Examining patient distress and unmet need for support across UK renal units with varying models of psychosocial care delivery : a cross-sectional survey study

Objective: To examine in-centre haemodialysis patients’ emotional distress and need for support across UK renal units with varying models of psychosocial service provision. Design: The study used a cross-sectional survey design. Logistic regression analysis was used to examine patient distress, as captured by the Distress Thermometer, and need for support, across different renal units. Setting: Seven renal units across England, Wales and Scotland. The units were purposively selected so that varying workforce models of renal psychosocial services were represented. Participants: In total, 752 patients were on dialysis in the participating centres on the days of data collection. All adult patients, who could understand English, and with capacity (as determined by the nurse in charge), were eligible to participate in the study. The questionnaire was completed by 509 patients, resulting in an overall response rate of 67.7%. Outcome measures: The prevalence of distress and patient-reported need for support. Results: The results showed that 48.9% (95% CI 44.5 to 53.4) of respondents experienced distress. A significant association between distress and models of renal psychosocial service provision was found (χ2(6)=15.05, p=0.019). Multivariable logistic regression showed that patients in units with higher total psychosocial staffing ratios (OR 0.65 (95% CI 0.47 to 0.89); p=0.008) and specifically higher social work ratios (OR 0.49 (95% CI 0.33 to 0.74); p=0.001) were less likely to experience distress, even after controlling for demographic variables. In addition, a higher patient-reported unmet need for support was found in units where psychosocial staffing numbers are low or non-existent (χ2(6)=37.80, p<0.001). Conclusions: The novel findings emphasise a need for increased incorporation of dedicated renal psychosocial staff into the renal care pathway. Importantly, these members of staff should be able to offer support for psychological as well as practical and social care-related issues

The mammary cellular hierarchy and breast cancer.

Advances in the study of hematopoietic cell maturation have paved the way to a deeper understanding the stem and progenitor cellular hierarchy in the mammary gland. The mammary epithelium, unlike the hematopoietic cellular hierarchy, sits in a complex niche where communication between epithelial cells and signals from the systemic hormonal milieu, as well as from extra-cellular matrix, influence cell fate decisions and contribute to tissue homeostasis. We review the discovery, definition and regulation of the mammary cellular hierarchy and we describe the development of the concepts that have guided our investigations. We outline recent advances in in vivo lineage tracing that is now challenging many of our assumptions regarding the behavior of mammary stem cells, and we show how understanding these cellular lineages has altered our view of breast cancer

The innate and adaptive infiltrating immune systems as targets for breast cancer immunotherapy.

A cancer cell-centric view has long dominated the field of cancer biology. Research efforts have focussed on aberrant cancer cell signalling pathways and on changes to cancer cell DNA. Mounting evidence demonstrates that many cancer-associated cell types within the tumour stroma co-evolve and support tumour growth and development, greatly modifying cancer cell behaviour, facilitating invasion and metastasis and controlling dormancy and sensitivity to drug therapy. Thus, these stromal cells represent potential targets for cancer therapy. Among these cell types, immune cells have emerged as a promising target for therapy. The adaptive and the innate immune system play an important role in normal mammary development and breast cancer. The number of infiltrating adaptive immune system cells with tumour-rejecting capacity, primarily, T lymphocytes, is lower in breast cancer compared with other cancer types, but infiltration occurs in a large proportion of cases. There is strong evidence demonstrating the importance of the immunosuppressive role of the innate immune system during breast cancer progression. A consideration of components of both the innate and the adaptive immune system is essential for the design and development of immunotherapies in breast cancer. In this review, we focus on the importance of immunosuppressive myeloid-derived suppressor cells (MDSCs) as potential targets for breast cancer therapy

Myeloid cell leukemia 1 (MCL-1), an unexpected modulator of protein kinase signaling during invasion.

Myeloid cell leukemia-1 (MCL-1), closely related to B-cell lymphoma 2 (BCL-2), has a well-established role in cell survival and has emerged as an important target for cancer therapeutics. We have demonstrated that inhibiting MCL-1 is efficacious in suppressing tumour progression in pre-clinical models of breast cancer and revealed that in addition to its role in cell survival, MCL-1 modulated cellular invasion. Utilizing a MCL-1-specific genetic antagonist, we found two possible mechanisms; firstly MCL-1 directly binds to and alters the phosphorylation of the cytoskeletal remodeling protein, Cofilin, a protein important for cytoskeletal remodeling during invasion, and secondly MCL-1 modulates the levels SRC family kinases (SFKs) and their targets. These data provide evidence that MCL-1 activities are not limited to endpoints of extracellular and intracellular signaling culminating in cell survival as previously thought, but can directly modulate the output of SRC family kinases signaling during cellular invasion. Here we review the pleotropic roles of MCL-1 and discuss the implications of this newly discovered effect on protein kinase signaling for the development of cancer therapeutics

ELF5 isoform expression is tissue-specific and significantly altered in cancer.

BACKGROUND: E74-like factor 5 (ELF5) is an epithelial-specific member of the E26 transforming sequence (ETS) transcription factor family and a critical regulator of cell fate in the placenta, pulmonary bronchi, and milk-producing alveoli of the mammary gland. ELF5 also plays key roles in malignancy, particularly in basal-like and endocrine-resistant forms of breast cancer. Almost all genes undergo alternative transcription or splicing, which increases the diversity of protein structure and function. Although ELF5 has multiple isoforms, this has not been considered in previous studies of ELF5 function. METHODS: RNA-sequencing data for 6757 samples from The Cancer Genome Atlas were analyzed to characterize ELF5 isoform expression in multiple normal tissues and cancers. Extensive in vitro analysis of ELF5 isoforms, including a 116-gene quantitative polymerase chain reaction panel, was performed in breast cancer cell lines. RESULTS: ELF5 isoform expression was found to be tissue-specific due to alternative promoter use but altered in multiple cancer types. The normal breast expressed one main isoform, while in breast cancer there were subtype-specific alterations in expression. Expression of other ETS factors was also significantly altered in breast cancer, with the basal-like subtype demonstrating a distinct ETS expression profile. In vitro inducible expression of the full-length isoforms 1 and 2, as well as isoform 3 (lacking the Pointed domain) had similar phenotypic and transcriptional effects. CONCLUSIONS: Alternative promoter use, conferring differential regulatory responses, is the main mechanism governing ELF5 action rather than differential transcriptional activity of the isoforms. This understanding of expression and function at the isoform level is a vital first step in realizing the potential of transcription factors such as ELF5 as prognostic markers or therapeutic targets in cancer

Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology.

Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches

Andy's Algorithms: new automated digital image analysis pipelines for FIJI.

Quantification of cellular antigens and their interactions via antibody-based detection methods are widely used in scientific research. Accurate high-throughput quantitation of these assays using general image analysis software can be time consuming and challenging, particularly when attempted by users with limited image processing and analysis knowledge. To overcome this, we have designed Andy's Algorithms, a series of automated image analysis pipelines for FIJI, that permits rapid, accurate and reproducible batch-processing of 3,3'-diaminobenzidine (DAB) immunohistochemistry, proximity ligation assays (PLAs) and other common assays. Andy's Algorithms incorporates a step-by-step tutorial and optimization pipeline to make batch image analysis simple for the untrained user and adaptable across laboratories. Andy's algorithms provide a simpler, faster, standardized work flow compared to existing programs, while offering equivalent performance and additional features, in a free to use open-source application of FIJI. Andy's Algorithms are available at GitHub, publicly accessed at https://github.com/andlaw1841/Andy-s-Algorithm