Digging into the NGS Information from a Large-Scale South European Population with Metastatic/Unresectable Pancreatic Ductal Adenocarcinoma: A Real-World Genomic Depiction

Despite ongoing oncological advances, pancreatic ductal adenocarcinoma (PDAC) continues to have an extremely poor prognosis with limited targeted and immunotherapeutic options. Its genomic background has not been fully characterized yet in large-scale populations all over the world. Methods: Replicating a recent study from China, we collected tissue samples from consecutive Greek patients with pathologically-confirmed metastatic/unresectable PDAC and retrospectively investigated their genomic landscape using next generation sequencing (NGS). Findings: From a cohort of 409 patients, NGS analysis was successfully achieved in 400 cases (56.50% males, median age: 61.8 years). Consistent with a previous study, KRAS was the most frequently mutated gene in 81.50% of tested samples, followed by TP53 (50.75%), CDKN2 (8%), and SMAD4 (7.50%). BRCA1/2 variants with on-label indications were detected in 2%, and 87.50% carried a variant associated with off-label treatment (KRAS, ERBB2, STK11, or HRR-genes), while 3.5% of the alterations had unknown/preliminary-studied actionability (TP53/CDKN2A). Most of HRR-alterations were in intermediate- and low-risk genes (CHEK2, RAD50, RAD51, ATM, FANCA, FANCL, FANCC, BAP1), with controversial actionability: 8% harbored a somatic non-BRCA1/2 alteration, 6 cases had a high-risk alteration (PALB2, RAD51C), and one co-presented a PALB2/BRCA2 alteration. Elevated LOH was associated with HRR-mutated status and TP53 mutations while lowered LOH was associated with KRAS alterations. Including TMB/MSI data, the potential benefit from an NGS-oriented treatment was increased from 1.91% to 13.74% (high-MSI: 0.3%, TMB > 10 muts/MB: 12.78%). TMB was slightly increased in females (4.75 vs. 4.46 muts/MB) and in individuals with age > 60 (4.77 vs. 4.40 muts/MB). About 28.41% showed PD-L1 > 1% either in tumor or immune cells, 15.75% expressed PD-L1 ≥ 10%, and only 1.18% had PD-L1 ≥ 50%. This is the largest depiction of real-world genomic characteristics of European patients with PDAC, which offers some useful clinical and research insights.

Interpretable XGBoost-SHAP Model Predicts Nanoparticles Delivery Efficiency Based on Tumor Genomic Mutations and Nanoparticle Properties

Understanding the complex interaction between nanoparticles (NPs) and tumors in vivo and how it dominates the delivery efficiency of NPs is critical for the translation of nanomedicine. Herein, we proposed an interpretable XGBoost-SHAP model by integrating the information on NPs physicochemical properties and tumor genomic profile to predict the delivery efficiency. The correlation coefficients were 0.66, 0.75, and 0.54 for the prediction of maximum delivery efficiency, delivery efficiency at 24 and 168 h postinjection for test sets. The analysis of the feature importance revealed that the tumor genomic mutations and their interaction with NPs properties played important roles in the delivery of NPs. The biological pathways of the NP-delivery-related genes were further explored through gene ontology enrichment analysis. Our work provides a pipeline to predict and explain the delivery efficiency of NPs to heterogeneous tumors and highlights the power of simultaneously using omics data and interpretable machine learning algorithms for discovering interactions between NPs and individual tumors, which is important for the development of personalized precision nanomedicine.

A clinical-grade HLA haplobank of human induced pluripotent stem cells matching approximately 40% of the Japanese population

BACKGROUND

Human induced pluripotent stem cells (iPSCs) are expected to be useful for regenerative medicine for many diseases. Many researchers have focused on and enabled the generation of differentiated cells or tissue-like structures, including organoids, which help to ameliorate target diseases. To promote such cell therapies, we established a clinically applicable iPSC haplobank matching as many people as possible in Japan.

METHODS

Through cooperation with several organizations, we recruited donors whose human leukocyte antigens (HLAs) involved in immunorejection were homozygous. The peripheral or umbilical cord blood collected from the donors was used for iPSC production by electroporation of episomal vectors. These iPSC lines were then subjected to testing, including genome analyses and sterility, to maximize safety.

FINDINGS

We constructed a clinical-grade haplobank of 27 iPSC lines from 7 donors according to good manufacturing practice regulations. However, reasons to avoid using iPSC lines include the presence of residual episomal vectors or genetic mutations in cancer-related genes.

CONCLUSIONS

This haplobank provides HLA-matched iPSC lines for approximately 40% of the Japanese population. Since the haplobank's release in 2015, these iPSC lines have been used in more than 10 clinical trials. The establishment of this haplobank is an important step toward the clinical application of iPSCs in cell therapies.

FUNDING

This study was supported by a research center network for the realization of regenerative medicine of the Japan Agency for Medical Research and Development (AMED) under grant number JP20bm0104001h0108.

Multimodal MRI radiomic models to predict genomic mutations in diffuse intrinsic pontine glioma with missing imaging modalities

Purpose

Predicting H3.1, TP53, and ACVR1 mutations in DIPG could aid in the selection of therapeutic options. The contribution of clinical data and multi-modal MRI were studied for these three predictive tasks. To keep the maximum number of subjects, which is essential for a rare disease, missing data were considered. A multi-modal model was proposed, collecting all available data for each patient, without performing any imputation.

Methods

A retrospective cohort of 80 patients with confirmed DIPG and at least one of the four MR modalities (T1w, T1c, T2w, and FLAIR), acquired with two different MR scanners was built. A pipeline including standardization of MR data and extraction of radiomic features within the tumor was applied. The values of radiomic features between the two MR scanners were realigned using the ComBat method. For each prediction task, the most robust features were selected based on a recursive feature elimination with cross-validation. Five different models, one based on clinical data and one per MR modality, were developed using logistic regression classifiers. The prediction of the multi-modal model was defined as the average of all possible prediction results among five for each patient. The performances of the models were compared using a leave-one-out approach.

Results

The percentage of missing modalities ranged from 6 to 11% across modalities and tasks. The performance of each individual model was dependent on each specific task, with an AUC of the ROC curve ranging from 0.63 to 0.80. The multi-modal model outperformed the clinical model for each prediction tasks, thus demonstrating the added value of MRI. Furthermore, regardless of performance criteria, the multi-modal model came in the first place or second place (very close to first). In the leave-one-out approach, the prediction of H3.1 (resp. ACVR1 and TP53) mutations achieved a balanced accuracy of 87.8% (resp. 82.1 and 78.3%).

Conclusion

Compared with a single modality approach, the multi-modal model combining multiple MRI modalities and clinical features was the most powerful to predict H3.1, ACVR1, and TP53 mutations and provided prediction, even in the case of missing modality. It could be proposed in the absence of a conclusive biopsy.

Prognostic value of KRAS subtype in patients with PDAC undergoing radical resection

Objective

To explore the frequency distribution of KRAS mutant subtypes in patients with resectable PDAC in China and then evaluate the prognostic value of different KRAS subtypes in patients with PDAC undergoing radical resection.

Methods

The clinicopathological data and gene test reports of 227 patients undergoing PDAC radical surgery at Hunan Provincial People's Hospital from 1 January 2016 to 1 January 1 2020 were retrospectively evaluated. There were 118 men (52%) and 109 women (48%). The mean age was 58.8 ± 10.3 years. After univariate analysis of the clinicopathological factors (sex, age, presence or absence of underlying disease, location of the primary tumour, tumour TNM stage, T stage, N stage, presence or absence of vascular invasion, presence or absence of nerve invasion, surgical margin, KRAS mutation subtype), variables with P < 0.1 were included in the multivariate Cox regression model analysis, and the log-rank sum test and Kaplan-Meier curves were used to assess the correlation of the KRAS mutation subtype with the overall survival time.

Results

KRAS mutations were detected in 184 of 227 patients (81.1%) (G12D: 66; G12V: 65; G12R: 27; Q61:26) and were not detected in 43 patients (18.9%). KRAS mutations were associated with tumour differentiation (P = 0.001), TNM stage (P = 0.013), and T stage (P < 0.001). Multivariate Cox regression model analysis showed that N stage, surgical margin, tumour differentiation, and KRAS-G12D mutation were independent prognostic factors for DFS and OS. Patients with the KRAS-G12D subtype had shorter OS with a median OS of 12 months (HR: 0.55, CI: 0.39-0.77, P < 0.001), and patients with KRAS wild-type had longer OS with a median OS of 19 months (HR: 0.57, CI: 0.42-0.76, P < 0.001).

Conclusion

KRAS wild-type individuals are more prevalent in the Chinese population than in European or American populations. Patients undergoing surgery had a reduced percentage of tumors with KRAS-G12D. When determining the prognosis of individuals with radically resected PDAC, reference markers for KRAS mutation subtypes can be employed.

Characterization of the genomic landscape in large-scale Chinese patients with pancreatic cancer

Background

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with an extremely poor prognosis. Effective targets for anticancer therapy confirmed in PDAC are limited. However, the characteristics of genomics have not been fully elucidated in large-scale patients with PDAC from China.

Methods

We collected both blood and tissue samples from 1080 Chinese patients with pancreatic cancer and retrospectively investigated the genomic landscape using next-generation sequencing (NGS).

Findings

We found recurrent somatic mutations in KRAS (83.2%), TP53 (70.6%), CDKN2A (28.8%), SMAD4 (23.0%), ARID1A (12.8%) and CDKN2B (8.9%) in Chinese PDAC patients. Compared with primary pancreatic cancers, more genomic alterations accumulated especially cell cycle regulatory gene variants (45.4% vs 31.6%, P < 0.001) were observed in metastatic tumors. The most common mutation site of KRAS is p.G12D (43.6%) in pancreatic cancer. Patients with KRAS mutations were significantly associated with older age and mutations in the other three driver genes, while KRAS wild-type patients contained more fusion mutations and alternative mechanisms of RTK/Ras/MAPK pathway including a number of clinically targetable mutations. KRAS mutations in Chinese cohort were significantly lower than those in Western cohorts (all P < 0.05). A total of 252 (23.3%) patients with the core DNA damage response (DDR) gene mutations were detected. ATM (n =59, 5.5%) was the most frequent mutant DDR gene in patients with pancreatic cancer from China. Patients with germline DDR gene mutations were younger (P = 0.018), while patients with somatic DDR gene mutations were more likely to accumulate in metastatic lesions (P < 0.001) and had higher TMB levels (P < 0.001). In addition, patients with mutant DDR genes and patients carrying TP53 mutation were observed mutually exclusive (P < 0.001).

Interpretation

We demonstrated the real-world genomic characteristics of large-scale patients with pancreatic cancer from China which may have promising implications for further clinical significance and drug development.

Funding

The funders are listed in the Acknowledgement.

Genomic Variation Prediction: A Summary From Different Views

Structural variations in the genome are closely related to human health and the occurrence and development of various diseases. To understand the mechanisms of diseases, find pathogenic targets, and carry out personalized precision medicine, it is critical to detect such variations. The rapid development of high-throughput sequencing technologies has accelerated the accumulation of large amounts of genomic mutation data, including synonymous mutations. Identifying pathogenic synonymous mutations that play important roles in the occurrence and development of diseases from all the available mutation data is of great importance. In this paper, machine learning theories and methods are reviewed, efficient and accurate pathogenic synonymous mutation prediction methods are developed, and a standardized three-level variant analysis framework is constructed. In addition, multiple variation tolerance prediction models are studied and integrated, and new ideas for structural variation detection based on deep information mining are explored.

Classification of Estrogen Receptor-Positive Breast Cancer Based on Immunogenomic Profiling and Validation at Single-Cell Resolution

Background: The aim of this paper was to identify an immunotherapy-sensitive subtype for estrogen receptor-positive breast cancer (ER+ BC) patients by exploring the relationship between cancer genetic programs and antitumor immunity via multidimensional genome-scale analyses. Methods: Multidimensional ER+ BC high-throughput data (raw count data) including gene expression profiles, copy number variation (CNV) data, single-nucleotide polymorphism mutation data, and relevant clinical information were downloaded from The Cancer Genome Atlas to explore an immune subtype sensitive to immunotherapy using the Consensus Cluster Plus algorithm based on multidimensional genome-scale analyses. One ArrayExpress dataset and eight Gene Expression Omnibus (GEO) datasets (GEO-meta dataset) as well as the Molecular Taxonomy of Breast Cancer International Consortium dataset were used as validation sets to confirm the findings regarding the immune profiles, mutational features, and survival outcomes of the three identified immune subtypes. Moreover, the development trajectory of ER+ BC patients from the single-cell resolution level was also explored. Results: Through comprehensive bioinformatics analysis, three immune subtypes of ER+ BC (C1, C2, and C3, designated the immune suppressive, activation, and neutral subtypes, respectively) were identified. C2 was associated with up-regulated immune cell signatures and immune checkpoint genes. Additionally, five tumor-related pathways (transforming growth factor, epithelial-mesenchymal transition, extracellular matrix, interferon-γ, and WNT signaling) tended to be more activated in C2 than in C1 and C3. Moreover, C2 was associated with a lower tumor mutation burden, a decreased neoantigen load, and fewer CNVs. Drug sensitivity analysis further showed that C2 may be more sensitive to immunosuppressive agents. Conclusion: C2 (the immune activation subtype) may be sensitive to immunotherapy, which provides new insights into effective treatment approaches for ER+ BC.

A new approach to decode DNA methylome and genomic variants simultaneously from double strand bisulfite sequencing

Genetic and epigenetic contributions to various diseases and biological processes have been well-recognized. However, simultaneous identification of single-nucleotide variants (SNVs) and DNA methylation levels from traditional bisulfite sequencing data is still challenging. Here, we develop double strand bisulfite sequencing (DSBS) for genome-wide accurate identification of SNVs and DNA methylation simultaneously at a single-base resolution by using one dataset. Locking Watson and Crick strand together by hairpin adapter followed by bisulfite treatment and massive parallel sequencing, DSBS simultaneously sequences the bisulfite-converted Watson and Crick strand in one paired-end read, eliminating the strand bias of bisulfite sequencing data. Mutual correction of read1 and read2 can estimate the amplification and sequencing errors, and enables our developed computational pipeline, DSBS Analyzer (https://github.com/tianguolangzi/DSBS), to accurately identify SNV and DNA methylation. Additionally, using DSBS, we provide a genome-wide hemimethylation landscape in the human cells, and reveal that the density of DNA hemimethylation sites in promoter region and CpG island is lower than that in other genomic regions. The cost-effective new approach, which decodes DNA methylome and genomic variants simultaneously, will facilitate more comprehensive studies on numerous diseases and biological processes driven by both genetic and epigenetic variations.

Quantitative Estimation of Oxidative Stress in Cancer Tissue Cells Through Gene Expression Data Analyses

Quantitative assessment of the intracellular oxidative stress level is a very important problem since it is the basis for elucidation of the fundamental causes of metabolic changes in diseased human cells, particularly cancer. However, the problem proves to be very challenging to solve in vivo because of the complex nature of the problem. Here a computational method is presented for predicting the quantitative level of the intracellular oxidative stress in cancer tissue cells. The basic premise of the predictor is that the genomic mutation level is strongly associated with the intracellular oxidative stress level. Based on this, a statistical analysis is conducted to identify a set of enzyme-encoding genes, whose combined expression levels can well explain the mutation rates in individual cancer tissues in the TCGA database. We have assessed the validity of the predictor by assessing it against genes that are known to have anti-oxidative functions for specific types of oxidative stressors. Then the applications of the predictor are conducted to illustrate its utility.

Impact of TP53 mutations in breast cancer: Clinicopathological features and prognosisImpact of TP53 mutations in breast CA

Background

TP53 is a crucial tumor suppressor gene. However, the mutation pattern of TP53 in Chinese patients with breast cancer has not yet been determined.

Methods

A total of 411 untreated patients with invasive breast cancer diagnosed at Guangdong Provincial People's Hospital (GDPH) between June 2017 to September 2018 were recruited into the study. Mutational alterations in TP53 were detected and correlations between TP53 mutations and clinicopathological features analyzed. Comparative analysis of the data in the GDPH cohort with those in the METABRIC cohort were carried out.

Results

A significantly higher rate of TP53 mutations was detected in the GDPH cohort (51.3%) compared with the METABRIC cohort (34.4%) (P < 0.01). In the GDPH cohort, 77.8% of the mutations were located in the conserved areas across exons 5–8 of TP53; among these, 112 were identified as missense mutations and mainly clustered in the DNA‐binding region. R273C/H (n = 11) and R248Q/W (n = 10) were two of the most common mutation sites of TP53 detected in the cohort of GDPH patients. Logistic regression multivariate analysis showed that histological grade III, ki‐67 > = 25%, HR‐ and Her2+ in breast cancer had higher mutation probability of TP53 (P < 0.001 in the GDPH cohort). Furthermore, receiver operating characteristic (ROC) model combining molecular typing and Ki‐67 was established to predict the mutation of TP53, and the AUC was 0.846.

Conclusions

A significantly higher rate of TP53 mutation was detected in the Chinese cohort compared with the METABRIC. Correlation analysis revealed a significant association of TP53 mutation with HR‐ and HER2+, higher Ki‐67 and histological grade in breast cancer patients.

Association of survival and genomic mutation signature with immunotherapy in patients with hepatocellular carcinoma

Background

Current guidelines lack recommendations for the use of immunotherapy and immune-related biomarkers for hepatocellular carcinoma (HCC). We aim to provide reliable evidence of the association of survival with HCC immunotherapy and to demonstrate that genomic mutation signature could be an effective biomarker to predict immunotherapy efficacy of HCC patients.

Methods

We conducted a meta-analysis of 17 randomized trials with 2055 patients and an individual patient-level analysis of 31 patients. Trial data were identified in PubMed, EMBASE and Cochrane Central library, and individual patient data were obtained from the cBioPortal database. Overall survival (OS) and progression-free survival (PFS) were assessed with the hazard ratio (HR) and 95% CI. This study is registered with PROSPERO, number CRD42018083991.

Results

The meta-analysis showed that compared to conventional therapy, immunotherapy resulted in prolonged OS (HR =0.65, P<0.0001, high quality) and PFS (HR =0.81, P<0.0001, high quality); the benefits were observed for cellular immunotherapy, tumor vaccine, and cytokine immunotherapy. Findings were robust to subgroup and trial sequential analyses. In the individual patient-level analysis of patients treated with immune checkpoint inhibitor, mutations in TERT, CTNNB1, BRD4, or MLL, and co-mutations in TP53 and TERT or BRD4 were associated with significantly worse survival. These oncogenes were used to develop a novel integrated mutation risk score, which exhibited better utility in predicting survival than the tumor mutation burden (TMB). Patients with low- versus high- mutation risk score had longer OS (HR =0.18, P=0.02) and PFS (HR =0.33, P=0.018). A nomogram comprising the mutation risk score and essential clinical factors further improved the predictive accuracy (AUC =0.840 for both 1- and 2-year OS).

Conclusions

Immunotherapy showed longer OS and PFS than conventional therapy among HCC patients, especially patients with a low mutation risk score. The nomogram based on genomic and clinical characteristics is effective in predicting survival of HCC patients undergoing immune checkpoint inhibitor.

Identification of LCN1 as a Potential Biomarker for Breast Cancer by Bioinformatic Analysis

The biological functions of lipocalin-1 (LCN1) are involved in innate immune responses and act as a physiological scavenger of potentially harmful lipophilic molecules. However, the relevance of LCN1 with cancer is rarely concerned currently. The aim of this study is to address the relevance of LCN1 with BRCA by bioinformatics. In this study, we found that the expressions of LCN1 increased significantly in various cancerous tissues, including BRCA, compared with their adjacent normal tissues through the TIMER database. Furthermore, UALCAN database analysis showed that the expression of LCN1 increased gradually from stage 1 to stage 4 and was upregulated in BRCA patients with different races and subtypes compared with that in the normal. In addition, those patients with perimenopause and postmenopause status displayed higher LCN1 expression. Importantly, LCN1 genetic alterations, including copy number amplification, deep deletion, and missense mutation, could be found, and the alteration frequency showed difference in various invasive BRCA through cBioPortal database. Moreover, a positive correlation between LCN1 somatic copy number alterations and immune cell enrichments was revealed in basal like BRCA by GISTIC 2.0. Finally, analysis on prognostic value of LCN1 by Kaplan-Meier plotter showed that low LCN1 expression correlated with poor prognosis for relapse-free survival in all types of BRCA, overall survival in luminal B BRCA, distant metastasis free survival in human epithelial growth factor receptor-2 (HER2) positive BRCA, and postprogression survival (PPS) in luminal A BRCA. But high LCN1 expression also displayed poor prognosis for PPS in HER2 positive BRCA. The results together verified the significance of LCN1 in BRCA, suggesting that it may be a potential biomarker for BRCA diagnosis.

Identification of Genomic Alterations Acquired During Treatment With EGFR-TKIs in Non-small Cell Lung Cancer

BACKGROUND/AIM

Patients with non-small cell lung cancer (NSCLC) treated with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) eventually develop resistance to these drugs. Although various mechanisms of such resistance have been identified, the mechanism in many cases remains unknown.

MATERIALS AND METHODS

Whole-exome sequencing was performed for tumor tissue from 15 patients with NSCLC who developed EGFR-TKI resistance. Tumor specimens obtained before EGFR-TKI treatment were also analyzed for four patients and normal white blood cell samples for six patients in order to detect genomic alterations that occurred during treatment.

RESULTS

The mutational signature and mutational load acquired during EGFR-TKI treatment varied among patients, with common EGFR-TKI resistance mechanisms including the T790M secondary mutation of EGFR and MET amplification being acquired together with many other genomic alterations. Our results provide insight into the mutational landscape acquired during the development of EGFR-TKI resistance in NSCLC.

Genomic mutation-driven metastatic breast cancer therapy: a single center experience

Background

Next-Generation Sequencing (NGS) has made genomic mutation-driven therapy feasible for metastatic breast cancer (MBC) patients. We frequently submit tumor tissue from MBC patients for targeted NGS of tumor using the Illumina HiSeq 2000 platform (FoundationOne®, Foundation Medicine, MA). Herein, we report the results and clinical impact of this test in MBC patients.

Patients and Methods

We identified patients with MBC treated at City of Hope from January 2014 to May 2016 who underwent NGS. Patients’ clinical characteristics, response to treatment (clinical assessment of tumor regression), and genomic mutation profiles were reviewed.

Results

Forty-four patients with MBC underwent NGS: 24 triple negative breast cancer, 16 estrogen receptor positive, and 4 human epidermal growth factor receptor 2 positive patients. Twenty-three patients received more than three lines of chemotherapy prior to NGS. Actionable mutations (potentially responsive to targeted therapies that are on the market or in registered clinical trials) were identified in almost all patients (42/44; 95%) and over half of these 42 patients with actionable mutations (23/42; 55%) initiated mutation-driven targeted therapies. Of these 23 patients, 16/23 (70%) had assessable responses, and 7/23 (30%) were not assessable for response due to short exposure (<2 weeks) or hospice transition. The remaining 19/42 (45%) patients did not initiate targeted therapy.

Conclusion

NGS can identify effective targeted therapy options for MBC patients based on actionable mutations that were not previously offered based on pathology type. NGS should be performed early in patients with good performance status and preferably in clinical settings where genomic mutation-driven therapeutic trials are available.

Recurrent Rearrangements of Human Amylase Genes Create Multiple Independent CNV Series

The human amylase gene cluster includes the human salivary (AMY1) and pancreatic amylase genes (AMY2A and AMY2B), and is a highly variable and dynamic region of the genome. Copy number variation (CNV) of AMY1 has been implicated in human dietary adaptation, and in population association with obesity, but neither of these findings has been independently replicated. Despite these functional implications, the structural genomic basis of CNV has only been defined in detail very recently. In this work, we use high-resolution analysis of copy number, and analysis of segregation in trios, to define new, independent allelic series of amylase CNVs in sub-Saharan Africans, including a series of higher-order expansions of a unit consisting of one copy each of AMY1, AMY2A, and AMY2B. We use fiber-FISH (fluorescence in situ hybridization) to define unexpected complexity in the accompanying rearrangements. These findings demonstrate recurrent involvement of the amylase gene region in genomic instability, involving at least five independent rearrangements of the pancreatic amylase genes (AMY2A and AMY2B). Structural features shared by fundamentally distinct lineages strongly suggest that the common ancestral state for the human amylase cluster contained more than one, and probably three, copies of AMY1.

Short-term differential adaptation to anaerobic stress via genomic mutations by Escherichia coli strains K-12 and B lacking alcohol dehydrogenase

Microbial adaptations often occur via genomic mutations under adverse environmental conditions. This study used Escherichia coli ΔadhE cells as a model system to investigate adaptation to anaerobic conditions, which we then compared with the adaptive mechanisms of two closely related E. coli strains, K-12 and B. In contrast to K-12 ΔadhE cells, the E. coli B ΔadhE cells exhibited significantly delayed adaptive growth under anaerobic conditions. Adaptation by the K-12 and B strains mainly employed anaerobic lactate fermentation to restore cellular growth. Several mutations were identified in the pta or pflB genes of adapted K-12 cells, but mostly in the pta gene of the B strains. However, the types of mutation in the adapted K-12 and B strains were similar. Cellular viability was affected directly by severe redox imbalance in B ΔadhE cells, which also impaired their ability to adapt to anaerobic conditions. This study demonstrates that closely related microorganisms may undergo different adaptations under the same set of adverse conditions, which might be associated with the specific metabolic characteristics of each strain. This study provides new insights into short-term microbial adaptation to stressful conditions, which may reflect dynamic microbial population changes in nature.

Synergistic effects of A1896, T1653 and T1762/A1764 mutations in genotype c2 hepatitis B virus on development of hepatocellular carcinoma

The effects of genomic changes in hepatitis B virus (HBV) on the occurrence of hepatocellular carcinoma (HCC) are still unclear, especially in relation to the genotype of HBV. In this study, we examined the effects of genomic changes in HBV of genotype C2 on the development of HCC. A total of 318 patients with HBV-associated HCC and 234 patients with chronic hepatitis B (CHB) were studied. All of HCC cases were diagnosed histologically and treated with surgical resection. The whole of the X, S, basal core promoter (BCP) and precore regions of the viral genome from sera or liver tissues were sequenced. All subjects had HBV of genotype C2. The prevalence of the T1653 mutation in the X region and the A1896 mutation in the precore region of HBV was significantly higher in the HCC group than in the control CHB group (22% vs 11%, P = 0.003; 50% vs 23%, P < 0.001, respectively). Moreover, the T1762/A1764 mutations in the BCP region in combination with either T1653 or A1896 were more common in the HCC compared with the CHB group (BCP+X1653: 18% vs 11%, P = 0.05; BCP+PC, 40% vs 15%, P < 0.001, respectively). In multivariate analysis, T1653 and A1896 were revealed to be independent risk factors for HCC development. G1896A in the precore region and C1653T mutation in the X region of genotype C2 HBV are important risk factors for HCC development. Also, the A1762T/G1764A double mutation may act in synergy with C1653T to increase the risk of HCC in patients chronically infected with HBV genotype C2.

Loss of N-glycolylneuraminic acid in humans: Mechanisms, consequences, and implications for hominid evolution

The surface of all mammalian cells is covered with a dense and complex array of sugar chains, which are frequently terminated by members of a family of molecules called sialic acids. One particular sialic acid called N-glycolylneuraminic acid (Neu5Gc) is widely expressed on most mammalian tissues, but is not easily detectable on human cells. In fact, it provokes an immune response in adult humans. The human deficiency of Neu5Gc is explained by an inactivating mutation in the gene encoding CMP-N-acetylneuraminic acid hydroxylase, the rate-limiting enzyme in generating Neu5Gc in cells of other mammals. This deficiency also results in an excess of the precursor sialic acid N-acetylneuraminic acid (Neu5Ac) in humans. This mutation appears universal to modern humans, occurred sometime after our last common ancestor with the great apes, and happens to be one of the first known human-great ape genetic differences with an obvious biochemical readout. While the original selection mechanisms and major biological consequences of this human-specific mutation remain uncertain, several interesting clues are currently being pursued. First, there is evidence that the human condition can explain differences in susceptibility or resistance to certain microbial pathogens. Second, the functions of some endogenous receptors for sialic acids in the immune system may be altered by this difference. Third, despite the lack of any obvious alternate pathway for synthesis, Neu5Gc has been reported in human tumors and possibly in human fetal tissues, and traces have even been detected in normal human tissues. One possible explanation is that this represents accumulation of Neu5Gc from dietary sources of animal origin. Finally, a markedly reduced expression of hydroxylase in the brains of other mammals raises the possibility that the human-specific mutation of this enzyme could have played a role in human brain evolution.