Accumulating evidence suggests that breast cancer originates from cancer stem cells (CSCs), which comprise a small percentage of the overall tumor but are highly tumorigenic and pluripotent with unlimited proliferation potential. Furthermore, CSCs are highly resistant to conventional treatment, which may explain certain difficulties in treating cancer with current therapy options. In this study, the third generation oncolytic herpes simplex virus (oHSV) vector G47∆ effectively killed different subtypes of breast cancer cells, with more than 98% of the tumor cells killed by Day 5. Moreover, G47∆ targeted equally non-cancer stem cells (NCSCs) and CSCs which showed resistance to paclitaxel. We demonstrated that G47∆ effectively replicated and spread among CSCs. G47∆ also impaired the self-renewal ability of CSCs, as the viable cells were unable to form secondary tumor spheres. We also showed that G47∆ was able to induce the regression of tumor xenografts in BALB/c nude mice and demonstrated the ability of G47∆ to synergize with paclitaxel by killing both NCSCs and CSCs, suggesting that oHSV may be an effective treatment modality for patients with breast cancer.
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http://dx.doi.org/10.3892/or.2012.2211 | DOI Listing |
Discov Oncol
January 2025
Department of Breast Surgery, The First Affiliated Hospital of Harbin Medical University, No. 23, Youzheng Street, Nangang District, Harbin, 150001, China.
Cancer vaccines are promising as an effective means of stimulating the immune system to clear tumors as well as to establish immune surveillance. In this paper, we discuss the main platforms and current status of cancer vaccines and propose a new cancer vaccine platform, the cytosolic vesicle vaccine. This vaccine has a unique structure that can integrate antigen and adjuvant carriers to improve the delivery efficiency and immune activation ability, which brings new ideas for cancer vaccine design.
View Article and Find Full Text PDFUpdates Surg
January 2025
Department of Radiation Oncology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Whether primary lesion surgery improves survival in patients with de novo metastatic breast cancer (dnMBC) is inconclusive. We aimed to establish a prognostic prediction model for patients with de novo metastatic breast invasive ductal carcinoma (dnMBIDC) based on machine learning algorithms and to investigate the value of primary site surgery. The data used in our study were obtained from the Surveillance, Epidemiology, and End Results database (SEER, 2010-2021) and the First Affiliated Hospital of Nanchang University (1st-NCUH, June 2013-June 2023).
View Article and Find Full Text PDFMol Biol Rep
January 2025
Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.
Background: Exosomes are extracellular vesicles released by cells that mediate intercellular communication and actively participate in cancer progression, metastasis, and regulation of immune response within the tumour microenvironment. Inhibiting exosome release from cancer cells could be employed as a therapeutic against cancer.
Methods And Results: In the present study, we have studied the effects of Acorus calamus in inhibiting exosome secretion via targetting Rab27a and neutral sphingomyelinase 2 (nSMase2) in HER2-positive (MDA-MB-453), hormone receptor-positive (MCF-7) and triple-negative breast cancer (MDA-MB-231) cells.
Discov Nano
January 2025
Department of Mathematics and Physics "Ennio De Giorgi", University of Salento, Via Arnesano, 73100, Lecce, LE, Italy.
Breast cancer is the most common cancer among women, with over 1 million new cases and around 400,000 deaths annually worldwide. This makes it a significant and costly global health challenge. Standard treatments like chemotherapy and radiotherapy, often used after mastectomy, show varying effectiveness based on the cancer subtype.
View Article and Find Full Text PDFInt J Comput Assist Radiol Surg
January 2025
Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Martensstr. 3, 91058, Erlangen, Bayern, Germany.
Purpose: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, attention-guided erasing (AGE), across various transfer learning classification tasks for breast abnormality classification in mammography.
Methods: AGE utilizes attention head visualizations from DINO self-supervised pretraining to weakly localize regions of interest (ROI) in images.
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