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Immunotherapy Outcome Predictors: Scientists Discover Methods to Forecast Responsiveness

Immunotherapy Outcomes Prediction: Scientists Discover Methods to Forecast Responses

Investigators are exploring means to enhance the potency of immunotherapy in combating malignant...
Investigators are exploring means to enhance the potency of immunotherapy in combating malignant tumors, as represented by this image from SAUL LOEB/AFP via Getty Images.

Immunotherapy Outcome Predictors: Scientists Discover Methods to Forecast Responsiveness

In the ever-evolving fight against cancer, immunotherapy is a popular and innovative treatment option that leverages the body's immune system. However, not every person with cancer, nor every cancer type, is responsive to this treatment. In an effort to better understand why some cancers respond to immunotherapy while others do not, researchers at Johns Hopkins University have identified a specific subset of mutations in cancer tumors that may indicate a tumor's receptiveness to immunotherapy.

This set of mutations, termed "persistent mutations," are perpetual and less likely to vanish as cancer progresses. This allows the cancer to remain visible to the immune system, making it more likely to respond positively to immunotherapy treatments. In their recent study, published in the journal Nature Medicine, the researchers hope that their findings will enable medical professionals to more accurately select patients for immunotherapy and predict outcomes more accurately.

Immunotherapy harnesses the power of the immune system to attack and destroy disease-causing cells. Typically, cancer cells develop mutations that enable them to hide from the immune system. Immunotherapy bolsters the immune system, making it easier for it to detect and eradicate cancer cells.

Currently, immunotherapy is being used to treat various cancers, including breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are also investigating its potential use for other types of cancer, such as prostate, brain, and ovarian.

To determine the receptiveness of a tumor to immunotherapy, doctors currently look at the total number of mutations in a tumor–called the tumor mutational burden (TMB)–to predict how well a tumor will respond to treatment.

However, the Johns Hopkins researchers found that the total number of mutations may not be the most accurate indicator, and that a more detailed examination of persistent mutations within the overall TMB is required.

"Persistent mutations are always there in cancer cells and these mutations may render the cancer cells continuously visible to the immune system eliciting an immune response," said study co-author Dr. Valsamo Anagnostou. "This response is augmented in the context of immune checkpoint blockade, allowing the immune system to continuously eliminate cancer cells harboring these persistent mutations over time, resulting in sustained immunologic tumor control and long survival."

By better understanding persistent mutations and their role in cancer, doctors can better predict a patient's response to immunotherapy and potentially make more accurate treatment choices for those with certain genetic backgrounds. This could lead to more effective therapy options, improved survival rates, and ultimately, better outcomes for cancer patients.

  1. The ongoing fight against cancer involves the use of immunotherapy, a treatment that utilizes the immune system to attack and destroy disease-causing cells.
  2. Researchers at Johns Hopkins University have identified a subset of mutations in cancer tumors, referred to as "persistent mutations," which may indicate a tumor's responsiveness to immunotherapy.
  3. These persistent mutations, which remain constant and are less likely to disappear as cancer progresses, keep the cancer visible to the immune system, enhancing the possibility of a positive response to immunotherapy treatments.
  4. By understanding the role of persistent mutations in cancer, doctors can potentially make more accurate treatment choices for patients with certain genetic backgrounds, leading to more effective therapy options, better survival rates, and improved outcomes for cancer patients.

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