Sex specific function of epithelial STAT3 signaling in pathogenesis of K-ras mutant lung cancer

Caetano, Mauricio S.; Hassane, Maya; Van, Hieu T.; Bugarin, Emmanuel; Cumpian, Amber M.; McDowell, Christina; Cavazos, Carolina Gonzalez; Zhang, Huiyuan; Deng, Shanshan; Diao, Lixia; Wang, Jing; Evans, Scott E.; Behrens, Carmen; Wistuba, Ignacio I.; Fuqua, Susan A. W.; Lin, Hailong; Stabile, Laura P.; Watowich, Stephanie S.; Kadara, Humam; Moghaddam, Seyed Javad

doi:10.1038/s41467-018-07042-y

Cited by 57 publications

(44 citation statements)

References 65 publications

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“…Indeed, K‐RAS ‐mutated lung AC cells secrete pro‐inflammatory cytokines including interleukin (IL)‐6 that activate JAK1 and JAK2 via glycoprotein 130 in an autocrine loop, thereby promoting tumor cell survival . On the other hand, genetic deletion of STAT3, a key signaling mediator of JAK1/2, enhances K‐RAS‐driven lung tumorigenesis, and activation of the interferon/JAK/STAT axis induces cell apoptosis and suppresses tumorigenesis in various experimental tumor models …”

Section: Introductionmentioning

confidence: 99%

“…7,10,11 On the other hand, genetic deletion of STAT3, a key signaling mediator of JAK1/2, enhances K-RAS-driven lung tumorigenesis, and activation of the interferon/JAK/STAT axis induces cell apoptosis and suppresses tumorigenesis in various experimental tumor models. [12][13][14][15][16] In addition to these tumor-cell intrinsic effects, JAK signaling is also substantially involved in shaping the tumor microenvironment (TME) by modulating T, natural killer (NK) and dendritic cell functions. 17 As in tumor cells, JAK activation in the TME and its role in tumorigenesis is controversially discussed.…”

Section: Introductionmentioning

confidence: 99%

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JAK–STAT inhibition impairs K‐RAS‐driven lung adenocarcinoma progression

Mohrherr

Haber

Breitenecker

et al. 2019

Intl Journal of Cancer

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Oncogenic K‐RAS has been difficult to target and currently there is no K‐RAS‐based targeted therapy available for patients suffering from K‐RAS‐driven lung adenocarcinoma (AC). Alternatively, targeting K‐RAS‐downstream effectors, K‐RAS‐cooperating signaling pathways or cancer hallmarks, such as tumor‐promoting inflammation, has been shown to be a promising therapeutic strategy. Since the JAK–STAT pathway is considered to be a central player in inflammation‐mediated tumorigenesis, we investigated here the implication of JAK–STAT signaling and the therapeutic potential of JAK1/2 inhibition in K‐RAS‐driven lung AC. Our data showed that JAK1 and JAK2 are activated in human lung AC and that increased activation of JAK–STAT signaling correlated with disease progression and K‐RAS activity in human lung AC. Accordingly, administration of the JAK1/2 selective tyrosine kinase inhibitor ruxolitinib reduced proliferation of tumor cells and effectively reduced tumor progression in immunodeficient and immunocompetent mouse models of K‐RAS‐driven lung AC. Notably, JAK1/2 inhibition led to the establishment of an antitumorigenic tumor microenvironment, characterized by decreased levels of tumor‐promoting chemokines and cytokines and reduced numbers of infiltrating myeloid derived suppressor cells, thereby impairing tumor growth. Taken together, we identified JAK1/2 inhibition as promising therapy for K‐RAS‐driven lung AC.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

JAK–STAT inhibition impairs K‐RAS‐driven lung adenocarcinoma progression

Mohrherr

Haber

Breitenecker

et al. 2019

Intl Journal of Cancer

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“…To demonstrate its generalizability, we used OBIF to analyze synergistic regulators in datasets derived from microarray, RNA-seq, RPPA and mass spectrometry-based metabolomics investigations of diverse factor classes and biological systems that demonstrate synergistic biological outcomes (Cleaver et al , 2014; Caetano et al , 2018; Singh et al , 2019; Han et al , 2019). As a preliminary step before full factorial analysis of individual features, OBIF performs an interaction analysis between the two factors of interest using a two-way ANOVA model to represent the impact of factorial effects at the whole “-ome” level.…”

Section: Resultsmentioning

confidence: 99%

“…To evaluate performance of full factorial analysis with OBIF, detection of interaction effects at the level of individual features is compared to a mixed-effect model (Caetano et al , 2018): where the expression level of features in a mixed-effect model (E f-Mix ) is a function of the estimated β coefficients for the fixed effects of individual factor A (F A ) and factor B (F B ) and their interaction (F A · F B ) with a random effect (1|S) for all sample conditions ( S (0,0) , S (1,0) , S (0,1) , S (1,1) ). After regression, empirical Bayesian shrinkage of the standard errors is used to stabilize inferences of t-statistics and F-statistics.…”

Section: Methodsmentioning

confidence: 99%

Omics-Based Interaction Framework – a systems model to reveal molecular drivers of synergy

García

Kulkarni

Reese

et al. 2020

Preprint

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26Bioactive molecule library screening strategies may empirically identify effective combination therapies. 27However, without a systems theory to interrogate synergistic responses, the molecular mechanisms 28 underlying favorable drug-drug interactions remain unclear, precluding rational design of combination 29 therapies. Here, we introduce Omics-Based Interaction Framework (OBIF) to reveal molecular drivers 30 of synergy through integration of statistical and biological interactions in supra-additive biological 31 responses. OBIF performs full factorial analysis of feature expression data from single vs. dual factor 32 exposures to identify molecular clusters that reveal synergy-mediating pathways, functions and 33 regulators. As a practical demonstration, OBIF analyzed a therapeutic dyad of immunostimulatory small 34 molecules that induces synergistic protection against influenza A pneumonia. OBIF analysis of 35 transcriptomic and proteomic data identified biologically relevant, unanticipated cooperation between 36 RelA and cJun that we subsequently confirmed to be required for the synergistic antiviral protection. To 37 demonstrate generalizability, OBIF was applied to data from a diverse array of Omics platforms and 38 experimental conditions, successfully identifying the molecular clusters driving their synergistic 39 responses. Hence, OBIF is a phenotype-driven systems model that supports multiplatform exploration 40 of synergy mechanisms. 41 42 Keywords 43 Data integration / Inducible epithelial resistance / Multi-Omics / Pneumonia / Synergy 44 45 Subject Categories

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“…In 2018, Caetano et al developed a lung epithelial-specific K-ras mutant/STAT3 conditional knockout mouse model, and deletion of epithelial STAT3 resulted in sex-associated discrepancies in which K-ras mutant tumors were decreased in female K-ras mutant/STAT3 conditional knockout, whereas tumor burdens were increased in males [98]. These reports spread light on the multifaceted role of STAT3 in oncogenic and tumor suppressor effects.…”

Section: Discussionmentioning

confidence: 99%

The IκB Kinase Inhibitor ACHP Targets the STAT3 Signaling Pathway in Human Non-Small Cell Lung Carcinoma Cells

et al. 2019

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STAT3 is an oncogenic transcription factor that regulates the expression of genes which are involved in malignant transformation. Aberrant activation of STAT3 has been observed in a wide range of human malignancies and its role in negative prognosis is well-documented.In this report, we performed high-throughput virtual screening in search of STAT3 signaling inhibitors using a cheminformatics platform and identified 2-Amino-6-[2-(Cyclopropylmethoxy)-6-Hydroxyphenyl]-4-Piperidin-4-yl Nicotinonitrile (ACHP) as the inhibitor of the STAT3 signaling pathway. The predicted hit was evaluated in non-small cell lung cancer (NSCLC) cell lines for its STAT3 inhibitory activity. In vitro experiments suggested that ACHP decreased the cell viability and inhibited the phosphorylation of STAT3 on Tyr705 of NSCLC cells. In addition, ACHP imparted inhibitory activity on the constitutive activation of upstream protein tyrosine kinases, including JAK1, JAK2, and Src. ACHP decreased the nuclear translocation of STAT3 and downregulated its DNA binding ability. Apoptosis was evidenced by cleavage of caspase-3 and PARP with the subsequent decline in antiapoptotic proteins, including Bcl-2, Bcl-xl, and survivin. Overall, we report that ACHP can act as a potent STAT3 signaling inhibitor in NSCLC cell lines.

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Sex specific function of epithelial STAT3 signaling in pathogenesis of K-ras mutant lung cancer

Cited by 57 publications

References 65 publications

JAK–STAT inhibition impairs K‐RAS‐driven lung adenocarcinoma progression

JAK–STAT inhibition impairs K‐RAS‐driven lung adenocarcinoma progression

Omics-Based Interaction Framework – a systems model to reveal molecular drivers of synergy

The IκB Kinase Inhibitor ACHP Targets the STAT3 Signaling Pathway in Human Non-Small Cell Lung Carcinoma Cells

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