TY - JOUR
T1 - Lymph node metastasis of primary endometrial cancers : associated proteins revealed by MALDI imaging
AU - Mittal, Parul
AU - Klingler-Hoffmann, Manuela
AU - Arentz, Georgia
AU - Winderbaum, Lyron
AU - Lokman, Noor A.
AU - Zhang, Chao
AU - Anderson, Lyndal
AU - Scurry, James
AU - Leung, Yee
AU - Stewart, Colin J. R.
AU - Carter, Jonathan
AU - Kaur, Gurjeet
AU - Oehler, Martin K.
AU - Hoffmann, Peter
PY - 2016
Y1 - 2016
N2 - Metastasis is a crucial step of malignant progression and is the primary cause of death from endometrial cancer. However, clinicians presently face the challenge that conventional surgical-pathological variables, such as tumour size, depth of myometrial invasion, histological grade, lymphovascular space invasion or radiological imaging are unable to predict with accuracy if the primary tumour has metastasized. In the current retrospective study, we have used primary tumour samples of endometrial cancer patients diagnosed with (n = 16) and without (n = 27) lymph node metastasis to identify potential discriminators. Using peptide matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), we have identified m/z values which can classify 88% of all tumours correctly. The top discriminative m/z values were identified using a combination of in situ sequencing and LC-MS/MS from digested tumour samples. Two of the proteins identified, plectin and -Actin-2, were used for validation studies using LCMS/MS data independent analysis (DIA) and immunohistochemistry. In summary, MALDIMSI has the potential to identify discriminators of metastasis using primary tumour samples.
AB - Metastasis is a crucial step of malignant progression and is the primary cause of death from endometrial cancer. However, clinicians presently face the challenge that conventional surgical-pathological variables, such as tumour size, depth of myometrial invasion, histological grade, lymphovascular space invasion or radiological imaging are unable to predict with accuracy if the primary tumour has metastasized. In the current retrospective study, we have used primary tumour samples of endometrial cancer patients diagnosed with (n = 16) and without (n = 27) lymph node metastasis to identify potential discriminators. Using peptide matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), we have identified m/z values which can classify 88% of all tumours correctly. The top discriminative m/z values were identified using a combination of in situ sequencing and LC-MS/MS from digested tumour samples. Two of the proteins identified, plectin and -Actin-2, were used for validation studies using LCMS/MS data independent analysis (DIA) and immunohistochemistry. In summary, MALDIMSI has the potential to identify discriminators of metastasis using primary tumour samples.
UR - https://hdl.handle.net/1959.7/uws:59411
U2 - 10.1002/pmic.201500455
DO - 10.1002/pmic.201500455
M3 - Article
SN - 1615-9853
VL - 16
SP - 1793
EP - 1801
JO - Proteomics
JF - Proteomics
IS - 45637
ER -