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Mutation analysis of circulating tumor DNA (ctDNA) has applications in monitoring of colorectal cancer (CRC) patients for recurrence. Considering the low tumor fraction of ctDNA in cell-free DNA (cfDNA) isolated from blood plasma, the sensitivity of the detection method is important. Here, plasma DNA collected at diagnosis and follow-up from 25 CRC patients was analyzed using a multiplex superRCA mutation detection assay. The assay was also performed on genomic DNA (gDNA) from tumor and normal tissue from 20 of these patients. The lower limit of detection for most sequence variants was in the range of 10−5, while when analyzing cfDNA from plasma with a typical input of 33 ng, the practical detection limit was ~10−4 or 0.01% mutant allele frequency (MAF). In 17 of 19 patients with identified hotspot mutations in tumor gDNA, at least one hotspot mutation could be detected in plasma DNA at the time of diagnosis. The MAF increased at subsequent time points in four of the patients who experienced a clinical relapse. Multiplex superRCA analysis of the remaining six patients did not reveal any hotspot mutations. In conclusion, multiplex superRCA assays proved suitable for monitoring CRC patients by analyzing hotspot mutations in cfDNA, and dynamic changes in MAF were observed in patients with clinical relapse.

Background Low-grade gliomas (LGGs) represent children’s most prevalent central nervous system tumor, necessitating molecular profiling to diagnose and determine the most suitable treatment. Developing highly sensitive screening techniques for liquid biopsy samples is particularly beneficial, as it enables the early detection and molecular characterization of tumors with minimally invasive samples. Methods We examined CSF and plasma samples from patients with pilocytic astrocytoma (PA) using custom multiplexed droplet digital polymerase chain reaction (ddPCR) assays based on whole genome sequencing data. These assays included a screening test to analyze BRAF duplication and a targeted assay for the detection of patient-specific KIAA1549::BRAF fusion junction sequences or single nucleotide variants. Results Our findings revealed that 5 out of 13 individual cerebrospinal fluid (CSF) samples tested positive for circulating tumor DNA (ctDNA). Among these cases, 3 exhibited the KIAA1549::BRAF fusion, which was detected through copy number variation (CNV) analysis (n = 1) or a fusion-specific probe (n = 2), while 1 case each displayed the BRAF V600E mutation and the FGFR1 N577K mutation. Additionally, a quantitative analysis of cell-free DNA (cfDNA) concentrations in PA CSF samples showed that most cases had low cfDNA levels, below the limit of detection of our assay (<1.9 ng). Conclusions While CNV analysis of CSF samples from LGGs still has some limitations, it has the potential to serve as a valuable complementary tool. Furthermore, it can also be multiplexed with other aberrations, for example, to the BRAF V600 test, to provide important insights into the molecular characteristics of LGGs.

Background Low-grade gliomas (LGGs) represent children’s most prevalent central nervous system tumor, necessitating molecular profiling to diagnose and determine the most suitable treatment. Developing highly sensitive screening techniques for liquid biopsy samples is particularly beneficial, as it enables the early detection and molecular characterization of tumors with minimally invasive samples. Methods We examined CSF and plasma samples from patients with pilocytic astrocytoma (PA) using custom multiplexed droplet digital polymerase chain reaction (ddPCR) assays based on whole genome sequencing data. These assays included a screening test to analyze BRAF duplication and a targeted assay for the detection of patient-specific KIAA1549::BRAF fusion junction sequences or single nucleotide variants. Results Our findings revealed that 5 out of 13 individual cerebrospinal fluid (CSF) samples tested positive for circulating tumor DNA (ctDNA). Among these cases, 3 exhibited the KIAA1549::BRAF fusion, which was detected through copy number variation (CNV) analysis (n = 1) or a fusion-specific probe (n = 2), while 1 case each displayed the BRAF V600E mutation and the FGFR1 N577K mutation. Additionally, a quantitative analysis of cell-free DNA (cfDNA) concentrations in PA CSF samples showed that most cases had low cfDNA levels, below the limit of detection of our assay (<1.9 ng). Conclusions While CNV analysis of CSF samples from LGGs still has some limitations, it has the potential to serve as a valuable complementary tool. Furthermore, it can also be multiplexed with other aberrations, for example, to the BRAF V600 test, to provide important insights into the molecular characteristics of LGGs.

Mutation analysis of circulating tumor DNA (ctDNA) has applications in monitoring of colorectal cancer (CRC) patients for recurrence. Considering the low tumor fraction of ctDNA in cell-free DNA (cfDNA) isolated from blood plasma, the sensitivity of the detection method is important. Here, plasma DNA collected at diagnosis and follow-up from 25 CRC patients was analyzed using a multiplex superRCA mutation detection assay. The assay was also performed on genomic DNA (gDNA) from tumor and normal tissue from 20 of these patients. The lower limit of detection for most sequence variants was in the range of 10−5, while when analyzing cfDNA from plasma with a typical input of 33 ng, the practical detection limit was ~10−4 or 0.01% mutant allele frequency (MAF). In 17 of 19 patients with identified hotspot mutations in tumor gDNA, at least one hotspot mutation could be detected in plasma DNA at the time of diagnosis. The MAF increased at subsequent time points in four of the patients who experienced a clinical relapse. Multiplex superRCA analysis of the remaining six patients did not reveal any hotspot mutations. In conclusion, multiplex superRCA assays proved suitable for monitoring CRC patients by analyzing hotspot mutations in cfDNA, and dynamic changes in MAF were observed in patients with clinical relapse.

Mutation analysis of circulating tumor DNA (ctDNA) has applications in monitoring of colorectal cancer (CRC) patients for recurrence. Considering the low tumor fraction of ctDNA in cell-free DNA (cfDNA) isolated from blood plasma, the sensitivity of the detection method is important. Here, plasma DNA collected at diagnosis and follow-up from 25 CRC patients was analyzed using a multiplex superRCA mutation detection assay. The assay was also performed on genomic DNA (gDNA) from tumor and normal tissue from 20 of these patients. The lower limit of detection for most sequence variants was in the range of 10−5, while when analyzing cfDNA from plasma with a typical input of 33 ng, the practical detection limit was ~10−4 or 0.01% mutant allele frequency (MAF). In 17 of 19 patients with identified hotspot mutations in tumor gDNA, at least one hotspot mutation could be detected in plasma DNA at the time of diagnosis. The MAF increased at subsequent time points in four of the patients who experienced a clinical relapse. Multiplex superRCA analysis of the remaining six patients did not reveal any hotspot mutations. In conclusion, multiplex superRCA assays proved suitable for monitoring CRC patients by analyzing hotspot mutations in cfDNA, and dynamic changes in MAF were observed in patients with clinical relapse.

Background Low-grade gliomas (LGGs) represent children’s most prevalent central nervous system tumor, necessitating molecular profiling to diagnose and determine the most suitable treatment. Developing highly sensitive screening techniques for liquid biopsy samples is particularly beneficial, as it enables the early detection and molecular characterization of tumors with minimally invasive samples. Methods We examined CSF and plasma samples from patients with pilocytic astrocytoma (PA) using custom multiplexed droplet digital polymerase chain reaction (ddPCR) assays based on whole genome sequencing data. These assays included a screening test to analyze BRAF duplication and a targeted assay for the detection of patient-specific KIAA1549::BRAF fusion junction sequences or single nucleotide variants. Results Our findings revealed that 5 out of 13 individual cerebrospinal fluid (CSF) samples tested positive for circulating tumor DNA (ctDNA). Among these cases, 3 exhibited the KIAA1549::BRAF fusion, which was detected through copy number variation (CNV) analysis (n = 1) or a fusion-specific probe (n = 2), while 1 case each displayed the BRAF V600E mutation and the FGFR1 N577K mutation. Additionally, a quantitative analysis of cell-free DNA (cfDNA) concentrations in PA CSF samples showed that most cases had low cfDNA levels, below the limit of detection of our assay (<1.9 ng). Conclusions While CNV analysis of CSF samples from LGGs still has some limitations, it has the potential to serve as a valuable complementary tool. Furthermore, it can also be multiplexed with other aberrations, for example, to the BRAF V600 test, to provide important insights into the molecular characteristics of LGGs.

Mutation analysis of circulating tumor DNA (ctDNA) has applications in monitoring of colorectal cancer (CRC) patients for recurrence. Considering the low tumor fraction of ctDNA in cell-free DNA (cfDNA) isolated from blood plasma, the sensitivity of the detection method is important. Here, plasma DNA collected at diagnosis and follow-up from 25 CRC patients was analyzed using a multiplex superRCA mutation detection assay. The assay was also performed on genomic DNA (gDNA) from tumor and normal tissue from 20 of these patients. The lower limit of detection for most sequence variants was in the range of 10−5, while when analyzing cfDNA from plasma with a typical input of 33 ng, the practical detection limit was ~10−4 or 0.01% mutant allele frequency (MAF). In 17 of 19 patients with identified hotspot mutations in tumor gDNA, at least one hotspot mutation could be detected in plasma DNA at the time of diagnosis. The MAF increased at subsequent time points in four of the patients who experienced a clinical relapse. Multiplex superRCA analysis of the remaining six patients did not reveal any hotspot mutations. In conclusion, multiplex superRCA assays proved suitable for monitoring CRC patients by analyzing hotspot mutations in cfDNA, and dynamic changes in MAF were observed in patients with clinical relapse.

Background Low-grade gliomas (LGGs) represent children’s most prevalent central nervous system tumor, necessitating molecular profiling to diagnose and determine the most suitable treatment. Developing highly sensitive screening techniques for liquid biopsy samples is particularly beneficial, as it enables the early detection and molecular characterization of tumors with minimally invasive samples. Methods We examined CSF and plasma samples from patients with pilocytic astrocytoma (PA) using custom multiplexed droplet digital polymerase chain reaction (ddPCR) assays based on whole genome sequencing data. These assays included a screening test to analyze BRAF duplication and a targeted assay for the detection of patient-specific KIAA1549::BRAF fusion junction sequences or single nucleotide variants. Results Our findings revealed that 5 out of 13 individual cerebrospinal fluid (CSF) samples tested positive for circulating tumor DNA (ctDNA). Among these cases, 3 exhibited the KIAA1549::BRAF fusion, which was detected through copy number variation (CNV) analysis (n = 1) or a fusion-specific probe (n = 2), while 1 case each displayed the BRAF V600E mutation and the FGFR1 N577K mutation. Additionally, a quantitative analysis of cell-free DNA (cfDNA) concentrations in PA CSF samples showed that most cases had low cfDNA levels, below the limit of detection of our assay (<1.9 ng). Conclusions While CNV analysis of CSF samples from LGGs still has some limitations, it has the potential to serve as a valuable complementary tool. Furthermore, it can also be multiplexed with other aberrations, for example, to the BRAF V600 test, to provide important insights into the molecular characteristics of LGGs.

HR+/HER2- stage IV breast cancer patients are treated with a combination of CDK4/6 inhibitors plus endocrine therapy (ET). Nevertheless, all patients will develop intrinsic or acquired resistance, but there are not predictive biomarkers identified so far. Hence, in this thesis, it was proved that the study of circulating material lets monitor disease evolution and tailor-patient therapy. The transcriptomic characterization of CTCs classified patients according to therapy response and determine resistance mechanisms to CDK4/6i plus ET. The cfDNA levels can be used to longitudinally study therapy response. In addition, it was proposed the characterization of circulating immune cells to identify predictive biomarkers to CDK4/6i plus ET in HR+/HER2- stage IV BC patients.

Background Low-grade gliomas (LGGs) represent children’s most prevalent central nervous system tumor, necessitating molecular profiling to diagnose and determine the most suitable treatment. Developing highly sensitive screening techniques for liquid biopsy samples is particularly beneficial, as it enables the early detection and molecular characterization of tumors with minimally invasive samples. Methods We examined CSF and plasma samples from patients with pilocytic astrocytoma (PA) using custom multiplexed droplet digital polymerase chain reaction (ddPCR) assays based on whole genome sequencing data. These assays included a screening test to analyze BRAF duplication and a targeted assay for the detection of patient-specific KIAA1549::BRAF fusion junction sequences or single nucleotide variants. Results Our findings revealed that 5 out of 13 individual cerebrospinal fluid (CSF) samples tested positive for circulating tumor DNA (ctDNA). Among these cases, 3 exhibited the KIAA1549::BRAF fusion, which was detected through copy number variation (CNV) analysis (n = 1) or a fusion-specific probe (n = 2), while 1 case each displayed the BRAF V600E mutation and the FGFR1 N577K mutation. Additionally, a quantitative analysis of cell-free DNA (cfDNA) concentrations in PA CSF samples showed that most cases had low cfDNA levels, below the limit of detection of our assay (<1.9 ng). Conclusions While CNV analysis of CSF samples from LGGs still has some limitations, it has the potential to serve as a valuable complementary tool. Furthermore, it can also be multiplexed with other aberrations, for example, to the BRAF V600 test, to provide important insights into the molecular characteristics of LGGs.

Mutation analysis of circulating tumor DNA (ctDNA) has applications in monitoring of colorectal cancer (CRC) patients for recurrence. Considering the low tumor fraction of ctDNA in cell-free DNA (cfDNA) isolated from blood plasma, the sensitivity of the detection method is important. Here, plasma DNA collected at diagnosis and follow-up from 25 CRC patients was analyzed using a multiplex superRCA mutation detection assay. The assay was also performed on genomic DNA (gDNA) from tumor and normal tissue from 20 of these patients. The lower limit of detection for most sequence variants was in the range of 10−5, while when analyzing cfDNA from plasma with a typical input of 33 ng, the practical detection limit was ~10−4 or 0.01% mutant allele frequency (MAF). In 17 of 19 patients with identified hotspot mutations in tumor gDNA, at least one hotspot mutation could be detected in plasma DNA at the time of diagnosis. The MAF increased at subsequent time points in four of the patients who experienced a clinical relapse. Multiplex superRCA analysis of the remaining six patients did not reveal any hotspot mutations. In conclusion, multiplex superRCA assays proved suitable for monitoring CRC patients by analyzing hotspot mutations in cfDNA, and dynamic changes in MAF were observed in patients with clinical relapse.

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) elicit potent cell cycle arrest in EGFR-mutant non-small-cell lung cancer (NSCLC) cells. However, little is known about the mechanisms through which these drugs alter the tumor phenotype that contributes to the immune escape of EGFR-mutant cells. Using EGFR-mutant NSCLC cell lines and tissue samples from patients, we investigated the changes in immune checkpoints expressed in tumor cells following EGFR inhibition. Subsequently, we also analyzed the role of soluble factors from the dying tumor cells in the activation of immune signaling pathways involved in therapy resistance. Upon EGFR-TKI treatment, we found that EGFR-mutant cells upregulated the expression of innate immune checkpoint CD24 in vitro. We then analyzed biopsy samples from six patients who developed resistance to a first-generation EGFR-TKI without the acquired T790M mutation. Immunohistochemistry revealed that levels of tumor CD24 expression were increased upon treatment compared with those from pre-treatment samples. Monocyte-derived macrophages facilitated antibody-dependent cellular phagocytosis when EGFR-TKI-treated EGFR-mutant cells were incubated with anti-CD24 antibodies in vitro, suggesting that CD24 may be a therapeutical target for EGFR-mutant lung cancer. Moreover, EGFR inhibition accelerated the release of cell-free DNA (cfDNA) from dying tumor cells, which activated the type I interferon signaling pathways in human THP-1 monocytes in a stimulator of interferon genes-dependent manner. Our study indicates that EGFR inhibition in EGFR-mutant NSCLC cells fosters a tumor microenvironment associated with immune escape. Thus, CD24 targeted therapy and cfDNA monitoring may contribute to improved treatment outcomes in patients with EGFR-mutant NSCLC.

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) elicit potent cell cycle arrest in EGFR-mutant non-small-cell lung cancer (NSCLC) cells. However, little is known about the mechanisms through which these drugs alter the tumor phenotype that contributes to the immune escape of EGFR-mutant cells. Using EGFR-mutant NSCLC cell lines and tissue samples from patients, we investigated the changes in immune checkpoints expressed in tumor cells following EGFR inhibition. Subsequently, we also analyzed the role of soluble factors from the dying tumor cells in the activation of immune signaling pathways involved in therapy resistance. Upon EGFR-TKI treatment, we found that EGFR-mutant cells upregulated the expression of innate immune checkpoint CD24 in vitro. We then analyzed biopsy samples from six patients who developed resistance to a first-generation EGFR-TKI without the acquired T790M mutation. Immunohistochemistry revealed that levels of tumor CD24 expression were increased upon treatment compared with those from pre-treatment samples. Monocyte-derived macrophages facilitated antibody-dependent cellular phagocytosis when EGFR-TKI-treated EGFR-mutant cells were incubated with anti-CD24 antibodies in vitro, suggesting that CD24 may be a therapeutical target for EGFR-mutant lung cancer. Moreover, EGFR inhibition accelerated the release of cell-free DNA (cfDNA) from dying tumor cells, which activated the type I interferon signaling pathways in human THP-1 monocytes in a stimulator of interferon genes-dependent manner. Our study indicates that EGFR inhibition in EGFR-mutant NSCLC cells fosters a tumor microenvironment associated with immune escape. Thus, CD24 targeted therapy and cfDNA monitoring may contribute to improved treatment outcomes in patients with EGFR-mutant NSCLC.

Introduction: Current prognostic blood-based biomarkers for pancreatic adenocarcinoma (PDAC) are limited. Recently, promoter hypermethylation of SFRP1 (phSFRP1) has been linked to poor prognosis in patients with gemcitabine-treated stage IV PDAC. This study explores the effects of phSFRP1 in patients with lower stage PDAC. Methods: Based on a bisulfite treatment process, the promoter region of the SFRP1 gene was analyzed with methylation-specific PCR. Kaplan-Meier curves, log-rank tests, and generalized linear regression analysis were used to assess restricted mean survival time survival at 12 and 24 months. Results: The study included 211 patients with stage I-II PDAC. The median overall survival of patients with phSFRP1 was 13.1 months, compared to 19.6 months in patients with unmethylated SFRP1 (umSFRP1). In adjusted analysis, phSFRP1 was associated with a loss of 1.15 months (95%CI -2.11, -0.20) and 2.71 months (95%CI -2.71, -0.45) of life at 12 and 24 months, respectively. There was no significant effect of phSFRP1 on disease-free or progression-free survival. In stage I-II PDAC, patients with phSFRP1 have worse prognoses than patients with umSFRP1. Discussion: Results could indicate that the poor prognosis may be caused by reduced benefit from adjuvant chemotherapy. SFRP1 may help guide the clinician and be a possible target for epigenetically modifying drugs.

Background: Our previous study has identified variant rs745430558 in the SMAD4 gene promoter as potential biomarker for adenocarcinoma of the pancreas. The allele delTT (10T instead of 12T) was present in malignant pancreatic tissue with a prevalence of 88%. As analysis of cfDNA in liquid biopsy represents a noninvasive approach for the diagnosis and monitoring of malignancies, the aim of this study was to determine the presence of 12T and 10T alleles in the peripheral blood of patients with suspected pancreatic malignancy. Material and Methods: The study was performed using cell-free DNA (cfDNA) isolated from the serum of 15 patients with morphological alterations of the pancreas. The presence of 12T and 10T alleles was assessed by allele specific quantitative real-time PCR. Results: Of 15 analyzed samples, 13 were diagnosed with adenocarcinoma of the pancreas (AcP), 1 with neuroendocrine tumor (NET), and 1 with pancreatitis. The 10T allele was present in 84.7% of cases with AcP and also in the sample from the patient with NET. In patient with pancreatitis only the 12T allele was detected. Conclusion: Our research has shown that the results of liquid biopsy of patients with AcP are in agreement with tissue specimens analysis. Targeted detection of the rs745430558 10T variant in patients with suspected pancreatic malignancies could be a potential biomarker for diagnosis of AcP in the future.

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) elicit potent cell cycle arrest in EGFR-mutant non-small-cell lung cancer (NSCLC) cells. However, little is known about the mechanisms through which these drugs alter the tumor phenotype that contributes to the immune escape of EGFR-mutant cells. Using EGFR-mutant NSCLC cell lines and tissue samples from patients, we investigated the changes in immune checkpoints expressed in tumor cells following EGFR inhibition. Subsequently, we also analyzed the role of soluble factors from the dying tumor cells in the activation of immune signaling pathways involved in therapy resistance. Upon EGFR-TKI treatment, we found that EGFR-mutant cells upregulated the expression of innate immune checkpoint CD24 in vitro. We then analyzed biopsy samples from six patients who developed resistance to a first-generation EGFR-TKI without the acquired T790M mutation. Immunohistochemistry revealed that levels of tumor CD24 expression were increased upon treatment compared with those from pre-treatment samples. Monocyte-derived macrophages facilitated antibody-dependent cellular phagocytosis when EGFR-TKI-treated EGFR-mutant cells were incubated with anti-CD24 antibodies in vitro, suggesting that CD24 may be a therapeutical target for EGFR-mutant lung cancer. Moreover, EGFR inhibition accelerated the release of cell-free DNA (cfDNA) from dying tumor cells, which activated the type I interferon signaling pathways in human THP-1 monocytes in a stimulator of interferon genes-dependent manner. Our study indicates that EGFR inhibition in EGFR-mutant NSCLC cells fosters a tumor microenvironment associated with immune escape. Thus, CD24 targeted therapy and cfDNA monitoring may contribute to improved treatment outcomes in patients with EGFR-mutant NSCLC.

Introduction: Current prognostic blood-based biomarkers for pancreatic adenocarcinoma (PDAC) are limited. Recently, promoter hypermethylation of SFRP1 (phSFRP1) has been linked to poor prognosis in patients with gemcitabine-treated stage IV PDAC. This study explores the effects of phSFRP1 in patients with lower stage PDAC. Methods: Based on a bisulfite treatment process, the promoter region of the SFRP1 gene was analyzed with methylation-specific PCR. Kaplan-Meier curves, log-rank tests, and generalized linear regression analysis were used to assess restricted mean survival time survival at 12 and 24 months. Results: The study included 211 patients with stage I-II PDAC. The median overall survival of patients with phSFRP1 was 13.1 months, compared to 19.6 months in patients with unmethylated SFRP1 (umSFRP1). In adjusted analysis, phSFRP1 was associated with a loss of 1.15 months (95%CI -2.11, -0.20) and 2.71 months (95%CI -2.71, -0.45) of life at 12 and 24 months, respectively. There was no significant effect of phSFRP1 on disease-free or progression-free survival. In stage I-II PDAC, patients with phSFRP1 have worse prognoses than patients with umSFRP1. Discussion: Results could indicate that the poor prognosis may be caused by reduced benefit from adjuvant chemotherapy. SFRP1 may help guide the clinician and be a possible target for epigenetically modifying drugs.

Melanoma is the most malignant of all skin cancers due to its high degree of heterogeneity, hypermutability and environmental susceptibility. It is the third most common cancer diagnosis, and the cause of 80% of skin cancer deaths in the United States. Melanoma is considered a multifactorial disease; common risk factors include ultraviolet radiation, melanocytic nevi, and having a lighter skin tone. There have been various genetic mutations associated with melanoma, such as in the genes encoding BRAF, NF1, NRAS, and p16. These genes are known to play a role in the regulation of cell proliferation and apoptosis. Epigenetic changes, such as aberrant DNA methylation, have also been reported to be involved in the development of melanoma. DNA methylation is a modification that takes place on cytosine nucleotides of CpG islands of DNA. This process suppresses the expression of the methylated gene. Hypermethylation and hypomethylation of tumor suppressor genes and oncogenes, respectively, are known epigenetic hallmarks of melanoma. Notably, aberrant DNA methylation can be detected in peripheral blood. It is known that tumors release fragments of themselves into the bloodstream, such as circulating tumors cells (CTCs), cell free DNA (cfDNA), and exosomes. These fragments can be collected from peripheral blood and provide real-time information regarding tumor status. Therefore, the detection of aberrant cfDNA methylation in plasma sample (liquid biopsy) can serve as a biomarker for the detection of melanoma. This thesis consists of a literature review on melanoma, a discussion on aberrant DNA methylation and its potential to be utilized as a biomarker, as well as liquid biopsy study design for the detection of melanoma.

Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that enter the plasma. Uncontrolled cell death, for example caused by cancer, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA can provide information about an individual's health. This research looks into how to increase the sensitivity of a methylation-based cell type deconvolution method. We do this by adapting an existing method, CelFiE, which uses the methylation values of individual CpG sites to estimate cell type proportions. Our new method, named CelFEER, instead differentiates cell types by the average methylation values of individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions in the genome that are differentially methylated between cell types. This approach compares the methylation values over 500 bp regions instead of at single CpG sites and solely takes hypomethylated regions into account. We show that CelFEER estimates cell type proportions with a higher correlation than CelFiE on simulated mixtures of cfDNA. Moreover, we found that it can find a significant difference between skeletal muscle cfDNA in ALS patients (n=4) and a control group (n=4)., Computer Science

Since the introduction of cell-free (cf) DNA analysis, Non-Invasive Prenatal Testing (NIPT) underwent a deep revolution. Pregnancies at high risk for common fetal aneuploidies can now be easily identified through the analysis of chromosome-derived components found in maternal circulation, with the highest sensitivity and specificity currently available. Consequently, the last decade has witnessed a widespread growth in cfDNA-based NIPT use, enough to be often considered an alternative method to other screening modalities. Nevertheless, the use of NIPT in clinical practice is still not devoid of discordant results. Hereby, we report a case of confined placental mosaicism (CPM) in which a NIPT false-positive result for trisomy 13 required not only amniocentesis but also cordocentesis, to rule out the fetal aneuploidy, with the additional support of molecular cytogenetics on placental DNA at delivery. Relevant aspects allowing for precision genetic diagnosis and counselling, including the number of analysed metaphases on the different fetal cells compartments and a repeated multidisciplinary evaluation, are discussed.

Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that enter the plasma. Uncontrolled cell death, for example caused by cancer, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA can provide information about an individual's health. This research looks into how to increase the sensitivity of a methylation-based cell type deconvolution method. We do this by adapting an existing method, CelFiE, which uses the methylation values of individual CpG sites to estimate cell type proportions. Our new method, named CelFEER, instead differentiates cell types by the average methylation values of individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions in the genome that are differentially methylated between cell types. This approach compares the methylation values over 500 bp regions instead of at single CpG sites and solely takes hypomethylated regions into account. We show that CelFEER estimates cell type proportions with a higher correlation than CelFiE on simulated mixtures of cfDNA. Moreover, we found that it can find a significant difference between skeletal muscle cfDNA in ALS patients (n=4) and a control group (n=4)., Computer Science

Melanoma is the most malignant of all skin cancers due to its high degree of heterogeneity, hypermutability and environmental susceptibility. It is the third most common cancer diagnosis, and the cause of 80% of skin cancer deaths in the United States. Melanoma is considered a multifactorial disease; common risk factors include ultraviolet radiation, melanocytic nevi, and having a lighter skin tone. There have been various genetic mutations associated with melanoma, such as in the genes encoding BRAF, NF1, NRAS, and p16. These genes are known to play a role in the regulation of cell proliferation and apoptosis. Epigenetic changes, such as aberrant DNA methylation, have also been reported to be involved in the development of melanoma. DNA methylation is a modification that takes place on cytosine nucleotides of CpG islands of DNA. This process suppresses the expression of the methylated gene. Hypermethylation and hypomethylation of tumor suppressor genes and oncogenes, respectively, are known epigenetic hallmarks of melanoma. Notably, aberrant DNA methylation can be detected in peripheral blood. It is known that tumors release fragments of themselves into the bloodstream, such as circulating tumors cells (CTCs), cell free DNA (cfDNA), and exosomes. These fragments can be collected from peripheral blood and provide real-time information regarding tumor status. Therefore, the detection of aberrant cfDNA methylation in plasma sample (liquid biopsy) can serve as a biomarker for the detection of melanoma. This thesis consists of a literature review on melanoma, a discussion on aberrant DNA methylation and its potential to be utilized as a biomarker, as well as liquid biopsy study design for the detection of melanoma.

[ES] El cáncer se posiciona como una de las principales causas de muerte a nivel mundial, siendo el cáncer de células renales (CCR) el 8º más frecuente en países desarrollados. A pesar de la mejora en el diagnóstico y manejo, el CCR sigue presentándose como una de las neoplasias urológicas malignas más letales. La falta de biomarcadores no invasivos que representen la heterogeneidad del tumor hace que las líneas de actuación actuales no se utilicen de manera extendida y no sean suficientes para aumentar las tasas de supervivencia. La biopsia líquida y en concreto la orina, es una fuente de biomarcadores de fácil y económica obtención que reúne estas características. En cánceres urológicos, la orina es el biofluido que está en contacto con las células tumorales. En ella, se encuentra el DNA libre circulante (cell-free DNA ¿ cfDNA), que proviene de células no tumorales que mueren principalmente por apoptosis y de células tumorales por necrosis. En la apoptosis se produce una mayor fragmentación del DNA por ser una muerte celular programada, mientras que en el ambiente tumoral la necrosis da lugar a una menor fragmentación. Este diferente grado de fragmentación del DNA da lugar a fragmentos de distintos tamaños que podría emplearse como biomarcador tumoral. Por tanto, el objetivo de este estudio fue evaluar la integridad del cfDNA en orina como biomarcador en CCR. Para ello se empleó una colección de muestras de orina de 57 pacientes con CCR de los tres subtipos principales (38 de células claras, 14 papilares y 5 cromófobos) y 27 controles sanos. De cada paciente se recogieron dos muestras, una previa a la cirugía y otra posterior (entre 1 y 2 años después) mientras que de los controles una única muestra. Tras el aislamiento del cfDNA a partir de orina, se cuantificó mediante PCR cuantitativa en tiempo real el nivel de expresión de un fragmento corto (potencialmente resultante de la apoptosis) y uno largo (potencialmente procedente de la necrosis) de los genes ACTB, AR, [EN] Cancer is one of the leading causes of death worldwide, with renal cell carcinoma (RCC) being the 8th most common cancer in developed countries. Despite improved diagnosis and management, RCC remains one of the most lethal urological malignancies. The absence of non-invasive biomarkers that represent the heterogeneity of the tumour results in the current approaches not being widely used and not being sufficient to increase survival rates. Liquid biopsy and specifically urine, is an easy and inexpensive source of biomarkers that fulfils these requirements. In urological cancers, urine is the biofluid that is in contact with tumour cells. It contains cell free DNA (cfDNA), which comes from non-tumour cells that die mainly by apoptosis and from tumour cells that die mainly by necrosis. In apoptosis, greater DNA fragmentation takes place due to programmed cell death, whereas in the tumour environment, necrosis results in less fragmentation. Consequently, the different degree of DNA fragmentation that originates fragments of different sizes might be used as a tumor biomarker. Hence, the aim of this project was to evaluate the integrity of cfDNA in urine as a biomarker for RCC. For this purpose, a collection of urine samples from 57 RCC patients with the three main subtypes (38 clear cell, 14 papillary and 5 chromophobe) and 27 healthy controls were used. Two samples were collected from each patient, one pre-surgery and one post-surgery (between 1-2 years later) and from the controls only one sample. After isolation of cfDNA from urine, the expression level of a short (potentially resulting from apoptosis) and a long (potentially resulting from necrosis) fragment of the ACTB, AR, BCAS1, MYC and STOX1 genes were quantified by real-time quantitative PCR (qPCR). The ratio of long to short fragments was calculated as a measure of DNA integrity and the differences between the clinic groups were evaluated. Some of the biomarkers studied showed diagnostic and classification

[ES] El cáncer se posiciona como una de las principales causas de muerte a nivel mundial, siendo el cáncer de células renales (CCR) el 8º más frecuente en países desarrollados. A pesar de la mejora en el diagnóstico y manejo, el CCR sigue presentándose como una de las neoplasias urológicas malignas más letales. La falta de biomarcadores no invasivos que representen la heterogeneidad del tumor hace que las líneas de actuación actuales no se utilicen de manera extendida y no sean suficientes para aumentar las tasas de supervivencia. La biopsia líquida y en concreto la orina, es una fuente de biomarcadores de fácil y económica obtención que reúne estas características. En cánceres urológicos, la orina es el biofluido que está en contacto con las células tumorales. En ella, se encuentra el DNA libre circulante (cell-free DNA ¿ cfDNA), que proviene de células no tumorales que mueren principalmente por apoptosis y de células tumorales por necrosis. En la apoptosis se produce una mayor fragmentación del DNA por ser una muerte celular programada, mientras que en el ambiente tumoral la necrosis da lugar a una menor fragmentación. Este diferente grado de fragmentación del DNA da lugar a fragmentos de distintos tamaños que podría emplearse como biomarcador tumoral. Por tanto, el objetivo de este estudio fue evaluar la integridad del cfDNA en orina como biomarcador en CCR. Para ello se empleó una colección de muestras de orina de 57 pacientes con CCR de los tres subtipos principales (38 de células claras, 14 papilares y 5 cromófobos) y 27 controles sanos. De cada paciente se recogieron dos muestras, una previa a la cirugía y otra posterior (entre 1 y 2 años después) mientras que de los controles una única muestra. Tras el aislamiento del cfDNA a partir de orina, se cuantificó mediante PCR cuantitativa en tiempo real el nivel de expresión de un fragmento corto (potencialmente resultante de la apoptosis) y uno largo (potencialmente procedente de la necrosis) de los genes ACTB, AR, [EN] Cancer is one of the leading causes of death worldwide, with renal cell carcinoma (RCC) being the 8th most common cancer in developed countries. Despite improved diagnosis and management, RCC remains one of the most lethal urological malignancies. The absence of non-invasive biomarkers that represent the heterogeneity of the tumour results in the current approaches not being widely used and not being sufficient to increase survival rates. Liquid biopsy and specifically urine, is an easy and inexpensive source of biomarkers that fulfils these requirements. In urological cancers, urine is the biofluid that is in contact with tumour cells. It contains cell free DNA (cfDNA), which comes from non-tumour cells that die mainly by apoptosis and from tumour cells that die mainly by necrosis. In apoptosis, greater DNA fragmentation takes place due to programmed cell death, whereas in the tumour environment, necrosis results in less fragmentation. Consequently, the different degree of DNA fragmentation that originates fragments of different sizes might be used as a tumor biomarker. Hence, the aim of this project was to evaluate the integrity of cfDNA in urine as a biomarker for RCC. For this purpose, a collection of urine samples from 57 RCC patients with the three main subtypes (38 clear cell, 14 papillary and 5 chromophobe) and 27 healthy controls were used. Two samples were collected from each patient, one pre-surgery and one post-surgery (between 1-2 years later) and from the controls only one sample. After isolation of cfDNA from urine, the expression level of a short (potentially resulting from apoptosis) and a long (potentially resulting from necrosis) fragment of the ACTB, AR, BCAS1, MYC and STOX1 genes were quantified by real-time quantitative PCR (qPCR). The ratio of long to short fragments was calculated as a measure of DNA integrity and the differences between the clinic groups were evaluated. Some of the biomarkers studied showed diagnostic and classification

[ES] El cáncer se posiciona como una de las principales causas de muerte a nivel mundial, siendo el cáncer de células renales (CCR) el 8º más frecuente en países desarrollados. A pesar de la mejora en el diagnóstico y manejo, el CCR sigue presentándose como una de las neoplasias urológicas malignas más letales. La falta de biomarcadores no invasivos que representen la heterogeneidad del tumor hace que las líneas de actuación actuales no se utilicen de manera extendida y no sean suficientes para aumentar las tasas de supervivencia. La biopsia líquida y en concreto la orina, es una fuente de biomarcadores de fácil y económica obtención que reúne estas características. En cánceres urológicos, la orina es el biofluido que está en contacto con las células tumorales. En ella, se encuentra el DNA libre circulante (cell-free DNA ¿ cfDNA), que proviene de células no tumorales que mueren principalmente por apoptosis y de células tumorales por necrosis. En la apoptosis se produce una mayor fragmentación del DNA por ser una muerte celular programada, mientras que en el ambiente tumoral la necrosis da lugar a una menor fragmentación. Este diferente grado de fragmentación del DNA da lugar a fragmentos de distintos tamaños que podría emplearse como biomarcador tumoral. Por tanto, el objetivo de este estudio fue evaluar la integridad del cfDNA en orina como biomarcador en CCR. Para ello se empleó una colección de muestras de orina de 57 pacientes con CCR de los tres subtipos principales (38 de células claras, 14 papilares y 5 cromófobos) y 27 controles sanos. De cada paciente se recogieron dos muestras, una previa a la cirugía y otra posterior (entre 1 y 2 años después) mientras que de los controles una única muestra. Tras el aislamiento del cfDNA a partir de orina, se cuantificó mediante PCR cuantitativa en tiempo real el nivel de expresión de un fragmento corto (potencialmente resultante de la apoptosis) y uno largo (potencialmente procedente de la necrosis) de los genes ACTB, AR, [EN] Cancer is one of the leading causes of death worldwide, with renal cell carcinoma (RCC) being the 8th most common cancer in developed countries. Despite improved diagnosis and management, RCC remains one of the most lethal urological malignancies. The absence of non-invasive biomarkers that represent the heterogeneity of the tumour results in the current approaches not being widely used and not being sufficient to increase survival rates. Liquid biopsy and specifically urine, is an easy and inexpensive source of biomarkers that fulfils these requirements. In urological cancers, urine is the biofluid that is in contact with tumour cells. It contains cell free DNA (cfDNA), which comes from non-tumour cells that die mainly by apoptosis and from tumour cells that die mainly by necrosis. In apoptosis, greater DNA fragmentation takes place due to programmed cell death, whereas in the tumour environment, necrosis results in less fragmentation. Consequently, the different degree of DNA fragmentation that originates fragments of different sizes might be used as a tumor biomarker. Hence, the aim of this project was to evaluate the integrity of cfDNA in urine as a biomarker for RCC. For this purpose, a collection of urine samples from 57 RCC patients with the three main subtypes (38 clear cell, 14 papillary and 5 chromophobe) and 27 healthy controls were used. Two samples were collected from each patient, one pre-surgery and one post-surgery (between 1-2 years later) and from the controls only one sample. After isolation of cfDNA from urine, the expression level of a short (potentially resulting from apoptosis) and a long (potentially resulting from necrosis) fragment of the ACTB, AR, BCAS1, MYC and STOX1 genes were quantified by real-time quantitative PCR (qPCR). The ratio of long to short fragments was calculated as a measure of DNA integrity and the differences between the clinic groups were evaluated. Some of the biomarkers studied showed diagnostic and classification

The chapters of this thesis emphasize the importance of characterization of tumor cells or tumor DNA and the role that liquid biopsies can play for this characterization

Over the past decade, substantial developments have been made in the detection of circulating tumor DNA (ctDNA)-cell-free DNA (cfDNA) fragments released into the circulation from tumor cells and displaying the genetic alterations of those cells. As such, ctDNA detected in liquid biopsies serves as a powerful tool for cancer patient stratification, therapy guidance, detection of resistance, and relapse monitoring. In this Review, we describe lung cancer diagnosis and monitoring strategies using ctDNA detection technologies and compile recent evidence regarding lung cancer-related mutation detection in liquid biopsy. We focus not only on epidermal growth factor receptor (EGFR) alterations, but also on significant co-mutations that shed more light on novel ctDNA-based liquid biopsy applications. Finally, we discuss future perspectives of early-cancer detection and clonal hematopoiesis filtering strategies, with possible inclusion of microbiome-driven liquid biopsy. Liquid biopsy can greatly contribute to better detection and management of lung cancer. ctDNA detection in liquid biopsies is a powerful tool for early detection, cancer patient stratification, therapy guidance, detection of resistance, and relapse monitoring. We describe lung cancer diagnosis and monitoring strategies using ctDNA detection technologies and compile recent evidence on the identification of lung cancer-related mutations through liquid biopsy.

In recent years the advent of multi-omic techniques have shown great promise in the field of oncology. In light of these advancements, this thesis focuses on the use of multiple data types to find methylation markers around transcription start site regions for colorectal cancer in the cell-free DNA (cfDNA) domain. It combines several methods of finding these markers, based on publicly available data obtained from solid tissue biopsies. These methods are both based on a single data type, as well as integrating multiple different data types. The resulting selections of methylation markers are then tested for significance on two independent datasets of cfDNA samples. The selections produced are tested on these datasets for their significance in distinguishing colorectal cancer samples from healthy samples. On one of these datasets, the selections are also tested for being differentially methylated between a group of patients with recurring tumors versus non-recurring tumors. The results on these two different datasets vary, showing that the methods of selecting potential methylation markers are capable of doing so on one platform, but that these results cannot be validated on another., Computer Science | Bioinformatics

Background: Paediatric tumours are often characterised by the presence of recurrent DNA copy number alterations (CNAs). These DNA copy number profiles, obtained from a tissue biopsy, can aid in the correct prognostic classification and therapeutic stratification of several paediatric cancer entities (e.g. MYCN amplification in neuroblastoma) and are part of the routine diagnostic practice. Liquid biopsies (LQBs) offer a potentially safer alternative for such invasive tumour tissue biopsies and can provide deeper insight into tumour heterogeneity. Procedure: The robustness and reliability of LQB CNA analyses was evaluated. We performed retrospective CNA profiling using shallow whole-genome sequencing (sWGS) on paired plasma circulating cell-free DNA (cfDNA) and tissue DNA samples from routinely collected samples from paediatric patients (n = 128) representing different tumour entities, including osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, Wilms tumour, brain tumours and neuroblastoma. Results: Overall, we observed a good concordance between CNAs in tissue DNA and cfDNA. The main cause of CNA discordance was found to be low cfDNA sample quality (i.e. the ratio of cfDNA (<700 bp) and high molecular weight DNA (>700 bp)). Furthermore, CNAs were observed that were present in cfDNA and not in tissue DNA, or vice-versa. In neuroblastoma samples, no false-positives or false-negatives were identified for the detection of the prognostic marker MYCN amplification. Conclusion: In future prospective studies, CNA analysis on LQBs that are of sufficient quality can serve as a complementary assay for CNA analysis on tissue biopsies, as either cfDNA or tissue DNA can contain CNAs that cannot be identified in the other biomaterial., SCOPUS: ar.j, info:eu-repo/semantics/published

Pancreatic ductal adenocarcinoma (PDAC) presents many challenges in the clinic and there are many areas for improvement in diagnostics and patient management. The five-year survival rate is around 7.2% as the majority of patients present with advanced disease at diagnosis that is treatment resistant. Approximately 10–15% of PDAC cases have a hereditary basis or Familial Pancreatic Cancer (FPC). Here we demonstrate the use of circulating free DNA (cfDNA) in plasma as a prognostic biomarker in PDAC. The levels of cfDNA correlated with disease status, disease stage, and overall survival. Furthermore, we show for the first time via BEAMing that the majority of hereditary or familial PDAC cases (around 84%) are negative for a KRAS somatic mutation. In addition, KRAS mutation negative cases harbor somatic mutations in potentially druggable genes such as KIT, PDGFR, MET, BRAF, and PIK3CA that could be exploited in the clinic. Finally, familial or hereditary cases have a longer overall survival compared to sporadic cases (10.2 vs. 21.7 months, respectively). Currently, all patients are treated the same in the clinic with cytotoxic agents, although here we demonstrate that there are different subtypes of tumors at the genetic level that could pave the way to personalized treatment.

In recent years the advent of multi-omic techniques have shown great promise in the field of oncology. In light of these advancements, this thesis focuses on the use of multiple data types to find methylation markers around transcription start site regions for colorectal cancer in the cell-free DNA (cfDNA) domain. It combines several methods of finding these markers, based on publicly available data obtained from solid tissue biopsies. These methods are both based on a single data type, as well as integrating multiple different data types. The resulting selections of methylation markers are then tested for significance on two independent datasets of cfDNA samples. The selections produced are tested on these datasets for their significance in distinguishing colorectal cancer samples from healthy samples. On one of these datasets, the selections are also tested for being differentially methylated between a group of patients with recurring tumors versus non-recurring tumors. The results on these two different datasets vary, showing that the methods of selecting potential methylation markers are capable of doing so on one platform, but that these results cannot be validated on another., Computer Science | Bioinformatics

Background: Disease progression and therapeutic resistance are hallmarks of advanced stage prostate cancer (PCa), which remains a major cause of cancer-related mortality around the world. Longitudinal studies, coupled with the use of liquid biopsies, offer a potentially new and minimally invasive platform to study the dynamics of tumour progression. Our aim was to investigate the dynamics of personal DNA methylomic profiles of metastatic PCa (mPCa) patients, during disease progression and therapy administration. Results: Forty-eight plasma samples from 9 mPCa patients were collected, longitudinally, over 13–21 months. After circulating cell-free DNA (cfDNA) isolation, DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The top 5% most variable probes across time, within each individual, were utilised to study dynamic methylation patterns during disease progression and therapeutic response. Statistical testing was carried out to identify differentially methylated genes (DMGs) in cfDNA, which were subsequently validated in two independent mPCa (cfDNA and FFPE tissue) cohorts. Individual cfDNA global methylation patterns were temporally stable throughout the disease course. However, a proportion of CpG sites presented a dynamic temporal pattern that was consistent with clinical events, including different therapies, and were prominently associated with genes linked to immune response pathways. Additionally, study of the tumour fraction of cfDNA identified > 2000 DMGs with dynamic methylation patterns. Conclusions: Longitudinal assessment of cfDNA methylation in mPCa patients unveiled dynamic patterns associated with disease progression and therapy administration, thus highlighting the potential of using liquid biopsies to study PCa evolution at a methylomic level. [Figure not available: see fulltext.]

Background: Disease progression and therapeutic resistance are hallmarks of advanced stage prostate cancer (PCa), which remains a major cause of cancer-related mortality around the world. Longitudinal studies, coupled with the use of liquid biopsies, offer a potentially new and minimally invasive platform to study the dynamics of tumour progression. Our aim was to investigate the dynamics of personal DNA methylomic profiles of metastatic PCa (mPCa) patients, during disease progression and therapy administration. Results: Forty-eight plasma samples from 9 mPCa patients were collected, longitudinally, over 13–21 months. After circulating cell-free DNA (cfDNA) isolation, DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The top 5% most variable probes across time, within each individual, were utilised to study dynamic methylation patterns during disease progression and therapeutic response. Statistical testing was carried out to identify differentially methylated genes (DMGs) in cfDNA, which were subsequently validated in two independent mPCa (cfDNA and FFPE tissue) cohorts. Individual cfDNA global methylation patterns were temporally stable throughout the disease course. However, a proportion of CpG sites presented a dynamic temporal pattern that was consistent with clinical events, including different therapies, and were prominently associated with genes linked to immune response pathways. Additionally, study of the tumour fraction of cfDNA identified > 2000 DMGs with dynamic methylation patterns. Conclusions: Longitudinal assessment of cfDNA methylation in mPCa patients unveiled dynamic patterns associated with disease progression and therapy administration, thus highlighting the potential of using liquid biopsies to study PCa evolution at a methylomic level. [Figure not available: see fulltext.]

Cancer is the common name to a group of biologically diverse malignant neoplastic diseases. Approximately 18 million people are diagnosed with cancer annually and 8.8 million patients die from it. Tumorigenesis and progression of cancer are driven by alterations in the cancer cell genome. These alterations lead to gain of oncogenic functions, loss of tumor suppressor functions, or may be chromosomal rearrangements without obvious function, and these alterations themselves can serve as tumor-specific biomarkers that may have diagnostic and clinical utility.In this thesis, we investigated oncogenic and tumor suppressive genes in breast cancers and leukemias, with a focus on the PTEN/PIK3CA pathway as well as minimally-invasive monitoring of cancer patients using “liquid biopsies.” We studied the underlying mechanism of PTEN protein loss in breast cancer, and showed how various types of tumor-specific mutations, including those in PIK3CA, can be used as biomarkers to monitor the dynamics of occult tumor burden, evaluate the degree of tumor content dissemination into the bloodstream with mammographic compression, and detect minimal residual disease in breast cancer and acute myeloid leukemia.In Paper I, we found that the frequent loss of PTEN protein in human breast cancer is not attributable to the overexpression of the E3 ubiquitin ligase NEDD4, and thus NEDD4 is unlikely to be a regulator of the oncogenic PI3K/PTEN signaling pathway. In Paper II, we showed that serial monitoring of tumor specific chromosomal rearrangements, identified with low coverage whole genome sequencing and then measured in blood samples by digital PCR (dPCR), is a highly sensitive and specific approach to detect occult breast cancer disease prior to the onset of symptoms and clinical detection. Detected plasma ctDNA level was a quantitative predictor of poor relapse-free and overall survival. In Paper III, we confirmed the general safety of mammography, using FDA approved CellSearch® and our u

Early cancer detection and localization using cell-free DNA (cfDNA) faces multiple challenges, including the low fraction of tumor DNA in cfDNA and the molecular heterogeneity of cancer. Many features have been used to detect cancer in cfDNA, such as fragment length profiles, copy number changes, and microbial composition, but methylation in particular has been found to detect cancer early. Additionally, the tissue specificity of methylation has aided noninvasive cancer typing efforts. Typically, cfDNA methylation profiling is done through whole genome bisulfite sequencing (WGBS) or targeted approaches, but these protocols are plagued by high cost or require prior knowledge of informative regions. Another procedure, reduced representation bisulfite sequencing (RRBS), strikes a balance between these two extremes, but is only applicable to intact genomic DNA, not naturally fragmented cfDNA. Herein, we develop an integrated cancer detection and typing system, CancerRadar, that addresses these challenges. First, we present a novel protocol, cell-free Methylation Sequencing (cfMethylSeq), which adapts the RRBS protocol to be applicable to cfDNA. We show cfMethylSeq yields more than 12-fold enrichment over WGBS in CpG islands while reliably and reproducibly quantifying methylation and capturing broad, genome-wide signals. Next, we develop a computational platform to extract information from cfMethylSeq data and diagnose the patient. The platform derives cfDNA methylation, cfDNA fragment sizes, copy number changes, and microbial composition from the raw cfMethylSeq data, and performs multi-feature ensemble learning.We demonstrate the power of CancerRadar in detecting and locating cancer in a cohort of 275 colon, liver, lung, and stomach cancer patients and 204 non-cancer individuals. For cancer detection, we achieved a sensitivity of 89.1% at 97% specificity in the independent validation set. For cancer typing, we achieved an accuracy of 91.5% in the independent validation

Although epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are the preferred treatment for patients with EGFR-mutated non-small cell lung cancer (NSCLC), not all patients benefit. We therefore explored the impact of the presence of mutations found in cell-free DNA (cfDNA) and TKI plasma concentrations during treatment on progression-free survival (PFS). In the prospective START-TKI study blood samples from 41 patients with EGFR-mutated NSCLC treated with EGFR-TKIs were available. Next generation sequencing (NGS) on cfDNA was performed, and plasma TKI concentrations were measured. Patients without complete plasma conversion of EGFR mutation at week 6 had a significantly shorter PFS (5.5 vs. 17.0 months, p = 0.002) and OS (14.0 vs. 25.5 months, p = 0.003) compared to patients with plasma conversion. In thirteen (second line) osimertinib-treated patients with a (plasma or tissue) concomitant TP53 mutation at baseline, PFS was significantly shorter compared to six wild-type cases; 8.8 vs. 18.8 months, p = 0.017. Erlotinib Cmean decreas

Early cancer detection and localization using cell-free DNA (cfDNA) faces multiple challenges, including the low fraction of tumor DNA in cfDNA and the molecular heterogeneity of cancer. Many features have been used to detect cancer in cfDNA, such as fragment length profiles, copy number changes, and microbial composition, but methylation in particular has been found to detect cancer early. Additionally, the tissue specificity of methylation has aided noninvasive cancer typing efforts. Typically, cfDNA methylation profiling is done through whole genome bisulfite sequencing (WGBS) or targeted approaches, but these protocols are plagued by high cost or require prior knowledge of informative regions. Another procedure, reduced representation bisulfite sequencing (RRBS), strikes a balance between these two extremes, but is only applicable to intact genomic DNA, not naturally fragmented cfDNA. Herein, we develop an integrated cancer detection and typing system, CancerRadar, that addresses these challenges. First, we present a novel protocol, cell-free Methylation Sequencing (cfMethylSeq), which adapts the RRBS protocol to be applicable to cfDNA. We show cfMethylSeq yields more than 12-fold enrichment over WGBS in CpG islands while reliably and reproducibly quantifying methylation and capturing broad, genome-wide signals. Next, we develop a computational platform to extract information from cfMethylSeq data and diagnose the patient. The platform derives cfDNA methylation, cfDNA fragment sizes, copy number changes, and microbial composition from the raw cfMethylSeq data, and performs multi-feature ensemble learning.We demonstrate the power of CancerRadar in detecting and locating cancer in a cohort of 275 colon, liver, lung, and stomach cancer patients and 204 non-cancer individuals. For cancer detection, we achieved a sensitivity of 89.1% at 97% specificity in the independent validation set. For cancer typing, we achieved an accuracy of 91.5% in the independent validation

Introduction: Blood-based, cancer-associated biomarkers are susceptible to a variety of well-known preanalytical factors. The influence of bowel preparation before a diagnostic colonoscopy on biomarker levels is, however, poorly investigated. The present study assessed the influence of bowel preparation on colorectal cancer-associated biomarkers. In addition, the effect of single versus double centrifugation of plasma biomarkers was assessed. Methods: Blood samples were collected pre- and post-bowel preparation from 125 subjects scheduled for first time diagnostic colonoscopy due to symptoms attributable to CRC. The samples were separated into serum and EDTA plasma, and analyzed by four independent collaborators for: 1) the proteins AFP, CA19-9, CEA, hs-CRP, CyFra21-1, Ferritin, Galectin-3 and TIMP-1, 2) the proteins BAG4, IL6ST, vWF, CD44 and EGFR, 3) the glycoprotein Galectin-3 ligand, and 4) cell-free DNA (cfDNA). Statistical analysis of biomarker data has been performed using mixed modelling, including repeated measures. Results: The biomarkers generally showed negligible variation between pre- and post-bowel preparation except for CyFra21-1, Ferritin, BAG4 and cfDNA. CyFra21-1 levels were systematically reduced with 29% (95% CI 21–36%) by bowel preparation (p ≤ 0.0001). Ferritin was not significantly different between pre- and post-bowel preparation (p = 0.07), however the estimated difference (increase) was 18%. BAG4 was systematically reduced by 12% (95% CI 1–22%, p = 0.04), while cfDNA showed a significant increase of 28% (95% CI 17–39%, p < 0.0001). Double centrifugation compared to single centrifugation showed reduced vWF (ratio 0.86, p ≤ 0.0001) and CD44 (ratio 0.85, p = 0.016), but increased IL6ST levels (ratio 1.18, p = 0.014). Conclusions: Results of the present study demonstrated systematic, statistically significant differences between pre-bowel and post-bowel preparation levels for three independent blood-based biomarkers (BAG4, CyFra21-1, cfD

Les anomalies chromosomiques sont une cause majeure de morbidité et de mortalité périnatales. Le dépistage de ces affections a toujours été crucial pour une prise en charge optimale des femmes enceintes.Initialement, le dépistage de trisomie 21 était uniquement basé selon le risque lié à l’âge maternel. L’ajout de différents marqueurs biochimiques sériques constituant successivement les double, triple et quadruple tests a pu améliorer le taux de détection. Néanmoins, c’est en 1997 qu’apparaît un point tournant de l’histoire de dépistage des trisomies :l’introduction de la mesure de la clarté nucale à l’échographie du premier trimestre.Depuis 2011, de nouvelles recherches se sont concentrées sur le dépistage prénatal non invasif (DPNI) utilisant l'ADN fœtal libre circulant dans le sang maternel. Cette technique a suggéré directement une supériorité marquée pour la détection de la trisomie 21 comparée à toutes les autres méthodes de dépistage connues. Rapidement, ce test a été introduit en pratique clinique dans le monde entier sans une évaluation préalable et approfondie, que ce soit au niveau scientifique, technique ou éthique.Les objectifs de cette thèse étaient de fournir des réponses aux diverses questions persistantes concernant l’utilisation clinique des tests de dépistages basés sur ADN fœtal libre dans la circulation maternelle.À notre connaissance, nous sommes la première équipe à essayer d'évaluer le taux d'échec et la performance du DPNI effectué par différents laboratoires utilisant différentes méthodes analytiques. Nous avons démontré que les approches « DANSR » (approche ciblée sur les chromosomes d’intérêt) et « GW-MPS » (approche globale sur les séquences géniques reparties sur la totalité du génome par un séquençage à haut débit) offraient toutes les deux un taux échec bas avec une bonne performance dans la détection des trisomies 21, 13 et 18. Cependant, le niveau de fraction fœtale semble varier d'un laboratoire à l'autre et n’est, par conséquent, Doctorat en Sciences médicales (Médecine), info:eu-repo/semantics/nonPublished

The current standard of care measures for kidney function, proteinuria, and serum creatinine (SCr) are poor predictors of early-stage kidney disease. Measures that can detect chronic kidney disease in its earlier stages are needed to enable therapeutic intervention and reduce adverse outcomes of chronic kidney disease. We have developed the Kidney Injury Test (KIT) and a novel KIT Score based on the composite measurement and validation of multiple biomarkers across a unique set of 397 urine samples. The test is performed on urine samples that require no processing at the site of collection and without target sequencing or amplification. We sought to verify that the pre-defined KIT test, KIT Score, and clinical thresholds correlate with established chronic kidney disease (CKD) and may provide predictive information on early kidney injury status above and beyond proteinuria and renal function measurements alone. Statistical analyses across six DNA, protein, and metabolite markers were performed on a subset of residual spot urine samples with CKD that met assay performance quality controls from patients attending the clinical labs at the University of California, San Francisco (UCSF) as part of an ongoing IRB-approved prospective study. Inclusion criteria included selection of patients with confirmed CKD and normal healthy controls; exclusion criteria included incomplete or missing information for sample classification, logistical delays in transport/processing of urine samples or low sample volume, and acute kidney injury. Multivariate logistic regression of kidney injury status and likelihood ratio statistics were used to assess the contribution of the KIT Score for prediction of kidney injury status and stage of CKD as well as assess the potential contribution of the KIT Score for detection of early-stage CKD above and beyond traditional measures of renal function. Urine samples were processed by a proprietary immunoprobe for measuring cell-free DNA (cfDNA), methyla

Standard methods for detecting chronic lung allograft dysfunction (CLAD) and rejection have poor sensitivity and specificity and have conventionally required bronchoscopies and biopsies. Plasma cell-free DNA (cfDNA) has been shown to be increased in various types of allograft injury in transplant recipients and CXCL10 has been reported to be increased in the lung tissue of patients undergoing CLAD. This study used a novel cfDNA and CXCL10 assay to evaluate the noninvasive assessment of CLAD phenotype and prediction of survival from bronchoalveolar lavage (BAL) fluid. A total of 60 BAL samples (20 with bronchiolitis obliterans (BOS), 20 with restrictive allograft syndrome (RAS), and 20 with stable allografts (STA)) were collected from 60 unique lung transplant patients; cfDNA and CXCL10 were measured by the ELISA-based KIT assay. Median cfDNA was significantly higher in BOS patients (6739 genomic equivalents (GE)/mL) versus STA (2920 GE/mL) and RAS (4174 GE/mL) (p < 0.01 all comparisons). Likelihood ratio tests revealed a significant association of overall survival with cfDNA (p = 0.0083), CXCL10 (p = 0.0146), and the interaction of cfDNA and CXCL10 (p = 0.023) based on multivariate Cox proportional hazards regression. Dichotomizing patients based on the median cfDNA level controlled for the mean level of CXCL10 revealed an over two-fold longer median overall survival time in patients with low levels of cfDNA. The KIT assay could predict allograft survival with superior performance compared with traditional biomarkers. These data support the pursuit of larger prospective studies to evaluate the predictive performance of cfDNA and CXCL10 prior to lung allograft failure.

A state of genetic chimerism is created by allogenic transplantation, the quality and quantity of which may have diagnostic significance. The monitoring of cellular macrochimerism following allogeneic hematopoietic cell transplantation (HCT) is standard of care. It provides an assessment of engraftment, prognostic information, and guides therapeutic interventions. Separately, the discovery of cell-free DNA (cfDNA) chimerism following solid organ transplantation has raised the possibility that increases in donor genotype graft-derived cfDNA may be biomarker for rejection. As a result of these and other developments, the clinical and research requirements for chimerism analysis in the transplantation context exceeds the capabilities offered by existing methodologies. To address this, a panel of 39 droplet digital PCR (ddPCR) assays was developed. These targeted highly polymorphic copy number variation (CNV) loci strategically selected using a population genomics approach to maximise the probability of a donor one copy, recipient zero copy genotype combination (and vice versa). These informative combinations create a negative background against which absolute quantification of the one copy genotype can be performed using ddPCR. Analytical validation of the developed chimerism analysis method for absolute quantification of cfDNA was performed. All studied assays performed linearly across the range <6-1280 copies/mL. Limit of blank was 0 copies/mL, limit of detection was 6 copies/mL, and limit of quantification was 8 copies/mL. A method for genotyping donor and recipient informative CNV loci from chimeric cfDNA was developed and conceptually validated using donor and recipient genomic DNA. The developed chimerism analysis method was used to evaluate the diagnostic validity of absolute measurements of plasma graft-derived cfDNA and total cfDNA, as well as the relative measure of graft fraction, for the diagnosis of kidney transplant (KT) rejection. 61 indication biopsy-ma

The current standard of care measures for kidney function, proteinuria, and serum creatinine (SCr) are poor predictors of early-stage kidney disease. Measures that can detect chronic kidney disease in its earlier stages are needed to enable therapeutic intervention and reduce adverse outcomes of chronic kidney disease. We have developed the Kidney Injury Test (KIT) and a novel KIT Score based on the composite measurement and validation of multiple biomarkers across a unique set of 397 urine samples. The test is performed on urine samples that require no processing at the site of collection and without target sequencing or amplification. We sought to verify that the pre-defined KIT test, KIT Score, and clinical thresholds correlate with established chronic kidney disease (CKD) and may provide predictive information on early kidney injury status above and beyond proteinuria and renal function measurements alone. Statistical analyses across six DNA, protein, and metabolite markers were performed on a subset of residual spot urine samples with CKD that met assay performance quality controls from patients attending the clinical labs at the University of California, San Francisco (UCSF) as part of an ongoing IRB-approved prospective study. Inclusion criteria included selection of patients with confirmed CKD and normal healthy controls; exclusion criteria included incomplete or missing information for sample classification, logistical delays in transport/processing of urine samples or low sample volume, and acute kidney injury. Multivariate logistic regression of kidney injury status and likelihood ratio statistics were used to assess the contribution of the KIT Score for prediction of kidney injury status and stage of CKD as well as assess the potential contribution of the KIT Score for detection of early-stage CKD above and beyond traditional measures of renal function. Urine samples were processed by a proprietary immunoprobe for measuring cell-free DNA (cfDNA), methyla

Standard methods for detecting chronic lung allograft dysfunction (CLAD) and rejection have poor sensitivity and specificity and have conventionally required bronchoscopies and biopsies. Plasma cell-free DNA (cfDNA) has been shown to be increased in various types of allograft injury in transplant recipients and CXCL10 has been reported to be increased in the lung tissue of patients undergoing CLAD. This study used a novel cfDNA and CXCL10 assay to evaluate the noninvasive assessment of CLAD phenotype and prediction of survival from bronchoalveolar lavage (BAL) fluid. A total of 60 BAL samples (20 with bronchiolitis obliterans (BOS), 20 with restrictive allograft syndrome (RAS), and 20 with stable allografts (STA)) were collected from 60 unique lung transplant patients; cfDNA and CXCL10 were measured by the ELISA-based KIT assay. Median cfDNA was significantly higher in BOS patients (6739 genomic equivalents (GE)/mL) versus STA (2920 GE/mL) and RAS (4174 GE/mL) (p < 0.01 all comparisons). Likelihood ratio tests revealed a significant association of overall survival with cfDNA (p = 0.0083), CXCL10 (p = 0.0146), and the interaction of cfDNA and CXCL10 (p = 0.023) based on multivariate Cox proportional hazards regression. Dichotomizing patients based on the median cfDNA level controlled for the mean level of CXCL10 revealed an over two-fold longer median overall survival time in patients with low levels of cfDNA. The KIT assay could predict allograft survival with superior performance compared with traditional biomarkers. These data support the pursuit of larger prospective studies to evaluate the predictive performance of cfDNA and CXCL10 prior to lung allograft failure.

BackgroundWe analyzed clinical associations of MET alterations in the plasma of patients with diverse malignancies.MethodsDigital sequencing of circulating tumor DNA (ctDNA) (54-70 genes) was performed in 438 patients; 263 patients also had tissue sequencing (182-315 genes). The most represented tumor types were gastrointestinal (28.1%), brain (24.9%), and lung (23.2%). Most patients (71.2%) had recurrent/metastatic disease.ResultsMET alterations were observed in 31 patients (7.1%) and correlated with bone metastasis (P = 0.007), with TP53 (P = 0.001) and PTEN (P = 0.003) abnormalities, and with an increased number of alterations (median, 4 vs 1, P = 0.001) (all multivariable analyses). Patients with MET alterations demonstrated a significantly shorter median time to metastasis/recurrence (1.0 vs 10.4 months, P = 0.044, multivariable) and a poorer survival (30.6 vs 58.4 months, P = 0.013, univariate only). Of the 31 patients with MET alterations, 18 also had tissue testing; only two also had tissue MET alterations (11.1%); MET alterations were detected at a lower frequency in tissue (1.14%) compared to ctDNA (7.1%), with P = 0.0002.ConclusionsIn conclusion, the detection of MET alterations by liquid biopsy is feasible. MET ctDNA alterations were associated with a poorer prognosis, higher numbers of genomic abnormalities, and bone metastases. The correlation with bone metastases may explain the higher frequency of MET alterations in blood ctDNA than in tissue (since bones are rarely biopsied) and the previous observations of bone-predominant responses to MET inhibitors. The high number of co-altered genes suggests that MET inhibitors may need to be combined with other agents to induce/optimize responses.

Standard noninvasive methods for detecting renal allograft rejection and injury have poor sensitivity and specificity. Plasma donor-derived cell-free DNA (dd-cfDNA) has been reported to accurately detect allograft rejection and injury in transplant recipients and shown to discriminate rejection from stable organ function in kidney transplant recipients. This study used a novel single nucleotide polymorphism (SNP)-based massively multiplexed PCR (mmPCR) methodology to measure dd-cfDNA in various types of renal transplant recipients for the detection of allograft rejection/injury without prior knowledge of donor genotypes. A total of 300 plasma samples (217 biopsy-matched: 38 with active rejection (AR), 72 borderline rejection (BL), 82 with stable allografts (STA), and 25 with other injury (OI)) were collected from 193 unique renal transplant patients; dd- cfDNA was processed by mmPCR targeting 13,392 SNPs. Median dd-cfDNA was significantly higher in samples with biopsy-proven AR (2.3%) versus BL (0.6%), OI (0.7%), and STA (0.4%) (p < 0.0001 all comparisons). The SNP-based dd-cfDNA assay discriminated active from non-rejection status with an area under the curve (AUC) of 0.87, 88.7% sensitivity (95% CI, 77.7⁻99.8%) and 72.6% specificity (95% CI, 65.4⁻79.8%) at a prespecified cutoff (>1% dd-cfDNA). Of 13 patients with AR findings at a routine protocol biopsy six-months post transplantation, 12 (92%) were detected positive by dd-cfDNA. This SNP-based dd-cfDNA assay detected allograft rejection with superior performance compared with the current standard of care. These data support the feasibility of using this assay to detect disease prior to renal failure and optimize patient management in the case of allograft injury.

Genomics is expected to soon overtake astronomy, particle physics, and even YouTube as the biggest creator of digital information (1). Analysis of this information has already led to important and ground breaking discoveries relevant to our health, but ongoing work will require creative solutions to the multitude of challenges arising from this volume of data. Practically speaking, one such challenge comes from determining what data should be collected and how it is to be managed. As cohort sizes in population based studies grow into the hundreds of thousands, practical issues about collection, storage, and filtering have begun to come more into focus. Additionally, frameworks that seamlessly integrate disparate datasets and also allow for flexible analysis will be required. Finally, as technical challenges and limitations arise, new analytical approaches and designs will have to be considered. This dissertation work was comprised of three projects relating to these questions as approached from the perspective of a bioinformatician. These projects describe the development of new software and methods for sample management, data integration and analysis, and design strategies to improve signal in noisy data. The first chapter of this dissertation consists of background material relating to the projects, including a description about the state of prostate cancer genomics, the development of biomarkers for its detection, and an exploration of a promising new biomarker, cell-free DNA (cfDNA). It also includes a discussion about some of the overarching questions of my PhD. The second chapter describes a web based sample management system, called Samasy. Born out of necessity, this tool addresses a very practical issue of sample subsetting that is often required of resequencing studies. Samasy was used to facilitate the selection of 16,600 samples from a much larger cohort of 54,000 while preserving ethnicity and age balance among cases and controls. This tool integrates w

Breast cancer is the most common type of cancer in women and second most common cancer worldwide. Most breast cancers are ER-positive (75-80%), for which anti-hormonal therapy is used. For ER-positive metastatic breast cancer (MBC), the objective response rate to anti-hormonal treatment is only 20-40%. This shows an urgent need for biomarkers which can identify patients who will or will not benefit from the therapy. As such, for those patients, unnecessary exposure to undesirable adverse events of (anti-hormonal) therapy can be avoided. Therefore, the aim of this thesis was to find biomarkers able to predict anti-hormonal treatment responsiveness or resistance in mainly advanced ER-positive breast cancer patients. To reach this goal different research approaches were followed. Since mutations in PIK3CA are the most prevalent mutations (up to 45%) in ER-positive breast cancers, the thesis was mainly focused on the relationship between PIK3CA genotype and PI3K pathway with treatment outcome. It was shown that PIK3CA mutations detected in primary breast tumors have a predictive value for aromatase inhibitors (AI) response in the advanced disease setting, but not for tamoxifen response nor for prognosis. Related to the PIK3CA genotype, it was demonstrated that high expression of LRG1 can be used as biomarker for AI treatment response, which upon neo-adjuvant AI therapy showed decreased levels in patients with clinical response. At the proteomic level, high MAPK1/3 phosphorylation levels in luminal breast cancer was shown to be related with PIK3CA exon specific mutations. This MAPK1/3 phosphorylation, especially when localized in the nuclei, has prognostic value in breast cancer. In an alternative approach, using ER-positive breast cancers with an inflammatory breast cancer phenotype, a metagene was constructed. This metagene, ABAT and STC2 were not prognostic. However, decreased expression of ABAT and STC2 were shown to be predictive for tamoxifen resistance in MBC. In