Anticancer Activity of 2α, 3α, 19β, 23β-Tetrahydroxyurs-12-en-28-oic Acid (THA), a Novel Triterpenoid Isolated from Sinojackia sarcocarpa

BACKGROUND: Natural products represent an important source for agents of cancer prevention and cancer treatment. More than 60% of conventional anticancer drugs are derived from natural sources, particularly from plant-derived materials. In this study, 2α, 3α, 19β, 23β-tetrahydroxyurs-12-en-28-oic acid (THA), a novel triterpenoid from the leaves of Sinojackia sarcocarpa, was isolated, and its anticancer activity was investigated both in vitro and in vivo. PRINCIPAL FINDINGS: THA possessed potent tumor selected toxicity in vitro. It exhibited significantly higher cytotoxicity to the cancer cell lines A2780 and HepG2 than to IOSE144 and QSG7701, two noncancerous cell lines derived from ovary epithelium and liver, respectively. Moreover, THA showed a dose-dependent inhibitory effect on A2780 ovary tumor growth in vivo in nude mice. THA induced a dose-dependent apoptosis and G2/M cell cycle arrest in A2780 and HepG2 cells. The THA-induced cell cycle arrest was accompanied by a downregulation of Cdc2. The apoptosis induced by THA was evident by induction of DNA fragmentation, release of cytoplasmic Cytochrome c from mitochondria, activation of caspases, downregulation of Bcl-2 and upregulation of Bax. CONCLUSION: The primary data indicated that THA exhibit a high toxicity toward two cancer cells than their respective non-cancerous counterparts and has a significant anticancer activity both in vitro and in vivo. Thus, THA and/or its derivatives may have great potential in the prevention and treatment of human ovary tumors and other malignancies

Knockdown of LncRNA MAPT-AS1 inhibites proliferation and migration and sensitizes cancer cells to paclitaxel by regulating MAPT expression in ER-negative breast cancers

Abstract Background MAPT-AS1, a long non-coding RNA, has not been reported in any previous research about its function in cancers. In this study, we investigated the role of MAPT-AS1 in the progression and paclitaxel resistance in breast cancer, and the regulation between MAPT-AS1 and its natural comparable sense transcripts MAPT. Methods We analysed the breast cancer patients’ clinical information and explored the function of MAPT-AS1 by gain- and loss-of function assays in vitro and in vivo. The regulation between MAPT-AS1 and MAPT was confirmed by gene expression analysis and rescue assays. To verify the hypothesis that MAPT-AS1 and MAPT might form a duplex structure, we performed RT-PCR assays on RNA after α-amanitin treatment. Results By analysing the breast cancer patients’ clinical information from the TCGA database, we found that ER-negative patients with younger age (< 60), larger tumors (≥ 2 cm), metastatic lymph nodes and stages (III–IV) had higher expression of MAPT-AS1. MAPT-AS1 is correlated with the cell growth, invasiveness and paclitaxel resistance by regulating its natural comparable sense transcripts MAPT in ER-negative breast cancer cells. The result revealed that MAPT-AS1 overexpression could partially protect the MAPT mRNA from degradation, while MAPT-AS1 knockdown decreased the stability of MAPT mRNA. Meanwhile, MAPT knockdown decreased the expression of MAPT-AS1 mRNA. MAPT-AS1 expressed coordinately with MAPT in breast tumor tissues. Conclusion Our study is the first to report a novel lncRNA MAPT-AS1 in human cancer. ER-negative patients with younger age (< 60), larger tumors (≥ 2 cm), metastatic lymph nodes and stages (III–IV) had higher expression of MAPT-AS1. MAPT-AS1 is correlated with the cell growth, invasiveness and paclitaxel resistance in ER-negative breast cancer cells through antisense pairing with MAPT. MAPT-AS1 may serve as a potential therapeutic target in ER-negative breast cancers

Integration of immobilized trypsin bead beds for protein digestion within a microfluidic chip incorporating capillary electrophoresis separations and an electrospray mass spectroscopy interface: Rapid Comm.Mass Spectrom.

NRC publication: Ye

Mechanisms underlying neutrophils adhesion to triple-negative breast cancer cells via CD11b-ICAM1 in promoting breast cancer progression

Abstract Background Triple-negative breast cancer (TNBC) is recognized as the most aggressive and immunologically infiltrated subtype of breast cancer. A high circulating neutrophil-to-lymphocyte ratio (NLR) is strongly linked to a poor prognosis among patients with breast cancer, emphasizing the critical role of neutrophils. Although the involvement of neutrophils in tumor metastasis is well documented, their interactions with primary tumors and tumor cells are not yet fully understood. Methods Clinical data were analyzed to investigate the role of neutrophils in breast cancer. In vivo mouse model and in vitro co-culture system were used for mechanism researches. Blocking experiments were further performed to identify therapeutic agents against TNBC. Results TNBC cells secreted GM-CSF to sustain the survival of mature neutrophils and upregulated CD11b expression. Through CD11b, neutrophils specifically binded to ICAM1 on TNBC cells, facilitating adhesion. Transcriptomic sequencing combined with human and murine functional experiments revealed that neutrophils, through direct CD11b-ICAM1 interactions, activated the MAPK signaling pathway in TNBC cells, thereby enhancing tumor cell invasion and migration. Atorvastatin effectively inhibited ICAM1 expression in tumor cells, and tumor cells with ICAM1 knockout or treated with atorvastatin were unresponsive to neutrophil activation. The MAPK pathway and MMP9 expression were significantly inhibited in the tumor tissues of TNBC patients treated with atorvastatin. Conclusions Targeting CD11b-ICAM1 with atorvastatin represented a potential clinical approach to reduce the malignant characteristics of TNBC. Graphical Abstrac

Osthole inhibits triple negative breast cancer cells by suppressing STAT3

Abstract Background Triple-negative breast cancer (TNBC) is an aggressive subgroup of human breast cancer. Patients with TNBC have poor clinical outcome as they are non-responsive to current targeted therapies. There is an urgent need to identify new therapeutic targets and develop more effective treatment options for TNBC patients. Osthole, a natural product from C. monnieri, has been shown to inhibit certain cancer cells. However, the mechanisms of action as well as its effect on TNBC cells are not currently known. Methods We investigated the effect of osthole in cultured TNBC cells as well as in a xenograft model of TNBC growth. We also used a high-throughput proteomics platform to identify the direct binding protein of osthole. Results We found that osthole inhibited the growth of a panel of TNBC cells and induced apoptosis in both cultured cells and TNBC xenografts. We used a high-throughput proteomics platform and identified signal transducer and activator of transcription 3 (STAT3) as a potential binding protein of osthole. We further show that osthole suppressed STAT3 in TNBC cells to inhibit growth and induce apoptosis. Overexpressing STAT3 in TNBC reduced the effectiveness of osthole treatment. Conclusions These results provide support for osthole as a potential new therapeutic agent for the management of TNBC. Moreover, our results indicate that STAT3 may be targeted for the development of novel anti-TNBC drugs

MOESM1 of Knockdown of LncRNA MAPT-AS1 inhibites proliferation and migration and sensitizes cancer cells to paclitaxel by regulating MAPT expression in ER-negative breast cancers

Additional file 1: Figure S1. a MAPT-AS1 expression in breast cancer patients from the TCGA database. b MAPT-AS1 expression level was determined in the breast cell lines by qRT-PCR

Diagnosis of Benign and Malignant Breast Lesions on DCE‐MRI by Using Radiomics and Deep Learning With Consideration of Peritumor Tissue

BackgroundComputer-aided methods have been widely applied to diagnose lesions detected on breast MRI, but fully-automatic diagnosis using deep learning is rarely reported.PurposeTo evaluate the diagnostic accuracy of mass lesions using region of interest (ROI)-based, radiomics and deep-learning methods, by taking peritumor tissues into consideration.Study typeRetrospective.PopulationIn all, 133 patients with histologically confirmed 91 malignant and 62 benign mass lesions for training (74 patients with 48 malignant and 26 benign lesions for testing).Field strength/sequence3T, using the volume imaging for breast assessment (VIBRANT) dynamic contrast-enhanced (DCE) sequence.Assessment3D tumor segmentation was done automatically by using fuzzy-C-means algorithm with connected-component labeling. A total of 99 texture and histogram parameters were calculated for each case, and 15 were selected using random forest to build a radiomics model. Deep learning was implemented using ResNet50, evaluated with 10-fold crossvalidation. The tumor alone, smallest bounding box, and 1.2, 1.5, 2.0 times enlarged boxes were used as inputs.Statistical testsThe malignancy probability was calculated using each model, and the threshold of 0.5 was used to make a diagnosis.ResultsIn the training dataset, the diagnostic accuracy was 76% using three ROI-based parameters, 84% using the radiomics model, and 86% using ROI + radiomics model. In deep learning using the per-slice basis, the area under the receiver operating characteristic (ROC) was comparable for tumor alone, smallest and 1.2 times box (AUC = 0.97-0.99), which were significantly higher than 1.5 and 2.0 times box (AUC = 0.86 and 0.71, respectively). For per-lesion diagnosis, the highest accuracy of 91% was achieved when using the smallest bounding box, and that decreased to 84% for tumor alone and 1.2 times box, and further to 73% for 1.5 times box and 69% for 2.0 times box. In the independent testing dataset, the per-lesion diagnostic accuracy was also the highest when using the smallest bounding box, 89%.Data conclusionDeep learning using ResNet50 achieved a high diagnostic accuracy. Using the smallest bounding box containing proximal peritumor tissue as input had higher accuracy compared to using tumor alone or larger boxes.Level of evidence3 Technical Efficacy: Stage 2

PDE4DIP contributes to colorectal cancer growth and chemoresistance through modulation of the NF1/RAS signaling axis

Abstract Phosphodiesterase 4D interacting protein (PDE4DIP) is a centrosome/Golgi protein associated with cyclic nucleotide phosphodiesterases. PDE4DIP is commonly mutated in human cancers, and its alteration in mice leads to a predisposition to intestinal cancer. However, the biological function of PDE4DIP in human cancer remains obscure. Here, we report for the first time the oncogenic role of PDE4DIP in colorectal cancer (CRC) growth and adaptive MEK inhibitor (MEKi) resistance. We show that the expression of PDE4DIP is upregulated in CRC tissues and associated with the clinical characteristics and poor prognosis of CRC patients. Knockdown of PDE4DIP impairs the growth of KRAS-mutant CRC cells by inhibiting the core RAS signaling pathway. PDE4DIP plays an essential role in the full activation of oncogenic RAS/ERK signaling by suppressing the expression of the RAS GTPase-activating protein (RasGAP) neurofibromin (NF1). Mechanistically, PDE4DIP promotes the recruitment of PLCγ/PKCε to the Golgi apparatus, leading to constitutive activation of PKCε, which triggers the degradation of NF1. Upregulation of PDE4DIP results in adaptive MEKi resistance in KRAS-mutant CRC by reactivating the RAS/ERK pathway. Our work reveals a novel functional link between PDE4DIP and NF1/RAS signal transduction and suggests that targeting PDE4DIP is a promising therapeutic strategy for KRAS-mutant CRC