Tumor slice culture system to assess drug response of primary breast cancer

Background The high incidence of breast cancer has sparked the development of novel targeted and personalized therapies. Personalization of cancer treatment requires reliable prediction of chemotherapy responses in individual patients. Effective selection can prevent unnecessary treatment that would mainly result in the unwanted side effects of the therapy. This selection can be facilitated by characterization of individual tumors using robust and specific functional assays, which requires development of powerful ex vivo culture systems and procedures to analyze the response to treatment. Methods We optimized culture methods for primary breast tumor samples that allowed propagation of tissue ex vivo. We combined several tissue culture strategies, including defined tissue slicing technology, growth medium optimization and use of a rotating platform to increase nutrient exchange. Results We could maintain tissue cultures for at least 7 days without losing tissue morphology, viability or cell proliferation. We also developed methods to determine the cytotoxic response of individual tumors to the chemotherapeutic treatment FAC (5-FU, Adriamycin [Doxorubicin] and Cyclophosphamide). Using this tool we designated tumors as sensitive or resistant and distinguished a clinically proven resistant tumor from other tumors. Conclusion This method defines conditions that allow ex vivo testing of individual tumor responses to anti-cancer drugs and therefore might improve personalization of breast cancer treatment

Towards controlled terminology for reporting germline cancer susceptibility variants: an ENIGMA report.

The vocabulary currently used to describe genetic variants and their consequences reflects many years of studying and discovering monogenic disease with high penetrance. With the recent rapid expansion of genetic testing brought about by wide availability of high-throughput massively parallel sequencing platforms, accurate variant interpretation has become a major issue. The vocabulary used to describe single genetic variants in silico, in vitro, in vivo and as a contributor to human disease uses terms in common, but the meaning is not necessarily shared across all these contexts. In the setting of cancer genetic tests, the added dimension of using data from genetic sequencing of tumour DNA to direct treatment is an additional source of confusion to those who are not experienced in cancer genetics. The language used to describe variants identified in cancer susceptibility genetic testing typically still reflects an outdated paradigm of Mendelian inheritance with dichotomous outcomes. Cancer is a common disease with complex genetic architecture; an improved lexicon is required to better communicate among scientists, clinicians and patients, the risks and implications of genetic variants detected. This review arises from a recognition of, and discussion about, inconsistencies in vocabulary usage by members of the ENIGMA international multidisciplinary consortium focused on variant classification in breast-ovarian cancer susceptibility genes. It sets out the vocabulary commonly used in genetic variant interpretation and reporting, and suggests a framework for a common vocabulary that may facilitate understanding and clarity in clinical reporting of germline genetic tests for cancer susceptibility

Performance of BRCA1/2 mutation prediction models in male breast cancer patients

To establish whether existing mutation prediction models can identify which male breast cancer (MBC) patients should be offered BRCA1 and BRCA2 diagnostic DNA screening, we compared the performance of BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm), BRCAPRO (BRCA probability) and the Myriad prevalence table ("Myriad"). These models were evaluated using the family data of 307 Dutch MBC probands tested for BRCA1/2, 58 (19%) of whom were carriers. We compared the numbers of observed vs predicted carriers and assessed the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) for each model. BOADICEA predicted the total number of BRCA1/2 mutation carriers quite accurately (observed/predicted ratio: 0.94). When a cut-off of 10% and 20% prior probability was used, BRCAPRO showed a non-significant better performance (observed/predicted ratio BOADICEA: 0.81, 95% confidence interval [CI]: [0.60-1.09] and 0.79, 95% CI: [0.57-1.09], vs. BRCAPRO: 1.02, 95% CI: [0.75-1.38] and 0.94, 95% CI: [0.68-1.31], respectively). Myriad underestimated the number of carriers in up to 69% of the cases. BRCAPRO showed a non-significant, higher AUC than BOADICEA (0.798 vs 0.776). Myriad showed a significantly lower AUC (0.671). BRCAPRO and BOADICEA can efficiently identify MBC patients as BRCA1/2 mutation carriers. Besides their general applicability, these tools will be of particular value in countries with limited healthcare resources

A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example

BACKGROUND: Assessment of the clinical significance of unclassified variants (UVs) identified in BRCA1 and BRCA2 is very important for genetic counselling. The analysis of co-segregation of the variant with the disease in families is a powerful tool for the classification of these variants. Statistical methods have been described in literature but these methods are not always easy to apply in a diagnostic setting. METHODS: We have developed an easy to use method which calculates the likelihood ratio (LR) of an UV being deleterious, with penetrance as a function of age of onset, thereby avoiding the use of liability classes. The application of this algorithm is publicly available http://www.msbi.nl/cosegregation. It can easily be used in a diagnostic setting since it requires only information on gender, genotype, present age and/or age of onset for breast and/or ovarian cancer. RESULTS: We have used the algorithm to calculate the likelihood ratio in favour of causality for 3 UVs in BRCA1 (p.M18T, p.S1655F and p.R1699Q) and 5 in BRCA2 (p.E462G p.Y2660D, p.R2784Q, p.R3052W and p.R3052Q). Likelihood ratios varied from 0.097 (BRCA2, p.E462G) to 230.69 (BRCA2, p.Y2660D). Typing distantly related individuals with extreme phenotypes (i.e. very early onset cancer or old healthy individuals) are most informative and give the strongest likelihood ratios for or against causality. CONCLUSION: Although co-segregation analysis on itself is in most cases insufficient to prove pathogenicity of an UV, this method simplifies the use of co-segregation as one of the key features in a multifactorial approach considerably

Tumor slice culture system to assess drug response of primary breast cancer

Background: The high incidence of breast cancer has sparked the development of novel targeted and personalized therapies. Personalization of cancer treatment requires reliable prediction of chemotherapy responses in individual patients. Effective selection can prevent unnecessary treatment that would mainly result in the unwanted side effects of the therapy. This selection can be facilitated by characterization of individual tumors using robust and specific functional assays, which requires development of powerful ex vivo culture systems and procedures to analyze the response to treatment. Methods: We optimized culture methods for primary breast tumor samples that allowed propagation of tissue ex vivo. We combined several tissue culture strategies, including defined tissue slicing technology, growth medium optimization and use of a rotating platform to increase nutrient exchange. Results: We could maintain tissue cultures for at least 7days without losing tissue morphology, viability or cell proliferation. We also developed methods to determine the cytotoxic response of individual tumors to the chemotherapeutic treatment FAC (5-FU, Adriamycin [Doxorubicin] and Cyclophosphamide). Using this tool we designated tumors as sensitive or resistant and distinguished a clinically proven resistant tumor from other tumors. Conclusion: This method defines conditions that allow ex vivo testing of individual tumor responses to anti-cancer drugs and therefore might improve personalization of breast cancer treatment

The RECAP Test Rapidly and Reliably Identifies Homologous Recombination-Deficient Ovarian Carcinomas

Recent studies have shown that the efficacy of PARP inhibitors in epithelial ovarian carcinoma (EOC) is related to tumor-specific defects in homologous recombination (HR) and extends beyond BRCA1/2 deficient EOC. A robust method with which to identify HR-deficient (HRD) carcinomas is therefore of utmost clinical importance. In this study, we investigated the proficiency of a functional HR assay based on the detection of RAD51 foci, the REcombination CAPacity (RECAP) test, in identifying HRD tumors in a cohort of prospectively collected epithelial ovarian carcinomas (EOCs). Of the 39 high-grade serous ovarian carcinomas (HGSOC), the RECAP test detected 26% (10/39) to be HRD, whereas ovarian carcinomas of other histologic subtypes (n = 10) were all HR-proficient (HRP). Of the HRD tumors that could be sequenced, 8/9 showed pathogenic BRCA1/2 variants or BRCA1 promoter hypermethylation, indicating that the RECAP test reliably identifies HRD, including but not limited to tumors related to BRCA1/2 deficiency. Furthermore, we found a trend towards better overall survival (OS) of HGSOC patients with RECAP-identified HRD tumors compared to patients with HRP tumors. This study shows that the RECAP test is an attractive alternative to DNA-based HRD tests, and further development of a clinical grade RECAP test is clearly warranted

Comprehensive Functional Characterization and Clinical Interpretation of 20 Splice-Site Variants of the RAD51C Gene

Hereditary breast and/or ovarian cancer is a highly heterogeneous disease with more than 10 known disease-associated genes. In the framework of the BRIDGES project (Breast Cancer Risk after Diagnostic Gene Sequencing), the RAD51C gene has been sequenced in 60,466 breast cancer patients and 53,461 controls. We aimed at functionally characterizing all the identified genetic variants that are predicted to disrupt the splicing process. Forty RAD51C variants of the intron-exon boundaries were bioinformatically analyzed, 20 of which were selected for splicing functional assays. To test them, a splicing reporter minigene with exons 2 to 8 was designed and constructed. This minigene generated a full-length transcript of the expected size (1062 nucleotides), sequence, and structure (Vector exon V1- RAD51C exons_2-8- Vector exon V2). The 20 candidate variants were genetically engineered into the wild type minigene and functionally assayed in MCF-7 cells. Nineteen variants (95%) impaired splicing, while 18 of them produced severe splicing anomalies. At least 35 transcripts were generated by the mutant minigenes: 16 protein-truncating, 6 in-frame, and 13 minor uncharacterized isoforms. According to ACMG/AMP-based standards, 15 variants could be classified as pathogenic or likely pathogenic variants: c.404G > A, c.405-6T > A, c.571 + 4A > G, c.571 + 5G > A, c.572-1G > T, c.705G > T, c.706-2A > C, c.706-2A > G, c.837 + 2T > C, c.905-3C > G, c.905-2A > C, c.905-2_905-1del, c.965 + 5G > A, c.1026 + 5_1026 + 7del, and c.1026 + 5G > T

Splicing predictions, minigene analyses, and ACMG-AMP clinical classification of 42 germline PALB2 splice-site variants.

PALB2 loss-of-function variants confer high risk of developing breast cancer. Here we present a systematic functional analysis of PALB2 splice-site variants detected in approximately 113,000 women in the large-scale sequencing project Breast Cancer After Diagnostic Gene Sequencing (BRIDGES; https://bridges-research.eu/). Eighty-two PALB2 variants at the intron-exon boundaries were analyzed with MaxEntScan. Forty-two variants were selected for the subsequent splicing functional assays. For this purpose, three splicing reporter minigenes comprising exons 1-12 were constructed. The 42 potential spliceogenic variants were introduced into the minigenes by site-directed mutagenesis and assayed in MCF-7/MDA-MB-231 cells. Splicing anomalies were observed in 35 variants, 23 of which showed no traces or minimal amounts of the expected full-length transcripts of each minigene. More than 30 different variant-induced transcripts were characterized, 23 of which were predicted to truncate the PALB2 protein. The pathogenicity of all variants was interpreted according to an in-house adaptation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP) variant classification scheme. Up to 23 variants were classified as pathogenic/likely pathogenic. Remarkably, three ±1,2 variants (c.49-2A>T, c.108+2T>C, and c.211+1G>A) were classified as variants of unknown significance, as they produced significant amounts of either in-frame transcripts of unknown impact on the PALB2 protein function or the minigene full-length transcripts. In conclusion, we have significantly contributed to the ongoing effort of identifying spliceogenic variants in the clinically relevant PALB2 cancer susceptibility gene. Moreover, we suggest some approaches to classify the findings in accordance with the ACMG-AMP rationale. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd on behalf of The Pathological Society of Great Britain and Ireland

Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel

The ENIGMA research consortium develops and applies methods to determine clinical significance of variants in hereditary breast and ovarian cancer genes. An ENIGMA BRCA1/2 classification sub-group, formed in 2015 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Food and Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics and Genomics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants and documentation revised for clarity and ease of use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 uncertain significance or conflicting, 14 pathogenic and/or likely pathogenic, and 13 benign and/or likely benign. Review resolved classification for 11/13 uncertain significance or conflicting variants and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in the research processes and the baseline ACMG/AMP criteria. Calibration of evidence strength was key to justify utility and strength of different data types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants