Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers.

Cancer is a disease of gene dysregulation, where cells acquire somatic and epigenetic alterations that drive aberrant cellular signaling. These alterations adversely impact transcriptional programs and cause profound changes in gene expression. Interpreting somatic alterations within context-specific transcriptional programs will facilitate personalized therapeutic decisions but is a monumental task. Toward this goal, we develop a partially interpretable neural network model called Chromatin-informed Inference of Transcriptional Regulators Using Self-attention mechanism (CITRUS). CITRUS models the impact of somatic alterations on transcription factors and downstream transcriptional programs. Our approach employs a self-attention mechanism to model the contextual impact of somatic alterations. Furthermore, CITRUS uses a layer of hidden nodes to explicitly represent the state of transcription factors (TFs) to learn the relationships between TFs and their target genes based on TF binding motifs in the open chromatin regions of tumor samples. We apply CITRUS to genomic, transcriptomic, and epigenomic data from 17 cancer types profiled by The Cancer Genome Atlas. CITRUS predicts patient-specific TF activities and reveals transcriptional program variations between and within tumor types. We show that CITRUS yields biological insights into delineating TFs associated with somatic alterations in individual tumors. Thus, CITRUS is a promising tool for precision oncology.

Ex vivo liver resection and auto-transplantation as an alternative for the treatment of liver malignancies: Progress and challenges.

Hepatectomy is still the major curative treatment for patients with liver malignancies. However, it is still a big challenge to remove the tumors in the central posterior area, especially if their location involves the retrohepatic inferior vena cava and hepatic veins. Ex vivo liver resection and auto-transplantation (ELRA), a hybrid technique of the traditional liver resection and transplantation, has brought new hope to these patients and therefore becomes a valid alternative to liver transplantation. Due to its technical difficulty, ELRA is still concentrated in a few hepatobiliary centers that have experienced surgeons in both liver resection and liver transplantation. The efficacy and safety of this technique has already been demonstrated in the treatment of benign liver diseases, especially in the advanced alveolar echinococcosis. Recently, the application of ELRA for liver malignances has gained more attention. However, standardization of clinical practice norms and international consensus are still lacking. The prognostic impact in these oncologic patients also needs further evaluation. In this review, we summarized the principles and recent progresses on ELRA.

Reconstructing tumor clonal lineage trees incorporating single-nucleotide variants, copy number alterations and structural variations.

MOTIVATION: Cancer develops through a process of clonal evolution in which an initially healthy cell gives rise to progeny gradually differentiating through the accumulation of genetic and epigenetic mutations. These mutations can take various forms, including single-nucleotide variants (SNVs), copy number alterations (CNAs) or structural variations (SVs), with each variant type providing complementary insights into tumor evolution as well as offering distinct challenges to phylogenetic inference. RESULTS: In this work, we develop a tumor phylogeny method, TUSV-ext, which incorporates SNVs, CNAs and SVs into a single inference framework. We demonstrate on simulated data that the method produces accurate tree inferences in the presence of all three variant types. We further demonstrate the method through application to real prostate tumor data, showing how our approach to coordinated phylogeny inference and clonal construction with all three variant types can reveal a more complicated clonal structure than is suggested by prior work, consistent with extensive polyclonal seeding or migration. AVAILABILITY AND IMPLEMENTATION: https://github.com/CMUSchwartzLab/TUSV-ext. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Semi-deconvolution of bulk and single-cell RNA-seq data with application to metastatic progression in breast cancer.

MOTIVATION: Identifying cell types and their abundances and how these evolve during tumor progression is critical to understanding the mechanisms of metastasis and identifying predictors of metastatic potential that can guide the development of new diagnostics or therapeutics. Single-cell RNA sequencing (scRNA-seq) has been especially promising in resolving heterogeneity of expression programs at the single-cell level, but is not always feasible, e.g. for large cohort studies or longitudinal analysis of archived samples. In such cases, clonal subpopulations may still be inferred via genomic deconvolution, but deconvolution methods have limited ability to resolve fine clonal structure and may require reference cell type profiles that are missing or imprecise. Prior methods can eliminate the need for reference profiles but show unstable performance when few bulk samples are available. RESULTS: In this work, we develop a new method using reference scRNA-seq to interpret sample collections for which only bulk RNA-seq is available for some samples, e.g. clonally resolving archived primary tissues using scRNA-seq from metastases. By integrating such information in a Quadratic Programming framework, our method can recover more accurate cell types and corresponding cell type abundances in bulk samples. Application to a breast tumor bone metastases dataset confirms the power of scRNA-seq data to improve cell type inference and quantification in same-patient bulk samples. AVAILABILITY AND IMPLEMENTATION: Source code is available on Github at https://github.com/CMUSchwartzLab/RADs.

LncRNA GASAL1 promotes hepatocellular carcinoma progression by up-regulating USP10-stabilized PCNA.

Hepatocellular carcinoma (HCC) is a fatal malignancy which has insufficient treatment options. Long non-coding RNA (lncRNA) GASAL1 was discovered to be conspicuously up-regulated in HCC. However, the study on the role of GASAL1 in HCC reamins limited. Our study aimed at exploring the role and mechanism of GASAL1 in HCC. RT-qPCR or Western blot was conducted to examine the expression of RNAs or proteins. Functional assays were carried out to investigate the impact of GASAL1, USP10, and PCNA on HCC cells. Mechanism assays were performed to fathom out the relationship among GASAL1, miR-193b-5p, USP10, and PCNA. In vivo assays were also employed to determine the role of GASAL1 in HCC tumor growth and metastases. According to the data collected, GASAL1 displayed a high expression in HCC cells and GASAL1 knockdown led to impeded cell proliferation and migration, as well as tumor progression. A series of mechanism analysis demonstrated GASAL1 could sponge miR-193b-5p to raise the expression of USP10. Moreover, USP10 could induce PCNA deubiquitination to promote HCC cell growth. To conclude, GASAL1 plays an oncogenic role in HCC. GASAL1 could up-regulate USP10 via competitively binding to miR-193b-5p. And USP10 could strengthen cell proliferative and migratory abilities through deubiquitinating PCNA.

The AGH score is a predictor of disease-free survival and targeted therapy efficacy after liver transplantation in patients with hepatocellular carcinoma.

BACKGROUND: Liver transplantation (LT) is the "cure" therapy for patients with hepatocellular carcinoma (HCC). However, some patients encounter HCC recurrence after LT. Unfortunately, there is no effective methods to identify the LT patients who have high risk of HCC recurrence and would benefit from adjuvant targeted therapy. The present study aimed to establish a scoring system to predict HCC recurrence of HCC patients after LT among the Chinese population, and to evaluate whether these patients are suitable for adjuvant targeted therapy. METHODS: Clinical data of HCC patients who underwent LT from March 2015 to June 2019 were retrospectively collected and analyzed. RESULTS: A total of 201 patients were included in the study. The multivariate Cox analysis suggested that preoperative alpha-fetoprotein (AFP) > 200 µg/L (HR = 2.666, 95% CI: 1.515-4.690; P = 0.001), glutamyl transferase (GGT) > 96 U/L (HR = 1.807, 95% CI: 1.012-3.224; P = 0.045), and exceeding the Hangzhou criteria (HR = 2.129, 95% CI: 1.158-3.914; P = 0.015) were independent risk factors for poor disease-free survival (DFS) in patients with HCC who underwent LT. We established an AFP-GGT-Hangzhou (AGH) scoring system based on these factors, and divided cases into high-, moderate-, and low-risk groups. The differences in overall survival (OS) and disease-free survival (DFS) rates among the three groups were significant (P < 0.05). The efficacy of the AGH scoring system to predict DFS was better than that of the Hangzhou criteria, UCSF criteria, Milan criteria, and TNM stage. Only in the high-risk group, we found that lenvatinib significantly improved prognosis compared with that of the control group (P < 0.05). CONCLUSIONS: The AGH scoring system provides a convenient and effective way to predict HCC recurrence after LT in HCC patients in China. Patients with a high-risk AGH score may benefit from lenvatinib adjuvant therapy after LT.

Tumor heterogeneity assessed by sequencing and fluorescence in situ hybridization (FISH) data.

MOTIVATION: Computational reconstruction of clonal evolution in cancers has become a crucial tool for understanding how tumors initiate and progress and how this process varies across patients. The field still struggles, however, with special challenges of applying phylogenetic methods to cancers, such as the prevalence and importance of copy number alteration (CNA) and structural variation events in tumor evolution, which are difficult to profile accurately by prevailing sequencing methods in such a way that subsequent reconstruction by phylogenetic inference algorithms is accurate. RESULTS: In this work, we develop computational methods to combine sequencing with multiplex interphase fluorescence in situ hybridization to exploit the complementary advantages of each technology in inferring accurate models of clonal CNA evolution accounting for both focal changes and aneuploidy at whole-genome scales. By integrating such information in an integer linear programming framework, we demonstrate on simulated data that incorporation of FISH data substantially improves accurate inference of focal CNA and ploidy changes in clonal evolution from deconvolving bulk sequence data. Analysis of real glioblastoma data for which FISH, bulk sequence and single cell sequence are all available confirms the power of FISH to enhance accurate reconstruction of clonal copy number evolution in conjunction with bulk and optionally single-cell sequence data. AVAILABILITY AND IMPLEMENTATION: Source code is available on Github at https://github.com/CMUSchwartzLab/FISH_deconvolution. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assessing the contribution of tumor mutational phenotypes to cancer progression risk.

Cancer occurs via an accumulation of somatic genomic alterations in a process of clonal evolution. There has been intensive study of potential causal mutations driving cancer development and progression. However, much recent evidence suggests that tumor evolution is normally driven by a variety of mechanisms of somatic hypermutability, which act in different combinations or degrees in different cancers. These variations in mutability phenotypes are predictive of progression outcomes independent of the specific mutations they have produced to date. Here we explore the question of how and to what degree these differences in mutational phenotypes act in a cancer to predict its future progression. We develop a computational paradigm using evolutionary tree inference (tumor phylogeny) algorithms to derive features quantifying single-tumor mutational phenotypes, followed by a machine learning framework to identify key features predictive of progression. Analyses of breast invasive carcinoma and lung carcinoma demonstrate that a large fraction of the risk of future clinical outcomes of cancer progression-overall survival and disease-free survival-can be explained solely from mutational phenotype features derived from the phylogenetic analysis. We further show that mutational phenotypes have additional predictive power even after accounting for traditional clinical and driver gene-centric genomic predictors of progression. These results confirm the importance of mutational phenotypes in contributing to cancer progression risk and suggest strategies for enhancing the predictive power of conventional clinical data or driver-centric biomarkers.

Robust and accurate deconvolution of tumor populations uncovers evolutionary mechanisms of breast cancer metastasis.

MOTIVATION: Cancer develops and progresses through a clonal evolutionary process. Understanding progression to metastasis is of particular clinical importance, but is not easily analyzed by recent methods because it generally requires studying samples gathered years apart, for which modern single-cell sequencing is rarely an option. Revealing the clonal evolution mechanisms in the metastatic transition thus still depends on unmixing tumor subpopulations from bulk genomic data. METHODS: We develop a novel toolkit called robust and accurate deconvolution (RAD) to deconvolve biologically meaningful tumor populations from multiple transcriptomic samples spanning the two progression states. RAD uses gene module compression to mitigate considerable noise in RNA, and a hybrid optimizer to achieve a robust and accurate solution. Finally, we apply a phylogenetic algorithm to infer how associated cell populations adapt across the metastatic transition via changes in expression programs and cell-type composition. RESULTS: We validated the superior robustness and accuracy of RAD over alternative algorithms on a real dataset, and validated the effectiveness of gene module compression on both simulated and real bulk RNA data. We further applied the methods to a breast cancer metastasis dataset, and discovered common early events that promote tumor progression and migration to different metastatic sites, such as dysregulation of ECM-receptor, focal adhesion and PI3k-Akt pathways. AVAILABILITY AND IMPLEMENTATION: The source code of the RAD package, models, experiments and technical details such as parameters, is available at https://github.com/CMUSchwartzLab/RAD. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Left Hepatic Vein Preferential Approach Based on Anatomy Is Safe and Feasible for Laparoscopic Living Donor Left Lateral Sectionectomy.

We assess the safety and feasibility of the left hepatic vein preferential approach (LHVPA) based on left hepatic vein (LHV) anatomy for living donor laparoscopic left lateral sectionectomy (LLLS). Data from 50 donors who underwent LLLS in Huashan Hospital from October 2016 to November 2019 were analyzed retrospectively. On the basis of the classification of the LHV anatomy, the vein was defined as the direct import type, upper branch type, or indirect import type. A subgroup analysis was performed to compare the outcomes between the LHVPA and non-LHVPA groups. All 50 patients underwent pure LLLS. The mean operative duration was 157.5 ± 29.7 minutes. The intraoperative blood loss was 160.4 ± 97.5 mL. No complications more severe than grade 3 occurred. LHVPA was applied in 13 patients, whereas non-LHVPA was applied in 10 patients with the direct import type and upper branch type anatomy. The operative duration was shorter in the LHVPA group than the non-LHVPA group (142.7 ± 22.0 versus 173.0 ± 22.8 minutes; P = 0.01). Intraoperative blood loss was reduced in the LHVPA group compared with the non-LHVPA group (116.2 ± 45.6 versus 170.0 ± 63.3 mL; P = 0.02). The length of the LHV reserved extrahepatically in the LHVPA group was longer than in the non-LHVPA group (4.3 ± 0.2 versus 3.3 ± 0.3 mm; P = 0.01). Fewer reconstructions of the LHV in the direct import type anatomy were required for the LHVPA group than for the non-LHVPA group (0/8 versus 4/6). LHVPA based on the LHV anatomy is recommended in LLLS because it can further increase the safety and the efficiency of surgery for suitable donors.

A Stepwise Evaluation of Hepatitis B Virus-Related Acute-on-Chronic Liver Failure to Optimize the Indication for Urgent Liver Transplantation.

BACKGROUND: Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a dynamic but reversible disease. AIM: We aimed to clarify whether the change in Chinese Group on the Study of Severe Hepatitis B-ACLF (COSSH-ACLF) grade in HBV-ACLF patients can be used to predict prognosis, and to explore the appropriate conditions for performing urgent liver transplantation. METHODS: We assessed the COSSH-ACLF grades of HBV-ACLF patients at different time points from June 2013 to May 2019 at Huashan Hospital in Shanghai, China, and analyzed the relationship between the change in grade and patient prognosis. RESULTS: A total of 207 HBV-ACLF patients were enrolled, of which 79 underwent urgent liver transplantation. Their COSSH-ACLF grades were calculated at diagnosis, 3-7 days after diagnosis, and on the final day. Most of the final ACLF grades were consistent with their corresponding grades at days 3-7 after diagnosis (62.5%), while only 44.5% were in accordance with the initial grades at diagnosis. In patients who had a poor prognosis (initial ACLF-3 and ACLF-2 or -3 at days 3-7), the 28-day survival rate was 93.3% in those who underwent transplantation and 6.8% in those who did not (P < 0.0001). However, in patients who had a good prognosis (ACLF-0 or ACLF-1 at days 3-7), the 28-day survival rate was 100% in transplanted patients and 91.5% in non-transplanted patients (P = 0.236). CONCLUSIONS: Reevaluation of the COSSH-ACLF grade 3-7 days after diagnosis could potentially show an indication for urgent liver transplantation.

Infection within 2 weeks before liver transplantation closely related to prognosis of posttransplant infection: A single-center retrospective observational study in China.

BACKGROUND: Infections still represent the main factors influencing morbidity and mortality following liver transplantation. This study aimed to evaluate the incidence and risk factors for infection and survival after liver transplantation. METHODS: We retrospectively examined medical records in 210 liver recipients who underwent liver transplantation between April 2015 and October 2017 in our hospital. Clinical manifestations and results of pathogen detection test were used to define infection. We analyzed the prevalence, risk factors and prognosis of patients with infection. RESULTS: The median follow-up was 214 days; the incidence of infection after liver transplantation was 46.7% (n = 98) which included pneumonia (43.4%), biliary tract infection (21.9%), peritonitis (21.4%) and bloodstream infection (7.6%). Among the pathogens in pneumonia, the most frequently isolated was Acinetobacter baumanii (23.5%) and Klebsiella pneumoniae (21.2%). Model for end-stage liver disease (MELD) score (OR = 1.083, 95% CI: 1.045-1.123; P < 0.001), biliary complication (OR = 4.725, 95% CI: 1.119-19.947; P = 0.035) and duration of drainage tube (OR = 1.040, 95% CI: 1.007-1.074; P = 0.017) were independent risk factors for posttransplant infection. All-cause mortality was 11.0% (n = 23). The prognostic factors for postoperative infection in liver recipients were prior-transplant infection, especially pneumonia within 2 weeks before transplantation. Kaplan-Meier curves of survival showed that recipients within 2 weeks prior infection had a significantly lower cumulative survival rate compared with those without infection (65.2% vs. 90.0%; hazard ratio: 4.480; P < 0.001). CONCLUSIONS: Infection, especially pneumonia within 2 weeks before transplantation, complication with impaired renal function and MELD score after 7 days of transplantation was an independent prognostic factor for postoperative infection in liver transplant recipients.

Blood cell parameters for screening and diagnosis of hereditary spherocytosis.

BACKGROUND: There is currently no single index for the diagnostic screening of hereditary spherocytosis (HS). However, hematology analyzers are widely used in hospital laboratories because of their highly automated performance and quality control procedure, and detection of some blood cell parameters may be useful for the early screening of HS. METHODS: We investigated the values of blood cell parameters for the screening and differential diagnosis of HS. We performed a descriptive study of 482 samples (67 cases of HS, 59 cases of G6PD deficiency, 57 cases of AIHA, 199 cases of thalassemia, and 100 cases of healthy controls) that were run on Beckman Coulter LH780 Hematology Analyzer. RESULTS: HS was characterized by increased MCHC, decreased MRV, MSCV-MCV < 0, and increased Ret with no concomitant increase in IRF. The areas under the ROC curves were MSCV-MCV (0.97; 95% CI 0.95-1.0) > MRV (0.94; 95% CI 0.91-0.97) > MCHC (0.92; 95% CI 0.88-0.97) > Ret/IRF (0.77; 95% CI 0.7-0.84). MSCV-MCV ≤ 0.6 fl was valuable parameter for the diagnostic screening of HS, with a sensitivity of 95.5% and specificity of 94.9%. CONCLUSION: These indices have high reference values for differentiating HS from thalassemia, AIHA, and G6PD deficiency.

Clinicopathological and Prognostic Significance of Cancer Stem Cell Markers in Ovarian Cancer Patients: Evidence from 52 Studies.

BACKGROUND/AIMS: Relevant markers of cancer stem cells (CSCs) may serve as commonly used biomarkers of ovarian cancer (OC). However, their actual clinicopathological and prognostic significance remains inconclusive. Thus, we conducted a meta-analysis to quantitatively evaluate the association between the expression of CSC-relevant markers (ALDH1, CD117, CD133, and CD44) and OC. METHODS: We used an odds ratio (OR) and a hazard ratio (HR) with a 95% confidence interval (CI) to estimate the effects by analyzing 52 studies from a literature search. Heterogeneity and sensitivity were evaluated, as well. Publication bias was assessed using funnel plots and Egger tests. RESULTS: ALDH1 expression was statistically associated with FIGO stage (OR=1.872, 95%CI=1.14-3.076, P=0.013) and lymph invasion (OR=2.78, 95%CI=1.08-7.152, P=0.034). CD117 expression was significantly associated with FIGO stage (OR=2.01, 95%CI=1.35-2.98, P=0.001). CD133 expression was correlated with FIGO stage (OR=3.410, 95%CI=2.196-5.294, P< 0.001) and differentiation grade (OR=2.672, 95%CI=1.354-5.272, P=0.005). CD44s was related to chemotherapy resistance (OR=3.218, 95%CI=1.148-9.016, P=0.026). Furthermore, overexpression of ALDH1 (HR=1.494, 95%CI=1.207-1.849, P< 0.001), CD117 (HR=1.395, 95%CI=1.025-1.898, P=0.034) or CD44s (HR=1.725, 95%CI=1.135-2.623, P=0.011) was associated with poor OS. Further, overexpression of both ALDH1 (HR=1.524, 95%CI=1.158-2.007, P=0.003) and CD44s (HR=2.12, 95%CI=1.692-2.657, P< 0.001) was correlated with worse DFS. CONCLUSION: CSC markers are useful predictive or prognostic biomarkers for OC in clinical assessments. Combined detection of CSC marker expression may be a powerful tool for prognostic predictions in clinical practice for patients with OC.

MicroRNA-144 suppresses the expression of cytokines through targeting RANKL in the matured immune cells.

To investigate whether the microRNA-144 (miR-144) had immune regulation effect on matured immune cells, we firstly used quantitative RT-PCR (qRT-PCR) to detect the expression changes of miR-144 between the matured and immature dendritic cells (DCs), macrophages, and the peripheral blood mononuclear cells (PBMCs). Then we went on inspecting the expression changes of TNF-α, IL-1ß, IL-6 and IL-23 in the matured DCs treated with miR-144 mimics or inhibitors using qRT-PCR, and also performed western blot to test phosphorylation state of ERK, JNK, p38 and p65 in these cells. Next, TargetScan was conducted to forecast the target gene of miR-144, receptor activator for nuclear factor-κB ligand (RANKL), and double luciferase reporter system was applied to research their banding sites. We also determined the expression changes of RANKL in the DCs treated with miR-144 mimics or inhibitors using qRT-PCR and ELISA, respectively. The siRNA of RANKL was synthesized and transfected into DCs to inspect how the immune regulation effect of miR-144 was conducted to inhibit the expression of TNF-α using qRT-PCR, and lastly we used flow cytometry to investigate whether this effect applied to Th17 cells. As results, we found that miR-144 was down-regulated in the matured DCs, macrophages and PBMCs of liver transplantation patients, and the miR-144 mimics could inhibit the expression levels of TNF-α, IL-1ß, IL-6 and IL-23 in the matured DCs. Furthermore, miR-144 interacted with RANKL at position 679-685 of RANKL 3'UTR, and suppressed the translation of RANKL mRNA to realize the negative-regulation. Besides, the silence of RANKL enhanced the suppression effect of miR-144 on TNF-α and this immune regulation effect was applied to Th17 cells, too. In conclusion, this study clearly illustrated that miR-144 could inhibit the expression of cytokine in matured immune cells through suppressing the translation of RANKL mRNA.

Molecular Genetic Mechanisms of Hereditary Spherocytosis: Current Perspectives.

With the widespread use of genetic diagnostic technologies, many novel mutations have been identified in hereditary spherocytosis (HS)-related genes, including SPTA1, SPTB, ANK1, SLC4A1, and EPB42. However, mutations in HS-related genes are dispersed and nonspecific in the diagnosis of some HS patients, indicating significant heterogeneity in the molecular deficiency of HS. It is necessary to provide the molecular and genetic characteristics of these 5 genes for clinicians to examine HS. Here, we reviewed the recent proposed molecular genetic mechanisms of HS.

CD44 and CD44v6 are Correlated with Gastric Cancer Progression and Poor Patient Prognosis: Evidence from 42 Studies.

BACKGROUND/AIMS: The prognostic power of the levels of total CD44 and its isoform CD44v6 for patients with gastric cancer (GC) remains controversial. Therefore, our study aims to generalize the clinicopathological and prognostic significance of these two proteins in GC. METHODS: A literature search of the PubMed, Web of Science and Embase databases was conducted to identify eligible studies. The odds ratio (OR) with a 95% confidence interval (CI) was used to assess the effects. RESULTS: In all, 42 studies including 6,229 patients were included in this analysis. Total CD44 was mentioned in 21 papers, and the results showed that CD44 was positively correlated with the T category, the N category, distant metastasis, lymphatic invasion and TNM stage. Moreover, patients with CD44 overexpression had a lower 5-year overall survival (OS) rate (OR = 3.35, 95%CI = 1.83-6.13). CD44v6 was mentioned in 24 studies, with results that were similar to those for total CD44. However, total CD44 or CD44v6 expression was not correlated with tumor size and histological grade. CONCLUSION: High CD44 or CD44v6 expression levels were correlated with cancer progression and poor prognosis in patients with GC. Both CD44 and CD44v6 may be useful diagnostic or prognostic biomarkers for GC.

Evaluation of a Flow-Cytometric Osmotic Fragility Test for Hereditary Spherocytosis in Chinese Patients.

BACKGROUND: Osmotic fragility testing based on flow cytometry was recently introduced for the screening of hereditary spherocytosis (HS). This study was undertaken to evaluate the clinical diagnostic value of a flow-cytometric osmotic fragility test for HS. METHODS: Peripheral blood was collected from 237 subjects at the First Affiliated Hospital of Guangxi Medical University, including 56 HS patients, 86 thalassemia patients and 95 healthy controls. The samples were examined by flow-cytometric osmotic fragility test and the percentage of residual red blood cells was used to determine HS. Peripheral blood smears were performed to examine the red blood cell morphology. RESULTS: With clinical diagnosis of HS as the gold standard and the percentage of residual red blood cells <23.6% as the diagnostic threshold in the flow-cytometric osmotic fragility test, the sensitivity of the flow-cytometric osmotic fragility test for HS was 85.71% and the specificity was 97.24%. CONCLUSION: The flow-cytometric osmotic fragility test combined with a red blood cell morphology test by peripheral blood smear could be a simple, practical and accurate laboratory screening method for HS.

Simultaneous use of in silico design and a correlated mutation network as a tool to efficiently guide enzyme engineering.

In order to improve the efficiency of directed evolution experiments, in silico multiple-substrate clustering was combined with an analysis of the variability of natural enzymes within a protein superfamily. This was applied to a Pseudomonas fluorescens esterase (PFE I) targeting the enantioselective hydrolysis of 3-phenylbutyric acid esters. Data reported in the literature for nine substrates were used for the clustering meta-analysis of the docking conformations in wild-type PFE I, and this highlighted a tryptophan residue (W28) as an interesting target. Exploration of the most frequently, naturally occurring amino acids at this position suggested that the reduced flexibility observed in the case of the W28F variant leads to enhancement of the enantioselectivity. This mutant was subsequently combined with mutations identified in a library based on analysis of a correlated mutation network. By interrogation of <80 variants a mutant with 15-fold improved enantioselectivity was found.