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Additional file 4: Figure S2. METABRIC mRNA expression data and patient survival. (a) Spearman correlations among GYS1 mRNA and GYS isoform 2 (GYS2), glycogen branching enzyme 1 (GBE1), glycogen breakdown enzymes glycogen phosphorylase muscle isoform (PYGM), brain isoform (PYGB) and liver isoform (PYGL), the hypoxic marker carbonic anhydrase 9 (CA9), and Marker of Proliferation Ki67 (MKI67). Numbers indicate Spearman’s p, only significant correlations are displayed. (b) GYS1 mRNA log2 expression levels across breast cancer clinical subtypes (left panel), tumor stage (middle) and tumor grade (right). Boxes represent the interquartile range and median, whiskers 1.5*interquartile range. Only significant Wilcoxon P-values are annotated. *P

Additional file 2: Table S2. Antibody and RNA specifications.

Additional file 8: Figure 6. (a) Clonogenic agarose assay of HCC1806 cells transfected with siCtrl or siGYS1, cultured in 5.6 mM glucose complete medium for 10 days in normoxia. (b) Ki67 proliferation index in spheroids of HCC1806 cells transfected with siRNA-mediated GYS1 knockdown or scrambled control. (c) Well confluency of HCC1806-shCtrl and -shGYS1 cells treated with different concentrations of GTPP, cultured in 5.6 mM glucose complete DMEM, was measured by Incucyte every 3h.

Additional file 3: Figure S1. METABRIC mRNA expression data (27) and patient overall survival. (a) Overall survival of breast cancer patients with high or low mRNA expression of the respective glycogen enzymes in their primary tumor. Curves are separated by the median mRNA expression. (b) Overall survival curves of triple-negative patients only. (c) Overall survival of respectively ER-/HER2+, ER+/HER2+ or ER+/HER2- breast cancer patients with high or low GYS1 mRNA expression in their primary tumor. Curves are separated by the median GYS1 expression. (d) Overall survival multivariate Cox regression analyses correcting for Nottingham Prognostic Index (NPI) for all (left) and triple-negative breast cancer patients (right) with respectively high and low GYS1 mRNA in their primary tumors. GBE1 = glycogen branching enzyme 1; GYS = glycogen synthase; PYGB = brain glycogen phosphorylase; PYGL = liver glycogen phosphorylase; PYGM = muscle glycogen phosphorylase

Additional file 6: Figure 4. (a) Western blot of GYS1 demonstrates differential expression in breast cancer cell lines. (b) Knock-down of GYS1 in a broad panel of breast cancer cell lines, cultured in 5.6 mM glucose complete DMEM medium for 5 days, reduces cell growth in most breast cancer cell lines.

Additional file 5: Figure S3. Patient selection, survival curves and scoring examples of the primary breast tumor tissue micro-array. (a) Flowchart of the included tumor samples. (b) Corresponding PAS, PAS+diastase and CA9 staining of the areas depicted in Figure 1c. (c) Representative examples of staining intensity per scoring intensity and corresponding output of the analysis app in tumor cores and positive controls. (d) Additional boxplots of GYS1 and glycogen tumor H-score stratified by subtypes and Ki67 low vs. high subgroups within subtypes (top), and scores per tumor grade (bottom). (e) Heatmap of individual primary breast tumor samples (one sample per column) after unsupervised hierarchical clustering based on GYS1, glycogen and Ki67 tumor scores. White boxes in the annotation bars indicate missing values. (f) Overall survival curves of all patients included in the TMA analysis, stratified by respectively GYS1 or glycogen tertiles. Patients with more than one primary breast tumor (n = 9) were excluded from survival analyses.

Additional file 7: Figure 5. (a) Western blot confirmation of siRNA GYS1 knockdown, belonging to Figure 2c. (b) Clonogenic agarose assay of MDA-MB-231 cells with siCtrl or siGYS1, cultured in 5.6 mM glucose complete medium + 0.3% agarose for 14 days in normoxia. (c) Background intracellular glucose levels of MDA-MB-231 with scrambled control or GYS1 shRNA, after 48h culture in 5.6 mM glucose complete DMEM. (d) Proliferation of MDA-MB-231 cells with scrambled control or GYS1 shRNA, after 5 days culture in 10 mM complete DMEM.

OBJECTIVE: To investigate the long-term association between four dietary quality indices and the risk of gastrointestinal (GI) cancer. METHODS: Baseline details of the dietary intake of participants, assessed by a single food frequency questionnaire from the prospective Lifelines population-based cohort were translated to diet quality scores using several dietary and dietary-lifestyle indices. Incident cases of GI cancer were then assessed by linkage to the Dutch nationwide histo-cytopathology registry. The association between GI cancer risk and diet quality (defined as higher quintiles on dietary indices compared to the first quintile) was assessed by multivariable Cox proportional hazard models. RESULTS: We included 72,695 participants aged 51.20 ± 8.71 years with a median follow-up to cancer diagnosis of 8 years (interquartile range 2 years). During follow-up, 434 colorectal cancers and 139 upper GI cancers were diagnosed. There was a significant reduction in colorectal cancer risk for high categories in the American Cancer Society (ACS) Index (hazard ratio 0.62; 95% CI 0.46–0.84). However, high dietary index scores were not associated with strong beneficial effects on upper GI cancer risk. CONCLUSION: High quintiles on the ACS Index were associated with a significantly reduced risk of colorectal cancer. This index may be of use in a colorectal cancer prevention program.

Background—Heart failure (HF) survival has improved and nowadays many patients with HF die from non-cardiac causes, including cancer. Our aim was to investigate whether a causal relationship exists between HF and the development of cancer. Methods—HF was induced by inflicting large anterior myocardial infarction (MI) in APCmin mice, which are prone to develop precancerous intestinal tumors, and tumor growth was measured. In addition, to rule out hemodynamic impairment, a heterotopic heart transplantation model was employed, where an infarcted or sham-operated heart was transplanted into a recipient mouse, while the native heart was left in situ. After 6 weeks, tumor number, volume, and proliferation were quantified. Candidate secreted proteins were selected because they were previously associated both with (colon) tumor growth and with myocardial production in post-MI proteomic studies. Myocardial gene expression levels of these selected candidates were analyzed, as well as their proliferative effects on HT-29 (colon cancer) cells. We validated these candidates by measuring them in plasma of healthy subjects and HF patients. Finally, we associated the relation between cardiac specific and inflammatory biomarkers and new-onset cancer in a large prospective general population cohort. Results—The presence of failing hearts, both native and heterotopically transplanted, resulted in significantly increased intestinal tumor load of 2.4fold in APCmin mice (all P