Citations

Abstract Lung cancer (LC) is the most common cause of cancer mortality and the third most common cancer by incidence in the United States. While environmental factors play an important role in its development, LC risk also exhibits a high degree of heritability. Linkage analyses and genome-wide association studies have identified multiple loci associated with increased LC risk; however, much of the heritability has yet to be explained by these loci. Structural mutations, including copy number variations (CNVs), contribute to phenotypic diversity through dosage and/or cis-regulatory effects. Unbiased CNV mapping is only possible with the use of high-depth, short-read sequencing and remains much more complicated and prone to false positives than SNP detection. As the tools necessary for CNV detection have improved, both somatic and germline CNVs have been shown to play an important role in disease, especially cancer, and often they account for a significant proportion of pathogenic variants. Little has been done to understand the role of germline CNVs in the biological pathways of hereditary lung cancer (HLC). The goal of the current project is to utilize the whole exome sequencing (WES) data in identifying the CNVs in the HLC families (≥3 LC/family) recruited by the Genetic Epidemiology of Lung Cancer Consortium (GELCC). This work uses germline WES data from 203 individuals (60 with a LC diagnosis) from 25 HLC families (≥3 LC affected/family). We limited our investigation to CNVs called by two independent tools using read depth to infer copy number changes and genomic breakpoints: GATK 4 (https://gatk.broadinstitute.org) and XHMM (https://atgu.mgh.harvard.edu/xhmm/). We have identified CNVs (deletions) in the following protein coding genes: KIR2DL1 (19q13.42; OR=1.77), DMBT1 (10q26.13; OR=1.56), SIBPB1 (20p13; OR=1.53), LILRA6 (20p13; OR=1.53), and HLA-DRB5 (6p21.32; OR=1.64) in ≥3 families in at least two individuals/family. All of these genes with the exception of HLA-DRB5 were previously reported in LC studies; HLA-DRB5 was reported in other cancer studies. DMBT1 was reported to be a candidate tumor suppressor gene and frequent loss of heterozygosity (LOH) was observed in several human tumors. It is highly expressed in lung and loss of expression was reported in LC cell lines. All CNVs identified in our study are consistent with Mendelian expectations and appear to be uncommon in the general population. CNVs in these genes may contribute to the lung cancer risk in the HLC families. Further validation of the identified variants is ongoing. We will consider overall CNV burden and disease association with identified deletions and duplications. The enrichment of rare variants in oncogenically associated genes that co-segregate with LC provides specific mutations for future work and improves our understanding of the inheritance and pathogenesis of LC. Citation Format: John Waldron, Kirsten W. Termine, Anthony M. Musolf, Mariza de Andrade, Colette Gaba, Ramaswamy Govindan, Ping Yang, Ming You, Ellen Jaeger, Angelle F. Bencaz, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson, Diptasri M. Mandal. Analyses of whole exome sequencing (WES) data of hereditary lung cancer families identify germline copy number variations (CNVs) in multiple genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1452.

525 Background: Homologous recombination deficiency (HRD) status can be used to identify patients who are eligible for treatment with DNA damaging agents. Using a 3-biomarker Genomic Instability Score (GIS) threshold of ≥42, studies have previously examined the association between HRD status and outcomes in patients with triple negative breast cancer (TNBC). However, evidence suggests that a GIS threshold of ≥33 may be more appropriate. Here, we conducted an exploratory analysis evaluating the ability of ≥33 and ≥42 GIS thresholds to predict response to platinum-based treatment in patients with TNBC. Methods: Patients across 5 cohorts (TBCRC0301, TBCRC0082, NCT013725793, PrECOG 01054, combined cisplatin cohort4) were included in this analysis if they had a primary TNBC diagnosis, received neoadjuvant platinum-based treatment, had a valid GIS, and had known pathologic complete response (pCR) status. GIS was determined by a combination of loss of heterozygosity, telomeric-allelic imbalance, and large-scale state transitions.4,5 BRCA mutation status was defined by loss of function resulting from a pathogenic variant in BRCA1 or BRCA2. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were calculated by comparing binary threshold status and binary pCR status. Results: A total of 204 tumors (158 BRCAwt; 33 BRCAm; 13 unknown) were included; pCR to platinum-based treatment occurred in 55 cases (39 BRCAwt; 14 BRCAm; 2 unknown). Sensitivity, specificity, PPV, and NPV were comparable between the ≥33 and ≥42 GIS thresholds, with the ≥33 threshold producing higher sensitivity values. This was true when thresholds were applied to all samples and to BRCAwt samples only (Table). Among patients who achieved pCR in response to platinum-based treatment, 5.5% of patients in the full cohort and 7.7% of those in the BRCAwt cohort had a GIS between 33-41. Conclusions: To ensure that the majority of patients likely to benefit from treatment are identified, a GIS of ≥33 may be the most appropriate threshold to predict response to platinum-based treatment in patients with TNBC; however, a prospective trial will be needed to confirm these findings. Additional studies will be important to determine whether this threshold may be appropriate to determine eligibility for other DNA-damaging agents such as PARP inhibitors. 1. Ann Oncol. 2020;31(11):1518-25 2. J Nucl Med. 2015;56(1):31-7. 3. Breast Cancer Res Treat. 2015;151(3):629-38. 4. Clin Cancer Res. 2016;22(15):3764-73. 5. Breast Cancer Res Treat. 2014;16(6):1-9. [Table: see text]

The effects of the COVID-19 pandemic on the healthcare system have been widespread, with many institutions in the United States pausing elective procedures to redirect resources to critical care. Fertility care and assisted reproductive procedures were classified as elective procedures and similarly paused. We conducted qualitative interviews with patients and/or their partners ( n = 25 female patients; n = 3 male partners) receiving care at a fertility clinic in the Midwest to understand patient appraisal of COVID-19 risk on the resumption of care following a month-long closure of an infertility clinic, and patient agreement with the clinic closure. Interview transcripts were thematically analyzed from a grounded theory approach. Study participants reported an increased sense of urgency due to the delay in fertility procedures. This urgency often superseded concerns of potential COVID-19 infection, motivating patients to continue fertility treatment during a pandemic. In hindsight, some participants did not agree with the clinic's closure and treatment cessation, feeling that these steps negatively interrupted time-sensitive reproductive goals. Patient responses highlight the need for additional resources to support decision-making during times of crisis. Triaging patients based on time-sensitivity of treatment instead of a total shutdown respects patient autonomy for continuing treatment amidst uncertain COVID-19-impact.

The prevalence of carbapenem-resistant Klebsiella pneumoniae (CR Kp ) infections in nosocomial settings remains a public health challenge. High-risk clones such as clonal group 258 (CG258) are particularly concerning due to their association with bla KPC carriage, which can severely complicate antimicrobial treatments.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Carbapenem-resistant Acinetobacter baumannii (CR Ab ) constitutes a major threat to public health. To elucidate the molecular and clinical epidemiology of CR Ab in the United States, clinical CR Ab isolates were collected along with data on patient characteristics and outcomes, and bacterial isolates underwent whole-genome sequencing and antibiotic susceptibility phenotyping.

AbstractBackgroundThe development of systemic treatment options leveraging the molecular landscape of advanced thyroid cancer is a burgeoning field. This is a multidisciplinary evidence‐based statement on the definition of advanced thyroid cancer and its targeted systemic treatment.MethodsAn expert panel was assembled, a literature review was conducted, and best practice statements were developed. The modified Delphi method was applied to assess the degree of consensus for the statements developed by the author panel.ResultsA review of the current understanding of thyroid oncogenesis at a molecular level is presented and characteristics of advanced thyroid cancer are defined. Twenty statements in topics including the multidisciplinary management, molecular evaluation, and targeted systemic treatment of advanced thyroid cancer are provided.ConclusionsWith the growth in targeted treatment options for thyroid cancer, a consensus definition of advanced disease and statements regarding the utility of molecular testing and available targeted systemic therapy is warranted.

Abstract Background: Patients with homologous recombin ation (HR) deficient tumors may benefit from treatment with DNA damaging agents. Markers of genomic instability can be used to identify HR deficiency, including a 3-biomarker Genomic Instability Score (GIS). For patients with ovarian cancer (OC), the FDA-approved GIS threshold for identifying HR deficiency is 42, set as the 5th percentile for BRCA deficient tumors. Recently, a lower 1st percentile cutoff of 33 was explored in OC; this threshold was significantly associated with improved outcome after platinum-based treatment.1,2 Determining an optimal GIS threshold for different types of tumors is crucial, as the GIS distribution may vary between different cancers and even between different cancer subtypes. We propose GIS thresholds for breast cancer separately for triple-negative breast cancer (TNBC) and estrogen receptor-positive (ER+) breast cancer, using the exploratory threshold of 33 for OC as a comparator. Methods: GISs in BRCA deficient tumors were determined for patients newly diagnosed with varying stages of OC, TNBC, or ER+ breast cancer across 5 cohorts (Timms et al,3 TCGA,4 Abkevich et al,5 TBCRC008,6 the OlympiaD trial7). GIS was determined as a combination of loss of heterozygosity, telomeric-allelic imbalance, and large-scale state transitions. BRCA deficiency was defined by loss of function resulting from a pathogenic variant in BRCA1 or BRCA2 or by methylation of the BRCA1 promoter region, with loss of heterozygosity in the affected gene. GIS distributions in different cancer types and subtypes were compared using the Kolmogorov-Smirnov test. A normal distribution was fit to GISs in BRCA deficient ER+ breast tumors. The 1st percentile of the fitted distribution was chosen as the threshold. Results: A total of 561 OC tumors (190 BRCA deficient), 99 TNBC tumors (44 BRCA deficient), and 406 ER+ breast tumors (76 BRCA deficient) were included across the 5 cohorts. When score distributions were evaluated for BRCA deficient tumors, the GIS distribution within ER+ breast cancer was significantly different than for OC (p=9.6x10-5) and TNBC (p=3.2x10-4). This indicates that different GIS thresholds are appropriate for breast cancer subtypes and that the GIS threshold developed for OC is not appropriate for ER+ breast cancer. The 1st percentile of a normal distribution fit in BRCA deficient ER+ breast cancer tumors yields a threshold of 24. Using this threshold, 45.1% (183/406; 75 BRCA deficient, 108 BRCA intact) of ER+ breast tumors were HR deficient. In contrast, the GIS distribution for TNBC was not significantly different than for OC (p=0.77). Using the exploratory threshold of 33, 63.6% (63/99; 44 BRCA deficient, 19 BRCA intact) of TNBC tumors were HR deficient. Conclusions: When compared to OC, the distribution of GIS in BRCA deficient tumors was different for ER+ breast cancer, but not for TNBC. These findings are consistent with the fact that OC and TNBC are known to have similar molecular signatures.8 Exploratory thresholds of 24 for ER+ breast cancer, and 33 for TNBC and OC could be examined to determine if these cutoffs are associated with a benefit from treatment with DNA targeting agents. Clinical validity and utility of these more inclusive 1% thresholds would require demonstration of correlation with clinical outcomes. The threshold difference observed between these cancer subtypes also suggests that cancer or cancer subtype specific thresholds may be needed as evaluations of HR deficiency expands beyond OC to identify candidates for PARP inhibitors. References: 1 Mol Cancer Res. 2018;16(7):1103-11. 2 Cancers. 2021;13(5):946. 3 Br J Cancer. 2012;107(10):1776-82. 4 Nature. 2012;490(7418):61-70. 5 Breast Cancer Res. 2014;16(145):1-9. 6 J Nucl Med. 2015;56(1):31-7. 7 NEJM. 2017;377(17):1700. 8 Int J Mol Sci. 2016;17(5):759. Citation Format: Kirsten M Timms, Lauren Lenz, Chris Neff, Cara Solimeno, Darl Flake, Judy C Boughey, Matthew P Goetz, Andrea Richardson, Anna Maria Storniolo, Alexander Gutin, Roisin M Connolly, Vered Stearns, Jerry S Lanchbury. Identifying homologous recombination deficiency in breast cancer: Genomic instability score thresholds differ in breast cancer subtypes [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-09.