Nicholas W Bateman

May 5, 2024 | nature.com | Nicholas W Bateman |Tamara Abulez |Dale W. Garsed |Pang-ning Teng |Clifton L. Dalgard |Mariaelena Pierobon | +5 more

Correction to: npj Precision Oncology https://doi.org/10.1038/s41698-024-00519-8, published online 13 March 2024In the original version of this article, the wrong file was inadvertently supplied for Supplementary Data 15. The original article has been corrected.

Mar 12, 2024 | nature.com | Nicholas W Bateman |Tamara Abulez |Dale W. Garsed |Pang-ning Teng |Clifton L. Dalgard |Mariaelena Pierobon | +5 more

AbstractWe performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity.

Dec 1, 2023 | nature.com | John McGee |Pei Su |Nicholas W Bateman |Thomas P Conrads |Jeannie M. Camarillo |Jared O. Kafader

Correction to: Nature Communications https://doi.org/10.1038/s41467-023-42208-3, published online 14 October 2023The original version of the Article contained the following errors in Fig. 2: the proteoform signature ‘7125 Da’ was incorrectly labelled as ‘PSMD1’ in panels b and c; the labels ‘237 tumor pixels’ and ‘235 stroma pixels’ were incorrectly added to panel d and they have been removed in the correct version. The correct version of Fig.

Nov 3, 2023 | nature.com | Katherine Foster |Nicholas W Bateman |Kathleen Darcy |Thomas P Conrads |Philip L. Lorenzi

AbstractIn this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined.

Oct 14, 2023 | nature.com | John McGee |Pei Su |Nicholas W Bateman |Thomas P Conrads |Jeannie M. Camarillo |Jared O. Kafader

AbstractThe molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS2) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform.