Eurochevalierines A-I, Sesquiterpene Alkaloid Hybrids with Anti-Triple Negative Breast Cancer Activity from Penicillium sp. HZ-5.

Nine new sesquiterpene alkaloids, eurochevalierines A-I (1-9), were separated from the rice cultures of the endophytic fungus Penicillium sp. HZ-5 originated from the fresh leaf of Hypericum wilsonii N. Robson. The structures' illumination was conducted by single-crystal X-ray diffraction, extensive spectroscopic analysis, alkaline hydrolysis reaction, and Snatzke's method. Importantly, the antitumor activities screen of these isolates indicated that 1 could suppress triple negative breast cancer (TNBC) cell proliferation and induce apoptosis, with an IC50 value of 5.4 µM, which is comparable to the positive control docetaxel (DXT). Flow cytometry experiments mentioned that compound 1 significantly reduced mitochondrial membrane potential (MMP) of TNBC cells. In addition, 1 could activate caspase-3 and elevated the levels of reactive oxygen species (ROS) and expressions of suppressive cytokines and chemokines. Further Western blot analysis showed that 1 could selectively induce mitochondria-dependent apoptosis in TNBC cells via the BAX/BCL-2 pathway. Remarkably, these finding provide a new natural product skeleton for the treatment of TNBC.

Neoadjuvant chemotherapy for breast cancer: an evaluation of its efficacy and research progress.

Neoadjuvant chemotherapy (NAC) for breast cancer is widely used in the clinical setting to improve the chance of surgery, breast conservation and quality of life for patients with advanced breast cancer. A more accurate efficacy evaluation system is important for the decision of surgery timing and chemotherapy regimen implementation. However, current methods, encompassing imaging techniques such as ultrasound and MRI, along with non-imaging approaches like pathological evaluations, often fall short in accurately depicting the therapeutic effects of NAC. Imaging techniques are subjective and only reflect macroscopic morphological changes, while pathological evaluation is the gold standard for efficacy assessment but has the disadvantage of delayed results. In an effort to identify assessment methods that align more closely with real-world clinical demands, this paper provides an in-depth exploration of the principles and clinical applications of various assessment approaches in the neoadjuvant chemotherapy process.

Preparing Data for Artificial Intelligence in Pathology with Clinical-Grade Performance.

The pathology is decisive for disease diagnosis but relies heavily on experienced pathologists. In recent years, there has been growing interest in the use of artificial intelligence in pathology (AIP) to enhance diagnostic accuracy and efficiency. However, the impressive performance of deep learning-based AIP in laboratory settings often proves challenging to replicate in clinical practice. As the data preparation is important for AIP, the paper has reviewed AIP-related studies in the PubMed database published from January 2017 to February 2022, and 118 studies were included. An in-depth analysis of data preparation methods is conducted, encompassing the acquisition of pathological tissue slides, data cleaning, screening, and subsequent digitization. Expert review, image annotation, dataset division for model training and validation are also discussed. Furthermore, we delve into the reasons behind the challenges in reproducing the high performance of AIP in clinical settings and present effective strategies to enhance AIP's clinical performance. The robustness of AIP depends on a randomized collection of representative disease slides, incorporating rigorous quality control and screening, correction of digital discrepancies, reasonable annotation, and sufficient data volume. Digital pathology is fundamental in clinical-grade AIP, and the techniques of data standardization and weakly supervised learning methods based on whole slide image (WSI) are effective ways to overcome obstacles of performance reproduction. The key to performance reproducibility lies in having representative data, an adequate amount of labeling, and ensuring consistency across multiple centers. Digital pathology for clinical diagnosis, data standardization and the technique of WSI-based weakly supervised learning will hopefully build clinical-grade AIP.

[Corrigendum] CXCR1 promotes malignant behavior of gastric cancer cells in vitro and in vivo in AKT and ERK1/2 phosphorylation.

Subsequently to the publication of the above article, the authors contacted the Editorial Office to explain that they had inadvertently included data from the same original source in the first row of data panels in Fig. 4B on p. 2191 (showing the results of cell migration assay experiments) to represent two differently performed experiments. Specifically, these images (second and third data panels) containing partially overlapping data corresponded to the 'Vacant­BGC823' in the empty plasmid transfection group and the background 'BGC823 cell' groups, respectively. However, the authors had retained their original data, which they presented to the office for our inspection, and were able to reassemble the data correctly in the figure. The revised version of Fig. 4, showing the replacement data for the 'Vacant­BGC823' and 'BGC823' Migration panels in Fig. 4B, is shown on the next page. The authors are grateful to the Editor of International Journal of Oncology for allowing them this opportunity to publish a Corrigendum, and all the authors agree with its publication. Furthermore, the authors apologize to the readership for any inconvenience caused. [International Journal of Oncology 48: 2184­2196, 2016; DOI: 10.3892/ijo.2016.3428].

Preclinical and Basic Research Strategies for Overcoming Resistance to Targeted Therapies in HER2-Positive Breast Cancer.

The amplification of epidermal growth factor receptor 2 (HER2) is associated with a poor prognosis and HER2 gene is overexpressed in approximately 15-30% of breast cancers. In HER2-positive breast cancer patients, HER2-targeted therapies improved clinical outcomes and survival rates. However, drug resistance to anti-HER2 drugs is almost unavoidable, leaving some patients with an unmet need for better prognoses. Therefore, exploring strategies to delay or revert drug resistance is urgent. In recent years, new targets and regimens have emerged continuously. This review discusses the fundamental mechanisms of drug resistance in the targeted therapies of HER2-positive breast cancer and summarizes recent research progress in this field, including preclinical and basic research studies.

Treatment strategies for clear cell renal cell carcinoma: Past, present and future.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent histological subtype of kidney cancer, which is prone to metastasis, recurrence, and resistance to radiotherapy and chemotherapy. The burden it places on human health due to its refractory nature and rising incidence rate is substantial. Researchers have recently determined the ccRCC risk factors and optimized the clinical therapy based on the disease's underlying molecular mechanisms. In this paper, we review the established clinical therapies and novel potential therapeutic approaches for ccRCC, and we support the importance of investigating novel therapeutic options in the context of combining established therapies as a research hotspot, with the goal of providing diversified therapeutic options that promise to address the issue of drug resistance, with a view to the early realization of precision medicine and individualized treatment.

Corrigendum: HER-2 positive primary neuroendocrine neoplasms of the breast with signet ring feature: A case report and review of literature.

[This corrects the article DOI: 10.3389/fonc.2022.1029007.].

Incorporating ultrasound-based lymph node staging significantly improves the performance of a clinical nomogram for predicting preoperative axillary lymph node metastasis in breast cancer.

Models for predicting axillary lymph node metastasis (ALNM) in breast cancer patients are lacking. We aimed to develop an efficient model to accurately predict ALNM. Three hundred fifty-five breast cancer patients were recruited and randomly divided into the training and validation sets. Univariate and multivariate logistic regressions were applied to identify predictors of ALNM. We developed nomograms based on these variables to predict ALNM. The performance of the nomograms was tested using the receiver operating characteristic curve and calibration curve, and a decision curve analysis was performed to assess the clinical utility of the prediction models. The nomograms that included clinical N stage (cN), pathological grade (pathGrade), and hemoglobin accurately predicted ALNM in the training and validation sets (area under the curve [AUC] 0.80 and 0.80, respectively). We then explored the importance of the cN and pathGradesignatures used in the integrated model and developed new nomograms by removing the two variables. The results suggested that the combine-pathGrade nomogram also accurately predicted ALNM in the training and validation sets (AUC 0.78 and 0.78, respectively), but the combine-cN nomogram did not (AUC 0.64 and 0.60, in training and validation sets, respectively). We described a cN-based ALNM prediction model in breast cancer patients, presenting a novel efficient clinical decision nomogram for predicting ALNM.

HER-2-positive primary neuroendocrine neoplasms of the breast with signet ring feature: A case report and review of literature.

Background: Primary neuroendocrine neoplasm of the breast (BNEN) is an uncommon breast neoplasm, and in most cases, it presents as hormone receptors positive and HER-2 negative. Moreover, in neuroendocrine neoplasms (NENs), the signet ring feature is a rare morphological subtype, and only a few cases have been reported. Here, we report the case of a primary breast neuroendocrine neoplasm with an unusual signet ring cell appearance in this paper. The documentation of this case, combined with a review of the literature, may add to existing knowledge about the outcome and management of this rare tumor. Methods: In the present review, we describe a unique case of HER-2-positive primary BNEN with a signet ring feature that has not been reported in English. Additionally, we performed a literature search of the PubMed and Web of Science databases and calculated statistics for clinical data and follow-up. Results: Our literature search, excluding non-English literature, identified 15 articles with data from 24 cases, including ours. The mean age was 51.25 years (range, 30-79 years), and there were 13 male patients (54%) and 11 female patients (46%). Of the 24 cases, some cases (11/24) were associated with lymph node metastases, a few cases (6/24) had distant metastasis, and the vast majority of cases (23/24) occurred in the digestive system. Primary hepatic signet ring cell neuroendocrine tumor showed slow progression and good prognosis. Lymph node involvement was identified in one of eight (12.5%) documented cases, and one of eight (12.5%) reported cases presented with distant metastatic disease. However, the prognosis of neuroendocrine tumors with signet ring cells in the pancreas and stomach was poor. Lymph node involvement was identified in 9 of 15 (60%) documented cases, and 5 of 15 (33.3%) reported cases presented with distant metastatic disease. Conclusion: NENs with a signet ring feature is uncommon, and this is the first case report of its occurrence in the breast. Current knowledge is limited to anecdotal experience based on case reports and small case series. We provide a literature review to summarize knowledge about this rare entity.

Tetraspanin-29 activates Notch signaling by interacting with ADAM10 to enhance its activity in colorectal cancer.

ADAM10 acts upstream of Notch signaling and plays oncogenic roles in various cancers. Tetraspanin family proteins regulate ADAM10 trafficking and activity. Here, we aimed to investigate whether and how tetraspanin-29 modulates ADAM10 in colorectal cancer (CRC). We found that ADAM10 expression was upregulated in CRC tissues and this was cross-validated in the TCGA COAD data set. The ADAM10 protein level and its α-secretase activity were enhanced in CRC cell lines compared with control cell lines. Co-immunoprecipitation showed ADAM10 interacted with tetraspanin-29 in the LoVo cell line. Tetraspanin-29 knockdown reduced the cell surface trafficking and α-secretase activity of ADAM10. In addition, tetraspanin-29 knockdown inhibited Notch activity in a luciferase reporter assay and reduced the levels of cleaved Notch1 and Notch target genes such as HES2, c-MYC, and cyclin D3. Consistently, tetraspanin-29 overexpression increased cleaved Notch1 and this effect was blocked by ADAM10 inhibitors. The TCGA COAD data set confirmed the positive correlations of tetraspanin-29 with HES2, c-MYC, and cyclin D3. Thus, the tetraspanin-29/ADAM10/Notch pathway plays an important role in CRC.

A low-cost pathological image digitalization method based on 5 times magnification scanning.

Background: Digital pathology has aroused widespread interest in modern pathology. The key to digitalization is to scan the whole slide image (WSI) at high magnification. The file size of each WSI at 40 times magnification (40×) may range from 1 gigabyte (GB) to 5 GB depending on the size of the specimen, which leads to huge storage capacity, very slow scanning and network exchange, seriously increasing time and storage costs for digital pathology. Methods: We design a strategy to scan slides with low resolution (LR) (5×), and a superresolution (SR) method is proposed to restore the image details during diagnosis. The method is based on a multiscale generative adversarial network, which can sequentially generate three high-resolution (HR) images: 10×, 20×, and 40×. A dataset consisting of 100,000 pathological images from 10 types of human body systems is used for training and testing. The differences between the generated images and the real images have been extensively evaluated using quantitative evaluation, visual inspection, medical scoring, and diagnosis. Results: The file size of each 5× WSI is approximately 15 Megabytes. The peak-signal-to-noise ratios (PSNRs) of 10× to 40× generated images are 24.167±3.734 dB, 22.272±4.272 dB, and 20.436±3.845 dB, and the structural similarity (SSIM) index values are 0.845±0.089, 0.680±0.150, and 0.559±0.179, which are better than those of other SR networks and conventional digital zoom methods. Visual inspections show that the generated images have details similar to the real images. Visual scoring average with 0.95 confidence interval from three pathologists are 3.630±1.024, 3.700±1.126, and 3.740±1.095, respectively, and the P value of analysis of variance is 0.367, indicating the pathologists confirm that generated images include sufficient information for diagnosis. The average value of the Kappa test of the diagnoses of paired generated and real images is 0.990, meaning the diagnosis of generated images is highly consistent with that of the real images. Conclusions: The proposed method can generate high-quality 10×, 20×, 40× images from 5× images, which can effectively reduce the time and storage costs of digitalization up to 1/64 of the previous costs, which shows the potential for clinical applications and is expected to be an alternative digitalization method after large-scale evaluation.

Breast Cancer Molecular Subtype Prediction on Pathological Images with Discriminative Patch Selection and Multi-Instance Learning.

Molecular subtypes of breast cancer are important references to personalized clinical treatment. For cost and labor savings, only one of the patient's paraffin blocks is usually selected for subsequent immunohistochemistry (IHC) to obtain molecular subtypes. Inevitable block sampling error is risky due to the tumor heterogeneity and could result in a delay in treatment. Molecular subtype prediction from conventional H&E pathological whole slide images (WSI) using the AI method is useful and critical to assist pathologists to pre-screen proper paraffin block for IHC. It is a challenging task since only WSI-level labels of molecular subtypes from IHC can be obtained without detailed local region information. Gigapixel WSIs are divided into a huge amount of patches to be computationally feasible for deep learning, while with coarse slide-level labels, patch-based methods may suffer from abundant noise patches, such as folds, overstained regions, or non-tumor tissues. A weakly supervised learning framework based on discriminative patch selection and multi-instance learning was proposed for breast cancer molecular subtype prediction from H&E WSIs. Firstly, co-teaching strategy using two networks was adopted to learn molecular subtype representations and filter out some noise patches. Then, a balanced sampling strategy was used to handle the imbalance in subtypes in the dataset. In addition, a noise patch filtering algorithm that used local outlier factor based on cluster centers was proposed to further select discriminative patches. Finally, a loss function integrating local patch with global slide constraint information was used to fine-tune MIL framework on obtained discriminative patches and further improve the prediction performance of molecular subtyping. The experimental results confirmed the effectiveness of the proposed AI method and our models outperformed even senior pathologists, which has the potential to assist pathologists to pre-screen paraffin blocks for IHC in clinic.

eEF2K promotes PD-L1 stabilization through inactivating GSK3ß in melanoma.

BACKGROUND: Immune checkpoint blockade (ICB) targeting programmed death ligand-1 (PD-L1)/programmed cell death protein-1 (PD-1) pathway has become an attractive strategy for cancer treatment; however, unsatisfactory efficacy has limited its clinical benefits. Therefore, a more comprehensive understanding of the regulation of PD-L1 expression is essential for developing more effective cancer immunotherapy. Recent studies have revealed the important roles of eukaryotic elongation factor 2 kinase (eEF2K) in promoting epithelial-mesenchymal transition (EMT), angiogenesis, tumor cell migration and invasion; nevertheless, the exact role of eEF2K in the regulation of tumor immune microenvironment (TIME) remains largely unknown. METHODS: In this study, we used a cohort of 38 patients with melanoma who received anti-PD-1 treatment to explore the association between eEF2K expression and immunotherapy efficacy against melanoma. Immunoprecipitation-mass spectrometry analysis and in vitro assays were used to examine the role and molecular mechanism of eEF2K in regulating PD-L1 expression. We also determined the effects of eEF2K on tumor growth and cytotoxicity of CD8+ T cells in TIME in a mouse melanoma model. We further investigated the efficacy of the eEF2K inhibition in combination with anti-PD-1 treatment in vivo. RESULTS: High eEF2K expression is correlated with better therapeutic response and longer survival in patients with melanoma treated with PD-1 monoclonal antibody (mAb). Moreover, eEF2K protein expression is positively correlated with PD-L1 protein expression. Mechanistically, eEF2K directly bound to and inactivated glycogen synthase kinase 3 beta (GSK3ß) by phosphorylating it at serine 9 (S9), leading to PD-L1 protein stabilization and upregulation, and subsequently tumor immune evasion. Knockdown of eEF2K decreased PD-L1 expression and enhanced CD8+ T cell activity, thus dramatically attenuating murine B16F10 melanoma growth in vivo. Clinically, p-GSK3ß/S9 expression is positively correlated with the expressions of eEF2K and PD-L1, and the response to anti-PD-1 immunotherapy. Furthermore, eEF2K inhibitor, NH125 treatment or eEF2K knockdown enhanced the efficacy of PD-1 mAb therapy in a melanoma mouse model. CONCLUSIONS: Our results suggest that eEF2K may serve as a biomarker for predicting therapeutic response and prognosis in patients receiving anti-PD-1 therapy, reveal a vital role of eEF2K in regulating TIME by controlling PD-L1 expression and provide a potential combination therapeutic strategy of eEF2K inhibition with ICB therapy.

Primary breast CD20-positive extranodal NK/T cell lymphoma with stomach involvement: a case report and literature review.

BACKGROUND: We present a unique case of primary breast CD20-positive extranodal NK/T cell lymphoma with stomach involvement in a young Chinese female patient. CASE PRESENTATION: The patient presented with a mass in her right breast that rapidly increased in size over approximately 2 months. Upper gastrointestinal endoscopy showed a giant serpentine ulcer in the stomach. Biopsy was performed, and microscopic inspection revealed that the fibrous tissue was diffusely involved by medium to large abnormal lymphocytes. The cytoplasm was low to moderate. The tumor cells had irregular nuclei and inconspicuous nucleoli. The lymphoid cells were strongly immunoreactive to CD20, CD3, CD4, CD56, TIA-1, EBER, and Ki-67 (90%). Epstein-Barr virus genomes were also found in tumor cells by in situ hybridization. A whole-body positron emission tomography (PET)-CT scan revealed intense FDG uptake in the right breast and greater curvature of the stomach. Monoclonal rearrangements of the T cell receptor (TCR-γ) and immunoglobulin heavy chain (IgH) were identified by genetic analysis. Whole-genome next-generation sequencing was performed, and up to 12 gene mutations, including a frameshift mutation in exon 4 of the BCOR (G97Rfs*87; 44.3%) gene and a base substitution mutation (Q61H 17.6%) in exon 3 of the KRAS gene, were detected. Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed using the database for annotation, visualization, and integrated discovery, which showed that rare primary breast CD20-positive extranodal NK/T cell lymphoma had a unique genetic background compared with diffuse large B cell lymphoma and extranodal NK/T cell lymphoma without CD20 expression. The patient received four cycles of the modified SMILE regimen. The second whole-body PET-CT scan revealed that the right breast mass was significantly smaller than before; additionally, FDG uptake in the stomach wall disappeared. CONCLUSIONS: Systemic examination, extensive immunohistochemistry, and molecular profiling are essential for an accurate diagnosis. More similar cases are required to clarify the biological pathways and even the potential molecular mechanisms of rare lymphomas, which may help direct further treatment.

Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images.

Machine-assisted pathological recognition has been focused on supervised learning (SL) that suffers from a significant annotation bottleneck. We propose a semi-supervised learning (SSL) method based on the mean teacher architecture using 13,111 whole slide images of colorectal cancer from 8803 subjects from 13 independent centers. SSL (~3150 labeled, ~40,950 unlabeled; ~6300 labeled, ~37,800 unlabeled patches) performs significantly better than the SL. No significant difference is found between SSL (~6300 labeled, ~37,800 unlabeled) and SL (~44,100 labeled) at patch-level diagnoses (area under the curve (AUC): 0.980 ± 0.014 vs. 0.987 ± 0.008, P value = 0.134) and patient-level diagnoses (AUC: 0.974 ± 0.013 vs. 0.980 ± 0.010, P value = 0.117), which is close to human pathologists (average AUC: 0.969). The evaluation on 15,000 lung and 294,912 lymph node images also confirm SSL can achieve similar performance as that of SL with massive annotations. SSL dramatically reduces the annotations, which has great potential to effectively build expert-level pathological artificial intelligence platforms in practice.

Purified Vitexin Compound 1 Serves as a Promising Antineoplastic Agent in Ovarian Cancer.

Ovarian cancer is a common gynecologic aggressive neoplasm. The mortality of ovarian cancer is top among gynecologic malignancies due to the insidious onset, atypical early symptoms, and chemoresistance. Therefore, it is urgent to seek another promising treatment for ovarian cancer. Purified vitexin compound 1 (VB1) is a kind of neolignan from the seed of traditional Chinese herb vitex negundo that possessed diverse pharmacological effects. VB1 can exhibit anti-neoplastic activities against various cancers. However, the role of VB1 in ovarian cancer treatment has not been elaborated, and the mechanism is unknown. The aim of this study was to investigate the therapeutic effects of VB1 in ovarian cancer cells both in vitro and in vivo, along with the molecular mechanism of action. In vitro, VB-1 can effectively suppress the proliferation, induce apoptosis, and block cell cycle at G2/M phase with a concentration dependent manner in ovarian cancer cells. Western blot assay showed that VB1 induce apoptosis via upregulating expression of cleaved-caspase3 and block cell cycle at G2/M phase through upregulating expression of P21. Meanwhile, VB1 can effectively inhibit tumor growth in xenograft mouse model. Our research indicated that VB1 can significantly exert its anti-neoplastic effects and may represent a new class of agents in ovarian cancer therapy.

MoS2-based nanocomposites for cancer diagnosis and therapy.

Molybdenum is a trace dietary element necessary for the survival of humans. Some molybdenum-bearing enzymes are involved in key metabolic activities in the human body (such as xanthine oxidase, aldehyde oxidase and sulfite oxidase). Many molybdenum-based compounds have been widely used in biomedical research. Especially, MoS2-nanomaterials have attracted more attention in cancer diagnosis and treatment recently because of their unique physical and chemical properties. MoS2 can adsorb various biomolecules and drug molecules via covalent or non-covalent interactions because it is easy to modify and possess a high specific surface area, improving its tumor targeting and colloidal stability, as well as accuracy and sensitivity for detecting specific biomarkers. At the same time, in the near-infrared (NIR) window, MoS2 has excellent optical absorption and prominent photothermal conversion efficiency, which can achieve NIR-based phototherapy and NIR-responsive controlled drug-release. Significantly, the modified MoS2-nanocomposite can specifically respond to the tumor microenvironment, leading to drug accumulation in the tumor site increased, reducing its side effects on non-cancerous tissues, and improved therapeutic effect. In this review, we introduced the latest developments of MoS2-nanocomposites in cancer diagnosis and therapy, mainly focusing on biosensors, bioimaging, chemotherapy, phototherapy, microwave hyperthermia, and combination therapy. Furthermore, we also discuss the current challenges and prospects of MoS2-nanocomposites in cancer treatment.

Skip participates in formation and lipid metabolism of beige adipose and might mediate the effects of SIRT1 activator BTM-0512 on beige remodeling.

Dissipating energy by activating thermogenic adipose to combating obesity attracts many interests. Ski-interacting protein (Skip) has been known to play an important role in cell proliferation and differentiation, but whether it participates in energy metabolism is not known. Our previous study revealed that BTM-0512 could induce beige adipose formation, accompanying with up-regulation of Skip, but the role of Skip in metabolism was unknown. In this study, we mainly investigated whether Skip was involved in beige remodeling of subcutaneous white preadipocytes as well as in lipid metabolism of differentiated beige adipocytes. The results showed that in high fat diet-induced obesity mice, the protein levels of Skip in subcutaneous and visceral white adipose as well as in brown adipose were all down-regulated, especially in subcutaneous white adipose. Then we cultured subcutaneous adipose derived-stem cells (ADSCs) and found knock-down of Skip (siSkip) inhibited the expressions of thermogenic adipose specific genes including PRDM16 and UCP1 in both undifferentiated ADSCs and differentiated beige adipocytes, which could abolish the effects of BTM-0512 on beige remodeling. We further observed that siSkip affected multiple rate-limiting enzymes in lipid metabolism. The expressions of ACC, GPAT-1, HSL and ATGL were down-regulated, while CPT1α expression was up-regulated by siSkip. The expression of AMPK was also decreased by siSkip. In conclusion, our study demonstrated that Skip might play an important role in the beige remodeling of white adipocytes as well as lipid metabolism of beige adipose.

Long-term consumption of recycled cooking oil induces cell death and tissue damage.

Recycled cooking oil (RCO) is widely used in many small restaurants. However, the health risk posed by long-term consumption of RCO is unclear. In this study, C57 mice were treated with RCO for 34 weeks. Organ coefficients of the liver, stomach, and kidney were found to be decreased. H&E staining revealed overt lesions in the pancreas, liver, kidney, esophagus, duodenum, and ileum of RCO-treated mice. Immunohistochemistry showed significant DNA damage in the duodenum and ileum and apoptosis in the lungs of the RCO-treated mice. Immunoblotting showed elevated levels of γ-H2AX, Bcl-2/Bax, TNFα, cleaved Caspase-3 and poly ADP-ribose polymerase (PARP). Increased levels of lactate dehydrogenase (LDH) and decreased levels of succinate dehydrogenase (SDH) were also detected. These findings suggest that long-term consumption of RCO produces various toxicities in mice with important implications for humans. DNA damage followed by mitochondria-associated apoptosis, and necrosis is likely to contribute to the toxicities.

Combined treatment of mitoxantrone sensitizes breast cancer cells to rapalogs through blocking eEF-2K-mediated activation of Akt and autophagy.

Oncogenic activation of the mTOR signaling pathway occurs frequently in tumor cells and contributes to the devastating features of cancer, including breast cancer. mTOR inhibitors rapalogs are promising anticancer agents in clinical trials; however, rapalogs resistance remains an unresolved clinical challenge. Therefore, understanding the mechanisms by which cells become resistant to rapalogs may guide the development of successful mTOR-targeted cancer therapy. In this study, we found that eEF-2K, which is overexpressed in cancer cells and is required for survival of stressed cells, was involved in the negative-feedback activation of Akt and cytoprotective autophagy induction in breast cancer cells in response to mTOR inhibitors. Therefore, disruption of eEF-2K simultaneously abrogates the two critical resistance signaling pathways, sensitizing breast cancer cells to rapalogs. Importantly, we identified mitoxantrone, an admitted anticancer drug for a wide range of tumors, as a potential inhibitor of eEF-2K via a structure-based virtual screening strategy. We further demonstrated that mitoxantrone binds to eEF-2K and inhibits its activity, and the combination treatment of mitoxantrone and mTOR inhibitor resulted in significant synergistic cytotoxicity in breast cancer. In conclusion, we report that eEF-2K contributes to the activation of resistance signaling pathways of mTOR inhibitor, suggesting a novel strategy to enhance mTOR-targeted cancer therapy through combining mitoxantrone, an eEF-2K inhibitor.