Interplay between key proteins could serve as a target for cancer treatment

Immunotherapy uses a person’s own immune system to fight cancer. Immune checkpoint inhibitors are one class of immunotherapy that block specific proteins from slowing the immune response. As a result, immune cells become more active and can more effectively kill cancer cells. However, most patients either respond poorly to checkpoint inhibitors or eventually become resistant to the treatment.
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Molecular mechanism that initiates colon cancer opens new path for prevention

Colorectal cancer is the third most diagnosed type of cancer worldwide. Up to 80% of the cases are related to environmental factors and lifestyle, such as poor diet, sedentarism, obesity, smoking or excessive alcohol consumption. Most colorectal cancers arise from adenomatous polyps, a precancerous lesion that may progress to a malignant tumor unless it is detected and removed in time.
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Advanced imaging, targeted therapy help men with prostate cancer safely defer surgery and radiation therapy

In a new study led by the UCLA Health Jonsson Comprehensive Cancer Center, investigators show that using advanced MRI imaging and targeted focal therapy can help many men with low- to intermediate-risk prostate cancer safely stay on active surveillance long-term, helping avoid follow-up biopsies and delay—or even avoid—invasive treatments like surgery or radiation.
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Protein linked to immunotherapy resistance in kidney cancer

A protein identified by researchers at UT Southwestern Medical Center may drive resistance to immune checkpoint inhibitors, a widely used form of immunotherapy to treat cancer. The findings, published in Communications Medicine, link glycoprotein non-metastatic melanoma protein B (GPNMB) to relapse after treatment and suggest it may help tumors evade immune surveillance in metastatic renal cell carcinoma.
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AI tool automates liver tumor detection and monitoring

Investigators of the Vall d’Hebron Institute of Oncology’s (VHIO) Radiomics Group, led by Raquel Perez-Lopez, have developed SALSA (System for Automatic Liver tumor Segmentation And detection), a fully automated deep learning-driven tool for the precise and completely automated detection and monitoring of liver tumors (hepatocellular carcinoma). Results of this work have been published in Cell Reports Medicine.
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