Blocking ATM-dependent NF-κB pathway overcomes niche protection and improves chemotherapy response in acute lymphoblastic leukemia.

Bone marrow (BM) niche responds to chemotherapy-induced cytokines secreted from acute lymphoblastic leukemia (ALL) cells and protects the residual cells from chemotherapeutics in vivo. However, the underlying molecular mechanisms for the induction of cytokines by chemotherapy remain unknown. Here, we found that chemotherapeutic drugs (e.g., Ara-C, DNR, 6-MP) induced the expression of niche-protecting cytokines (GDF15, CCL3 and CCL4) in both ALL cell lines and primary cells in vitro. The ATM and NF-κB pathways were activated after chemotherapy treatment, and the pharmacological or genetic inhibition of these pathways significantly reversed the cytokine upregulation. Besides, chemotherapy-induced NF-κB activation was dependent on ATM-TRAF6 signaling, and NF-κB transcription factor p65 directly regulated the cytokines expression. Furthermore, we found that both pharmacological and genetic perturbation of ATM and p65 significantly decreased the residual ALL cells after Ara-C treatment in ALL xenograft mouse models. Together, these results demonstrated that ATM-dependent NF-κB activation mediated the cytokines induction by chemotherapy and ALL resistance to chemotherapeutics. Inhibition of ATM-dependent NF-κB pathway can sensitize ALL to chemotherapeutics, providing a new strategy to eradicate residual chemo-resistant ALL cells.

Simultaneous targeting of PI3Kδ and a PI3Kδ-dependent MEK1/2-Erk1/2 pathway for therapy in pediatric B-cell acute lymphoblastic leukemia.

B cell acute lymphoblastic leukemia (B-ALL) is the most common hematological malignancy diagnosed in children, and blockade of the abnormally activated PI3Kδ displayed promising outcomes in B cell acute or chronic leukemias, but the mechanisms are not well understood. Here we report a novel PI3Kδ selective inhibitor X-370, which displays distinct binding mode with p110δ and blocks constitutively active or stimulus-induced PI3Kδ signaling. X-370 significantly inhibited survival of human B cell leukemia cells in vitro, with associated induction of G1 phase arrest and apoptosis. X-370 abrogated both Akt and Erk1/2 signaling via blockade of PDK1 binding to and/or phosphorylation of MEK1/2. Forced expression of a constitutively active MEK1 attenuated the antiproliferative activity of X-370. X-370 preferentially inhibited the survival of primary pediatric B-ALL cells displaying PI3Kδ-dependent Erk1/2 phosphorylation, while combined inhibition of PI3Kδ and MEK1/2 displayed enhanced activity. We conclude that PI3Kδ inhibition led to abrogation of both Akt and Erk1/2 signaling via a novel PI3K-PDK1/MEK1/2-Erk1/2 signaling cascade, which contributed to its efficacy against B-ALL. These findings support the rationale for clinical testing of PI3Kδ inhibitors in pediatric B-ALL and provide insights needed to optimize the therapeutic strategy.

[Expression of zinc finger protein X-linked in childhood B lineage acute lymphoblastic leukemia].

OBJECTIVE: To study the expression of zinc finger protein X-linked (ZFX) in bone marrow mononuclear cells (BMMCs) of children with B lineage acute lymphoblastic leukemia (B-ALL) and its relationship with prognosis. METHODS: The expression of ZFX in human leukemia cell lines (REH, HL-60, NB(4) and K562) was measured by Western blot. ZFX gene was cloned by PCR from one patient and DNA sequencing technology was used to confirm it. Real-time PCR was used for detecting ZFX mRNA expression in the BMMCs of 82 children with newly-diagnosed B-ALL, 24 children with complete remission (CR) after induction therapy and 64 control children (fracture or congenital heart disease patients). According to the presence of bone marrow or central nervous system relapse during a follow-up of 3 years, the patients were identified as having a good or poor prognosis. Their ZFX mRNA levels in BMMCs at diagnosis were compared. RESULTS: ZFX protein was expressed in human leukemia cell lines REH, HL-60, NB(4) and K562. ZFX mRNA expression was significantly higher in the newly-diagnosed ALL group than in the control group (P < 0.01). ZFX mRNA expression in the ALL CR group was significantly reduced compared with the newly-diagnosed ALL group (P < 0.01). Children with a poor prognosis had significantly higher ZFX mRNA levels at diagnosis than those with a good prognosis (P < 0.05). CONCLUSIONS: ZFX is over-expressed in children with B-ALL and its levels are higher in those with a poor prognosis than those with a good prognosis, which suggests that ZFX is important in the prognosis evaluation of B-ALL.

[Hyperspectral feature band selection based on mean confidence interval and tree species discrimination].

In the present study, based on the leaf-level hyperspectral data of BaiMu, LeiZhu and WuHuanZi, the authors come up with two solutions through the theory of statistics; the first one is that optimal discriminating band between tree species is extracted by mean interval confidence, the other one is that tree species is discriminated by the Manhattan distance and the Min Max interval similarity. The research results showed that (1) the optimal discriminating bands between BaiMu and LeiZhu are around 350-446, 497-527, 553-1 330, 1 355-2 400 and 2 436-2 500 nm; the optimal discriminating bands between BaiMu and WuHuanZi are around 434-555, 580-1 903, 1 914-2 089, 2 172-2 457 and 2 475-2 500 nm; the optimal discriminating bands between LeiZhu and WuHuanZi are around 434-555, 580-1 903, 1 914-2 089, 2 172-2 457 and 2 475-2 500 nm; and this result is helpful for us to find maximum difference to identifying tree species respectively. (2) In these optimal discriminating bands, we find that the Manhattan distance between the same species is far less than the different species; but the Min-Max interval similarity between the same species is far more than the different species, so this result could help us to discriminate and identify different types of tree species effectively.

[Hyperspectral Bambusoideae discrimination based on Mann-Whitney non-parametric test and SVM].

In the present study, based on the leaf-level hyperspectral data of MaoZhu, LeiZhu and XiaoShunZhu, We come up with two solutions to discrimination through the theory of non-parametric test and pattern recognition; the first one is that optimal discriminating band between bambusoideae species is extracted by Mann-Whitney non-parametric test, the other is that bambusoideae species is discriminated by the support vector machine. The research results showed that (1) the optimal discriminating band between MaoZhu and LeiZhu is around 503-655, 689-732, 757-1 000, 1 038-1 084, 1 238-1 311, 1 404-1 591, 1682-1 800, 1 856-1 904, and 1 923-2 500 nm; the optimal discriminating band between MaoZhu and XiaoShunZhu is around 350-386, 731-1 430, 1 584-1 687, and 1 796-1 873 nm; the optimal discriminating band between LeiZhu and XiaoShunZhu is around 355-356, 498-662, 689-745, and 1 344-2 500 nm; and it can eliminate 30.0%, 57.7%, and 35.8% of the invalid distinction between bands by Mann-Whitney non-parametric test method. (2) In these optimal discriminating bands, we found that the accuracy of bambusoideae discrimination is 98.4%, 93.5%, and 95.1%, the generalization accuracy is 93.3%, 90.0%, and 86.7% by sequential minimal optimization algorithm. It indicates that this method is valid for selecting feature band and discriminating bambusoideae species.

[Raman spectroscopy fluorescence background correction and its application in clustering analysis of medicines].

During Raman spectroscopy analysis, the organic molecules and contaminations will obscure or swamp Raman signals. The present study starts from Raman spectra of prednisone acetate tablets and glibenclamide tables, which are acquired from the BWTek i-Raman spectrometer. The background is corrected by R package baselineWavelet. Then principle component analysis and random forests are used to perform clustering analysis. Through analyzing the Raman spectra of two medicines, the accurate and validity of this background-correction algorithm is checked and the influences of fluorescence background on Raman spectra clustering analysis is discussed. Thus, it is concluded that it is important to correct fluorescence background for further analysis, and an effective background correction solution is provided for clustering or other analysis.

[Tree species discrimination based on leaf-level hyperspectral characteristic analysis].

The emergence of hyperspectral remote sensing technology will provide chance for solving problems of identifying forest tree species precisely. For discrimination of tree species with hyperspectral remote sensing technology, extraction and selection of the spectral characteristics is a very important process. Compared with multispectral data, hyperspectral data have the characteristics of more bands, larger amount of data and larger redundancy degree. The method of derivative reflectance was used to deal with the original spectral data, analyze and compare curves of the original spectrum, the first derivative reflectance and second derivative reflectance of the different tree species, and the bands with bigger difference were selected to identify the different tree species. Then the Euclidean distance method was used to test the selective bands identifying different tree species, and the results showed that the selective bands could identify different tree species effectively. The bands for identifying different tree species were most near-infrared bands, and the bands with maximum difference derived from the three methods are 1,657-1,666, 1,868-1,877 and 1,868-1,877 nm respectively.