NEW FINDINGS — CANCER
Breast Cancer and Brain Metastasis Even though we’ve gotten better at treating breast cancer, there is still a concern that breast cancer cells can survive and spread to other parts of the body after treatment. Nearly half of
Battling T Cell Burnout T cells are a key part of the immune system and they help fight cancer by infiltrating tumors and attacking cancer cells. High levels of active T cells in and around tumors are linked to better survival rates and improved responses to immunotherapies. However, in the tumor
breast cancer patients who receive standard chemotherapies later develop cancer in other organs. Many treatments, like chemotherapy, have trouble reaching the brain because of a protective barrier, making the brain particularly vulnerable to metastasis. To better understand how breast cancer spreads to the brain, researchers studied small extracellular molecules released by cancer cells. These molecules, called microRNAs (miRNAs) regulate gene expression by binding to specific messenger RNAs (mRNAs) and preventing protein production. The team found that miR-199b-5p is uniquely secreted by breast cancer cells. This miRNA was found to be more abundant in breast cancer patients with brain metastases than those without, and was previously reported to be more prevalent in metastatic brain tumors than tumors originating in the brain. The brain has specialized cells called neurons and astrocytes that work together for proper brain functioning. Astrocytes convert the amino acid glutamate into glutamine and secrete lactate to fuel neurons. However, miR-199b-5p disrupts this metabolic pathway, increasing extracellular glutamate and lactate levels. These excess compounds are harmful to brain cells and actually provide fuel for the cancer cells to grow and spread. Researchers discovered that reversing miR-199b-5p's effects restored normal metabolic activity and reduced metastasis This suggests that targeting this pathway could be a promising therapeutic strategy for preventing brain me- tastasis among patients with breast cancer. n REFERENCE: Ruan, X., et al. Breast cancer cell-secreted miR-199b-5p hijacks neuromet- abolic coupling to promote brain metastasis. Nature Communications (2024) 15, 4549. https://doi.org/10.1038/s41467-024-48740-0
environment, T cells face constant stimulation and limited energy resources, leading to decreased func- tion or cell death. A recent study identified the protein METRNL as a key factor in this process. Previously
known for its role in glucose metabolism and heat generation during exercise or cold exposure, METRNL was found to play a critical role in T cell dysregulation. The study showed that overstimulated T cells release excessive METRNL, which in turn reduces the ability of the cell’s mitochondria to produce energy. Without sufficient energy, T cells lose function and die. In lab experiments, most T cells initiated the cell death process within 48 hours of being exposed to METRNL. Importantly, researchers discovered that removing METRNL in cancer cell models slowed tumor growth significantly. This finding suggests that targeting METRNL could enhance T cell activity and improve cancer treatment outcomes. Developing therapies to block METRNL, either alone or alongside immunotherapies, could be a promising approach to strengthen the immune response against cancer. n REFERENCE: Jackson, CM., et al. The cytokine Meterorin-like inhibits anti-tumor CD8+ T cell responses by disrupting mitochondrial function. Immunity. (2024) 57:8, 1864-1877. https://www.pubmed.ncbi.nlm.nih.gov/39111315 Smarter Cancer Treatments Genetic testing is becoming increasingly important in oncology and cancer treatment. DNA-based tests identify specific changes in the DNA sequence in tumor cells, while RNA-based tests reveal how the changes affect how genes work. This molecular-level view of cancer helps physicians choose the best treatments for each patient. However, tumors are made up of a mixture of different cells with unique genetic profiles. Currently, tumor genetic testing analyzes an average of all of these cells. Analyzing individual cancer cells is ideal for fully understanding a tumor but remains expensive and clinically inaccessible. The massive amounts of data generated from single-cell analysis also requires advanced bioinformatics tools to interpret and guide treatment decisions in a scalable way. Researchers at the National Institutes of Health recently devel- oped an artificial intelligence (AI) tool, PERCEPTION (PERsonalized single-Cell Expression-based Planning for Treatments IN ONcology), to predict patient responses to cancer drugs. The AI model was trained on bulk RNA sequencing data from many tumors and refined with single-cell data, targeting 44 FDA-approved cancer drugs.
PERCEPTION was validated using patient datasets for multiple myeloma and breast cancer, accurately predicting individual and overall patient responses to both single drugs and drug combina- tions. A key finding was that even if most cells respond to a drug, a few resistant cells can make the treatment ineffective, emphasizing the importance of targeting the most resistant cells. These findings pave the way for further development of this and other AI-developed tools to leverage genomic data and advance precision medicine. n REFERENCE: Sinha, S., et al. PERCEPTION predicts patient response and resistance to treatment using single-cell transcriptomics of their tumors. Nat Cancer (2024) 5, 938–952. https://doi.org/10.1038/s43018-024-00756-7
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