Summary of Study ST001857
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001171. The data can be accessed directly via it's Project DOI: 10.21228/M8BM4Q This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST001857 |
| Study Title | Peak Learning of Mass Spectrometry Imaging Data Using Artificial Neural Networks (Prostate tissue) |
| Study Summary | The human prostate tissue sample was analyzed by 2D MALDI FT ICR MSI. For detailed information we refer to the msiPL manuscript by Abdelmoula et al. |
| Institute | Brigham and Women's Hospital |
| Last Name | Abdelmoula |
| First Name | Walid |
| Address | 60 Fenwood RD, Boston, MA |
| wahassan@bwh.harvard.edu | |
| Phone | 8572149765 |
| Submit Date | 2021-06-20 |
| Publications | https://www.nature.com/articles/s41467-021-25744-8 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | h5 |
| Analysis Type Detail | MALDI-MS |
| Release Date | 2021-07-18 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR001171 |
| Project DOI: | doi: 10.21228/M8BM4Q |
| Project Title: | msiPL: Peak Learning of Mass Spectrometry Imaging Data Using Artificial Neural Networks |
| Project Type: | Deep Learning for MSI data analysis |
| Project Summary: | The attached MSI datasets of GBM and prostate cancer tissues were analyzed in the manuscript by Abdelmoula et al. (bioRxiv 2020.08.13.250142). The below is taken from the abstract: Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving clinical diagnosis, biomarker discovery, metabolomics research and pharmaceutical applications. The large data size and high dimensional nature of MSI pose computational and memory complexities that hinder accurate identification of biologically-relevant molecular patterns. We propose msiPL, a robust and generic probabilistic generative model based on a fully-connected variational autoencoder for unsupervised analysis and peak learning of MSI data. The method can efficiently learn and visualize the underlying non-linear spectral manifold, reveal biologically-relevant clusters of tumor heterogeneity and identify underlying informative m/z peaks. The method provides a probabilistic parametric mapping to allow a trained model to rapidly analyze a new unseen MSI dataset in a few seconds. The computational model features a memory-efficient implementation using a minibatch processing strategy to enable the analyses of big MSI data (encompassing more than 1 million high-dimensional datapoints) with significantly less memory. We demonstrate the robustness and generic applicability of the application on MSI data of large size from different biological systems and acquired using different mass spectrometers at different centers, namely: 2D Matrix-Assisted Laser Desorption Ionization (MALDI) Fourier Transform Ion Cyclotron Resonance (FT ICR) MSI data of human prostate cancer, 3D MALDI Time-of-Flight (TOF) MSI data of human oral squamous cell carcinoma, 3D Desorption Electrospray Ionization (DESI) Orbitrap MSI data of human colorectal adenocarcinoma, 3D MALDI TOF MSI data of mouse kidney, and 3D MALDI FT ICR MSI data of a patient-derived xenograft (PDX) mouse brain model of glioblastoma. |
| Institute: | Brigham and Women's Hospital |
| Department: | Neurosurgery |
| Laboratory: | Surgical Molecular Imaging Laboratory |
| Last Name: | Abdelmoula |
| First Name: | Walid |
| Address: | 60 Fenwood RD, Boston, Massachusetts, 02115, USA |
| Email: | wahassan@bwh.harvard.edu |
| Phone: | 617-525-7374 |
| Publications: | https://www.nature.com/articles/s41467-021-25744-8 |
Subject:
| Subject ID: | SU001934 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens;Mus musculus |
| Taxonomy ID: | 9606;10090 |
Factors:
Subject type: Human; Subject species: Homo sapiens;Mus musculus (Factor headings shown in green)
| mb_sample_id | local_sample_id | Tissue Type |
|---|---|---|
| SA174242 | P_1900 | Human Prostate |
| SA174243 | Dataset_S4 | PDX GBM - mouse brain tumor section |
| SA174244 | Dataset_S2 | PDX GBM - mouse brain tumor section |
| SA174245 | Dataset_S1 | PDX GBM - mouse brain tumor section |
| SA174246 | Dataset_S3 | PDX GBM - mouse brain tumor section |
| Showing results 1 to 5 of 5 |
Collection:
| Collection ID: | CO001927 |
| Collection Summary: | As stated in the msiPL paper: Briefly, 12 µm thickness prostate sample diagnosed with a Gleason score of (3+4)=7 were mounted on a microscopy glass slide and coated with CHCA (5 mg/mL in 70/30 methanol/water with 0.1% trifluoroacetic acid V/V) using an automated sprayer (TM-Sprayer, HTX Imaging, Carrboro, NC). The analysis of the samples was performed on a 9.4 Tesla SolariX XR FT ICR mass spectrometer (Bruker Daltonics, Billerica, MA) using the MALDI source in positive ion mode in the mass range between 250-1000 m/z, with a spatial resolution of 120 µm. |
| Sample Type: | Prostate |
Treatment:
| Treatment ID: | TR001946 |
| Treatment Summary: | N/A |
Sample Preparation:
| Sampleprep ID: | SP001940 |
| Sampleprep Summary: | As stated in the msiPL paper: For the Prostate tissue: Briefly, 12 µm thickness prostate sample diagnosed with a Gleason score of (3+4)=7 were mounted on a microscopy glass slide and coated with CHCA (5 mg/mL in 70/30 methanol/water with 0.1% trifluoroacetic acid V/V) using an automated sprayer (TM-Sprayer, HTX Imaging, Carrboro, NC). The analysis of the samples was performed on a 9.4 Tesla SolariX XR FT ICR mass spectrometer (Bruker Daltonics, Billerica, MA) using the MALDI source in positive ion mode in the mass range between 250-1000 m/z, with a spatial resolution of 120 µm. For the PDX GBM mouse brain dataset: The intracranial tumor belonging to a PDX model of GBM12 (PDX National Resource, Mayo Clinic), was analyzed by MALDI FT ICR MSI using a 9.4 Tesla SolariX mass spectrometer (Bruker Daltonics, Billerica, MA), using continuous accumulation of selected ions in the mass range between 380-620 m/z. The indium tin oxide (ITO)-coated slide with 12 µm thickness tissue sections , was coated with DHB (160 mg/mL in a 70/30 v/v solution of methanol/0.2% TFA), according to Randall et al2. The 3D MSI dataset was collected from 4 tissue sections with an inter-slice distance of 160 µm. Internal online calibration was performed using heme m/z 616.1776 during data acquisition. |
Combined analysis:
| Analysis ID | AN003010 |
|---|---|
| Analysis type | MS |
| Chromatography type | Unspecified |
| Chromatography system | none |
| Column | none |
| MS Type | MALDI |
| MS instrument type | FT-ICR |
| MS instrument name | Bruker Solarix FT-ICR-MS |
| Ion Mode | POSITIVE |
| Units | Da |
Chromatography:
| Chromatography ID: | CH002231 |
| Instrument Name: | none |
| Column Name: | none |
| Chromatography Type: | Unspecified |
MS:
| MS ID: | MS002799 |
| Analysis ID: | AN003010 |
| Instrument Name: | Bruker Solarix FT-ICR-MS |
| Instrument Type: | FT-ICR |
| MS Type: | MALDI |
| MS Comments: | Bruker software |
| Ion Mode: | POSITIVE |
