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Non-Invasive Detection of Clinically Significant Prostate Cancer Using Circulating Tumor Cells

A new and simple blood test has been found to efficiently and accurately detect the presence of aggressive prostate cancer, according to a new study (J Urol 2019; doi: 10.1097/JU.0000000000000475). In combination with the current prostate-specific antigen (PSA) test, the new test could help men avoid unnecessary and invasive biopsies, overdiagnosis, and overtreatment. It detects early cancer cells, or circulating tumor cells (CTCs), that have left the original tumor and entered the bloodstream prior to spreading around the body. By measuring intact living cancer cells in the patient's blood, rather than the PSA protein which may be present in the blood for reasons other than cancer, it potentially provides a more accurate test for prostate cancer. The study looked at the use of the CTC test in 98 pre-biopsy patients and 155 newly diagnosed prostate cancer patients enrolled at St. Bartholomew's Hospital in London. The research team found that the presence of CTCs in pre-biopsy blood samples were indicative of the presence of aggressive prostate cancer, and efficiently and non-invasively predicted the later outcome of biopsy results. When the CTC tests were used in combination with the current PSA test, it was able to predict the presence of aggressive prostate cancer in subsequent biopsies with over 90 percent accuracy, better than any previously reported biomarkers. Additionally, the number and type of CTCs present in the blood were also indicative of the aggressiveness of the cancer. Focusing on more aggressive prostate cancer may reduce overtreatment and unnecessary biopsies for benign and non-aggressive conditions.



Proteomics of Melanoma Response to Immunotherapy Reveals Mitochondrial Dependence

In a new study, researchers set out to answer the question: Why do immunotherapy treatments greatly help some patients with melanoma but not affect 60 percent of metastatic melanoma patients? (Cell 2019; doi: 10.1016/j.cell.2019.08.012) The researchers compared the responses of 116 melanoma patients to immunotherapy-one group in which immunotherapy was successful and a second in which immunotherapy was not successful. Using proteomics, they discovered differences in the metabolism, or energy production process, of the cancer cells of the two groups. To better understand treatment resistance mechanisms, the scientists examined tumors taken from 116 patients. The proteomic comparison identified major differences between responders and non-responders to immunotherapy. In the responders, researchers found higher levels of proteins associated with lipid metabolism, which led to better recognition by the immune system. Researchers then examined their findings in melanoma tissue cultures and a mouse model of metastatic melanoma. Using genetic engineering, they were able to silence the mechanism responsible for fatty acid metabolism. Upon silencing this metabolic pathway, researchers reported the cancer cells managed to "hide" from T cells that are supposed to detect and destroy them. Cancer in those mouse models developed at a faster rate compared to the control group.



Spatial Optimization for Radiation Therapy of Brain Tumors

Researchers have developed a new model to optimize radiation therapy and significantly increase the number of tumor cells killed during treatment. The new mathematical model, outlined in a recent study, can use information about where the majority of the cells in a tumor are located, allowing for radiation treatment to be administered to the densest area (PLOS ONE 2019; doi: 10.1371/journal.pone.0217354). Much consideration is usually given to optimal scheduling and dosing when radiation therapy is being prescribed, but the researchers found the treatment could be far more effective at killing brain tumor cells if oncologists also use the information on cell density and irradiate the densest area of the tumor. In developing their mathematical model to spatially optimize radiation therapy in brain tumors, the researchers set a cap on the total dose a patient could receive throughout their treatment. They then divided the tumor into multiple portions: with the area most densely populated with cells being one portion and the remainder of cells the other. In some instances, they prescribed the dosage of radiation given to each portion, and in other cases they allowed the model to determine the best ratio. Given the results of their study, the researchers have proposed the following procedure for spatial optimization of radiation: image the tumor twice, determine the dose and treatment schedule, ascertain the physical limitations of the radiation apparatus, then optimize the first radiation fraction using their mathematical model. Finally, using the growth model deduced from the initial two images to simulate the development of the tumor cells between fractions, oncologists can use the derived cell density profile prior to each instance of radiation application as input to optimize the shape of the radiation beam.



Interferon Signaling Is Diminished With Age and Is Associated With Immune Checkpoint Blockade Efficacy in Triple-Negative Breast Cancer

To understand the influence of aging on the effectiveness of immune checkpoint blockade (ICB) therapy, researchers conducted preclinical studies using younger and older mice with triple-negative breast cancer (TNBC), finding that age affects the efficacy of ICB therapy (Cancer Discov 2019; doi: 10.1158/2159-8290.CD-18-1454). The team injected TNBC cell lines into young mice, aged 8-12 weeks, and old mice, aged 12-15 months. Once the mice formed palpable tumors, the researchers gave them four doses of one of two ICB drugs-anti-PD-L1 or anti-CTLA-4 antibodies. They also injected a group with control antibodies. They then measured the tumor growth over time. The study revealed that age had a huge effect on response to immunotherapy. The young mice experienced significant reduction in tumor growth and better overall survival rates in response to treatment than those who did not receive the treatment. Immunotherapy treatment did not significantly benefit the aged mice compared to those injected with the control. The investigators also interrogated the METABRIC database, which includes data on tumor samples from patients with TNBC. Gene markers that predicted responsiveness to ICB in the young mice were prevalent in younger patients, but not in older ones. They also found signs indicative of failure of the innate immune system in the tumors of both aged mice and in samples from older patients with TNBC, implying that this study could be relevant to the treatment of people as well. Those findings led the authors to test a new combination therapy. By combining ICB with a STING agonist, a drug that has immune activation properties, they found that tumors in aged mice now responded to ICB and the mice had improved survival.


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