Glyphosate is a broad-spectrum herbicide that is used worldwide. It represents a potential harm to surface water, and when commercially mixed with surfactants, its uptake is greatly magnified. The most well-known glyphosate-based product is Roundup. This herbicide is potentially an endocrine disruptor and many studies have shown the cytotoxicity potential of glyphosate-based herbicides. In breast cancer (BC) cell lines it has been demonstrated that glyphosate can induce cellular proliferation via estrogen receptors. Therefore, we aimed to identify gene expression changes in ER+ and ER- BC cell lines treated with Roundup and AMPA, to address changes in canonical pathways that would be related or not with the ER pathway, which we believe could interfere with cell proliferation. Using the Human Transcriptome Arrays 2.0, we identified gene expression changes in MCF-7 and MDA-MB-468 exposed to low concentrations and short exposure time to Roundup Original and AMPA. The results showed that at low concentration (0.05% Roundup) and short exposure (48h), both cell lines suffered deregulation of 11 canonical pathways, the most important being cell cycle and DNA damage repair pathways. Enrichment analysis showed similar results, except that MDA-MB-468 altered mainly metabolic processes. In contrast, 48h 10mM AMPA showed fewer differentially expressed genes, but also mainly related with metabolic processes. Our findings suggest that Roundup affects survival due to cell cycle deregulation and metabolism changes that may alter mitochondrial oxygen consumption, increase ROS levels, induce hypoxia, damage DNA repair, cause mutation accumulation and ultimately cell death. To our knowledge, this is the first study to analyze the effects of Roundup and AMPA on gene expression in triple negative BC cells. Therefore, we conclude that both compounds can cause cellular damage at low doses in a relatively short period of time in these two models, mainly affecting cell cycle and DNA repair. N-(phosphonomethyl) glycine) is a broad-spectrum herbicide used worldwide in agriculture and forestry for weed control, representing a potential harm to surface water, ground waters and sediments [Glyphosate (ediments –6. It haediments .50 >4g/kg in humans). Because of these characteristics, glyphosate has been the most successful herbicide in history [Roundup is a powerful herbicide due to its action in the shikimate pathway targeting the enzyme 5-enolpyruvyl-3-shikimate phosphate synthase (EPSPS), a production pathway of essential aminoacids, such as tryptophan, phenylalanine and tyrosine ,9. The sAdjuvants used to produce Roundup are surfactants that facilitate glyphosate uptake in cells through plasma membranes, increasing efficiency, stability and bioaccumulation . The exaGlyphosate is degraded in the soil by microorganisms to aminomethylphosphonic acid (AMPA) ,13. In min vitro studies and animal models have shown genotoxic potential, chromosomal damage, and oxidative stress induction [Although currently considered by the International Agency for Research on Cancer (IARC) as a class 2A carcinogen (probably carcinogenic), there is no consensus about how toxic GBHs are to mammals. Typically, GBHs are used in concentrations between 1–2%, or 21-42mM of glyphosate, but in some cases, even lower concentrations can have an impact on human health . Neverthnduction . In addinduction  through Thongprakaisang (2013) and Mesnage et al (2017) showed glyphosate stimulation of estrogen receptor (ER) in ER+ BC cell lines, but not in ER-, in a dose-dependent manner. Hokanson et al (2005) showed a similar effect of glyphosate and estrogen in ER+ cells. De Almeida et al (2018) showed that low concentrations of glyphosate alone and Roundup did not show significant effects on viability in MDA-MB-231 and MCF-7 cells, but observed an increase in DNA damage with the Roundup formulation . The eff(Aminomethyl) phosphonic acid , 3--2,5-diphenyl tetrazolium bromide (MTT) and dimethyl sulfoxide (DMSO) were purchased from Sigma Aldrich . The Roundup Original herbicide formulation (N—(Phosphonomethyl) glycine Isopropylamine salt—480 g/L and 360g/L of glyphosate)  was available on the market.2. Culture medium and supplements were purchased from Gibco-Invitrogen Life Technology .A hormone-independent human breast cancer cell line MDA-MB-468 (ER-) and a hormone-dependent human BC cell line MCF-7 (ER+), were obtained from the American Type Collection (ATCC), USA. The MDA-MB-468 were cultured in RPMI 1640 (1X) and MCF-7 were cultured in DMEM (1X), both supplemented with 10% Fetal Bovine Serum (FBS) and 1% Penicillin-streptomycin. Cells were maintained at 37°C in humidified environment with 95% air and 5% CO3cells /100μL/well in 96-well microtiter plates. After 24h incubation for attachment, cells were treated with concentrations of AMPA ranging from 0.01 to 10mM and 0.01% to 0.3% of Roundup. After 3h, 15h, 24 and 48h of incubation period, the medium was removed and 0.5mg/mL of MTT was added into each well. Cells were incubated for 3h, then the medium was removed and 100μL of DMSO was added to each well to dissolve the precipitated dye. After 1 hour, the changes were measured by optical density at 570 nm, using microplate readers FLUOstar Omega (BGM LabTech). Cell sensitivity to a chemical was expressed as the % cell viability compared to control cells. All the experiments were made in biological and technical triplicates.Cell growth and viability were tested using the MTT reagent assay. Cells were seeded at 5X10Total RNA was extracted from biological samples treated with Roundup at 0.05% (1.1mM of glyphosate) and AMPA at 10mM for 48 hours, using RNeasy Mini Kit  according to the manufacturer’s recommendations. RNA purity was assessed using a NanoDrop 2000  and RNA quality was checked using Agilent Bioanalyzer 2100 . Only RNA preparations with an RNA integrity number (RIN) >7 were considered for microarray analysis. All samples were analyzed in triplicates.RNA was analyzed using the Human Transcriptome Arrays 2.0 (HTA 2.0), which evaluates more than 67,500 coding and non-coding transcripts, with more than six million oligonucleotide probes (25 bases in length). This array is able to interrogate all transcript isoforms in the human transcriptome with probes targeting coding transcripts, exon-exon splice junctions and non-coding transcripts ,17.All procedures were performed according to the manufacturer’s protocols. From each sample, complementary RNA (cRNA) was prepared from 100ng of total RNA according to the Affymetrix Whole Transcript (WT) protocol. cRNA was used to generate single-stranded DNA, which was fragmented and biotinylated. The labeled single-stranded DNA was hybridized for 16 h at 45 °C on the Affymetrix HTA 2.0 microarrays. Then, microarrays were washed and stained with a streptavidin-phycoerythrin conjugate in the Affymetrix Fluidics Station 450. Scanning and data extraction were followed by the transformation of fluorescence data into CEL files employing the Affymetrix GeneChip Command Console (AGCC) software .Data were analyzed using the Partek Genomics Suite v 6.6 . Principal Component Analysis (PCA) was applied to assess sample distribution. Pre-processing of Affymetrix CEL-files was performed using the robust multi-chip analysis (RMA) algorithm, which performs background adjustment, quantile normalization and probe summarization. Differential expression analysis was realized using a one-way ANOVA. Class comparison was performed using ANOVAs, which included a multiple testing correction using False Discovery Rates (FDRs) set with a p-value <0.01 considered as significant for biological and molecular function analyses. Up- and down-regulated genes were identified using a fold-change of ≥1.5 and ≤ −1.5.Enrichment analysis (EA) was performed using MetaCore , where genes with altered expression were mapped to Gene Ontology (GO). GO annotations were used as indicators of biological functions. GO describes gene products in terms of their associated biological processes, cellular components, and molecular functions . PathvieThe cell viability assay (MTT) is shown in AMPA effects at 48h were less toxic than at 3h, for all concentrations on both cell lines. Similar results were observed for 10mM/48 hours, with a survival rate of approximately 70%. In MCF-7, a 15 hour-treatment cause more death, and in MDA-MB-468 the 3-hour exposure caused the most death, for all concentrations. Observed cell death levels at 3 hours could be an effect of the type of assay used (MTT) that measures the mitochondrial metabolic rate and indirectly reflects viable cell numbers.BNIP3, FAM162A and PGK1) (A 48-hour treatment of 1.1mM glyphosate (0.05%) and 10mM AMPA was chosen to analyze gene expression. Differentially expressed genes (DEGs) were identified using a p-value adjusted (FDR) of <0.01 and a minimal fold change of 1.5. There were 1,686 DEGs identified in MCF-7 after Roundup exposure and 7 DEGs after AMPA treatment. There were 1,214 DEGs identified in Roundup-treated MDA-MB-468 and 268 DEGs after AMPA treatment. In nd PGK1) . Fig 2, Comprehensive process networks analysis of deregulated genes after Roundup treatment revealed their association with cell cycle and DNA damage repair. MCF-7 GO (Gene Ontology) cellular process analysis showed changes related to cell cycle and cell metabolism processes, whereas MDA-MB-468 cell changes were related to metabolism. There was no significant pathway enrichment for either cell line exposed to AMPA. However, some enrichment was found for GO cellular processes see . MDA-MB-When looking at MCF-7 unique differentially expressed genes, cellular component organization or biogenesis is the main altered GO cellular process, which is responsible for biosynthesis of constituent macromolecules, assembly, and arrangement of constituent parts or disassembly of cellular components. The second GO cellular process enriched for this cell line was cell cycle. The top 10 GO cellular processes of MDA-MB-468 unique differentially expressed genes did not include cell cycle. However, most processes were related to metabolism, which was confirmed by the process networks analysis .HIF-1 targets pathway .Despite the low number of common DEGs (3 genes), the EA indicates that GO cellular process response to hypoxia was significantly enriched. A Metacore pathway enrichment analysis indicates a significant enrichment in the transcription of Using Pathview web, the effect of DEGs in 11 canonical pathways was analyzed: NOTCH, WNT, Hedgehog, TGF-β, MAPK, JAK-STAT, PI3K-AKT, RAS, Cell cycle, Apoptosis and DNA damage control. Roundup treatment showed deregulation of all these pathways in both cell lines. AMPA-treated MDA-MB-468 showed some DEGs in WNT, Hedgehog, MAPK, JAK-STAT, PI3K, RAS, Cell cycle and Apoptosis, which were not found in MCF-7. c-MYC, cyclins and PCNA. MDA-MB-468 was also deregulated, however, fewer genes were affected.As previously reported in EA, cell cycle was the most affected process. MDA-MB-468 exhibited changes when exposed to both treatments, while MCF-7 exhibited changes only with Roundup , leads to cell death, due to a toxic cellular effect. Our aim was to show gene expression changes in ER+ BC cell line (MCF-7) and in a triple negative BC cell line (MDA-MB-468) exposed to Roundup and AMPA to understand if the effect of these chemicals are dependent on cell ER positivity.Concentrations used here were lower than the manufacturer’s concentration recommendation for agricultural use. Roundup Original is diluted in water in concentrations between 0.5%-2% depending on the specific product. In Brazil, the ANVISA, , allows the maximum use of 1% (1.0ppm). The US FDA currently allows for the use of 0.1 to 310ppm ,21. We iOur data show that AMPA is less toxic than Roundup. Similar results were found by Li et al. (2013) where 8 human cancer and 2 immortalized human cell lines treated with AMPA at 50mM were analyzed. Their results showed inhibition of cell proliferation of all cancer cell lines, but not non-immortalized ones, suggesting that highly proliferative cancer cells are more sensitive to these drugs than slower ones .de novo thymidylate biosynthesis [AMPA is a glycine analog which may decrease intracellular glycine synthesis through inhibition of serine hydroxymethyltransferase (SHMT), the enzyme responsible to catalyze the conversion of glycine to serine and vice-versa. This occurs because SHMT catalyzes the production of one-carbon units used for ynthesis ,23,24. Rynthesis ,25. TherAfter Roundup treatment, analysis of 11 canonical pathways and association with EA showed that cell cycle and DNA damage repair are affected, and that this compound is more toxic to MCF-7. Chaufan et al. 2014) analyzed the effects of glyphosate, GBHs and AMPA on HepG2 (liver hepatocellular cells), finding that AMPA and glyphosate alone did not affect cell viability in a concentration up to 1000mg/L, while GBHs caused rapid cell death. In addition, GBHs induced cytotoxicity, reactive oxygen species (ROS) production and apoptosis at low doses . In a si analyzedDe Almeida et al. (2018) also explored the effects of GBH and glyphosate in ER+ and ER- BC cell lines. Their results showed that these compounds can cause DNA damage at low concentrations and short exposure , as propStudies with sea urchin have shown that Roundup is able to cause a delay in cell cycle progression after 30 minutes of treatment, suggesting that the delay in activation of CDK1/cyclin B complex is responsible for the deregulation of cell cycle progression . SimilarOur results show downregulation of cyclins and DNA damage repair pathways. Based on pathway analysis, main cell cycle changes could happen in G1 and S phases Fig B in . Our finTo our knowledge, this is the first study that analyzes the effects of Roundup and AMPA on gene expression in triple negative BC cells. EA analysis shows that independently of ER positivity, the two cell lines can suffer deregulation of cell cycle and DNA repair.MDA-MB-468 changes were more related to metabolism, whereas MCF-7 changes were more linked to cell cycle. Considering both cell lines doubling time , it is possible that our 48-hour treatment allowed MCF-7 cells to divide twice and show changes in the cell cycle more clearly than MDA-MB-468 cells.In summary, we can conclude that Roundup, at much lower doses than the ones used in agriculture, was able to deregulate important intracellular pathways in ER+ and triple negative BC cell lines, showing that glyphosate’s effect on cells is not exclusive to the ER pathway. Alterations in gene expression of cell cycle pathways were more prominent on MCF-7 than MDA-MB-468 cells. In contrast, AMPA exposure had a higher effect on MDA-MB-468 than MCF-7 cells.S1 File(DOC)Click here for additional data file.


Hemoglobin measurement is important for transfusion decision-making. Pulse CO-Oximetry provides real-time continuous hemoglobin (SpHb) monitoring. The triage role of SpHb trends based on hemoglobin measurements was investigated.In this diagnostic randomized controlled trial, 69 patients undergoing spine or cytoreductive surgery were randomly enrolled into SpHb-monitoring and standard-care groups. Diagnostic blood samples were drawn for CO-oximetry Hb (CoOxHb) when the SpHb decreased by 1 g/dl or at the clinician’s discretion in the standard-care group. The positive predictive value (PPV) was defined as the ability to detect a decrease in CoOxHb > 1 g/dl or a CoOxHb < 10 g/dl; the PPVs were compared using Fisher’s exact test. The SpHb and trend accuracies were calculated. The transfusion units and postoperative hemoglobin levels were compared.p = 0.002). The PPV of CoOxHb < 10 g/dl was 86.7% vs. 50.0% for these groups (p = 0.015). The CoOxHb was never < 7 g/dl with SpHb monitoring. Sixty SpHb–CoOxHb data pairs and 28 delta pairs (ΔSpHb-ΔCoOxHb) were collected. The bias, precision and limits of agreement were − 0.29, 1.03 and − 2.30 to 1.72 g/dl, respectively. When ΔSpHb and ΔCoOxHb were > 1 g/dl, the concordance rate for changes in hemoglobin reached 100%. The delta pairs revealed a positive correlation . No significant differences were found in the transfusion volume or postoperative anemia state.The PPV of a decrease in CoOxHb > 1 g/dl was 93.3% in the SpHb group vs 54.5% without SpHb monitoring (The SpHb trend tracked changes in hemoglobin satisfactorily during surgery and more accurately estimated the appropriate timing for invasive hemoglobin measurements than the clinicians.ChiCTR1800016290 (Prospective registered). Initial registration date was 24/05/2018. A red blood cell transfusion decision should be made based on the patient’s hemoglobin concentration (Hb) to balance sufficient oxygen supply and transfusion-related reactions. In China, the rate of unnecessary erythrocyte transfusion reached 30.9, 95% CI [confidence interval] = 27.1–35.0%  and a regression analysis was performed to calculate correlation coefficients (r) and 95% CIs were reported for all data using R . The coefficient from the model could be interpreted as each unit increase of SpHb was associated with CoOxHb. A two-sided One hundred sixty patients were assessed for eligibility from May 2018 to September 2018, of whom fifty-eight patients were excluded before allocation for various reasons . The PPV of CoOxHb falling below 10 g/dl was 86.7% vs. 50.0% for these groups (p = 0.015). No case had a CoOxHb < 7 g/dl with SpHb monitoring . Linear regression analysis revealed ΔSpHb = 0.49*ΔCoOxHb - 0.13 .Pulse CO-Oximetry is a promising technique that provides noninvasive, continuous detection of anemia but cannot be used as a substitute for invasive Hb measurements. Multiple factors, such as serious anemia and large amounts of vascular drugs leading to poor peripheral perfusion , 12, canr = 0.76, 95% CI = 0.57, 0.86 [r = 0.69). Decreases in SpHb probably warn of substantial changes in patients’ Hb in a timely manner in dynamic situations. However, only a small minority of SpHb studies have evaluated trend accuracy, and the triage role of the trend in SpHb has not been evaluated.Although hemodilution, active blood loss  and rapiWe demonstrated the consistency between the trends in SpHb and CoOxHb in detail. The application of SpHb monitoring is shown in Fig. A novel method that takes full advantage of the trend in SpHb for the detection of anemia is described in this study. We found that timing the diagnostic blood draws according to changes in SpHb increased the PPV for anemia. Some studies that aimed to determine the PPV of SpHb changes compared to that of Hb changes reported PPVs only of 49–80% , 19. HowAlthough no patients received delayed treatment in the SpHb monitoring group, some arguments suggest that the change in SpHb may be delayed . HoweverIn this study, no differences were found in intraoperative transfusion units or postoperative anemia between groups. Some studies found that intraoperative SpHb monitoring could save transfusion units , even reOne of the shortcomings of this study was the relatively high number of patients with a sufficiently large intraoperative blood loss volume to lead to anemia, which could have resulted in an overestimation of the SpHb monitoring PPV in the assessment of the decrease in CoOxHb. However, in this randomized trial, the PPV of the clinicians’ perceptions was also overestimated. Therefore, we could draw the conclusion that SpHb monitoring performed better in patients with a higher risk of blood loss than clinicians’ perceptions. Second, stratification analyses for various factors that affected accuracy were not performed in this study. More studies are needed to evaluate the triage role of SpHb monitoring in various clinical scenarios. Third, other investigators found that SpHb could reduce the number of transfusion units used, but this study did not influence the transfusion decision; therefore, that aspect requires further investigation.This study was the first diagnostic randomized controlled trial to explore the triage role of Pulse CO-Oximetry in the intraoperative detection of anemia. We found that the trend in SpHb could detect a decrease in Hb in dynamic situations and indicate the appropriate timing for further Hb measurements.


Protein tyrosine phosphatases (PTPs) regulate neuronal differentiation and survival, but their expression patterns and functions in human neuroblastoma (NB) are scarcely known. Here, we have investigated the function and expression of the non-receptor PTPN1 on human NB cell lines and human NB tumor samples.NB tumor samples from 44 patients were analysed by immunohistochemistry using specific antibodies against PTPN1, PTPRH, PTPRZ1, and PTEN. PTPN1 knock-down, cell proliferation and tyrosine phosphorylation analyses, and RT-qPCR mRNA expression was assessed on SH-SY5Y, SMS-KCNR, and IMR-32 human NB cell lines.Knock-down of PTPN1 in SH-SY5Y NB cells resulted in increased tyrosine phosphorylation and cell proliferation. Retinoic acid-mediated differentiation of NB cell lines did not affect PTPN1 mRNA expression, as compared with other PTPs. Importantly, PTPN1 displayed high expression on NB tumors in association with metastasis and poor prognosis.Our results identify PTPN1 as a candidate regulator of NB cell growth and a potential NB prognostic biomarker. Neuroblastoma (NB) constitutes a heterogeneous malignancy arising from sympathetic neural precursor cells from the neural crest. NB is the most common extracranial tumor in children, accounting in its high-risk forms for about 15% of childhood cancer mortality. The majority of NB tumors develop in the adrenal medulla, and, with less frequency, in the paraspinal ganglia from neck, chest, abdomen, and pelvis . UnbalanMYCN gene amplification, the major biomarker for high-risk NB, and potentiates MYCN oncogenic activity [Tyrosine phosphorylation, executed by protein tyrosine kinases (PTKs), is one of the landmark protein posttranslational modifications in human cancer . The recactivity , 20. In activity , 22. TheProtein tyrosine phosphatases (PTPs) are the direct executers of dephosphorylation of specific tyrosine residues on specific protein substrates, playing relevant roles in many physiologic and pathologic processes, including those related with the regulation of cell differentiation, transformation, and growth –27. InhiThe characteristics of the patients included in the study have been previously described  Table 11. HistolMYCN amplified), and IMR-32 (MYCN amplified) are from ATCC. Cells were grown at 37 °C in a humidified 5% CO2, 95% air incubator. SH-SY5Y and IMR-32 cells were grown in DMEM/F12 supplemented with 10% FBS, 2 mM L-glutamine, 100 units/ml of penicillin, 0.1 mg/ml of streptomycin, and 1% non-essential amino acids. SMS-KCNR were grown in DMEM supplemented with 10% FBS, 2 mM L-glutamine, 100 units/ml of penicillin, and 0.1 mg/ml of streptomycin. The three cell lines differentiate upon RA treatment [Human NB cell lines SH-SY5Y (ALK F1174 L), SMS-KCNR , respectively. Non-significant up-regulation or down-regulation was considered between 1 and 2 fold change or between − 1 and − 2 fold change, respectively. Those classical PTPs displaying coordinated significant increases in the three cell lines were considered as PTPs with significant up-regulation, whereas those PTPs displaying coordinated significant changes in two cell lines and non-significant changes in one cell line were considered as PTPs with significant up-regulation or down-regulation trends.RT-qPCR was performed using RNA from SH-SY5Y, SMS-KCNR, and IMR-32 cells treated or not with RA, using the IllustraRNAspin mini purification kit . 1 μg of total RNA was reverse transcribed using RevertAidTM reverse transcriptase, oligo (dT)18 primers, and RiboLock and RNase inhibitor . qPCR was performed as previously described  using vaPTPN1 knock-down was performed by transfection of specific siRNAs using Lipofectamine 3000 (Thermo Fisher) or PepMute (SignaGen) reagents following manufacturer’s protocol. PTPN1 siRNAs  were from Qiagen, and siNS (non-specific) and siGAPDH siRNAs were from Ambion. PTPN1 knock-down was verified 72 h post-transfection at mRNA level by isolation of RNA and RT-qPCR as described above. Cell proliferation was analyzed 72 h post-transfection using CellTiter 96® AQueous One Solution Cell Proliferation Assay (MTS) (Promega) following manufacturer’s protocol. For immunoblot analysis, SH-SY5Y cells were incubated in the presence of epidermal growth factor  for 5 min, and whole cell protein extracts were prepared by cell lysis in ice-cold M-PER™ lysis buffer (ThermoFisher Scientific) supplemented with PhosSTOP phosphatase inhibitor and cOmplete protease inhibitor cocktails , followed by centrifugation at 15200 g for 10 min and collection of the supernatant. Proteins (50 μg) were resolved in 10% SDS-PAGE under reducing conditions and transferred to PVDF membranes (Merck Millipore). Immunoblotting was performed using anti-phosphotyrosine 4G10  and anti-GAPDH  antibodies, followed by IRDye secondary antibody (LI-COR) and visualization by Odyssey® CLx Imaging System. Electrophoretic bands were quantified using ImageJ software.p-values, and interval by interval symmetric measures for Pearson’s R value.Statistical analysis was performed using IBM SPSS Statistics package, and we performed crosstabs Pearson Chi square analysis, using 2-sided asymptotic Significance to calculate To investigate the impact of the expression of PTPN1 in the modulation of growth of human NB cells, SH-SY5Y cells were transiently transfected with specific siRNAs targeting PTPN1 for down-regulation  and in the SH-SY5Y human NB cell line (the more studied human NB cell line) is shown in Fig.  primers . Figure . PTPRH and PTPRZ1 were expressed in a large number of NB tumor samples, mostly displaying a cytoplasmic granular staining pattern. PTPRZ1 was expressed with high intensity in most of the tumor samples, suggesting that it could be a good marker in NB. High staining of PTPRH associated with low risk and non-IV stage. PTEN tumor suppressor was expressed in the majority of NB tumor samples and no clinical correlations were found, in agreement with previous reports [p = 0.001, R = -0.501), non-metastatic , non-IV stage , and non-III/non-IV stage  for samples displaying high PTPRH and low PTPN1 expression. In conclusion, our findings suggest a differential involvement of PTPN1 and PTPRH in malignant NB progression, and argue for PTPN1 high expression as a potential surrogate marker for poor outcome NB.Next, the expression on human NB tumor samples of PTPN1, PTPRH, PTPRZ1, and PTEN was analyzed by IHC using specific antibodies. A summary of our IHC results is shown in Table 3 reports , indicat reports . PTPN1 wThe efficacy of high-risk NB novel targeted therapies relies on a precise patient stratification based on novel genetic, epigenetic, or protein biomarkers , 45, 46.PTPN1 high expression in NB tumors associated with patient poor outcome, and PTPN1 knock-down affected the tyrosine phosphorylation status and proliferation of NB cells. This makes PTPN1 a suitable candidate for NB prognostic and intervention marker.


In addition, many active compounds identified, including the non-anticancer drugs and other compounds, diversely inhibited the growth of three gynecologic cancer cell groups and individual cancer cell lines. These newly identified compounds are valuable for further studies of new therapeutics development, synergistic drug combinations, and new target identification for gynecologic cancers. The results also provide a rationale for the personalized chemotherapeutic testing of anticancer drugs in treatment of gynecologic cancer.Heterogeneous response to chemotherapy is a major issue for the treatment of cancer. For most gynecologic cancers including ovarian, cervical, and placental, the list of available small molecule therapies is relatively small compared to options for other cancers. While overall cancer mortality rates have decreased in the United States as early diagnoses and cancer therapies have become more effective, ovarian cancer still has low survival rates due to the lack of effective treatment options, drug resistance, and late diagnosis. To understand chemotherapeutic diversity in gynecologic cancers, we have screened 7914 approved drugs and bioactive compounds in 11 gynecologic cancer cell lines to profile their chemotherapeutic sensitivity. We identified two HDAC inhibitors, mocetinostat and entinostat, as pan-gynecologic cancer suppressors with IC The five main gynecologic cancers, including ovarian, cervical, uterine, vaginal, and vulvar, correspond to 12%  of new female cancer diagnoses annually in the United States While ovarian cancer is usually diagnosed at later stages of disease, resulting in a low 5-year survival of 29% for distant-stage disease, cervical cancer is typically diagnosed at early stages and thus has more favorable outcomes Placental cancers, or gestational trophoblastic disease (GTD) choriocarcinomas, are another type of gynecologic cancer. Gestational carcinomas arise from the fetal-derived layer of cells called the trophoblast that surrounds an embryo There is currently a set of standard anticancer drugs used in the clinic to treat gynecologic cancers. For ovarian and cervical cancer, these include chemotherapy agents gemcitabine, cisplatin, and doxorubicin as well as targeted therapeutics such as topotecan, a topoisomerase inhibitor, and bevacizumab, a monoclonal antibody directed against vascular endothelial growth factor To understand the diversity in compound efficacy across gynecologic cancers within individual cancer groups and identify new active compounds, we have screened 7914 compounds consisting of approved drugs and bioactive compounds using a quantitative high-throughput screening (qHTS) method against 11 unique gynecologic cancer cell lines derived from ovarian, cervical, and placental cancers. The results were analyzed to profile the chemotherapeutic activities of compounds against these gynecologic cancer cell lines. Our data demonstrate the commonality and diversity in responses of gynecologic cancers to the anticancer agents. We have also identified a group of non-anticancer compounds with antigynecologic cancer activities that can be further studied for target identification and drug development.A, B and Supplementary Figure 2A-C) and CAOV-3  cell lines. Based on the assay optimization results, we used 1000 cells per well plated in 1536-well plates and a 48-hour incubation with compounds. The control compound activities (IC50) of adriamycin and curcubitacin B reached the steady state at this assay condition. Other standard-of-care (SOC) anticancer drugs examined during optimization included paclitaxel and topotecan A-F). Adriamycin and curcubitacin B were designated as the positive control compounds in the subsequent screens .To determine the inhibitory effects of approved drugs and bioactive compounds on the common gynecologic cancer cell lines, 11 cell lines including 7 ovarian cancer lines , 3 cervical cancer lines , and 2 placental cancer lines  were used in the drug repurposing screen with HEK 293T cells as a control line to determine selectivity index of anticancer compounds (SI) Figure 150 less than 10 μM, efficacy greater than 50%, and three-fold greater selectivity over the HEK 293T cells. From the primary screen, the signal-to-basal ratio was 9.30, coefficient of variation was 13.2% and Z' factor was 0.69 in the PA-1 cell line. For the CAOV-3 cell line, the signal-to-basal ratio was 9.86, coefficient of variation was 11.3%, and Z' factor was 0.71.Following optimization, we next screened a collection of 7914 compounds including the FDA-approved drugs and bioactive compounds in 11 cancer cell lines shown in 50 less than 30 μM, efficacy greater than 70%, and five-fold greater selectivity over HEK cells. A group of hits that were toxic to both cancer cells and HEK 293T cells was designated as the pan-toxic compounds  and givinostat , two HDAC inhibitors, are used as examples to illustrate the toxicity .Among the primary hits tested in a follow-up screen (Pubchem AID 1345085), 205 compounds were confirmed using criteria of IC50 = 2.76 ± 1.98 μM; SI >100) and entinostat 50 = 7.11 ± 6.62 μM; SI >100), both class I HDAC inhibitors and in clinical trials, as pan-killers of all three cancer cell groups , a DNA intercalator and common drug for GTD, and fedratinib 50 = 13.1 ± 7.51 μM; SI >100), a JAK2 inhibitor , a JAK2 inhibitor, and CCT137690 50 = 20.0 ± 7.02 μM; SI >100), an Aurora kinase inhibitor , a Syk kinase inhibitor , an anti-parasitic alkaloid targeting Complex I of the mitochondrial respiratory chain and AP-1 machinery  in each group. Interestingly, while there were only 2 placental lines included in the study, 13 compounds reached an SI of 5 or greater in this group. Four compounds killed all three cervical cancer lines selectively, and only one compound, fedratinib, selectivity killed all six ovarian cancer lines. Fedratinib, one of the ovarian and cervical CCL selective inhibitors, has completed two Phase I clinical trials for solid tumors  but is not an FDA-approved drug. The heat maps for each cancer tissue group provided a high-level view of the SI for each compound that fulfilled the criteria (C-E). These maps reveal that PA-1, TOV-21-G, and HeLa cells, the faster growing lines . Neratinib 50 = 0.619 μM; SI >100), an FDA-approved epidermal growth factor receptor (EGFR) inhibitor, and milciclib 50 = 0.0897 μM (SI = 50.1), a CDK inhibitor, were the two most potent TOV-21-G inhibitors. The top HeLa suppressor was LY2874455 50 = 0.240; SI = 38.8) μM, a pan-FGFR inhibitor.In addition to finding compounds with general antineoplastic activity, the selective inhibitory activities of compounds to individual cell lines were evaluated. We identified five compounds with selective inhibitory activities for PA-1, two compounds for TOV-21-G, and four compounds for HeLa . As mentA). We arranged the data to reflect how many cell lines have a number of compounds with a potency less than 1 μM. These data show that only one compound, the multitargeted HDAC inhibitor panobinostat , exhibited sub-μM potency in every cancer cell line among 11 cancer cell lines tested .The results from our qHTS gynecologic cancer profiling revealed a diverse set of compounds with potencies ranging from the nanomolar to micromolar and different selectivity among three types of cancer tissues. We wanted to highlight these nanomolar compounds which may be useful to researchers and clinicians alike as these are the ones with anticancer activity to likely be far below their blood plasma concentrations, Cmax, in patients. We analyzed our data to uncover the number of compounds with less than 1 μM potency and greater than 70% efficacy regardless of selectivity. The data correspond with the similar trend for cytotoxic susceptibility in PA-1 (43 compounds), TOV-21-G (19 compounds), and HeLa (33 compounds) cells  2 resulted in a Cmax of 0.107 to 2.24 μM 50 of panobinostat for the ovarian, cervical, and placental lines in our study is 0.343, 0.224, and 0.516 μM, respectively. The IC90 average for all cell lines is 0.719 μM, within the range of the intravenous, but not oral, Cmax values.To provide useful information with clinical relevance, we have analyzed the IC50 of 0.150 μM with good efficacy in 8 of the 11 cancer cell lines excluding SKOV-3, HeLa, and JAR. Its average IC90 was 0.218 μM, well within the intravenous dose Cmax of 580 nM 50 of 0.173 μM and an IC90 of 0.283 μM. The Cmax of elesclomol in a clinical trial ranged from 1.32 to 12.84 μM with doses of 44 to 438 mg/m290 for Actinomycin D in our study against ES-2, CAOV3, PA-1, TOV-21-G, SK-OV-3, and Ca Ski was 512 nM, while the Cmax in a pediatric population can range from 4 to 97.2 nM after 15 minutes of exposure to the drug 90 identified in our study is several-fold above what can be achieved in human blood plasma 90 to Cmax values for the most promising clinical candidates from Supplementary Figure 9 is presented in Bortezomib, a 20S proteasome inhibitor, exhibited an average ICHeterogeneous responses in gynecologic cancers to chemotherapeutic drugs make it challenging to predict the drug's clinical effectiveness. This heterogeneity arises from differences in patient genetic background, patient age, tumor microenvironment, treatment regimen, and intrinsic resistance to drug therapy. In general, overall cancer incidence and death rates for women have been falling since the 1930s We assessed the cytotoxicity of 7914 compounds consisting of approved drugs, drug candidates tested in clinical trials, and bioactive compounds in six ovarian, three cervical, and two placental cancer cell lines. Two Class I HDACIs, mocetinostat and entinostat, were identified and confirmed as pan-gynecologic cancer inhibitors with high degrees of efficacy and selectivity (SI >100) in all three cancer groups. Interestingly, we did not find other HDACIs to be as selective except for these two. Indeed, panobinostat, givinostat, and vorinostat, three other HDAC inhibitors, were found to be equally toxic to HEK 293T cells in our screens in addition to suppressing the 11 gynecologic cancer cell lines. HDACIs prevent the removal of acetyl groups on histone lysines and, in effect, open chromatin structure to modulate gene expression 50 value or similar to or below its IC90 value in the cells of the newly identified indication. We researched the human Cmax values of our most broadly potent compounds and compared them to the experimental IC90 values in this study. In most cases, our experimental IC90 is at or below the human plasma concentration, indicating that the effective drug concentration against the new indication is achievable in patients. Mocetinostat has a Cmax of approximately 21.4 μM at 10 mg/kg and 75.7 μM at 40 mg/kg in humans 50 in our work was found to be 2.76 ± 1.98 μM, this indicates that the Cmax is well above its anticancer activity. For entinostat, however, although the patient Cmax is significantly lower than the average IC50 achieved in our study (7.11 ± 6.62 μM) for gynecologic cancers, its in vivo activity could possibly be achieved in higher doses or with compound structure-activity optimization. It is possible that the low toxicity of mocetinostat and entinostat is due to their specific HDAC isotype selectivity for certain HDACs. Both are class I HDAC inhibitors but exhibit varying IC50s for specific HDACs. For example, mocetinostat was found to inhibit only HDAC 1/2/3/11 at low micromolar potency or below in vitro effects against gynecologic cancers in our study. This HDAC isotype selectivity may be related to the drugs' activity against the gynecologic cancer cell lines as HDAC 1/2/3 have been implicated in ovarian tumor malignancy and growth In order to advance the compounds identified from a drug repurposing screen to potential clinical trials, the blood plasma concentration of the drug should be a few-fold higher than its ICi.e., G0 to G1We also identified single cell line selective compounds with submicromolar potency and high selectivity for PA-1 (ovarian), TOV-21-G (ovarian), and HeLa , which could be due to their faster growth rates compared to other cancer cell lines and the cell cycle–interrupting nature of many compounds. Empirically, cells which cycle faster are more susceptible to interruptions of cell growth at different cycle stages in vivo toxicity of compounds may also be different from the in vitro SI data. The selectivity reported here is for reference, and it should be noted that it cannot replace the data obtained from in vivo drug safety experiments and in clinical trials. We acknowledge the unequal numbers of lines for each cancer group . Having fewer lines in one group will potentially increase the number of compounds that are pan-killers for that particular group. This is evident in the larger number of compounds that killed both placental lines as compared to the number of compounds that killed all six ovarian lines.The control cell line in this study, HEK 293T, is a normal human cell line originating from human embryonic kidney cells that is typically used as control cell line. The selectivity values determined in this study were relevant to the cytotoxicity of the compounds in HEK 293T cells. Given a different control line, the resulting selectivity may be different. The in vivo against adenocarcinomic human alveolar basal epithelial (A549 cells) and colorectal carcinoma (HCT116 cells) xenografts in combination with chlorpromazine in vivo xenograft models that could provide more physiologically relevant data on tumor killing.The results of this study warrant further investigation into the different responses cancers have to similar classes of compounds. Here, different HDAC inhibitors exhibit differential selectivity. This could possibly be due to differences in HDAC class specificity, with some inhibitors targeting class I HDACs preferentially to class II HDACs, for example Drug resistance to chemotherapy is a common cause for relapse and recurrence of many different types of cancers bona fide gynecologic cancer therapeutics. Indeed, entinostat in combination with avelumab is already in Phase I/II clinical trials for epithelial ovarian cancer, peritoneal cancer, and fallopian tube cancer . Likewise, despite its toxicity to HEK 293T cells, panobinostat may be further studied in in vivo experiments due to its extremely high potency in gynecologic cancers. In conclusion, the chemotherapeutic profiling in individual cancer cells is an effective method to reveal the best anticancer therapeutics that might be particularly useful for those cancers with multidrug resistance, poor prognosis, and survival rates.In conclusion, the compounds identified and confirmed in this drug repurposing screen and profiling can be used to further investigate their utility in the treatment of gynecological cancer, especially for multidrug-resistant cancer patients. We demonstrate here the variability and heterogeneous responses of gynecologic cancer cells to anticancer drugs that may be related to patient genetic background, age, intrinsic drug resistance, and cancer aggressiveness. Two HDAC inhibitors identified in this study, mocetinostat and entinostat, may have high clinical relevance and can be moved to clinical trials as DMEM (11965092), penicillin/streptomycin (15140163), and TrypLE (12605010) were purchased from Life Technologies. FBS (SH30071.03) was purchased from HyClone (SH30071.03). ATPlite (6016739) was purchased from Perkin Elmer.The following cell lines were purchased from ATCC: CAOV-3 , SK-OV-3 , SW 626 , ES-2 , PA-1 , TOV-21G , HeLa , Ca ski , C-33 A , JAR , JEG-3 , and HEK 293T .Cells were kept in cryovials frozen at −150°C and thawed quickly in a 37°C water bath. A total of 1.5 million cells were seeded into T-225 flasks and subcultured once using TrypLE before freezing down for future experiments. For all assays, cells were seeded at 1000 cells per well into white, solid-bottom 1536-well plates using a Thermo Fisher Multidrop Combi reagent dispenser.2 in assay plates, followed by the addition of DMSO or 16 SOC chemotherapeutic compounds dissolved in DMSO. SOC compounds were dosed at 11 concentrations (1:3 dilution) in quadruplicate from 57.5 μM to 0.977 nM using the automated Wako 1536 Pin Tool workstation and incubated at 37°C with 5% CO2 for 24, 48, or 72 hours. Four microliters of ATPlite, the ATP monitoring reagent, was then added to each well of the assay plates using the Multidrop Combi reagent dispenser followed by incubation for 15 minutes at room temperature. The resulting luminescence was measured using the ViewLux plate reader. Data were normalized for each drug using the largest luminescence value as 100% full cell viability (0% cell killing) and to the smallest luminescence value 0% viability (100% cell killing).The ATPlite luminescence assay system assay kit was used to determine cell viability. The reagent was reconstituted and prepared as described by the manufacturer. To measure the cell death caused by the compounds, cells were cultured in 4 μl of media for 16 hours at 37°C with 5% CO50 values for each compound was conducted as described above. Plates were processed on the fully integrated Kalypsys robotic system. Hits were selected from the primary screen for follow-up confirmation, dosed in triplicate at 11 concentrations (1:3 dilution) from 57.5 μM to 0.977 nM, and incubated for 48 hours, and the ATPlite assay was used to determine the IC50 values.A qHTS Data analysis was performed using Microsoft Excel, and figures were generated using Prism Graphpad 7.0. In-house qHTS data normalization, correction, curve fitting, and classification were performed using custom programs developed at NCATS Data have been submitted to Pubchem. Primary Screen AID: 1345084. Confirmatory Screen AID: 1345085.


MYC rearrangement is the most commonly encountered genetic alteration, with immunoglobulin (IG), especially immunoglobulin heavy (IGH) chain, being the most frequent partner. We report a case of PBL in a 48-year-old human immunodeficiency virus- (HIV-) positive male who was admitted to the hospital with signs and symptoms suspicious for tumor lysis syndrome. Bone marrow examination revealed hypercellular marrow with trilineage hypoplasia and sheets of intermediate to large neoplastic cells with basophilic vacuolated cytoplasm comprising the majority of cellular elements of the bone marrow. The neoplastic cells were negative for conventional B-cell, T-cell, plasma cell, and myeloid markers, while flow cytometric analysis revealed an abnormal CD45-dim population that was partially weakly positive for CD71 and CD79b. The diagnosis was initially thought to be a high-grade primitive hematopoietic neoplasm, possibly an acute undifferentiated leukemia. BOB-1, however, was immunopositive in the neoplastic cells, confirming its B-cell origin. MYC was positive by immunohistochemistry and break-apart FISH, as were CD45, MUM-1, and EMA immunostains. There was immunoglobulin kappa (IGK) light chain gene rearrangement by polymerase chain reaction (PCR). Additionally, Epstein–Barr virus- (EBV–) encoded small RNAs (EBER) were positive by in situ hybridization (ISH). The tumor proliferation index by Ki-67 immunostaining approached 95%. Although the tumor cells were negative for CD38 and CD138, the diagnosis of PBL was still rendered. We recommend using a broad spectrum of B-cell markers, including BOB-1 and OCT-2, in such challenging cases of B-cell lymphomas with no expression of conventional B-cell markers. We also emphasize that the negative CD38 and CD138 should not exclude PBL from the differential diagnosis.Plasmablastic lymphoma (PBL) is an aggressive malignancy that usually occurs in the setting of immunosuppression. The immunohistochemical profile of PBL is that of terminally differentiated B lymphocytes. CD138, CD38, and MUM1 are usually immunopositive. However, pan B-cell markers such as CD20 and PAX-5 are usually negative.  MYC rearrangements are common, often translocated with the immunoglobulin (IG) heavy chains (IGH), as the most commonly encountered genetic alteration [Plasmablastic lymphoma (PBL) is an aggressive postgerminal center, terminally differentiated B-cell malignancy that usually occurs in the setting of immunosuppression. Initially, PBL was considered a subtype of diffuse large B-cell lymphoma arising in the oral cavity of human immunodeficiency virus- (HIV–) positive patients, as was first described by Delecluse et al. –3. It wateration . The rarteration .µL and 190/µL during admission. The patient's past medical history also included HIV-associated immune complex-mediated proliferative glomerulonephritis, chronic kidney disease with multiple episodes of acute kidney injury, electrolyte abnormalities, myocardial infarction, congestive heart failure (ejection fraction of 15–20% two years prior to his most recent admission and then improved to 50–55%), hypertension, diabetes mellitus, anemia, thrombocytopenia, benign prostatic hyperplasia, and major depressive disorder with psychosis and suicidal ideation. He had previously been admitted on several occasions with chief complaints of shortness of breath, hematuria, electrolyte abnormalities, and psychiatric disorders. He eventually developed a subdural hemorrhage confirmed by magnetic resonance imaging (MRI), lactic acidosis, pancytopenia, hypercalcemia, and acute kidney injury (creatinine level of 3.4 mg/dL from 0.93 mg/dL). He reported having progressive dyspnea on exertion over the past few months, along with a chronic cough, productive of green to gray sputum, night sweats, and weight loss of 30 pounds. He denied, however, any hemoptysis, chest pain, paroxysmal nocturnal dyspnea, orthopnea, fever, or chills. He was transferred to the medical intensive care unit and was treated with hydration. His serum calcium level was 13.4 mg/dL, with lactate dehydrogenase levels more than 4000 U/L, and uric acid levels at 26.9 mg/dL. These findings were concerning for tumor lysis syndrome. Chest, abdomen, and pelvic computed tomography (CT) scans revealed hepatosplenomegaly , and Epstein–Barr virus- (EBV-) encoded small RNAs (EBERs), measured by in situ hybridization (ISH)  using a locus specific probe for the 8q24/MYC region was performed at our institution and was positive for MYC gene rearrangement in 9% (9/100) of the cells analyzed with adequate controls (IGK) V-J gene segments, indicating a clonal immunoglobulin kappa light chain gene rearrangement and likely a B-cell lymphoproliferation. There was no evidence of clonal immunoglobulin heavy chain gene rearrangement. The diagnosis of a CD38-/CD138-negative plasmablastic lymphoma was made based on the clinical features of lymphadenopathy, hepatosplenomegaly, HIV and EBV status, B-cell marker BOB-1, CD45, MUM-1, and EMA expression, a high proliferative index, and MYC translocation. With this interesting IHC profile, we think it is highly recommended that using a broad spectrum of B-cell markers, including BOB-1, in such cases where other markers are negative or only focally and weakly positive. We also emphasize that a negative CD38 and CD138 expression pattern in tumor cells should not exclude PBL from the differential diagnosis and clinical management.The bone marrow core biopsy and aspirate revealed a hypercellular marrow for the patient's age, at 90% cellularity, with trilineage hypoplasia and slight myelodysplastic changes. The neoplastic cells comprised approximately 75% of the cellular marrow and were arranged in clusters and sheets from intermediate to large cells , with pr Figures . A high  Figures . The tum Figures , E-cadhe Figures  and nega Figures . Seventecontrols . AdditioPBL is a rare yet aggressive postgerminal center B-cell malignancy with morphologic and immunophenotypic features of terminal B-cell or plasma cell differentiation. PBL was first described by Delecluse et al. as a subtype of diffuse large B-cell lymphoma (DLBCL) . In the Morphologically, PBL may show variation depending on the sites and possibly the HIV status , 8. SomeThe immunophenotypic profile of PBL is that of terminally differentiated B lymphocytes. CD138, CD38, VS38c, MUM1, PRDMA, and XBP1 positivity is demonstrated in the majority of the cases. However, pan B-cell markers including CD20 and PAX-5 and leukocyte common antigen CD45 are usually negative or can be weakly positive in a minority of cases. CD79a, EMA, and CD30 are often expressed, as well as cytoplasmic immunoglobulin, commonly IgG, frequently with either kappa or lambda light chain restriction. CD4, CD10, CD43, CD45RO, and CD56 have been reported to be expressed in a subset of cases. BCL-1, BCL-2, and BCL-6 expression is usually absent. Ki-67 is usually diffusely positive, typically above 90% . AlthougMYC break-apart FISH results. The dissociation between the karyotype and FISH data may be possibly due to a cryptic MYC translocation with an unknown partner gene, undetected by conventional cytogenetics. MYC gene rearrangements are the most commonly encountered PBL genetic alteration, with IG, particularly IGH, being the most frequent partner. These alterations are usually associated with several other complex heterogeneous cytogenetic alterations [MYC rearrangements has not been established, MYC alterations were more frequently detected when EBV infection was confirmed. Furthermore, Morcsio et al. have shown that EBV was detected in about 75% of AIDS patients' tumor cells but dropped down to 67% in transplant patients and further down to 50% in immunocompetent patients [MYC gene rearrangement and HIV negativity were adverse prognostic factors [IGH rearrangement was the most frequent alteration accounting for 33.3% of all 14 different types of genetic alterations they found. They also reported, for the first time, the presence of PML/RARA fusion in PBL [Our patient showed a complex karyotype with positive erations , 21, 22.patients . More stn in PBL .MYC translocation supports the diagnosis [The diagnosis of this rare entity depends not only on the histopathological features, but also on the integration of the clinical history, radiologic studies, and laboratory tests. The differential diagnosis encompasses lymphoid tumors with plasmacytic features, including plasmablastic myeloma, ALK-positive diffuse large B-cell lymphoma, Burkitt's lymphoma with plasmacytoid differentiation, immunoblastic DLBCL, and primary effusion lymphoma (PEL) , 13, 15.iagnosis , 23. Theiagnosis . Anotheriagnosis . ALK posiagnosis , 23, 24.iagnosis . The expiagnosis , 10.PBL is a real therapeutic challenge with a very aggressive course. The median overall survival ranges variably between different studies, but generally falls between 11 and 15 months in most cases , 26. The


Targeted therapies against cancer types with more than one driver gene hold bright but elusive promise, since approved drugs are not available for all driver mutations and monotherapies often result in resistance. Targeting multiple driver genes in different pathways at the same time may provide an impact extensive enough to fight resistance. Our goal was to find synergistic drug combinations based on the availability of targeted drugs and their biological activity profiles and created an associated compound library based on driver gene-related protein targets. In this study, we would like to show that driver gene pattern based customized combination therapies are more effective than monotherapies on six cell lines and patient-derived primary cell cultures.We tested 55–102 drug combinations targeting driver genes and driver pathways for each cell line and found 25–85% of these combinations highly synergistic. Blocking 2–5 cancer pathways using only 2–3 targeted drugs was sufficient to reach high rates of tumor cell eradication at remarkably low concentrations.Our results demonstrate that the efficiency of cancer treatment may be significantly improved by combining drugs against multiple tumor specific drivers. The definition and nature of driver genes have been discussed intensely in the last decade. Here, for the sake of simplicity, we highlight a manageable number of cancer driver genes as therapeutic targets based on the 138 driver genes identified by B. Vogelstein and his group and treat these genes as common feature points of multiple cancer genome mutational landscapes, a kind of focus that is critical for targeted drug development .Since the majority of targeted therapies address only one oncogene, resistance develops eventually even if one of the actual drivers was targeted. The rapid development of drug resistance is due to the fact that more than a single driver may exist in a given tumor –8. In adHere we present sequencing-based, targeted combination therapy studies on colon, lung and multiple myeloma cell lines and also on patient-derived surviving cultures in order to underpin the potency of the individual driver gene pattern based combinational method. We also would like to propose that the pursuit for simplicity may offer highly efficient approaches.Multiple myeloma is a currently incurable hematological tumor with several well characterized cell line models –32. In tThe three cell lines share many common tumor suppressor genes (TSGs) with at least one loss-of-function mutation: KDM6A, ARID1A , MAP3K1, TP53 and MLL. RPMI8226 and U266 have some other mutated drivers in common .50 values have been typically utilized for the characterization of the efficacy of a given compound, here we introduce the IC95 values and the corresponding Combination Indices (CI95s), because we found that these values are more informative when the research objective is to decrease the cancer cell number as much as possible. The range of combinational doses were chosen in a way that using the highest concentrations no detectable amount of living cells remained and then used the same curve fitting method as in the case of IC50 value determination, only had the cutoff at 5% viability instead of 50 when determining the IC95 value. CI95 values are derived from IC95 values in the same way as in the case of CI95 values. In this study, we considered a given drug combination effective based on two major factors: the IC95 value (which represents efficacy) and the CI95 value (which demonstrates the synergism or antagonism of the compounds when applied together).Although ICIC and CI values for the myeloma cell lines can be found in 95 was used as a basis to define synergism among two or three compounds we found that 48 out of 75 designed combinations (64%) were synergistic. Furthermore, 38 out of the 48 synergistic combinations (79%) had a CI value < 0.1 which means strong synergism. Regarding the ratio of the synergistic–non-synergistic combinations with respect to the number of drugs used, 26 out of 50 (52%) double combinations were synergistic and 22 out of 25 triple combinations were synergistic (88%). In 95 value.We designed 75 combinations of 16 inhibitors. Mutated KRAS activity, which may be crucial in this system, was blocked by the farnesyl transferase inhibitor tipifarnib . We used95 value, 25 out of 102 combinations were synergistic (25%), 15 double (15%) and 10 triple (10%) combinations. Here we defined a highly similar set of driver genes and targets as on RPMI8226, however, U266 proved to be a much more resilient model system. To improve the effects on KRAS, proteasome and JAK targets, we incorporated compounds with different mechanisms of action or a slightly altered inhibitory profile and used the novel experimental KRAS inhibitor 6H05 , carfilzThe LP1 cell line has some mutational qualities in common with the RPMI8226 and U266 lines. The ARID1B, CDKN1A and caspase 8 genes are mutant but the KRAS, NOTCH1, JAK and CDH1 genes are not. Out of the 86 designed combinations, 65 contained two and 21 had three drugs. We found that 48 combinations out of 86 were synergistic (56%) with close to 100% cell killing. 23 out of the 48 synergistic combinations (48%) had a CI value < 0.1. The ratio of synergistic to non-synergistic combinations was as follows: 31 out of 65 (48%) double combinations and 17 out of 21 (81%) triple combinations were synergistic. For a successful combination see Using FACS analysis, we investigated the beneficial (apoptotic) cell killing potential of the synergistic combinations at low concentrations looking for the ratio of apoptotic cells. We present concentration values predicted to produce maximal detectable cell killing based on the data extracted from viability assays on multiple myeloma cell lines and performed measurements for dose series that covered these values in order to identify the lowest value capable of achieving maximal cell death. In Parallel to the studies on myeloma we investigated the effectiveness of our method on solid tumor models using three adherent cell line models with well-established driver status: HCT116 and HT29 colon carcinoma cell lines and the A549 lung adenocarcinoma cell line.t-test using the pIC50 values of the compounds. The two-tailed P-value turned out to be 0.0015. This indicates that prior to drug selection a careful analysis of the actually present and targetable driver genes has to be performed.Prior to the combination studies we conducted an experiment on the HCT116 cell line to explore the difference between the effectiveness of the compounds of the DriverHit Library on the actually present driver-related proteins and molecules having no target in the given model. According to this, the first group of targeted proteins were products of driver genes associated with HCT116, whereas the second cohort of targets were not involved in the pathologic proliferation of HCT116 cells. We performed an unpaired 95 as the basis for evaluation of synergism between compounds we found that 57 combinations out of 82 were synergistic (70%). Ten out of 57 synergistic combinations (18%) had a CI value < 0.1 representing an extremely strong synergism. The number of synergistic combinations was 31 (56%) in double and 26 (96%) in the case of triple combinations. To determine and characterize driver genes in HCT116 and HT29 colon cell lines we used the COSMIC database. Subsequently, we designed 77 for HCT116 and 82 drug combinations for HT29. Of the 77 HCT116 combinations 37 contained two and 40 had three drugs. Forty three combinations out of 77 proved to be synergistic (56%). Three out of 43 synergistic combinations (7%) had a CI value < 0.1. Sixteen of 37 double combinations (43%) and 27 of 40 triple combinations (68%) were synergistic. Out of the 82 combinations for HT29 55 had two and 27 had three drugs. Using CIIn order to increase the diversity of models we also performed experiments on the A549 lung adenocarcinoma cell line. Out of 55 combinations for A549 28 contained two and 27 had three drug compounds. Forty six out of 55 combinations proved to be synergistic (84%). Twenty out of 46 synergistic combinations (43%) had CI values < 0.1. The number of synergistic combinations depending on the number of drugs included was 23 (82%) in the case of double and 23 (85%) in the case of triple combinations. For all combinations see in vitro combination treatments in 9 cases . Samples that were transformed to stable co-cultures originated from patients before or under treatment. We focused on already approved drugs or compounds being still in clinical trials. We used bortezomib and MG-132 as proteasome inhibitor monotherapy controls therefore the combinations used were comparable with the clinically applied therapies. Combinations were used at 0.5 and 0.5 μM concentrations and proteasome inhibitors were applied at 1 μM. We managed to effectively shift the cell killing profile from stromal cells to myeloma cells in most cases. A selection of our results is shown in For our experimental purposes we produced balanced patient-derived myeloma-stroma cell co-cultures and performed Myeloma cell lines and patient-derived surviving cultures are multiple myeloma models, while HCT116 and HT29 are colon and A549 is lung adenocarcinoma cell lines. As a result, we intend to discuss the two groups separately due to their distinctive driver gene characteristics.in vitro experiments we found that blocking 2–5 cancer pathways using only 2–3 drugs was sufficient to reach maximal levels of cell killing at extraordinarily low doses due to synergisms among drugs  immunomodulatory drugs (IMiDs) ; b) proteasome inhibitors ; c) traditional cytotoxic drugs (i.e. doxorubicine); d) HDAC inhibitors  and e) corticosteroids . CDK inhibitors have also been extensively studied in clinical trials. Because IMiDs, cytotoxics and steroids do not target the signal transduction pathways of cancer cells only HDAC, proteasome and CDK inhibitors were considered as targeted compounds in recent myeloma studies .Combination of the HDAC inhibitor CUDC907 with the BCL2 inhibitor GX15-070 at extremely low doses resulted in synergism and total cell killing in all three cell lines. The combinations of CUDC907 with tipifarnib also proved to be successful, although this did not allow for dosages as low as those used with the HDAC plus BCL2 inhibitor combinations. When used as a combination partner, the androgen receptor (AR) inhibitor flutamide analogue also improved the therapeutic efficacy of CUDC907. HDAC and CDK inhibitors were also synergistic in all cell lines. CUDC101, another HDAC inhibitor was synergistic with Dp44mT, a topoisomerase inhibitor. This finding could be observed in all cell lines with the exception of U266. With a reference to the triple combinations, HDAC inhibitors tended to synergize with combinations containing a CDK inhibitor and a cell line-specific inhibitor, such as PF-03084014 (a NOTCH inhibitor), trametinib (a MEK1/2 inhibitor), 6H05 , BI2536 (a PLK inhibitor), GSK2126458  and MKK2206  See –1C. The 95 values for proteasome inhibitors. The results of our experiments on surviving cultures demonstrate that these new targets improve myeloma cell killing rather than stromal cell killing.In the case of U266 and patient derived co-cultures we were able to successfully enhance the effect of proteasome inhibitors in combinations but we were not successful to find synergistic partners when experimenting with the LP1 cell line. We found only one synergistic partner  in studies with the RPMI8226 cell line. However, we showed, that targeting HDACs, PLK1, KRAS, CDKs, AURKA and FGFRs may provide significant benefits in the improvement of ICWe found the inhibition of CDKs to be exceptionally beneficial in all investigated multiple myeloma models. Dinaciclib, a pan-CDK inhibitor, synergizes with the vast majority of driver target inhibitors. The most potent partners for CDK inhibitors in multiple myeloma are the HDAC inhibitors CUDC101 and CUDC907, the MEK1/2 inhibitor trametinib, the NOTCH inhibitor PF-03084014, the BCL2 inhibitors GX15-070 and ABT-263, the IDH1/2 inhibitor AGI-5180, the FLT3 and JAK2 inhibitor SB1317 and also the FGFR-targeting inhibitors XL999 and nintedanib. Dinaciclib was also part of synergistic duos and trios with inhibitors affecting the PI3K-AKT-mTOR pathway. Dinaciclib was synergistic with the PI3K-mTOR dual inhibitor GSK2126458 in experiments on the LP1 cell line and in patient-derived surviving cultures, as well as with AKT1 inhibitors MK2206 and PP242. Dinaciclib also synergized with the proteasome inhibitor MG-132 and the AURKA inhibitor danusertib. FACS results of experiments on the RPMI8226 and LP1 cell lines also confirmed that CDK inhibitors can play a key role in combination therapy.Our results raised new potential targets in multiple myeloma therapy. These targets may offer effective therapeutic surfaces for use in combination with previously known targets. These new targets to be considered in multiple myeloma treatment are the NOTCHs, BCL2, the IDHs, AR, NF2, Porcupine, the JAKs, MEK1/2 and the Aurora kinases.The HCT116 and A549 cell lines both have activating KRAS mutations, while KRAS in HT29 is not mutated. We used farnesyl transferase inhibitors (lonafarnib and tipifarnib), allosteric KRAS inhibitors and downstream MEK1/2 inhibitors to eliminate the effect of mutated KRAS. The most successful targets and combinations covered the HDACs, the CHEKs, the PI3K-mTOR axis and BCL2 in all three cell lines. However, A549 has a wild-type TP53 and was therefore less sensitive to the blockage of TP53 TSG targets and more sensitive to the MALT1 inhibitor and JNK inhibitor 1. Results of combination therapies for these models are shown in For information on Materials and Methods see in vitro models we demonstrated that combination therapies based on the individual driver gene patterns are more efficient than monotherapies in the majority of cases. We concluded that strong synergisms among compounds in driver-targeted drug combinations may result in shorter treatment periods and/or may help to reduce unwanted toxic side effects, because it may allow us to use remarkably lower doses. Because of the common targets in drivers matched with the different inhibitory profiles of the particular drugs used, even double and triple combinations may be highly effective in extremely low concentrations. In each case we proposed crucial driver combinations which affect 3–5 important cancer pathways in a given system. By using the method of targeting tumor specific driver gene sets we would like to form a common rationale for combination therapy design in different types of cell lines or patient derived primary cultures.Concentrating on the individual driver gene pattern of a tumor may contribute to an effective selection method to design synergistic combination therapies. In our


We report the first case of spontaneous syndactyly reported in a pet rabbit. Syndactyly only caused an atypical gait in the rabbit. The radiological study revealed bilateral 3rd and 4th metatarsal bones fused in its entire length preserving normal joint surfaces resembling syndactyly type Ia. The cause of this congenital malformation was unknown. Syndactyly is a congenital malformation in which two or more fingers are joined because they fail to separate or fuse during limb development. The fusion of carpal, tarsal, metacarpal, and metatarsal bones is included in the term syndactyly, as they often occur together . In humaCongenital syndactyly has been observed in dogs, cats, sheep, pigs, and cows –8. AlthoIn humans syndactyly is associated with a mutation in the HoxD-13 gene in a syndrome called synpolydactyly, where bone fusions and duplications in hands and feet occur . There aMice genetically modified for experimental embryology have been employed to investigate the embryonic development of the limbs. In these studies syndactyly appeared in the offspring occasionally. Syndactyly was found both in mice lacking laminin alpha-5 chain gene and in mice null for fibrillin-2 gene. Retinoic acid receptor gene mutation in mouse also caused syndactyly. Inhibition of interdigital cell death was observed in functional cell proteins TGF Beta-2/TGF Beta-3 double knockout mice. Mice null for both Apaf1 and bax/bak, respectively, gene, and cell proteins implicated in apoptosis developed soft tissue syndactyly , 12.In reference texts of pet rabbit medicine the following congenital conditions are cited: cryptorchidism, incisor malocclusion, spinal deformities, incomplete tracheal rings, splay leg, uterine malformations, renal agenesis, congenital cardiac disease, polycystic kidney disease, hereditary ataxia, glaucoma, cataracts, lymphoma, and cutaneous asthenia –15. HowePreviously, syndactyly has only been observed in laboratory rabbits on studies to assess the teratogenic effects in fetuses of different compounds administered to pregnant does. Vitamin A, 6-aminonicotinamide, hydroxyurea, thalidomide, and cyclophosphamide resulted in offspring syndactyly, in addition to other malformations –30. SyndA three-year-old mixed breed pet male rabbit weighing 1.6 kg was admitted in a veterinary surgeon for routine sterilization. During the consultation, the owner referred an unusual walking since he bought it in a store when it was 6 weeks old. A detailed physical examination revealed no abnormalities. A radiological study of the hindlimbs was accepted by the owner.The radiological study showed bilateral 3rd and 4th metatarsal bones fused in its entire length preserving normal joint surfaces . The own Encephalitozoon cuniculi by indirect immunofluorescence in an external laboratory. The second blood sample was obtained from the left saphenous vein with a special heparinized syringe  for the evaluation of blood gases and electrolytes in a gasometer .Two blood samples were obtained. The first blood sample was obtained from the right saphenous vein for hematology  and biochemical profile  and to obtain a serum sample for serology ofA urinalysis was also performed. The urine was collected with a sterile syringe from a clean surface by manual expression of the bladder. Urinalysis consisted in determination of urine specific gravity by refractometry, protein : creatinine (UP/UCr), and gamma-glutamyl transferase : creatinine (GGTU/CrU) ratios as indicated in the literature , 35 and  Encephalitozoon cuniculi was positive, 1 : 640 [The probes revealed the following alterations : hypergl 1 : 640 .Orchiectomy and follow-up were uneventful. During anesthesia a complete radiological exam, previously approved by the owner, was performed and no other abnormalities were observed.The rabbit presented in this case report is the first case of spontaneous syndactyly in a domestic rabbit. Authors have done a comprehensive search in animal dysmorphology databases  resultinHyperglobulinemia in rabbits has been associated with inflammatory or infectious processes; in this case the encephalitozoonosis can explain this finding .Increased plasma total calcium was not considered relevant because the value of venous ionized calcium (iCa) was within the reference range . Althoug Encephalitozoon cuniculi titer does not always correspond with histological lesions [ Encephalitozoon or other microsporidia have been associated with congenital malformations in animals or people [Raised UP/UCr ratio value (without active sediment) has been associated with renal damage in rabbits , 39, 43. lesions  and elev lesions , the par lesions . Neitherr people .Due to the absence of symptoms it was decided to evaluate kidney function in later visits, but the owner refused further testing. It is interesting to note that in human medicine syndactyly appears in numerous multiple malformation syndromes, some with renal impairment .The etiology of syndactyly of this rabbit is difficult to assess but is linked to the embryology of the limbs. The development of fingers in rabbits occurs between 14 and 18 days of gestation , 46, aft


NAMPT), the gene involved in metabolic pathways and known to be upregulated in drug‐resistant tumor cells, was shown to increase the apoptosis of cisplatin‐resistant A549 cells following cisplatin treatment. Thus, our results provide an in‐depth analysis of the signaling pathways that are commonly altered in drug‐resistant NSCLC cell lines and highlight the potential strategy that facilitates the development of interventions to interfere with upregulated signaling pathways as well as to boost downregulated signaling pathways in drug‐resistant tumors for the elimination of multiple resistance of NSCLC.Lung cancer is the leading cause of cancer‐related deaths worldwide. Although several therapeutic strategies have been employed to curb lung cancer, the survival rate is still poor owing to the development of drug resistance. The mechanisms underlying drug resistance development are incompletely understood. Here, we aimed to identify the common signaling pathways involved in drug resistance in non‐small cell lung cancer (NSCLC). Three published transcriptome microarray data were downloaded from the Gene Expression Omnibus (GEO) database comprising different drug‐resistant cell lines and their parental cell lines. Differentially expressed genes (DEGs) were identified and used to perform Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. An overlapping analysis was performed for KEGG pathways enriched from all the three datasets to identify the common signaling pathways. As a result, we found that metabolic pathways, ubiquitin‐mediated proteolysis, and mitogen‐activated protein kinase (MAPK) signaling were the most aberrantly expressed signaling pathways. The knockdown of nicotinamide phosphoribosyltransferase ( We firs22.1https://www.ncbi.nlm.nih.gov/geo/) database. A total of 24 samples were used, including 10 drug‐resistant NSCLC cell lines and 14 parental cell lines. GSE6914 comprised one dataset, Calu3, containing four gemcitabine‐resistant Calu3 NSCLC cell lines and four parental cell lines. These eight samples were accessed using GPL96 Affymetrix Human Genome U133A Array. GSE77209 comprised two datasets, H1299T18 and H1355T16. The H1299T18 dataset had three taxane‐platin‐resistant H1299T NSCLC cell lines and five parental cell lines, while the H1355T16 dataset was composed of three taxane‐platin‐resistant H1355 NSCLC cell lines and five parental cell lines. These 16 samples were accessed using GPL10058 Illumina HumanHT‐12 v4.0 expression BeadChip.The transcriptome profiles of GSE6914 and GSE77209 were downloaded from GEO  through the GEO database. The Z‐score method was used for the normalization of the three microarray data. Values of multiple probes that corresponded to the same gene were averaged as the final expression level for the specific gene.2.3t test was applied to filter the DEGs between the two groups, and the cut‐off value was set as |log (fold change)| >1.2 and false discovery rate (FDR) <0.05. Hierarchical clustering of the DEGs was based on the Euclidean distance, and was performed with EPCLUST.The limma package was used for the identification of the DEGs between drug‐resistant cell lines and parental cell lines. The random variance model (RVM) 2.4P‐values.The GO analysis was used to analyze the biological functions of the genes, while KEGG pathway enrichment analysis was performed to investigate the signaling pathways that were related to the unique DEGs. The bioconductor package was used to perform GO and KEGG enrichment analyses. In particular, two‐sided Fisher's exact and chi‐squared tests were used to classify the GO category, FDR and q values were calculated to correct the 2.52 atmosphere at 37°C and maintained in Dulbecco's modified Eagle's medium  supplemented with 10% fetal bovine serum , 100 U/L of penicillin, and 100 μg/mL streptomycin .Human lung adenocarcinoma cancer cell line A549 (#SCSP‐503) and cisplatin‐resistant A549 (#ZQ0461) were purchased from the Chinese Academy of Sciences Cell Repertoire . All cells were cultured with 5% CO2.6−ΔΔCt method for the analysis of the relative gene expression level. Each experiment was independently performed in triplicates, and glyceraldehyde 3‐phosphate dehydrogenase (GAPDH) was used for the normalization of data.The total RNA from cisplatin‐resistant A549 cells was extracted with Trizol . NanoDrop 2000  was used to detect the concentration and purity of total RNA. The 1 μg of total RNA was reversely transcribed into complementary DNA (cDNA) with Prime Script RT reagent kit with genomic DNA eraser . The primers used for cDNA preparation were oligo(dT). Real‐time quantitative PCR was performed on Agilent Mx3005P  consisting of specific primers and SYBR Premix Ex Taq II . Primers used for this experiment are listed in Supplementary Table 2.75 cells per well. After reaching approximately 60% confluency, the cells were transfected with the siRNA or negative control (2 μM/well) using Lipofectamine 3000  for 48 hours. After transfection, the cells were collected for RT‐PCR analysis or treated with cisplatin.For transient expression knockdown, small‐interfering RNA (siRNA)‐NAMPT and negative control were designed and purchased from Gene Pharma Company ; the siRNA sequences are shown in Supplementary Table 2.86 cells/mL, and 100 μL of cell suspension was transferred into a 1.5 mL centrifuge tube and incubated with 5 μL of Alexa Fluor 647 Annexin‐V fluorescein isothiocyanate  and RNase  for 15 min at 4°C in the dark. After incubation, the samples were treated with propidium iodide (5 μL)  and immediately analyzed with flow cytometry .After 24 hours of treatment with cisplatin, the supernatant was harvested and tumor cells were washed twice with ice‐cold phosphate‐buffered saline (PBS). The cells were suspended in Annexin‐V‐binding buffer  at a final concentration of 102.9Radioimmunoprecipitation assay (RIPA) buffer  mixed with protease and phosphatase inhibitors was used to isolate total proteins from cells. The protein concentration was measured using the bicinchoninic acid (BCA) Protein Assay Kit , as per the manufacturer's instruction. Total protein was mixed with 5 × protein loading buffer  at 1:4 ratio and boiled for 15 minutes. A total of 15 μg (10 μL volume) protein was added to 5% concentrated gel and 10% separation gel with 15 wells . After electrophoresis (80 V for 30 minutes and 120 V for 1.5 hours), the protein bands from sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS‐PAGE) gel were transferred onto nitrocellulose filter membranes (0.2 μm)  using the transfer slot  and SDS‐PAGE transfer buffer  (200 mA for 1.5 hours). The membranes were stained with Ponceau S to investigate total protein level and washed thrice with TBST. The membranes were placed in a block buffer (TBST with 5% skim milk powder) for 1 hour at room temperature. After incubation, the membranes were washed thrice with TBST and incubated with 5% bovine serum albumin  containing anti‐total P44/42 mitogen‐activated protein kinase , phosphorylated P44/42 MAPK(Thr202/Tyr204) , and anti‐β‐actin  overnight at 4°C. The membranes were washed thrice with TBST and incubated with a horseradish peroxidase (HRP)‐labeled goat anti‐rabbit IgG  for 1 hour at room temperature. Following incubation, the membranes were washed thrice with TBST and treated with an enhanced chemiluminescence (ECL) substrate . FluorChem E System  was used to evaluate protein expression.2.10t test was used to compare the difference in the relative gene expression and apoptosis ratios between experimental and control groups. The results were presented as histograms with overlaid dot plots; the whiskers represented error bars, and the upper box boundaries represented an average value. The dots represented the mean values of two technical repetitions. Each experiment has at least three biological replicates. P‐value less than 0.05 was considered statistically significant.Data were analyzed with SPSS software  and GraphPad Prism 7 , and the results were presented as mean ± SD. The ratio data were subjected to log2 transformation and the proportion data were subjected to logit transformation. The two‐tailed unpaired 33.1The transcriptome profiles of GSE6914 and GSE77209 were downloaded from the GEO database. The two profiles comprised 10 drug‐resistant cell lines and 14 paired parental cell lines. GSE6914 carried one dataset, Calu3, consisting of four gemcitabine‐resistant NSCLC cell lines, and four parental cell lines, while GSE77209 included two datasets, H1299T18 and H1355T16, comprising three taxane‐platin‐resistant NSCLC cell lines (H1299 or H1355) and five of their parental cell lines. The characteristics of the three individual datasets are shown in Table 3.2To investigate the functional role of the DEGs from the three independent datasets, we performed GO enrichment analysis. We observed 572 significantly enriched GO terms in Calu3 dataset, including 174 upregulated and 378 downregulated terms. In addition, we observed 307 GO terms in H1299T18 dataset, including 107 upregulated and 200 downregulated terms, and 343 GO terms in H1355T16 dataset, including 181 upregulated and 162 downregulated terms. The top 15 GO terms are shown in Figure 3.3To systematically understand the central pathways involved in drug resistance, we performed KEGG pathway analysis of the DEGs from the three datasets. The results revealed 180 significantly enriched KEGG pathways in Calu3 dataset, including 64 upregulated and 116 downregulated pathways, 89 KEGG pathways in the H1299T18 dataset, including 50 upregulated and 39 downregulated pathways, and 69 KEGG pathways in the H1355T16 dataset, including 47 upregulated and 22 downregulated pathways. The top 15 KEGG pathways are shown in Figure 3.4To further identify the KEGG pathways that were common in drug resistance, we performed an overlapping analysis of KEGG pathways that were enriched in all three datasets Figure . We repo3.5MDR‐1), ATP‐binding cassette subfamily C member 1 (ABCC1), ABCC2, ABCC3, and ABCC4. The results revealed that the expression of these genes was upregulated in cisplatin‐resistant tumor cells, suggesting that these cell lines are resistant to cisplatin , hexokinase (HK), pyruvate kinase M2 (PKM2), LDHA, pyruvate dehydrogenase kinase (PDK), and glutaminase (GLS), were shown to achieve a remarkable progress in reducing drug resistance in experimental and clinical studies.Drug resistance is a major obstacle observed during chemotherapy treatment, and different pathways are activated in the tumor cells in response to different drug treatments. Therefore, the identification of the common signaling pathways that are important to mediate drug resistance in NSCLC is desirable to eliminate drug resistance. We performed an overlapping analysis of three KEGG pathways for each dataset and found most significant alterations in metabolic pathways. Metabolic reprogramming is a hallmark of cancer development. Many studies have confirmed increased aerobic glycolysis, fatty acid synthesis, and glutamine metabolism to be associated with therapeutic resistance in cancer.+) from nicotinamide. NAMPT has been reported to activate MAPK signaling. As per our results, MAPK signaling was synergistically upregulated with NAMPT expression.In this study, we found that NAMPT upregulation was the most common. NAMPT is a rate‐limiting enzyme in the salvage pathway for the biosynthesis of nicotinamide adenine dinucleotide , a member of E3 ubiquitin ligases, was overexpressed in drug‐resistant cell lines. CUL4B promoted the degradation of P53 and inhibited the expression of phosphatase and tension homology (PTEN) through posttranscriptional modifications.MDR1 gene product, P‐glycoprotein, and affects the functions of this membrane transporter, resulting in multidrug resistance. This phenomenon was confirmed by Liu et al These authors found that the seven‐in‐absentia homologue 1 (Siah1), an E3 ubiquitin ligase that regulates ubiquitination, was downregulated in P‐glycoprotein‐mediated multiple drug‐resistant cancer cells. Siah1 exhibits the function of decreasing P‐glycoprotein level, and low expression level of Siah1 was shown to induce multidrug resistance in cancer cells.Ubiquitin‐mediated proteolysis pathway was the second most significantly upregulated pathway shared by the three datasets. Ubiquitin‐mediated proteolysis is involved in most cellular processes, including cell cycle, DNA repair, transcription, apoptosis, angiogenesis, protein synthesis, polyamine biosynthesis, and antigen presentation.MAPK1 gene in EGFR kinase inhibitor‐resistant NSCLC cell lines. Inhibition of MAPK signaling using MEK inhibitor, CI‐1040, resulted in the restoration of sensitivity to WZ4002. Furthermore, MAPK feedback activation was another mechanism underlying drug resistance observed following EGFR inhibitor treatment. Dysregulation of MAPK signaling pathway was shown to correlate with the progression of pancreatic ductal adenocarcinoma. The blockade of MAPK signaling using FBP1‐derived small peptide could overcome the gemcitabine‐induced ERK activation and increase the efficacy of anticancer treatment.et al also revealed the upregulated expression of MAPK signaling pathway in cisplatin‐resistant A549 cells, thereby supporting our analysis and validation . These authors also found that the phosphoinositide 3‐kinase (PI3K)/protein kinase B (AKT) signaling pathway was upregulated in cisplatin‐resistant A549 cells. However, we failed to observe any consistent activation of PI3K/AKT signaling in the three datasets, as PI3K/AKT signaling was upregulated in gemcitabine‐resistant Calu3 cell line but downregulated in taxane‐platin‐resistant NSCLC cell line (H1299 or H1355).MAPK signaling pathway is well‐known to participate in mediating drug resistance and is crucial for the damage‐induced DNA replication. Therefore, aberrant activation of MAPK signaling may prevent the death of cancer cells from drug treatment.To our knowledge, this is the first study to focus on the common signaling pathways involved in mediating drug resistance in NSCLC. Although many pathways identified in our study have already been known, our results prove that these pathways play an important role in mediating resistance to different drugs. In addition, we found that the genes in the same pathways may show different levels of alterations in response to different drugs, and revealed the functions of several genes involved in drug resistance. However, our study has a few limitations. For instance, only two types of drug‐resistant cell lines (gemcitabine and taxane‐platin) were used, only three cell lines were used, and the sample size was small. In addition, the backgrounds of tumor cell lines used were different, and our results lack the validation of mouse experiments and tumor specimen analysis. Further investigations in suitable mouse models and tumor samples from patients with NSCLC that are confirmed as drug resistant are warranted to validate the common pathways identified in this study.In summary, our study provides a deep understanding of the signaling pathways that contribute to drug resistance in NSCLC and highlight some key molecules involved in these altered pathways. Notably, the most common signaling pathways identified in our study may facilitate the development of therapeutic interventions for drug‐resistant NSCLC.No potential conflicts of interest were disclosed. Click here for additional data file. Click here for additional data file. Click here for additional data file.