Improving the accuracy of noninvasive prenatal testing through size-selection between fetal and maternal cfDNA.

OBJECTIVES: In general, fetal cfDNA is shorter than maternal cfDNA, and accuracy of noninvasive prenatal testing (NIPT) results can be improved by selecting shorter cfDNA fragments to enrich fetal-derived cfDNA. This study investigated potential improvements in the accuracy of NIPT by performing classification and analysis based on differences in cfDNA size. METHODS: We performed paired-end sequencing to identify size ranges of fetal and maternal cfDNA from 62,374 pregnant women. We then developed a size-selection method to isolate and analyze both fetal and maternal cfDNA, defining fetal-derived cfDNA as less than 150 bp and maternal-derived cfDNA as greater than 180 bp. RESULTS: By implementing size-selection method, the accuracy of NIPT was improved, resulting in an increase in the overall positive predictive value for all aneuploidies from 89.57% to 97.1%. This was achieved by enriching both fetal and maternal-derived cfDNA, which increased fetal DNA fraction while the number of false positives for all aneuploidies was reduced by more than 70%. CONCLUSIONS: We identified the differences in read length between fetal and maternal-derived cfDNA, and selectively enriched both shorter and longer cfDNA fragments for subsequent analysis. Our approach can increase the detection accuracy of NIPT for detecting fetal aneuploidies and reduce the number of false positives caused by maternal chromosomal abnormalities.

Enhancing Lung Cancer Classification through Integration of Liquid Biopsy Multi-Omics Data with Machine Learning Techniques.

Early detection of lung cancer is crucial for patient survival and treatment. Recent advancements in next-generation sequencing (NGS) analysis enable cell-free DNA (cfDNA) liquid biopsy to detect changes, like chromosomal rearrangements, somatic mutations, and copy number variations (CNVs), in cancer. Machine learning (ML) analysis using cancer markers is a highly promising tool for identifying patterns and anomalies in cancers, making the development of ML-based analysis methods essential. We collected blood samples from 92 lung cancer patients and 80 healthy individuals to analyze the distinction between them. The detection of lung cancer markers Cyfra21 and carcinoembryonic antigen (CEA) in blood revealed significant differences between patients and controls. We performed machine learning analysis to obtain AUC values via Adaptive Boosting (AdaBoost), Multi-Layer Perceptron (MLP), and Logistic Regression (LR) using cancer markers, cfDNA concentrations, and CNV screening. Furthermore, combining the analysis of all multi-omics data for ML showed higher AUC values compared with analyzing each element separately, suggesting the potential for a highly accurate diagnosis of cancer. Overall, our results from ML analysis using multi-omics data obtained from blood demonstrate a remarkable ability of the model to distinguish between lung cancer and healthy individuals, highlighting the potential for a diagnostic model against lung cancer.

Advances in methylation analysis of liquid biopsy in early cancer detection of colorectal and lung cancer.

Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic feature for detecting the presence of cancer and determining its origin. The purpose of this study was to evaluate the diagnostic performance of methylation-sensitive restriction enzyme digestion followed by sequencing (MRE-Seq) using cfDNA, and to investigate the cancer signal origin (CSO) of the cancer using a deep neural network (DNN) analyses for liquid biopsy of colorectal and lung cancer. We developed a selective MRE-Seq method with DNN learning-based prediction model using demethylated-sequence-depth patterns from 63,266 CpG sites using SacII enzyme digestion. A total of 191 patients with stage I-IV cancers (95 lung cancers and 96 colorectal cancers) and 126 noncancer participants were enrolled in this study. Our study showed an area under the receiver operating characteristic curve (AUC) of 0.978 with a sensitivity of 78.1% for colorectal cancer, and an AUC of 0.956 with a sensitivity of 66.3% for lung cancer, both at a specificity of 99.2%. For colorectal cancer, sensitivities for stages I-IV ranged from 76.2 to 83.3% while for lung cancer, sensitivities for stages I-IV ranged from 44.4 to 78.9%, both again at a specificity of 99.2%. The CSO model's true-positive rates were 94.4% and 89.9% for colorectal and lung cancers, respectively. The MRE-Seq was found to be a useful method for detecting global hypomethylation patterns in liquid biopsy samples and accurately diagnosing colorectal and lung cancers, as well as determining CSO of the cancer using DNN analysis.Trial registration: This trial was registered at ClinicalTrials.gov (registration number: NCT04253509) for lung cancer on 5 February 2020, https://clinicaltrials.gov/ct2/show/NCT04253509 . Colorectal cancer samples were retrospectively registered at CRIS (Clinical Research Information Service, registration number: KCT0008037) on 23 December 2022, https://cris.nih.go.kr , https://who.init/ictrp . Healthy control samples were retrospectively registered.

Theranostic Surrogacy of [123I]NaI for Differentiated Thyroid Cancer Radionuclide Therapy.

Precise dosimetry has gained interest for interpreting the response assessments of novel therapeutic radiopharmaceuticals, as well as for improving conventional radiotherapies such as the "one dose fits all" approach. Although radioiodine as same-element isotope theranostic pairs has been used for differentiated thyroid cancer (DTC), there are insufficient studies on the determination of its dosing regimen for personalized medicine and on extrapolating strategies for companion diagnostic radiopharmaceuticals. In this study, DTC xenograft mouse models were generated after validating iodine uptakes via sodium iodine symporter proteins (NIS) through in vitro assays, and theranostic surrogacy of companion radiopharmaceuticals was investigated in terms of single photon emission computed tomography (SPECT) imaging and voxel-level dosimetry. Following a Monte Carlo simulation, the hypothetical energy deposition/dose distribution images were produced as [123I]NaI SPECT scans with the use of 131I ion source simulation, and dose rate curves were used to estimate absorbed dose. For the tumor, a peak concentration of 96.49 ± 11.66% ID/g occurred 2.91 ± 0.42 h after [123I]NaI injection, and absorbed dose for 131I therapy was estimated as 0.0344 ± 0.0088 Gy/MBq. The absorbed dose in target/off-target tissues was estimated by considering subject-specific heterogeneous tissue compositions and activity distributions. Furthermore, a novel approach was proposed for simplifying voxel-level dosimetry and suggested for determining the minimal/optimal scan time points of surrogates for pretherapeutic dosimetry. When two scan time points were set to Tmax and 26 h and the group mean half-lives were applied to the dose rate curves, the most accurate absorbed dose estimates were determined [-22.96, 2.21%]. This study provided an experimental basis to evaluate dose distribution and is expected hopefully to improve the challenging dosimetry process for clinical use.

Improving CNV Detection Performance in Microarray Data Using a Machine Learning-Based Approach.

Copy number variation (CNV) is a primary source of structural variation in the human genome, leading to several disorders. Therefore, analyzing neonatal CNVs is crucial for managing CNV-related chromosomal disabilities. However, genomic waves can hinder accurate CNV analysis. To mitigate the influences of the waves, we adopted a machine learning approach and developed a new method that uses a modified log R ratio instead of the commonly used log R ratio. Validation results using samples with known CNVs demonstrated the superior performance of our method. We analyzed a total of 16,046 Korean newborn samples using the new method and identified CNVs related to 39 genetic disorders were identified in 342 cases. The most frequently detected CNV-related disorder was Joubert syndrome 4. The accuracy of our method was further confirmed by analyzing a subset of the detected results using NGS and comparing them with our results. The utilization of a genome-wide single nucleotide polymorphism array with wave offset was shown to be a powerful method for identifying CNVs in neonatal cases. The accurate screening and the ability to identify various disease susceptibilities offered by our new method could facilitate the identification of CNV-associated chromosomal disease etiologies.

A therapeutic neutralizing antibody targeting receptor binding domain of SARS-CoV-2 spike protein.

Vaccines and therapeutics are urgently needed for the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we screen human monoclonal antibodies (mAb) targeting the receptor binding domain (RBD) of the viral spike protein via antibody library constructed from peripheral blood mononuclear cells of a convalescent patient. The CT-P59 mAb potently neutralizes SARS-CoV-2 isolates including the D614G variant without antibody-dependent enhancement effect. Complex crystal structure of CT-P59 Fab/RBD shows that CT-P59 blocks interaction regions of RBD for angiotensin converting enzyme 2 (ACE2) receptor with an orientation that is notably different from previously reported RBD-targeting mAbs. Furthermore, therapeutic effects of CT-P59 are evaluated in three animal models (ferret, hamster, and rhesus monkey), demonstrating a substantial reduction in viral titer along with alleviation of clinical symptoms. Therefore, CT-P59 may be a promising therapeutic candidate for COVID-19.

Comparison of Ion Personal Genome Machine Platforms for the Detection of Variants in BRCA1 and BRCA2.

PURPOSE: Transition to next generation sequencing (NGS) for BRCA1/BRCA2 analysis in clinical laboratories is ongoing but different platforms and/or data analysis pipelines give different results resulting in difficulties in implementation. We have evaluated the Ion Personal Genome Machine (PGM) Platforms (Ion PGM, Ion PGM Dx, Thermo Fisher Scientific) for the analysis of BRCA1/2. MATERIALS AND METHODS: The results of Ion PGM with OTG-snpcaller, a pipeline based on Torrent mapping alignment program and Genome Analysis Toolkit, from 75 clinical samples and 14 reference DNA samples were compared with Sanger sequencing for BRCA1/BRCA2. Ten clinical samples and 14 reference DNA samples were additionally sequenced by Ion PGM Dx with Torrent Suite. RESULTS: Fifty types of variants including 18 pathogenic or variants of unknown significance were identified from 75 clinical samples and known variants of the reference samples were confirmed by Sanger sequencing and/or NGS. One false-negative results were present for Ion PGM/OTG-snpcaller for an indel variant misidentified as a single nucleotide variant. However, eight discordant results were present for Ion PGM Dx/Torrent Suite with both false-positive and -negative results. A 40-bp deletion, a 4-bp deletion and a 1-bp deletion variant was not called and a false-positive deletion was identified. Four other variants were misidentified as another variant. CONCLUSION: Ion PGM/OTG-snpcaller showed acceptable performance with good concordance with Sanger sequencing. However, Ion PGM Dx/Torrent Suite showed many discrepant results not suitable for use in a clinical laboratory, requiring further optimization of the data analysis for calling variants.

Comparable Immune Function Inhibition by the Infliximab Biosimilar CT-P13: Implications for Treatment of Inflammatory Bowel Disease.

BACKGROUND AND AIMS: CT-P13 is the first biosimilar monoclonal antibody to infliximab, and was recently approved in the European Union, Japan, Korea, and USA for all six indications of infliximab. However, studies directly assessing the biologic activity of CT-P13 versus inflximab in the context of inflammatory bowel disease [IBD] are still scanty. In the present study, we aimed to compare the biological activities of CT-P13 and infliximab with specific focus on intestinal cells so as to gain insight into the potential biosimilarity of these two agents for treatment of IBD. METHODS: CT-P13 and infliximab were investigated and compared by in vitro experiments for their neutralisation ability of soluble tumour necrosis factor alpha [sTNFα] and membrane-bound tumour necrosis factor alpha [mTNFα], suppression of cytokine release by reverse signalling, induction of regulatory macrophages and wound healing, and antibody-dependent cell cytotoxicity [ADCC]. RESULTS: CT-P13 showed similar biological activities to infliximab as gauged by neutralisation of soluble TNFα, as well as blockade of apoptosis and suppression of pro-inflammatory cytokines in intestinal Caco-2 cells. Infliximab and CT-P13 equally induced apoptosis and outside-to-inside signals through transmembrane TNFα [tmTNFα]. Moreover, regulatory macrophage induction and ensuing wound healing were similarly exerted by CT-P13 and infliximab. However, neither CT-P13 nor infliximab exerted any significant ADCC of ex vivo-stimulated peripheral blood monocytes or lamina propria mononuclear cells from IBD patients. CONCLUSIONS: These findings indicate that CT-P13 and infliximab exert highly similar biological activities in intestinal cells, and further support a mechanistic comparability of these two drugs in the treatment of IBD.

Modulation on brain gray matter activity and white matter integrity by APOE ε4 risk gene in cognitively intact elderly: A multimodal neuroimaging study.

Apolipoprotein E (APOE) ε4 allele is the genetic risk factor with the most established evidence for sporadic Alzheimer's disease. Previous neuroimaging studies have demonstrated insufficiently consistent functional and structural changes among healthy APOE ε4 carriers when compared to non-carriers. Here, in a cognitively intact elderly group (a total of 110: 45 APOE ε4 carriers, 65 non-carriers), we aimed to investigate the potential role of APOE ε4 in the modulation of grey matter activity, white matter integrity, and brain morphology before the development of clinically significant symptoms and signs, by methods of: amplitude of low frequency fluctuations and regional homogeneity analysis based on resting state fMRI, and fiber tractography approach based on diffusion tensor imaging. Our results revealed that compared to non-carriers, APOE ε4 carriers showed: (1) an inconsistent pattern of activity change in the default mode network, including increased gray matter activity in anterior cingulate cortex and medial prefrontal cortex and decreased activity in precuneus; (2) lower mean diffusivity (MD) in fibers of corona radiata and corpus callosum, and lower axial diffusivity in genu of corpus callosum; and (3) significant positive correlation between the MD value of the right superior corona radiate and gross white matter volume; significant negative correlation between the MD value of the right superior corona radiate and Mini-Mental State Examination (MMSE) score. Our results suggested that APOE ε4 gene can modulate gray matter activity and white matter integrity in cognitive and memory related regions, even before any clinical or neuropsychic symtoms or signs of imminent disease.

Polymorphisms in maternal and fetal genes encoding for proteins involved in extracellular matrix metabolism alter the risk for small-for-gestational-age.

OBJECTIVE: To examine the association between maternal and fetal genetic variants and small-for-gestational-age (SGA). METHODS: A case-control study was conducted in patients with SGA neonates (530 maternal and 436 fetal) and controls (599 maternal and 628 fetal); 190 candidate genes and 775 SNPs were studied. Single-locus, multi-locus and haplotype association analyses were performed on maternal and fetal data with logistic regression, multifactor dimensionality reduction (MDR) analysis, and haplotype-based association with 2 and 3 marker sliding windows, respectively. Ingenuity pathway analysis (IPA) software was used to assess pathways that associate with SGA. RESULTS: The most significant single-locus association in maternal data was with a SNP in tissue inhibitor of metalloproteinase 2 (TIMP2) (rs2277698 OR = 1.71, 95% CI [1.26-2.32], p = 0.0006) while in the fetus it was with a SNP in fibronectin 1 isoform 3 preproprotein (FN1) (rs3796123, OR = 1.46, 95% CI [1.20-1.78], p = 0.0001). Both SNPs were adjusted for potential confounders (maternal body mass index and fetal sex). Haplotype analyses resulted in associations in α 1 type I collagen preproprotein (COL1A1, rs1007086-rs2141279-rs17639446, global p = 0.006) in mothers and FN1 (rs2304573-rs1250204-rs1250215, global p = 0.045) in fetuses. Multi-locus analyses with MDR identified a two SNP model with maternal variants collagen type V α 2 (COL5A2) and plasminogen activator urokinase (PLAU) predicting SGA outcome correctly 59% of the time (p = 0.035). CONCLUSIONS: Genetic variants in extracellular matrix-related genes showed significant single-locus association with SGA. These data are consistent with other studies that have observed elevated circulating fibronectin concentrations in association with increased risk of SGA. The present study supports the hypothesis that DNA variants can partially explain the risk of SGA in a cohort of Hispanic women.

A genetic association study of maternal and fetal candidate genes that predispose to preterm prelabor rupture of membranes (PROM).

OBJECTIVE: We sought to determine whether maternal/fetal single-nucleotide polymorphisms (SNPs) in candidate genes are associated with preterm prelabor rupture of membranes (pPROM). STUDY DESIGN: A case-control study was conducted in patients with pPROM (225 mothers and 155 fetuses) and 599 mothers and 628 fetuses with a normal pregnancy; 190 candidate genes and 775 SNPs were studied. Single locus/haplotype association analyses were performed; false discovery rate was used to correct for multiple testing (q* = 0.15). RESULTS: First, a SNP in tissue inhibitor of metalloproteinase 2 in mothers was significantly associated with pPROM (odds ratio, 2.12; 95% confidence interval, 1.47-3.07; P = .000068), and this association remained significant after correction for multiple comparisons. Second, haplotypes for Alpha 3 type IV collagen isoform precursor in the mother were associated with pPROM (global P = .003). Third, multilocus analysis identified a 3-locus model, which included maternal SNPs in collagen type I alpha 2, defensin alpha 5 gene, and endothelin 1. CONCLUSION: DNA variants in a maternal gene involved in extracellular matrix metabolism doubled the risk of pPROM.

Identification of fetal and maternal single nucleotide polymorphisms in candidate genes that predispose to spontaneous preterm labor with intact membranes.

OBJECTIVE: The purpose of this study was to determine whether maternal/fetal single nucleotide polymorphisms (SNPs) in candidate genes are associated with spontaneous preterm labor/delivery. STUDY DESIGN: A genetic association study was conducted in 223 mothers and 179 fetuses (preterm labor with intact membranes who delivered <37 weeks of gestation [preterm birth (PTB)]), and 599 mothers and 628 fetuses (normal pregnancy); 190 candidate genes and 775 SNPs were studied. Single locus/haplotype association analyses were performed; the false discovery rate was used to correct for multiple testing. RESULTS: The strongest single locus associations with PTB were interleukin-6 receptor 1 (fetus; P=.000148) and tissue inhibitor of metalloproteinase 2 (mother; P=.000197), which remained significant after correction for multiple comparisons. Global haplotype analysis indicated an association between a fetal DNA variant in insulin-like growth factor F2 and maternal alpha 3 type IV collagen isoform 1 (global, P=.004 and .007, respectively). CONCLUSION: An SNP involved in controlling fetal inflammation (interleukin-6 receptor 1) and DNA variants in maternal genes encoding for proteins involved in extracellular matrix metabolism approximately doubled the risk of PTB.