Noninvasive prediction of axillary lymph node status in breast cancer using promoter profiling of circulating cell-free DNA.

BACKGROUND: Lymph node metastasis (LNM) is one of the most important factors affecting the prognosis of breast cancer. The accurate evaluation of lymph node status is useful to predict the outcomes of patients and guide the choice of cancer treatment. However, there is still lack of a low-cost non-invasive method to assess the status of axillary lymph node (ALN). Gene expression signature has been used to assess lymph node metastasis status of breast cancer. In addition, nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of its original tissues, so it may be used to evaluate the axillary lymph node status in breast cancer. METHODS: In this study, we found that the cfDNA nucleosome footprints between the ALN-positive patients and ALN-negative patients showed different patterns by implementing whole-genome sequencing (WGS) to detect 15 ALN-positive and 15 ALN-negative patients. In order to further evaluate its potential for assessing ALN status, we developed a classifier with multiple machine learning models by using 330 WGS data of cfDNA from 162 ALN-positive and 168 ALN-negative samples to distinguish these two types of patients. RESULTS: We found that the promoter profiling between the ALN-positive patients and ALN-negative patients showed distinct patterns. In addition, we observed 1071 genes with differential promoter coverage and their functions were closely related to tumorigenesis. We found that the predictive classifier based on promoter profiling with a support vector machine model, named PPCNM, produced the largest area under the curve of 0.897 (95% confidence interval 0.86-0.93). CONCLUSIONS: These results indicate that promoter profiling can be used to distinguish ALN-positive patients from ALN-negative patients, which may be helpful to guide the choice of cancer treatment.

A Genotype Signature for Predicting Pathologic Complete Response in Locally Advanced Rectal Cancer.

PURPOSE: To construct and validate a predicting genotype signature for pathologic complete response (pCR) in locally advanced rectal cancer (PGS-LARC) after neoadjuvant chemoradiation. METHODS AND MATERIALS: Whole exome sequencing was performed in 15 LARC tissues. Mutation sites were selected according to the whole exome sequencing data and literature. Target sequencing was performed in a training cohort (n = 202) to build the PGS-LARC model using regression analysis, and internal (n = 76) and external validation cohorts (n = 69) were used for validating the results. Predictive performance of the PGS-LARC model was compared with clinical factors and between subgroups. The PGS-LARC model comprised 15 genes. RESULTS: The area under the curve (AUC) of the PGS model in the training, internal, and external validation cohorts was 0.776 (0.697-0.849), 0.760 (0.644-0.867), and 0.812 (0.690-0.915), respectively, and demonstrated higher AUC, accuracy, sensitivity, and specificity than cT stage, cN stage, carcinoembryonic antigen level, and CA19-9 level for pCR prediction. The predictive performance of the model was superior to clinical factors in all subgroups. For patients with clinical complete response (cCR), the positive prediction value was 94.7%. CONCLUSIONS: The PGS-LARC is a reliable predictive tool for pCR in patients with LARC and might be helpful to enable nonoperative management strategy in those patients who refuse surgery. It has the potential to guide treatment decisions for patients with different probability of tumor regression after neoadjuvant therapy, especially when combining cCR criteria and PGS-LARC.

Noninvasive inferring expressed genes and in vivo monitoring of the physiology and pathology of pregnancy using cell-free DNA.

BACKGROUND: Noninvasive monitoring of fetal development and the early detection of pregnancy-associated complications is challenging, largely because of the lack of information about the molecular spectrum during pregnancy. Recently, cell-free DNA in plasma was found to reflect the global nucleosome footprint and status of gene expression and showed potential for noninvasive health monitoring during pregnancy. OBJECTIVE: We aimed to test the relationships between plasma cell-free DNA profiles and pregnancy biology and evaluate the use of a cell-free DNA profile as a noninvasive method for physiological and pathologic status monitoring during pregnancy. STUDY DESIGN: We used genome cell-free DNA sequencing data generated from noninvasive prenatal testing in a total of 2937 pregnant women. For each physiological and pathologic condition, features of the cell-free DNA profile were identified using the discovery cohort, and support vector machine classifiers were built and evaluated using independent training and validation cohorts. RESULTS: We established nucleosome occupancy profiles at transcription start sites in different gestational trimesters, demonstrated the relationships between gene expression and cell-free DNA coverage at transcription start sites, and showed that the cell-free DNA profiles at transcription start sites represented the biological processes of pregnancy. In addition, using cell-free DNA data, nucleosome profiles of transcription factor binding sites were identified to reflect the transcription factor footprint, which may help to reveal the molecular mechanisms underlying pregnancy. Finally, by using machine-learning models on low-coverage noninvasive prenatal testing data, we evaluated the use of cell-free DNA nucleosome profiles for distinguishing gestational trimesters, fetal sex, and fetal trisomy 21 and highlighted its potential utility for predicting physiological and pathologic fetal conditions by using low-coverage noninvasive prenatal testing data. CONCLUSION: Our analyses profiled nucleosome footprints and regulatory networks during pregnancy and established a noninvasive proof-of-principle methodology for health monitoring during pregnancy.

Identification of SARS-CoV-2 Variants and Their Clinical Significance in Hefei, China.

The ongoing coronavirus disease 2019 (COVID-19) pandemic represents one of the most exigent threats of our lifetime to global public health and economy. As part of the pandemic, from January 10 to March 10, 2020, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) began to spread in Hefei (Anhui Province, China) with a total of 174 confirmed cases of COVID-19. During this period, we were able to gather critical information on the transmission and evolution of pathogens through genomic surveillance. Particularly, the objective of our study was to track putative variants of SARS-CoV-2 circulating in Hefei for the first time and contribute to the global effort toward elucidating the molecular epidemic profile of the virus. Patients who showed symptoms of COVID-19 were routinely tested for SARS-CoV-2 infections via RT-PCR at the First Affiliated Hospital of Anhui Medical University. Whole-genome sequencing was performed on 97 clinical samples collected from 29 confirmed COVID-19 patients. As a result, we identified a local novel single-nucleotide polymorphism site (10,380) harboring a G → T mutation (Gly → Val) in Hefei. Further phylogenetic network analysis with all the sequences of SARS-CoV-2 deposited in GenBank collected in East and Southeast Asia revealed a local subtype of S-type SARS-CoV-2 (a1) harboring a C → T synonymous mutation (Leu) at position 18,060 of ORF1b, likely representing a local SARS-CoV-2 mutation site that is obviously concentrated in Hefei and the Yangtze River Delta region. Moreover, clinical investigation on the inflammatory cytokine profile of the patients suggested that mutations at positions 18,060 (the shared variable site of subtype a1) and 28,253(harboring a C → T synonymous mutation, Phe) were associated with milder immune responses in the patients.

Detection of chromosomal abnormalities in spontaneous miscarriage by low­coverage next­generation sequencing.

Chromosomal abnormalities (CAs) can cause spontaneous miscarriage and increase the incidence of subsequent pregnancy loss and other complications. Presently, CAs are detected mainly by array comparative genomic hybridization (CGH) and single nucleotide polymorphism microarrays. The present study developed a low­coverage next­generation sequencing method to detect CAs in spontaneous miscarriage and assess its clinical performance. In total, 1,401 patients who had experienced an abortion were enrolled in the present study and divided into two groups. In group I, 437 samples that had been previously validated by array CGH were used to establish a method to detect CAs using a semiconductor sequencing platform. In group II, 964 samples, which were not verified, were assessed using established methods with respect to clinical significance. Copy number variant (CNV)­positive and euploidy samples were verified by array CGH and short tandem repeat profiling, respectively, based on quantitative fluorescent PCR. The low­coverage sequencing method detected CNVs >1 Mb in length and a total of 3.5 million unique reads. Similar results to array CGH were obtained in group I, except for six CNVs <1 Mb long. In group II, there were 341 aneuploidies, 195 CNVs, 25 mosaicisms and 403 euploidies. Overall, among the 1,401 abortion samples, there were 536 aneuploidies, 263 CNVs, 34 mosaicisms, and 568 euploidies. Trisomies were present in all autosomal chromosomes. The most common aneuploidies were T16, monosomy X, T22, T15, T21 and T13. Furthermore, one tetrasomy 21, one CNV associated with Wolf­Hirschhorn syndrome, one associated with DiGeorge syndrome and one associated with both Prader­Willi and Angelman syndromes were identified. These four cases were confirmed by short tandem repeat profiling and array CGH. Quantitative fluorescent PCR revealed nine polyploidy samples. The present method demonstrated equivalent efficacy to that of array CGH in detecting CNVs >1 Mb, with advantages of requiring less input DNA and lower cost.

Noninvasive Prenatal Testing of Rare Autosomal Aneuploidies by Semiconductor Sequencing.

Rare autosomal aneuploidies (RAAs) can cause miscarriage or other pregnancy complications and lead to inconsistent results of noninvasive prenatal testing (NIPT), but many NIPT providers have not yet started to provide related services. Our aim was to develop a semiconductor sequencing platform (SSP)-based method for detecting RAAs when pregnant women performed NIPT. Fifty-three aneuploidy samples with verified karyotyping or array comparative genomic hybridization (aCGH) results were collected and subjected to RAAs detection using an SSP to develop a method by genomic sequencing. Various trisomies on all chromosomes other than chromosomes 17 and 19, four multiple aneusomies, one monosomy and five sex chromosome abnormalities were got by our method which can directly identify RAAs via a z-score. Then, artificial mixtures of 10% and 5% DNA were created by adding fragmented fifty-three tissue samples and used in an NIPT simulation to develop a bioinformatics analysis method which can use in NIPT. And the results were in accordance with those of karyotyping and aCGH. Therefore, our method has potential for use in NIPT. Finally, 23,823 clinical plasma samples were tested to verify the performance of our approach. Karyotyping or aCGH was performed on the positive clinical samples. In total, 188 of 23,823 clinical samples were positive (T2, n = 1; T7, n = 1; T13, n = 15; T18, n = 45; T21, n = 125; and multiple aneusomies, n = 1) and verified by karyotyping or aCGH; no sample was a false negative. Several false positives were detected, one of which showed maternal copy number variation (CNV). One case of multiple aneusomies was caused by a maternal tumor. The method developed enables detection of RAAs without increasing costs.

Identification of SNPs involved in regulating a novel alternative transcript of P450 CYP6ER1 in the brown planthopper.

Cytochrome P450-mediated metabolic resistance is one of the major mechanisms involved in insecticide resistance. Although the up-regulation of cytochrome P450 plays a vital role in insecticide metabolism, the molecular basis for the transcriptional regulation of cytochrome P450 remains largely unknown. The P450 gene CYP6ER1, has been reported to confer imidacloprid resistance to the brown planthopper, Nilaparvata lugens. Here, we identified a novel alternative transcript of CYP6ER1 (transcript A2) that had different expression patterns between resistant and susceptible populations, and was more stable after insecticide induction. The promoter of this transcript was sequenced and multiple single nucleotide polymorphisms (SNPs) were detected in individuals from susceptible and resistant field-collected populations. Resistant alleles of four SNPs were found to significantly enhance the promoter activity of the CYP6ER1 transcript A2. Electrophoretic mobility shift assays (EMSAs) revealed that these SNPs might regulate the binding of transcription factors to the promoter. Our findings provide novel evidence regarding the transcriptional regulation of a metabolic resistance-related gene and may be useful to understand the resistance mechanism of N. lugens in the field.

Preparative isolation of paclitaxel and related taxanes from cell cultures of Taxus chinensis using reversed-phase flash chromatography.

In this study, paclitaxel, baccatin III, taxuyunnanine C and sinenxane C were successfully separated by reversed-phase flash chromatography on a manually packed C18 column from Taxus chinensis cell culture extract. The crude cell culture extract was first treated with Al2O3 column chromatography and then divided into two parts: fraction 1 and fraction 2. Ten milligrams of baccatin III and 19 mg of paclitaxel were obtained from 100 mg dried fraction 1. Fifty-two milligrams of taxuyunnanine C and 11 mg sinenxane C were obtained from 100 mg dried fraction 2. The purities of the four compounds were 98.02%, 98.53%, 98.93% and 98.76%, respectively. Their structures were characterised by using UV, MS and NMR. These results indicate that paclitaxel and related taxanes including baccatin III can be obtained from cell culture in a highly pure state using reversed-phase flash chromatography.

Preparative separation and purification of deoxyschizandrin from Schisandrae Sphenantherae Fructus by high-speed counter-current chromatography.

A high-speed counter-current chromatography (HSCCC) method was successfully developed for the preparative separation and purification of deoxyschizandrin from Schisandrae Sphenantherae Fructus in one step. The purity of deoxyschizandrin was 98.5%, and the structure was identified by MS, UV and NMR. This method was simple, fast, convenient and appropriate to prepare pure compound as reference substances for related research on Schisandrae Sphenantherae Fructus.

Preparative isolation of Heteroclitin D from Kadsurae Caulis using normal-phase flash chromatography.

Heteroclitin D (H.D) was successfully isolated from Kadsurae Caulis by using flash chromatography and recrystallized by methanol, 10.2 mg of H.D was obtained from 4.86 g of crude extract, and the purity determined by HPLC was 99.4%. The structure was identified by UV, IR, MS, and NMR analysis. The fast, simple and efficient method can be applied to the preparation of reference substance of H. D.