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Aims/hypothesisIt is unclear whether type 1 diabetes is a single disease or if endotypes exist. Our aim was to use a unique collection of pancreas samples recovered soon after disease onset to resolve this issue.MethodsImmunohistological analysis was used to determine the distribution of proinsulin and insulin in the islets of pancreas samples recovered soon after type 1 diabetes onset (<2 years) from young people diagnosed at age <7 years, 7–12 years and ≥13 years. The patterns were correlated with the insulitis profiles in the inflamed islets of the same groups of individuals. C-peptide levels and the proinsulin:C-peptide ratio were measured in the circulation of a cohort of living patients with longer duration of disease but who were diagnosed in these same age ranges.ResultsDistinct patterns of proinsulin localisation were seen in the islets of people with recent-onset type 1 diabetes, which differed markedly between children diagnosed at <7 years and those diagnosed at ≥13 years. Proinsulin processing was aberrant in most residual insulin-containing islets of the younger group but this was much less evident in the group ≥13 years (p < 0.0001). Among all individuals (including children in the middle [7–12 years] range) aberrant proinsulin processing correlated with the assigned immune cell profiles defined by analysis of the lymphocyte composition of islet infiltrates. C-peptide levels were much lower in individuals diagnosed at <7 years than in those diagnosed at ≥13 years (median <3 pmol/l, IQR <3 to <3 vs 34.5 pmol/l, IQR <3–151; p < 0.0001), while the median proinsulin:C-peptide ratio was increased in those with age of onset <7 years compared with people diagnosed aged ≥13 years (0.18, IQR 0.10–0.31) vs 0.01, IQR 0.009–0.10 pmol/l; p < 0.0001).Conclusions/interpretationAmong those with type 1 diabetes diagnosed under the age of 30 years, there are histologically distinct endotypes that correlate with age at diagnosis. Recognition of such differences should inform the design of future immunotherapeutic interventions designed to arrest disease progression.

p53 immunohistochemistry is considered an accurate surrogate marker reflecting the underlying TP53 mutation status and has utility in tumor diagnostics. In the present study, 269 primary CRCs were immunohistochemically evaluated for p53 expression to assess its utility in diagnostic pathology and prognostication. p53 expression was wild-type in 59 cases (23%), overexpressed in 143 cases (55%), completely lost in 50 cases (19%), and cytoplasmic in 10 cases (4%). p53 immunoreactivity was associated with tumor size (p = 0.0056), mucus production (p = 0.0015), and mismatch repair (MMR) system status (p < 0.0001). Furthermore, among CRCs with wild-type p53 expression, a significantly higher number of cases had decreased CDX2 than those with p53 overexpression (p = 0.012) or complete p53 loss (p = 0.043). In contrast, among CRCs with p53 overexpression, there were significantly fewer ALCAM-positive cases than p53 wild-type cases (p = 0.0045). However, no significant association was detected between p53 immunoreactivity and the “stem-like” immunophenotype defined by CDX2 downregulation and ALCAM-positivity. Multivariate Cox hazards regression analysis identified tubular-forming histology (hazard ratio [HR] = 0.17, p < 0.0001), younger age (HR = 0.52, p = 0.021), and female sex (HR = 0.55, p = 0.046) as potential favorable factors. The analysis also revealed complete p53 loss (HR = 2.16, p = 0.0087), incomplete resection (HR = 2.65, p = 0.0068), and peritoneal metastasis (HR = 5.32, p < 0.0001) as potential independent risk factors for patients with CRC. The sub-cohort survival analyses classified according to chemotherapy after surgery revealed that CRC patients with wild-type p53 expression tended to have better survival than those with overexpression or complete loss after chemotherapy. Thus, immunohistochemistry for p53 could be used for the prognostication and chemotherapy target selection of patients with CRC.

To define differences in tumor microenvironment (TME) immune phenotypes between right and left colorectal cancers (CRCs) and explore their therapeutic implications. Gene expression profiling and clinical characteristics of patients with CRC were retrieved from The Cancer Genome Atlas data portal. Immune cell infiltration was estimated based on single-sample gene set enrichment analysis. CRCs tissue microarrays (TMAs) containing 90 consecutive cases of surgical samples were used for validation. Expression of CD8A and VEGFA was confirmed by immunohistochemistry (IHC) analysis with TMAs, and overall survival (OS) was analyzed. Expression profiling data demonstrated that CRC immune microenvironment from right side tumor was characterized as increased infiltration of immune cells with enhanced cytotoxic function, based on higher cytotoxic activity scores (CYT) and interferon-γ signatures. Expression of VEGFA, which could be neutralized by bevacizumab, was associated with decreased levels of activated CD8 T-cells, Th1 cells, and PRF1 expression on the right side, but not on the left side. IHC analysis of TMAs further confirmed an inverse correlation between CD8A and VEGFA expression, and revealed a favorable OS for patients with CD8A VEGFA disease among right-side CRCs. For the left side, higher CD56 natural killer cell infiltration and active 4-1BB/IFN-ɑ signaling, which could providing a favorable condition for cetuximab-mediated antibody-dependent cell-mediated cytotoxicity effect, was present in a cohort with extended OS. In the TME, features of immune phenotype sidedness were identified, providing an implication for differential responses to bevacizumab/cetuximab treatment. In addition, a new avenue for innovative experimental design and combinational immunotherapy to treat CRC patients was suggested.

Objectives We sought to investigate the morphologic and immunophenotypic characteristics of TCL1 family–negative T-cell prolymphocytic leukemia (T-PLL) Methods Twenty cases of TCL1 family–negative T-PLL were studied. Results The doubling time of leukemic cells ranged from less than 2 days to more than 5 years, with a median of 5.5 months. Leukemic cells were small to medium-sized, with round to irregular nuclei, variably condensed chromatin, and small amounts of agranular cytoplasm. A visible nucleolus was identified in 11 (55%) cases. Cytoplasmic blebs/protrusions were identified in all cases, but their occurrence was highly variable from case to case. Bone marrow biopsy showed an interstitial pattern in 90% of cases and a diffuse pattern in the remaining 10% of cases. Flow cytometric immunophenotypic analysis showed that the leukemic cells in all cases were CD4 positive; 3 (15%) also showed concurrent CD8 expression. All cases were positive for CD2 and CD5. Surface CD3 and CD7 were positive in 19 of 20 (95%) cases, and all CD3-positive cases expressed the T-cell receptor αβ. Compared with prototypic T-PLL cases, these 2 groups shared many immunophenotypic findings, except CD8 and CD26, both of which were more commonly expressed in prototypic T-PLL cases. Conclusions TCL1 family–negative T-PLL cases have morphologic and immunophenotypic features that are similar to prototypic T-PLL. They are characterized by neoplastic proliferation of small to medium-sized mature T cells with CD4-positive T-cell receptor αβ phenotype. Tumor cells frequently maintain pan-T antigen expression. Recognizing these morphologic and immunophenotypic features will aid in accurately diagnosing this rare subset of T-PLL.

Objective: There is a particular lack of studies on the immune response of camels to cold stress conditions. The present study aimed, therefore, at the ex vivo investigation of the effect of a sudden decline in ambient temperature on some phenotypic and functional immunological parameters in camels. Materials and Methods: Using flow cytometry and antibody staining, leukocyte composition, distribution of lymphocyte subsets, and the expression of some cell activation markers were analyzed in camels under normal temperatures and a few days following a sudden environmental temperature decrease. In addition, phagocytosis activity and capacity of neutrophils and monocytes incubated ex vivo with Zymosan A Bioparticles or Staphylococcus aureus were comparatively investigated before and after cold exposure of the camels. Results: Exposure of the camels to low ambient temperatures resulted in a significant increase in the total white blood cell count and the absolute counts of neutrophils and lymphocytes. On the other hand, the decrease in monocyte counts after cold exposure resulted in a decreased lymphocyte-to-monocyte ratio. In addition, ex vivo analysis of phagocytosis and activation marker expression revealed reduced phagocytosis activity and capacity, as well as the downregulation of the activation markers CD44 and lymphocyte function-associated antigen 1 on leukocytes from the camels after cold exposure. Conclusion: The current study identified a significant impact of exposure to low ambient temperatures on the distribution of leukocyte subpopulations in camel blood. In addition, ex vivo analysis of phagocytosis revealed the impaired innate antimicrobial function of phagocytes in camels under cold stress. The underlying mechanisms for the observed effects of cold stress on the camel’s immune system and their clinical significance for camel health remain to be elucidated in further studies.

The tumor microenvironment is a complex network of various interactions between immune cells and non-cellular components such as the extracellular matrix, exosomes and interleukins. Moreover, tumor heterogeneity and its constant modification may alter the immunophenotype and become responsible for its resistance regarding the therapies applied However, it should be remembered that in a strongly immunosuppressive neoplastic microenvironment, the immune system cells undergo reprogramming and most often cease to fulfill their original function. Therefore, understanding what happens within the tumor microenvironment, and which mechanisms are responsible for tumor development and progression should let us know how cancer could protect itself against the immune system. The presented review summarizes the latest information on the interactions between the tumor microenvironment and the cellular and non-cellular components, as well as their impact on cancer development, progression and immune system exhaustion.

Immune-checkpoint blockades (ICBs) have been routinely implemented to treat metastatic urothelial cancer (mUC), whereas robust biomarkers are urgently warranted. Herein, we explored latent promising biomarkers based on 348 pretreatment mUC samples from IMvigor210. The genome, transcriptome, immunome, and metabolome were systemically analyzed using the external TCGA dataset for validation. Kaplan-Meier and ROC curve analyses were performed to estimate the predictive capacity of M1-macrophage infiltration. Chi-square/Spearman/Mann Whitney U test are used to determine its correlation to genetic, biochemical, and clinicopathological parameters. M1 frequency is a robust biomarker for predicting the prognosis and response to ICBs, which is non-inferior to tumor mutation burden (TMB) or tumor neoantigen burden (TNB), and exceeds CD8 T cells, T cell inflamed gene expression profile (GEP), and PD-L1 expression. Moreover, M1 infiltration is associated with immune phenotypes (AUC = 0.785) and is negatively correlated with immune exclusion. Additionally, transcriptomic analysis showed immune activation in the high-M1 subgroup, whereas it showed steroid and drug metabolism reprograming in the M1-deficient subset, which characterized the limited sensitivity to ICB therapy. Notably, investigation of the corresponding intrinsic genomic profiles highlighted the significance of and alterations. M1 infiltration is a robust biomarker for immunotherapeutic response and immunophenotype determination in an mUC setting. Innate immunity activation involving macrophage polarization remodeling and anti- mutations may be promising strategies for synergy with anti-PD-L1 treatments and may help prolong the clinical survival of patients with mUC.

The development and progression of colorectal cancer (CRC) are known to be affected by the interplay between tumor and immune cells. However, the impact of CRC cells on the systemic immunity has yet to be elucidated. We aimed to comprehensively evaluate the circulating immune subsets and transcriptional profiles of CRC patients. In contrast to healthy controls (HCs), CRC patients had a lower percentage of B and T lymphocytes, T helper (Th) cells, non-classical monocytes, dendritic cells, and a higher proportion of polymorphonuclear myeloid-derived suppressor cells, as well as a reduced expression of CD69 on NK cells. Therefore, CRC patients exhibit a more evident systemic immune suppression than HCs. A diagnostic model integrating seven immune subsets was constructed to distinguish CRC patients from HCs with an AUC of 1.000. Moreover, NR3C2, CAMK4, and TRAT1 were identified as candidate genes regulating the number of Th cells in CRC patients. The altered composition of circulating immune cells in CRC could complement the regional immune status of the tumor microenvironment and contribute to the discovery of immune-related biomarkers for the diagnosis of CRC.

Our study aimed to develop a machine learning (ML) model to accurately classify acute promyelocytic leukemia (APL) from other types of acute myeloid leukemia (other AML) using multicolor flow cytometry (MFC) data. Multicolor flow cytometry is used to determine immunophenotypes that serve as disease signatures for diagnosis. We used a data set of MFC files from 27 patients with APL and 41 patients with other AML, including those with uncommon immunophenotypes. Our ML pipeline involved training a graph neural network (GNN) to output graph-level labels and identifying the most crucial MFC parameters and cells for predictions using an input perturbation method. The top-performing GNN achieved 100% accuracy on the training/validation and test sets on classifying APL from other AML and used MFC parameters similarly to expert pathologists. Pipeline performance is amenable to use in a clinical decision support system, and our deep learning architecture readily enables prediction explanations. Our ML pipeline shows robust performance on predicting APL and could be used to screen for APL using MFC data. It also allowed for intuitive interrogation of the model's predictions by clinicians.

Mesenchymal stem cells (MSCs) can be isolated from not only bone marrow, but also various adult mesenchymal tissues such as periosteum, skeletal muscle, and adipose tissue. MSCs from different tissue sources have different molecular phenotypes and differentiation potential. Synovial membrane (SM) is an important and highly specific component of synovial joints. Previous studies have suggested that the synovium is a structure with a few cell layers thick and consists mainly of fibroblast-like synoviocytes (FLS), which forms a layer that lining the synovial membrane on the joint cavity and synovial fluid through cell-cell contact. In recent years, studies have found that there are also mesenchymal stem cells in the synovium, and as an important part of the mesenchymal stem cell family, it has strong capabilities of cartilage forming and tissue repairing. This article reviews the sources, surface markers, subtypes, influencing factors, and applications in inflammatory joints of synovial membrane mesenchymal stem cells (SM-MSCs) in recent years, aiming to clarify the research status and existing problems of SM-MSCs.