TH1 and TH2 cytokines dataset in insulin users with diabetes mellitus and newly diagnosed breast cancer

Exogenous insulin use may interfere with the T helper cells’ cytokine production. This dataset presents the relationship between pre-existing use of injectable insulin in women diagnosed with breast cancer and type 2 diabetes mellitus, the T-helper 1 and 2 produced cytokine profiles at the time of breast cancer diagnosis, and subsequent cancer outcomes. A Pearson correlation analysis evaluating the relationship between T-helper cytokines stratified by of insulin use and controls is also provided.

The data we present here has the potential to guide future research evaluating the role of insulin in the modulation of type 1 and type 2 immunity.
Our observations can assist further research exploring the relationship between insulin administration and T-helper-driven signaling in breast cancer occurrence.

Data
Reported data represents the observed association between pre-existing use of injectable insulin before breast cancer diagnosis and the T-helper 1 and 2 produced cytokine profiles upon cancer diagnosis in women with both breast cancer and diabetes mellitus (Table 1). Data in Table 2 includes the observed correlations between T-helper 1 and 2 cytokines stratified by diabetes mellitus pharmacotherapy and controls.

Experimental design, materials and methods
Evaluation of the association between profiles of T-helper 1 and 2 produced cytokines, injectable insulin use and BC outcomes was carried out under two protocols approved by both Roswell Park Cancer Institute (EDR154409 and NHR009010) and the State University of New York at Buffalo . Demographic and clinical patient information was linked with cancer outcomes and profiles of T-helper 1 and 2 produced cytokines of corresponding plasma specimen harvested at BC diagnosis and banked in the Roswell Park Cancer Institute Data Bank and Bio-Repository.

Study population
All incident breast cancer cases diagnosed at Roswell Park Cancer Institute (01/01/2003-12/31/ 2009) were considered for inclusion (n ¼2194). Medical and pharmacotherapy history were used to determine the baseline presence of diabetes.

Inclusion and exclusion criteria
All adult women with pre-existing diabetes at breast cancer diagnosis having available banked treatment-naïve plasma specimens (blood collected prior to initiation of any cancer-related therapysurgery, radiation or pharmacotherapy) in the Institute's Data Bank and Bio-Repository were included.
Subjects were excluded if they had prior cancer history or unclear date of diagnosis, incomplete clinical records, type 1 or unclear diabetes status. For a specific breakdown of excluded subjects, please see the original research article by Wintrob et al. [1].
A total of 97 female subjects with breast cancer and baseline diabetes mellitus were eligible for inclusion in this analysis.

Demographic and clinical data collection
Clinical and treatment history was documented as previously described [1]. Briefly, users of any insulin were defined as patients receiving a form of injectable insulinalone or in combinationat the time of breast cancer diagnosis. Vital status was obtained from the Institute's Tumor Registry, a database updated biannually with data obtained from the National Comprehensive Cancer Networks' Oncology Outcomes Database. Outcomes of interest were breast cancer recurrence and/or death. Details regarding patient demographics and clinical characteristics have been previously published [1].

Plasma specimen storage and retrieval
All the plasma specimens retrieved from long-term storage were individually aliquoted in color coded vials labeled with unique, subject specific barcodes. Overall duration of freezing time was accounted for all matched controls ensuring that the case and matched control specimens had similar overall storage conditions. Only two instances of freeze-thaw were allowed between biobank retrieval and biomarker analyses: aliquoting procedure step and actual assay.
were performed accounting for age, tumor stage, body mass index, estrogen receptor status, and cumulative comorbidity. The biomarker analysis was performed using R Version 2.15.3. Please see the original article for an illustration of the analysis workflow [1]. Correlations between biomarkers stratified by type 2 diabetes mellitus pharmacotherapy and controls were assessed by the Pearson method. Correlation models were constructed both with and without adjustment for age, body mass index, and the combined comorbidity index. Correlation analyses were performed using SAS Version 9.4.

Funding sources
This research was funded by the following grant awards: Wadsworth Foundation Peter Rowley Breast Cancer Grant awarded to A.C.C. (UB Grant number 55705, Contract CO26588).