Clinical Validation of the Unparalleled Sensitivity of the Novel Allele-Discriminating Priming System Technology-Based EGFR Mutation Assay in Patients with Operable Non-Small Cell Lung Cancer

PURPOSE

Recently, we developed allele-discriminating priming system (ADPS) technology. This method increases the sensitivity of conventional quantitative polymerase chain reaction up to 100 folds, with limit of detection, 0.01%, with reinforced specificity. This prospective study aimed to develop and validate the accuracy of ADPS epidermal growth factor receptor (EGFR) Mutation Test Kit using clinical specimens.

MATERIALS AND METHODS

In total 189 formalin-fixed paraffin-embedded tumor tissues resected from patients with non-small cell lung cancer were used to perform a comparative evaluation of the ADPS EGFR Mutation Test Kit versus the cobas EGFR Mutation Test v2, which is the current gold standard. When the two methods had inconsistent results, next-generation sequencing-based CancerSCAN was utilized as a referee.

RESULTS

The overall agreement of the two methods was 97.4% (93.9%-99.1%); the positive percent agreement, 95.0% (88.7%-98.4%); and the negative percent agreement, 100.0% (95.9%-100.0%). EGFR mutations were detected at a frequency of 50.3% using the ADPS EGFR Mutation Test Kit and 52.9% using the cobas EGFR Mutation Test v2. There were 10 discrepant mutation calls between the two methods. CancerSCAN reproduced eight ADPS results. In two cases, mutant allele fraction was ultra-low at 0.02% and 0.06%, which are significantly below the limit of detection of the cobas assay and CancerSCAN. Based on the EGFR genotyping by ADPS, the treatment options could be switched in five patients.

CONCLUSION

The highly sensitive and specific ADPS EGFR Mutation Test Kit would be useful in detecting the patients who have lung cancer with EGFR mutation, and can benefit from the EGFR targeted therapy.

Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy: development and validation study

BACKGROUND : Deep learning models have previously been established to predict the histopathology and invasion depth of gastric lesions using endoscopic images. This study aimed to establish and validate a deep learning-based clinical decision support system (CDSS) for the automated detection and classification (diagnosis and invasion depth prediction) of gastric neoplasms in real-time endoscopy. METHODS : The same 5017 endoscopic images that were employed to establish previous models were used for the training data. The primary outcomes were: (i) the lesion detection rate for the detection model, and (ii) the lesion classification accuracy for the classification model. For performance validation of the lesion detection model, 2524 real-time procedures were tested in a randomized pilot study. Consecutive patients were allocated either to CDSS-assisted or conventional screening endoscopy. The lesion detection rate was compared between the groups. For performance validation of the lesion classification model, a prospective multicenter external test was conducted using 3976 novel images from five institutions. RESULTS : The lesion detection rate was 95.6 % (internal test). On performance validation, CDSS-assisted endoscopy showed a higher lesion detection rate than conventional screening endoscopy, although statistically not significant (2.0 % vs. 1.3 %; P = 0.21) (randomized study). The lesion classification rate was 89.7 % in the four-class classification (advanced gastric cancer, early gastric cancer, dysplasia, and non-neoplastic) and 89.2 % in the invasion depth prediction (mucosa confined or submucosa invaded; internal test). On performance validation, the CDSS reached 81.5 % accuracy in the four-class classification and 86.4 % accuracy in the binary classification (prospective multicenter external test). CONCLUSIONS : The CDSS demonstrated its potential for real-life clinical application and high performance in terms of lesion detection and classification of detected lesions in the stomach.

Temporal Change in the Use of Laboratory and Imaging Tests in One Week Before Death, 2006–2015

BACKGROUND

To analyze the trends in laboratory and imaging test use 1 week before death among decedents who died in Korean hospitals, tests used per decedents from 2006 to 2015 were examined by using the National Health Insurance Service-Elderly Sample Cohort (NHIS-ESC) dataset.

METHODS

The study population consisted of decedents aged ≥ 60 years old with a history of admission and death at a hospital, and tests recorded in the payment claims for laboratory and imaging tests according to the Healthcare Common Procedure Coding System codes were examined. Twenty-eight laboratory and 6 imaging tests were selected. For each year, crude rates of test use per decedents in each age and sex stratum were calculated. Regression analysis was used to examine the temporal changes in the test use.

RESULTS

During the follow-up period, 6,638 subjects included in the sample cohort died. The number of total laboratory and imaging tests performed on the deceased increased steadily throughout the study year from 10.3 tests/deceased in 2006 to 16.6 tests/deceased in 2015. The use of tests increased significantly in general hospitals, however, not in nursing hospitals. Laboratory tests showed yearly increase, from 9.46/deceased in 2006 to 15.57/deceased in 2015, an annual increase of 7.39%. On the other hand, the use of imaging increased from 0.86/deceased in 2006 to 1.01/deceased in 2015, which was not statistically significant.

CONCLUSION

The use of tests, especially laboratory tests, increased steadily over the years even among those elderly patients at imminent death. Reducing acute healthcare at the end of life would be one target not only to support the sustainability of the health care budget but also to improve the quality of dying and death.

Correlation between the ratio of physician consultation fees to hourly minimum wage and consultation length: a cross-sectional study of nine countries

OBJECTIVES

Current healthcare reimbursement system is criticised for not adequately compensating physicians' cognitive services. This study was performed to examine primary care physicians' consultation fees in nine countries, relative to the national hourly minimum wage and to examine the correlations of the physician consultation fee with consultation length and other healthcare indices.

DESIGN AND OUTCOME MEASURES

Nine reference countries for which healthcare statistics are publicly available and outpatient consultation is compensated by fee-for-service payment were selected. A representative consultation fee was chosen to calculate the ratio of the consultation fee to the hourly minimum wage. The primary outcome was the correlation between the consultation fee/hourly minimum wage ratio and consultation length. In addition, the consultation fees were compared with fees for haemoglobin A1c tests and brain imaging. Pearson's method was primarily used for correlation analysis.

RESULTS

The mean representative consultation fee/hourly minimum wage ratio was 4.02 (median, 2.7; range, 0.80-10.36). The mean consultation length was 12.9 min (median, 14.7 min; range, 5-21.1 min). A significant correlation (r=0.79) was found between consultation length and the consultation fee/hourly minimum wage ratio. The ratio of consultation fee to hourly minimum wage was moderately negatively correlated with the annual number of physician visits, number of consultations per doctor and length of hospital stay. The brain CT fee/consultation fee ratio was moderately positively correlated with the number of CT units per 1 million population. In Japan and Korea, where the brain CT/consultation fee ratio was highest, the number of CT examinations per population was also highest.

CONCLUSIONS

The relationship of consultation fees to each country's hourly minimum wage varied in nine reference countries; however, it was strongly correlated with consultation length. The imbalance in compensation for cognitive services might drive increased use of imaging tests in some countries.

Comparison of cell type distribution between single-cell and single-nucleus RNA sequencing: enrichment of adherent cell types in single-nucleus RNA sequencing

Single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) is an effective technique for estimating the cellular composition and transcriptional profiles of individual cells from fresh tissue. Single-nucleus RNA sequencing (snRNA-seq) is necessary to perform this type of analysis in frozen or difficult-to-dissociate tissues, which cannot be subjected to scRNA-seq. This difference in the state of tissues leads to variation in cell-type distributions among each platform. To identify the characteristics of these methods and their differences, scRNA-seq and snRNA-seq were performed in parallel for colon and liver tissues. The two platforms revealed similar diversity but different proportions of cell types in matched tissues. The proportions of epithelial cells in the colon and hepatocytes in the liver were relatively high in snRNA-seq and that of immune cells was relatively high in scRNA-seq. This difference could be explained by variations in the expression scores of adhesion genes due to the disruption of the cytoplasmic contents during scRNA-seq. The enrichment of epithelial cells in the colon resulted in a discrepancy in the differentiation of epithelial cells. This enrichment was also well matched with the images of hematoxylin and eosin staining and the estimated distribution of cell types in bulk RNA sequencing. These results showed that snRNA-seq could be used to analyze tissues that cannot be subjected to scRNA-seq and provides more information in specific cell type analysis.

Chronic Rhinosinusitis and the Increased Incidence of Atopic Dermatitis

BACKGROUND

Chronic rhinosinusitis (CRS) is often associated with other comorbidities due to chronic inflammation. However, no population-based, longitudinal study has investigated the relationship between CRS and chronic skin inflammation.

OBJECTIVE

To investigate the potential relationship between CRS and chronic skin inflammatory diseases, such as atopic dermatitis (AD), vitiligo, and psoriasis.

METHODS

A total of 5638 patients with CRS and 11 276 without CRS as a comparison group, were included from the Korean National Health Insurance Service database from 2002-2013. A propensity score matching (1:2) was performed using the nearest neighbor matching method, sociodemographic factors, and enrollment year. The Cox proportional hazards model was used to analyze the hazard ratio of CRS for AD, vitiligo, and psoriasis.

RESULTS

Results from this study showed that patients with CRS had no significant risk of the subsequent development of vitiligo or psoriasis compared to patients without CRS. However, we found a significantly higher incidence of AD in CRS patients than in those without CRS. The incidence of AD was 63.59 per 1000 person-years in the CRS group and 45.38 per 1000 person-years in the comparison group. Additionally, young and middle-aged CRS patients were independently associated with a higher incidence of subsequent AD events, but we could not find a significantly higher incidence of AD events in the elderly group.

CONCLUSIONS

Our findings suggest there are no significant differences in the overall risk of vitiligo and psoriasis events in patients with CRS; however, we detected a higher risk of AD in young and middle-aged CRS patients. Therefore, clinicians should consider the risk of developing AD in specific patients who are newly diagnosed with CRS.

Fast Healthcare Interoperability Resources (FHIR)-Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study

Background

Next-generation sequencing (NGS) technology has been rapidly adopted in clinical practice, with the scope extended to early diagnosis, disease classification, and treatment planning. As the number of requests for NGS genomic testing increases, substantial efforts have been made to deliver the testing results clearly and unambiguously. For the legitimacy of clinical NGS genomic testing, quality information from the process of producing genomic data should be included within the results. However, most reports provide insufficient quality information to confirm the reliability of genomic testing owing to the complexity of the NGS process.

Objective

The goal of this study was to develop a Fast Healthcare Interoperability Resources (FHIR)–based web app, NGS Quality Reporting (NGS-QR), to report and manage the quality of the information obtained from clinical NGS genomic tests.

Methods

We defined data elements for the exchange of quality information from clinical NGS genomic tests, and profiled a FHIR genomic resource to enable information exchange in a standardized format. We then developed the FHIR-based web app and FHIR server to exchange quality information, along with statistical analysis tools implemented with the R Shiny server.

Results

Approximately 1000 experimental data entries collected from the targeted sequencing pipeline CancerSCAN designed by Samsung Medical Center were used to validate implementation of the NGS-QR app using real-world data. The user can share the quality information of NGS genomic testing and verify the quality status of individual samples in the overall distribution.

Conclusions

This study successfully demonstrated how quality information of clinical NGS genomic testing can be exchanged in a standardized format. As the demand for NGS genomic testing in clinical settings increases and genomic data accumulate, quality information can be used as reference material to improve the quality of testing. This app could also motivate laboratories to perform diagnostic tests to provide high-quality genomic data.

Evaluation of Combined Cancer Markers With Lactate Dehydrogenase and Application of Machine Learning Algorithms for Differentiating Benign Disease From Malignant Ovarian Cancer

BACKGROUND

The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classified by machine learning algorithms in patients with early stage ovarian cancer, which has rarely been reported.

METHODS

In total, 730 serum samples were assayed for lactate dehydrogenase (LD), neutrophil-to-lymphocyte ratio (NLR), human epididymis protein 4 (HE4), cancer antigen 125 (CA125), and risk of ovarian malignancy algorithm (ROMA). Among them, 53 were diagnosed with early stage ovarian cancer, and the remaining 677 were diagnosed with benign disease.

RESULTS

The areas under the receiver operating characteristic curves (ROC-AUCs) of the ROMA, HE4, CA125, LD, and NLR for discriminating ovarian cancer from non-cancerous disease were .707, .680, .643, .657, and .624, respectively. ROC-AUC of the combination of ROMA and LD (.709) was similar to that of single ROMA in the total population. In the postmenopausal group, ROC-AUCs of HE4 and CA125 combined with LD presented the highest value (.718). When machine learning algorithms were applied to ROMA combined with LD, the ROC-AUC of random forest was higher than that of other applied algorithms in the total population (.757), showing acceptable performance.

CONCLUSION

Our data suggest that the combinations of ovarian cancer-specific markers with LD classified by random forest may be a useful tool for predicting ovarian cancer, particularly in clinical settings, due to easy accessibility and cost-effectiveness. Application of an optimal combination of cancer markers and algorithms would facilitate appropriate management of ovarian cancer patients.

Tumor-promoting macrophages prevail in malignant ascites of advanced gastric cancer

Gastric cancer (GC) patients develop malignant ascites as the disease progresses owing to peritoneal metastasis. GC patients with malignant ascites have a rapidly deteriorating clinical course with short survival following the onset of malignant ascites. Better optimized treatment strategies for this subset of patients are needed. To define the cellular characteristics of malignant ascites of GC, we used single-cell RNA sequencing to characterize tumor cells and tumor-associated macrophages (TAMs) from four samples of malignant ascites and one sample of cerebrospinal fluid. Reference transcriptomes for M1 and M2 macrophages were generated by in vitro differentiation of healthy blood-derived monocytes and applied to assess the inflammatory properties of TAMs. We analyzed 180 cells, including tumor cells, macrophages, and mesothelial cells. Dynamic exchange of tumor-promoting signals, including the CCL3–CCR1 or IL1B–IL1R2 interactions, suggests macrophage recruitment and anti-inflammatory tuning by tumor cells. By comparing these data with reference transcriptomes for M1-type and M2-type macrophages, we found noninflammatory characteristics in macrophages recovered from the malignant ascites of GC. Using public datasets, we demonstrated that the single-cell transcriptome-driven M2-specific signature was associated with poor prognosis in GC. Our data indicate that the anti-inflammatory characteristics of TAMs are controlled by tumor cells and present implications for treatment strategies for GC patients in which combination treatment targeting cancer cells and macrophages may have a reciprocal synergistic effect.

New strategies for treating advanced gastric cancer could emerge from insights into the interactions between white blood cells called macrophages and tumor cells in fluid known as malignant ascites that accumulates in the abdomen. Researchers in Seoul, South Korea, led by Hae-Ock Lee at The Catholic University of Korea and Woong-Yang Park at the Samsung Medical Center compared macrophages from healthy subjects with those from gastric cancer ascites. They identified molecular signaling interactions between tumor cells and macrophages that recruited macrophages into the ascites and converted them into more anti-inflammatory forms. The macrophages were then able to promote the activities of the cancer cells. The results suggest that chemicals able to inhibit or deplete proteins now identified as involved in controlling these synergistic interactions could become a new class of therapeutic agents.

Clinical Targeted Next-Generation sequencing Panels for Detection of Somatic Variants in Gliomas

PURPOSE

Targeted next-generation sequencing (NGS) panels for solid tumors have been useful in clinical framework for accurate tumor diagnosis and identifying essential molecular aberrations. However, most cancer panels have been designed to address a wide spectrum of pan-cancer models, lacking integral prognostic markers that are highly specific to gliomas.

Materials and Methods

To address such challenges, we have developed a glioma-specific NGS panel, termed "GliomaSCAN," that is capable of capturing single nucleotide variations and insertion/deletion, copy number variation, and selected promoter mutations and structural variations that cover a subset of intron regions in 232 essential glioma-associated genes. We confirmed clinical concordance rate using pairwise comparison of the identified variants from whole exome sequencing (WES), immunohistochemical analysis, and fluorescence in situ hybridization.

RESULTS

Our panel demonstrated high sensitivity in detecting potential genomic variants that were present in the standard materials. To ensure the accuracy of our targeted sequencing panel, we compared our targeted panel to WES. The comparison results demonstrated a high correlation. Furthermore, we evaluated clinical utility of our panel in 46 glioma patients to assess the detection capacity of potential actionable mutations. Thirty-two patients harbored at least one recurrent somatic mutation in clinically actionable gene.

CONCLUSION

We have established a glioma-specific cancer panel. GliomaSCAN highly excelled in capturing somatic variations in terms of both sensitivity and specificity and provided potential clinical implication in facilitating genome-based clinical trials. Our results could provide conceptual advance towards improving the response of genomically guided molecularly targeted therapy in glioma patients.

Genomic Common Data Model for Seamless Interoperation of Biomedical Data in Clinical Practice: Retrospective Study

Background

Clinical sequencing data should be shared in order to achieve the sufficient scale and diversity required to provide strong evidence for improving patient care. A distributed research network allows researchers to share this evidence rather than the patient-level data across centers, thereby avoiding privacy issues. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) used in distributed research networks has low coverage of sequencing data and does not reflect the latest trends of precision medicine.

Objective

The aim of this study was to develop and evaluate the feasibility of a genomic CDM (G-CDM), as an extension of the OMOP-CDM, for application of genomic data in clinical practice.

Methods

Existing genomic data models and sequencing reports were reviewed to extend the OMOP-CDM to cover genomic data. The Human Genome Organisation Gene Nomenclature Committee and Human Genome Variation Society nomenclature were adopted to standardize the terminology in the model. Sequencing data of 114 and 1060 patients with lung cancer were obtained from the Ajou University School of Medicine database of Ajou University Hospital and The Cancer Genome Atlas, respectively, which were transformed to a format appropriate for the G-CDM. The data were compared with respect to gene name, variant type, and actionable mutations.

Results

The G-CDM was extended into four tables linked to tables of the OMOP-CDM. Upon comparison with The Cancer Genome Atlas data, a clinically actionable mutation, p.Leu858Arg, in the EGFR gene was 6.64 times more frequent in the Ajou University School of Medicine database, while the p.Gly12Xaa mutation in the KRAS gene was 2.02 times more frequent in The Cancer Genome Atlas dataset. The data-exploring tool GeneProfiler was further developed to conduct descriptive analyses automatically using the G-CDM, which provides the proportions of genes, variant types, and actionable mutations. GeneProfiler also allows for querying the specific gene name and Human Genome Variation Society nomenclature to calculate the proportion of patients with a given mutation.

Conclusions

We developed the G-CDM for effective integration of genomic data with standardized clinical data, allowing for data sharing across institutes. The feasibility of the G-CDM was validated by assessing the differences in data characteristics between two different genomic databases through the proposed data-exploring tool GeneProfiler. The G-CDM may facilitate analyses of interoperating clinical and genomic datasets across multiple institutions, minimizing privacy issues and enabling researchers to better understand the characteristics of patients and promote personalized medicine in clinical practice.

Bridging genomics and phenomics of gastric carcinoma

Genetic alterations are the starting point leading to numerous changes in clinical and pathologic features (phenotypes) of individual cancers; however, their inter-relationships in gastric cancers (GC) are unclear. We performed massive parallel sequencing of 381 cancer-related genes and compared the results with clinical and pathologic findings in 330 GC. High tumor mutation burden (TMB) accounted for 11% of GC (n = 37) and all 19 MSI-H GCs were high TMB. High TMB was significantly more frequent in intestinal-type by Lauren, tumor with higher host cellular immune response, earlier AJCC stage and favorable prognosis. The most significantly mutated genes were TP53 (54%), ARID1A (23%), CDH1 (22%), PIK3CA (12%), RNF43 (10%) and KRAS (9%). For receptor tyrosine kinases, amplifications detected by immunohistochemistry were higher than sequencing (HER2, 9.1% vs. 5.8%; EGFR, 11.2% vs. 6.1%; FGFR2, 4.6% vs. 3.9%, c-MET, 3.4% vs. 0.9%). PTEN protein loss (22%) correlated well with underlying PTEN alterations while ATM loss (27%) was not significantly correlated with genetic alterations of ATM. p53 protein expression predicted alterations of TP53 with high sensitivity (97.8%) and low (15.9%) specificity. The poorly cohesive histology/CDH1-mutant GC subgroup showed the worst survival (p < 0.001). PD-L1 expression was significantly associated with MSI-H, MLH1 loss, ATM loss, MET positivity, higher host immune response, and genetic alterations of ARID1A, BRD3, PIK3CA, KRAS, MAP3K13, CDH2, PTEN and ESR1. The merged clinical, pathology and genomics of GC provide a better understanding of GC and new insights into the treatment of GC.

Performance evaluation of commercial library construction kits for PCR-based targeted sequencing using a unique molecular identifier

Background

Target enrichment is a critical component of targeted deep next-generation sequencing for the cost-effective and sensitive detection of mutations, which is predominantly performed by either hybrid selection or PCR. Despite the advantages of efficient enrichment, PCR-based methods preclude the identification of PCR duplicates and their subsequent removal. Recently, this limitation was overcome by assigning a unique molecular identifier(UMI) to each template molecule. Currently, several commercial library construction kits based on PCR enrichment are available for UMIs, but there have been no systematic studies to compare their performances. In this study, we evaluated and compared the performances of five commercial library kits from four vendors: the Archer® Reveal ctDNA™ 28 Kit, NEBNext Direct® Cancer HotSpot Panel, Nugen Ovation® Custom Target Enrichment System, Qiagen Human Comprehensive Cancer Panel(HCCP), and Qiagen Human Actionable Solid Tumor Panel(HASTP).

Results

We evaluated and compared the performances of the five kits using 50 ng of genomic DNA for the library construction in terms of the library complexity, coverage uniformity, and errors in the UMIs. While the duplicate rates for all kits were dramatically decreased by identifying unique molecules with UMIs, the Qiagen HASTP achieved the highest library complexity based on the depth of unique coverage indicating superb library construction efficiency. Regarding the coverage uniformity, the kits from Nugen and NEB performed the best followed by the kits from Qiagen. We also analyzed the UMIs, including errors, which allowed us to adjust the depth of unique coverage and the length required for sufficient complexity. Based on these comparisons, we selected the Qiagen HASTP for further performance evaluations. The targeted deep sequencing method based on PCR target enrichment combined with UMI tagging sensitively detected mutations present at a frequency as low as 1% using 6.25 ng of human genomic DNA as the starting material.

Conclusion

This study is the first systematic evaluation of commercial library construction kits for PCR-based targeted deep sequencing utilizing UMIs. Because the kits displayed significant variability in different quality metrics, our study offers a practical guideline for researchers to choose appropriate options for PCR-based targeted sequencing and useful benchmark data for evaluating new kits.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5583-7) contains supplementary material, which is available to authorized users.

Utility of targeted deep sequencing for detecting circulating tumor DNA in pancreatic cancer patients

Targeted deep sequencing across broad genomic regions has been used to detect circulating tumor DNA (ctDNA) in pancreatic ductal adenocarcinoma (PDAC) patients. However, since most PDACs harbor a mutation in KRAS, sequencing of broad regions needs to be systemically compared to analyzing only KRAS mutations for PDAC. Using capture-based targeted deep sequencing, we detected somatic tumor mutations in 17 fine needle aspiration biopsy and 69 longitudinal cell-free DNA (cfDNA) samples from 17 PDAC patients. KRAS mutations were detected in 10 out of 17 pretreatment patient plasma samples. Next, interrogation of genetic alterations in matched primary tumor samples detected ctDNA in 12 of 17 pretreatment plasma samples and cfDNA sequencing across the 83 target genes identified ctDNA in 15 of 17 cases (88.2% sensitivity). This improved sensitivity of ctDNA detection resulted in enhanced tumor burden monitoring when we analyzed longitudinal plasma samples. We found that cfDNA sequencing detected the lowest mutant allelic fractions and number of variants when complete response or partial response to chemotherapy was achieved. We demonstrated that ctDNA levels measured by targeted deep sequencing sensitively indicate the presence of cancer and correlate well with clinical responses to therapy and disease progression in PDAC patients.

Nonlinear tumor evolution from dysplastic nodules to hepatocellular carcinoma

Dysplastic nodules are premalignant neoplastic nodules found in explanted livers with cirrhosis. Genetic signatures of premalignant dysplastic nodules (DNs) with concurrent hepatocellular carcinoma (HCC) may provide an insight in the molecular evolution of hepatocellular carcinogenesis. We analyzed four patients with multifocal nodular lesions and cirrhotic background by whole-exome sequencing (WES). The genomic profiles of somatic single nucleotide variations (SNV) and copy number variations (CNV) in DNs were compared to those of HCCs. The number and variant allele frequency of somatic SNVs of DNs and HCCs in each patient was identical along the progression of pathological grade. The somatic SNVs in DNs showed little conservation in HCC. Additionally, CNVs showed no conservation. Phylogenetic analysis based on SNVs and copy number profiles indicated a nonlinear segregation pattern, implying independent development of DNs and HCC in each patient. Thus, somatic mutations in DNs may be developed separately from other malignant nodules in the same liver, suggesting a nonlinear model for hepatocarcinogenesis from DNs to HCC.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level.

Analysis of intrapatient heterogeneity uncovers the microevolution of Middle East respiratory syndrome coronavirus

Genome sequence analysis of Middle East respiratory syndrome coronavirus (MERS-CoV) variants from patient specimens has revealed the evolutionary dynamics and mechanisms of pathogenesis of the virus. However, most studies have analyzed the consensus sequences of MERS-CoVs, precluding an investigation of intrapatient heterogeneity. Here, we analyzed non–consensus sequences to characterize intrapatient heterogeneity in cases associated with the 2015 outbreak of MERS in South Korea. Deep-sequencing analysis of MERS-CoV genomes performed on specimens from eight patients revealed significant intrapatient variation; therefore, sequence heterogeneity was further analyzed using targeted deep sequencing. A total of 35 specimens from 24 patients (including a super-spreader) were sequenced to detect and analyze variants displaying intrapatient heterogeneity. Based on the analysis of non–consensus sequences, we demonstrated the intrapatient heterogeneity of MERS-CoVs, with the highest level in the super-spreader specimen. The heterogeneity could be transmitted in a close association with variation in the consensus sequences, suggesting the occurrence of multiple MERS-CoV infections. Analysis of intrapatient heterogeneity revealed a relationship between D510G and I529T mutations in the receptor-binding domain (RBD) of the viral spike glycoprotein. These two mutations have been reported to reduce the affinity of the RBD for human CD26. Notably, although the frequency of both D510G and I529T varied greatly among specimens, the combined frequency of the single mutants was consistently high (87.7% ± 1.9% on average). Concurrently, the frequency of occurrence of the wild type at the two positions was only 6.5% ± 1.7% on average, supporting the hypothesis that selection pressure exerted by the host immune response played a critical role in shaping genetic variants and their interaction in human MERS-CoVs during the outbreak.

Performance evaluation method for read mapping tool in clinical panel sequencing

In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recently. With the accumulated panel sequencing data, detected variant lists were cataloged and inserted into simulated reads produced from the reference genome (h19). The amount of unmapped reads and misaligned reads, mapping quality distribution, and runtime were measured as standards for comparison. As the most widely used tools, Bowtie2 and BWA–MEM each showed explicit performance with AUC of 0.9984 and 0.9970 respectively. Kart, maintaining superior runtime and less number of misaligned read, also similarly possessed high level of AUC (0.9723). Such selection and optimization method of tools appropriate for panel sequencing can be utilized for fields requiring error minimization, such as clinical application and liquid biopsy studies.

Circulating tumor DNA shows variable clonal response of breast cancer during neoadjuvant chemotherapy

Circulating tumor DNA (ctDNA) correlates with tumor burden and provides early detection of treatment response and tumor genetic alterations in breast cancer (BC). In this study, we aimed to identify genetic alterations during the process of tumor clonal evolution and examine if ctDNA level well indicated clinical response to neoadjuvant chemotherapy (NAC) and BC recurrence.

We performed targeted ultra-deep sequencing of plasma DNAs, matched germline DNAs and tumor DNAs from locally advanced BC patients. Serial plasma DNAs were collected at diagnosis, after the 1^st cycle of NAC and after curative surgery. For the target enrichment, we designed RNA baits covering a total of ∼202kb regions of the human genome including a total of 82 cancer-related genes.

For ctDNA, 15 serial samples were collected and 87% of plasma SNVs were detected in 13 BC samples that had somatic alterations in tumor tissues. The TP53 mutation was most commonly detected in primary tumor tissues and plasma followed by BRCA1 and BRCA2. At BC diagnosis, the amount of plasma SNVs did not correlate with clinical stage at diagnosis. With respect to the therapeutic effects of NAC, we found two samples in which ctDNA disappeared after the 1^st NAC cycle achieved a pathologic complete response (pCR). In addition, the amount of ctDNA correlated with residual cancer volume detected by breast MRI.

This targeted ultra-deep sequencing for ctDNA analysis would be useful for monitoring tumor burden and drug resistance. Most of all, we suggest that ctDNA could be the earliest predictor of NAC response.

Characterization of background noise in capture-based targeted sequencing data

Background

Targeted deep sequencing is increasingly used to detect low-allelic fraction variants; it is therefore essential that errors that constitute baseline noise and impose a practical limit on detection are characterized. In the present study, we systematically evaluate the extent to which errors are incurred during specific steps of the capture-based targeted sequencing process.

Results

We removed most sequencing artifacts by filtering out low-quality bases and then analyze the remaining background noise. By recognizing that plasma DNA is naturally fragmented to be of a size comparable to that of mono-nucleosomal DNA, we were able to identify and characterize errors that are specifically associated with acoustic shearing. Two-thirds of C:G > A:T errors and one quarter of C:G > G:C errors were attributed to the oxidation of guanine during acoustic shearing, and this was further validated by comparative experiments conducted under different shearing conditions. The acoustic shearing step also causes A > G and A > T substitutions localized to the end bases of sheared DNA fragments, indicating a probable association of these errors with DNA breakage. Finally, the hybrid selection step contributes to one-third of the remaining C:G > A:T and one-fifth of the C > T errors.

Conclusions

The results of this study provide a comprehensive summary of various errors incurred during targeted deep sequencing, and their underlying causes. This information will be invaluable to drive technical improvements in this sequencing method, and may increase the future usage of targeted deep sequencing methods for low-allelic fraction variant detection.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1275-2) contains supplementary material, which is available to authorized users.

Abstract 423: Detection of genetic alterations to predict the chemotherapeutic responses in unresectable pancreatic ductal adenocarcinomas

Background & Aims: Next-generation sequencing (NGS) that enables the analyses of massively parallel sequences of DNA can advance the understanding of the underlying molecular pathophysiologies of cancer. Such recent genomic analyses have revealed a complex mutational landscape for PDACs. The aims of this study were to investigate the genomic profile to predict the chemotherapy response in unresectable PDACs.

Methods: The total of 80 pathologically confirmed PDACs were enrolled and genomic DNA was extracted and quality control metrics of DNA analytes were measured. The specimens that passed a quality control test underwent targeted deep sequencing using a customized cancer panel (CancerSCAN) enriched in the exons of 83 genes.

Results: Clinical prognostic factors associated with survival in PDAC were gender, tumor mass size, stage and chemotherapy response rate. (P=0.078, 0.009, 0.052 and &lt;0.001, respectively). Multivariate Cox proportional-hazards analysis revealed chemotherapy response rate (P &lt; 0.001, hazard ratio (HR) = 1.908, 95% CI, 1.281 to 2.840) is an independent prognostic factor. There were 56 (71%) and 9 (11%) study patients who underwent gemcitabine based chemotherapy and FOLFIRINOX respectively. Response rate of study patients were as follows; CR+PR 14 (20%), SD (27%) and PD 28 (41%). There were only 9 (16%) and 4 (50%) patients who had CR+PR response gemcitabine based chemotherapy and FOLFIRINOX respectively.

Conclusion: Targeted sequencing using EUS-FNA specimens in PDAC showed excellent compatibilities to analyze genomic profiles of PDACs. Furthermore, novel genes associated with survival, metastasis and chemotherapy response in PDAC were identified.

Citation Format: Joo Kyung Park, Kwang Hyuck Lee, Donghyun Park, Woong-Yang Park, Dae-Soon Son, Jong Kyun Lee, Kyu Taek Lee. Detection of genetic alterations to predict the chemotherapeutic responses in unresectable pancreatic ductal adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 423. doi:10.1158/1538-7445.AM2017-423

Vertical Magnetic Separation of Circulating Tumor Cells for Somatic Genomic-Alteration Analysis in Lung Cancer Patients

Efficient isolation and genetic analysis of circulating tumor cells (CTCs) from cancer patients’ blood is a critical step for clinical applications using CTCs. Here, we report a novel CTC-isolation method and subsequent genetic analysis. CTCs from the blood were complexed with magnetic beads coated with antibodies against the epithelial cell adhesion molecule (EpCAM) and separated vertically on a density-gradient medium in a modified well-plate. The recovery rate of model CTCs was reasonable and the cell purity was enhanced dramatically when compared to those parameters obtained using a conventional magnetic isolation method. CTCs were recovered from an increased number of patient samples using our magnetic system vs. the FDA-approved CellSearch system (100% vs. 33%, respectively). In 8 of 13 cases, targeted deep sequencing analysis of CTCs revealed private point mutations present in CTCs but not in matched tumor samples and white blood cells (WBCs), which was also validated by droplet digital PCR. Copy-number alterations in CTCs were also observed in the corresponding tumor tissues for some patients. In this report, we showed that CTCs isolated by the EpCAM-based method had complex and diverse genetic features that were similar to those of tumor samples in some, but not all, cases.

Abstract 96: Targeted sequencing from endoscopic ultrasound-guided fine needle aspirates of pancreatic ductal adenocarcinoma

Next-generation sequencing (NGS) that enables the analyses of massively parallel sequences of DNA can advance the understanding of the underlying molecular pathophysiologies of cancer. Such recent genomic analyses have revealed a complex mutational landscape in surgical specimens of PDAC. Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is used in the diagnosis of pancreatic cancer. Several genomic analyses using EUS-FNA in PDAC have been undertaken in a small number of patients. This study evaluated the feasibility of targeted NGS of specimens obtained using EUS-FNA to clarify genetic markers associated with the prognosis of pancreatic cancer. One hundred sixty six patients who underwent EUS-FNA with pathologically confirmed PDAC were included. Genomic DNA was extracted and quality control metrics of DNA analytes were measured. The specimens that passed a quality control test (N = 101, 61%) underwent NGS using a customized cancer panel (CancerSCAN) enriched in the exons of 83 genes. Clinical prognostic factors associated with survival in PDAC were age, performance status, CA 19-9 level, curative resection, chemotherapy, tumor mass size, tumor location, stage and metastasis site in univariate analysis (P = 0.020, &lt;0.001, 0.015, 0.022, &lt;0.001, &lt;0.001, 0.031, 0.024 and 0.028, respectively). Multivariate Cox proportional-hazards analysis revealed chemotherapy (P &lt; 0.001, hazard ratio (HR) = 5.7, 95% CI, 2.8 to 11.3) and tumor mass size (P = 0.001, HR = 0.4, 95% CI, 0.2 to 0.7) as independent prognostic factors. Each patient had different numbers of genetic alterations ranging from 0 to 17, and 99% of the patients had at least a single genetic alteration. KRAS mutation was found in 86 patients (86%); KRAS variant allele frequency ranged from 2 to 79%. The frequencies of major gene mutations responsible for PDACs were KRAS 86%, CDKN2A 22%, TP53 72%, SMAD4 25% and BRCA 14%. Genetic alterations associated with survival were ARID1A, AURKB1, CDK4, ERBB4, HNF1A, JAK3, MPL, PIK3R, PTCH1, STK11 and TOP1 in univariate analysis. In multivariate analysis, CDK4, HNF1A, MPL, PIK3R, PTCH1, STK11 and TOP1 mutations were independently associated with overall survival (P = 0.011, P = 0.001, P = 0.001, P = 0.005, P = 0.041, P = 0.050 and P = 0.003, respectively). KRAS gene (variant allele frequency 50%) and the EphB4 mutation were significantly associated with PDAC metastasis. ATRX and TERT genes were significantly associated with the pattern of metastasis in PDACs. ABL1 and BRAF mutations were significantly associated with stable disease as well as partial response to chemotherapy (P = 0.047 and P = 0.015, respectively). Targeted sequencing using EUS-FNA specimens in PDAC is feasible and shows similar genomic profiles in surgical specimens. Novel genes associated with survival, metastasis and chemotherapy response in PDAC were identified.

Citation Format: Joo Kyung Park, Kwang Hyuk Lee, Jong Kyun Lee, Kyu Taek Lee, Woong-Yang Park, Dae-Soon Son. Targeted sequencing from endoscopic ultrasound-guided fine needle aspirates of pancreatic ductal adenocarcinoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 96.

The minimal amount of starting DNA for Agilent's hybrid capture-based targeted massively parallel sequencing

Targeted capture massively parallel sequencing is increasingly being used in clinical settings, and as costs continue to decline, use of this technology may become routine in health care. However, a limited amount of tissue has often been a challenge in meeting quality requirements. To offer a practical guideline for the minimum amount of input DNA for targeted sequencing, we optimized and evaluated the performance of targeted sequencing depending on the input DNA amount. First, using various amounts of input DNA, we compared commercially available library construction kits and selected Agilent’s SureSelect-XT and KAPA Biosystems’ Hyper Prep kits as the kits most compatible with targeted deep sequencing using Agilent’s SureSelect custom capture. Then, we optimized the adapter ligation conditions of the Hyper Prep kit to improve library construction efficiency and adapted multiplexed hybrid selection to reduce the cost of sequencing. In this study, we systematically evaluated the performance of the optimized protocol depending on the amount of input DNA, ranging from 6.25 to 200 ng, suggesting the minimal input DNA amounts based on coverage depths required for specific applications.

Practical approach to determine sample size for building logistic prediction models using high-throughput data

An empirical method of sample size determination for building prediction models was proposed recently. Permutation method which is used in this procedure is a commonly used method to address the problem of overfitting during cross-validation while evaluating the performance of prediction models constructed from microarray data. But major drawback of such methods which include bootstrapping and full permutations is prohibitively high cost of computation required for calculating the sample size. In this paper, we propose that a single representative null distribution can be used instead of a full permutation by using both simulated and real data sets. During simulation, we have used a dataset with zero effect size and confirmed that the empirical type I error approaches to 0.05. Hence this method can be confidently applied to reduce overfitting problem during cross-validation. We have observed that pilot data set generated by random sampling from real data could be successfully used for sample size determination. We present our results using an experiment that was repeated for 300 times while producing results comparable to that of full permutation method. Since we eliminate full permutation, sample size estimation time is not a function of pilot data size. In our experiment we have observed that this process takes around 30min. With the increasing number of clinical studies, developing efficient sample size determination methods for building prediction models is critical. But empirical methods using bootstrap and permutation usually involve high computing costs. In this study, we propose a method that can reduce required computing time drastically by using representative null distribution of permutations. We use data from pilot experiments to apply this method for designing clinical studies efficiently for high throughput data.

Prediction of a time-to-event trait using genome wide SNP data

Background

A popular objective of many high-throughput genome projects is to discover various genomic markers associated with traits and develop statistical models to predict traits of future patients based on marker values.

Results

In this paper, we present a prediction method for time-to-event traits using genome-wide single-nucleotide polymorphisms (SNPs). We also propose a MaxTest associating between a time-to-event trait and a SNP accounting for its possible genetic models. The proposed MaxTest can help screen out nonprognostic SNPs and identify genetic models of prognostic SNPs. The performance of the proposed method is evaluated through simulations.

Conclusions

In conjunction with the MaxTest, the proposed method provides more parsimonious prediction models but includes more prognostic SNPs than some naive prediction methods. The proposed method is demonstrated with real GWAS data.

Selecting SNPs for pharmacogenomic association study

SNP genotyping device is an essential tool in the upcoming era ofpersonal genome and personalised medicine. Human genome has more than 10 million SNPs whereas conventional SNP genotyping device can only hold 1 million SNPs. Thus, intelligent SNP contents selection is required to maximise the value of SNP genotyping device. Here, we developed a new selection algorithm and applied this method to design genotyping contents for cancerand pharmacogenomic association study. This approach significantly increased the product value when compared with contents of competitive SNP genotyping product.

Predicting recurrence using the clinical factors of patients with non-small cell lung cancer after curative resection

We present a recurrence prediction model using multiple clinical parameters in patients surgically treated for non-small cell lung cancer. Among 1,578 lung cancer patients who underwent complete resection, we compared the early-recurrence group with the 3-yr non-recurrence group for evaluating those factors that influence early recurrence within one year after surgery. Adenocarcinoma and squamous cell carcinoma were analyzed independently. We used multiple logistic regression analysis to identify the independent clinical predictors of recurrence and Cox's proportional hazard regression method to develop a clinical prediction model. We randomly divided our patients into the training and test subsets. The pathologic stages, tumor cell type, differentiation of tumor, neoadjuvant therapy and age were significant factors on the multivariable analysis. We constructed the model for the training set with adenocarcinoma (n=236) and squamous cell carcinoma (n=305), and we applied it to the test set with adenocarcinoma (n=110) and squamous cell carcinoma (n=154). It was predictive for the in adenocarcinoma (P<0.001) and the squamous cell carcinoma (P=0.037), respectively. Our results showed that our recurrence prediction model based on the clinical parameters could significantly predict the individual patients who were at high risk or low risk for recurrence.

Prediction of recurrence-free survival in postoperative non-small cell lung cancer patients by using an integrated model of clinical information and gene expression

PURPOSE

One of the main challenges of lung cancer research is identifying patients at high risk for recurrence after surgical resection. Simple, accurate, and reproducible methods of evaluating individual risks of recurrence are needed.

EXPERIMENTAL DESIGN

Based on a combined analysis of time-to-recurrence data, censoring information, and microarray data from a set of 138 patients, we selected statistically significant genes thought to be predictive of disease recurrence. The number of genes was further reduced by eliminating those whose expression levels were not reproducible by real-time quantitative PCR. Within these variables, a recurrence prediction model was constructed using Cox proportional hazard regression and validated via two independent cohorts (n = 56 and n = 59).

RESULTS

After performing a log-rank test of the microarray data and successively selecting genes based on real-time quantitative PCR analysis, the most significant 18 genes had P values of <0.05. After subsequent stepwise variable selection based on gene expression information and clinical variables, the recurrence prediction model consisted of six genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, and IFI44). Two pathologic variables, pStage and cellular differentiation, were developed. Validation by two independent cohorts confirmed that the proposed model is significantly accurate (P = 0.0314 and 0.0305, respectively). The predicted median recurrence-free survival times for each patient correlated well with the actual data.

CONCLUSIONS

We have developed an accurate, technically simple, and reproducible method for predicting individual recurrence risks. This model would potentially be useful in developing customized strategies for managing lung cancer.

Gene expression profiling for the prediction of lymph node metastasis in patients with cervical cancer

We investigated whether gene expression profiling of primary cervical tumor tissue could be used to predict lymph node (LN) metastasis and compared this with conventional magnetic resonance imaging. We obtained 43 primary cervical cancer samples (16 with LN metastasis and 27 without LN metastasis) for microarray analysis. A prediction model for LN metastasis from the training set was developed by support vector machine methods using a 10-fold cross-validation. The 'LN prediction model' derived from the signature of 156 distinctive genes (P < 0.01) had a prediction accuracy of 77%. Correlation between mRNA expressions measured by microarray and semiquantitative reverse transcription-polymerase chain reaction was ascertained in four (RBM8A, SDHB, SERPINB13, and gamma-interferon) out of 10 genes. Magnetic resonance imaging showed accuracy (69%) for the prediction of LN metastasis. These results suggest that gene expression profiling allows reliable prediction of LN metastasis in cervical cancer.

Clinical validity of the lung cancer biomarkers identified by bioinformatics analysis of public expression data

Identification of molecular markers often leads to important clinical applications such as early diagnosis, prognosis, and drug targeting. Lung cancer, the leading cause of cancer-related deaths, still lacks reliable molecular markers. We have combined the bioinformatics analysis of the public gene expression data and clinical validation to identify biomarker genes for non-small-cell lung cancer. The serial analysis of gene expression and the expressed sequence tag data were meta-analyzed to produce a list of the differentially expressed genes in lung cancer. Through careful inspection of the predicted genes, we selected 20 genes for experimental validation using semiquantitative reverse transcriptase-PCR. The microdissected clinical specimens used in the study consisted of three groups: lung tissues from benign diseases and the paired (cancer and pathologic normal) tissues from non-small-cell lung cancer patients. After extensive statistical analyses, seven genes (CBLC, CYP24A1, ALDH3A1, AKR1B10, S100P, PLUNC, and LOC147166) were identified as potential diagnostic markers. Quantitative real-time PCR was carried out to additionally assess the value of the seven identified genes leading to the confirmation of at least two genes (CBLC and CYP24A1) as highly probable novel biomarkers. The gene properties of the identified markers, especially their relationship to lung cancer and cell signaling pathway regulation, further suggest their potential value as drug targets as well.

Elevated activities of MMP-2 in the non-tumorous lung tissues of curatively resected stage I NSCLC patients are associated with tumor recurrence and a poor survival

BACKGROUND AND OBJECTIVES

We wanted to assess whether the level of enzyme activity for a particular matrix metalloproteinase (MMP), and not the amount of expressed protein, in lung tissue could be used as a reliable prognostic biomarker for tumor recurrence leading to poorer survival in a certain subgroup of patients who have undergone curative resection for stage I human NSCLC.

METHODS

We determined what type of MMP was significant for tumor recurrence by using a mouse model of pulmonary metastasis with inoculating the footpad with H460 human cancer cells. We then looked for any association between tumor recurrence and the level of enzyme activities for the selected MMP in the tumor and also in the pathologically non-tumorous tissues from 34 stage I lung cancer patients.

RESULTS

We obtained H460/PM6 cells having a highly metastatic potential after six repeated cycles of pulmonary metastasis by using the mouse footpad inoculated with the metastasized cancer cells in the previous cycle. We started with human lung cancer cells, H460, and we found that among the tested MMPs we tested for, the level of MMP-2 mRNA was elevated. No significant difference was seen in the level of enzyme activity of the MMP-2 cells from the curatively resected tumor tissues of the stage I NSCLC patients who were later found with or without recurrence. However, the level of MMP-2 enzyme activity was found to be significantly different between the non-tumorous lung tissues from patients later found with and without recurrence, and it was associated with the 5-year survival rate.

CONCLUSIONS

This observation suggests that the higher level of MMP-2 enzyme activity in the non-tumorous tissues from the patients could be used as a prognostic biomarker to predict post-operative tumor recurrence and survival for patients with stage I NSCLC. The elevated enzyme activity of MMP-2 in the non-tumorous tissue resected from stage I NSCLC could be used as a prognostic indicator for post-operative tumor recurrence and the patients' poor survival. Further, this could be an important aid for physicians' making decision on whether to subject particular patients to post-operative adjunct chemotherapy.

The signature from messenger RNA expression profiling can predict lymph node metastasis with high accuracy for non-small cell lung cancer

BACKGROUND

The extent of regional lymph node (LN) metastasis is the most important factor in the evaluation of resectability and prognosis of non-small cell lung cancer (NSCLC) to increase the chance of complete cure. The authors attempted to deduce a group of genes from the analysis of mRNA expression profiles of the tumor tissues of NSCLC patients with or without LN metastasis, and make a classification model for better prediction of LN metastasis.

METHODS

The authors analyzed mRNA expression profiles of 79 NSCLC patients with or without LN metastasis, and deduced the gene signature for the predictive model of LN metastasis in lung cancer. The authors evaluated the predictive accuracy of each of four algorithms by applying them to another set of 33 NSCLC patients. Each algorithm's accuracy was calculated by 10-fold cross-validation, and a combined model showed a level of accuracy that was higher than any one of the better three component algorithms (i.e., ANN, DT, or NB). Avadis, SAS, ArrayXPath, and R-package were the statistical analysis software packages used.

RESULTS

The authors selected 949 genes using a classical permutation t test (p < 0.01) and finally obtained a gene signature consisting of 31 genes by adjustment of multiple-hypothesis testing. The LN metastasis prediction model derived from the signature (31 genes) and their characteristic interactions provided a predictive accuracy of 84.85% when applied to a test set of 33 patients.

CONCLUSIONS

The authors have demonstrated that their gene signature developed by the expression profiling of mRNAs from the primary tissue could predict the LN metastasis status of NSCLC.

Effects of teat number on litter size in gilts

This study was carried out to investigate the effects of teat number and interval at first estrus and mating on litter size in Duroc, Landrace and Yorkshire gilts. Gilt body weight at first estrus was from 101.5 kg to 115.3 kg and gilts normally attained puberty at 170.5-181.5 days of age. Breed differences among Duroc, Landrace and Yorkshire in body weight and age at first estrus and mating were found. Total teat number of Duroc, Landrace and Yorkshire were 12.5, 14.9 and 13.7, respectively. Teat interval from pectoral to inguinal region and from left to right at first estrus and mating did not show any differences among the breeds. In conclusion, 14 or more teat number compared to 11-13 teat number in gilts increased litter size at birth and at 21 day weaning.

RASSF1A is not appropriate as an early detection marker or a prognostic marker for non‐small cell lung cancer

Aberrant methylation of several tumor suppressor genes often occurs during the pathogenesis of lung cancer. RASSF1A is one of the tumor suppressor genes, and it is frequently inactivated by hypermethylation of its promoter region in a variety of human cancers, including lung cancer. It has recently been suggested that RASSF1A methylation was frequently observed in poorly differentiated tumors, and that it was correlated with adverse survival in lung adenocarcinoma (Tomizawa Y, et al., Clin Cancer Res 2002;8:2362-8). In this study, we investigated the pathogenetic and clinicopathologic significance of RASSF1A methylation for the development and/or progression of non small cell lung cancer (NSCLC). We examined 116 cases of NSCLC for the methylation status of RASSF1A. Methylation-specific analysis demonstrated that 40.5% (47 of 116) of the cases were methylated at the CpG sites in the promoter. Methylation of RASSF1A was associated with cellular differentiation (p = 0.0244) and it was related to survival (p = 0.0276). However, there was no association between RASSF1A methylation and the individual clinicopathologic features: TNM stage (p > 0.1), recurrence (p > 0.1), lymphatic permeation (p > 0.1) and smoking duration time (p > 0.1). Furthermore, we analyzed RASSF1A's probability as a prognostic marker by using stepwise Cox proportional hazard regression testing. As a result, the stage proved to be the most important factor (p = 0.0089), more than any other factors such as age, gender, cell type, methylation status, differentiation, smoking duration time, tumor size and lymph node permeation. There was no other significant factor other than stage and age. These results show that epigenetic inactivation of RASSF1A cannot be a prognostic marker of NSCLC.

Effects of altered plasma alpha-1-acid glycoprotein levels on pharmacokinetics of some basic antibiotics in pigs: simulation analysis

Effects of altered plasma alpha-1-acid glycoprotein (AGP) levels on pharmacokinetic parameters of basic antimicrobials, erythromycin (EM), lincomycin (LM) and clindamycin (CM) were evaluated in pigs by simulation analysis. Intravenous (i.v.) injections of EM, LM and CM were performed to obtain pharmacokinetic parameters in healthy conditions. Binding parameters were obtained from an in vitro study using ultrafiltration. Simulation studies indicated that an increase of plasma AGP levels resulted in a decrease of both volume of distribution at steady state (Vdss) and total body clearance (Cltot) for all the drugs. Elimination rate constant for LM was almost unchanged by an increase of plasma AGP levels, whereas those for EM and CM were increased. Plasma concentration-time profiles at a high AGP level (often observed in pathophysiological conditions) were also simulated. All of the total plasma concentration-time profiles were different from those at normal AGP level. The differences were characterized by a higher initial concentration with faster or similar elimination. Unbound plasma concentration-time profile of LM was unaffected by AGP levels, whereas EM and CM were eliminated from plasma more rapidly at high AGP level. These results suggested that adjustment of dosage regimen of EM and CM is required in pathophysiological conditions, but that of LM is not required.

Effect of dominant follicle removal before superstimulation on follicular growth, ovulation and embryo production in Holstein cows

This study was to investigate whether removing the dominant follicle 48 h before superstimulation influences follicular growth, ovulation and embryo production in Holstein cows. After synchronization, ovaries were scanned to assess the presence of a dominant follicle by ultrasonography with a real-time linear scanning ultrasound system on Days 4, 6 and 8 of the estrus cycle (Day 0 = day of estrus). Twenty-six Holstein cows with a dominant follicle were divided into 2 groups in which the dominant follicle was either removed (DFR group, n=13) by ultrasound-guided follicular aspiration or left intact (control group, n=13) on Day 8 of the estrus cycle. Superovulation treatment was initiated on Day 10. All donors were superovulated with injections of porcine FSH (Folltropin) twice daily with constant doses (total: 400 mg) over 4 d. On the 6th and 7th injections of Folltropin, 30 mg and 15 mg of PGF2alpha (Lutalyse) were given. Donors were inseminated twice at 12 h and 24 h after the onset of estrus. Embryos were recovered on Day 6 or 7 after AI. During superstimulation, the number of follicles 2 to 5 mm (small), 6 to 9 mm (medium) and > or = 10 mm (large) was determined by ultrasonography on a daily basis. At embryo recovery, the number of corpora lutea (CL) was also determined by ultrasonography and blood samples were collected for analysis of progesterone concentration. Follicular growth during superstimulation was earlier in the DFR group than in the control group. The number of medium and large follicles was greater (P < 0.01) in the DFR group than in the control group on Days 1 to 2 and Days 3 to 4 of superstimulation, respectively. The numbers of CL (9.6+/-1.1 vs 6.1+/-0.9) and progesterone concentration (30.9+/-5.4 vs 18.6+/-3.5 ng/mL) were greater (P < 0.05) in the DFR group than in the control group, respectively. The numbers of total ova (7.7+/-1.3 vs 3.9+/-1.0) and transferable embryos (4.6+/-0.9 vs 2.3+/-0.8) were also greater (P < 0.05) in the DFR group than in the control group, respectively. It is concluded that the removal of the dominant follicle 48 h before superstimulation promoted follicular growth, and increased ovulation and embryo production in Holstein cows.

In vitro development of reconstructed porcine oocytes after somatic cell nuclear transfer

This study was designed to examine the developmental ability of porcine embryos after somatic cell nuclear transfer. Porcine fibroblasts were isolated from fetuses at Day 40 of gestation. In vitro-matured porcine oocytes were enucleated and electrically fused with somatic cells. The reconstructed eggs were activated using electrical stimulus and cultured in vitro for 6 days. Nuclear-transferred (NT) embryos activated at a field strength of 120 V/mm (11.6 +/- 1.6%) showed a higher developmental rate as compared to the 150-V/mm group (6.5 +/- 2.3%) (P: < 0.05), but the mean cell numbers of blastocysts were similar between the two groups. Rates of blastocyst development from NT embryos electrically pulsed at different times (2, 4, and 6 h) after electrofusion were 11.6 +/- 2.9, 6.6 +/- 2.3, and 8.1 +/- 3.3%, respectively. The mean cell numbers of blastocysts developed from NT embryos were gradually decreased (30.4 +/- 10.4 > 24.6 +/- 10.1 > 16.5 +/- 7.4 per blastocyst) as exposure time (2, 4, and 6 h) of nuclei to oocyte cytoplast before activation was prolonged. There was a significant difference in the cell number between the 2- and 6-h groups (P: < 0. 05). Nuclear-transferred embryos (9.4 +/- 0.9%) had a lower developmental rate than in vitro fertilization (IVF)-derived (21.4 +/- 1.9%) or parthenogenetic embryos (22.4 +/- 7.2%) (P: < 0.01). The mean cell number (28.9 +/- 11.4) of NT-derived blastocysts was smaller than that (38.6 +/- 10.4) of IVF-derived blastocysts (P: < 0. 05) and was similar to that (29.9 +/- 12.1) of parthenogenetic embryos. Our results suggest that porcine NT eggs using somatic cells after electrical activation have developmental potential to the blastocyst stage, although with smaller cell numbers compared to IVF embryos.

Non-linear pharmacokinetics of ofloxacin after a single intravenous bolus dose in pigs

The pharmacokinetics of ofloxacin (OFLX) was investigated after intravenous administration of 3, 10 and 30 mg/kg of body weight in pigs. Plasma OFLX concentration-time course collected from the highest dosage showed a convex decline, indicating a capacity-limited process in drug elimination (Michaelis-Menten elimination). Dose-normalized area under curve (AUC/Dose) and mean resident time (MRT) were dose-dependent, indicating a classical pattern of non-linear elimination pharmacokinetics. Based on simultaneous curve fitting from three doses, non-linear pharmacokinetic parameters were as follows: 0.87 mg/h/kg for maximum velocity, 2.20 microg/mL in Michaelis-Menten constant and 2.06 L/kg for apparent volume of distribution. Based on a model-independent analysis, the apparent volume of distribution at steady-state (Vdss) was dose-independent whereas total body clearance (CLtot) was dose-dependent, mainly contributed by renal clearance (CLr) with the regression line of CLtot=1.14xCLr+0.09 (r=0.92). The intercept of the regression line indicates non-renal clearance (CLnr), corresponding to the value of observed CLnr without dose-dependency. Because of a higher CLr compared with glomerular filtration rate (GFR) in spite of drug reabsorption, the CLr must contain the renal active tubular secretion. With increasing dosage, the level of saturation of tubular secretion of OFLX decreased the CLr, resulting in the decrease in CLtot. The plasma protein binding to OFLX was dose-independent: mean free fraction (fp)=0.73, with probably no influential effect on OFLX disposition. In conclusion, the degree of saturation in the renal active tubular secretion of OFLX could be a major causal factor in the alteration of CLr in an increasing dosage of OFLX. Accordingly, the alteration of CLr could directly induce the non-linear pharmacokinetics of OFLX in pigs, an important consideration in clinical therapeutics.

Alterations of events related to ovarian function in tumor necrosis factor receptor type I knockout mice

C57BL6 mice with targeted disruption of tumor necrosis factor (TNF) type 1 receptor (TNFRI) exhibited early vaginal opening when compared with wild-type mice (Day 24 +/- 0.6, n = 10, vs. 28 +/- 0.2, n = 11, P < 0.001). Equine CG- and hCG-treated TNFRI null mice ovulated more ova than did controls at two distinct times during the prepubertal period (Day 21: 13.4 +/- 1.7 vs. 7.3 +/- 1.4, P < 0.05; Day 25: 20.7 +/- 2.7 vs. 13.0 +/- 1.3, P < 0.05). Enhanced responsiveness to gonadotropins was not observed in adult mice. At 6 mo of age only 40% of TNFRI null mice exhibited estrous cycles. Those TNFRI null mice with estrous cycles spent significantly more time in diestrus and less time in estrus than controls. TNFRI null mice delivered significantly fewer litters (P < 0.001) than did C57BL6 and TNFRII null mice (TNFRI null 2.59 +/- 0.39; C57BL6 4.91 +/- 0.57; TNFRII null 5.40 +/- 0.60 litters/mo/10 pairs over a 12-mo period). Ovarian dispersates prepared on Day 25 of age from control and TNFRI knockout mice were cultured with and without 10 ng TNF/ml. TNF inhibited LH-stimulated progesterone and estradiol secretion by control dispersates but had no effect on cAMP. In contrast, TNF did not affect LH-stimulated accumulation of progesterone, estradiol, or cAMP by ovarian dispersates from TNFRI knockout mice. The results indicate that lack of TNFRI enhances ovarian responsiveness to gonadotropins during the prepubertal period and may be related to early vaginal opening. The lack of TNFRI is associated with early senescence and poor fertility. These studies demonstrate that the mechanism of TNF-mediated inhibition of steroidogenesis is most likely via TNFRI.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) blocks ovulation by a direct action on the ovary without alteration of ovarian steroidogenesis: lack of a direct effect on ovarian granulosa and thecal-interstitial cell steroidogenesis in vitro

The main purpose of this study was to investigate the direct effect of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on ovarian function including ovulation and steroidogenesis. In vivo effects of TCDD were investigated on ovulation and alteration of circulating and ovarian steroid hormones in immature hypophysectomized rats (IHR) primed with equine chorionic gonadotropin (eCG) and human chorionic gonadotropin (hCG). In addition, in vitro effects of TCDD on the steroidogenesis of granulosa cells (GC), theca-interstitial cells (TIC), and whole ovarian dispersates derived from the ovary of IHR were investigated. In the ovulation model, rats were hypophysectomized on Day 23 of age. On Day 26, the IHR were given 20 microg TCDD/kg by gavage. The next day eCG (10 IU) was injected sc to stimulate follicular development. Fifty-two hours after eCG, 10 IU hCG was given to induce ovulation. TCDD (20 microg/kg) blocked ovulation and reduced ovarian weight in IHR. Concentrations of progesterone (P4), androstenedione (A4), and estradiol (E2) in sera and ovaries were not altered by TCDD at 12, 24, 48, and 72 h after eCG. except for a two-fold increase in ovarian concentration of A4 at 48 h after TCDD. However, this higher concentration of A4 at 48 h after TCDD did not reflect that of A4 in sera and did not correlate with E2 in either sera or ovaries. In isolated GC from untreated IHR, TCDD (0.1 to 100 nM) had no significant effect on P4 and E2 after stimulation by LH or FSH. In TIC and whole ovarian dispersates containing GC, TIC, and other ovarian cells, TCDD (0.1 to 800 nM) had no effect on A4 and P4 secretion stimulated by LH. Using RT-PCR, AhR mRNA was shown to be expressed constitutively in the whole ovary of IHR with maximum down-regulation at 6 h after TCDD (20 microg/kg). Ovarian CYP1A1 was induced maximally at 6 h after TCDD, whereas CYP1B1 could not be detected. The induction of AhR related genes by TCDD in the ovary implies the existence of AhR-mediated signal transduction pathways. In summary, these results indicate that TCDD does not affect ovulation in IHR by altering ovarian steroidogenesis. It seems that inhibition of ovulation by TCDD is due to processes related to follicular rupture.

Toxic equivalency factors of polychlorinated dibenzo-p-dioxins in an ovulation model: validation of the toxic equivalency concept for one aspect of endocrine disruption

Polychlorinated dibenzo-p-dioxins (PCDDs) are structural analogues, which produce a similar spectrum of biological and toxicological responses in animals, albeit with differential potencies. Very consistent structure-activity relationships have been found for acute toxicity and some biochemical effects among these compounds. For the current experiments, the gonadotropin-primed immature female rat model was used to study the effect of 2,3,7, 8-tetrachlorodibenzo-p-dioxin (TCDD), 1,2,3,7, 8-pentachlorodibenzo-p-dioxin (PeCDD), and 1,2,3,4,7, 8-hexachlorodibenzo-p-dioxin (HxCDD) on ovulation. Single doses of different PCDDs and their mixture were given orally to 23-day-old rats. Gonadotropin from pregnant mare's serum (PMSG) was injected (5 IU) 24 h later to induce follicular maturation. Rats were decapitated at various times after PMSG, blood was collected, and ovarian weight was measured. Serum concentrations of 17beta-estradiol (E2), progesterone (P4), luteinizing hormone (LH), follicle stimulating hormone (FSH), and prolactin (PrL) were determined by radioimmunoassay. Ovulation was measured at 72 h after injection of PMSG by counting ova flushed from oviducts. PCDDs dose dependently decreased the number of ova per ovary and reduced ovarian weight gain induced by PMSG. The slopes of the dose-response curves generated by individual PCDDs and/or their mixture were similar. PMSG-induced increase in serum E2 was enhanced on the day of expected ovulation by PCDDs; in contrast, serum P4 and FSH were decreased at that same time point. PCDDs also altered the temporal pattern of serum E2, FSH, and LH but not that of PrL. Histologically the effect of all three PCDDs consisted of ova trapped in preovulatory follicles and a lack of or reduced number of corpora lutea. The results indicate that the PCDDs, tested in the present model, have the same mode of action on ovulation and the reproductive hormones, e.g., LH, FSH, P4 and E2. Furthermore, the dose responses of the individual congeners are parallel to each other and also to that of their equipotent mixture, which represent a validation of the TEQ concept for one aspect of endocrine disruption, that is for inhibition of ovulation.

Bacteria in semen used for IVF affect embryo viability but can be removed by stripping cumulus cells by vortexing

Bacterial contamination of in vitro vs in vivo produced embryos presents a particular danger because of the alteration of the zona pellucida and the use of various biological products during culture. Our objective was to investigate the effects of semen contaminated with bacteria on IVF of bovine oocytes and to determine if removal of cumulus cells by vortexing as opposed to pipetting would reduce contamination and improve subsequent embryonic development. Semen from 5 bulls of the Native Korean breed (Bulls A, B, C, D, E) was used for IVF of matured oocytes. Preliminary studies had shown that the semen from Bulls A, B, D and E but not Bull C was contaminated with various species of common bacteria. After IVF, the cumulus cells surrounding the oocytes were removed either by pipetting or vortexing. Viability and cleavage rates of the resulting zygotes was assessed after 44 h in culture. When cumulus cells were removed by pipetting, only zygotes derived from oocytes that were fertilized with uncontaminated semen from Bull C developed to morula and blastocyst stages; zygotes derived from oocytes that were fertilized with contaminated semen from Bulls A, B, D and E started to degenerate, and the culture media became noticeably turbid. When cumulus cells were removed by vortexing, zygotes derived from oocytes fertilized with either contaminated or uncontaminated semen showed good rates of development (16 to 32%) to morula or blastocyst stages. From these results it can be concluded that the bacteria introduced with the semen contaminated the in vitro system and severely reduced the viability of the embryos. In contrast, complete removal of the cumulus cells with vortexing, as opposed to pipetting, reduced the contamination of the culture medium, allowing embryonic development to take place.

Contribution of alpha 1-acid glycoprotein to species difference in lincosamides-plasma protein binding kinetics

Protein binding kinetics of lincomycin (LM) and clindamycin (CM) were studied using plasma, albumin and alpha 1-acid glycoprotein (AGP) derived from humans, dogs, cattle and sheep. Based on Rosenthal plots of LM and CM, drug-binding property in plasma presented specific and non-specific binding, except for LM in cattle and sheep and for CM in sheep, where only non-specific binding was demonstrated. Dissociation constant (Kd) and binding capacity (Bmax) for specific binding and proportionality constant (PC) for non-specific binding were as follows: Kd = 3.14 mumol/L, Bmax = 15.28 mumol/L, PC = 0.19 for humans; Kd = 3.84 mumol/L, Bmax = 6.55 mumol/L, PC = 0.14 for dogs; PC = 0.12 for cattle; PC = 0.16 for sheep in LM and Kd = 0.94 mumol/L, Bmax = 12.24 mumol/L, PC = 4.98 for humans; Kd = 1.48 mumol/L, Bmax = 9.52 mumol/L, PC = 2.91 for dogs; Kd = 1.22 mumol/L, Bmax = 4.45 mumol/L, PC = 2.40 for cattle; PC = 1.48 for sheep in CM. The specific binding for each species was different, showing more difference in Bmax compared with Kd. The non-specific binding of LM was similar among species whereas that of CM was different, implying species difference. The drug-binding property of AGP for each species was all specific binding and the Kd was comparable to that obtained from plasma, indicating that AGP is a major specific binder in plasma. The lack of detection of specific binding for LM in cattle and sheep and for CM in sheep plasma could be attributable to a higher Kd and lower plasma AGP concentration compared with other species. The drug-binding property of albumin was characterized as all non-specific, without a great difference among species. Except for CM in sheep, the lower PC in albumin solution compared with that in plasma suggested the presence of another non-specific binder in plasma, i.e. lipoprotein. From the simulation of drug-binding percentage to AGP concentrations, AGP could be a major contributor to drug-plasma protein binding in pathological states. The degree of AGP-drug binding for each species could vary according to the degree of increase of AGP concentrations from a healthy to a pathological state, inducing a decrease in the unbound fraction (fp): 6.1 fold for dogs, 4.6 fold for humans, 1.8 fold for sheep and 1.4 fold for cattle in LM; 5.8 fold for dogs, 5.7 fold for cattle, 4.0 fold for humans and 1.5 fold for sheep in CM. Therefore, the disposition and efficacy of lincosamides affected by fp can be modified differently by the change of fp attributable to the alteration of plasma AGP concentration in each species.

Deacetylation as a determinant of sulphonamide pharmacokinetics in pigs

Sulphamonomethoxine (SMM), sulphadimidine (SDD), sulphadiazine (SDZ) and their N4-acetyl derivatives (AcSMM, AcSDD and AcSDZ) were intravenously injected into Goettingen miniature pigs and deacetylation was evaluated from plasma concentration-time curves, renal excretion, and rate constants obtained from pharmacokinetic analysis, using a non-linear least-squares method. Deacetylated metabolite was detected in both plasma and urine after intravenous injection of AcSMM, AcSDD and AcSDZ. The area under the curve (AUC) values for the deacetylated metabolite were significantly higher than those for acetyl derivatives after AcSMM and AcSDD administration, but significantly lower after AcSDZ. After AcSMM and AcSDD injection, the concentration ratio between deacetylated metabolite and acetyl derivative was almost constant in the terminal linear phase and similar to that seen after injection of sulphonamide. After AcSDZ injection, however, a constant ratio was not observed. These results indicate that deacetylation can have a significant effect on the pharmacokinetics of SMM and SDD, but not on those of SDZ in pigs. The rate constant for deacetylation was significantly higher than that for acetylation for SMM and SDD, but significantly lower for SDZ. It is, therefore, concluded that deacetylation may be a determinant of the pharmacokinetics of SMM and SDD in pigs. It was, however, not a determinant of SDZ pharmacokinetics because N4-acetylation is not the main elimination route in pigs.