Identification of mutation-independent BRCA2 protein deficiency expands diagnostics and selection of pancreatic cancer patients for personalized therapy with PARP1 inhibitors

doi:10.21203/rs.3.rs-4840364/v1

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Identification of mutation-independent BRCA2 protein deficiency expands diagnostics and selection of pancreatic cancer patients for personalized therapy with PARP1 inhibitors

https://doi.org/10.21203/rs.3.rs-4840364/v1

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Background: Recently, therapies involving poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP1) inhibitors have been approved for metastatic BRCA1/2-mutated pancreatic ductal adenocarcinoma (PDAC). The current scheme of identification of patients with BRCA deficiency relies on genetic screening. Here, we tested the hypothesis that pancreatic tumors have a broader spectrum of BRCAness than can be identified solely by gene mutations. We focused on BRCA2 deficiency, which is predominant in pancreatic ductal adenocarcinoma (PDAC).

Methods: Pancreatic cancer cell lines (wt or BRCA2mutated) were used to set up a protocol to verify antibody specificity and detect BRCA2 protein levels by flow cytometry.Post-surgery pancreatic tumor samples were assessed by spectral cytometry with unsupervised analysis to identify BRCA2-deficient clusters together with the expression of stemness and metastasis markers. Personalized tumor signatures specified BRCAness phenotype and cancer state to increase the accuracy of selection for therapy with PARP1 inhibitors (PARPis). In parallel, BRCA2 mutations were identified by NGS analysis.

Results: We developed a cytometric panel to assess BRCA2 levels associated with sensitivity to PARPis (olaparib and talazoparib). Analysis of BRCA2 protein levels in patients’ samples showed high diversity. Unsupervised cluster analysis identified BRCA2-deficient clusters, together with metastasis and stemness markers, which indicated advanced tumors with dismal prognoses. Cluster composition confirmed the high heterogeneity of pancreatic tumors. In parallel, NGS did not recognize the BRCA2/1 mutations in any of the analyzed tumors. Therefore, based on the current selection, these patients would be excluded from PARPis therapy. Finally, analysis of each tumor personalized signatures of tumor cell subsets potentially sensitive to PARPis were demonstrated.

Conclusions: We found that BRCA2 protein deficiency (BRCAness) is detected with metastasis/stemness markers in pancreatic tumors also in individuals lacking BRCA2 mutations. Our findings show that integrating the flow cytometry-based BRCA2 protein assessment with genetic screening is important to improve the effective selection of PDAC patients for therapy with PARPis. This might also be relevant for other BRCA-deficient tumors.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies. It is the seventh most common cause of cancer-related deaths worldwide, with a 5-year survival rate of only 9%-11% (1, 2). Surgery and multidrug chemotherapy remain the standard of care, although fewer than 20% of patients are candidates for surgery (3). Although improvements in diagnostic methods and therapies have substantially reduced patient mortality in several cancer types, breakthroughs in the treatment of pancreatic cancer are still awaited. Due to the high level of heterogeneity, there is a need for personalized therapy based on the molecular characteristics of the tumor (4).

The advancement of genetic diagnostics allows the proposal of a targeted, personalized therapeutic option. In tumors with defects in DNA damage repair mechanisms, such as tumors with BRCA1/2 mutations, the poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP1) pathway can be utilized as a salvage mechanism. The PARP1 protein controls a pathway for base excision repair, which is critical for repairing DNA single-strand breaks. Thus, PARP1 inhibition halts single-strand break repair and blocks replication fork progression, leading to double-strand breaks, which are recognized by functional BRCA1/2 proteins and repaired via the homologous recombination (HR) pathway. Therefore, the use of PARP1 inhibitors (PARPis) leads to synthetic lethality due to DNA damage accumulation in the presence of BRCA1/2 mutations (5, 6). Treatment with PARPis has beneficial clinical effects and is well tolerated in patients with breast, ovarian and prostate cancers harboring BRCA1/2 mutations (7, 8).

Approximately 4%-7% of patients diagnosed with PDAC harbor deleterious germline BRCA1/2 mutations, with BRCA2 mutation being the most common inherited risk factor (3.5% compared to that of non-mutation carriers) (9). The first phase 3 randomized trial, i.e., the POLO (Pancreas Cancer Olaparib Ongoing) trial, demonstrated a progression-free survival (PFS) benefit in patients with metastatic PDAC with germline BRCA1/2 mutations who were treated with olaparib following platinum-based chemotherapy. The primary endpoint of this study was progression-free survival (PFS), and the PFS time was nearly doubled after olaparib treatment compared to placebo (PFS 7.4 vs. 3.8 m, p = 0.004) (10), leading to FDA approval.

Currently, patient selection for PARPi therapy is based on the identification of the BRCA-deficient phenotype by genetic screening and the detection of BRCA1/2 mutations. Our study in myeloid leukemias indicated that the development of the “BRCAness” phenotype can occur even without BRCA1/2 mutations and can be dependent on different intracellular mechanisms or exposure to therapies (11–13). Therefore, genetic-based qualification appears insufficient in such cases. Implementing diagnostics targeting “BRCAness” detected at the translational level would identify a broader cohort of patients for therapy with PARPis (11–13).

Here, we tested the hypothesis that pancreatic tumors might have a broader spectrum of BRCAness than that identified solely by BRCA1/2 gene mutations, with a focus on BRCA2 deficiency, which is predominant in PDAC (9). We found that BRCA2 deficiency is detected at the protein level and is not always associated with BRCA2 gene mutations. Combinatorial analysis with the evaluation of protein markers for stemness and metastasis identified personalized signatures of PDACs indicating the presence of cell clusters with BRCAness. Thus, we provide evidence to support the use of this strategy as an alternative approach to expand the diagnostic indications and the selection PDAC patients for therapy with PARPis.

Isolation of pancreatic tumor cells

Five patients with PDAC (2 males, 3 females, of age 37–72), three with pNET (1 female, 2 males of age 45–68) and one with ChP (male, 72 years old) were selected for this study (for clinical characteristics see Supplementary Table 1). Pancreatic tumor sample of 10x5x5 mm size (between 0.3–0.5 g) from postoperative resected human pancreas material was isolated and transferred in Hanks’ salt solution (Sigma-Aldrich) at 4°C. The sample was chopped using blades, washed and spun down at 700xg for 7 min at 4°C. The tissue was further dismantled using Tumor Dissociation Kit (Miltenyi Biotec) in DMEM medium, filtered through 40 µM cell strainer and the cell pellet was collected by centrifugation at 700xg for 7 min at 4°C. RBC were eliminated using RBC lysis buffer (Sigma-Aldrich).

Cell lines

PANC-1 cell line (ATCC#CRL-1469) was kindly provided by Prof. U. Wojda (Nencki Institute of Experimental Biology, PAS in Warsaw, Poland). The cell line was authenticated by the ATCC Cell Line Authentication Service, with the exact match based on ATCC STR database. Cells were cultured in DMEM medium with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. The cell line PANC-1 was authenticated by the ATCC Cell Line Authentication Service, with the exact match based on ATCC STR database.

CAPAN-1 cell line (ATCC#HTB-79) was cultured in IMDM medium (Biowest) with 20% fetal bovine serum (FBS) and 1% penicillin/streptomycin, as recommended by ATCC. Cells were treated with 5 µM olaparib (Selleckchem) or 25 nM BMN673 (talazoparib) (Selleckchem).

Histological analysis

Histological analysis of the resection tumor tissue sections has been performed by the standard hematoxylin and eosin (H&E) staining with additional immunochemistry staining when needed.

Western Blot

Cells were lysed at 95°C in SDS lysis buffer (50 mM Tris-HCl pH 6.8, 10% glycerol and 2% SDS) for 5 min. Equal amounts of proteins were boiled 95°C for 5 min with Laemmli buffer and subjected to SDS-PAGE followed by Western Blotting with the use of antibodies: anti-BRCA2 (R&D, #MAB2476), anti-α-tubulin (Calbiochem, #CP06-100UG), anti-β-actin (Sigma Aldrich, #A5316). Activity of HRP was assayed using ECL substrate (BioRad, #170–5061). Western Blots were imaged and analyzed using ChemiDoc MP Imaging system (BioRad).

Cell cycle

PANC-1 and CAPAN-1 cells were seeded on 6-well plates (0.1 mln/well) and treated with 5 µM olaparib or 25 nM BMN673 (talazoparib) for 48h. Cells were washed in PBS, fixed in ice-cold 70% ethanol at − 20℃ for 1h, incubated for 5 min in extraction buffer (8 mM citric acid in 0.2 M Na₂HPO₄) followed by staining for 30 min in a staining buffer (3.8 mM sodium citrate, 50 µg/ml propidium iodide (PI) and 50 µg/ml RNAse A). The PI fluorescence indicating DNA content was measured by flow cytometry (BD LSR Fortessa). The percentage of cells in each phase of cell cycle was determined using ModFit software.

Cell death detection

PANC-1 and CAPAN-1 cells were seeded on 6-well plates (0.1 mln/well) and treated with 5 µM olaparib or 25 nM BMN673 (talazoparib) for 72h. For detection of dead cells, the Annexin V Apoptosis Detection Kit I (BD) was used and fluorescent signal was measured by flow cytometry (BD LSR Fortessa). The percentage of AnnexinV and 7-AAD positive cells was determined using FlowJo software.

Anti-BRCA2 antibody screening

PANC-1 and CAPAN-1 cells were harvested, fixed and permeabilized using Intracellular Fixation & Permeabilization Buffer Set (eBioscience), followed by blocking with 1% BSA in PBS. Anti-BRCA2 antibodies in serial dilution (0,03125–2,0 µg /100 µl/ 1 mln cells) were used for intracellular staining. The matched isotypic IgG antibodies were used as background control. A fluorochrome-conjugated secondary antibody was used for signal detection. The specificity of BRCA2 detection was evaluated based on Stain Index value:

Stain Index = (Median of Positive - Median of Negative) / (SD of Negative * 2)

Multiparameter flow cytometry and data analysis

For multiparameter phenotyping of pancreatic cancer cells, the freshly isolated cells were incubated with Fc Receptor Binding Inhibitor (eBioscience) to reduce the non-specific antibody binding and stained with surface antibody cocktail (including viability/dead stain dye) (Supplementary Table 2) in Brilliant Stain Buffer (BD), both for 30 minutes at 4°C. Cells were fixed and permeabilized for intracellular staining by Intracellular Fixation & Permeabilization Buffer Set (eBioscience). Intracellular proteins were stained for 1 hour. Next, the cells were incubated with 50 nM Syto16 (Invitrogen) in PBS for 20 min for DNA staining. Samples were acquired using BD LSRFortessa cytometer and analysed using FlowJo software version 10 (BD) using FlowAI algorithm for data quality control (24). All anomalies and outliers were removed. The cleaned dataset was acquired by manual gating to eliminate doublets, dead cells (FVD+) and cellular debris (DNA negative; Syto16-). The positive staining of all fluorescent markers was verified with FMO controls. Then, the viable and intact cells were exported for further analysis in R. Data were normalized using the warpSet function from Bioconductor libraries and R statistical package (flowStats 4.10.0). After normalization, data from 6 samples were downsampled to 1211 cells and clustered using Flow-SOM (2.00) to perform 25 meta- clusters (K = 25). Created Flow-SOM object was used to map the whole dataset (9 patients, without downsampling) with 1.35% outliers (madAllowed = 4). Mapped data was further analysed in R by following a script (CATALYST 1.16.2) and diffcyt (1.12.0). Clusters with similar marker distribution were merged. Clusters without tumor cells were filtered out.

BRCA2 mutation analysis by Devyser NGS Assay

Next-generation sequencing has been performed at the Laboratory of Human Cancer Genetics, Center of New Technologies, CENT, University of Warsaw, Warsaw, Poland. Briefly, DNA from FFPE was extracted with QIAamp DNA FFPE Tissue Kit (Qiagen). The quantity of DNA was assessed with Quantus Fluorometer with QuantiFluor dsDNA System (Promega). The High Throughput Sequencing assay was performed according to the manufacturer’s instructions (Devyser BRCA kit, Illumina). A total of 5 µL (50 ng) per sample was used as input for multiplex PCR amplification to create a target amplicon library from each DNA sample. Sequencing adapters including unique index sequences (combination of N50x and N70x) were introduced into each amplicon. The quality of final libraries was assessed on Tapestation D1000 System (Agilent). Libraries were quantified on a Quantus Fluorometer. Six indexed libraries were pooled together followed by purification step using the Devyser Library Clean (Devyser). Final library was diluted to 1nM and sequenced on NextSeq500 instrument (Illumina). The sequencing results were analyzed using BWA, samtools (1.8), picardtools (2.10.0), vcftools (0.1.13), and bedtools (2.26.0).

Statistics

Experiments were done in duplicate or triplicate, and the quantified data shown in dot plots represent combined data, unless otherwise noted. Summary graphs and statistics were performed in GraphPad Prism v9.3 and R 4.3.1 with rstatix 0.7.2 package. Statistical significance was set at a p value lower than 0.05. To test differences across the treatment groups, t test or one-way ANOVA with Tukey post-hoc test with multiple comparison adjustment (fdr) were used, as indicated in the figure legends.

BRCA2 deficiency can be specifically assessed by flow cytometry and corresponds to sensitivity to PARP1 inhibitors

To assess BRCA2 protein deficiency, we used flow cytometry as a precise and sensitive protein detection method. The use of the model cell lines PANC-1 and CAPAN-1, with different BRCA2 expression levels (Fig. 1A), allowed us to verify the anti-BRCA2 antibodies and select the antibody with high specificity, signal intensity, and resolution (Supplementary Fig. 1A, B). Finally, the selected antibody was directly conjugated to the fluorochrome APC to avoid the need for two-step staining. This allowed us to perform tumor sample analysis and develop a multiparameter flow cytometry panel. The results of treatment with the PARP1 inhibitors olaparib and BMN673 (talazoparib) confirmed that the BRCA2 protein abundance estimated by flow cytometry can be used to predict sensitivity to PARP1 inhibitors (Fig. 1B, C). Compared with wt BRCA2-expressing PANC-1 cells, BRCA2-deficient CAPAN-2 cells were more sensitive to PARPis, as indicated by the occurrence of G2/M arrest (Fig. 1B) followed by apoptosis (Fig. 1C). This proof-of-concept experiment confirmed that BRCA2 deficiency detected by flow cytometry in pancreatic tumor cells is correlated with PARPis sensitivity.

Pancreatic tumors show different and heterogenic BRCA2 levels

Pancreatic tumor specimens from 9 patients (5 men and 4 women) aged 37–72 years were freshly processed after resection surgery (for the clinical characteristics, see Supplementary Table 1). The experimental pipeline is shown in Fig. 2A. Histological analysis (Fig. 2B) revealed the typical characteristics of PDAC at the G1 or G2 stage (PDAC patients 1, 2, 5, 7, and 9) and of pNET (NET) at the G2 stage (NET patients 3, 4, and 6). Chronic pancreatitis without malignancy was detected in one patient (ChP patient 8), and the sample from this patient was used as a control. Additional immunohistochemical staining was performed for complete diagnostics if needed (Supplementary Table 3).

Flow cytometry revealed that the analyzed tumor samples had different BRCA2 protein levels (Fig. 2C) (for the gating strategy, see Supplementary Fig. 2), with the lowest levels detected in four of the five PDAC samples (red histograms). Moreover, the shape of the single histograms indicated diverse BRCA2 levels within each tumor sample, indicating the presence of heterogenic cell populations within a single pancreatic tumor.

Unsupervised flow cytometry identifies cell clusters with BRCA2 protein deficiency in PDAC patients that do not necessarily carry BRCA2 mutations

To identify all BRCA2-deficient cell subsets and further examine tumor heterogeneity and the tumor state, we implemented multiparameter flow cytometry followed by unsupervised analysis. Antibodies specific for biomarkers for pancreatic cancer (CA19-9, CK19), stemness (CD44, CD133, CEA) and metastasis (EpCAM) were combined with an APC-conjugated anti-BRCA2 antibody in a single flow cytometry panel (Supplementary Table 2). A representative full gating strategy is presented in Supplementary Fig. 3A-C. All obtained data were analyzed collectively by an unsupervised method to better reveal the unique single-cell phenotypes to identify all cell subsets.

Unsupervised clustering resulted in the identification of 10 different cell populations/clusters (Fig. 3A) showing different BRCA2 levels accompanied by diverse levels of metastasis and stemness markers (the expression frequency is presented on a heatmap). The intensity of BRCA2 and other markers (denoted “very low”, “low”, “hi”, “+” or “-”) was estimated based on the individual marker histograms, FMO controls and mean fluorescence values (see the Materials and Methods and Supplementary Fig. 4). The mean fluorescence values of BRCA2-deficient CAPAN-1 (blue dotted line) and wt PANC-2 cells expressing high levels of BRCA2 (red/gray solid line), which were overlaid on BRCA2 histograms from the primary tumors (Fig. 3B), confirmed the appropriate estimation of BRCA2 deficiency.

We identified three unique clusters with significant BRCA2 deficiency (BRCA2very_low Clusters 1–3) and four clusters with a decreased/low level of BRCA2 expression (BRCA2low Clusters 1–4) (Fig. 3A, marked in bold) among all analyzed samples. Notably, the majority of the cells in the BRCA2low clusters also showed elevated levels of metastasis (EpCAM) and/or stemness (CEA, CD44, CD133) markers, indicating their origin in late-stage, aggressive tumors. This pattern was not observed in the BRCA2very_low clusters.

Next, to identify individuals with BRCA2 deficiency for therapy, each patient (tumor sample) was analyzed separately (Fig. 4). The percentage of cells in each of the identified clusters is indicated for each patient, and the BRCA-deficient clusters (BRCA2very_low and BRCA2low clusters) are shown in bold.

Five PDAC patients and two pNET patients exhibited significant BRCA2 deficiency, with 50–65% of tumor cells exhibiting the BRCAness phenotype; however, heterogeneity was also clearly detected. For most patients, more than one BRCA2-deficient cluster was recognized, confirming heterogeneity among cancer cell subsets and the rationality of PARPi therapy as a strategy to eliminate those cells. As mentioned, stemness or metastasis markers were also detected in clusters with BRCA2 deficiency. We believe that these expression patterns may represent a highly aggressive and resistant cell population that is associated with a clinically unfavorable prognosis but is potentially sensitive to PARP1 inhibitors due to BRCA2 deficiency. Interestingly, BRCA2-deficient pNET patients (pNET 3 and 4) with elevated levels of metastasis and stemness markers were also identified, indicating advanced high-grade stage. This revealed that these patients should also possibly be considered sensitive to PARPis.

To determine whether the BRCA2-deficient patients selected by flow cytometric analysis carried BRCA2 mutations, NGS analysis of the BRCA2 gene locus was performed for all patients except PDAC patient 9 and pNET patient 6 (due to an insufficient amount of material). NGS analysis did not reveal pathogenic mutations in either the BRCA2 or BRCA1 gene, which has been checked in parallel.

In summary we found that BRCA2 deficiency can be detected not only in individuals with BRCA2 mutations but also can be detected exclusively by flow cytometry at the protein level. In combination with evaluations of additional markers, this strategy allows the functional assessment of the tumor cell state and also improves the accuracy of classification for treatment. Therefore, we recommend that assessment of the BRCA2 protein level (if possible, together with the BRCA1 protein) should be considered in PDAC patients as an alternative test in addition to genetic screening. We suggest that improvements in diagnostic approaches are critical for identifying all pancreatic tumor patients with BRCA deficiency who can potentially qualify for personalized therapy with FDA-approved PARP1 inhibitors.

The success of the PARPi olaparib (Lynparza) for the treatment of BRCA-deficient metastatic breast tumors has established a proof of concept for personalized therapeutic regimens that eradicate tumor cells via synthetic lethality (5, 6). Even though prolonged progression-free survival has not been observed in every ongoing trial, the application of PARPis is one of the most promising cancer strategies (7, 8). The current standard regimens for PDAC patients include surgery, which is possible in a limited number of patients, and multidrug chemotherapies, which are highly toxic and have limited specificity. Moreover, patients experience rapid metastatic progression, with the development of resistance and a short overall survival time (14). Olaparib has been approved for the treatment of germline BRCA-mutated metastatic pancreatic cancer (10), and the use of various PARPis as monotherapy or combination treatments in several other ongoing trials where genetic identification of BRCA1/2 mutation is an eligibility criterion.

The most important finding reported here is that BRCA2 protein deficiency (i.e., the BRCAness phenotype) in pancreatic tumor cells can also be detected at the protein level in individuals lacking BRCA2 mutations. Therefore, our data indicate that the cohort of BRCA2-deficient patients is broader than currently believed and that all potentially eligible patients may not be identified by the actual selection criteria based solely on mutation analysis. Similarly, we previously reported that in leukemia, different intracellular mechanisms result in deficiency of the BRCA1/2 proteins or other components of the HRR pathway, leading to PARPi sensitivity (11–13). Therefore, we designed a personalized medicine approach called GEMA (gene expression and mutation analysis) to identify BRCA1/2- and DNA-PK-deficient leukemias by using different methods to assess gene and protein deficiencies (15). Later, similar observations indicating HR-related protein deficiencies were reported by others in hematological malignancies (16, 17) and in solid tumors (18, 19). Our data presented herein also confirm this phenomenon and show that the concept of mutation-independent BRCAness also applies to pancreatic tumors.

We propose the introduction of advanced flow cytometry followed by unsupervised analysis to identify BRCA2 protein deficiency and the unique personalized signatures of PDAC tumors. Together with the evaluation of metastasis and stemness markers, this approach allows the assessment of the degree of advanced progression/aggressiveness. Most PDAC patients are diagnosed when the disease is at an advanced stage and have poor clinical outcomes due to metastatic disease and tumor heterogeneity (14). Therefore, identifying the clones with metastatic signature of BRCA2 deficiency and exploring the possibility of eradicating BRCA2-deficient metastatic tumor cells by PARPi treatment would be extremely beneficial.

We propose that the detection of BRCA2 deficiency at the protein level, in addition to the genetic screening methods already being applied, should be considered a strategy for determining the diagnostic indication for PARPi treatment in patients with pancreatic tumors. As the size of databases continuously increases, machine learning strategies might be implemented to identify patients who are potentially sensitive to therapy.

However, our data showed high heterogeneity in each analyzed pancreatic tumor, as indicated by the presence of different cell clusters/clones. PARPis target only clusters with the BRCAness phenotype. As a personalized strategy, we propose the verification of combinations of PARPis targeting BRCA-deficient tumor cells with conventional chemotherapeutic drugs. These combinations might be based on current regimens, including combinations with gemcitabine (20, 21) or platinum-based chemotherapy, where induced DNA damage can increase the cellular reliance on DNA repair and hence sensitize tumors to PARPis (8). Alternatively, combinations involving targeted immunotherapy with anti-PD-1 (nivolumab) or anti-CTLA-4 (ipilimumab) agents have also been tested in advanced pancreatic cancer (22).

Taken together, our data presented herein imply that flow cytometric detection of BRCA deficiency at the translational level can identify more patients susceptible to PARPis than can genetic screening alone. We propose that such a personalized diagnostic approach based on protein markers might significantly improve the identification of BRCA1/2 deficiency in pancreatic tumors and should be implemented in addition to genetic screening. This will increase the efficiency of selection of PDAC patients for PARPi therapy and include those harboring BRCA-deficient metastatic clones, and this strategy might be highly relevant for other tumors with BRCA1/2 deficiency.

BRCA1 Breast cancer gene 1

BRCA2 Breast cancer gene 2

PDAC Pancreatic ductal adenocarcinoma

pNET Pancreatic neuroendocrine tumor

ChP Chronic pancreatitis

PARP1 Poly(adenosine diphosphate [ADP]-ribose) polymerase

PARPis Poly(adenosine diphosphate [ADP]-ribose) polymerase inhibitors

NGS Next-generation sequencing

Ethics approval and consent to participate

The study protocol was approved by the Bioethics Committee at the Maria Sklodowska-Curie National Research Institute of Oncology in Warsaw (Decision No 11/2016) with the informed consent of enrolled individuals. The study was performed following the latest version of the Declaration of Helsinki and the guidelines for good clinical practice.

Consent for publication

Not applicable

Data availability

The raw data generated in this study are available upon reasonable request to the corresponding author.

Authors’ Disclosures

The authors have nothing to disclose.

Funding:

This study was supported by the Foundation for Polish Science grant TEAM TECH Core Facility Plus/2017-2/2 (POIR.04.04.00-00-23C2/17-00, co-financed by the European Union under the European Regional Development Fund) (to KP).

Authors’ Contributions:

P. Chroscicki: Conceptualization, methodology, investigation, data analysis and visualization, supervision, participation in writing the original draft. R. Samsel: Conceptualization, clinical assessment and selection of patients, surgery and sample preparation, and participation in writing the original draft. D. Stepnik: Visualization, investigation, flow cytometry data analysis, unsupervised clustering analysis, and participation in the preparation of the original draft. K. Roszkowska-Purska: clinical assessment, patient analysis and stratification, tumor sample analysis, and writing - review and editing. A-M Tybuchowska: Methodology, investigation, data analysis, and writing - review and editing. J. Swatler: Methodology – flow cytometry, data analysis, and writing—review and editing. M. Brewinska-Olchowik: Methodology – flow cytometry, data analysis, and writing—review and editing. M. Wiech: Methodology – flow cytometry, data analysis, and writing—review and editing. K. Jakubowicz: clinical assessment, surgery and sample preparation, and writing - review and editing. J. Franke: Visualization, methodology, investigation, data analysis, and writing - review and editing. K. Jazdzewski: Supervision, methodology, data analysis, and writing - review and editing. A. Cichocki: Writing—review and editing. T. Skorski: Conceptualization and writing - review and editing. K. Piwocka: Conceptualization, supervision, resources, funding acquisition, writing the original draft, project administration, and writing - review and editing.

Acknowledgments:

We would like to thank prof. Urszula Wojda for providing the PANC-1 cell line and Dr. Anna Mietelska-Porowska for performing histopathological imaging.

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No competing interests reported.

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Identification of mutation-independent BRCA2 protein deficiency expands diagnostics and selection of pancreatic cancer patients for personalized therapy with PARP1 inhibitors

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Abstract

Figures

Introduction

Materials and methods

Isolation of pancreatic tumor cells

Cell lines

Histological analysis

Western Blot

Cell cycle

Cell death detection

Anti-BRCA2 antibody screening

Multiparameter flow cytometry and data analysis

BRCA2 mutation analysis by Devyser NGS Assay

Statistics

Results

Pancreatic tumors show different and heterogenic BRCA2 levels

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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