Synaptojanin 2 is recognized by HLA class II-restricted hairy cell leukemia-specific T cells

SYNJ2 is a novel and potential biomarker for the prediction and treatment of cancers: from lung squamous cell carcinoma to pan-cancer

BACKGROUND

The roles and clinical values of synaptojanin 2 (SYNJ2) in lung squamous cell carcinoma (LUSC) remain unclear.

METHODS

A total of 2824 samples from multi-center were collected to identify the expression of SYNJ2 in LUSC by using Wilcoxon rank-sum test, t-test, and standardized mean difference (SMD), and 194 in-house samples were also included to validate SYNJ2 expression in LUSC. The clinical roles of SYNJ2 were investigated via receiver operating characteristic (ROC) curves, univariate Cox regression analysis, and Kaplan-Meier plots. The underlying mechanisms of SYNJ2 in LUSC were explored by gene set enrichment analysis and immune correlation analysis. Further, a pan-cancer analysis based on 10,238 sapiens was performed to promote the understating of the expression and clinical significance of SYNJ2 in multiple human cancers.

RESULTS

SYNJ2 was found to be significantly upregulated in LUSC at both mRNA and protein levels (p < 0.05, SMD = 0.89 [95% CI 0.34-1.45]) via public and in-house samples. Overexpressed SYNJ2 predicted poor prognosis for LUSC patients (hazard ratio = 2.38 [95% CI 1.42-3.98]). The cancer-promoting effect of SYNJ2 may be related to protein digestion and absorption and extracellular matrix-receptor interaction. SYNJ2 expression was closely related to immune cell infiltration, indicating its role in the immune response. Moreover, the distinct expression levels and essential clinical relevance of SYNJ2 in a series of cancers were initially revealed in this study.

CONCLUSIONS

This study disclosed the clinical significance of SYNJ2 in LUSC and multiple cancers, demonstrating the novel and potential biomarker for predicting and treating cancers.

Membrane trafficking in health and disease

Membrane trafficking pathways are essential for the viability and growth of cells, and play a major role in the interaction of cells with their environment. In this At a Glance article and accompanying poster, we outline the major cellular trafficking pathways and discuss how defects in the function of the molecular machinery that mediates this transport lead to various diseases in humans. We also briefly discuss possible therapeutic approaches that may be used in the future treatment of trafficking-based disorders.

Summary: This At a Glance article and poster summarise the major intracellular membrane trafficking pathways and associated molecular machineries, and describe how defects in these give rise to disease in humans.

Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation

In order to provide the most effective therapy for cancer, it is important to be able to diagnose whether a patient's cancer will respond to a proposed treatment. Methylation profiling could contain information from which such predictions could be made. Currently, hypothesis testing is used to determine whether possible biomarkers for cancer progression produce statistically significant results. However, this approach requires the identification of individual genes, or sets of genes, as candidate hypotheses, and with the increasing size of modern microarrays, this task is becoming progressively harder. Exhaustive testing of small sets of genes is computationally infeasible, and so hypothesis generation depends either on the use of established biological knowledge or on heuristic methods. As an alternative machine learning, methods can be used to identify groups of genes that are acting together within sets of cancer data and associate their behaviors with cancer progression. These methods have the advantage of being multivariate and unbiased but unfortunately also rapidly become computationally infeasible as the number of gene probes and datasets increases. To address this problem, we have investigated a way of utilizing prior knowledge to segment microarray datasets in such a way that machine learning can be used to identify candidate sets of genes for hypothesis testing. A methylation dataset is divided into subsets, where each subset contains only the probes that relate to a known gene pathway. Each of these pathway subsets is used independently for classification. The classification method is AdaBoost with decision trees as weak classifiers. Since each pathway subset contains a relatively small number of gene probes, it is possible to train and test its classification accuracy quickly and determine whether it has valuable diagnostic information. Finally, genes from successful pathway subsets can be combined to create a classifier of high accuracy.

Update on the biology and treatment options for hairy cell leukemia

Hairy cell leukemia (HCL) is an uncommon chronic leukemia of mature B cells. Leukemic B cells of HCL exhibit a characteristic morphology and immunophenotype and coexpress multiple clonally related immunoglobulin isotypes. Precise diagnosis and detailed workup is essential, because the clinical profile of HCL can closely mimic that of other chronic B-cell lymphoproliferative disorders that are treated differently. Variants of HCL, such as HCLv and VH4-34 molecular variant, vary in the immunophenotype and specific VH gene usage, and have been more resistant to available treatments. On the contrary, classic HCL is a highly curable disease. Most patients show an excellent long-term response to treatment with single-agent cladribine or pentostatin, with or without the addition of an anti-CD20 monoclonal antibody such as rituximab. However, approximately 30-40 % of patients with HCL relapse after therapy; this can be treated with the same purine analogue that was used for the initial treatment. Advanced molecular techniques have identified distinct molecular aberrations in the Raf/MEK-ERK pathway and BRAF (V600E) mutations that drive the proliferation and survival of HCL B cells. Currently, research in the field of HCL is focused on identifying novel therapeutic targets and potential agents that are safe and can universally cure the disease. Ongoing and planned clinical trials are assessing various treatment strategies, such as the combination of purine analogues and various anti-CD20 monoclonal antibodies, recombinant immunotoxins targeting CD22 (e.g., moxetumomab pasudotox), BRAF inhibitors, such as vemurafenib, and B-cell receptor signaling inhibitors, such as ibrutinib, which is a Bruton's tyrosine kinase inhibitor. This article provides an update of our current understanding of the pathophysiology of HCL and the treatment options available for patients with classic HCL. Discussion of variant forms of HCL is beyond the scope of this manuscript.

The biology of hairy-cell leukaemia

PURPOSE OF REVIEW

The biology of hairy-cell leukaemia is reviewed, focussing first on the hairy cell itself and then on its interactions with the microenvironment.

RECENT FINDINGS

Hairy cells are highly activated clonal B cells related to memory cells, normally resident in the marginal zone of the spleen. Their activation results from multiple stimuli arising from the microenvironment, autocrine cytokines and the still unknown transforming oncogenic event(s) responsible for the disease. Protein kinase Cepsilon is a central player in the activation process.

SUMMARY

The activation of hairy cells makes them unusually sensitive to interferon and nucleosides. Future important research topics include characterization of the oncogenic events responsible for the disease and for its associated differentiation block.

Characterization of T-cell repertoire in hairy cell leukemia patients before and after recombinant immunotoxin BL22 therapy

We previously reported that hairy cell leukemia (HCL) patients have high percentages of CD56+/CD57+/CD3+ large granular lymphocytes consistent with cytotoxic T-lymphocytes (CTLs), and other investigators have reported skewing of the T-cell repertoire. In previous studies of up to seven HCL patients, many of the 22 established T-cell receptor (TCR) beta variable region (TRBV) families showed mono- or oligoclonal restriction. To determine whether percentages of CTLs are correlated with TRBV clonal excess, we studied 20 HCL patients with flow cytometry, PCR of TCR gamma and TRBV regions, and fractional gel electrophoresis of PCR-amplified TRBV CDR3 domains (CDR3 spectratyping). Increased percentages of CD3+/CD8+/CD57+ CTLs correlated with more mono/oligoclonal and fewer polyclonal TRBV families (r=0.53; P=0.016). Age correlated with number of mono/oligoclonal TRBV families (r=0.51; P=0.022). Time since last purine analog therapy correlated with number of polyclonal TRBV families (r=0.46; P=0.040), but treatment with the anti-CD22 recombinant immunotoxin BL22 was not related to clonal excess. We conclude that abnormalities in the T-cell repertoire in HCL patients may represent deficient immunity, and may be exacerbated by purine analogs. Increased CD3+/CD57+ T-cells may be a useful marker of abnormal TRBV repertoire in HCL patients, and might prove useful in deciding whether patients should receive biologic antibody-based treatment rather than repeated courses of purine analog for relapsed disease.