Mutation Analysis of Pancreatic Juice and Plasma for the Detection of Pancreatic Cancer

Molecular profiling may enable earlier detection of pancreatic cancer (PC) in high-risk individuals undergoing surveillance and allow for personalization of treatment. We hypothesized that the detection rate of DNA mutations is higher in pancreatic juice (PJ) than in plasma due to its closer contact with the pancreatic ductal system, from which pancreatic cancer cells originate, and higher overall cell-free DNA (cfDNA) concentrations. In this study, we included patients with pathology-proven PC or intraductal papillary mucinous neoplasm (IPMN) with high-grade dysplasia (HGD) from two prospective clinical trials (KRASPanc and PACYFIC) for whom both PJ and plasma were available. We performed next-generation sequencing on PJ, plasma, and tissue samples and described the presence (and concordance) of mutations in these biomaterials. This study included 26 patients (25 PC and 1 IPMN with HGD), of which 7 were women (27%), with a median age of 71 years (IQR 12) and a median BMI of 23 kg/m2 (IQR 4). Ten patients with PC (40%) were (borderline) resectable at baseline. Tissue was available from six patients (resection n = 5, biopsy n = 1). A median volume of 2.9 mL plasma (IQR 1.0 mL) and 0.7 mL PJ (IQR 0.1 mL, p &lt; 0.001) was used for DNA isolation. PJ had a higher median cfDNA concentration (2.6 ng/μL (IQR 4.2)) than plasma (0.29 ng/μL (IQR 0.40)). A total of 41 unique somatic mutations were detected: 24 mutations in plasma (2 KRAS, 15 TP53, 2 SMAD4, 3 CDKN2A 1 CTNNB1, and 1 PIK3CA), 19 in PJ (3 KRAS, 15 TP53, and 1 SMAD4), and 8 in tissue (2 KRAS, 2 CDKN2A, and 4 TP53). The mutation detection rate (and the concordance with tissue) did not differ between plasma and PJ. In conclusion, while the concentration of cfDNA was indeed higher in PJ than in plasma, the mutation detection rate was not different. A few cancer-associated genetic variants were detected in both biomaterials. Further research is needed to increase the detection rate and assess the performance and suitability of plasma and PJ for PC (early) detection.</p

Comparison of Single Cell Transcriptome Sequencing Methods:Of Mice and Men

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.</p

Comparison of Single Cell Transcriptome Sequencing Methods:Of Mice and Men

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.</p

Combined Analysis of Transcriptome and T-Cell Receptor Alpha and Beta (TRA /TRB ) Repertoire in Paucicellular Samples at the Single-Cell Level

With the advent of next-generation sequencing (NGS) methodologies, the total repertoires of B and T cells can be disclosed in much more detail than ever before. Even though many of these strategies do provide in-depth and high-resolution information of the immunoglobulin (IG) and/or T-cell receptor (TR) repertoire, one clear disadvantage is that the IG/TR profiles cannot be connected to individual cells. Single-cell technologies do allow to study the IG/TR repertoire at the individual cell level. This is especially relevant in cell samples in which much heterogeneity of the cell population is expected. By combining the IG/TR repertoire with transcriptome data, the reactivity of the B or T cell can be associated with activation or maturation stages. An additional advantage of such single-cell technologies is that the combination of both IG and both TR chains can be studied on a per cell basis, which better reflects the antigen receptor reactivity of cells. Here we present the ICELL8 single-cell method for the parallel analysis of the TR repertoire and transcriptome, which is especially useful in samples that contain relatively few cells

Molecular analysis of the erythroid phenotype of a patient with BCL11A haploinsufficiency

The BCL11A gene encodes a transcriptional repressor with essential functions in multiple tissues during human development. Haploinsufficiency for BCL11A causes Dias-Logan syndrome (OMIM 617101), an intellectual developmental disorder with hereditary persistence of fetal hemoglobin (HPFH). Due to the severe phenotype, disease-causing variants in BCL11A occur de novo. We describe a patient with a de novo heterozygous variant, c.1453G.T, in the BCL11A gene, resulting in truncation of the BCL11A-XL protein (p.Glu485X). The truncated protein lacks the 3 C-terminal DNA-binding zinc fingers and the nuclear localization signal, rendering it inactive. The patient displayed high fetal hemoglobin (HbF) levels (12.1-18.7% of total hemoglobin), in contrast to the parents who had HbF levels of 0.3%. We used cultures of patient-derived erythroid progenitors to determine changes in gene expression and chromatin accessibility. In addition, we investigated DNA methylation of the promoters of the g-globin genes HBG1 and HBG2. HUDEP1 and HUDEP2 cells were used as models for fetal and adult human erythropoiesis, respectively. Similar to HUDEP1 cells, the patient's cells displayed Assay for Transposase-Accessible Chromatin (ATAC) peaks at the HBG1/2 promoters and significant expression of HBG1/2 genes. In contrast, HBG1/2 promoter methylation and genome-wide gene expression profiling were consistent with normal adult erythropoiesis. We conclude that HPFH is the major erythroid phenotype of constitutive BCL11A haploinsufficiency. Given the essential functions of BCL11A in other hematopoietic lineages and the neuronal system, erythroid-specific targeting of the BCL11A gene has been proposed for reactivation of g-globin expression in b-hemoglobinopathy patients. Our data strongly support this approach

Circulating TP53 mutations are associated with early tumor progression and poor survival in pancreatic cancer patients treated with FOLFIRINOX

Background: Biomarkers predicting treatment response may be used to stratify pancreatic ductal adenocarcinoma (PDAC) patients for therapy. The aim of this study was to identify circulating tumor DNA (ctDNA) mutations that associate with tumor progression during FOLFIRINOX chemotherapy, and overall survival (OS). Methods: Circulating cell-free DNA was analyzed with a 57 gene next-generation sequencing panel using plasma samples of 48 PDAC patients of all disease stages. Patients received FOLFIRINOX as initial treatment. Chemotherapy response was determined on CT scans as disease control (n = 30) or progressive disease (n = 18) within eight cycles of FOLFIRINOX, based on RECIST 1.1 criteria. Results: Detection of a TP53 ctDNA mutation before start of FOLFIRINOX [odds ratio (OR) 10.51, 95% confidence interval (CI) 1.40–79.14] and the presence of a homozygous TP53 Pro72Arg germline variant (OR 6.98, 95% CI 1.31–37.30) were predictors of early tumor progression during FOLFIRINOX in multivariable analysis. Five patients presented with the combination of a TP53 ctDNA mutation before start of FOLFIRINOX and the homozygous Pro72Arg variant. All five patients showed progression during FOLFIRINOX. The combination of the TP53 mutation and TP53 germline variant was associated with shorter survival (median OS 4.4 months, 95% CI 2.6–6.2 months) compared with patients without any TP53 alterations (median OS 13.0 months, 95% CI 8.6–17.4 months). Conclusion: The combination of a TP53 ctDNA mutation before start of FOLFIRINOX and a homozygous TP53 Pro72Arg variant is a promising biomarker, associated with early tumor progression during FOLFIRINOX and poor OS. The results of this exploratory study need to be validated in an independent cohort