RESUMO
It has been highlighted that in the original manuscript [1] Table S3 'An example of the predictive computational modeling process. Specific details on an annexure section of the PD-L1 pathway show the step-by-step reactions, mechanisms, and reaction equations that occur. Such reactions also occurred in all of the other pathways' was omitted and did not appear in the Additional files and that the Additional files were miss-numbered thereafter. This Correction shows the correct and incorrect Additional files. The original article has been updated.
RESUMO
BACKGROUND: Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses. METHODS: We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses. RESULTS: Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses. CONCLUSIONS: Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.
Assuntos
Anticorpos Monoclonais Humanizados/farmacologia , Antígeno B7-H1/genética , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Simulação por Computador , Imunoterapia , Receptor de Morte Celular Programada 1/antagonistas & inibidores , Anticorpos Monoclonais Humanizados/uso terapêutico , Antineoplásicos Imunológicos/farmacologia , Antineoplásicos Imunológicos/uso terapêutico , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/metabolismo , Quimiocinas/genética , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , Modelos Biológicos , Mutação , Receptor de Morte Celular Programada 1/metabolismo , Transdução de Sinais/efeitos dos fármacos , Resultado do TratamentoRESUMO
PURPOSE: Interaction of the programmed death-1 (PD-1) co-receptor on T cells with the programmed death-ligand 1 (PD-L1) on tumor cells can lead to immunosuppression, a key event in the pathogenesis of many tumors. Thus, determining the amount of PD-L1 in tumors by immunohistochemistry (IHC) is important as both a diagnostic aid and a clinical predictor of immunotherapy treatment success. Because IHC reactivity can vary, we developed computational simulation models to accurately predict PD-L1 expression as a complementary assay to affirm IHC reactivity. METHODS: Multiple myeloma (MM) and oral squamous cell carcinoma (SCC) cell lines were modeled as examples of our approach. Non-transformed cell models were first simulated to establish non-tumorigenic control baselines. Cell line genomic aberration profiles, from next-generation sequencing (NGS) information for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines, were introduced into the workflow to create cancer cell line-specific simulation models. Percentage changes of PD-L1 expression with respect to control baselines were determined and verified against observed PD-L1 expression by ELISA, IHC, and flow cytometry on the same cells grown in culture. RESULT: The observed PD-L1 expression matched the predicted PD-L1 expression for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines and clearly demonstrated that cell genomics play an integral role by influencing cell signaling and downstream effects on PD-L1 expression. CONCLUSION: This concept can easily be extended to cancer patient cells where an accurate method to predict PD-L1 expression would affirm IHC results and improve its potential as a biomarker and a clinical predictor of treatment success.
Assuntos
Antígeno B7-H1/metabolismo , Carcinoma de Células Escamosas/genética , Neoplasias Bucais/genética , Mieloma Múltiplo/genética , Adulto , Carcinoma de Células Escamosas/patologia , Simulação por Computador , Humanos , Pessoa de Meia-Idade , Modelos Biológicos , Simulação de Dinâmica Molecular , Neoplasias Bucais/patologia , Mieloma Múltiplo/patologiaRESUMO
BACKGROUND: The personalization of cancer treatments implies the reconsideration of a one-size-fits-all paradigm. This move has spawned increased use of next generation sequencing to understand mutations and copy number aberrations in cancer cells. Initial personalization successes have been primarily driven by drugs targeting one patient-specific oncogene (e.g., Gleevec, Xalkori, Herceptin). Unfortunately, most cancers include a multitude of aberrations, and the overall impact on cancer signaling and metabolic networks cannot be easily nullified by a single drug. METHODS: We used a novel predictive simulation approach to create an avatar of patient cancer cells using point mutations and copy number aberration data. Simulation avatars of myeloma patients were functionally screened using various molecularly targeted drugs both individually and in combination to identify drugs that are efficacious and synergistic. Repurposing of drugs that are FDA-approved or under clinical study with validated clinical safety and pharmacokinetic data can provide a rapid translational path to the clinic. High-risk multiple myeloma patients were modeled, and the simulation predictions were assessed ex vivo using patient cells. RESULTS: Here, we present an approach to address the key challenge of interpreting patient profiling genomic signatures into actionable clinical insights to make the personalization of cancer therapy a practical reality. Through the rational design of personalized treatments, our approach also targets multiple patient-relevant pathways to address the emergence of single therapy resistance. Our predictive platform identified drug regimens for four high-risk multiple myeloma patients. The predicted regimes were found to be effective in ex vivo analyses using patient cells. CONCLUSIONS: These multiple validations confirm this approach and methodology for the use of big data to create personalized therapeutics using predictive simulation approaches.
Assuntos
Simulação por Computador , Mieloma Múltiplo/terapia , Linhagem Celular Tumoral , Genômica , Humanos , Mieloma Múltiplo/patologia , Medicina de PrecisãoRESUMO
The phosphatidylinositide 3-kinase (PI3K) pathway is activated and correlated with drug resistance in multiple myeloma (MM). In the present study we investigated the role of PI3KCA (PI3K-α) in the progression and drug resistance in MM. We showed that the gene expression of PI3KCA isoform was higher in MM compared to normal subjects. BYL719, a novel and specific PI3KCA inhibitor inhibited the survival of primary MM cells and cell lines but not normal peripheral blood mononuclear cells. BYL719 induced the apoptosis of MM cells and inhibited their cell cycle by causing G1 arrest. BYL719 inhibited PI3K signalling, decreased proliferation and cells cycle signalling, and induced apoptosis signalling in MM cells. Finally, BYL719 synergized with bortezomib and carfilzomib, and overcame drug resistance induced by bone marrow stroma. These results were confirmed using in silico simulation of MM cell lines, BYL719 and bortezomib, and showed similar trends in survival, proliferation, apoptosis, cell signalling and synergy with drugs. In conclusion, PI3KCA plays a major role in proliferation and drug resistance of MM cells, the effects of which were inhibited with BYL719. These results provide a preclinical basis for a future clinical trial of BYL719 in MM as a single agent or in combination with other drugs.
Assuntos
Antineoplásicos/farmacologia , Resistencia a Medicamentos Antineoplásicos , Mieloma Múltiplo/metabolismo , Proteínas Nucleares/antagonistas & inibidores , Proteínas Nucleares/metabolismo , Células Estromais/metabolismo , Fatores de Transcrição/antagonistas & inibidores , Fatores de Transcrição/metabolismo , Apoptose/efeitos dos fármacos , Adesão Celular/efeitos dos fármacos , Pontos de Checagem do Ciclo Celular/efeitos dos fármacos , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Progressão da Doença , Sinergismo Farmacológico , Humanos , Isoenzimas/antagonistas & inibidores , Isoenzimas/metabolismo , Mieloma Múltiplo/patologia , Inibidores de Proteassoma/farmacologiaRESUMO
Constitutive activation of STAT3 is frequently observed and closely linked with proliferation, survival, invasion, metastasis and angiogenesis in tumor cells. In the present study, we investigated whether ß-caryophyllene oxide (CPO), a sesquiterpene isolated primarily from the essential oils of medicinal plants such as guava (Psidium guajava), and oregano (Origanum vulgare L.), can mediate its effect through interference with the STAT3 activation pathway in cancer cells. The effect of CPO on STAT3 activation, associated protein kinases and phosphatase, STAT3-regulated gene products and apoptosis was investigated using both functional proteomics tumor pathway technology platform and different tumor cell lines. We found that CPO suppressed constitutive STAT3 activation in multiple myeloma (MM), breast and prostate cancer cell lines, with a significant dose- and time-dependent effects observed in MM cells. The suppression was mediated through the inhibition of activation of upstream kinases c-Src and JAK1/2. Also, vanadate treatment reversed CPO-induced down-regulation of STAT3, suggesting the involvement of a tyrosine phosphatase. Indeed, we found that CPO induced the expression of tyrosine phosphatase SHP-1 that correlated with the down-regulation of constitutive STAT3 activation. Interestingly, deletion of SHP-1 gene by siRNA abolished the ability of CPO to inhibit STAT3 activation. The inhibition of STAT3 activation by CPO inhibited proliferation, induced apoptosis and abrogated the invasive potential of tumor cells. Our results suggest for the first time that CPO is a novel blocker of STAT3 signaling cascade and thus has an enormous potential for the treatment of various cancers harboring constitutively activated STAT3.
Assuntos
Antineoplásicos/farmacologia , Proteína Tirosina Fosfatase não Receptora Tipo 6/metabolismo , Fator de Transcrição STAT3/metabolismo , Sesquiterpenos/farmacologia , Transdução de Sinais , Apoptose , Proteínas Reguladoras de Apoptose/metabolismo , Linhagem Celular Tumoral , Núcleo Celular/metabolismo , Proliferação de Células/efeitos dos fármacos , Ensaios de Seleção de Medicamentos Antitumorais , Indução Enzimática/efeitos dos fármacos , Expressão Gênica/efeitos dos fármacos , Humanos , Interleucina-6/fisiologia , Janus Quinase 2/metabolismo , Potencial da Membrana Mitocondrial , Invasividade Neoplásica , Fosforilação , Sesquiterpenos Policíclicos , Ligação Proteica , Processamento de Proteína Pós-Traducional , Proteína Tirosina Fosfatase não Receptora Tipo 6/genética , Quinases da Família src/metabolismoRESUMO
BACKGROUND: Glioblastoma (GBM) is an aggressive disease associated with poor survival. It is essential to account for the complexity of GBM biology to improve diagnostic and therapeutic strategies. This complexity is best represented by the increasing amounts of profiling ("omics") data available due to advances in biotechnology. The challenge of integrating these vast genomic and proteomic data can be addressed by a comprehensive systems modeling approach. METHODS: Here, we present an in silico model, where we simulate GBM tumor cells using genomic profiling data. We use this in silico tumor model to predict responses of cancer cells to targeted drugs. Initially, we probed the results from a recent hypothesis-independent, empirical study by Garnett and co-workers that analyzed the sensitivity of hundreds of profiled cancer cell lines to 130 different anticancer agents. We then used the tumor model to predict sensitivity of patient-derived GBM cell lines to different targeted therapeutic agents. RESULTS: Among the drug-mutation associations reported in the Garnett study, our in silico model accurately predicted ~85% of the associations. While testing the model in a prospective manner using simulations of patient-derived GBM cell lines, we compared our simulation predictions with experimental data using the same cells in vitro. This analysis yielded a ~75% agreement of in silico drug sensitivity with in vitro experimental findings. CONCLUSIONS: These results demonstrate a strong predictability of our simulation approach using the in silico tumor model presented here. Our ultimate goal is to use this model to stratify patients for clinical trials. By accurately predicting responses of cancer cells to targeted agents a priori, this in silico tumor model provides an innovative approach to personalizing therapy and promises to improve clinical management of cancer.
Assuntos
Ensaios de Seleção de Medicamentos Antitumorais , Antineoplásicos/uso terapêutico , Linhagem Celular Tumoral , Simulação por Computador , Humanos , Estudos RetrospectivosRESUMO
BACKGROUND: Glioblastoma (GBM) is a therapeutic challenge, associated with high mortality. More effective GBM therapeutic options are urgently needed. Hence, we screened a large multi-class drug panel comprising the NIH clinical collection (NCC) that includes 446 FDA-approved drugs, with the goal of identifying new GBM therapeutics for rapid entry into clinical trials for GBM. METHODS: Screens using human GBM cell lines revealed 22 drugs with potent anti-GBM activity, including serotonergic blockers, cholesterol-lowering agents (statins), antineoplastics, anti-infective, anti-inflammatories, and hormonal modulators. We tested the 8 most potent drugs using patient-derived GBM cancer stem cell-like lines. Notably, the statins were active in vitro; they inhibited GBM cell proliferation and induced cellular autophagy. Moreover, the statins enhanced, by 40-70 fold, the pro-apoptotic activity of irinotecan, a topoisomerase 1 inhibitor currently used to treat a variety of cancers including GBM. Our data suggest that the mechanism of action of statins was prevention of multi-drug resistance protein MDR-1 glycosylation. This drug combination was synergistic in inhibiting tumor growth in vivo. Compared to animals treated with high dose irinotecan, the drug combination showed significantly less toxicity. RESULTS: Our data identifies a novel combination from among FDA-approved drugs. In addition, this combination is safer and well tolerated compared to single agent irinotecan. CONCLUSIONS: Our study newly identifies several FDA-approved compounds that may potentially be useful in GBM treatment. Our findings provide the basis for the rational combination of statins and topoisomerase inhibitors in GBM.
Assuntos
Antineoplásicos/uso terapêutico , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Neoplasias Encefálicas/tratamento farmacológico , Aprovação de Drogas , Glioblastoma/tratamento farmacológico , United States Food and Drug Administration , Subfamília B de Transportador de Cassetes de Ligação de ATP , Membro 1 da Subfamília B de Cassetes de Ligação de ATP/genética , Membro 1 da Subfamília B de Cassetes de Ligação de ATP/metabolismo , Animais , Antineoplásicos/farmacologia , Protocolos de Quimioterapia Combinada Antineoplásica/administração & dosagem , Protocolos de Quimioterapia Combinada Antineoplásica/farmacologia , Autofagia/efeitos dos fármacos , Barreira Hematoencefálica/patologia , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Camptotecina/administração & dosagem , Camptotecina/análogos & derivados , Camptotecina/farmacologia , Camptotecina/uso terapêutico , Linhagem Celular Tumoral , Sobrevivência Celular/efeitos dos fármacos , Intervalo Livre de Doença , Relação Dose-Resposta a Droga , Regulação para Baixo/efeitos dos fármacos , Sinergismo Farmacológico , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Glioblastoma/genética , Glioblastoma/patologia , Humanos , Irinotecano , Camundongos , Camundongos Nus , Células-Tronco Neoplásicas/patologia , Quinolinas/administração & dosagem , Quinolinas/farmacologia , Quinolinas/uso terapêutico , Esferoides Celulares/patologia , Estados Unidos , Ensaios Antitumorais Modelo de XenoenxertoRESUMO
Following penetrating injury of the skin, a highly orchestrated and overlapping sequence of events helps to facilitate wound resolution. Inflammation is a hallmark that is initiated early, but the reciprocal relationship between cells and matrix molecules that triggers and maintains inflammation is poorly appreciated. Elastin is enriched in the deep dermis of skin. We propose that deep tissue injury encompasses elastin damage, yielding solubilized elastin that triggers inflammation. As dermal fibroblasts dominate the deep dermis, this means that a direct interaction between elastin sequences and fibroblasts would reveal a proinflammatory signature. Tropoelastin was used as a surrogate for elastin sequences. Tropoelastin triggered fibroblast expression of the metalloelastase MMP-12, which is normally expressed by macrophages. MMP-12 expression increased 1056 ± 286-fold by 6 h and persisted for 24 h. Chemokine expression was more transient, as chemokine C-X-C motif ligand 8 (CXCL8), CXCL1, and CXCL5 transcripts increased 11.8 ± 2.6-, 10.2 ± 0.4-, and 8593 ± 996-fold, respectively, by 6-12 h and then decreased. Through the use of specific inhibitors and protein truncation, we found that transduction of the tropoelastin signal was mediated by the fibroblast elastin binding protein (EBP). In silico modeling using a predictive computational fibroblast model confirmed the up-regulation, and simulations revealed PKA as a key part of the signaling circuit. We tested this prediction with 1 µM PKA inhibitor H-89 and found that 2 h of exposure correspondingly reduced expression of MMP-12 (63.9±12.3%) and all chemokine markers, consistent with the levels seen with EBP inhibition, and validated PKA as a novel node and druggable target to ameliorate the proinflammatory state. A separate trigger that utilized C-terminal RKRK of tropoelastin reduced marker expression to 65.0-76.5% and suggests the parallel involvement of integrin αVß3. We propose that the solubilization of elastin as a result of dermal damage leads to rapid chemokine up-regulation by fibroblasts that is quenched when exposed elastin is removed by MMP-12.
Assuntos
Derme/citologia , Elastina/metabolismo , Fibroblastos/metabolismo , Adesão Celular/efeitos dos fármacos , Proliferação de Células/efeitos dos fármacos , Células Cultivadas , Quimiocinas/genética , Quimiocinas/metabolismo , Proteínas Quinases Dependentes de AMP Cíclico/genética , Proteínas Quinases Dependentes de AMP Cíclico/metabolismo , Fibroblastos/citologia , Humanos , Metaloproteinase 12 da Matriz/genética , Metaloproteinase 12 da Matriz/metabolismo , Ligação Proteica , Reação em Cadeia da Polimerase em Tempo Real , Receptores de Superfície Celular/genética , Receptores de Superfície Celular/metabolismo , Transdução de Sinais/efeitos dos fármacos , Transdução de Sinais/genética , Tropoelastina/farmacologia , Cicatrização/efeitos dos fármacosRESUMO
Akt plays a major role in insulin regulation of metabolism in muscle, fat, and liver. Here, we show that in 3T3-L1 adipocytes, Akt operates optimally over a limited dynamic range. This indicates that Akt is a highly sensitive amplification step in the pathway. With robust insulin stimulation, substantial changes in Akt phosphorylation using either pharmacologic or genetic manipulations had relatively little effect on Akt activity. By integrating these data we observed that half-maximal Akt activity was achieved at a threshold level of Akt phosphorylation corresponding to 5-22% of its full dynamic range. This behavior was also associated with lack of concordance or demultiplexing in the behavior of downstream components. Most notably, FoxO1 phosphorylation was more sensitive to insulin and did not exhibit a change in its rate of phosphorylation between 1 and 100 nm insulin compared with other substrates (AS160, TSC2, GSK3). Similar differences were observed between various insulin-regulated pathways such as GLUT4 translocation and protein synthesis. These data indicate that Akt itself is a major amplification switch in the insulin signaling pathway and that features of the pathway enable the insulin signal to be split or demultiplexed into discrete outputs. This has important implications for the role of this pathway in disease.
Assuntos
Adipócitos/enzimologia , Resistência à Insulina/fisiologia , Insulina/metabolismo , Proteínas Proto-Oncogênicas c-akt/metabolismo , Transdução de Sinais/fisiologia , Células 3T3-L1 , Adipócitos/citologia , Adipócitos/efeitos dos fármacos , Animais , Antibióticos Antineoplásicos/farmacologia , Simulação por Computador , Metabolismo Energético/efeitos dos fármacos , Metabolismo Energético/fisiologia , Transportador de Glucose Tipo 4/metabolismo , Hipoglicemiantes/metabolismo , Hipoglicemiantes/farmacologia , Insulina/farmacologia , Proteínas Substratos do Receptor de Insulina/metabolismo , Camundongos , Dinâmica não Linear , Fosforilação/efeitos dos fármacos , Fosforilação/fisiologia , Fator de Crescimento Derivado de Plaquetas/metabolismo , Proteínas Proto-Oncogênicas c-akt/antagonistas & inibidores , Proteínas Proto-Oncogênicas c-akt/genética , RNA Interferente Pequeno/farmacologia , Transdução de Sinais/efeitos dos fármacos , Sirolimo/farmacologia , Serina-Treonina Quinases TOR/metabolismoRESUMO
Gastric cancer (GC) is a lethal malignancy and the second most common cause of cancer-related deaths. Although treatment options such as chemotherapy, radiotherapy, and surgery have led to a decline in the mortality rate due to GC, chemoresistance remains as one of the major causes for poor prognosis and high recurrence rate. In this study, we investigated the potential effects of isorhamnetin (IH), a 3'-O-methylated metabolite of quercetin on the peroxisome proliferator-activated receptor γ (PPAR-γ) signaling cascade using proteomics technology platform, GC cell lines, and xenograft mice model. We observed that IH exerted a strong antiproliferative effect and increased cytotoxicity in combination with chemotherapeutic drugs. IH also inhibited the migratory/invasive properties of GC cells, which could be reversed in the presence of PPAR-γ inhibitor. We found that IH increased PPAR-γ activity and modulated the expression of PPAR-γ regulated genes in GC cells. Also, the increase in PPAR-γ activity was reversed in the presence of PPAR-γ-specific inhibitor and a mutated PPAR-γ dominant negative plasmid, supporting our hypothesis that IH can act as a ligand of PPAR-γ. Using molecular docking analysis, we demonstrate that IH formed interactions with seven polar residues and six nonpolar residues within the ligand-binding pocket of PPAR-γ that are reported to be critical for its activity and could competitively bind to PPAR-γ. IH significantly increased the expression of PPAR-γ in tumor tissues obtained from xenograft model of GC. Overall, our findings clearly indicate that antitumor effects of IH may be mediated through modulation of the PPAR-γ activation pathway in GC.
Assuntos
Apoptose/efeitos dos fármacos , Proliferação de Células/efeitos dos fármacos , PPAR gama/metabolismo , Quercetina/análogos & derivados , Transdução de Sinais/efeitos dos fármacos , Neoplasias Gástricas/tratamento farmacológico , Anilidas/farmacologia , Animais , Antineoplásicos/farmacologia , Proteínas Reguladoras de Apoptose/metabolismo , Western Blotting , Pontos de Checagem do Ciclo Celular/efeitos dos fármacos , Linhagem Celular , Linhagem Celular Tumoral , Movimento Celular/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Sinergismo Farmacológico , Feminino , Humanos , Camundongos , Camundongos Nus , Invasividade Neoplásica , PPAR gama/antagonistas & inibidores , Ligação Proteica/efeitos dos fármacos , Proteômica , Quercetina/metabolismo , Quercetina/farmacologia , Neoplasias Gástricas/metabolismo , Neoplasias Gástricas/patologia , Ensaios Antitumorais Modelo de XenoenxertoRESUMO
The activation of signal transducers and activators of transcription 3 (STAT3) has been closely linked with the proliferation, survival, invasion, and angiogenesis of hepatocellular carcinoma (HCC) and represents an attractive target for therapy. In the present report, we investigated whether honokiol mediates its effect through interference with the STAT3 activation pathway. The effect of honokiol on STAT3 activation, associated protein kinases, and phosphatase, STAT3-regulated gene products and apoptosis was investigated using both functional proteomics tumor pathway technology platform and different HCC cell lines. We found that honokiol inhibited both constitutive and inducible STAT3 activation in a dose- and time-dependent manner in HCC cells. The suppression was mediated through the inhibition of activation of upstream kinases c-Src, Janus-activated kinase 1, and Janus-activated kinase 2. Vanadate treatment reversed honokiol-induced down-regulation of STAT3, suggesting the involvement of a tyrosine phosphatase. Indeed, we found that honokiol induced the expression of tyrosine phosphatase SHP-1 that correlated with the down-regulation of constitutive STAT3 activation. Moreover, deletion of SHP-1 gene by siRNA abolished the ability of honokiol to inhibit STAT3 activation. The inhibition of STAT3 activation by honokiol led to the suppression of various gene products involved in proliferation, survival, and angiogenesis. Finally, honokiol inhibited proliferation and significantly potentiated the apoptotic effects of paclitaxel and doxorubicin in HCC cells. Overall, the results suggest that honokiol is a novel blocker of STAT3 activation and may have a great potential for the treatment of HCC and other cancers.
Assuntos
Antineoplásicos Fitogênicos/farmacologia , Compostos de Bifenilo/farmacologia , Carcinoma Hepatocelular/fisiopatologia , Proliferação de Células/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Lignanas/farmacologia , Neoplasias Hepáticas/fisiopatologia , Proteína Tirosina Fosfatase não Receptora Tipo 6/metabolismo , Fator de Transcrição STAT3/antagonistas & inibidores , Antineoplásicos Fitogênicos/química , Compostos de Bifenilo/química , Proteína Tirosina Quinase CSK , Carcinoma Hepatocelular/patologia , Caspase 3/metabolismo , Linhagem Celular Tumoral , Fase G1/efeitos dos fármacos , Genes Reporter , Humanos , Interleucina-6/metabolismo , Janus Quinase 1/metabolismo , Janus Quinase 2/metabolismo , Lignanas/química , Neoplasias Hepáticas/patologia , Modelos Biológicos , Poli(ADP-Ribose) Polimerases/metabolismo , Proteína Tirosina Fosfatase não Receptora Tipo 6/genética , Proteínas Tirosina Quinases/metabolismo , Proteínas Proto-Oncogênicas c-akt/metabolismo , Fator de Transcrição STAT3/genética , Fator de Transcrição STAT3/metabolismo , Transdução de Sinais/efeitos dos fármacos , Quinases da Família srcRESUMO
BACKGROUND: Increasing evidence indicates that the interaction between the CXC chemokine receptor-4 (CXCR4) and its ligand CXCL12 is critical in the process of metastasis that accounts for more than 90% of cancer-related deaths. Thus, novel agents that can downregulate the CXCR4/CXCL12 axis have therapeutic potential in inhibiting cancer metastasis. METHODS: In this report, we investigated the potential of an agent, plumbagin (5-hydroxy-2-methyl-1, 4-naphthoquinone), for its ability to modulate CXCR4 expression and function in various tumor cells using Western blot analysis, DNA binding assay, transient transfection, real time PCR analysis, chromatin immunoprecipitation, and cellular migration and invasion assays. RESULTS: We found that plumbagin downregulated the expression of CXCR4 in breast cancer cells irrespective of their HER2 status. The decrease in CXCR4 expression induced by plumbagin was not cell type-specific as the inhibition also occurred in gastric, lung, renal, oral, and hepatocellular tumor cell lines. Neither proteasome inhibition nor lysosomal stabilization had any effect on plumbagin-induced decrease in CXCR4 expression. Detailed study of the underlying molecular mechanism(s) revealed that the regulation of the downregulation of CXCR4 was at the transcriptional level, as indicated by downregulation of mRNA expression, inhibition of NF-κB activation, and suppression of chromatin immunoprecipitation activity. In addition, using a virtual, predictive, functional proteomics-based tumor pathway platform, we tested the hypothesis that NF-κB inhibition by plumbagin causes the decrease in CXCR4 and other metastatic genes. Suppression of CXCR4 expression by plumbagin was found to correlate with the inhibition of CXCL12-induced migration and invasion of both breast and gastric cancer cells. CONCLUSIONS: Overall, our results indicate, for the first time, that plumbagin is a novel blocker of CXCR4 expression and thus has the potential to suppress metastasis of cancer.
Assuntos
Antineoplásicos Fitogênicos/farmacologia , Movimento Celular/efeitos dos fármacos , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Naftoquinonas/farmacologia , Receptores CXCR4/metabolismo , Neoplasias da Mama , Linhagem Celular Tumoral , Quimiocina CXCL12/farmacologia , Quimiocina CXCL12/fisiologia , Simulação por Computador , Regulação para Baixo , Feminino , Genes Reporter , Humanos , Luciferases/biossíntese , Luciferases/genética , Modelos Biológicos , NF-kappa B/genética , NF-kappa B/metabolismo , Invasividade Neoplásica , Ligação Proteica , Receptores CXCR4/genética , Neoplasias Gástricas , Transcrição Gênica/efeitos dos fármacosRESUMO
PURPOSE: KRAS-mutated (KRASMUT) non-small-cell lung cancer (NSCLC) is emerging as a heterogeneous disease defined by comutations, which may confer differential benefit to PD-(L)1 immunotherapy. In this study, we leveraged computational biological modeling (CBM) of tumor genomic data to identify PD-(L)1 immunotherapy sensitivity among KRASMUT NSCLC molecular subgroups. MATERIALS AND METHODS: In this multicohort retrospective analysis, the genotype clustering frequency ranked method was used for molecular clustering of tumor genomic data from 776 patients with KRASMUT NSCLC. These genomic data were input into the CBM, in which customized protein networks were characterized for each tumor. The CBM evaluated sensitivity to PD-(L)1 immunotherapy using three metrics: programmed death-ligand 1 expression, dendritic cell infiltration index (nine chemokine markers), and immunosuppressive biomarker expression index (14 markers). RESULTS: Genotype clustering identified eight molecular subgroups and the CBM characterized their shared cancer pathway characteristics: KRASMUT/TP53MUT, KRASMUT/CDKN2A/B/CMUT, KRASMUT/STK11MUT, KRASMUT/KEAP1MUT, KRASMUT/STK11MUT/KEAP1MUT, KRASMUT/PIK3CAMUT, KRAS MUT/ATMMUT, and KRASMUT without comutation. CBM identified PD-(L)1 immunotherapy sensitivity in the KRASMUT/TP53MUT, KRASMUT/PIK3CAMUT, and KRASMUT alone subgroups and resistance in the KEAP1MUT containing subgroups. There was insufficient genomic information to elucidate PD-(L)1 immunotherapy sensitivity by the CBM in the KRASMUT/CDKN2A/B/CMUT, KRASMUT/STK11MUT, and KRASMUT/ATMMUT subgroups. In an exploratory clinical cohort of 34 patients with advanced KRASMUT NSCLC treated with PD-(L)1 immunotherapy, the CBM-assessed overall survival correlated well with actual overall survival (r = 0.80, P < .001). CONCLUSION: CBM identified distinct PD-(L)1 immunotherapy sensitivity among molecular subgroups of KRASMUT NSCLC, in line with previous literature. These data provide proof-of-concept that computational modeling of tumor genomics could be used to expand on hypotheses from clinical observations of patients receiving PD-(L)1 immunotherapy and suggest mechanisms that underlie PD-(L)1 immunotherapy sensitivity.
Assuntos
Antígeno B7-H1/imunologia , Antígeno B7-H1/metabolismo , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Carcinoma Pulmonar de Células não Pequenas/genética , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/genética , Proteínas Proto-Oncogênicas p21(ras)/genética , Análise por Conglomerados , Biologia Computacional , Simulação por Computador , Genótipo , Humanos , Imunoterapia/métodos , Estudos Retrospectivos , Resultado do TratamentoRESUMO
Prostate cancer (PCa) is a common disease among men especially in the old age. The deregulated activation of oncogenic and pro-survival transcription factors has been linked with tumor progression in PCa patients. The consequence of diosgenin treatment on NF-κB/STAT3 activation in PCa cells as well as transgenic mouse model was determined. We also validated the hypothesis of targeting these transcription factors using in silico proteomics simulation model. Diosgenin abrogated NF-κB/STAT3 activation and this action was caused as a result of suppression of protein kinases and reporter gene activity that led to a substantial reduction in the expression of various tumorigenic gene products. In vivo, diosgenin (2% w/w) when mixed in diet and fed to mice abrogated tumor progression in transgenic mice. Diosgenin was also detected in serum and was well absorbed orally. Overall, our data highlights the promising efficacy of diosgenin in PCa therapy.
Assuntos
Diosgenina/farmacologia , Neoplasias da Próstata/tratamento farmacológico , Administração Oral , Animais , Linhagem Celular Tumoral , Simulação por Computador , Diosgenina/uso terapêutico , Modelos Animais de Doenças , Ensaios de Seleção de Medicamentos Antitumorais , Humanos , Masculino , Camundongos , Camundongos Transgênicos , NF-kappa B/metabolismo , Neoplasias da Próstata/genética , Neoplasias da Próstata/patologia , Proteômica , Fator de Transcrição STAT3/metabolismo , Transdução de Sinais/efeitos dos fármacosRESUMO
Clinical trials repurposing peroxisome proliferator-activated receptor-gamma (PPARγ) agonists as anticancer agents have exhibited lackluster efficacy across a variety of tumor types. Here, we report that increased PPARG expression is associated with a better prognosis but is anticorrelated with histone deacetylase (HDAC) 1 and 2 expressions. We show that HDAC overexpression blunts anti-proliferative and anti-angiogenic responses to PPARγ agonists via transcriptional and post-translational mechanisms, however, these can be neutralized with clinically approved and experimental HDAC inhibitors. Supporting this notion, concomitant treatment with HDAC inhibitors was required to license the tumor-suppressive effects of PPARγ agonists in triple-negative and endocrine-refractory breast cancer cells, and combination therapy also restrained angiogenesis in a tube formation assay. This combination was also synergistic in estrogen receptor-alpha (ERα)-positive cells because HDAC blockade abrogated ERα interference with PPARγ-regulated transcription. Following a pharmacokinetics optimization study, the combination of rosiglitazone and a potent pan-HDAC inhibitor, LBH589, stalled disease progression in a mouse model of triple-negative breast cancer greater than either of the monotherapies, while exhibiting a favorable safety profile. Our findings account for historical observations of de-novo resistance to PPARγ agonist monotherapy and propound a therapeutically cogent intervention against two aggressive breast cancer subtypes.
RESUMO
Oxidative stress is implicated in mitochondrial dysfunction associated with neurodegeneration in Parkinson's disease (PD). Depletion of the cellular antioxidant glutathione (GSH) resulting in oxidative stress is considered as an early event in neurodegeneration. We previously showed that curcumin, a dietary polyphenol from turmeric induced GSH synthesis in experimental models and protected against oxidative stress. Here we tested the effect of three bioconjugates of curcumin (involving diesters of demethylenated piperic acid, valine and glutamic acid) against GSH depletion mediated oxidative stress in dopaminergic neuronal cells and found that the glutamic acid derivative displayed improved neuroprotection compared to curcumin.
Assuntos
Antioxidantes/síntese química , Curcumina/análogos & derivados , Curcumina/química , Dopamina/fisiologia , Glutationa/metabolismo , Neurônios/metabolismo , Fármacos Neuroprotetores/síntese química , Estresse Oxidativo/efeitos dos fármacos , Doença de Parkinson/tratamento farmacológico , Antioxidantes/farmacologia , Disponibilidade Biológica , Linhagem Celular , Curcumina/farmacologia , Glutationa Transferase/metabolismo , Humanos , Peróxido de Hidrogênio/metabolismo , Indicadores e Reagentes , Peroxidação de Lipídeos/efeitos dos fármacos , Modelos Moleculares , Neurônios/efeitos dos fármacos , Fármacos Neuroprotetores/farmacologia , Oxidantes/metabolismo , Espécies Reativas de Oxigênio/metabolismoRESUMO
PURPOSE: Precision medicine has been most successful in targeting single mutations, but personalized medicine using broader genomic tumor profiles for individual patients is less well developed. We evaluate a genomics-informed computational biology model (CBM) to predict outcomes from standard treatments and to suggest novel therapy recommendations in glioblastoma (GBM). METHODS AND MATERIALS: In this retrospective study, 98 patients with newly diagnosed GBM undergoing surgery followed by radiation therapy and temozolomide at a single institution with available genomic data were identified. Incorporating mutational and copy number aberration data, a CBM was used to simulate the response of GBM tumor cells and generate efficacy predictions for radiation therapy (RTeff) and temozolomide (TMZeff). RTeff and TMZeff were evaluated for association with overall survival and progression-free survival in a Cox regression model. To demonstrate a CBM-based individualized therapy strategy, treatment recommendations were generated for each patient by testing a panel of 45 central nervous system-penetrant US Food and Drug Administration-approved agents. RESULTS: High RTeff scores were associated with longer survival on univariable analysis (P < .001), which persisted after controlling for age, extent of resection, performance status, MGMT, and IDH status (P = .017). High RTeff patients had a longer overall survival compared with low RTeff patients (median, 27.7 vs 14.6 months). High TMZeff was also associated with longer survival on univariable analysis (P = .007) but did not hold on multivariable analysis, suggesting an interplay with MGMT status. Among predictions of the 3 most efficacious combination therapies for each patient, only 2.4% (7 of 294) of 2-drug recommendations produced by the CBM included TMZ. CONCLUSIONS: CBM-based predictions of RT and TMZ effectiveness were associated with survival in patients with newly diagnosed GBM treated with those therapies, suggesting a possible predictive utility. Furthermore, the model was able to suggest novel individualized monotherapies and combinations. Prospective evaluation of such a personalized treatment strategy in clinical trials is needed.
Assuntos
Antineoplásicos Alquilantes/uso terapêutico , Neoplasias Encefálicas/terapia , Glioblastoma/terapia , Modelos Biológicos , Medicina de Precisão/métodos , Temozolomida/uso terapêutico , Adulto , Idoso , Idoso de 80 Anos ou mais , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/mortalidade , Terapia Combinada/métodos , Biologia Computacional , Feminino , Dosagem de Genes , Glioblastoma/genética , Glioblastoma/mortalidade , Humanos , Masculino , Pessoa de Meia-Idade , Mutação , Intervalo Livre de Progressão , Modelos de Riscos Proporcionais , Estudos Retrospectivos , Análise de Sobrevida , Resultado do TratamentoRESUMO
Active GTPase-Rac1 is associated with cellular processes involved in carcinogenesis and expression of Bcl-2 endows cells with the ability to evade apoptosis. Here we provide evidence that active Rac1 and Bcl-2 work in a positive feedforward loop to promote sustained phosphorylation of Bcl-2 at serine-70 (S70pBcl-2), which stabilizes its anti-apoptotic activity. Pharmacological and genetic inactivation of Rac1 prevent interaction with Bcl-2 and reduce S70pBcl-2. Similarly, BH3-mimetic inhibitors of Bcl-2 could disrupt Rac1-Bcl-2 interaction and reduce S70pBcl-2. This effect of active Rac1 could also be rescued by scavengers of intracellular superoxide (O2.-), thus implicating NOX-activating activity of Rac1 in promoting S70pBcl-2. Moreover, active Rac1-mediated redox-dependent S70pBcl-2 involves the inhibition of phosphatase PP2A holoenzyme assembly. Sustained S70pBcl-2 in turn secures Rac1/Bcl-2 interaction. Importantly, inhibiting Rac1 activity, scavenging O2.- or employing BH3-mimetic inhibitor significantly reduced S70pBcl-2-mediated survival in cancer cells. Notably, Rac1 expression, and its interaction with Bcl-2, positively correlate with S70pBcl-2 levels in patient-derived lymphoma tissues and with advanced stage lymphoma and melanoma. Together, we provide evidence of a positive feedforward loop involving active Rac1, S70pBcl-2 and PP2A, which could have potential diagnostic, prognostic and therapeutic implications.
Assuntos
Linfoma/enzimologia , Melanoma/enzimologia , Proteínas Proto-Oncogênicas c-bcl-2/metabolismo , Neoplasias Cutâneas/enzimologia , Proteínas rac1 de Ligação ao GTP/metabolismo , Apoptose , Progressão da Doença , Resistencia a Medicamentos Antineoplásicos , Retroalimentação Fisiológica , Regulação Enzimológica da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , Células Jurkat , Linfoma/tratamento farmacológico , Linfoma/genética , Linfoma/patologia , Melanoma/tratamento farmacológico , Melanoma/genética , Melanoma/patologia , Mutação , NADPH Oxidases/metabolismo , Fosforilação , Ligação Proteica , Proteína Fosfatase 2/metabolismo , Proteínas Proto-Oncogênicas c-bcl-2/genética , Transdução de Sinais , Neoplasias Cutâneas/tratamento farmacológico , Neoplasias Cutâneas/genética , Neoplasias Cutâneas/patologia , Esferoides Celulares , Superóxidos/metabolismo , Proteínas rac1 de Ligação ao GTP/genéticaRESUMO
Despite advances in understanding the molecular pathogenesis of acute myeloid leukaemia (AML), overall survival rates remain low. The ability to predict treatment response based on individual cancer genomics using computational modeling will aid in the development of novel therapeutics and personalize care. Here, we used a combination of genomics, computational biology modeling (CBM), ex vivo chemosensitivity assay, and clinical data from 100 randomly selected patients in the Beat AML project to characterize AML sensitivity to a bromodomain (BRD) and extra-terminal (BET) inhibitor. Computational biology modeling was used to generate patient-specific protein network maps of activated and inactivated protein pathways translated from each genomic profile. Digital drug simulations of a BET inhibitor (JQ1) were conducted by quantitatively measuring drug effect using a composite AML disease inhibition score. 93% of predicted disease inhibition scores matched the associated ex vivo IC50 value. Sensitivity and specificity of CBM predictions were 97.67%, and 64.29%, respectively. Genomic predictors of response were identified. Patient samples harbouring chromosomal aberrations del(7q) or -7, +8, or del(5q) and somatic mutations causing ERK pathway dysregulation, responded to JQ1 in both in silico and ex vivo assays. This study shows how a combination of genomics, computational modeling and chemosensitivity testing can identify network signatures associating with treatment response and can inform priority populations for future clinical trials of BET inhibitors.