MALT1 proteolytic activity suppresses autoimmunity in a T cell intrinsic manner

MALT1 is a central signaling component in innate and adaptive immunity by regulating NF-kappa B and other key signaling pathways in different cell types. Activities of MALT1 are mediated by its scaffold and protease functions. Because of its role in lymphocyte activation and proliferation, inhibition of MALT1 proteolytic activity is of high interest for therapeutic targeting in autoimmunity and certain lymphomas. However, recent studies showing that Mak1 protease-dead knock-in (Malt1-PD) mice suffer from autoimmune disease have somewhat tempered the initial enthusiasm. Although it has been proposed that an imbalance between immune suppressive regulatory T cells (Tregs) and activated effector CD4(+) T cells plays a key role in the autoimmune phenotype of Malt1-PD mice, the specific contribution of MALT1 proteolytic activity in T cells remains unclear. Using T cell-conditional Malt1 protease-dead knock-in (Malt1-PDT) mice, we here demonstrate that MALT1 has a T cell-intrinsic role in regulating the homeostasis and function of thymic and peripheral T cells. T cell-specific ablation of MALT1 proteolytic activity phenocopies mice in which MALT1 proteolytic activity has been genetically inactivated in all cell types. The Malt1-PDT mice have a reduced number of Tregs in the thymus and periphery, although the effect in the periphery is less pronounced compared to full-body Malt1-PD mice, indicating that also other cell types may promote Treg induction in a MALT1 protease-dependent manner. Despite the difference in peripheral Treg number, both T cell-specific and full-body Malt1-PD mice develop ataxia and multi-organ inflammation to a similar extent. Furthermore, reconstitution of the full-body Malt1-PD mice with T cell-specific expression of wild-type human MALT1 eliminated all signs of autoimmunity. Together, these findings establish an important T cell-intrinsic role of MALT1 proteolytic activity in the suppression of autoimmune responses

Are triple-negative tumours and basal-like breast cancer synonymous? Authors' response

We read with interest the issues raised by Rakha and colleagues [1] in their response to our recent research article [2], and we are pleased to address them. An important conclusion from our research article is that triple-negative breast cancer can be equated to basal-like breast cancer. In their letter, Rakha and colleagues [1] state that equating triple-negative phenotype (TNP) tumours with basal-like breast cancer is misleading and is not supported by the data we have presented. It is important to realize that, as we have also pointed out in our article [2], the basal-like breast cancer subtype was initially defined based on the gene expression pattern of the so-called ‘intrinsic gene list ’ in only six breast tumours [3]. Since this initial report, the intrinsic gene list that is used to identify basallike breast tumours has been updated multiple times [3-5]

Mepazine inhibits RANK-induced osteoclastogenesis independent of its MALT1 inhibitory function

Mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) is an intracellular cysteine protease (paracaspase) that plays an integral role in innate and adaptive immunity. The phenothiazine mepazine has been shown to inhibit the proteolytic activity of MALT1 and is frequently used to study its biological role. MALT1 has recently been suggested as a therapeutic target in rheumatoid arthritis. Here, we analyzed the effect of mepazine on the receptor activator of nuclear factor κ-B (RANK)-induced osteoclastogenesis. The treatment of mouse bone marrow precursor cells with mepazine strongly inhibited the RANK ligand (RANKL)-induced formation of osteoclasts, as well as the expression of several osteoclast markers, such as TRAP, cathepsin K, and calcitonin. However, RANKL induced osteoclastogenesis equally well in bone marrow cells derived from wild-type and Malt1 knock-out mice. Furthermore, the protective effect of mepazine was not affected by MALT1 deficiency. Additionally, the absence of MALT1 did not affect RANK-induced nuclear factor κB (NF-κB) and activator protein 1 (AP-1) activation. Overall, these studies demonstrate that MALT1 is not essential for RANK-induced osteoclastogenesis, and implicate a MALT1-independent mechanism of action of mepazine that should be taken into account in future studies using this compound

MALT1-deficient mice develop atopic-like dermatitis upon aging

MALT1 plays an important role in innate and adaptive immune signaling by acting as a scaffold protein that mediates NF-kappa B signaling. In addition, MALT1 is a cysteine protease that further fine tunes proinflammatory signaling by cleaving specific substrates. Deregulated MALT1 activity has been associated with immunodeficiency, autoimmunity, and cancer in mice and humans. Genetically engineered mice expressing catalytically inactive MALT1, still exerting its scaffold function, were previously shown to spontaneously develop autoimmunity due to a decrease in Tregs associated with increased effector T cell activation. In contrast, complete absence of MALT1 does not lead to autoimmunity, which has been explained by the impaired effector T cell activation due to the absence of MALT1-mediated signaling. However, here we report that MALT1-deficient mice develop atopic-like dermatitis upon aging, which is preceded by Th2 skewing, an increase in serum IgE, and a decrease in Treg frequency and surface expression of the Treg functionality marker CTLA-4

Microarray-Based Class Discovery for Molecular Classification of Breast Cancer: Analysis of Interobserver Agreement

Background Breast cancers can be classified by hierarchical clustering using an "intrinsic" gene list into one of at least five molecular subtypes: basal-like, HER2, luminal A, luminal B, and normal breast-like. Five different intrinsic gene lists composed of varying numbers of genes have been used for molecular subtype identification and classification of breast cancers. The aim of this study was to determine the objectivity and interobserver reproducibility of the assignment of molecular subtype classes by hierarchical cluster analysis. Methods Three publicly available breast cancer datasets (n = 779) were subjected to two-way average-linkage hierarchical cluster analysis using five distinct intrinsic gene lists. We used free-marginal Kappa statistics to analyze interobserver agreement among five breast cancer researchers for the whole classification and for each molecular subtype separately according to each intrinsic gene list for each breast cancer dataset. Results None of the classification systems tested produced almost perfect agreement (Kappa >= 0.81) among observers. However, substantial interobserver agreement (70.8% to 76.1% of the samples and free-marginal Kappa scores from 0.635 to 0.701) was consistently observed in all datasets for four molecular subtypes (luminal, basal-like, HER2, and normal breast-like). When luminal cancers were subdivided (luminal A, B, and C), none of the classification systems produced substantial agreement (Kappa >= 0.61) in all the datasets analyzed. Analysis of each subtype separately revealed that only two (basal-like and HER2) could be reproducibly identified by independent observers (Kappa >= 0.81). Conclusions Assignment of molecular subtype classes of breast cancer based on the analysis of dendrograms obtained with hierarchical cluster analysis is subjective and shows modest interobserver reproducibility. For the development of a molecular taxonomy, objective definitions for each molecular subtype and standardized methods for their identification are required

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions