The Potential of Albuminuria as a Biomarker of Diabetic Complications

Diabetes mellitus is a disease of dysregulated blood glucose homeostasis. The current pandemic of diabetes is a significant driver of patient morbidity and mortality, as well as a major challenge to healthcare systems worldwide. The global increase in the incidence of diabetes has prompted researchers to focus on the different pathogenic processes responsible for type 1 and type 2 diabetes. Similarly, increased morbidity due to diabetic complications has accelerated research to uncover pathological changes causing these secondary complications. Albuminuria, or protein in the urine, is a well-recognised biomarker and risk factor for renal and cardiovascular disease. Albuminuria is a mediator of pathological abnormalities in diabetes-associated conditions such as nephropathy and atherosclerosis. Clinical screening and diagnosis of diabetic nephropathy is chiefly based on the presence of albuminuria. Given the ease in measuring albuminuria, the potential of using albuminuria as a biomarker of cardiovascular diseases is gaining widespread interest. To assess the benefits of albuminuria as a biomarker, it is important to understand the association between albuminuria and cardiovascular disease. This review examines our current understanding of the pathophysiological mechanisms involved in both forms of diabetes, with specific focus on the link between albuminuria and specific vascular complications of diabetes.

CTCF maintains regulatory homeostasis of cancer pathways

BACKGROUND

CTCF binding to DNA helps partition the mammalian genome into discrete structural and regulatory domains. Complete removal of CTCF from mammalian cells causes catastrophic genome dysregulation, likely due to widespread collapse of 3D chromatin looping and alterations to inter- and intra-TAD interactions within the nucleus. In contrast, Ctcf hemizygous mice with lifelong reduction of CTCF expression are viable, albeit with increased cancer incidence. Here, we exploit chronic Ctcf hemizygosity to reveal its homeostatic roles in maintaining genome function and integrity.

RESULTS

We find that Ctcf hemizygous cells show modest but robust changes in almost a thousand sites of genomic CTCF occupancy; these are enriched for lower affinity binding events with weaker evolutionary conservation across the mouse lineage. Furthermore, we observe dysregulation of the expression of several hundred genes, which are concentrated in cancer-related pathways, and are caused by changes in transcriptional regulation. Chromatin structure is preserved but some loop interactions are destabilized; these are often found around differentially expressed genes and their enhancers. Importantly, the transcriptional alterations identified in vitro are recapitulated in mouse tumors and also in human cancers.

CONCLUSIONS

This multi-dimensional genomic and epigenomic profiling of a Ctcf hemizygous mouse model system shows that chronic depletion of CTCF dysregulates steady-state gene expression by subtly altering transcriptional regulation, changes which can also be observed in primary tumors.

Patterns of Immune Infiltration in Breast Cancer and Their Clinical Implications: A Gene-Expression-Based Retrospective Study

BACKGROUND

Immune infiltration of breast tumours is associated with clinical outcome. However, past work has not accounted for the diversity of functionally distinct cell types that make up the immune response. The aim of this study was to determine whether differences in the cellular composition of the immune infiltrate in breast tumours influence survival and treatment response, and whether these effects differ by molecular subtype.

METHODS AND FINDINGS

We applied an established computational approach (CIBERSORT) to bulk gene expression profiles of almost 11,000 tumours to infer the proportions of 22 subsets of immune cells. We investigated associations between each cell type and survival and response to chemotherapy, modelling cellular proportions as quartiles. We found that tumours with little or no immune infiltration were associated with different survival patterns according to oestrogen receptor (ER) status. In ER-negative disease, tumours lacking immune infiltration were associated with the poorest prognosis, whereas in ER-positive disease, they were associated with intermediate prognosis. Of the cell subsets investigated, T regulatory cells and M0 and M2 macrophages emerged as the most strongly associated with poor outcome, regardless of ER status. Among ER-negative tumours, CD8+ T cells (hazard ratio [HR] = 0.89, 95% CI 0.80-0.98; p = 0.02) and activated memory T cells (HR 0.88, 95% CI 0.80-0.97; p = 0.01) were associated with favourable outcome. T follicular helper cells (odds ratio [OR] = 1.34, 95% CI 1.14-1.57; p < 0.001) and memory B cells (OR = 1.18, 95% CI 1.0-1.39; p = 0.04) were associated with pathological complete response to neoadjuvant chemotherapy in ER-negative disease, suggesting a role for humoral immunity in mediating response to cytotoxic therapy. Unsupervised clustering analysis using immune cell proportions revealed eight subgroups of tumours, largely defined by the balance between M0, M1, and M2 macrophages, with distinct survival patterns by ER status and associations with patient age at diagnosis. The main limitations of this study are the use of diverse platforms for measuring gene expression, including some not previously used with CIBERSORT, and the combined analysis of different forms of follow-up across studies.

CONCLUSIONS

Large differences in the cellular composition of the immune infiltrate in breast tumours appear to exist, and these differences are likely to be important determinants of both prognosis and response to treatment. In particular, macrophages emerge as a possible target for novel therapies. Detailed analysis of the cellular immune response in tumours has the potential to enhance clinical prediction and to identify candidates for immunotherapy.