Every day there are news about new knowledge about cancer. Often this is related to how a drug works against a specific type of cancer.
For example, this week only, Therapeutic Achilles dose the first patient with custom clonal reactive neo-antigen (cNeT) T cells made using the company’s higher-dose VELOS process. The phase I/IIa CHIRON trial is evaluating the drug in advanced non-small cell lung cancer (NSCLC). She also initiated enrollment in Cohort B of the THETIS trial of cNeT in combination with a PD-1 checkpoint inhibitor for metastatic malignant melanoma.
Somewhere else, Elpiscience Biopharma has received the green light from the United States Food and Drug Administration to initiate a phase I trial of ES014 in advanced solid tumors. E014 is an anti-CD39xTGF-beta bispecific antibody that simultaneously targets the CD39-adenosine and TGF-beta pathways.
Less common is something fundamental to our understanding of cancer. Over the past few weeks, researchers from Yale University published research in Molecular biology and evolution describing a novel molecular analysis approach to quantifying DNA changes that contribute to cancer growth.
Of course, environmental factors can lead to genetic mutations leading to cancer. For example, ultraviolet light or tobacco use. It is, however, much more difficult to determine the extent to which a person’s cancer has developed due to these environmental factors or aging and bad luck. But Yale researchers have developed an approach that quantifies the contribution of each mutation to cancer.
“We can now answer the question – to the best of our knowledge – ‘What is the underlying source of the key mutations that turned these cells into cancer instead of remaining normal tissue?’ “” Jeffrey Townsend, Ph.D., the Elihu professor of biostatistics in the department of biostatistics at the Yale School of Public Health, said.
They were able to combine an ability to predict how specific factors cause specific mutations with a method that quantifies the contribution of each mutation to cancer. “This gives us the final piece of the puzzle to connect what happened to your genome with cancer,” Townsend said. “It’s really direct: we look into your tumor, and we see the signal written in your tumor of what caused this cancer.”
For example, some tumors such as bladder and skin tend to grow more due to preventable factors. Prostate cancers and gliomas (types of brain tumors) are largely due to age-related processes.
Specific locations or even professions that have unusually high levels of cancer might be able to use the method to identify cases of exposure to carcinogens, Townsend suggests. “It can be useful for giving people feedback that lets them know what caused their cancer,” he said. “Not everyone may want to know. But on a personal level, it can be helpful for people to attribute their cancer to its cause.
Currently, their methodology does not take into account all the genetic changes that lead to cancers. Further research will be needed to fully understand all of the genetic changes associated with cancer, and there are many more, even rare cancers, to be evaluated.
The authors wrote that “mutational processes in tumors create distinctive patterns of mutations, composed of neutral ‘passenger’ mutations and oncogenic factors that have quantifiable effects on the proliferation and survival of cancer cell lines. Increases in proliferation and survival are mediated by natural selection, which can be quantified by comparing the frequency with which we detect substitutions to the frequency with which we expect to detect substitutions assuming neutrality.
Most of the variants that they can assess with whole-exome tumor sequencing are neutral or nearly neutral. Therefore, the processes that cause the majority of mutations might not be the primary source of carcinogenic mutations.
By evaluating 24 types of cancer, the research team identified the contributions of mutational processes to each oncogenic variant and quantified the extent to which each process contributed to tumor development. In addition to their findings in melanomas and lung cancer, gliomas and prostate adenocarcinomas, they found that preventable mutations associated with exposure to pathogens and l Apolipoprotein B mRNAs account for a high percentage of head and neck cancers, bladder, cervix, and breast cancers.