Ring finger protein 138 inhibits transcription factor C/EBPα protein turnover leading to differentiation arrest in acute myeloid leukemia.

E3 ubiquitin ligase, ring finger protein 138 (RNF138) is involved in several biological processes; however, its role in myeloid differentiation or tumorigenesis remains unclear. RNAseq data from TNMplot showed that RNF138 mRNA levels are highly elevated in acute myeloid leukemia (AML) bone marrow samples as compared with bone marrow of normal volunteers. Here, we show that RNF138 serves as an E3 ligase for the tumor suppressor CCAAT/enhancer binding protein (C/EBPα) and promotes its degradation leading to myeloid differentiation arrest in AML. Wild-type RNF138 physically interacts with C/EBPα and promotes its ubiquitin-dependent proteasome degradation while a mutant RNF-138 deficient in ligase activity though interacts with C/EBPα, fails to down-regulate it. We show that RNF138 depletion enhances endogenous C/EBPα levels in peripheral blood mononuclear cells (PBMCs) isolated from healthy volunteers. Our data further shows that RNF138-mediated degradation of C/EBPα negatively affects its transactivation potential on its target genes. Furthermore, RNF138 overexpression inhibits all-trans-retinoic acid-induced differentiation of HL-60 cells whereas RNF138 RNAi enhances. In line with RNF138 inhibiting C/EBPα protein turnover, we also observed that RNF138 overexpression inhibited ß-estradiol (E2)-induced C/EBPα driven granulocytic differentiation in C/EBPα inducible K562-p42C/EBPα-estrogen receptor cells. Furthermore, we also recapitulated these findings in PBMCs isolated from AML patients where depletion of RNF138 increased the expression of myeloid differentiation marker CD11b. These results suggest that RNF138 inhibits myeloid differentiation by targeting C/EBPα for proteasomal degradation and may provide a plausible mechanism for loss of C/EBPα expression often observed in myeloid leukemia. Also, targeting RNF138 may resolve differentiation arrest by restoring C/EBPα expression in AML.

Molecular Changes in Breast Cancer Induced by Radiation Therapy.

PURPOSE: Breast cancer treatments are based on prognostic clinicopathologic features that form the basis for therapeutic guidelines. Although the utilization of these guidelines has decreased breast cancer-associated mortality rates over the past three decades, they are not adequate for individualized therapy. Radiation therapy (RT) is the backbone of breast cancer treatment. Although a highly successful therapeutic modality clinically, from a biological perspective, preclinical studies have shown RT to have the potential to alter tumor cell phenotype, immunogenicity, and the surrounding microenvironment, potentially changing the behavior of cancer cells and resulting in a significant variation in RT response. This review presents the recent advances in revealing the complex molecular changes induced by RT in the treatment of breast cancer and highlights the complexities of translating this information into clinically relevant tools for improved prognostic insights and the revelation of novel approaches for optimizing RT. METHODS AND MATERIALS: Current literature was reviewed with a focus on recent advances made in the elucidation of tumor-associated radiation-induced molecular changes across molecular, genetic, and proteomic bases. This review was structured with the aim of providing an up-to-date overview over the very broad and complex subject matter of radiation-induced molecular changes and radioresistance, familiarizing the reader with the broader issue at hand. RESULTS: The subject of radiation-induced molecular changes in breast cancer has been broached from various physiological focal points including that of the immune system, immunogenicity and the abscopal effect, tumor hypoxia, breast cancer classification and subtyping, molecular heterogeneity, and molecular plasticity. It is becoming increasingly apparent that breast cancer clinical subtyping alone does not adequately account for variation in RT response or radioresistance. Multiple components of the tumor microenvironment and immune system, delivered RT dose and fractionation schedules, radiation-induced bystander effects, and intrinsic tumor physiology and heterogeneity all contribute to the resultant RT outcome. CONCLUSIONS: Despite recent advances and improvements in anticancer therapies, tumor resistance remains a significant challenge. As new analytical techniques and technologies continue to provide crucial insight into the complex molecular mechanisms of breast cancer and its treatment responses, it is becoming more evident that personalized anticancer treatment regimens may be vital in overcoming radioresistance.

RING finger E3 ligase, RNF138 inhibits osteoblast differentiation by negatively regulating Runx2 protein turnover.

A few ubiquitin ligases have been shown to target Runx2, the key osteogenic transcription factor and thereby regulate bone formation. The regulation of Runx2 expression and function are controlled both at the transcriptional and posttranslational levels. Really interesting new gene (RING) finger ubiquitin ligases of which RNF138 is a member are important players in the ubiquitin-proteasome system, contributing to the regulation of protein turnover and cellular processes. Here, we demonstrated that RNF138 negatively correlated with Runx2 protein levels in osteopenic ovariectomized rats which implied its role in bone loss. Accordingly, RNF138 overexpression potently inhibited osteoblast differentiation of mesenchyme-like C3H10T1/2 as well primary rat calvarial osteoblast (RCO) cells in vitro, whereas overexpression of catalytically inactive mutant RNF138Δ18-58 (lacks RING finger domain) had mild to no effect. Contrarily, RNF138 depletion copiously enhanced endogenous Runx2 levels and augmented osteogenic differentiation of C3H10T1/2 as well as RCOs. Mechanistically, RNF138 physically associates within multiple regions of Runx2 and ubiquitinates it leading to its reduced protein stability in a proteasome-dependent manner. Moreover, catalytically active RNF138 destabilized Runx2 which resulted in inhibition of its transactivation potential and physiological function of promoting osteoblast differentiation leading to bone loss. These findings underscore the functional involvement of RNF138 in bone formation which is primarily achieved through its modulation of Runx2 by stimulating ubiquitin-mediated proteasomal degradation. Thus, our findings indicate that RNF138 could be a promising novel target for therapeutic intervention in postmenopausal osteoporosis.

Patient-specific signaling signatures predict optimal therapeutic combinations for triple negative breast cancer.

Triple negative breast cancer (TNBC) is a heterogeneous group of tumors which lack estrogen receptor, progesterone receptor, and HER2 expression. Targeted therapies have limited success in treating TNBC, thus a strategy enabling effective targeted combinations is an unmet need. To tackle these challenges and discover individualized targeted combination therapies for TNBC, we integrated phosphoproteomic analysis of altered signaling networks with patient-specific signaling signature (PaSSS) analysis using an information-theoretic, thermodynamic-based approach. Using this method on a large number of TNBC patient-derived tumors (PDX), we were able to thoroughly characterize each PDX by computing a patient-specific set of unbalanced signaling processes and assigning a personalized therapy based on them. We discovered that each tumor has an average of two separate processes, and that, consistent with prior research, EGFR is a major core target in at least one of them in half of the tumors analyzed. However, anti-EGFR monotherapies were predicted to be ineffective, thus we developed personalized combination treatments based on PaSSS. These were predicted to induce anti-EGFR responses or to be used to develop an alternative therapy if EGFR was not present.In-vivo experimental validation of the predicted therapy showed that PaSSS predictions were more accurate than other therapies. Thus, we suggest that a detailed identification of molecular imbalances is necessary to tailor therapy for each TNBC. In summary, we propose a new strategy to design personalized therapy for TNBC using pY proteomics and PaSSS analysis. This method can be applied to different cancer types to improve response to the biomarker-based treatment.

Dexamethasone induces cancer mitigation and irreversible senescence in lung cancer cells via damaging cortical actin and sustained hyperphosphorylation of pRb.

Activation of the glucocorticoid receptors by its cognate ligand, dexamethasone (DEX) is commonly used as an adjuvant treatment in solid tumors. However, its direct effect on cancerous phenotype is not fully understood. We explored the effect and molecular mechanisms of DEX action in lung cancer. In in vitro experiments, DEX treatment causes decrease in migration, invasion and colony formation ability of A549 cells even at lower doses. DEX also decreased adhesion of A549 cells by reducing the formation of cortical actin. Treatment with RU486, a GR antagonist, indicated that these effects are partially mediated through GR. Further; DEX induces G0/G1 arrest of A549 cells. Mechanistically, DEX induces expression of both CDK inhibitors (p21Cip1, p27Kip1) and cyclin-dependent kinases (CDK4, CDK6). Due to this compensatory activation of CDKs and CDKIs, DEX induces the hyper phosphorylation state of Rb protein (pRb) leading to irreversible senescence as confirmed by ß-gal staining. Next, in clinical dataset of NSCLC (Non-small cell lung cancer), GR was lowly expressed in cancer patients as compared to the normal group, where higher expression of GR led to higher overall survival of NSCLC indicating for a protective role of GR. Interestingly, when combined with chemotherapeutic agents, DEX can modulate the drug-sensitivity of cells. Taken together, these data indicate that DEX through GR activation may suppress tumor growth by decreasing proliferation and inducing irreversible senescence and combination of standard chemotherapy and DEX can be a potential treatment for NSCLC.

AIP4 regulates adipocyte differentiation by targeting C/EBPα for ubiquitin-mediated proteasomal degradation.

Adipogenesis, that is, the formation of terminally differentiated adipocytes is intricately regulated by transcription factors where CCAAT/enhancer binding protein alpha (C/EBPα) plays a key role. In the current study, we demonstrate that E3 ubiquitin ligase AIP4 negatively regulates C/EBPα protein stability leading to reduced adipogenesis. While AIP4 overexpression in 3T3-L1 cells preadipocytes inhibited lipid accumulation when treated with differentiation inducing media (MDI), AIP4 depletion was sufficient to partially promote lipid accumulation even in the absence of MDI. Mechanistically, overexpression of AIP4 inhibited protein levels of both ectopically expressed as well as endogenous C/EBPα while catalytically inactive AIP4 failed. On the contrary, AIP4 depletion profoundly enhanced endogenous C/EBPα protein levels. The observation that AIP4 levels decrease with concomitant increase in C/EBPα levels during adipocyte differentiation further indicated that AIP4 negatively regulates C/EBPα levels. We further show that AIP4 physically interacts with C/EBPα and ubiquitinates it leading to its proteasomal degradation. AIP4 promoted K48-linked ubiquitination of C/EBPα while catalytically inactive AIP4-C830A failed. Taken together, our data demonstrate that AIP4 inhibits adipogenesis by targeting C/EBPα for ubiquitin-mediated proteasome degradation.

Dexamethasone activates c-Jun NH2-terminal kinase (JNK) which interacts with GR and protects it from ubiquitin-mediated degradation in NSCLC cells.

Dexamethasone-mediated pharmacological activation of the glucocorticoid receptor (GR) is widely used in the treatment regimen of hematological malignancies and solid cancers. However, DEX sensitivity towards patients primarily depends on the endogenous protein levels of GR. We observed that DEX treatment leads to an increase in GR protein levels despite inhibition of neo-protein synthesis in non-small cell lung cancer (NSCLC) cells. Mechanistically, DEX-stimulation concomitantly increased the JNK phosphorylation and GR protein levels, however the JNK stimulation preceds GR upregulation. Moreover, we also observed that DEX-mediated phosphorylation is partially mediated by upregulation in MEKK1 phosphorylation. Further, GR protein levels were significantly decreased in JNK inhibitor (JNKi, SP600125) treated cells whereas MG132 treatment restored GR levels indicating that DEX induced JNK activity regulated the GR protein levels through proteasomal-degradation pathway. Next, we showed that DEX led to JNK activation which physically interacts with GR and protects it from ubiquitination-mediated degradation. Furthermore, at basal level GR interacts with JNK in cytoplasm whereas upon DEX stimulation GR and pJNK both localized to nucleus and interact with each other. Next, we show that JNK-mediated GR stabilization affects its nuclear transcriptional functional activity in NSCLC cells. In line with these in vitro data, patient dataset analysis also shows that increased levels of both JNK and GR contributes towards better prognosis of NSCLC patients. Taken together, our data shows that DEX treatment may lead to positive feedback regulation of GR by activating JNK and thus highlights importance of GR-JNK crosstalk in NSCLC.

Origin, production and molecular determinants of macrophages for their therapeutic targeting.

Macrophages, the most heterogeneous cells of the hematopoietic system and the giant eaters of the immune system that present either as tissue-resident cells or infiltrated immune cells, eliminate foreign pathogens and microbes and also play different physiological roles to maintain the body's immune response. In this review, we basically provide a broad overview of macrophages from their origin, functional diversity to M1-M2 polarization, specialized markers, and their role as important therapeutic targets in different diseases based on the current research and evidence. Apart from this, we have precisely discussed about tumor-associated macrophages (TAMs) and their role in tumor progression and newly discovered lesser-known markers of TAMs that could be used as potential therapeutic targets to treat life-threatening diseases. It is really very important to understand the diversity of macrophages to develop TAM-modulating strategies to activate our own immune system against diseases and to overcome immune resistance.

Computational quantification and characterization of independently evolving cellular subpopulations within tumors is critical to inhibit anti-cancer therapy resistance.

BACKGROUND: Drug resistance continues to be a major limiting factor across diverse anti-cancer therapies. Contributing to the complexity of this challenge is cancer plasticity, in which one cancer subtype switches to another in response to treatment, for example, triple-negative breast cancer (TNBC) to Her2-positive breast cancer. For optimal treatment outcomes, accurate tumor diagnosis and subsequent therapeutic decisions are vital. This study assessed a novel approach to characterize treatment-induced evolutionary changes of distinct tumor cell subpopulations to identify and therapeutically exploit anticancer drug resistance. METHODS: In this research, an information-theoretic single-cell quantification strategy was developed to provide a high-resolution and individualized assessment of tumor composition for a customized treatment approach. Briefly, this single-cell quantification strategy computes cell barcodes based on at least 100,000 tumor cells from each experiment and reveals a cell-specific signaling signature (CSSS) composed of a set of ongoing processes in each cell. RESULTS: Using these CSSS-based barcodes, distinct subpopulations evolving within the tumor in response to an outside influence, like anticancer treatments, were revealed and mapped. Barcodes were further applied to assign targeted drug combinations to each individual tumor to optimize tumor response to therapy. The strategy was validated using TNBC models and patient-derived tumors known to switch phenotypes in response to radiotherapy (RT). CONCLUSIONS: We show that a barcode-guided targeted drug cocktail significantly enhances tumor response to RT and prevents regrowth of once-resistant tumors. The strategy presented herein shows promise in preventing cancer treatment resistance, with significant applicability in clinical use.

Drug-Induced Resistance and Phenotypic Switch in Triple-Negative Breast Cancer Can Be Controlled via Resolution and Targeting of Individualized Signaling Signatures.

Triple-negative breast cancer (TNBC) is an aggressive subgroup of breast cancers which is treated mainly with chemotherapy and radiotherapy. Epidermal growth factor receptor (EGFR) was considered to be frequently expressed in TNBC, and therefore was suggested as a therapeutic target. However, clinical trials of EGFR inhibitors have failed. In this study, we examine the relationship between the patient-specific TNBC network structures and possible mechanisms of resistance to anti-EGFR therapy. Using an information-theoretical analysis of 747 breast tumors from the TCGA dataset, we resolved individualized protein network structures, namely patient-specific signaling signatures (PaSSS) for each tumor. Each PaSSS was characterized by a set of 1-4 altered protein-protein subnetworks. Thirty-one percent of TNBC PaSSSs were found to harbor EGFR as a part of the network and were predicted to benefit from anti-EGFR therapy as long as it is combined with anti-estrogen receptor (ER) therapy. Using a series of single-cell experiments, followed by in vivo support, we show that drug combinations which are not tailored accurately to each PaSSS may generate evolutionary pressure in malignancies leading to an expansion of the previously undetected or untargeted subpopulations, such as ER+ populations. This corresponds to the PaSSS-based predictions suggesting to incorporate anti-ER drugs in certain anti-TNBC treatments. These findings highlight the need to tailor anti-TNBC targeted therapy to each PaSSS to prevent diverse evolutions of TNBC tumors and drug resistance development.

Overcoming resistance to BRAFV600E inhibition in melanoma by deciphering and targeting personalized protein network alterations.

BRAFV600E melanoma patients, despite initially responding to the clinically prescribed anti-BRAFV600E therapy, often relapse, and their tumors develop drug resistance. While it is widely accepted that these tumors are originally driven by the BRAFV600E mutation, they often eventually diverge and become supported by various signaling networks. Therefore, patient-specific altered signaling signatures should be deciphered and treated individually. In this study, we design individualized melanoma combination treatments based on personalized network alterations. Using an information-theoretic approach, we compute high-resolution patient-specific altered signaling signatures. These altered signaling signatures each consist of several co-expressed subnetworks, which should all be targeted to optimally inhibit the entire altered signaling flux. Based on these data, we design smart, personalized drug combinations, often consisting of FDA-approved drugs. We validate our approach in vitro and in vivo showing that individualized drug combinations that are rationally based on patient-specific altered signaling signatures are more efficient than the clinically used anti-BRAFV600E or BRAFV600E/MEK targeted therapy. Furthermore, these drug combinations are highly selective, as a drug combination efficient for one BRAFV600E tumor is significantly less efficient for another, and vice versa. The approach presented herein can be broadly applicable to aid clinicians to rationally design patient-specific anti-melanoma drug combinations.