Publication: Dataset for the proteomic inventory and quantitative analysis of the breast cancer hypoxic secretome associated with osteotropism

Thomas R. Cox, Nov 2015

As part of our recent Nature paper (see previous post here) we sought to catalogue all of the different proteins secreted by breast cancer cells (the secretome) under conditions of hypoxia (low oxygen). Hypoxia is a common feature of most solid tumours and is very important in determining how cancer cells behave. Our hypothesis was that the breast cancer secretome changes under hypoxic conditions and that these changes were important in determining the how a patient’s tumour spreads around the body.

To create this catalogue, we performed Mass Spectrometry, a powerful analytical chemistry technique which allows us to both indentify and quantify proteins in a given sample. By creating a list of all the proteins present in the secretome of breast cancer cells, we were able to identify important proteins which may be responsible for determining how and where breast cancer spreads. In our paper we chose to focus specifically on one of these identified secreted proteins called Lysyl Oxidase (LOX).

Open Access – Open Data

However, the list we generated had over 150 proteins on it that changed under conditions of hypoxia in breast cancer cells. What happens to all this other useful data we didn’t investigate further? We decided that we should make our raw, unmodified data freely available to other scientists to interpret and analyse in their own ways. We firmly believe that sharing our raw data, in addition to publishing the final results on the validation of our candidate of choice (LOX) has clear advantages. Not only does this raw data offer complete transparency so that other researchers can compare their own data to ours, but more importantly, it allows other scientists to ask novel questions of our dataset without the need to repeat exactly the same experiment, therefore saving research time and money. That way researchers both inside and outside of our field of interest can build upon our work easily and efficiently.

With this is mind, our raw Mass Spectrometry data has been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD000397

However, the raw data itself is not enough, and in order to use our data properly, careful documentation of our research process and the data is also needed. A detailed protocol including our experimental setup, the  cancer cells used, how we collected and prepared the secreted proteins for Mass Spectrometry and the exact settings of the Mass Spectrometer have also just been published in Elsevier’s Open Access journal Data In Brief. With these two resources, fellow researchers can now make full use of our raw datasets and we hope that they will be able to build upon these to make further scientific advancements.


Dataset for the proteomic inventory and quantitative analysis of the breast cancer hypoxic secretome associated with osteotropism
Cox TR1,2, Schoof EM1, Gartland A, Erler JT, Linding R2
Data In Brief (5) 621-625 (2015) | doi:10.1016/j.dib.2015.09.039
1First authors contributed equally
2Corresponding Authors


Mass Spectrometry experiments in the laboratory of Professor Rune Linding were funded by the Lundbeck Foundation and the work was supported by the Velux Foundations (VKR)-funded Instrument Center for Systems Proteomics (VKR 022758).