Fast, automatized fluorescence nanoscopy resolves rearrangements of SNARE and cargo proteins in platelets co-incubated with cancer cells.

This folder contains all raw data underlying the results presented in a manuscript, submitted to Nanoscale, and entitled:

Fast, automatized fluorescence nanoscopy resolves rearrangements of SNARE and cargo proteins in platelets co-incubated with cancer cells.

Authored by:

Jan Bergstranda,+, Xinyan Miaoa,+, Chinmaya Venugopal Srambickala,+, Gert Auerb, Jerker Widengrena,*

a Royal Institute of Technology (KTH), Department of Applied Physics, Experimental Biomolecular Physics, Albanova Univ Center, SE-106 91 Stockholm, Sweden

b Karolinska Institutet, Department of Oncology-Pathology, K7, Z1:00, Karolinska University Hospital, 171 76 Stockholm, Sweden

* To whom correspondence should be addressed. E-mail: [e-mail], Phone: [phone]

+ These authors contributed equally

The data files are grouped into the different figures where they are presented.

ABSTRACT

Increasing evidence suggests that platelets play a central role in cancer progression and metastasis, with altered storage and selective release from platelets of specific proteins promoting tumor growth and spread as a major mechanism. With fluorescence-based super-resolution microscopy (SRM) nanoscale spatial distribution patterns of specific proteins in platelets can be resolved, and also alterations of such patterns upon different activations. We applied stimulated emission depletion (STED) SRM to study two categories of platelet proteins; four different SNAREs (soluble N-ethylmaleimide factor attachment protein receptors) mediating protein secretion by membrane fusion of storage granules, and two angiogenesis regulating proteins, representing cargo proteins within these granules coupled to tumor progression. By an automatized procedure, we recorded about 100 STED images of platelets, for each of these six proteins, and for five different categories of platelets; incubated with cancer cells (MCF-7, MDA-MB-231, EFO-21), non-cancer cells (MCF-10A), or no cells at all. From these images, structural similarity and protein cluster parameters were determined, and probability functions of these parameters were generated for the different platelet categories. By comparing these probability functions between the categories, we could identify nanoscale alterations in the protein distributions, not evident by visual inspection of the images, and allowing us to classify the platelets into their correct categories. The fast, automatized and objective acquisition and analysis procedure established in this work confirms the role of SNAREs and angiogenesis-regulating proteins in platelet-mediated cancer progression, and overcomes major thresholds for using redistribution of nanoscale protein patterns in platelets as a basis for cancer diagnostics.

Key Words:

STED, super-resolution microscopy, platelet, cancer, tumorigenesis, SNARE protein, dictionary learning