External Quality Assessment on Molecular Tumor Profiling with Circulating Tumor DNA-Based Methodologies Routinely Used in Clinical Pathology within the COIN Consortium.

BACKGROUND: Identification of tumor-derived variants in circulating tumor DNA (ctDNA) has potential as a sensitive and reliable surrogate for tumor tissue-based routine diagnostic testing. However, variations in pre(analytical) procedures affect the efficiency of ctDNA recovery. Here, an external quality assessment (EQA) was performed to determine the performance of ctDNA mutation detection work flows that are used in current diagnostic settings across laboratories within the Dutch COIN consortium (ctDNA on the road to implementation in The Netherlands). METHODS: Aliquots of 3 high-volume diagnostic leukapheresis (DLA) plasma samples and 3 artificial reference plasma samples with predetermined mutations were distributed among 16 Dutch laboratories. Participating laboratories were requested to perform ctDNA analysis for BRAF exon 15, EGFR exon 18-21, and KRAS exon 2-3 using their regular circulating cell-free DNA (ccfDNA) analysis work flow. Laboratories were assessed based on adherence to the study protocol, overall detection rate, and overall genotyping performance. RESULTS: A broad range of preanalytical conditions (e.g., plasma volume, elution volume, and extraction methods) and analytical methodologies (e.g., droplet digital PCR [ddPCR], small-panel PCR assays, and next-generation sequencing [NGS]) were used. Six laboratories (38%) had a performance score of >0.90; all other laboratories scored between 0.26 and 0.80. Although 13 laboratories (81%) reached a 100% overall detection rate, the therapeutically relevant EGFR p.(S752_I759del) (69%), EGFR p.(N771_H773dup) (50%), and KRAS p.(G12C) (48%) mutations were frequently not genotyped accurately. CONCLUSIONS: Divergent (pre)analytical protocols could lead to discrepant clinical outcomes when using the same plasma samples. Standardization of (pre)analytical work flows can facilitate the implementation of reproducible liquid biopsy testing in the clinical routine.

Detection of circulating tumour DNA after neoadjuvant chemoradiotherapy in patients with locally advanced oesophageal cancer.

Active surveillance instead of standard surgery after neoadjuvant chemoradiotherapy (nCRT) has been proposed for patients with oesophageal cancer. Circulating tumour DNA (ctDNA) may be used to facilitate selection of patients for surgery. We show that detection of ctDNA after nCRT seems highly suggestive of major residual disease. Tumour biopsies and blood samples were taken before, and 6 and 12 weeks after, nCRT. Biopsies were analysed with regular targeted next-generation sequencing (NGS). Circulating cell-free DNA (cfDNA) was analysed using targeted NGS with unique molecular identifiers and digital polymerase chain reaction. cfDNA mutations matching pre-treatment biopsy mutations confirmed the presence of ctDNA. In total, 31 patients were included, of whom 24 had a biopsy mutation that was potentially detectable in cfDNA (77%). Pre-treatment ctDNA was detected in nine of 24 patients (38%), four of whom had incurable disease progression before surgery. Pre-treatment ctDNA detection had a sensitivity of 47% (95% CI 24-71) (8/17), specificity of 85% (95% CI 42-99) (6/7), positive predictive value (PPV) of 89% (95% CI 51-99) (8/9), and negative predictive value (NPV) of 40% (95% CI 17-67) (6/15) for detecting major residual disease (>10% residue in the resection specimen or progression before surgery). After nCRT, ctDNA was detected in three patients, two of whom had disease progression. Post-nCRT ctDNA detection had a sensitivity of 21% (95% CI 6-51) (3/14), specificity of 100% (95% CI 56-100) (7/7), PPV of 100% (95% CI 31-100) (3/3), and NPV of 39% (95% CI 18-64) (7/18) for detecting major residual disease. The addition of ctDNA to the current set of diagnostics did not lead to more patients being clinically identified with residual disease. These results indicate that pre-treatment and post-nCRT ctDNA detection may be useful in identifying patients at high risk of disease progression. The addition of ctDNA analysis to the current set of diagnostic modalities may not improve detection of residual disease after nCRT. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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 < 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.

Dutch National Round Robin Trial on Plasma-Derived Circulating Cell-Free DNA Extraction Methods Routinely Used in Clinical Pathology for Molecular Tumor Profiling.

BACKGROUND: Efficient recovery of circulating tumor DNA (ctDNA) depends on the quantity and quality of circulating cell-free DNA (ccfDNA). Here, we evaluated whether various ccfDNA extraction methods routinely applied in Dutch laboratories affect ccfDNA yield, ccfDNA integrity, and mutant ctDNA detection, using identical lung cancer patient-derived plasma samples. METHODS: Aliquots of 4 high-volume diagnostic leukapheresis plasma samples and one artificial reference plasma sample with predetermined tumor-derived mutations were distributed among 14 Dutch laboratories. Extractions of ccfDNA were performed according to local routine standard operating procedures and were analyzed at a central reference laboratory for mutant detection and assessment of ccfDNA quantity and integrity. RESULTS: Mutant molecule levels in extracted ccfDNA samples varied considerably between laboratories, but there was no indication of consistent above or below average performance. Compared to silica membrane-based methods, samples extracted with magnetic beads-based kits revealed an overall lower total ccfDNA yield (-29%; P < 0.0001) and recovered fewer mutant molecules (-41%; P < 0.01). The variant allelic frequency and sample integrity were similar. In samples with a higher-than-average total ccfDNA yield, an augmented recovery of mutant molecules was observed. CONCLUSIONS: In the Netherlands, we encountered diversity in preanalytical workflows with potential consequences on mutant ctDNA detection in clinical practice. Silica membrane-based methodologies resulted in the highest total ccfDNA yield and are therefore preferred to detect low copy numbers of relevant mutations. Harmonization of the extraction workflow for accurate quantification and sensitive detection is required to prevent introduction of technical divergence in the preanalytical phase and reduce interlaboratory discrepancies.

The prognostic and predictive value of ESR1 fusion gene transcripts in primary breast cancer.

BACKGROUND: In breast cancer (BC), recurrent fusion genes of estrogen receptor alpha (ESR1) and AKAP12, ARMT1 and CCDC170 have been reported. In these gene fusions the ligand binding domain of ESR1 has been replaced by the transactivation domain of the fusion partner constitutively activating the receptor. As a result, these gene fusions can drive tumor growth hormone independently as been shown in preclinical models, but the clinical value of these fusions have not been reported. Here, we studied the prognostic and predictive value of different frequently reported ESR1 fusion transcripts in primary BC. METHODS: We evaluated 732 patients with primary BC (131 ESR1-negative and 601 ESR1-positive cases), including two ER-positive BC patient cohorts: one cohort of 322 patients with advanced disease who received first-line endocrine therapy (ET) (predictive cohort), and a second cohort of 279 patients with lymph node negative disease (LNN) who received no adjuvant systemic treatment (prognostic cohort). Fusion gene transcript levels were measured by reverse transcriptase quantitative PCR. The presence of the different fusion transcripts was associated, in uni- and multivariable Cox regression analysis taking along current clinico-pathological characteristics, to progression free survival (PFS) during first-line endocrine therapy in the predictive cohort, and disease- free survival (DFS) and overall survival (OS) in the prognostic cohort. RESULTS: The ESR1-CCDC170 fusion transcript was present in 27.6% of the ESR1-positive BC subjects and in 2.3% of the ESR1-negative cases. In the predictive cohort, none of the fusion transcripts were associated with response to first-line ET. In the prognostic cohort, the median DFS and OS were respectively 37 and 93 months for patients with an ESR1-CCDC170 exon 8 gene fusion transcript and respectively 91 and 212 months for patients without this fusion transcript. In a multivariable analysis, this ESR1-CCDC170 fusion transcript was an independent prognostic factor for DFS (HR) (95% confidence interval (CI): 1.8 (1.2-2.8), P = 0.005) and OS (HR (95% CI: 1.7 (1.1-2.7), P = 0.023). CONCLUSIONS: Our study shows that in primary BC only ESR1-CCDC170 exon 8 gene fusion transcript carries prognostic value. None of the ESR1 fusion transcripts, which are considered to have constitutive ER activity, was predictive for outcome in BC with advanced disease treated with endocrine treatment.

Establishment of the Dutch Nationwide, Interdisciplinary Infrastructure and Biobank for Fundamental and Translational Ovarian Cancer Research: Archipelago of Ovarian Cancer Research.

OBJECTIVES: Ovarian cancer has the worst overall survival rate of all gynecologic malignancies. For the majority of patients, the 5-year overall survival rate of less than 50% has hardly improved over the last decades. To improve the outcome of patients with all subtypes of ovarian cancer, large-scale fundamental and translational research is needed. To accommodate these types of ovarian cancer research, we have established a Dutch nationwide, interdisciplinary infrastructure and biobank: the Archipelago of Ovarian Cancer Research (AOCR). The AOCR will facilitate fundamental and translational ovarian cancer research and enhance interdisciplinary, national, and international collaboration. DESIGN: The AOCR biobank is a prospective ovarian cancer biobank in which biomaterials are collected, processed, and stored in a uniform matter for future (genetic) scientific research. All 19 Dutch hospitals in which ovarian cancer surgery is performed participate and collaborate in the AOCR biobank. PARTICIPANTS/MATERIALS, SETTING, METHODS: Patients of 16 years and older with suspected or diagnosed ovarian, fallopian tube, or primary peritoneal cancer are recruited for participation. Patients who agree to participate give written informed consent for collection, storage, and issue of their biomaterials for future studies. After inclusion, different blood samples are taken at various predefined time points both before and during treatment. In case of a diagnostic paracentesis or biopsy, the residual biomaterials of these procedures are stored in the biobank. During surgery, primary tumor tissue and, if applicable, tissue from metastatic sites are collected and stored. From each patient, a representative histological hematoxylin and eosin stained slide is digitalized for research purposes, including reassessment by a panel of gynecologic pathologists. Clinical and pathological data are obtained on a per-study basis from Dutch registries. Research proposals for the issue of biomaterials and data are evaluated by both the Archipelago Scientific Committee and the Steering Committee. Researchers using the biomaterials from the AOCR biobank are encouraged to enrich the biobank with data and materials resulting from their analyses and experiments. LIMITATIONS: The implementation and first 4 years of collection are financed by an infrastructural grant from the Dutch Cancer Society. Therefore, the main limitation is that the costs for sustaining the biobank after the funding period will have to be covered. This coverage will come from incorporation of budget for biobanking in future grant applications and from fees from external researchers and commercial parties using the biomaterials stored in the AOCR biobank. Moreover, we will apply for grants aimed at sustaining and improving research infrastructures and biobanks. CONCLUSIONS: With the establishment of the Dutch nationwide, interdisciplinary Archipelago of Ovarian Cancer Research infrastructure and biobank, fundamental and translational research on ovarian cancer can be greatly improved. The ultimate aim of this infrastructure is that it will lead to improved diagnostics, treatment, and survival of patients with ovarian cancer.

Detection of tumor-derived extracellular vesicles in plasma from patients with solid cancer.

BACKGROUND: Extracellular vesicles (EVs) are actively secreted by cells into body fluids and contain nucleic acids of the cells they originate from. The goal of this study was to detect circulating tumor-derived EVs (ctEVs) by mutant mRNA transcripts (EV-RNA) in plasma of patients with solid cancers and compare the occurrence of ctEVs with circulating tumor DNA (ctDNA) in cell-free DNA (cfDNA). METHODS: For this purpose, blood from 20 patients and 15 healthy blood donors (HBDs) was collected in different preservation tubes (EDTA, BCT, CellSave) and processed into plasma within 24 h from venipuncture. EVs were isolated with the ExoEasy protocol from this plasma and from conditioned medium of 6 cancer cell lines and characterized according to MISEV2018-guidelines. RNA from EVs was isolated with the ExoRNeasy protocol and evaluated for transcript expression levels of 96 genes by RT-qPCR and genotyped by digital PCR. RESULTS: Our workflow applied on cell lines revealed a high concordance between cellular mRNA and EV-RNA in expression levels as well as variant allele frequencies for PIK3CA, KRAS and BRAF. Plasma CD9-positive EV and GAPDH EV-RNA levels were significantly different between the preservation tubes. The workflow detected only ctEVs with mutant transcripts in plasma of patients with high amounts (> 20%) of circulating tumor DNA (ctDNA). Expression profiling showed that the EVs from patients resemble healthy donors more than tumor cell lines supporting that most EVs are derived from healthy tissue. CONCLUSIONS: We provide a workflow for ctEV detection by spin column-based generic isolation of EVs and PCR-based measurement of gene expression and mutant transcripts in EV-RNA derived from cancer patients' blood plasma. This workflow, however, detected tumor-specific mutations in blood less often in EV-RNA than in cfDNA.

Optimization of Pancreatic Juice Collection: A First Step Toward Biomarker Discovery and Early Detection of Pancreatic Cancer.

INTRODUCTION: Imaging-based surveillance programs fail to detect pancreatic ductal adenocarcinoma at a curable stage, creating an urgent need for diagnostic biomarkers. METHODS: Secretin-stimulated pancreatic juice (PJ) was collected from the duodenal lumen during endoscopic ultrasound. The yield of biomarkers and organoids was compared for 2 collection techniques (endoscope suction channel vs catheter-based) and 3 periods (0-4 vs 4-8 vs 8-15 minutes). RESULTS: Collection through the endoscope suction channel was superior to collection with a catheter. Collection beyond 8 minutes reduced biomarker yield. PJ-derived organoid culture was feasible. DISCUSSION: The optimal protocol for secretin-stimulated PJ collection is through the endoscope suction channel for 8 minutes allowing biomarker detection and organoid culture.

An 8-gene mRNA expression profile in circulating tumor cells predicts response to aromatase inhibitors in metastatic breast cancer patients.

BACKGROUND: Molecular characterization of circulating tumor cells (CTC) is promising for personalized medicine. We aimed to identify a CTC gene expression profile predicting outcome to first-line aromatase inhibitors in metastatic breast cancer (MBC) patients. METHODS: CTCs were isolated from 78 MBC patients before treatment start. mRNA expression levels of 96 genes were measured by quantitative reverse transcriptase polymerase chain reaction. After applying predefined exclusion criteria based on lack of sufficient RNA quality and/or quantity, the data from 45 patients were used to construct a gene expression profile to predict poor responding patients, defined as disease progression or death <9 months, by a leave-one-out cross validation. RESULTS: Of the 45 patients, 19 were clinically classified as poor responders. To identify them, the 75% most variable genes were used to select genes differentially expressed between good and poor responders. An 8-gene CTC predictor was significantly associated with outcome (Hazard Ratio [HR] 4.40, 95% Confidence Interval [CI]: 2.17-8.92, P < 0.001). This predictor identified poor responding patients with a sensitivity of 63% and a positive predictive value of 75%, while good responding patients were correctly predicted in 85% of the cases. In multivariate Cox regression analysis, including CTC count at baseline, the 8-gene CTC predictor was the only factor independently associated with outcome (HR 4.59 [95% CI: 2.11-9.56], P < 0.001). This 8-gene signature was not associated with outcome in a group of 71 MBC patients treated with systemic treatments other than AI. CONCLUSIONS: An 8-gene CTC predictor was identified which discriminates good and poor outcome to first-line aromatase inhibitors in MBC patients. Although results need to be validated, this study underscores the potential of molecular characterization of CTCs.

Cellular sterol trafficking and metabolism: spotlight on structure.

Cholesterol is the main but not the only sterol in cell membranes of higher eukaryotes. Currently, there is an increasing interest toward structurally different sterols, because their membrane partitioning, trafficking, and metabolic properties may differ considerably from those of cholesterol. There is also growing information on specific sterol-protein interactions and their functional consequences, as exemplified by NPC proteins and select ABC-transporters. Several aspects of sterol trafficking and homeostasis are conserved between eukaryotes, and novel, unanticipated findings in this area have recently been made, particularly from genetic screens in yeast. This includes a novel, reversible modification of the sterol structure that affects the choice of transport route.

Protein Kinase A-induced tamoxifen resistance is mediated by anchoring protein AKAP13.

BACKGROUND: Estrogen Receptor alpha (ERα)-positive breast cancer patients receive endocrine therapy, often in the form of tamoxifen. However, resistance to tamoxifen is frequently observed. A signalling cascade that leads to tamoxifen resistance is dictated by activation of the Protein Kinase A (PKA) pathway, which leads to phosphorylation of ERα on Serine 305 and receptor activation, following tamoxifen binding. Thus far, it remains elusive what protein complexes enable the PKA-ERα interaction resulting in ERα Serine 305 phosphorylation. METHODS: We performed immunohistochemistry to detect ERαSerine 305 phosphorylation in a cohort of breast cancer patients who received tamoxifen treatment in the metastatic setting. From the same tumor specimens, Agilent 44 K gene expression analyses were performed and integrated with clinicopathological data and survival information. In vitro analyses were performed using MCF7 breast cancer cells, which included immunoprecipitations and Fluorescence Resonance Energy Transfer (FRET) analyses to illustrate ERα complex formation. siRNA mediated knockdown experiments were performed to assess effects on ERαSerine 305 phosphorylation status, ERα/PKA interactions and downstream responsive gene activity. RESULTS: Stratifying breast tumors on ERα Serine 305 phosphorylation status resulted in the identification of a gene network centered upon AKAP13. AKAP13 mRNA expression levels correlate with poor outcome in patients who received tamoxifen treatment in the metastatic setting. In addition, AKAP13 mRNA levels correlate with ERαSerine 305 phosphorylation in breast tumor samples, suggesting a functional connection between these two events. In a luminal breast cancer cell line, AKAP13 was found to interact with ERα as well as with a regulatory subunit of PKA. Knocking down of AKAP13 prevented PKA-mediated Serine 305 phosphorylation of ERα and abrogated PKA-driven tamoxifen resistance, illustrating that AKAP13 is an essential protein in this process. CONCLUSIONS: We show that the PKA-anchoring protein AKAP13 is essential for the phosphorylation of ERαS305, which leads to tamoxifen resistance both in cell lines and tamoxifen-treated breast cancer patients.

VAV3 mediates resistance to breast cancer endocrine therapy.

INTRODUCTION: Endocrine therapies targeting cell proliferation and survival mediated by estrogen receptor α (ERα) are among the most effective systemic treatments for ERα-positive breast cancer. However, most tumors initially responsive to these therapies acquire resistance through mechanisms that involve ERα transcriptional regulatory plasticity. Herein we identify VAV3 as a critical component in this process. METHODS: A cell-based chemical compound screen was carried out to identify therapeutic strategies against resistance to endocrine therapy. Binding to ERα was evaluated by molecular docking analyses, an agonist fluoligand assay and short hairpin (sh)RNA-mediated protein depletion. Microarray analyses were performed to identify altered gene expression. Western blot analysis of signaling and proliferation markers, and shRNA-mediated protein depletion in viability and clonogenic assays, were performed to delineate the role of VAV3. Genetic variation in VAV3 was assessed for association with the response to tamoxifen. Immunohistochemical analyses of VAV3 were carried out to determine its association with therapeutic response and different tumor markers. An analysis of gene expression association with drug sensitivity was carried out to identify a potential therapeutic approach based on differential VAV3 expression. RESULTS: The compound YC-1 was found to comparatively reduce the viability of cell models of acquired resistance. This effect was probably not due to activation of its canonical target (soluble guanylyl cyclase), but instead was likely a result of binding to ERα. VAV3 was selectively reduced upon exposure to YC-1 or ERα depletion, and, accordingly, VAV3 depletion comparatively reduced the viability of cell models of acquired resistance. In the clinical scenario, germline variation in VAV3 was associated with the response to tamoxifen in Japanese breast cancer patients (rs10494071 combined P value = 8.4 × 10-4). The allele association combined with gene expression analyses indicated that low VAV3 expression predicts better clinical outcome. Conversely, high nuclear VAV3 expression in tumor cells was associated with poorer endocrine therapy response. Based on VAV3 expression levels and the response to erlotinib in cancer cell lines, targeting EGFR signaling may be a promising therapeutic strategy. CONCLUSIONS: This study proposes VAV3 as a biomarker and a rationale for its use as a signaling target to prevent and/or overcome resistance to endocrine therapy in breast cancer.

What dictates the accumulation of desmosterol in the developing brain?

The brain is the most cholesterol-enriched tissue in the body. During brain development, desmosterol, an immediate precursor of cholesterol, transiently accumulates up to 30% of total brain sterols. This massive desmosterol deposition appears to be present in all mammalian species reported so far, including humans, but how it is achieved is not well understood. Here, we propose that desmosterol accumulation in the developing brain may be primarily caused by post-transcriptional repression of 3ß-hydroxysterol 24-reductase (DHCR24) by progesterone. Furthermore, distinct properties of desmosterol may serve to increase the membrane active pool of sterols in the brain: desmosterol cannot be hydroxylated to generate 24S-hydroxycholesterol, a brain derived secretory sterol, desmosterol has a reduced propensity to be esterified as compared to cholesterol, and desmosterol may activate LXR to stimulate astrocyte sterol secretion. This regulated accumulation of desmosterol by progesterone-induced suppression of DHCR24 may facilitate the rapid enrichment and distribution of membrane sterols in the developing brain.

A Multiplex Assay for Fast PIK3CA Hotspot Mutation Characterization in a Single Specimen by 3-Color Digital PCR Analysis.

BACKGROUND: Activating mutations in the phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) gene have been detected often in solid tumors. Targeted therapy for mutant PIK3CA is now available in the clinic, making molecular diagnostics pivotal. Our aim was to design a multiplex digital PCR (dPCR) assay to evaluate the 4 most common PIK3CA hotspot mutations simultaneously to characterize and quantify these in liquid biopsies. METHODS: A multiplex assay was developed to detect exon 9 p.E542K and p.E545K mutations, and exon 20 p.H1047L and p.H1047R mutations using the Stilla 3-color dPCR Naica system. The assay was evaluated on stock and pre-amplified DNA from cell lines with the above mutations as single and pooled samples, and on cell-free DNA (cfDNA) from healthy blood donors (HBDs) and breast cancer patients, to determine detection thresholds and diagnostic accuracy. RESULTS: The assay distinguished all 4 PIK3CA mutations in (cf)DNA, and also when dual mutations were present. Detection thresholds of stock and pre-amplified cfDNA samples were 0.11 and 0.40 copies/uL (cp/uL) for mutant copies concentration, and 0.003% and 0.68% for variant allele frequencies (VAFs), respectively. The assay confirmed the PIK3CA (mutation) status as defined by targeted next-generation sequencing (NGS) in 82 out of 96 patients that were mutant for PIK3CA, and in 11 out of 12 patients with wild-type PIK3CA. CONCLUSIONS: Our designed multiplex dPCR assay detected PIK3CA mutations with high accuracy in stock and pre-amplified cfDNA. Furthermore, it is affordable and demands less cfDNA input when compared to available uniplex dPCR assays and NGS analyses.

Epigenetic and Genomic Hallmarks of PARP-Inhibitor Resistance in Ovarian Cancer Patients.

BACKGROUND: Patients with advanced-stage epithelial ovarian cancer (EOC) receive treatment with a poly-ADP ribose-polymerase (PARP) inhibitor (PARPi) as maintenance therapy after surgery and chemotherapy. Unfortunately, many patients experience disease progression because of acquired therapy resistance. This study aims to characterize epigenetic and genomic changes in cell-free DNA (cfDNA) associated with PARPi resistance. MATERIALS AND METHODS: Blood was taken from 31 EOC patients receiving PARPi therapy before treatment and at disease progression during/after treatment. Resistance was defined as disease progression within 6 months after starting PARPi and was seen in fifteen patients, while sixteen patients responded for 6 to 42 months. Blood cfDNA was evaluated via Modified Fast Aneuploidy Screening Test-Sequencing System (mFast-SeqS to detect aneuploidy, via Methylated DNA Sequencing (MeD-seq) to find differentially methylated regions (DMRs), and via shallow whole-genome and -exome sequencing (shWGS, exome-seq) to define tumor fractions and mutational signatures. RESULTS: Aneuploid cfDNA was undetectable pre-treatment but observed in six patients post-treatment, in five resistant and one responding patient. Post-treatment ichorCNA analyses demonstrated in shWGS and exome-seq higher median tumor fractions in resistant (7% and 9%) than in sensitive patients (7% and 5%). SigMiner analyses detected predominantly mutational signatures linked to mismatch repair and chemotherapy. DeSeq2 analyses of MeD-seq data revealed three methylation signatures and more tumor-specific DMRs in resistant than in responding patients in both pre- and post-treatment samples (274 vs. 30 DMRs, 190 vs. 57 DMRs, Χ2-test p < 0.001). CONCLUSION: Our genome-wide Next-Generation Sequencing (NGS) analyses in PARPi-resistant patients identified epigenetic differences in blood before treatment, whereas genomic alterations were more frequently observed after progression. The epigenetic differences at baseline are especially interesting for further exploration as putative predictive biomarkers for PARPi resistance.

Tropomyosin1 isoforms underlie epithelial to mesenchymal plasticity, metastatic dissemination, and resistance to chemotherapy in high-grade serous ovarian cancer.

Phenotypic plasticity, defined as the ability of individual cells with stable genotypes to exert different phenotypes upon exposure to specific environmental cues, represent the quintessential hallmark of the cancer cell en route from the primary lesion to distant organ sites where metastatic colonization will occur. Phenotypic plasticity is driven by a broad spectrum of epigenetic mechanisms that allow for the reversibility of epithelial-to-mesenchymal and mesenchymal-to-epithelial transitions (EMT/MET). By taking advantage of the co-existence of epithelial and quasi-mesenchymal cells within immortalized cancer cell lines, we have analyzed the role of EMT-related gene isoforms in the regulation of epithelial mesenchymal plasticity (EMP) in high grade serous ovarian cancer. When compared with colon cancer, a distinct spectrum of downstream targets characterizes quasi-mesenchymal ovarian cancer cells, likely to reflect the different modalities of metastasis formation between these two types of malignancy, i.e. hematogenous in colon and transcoelomic in ovarian cancer. Moreover, upstream RNA-binding proteins differentially expressed between epithelial and quasi-mesenchymal subpopulations of ovarian cancer cells were identified that underlie differential regulation of EMT-related isoforms. In particular, the up- and down-regulation of RBM24 and ESRP1, respectively, represent a main regulator of EMT in ovarian cancer cells. To validate the functional and clinical relevance of our approach, we selected and functionally analyzed the Tropomyosin 1 gene (TPM1), encoding for a protein that specifies the functional characteristics of individual actin filaments in contractile cells, among the ovarian-specific downstream AS targets. The low-molecular weight Tpm1.8/9 isoforms are specifically expressed in patient-derived ascites and promote invasion through activation of EMT and Wnt signaling, together with a broad spectrum of inflammation-related pathways. Moreover, Tpm1.8/9 expression confers resistance to taxane- and platinum-based chemotherapy. Small molecule inhibitors that target the Tpm1 isoforms support targeting Tpm1.8/9 as therapeutic targets for the development of future tailor-made clinical interventions.

The Information Technology (IT) Infrastructure of the Multicenter Archipelago of Ovarian Cancer Research Biobank: A Potential Blueprint for Other Biobanks.

Objective: Biobanks play a crucial role in fundamental and translational research by storing valuable biomaterials and data for future analyses. However, the design of their information technology (IT) infrastructures is often customized to specific requirements, thereby lacking the ability to be used for biobanks comprising other (types of) diseases. This results in substantial costs, time, and efforts for each new biobank project. The Dutch multicenter Archipelago of Ovarian Cancer Research (AOCR) biobank has developed an innovative, reusable IT infrastructure capable of adaptation to various biobanks, thereby enabling cost-effective and efficient implementation and management of biobank IT systems. Methods and Results: The AOCR IT infrastructure incorporates preexisting biobank software, mainly managed by Health-RI. The web-based registration tool Ldot is used for secure storage and pseudonymization of patient data. Clinicopathological data are retrieved from the Netherlands Cancer Registry and the Dutch nationwide pathology databank (Palga), both established repositories, reducing administrative workload and ensuring high data quality. Metadata of collected biomaterials are stored in the OpenSpecimen system. For digital pathology research, a hematoxylin and eosin-stained slide from each patient's tumor is digitized and uploaded to Slide Score. Furthermore, adhering to the Findable, Accessible, Interoperable, and Reusable (FAIR) principles, genomic data derived from the AOCR samples are stored in cBioPortal. Conclusion: The IT infrastructure of the AOCR biobank represents a new standard for biobanks, offering flexibility to handle diverse diseases and types of biomaterials. This infrastructure bypasses the need for disease-specific, custom-built software, thereby being cost- and time-effective while ensuring data quality and legislative compliance. The adaptability of this infrastructure highlights its potential to serve as a blueprint for the development of IT infrastructures in both new and existing biobanks.

Role of ORPs in sterol transport from plasma membrane to ER and lipid droplets in mammalian cells.

In this study, we investigated the mechanisms of sterol transport from the plasma membrane (PM) to the endoplasmic reticulum (ER) and lipid droplets (LDs) in HeLa cells. By overexpressing all mammalian oxysterol-binding protein-related proteins (ORPs), we found that especially ORP1S and ORP2 enhanced PM-to-LD sterol transport. This reflected the stimulation of transport from the PM to the ER, rather than from the ER to LDs. Double knockdown of ORP1S and ORP2 inhibited sterol transport from the PM to the ER and LDs, suggesting a physiological role for these ORPs in the process. A two phenylalanines in an acidic tract (FFAT) motif in ORPs that mediates interaction with VAMP-associated proteins (VAPs) in the ER was not necessary for the enhancement of sterol transport by ORPs. However, VAP-A and VAP-B silencing slowed down PM-to-LD sterol transport. This was accompanied by enhanced degradation of ORP2 and decreased levels of several FFAT motif-containing ORPs, suggesting a role for VAPs in sterol transport by stabilization of ORPs.

Hotspot mutations in PIK3CA associate with first-line treatment outcome for aromatase inhibitors but not for tamoxifen.

PIK3CA mutations occur frequently in breast cancer, predominantly in exons 9 and 20. The aim of this retrospective study is to evaluate the PIK3CA mutation status for its relationship with prognosis and first-line endocrine therapy outcome. PIK3CA exon 9 and 20 were evaluated for mutations in 1,352 primary breast cancer specimens by SnaPshot multiplex analyses. The mutation status was studied for their relationship with metastasis-free survival (MFS) in 342 untreated lymph node-negative (LNN) patients and to time to progression (TTP) in estrogen receptor (ER)-positive patients with metastatic disease treated with first-line tamoxifen (N = 447) or aromatase inhibitors (AIs; N = 84). We detected in 423 patients hotspot mutations for PIK3CA (31 %). Mutations in exon 20 were detected in 251 patients (59 %), with H1047L and H1047R mutations in 37 (15 %) and 214 (85 %) cases, respectively. Mutations in PIK3CA exon 9 were discovered in 173 patients (41 %), with E542K and E545K mutations in 57 (32 %) and 104 (60 %) cases as most prevalent ones. Evaluation of the untreated LNN patients for prognosis showed no relationship between MFS and PIK3CA mutations, neither for exon 9 [HR = 1.04 (95 % CI 0.57-1.89), P = 0.90] nor for exon 20 [HR = 0.98 (95 % CI 0.63-1.54); P = 0.94] when compared to wild-type. The PIK3CA mutation status was also not associated with treatment outcome after first-line tamoxifen. On the other hand, patients treated with first-line AIs showed a longer TTP when having a PIK3CA mutation in exon 9 [HR = 0.40 (95 % CI 0.17-0.95); P = 0.038] or exon 20 [HR = 0.50 (95 % CI 0.27-0.91); P = 0.024] compared to wild-types, both significant in uni- and multivariate analysis including traditional predictive factors. All results remained when only HER2-negative patients were evaluated for each cohort. PIK3CA mutations in ER-positive tumors were significantly associated with a favorable outcome after first-line AIs, which needs further confirmation in other datasets. Mutations were not associated with prognosis in untreated LNN patients nor predictive outcome after first-line tamoxifen therapy in advanced disease patients.

Machine learning-based somatic variant calling in cell-free DNA of metastatic breast cancer patients using large NGS panels.

Next generation sequencing of cell-free DNA (cfDNA) is a promising method for treatment monitoring and therapy selection in metastatic breast cancer (MBC). However, distinguishing tumor-specific variants from sequencing artefacts and germline variation with low false discovery rate is challenging when using large targeted sequencing panels covering many tumor suppressor genes. To address this, we built a machine learning model to remove false positive variant calls and augmented it with additional filters to ensure selection of tumor-derived variants. We used cfDNA of 70 MBC patients profiled with both the small targeted Oncomine breast panel (Thermofisher) and the much larger Qiaseq Human Breast Cancer Panel (Qiagen). The model was trained on the panels' common regions using Oncomine hotspot mutations as ground truth. Applied to Qiaseq data, it achieved 35% sensitivity and 36% precision, outperforming basic filtering. For 20 patients we used germline DNA to filter for somatic variants and obtained 245 variants in total, while our model found seven variants, of which six were also detected using the germline strategy. In ten tumor-free individuals, our method detected in total one (potentially germline) variant, in contrast to 521 variants detected without our model. These results indicate that our model largely detects somatic variants.