Brian Drohan

Inducible and constitutive heat shock gene expression responds to modification of Hsp70 copy number in Drosophila melanogaster but does not compensate for loss of thermotolerance in Hsp70 null flies

BackgroundThe heat shock protein Hsp70 promotes inducible thermotolerance in nearly every organism examined to date. Hsp70 interacts with a network of other stress-response proteins, and dissecting the relative roles of these interactions in causing thermotolerance remains difficult. Here we examine the effect of Hsp70 gene copy number modification on thermotolerance and the expression of multiple stress-response genes in Drosophila melanogaster, to determine which genes may represent mechanisms of stress tolerance independent of Hsp70.ResultsHsp70 copy number in four strains is positively associated with Hsp70 expression and inducible thermotolerance of severe heat shock. When assayed at carefully chosen temperatures, Hsp70 null flies are almost entirely deficient in thermotolerance. In contrast to expectations, increasing Hsp70 expression levels induced by thermal pretreatment are associated with increasing levels of seven other inducible Hsps across strains. In addition, complete Hsp70 loss causes upregulation of the inducible Hsps and six constitutive stress-response genes following severe heat shocks.ConclusionModification of Hsp70 copy number quantitatively and qualitatively affects the expression of multiple other stress-response genes. A positive association between absolute expression levels of Hsp70 and other Hsps after thermal pretreatment suggests novel regulatory mechanisms. Severe heat shocks induce both novel gene expression patterns and almost total mortality in the Hsp70 null strain: alteration of gene expression in this strain does not compensate for Hsp70 loss but suggests candidates for overexpression studies.

Identification and Management of Women at High Risk for Hereditary Breast/Ovarian Cancer Syndrome

Abstract:  Despite advances in identifying genetic markers of high risk patients and the availability of genetic testing, it remains challenging to efficiently identify women who are at hereditary risk and to manage their care appropriately. HughesRiskApps, an open‐source family history collection, risk assessment, and Clinical Decision Support (CDS) software package, was developed to address the shortcomings in our ability to identify and treat the high risk population. This system is designed for use in primary care clinics, breast centers, and cancer risk clinics to collect family history and risk information and provide the necessary CDS to increase quality of care and efficiency. This paper reports on the first implementation of HughesRiskApps in the community hospital setting. HughesRiskApps was implemented at the Newton‐Wellesley Hospital. Between April 1, 2007 and March 31, 2008, 32,966 analyses were performed on 25,763 individuals. Within this population, 915 (3.6%) individuals were found to be eligible for risk assessment and possible genetic testing based on the 10% risk of mutation threshold. During the first year of implementation, physicians and patients have fully accepted the system, and 3.6% of patients assessed have been referred to risk assessment and consideration of genetic testing. These early results indicate that the number of patients identified for risk assessment has increased dramatically and that the care of these patients is more efficient and likely more effective.

Hereditary Breast and Ovarian Cancer and Other Hereditary Syndromes: Using Technology to Identify Carriers

Purpose and MethodsMost patients who harbor a genetic mutation for hereditary breast cancer have not been identified, despite the availability of genetic testing. Developing an effective approach to the identification of high-risk individuals is the key to preventing and/or providing early diagnosis of cancer in this patient population. This educational review addresses these issues.Results and DiscussionUsing data available on the internet, and making assumptions regarding the types and results of genetic testing, we have estimated the number of mutation carriers in the country and the number who have been tested and identified as such. Overall, our ability to fund and more effectively manage carriers is weak. A technological solution is discussed.

The feasibility of using natural language processing to extract clinical information from breast pathology reports.

Objective: The opportunity to integrate clinical decision support systems into clinical practice is limited due to the lack of structured, machine readable data in the current format of the electronic health record. Natural language processing has been designed to convert free text into machine readable data. The aim of the current study was to ascertain the feasibility of using natural language processing to extract clinical information from >76,000 breast pathology reports. Approach and Procedure: Breast pathology reports from three institutions were analyzed using natural language processing software (Clearforest, Waltham, MA) to extract information on a variety of pathologic diagnoses of interest. Data tables were created from the extracted information according to date of surgery, side of surgery, and medical record number. The variety of ways in which each diagnosis could be represented was recorded, as a means of demonstrating the complexity of machine interpretation of free text. Results: There was widespread variation in how pathologists reported common pathologic diagnoses. We report, for example, 124 ways of saying invasive ductal carcinoma and 95 ways of saying invasive lobular carcinoma. There were >4000 ways of saying invasive ductal carcinoma was not present. Natural language processor sensitivity and specificity were 99.1% and 96.5% when compared to expert human coders. Conclusion: We have demonstrated how a large body of free text medical information such as seen in breast pathology reports, can be converted to a machine readable format using natural language processing, and described the inherent complexities of the task.

Which risk model to use? Clinical implications of the ACS MRI screening guidelines.

The American Cancer Society (ACS) guidelines define the appropriate use of MRI as an adjunct to mammography for breast cancer screening. Three risk assessment models are recommended to determine if women are at sufficient risk to warrant the use of this expensive screening tool, however, the real-world application of these models has not been explored. We sought to understand how these models behave in a community setting for women undergoing mammography screening. We conducted a retrospective analysis of 5,894 women, who received mammography screening at a community hospital and assessed their eligibility for MRI according to the ACS guidelines. Of the 5,894 women, 342 (5.8%) were eligible for MRI, but we found significant differences in the number of eligible women identified by each model. Our results indicate that these models identify very different populations, implying that the ACS guidelines deserve further development and consideration. Cancer Epidemiol Biomarkers Prev; 22(1); 146–9. ©2012 AACR.

Bias in the reporting of family history: implications for clinical care.

Family history of cancer is critical for identifying and managing patients at risk for cancer. However, the quality of family history data is dependent on the accuracy of patient self reporting. Therefore, the validity of family history reporting is crucial to the quality of clinical care. A retrospective review of family history data collected at a community hospital between 2005 and 2009 was performed in 43,257 women presenting for screening mammography. Reported numbers of breast, colon, prostate, lung, and ovarian cancer were compared in maternal relatives vs. paternal relatives and in first vs. second degree relatives. Significant reporting differences were found between maternal and paternal family history of cancer, in addition to degree of relative. The number of paternal family histories of cancer was significantly lower than that of maternal family histories of cancer. Similarly, the percentage of grandparents’ family histories of cancer was significantly lower than the percentage of parents’ family histories of cancer. This trend was found in all cancers except prostate cancer. Self-reported family history in the community setting is often influenced by both bloodline of the cancer history and the degree of relative affected. This is evident by the underreporting of paternal family histories of cancer, and also, though to a lesser extent, by degree. These discrepancies in reporting family history of cancer imply we need to take more care in collecting accurate family histories and also in the clinical management of individuals in relation to hereditary risk.

Accuracy of Self-Reported Personal History of Cancer in an Outpatient Breast Center

The self-reporting of cancer history is becoming increasingly important, as it frequently guides medical decision-making. We studied the accuracy of personal cancer history using a self-administered questionnaire, comparing the results with the Tumor Registry at our institution. Among 39,662 records, we identified 3614 women with a single cancer in the Tumor Registry who reported none or one cancer on their questionnaire. The sensitivity in self-reporting cancers was 85.7%, ranging from 92.1% for breast cancer to 42.9% for leukemia. The accuracy for breast cancer and Hodgkins Lymphoma was significantly better than other cancers (p=0.00027, CI: 1.4–3.88). Analysis of patients characteristics showed that Caucasians reported breast cancer more accurately than Asian/Pacific Islanders (p=0.008), and those with Jewish ancestry more accurately than non-Jewish (p=0.0435). These results will help us to improve data collection and thus improve medical decision-making.

The American Cancer Society guidelines for breast screening with magnetic resonance imaging: an argument for genetic testing.

The American Cancer Society (ACS) guidelines for screening with breast magnetic resonance imaging (MRI) recommend MRI for women who have a lifetime risk ≥20% of developing breast cancer. Genetic testing for breast cancer gene (BRCA) mutations is offered to women who have a risk ≥10% of carrying a mutation. The objectives of the current study were 1) to identify the number of women in a breast cancer screening population who had ≥20% lifetime breast cancer risk and, thus, were candidates for screening MRI; and 2) to determine the number of women who had ≥10% risk of BRCA mutation yet had <20% lifetime risk of breast cancer and, thus, may not have been identified as candidates for MRI screening.

Electronic Health Records and the Management of Women at High Risk of Hereditary Breast and Ovarian Cancer

Abstract:  Currently, management strategies exist that can decrease the morbidity and mortality associated with having a BRCA1 or BRCA2 mutation. Unfortunately, the task of identifying these patients at high risk is a daunting challenge. This problem is intensified because Electronic Health Records (EHRs) today lack the functionality needed to identify these women and to manage those women once they have been identified. Numerous niche software programs have been developed to fill this gap. Unfortunately, these extremely valuable niche programs are prevented from being interoperable with the EHRs, on the premise that each EHR vendor will build their own programs. Effectively, in our efforts to adopt EHRs, we have lost sight of the fact that they can only have a major impact on quality of care if they contain structured data and if they interact with robust Clinical Decision Support (CDS) tools. We are at a cross roads in the development of the health care Information Technology infrastructure. We can choose a path where each EHR vendor develops each CDS module independently. Alternatively, we can choose a path where experts in each field develop external niche software modules that are interoperable with any EHR vendor. We believe that the modular approach to development of niche software programs that are interoperable with current EHRs will markedly increase the speed at which useful and functional EHRs that improve quality of care become a reality. Thus, in order to realize the benefits of CDS, we suggest vendors develop means to become interoperable with external modular niche programs.

Implementation of an electronic genomic and family health history tool in primary prenatal care

“The Pregnancy and Health Profile,” (PHP) is a free genetic risk assessment software tool for primary prenatal providers that collects patient‐entered family (FHH), personal, and obstetrical health history, performs risk assessment, and presents the provider with clinical decision support during the prenatal encounter. The tool is freely available for download at www.hughesriskapps.net. We evaluated the implementation of PHP in four geographically diverse clinical sites. Retrospective chart reviews were conducted for patients seen prior to the study period and for patients who used the PHP to collect data on documentation of FHH, discussion of cystic fibrosis (CF) and hemoglobinopathy (HB) carrier screening, and CF and HB interventions (tests, referrals). Five hundred pre‐implementation phase and 618 implementation phase charts were reviewed. Documentation of a 3‐generation FHH or pedigree improved at three sites; patient race/ethnicity at three sites, father of the baby (FOB) race/ethnicity at all sites, and ancestry for the patient and FOB at three sites (P < 0.001–0001). CF counseling improved for implementation phase patients at one site (8% vs. 48%, P < 0.0001) and CF screening/referrals at two (2% vs. 14%, P < 0.0001; 6% vs. 14%; P = 0.05). Counseling and intervention rates did not increase for HB. This preliminary study suggests that the PHP can improve documentation of FHH, race, and ancestry, as well as the compliance with current CF counseling and intervention guidelines in some prenatal clinics. Future evaluation of the PHP should include testing in a larger number of clinical environments, assessment of additional performance measures, and evaluation of the systems overall clinical utility.