New InFlo Computer Method Predicts Cancer Cell Activity, Identifies Biomarkers

New InFlo Computer Method Predicts Cancer Cell Activity, Identifies Biomarkers

A new computed-based method called InFlo assesses cellular communication networks and identifies disease-specific network anomalies that can cause cancer and other diseases. This new tool may facilitate the discovery of new biomarkers and targets for therapy.

The InFlo tool, which resulted from the collaborative work of Case Western Reserve University School of Medicine with researchers at Philips and Princeton University, was described in the study “InFlo: a novel systems biology framework identifies cAMP-CREB1 axis as a key modulator of platinum resistance in ovarian cancer,” published in Oncogene.

“Complex diseases such as cancer involve the simultaneous disruptions of multiple cellular processes acting in tandem,” Vinay Varadan, PhD, assistant professor at Case Western School of Medicine, a member of the Case Comprehensive Cancer Center, and senior author of the study, said in a press release.

“We developed InFlo to robustly integrate multiple molecular data streams and develop an integrative molecular portrait of an individual cancer sample.”

This new tool integrates data related to each level of cell communication, including genes, proteins, and other elements commonly attached to proteins, such as chemical methyl groups. Making use of mathematical strategies, InFlo can gather all the information to build activity webs to reveal protein interactions most likely to cause disease.

InFlo can be used to compare healthy and diseased tissues, revealing the major differences in signaling. Unlike other methods, InFlo also includes in its predictions tissue-specific markers and genetic alterations associated with disease, improving its specificity and reliability.

The model was validated in ovarian cancer cells that were resistant to platinum-based chemotherapy, pinpointing two proteins, cAMP and CREB1, involved in the chemoresistance mechanism.

“Following up on InFlo’s predictions, we showed that inhibiting CREB1 potently sensitizes ovarian cancer cells to platinum therapy and is also effective in killing ovarian cancer stem cells,” said Analisa DiFeo, PhD, senior author of the study.

She said the research team is evaluating whether InFlo “could lead to a potential therapeutic target for the treatment of platinum-resistant ovarian cancer.”

This new tool will soon be available for basic and translational research settings, and will be incorporated into the Philips IntelliSpace Genomics platform — an application built for pathologists, oncologists, and researchers to gather the information on oncologic patients.

“We are currently collaborating with the Imaging Informatics research group in the Center for Computational Imaging and Personalized Diagnostics at Case Western Reserve University to integrate InFlo with imaging-features derived from pathology and radiology data,” Varadan said.

The expansion of InFlo to incorporate other data streams would result in one of the most complete and effective tools available to researchers and clinicians to evaluate mechanisms triggering complex diseases, such as cancer.

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