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Classifying variants in the CHEK2 gene: the importance of collaboration
Poster Session, Saturday 28 January 2017 Results: Of 356 eligible patients, 218 (61%) were included in the analyses. Patient experienced continuity was statistically significantly higher in the smaller BCU as compared to the larger (76.3 and 67.1 points respectively of 100 points possible, p < 0.0001). Corresponding results were shown for proportion of patients scoring above the cut-off score of 75 points for “high continuity” (60.8% at the smaller BCU and 23.7% at the larger BCU, p < 0.0001). However, no clinically significant differences were found regarding medical quality and lead times. Regarding the association between experienced continuity and HRQoL, differences were found in HRQoL between the two groups of patients; high experienced continuity and low experienced continuity. High experienced continuity was associated with higher levels in all measured HRQoL scales. The differences in HRQoL score between the two groups were clinically significant (= difference more than four) regarding global HRQoL (9.3), emotional functioning (11.8), cognitive functioning (7.3), role functioning (5.8) and fatigue (11.2). The differences were also statistically significant, regarding global HRQoL (p = 0.03), emotional functioning (p = 0.006) and fatigue (p = 0.02). Conclusion: The higher continuity of care at the smaller unit was compatible with good medical quality and approved lead times. High experienced continuity and HRQoL were strongly associated. Prospective studies of interventions to improve continuity of care are warranted, using standardised assessment tools. No conflict of interest. 208 POSTER Classifying variants in the CHEK2 gene: the importance of collaboration C. Espenschied1 , P. Kleiblova2 , M. Richardson1 , L. Stolarova3 , J. Soukupova3 , P. Zemankova3 , M. Vocka4 , L. Panos Smith5 , J. Dolinsky1 , C.L. Gau1 , Z. Kleibl3 . 1 Ambry Genetics, Clinical Diagnostics, Aliso Viejo, USA; 2 Charles University in Prague, Institute of Biochemistry and Experimental Oncology- First Faculty of Medicine and Institute of Biology and Medical Genetics- First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic; 3 Charles University in Prague, Institute of Biochemistry and Experimental Oncology- First Faculty of Medicine, Prague, Czech Republic; 4 Charles University in Prague, Department of Oncology- First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic; 5 Ambry Genetics, Genetics, Aliso Viejo, USA Background: In recent years, analysis for hereditary cancer has expanded beyond well-known, high-risk genes, such as BRCA1 and BRCA2, to multi-gene panels. One gene in which mutations are frequently identified is CHEK2. Mutations in CHEK2 have been linked to an increased risk of several cancers, primarily breast and colorectal cancer, but these risks are not well defined. Advising patients on variants of unknown significance, which are inconclusive with regard to predicting cancer risk, is challenging for clinicians. Clinical laboratories must constantly work to classify these variants based on evolving data. Recommendations for interpreting genetic variants are well established, but may not completely apply for moderately penetrant genes, like CHEK2. For these genes, functional data is often required, but can be difficult to obtain. Variations in the data available to, and lines of evidence used by, different laboratories can lead to discrepancies in variant classification. These discrepancies further complicate the clinical interpretation of test results and may increase anxiety for patients. Here, we report on the collaboration of two laboratories to improve CHEK2 variant classifications using a data sharing approach. Material and Methods: CHEK2 alterations identified at one U.S. commercial laboratory and one European academic laboratory were compiled and compared for shared alterations. When classifications differed between labs, supporting evidence for the classification, including functional evidence, structural analysis, and in some cases, internal frequency data were shared as well as interpretation of in silico and population frequency data. Discussions regarding evidence and resolving classification discrepancies are in progress. Results: Of the CHEK2 variants in common between both labs (n = 28), classifications were concordant for 67.9% (n = 19), including two alterations with only confidence discrepancies, i.e. pathogenic versus likely pathogenic or likely benign versus polymorphism. Classification discrepancies (n = 9, 32.1%) were primarily due to differences in how phenotype, general population frequency, and familial segregation data are used and/or the amount of evidence needed to classify a variant. Conclusions: In this comparison, 32.1% of classifications were discrepant based on differences in classification criteria and available data at each lab. We are currently working to resolve these discrepancies by sharing data and supporting evidence. Our study highlights the challenges of interpreting variants in moderate risk cancer genes, and the importance of data sharing and collaboration between laboratories
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to reduce classification discrepancies, improve variant interpretation, and provide clearer information for clinicians and patients. This work was supported by grants NV15–28830A, NV15–27695A and NV16–29959A. Conflict of interest: Other Substantive Relationships: Espenschied, Richardson, Panos Smith, Dolinksy, and Gau are full-time employees of Ambry Genetics, a diagnostic laboratory which provides hereditary cancer genetic testing. 208A POSTER Early phase clinical trials conducted in North America are more likely to exclude breast cancer patients based on organ function and comorbidities compared to other countries: Analysis of 484 studies V. Mariotti1 , M. Gonzalez Velez1 , N. Duma2 , R. Parrondo1 , S. Kothadia1 , B. Gladney1 , R. Panchal1 , J. Liu1 , K. Patel1 , R. Undamatla1 . 1 Rutgers NJMS, Internal Medicine, Newark, USA; 2 Mayo Clinic, Hematology Oncology, Rochester, USA Background: Exclusion criteria used in Early phase clinical trials (EPCT) help to achieve accurate results and protect volunteers from potential risks associated with treatments. Such exclusions, however, can impair the applicability of EPCT results. The aim of this study is to analyze and compare the most common exclusion criteria used in breast cancer (BC) EPCT in North America (NA) with the ones used internationally. Material and Methods: ClinicalTrials.gov was queried in 12/01/2015. We reviewed the exclusion criteria of 484 BC EPCT including: age, organ function and comorbidities. Logistic regressions were used to assess association between exclusion criteria and EPCT location/funding. Results: Among the 484 EPCT, 273 (56.4%) were conducted in North America (NA), 55 (11.4%) in Europe (EU) and 156 (32%) in other countries. 241 (49.8%) EPCT were funded by industry, while 243 (50.2%) were investigator initiated or internally funded. NA EPCT were less likely to be industry funded compared to EPCT conducted elsewhere (NA 33.3% vs. EU 60% vs. international/other countries 75%). 149 (67.7%) EPCT excluded patients (pts) <18 years old, 56 (11.6%) pts with diabetes mellitus, 122 (25.2%) pts with arrhythmias, 233 (48.1%) pts with heart failure, 231 (47.7%) pts with coronary artery disease, 139 (28.7%) pts with HIV, 92 (19%) pts with hepatitis, 235 (48.6%) pts with previous or synchronous cancer history, and 347 (71.7%) pts with brain metastasis. On univariate analysis, trials conducted in NA were more likely to exclude pts with brain metastasis (OR 0.63, 95% CI 0.42–0.93, p < 0.05), hemoglobin 12 g/dL or lower (OR 0.6, 95% CI 0.41–0.87, p < 0.05), platelets 150×109 cells/L or lower (OR 0.3, 95% CI 0.20–0.43, p < 0.05), white blood cells (WBC) 4500 cells/mL or lower (OR 0.34, 95% CI 0.18–0.63), heart failure (OR 0.47, CI 0.32–0.66, p < 0.05), arrhythmias (OR 0.54, CI 0.35– 0.83, p < 0.05), coronary artery disease (CAD) (OR 0.43, 95% CI 0.29– 0.62, p < 0.05), HIV (OR 0.37, 95% CI 0.24–0.57, p < 0.05) or hepatitis (OR 0.56, 95% CI 0.35–0.91, p < 0.05). EPCT funded by the industry were more likely to include pts with platelets 150×109 cells/L or lower (OR 5.9, 95% CI 4−8.7, p < 0.05), WBC 4500 cells/mL or lower (OR 4.8, 95% CI 2.5−9.3, p < 0.05), CAD (OR 1.5, 95% CI 1−2.1, p < 0.05), HIV (OR 1.8, 95% CI 1.2−2.7, p < 0.05) and previous or synchronous cancer history (OR 1.7, 95% CI 1.1−2.4, p < 0.05) compared to EPCT funded by investigators or institutions. Conclusions: EPCT conducted in NA are more likely to exclude BC pts based on organ function and comorbidities, and EPCT funded by industry are more likely to include pts with organ dysfunction or with comorbidities. Our findings highlight that careful evaluation of exclusion criteria in EPCT is needed, as the results might not be applicable to the real-world BC patient population. No conflict of interest. 209 POSTER Assessing breast cancer cell lines as tumour models by comparison of mRNA expression profiles J. Nandunga1 . 1 SAVE ALIFE Foundation, Research, Kampala, Ouganda Background: Breast cancer researchers use cell lines to model myriad phenomena ranging from DNA repair to cancer stem cell phenotypes. Though appropriate, and even requisite, for many studies, the suitability of cell lines as tumour models has come into question owing to possibilities of tissue culture artefacts and clonal selection. These issues are compounded by the inability of cancer cells grown in isolation to fully model the in situ tumour environment, which also contains a plethora of non-tumour cell types. It is thus important to understand similarities and differences between cancer cell lines and the tumours that they represent so that the optimal tumour models can be chosen to answer specific research questions.
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to reduce classification discrepancies, improve variant interpretation, and provide clearer information for clinicians and patients. This work was supported by grants NV15–28830A, NV15–27695A and NV16–29959A. Conflict of interest: Other Substantive Relationships: Espenschied, Richardson, Panos Smith, Dolinksy, and Gau are full-time employees of Ambry Genetics, a diagnostic laboratory which provides hereditary cancer genetic testing. 208A POSTER Early phase clinical trials conducted in North America are more likely to exclude breast cancer patients based on organ function and comorbidities compared to other countries: Analysis of 484 studies V. Mariotti1 , M. Gonzalez Velez1 , N. Duma2 , R. Parrondo1 , S. Kothadia1 , B. Gladney1 , R. Panchal1 , J. Liu1 , K. Patel1 , R. Undamatla1 . 1 Rutgers NJMS, Internal Medicine, Newark, USA; 2 Mayo Clinic, Hematology Oncology, Rochester, USA Background: Exclusion criteria used in Early phase clinical trials (EPCT) help to achieve accurate results and protect volunteers from potential risks associated with treatments. Such exclusions, however, can impair the applicability of EPCT results. The aim of this study is to analyze and compare the most common exclusion criteria used in breast cancer (BC) EPCT in North America (NA) with the ones used internationally. Material and Methods: ClinicalTrials.gov was queried in 12/01/2015. We reviewed the exclusion criteria of 484 BC EPCT including: age, organ function and comorbidities. Logistic regressions were used to assess association between exclusion criteria and EPCT location/funding. Results: Among the 484 EPCT, 273 (56.4%) were conducted in North America (NA), 55 (11.4%) in Europe (EU) and 156 (32%) in other countries. 241 (49.8%) EPCT were funded by industry, while 243 (50.2%) were investigator initiated or internally funded. NA EPCT were less likely to be industry funded compared to EPCT conducted elsewhere (NA 33.3% vs. EU 60% vs. international/other countries 75%). 149 (67.7%) EPCT excluded patients (pts) <18 years old, 56 (11.6%) pts with diabetes mellitus, 122 (25.2%) pts with arrhythmias, 233 (48.1%) pts with heart failure, 231 (47.7%) pts with coronary artery disease, 139 (28.7%) pts with HIV, 92 (19%) pts with hepatitis, 235 (48.6%) pts with previous or synchronous cancer history, and 347 (71.7%) pts with brain metastasis. On univariate analysis, trials conducted in NA were more likely to exclude pts with brain metastasis (OR 0.63, 95% CI 0.42–0.93, p < 0.05), hemoglobin 12 g/dL or lower (OR 0.6, 95% CI 0.41–0.87, p < 0.05), platelets 150×109 cells/L or lower (OR 0.3, 95% CI 0.20–0.43, p < 0.05), white blood cells (WBC) 4500 cells/mL or lower (OR 0.34, 95% CI 0.18–0.63), heart failure (OR 0.47, CI 0.32–0.66, p < 0.05), arrhythmias (OR 0.54, CI 0.35– 0.83, p < 0.05), coronary artery disease (CAD) (OR 0.43, 95% CI 0.29– 0.62, p < 0.05), HIV (OR 0.37, 95% CI 0.24–0.57, p < 0.05) or hepatitis (OR 0.56, 95% CI 0.35–0.91, p < 0.05). EPCT funded by the industry were more likely to include pts with platelets 150×109 cells/L or lower (OR 5.9, 95% CI 4−8.7, p < 0.05), WBC 4500 cells/mL or lower (OR 4.8, 95% CI 2.5−9.3, p < 0.05), CAD (OR 1.5, 95% CI 1−2.1, p < 0.05), HIV (OR 1.8, 95% CI 1.2−2.7, p < 0.05) and previous or synchronous cancer history (OR 1.7, 95% CI 1.1−2.4, p < 0.05) compared to EPCT funded by investigators or institutions. Conclusions: EPCT conducted in NA are more likely to exclude BC pts based on organ function and comorbidities, and EPCT funded by industry are more likely to include pts with organ dysfunction or with comorbidities. Our findings highlight that careful evaluation of exclusion criteria in EPCT is needed, as the results might not be applicable to the real-world BC patient population. No conflict of interest. 209 POSTER Assessing breast cancer cell lines as tumour models by comparison of mRNA expression profiles J. Nandunga1 . 1 SAVE ALIFE Foundation, Research, Kampala, Ouganda Background: Breast cancer researchers use cell lines to model myriad phenomena ranging from DNA repair to cancer stem cell phenotypes. Though appropriate, and even requisite, for many studies, the suitability of cell lines as tumour models has come into question owing to possibilities of tissue culture artefacts and clonal selection. These issues are compounded by the inability of cancer cells grown in isolation to fully model the in situ tumour environment, which also contains a plethora of non-tumour cell types. It is thus important to understand similarities and differences between cancer cell lines and the tumours that they represent so that the optimal tumour models can be chosen to answer specific research questions.