How prostate cancer cells mimic bone when they metastasize

Prostate cancer often becomes lethal as it spreads to the bones, and the process behind this deadly feature could potentially be turned against it as a target for bone-targeting radiation and potential new therapies.

Study published online in the journal PLOS ONE, Duke Cancer Institute researchers describe how prostate cancer cells develop the ability to mimic bone-forming cells called osteoblasts, enabling them to proliferate in the bone microenvironment.

Attacking these cells with radium-233, a radioactive isotope that selectively targets cells in these bone metastases, has been shown to prolong patients' lives. But a better understanding of how radium works in the bone was needed.

The mapping of this mimicking process could lead to a more effective use of radium-233 and to the development of new therapies to treat or prevent the spread of prostate cancer to bone.

"Given that most men who die of prostate cancer have bone metastases, this work is critical to helping understand this process," said lead author Andrew Armstrong, Director of Research at the Duke Cancer Institute Center for Prostate and Urologic Cancers.

The research team enrolled a small study group of 20 men with symptomatic bone-metastatic prostate cancer. When analyzing the circulating tumor cells from study participants, they found that bone-forming enzymes appeared to be expressed commonly, and that genetic alterations in bone forming pathways were also common in these prostate cancer cells.

They validated these new genetic findings in a separate multicenter trial involving a larger group of more than 40 men with prostate cancer and bone metastases.

Following treatment with radium-223, the researchers found that the radioactive isotope was concentrated in bone metastases, but tumor cells still circulated and cancer progressed within six months of therapy. The researchers found a range of complex genetic alterations in these tumor cells that likely enabled them to persist and develop resistance to the radiation over time.

"Osteomimicry may contribute in part to how prostate cancer spreads to bone, but also to the uptake of radium-223 within bone metastases and may thereby enhance the therapeutic benefit of this bone targeting radiotherapy," Armstrong said.

He said by mapping this lethal pathway of prostate cancer bone metastasis, the study points to new targets and thus critical areas of research into designing better tumor-targeting therapies.

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AI predicts cancer patients' symptoms

Doctors could get a head start treating cancer thanks to new AI developed at the University of Surrey that is able to predict symptoms and their severity throughout the course of a patient's treatment.

The study was first of its kind published in the PLOS One journal. Researchers from the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey shared the detail how they created two machine learning models that are both able to accurately predict the severity of three common symptoms faced by cancer patients  are depression, anxiety and sleep disturbance. All three symptoms are associated with severe reduction in cancer patients' quality of life.

Researchers analysed existing data of the symptoms experienced by cancer patients during the course of computed tomography x-ray treatment. The team used different time periods during this data to test whether the machine learning algorithms are able to accurately predict when and if symptoms surfaced.

The results found that the actual reported symptoms were very close to those predicted by the machine learning methods.

This work has been a collaboration between the University of Surrey and the University of California in San Francisco (UCSF). The UCSF research in this joint collaboration is led by Professor Christine Miaskowski.

Payam Barnaghi, Professor of Machine Intelligence at the University of Surrey, said: "These exciting results show that there is an opportunity for machine learning techniques to make a real difference in the lives of people living with cancer. They can help clinicians identify high-risk patients, help and support their symptom experience and pre-emptively plan a way to manage those symptoms and improve quality of life."

Nikos Papachristou, who worked on designing the machine learning algorithms for this project, said: "I am very excited to see how machine learning and AI can be used to create solutions that have a positive impact on the quality of life and well-being of patients."

Researchers from different part of the world are invited to submit abstract on their unpublished latest research at our upcoming conference Cell Tissue Science 2019 which is focused on the complications and consequences of Stem Cell, Regenerative Medicine, Stem Cell Therapy, Cancer Cell Biology,Technical Advancements in cancer treatment and many more. We as committee members of the conference welcome you to be a part of the conference “ 12th World Congress on Cell & Tissue Science” in Singapore on March 11-12, 2019. 

You can submit your abstract on Session or Track : 07. Cancer Cell Biology

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