MasSpec Pen

Livia S. Eberlin, Ph.D., an Assistant Professor of Chemistry at the University of Texas at Austin, first reported the invention of the MasSpec Pen in 2017. Within her laboratory, the device has been used to analyze human tissue biopsies, including normal and cancerous breast, lung, ovarian, and thyroid samples. The MasSpec Pen has been licensed to Genio Technologies, Inc., a subsidiary of MS Pen Technologies, Inc. ==Principle of operation==

Ambient ionization mass spectrometry for disease diagnosis The MasSpec Pen technology is based on the principles of ambient ionization, in which ions are generated directly from a sample without need for extensive sample preparation or chromatographic separations. The MasSpec Pen can further be categorized as a solid-liquid extraction based ambient ionization method, described as methods that utilize a solvent system to gently extract molecules from a sample surface that are subsequently analyzed by a mass spectrometer. Desorption electrospray ionization (DESI) was the first liquid-based ambient ionization MS method. These methods have been deployed for the discrimination of normal and cancerous regions of tissue samples for many solid tumor indications, including breast, brain, prostate, ovarian, and colorectal, among others. Multivariate statistical analysis methods are often utilized to generate statistical models from the mass spectral data acquired from direct analysis of tissue samples to distinguish between healthy and diseased tissues. MasSpec Pen analysis mechanism The MasSpec Pen, initially described in 2017, is a solvent-based ambient ionization technique but differs from its predecessors due to the handheld nature of the device, allowing analysis of samples distant from the mass spectrometer in a geometry independent manner. The MasSpec Pen was used on both ex vivo and in vivo tissue samples to discriminate between healthy pancreas and pancreatic tumor tissue. The device was also used to detect cancerous margins near adjacent structures of the pancreas such as the bile duct. The system was used in 18 pancreatic cancer surgeries and the data collected allowed the detection of cancerous tissue with high accuracy. == References ==