Scientists develop first-ever application to detect cancer within a single cell

By Kelly Hodgkins Published April 20, 2016

MD Anderson Cancer Center — Facebook

Researchers from the University of Texas MD Anderson Cancer Center have developed the world’s first application capable of detecting cancerous changes in a single cell. This new approach makes it possible for researchers to detect slight alterations in a DNA sequence from multiple individual cells, a level of detection not currently possible using methods that require the analysis of a vast number of cells.

This new method is based on a recent form of DNA analysis called single-cell sequencing (SCS) that looks for DNA mutations in multiple individual cells, allowing researcher to detect cancerous mutations within a tissue sample. This SCS technology differs significantly from the existing next-generation sequencing (NGS) method that measures genomes derived from millions of cells. SCS has made a significant impact in the field of medicine and molecular biology, but the computational tools that analyze the DNA sequences are not as accurate as researchers wanted.

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The University of Texas research team has improved these analytics tools, creating a new application they call Monovar. This method makes it possible to detect small changes in DNA known as single-nucleotide variants (SNVs). SNVs are commonly used as markers to identify both inheritable diseases and DNA-related diseases such as cancer.

Monovar is a flexible tool, capable of analyzing DNA in a variety of applications beyond early cancer detection and treatment. “Monovar will have significant translational applications in cancer diagnosis and treatment, personalized medicine, and prenatal genetic diagnosis, where the accurate detection of SNVs is critical for patient care,” said study co-authors Nicholas Navin, Ph.D., and Ken Chen, Ph.D.. The results of this study were published recently in the online version of Nature Methods.

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Kelly's been writing online for ten years, working at Gizmodo, TUAW, and BGR among others. Living near the White Mountains of…

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The National Highway Traffic Safety Administration (NHTSA) is concerned that Tesla’s use of social media and its website makes false promises about the automaker’s full-self driving (FSD) software.
The warning dates back from May, but was made public in an email to Tesla released on November 8.
The NHTSA opened an investigation in October into 2.4 million Tesla vehicles equipped with the FSD software, following three reported collisions and a fatal crash. The investigation centers on FSD’s ability to perform in “relatively common” reduced visibility conditions, such as sun glare, fog, and airborne dust.
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The postings, which included reposted YouTube videos, may encourage viewers to see FSD-supervised as a “Robotaxi” instead of a partially automated, driver-assist system that requires “persistent attention and intermittent intervention by the driver,” Magno said.
In one of a number of Tesla posts on X, the social media platform owned by Tesla CEO Elon Musk, a driver was seen using FSD to reach a hospital while undergoing a heart attack. In another post, a driver said he had used FSD for a 50-minute ride home. Meanwhile, third-party comments on the posts promoted the advantages of using FSD while under the influence of alcohol or when tired, NHTSA said.
Tesla’s official website also promotes conflicting messaging on the capabilities of the FSD software, the regulator said.
NHTSA has requested that Tesla revisit its communications to ensure its messaging remains consistent with FSD’s approved instructions, namely that the software provides only a driver assist/support system requiring drivers to remain vigilant and maintain constant readiness to intervene in driving.
Tesla last month unveiled the Cybercab, an autonomous-driving EV with no steering wheel or pedals. The vehicle has been promoted as a robotaxi, a self-driving vehicle operated as part of a ride-paying service, such as the one already offered by Alphabet-owned Waymo.
But Tesla’s self-driving technology has remained under the scrutiny of regulators. FSD relies on multiple onboard cameras to feed machine-learning models that, in turn, help the car make decisions based on what it sees.
Meanwhile, Waymo’s technology relies on premapped roads, sensors, cameras, radar, and lidar (a laser-light radar), which might be very costly, but has met the approval of safety regulators.