Clinical characteristics and analysis of related factors associated with early death in newly diagnosed patients with acute promyelocytic leukemia.

OBJECTIVE: The objective of this study was to investigate the clinical characteristics and analysis of related factors associated with early death in newly diagnosed patients with acute promyelocytic leukemia (APL). METHODS: This retrospective study included patients who visited our hospital between January 2010 and August 2022 and were diagnosed with APL for the first time. We analyzed their clinical and laboratory characteristics and analysis of related factors associated with early death. RESULTS: A total of 269 patients with a primary diagnosis of APL were collected. The male to female ratio was 6:5, and the median age was 42 years (range 7-80). Among patients with initial APL diagnosis, there were 34 early deaths, resulting in an early mortality rate of 13%. The median time from diagnosis to death was 8.5 days (range 3-24). Comparative analysis of the clinical characteristics between patients who died early and those who did not, using a logistic regression model, revealed that age, white blood cell count (WBC) at initial diagnosis, and prolongation time of prothrombin time (PT) were independent risk factors for early death in patients with primary APL (P < 0.05). Comparing the clinical characteristics during hospitalization between the early death group and the non-early death group, it was observed that the daily mean of WBC during hospitalization was significantly higher in patients who died early than in those who did not (P < 0.001). Conversely, the daily mean of platelet count (PLT) was significantly lower in patients who died early compared to those who did not (P < 0.001). Furthermore, statistically significant differences were found in the mean daily infusion of PLT (P < 0.05), fibrinogen (Fib) (P < 0.05), and fresh frozen plasma (FFP) (P < 0.05) during hospitalization between patients who died early and those who did not. Specifically, the mean daily infusion of PLT and FFP was significantly higher in the early-death group than in the non-early-death group. Cerebral hemorrhage was identified as the immediate cause of death in 25 out of the 34 early-death patients (74%). The remaining causes of death included infection in 5 cases (15%), all of which were severe pulmonary infections, including 2 cases of combined differentiation syndrome, and abandonment of treatment in 4 patients (11%) at initial diagnosis. CONCLUSION: In patients with primary APL, age, WBC at initial diagnosis, and PT prolongation time were identified as independent risk factors for early death (P < 0.05). Laboratory findings regarding WBC and PLT during hospitalization, as well as the infusion of PLT, Fib, and FFP during hospitalization, were also statistically significant. Cerebral hemorrhage was found to be the main cause of early death in patients with primary APL.

Conceptual breakthroughs of the long noncoding RNA functional system and its endogenous regulatory role in the cancerous regime.

Long noncoding RNAs (lncRNAs) derived from noncoding regions in the human genome were once regarded as junks with no biological significance, but recent studies have shown that these molecules are highly functional, prompting an explosion of studies on their biology. However, these recent efforts have only begun to recognize the biological significance of a small fraction (< 1%) of the lncRNAs. The basic concept of these lncRNA functions remains controversial. This controversy arises primarily from conventional biased observations based on limited datasets. Fortunately, emerging big data provides a promising path to circumvent conventional bias to understand an unbiased big picture of lncRNA biology and advance the fundamental principles of lncRNA biology. This review focuses on big data studies that break through the critical concepts of the lncRNA functional system and its endogenous regulatory roles in all cancers. lncRNAs have unique functional systems distinct from proteins, such as transcriptional initiation and regulation, and they abundantly interact with mitochondria and consume less energy. lncRNAs, rather than proteins as traditionally thought, function as the most critical endogenous regulators of all cancers. lncRNAs regulate the cancer regulatory regime by governing the endogenous regulatory network of all cancers. This is accomplished by dominating the regulatory network module and serving as a key hub and top inducer. These critical conceptual breakthroughs lay a blueprint for a comprehensive functional picture of the human genome. They also lay a blueprint for combating human diseases that are regulated by lncRNAs.

Palbociclib promotes the antitumor activity of Venetoclax plus Azacitidine against acute myeloid leukemia.

Around 70 % of patients diagnosed with acute myeloid leukemia (AML) survive less than 5 years due to drug resistance and disease relapse. Consequently, improved clinical treatments are urgently needed. Some but not all AML patients benefit from the combination of the BCL-2 inhibitor Venetoclax with the hypomethylation agent Azacitidine. Here we investigated the utility of employing the cyclin dependent kinase (CDK6) inhibitor Palbociclib to improve the efficacy of Venetoclax/Azacitidine combination therapy. Our analysis of publicly available RNA sequencing datasets showed CDK6 was highly expressed in the major acute forms of leukemia including AML. Consistently, using qPCR and flow cytometry we found that CDK6 was overexpressed in bone marrow mononuclear cells from AML patients compared to healthy controls. Subsequent in vitro testing of Palbociclib, Venetoclax and Azacitidine, alone and in combination against CDK6-overexpressing AML cells lines THP-1 and KG-1 and primary AML cells showed that the Palbociclib/Venetoclax/Azacitidine combination improved treatment efficacy compared to Venetoclax/Azacitidine treatment alone. Additional investigations in a subcutaneous KG-1 mouse model showed similarly the three-drug combination produced the most significant reductions in tumor load together with the least amount of spleen infiltration. We established Palbociclib functioned in combination with Venetoclax/Azacitidine by increasing the rates of apoptosis in AML cells. Further investigations revealed that Palbociclib does not affect BCL-2 activity but downregulated the anti-apoptotic proteins MCL-1 and BCL-XL, making AML cells more sensitive to Venetoclax/Azacitidine treatment. Our results propose that the Palbociclib/Venetoclax/Azacitidine regimen warrants further preclinical research for clinical application in AML patients.

Correlation Analysis and Prognostic Impacts of Biological Characteristics in Elderly Patients with Acute Myeloid Leukemia.

Background: The significant heterogeneity of elderly AML patients' biological features has caused stratification difficulties and adverse prognosis. This paper did a correlation study between their genetic mutations, clinical features, and prognosis to further stratify them. Methods: 90 newly diagnosed elderly acute myeloid leukemia (AML) patients (aged ≥60 years) who detected genetic mutations by next-generation sequencing (NGS) were enrolled between April 2015 and March 2021 in our medical center. Results: A total of 29 genetic mutations were identified in 82 patients among 90 cases with a frequency of 91.1%. DNMT3A, BCOR, U2AF1, and BCORL1 mutations were unevenly distributed among different FAB classifications (p < 0.05). DNMT3A, IDH2, NPM1, FLT3-ITD, ASXL1, IDH1, SRSF2, BCOR, NRAS, RUNX1, U2AF1, MPO, and WT1 mutations were distributed differently when an immunophenotype was expressed or not expressed (p<0.05). NPM1 and FLT3-ITD had higher mutation frequencies in patients with normal chromosome karyotypes than abnormal chromosome karyotypes (p<0.001, p=0.005). DNMT3A and NRAS mutations predicted lower CR rates. DNMT3A, TP53, and U2AF1 mutations were related to unfavorable OS. TET2 mutation with CD123+, CD11b+ or CD34- predicted lower CR rate. IDH2+/CD34- predicted lower CR rate. ASXL1+/CD38+ and SRSF2+/CD123- predicted shorter OS. Conclusion: The study showed specific correlations between elderly AML patients' genetic mutations and clinical features, some of which may impact prognosis.

[Clinical Study on Dynamic Detection of Minimal Residual Disease in Acute Myeloid Leukemia by Multiparameter Flow Cytometry].

OBJECTIVE: To investigate the prognostic significance of dynamic detection of minimal residual disease (MRD) in patients with acute myeloid leukemia (AML) by 8-color flow cytometry. METHODS: MRD of 282 AML patients who achieved remission after initial therapy was detected by 8-color flow cytometry. MRD threshold for predicting recurrence was determined by receiver operating characteristic (ROC) curve, and time from MRD-positive to clinical recurrence was analyzed. The differences in overall survival (OS) time and relapse-free survival (RFS) time of patients with different MRD-changes were compared, and the related factors of recurrence in patients with MRD-negative were analyzed by univariate and logistic regression analysis. RESULTS: ROC curve determined that the MFC-MRD threshold for predicting the recurrence of AML was 0.105%, and the recurrence rate of MRD-positive patients was significantly higher than that of MRD-negative patients [52.45% (75/143 cases) vs 35.97% (50/139 cases), P=0.005]. The patients in MRD persistent positive group and negative to positive group recurred earlier than those in positive to negative group and negative-positive fluctuation group (P<0.005). Survival analysis showed that OS and RFS time of patients with MRD persistent positive were significantly shorter than those of patients with MRD persistent negative, positive to negative, and negative-positive fluctuation (P<0.005). There was no significant difference in OS and RFS between MRD negative to positive group and MRD persistent positive group (P>0.005), either between MRD persistent negative group and MRD positive to negative group (P>0.005). Among 139 MRD-negative patients, 50 recurred. Univariate and logistic regression analysis showed that the risk of recurrence increased with the increase of white blood cells level (95%CI: 1.000-1.013, P=0.045). The risk of recurrence in patients without hematopoietic stem cell transplantation (HSCT) was 9.694 times higher than that in patients who received HSCT (95%CI: 1.720-54.651, P=0.010), and in the high-risk group was 5.848 times higher than that in the low-risk group (95%CI: 1.418-24.121, P=0.015). CONCLUSION: The prognosis of AML patients with different MRD changes is significantly different. No matter MRD-positive or MRD-negative at the initial remission, dynamic detection of MRD after treatment is more helpful to accurately guide treatment.

Noncoding RNAs endogenously rule the cancerous regulatory realm while proteins govern the normal.

Cancers evolve from normal tissues and share an endogenous regulatory realm distinctive from that of normal human tissues. Unearthing such an endogenous realm faces challenges due to heterogeneous biology data. This study computes petabyte level data and reveals the endogenous regulatory networks of normal and cancers and then unearths the most important endogenous regulators for normal and cancerous realm. In normal, proteins dominate the entire realm and trans-regulate their targets across chromosomes and ribosomal proteins serve as the most important drivers. However, in cancerous realm, noncoding RNAs dominate the whole realm and pseudogenes work as the most important regulators that cis-regulate their neighbors, in which they primarily regulate their targets within 1 million base pairs but they rarely regulate their cognates with complementary sequences as thought. Therefore, two distinctive mechanisms rule the normal and cancerous realm separately, in which noncoding RNAs endogenously regulate cancers, instead of proteins as currently conceptualized. This establishes a fundamental avenue to understand the basis of cancerous and normal physiology.

Noncoding RNAs and Deep Learning Neural Network Discriminate Multi-Cancer Types.

Detecting cancers at early stages can dramatically reduce mortality rates. Therefore, practical cancer screening at the population level is needed. To develop a comprehensive detection system to classify multiple cancer types, we integrated an artificial intelligence deep learning neural network and noncoding RNA biomarkers selected from massive data. Our system can accurately detect cancer vs. healthy objects with 96.3% of AUC of ROC (Area Under Curve of a Receiver Operating Characteristic curve), and it surprisingly reaches 78.77% of AUC when validated by real-world raw data from a completely independent data set. Even validating with raw exosome data from blood, our system can reach 72% of AUC. Moreover, our system significantly outperforms conventional machine learning models, such as random forest. Intriguingly, with no more than six biomarkers, our approach can easily discriminate any individual cancer type vs. normal with 99% to 100% AUC. Furthermore, a comprehensive marker panel can simultaneously multi-classify common cancers with a stable 82.15% accuracy rate for heterogeneous cancerous tissues and conditions. This detection system provides a promising practical framework for automatic cancer screening at population level. Key points: (1) We developed a practical cancer screening system, which is simple, accurate, affordable, and easy to operate. (2) Our system binarily classify cancers vs. normal with >96% AUC. (3) In total, 26 individual cancer types can be easily detected by our system with 99 to 100% AUC. (4) The system can detect multiple cancer types simultaneously with >82% accuracy.

The Impact of a Dried Fruit and Vegetable Supplement and Fiber Rich Shake on Gut and Health Parameters in Female Healthcare Workers: A Placebo-Controlled, Double-Blind, Randomized Clinical Trial.

Aim: Phytochemicals from fruits and vegetables are known to reduce inflammation and improve overall health. The objective of this study was to determine the effect of a fruit and vegetable concentrate (FVC) and high fiber component on the gut microbiome in an overweight/obese, female population. Methods: The study was a randomized, double blind, placebo-controlled trial with 57 asymptomatic, pre-menopausal, overweight/obese females between 25-50 years of age working in healthcare. Blood and fecal samples were collected before and after two, four and five months of daily supplementation. Metabolic parameters were measured, and the gut microbiome analyzed. Results: No effect was observed with FVC supplementation for blood lipids, glucose and immune parameters. There was an improvement in glucose clearance. The FVC supplement did not result in taxonomic alterations at phyla level, or changes in α or ß diversity, but reduced Bacteroides abundance and increased fecal butyrate. An additional high fiber component improved levels of health associated bacteria. Conclusion: The results suggest that a dried fruit and vegetable supplement, with a high fiber meal replacement can alter the intestinal microbiota and improve glucose clearance, suggesting that this combination of supplements can improve glucose metabolism and possibly reduce the risk of insulin resistance.

Noncoding RNAs Serve as the Deadliest Universal Regulators of all Cancers.

Numerous cancer drivers have been identified, but they are specific to a given cancer type and condition; universal cancer drivers and universal cancer mechanisms still remain largely unclear. Here, we identified the deadliest universal drivers for all cancers via developing algorithms to analyze massive RNAseqs and clinical data from The Cancer Genome Atlas (TCGA). In general, noncoding RNAs primarily serve as the most important inducers and suppressors for all types of cancers. In particular, pseudogenes are primary inducers, and specifically the antisense RNA RP11-335K5.2 serves as the most universal cancerous driver, independently of the cancer type and condition. Therefore, noncoding RNAs, instead of proteins as conventionally thought, primarily drive cancer, which establishes a novel field for future cancer research and therapy.

[Killing Effect of A CD7 Chimeric Antigen Receptor-Modified NK-92MI Cell Line on CD7-Positive Hematological Malignant Cells].

OBJECTIVE: To investigate the killing effect of NK-92MI cells modified by chimeric antigen receptor (CD7-CAR) and specifically targeting CD7 to CD7+ hematological malignant cells. METHODS: Three types of hematological malignant tumor cells, including 5 cases of CD7+ acute T-lymphoblastic leukemia (T-ALL), 10 cases of acute myeloid leukemia (AML) and 6 cases of T-cell lymphoma were collected, centrifuged, cultured and used to detect the expression levels of tumor cell surface targets; 7-AAD, CD56-APC, CD3-FITC, IgG Fc-PE flow cytometry were used to detected the transfection efficiency of NK-92MI and CD7-CAR-NK-92MI cells, killing efficiencies of CD7-CAR-NK-92MI cells to CD7+ hematological tumor cells in vitro were determined by flow cytometry using PE Annexin V Apoptosis Detection Kit. Secretion differences of NK-92MI and CD7-CAR-NK-92MI cytokines interleukin (IL)-2, interferon (IFN)-γ, and granzyme B detection were estimated by using CBA kit. RESULTS: The killing efficiencies of CD7-CAR-modified NK-92MI cells to CD7+ T-ALL, AML, T-cell lymphoma tumor cells were significantly higher than those of NK-92MI cells without genetical modification. The difference showed statistically significant (P＜0.05). The level of IFN-γ and granzyme B were significantly increased among cytokines secreted by CD7-CAR-modified NK-92MI cells as compared with those of NK-92MI cells without genetical modification (P＜0.05) . CONCLUSION: CD7-CAR-modified NK-92MI cells have significantly improved killing efficiency against CD7+ T-ALL, AML and T lymphoma cells, and shows specific targeting effects, which provides a clinical basis for the treatment of CD7+ hematological malignancies.

Mining the human urine proteome for monitoring renal transplant injury.

The human urinary proteome provides an assessment of kidney injury with specific biomarkers for different kidney injury phenotypes. In an effort to fully map and decipher changes in the urine proteome and peptidome after kidney transplantation, renal allograft biopsy matched urine samples were collected from 396 kidney transplant recipients. Centralized and blinded histology data from paired graft biopsies was used to classify urine samples into diagnostic categories of acute rejection, chronic allograft nephropathy, BK virus nephritis, and stable graft. A total of 245 urine samples were analyzed by liquid chromatography-mass spectrometry using isobaric Tags for Relative and Absolute Quantitation (iTRAQ) reagents. From a group of over 900 proteins identified in transplant injury, a set of 131 peptides were assessed by selected reaction monitoring for their significance in accurately segregating organ injury causation and pathology in an independent cohort of 151 urine samples. Ultimately, a minimal set of 35 proteins were identified for their ability to segregate the 3 major transplant injury clinical groups, comprising the final panel of 11 urinary peptides for acute rejection (93% area under the curve [AUC]), 12 urinary peptides for chronic allograft nephropathy (99% AUC), and 12 urinary peptides for BK virus nephritis (83% AUC). Thus, urinary proteome discovery and targeted validation can identify urine protein panels for rapid and noninvasive differentiation of different causes of kidney transplant injury, without the requirement of an invasive biopsy.

All-trans retinoic acid modulates the balance of ADAMTS13 and VWF in human microvascular endothelial cells.

PURPOSE: To better understand the antithrombotic property of All-trans retinoic acid (ATRA), we investigated whether ATRA may affect the balance between ADAMTS13 and von Willebrand factor (VWF) in human microvascular endothelial cell. METHODS: Compared to tumor necrosis factor-alpha (TNF-α), we observed the effects of ATRA on the expression of ADAMTS13 and VWF. ADAMTS13mRNA in human microvascular endothelial cell (HMEC-1 cell line) were detected by real-time polymerase chain reaction amplification (RT-PCR). The levels of ADAMTS13 and VWF antigen were detected by western blot or enzyme-linked immunosorbent assay (ELISA), and the proteolytic activity of ADAMTS13 was also determined by using GST-VWF73-His peptide as a specific substrate. RESULTS: ATRA significantly upregulated the expression of ADAMTS13mRNA in HMEC-1, while TNF-α inhibited ADAMTS13mRNA expression. ATRA could reverse the inhibition expression of ADAMTS13 by TNF-α. The results were confirmed from the levels of ADAMTS13 protein and its activity, while ATRA had no significant affection on triggering release of VWF. CONCLUSIONS: This study provides the evidence that ATRA modulates the balance of ADAMTS13 and VWF in human microvascular endothelial cell, which might be a very relevant compartment for the antithrombotic property of ATRA.

Combined Targeted DNA Sequencing in Non-Small Cell Lung Cancer (NSCLC) Using UNCseq and NGScopy, and RNA Sequencing Using UNCqeR for the Detection of Genetic Aberrations in NSCLC.

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07-0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11-1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion.

Alterations of LKB1 and KRAS and risk of brain metastasis: comprehensive characterization by mutation analysis, copy number, and gene expression in non-small-cell lung carcinoma.

BACKGROUND: Brain metastases are one of the most malignant complications of lung cancer and constitute a significant cause of cancer related morbidity and mortality worldwide. Recent years of investigation suggested a role of LKB1 in NSCLC development and progression, in synergy with KRAS alteration. In this study, we systematically analyzed how LKB1 and KRAS alteration, measured by mutation, gene expression (GE) and copy number (CN), are associated with brain metastasis in NSCLC. MATERIALS AND METHODS: Patients treated at University of North Carolina Hospital from 1990 to 2009 with NSCLC provided frozen, surgically extracted tumors for analysis. GE was measured using Agilent 44,000 custom-designed arrays, CN was assessed by Affymetrix GeneChip Human Mapping 250K Sty Array or the Genome-Wide Human SNP Array 6.0 and gene mutation was detected using ABI sequencing. Integrated analysis was conducted to assess the relationship between these genetic markers and brain metastasis. A model was proposed for brain metastasis prediction using these genetic measurements. RESULTS: 17 of the 174 patients developed brain metastasis. LKB1 wild type tumors had significantly higher LKB1 CN (p<0.001) and GE (p=0.002) than the LKB1 mutant group. KRAS wild type tumors had significantly lower KRAS GE (p<0.001) and lower CN, although the latter failed to be significant (p=0.295). Lower LKB1 CN (p=0.039) and KRAS mutation (p=0.007) were significantly associated with more brain metastasis. The predictive model based on nodal (N) stage, patient age, LKB1 CN and KRAS mutation had a good prediction accuracy, with area under the ROC curve of 0.832 (p<0.001). CONCLUSION: LKB1 CN in combination with KRAS mutation predicted brain metastasis in NSCLC.

A web-server of cell type discrimination system.

Discriminating cell types is a daily request for stem cell biologists. However, there is not a user-friendly system available to date for public users to discriminate the common cell types, embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and somatic cells (SCs). Here, we develop WCTDS, a web-server of cell type discrimination system, to discriminate the three cell types and their subtypes like fetal versus adult SCs. WCTDS is developed as a top layer application of our recent publication regarding cell type discriminations, which employs DNA-methylation as biomarkers and machine learning models to discriminate cell types. Implemented by Django, Python, R, and Linux shell programming, run under Linux-Apache web server, and communicated through MySQL, WCTDS provides a friendly framework to efficiently receive the user input and to run mathematical models for analyzing data and then to present results to users. This framework is flexible and easy to be expended for other applications. Therefore, WCTDS works as a user-friendly framework to discriminate cell types and subtypes and it can also be expended to detect other cell types like cancer cells.

Transcription factor complex AP-1 mediates inflammation initiated by Chlamydia pneumoniae infection.

Chlamydia pneumoniae is responsible for a high prevalence of respiratory infections worldwide and has been implicated in atherosclerosis. Inflammation is regulated by transcription factor (TF) networks. Yet, the core TF network triggered by chlamydiae remains largely unknown. Primary human coronary artery endothelial cells were mock-infected or infected with C. pneumoniae to generate human transcriptome data throughout the chlamydial developmental cycle. Using systems network analysis, the predominant TF network involved receptor, binding and adhesion and immune response complexes. Cells transfected with interfering RNA against activator protein-1 (AP-1) members FOS, FOSB, JUN and JUNB had significantly decreased expression and protein levels of inflammatory mediators interleukin (IL)6, IL8, CD38 and tumour necrosis factor compared with controls. These mediators have been shown to be associated with C. pneumoniae disease. Expression of AP-1 components was regulated by MAPK3K8, a MAPK pathway component. Additionally, knock-down of JUN and FOS showed significantly decreased expression of Toll-like receptor (TLR)3 during infection, implicating JUN and FOS in TLR3 regulation. TLR3 stimulation led to elevated IL8. These findings suggest that C. pneumoniae initiates signalling via TLR3 and MAPK that activate AP-1, a known immune activator in other bacteria not previously shown for chlamydiae, triggering inflammation linked to C. pneumoniae disease.

(Bortezomib plus lenalidomide/thalidomide)- vs. (bortezomib or lenalidomide/thalidomide)-containing regimens as induction therapy in newly diagnosed multiple myeloma: a meta-analysis of randomized controlled trials.

The aim of the study was to perform a meta-analysis of the efficacy and safety of (bortezomib plus lenalidomide/thalidomide)- vs. (bortezomib or lenalidomide/thalidomide)-containing regimens as induction therapy in newly diagnosed multiple myeloma. We searched electronic and printed sources for relevant articles published. Inclusion criteria was as follows: randomized controlled trials (RCT) of (bortezomib plus lenalidomide/thalidomide) vs. (bortezomib or lenalidomide/thalidomide)-containing regimens as induction therapy in newly diagnosed multiple myeloma. Two reviewers independently assessed potentially eligible studies and extracted relevant data. We retrieved five RCT studies including a total of 1,200 patients. Using the random-effects model to pool the five RCT with a statistically significant heterogeneity (P = 0.03; X² = 10.69; df = 4; I² = 63%), the weighted risk ratios of a complete response (CR) for (bortezomib plus lenalidomide/thalidomide)-containing regimens was 1.81 (P = 0.005; 95% CI: 1.20-2.73). When we excluded the study by Cavo et al. (Lancet 376:2075-2085, 2010), the pooled risk ratio for CR was 1.59 (P < 0.0001, 95% CI: 1.29-1.96) with no statistically significant heterogeneity (P = 0.54; X² = 2.14; df = 3; I² = 0%) among four RCT under the fixed effects mode. The pooled odds ratio for the main grade III/IV adverse events (the peripheral neuropathy, thrombotic events, and infections) were 1.76 (P = 0.32; 95% CI: 0.58-5.31), 0.92 (P = 0.76, 95% CI: 0.52-1.61), and 1.05 (P = 0.82, 95% CI: 0.70-1.57), respectively. Our analysis showed (bortezomib plus lenalidomide/thalidomide)-containing regimens as induction treatment in newly diagnosed multiple myeloma improved CR but did not increase the risk of major adverse events (the peripheral neuropathy, thrombotic events, and infections).

A systemic network for Chlamydia pneumoniae entry into human cells.

Bacterial entry is a multistep process triggering a complex network, yet the molecular complexity of this network remains largely unsolved. By employing a systems biology approach, we reveal a systemic bacterial-entry network initiated by Chlamydia pneumoniae, a widespread opportunistic pathogen. The network consists of nine functional modules (i.e., groups of proteins) associated with various cellular functions, including receptor systems, cell adhesion, transcription, and endocytosis. The peak levels of gene expression for these modules change rapidly during C. pneumoniae entry, with cell adhesion occurring at 5 min postinfection, receptor and actin activity at 25 min, and endocytosis at 2 h. A total of six membrane proteins (chemokine C-X-C motif receptor 7 [CXCR7], integrin beta 2 [ITGB2], platelet-derived growth factor beta polypeptide [PDGFB], vascular endothelial growth factor [VEGF], vascular cell adhesion molecule 1 [VCAM1], and GTP binding protein overexpressed in skeletal muscle [GEM]) play a key role during C. pneumoniae entry, but none alone is essential to prevent entry. The combination knockdown of three genes (coding for CXCR7, ITGB2, and PDGFB) significantly inhibits C. pneumoniae entry, but the entire network is resistant to the six-gene depletion, indicating a resilient network. Our results reveal a complex network for C. pneumoniae entry involving at least six key proteins.

Global gene expression responses to cadmium toxicity in Escherichia coli.

Genome-wide analysis of temporal gene expression profiles in Escherichia coli following exposure to cadmium revealed a shift to anaerobic metabolism and induction of several stress response systems. Disruption in the transcription of genes encoding ribosomal proteins and zinc-binding proteins may partially explain the molecular mechanisms of cadmium toxicity.