S100A8/A9 predicts response to PIM kinase and PD-1/PD-L1 inhibition in triple-negative breast cancer mouse models.

BACKGROUND: Understanding why some triple-negative breast cancer (TNBC) patients respond poorly to existing therapies while others respond well remains a challenge. This study aims to understand the potential underlying mechanisms distinguishing early-stage TNBC tumors that respond to clinical intervention from non-responders, as well as to identify clinically viable therapeutic strategies, specifically for TNBC patients who may not benefit from existing therapies. METHODS: We conducted retrospective bioinformatics analysis of historical gene expression datasets to identify a group of genes whose expression levels in early-stage tumors predict poor clinical outcomes in TNBC. In vitro small-molecule screening, genetic manipulation, and drug treatment in syngeneic mouse models of TNBC were utilized to investigate potential therapeutic strategies and elucidate mechanisms of drug action. RESULTS: Our bioinformatics analysis reveals a robust association between increased expression of immunosuppressive cytokine S100A8/A9 in early-stage tumors and subsequent disease progression in TNBC. A targeted small-molecule screen identifies PIM kinase inhibitors as capable of decreasing S100A8/A9 expression in multiple cell types, including TNBC and immunosuppressive myeloid cells. Combining PIM inhibition and immune checkpoint blockade induces significant antitumor responses, especially in otherwise resistant S100A8/A9-high PD-1/PD-L1-positive tumors. Notably, serum S100A8/A9 levels mirror those of tumor S100A8/A9 in a syngeneic mouse model of TNBC. CONCLUSIONS: Our data propose S100A8/A9 as a potential predictive and pharmacodynamic biomarker in clinical trials evaluating combination therapy targeting PIM and immune checkpoints in TNBC. This work encourages the development of S100A8/A9-based liquid biopsy tests for treatment guidance.

Breast cancer is a complex disease, and not all patients respond well to existing treatments. In this study, we sought to understand why some patients with a specific type of breast cancer called triple-negative breast cancer respond poorly to current therapies. We also aimed to identify new treatments for these patients. We analyzed genetic data from breast cancer patients and identified a factor called S100A8/A9, which is linked to poor outcomes in early-stage cancer. We tested drugs that can reduce the levels of this factor in tumors and found promising results, especially when combined with another treatment called immunotherapy. Our findings suggest that S100A8/A9 could help predict how patients will respond to treatments, potentially leading to better therapies in the future.

The impact of circulating protein levels identified by affinity proteomics on short-term, overall breast cancer risk.

OBJECTIVE: Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk. SUBJECTS: In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort. RESULTS: In a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy. CONCLUSIONS: Our results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.

Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation.

Biomarkers for early detection of breast cancer may complement population screening approaches to enable earlier and more precise treatment. The blood proteome is an important source for biomarker discovery but so far, few proteins have been identified with breast cancer risk. Here, we measure 2929 unique proteins in plasma from 598 women selected from the Karolinska Mammography Project to explore the association between protein levels, clinical characteristics, and gene variants, and to identify proteins with a causal role in breast cancer. We present 812 cis-acting protein quantitative trait loci for 737 proteins which are used as instruments in Mendelian randomisation analyses of breast cancer risk. Of those, we present five proteins (CD160, DNPH1, LAYN, LRRC37A2 and TLR1) that show a potential causal role in breast cancer risk with confirmatory results in independent cohorts. Our study suggests that these proteins should be further explored as biomarkers and potential drug targets in breast cancer.

S100A8/A9 predicts triple-negative breast cancer response to PIM kinase and PD-1/PD-L1 inhibition.

It remains elusive why some triple-negative breast cancer (TNBC) patients respond poorly to existing therapies while others respond well. Our retrospective analysis of historical gene expression datasets reveals that increased expression of immunosuppressive cytokine S100A8/A9 in early-stage tumors is robustly associated with subsequent disease progression in TNBC. Although it has recently gained recognition as a potential anticancer target, S100A8/A9 has not been integrated into clinical study designs evaluating molecularly targeted therapies. Our small molecule screen has identified PIM kinase inhibitors as capable of decreasing S100A8/A9 expression in multiple cell types, including TNBC and immunosuppressive myeloid cells. Furthermore, combining PIM inhibition and immune checkpoint blockade induces significant antitumor responses, especially in otherwise resistant S100A8/A9-high PD-1/PD-L1-positive tumors. Importantly, serum S100A8/A9 levels mirror those of tumor S100A8/A9 in a syngeneic mouse model of TNBC. Thus, our data suggest that S100A8/A9 could be a predictive and pharmacodynamic biomarker in clinical trials evaluating combination therapy targeting PIM and immune checkpoints in TNBC and encourage the development of S100A8/A9-based liquid biopsy tests.

Quantifying the potential effects of air pollution reduction on population health and health expenditure in Taiwan.

Air pollution, particularly ambient fine particulate matter (PM2.5) pollution, poses a significant risk to public health, underscoring the importance of comprehending the long-term impact on health burden and expenditure at national and subnational levels. Therefore, this study aims to quantify the disease burden and healthcare expenditure associated with PM2.5 exposure in Taiwan and assess the potential benefits of reducing pollution levels. Using a comparative risk assessment framework that integrates an auto-aggressive integrated moving average model, we evaluated the avoidable burden of cardiopulmonary diseases (including ischemic heart disease, stroke, chronic obstructive pulmonary disease, lung cancer, and diabetes mellitus) and related healthcare expenditure under different air quality target scenarios, including status quo and target scenarios of 15, 10, and 5 µg/m3 reduction in PM2.5 concentration. Our findings indicate that reducing PM2.5 exposure has the potential to significantly alleviate the burden of multiple diseases. Comparing the estimated attributable disease burden and healthcare expenditure between reference and target scenarios from 2022 to 2050, the avoidable disability-adjusted life years were 0.61, 1.83, and 3.19 million for the 15, 10, and 5 µg/m3 target scenarios, respectively. Correspondingly, avoidable healthcare expenditure ranged from US$ 0.63 to 3.67 billion. We also highlighted the unequal allocation of resources and the need for policy interventions to address health disparities due to air pollution. Notably, in the 5 µg/m3 target scenario, Kaohsiung City stands to benefit the most, with 527,368 disability-adjusted life years avoided and US$ 0.53 billion saved from 2022 to 2050. Our findings suggest that adopting stricter emission targets can effectively reduce the health burden and associated healthcare expenditure in Taiwan. Overall, this study provides policymakers in Taiwan with valuable insights for mitigating the negative effects of air pollution by establishing a comprehensive framework for evaluating the co-benefits of air pollution reduction on healthcare expenditure and disease burden.

Controlling the confounding effect of metabolic gene expression to identify actual metabolite targets in microsatellite instability cancers.

BACKGROUND: The metabolome is the best representation of cancer phenotypes. Gene expression can be considered a confounding covariate affecting metabolite levels. Data integration across metabolomics and genomics to establish the biological relevance of cancer metabolism is challenging. This study aimed to eliminate the confounding effect of metabolic gene expression to reflect actual metabolite levels in microsatellite instability (MSI) cancers. METHODS: In this study, we propose a new strategy using covariate-adjusted tensor classification in high dimensions (CATCH) models to integrate metabolite and metabolic gene expression data to classify MSI and microsatellite stability (MSS) cancers. We used datasets from the Cancer Cell Line Encyclopedia (CCLE) phase II project and treated metabolomic data as tensor predictors and data on gene expression of metabolic enzymes as confounding covariates. RESULTS: The CATCH model performed well, with high accuracy (0.82), sensitivity (0.66), specificity (0.88), precision (0.65), and F1 score (0.65). Seven metabolite features adjusted for metabolic gene expression, namely, 3-phosphoglycerate, 6-phosphogluconate, cholesterol ester, lysophosphatidylethanolamine (LPE), phosphatidylcholine, reduced glutathione, and sarcosine, were found in MSI cancers. Only one metabolite, Hippurate, was present in MSS cancers. The gene expression of phosphofructokinase 1 (PFKP), which is involved in the glycolytic pathway, was related to 3-phosphoglycerate. ALDH4A1 and GPT2 were associated with sarcosine. LPE was associated with the expression of CHPT1, which is involved in lipid metabolism. The glycolysis, nucleotide, glutamate, and lipid metabolic pathways were enriched in MSI cancers. CONCLUSIONS: We propose an effective CATCH model for predicting MSI cancer status. By controlling the confounding effect of metabolic gene expression, we identified cancer metabolic biomarkers and therapeutic targets. In addition, we provided the possible biology and genetics of MSI cancer metabolism.

Molecular interaction mechanisms of glycol chitosan self-healing hydrogel as a drug delivery system for gemcitabine and doxorubicin.

Glycol chitosan is a derivative of chitosan that has attracted attention in recent years due to its biocompatibility and biodegradability. Due to its unique biological characteristics, it has been widely used in hydrogels and biomaterials. In this study, we explored the loading efficiency of a self-healing hydrogel (GC-DP) comprising glycol chitosan (GC) and telechelic difunctional poly(ethylene glycol) (DF-PEG) for delivering the anticancer drugs gemcitabine and doxorubicin through full atomistic simulations. We also constructed full atomistic models of the two drug delivery systems at three drug concentrations of 10%, 40%, and 80% to understand how the drug concentration affects the loading efficiency and molecular structure of the GC-DP hydrogels. Through the analysis of the results, we show that the GC-DP hydrogel exhibits excellent loading efficiency for both gemcitabine and doxorubicin at all drug concentrations (10%, 40% and 80%). Our results reveal that the main mechanism of interaction between the GC-DP hydrogels and gemcitabine is van der Waals adsorption and that the dominant interactions between the GC-DP hydrogel and doxorubicin are hydrogen bonds for the D10 model and van der Waals adsorption for the D40 and D80 models. Our results provide molecular insights into how drug molecules are carried by hydrogel materials and indicate that the GC-DP hydrogel is a promising candidate for carrying both gemcitabine and doxorubicin, and thus serving as a novel drug carrier for cancer treatment.

An Engineered IL15 Cytokine Mutein Fused to an Anti-PD1 Improves Intratumoral T-cell Function and Antitumor Immunity.

The use of cytokines for immunotherapy shows clinical efficacy but is frequently accompanied by severe adverse events caused by excessive and systemic immune activation. Here, we set out to address these challenges by engineering a fusion protein of a single, potency-reduced, IL15 mutein and a PD1-specific antibody (anti-PD1-IL15m). This immunocytokine was designed to deliver PD1-mediated, avidity-driven IL2/15 receptor stimulation to PD1+ tumor-infiltrating lymphocytes (TIL) while minimally affecting circulating peripheral natural killer (NK) cells and T cells. Treatment of tumor-bearing mice with a mouse cross-reactive fusion, anti-mPD1-IL15m, demonstrated potent antitumor efficacy without exacerbating body weight loss in B16 and MC38 syngeneic tumor models. Moreover, anti-mPD1-IL15m was more efficacious than an IL15 superagonist, an anti-mPD-1, or the combination thereof in the B16 melanoma model. Mechanistically, anti-PD1-IL15m preferentially targeted CD8+ TILs and single-cell RNA-sequencing analyses revealed that anti-mPD1-IL15m treatment induced the expansion of an exhausted CD8+ TIL cluster with high proliferative capacity and effector-like signatures. Antitumor efficacy of anti-mPD1-IL15m was dependent on CD8+ T cells, as depletion of CD8+ cells resulted in the loss of antitumor activity, whereas depletion of NK cells had little impact on efficacy. The impact of anti-hPD1-IL15m on primary human TILs from patients with cancer was also evaluated. Anti-hPD1-IL15m robustly enhanced the proliferation, activation, and cytotoxicity of CD8+ and CD4+ TILs from human primary cancers in vitro, whereas tumor-derived regulatory T cells were largely unaffected. Taken together, our findings showed that anti-PD1-IL15m exhibits a high translational promise with improved efficacy and safety of IL15 for cancer immunotherapy via targeting PD1+ TILs.See related Spotlight by Felices and Miller, p. 1110.

Combining analysis of multi-parametric MR images into a convolutional neural network: Precise target delineation for vestibular schwannoma treatment planning.

Manual delineation of vestibular schwannoma (VS) by magnetic resonance (MR) imaging is required for diagnosis, radiosurgery dose planning, and follow-up tumor volume measurement. A rapid and objective automatic segmentation method is required, but problems have been encountered due to the low through-plane resolution of standard VS MR scan protocols and because some patients have non-homogeneous cystic areas within their tumors. In this study, we retrospectively collected multi-parametric MR images from 516 patients with VS; these were extracted from the Gamma Knife radiosurgery planning system and consisted of T1-weighted (T1W), T2-weighted (T2W), and T1W with contrast (T1W + C) images. We developed an end-to-end deep-learning-based method via an automatic preprocessing pipeline. A two-pathway U-Net model involving two sizes of convolution kernel (i.e., 3 × 3 × 1 and 1 × 1 × 3) was used to extract the in-plane and through-plane features of the anisotropic MR images. A single-pathway model that adopted the same architecture as the two-pathway model, but used a kernel size of 3 × 3 × 3, was also developed for comparison purposes. In addition, we used multi-parametric MR images with different image contrasts as the model training input in order to effectively segment tumors with solid as well as cystic parts. The results of the automatic segmentation demonstrated that (1) the two-pathway model outperformed single-pathway model in terms of dice scores (0.90 ± 0.05 versus 0.87 ± 0.07); both of them having been trained using the T1W, T1W + C and T2W anisotropic MR images, (2) the optimal single-parametric two-pathway model (dice score: 0.88 ± 0.06) was then trained using the T1W + C images, and (3) the two-pathway models trained using bi-parametric (T1W + C and T2W) and tri-parametric (T1W, T2W, and T1W + C) images outperformed the model trained using the single-parametric (T1W + C) images (dice scores: 0.89 ± 0.05 and 0.90 ± 0.05, respectively, larger than 0.88 ± 0.06) because it showed improved segmentation of the non-homogeneous parts of the tumors. The proposed two-pathway U-Net model outperformed the single-pathway U-Net model when segmenting VS using anisotropic MR images. The multi-parametric models effectively improved on the defective segmentation obtained using the single-parametric models by separating the non-homogeneous tumors into their solid and cystic parts.

Empowering therapeutic antibodies with IFN-α for cancer immunotherapy.

Type 1 IFNs stimulate secretion of IP-10 (CXCL10) which is a critical chemokine to recruit effector T cells to the tumor microenvironment and IP-10 knockout mice exhibit a phenotype with compromised effector T cell generation and trafficking. Type 1 IFNs also induce MHC class 1 upregulation on tumor cells which can enhance anti-tumor CD8 T cell effector response in the tumor microenvironment. Although type 1 IFNs show great promise in potentiating anti-tumor immune response, systemic delivery of type 1 IFNs is associated with toxicity thereby limiting clinical application. In this study, we fused tumor targeting antibodies with IFN-α and showed that the fusion proteins can be produced with high yields and purity. IFN fusions selectively induced IP-10 secretion from antigen positive tumor cells, which was critical in recruiting the effector T cells to the tumor microenvironment. Further, we found that treatment with the anti-PDL1-IFN- α fusion at concentrations as low as 1 pM exhibited potent activity in mediating OT1 CD8+ T cell killing against OVA expressing tumor cells, while control IFN fusion did not exhibit any activity at the same concentration. Furthermore, the IFN-α fusion antibody was well tolerated in vivo and demonstrated anti-tumor efficacy in an anti-PD-L1 resistant syngeneic mouse tumor model. One of the potential mechanisms for the enhanced CD8 T cell killing by anti-PD-L1 IFN fusion was up-regulation of MHC class I/tumor antigen complex. Our data supports the hypothesis of targeting type 1 IFN to the tumor microenvironment may enhance effector T cell functions for anti-tumor immune response.

Double Notched Long-Period Fiber Grating Characterization for CO2 Gas Sensing Applications †.

In this study, we applied a double-sided inductively coupled plasma (ICP) process to nanostructure long-period fiber grating (LPFG) in order to fabricate a double-notched LPFG (DNLPFG) sensor with a double-sided surface corrugated periodic grating. Using the sol-gel method, we also added thymol blue and ZnO to form a gas sensing layer, thus producing a DNLPFG CO2 gas sensor. The resulting sensor is the first double-sided etching sensor used to measure CO2. The experimental results showed that as the CO2 concentration increased, the transmission loss increased, and that the smaller the fiber diameter, the greater the sensitivity and the greater the change in transmission loss. When the diameter of the fiber was 32 µm (and the period was 570 µm) and the perfusion rate of CO2 gas was 15%, the maximum loss variation of up to 3.881 dB was achieved, while the sensitivity was 0.2146 dB/% and the linearity was 0.992. These results demonstrate that the DNLPG CO2 gas sensor is highly sensitive.

Eradication of Triple-Negative Breast Cancer Cells by Targeting Glycosylated PD-L1.

Protein glycosylation provides proteomic diversity in regulating protein localization, stability, and activity; it remains largely unknown whether the sugar moiety contributes to immunosuppression. In the study of immune receptor glycosylation, we showed that EGF induces programmed death ligand 1 (PD-L1) and receptor programmed cell death protein 1 (PD-1) interaction, requiring ß-1,3-N-acetylglucosaminyl transferase (B3GNT3) expression in triple-negative breast cancer. Downregulation of B3GNT3 enhances cytotoxic T cell-mediated anti-tumor immunity. A monoclonal antibody targeting glycosylated PD-L1 (gPD-L1) blocks PD-L1/PD-1 interaction and promotes PD-L1 internalization and degradation. In addition to immune reactivation, drug-conjugated gPD-L1 antibody induces a potent cell-killing effect as well as a bystander-killing effect on adjacent cancer cells lacking PD-L1 expression without any detectable toxicity. Our work suggests targeting protein glycosylation as a potential strategy to enhance immune checkpoint therapy.

Identification of novel resistance mechanisms to NAMPT inhibition via the de novo NAD+ biosynthesis pathway and NAMPT mutation.

Cancer cells have an unusually high requirement for the central and intermediary metabolite nicotinamide adenine dinucleotide (NAD+), and NAD+ depletion ultimately results in cell death. The rate limiting step within the NAD+ salvage pathway required for converting nicotinamide to NAD+ is catalyzed by nicotinamide phosphoribosyltransferase (NAMPT). Targeting NAMPT has been investigated as an anti-cancer strategy, and several highly selective small molecule inhibitors have been found to potently inhibit NAMPT in cancer cells, resulting in NAD+ depletion and cytotoxicity. To identify mechanisms that could cause resistance to NAMPT inhibitor treatment, we generated a human fibrosarcoma cell line refractory to the highly potent and selective NAMPT small molecule inhibitor, GMX1778. We uncovered novel and unexpected mechanisms of resistance including significantly increased expression of quinolinate phosphoribosyl transferase (QPRT), a key enzyme in the de novo NAD+ synthesis pathway. Additionally, exome sequencing of the NAMPT gene in the resistant cells identified a single heterozygous point mutation that was not present in the parental cell line. The combination of upregulation of the NAD+ de novo synthesis pathway through QPRT over-expression and NAMPT mutation confers resistance to GMX1778, but the cells are only partially resistant to next-generation NAMPT inhibitors. The resistance mechanisms uncovered herein provide a potential avenue to continue exploration of next generation NAMPT inhibitors to treat neoplasms in the clinic.

HER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer.

Resistance to HER2-targeted therapies remains a major obstacle in the treatment of HER2-overexpressing breast cancer. Understanding the molecular pathways that contribute to the development of drug resistance is needed to improve the clinical utility of novel agents, and to predict the success of targeted personalized therapy based on tumor-specific mutations. Little is known about the clinical significance of HER family mutations in breast cancer. Because mutations within HER1/EGFR are predictive of response to tyrosine kinase inhibitors (TKI) in lung cancer, we investigated whether mutations in HER family kinase domains are predictive of response to targeted therapy in HER2-overexpressing breast cancer. We sequenced the HER family kinase domains from 76 HER2-overexpressing invasive carcinomas and identified 12 missense variants. Patients whose tumors carried any of these mutations did not respond to HER2 directed therapy in the metastatic setting. We developed mutant cell lines and used structural analyses to determine whether changes in protein conformation could explain the lack of response to therapy. We also functionally studied all HER2 mutants and showed that they conferred an aggressive phenotype and altered effects of the TKI lapatinib. Our data demonstrate that mutations in the finely tuned HER kinase domains play a critical function in breast cancer progression and may serve as prognostic and predictive markers.

Apo2L/TRAIL and the death receptor 5 agonist antibody AMG 655 cooperate to promote receptor clustering and antitumor activity.

Death receptor agonist therapies have exhibited limited clinical benefit to date. Investigations into why Apo2L/TRAIL and AMG 655 preclinical data were not predictive of clinical response revealed that coadministration of Apo2L/TRAIL with AMG 655 leads to increased antitumor activity in vitro and in vivo. The combination of Apo2L/TRAIL and AMG 655 results in enhanced signaling and can sensitize Apo2L/TRAIL-resistant cells. Structure determination of the Apo2L/TRAIL-DR5-AMG 655 ternary complex illustrates how higher order clustering of DR5 is achieved when both agents are combined. Enhanced agonism generated by combining Apo2L/TRAIL and AMG 655 provides insight into the limited efficacy observed in previous clinical trials and suggests testable hypotheses to reconsider death receptor agonism as a therapeutic strategy.

Activation of Keap1/Nrf2 signaling pathway by nuclear epidermal growth factor receptor in cancer cells.

Nuclear translocation of EGFR has been shown to be important for tumor cell growth, survival, and therapeutic resistance. Previously, we detected the association of EGFR with Keap1 in the nucleus. Keap1 is a Kelch-like ECH-associated protein, which plays an important role in cellular response to chemical and oxidative stress by regulating Nrf2 protein stability and nuclear translocation. In this study, we investigate the role of EGFR in regulating Keap1/Nrf2 cascade in the nucleus and provide evidence to show that nuclear EGFR interacts with and phosphorylates nuclear Keap1 to reduce its nuclear protein level. The reduction of nuclear Keap1 consequently stabilizes nuclear Nrf2 and increases its transcriptional activity in cancer cells, which contributes to tumor cell resistance to chemotherapy.

Epidermal growth factor receptor potentiates MCM7-mediated DNA replication through tyrosine phosphorylation of Lyn kinase in human cancers.

Epidermal growth factor receptor (EGFR) initiates a signaling cascade that leads to DNA synthesis and cell proliferation, but its role in regulating DNA replication licensing is unclear. Here, we show that activated EGFR phosphorylates the p56 isoform of Lyn, p56(Lyn), at Y32, which then phosphorylates MCM7, a licensing factor critical for DNA replication, at Y600 to increase its association with other minichromosome maintenance complex proteins, thereby promoting DNA synthesis complex assembly and cell proliferation. Both p56(Lyn) Y32 and MCM7 Y600 phosphorylation are enhanced in proliferating cells and correlated with poor survival of breast cancer patients. These results establish a signaling cascade in which EGFR enhances MCM7 phosphorylation and DNA replication through Lyn phosphorylation in human cancer cells.

The crosstalk of mTOR/S6K1 and Hedgehog pathways.

Esophageal adenocarcinoma (EAC) is the most prevalent esophageal cancer type in the United States. The TNF-α/mTOR pathway is known to mediate the development of EAC. Additionally, aberrant activation of Gli1, downstream effector of the Hedgehog (HH) pathway, has been observed in EAC. In this study, we found that an activated mTOR/S6K1 pathway promotes Gli1 transcriptional activity and oncogenic function through S6K1-mediated Gli1 phosphorylation at Ser84, which releases Gli1 from its endogenous inhibitor, SuFu. Moreover, elimination of S6K1 activation by an mTOR pathway inhibitor enhances the killing effects of the HH pathway inhibitor. Together, our results established a crosstalk between the mTOR/S6K1 and HH pathways, which provides a mechanism for SMO-independent Gli1 activation and also a rationale for combination therapy for EAC.

RNA helicase A is a DNA-binding partner for EGFR-mediated transcriptional activation in the nucleus.

EGF induces the translocation of EGF receptor (EGFR) from the cell surface to the nucleus where EGFR activates gene transcription through its binding to an AT-rich sequence (ATRS) of the target gene promoter. However, how EGFR, without a DNA-binding domain, can bind to the gene promoter is unclear. In the present study, we show that RNA helicase A (RHA) is an important mediator for EGFR-induced gene transactivation. EGF stimulates the interaction of EGFR with RHA in the nucleus of cancer cells. The EGFR/RHA complex then associates with the target gene promoter through binding of RHA to the ATRS of the target gene promoter to activate its transcription. Knockdown of RHA expression in cancer cells abrogates the binding of EGFR to the target gene promoter, thereby reducing EGF/EGFR-induced gene expression. In addition, interruption of EGFR-RHA interaction decreases the EGFR-induced promoter activity. Consistently, we observed a positive correlation of the nuclear expression of EGFR, RHA, and cyclin D1 in human breast cancer samples. These results indicate that RHA is a DNA-binding partner for EGFR-mediated transcriptional activation in the nucleus.

ARD1 stabilization of TSC2 suppresses tumorigenesis through the mTOR signaling pathway.

Mammalian target of rapamycin (mTOR) regulates various cellular functions, including tumorigenesis, and is inhibited by the tuberous sclerosis 1 (TSC1)-TSC2 complex. Here, we demonstrate that arrest-defective protein 1 (ARD1) physically interacts with, acetylates, and stabilizes TSC2, thereby repressing mTOR activity. The inhibition of mTOR by ARD1 inhibits cell proliferation and increases autophagy, thereby inhibiting tumorigenicity. Correlation between ARD1 and TSC2 abundance was apparent in multiple tumor types. Moreover, evaluation of loss of heterozygosity at Xq28 revealed allelic loss in 31% of tested breast cancer cell lines and tumor samples. Together, our findings suggest that ARD1 functions as an inhibitor of the mTOR pathway and that dysregulation of the ARD1-TSC2-mTOR axis may contribute to cancer development.