Cancer cell

About: Cancer cell is a research topic. Over the lifetime, 93402 publications have been published within this topic receiving 3512390 citations. The topic is also known as: cancerous cell & tumor cell.

Cannabinoid action induces autophagy-mediated cell death through stimulation of ER stress in human glioma cells

Abstract: Autophagy can promote cell survival or cell death, but the molecular basis underlying its dual role in cancer remains obscure. Here we demonstrate that delta(9)-tetrahydrocannabinol (THC), the main active component of marijuana, induces human glioma cell death through stimulation of autophagy. Our data indicate that THC induced ceramide accumulation and eukaryotic translation initiation factor 2alpha (eIF2alpha) phosphorylation and thereby activated an ER stress response that promoted autophagy via tribbles homolog 3-dependent (TRB3-dependent) inhibition of the Akt/mammalian target of rapamycin complex 1 (mTORC1) axis. We also showed that autophagy is upstream of apoptosis in cannabinoid-induced human and mouse cancer cell death and that activation of this pathway was necessary for the antitumor action of cannabinoids in vivo. These findings describe a mechanism by which THC can promote the autophagic death of human and mouse cancer cells and provide evidence that cannabinoid administration may be an effective therapeutic strategy for targeting human cancers.

In situ sprayed bioresponsive immunotherapeutic gel for post-surgical cancer treatment

Abstract: Cancer recurrence after surgical resection remains a significant cause of treatment failure. Here, we have developed an in situ formed immunotherapeutic bioresponsive gel that controls both local tumour recurrence after surgery and development of distant tumours. Briefly, calcium carbonate nanoparticles pre-loaded with the anti-CD47 antibody are encapsulated in the fibrin gel and scavenge H+ in the surgical wound, allowing polarization of tumour-associated macrophages to the M1-like phenotype. The released anti-CD47 antibody blocks the ‘don’t eat me’ signal in cancer cells, thereby increasing phagocytosis of cancer cells by macrophages. Macrophages can promote effective antigen presentation and initiate T cell mediated immune responses that control tumour growth. Our findings indicate that the immunotherapeutic fibrin gel ‘awakens’ the host innate and adaptive immune systems to inhibit both local tumour recurrence post surgery and potential metastatic spread. A gel with therapeutic nanoformulation that can be sprayed at the tumour resection site after surgery activates immune response in the tissue microenviroment, inhibiting tumour recurrence and potential metastasis.

The IGF-1 receptor in cancer biology.

Abstract: The type 1 insulin-like growth factor receptor (IGF-1R) plays an important role in the establishment and maintenance of the transformed phenotype. It also has a strong antiapoptotic activity and has a significant influence on the control of cell and body size. Downregulation of the IGF-1R leads to massive apoptosis of cancer cells. These characteristics make it an attractive target for anticancer therapy.

Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data.

Abstract: Malignant tumors do not only contain cancer cells. Normal cells from the body also infiltrate tumors. These often include a variety of immune cells that can help detect and kill cancer cells. Many evidences suggest that the proportion of different immune cell types in a tumor can affect tumor growth and which treatments are effective. Researchers often study tumors by measuring the expression of genes, i.e., which genes are active in tumors. However, the proportion of different cell types in the tumor is often not measured for tumors studied at the gene expression level. Racle et al. have now demonstrated that a new computer-based tool can accurately detect all the main cell types in a tumor directly from the expression of genes in this tumor. The tool is called “Estimating the Proportion of Immune and Cancer cells” – or EPIC for short. It compares the level of expression of genes in a tumor with a library of the gene expression profiles from specific cell types that can be found in tumors and uses this information to predict how many of each type of cell are present. Experimental measurements of several human tumors confirmed that EPIC’s predictions are accurate. EPIC is freely available online. Since the active genes in tumors from many patients have already been documented together with clinical data, researchers could use EPIC to investigate whether the cell types in a tumor affect how harmful it is or how well a particular treatment works on it. In the future, this information could help to identify the best treatment for a particular patient and may reveal new genes that cause malignant tumors to develop and grow.