Researchers have found a remedy to prevent metastatic spread of breast cancer, a leading cause of death among women.
The findings, published in the journal Nature Communications, showed that by inhibiting a protein called TAK1, the researchers were able to reduce lung metastasis in mice with triple-negative breast cancer (TNBC). TNBC is the deadliest type of breast cancer that comprises 20 per cent of breast cancer cases and is particularly difficult to treat.
"For this subtype of breast cancer, few treatment options are available to target metastasis, and typically, these treatments are associated with high toxicity," said co-author Min Yu, Assistant Professor from the University of Southern California.
"A better understanding of tumour cells and their interactions with organs and tissues could help us design targeted therapies specific for metastasis," Yu added. According to the study, TAK1 enables malignant cells from the breast to survive in the lungs and form new metastatic tumours.
Metastasis are the most common cause of cancer-related death. There is already a potential drug, called OXO - that can inhibit TAK1-- and presumably make it much more difficult for breast cancer cells to form lung metastases. However, OXO is not stable in the blood, and therefore would not work in patients, the researcher said.
The researchers developed a nanoparticle - consisting of a tiny fatty sac - that works like a smart bomb to carry drugs through the bloodstream and deliver them directly to tumours. The scientists loaded this nanoparticle with OXO, and used it to treat mice that had been injected with human breast cancer cells. While OXO did not shrink primary tumours in the breast, it greatly reduced metastatic tumours in the lungs with minimal toxic side effects.
"For patients with triple-negative breast cancer, systemic chemotherapies are largely ineffective and highly toxic. So nanoparticles are a promising approach for delivering more targeted treatments, such as OXO, to stop the deadly process of metastasis," Yu noted.
(With IANS inputs)
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