison to the tumors treated with ganetespib or vehicle .Immunoblots of harvested tumors, carefully dissected for viable and not necrotic regions, and livers, of mice treated with vehicle, rapamycin, INK 128, ganetespib, and the combinations were performed to examine the effect of the drugs on protein expression and the mTORC1 pathway in vivo. None of the treated livers showed major changes in expression of AKT or S6K . SimilarThe current and accelerating trend in cancer therapy is the use of personalized  cancer treatment. Such targeted therapies may be directed at genetic mutations which are driver events in cancer; or at expressed proteins, such as the estrogen receptor in breast cancer .TSC1 or TSC2 from this resource. From a large set of candidate cell lines, subjected to sequencing and immunoblotting, we identified 5 cell lines with a total loss of either TSC1 or TSC2, and which also showed constitutively upregulated mTORC1 signaling, as indicated by high expression of pS6K (Thr389) and pS6 (Ser240/244) in the absence of serum. Two other cell lines, MFE-319 and OVK18, also showed constitutively upregulated mTORC1 signaling as well as upregulated pAKT (Ser473) expression, likely due to loss of PTEN by mutation [One resource that has been developed for a better understanding of cancer development, and to investigate potential targeted therapies are cancer cell lines, including the Cancer Cell Line Encyclopedia of 947 human cancer cell lines . In thismutation .The mTORC1 signaling pathway is one of the main regulators of cell growth, which acts by enhancing anabolic biosynthetic pathways in both normal and cancer cells. The mTOR signaling pathway is involved in many important processes including proliferation, autophagy, protein and lipid synthesis , 51, lysmTOR is an atypical serine/threonine kinase, and forms the key component of two protein complexes, mTORC1 and mTORC2. The TSC1 and TSC2 proteins function in a complex with a third component, TBC1D7 , as one TSC1 or TSC2 in the germ line cause Tuberous Sclerosis Complex, an autosomal dominant neurocutaneous disorder, characterized by skin lesions, neuropsychiatric disorders and mainly benign tumors of the brain, kidney, lung, heart, and skin [TSC1 and/or TSC2 have also been shown to occur consistently in a variety of sporadic cancers including bladder, kidney, pancreatic neuroendocrine tumors, and PEComa. More rarely TSC1/TSC2 mutations have been identified in many other cancer types, though whether they are important driver events or passenger mutations is not clear in many instances.Inactivating mutations in either and skin . MutatioTSC1 or TSC2, we performed drug screen using 197 kinase inhibitors. The cell lines were sensitive to several mTOR inhibitors, but also HSP90 and cell cycle inhibitors. In addition, PEER cells were sensitive to Aurora kinase inhibitors.Following our identification of five cell lines, PEER, CAL-72, SNU-886, SNU-878, and SNU-398, with bi-allelic mutation and loss of either We showed that the sensitivity of these cell lines to mTOR inhibitors like Torin1 and INK 128 correlated strongly with the deficiency of TSC2 and could be reversed by add back of TSC2 expression. However, we did not see this correlation with WYE-125132, AZD8055, and Torin2, which may reflect the activities of these compounds on kinases other than mTOR.Various rapalogs have been approved for treatment of various cancers, but complete responses are rare, and the PR rate is typically 5–10% –57. In aOne potential reason for the limited therapeutic benefit of rapalogs, is their lack of effect on many mTORC1 phosphorylation targets, including 4E-BP1 , 61. In Potentially, newer ATP kinase pocket directed mTOR inhibitors could or should be more effective in controlling the growth of cells and tumors with TSC1/TSC2 inactivation. Torin1, for example, showed complete inhibition of phosphorylated 4E-BP1 and AKT. However, an apoptotic effect was still lacking. In addition, in our xenograft assay, rapamycin was more effective than the dual mTORC1/2 inhibitor INK 128 in inhibition of growth of the TSC2 null S-398 cell line. However, this may reflect the consequence of dual mTORC1 and mTORC2 inhibition by INK 128, leading to a lower tolerable dose, and less effective suppression of each of mTORC1 and mTORC2. Other off-target effects of this drug may also contribute to in vivo toxicity, limiting effective targeting of mTOR.The HSP90 inhibitors ganetespib and NVP-AUY922 both showed strong inhibition of growth of all five TSC1/TSC2 null cell lines in vitro, with IC50’s in the range of 2 to 35 nM. Ganetespib was studied in greater detail. Ganetespib reduced mTOR, AKT, and S6K, as well as pS6, levels in all cell lines, but at 100 nM, a dose higher than the IC50 dose. These results suggest that ganetespib’s effect was not due directly to effects on mTOR signaling, but rather likely to broad effects in lowering expression of HSP90’s client proteins.Based on these findings of growth inhibition by ganetespib in vitro, we performed tumor xenograft experiments using the TSC2 null SNU-398 cell line. This cell line showed robust growth in immunodeficient CB17SC-M scid mice as subcutaneous xenografts. All three of rapamycin, INK 128, and ganetespib, when given at previously determined doses near the maximally tolerated dose, showed a significant effect on the growth of the SNU-398 xenografts . RapamycNext, we examined the potential of combination therapy using ganetespib with each of the other two drugs. Ganetespib combined with INK 128 showed greater reduction in tumor growth than either drug alone, although this did not quite meet statistical significance . In contTSC1 or TSC2. Blenis and colleagues found that the combination of glutaminase (GLS) and HSP90 inhibition selectively triggered the death of TSC1/TSC2 deficient cells [Multiple past studies have examined the interaction between mTOR signaling and HSP90, and the potential benefit of HSP90 inhibition on growth of cell lines lacking nt cells , likely nt cells . They thnt cells .In addition, the combination of rapamycin and HSP90 inhibitors has been previously studied for treatment of hepatocellular cancer (HCC) . Lang ethttps://www.clinicaltrials.gov/).Numerous inhibitors of HSP90 have been developed as potential anticancer drugs. Many such drugs, including ganetespib, have been evaluated in clinical trials, but none have been approved by the FDA, due to lack of benefit. The main reason for the limited efficacy appears to be that at effective doses of HSP90 inhibition, there is release of the HSF1 transcription factor from HSP90, which enters the nucleus leading to a prosurvival heat shock response . NonetheTSC1 or TSC2, and consequent constitutive mTORC1 activation. Through our kinase inhibitor screen, we identified a number of inhibitors that have some activity on these cell lines, including cell cycle kinase and HSP90 kinase inhibitors. In vitro, the HSP90 inhibitors NVP-AUY922 and ganetespib had major inhibitory effects on the growth of all five lines in the nanomolar range. However, this appeared to be due to global effects on HSP90 client protein expression, and not a specific effect on components of the mTOR signaling pathway. In vivo analysis of an HCC subcutaneous xenograft model using the TSC2 null SNU-398 cell line showed that ganetespib at usual doses had minimal effects on tumor growth both alone and in combination with rapamycin and INK 128. Rapamycin showed activity superior to that of INK 128 in vivo.In conclusion, we have identified and validated five cancer cell lines that have complete loss of either S1 Raw images(PDF)Click here for additional data file.S1 File(PDF)Click here for additional data file.S1 Table(DOC)Click here for additional data file.


Recent research has suggested that the endocannabinoid system offers several pharmacotherapeutic targets for drug administration as new options for the treatment and prophylaxis of skin cancer. This review focused on the anticarcinogenic mechanisms of cannabinoids at the different levels of skin cancer progression, such as inhibition of tumour growth, proliferation, invasion and angiogenesis, as well as inducing apoptosis and autophagy.Drugs targeting the endocannabinoid system are of interest as potential systemic chemotherapeutic treatments and for palliative care in cancer. In this context, cannabinoid compounds have been successfully tested as a systemic therapeutic option in preclinical models over the past decades. Recent findings have suggested an essential function of the endocannabinoid system in the homeostasis of various skin functions and indicated that cannabinoids could also be considered for the treatment and prophylaxis of tumour diseases of the skin. Cannabinoids have been shown to exert their anticarcinogenic effects at different levels of skin cancer progression, such as inhibition of tumour growth, proliferation, invasion and angiogenesis, as well as inducing apoptosis and autophagy. This review provides an insight into the current literature on cannabinoid compounds as potential pharmaceuticals for the treatment of melanoma and squamous cell carcinoma. Skin cancer essentially comprises three tumour categories, namely, cutaneous melanoma, basal cell carcinoma and squamous cell carcinoma. The latter two are grouped under the term non-melanoma skin cancer, which also includes other primary skin neoplasms such as cutaneous lymphoma, adnexal carcinoma, dermatofibrosarcoma protuberans and Merkel cell carcinoma. Therefore, “keratinocyte carcinoma” is the preferred term, combining basal cell carcinomas and cutaneous squamous cell carcinomas because of their common descent from epidermal keratinocytes . Basal cRegarding some previous studies, the treatment of cutaneous melanoma with classical chemotherapeutic agents such as the Dartmouth regimen   and withBRAF) is found in half of all cases of skin tumours, whereas mutations in the neuroblastoma RAS (rat sarcoma) viral oncogene homologue (NRAS) occur in 21% GTPγS binding assays [As early as 1984, Allyn C. Howlett demonstrated that Δactivity . The rec and CB2 ,32. Witht of THC ,34. Furtactivity . A studyreceptor . On the receptor ,36. Anotreceptor . The aut agonist . Accordima cells . Finallyg assays .i values, while the non-psychoactive phytocannabioid cannabidiol (CBD) has only weak cannabinoid receptor affinity with Ki values in the micromolar range . Competectively . In anotagonists . In a ree of THC . This coe of THC ).1 and CB2 receptors [1 and weak CB2 receptor agonist properties [The extended endocannabinoid system likewise includes other receptors modulated by cannabinoids, such as transient receptor potential vanilloid 1 (TRPV1), which is activated by AEA  and CBD eceptors . Moreoveeceptors . It was operties , acts asoperties . From thoperties .50 values for AEA, 2-AGE, 2-AG, PEA, OEA, abnormal CBD (synthetic regioisomer of CBD) and O-1602  were registered that were lower than the corresponding EC50 values in CB1 and CB2 activity assays, while for CBD an antagonistic effect at GPR55 was demonstrated [q and G12 proteins. The human G protein-coupled receptor 55 (GPR55), which was first isolated and cloned in 1999, is also activated by various cannabinoids in a cell-type- and tissue-dependent manner. Only two studies on this topic are outlined here. In GPR55-transfected cells, ECnstrated . In anotFinally, the proliferator-activated receptor (PPAR) α was reported to be activated by different endocannabinoid-like substances. In this context, OEA  and PEA Among the cannabinoid compounds, ajulemic acid, a synthetic analogue of the THC metabolite THC-11-oic acid, was first found to bind directly to PPARγ and activate its transcriptional activity . Moreove2 ethanolamide [2 glycerol ester [2 glycerol ester is subsequently converted to PGE2 glycerol ester by PGE synthase and to PGD2 glycerol ester by PGD synthase. Later, the same group discovered that AEA and 2-AG can be further metabolised by thromboxane and prostacyclin (PGI) synthase to thromboxane and PGI ethanolamides and glycerol esters, respectively [The synthesis of AEA is mainly carried out by N-acylphosphatidylethanolamine phospholipase D (NAPE-PLD). 2-AG, on the other hand, is synthesised by phospholipase C or by diacylglycerol lipase α and β . The denolamide . Regardiol ester . Using cectively . AccordiThe presence of the endocannabinoid system in skin tissue was demonstrated in the mid-1990s by the discovery of the endocannabinoid AEA in rat skin, where it was found in concentrations similar to those in the rat brain . Later, 1/CB2 receptor double knockout mice showed increased allergic inflammation, while conversely, FAAH-deficient mice with correspondingly higher AEA levels exhibited fewer allergic skin reactions. In line with this, numerous studies on the role of endocannabinoids in various skin functions have led to these compounds now being considered important neuroendocrine regulators in the maintenance of skin homeostasis [The great importance of cannabinoid receptors for the homeostasis of the skin was clarified in a comprehensive study that demonstrated an involvement of these receptors in the pathogenesis of allergic contact dermatitis . The auteostasis . Accordieostasis , regenereostasis ,74 and meostasis . Current2 receptor is upregulated in melanoma tissue [1 receptor-positive squamous cell carcinomas of the oesophagus were associated with poorer patient survival compared with patients with CB1 receptor-negative tissue [2 receptor immunoreactivity in biopsies from patients with squamous cell carcinoma of the head and neck was significantly associated with a reduced disease-specific survival rate [2 receptor expression and concurrent CB1/CB2 receptor expression occurring more frequently in female than male patients. An increase in cannabinoid receptors was also observed more frequently in older than in younger patients. Therefore, it is difficult to make a statement about whether the regulation of cannabinoid receptors in tumour tissue in melanoma or squamous cell carcinoma is predictive of disease progression or even of the functional role of these receptors in the pathogenesis of these cancers.Recently, several studies have investigated possible regulations of cannabinoid receptors and other elements of the endocannabinoid system in skin cancer tissues, as well as a possible link between these factors and skin tissue malignancy. In this context, one study showed that the CBa tissue . Other ee tissue . Anotherval rate . In contval rate . This stRegarding the regulation of other elements of the endocannabinoid system in skin cancer, one study found upregulation of MAGL in melanoma tissue, with increased expression associated with higher tumour aggressiveness .1 and CB2 receptors. In 2006, Blázquez et al. showed that activation of CB1 and CB2 leads to a reduction in growth, proliferation, and metastasis of melanoma cells, as well as neovascularisation of melanoma xenografts [1 and CB2 antagonists. A similar decrease in viability by cannabinoids could not be detected in non-transformed melanocytic cell lines. The authors also reported a pronounced inhibitory effect of WIN 55,212-2 or JWH-133 at 50 µg per day on the growth of xenografts generated by injection of B16 mouse melanoma cells into C57BL/6 mice. In another work, WIN 55,212-2 was shown to have an antiproliferative effect on the metastatic skin melanoma cell line SK-MEL28 and the non-metastatic ocular uveal melanoma cell line OCM-1 via a receptor-independent pathway involving lipid rafts [1 and CB2 antagonists did not rescue melanoma cells from cannabinoid-induced cell death, whereas disruption of lipid rafts by methyl-β-cyclodextrin protected cancer cells. A recent study tested the effect of CBD on malignant melanoma cell growth and metastasis in a mouse model in which B16F10 mouse melanoma cells were injected into C57BL/6 mice [There have been numerous investigations into the antiproliferative and proapoptotic effects of cannabinoids on human melanoma cancer cells expressing CBnografts . Part ofnografts . In addiid rafts . Here, CL/6 mice . CompareL/6 mice . A furthL/6 mice . HoweverCannabis sativa extract alone or in combination with a single dose of radiation significantly inhibited melanoma cell viability and proliferation in vitro in a concentration-dependent manner. Remarkably, this inhibition of melanoma cell viability was accompanied by an increase in necrosis but not apoptosis [As for combinations with radiation treatments, a standardised poptosis .1 receptors partially reduced the cytotoxicity of AEA. In contrast, methyl-β-cyclodextrin, tested at a concentration sufficient to destroy membrane lipid rafts without affecting viability, completely reversed cytotoxicity by AEA and by the GPR55 agonist O-1602, suggesting a possible role of lipid rafts and GRP55 in the viability-impairing effect of AEA [A number of publications further found endocannabinoids and inhibitors of endocannabinoid-degrading enzymes to influence melanoma growth. Accordingly, antitumour activity of AEA on A375 melanoma cells was reported in a study showing concentration-dependent cytotoxicity of AEA in association with a caspase-dependent apoptotic signalling pathway . Here, ct of AEA . Anothert of AEA . The stut of AEA . In addition, MAGL has been shown to be a factor that decisively influences the malignancy of melanoma cells. One study showed that the melanoma cell line C8161, in which MAGL was permanently downregulated by transfection with a small hairpin (sh) RNA, exhibited reduced viability. Interestingly, the authors could not confirm inhibition of cell survival when using the MAGL inhibitor JZL184. However, both MAGL shRNA and JZL184 inhibited xenograft growth in vivo, with the effect of MAGL shRNA being abolished by a high-fat diet . Consist2 ethanolamide [12,14-PGJ2 ethanolamide [Finally, PGDnolamide  and 15-dnolamide , both prnolamide .1 agonist AM-251 has been associated in vitro with arrest of the G2-M cell cycle, inhibition of the expression of anti-apoptotic proteins such as B-cell lymphoma 2 (BCL2) and survivin, and increased expression of the proapoptotic Bcl-2-associated X protein (BAX) [i/o protein-coupled CB1 receptor, a 40% increase in basal cAMP levels was observed after treatment of A375 melanoma cells with AM-251, although its causal involvement in cell cycle arrest was not further investigated [1 using shRNAs, led to a slowing in the cell cycle in the G1-S phase, which was accompanied by reduced activation of protein kinase B (Akt) and ERK, suggesting a possible function of the CB1 receptor as a tumour-promoting signal in human skin melanomas [1 receptor antagonist/inverse agonist AM-251.It is also noteworthy that cannabinoid receptor activation is not a process that has been uniformly described as growth inhibitory. For example, in A375 melanoma cells, the inverse CBin (BAX) . Consiststigated . In anotelanomas . In a fuelanomas . Paradox1 agonist ACEA and 2-AG, induced melanogenesis via CB1 activation up to a concentration of 3 µM, whereas apoptosis of primary normal human epidermal melanocytes occurred via activation of TRPV1 at high concentrations of Met-AEA (≥4 µM) [It can be assumed that the mode of action of cannabinoids under certain conditions can induce concentration-dependent opposite effects with low, proliferatively effective concentrations and high antiproliferative and proapoptotic concentrations. Thus, Met-AEA and other cannabinoids, such as AEA, the CB (≥4 µM) .2 agonist JWH-133 induce apoptosis in a mouse spindle cell squamous cell carcinoma cell line (PDVC 57B cells) in vitro and reduce tumour growth in a murine xenograft model represents the first ever report of anticarcinogenic cannabinoid effects in skin cancer.As for melanomas, there are several studies on possible antiproliferative and proapoptotic effects of (endo)cannabinoids on squamous cell carcinomas. In this context, the finding published by Casanova et al. in 2003  that the2 and PGD2-ethanolamide as well as PGJ2 and 15-deoxy-Δ12,14-PGJ2 [2 ethanolamide, Δ12-PGJ2 ethanolamide and 15-deoxy-Δ12,14-PGJ2 ethanolamide, metabolites of AEA formed via COX-2 that cause stress in the endoplasmic reticulum, finally leading to apoptotic cell death [2 ethanolamide leads to apoptotic cell death of skin cancer cells via both oxidative and endoplasmic reticulum stress [It was later shown that cannabinoids in squamous cell carcinomas lead to the death of the cancer cells not only through their effect on the cannabinoid receptors, but also through other mechanisms of action. In this context, the fact that most non-melanoma skin cancers as well as other epithelial tumours overexpress COX-2 plays an important role. According to van Dross et al., treatment with AEA in the murine COX-2-overexpressing keratinocyte squamous cell carcinoma cell line JWF2 led to cell death due to the metabolism of AEA to cytotoxic PGD,14-PGJ2 . The aut,14-PGJ2 . Further,14-PGJ2 . This wall death . Finallym stress . At the 1 receptor and TRPV1 activation and instead partially abrogated by antioxidants and 5-LOX inhibition. Further experiments showed that in addition to the growth inhibitory effects, the ROS-increasing and Akt phosphorylation-inhibiting effects of the PUFAs tested were reduced by inhibition of 5-LOX, suggesting that ROS generated by the 5-LOX pathway mediate the anticancer effects of DHEA and NALA [Furthermore, AEA, but not 2-AG, was found to exert an anticancer effect on head and neck squamous cell carcinoma cell lines  via a receptor-independent mechanism mediated by an increase in ROS . It is nand NALA . Regarding the anticancer effects of phytocannabinoids, CBD was demonstrated to significantly reduce cell viability of the human tongue carcinoma cell line SCC-25 and induce apoptosis . In thisTo determine the contribution of GPR55 as another cannabinoid-driven target to squamous cell carcinoma carcinogenesis, a study was conducted using GPR55-deficient mice. Here, GPR55 was shown to increase the number of papillomas and carcinomas in a mouse skin carcinogenesis model. Using the murine transformed mouse keratinocyte cell line PDV, the authors also found that cells with stable suppression of GPR55 had lower viability, colony formation and invasion in vitro, and lower xenograft tumour growth in vivo . However1 agonist ACEA, the CB2 agonist HU308 and THC were found to increase proliferation in three out of five different HPV-positive head and neck squamous cell carcinoma cell lines at concentrations up to 1 µM after an incubation period of three days. ACEA and HU308 left proliferation virtually unchanged in the other two cell lines, while THC inhibited proliferation in one cell line and had no effect in another cell line. ACEA and HU308, at concentrations of 10 µM each, resulted in additional inhibition of cell growth in another of the five cell lines (UM-SCC-47). The selective CB1 receptor antagonist rimonabant and the CB2 receptor antagonist SR144528 each inhibited proliferation in three of these five cell lines and had no effect on cell growth in the other two cell lines. The authors also confirmed the trend of these results in vivo with rimonabant, SR144528 and suppression of CB1 and CB2 by shRNA transfection, each of which reduced the growth of xenografts of UD-SCC-2 cells in nude mice. The administration of THC accelerated tumour growth accordingly [1 receptor expression and the degree of metastasis to lymph nodes. Consistent with this notion, the authors found that the inverse CB1 agonist AM-251 significantly suppressed the proliferation of several oesophageal cancer cell lines [As with the effects of cannabinoid receptor-associated signalling pathways in melanoma cells, antagonisation rather than activation of cannabinoid receptors has been shown to mediate anticarcinogenic effects in squamous cell carcinoma cells. Accordingly, using the human papillomavirus (HPV)-positive squamous cell carcinoma cell lines UD-SCC-2, UPCI-SCC-090, UM-SCC-47 and 93VU147T, it has been reported that cannabinoid receptor silencing inhibits the proliferation of these cancer cells . In the ordingly . Hijiya ll lines .2 receptor antagonist [Finally, it should be mentioned that with regard to cannabinoid effects, other skin cancer types have been investigated in addition to melanoma and squamous cell carcinoma cells. For example, cannabinoids have been successfully tested preclinically for their anticarcinogenic effects on cells of Kaposi’s sarcoma, a tumour of endothelial origin with multiple lesions of the skin, the etiological agent of which is a Kaposi’s sarcoma-associated herpes virus (KSHV), also known as human herpesvirus 8 (HHV-8). In this context, CBD was shown to inhibit proliferation and induce apoptosis in KSHV-infected human dermal microvascular endothelial cells . The opptagonist . In a retagonist . TherebyBRAF wild-type melanoma xenografts generated with CHL-1 melanoma cells or treatment with a combination of THC and CBD resulted in a stronger reduction in cancer growth than treatment with temozolomide [As a further mode of action, treatment of melanoma cells with cannabinoids resulted in loss of cell viability due to activation of autophagy in several publications. The induction of autophagy in the melanoma cell lines HL-1, A375 and SK-MEL-28 after treatment with THC and the resulting apoptosis was prevented by simultaneous treatment with chloroquine, a classical inhibitor of autophagy that acts by changing the acidic content of the lysosomes . THC-indzolomide .Triggering of autophagy processes by cannabinoids in squamous cell carcinoma cells was demonstrated only in those of the head and neck treated with CBD . In the Tumours require an adequate supply of oxygen and nutrients to grow. To meet this need, tumours are able to promote the formation of new blood vessels, a condition that represents a potential target for therapeutic agents. In xenografts of the epidermal tumour cell line PDV C57B, derived from spindle cell squamous cell carcinoma of mouse skin, Casanova et al. found an impairment of tumour vascularisation and decreases in several growth factors associated with angiogenesis, such as vascular epithelial growth factor (VEGF), placenta-derived growth factor (PlGF) and angiopoietin-2, after treatment of nude mice with WIN 55,212-2 and JWH-133. In addition, both cannabinoids reduced epidermal growth factor (EGF) receptor activation in tissues derived from PDV C57B xenografts. . An anti2 receptor with JWH-133 was shown to reduce melanoma cell attachment to brain endothelial cells and transendothelial migration of melanoma cells [2 receptor can reduce the transmigration of melanoma cells across the blood–brain barrier in the context of the formation of parenchymal brain metastases. Further in vitro work revealed that migration of B16F10 melanoma cells was reduced by treatment with a standardised cannabis extract [Several publications have indicated that cannabinoids inhibit melanoma cell motility, invasion, and metastasis. In this context, activation of the CBma cells . These i extract .In vivo studies in mice found that treatment with WIN 55,212-2 reduced the number of metastatic nodules in the lungs and livers of immunocompetent C57BL/6 and immunodeficient nude mice injected with B16 melanoma cells . In anot1 or CB2 receptor antagonists, restored migration suppressed by MAGL shRNA, suggesting that the mechanism of MAGL-mediated cancer aggressiveness in these cells is mediated by free fatty acids rather than by reduction in the MAGL substrate 2-AG. Consistent with this, the addition of free fatty acids also abolished the migration inhibition induced by JZL184 in MAGL-overexpressing MUM2C melanoma cells [The results of another study suggested that MAGL may play an important role in the malignancy of melanomas . The melma cells .1 receptor agonist AM-251 inhibited the invasion of the oesophageal cancer cell lines TE-1, TE-8 and T-Tn [1 antagonist rimonabant and the CB2 antagonist SR144528 at 1 µM each resulted in inhibition of migration of UD-SCC-2, UM-SCC-47 (rimonabant only), UPCI-SCC-090 (SR144528 only) and 93VU147T cells [Data on a possible impact of cannabinoids on squamous cell carcinoma migration, invasion, and metastasis are limited to a few studies. In one study, CBD was reported to reduce invasion of squamous cell carcinoma of the oral tongue cell line SCC15 in a concentration-dependent manner at low micromolar concentrations (4–8 µM) . Remarkaand T-Tn . Consist7T cells . It is known that cannabinoid compounds influence the functional activities of immune cells. Therefore, the role of cannabinoids in the immune defence of tumours has been critically discussed. About 30 years ago, it was already proven that THC and 11-hydroxy-THC suppress the cytolytic activity of cultured natural killer cells ,115. LatR24C mice, with melanoma growth induced by a single epicutaneous application of DMBA. In view of these data, the role of cannabinoid receptors in chemically induced skin cancer appears to be of secondary importance. However, as a consequence of an antagonistic effect on the proinflammatory microenvironment, THC inhibited tumour growth of HCmel12 melanoma xenografts, which was associated with reduced infiltration of protumorigenic myeloid immune cells into the tumour microenvironment [To further deepen the knowledge about the effect of cannabinoids on the immunological tumour defence of melanoma cells, the effect of systemically administered THC on the growth of the melanoma cell line HCmel12 was investigated in a mouse model . Flow cyironment . Interesironment . In summ9-tetrahydrocannabivarin (THCV) were found to downregulate lipopolysaccharide-induced release of the proinflammatory cytokines IL-1α, IL-1β, IL-6, IL-8 and tumour necrosis factor (TNF)-α in sebocytes [2 receptor agonist that showed an inhibitory effect on 1-fluoro-2,4-dinitrobenzene (DNFB)-induced ear inflammation in Balb/c mice [2 receptor and phospholipase A2. Subsequently, increased concentrations of 15-deoxy-Δ12,14-PGJ2 are formed via COX-2, which leads to apoptosis and the subsiding of chronic inflammation via caspase-3 release. A LOX-mediated pathway is also thought to mediate the production of anti-inflammatory and proresolving lipoxin A4 and other proresolving mediators. However, the corresponding conditions of both possible signalling pathways and their interaction have not yet been clearly defined. PPARγ activation as a possible mechanism of anti-inflammatory action of lenabasum has been referred to earlier in this review [The results of some experimental setups demonstrating a chemopreventive effect of the test substances used give hope that cannabinoids could possibly exert a skin tumour-preventive effect. The successful preclinical testing of cannabinoids in inflammatory skin diseases supports this hypothesis insofar as inflammatory processes are associated with tumour-promoting effects. Accordingly, the non-psychoactive cannabinoids cannabichromene (CBC), cannabidivarin (CBDV), cannabigerol (CBG), cannabigerovarin (CBGV) and Δebocytes . Other cebocytes , is a nob/c mice . Lenabasb/c mice , enzymess review .1 and CB2 phosphorylation and internalisation and subsequent activation of MAPK signalling pathways [1 and CB2 receptor double knockout mice showed less pronounced inflammation with lower activation of the transcription factor nuclear factor-κB (NF-κB), lower production of TNF-α and consequently a lower incidence of subcorneal pustules and epidermal erosions. Consistent with this finding, wild-type mice were four times more likely to develop papillomas than CB1 and CB2 double knockout mice. Inhibition of cannabinoid receptors could therefore be a prophylactic option to prevent skin cancer caused by UV radiation.Regarding the effect of cannabinoids on cancerous or precancerous lesions of the skin, some preclinical data have already suggested the potential of cannabinoids as preventive agents for skin cancer. For example, in a two-stage model of skin carcinogenesis in mice, in which skin carcinogenesis was induced by DMBA and promoted by TPA, the synthetic cannabinoid naphthoylindoles JWH-018, JWH-122, and JWH-210 were shown to reduce the promotion of TPA-induced carcinogenesis in mouse skin when applied topically 30 min before each TPA treatment. Thus, a topical chemopreventive effect for cannabinoids was demonstrated, at least in animal experiments . Howeverpathways . In the 4, while proinflammatory and protumorigenic lysophospholipids, as well as PGE2 and thromboxane B2, were downregulated [In the case of CBD, one study further showed that this cannabinoid increases the activity of antioxidant enzymes such as superoxide dismutase and thioredoxin reductase in keratinocytes exposed to UV radiation, suggesting that CBD may serve as a protective agent for skin cancer prevention . The antegulated . In summclinicaltrials.gov website that addressed the systemic effects of cannabinoids in cancer patients . HoweveIn a systematic review and meta-analysis of note, the quality of clinical studies on the use of cannabinoids for various medical indications was assessed with regard to chronic pain  and improvement of nausea and vomiting due to chemotherapy (28 studies) . For theAnother recent systematic review of randomised controlled trials showed with moderate- to high-certainty evidence that compared with placebo, treatment with non-inhaled medicinal cannabis or cannabinoids results in a very small increase in the proportion of patients with chronic cancer and non-cancer pain who experience significant improvement in pain relief, physical functioning and sleep quality, along with some adverse side effects . FinallyIt is also worth noting that in a study of cannabis use in patients with head and neck cancer undergoing radiotherapy, medical marijuana was reported to contribute to benefits in altered cognition, weight maintenance, depression, pain, loss of appetite, dysphagia, xerostomia, muscle cramps and sticky saliva . HoweverIn recent years, some clinical research has been conducted on the effects of cannabis use on chemotherapy outcomes. For example, a recent retrospective observational study showed a lower response rate of cancer patients with advanced melanoma, non-small cell lung cancer and clear cell renal carcinoma to treatment with nivolumab when cannabis was used concomitantly. Therefore, the use of cannabis in connection with immunotherapies has to be evaluated critically . HoweverAnother study reached a more concerning conclusion regarding the effect of cannabis use during immunotherapies. Here, cannabis reduced some of the adverse effects associated with immunotherapy, such as skin toxicity, colitis and thyroid disorders. On the other hand, cannabis users showed a less favourable prognosis in terms of time to tumour progression and overall survival than patients who did not use cannabis . It is np = 0.065), which became statistically significant  after removing the data on testicular cancer, which showed an increased risk [Although not comparable with each other, there have also been studies that showed that marijuana use generally reduces the risk of cancer. For example, a population-based case-control study from 2009 found that 10 to 20 years of marijuana use was associated with a lower risk of head and neck squamous cell carcinoma after adjustment for potential confounding factors such as smoking and alcohol consumption . Anothersed risk . NotablyIn order to be able to make reasonable predictions about the systemic efficacy of cannabinoids, more prospective studies must be conducted in the future, which would then also allow statements about the correct application and dosage.Currently, clinical data on the effect of cannabinoids on cancer progression from comprehensive clinical trials is lacking. Nevertheless, the data on the systemic anticancer effect of nabiximols in high-grade glioblastoma  also givWith regard to possible use of cannabinoid-based medicinal products in connection with skin cancer, different forms of application and indications of these substances have to be considered and discussed in a differentiated way. This concerns the systemic application of cannabinoids and the prophylactic topical application of cannabinoids for the prevention of sun-related and chemically induced skin cancers. Concerning the latter, the beneficial effects of CBD on reducing inflammation need to be further investigated in order to fathom the potential inhibitory effect of CBD on the development of skin cancer. On the adverse side effects of topical cannabinoid compounds in general, it should be noted that caution is also advised in eczema patients, as many topical cannabinoid-containing formulations contain a number of known irritants . In factIn terms of the systemic effects of cannabinoids in the context of skin cancer, the preclinical data on the effect of CBD on melanoma  and squaAs a matter of fact, cannabinoids could be promising drugs for the treatment and prophylaxis of skin cancer. However, in view of the recent observations mentioned above that cannabis use does not improve the efficacy of tumour immunotherapies but rather impairs it ,138, it A major threat to the potentially valuable therapeutic use of cannabinoids is that cannabis product providers are increasingly making and promoting numerous unsubstantiated claims to consumers , therebyPreclinical results of recent years, especially with regard to antiproliferative and growth inhibitory effects, show that cannabinoids could be a promising option for the systemic treatment of melanoma and squamous cell carcinoma of the skin. Important questions in the clinical context will be which cannabinoid or combination of cannabinoids is actually most effective for which type of skin cancer and how high the dosage can be chosen without compromising patients’ quality of life through adverse drug effects. Another crucial question is in which combination with other cancer therapies cannabinoids show a synergistic anticancer effect and thereby possibly also reduce cytostatic-typical side effects and prevent chemoresistance. A consistent continuation of the previous preclinical studies as well as the implementation of randomised clinical studies on the effect of cannabinoids in skin cancer is encouraged on the basis of the data available so far.


Annona crassiflora, Miconia albicans, Miconia chamissois, Stryphnodendron adstringens, Tapirira guianensis, Xylopia aromatica, and Achyrocline alata showed half-maximal inhibitory concentration (IC50) values < 30 μg/mL for at least one CCC. A. crassiflora and S. adstringens extracts were selective for CCC. Mass spectrometry (Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (ESI FT-ICR MS)) of A. crassiflora identified fatty acids and flavonols as secondary compounds. One of the A. crassiflora fractions, 7C24 (from chloroform partition), increased H2AX phosphorylation (suggesting DNA damage), PARP cleavage, and cell cycle arrest in CCC. Kaempferol-3-O-rhamnoside and oleic acid were bioactive molecules identified in 7C24 fraction. These findings emphasize the importance of investigating bioactive molecules from natural sources for developing new anti-cancer drugs.Cervical cancer is the third most common in Brazilian women. The chemotherapy used for the treatment of this disease can cause many side effects; then, to overcome this problem, new treatment options are necessary. Natural compounds represent one of the most promising sources for the development of new drugs. In this study, 13 different species of 6 families from the Brazilian Cerrado vegetation biome were screened against human cervical cancer cell lines (CCC). Some of these species were also evaluated in one normal keratinocyte cell line (HaCaT). The effect of crude extracts on cell viability was evaluated by a colorimetric method (MTS assay). Extracts from  Among several cancer types with a higher incidence in Brazil, cancer of the uterine cervix is the third most common in women, excluding non-melanoma skin cancer (NMSC) . In 2018Natural compounds represent one of the most promising sources for new drug discovery. From 1940 to 2014, 175 small molecules were approved for cancer treatment, including 131 (75%) of non-synthetic origin and 85 (49%) being natural products or their derivatives . The cheThese metabolites also have beneficial effects on human health. For this reason, some Cerrado plants are traditionally used to treat issues such as bacterial, fungal, or parasitic infections, gastrointestinal disorders, arthritis, respiratory disorders, wound healing, and cancer-related conditions ,16,17.Annona crassiflora was selected for the partitioning process, using four different solvents with increasing polarity: alcohol, hexane, chloroform, and ethyl acetate. The chloroform partition of A. crassiflora was fractionated, and the 7C24 fraction was evaluated for proteins related to DNA damage, apoptosis, and cell cycle regulation.We evaluated the in vitro effect of different Brazilian Cerrado plant species against cervical cancer, which has a high incidence rate in Brazil. For this, 13 crude extracts from the leaves of plants from 6 families  were screened in human cervical cancer cell (CCC) lines. A. crassiflora with biological activity and revealed cytotoxic potential in extracts from Cerrado vegetation that can contribute to the development of new anti-cancer drugs.Our findings identified compounds in 50) values ranging from 8.24 to 169.50 μg/mL, when all extracts were considered for all cancer cell types in the main panel . In this study, four species showed IC50 values < 30 μg/mL in at least one of the lines in the central panel: Annona crassiflora (7), Miconia albicans (18), Miconia chamissois (19), and Stryphnodendron adstringens (21-I). Three species showed lower IC50 values in the cancer cell lines listed in Tapirira guianensis (1), Xylopia aromatica (3), and Achyrocline alata (10).The National Cancer Institute’s screening program indicates that crude extracts yielding IC50 values in all main panel cell lines were Annona crassiflora (7) (which ranged from 8.24 to 42.44 μg/mL) and Stryphnodendron adstringens (21-I) (from 21.12 to 47.01 μg/mL).The species that presented the lowest IC50 value) of a normal human skin keratinocyte cell line, HaCaT. HaCat cell line is commonly used to represent in vitro human papillomavirus (HPV) infection-induced carcinogenesis [A. crassiflora and S. adstringens in CaSki and HeLa cell lines (A. crassiflora) to proceed with the partitioning process).We next evaluated the selectivity index (SI) for these species based on the response  [The ICin panel . It was . (2018) .A. crassiflora chloroform partition indicated the presence of fatty acids and flavonols (A. crassiflora chloroform partition are shown in Electrospray Ionization Fourier Transform Ion Cyclotron Resonance (ESI FT-ICR) mass spectrometry was performed to characterize the constituents of the natural compounds. The profile of the lavonols . The conPartition 7C was identified as one of the most cytotoxic for CCCs and was chosen for additional viability assays and evaluation to identify the possible mechanism of action.50 values lower than 30 µg/mL in HeLa and C4-I cell lines; 7C25 in C4-I; 7C28 in CaSki, HeLa and C4-I; 7C57 in C4-I; and 7C60 in HeLa and C4-I  and cisplatin . After 24 h, Western blotting showed histone H2AX phosphorylation and PARP cleavage in SiHa, and an increase in these events in HeLa cells, suggesting 7C24 modulated the DNA damage and cell death pathways.Among the fractions that reduced viability in all cell lines, 7C24 had one of the lowest ICThe 7C24 fraction induced a slight increase in p21 expression in SiHa cells and a decrease in HeLa cells. Cisplatin induced a slight increase in PARP cleavage and H2AX activity and decreased p21 expression in both cell lines a. ChangeESI FT-ICR mass spectrometry showed the chloroform fraction of 7C24 contained oleic acid and kaempferol-3-O-rhamnoside .50 values lower than 30 µg/mL after treatment with Annona crassiflora, Miconia albicans, Miconia chamissois, Stryphnodendron adstringens, Tapirira guianensis, Xylopia aromatica and Achyrocline alata. A. crassiflora and S. adstringens were tested and showed selectivity for cancer cells. The bioassay-guided fractionation of A. crassiflora revealed the effect of one fraction, 7C24, on pathways in DNA damage and apoptosis, and caused cell cycle arrest.Brazilian flora represents a vast resource for the discovery of substances with biological properties, and studies have shown that extracts from a variety of plants have cytotoxic effects on human tumor cell lines ,19,25,26Annona is the second largest genus of this family, corresponding to approximately 166 species [Annona species, in vitro antitumor potential has been demonstrated for many compounds isolated from the essential oils of leaves of A. vepretorum and A. sylvatica [A. squamosa, A. muricata, A. coriacea, and A. cacans plants carry acetogenin compounds which exhibit activity against human cancer cell lines [Annona sp., and they are well known as potent inhibitors of mitochondrial respiratory chain complex I and nicotinamide adenine dinucleotide (NADH) oxidase [The Annonaceae family includes 135 genera and 2500 species distributed mainly in tropical zones . Annona  species . Among Aylvatica . Differell lines ,30. Thes oxidase .A. crassiflora possess antitumor properties (methanolic and hexane extract), antimalarial effects , antimicrobial and antioxidant activities (flavonoids), and chemopreventive and anti-inflammatory effects (methanolic extract) [50) ranged from 2.49 to 44.83 µg/mL, and only one cell line was resistant to the highest tested concentration. In the same study, the crude extracts from seeds were even more promising, with GI50 values of 0.01 to 8.90 µg/mL [50 values of 6.00 to 14.90 µg/mL in colon and brain cancer, melanoma, and leukemia cell lines [Extracts and compounds isolated from extract) . Formagi90 µg/mL . Mesquitll lines . We recell lines .Schima wallichii  Korth. (Theaceae family). The compound has shown promising results in the induction of apoptosis in breast and prostate cancer [Nymphaea odorata and exhibited anti-cancer activity against androgen-sensitive LNCaP and androgen-independent PC-3 prostate cancer cells through the inhibition of LIM domain kinase 1, which catalyzes various processes in cancer progression [In this study, we showed that the chloroform fractions reduced cell viability. One of these fractions, 7C24, induced alterations suggestive of DNA damage and apoptosis  and modulated the cell cycle, observed as changes in p21 expression and arrest in the G0/G1 phase in SiHa cells. NMR analysis of the 7C24 fraction revealed different molecules as its constituents. Among them we identified the kaempferol-3-O-rhamnoside and oleic acid. Although it is not possible to affirm the effect is due to those molecules, the role of each one of them was already described in the literature. Kaempferol-3-O-rhamnoside is a glycosyloxyflavone identified in the Indonesian plant, e cancer ,33. Moregression .Annona hypoglauca, from where it presented activities against diseases other than cancer [Oleic acid is a fatty acid already found in seed from n cancer . Regardin cancer . In genen cancer , and redn cancer .50 did not confirm a higher cytotoxic potential than partition. This could be explained by characteristics of secondary metabolites, which can interact, producing synergistic, additive, or antagonistic effects [During the initial screening of natural extracts, the cytotoxic potential can provide a guide to isolating fractions purer than the crude extract, which, in general, are expected to be more bioactive . Despite effects .A. crassiflora, it is noteworthy that the other twelve species tested presented some degree of cytotoxic potential. During the initial screening of natural extracts, this potential can provide a guide to isolating fractions purer than the crude extract, which, in general, are expected to be more bioactive [50 value, Bauhinia variegata, when submitted to fractionation cycles by our group, reduced viability of MDA-MB231 human breast cell line after 24 h, exhibiting an IC50 value of 10.2 µg/mL [Beyond ioactive . Interes.2 µg/mL . This fr.2 µg/mL . The con.2 µg/mL .M. chamissois and showed the effect of the crude extract on cervical cancer cell viability, but this effect was more evident in other cell types, such as breast (data not published) and glioblastoma [We also evaluated blastoma . In glioblastoma . Furtherblastoma , leadingStryphnodendron adstringens containing gallic acid, procyanidin dimer B1, and (−)-epicatechin-3-O-gallate showed antioxidant activity and cytotoxicity toward human breast cancer cell lines [Some species that produced extracts with the ability to inhibit cervical cancer cell viability have been tested in other tumor types. Recently, a leaf fraction of ll lines . A proanll lines .Achyrocline alata are cytotoxic to human hepatocellular carcinoma cell lines but not normal primary human hepatocytes [Ethanolic extracts from the aerial parts and flowers of atocytes .Tapira guainensis and Xylopia aromatica. Woody tissue extracts have been evaluated elsewhere and showed cytotoxic effects at 100 µg/mL against a central nervous system cancer cell line SF-268 (T. guainensis) and a leukemia cancer cell line RPMI-8226 (X. aromatica) [Astronium fraxinifolium extract on cancer cells.Our article represents the first report of the cytotoxic activity of crude leaf extracts of omatica) . This reSiparuna guianensis, which exhibited cytostatic activity against human and mouse cancer cells, including breast cancer [Only one report has described the antitumor potential of leaf extracts from t cancer .A. crassiflora, with fraction 7C24 promoting cell cycle arrest, DNA damage, and cleavage of PARP in cervical cancer cells. These findings contribute to the investigation of bioactive molecules from natural sources and their potential in developing new therapies for cervical cancer.In this study, most screened extracts reduced viability of human cancer cell lines and is the first time that this cytotoxic potential has been reported for some species. Through bioactivity-guided fractionation cycles, some putative bioactive compounds were identified in Thirteen plant species from the Brazilian Cerrado biome were collected in Ituiutaba, MG  or Uberlândia-MG , between November 2007 and 2008. After identification, they were deposited in the Herbarium of the Federal University of Uberlândia (HUFU), the Herbarium of the Federal University of Minas Gerais (BHCB), or the Herbarium of the Federal University of Mato Grosso do Sul, Campo Grande campus, Brazil (CGMS), as indicated in The leaves were washed, air-dried and ground into a powder. Then, 100 g of each specie were extracted in an hydroethanolic solution (7:3), with a ratio of powder plant material/solvent of 1:5. The extracts were filtered and freeze-dried to obtain a crude extract and different yield were obtained, as follows: specie 1 (2.1%), 7 (approximately 10%), 8 (13.2%), 10 (2.5%), 14-I (4.5%), 15-I (6.9%), 16-I (3.7%), species 2, 3, 17-I, 18 and 19 (approximately 15%) and 21-I (17%). Screens were performed with extracts 1, 2, 3, 7, 8, 10, 14-I, 15-I, 16-I, 17, 18, 19, and 21-I . They weAnnona crassiflora (7), was selected for partitioning. This partitioning, already described in Silva et al. [After screening the crude extracts, the most cytotoxic, a et al. , was perOnce the chloroform partition was identified as one of the most cytotoxic for cervical cancer cells, it was fractionated by classical chromatography, resulting in several fractions. All the fractions with enough material available were tested, ten in total, identified as 7C18, 7C22, 7C24, 7C25, 7C28, 7C39, 7C45, 7C52, 7C57, and 7C60.A. crassiflora, they were submitted for analysis in a negative ion-mode Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (ESI (−) FT-ICR MS, model 9.4 T Solarix, Bruker Daltonics). The mass spectra were externally calibrated using NaTFA, with the m/z from 200 to 2000). The parameters of the ESI (−) source were: capillary voltage 3–3.5 kV, capillary transfer temperature 250 °C and nebulizer gas pressure of 0.5–1.0 bar. The resolution power was m/Δm50% ≅ 200,000 (where Δm50% is the maximum peak width at peak height m/z ≅ 400) and mass accuracy < 8 ppm. The equation double bond equivalent (DBE) = c − h/2 + n/2 + 1  was used to deduce the degree of unsaturation for each molecule directly from its DBE value. The FT-ICR mass spectrum was acquired and processed using Compass Data Analysis software. The elemental compositions of the present compounds were determined by measuring the m/z ratio. The proposed molecule for each formula was determined using the KNApSAcK database (last update 2020/09/15).To identify the molecules present in the chloroform partition and the fraction 7C24 of The cervical cancer cell lines used throughout this work are described in 3 to 5 × 103 cells per well in a 96-well culture plate. The next day, 10% fetal bovine serum (FBS) medium was replaced with 0.5% FBS medium. After approximately 24 h, the cells were treated with 100 μL medium plus the diluted drugs. Control wells received medium + DMSO (1%). Seventy-two hours after treatment, cell viability was evaluated by a colorimetric assay based on mitochondrial metabolism, Cell Titer 96 Aqueous cell proliferation assay  following the manufacturer’s instructions. The absorbance values at 490 nm were read in a microplate reader Varioskan . The half-maximal inhibitory concentration (IC50) value was determined by nonlinear regression curve using GraphPad Prism version 5.01 for Windows (GraphPad Software).Cells were disaggregated by trypsin, counted, and plated at a density of 3 × 10A. crassiflora, S. adstringens, and cisplatin. The cisplatin IC50 value was determined and those extracts that had at least a two-fold greater effect were considered selective.The SI was determined to evaluate whether the compounds selectively inhibit the viability of cancer cells versus normal cells . This inThe CCC lines were treated with cisplatin to compare the effect of these compounds with treatment used in clinical practice (from 3–250 µg/mL). The stock solution of cisplatin  was diluted in an aqueous solution of 0.9% NaCl and stored at 4 °C.A. crassiflora fraction 7C24 could modulate signaling pathways involved in cell death, DNA damage, and the cell cycle, we evaluated the expression of cleaved-PARP, phosphor-H2AX, and p21 by Western blotting. Cell lines were selected according to their IC50 values, HeLa (15.96 µg/mL) as a low example and SiHa (33.88 µg/mL) as a high one. Cells were seeded into 6-well plates at a density of 0.5 × 106 and treated with an IC50 dose of 7C24. After 24 h, the cells were rinsed in Dulbecco’s phosphate-buffered saline , lysed , and the sample was scraped and prepared for Western blotting. Proteins were separated by SDS-PAGE gel electrophoresis, transferred to a nitrocellulose membrane, and incubated overnight with primary antibodies targeting PARP, phospho-H2AX, p21 (dilution 1:1000) or α-tubulin (dilution 1:2000), used as the loading control. All antibodies were from Cell Signaling Technology . The membranes were incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies (1:5000) and enhanced chemiluminescence Western Blotting Detection Reagents , with detection using an ImageQuant LAS 4000 mini documentation system .To analyze whether 50 value) for 24 h. The cells were harvested, centrifuged, washed in PBS, and stained with the nuclear marker propidium iodide with the kit BD Cycle test Plus DNA kit (BD Biosciences). Data acquisition was performed using the BD Accuri flow cytometer (BD Biosciences) and was analyzed using the BD Accuri program (BD Biosciences).The SiHa cell line was cultured in 6-well plates and treated with 33.88 µg/mL 7C24 .An unpaired t-test was used to compare flow cytometry results for the control and treated groups, with


Predicting patient drug response based on a patient’s molecular profile is one of the key goals of precision medicine in breast cancer (BC). Multiple drug response prediction models have been developed to address this problem. However, most of them were developed to make sensitivity predictions for multiple single drugs within cell lines from various cancer types instead of a single cancer type, do not take into account drug properties, and have not been validated in cancer patient-derived data. Among the multi-omics data, gene expression profiles have been shown to be the most informative data for drug response prediction. However, these models were often developed with individual genes. Therefore, this study aimed to develop a drug response prediction model for BC using multiple data types from both cell lines and drugs.50 values for 220 drugs tested in these cell lines from Genomics of Drug Sensitivity in Cancer (GDSC). Using these data, we developed a multiple-layer cell line-drug response network (ML-CDN2) by integrating a one-layer cell line similarity network based on the pathway activity profiles and a three-layer drug similarity network based on the drug structures, targets, and pan-cancer IC50 profiles. We further used ML-CDN2 to predict the drug response for new BC cell lines or patient-derived samples.We first collected the baseline gene expression profiles of 49 BC cell lines along with IC50 values for all GDSC cell line-drug pairs of 0.873. Also, ML-CDN2 showed a good performance when used to predict drug response in new BC cell lines from the Cancer Cell Line Encyclopedia (CCLE), with a Pearson correlation coefficient of 0.718. Moreover, we found that the cell line-derived ML-CDN2 model could be applied to predict drug response in the BC patient-derived samples from The Cancer Genome Atlas (TCGA).ML-CDN2 demonstrated a good predictive performance, with the Pearson correlation coefficient between the observed and predicted ICThe ML-CDN2 model was built to predict BC drug response using comprehensive information from both cell lines and drugs. Compared with existing methods, it has the potential to predict the drug response for BC patient-derived samples.The online version contains supplementary material available at 10.1186/s12885-021-08359-6. One of the key goals of precision medicine in breast cancer (BC) is to predict how a cancer patient will respond to a particular chemotherapy or targeted therapy, which could help clinicians prescribe the most effective and least toxic therapeutic strategy. To this end, researchers have been developing computational models to predict the anti-cancer drug response of cancer cells based on their molecular profiles  using cell line-derived (in vitro) datasets. Ideally, a drug response prediction model should be first trained using existing patient-derived (in vivo) data and then used to predict the response of new patients to a particular drug. However, currently available in vivo datasets, such as The Cancer Genome Atlas (TCGA) , do not 50) also play important roles in drug response prediction. Thus, computational models combining genomic profiles with information about the drug’s chemical structure would improve drug response prediction in vitro and in vivo [Many computational models have been developed to predict anti-cancer drug response using cell lines from various cancer types and these models are known as pan-cancer prediction models . Most of in vivo , 13. Men in vivo  develope in vivo  proposed in vivo  proposed in vivo . We note in vivo : 1) the More importantly, the models mentioned above were trained only on a per-drug and pan-cancer basis, but they do not take the heterogeneity of cancer types into consideration. Thus, new efforts have been focused on making predictions for drugs for a specific cancer type and are referred to as cancer-specific response prediction models . Some BCIn the present study, inspired by Wei et al.’s dual-layer network model  and the ftp://ftp.sanger.ac.uk/pub4/cancerrxgene/releases/release-7.0) as a benchmark dataset in this study, which consists of 1065 cancer cell lines and 266 tested drugs. We downloaded the gene expression, CNV and mutation profiles for 49 BC cell lines. For gene expression data, we used the Robust Multichip Average (RMA) [50 value (potency).We used the GDSC release 7.0 dataset (ge (RMA)  to normage (RMA)  of Affymge (RMA) , and hav50 to 13 out of the GDSC drugs downloaded from CCLE  were used for model validation in this study. For the RNA-Seq data, we used expression level computed using the RNA-Seq by Expectation-Maximization (RSEM) method [6 to obtain Transcripts Per Million (TPM) [50 values can vary widely depending on experimental conditions. Therefore, for each of the two datasets (GDSC and CCLE), we subtracted the mean IC50 value  from each IC50 value and then divided this value by the standard deviation of IC50 values for all drugs. This normalization process gives different drugs the same baseline value and range across all BC cell lines for the GDSC and CCLE studies.RNA-Seq expression profiles of 28 BC cell lines, as well as their response measured by IC) method  providedon (TPM)  and log2parse.smiles function of the R package rcdk [get.fingerprints function of the R package rcdk. Regarding the drug targets, we extract the interactions between the 220 drugs and 272 target proteins from GDSC.Drug chemical structure data were also curated. In order to reduce 3D drug chemical structure data into a 1D string variable we used the simplified molecular-input line-entry system (SMILES). We extracted the canonical SMILES strings for 220 out of the 266 GDSC small molecules from PubChem , a databhttps://gdac.broadinstitute.org), multiplied by 106 to obtain TPM [For the TCGA BC cohort, the patient-specific RNA-Seq gene expression data computed by the RSEM algorithm  were dowtain TPM  and log2tain TPM . We also, we scored the pathway activities using the gene expression profiles of BC cell lines or patients from GDSC, CCLE or TCGA datasets. Note that we first standardized gene expression within each cohort, and then performed pairwise homogenization procedure before scoring pathway activities as described in other studies [ComBat function from the sva R package [Gene sets of 1329 canonical pathways, which were curated from various pathway databases , were extracted from the Molecular Signatures Database (MSigDB) website . As desc studies , 25 to m package  to adjuscnv, where associations between every two cell lines C and Ci are measured by the Tanimoto correlation ) between their CNV profiles; 2) CSNmut, which connects every cell line pair C and Ci using the Tanimoto correlation ) calculated based on their gene mutation profiles; and 3) CSNpath, which connects every two cell lines C and Ci based on their Pearson correlation ) of pathway activity profiles. Hence, these CNSs are weighted networks. The CSNs were generated using GDSC data and all of them are complete graphs of 49 BC cell lines, where the weights of the interactions between each pair of the cell lines were measured by the correlation coefficients of their respective pathway activity, CNV, and mutation profiles. Each of the three CSNs is a single-layer CSN since each was constructed using a single data type. Next, we used the Similarity Network Fusion (SNF) algorithm in the R SNFtool package [affinityMatrix function with default parameters; 2) the three affinity matrices were fused into a cell line similarity network fusion (CSNF) using the SNF function, which connects every cell line pair C and Ci by the SNF algorithm-derived correlation ). The CSNF is a three-layer CSN since it combined CSNpath, CSNcnv, and CSNmut.We estimated the cell line similarities by constructing three CSNs using CNV, mutation, and pathway activity profiles Fig. a: 1) CSN package  to integstru, which connects every two drugs D and Dj based on the Tanimoto correlation ) of their molecular fingerprint properties; 2) DSNtarg, where associations between every two drugs D and Dj are measured by the Jaccard correlation ) between their target information; and 3) DSNsens, which connects every drug pair D and Dj using the Pearson correlation ) calculated based on their sensitivity profiles with respect to the IC50 values across the 1065 cell lines from all cancer types. Next, we integrated the three single-layer DSNs into a three-layer drug similarity network fusion (DSNF) using the SNFtool package [D and Dj using the SNF correlation ).Three drug data types  were used to construct three DSNs to estimate drug similarities Fig. b: 1) DSN package  by conne50 values). Note that a ML-CDN is not a complete bipartite graph due to some missing values in the GDSC dataset. With the four CSNs and four DSNs constructed in the above two sections, we obtained a total of 16 ML-CDNs: 1) nine dual-layer CDNs were built using each of the three single-layer CSNs  and each of the three single-layer DSNs ; 2) three four-layer CDNs were built using the three-layer CSNF combined with each of the three single-layer DSNs; 3) similarly, another three four-layer CDNs were built using the three-layer DSNF combined with each of the three single-layer CSNs; 4) finally, a six-layer CDN was built using the two integrated similarity networks, CSNF and DSNF. In this study, we referred to the ML-CDN based on CSNF and DSNF as ML-CDN1 and the one based on CSNpath and DSNF as ML-CDN2.We next integrated each of the four CSNs and each of the four DSNs together to develop a multiple-layer cell line-drug response network (ML-CDNs), which predicts drug response in previously tested BC cell lines Fig. c. In thiC, D), we are able to make a prediction of the response of the cell line C to the drug D using Eq. Ω\{} is the set of all other pairs  except , R denotes the observed response of the pair . C, D). The product of w and w reflects the contribution of R to w is the weight function between cell lines C and Ci and w is the weight function between drugs D and Dj, which can be calculated as Eqs. w increases with respect to the cell line similarity correlation ρ, and σ measures the decay rate when ρ decreases. Similarly, the parameter τ measures the decay rate with the decrease of ρ.For a given cell line-drug pair , to be used in the weight function of cell lines and drugs, respectively. The decay parameter pair  was optimized by minimizing the sum of the squared errors for all possible cell line-drug pairs using Eq. R is the observed response value of cell line C to drug D, and C to the drug D. σ and τ are both ranged from 0 to 1 with an increment of 0.01, and the pair  takes all possible combinations.The ML-CDN models contain two decay parameters  while the remaining fold used as the test set for estimating the prediction performance of the models. The performance was evaluated using Pearson correlation coefficient and root mean squared error (RMSE) between the predicted and the observed drug responses for all drugs. RMSE is the square root of the mean squared error. A higher Pearson correlation coefficient and lower RMSE indicate a better prediction performance of a method.To compare the performance of the 16 ML-CDN models, we split all cell line-drug pairs into three folds. Two folds were used as the training set for optimizing the decay parameter pairs (path and DSNF and demonstrated good prediction performance in terms of Pearson correlation and RMSE (See the Results Section), was chosen for predicting the response of a new BC patient- or cell line-derived sample S to a known drug D , we first estimated the similarity between the new sample S and any existing cell line Ci by calculating the Pearson correlation ) in terms of their pathway activity profiles and further obtained the weight ) between S and Ci using Eq. σ optimized from ML-CDN2. In parallel, the similarity between D and any existing drugs Dj was measured using ρDSNF from DSNF and further weighted using Eq. τ optimized from ML-CDN2 to obtain wDSFN. R is the observed response value of existing cell line Ci to existing drug Dj. Thus, R can be predicted by taking advantage of response data from all existing cell lines Ci based on their weighted similarities with the new sample S and all existing drugs Dj based their weighted similarities with D as shown in Eq. Although the ML-CDN models can be used to predict drug response in a new cell line or tumor tissue sample based on the CSN, or cell line response to a new drug based on the DSN, we focused on the former in this study. We therefore expected that the BC cell line-derived ML-CDNs could have good predictive performance in BC patient-derived data. Among the 16 ML-CDN models, ML-CDN2, which was constructed by connecting CSNσ optimized from ML-CDN2. The prediction of the drug response could then be made using Eq. To validate the performance of ML-CDN2, we employed the ML-CDN2 model, which was trained using the GDSC dataset. We then predicted the drug response of the same drugs in new BC cell lines from the CCLE dataset using Eq. σ optimized from ML-CDN2. In the end, the responses of these TCGA BC patients to the five drugs were made with Eq. 50 values in the GDSC study were measured using cell viability, we expected that patients in the Responder group would have a lower predicted IC50 value than patients in the Non-responder group.To further study ML-CDN2’s performance in vivo, we employed the model to predict the drug response of five drugs for patients in the TCGA BC dataset for which drug response was recorded. Five drugs were tested in the GDSC study, including paclitaxel, fluorouracil, tamoxifen, doxorubicin, and docetaxel. For each of the five drugs, the patients were assigned to two groups based on the recorded drug response: Responder (patients showing a “complete response”) and Non-responder . For these patients, we first calculated their pathway activity scores based on their whole-genome gene expression profiles and then measured the similarity between these BC tumors and the GDSC BC cell lines using the Pearson correlations of their pathway activity profiles. The Pearson correlations were further weighted using Eq. 50 values for lapatinib among the four groups. We expected to see that groups with higher HER2 expression levels would demonstrate lower predicted IC50 values. BC patients treated with tamoxifen were divided into two groups (Negative and Positive) based on the IHC status of ER. Then the predicted IC50 values for tamoxifen were compared between the two groups. We expected that the predicted IC50 values for patients in the ER Positive group would be lower than the IC50 values from the patients in the ER Negative group.Using Eq. 50 value (response variable) of the inhibitor and the expression levels of the pathway genes (predictors). We obtained the p-value for each gene and corrected them for multiple comparison, using Bonferroni correction (α = 0.05).In addition, we used Eq. 50 profiles  and each of the four DSNs  to build a total of 16 ML-CDNs and compared their prediction performance  is  for ML-CDN1 and  for ML-CDN2. The IC50 values were predicted for all pairs using the ML-CDN1 and ML-CDN2 models to calculate the Pearson correlation and RMSE. The scatter plots for ML-CDN1  and ML-CDN2 . The ML-CDN2 model obtained a correlation between the predicted and the observed responses of 0.873, while Zhang et al.’s method had a value of 0.670  and compared this to those with responses (available observed). We predicted the missing responses to five EGFR tyrosine kinase inhibitors . Since such EGFR inhibitors are more potent (lower IC50) in individuals with mutations in EGFR, we stratified the data into wild type and mutant groups. The predicted missing median IC50 values of EGFR inhibitors for the EGFR wild type and mutant cell lines are − 0.09 and − 0.32, respectively, and the available observed median IC50 values for the EGFR wild type and mutant groups are 0.10 and − 0.28, respectively , likely because there are only two data points in the mutant group. However, we found that the predicted missing median IC50 of the EGFR-wild type group was significantly higher than the available observed median IC50 of the EGFR-mutant cell lines  . Overall, our results suggest that our ML-CDN2 model can correctly predict the drug responses of missing data in the GDSC dataset.Similar to the EGFR inhibitors, we predicted the missing responses of three mitogen-activated protein kinase inhibitors . These compounds are expected to be more potent and therefore have lower ICF kinase , so we s). The results suggest that the ML-CDN2 model can be used to predict response values of new BC cell lines to the existing drugs. However, the model did not work well with cell-drug pairs with observed IC50 values of 8 μM or higher. In CCLE, drugs were tested in eight doses with 8 μM being the maximum. Thus, some drugs ended up having an IC50 of 8 μM or higher in some cell lines but these are all listed as having an IC50 of 8 μM. The IC50 of 8 μM is 0.55 after normalization, hence all IC50 values of 8 μM or higher from CCLE are represented as the observed normalized value of 0.55 . In the tamoxifen treatment group, patients in the “Responder” group appeared to have a lower median predicted IC50 value than patients in the “Non-responder” group but the results are not statistically significant .Although drug response data in BC cell lines is more widely available and easier to obtain, it is less representative of the disease than human tumor samples. In addition, a goal of models such as ours is to predict successful cancer drug treatment based on BC patient tumor samples. We therefore tested our ML-CDN2 against the TCGA dataset on a subset of BC patients where their drug response was recorded as “Responder” or “Non-responder”. The predicted drug ICp-value = 0.01 by ANOVA). Tamoxifen responses were similarly grouped by ER status. Although tamoxifen appeared to be more sensitive in the ER-positive than in the ER-negative group this result was not statistically significant  and FASLG .We also employed the ML-CDN2 model to predict the drug response of several phosphoinositide 3-kinase (PI3K) / mechanistic target of rapamycin (mTOR) signaling pathway inhibitors for TCGA breast tumor samples. 20 PI3K inhibitors were tested in the GDSC study and we observed statistically significant associations between the level of pathway gene expression and predicted drug responses for each inhibitor. A total of 120 associations were obtained for seven inhibitors  was used, the ML-CDN models derived from CSNpath and CSNF show a higher Pearson correlation and a lower RMSE than the ML-CDN models derived from CSNcnv and CSNmut, implying that pathway activity profiles and CSNF are more informative than the CNV and mutation profiles. The best-preforming model is ML-CDN1, derived from CSNF and DSNF, suggesting that integration of the three types of data from cell lines along with the three types of data from drugs improve predictive performance of the model.All of the 16 ML-CDN models we constructed show good predictive performance, with Pearson correlation coefficients greater than 0.8. When the same CSN was used, the ML-CDN model derived from DSNIt is noteworthy that the 16 ML-CDNs do not differ much in their predictive performance. The Pearson correlation ranges from 0.833 to 0.875 while the RMSE ranges from 0.493 to 0.563. A possible reason for this could be that the ML-CDN models are BC-specific models. The idea behind the ML-CDN modeling method is that similar cell lines exhibit similar drug response. These models were trained on 49 BC cell lines, which show high similarity among each other in terms of pathway activity, CNV, or gene mutation profiles. Therefore, any of the three types of profiles can be used by the ML-CDN model to accurately predict drug response.50 values for the paclitaxel “Responders” than the “Non-responders”  is the most aggressive BC subtype with the lowest survival time and having few effective therapies. Our model was developed with different BC subtypes taken into consideration and was validated using different BC subtypes represented by cell lines in CCLE and patient-derived samples in TCGA. It would be interesting to look at the performance of our model specifically in the TNBC subtype in future work.A limitation of this study was that our model did not take into account cell lines that are known to be resistant to specific chemotherapeutic drugs. Therefore, when we validated our model in the CCLE dataset, it did not work well with cell-drug pairs with observed ICWe developed a BC-specific computational model by integrating multiple cell line and drug data types to predict anticancer drug responses. One of the main contributions is that this BC cell line-derived model has the potential to predict the drug response for BC tissue samples. Such a model may one day be used to predict drug response and influence drug selection for BC treatment.Additional file 1: Table S1. Correlations of cell line pairs with respect to their CNV, mutation and pathway activity profiles, as well as their response to all tested drugs in the GDSC.Additional file 2: Table S2. Associations between the expression level of PI3K pathway genes and PI3K inhibitor responses predicted by ML-CDN2. This table lists the PI3K pathway genes which show significant association between their expression levels with the predicted IC50 values of the PI3K pathway inhibitors.Additional file 3: Figure S1. Correlations of cell line pairs, tumor pairs and cell line-tumor pairs. (a) The pairwise Pearson correlation of the 49 BC cell lines from GDSC was calculated based on their gene expression profiles. (b) The pairwise Pearson correlation of the 1100 BC samples from TCGA was calculated based their gene expression profiles. (c) The pairwise Pearson correlation between the 49 BC cell lines and the 1100 BC samples was calculated based their gene expression profiles. (d) The pairwise Pearson correlation of the 49 BC cell lines was calculated based on their pathway activity profiles. (e) The pairwise Pearson correlation of the 1100 BC samples from TCGA was calculated based their pathway activity profiles. (f) The pairwise Pearson correlation between the 49 BC cell lines and the 1100 BC samples was calculated based their pathway activity profiles.