Intermuscular Coherence in Spinocerebellar Ataxias 3 and 6: a Preliminary Study

Spinocerebellar ataxias (SCAs) are familial neurodegenerative diseases involving the cerebellum and spinocerebellar tracts. While there is variable involvement of corticospinal tracts (CST), dorsal root ganglia, and motor neurons in SCA3, SCA6 is characterized by a pure, late-onset ataxia. Abnormal intermuscular coherence in the beta-gamma frequency range (IMCβγ) implies a lack of integrity of CST or the afferent input from the acting muscles. We test the hypothesis that IMCβγ has the potential to be a biomarker of disease activity in SCA3 but not SCA6. Intermuscular coherence between biceps brachii and brachioradialis muscles was measured from surface EMG waveforms in SCA3 (N = 16) and SCA6 (N = 20) patients and in neurotypical subjects (N = 23). IMC peak frequencies were present in the β range in SCA patients and in the γ range in neurotypical subjects. The difference between IMC amplitudes in the γ and β ranges was significant when comparing neurotypical control subjects to SCA3 (p < 0.01) and SCA6 (p = 0.01) patients. IMCβγ amplitude was smaller in SCA3 patients compared to neurotypical subjects (p < 0.05), but not different between SCA3 and SCA6 patients or between SCA6 and neurotypical subjects. IMC metrics can differentiate SCA patients from normal controls.

Electronic Health Records (EHRs) Can Identify Patients at High Risk of Fracture but Require Substantial Race Adjustments to Currently Available Fracture Risk Calculators

BACKGROUND

Osteoporotic fracture prediction calculators are poorly utilized in primary care, leading to underdiagnosis and undertreatment of those at risk for fracture. The use of these calculators could be improved if predictions were automated using the electronic health record (EHR). However, this approach is not well validated in multi-ethnic populations, and it is not clear if the adjustments for race or ethnicity made by calculators are appropriate.

OBJECTIVE

To investigate EHR-generated fracture predictions in a multi-ethnic population.

DESIGN

Retrospective cohort study using data from the EHR.

SETTING

An urban, academic medical center in Philadelphia, PA.

PARTICIPANTS

12,758 White, 7,844 Black, and 3,587 Hispanic patients seeking routine care from 2010 to 2018 with mean 3.8 years follow-up.

INTERVENTIONS

None.

MEASUREMENTS

FRAX and QFracture, two of the most used fracture prediction tools, were studied. Risk for major osteoporotic fracture (MOF) and hip fracture were calculated using data from the EHR at baseline and compared to the number of fractures that occurred during follow-up.

RESULTS

MOF rates varied from 3.2 per 1000 patient-years in Black men to 7.6 in White women. FRAX and QFracture had similar discrimination for MOF prediction (area under the curve, AUC, 0.69 vs. 0.70, p=0.08) and for hip fracture prediction (AUC 0.77 vs 0.79, p=0.21) and were similar by race or ethnicity. FRAX had superior calibration than QFracture (calibration-in-the-large for FRAX 0.97 versus QFracture 2.02). The adjustment factors used in MOF prediction were generally accurate in Black women, but underestimated risk in Black men, Hispanic women, and Hispanic men.

LIMITATIONS

Single center design.

CONCLUSIONS

Fracture predictions using only EHR inputs can discriminate between high and low risk patients, even in Black and Hispanic patients, and could help primary care physicians identify patients who need screening or treatment. However, further refinements to the calculators may better adjust for race-ethnicity.

Identifying treatment heterogeneity in atrial fibrillation using a novel causal machine learning method

BACKGROUND

Lifelong oral anticoagulation is recommended in patients with atrial fibrillation (AF) to prevent stroke. Over the last decade, multiple new oral anticoagulants (OACs) have expanded the number of treatment options for these patients. While population-level effectiveness of OACs has been compared, it is unclear if there is variability in benefit and risk across patient subgroups.

METHODS

We analyzed claims and medical data for 34,569 patients who initiated a nonvitamin K antagonist oral anticoagulant (non-vitamin K antagonist oral anticoagulant (NOAC); apixaban, dabigatran, and rivaroxaban) or warfarin for nonvalvular AF between 08/01/2010 and 11/29/2017 from the OptumLabs Data Warehouse. A machine learning (ML) method was applied to match different OAC groups on several baseline variables including, age, sex, race, renal function, and CHA2DS2 -VASC score. A causal ML method was then used to discover patient subgroups characterizing the head-to-head treatment effects of the OACs on a primary composite outcome of ischemic stroke, intracranial hemorrhage, and all-cause mortality.

RESULTS

The mean age, number of females and white race in the entire cohort of 34,569 patients were 71.2 (SD, 10.7) years, 14,916 (43.1%), and 25,051 (72.5%) respectively. During a mean follow-up of 8.3 (SD, 9.0) months, 2,110 (6.1%) of patients experienced the composite outcome, of whom 1,675 (4.8%) died. The causal ML method identified 5 subgroups with variables favoring apixaban over dabigatran; 2 subgroups favoring apixaban over rivaroxaban; 1 subgroup favoring dabigatran over rivaroxaban; and 1 subgroup favoring rivaroxaban over dabigatran in terms of risk reduction of the primary endpoint. No subgroup favored warfarin and most dabigatran vs warfarin users favored neither drug. The variables that most influenced favoring one subgroup over another included Age, history of ischemic stroke, thromboembolism, estimated glomerular filtration rate, Race, and myocardial infarction.

CONCLUSIONS

Among patients with AF treated with a NOAC or warfarin, a causal ML method identified patient subgroups with differences in outcomes associated with OAC use. The findings suggest that the effects of OACs are heterogeneous across subgroups of AF patients, which could help personalize the choice of OAC. Future prospective studies are needed to better understand the clinical impact of the subgroups with respect to OAC selection.

Dismissal disagreement and discharge delays: Associations of patient-clinician plan of care agreement with discharge outcomes

BACKGROUND

Many hospitalized patients do not understand or agree with their clinicians about their discharge plan. However, the effect of disagreement on discharge outcomes is unknown.

OBJECTIVE

To measure the correlation between patient-clinician care agreement and discharge outcomes.

DESIGN

A prospective cohort study was performed from September 2019 to March 2020 (Rochester, MN, USA).

SETTING AND PARTICIPANTS

Internal medicine patients and their primary clinician (resident, advanced practice clinician or attending) hospitalized from September 2019-March 2020 at Mayo Clinic Hospital. Participants were independently surveyed following hospital day #3 ward rounds regarding the goals of the hospitalization and discharge planning.

MAIN OUTCOME AND MEASURES

Patient-clinician agreement for main diagnosis, patient's main concern, and four domains of discharge planning was assessed. Readiness for hospital discharge, delayed discharge, and 30-day readmission was measured. Then, associations between patient-clinician agreement, delayed discharge, and 30-day readmissions were analyzed using multivariable logistic regression.

RESULTS

Of the 436 patients and clinicians, 17.7% completely agreed about what needs to be accomplished before dismissal, 40.8% agreed regarding discharge date, and 71.1% agreed regarding discharge location. In the multivariable model, patient-clinician agreement scores were not significantly correlated with discharge outcomes. Patient-clinician agreement on discharge location was higher for those discharged to home (81.5%) versus skilled nursing facility (48.5%) or assisted living (42.9%) (p < .0001). The agreement on the expected length of stay was highest for home-goers (45.9%) compared to skilled nursing (32.0%) or assisted living (21.4%) (p = .004).

CONCLUSIONS

Patients and their clinicians frequently disagree about when and where a patient will go after hospitalization, particularly for those discharged to a skilled nursing facility. While disagreement did not predict discharge outcomes, our findings suggest opportunities to improve effective communication and promote shared mental models regarding discharge earlier in the hospital stay.

Abstract P2-09-01: Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes

Introduction: The risk of specific clinical subtype of breast cancer (defined by ER and HER2 status) among women in the general population who are carriers of germline pathogenic variants (PVs) in cancer predisposition genes is not well-defined. Methods: A total of 13,153 women with breast cancer (ER+/HER2-: 9381; ER+/HER2+: 1462; ER-/HER2+: 690; and ER-/HER2-: 1620) and 25,005 unaffected women (controls) from nine studies within the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium that were not enriched for family history or early onset disease were included in the present analysis. A multiplex amplicon-based panel was used to perform germline sequencing for cancer predisposition genes. Case-control associations for each of the four clinical subtype of breast cancer was performed for PVs in 5 common breast cancer predisposition genes (ATM, BRCA1, BRCA2, CHEK2 and PALB2) utilizing a logistic regression model adjusting for study, age at diagnosis, race/ethnicity and family history of breast cancer. Results: The frequency of PVs in 5 genes was 3.8% for ER+/HER2-, 6.2% for ER+/HER2+, 4.2% for ER-/HER2+ and 9.3% for ER-/HER2- subtypes. PVs in BRCA1 and BRCA2 were associated with high risk (Odds Ratio (OR) &gt;4) for all clinical subtypes of breast cancer, but the risk was highest (OR&gt;8) for ER-/HER2- breast cancer. PVs in PALB2 were associated with high risk (OR&gt;4) of ER-/HER2- and ER+/HER2+ subtypes and moderate risk (OR: 2-4) of ER+/HER2- breast cancer. Irrespective of the HER2 status, PVs in ATM were associated with a moderately increased risk (OR: 2-4) of ER+ breast cancer but the risk of ER- breast cancer was not elevated. In contrast, PVs in CHEK2 were associated with high risk (OR&gt;4) of ER+/HER2+ breast cancer and moderate risk (OR: 2-4) of ER+/HER2- and ER-/HER2+ breast cancer, but the risk of ER-/HER2- breast cancer was not elevated. Conclusions: This study provides population-based estimates of risk of specific clinical subtypes of breast cancer which will be useful for genetic counseling and targeting appropriate screening strategies in PV carriers based on subtype specific risks of breast cancer.

Citation Format: Siddhartha Yadav, Chunling Hu, Nicholas J. Boddicker, Eric Polley, Steven Hart, Rohan Gnanaolivu, Jie Na, Hongyan Huang, Song Yao, Celine M. Vachon, Lauren Teras, Jack A. Taylor, Dale P. Sandler, Julie R. Palmer, Janet E. Olson, Susan Neuhausen, Elena Martinez, Sara Lindstroem, Loic Le Marchand, Charles Kooperberg, Christopher Haiman, Mia M. Gaudet, James V. Lacey, Kimberly A. Bertrand, Leslie Bernstein, Paul W. Auer, Christine Ambrosone, Jeffrey N. Weitzel, Peter Kraft, David E. Goldgar, Katherine L. Nathanson, Susan M. Domchek, Fergus J. Couch, CARRIERS Consortium. Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes [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 P2-09-01.

Germline pathogenic variants in cancer predisposition genes among women with invasive lobular cancer of breast

10581

Background: The prevalence of germline pathogenic variants (PVs) in cancer predisposition genes among women with invasive lobular breast cancer (ILC) and the risk of ILC in PV carriers is not well-defined. Methods: The study included 2,999 women with ILC and 32,544 unaffected controls from a population-based cohort; 3,796 women with ILC and 20,323 women with invasive ductal carcinoma (IDC) undergoing clinical multigene panel testing (clinical cohort); and 125,748 exome sequences from unrelated women without a cancer diagnosis in the gnomAD 3.0 dataset. Frequencies of germline PVs in breast cancer predisposition genes ( ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, and TP53) were compared between women with ILC and unaffected controls in both cohorts and between women with ILC and IDC in the clinical cohort. Results: The frequency of PVs in breast cancer predisposition genes among women with ILC was 6.5% in the clinical cohort and 5.2% in the population-based cohort. In case-control analyses, CDH1 and BRCA2 PVs were associated with high risks of ILC (Odds ratio (OR) > 4), and CHEK2, ATM and PALB2 PVs were associated with moderate (OR = 2-4) risks. BRCA1 PVs and CHEK2 p.Ile157Thr were not associated with clinically relevant risks (OR < 2) of ILC. PV frequencies in these genes in ILC and IDC were similar except for PV frequencies in BRCA1 and CDH1. Conclusions: The study establishes that PVs in ATM, BRCA2, CDH1, CHEK2 and PALB2 are associated with an increased risk of ILC, whereas BRCA1 PVs are not. The similar overall PV frequencies for ILC and IDC suggest that cancer histology should not influence the decision to proceed with genetic testing. While, multigene panel testing may be appropriate for women with ILC, CDH1 should be specifically discussed in the context of low prevalence and attendant gastric cancer risk.

Breast cancer screening for carriers of ATM, CHEK2, and PALB2 pathogenic variants: A comparative modeling analysis

10500

Background: Inherited pathogenic variants in ATM, CHEK2, and PALB2 confer moderate to high risks of breast cancer. The optimal approach to screening in these women has not been established. Methods: We used two simulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) and data from the Cancer Risk Estimates Related to Susceptibility consortium (CARRIERS) to project lifetime breast cancer incidence and mortality in ATM, CHEK2, and PALB2 carriers. We simulated screening with annual mammography from ages 40-74 alone and with annual magnetic resonance imaging (MRI) starting at ages 40, 35, 30, and 25. Joint and separate mammography and MRI screening performance was based on published literature. Lifetime outcomes per 1,000 women were reported as means and ranges across both models. Results: Estimated risk of breast cancer by age 80 was 22% (21-23%) for ATM, 28% (26-30%) for CHEK2, and 40% (38-42%) for PALB2. Screening with MRI and mammography reduced breast cancer mortality by 52-60% across variants (Table). Compared to no screening, starting MRI at age 30 increased life years (LY)/1000 women by 501 (478-523) in ATM, 620 (587-652) in CHEK2, and 1,025 (998-1,051) in PALB2. Starting MRI at age 25 versus 30 gained 9-12 LY/1000 women with 517-518 additional false positive screens and 197-198 benign biopsies. Conclusions: For women with ATM, CHEK2, and PALB2 pathogenic variants, breast cancer screening with MRI and mammography halves breast cancer mortality. These mortality benefits are similar to those for MRI screening for BRCA1/2 mutation carriers and should inform practice guidelines.[Table: see text]

Relationships Between Time-at-Bedside During Hospital Ward Rounds, Clinician-Patient Agreement, and Patient Experience

Hospital medicine ward rounds are often conducted away from patients’ bedsides, but it is unknown if more time-at-bedside is associated with improved patient outcomes. Our objective is to measure the association between “time-at-bedside,” patient experience, and patient–clinician care agreement during ward rounds. Research assistants directly observed medicine services to quantify the amount of time spent discussing each patient’s care inside versus outside the patient’s room. “Time-at-bedside” was defined as the proportion of time spent discussing a patient’s care in his or her room. Patient experience and patient–clinician care agreement both were measured immediately after ward rounds. Results demonstrated that the majority of patient and physicians completely agreement on planned tests (66.3%), planned procedures (79.7%), medication changes (50.6%), and discharge location (66.9%), but had no agreement on the patient’s main concern (74.4%) and discharge date (50.6%). Time-at-bedside was not correlated with care agreement or patient experience (P > .05 for all comparisons). This study demonstrates that spending more time at the bedside during ward rounds, alone, is insufficient to improve patient experience.

Molecular Profiling-Based Assignment of Cancer Therapy (NCI-MPACT): A Randomized Multicenter Phase II Trial

This trial assessed the utility of applying tumor DNA sequencing to treatment selection for patients with advanced, refractory cancer and somatic mutations in one of four signaling pathways by comparing the efficacy of four study regimens that were either matched to the patient's aberrant pathway (experimental arm) or not matched to that pathway (control arm).

MATERIALS AND METHODS

Adult patients with an actionable mutation of interest were randomly assigned 2:1 to receive either (1) a study regimen identified to target the aberrant pathway found in their tumor (veliparib with temozolomide or adavosertib with carboplatin [DNA repair pathway], everolimus [PI3K pathway], or trametinib [RAS/RAF/MEK pathway]), or (2) one of the same four regimens, but chosen from among those not targeting that pathway.

RESULTS

Among 49 patients treated in the experimental arm, the objective response rate was 2% (95% CI, 0% to 10.9%). One of 20 patients (5%) in the experimental trametinib cohort had a partial response. There were no responses in the other cohorts. Although patients and physicians were blinded to the sequencing and random assignment results, a higher pretreatment dropout rate was observed in the control arm (22%) compared with the experimental arm (6%; P = .038), suggesting that some patients may have had prior tumor mutation profiling performed that led to a lack of participation in the control arm.

CONCLUSION

Further investigation, better annotation of predictive biomarkers, and the development of more effective agents are necessary to inform treatment decisions in an era of precision cancer medicine. Increasing prevalence of tumor mutation profiling and preference for targeted therapy make it difficult to use a randomized phase II design to evaluate targeted therapy efficacy in an advanced disease setting.

Assessment of MRI-detected lesions on screening tomosynthesis in patients with newly diagnosed breast cancer

OBJECTIVES

The purpose of this study is to retrospectively evaluate the presence of screening digital breast tomosynthesis (DBT) correlates for suspicious lesions detected on pre-operative staging magnetic resonance imaging (MRI) in patients with newly diagnosed breast cancer.

METHODS

After approval from the institutional review board (IRB), screening DBTs on breast cancer patients with BI-RADS 4 or 5 staging MRI exams between 8/1/17 and 8/1/18 were assessed for presence of DBT correlates for suspicious MRI findings. The pathology of the index lesion, type of additional MRI finding (mass, non-mass enhancement, or focus), correlative finding on tomosynthesis (mass, asymmetry/focal asymmetry, distortion, or calcifications), size on MRI and tomosynthesis, breast density, and pathology of the additional lesion were recorded. The chi-square test of association was used unless otherwise specified. Confidence intervals for proportions were estimated using the Wilson's score method.

RESULTS

17/70 (24%) of additional lesions seen on pre-operative MRI exams in patients with newly diagnosed cancer had a mammographic correlate on corresponding screening DBT. There was no significant relationship between the presence of a mammographic correlate and the type of MRI finding (mass, NME, or focus), breast density, size of lesion, pathology of index cancer, or pathology of the additional lesion (p≥ 0.05).

CONCLUSIONS

76% of additional lesions seen on pre-operative staging MRI in patients with newly diagnosed breast cancer are not seen retrospectively on screening DBT. Since about 24% of MRI-detected additional lesions may have a DBT correlate, DBT exams should be reviewed in patients recalled for further workup of findings seen on pre-operative MRI since this may facilitate DBT-guided biopsy of suspicious lesions, which is preferable to MRI-guided biopsy for cost and patient comfort reasons.

HIV elite control is associated with reduced TRAILshort expression

OBJECTIVE

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) dependent apoptosis has been implicated in CD4 T-cell death and immunologic control of HIV-1 infection. We have described a splice variant called TRAILshort, which is a dominant negative ligand that antagonizes TRAIL-induced cell death in the context of HIV-1 infection. HIV-1 elite controllers naturally control viral replication for largely unknown reasons. Since enhanced death of infected cells might be responsible, as might occur in situations of low (or inhibited) TRAILshort, we tested whether there was an association between elite controller status and reduced levels of TRAILshort expression.

DESIGN

Cohort study comparing TRAILshort and full length TRAIL expression between HIV-1 elite controllers and viremic progressors from two independent populations.

METHODS

TRAILshort and TRAIL gene expression in peripheral blood mononuclear cells (PBMCs) was determined by RNA-seq. TRAILshort and TRAIL protein expression in plasma was determined by antibody bead array and proximity extension assay respectively.

RESULTS

HIV-1 elite controllers expressed less TRAILshort transcripts in PBMCs (P = 0.002) and less TRAILshort protein in plasma (P < 0.001) than viremic progressors.

CONCLUSION

Reduced TRAILshort expression in PBMCs and plasma is associated with HIV-1 elite controller status.

Racial and ethnic differences in the results of multigene panel testing of inherited cancer predisposition genes in breast cancer patients

1514

Background: The prevalence of germline mutations in non-white patients with breast cancer and the germline genetic drivers of breast cancer risk in non-white populations are largely unknown. Methods: The study population included 77,900 women with breast cancer (Non-Hispanic white: 57,003; Black: 6,722; Asian: 4,183; Hispanic: 5,194; Ashkenazi-Jewish: 4,798) who underwent germline multigene panel testing of cancer predisposition genes from March 2012 to December 2016. The prevalence of predisposition gene mutations in racial and ethnic populations relative to non-Hispanic Whites was assessed while accounting for age at diagnosis of breast cancer, family history of breast and ovarian cancer, and estrogen receptor status of breast tumors. Associations between mutations in each gene and breast cancer risk were evaluated using reference controls. Results: The overall frequency of pathogenic mutations in known breast cancer predisposition genes was 9.1% for non-Hispanic Whites, 9.8% for African Americans, 10.2% for Hispanics, 7.6% for Ashkenazi-Jewish, and 7.5% for Asians. BRCA1 mutations were enriched (p < 0.05) and CHEK2 mutations were under-represented in all racial and ethnic populations relative to non-Hispanic Whites. BRCA2 and BARD1 mutations were enriched in African Americans and Hispanics relative to non-Hispanic Whites, whereas PALB2 and RAD51C mutations were enriched in Hispanics. Among genes with mutation counts large enough for assessment, mutations in BARD1, BRCA1, BRCA2, PALB2 and TP53 were significantly associated with clinically relevant increased risks (odds ratio (OR) > 2) of breast cancer across all ethnicities and races. Rates of variants of uncertain significance were highest among Asians (29%), followed by blacks (27%), Hispanics (21%), non-Hispanic whites (16%) and Ashkenazi-Jews (14%). Conclusions: While there is some similarity across ethnic groups, substantial heterogeneity exists in the prevalence of mutations in breast cancer predisposition genes across major racial and ethnic groups in the US population. These findings contribute to our understanding of breast cancer risk and have significant implications for genetic testing, screening, and management of patients with an inherited predisposition to breast cancer, with a need for continued analysis with increased cohort size in ethnic minority groups.

Genetic predisposition to breast cancer among African American women

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Background: The identification of pathogenic mutations in breast cancer susceptibility genes through clinical genetic testing leads to focused screening and prevention strategies for women at increased risk of cancer. However, the frequency of mutations and the risks of cancer associated with breast cancer predisposition genes has not been established for the African American population. Methods: Germline DNA samples from African American women (5,054 breast cancer cases and 4,993 age-matched unaffected controls) from 10 U.S. studies were tested for mutations in 20 established breast cancer predisposition genes using a QIAseq multiplex amplicon panel as part of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study. The frequency of mutations in each gene and associations between mutations and breast cancer risk, adjusted for study design, age, and first-degree family history of breast cancer, were evaluated. Results: The mean age at diagnosis of breast cancer cases was 54.4 years and the mean age of controls was 55.2 years. 18.2% of cases and 10.8% of controls reported a first-degree family history of breast cancer. Pathogenic mutations in any of the 20 breast cancer predisposition genes were identified in 7.6% of breast cancer cases and 2.4% of controls. In multivariable analyses, mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (odds ratio (OR) > 5.0). Mutations in CHEK2 were associated with moderate risks of breast cancer (OR > 2.0), whereas mutations in ATM had lower clinical relevance (OR = 1.8). Mutations in BRCA1, BRCA2, PALB2, and RAD51D, but not CHEK2 or ATM, were associated with increased risks of estrogen receptor negative breast cancer. Conclusions: Cancer predisposition genes confer similar risks of breast cancer in the African American population as in non-Hispanic Whites. These studies provide important insights into the risks of breast cancer associated with predisposition gene mutations in the African American population.

Prognostic impact of DNA repair germline variants in hormone sensitive prostate cancer stage

262

Background: Inherited and somatic aberrations in DNA repair genes in castrate resistant prostate cancer (CRPC) are associated with poor prognosis, but respond well to poly ADP ribose polymerase (PARP) inhibitors. We evaluated the prevalence and prognostic impact of harboring germline DNA repair variants in hormone sensitive prostate cancer (HSPC). Methods: Germline DNA from buffy coat was sequenced on HiSeq4000 with a median coverage of 200X for DNA repair variants in 20 genes in HSPC and CRPC patients (pts) enrolled in a hospital registry. Pts were divided into two groups; Group A: pts enrolled at the time of CRPC stage; Group B: treatment naïve HSPC stage pts. The primary endpoints were to determine any impact of harboring DNA repair variants on time to progression from HSPC to CRPC and, from CRPC to death. Group A pts were retrospectively analyzed for time to progression from HSPC to CRPC while Group B patients were followed prospectively for outcomes. Statistical analysis included Cox proportional hazard models and Wilcoxon Rank sum test with significance at p≤0.05. Results: In Group A, 51/562 CRPC pts (9.07%) had variants in the 20 genes (most frequently in BRCA2; n = 15). 44/51 pts with variants and 399/511 without variants had died. Median time of progression from HSPC to CRPC with/without variants was 22.1 vs. 25.1 months (mths); p-value = 0.679. Median time from CRPC to death with/without variants was 32.2 Vs. 27.7 mths (p = 0.6). In HSPC Group B, 14/100 pts were identified with germline variants in ATM (n = 5), CHEK2 (n = 3), BRCA1 (n = 2), BRCA2 (n = 2), RAD50 (n = 1), and MSH2 (n = 1). 31/100 have died and median time to progression from HSPC to CRPC with/without variants was 15.6 vs.11.8 mths, p-value = 0.76. Conclusions: Pts with germline DNA repair variants detected in HSPC stage were not associated with poor prognosis. Presence of additional somatic DNA repair gene aberrations in cell-free DNA, not investigated in this cohort may add to the prevalence of DNA repair gene variations in HSPC and together impact prognosis adversely so as to provide a rationale for PARP inhibitor therapy in select HSPC stage pts.

Germline BRCA1/2, PALB2, and ATM mutations in 3,030 patients with pancreatic adenocarcinoma: Survival analysis of carriers and noncarriers

280

Background: Patients with pancreatic adenocarcinoma (PDAC) can have mutations in breast cancer associated genes ( BRCA1/2) and other homologous recombination (HR) pathway genes. The therapeutic significance of these mutations for PDAC patients is not yet established. We performed a comprehensive survival analysis of 3,030 unselected PDAC patients comparing non-carriers and carriers of BRCA1/2, PALB2, and ATM mutations. Methods: We analyzed germline DNA samples and outcomes from confirmed PDAC patients recruited from 1999-2014 into the Mayo Clinic SPORE in Pancreatic Cancer registry. A total of 3,046 genomic DNA samples were analyzed by next generation sequencing. All pathogenic variants were validated by Sanger sequencing. Survival analysis of PDAC patients with and without BRCA1, BRCA2, PALB2, or ATM germline mutations was performed using the Kaplan-Meier method and log-rank tests. Hazard ratios (HR) were calculated using Cox proportional hazard modeling adjusted for co-variates including age, sex, and stage. A p-value < 0.05 was considered statistically significant. Pre- and post-FOLFIRINOX eras were defined as before and after June 1, 2011. Results: A total of 139 (4.6%) patients were noted to have deleterious mutations in BRCA1, BRCA2, PALB2, or ATM genes. After exclusion of patients with missing data, final analysis was restricted to 2,452 PDAC patients. Overall survival was slightly better (14.2 months versus 11.3 months) in patients with mutations as compared to those without mutations, although this finding was not statistically significant (p = 0.07). When stratified by FOLFIRINOX era, 40 patients with these mutations in the post-FOLFIRINOX era had better outcomes than 668 non-carriers (adjusted HR 0.62; 95% CI 0.43-0.89; p = 0.0062). Conclusions: Deleterious germline BRCA1/2, PALB2, and ATM mutations were seen in approximately 5% of patients with PDAC. Post-FOLFIRINOX era patients with these mutations had improved outcomes, possibly secondary to exposure to DNA-damaging chemotherapies. Germline screening of PDAC patients and development of trials incorporating this information (e.g., PARP inhibitors) has potential value for PDAC patients.

Abstract 1287: Multigene panel testing and risk estimates in 10,233 ovarian cancer cases

Germline pathogenic variants in BRCA1 and BRCA2 account for 10% of ovarian cancer (OC), including ovarian, fallopian tube, and primary peritoneal carcinomas. Pathogenic variants in BRIP1, RAD51C, RAD51D, and other cancer predisposition genes have been observed in another 2% to 5% of OCs. However, the specific genes associated with OC and estimates of risk associated with pathogenic variants in the individual genes are not well defined. We sought to determine the relevance of multigene panel testing results for OC cases. The study was focused on 140,449 individuals, including 10,233 OC cases, receiving clinical panel testing of cancer predisposition genes. Standardized relative risks (SRR) for pathogenic variants in 18 cancer predisposition genes were estimated using reference controls from the Exome Aggregation Consortium (ExAC). The median (range) age at diagnosis of OC was 57 (21-90) years. OC cases were 76.2% Caucasian, 3.6% African American, 4.6% Asian, 4.7% Hispanic, and 10.9% unknown/other. Among the 10,233 OC cases, 1391 (13.6%) had pathogenic mutations, including 1032 pathogenic mutations among the 7793 Caucasian OC cases (13.2%). Using the non-Finnish European ExAC (excluding TCGA samples) reference controls, the allele frequency for all pathogenic variants in each gene was summed and compared to the frequency of mutations in the Caucasian OC cases. Pathogenic variants in the known OC predisposition genes: BRCA1, BRCA2, BRIP1, MSH2, MSH6, RAD51C, and RAD51D were associated with a high risk of OC (SRR&gt;4.0). Additionally, significant associations were observed for pathogenic variants in suspected OC risk genes ATM and PALB2 (SRR=2.06 and 2.78, respectively). This study identified several genes routinely screened on multigene panel testing that confer high or moderate risks of OC. Associations with known OC predisposition genes were confirmed. In addition, this study provides evidence that PALB2 is a moderate risk OC gene, and that ATM may confer lower to moderate risks of OC. If confirmed in future studies, these risks should be carefully considered in future screening and management of OC patients. In contrast, BARD1 and genes in the MRN complex were not associated with clinically relevant risks of OC.

Citation Format: Jenna Lilyquist, Holly LaDuca, Eric Polley, Hermela Shimelis, Chunling Hu, Raymond Moore, Steven N. Hart, Fergus J. Couch, Jill Dolinsky, David E. Goldgar. Multigene panel testing and risk estimates in 10,233 ovarian cancer cases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1287. doi:10.1158/1538-7445.AM2017-1287

Abstract 4925: Microbiome-TP53 gene interaction in human lung cancer

Lung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier function and increases susceptibility to infections. Herein, we hypothesized that somatic mutations together with cigarette smoke create a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from controls (n=33) or cancer cases (n=143), we conducted 16S rRNA gene sequencing (MiSeq), with RNA-seq data from lung cancer cases in The Cancer Genome Atlas (n=1112) serving as the validation cohort. We demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue, indicating a shift in the overall microbial community in lung cancer patients as compared to those without cancer. Lung cancer cases were classified by the relative abundance of two taxa, Variovorax and Streptococcus, with an increase in Variovorax abundance in tumors as compared to non-tumor adjacent paired lung tissue (FDR corrected P=0.013). The species of Variovorax was identified histologically, and also by two additional 16S rRNA strategies (Resphera Insight analysis and PacBio sequencing). A group of taxa were associated with squamous cell carcinoma (SCC), of which Acidovorax were enriched in smokers (P =0.0013). Further, these taxa, including Acidovorax, exhibited higher abundance among the subset of SCC cases with TP53 mutations, an association not seen in adenocarcinomas (AD). Therefore, we observed a microbiome-gene and a microbiome-exposure interaction in SCC lung cancer tissue. Together, these results open the door for future biomarker research that could be used to improve screening and direct mechanistic studies of lung cancer therapy.

Citation Format: Leigh Greathouse, James White, Valery Bliskovsky, Ashley Vargas, Eric Polley, Elise Bowman, Mohammed Khan, Ana Robles, Brid Ryan, Amiran Dzutsev, Giorgio Trinchieri, Marbin Pineda, Sven Bilke, Paul Meltzer, Marina Walther-Antonio, Garth Ehrlich, Joshua Mell, Joshua Earl, Sergey Balashov, Archana Bhat, Alex Valm, Clayton Deming, Sean Conlan, Julia Oh, Julie Segre, Curtis Harris. Microbiome-TP53 gene interaction in human lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4925. doi:10.1158/1538-7445.AM2017-4925

Abstract 4286: What have we learned from pancreatic cancer patients undergoing multigene panel testing

Purpose: The relevance of inherited pathogenic variants in cancer predisposition genes to pancreatic cancer (PC) is not well understood. Several small studies have identified pathogenic variants in 4% to 14% of unselected PC patients using multigene panels of predisposition genes, but only BRCA2, ATM, and PALB2 have been clearly implicated in this disease. We aimed to assess the clinical and molecular characteristics of PC patients referred for hereditary cancer genetic testing, and to estimate the risk of PC associated with pathogenic variants in panel-based cancer predisposition genes.

Methods: PC patients (n=1,819) were ascertained from a large cohort of over 140,000 patients undergoing multigene panel testing (MGPT) of predisposition genes between March 2012 and June 2016 at a single diagnostic laboratory. Clinical histories and molecular results were reviewed and summarized. Gene-level variant frequencies among PC cases were compared to those from the Exome Aggregation Consortium (ExAC) to calculate gene-specific pancreatic cancer risk ratios.

Results: PC patients were predominantly Caucasian (76.5%) and female (58.9%), with a median age at diagnosis of 61 years (51.7). Of these, 33.5% reported additional cancer primaries, and 44.8% reported a family history of PC. Overall, 15.4% of PC patients were found to have at least one pathogenic/likely pathogenic variant in panel-based predisposition genes. Genes with the highest frequencies of pathogenic/likely pathogenic variants included BRCA2 (3.9%), ATM (3.6%), CHEK2 (excluding p.Ile157Thr) (2.0%), PALB2 (1.5%), VHL (1.4%), CDKN2A (1.2%), BRCA1 (0.8%), and MSH6 (0.8%). 21.8% of BRCA1 and BRCA2 carriers did not meet BRCA1/2 testing criteria and 61.5% of MSH6 carriers did not meet Lynch syndrome testing criteria. No CDKN2A families met diagnostic criteria for familial atypical multiple mole melanoma syndrome, and 44% did not report any personal or family history of melanoma. To estimate associations between pathogenic variants and pancreatic cancer, Caucasian PC cases were compared to non-Finnish European, non-TCGA ExAC reference controls. Pathogenic variants in ATM, BRCA2, CDKN2A, MSH6, and PALB2 were significantly associated with high PC risks. Pathogenic variants in BRCA1 were associated with a moderate risk of PC (RR=2.7).

Conclusions: These findings shed light on the spectrum of mutations that can be expected for PC patients referred for cancer predisposition testing. The results confirm the associations of CDKN2A and BRCA2 variants with PC, and expand on the phenotypic spectrum associated with these variants. Furthermore, these results suggest that ATM, PALB2, and MSH6 may be high-risk PC genes, warranting further investigation in case-control and family-based studies.

Citation Format: Holly LaDuca, Chunling Hu, Hermela Shimelis, Eric Polley, Jenna Lilyquist, Mary Helen Black, Brigette Tippin Davis, David E. Goldgar, Jill Dolinsky, Fergus J. Couch. What have we learned from pancreatic cancer patients undergoing multigene panel testing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4286. doi:10.1158/1538-7445.AM2017-4286

Survival profile in breast cancer molecular subtypes without systemic and locoregional treatment

11599

Background: It is unclear whether survival varies among breast cancer molecular subtypes without systemic and locoregional therapy. This study aims to evaluate the survival profile by molecular subtypes after surgery. Methods: In total, we evaluated 301 women with invasive breast cancer with stage I, II or III disease. Patients were classified into four major breast cancer subtypes by immunohistochemistry/FISH classifiers: luminal-A (ER+ and/or PR+/HER2-), luminal-B (ER+ and/or PR+/HER2+), HER2-enriched (HER2+/ER-/PR-) or basal-like (ER-/PR-/HER2-; triple-negative). Overall survival (OS) was analyzed by Kaplan-Meier analysis, and log-rank test for differences. Association between clinical outcome and subtype adjusting for breast cancer prognostic factors was assessed by multivariable Cox proportional hazards model. Results: All patients did not receive systemic chemotherapy and hormone therapy as well as radiation therapy. Luminal A was the most common subtype (N = 224), followed by basal-like (N = 43), luminal B (N = 21) and HER2-enriched (N = 13). Median follow-up for OS was 197 months (range: 1 – 273 months). Age at diagnosis was statistically different among the subtypes, with basal-like and luminal B having high proportions less than 50 years (P = 0.047). Patients with basal-like and HER2-enriched had more high grade tumors (P < 0.001). Notably, there was no difference in OS among the four subtypes (log-rank P = 0.983). In multivariable analysis, the adjusted hazard ratio (HR) was 1.1 for luminal A vs. luminal B (P = 0.781), 0.62 in luminal A vs. HER2-enriched (P = 0.273), or 0.67 in luminal A vs. basal-like (P = 0.158). In contrast, the adjusted HR were 2.2 in age less than 50 years (P = 0.0017), and 1.1 for number of positive nodes (P = 0.00074). Conclusions: OS, through long-term clinical follow-up, is not significantly different among molecular subtypes if not controlling for other prognostic factors in patients who only received surgery. Age and number of positive nodes are independent prognostic factors in patients with no systemic and locoregional treatments.

The National Cancer Institute ALMANAC: A Comprehensive Screening Resource for the Detection of Anticancer Drug Pairs with Enhanced Therapeutic Activity

To date, over 100 small-molecule oncology drugs have been approved by the FDA. Because of the inherent heterogeneity of tumors, these small molecules are often administered in combination to prevent emergence of resistant cell subpopulations. Therefore, new combination strategies to overcome drug resistance in patients with advanced cancer are needed. In this study, we performed a systematic evaluation of the therapeutic activity of over 5,000 pairs of FDA-approved cancer drugs against a panel of 60 well-characterized human tumor cell lines (NCI-60) to uncover combinations with greater than additive growth-inhibitory activity. Screening results were compiled into a database, termed the NCI-ALMANAC (A Large Matrix of Anti-Neoplastic Agent Combinations), publicly available at https://dtp.cancer.gov/ncialmanac Subsequent in vivo experiments in mouse xenograft models of human cancer confirmed combinations with greater than single-agent efficacy. Concomitant detection of mechanistic biomarkers for these combinations in vivo supported the initiation of two phase I clinical trials at the NCI to evaluate clofarabine with bortezomib and nilotinib with paclitaxel in patients with advanced cancer. Consequently, the hypothesis-generating NCI-ALMANAC web-based resource has demonstrated value in identifying promising combinations of approved drugs with potent anticancer activity for further mechanistic study and translation to clinical trials. Cancer Res; 77(13); 3564-76. ©2017 AACR.

Clinical Activity of the γ-Secretase Inhibitor PF-03084014 in Adults With Desmoid Tumors (Aggressive Fibromatosis)

Purpose Desmoid tumors (aggressive fibromatosis) arise from connective tissue cells or fibroblasts. In general, they are slow growing and do not metastasize; however, locally aggressive desmoid tumors can cause severe morbidity and loss of function. Disease recurrence after surgery and/or radiation and diagnosis of multifocal desmoid tumors highlight the need to develop effective systemic treatments for this disease. In this study, we evaluate objective response rate after therapy with the γ-secretase inhibitor PF-03084014 in patients with recurrent, refractory, progressive desmoid tumors. Patients and Methods Seventeen patients with desmoid tumors received PF-03084014 150 mg orally twice a day in 3-week cycles. Response to treatment was evaluated at cycle 1 and every six cycles, that is, 18 weeks, by RECIST (Response Evaluation Criteria in Solid Tumors) version 1.1. Patient-reported outcomes were measured at baseline and at every restaging visit by using the MD Anderson Symptoms Inventory. Archival tumor and blood samples were genotyped for somatic and germline mutations in APC and CTNNB1. Results Of 17 patients accrued to the study, 15 had mutations in APC or CTNNB1 genes. Sixteen patients (94%) were evaluable for response; five (29%) experienced a confirmed partial response and have been on study for more than 2 years. Another five patients with prolonged stable disease as their best response remain on study. Patient-reported outcomes confirmed clinician reporting that the investigational agent was well tolerated and, in subgroup analyses, participants who demonstrated partial response also experienced clinically meaningful and statistically significant improvements in symptom burden. Conclusion PF-03084014 was well tolerated and demonstrated promising clinical benefit in patients with refractory, progressive desmoid tumors who receive long-term treatment.

Small Cell Lung Cancer Screen of Oncology Drugs, Investigational Agents, and Gene and microRNA Expression

BACKGROUND

Small cell lung carcinoma (SCLC) is an aggressive, recalcitrant cancer, often metastatic at diagnosis and unresponsive to chemotherapy upon recurrence, thus it is challenging to treat.

METHODS

Sixty-three human SCLC lines and three NSCLC lines were screened for response to 103 US Food and Drug Administration-approved oncology agents and 423 investigational agents. The investigational agents library was a diverse set of small molecules that included multiple compounds targeting the same molecular entity. The compounds were screened in triplicate at nine concentrations with a 96-hour exposure time using an ATP Lite endpoint. Gene expression was assessed by exon array, and microRNA expression was derived by direct digital detection. Activity across the SCLC lines was associated with molecular characteristics using pair-wise Pearson correlations.

RESULTS

Results are presented for inhibitors of targets: BCL2, PARP1, mTOR, IGF1R, KSP/Eg5, PLK-1, AURK, and FGFR1. A relational map identified compounds with similar patterns of response. Unsupervised microRNA clustering resulted in three distinct SCLC subgroups. Associating drug response with micro-RNA expression indicated that lines most sensitive to etoposide and topotecan expressed high miR-200c-3p and low miR-140-5p and miR-9-5p. The BCL-2/BCL-XL inhibitors produced similar response patterns. Sensitivity to ABT-737 correlated with higher ASCL1 and BCL2. Several classes of compounds targeting nuclear proteins regulating mitosis produced a response pattern distinct from the etoposide response pattern.

CONCLUSIONS

Agents targeting nuclear kinases appear to be effective in SCLC lines. Confirmation of SCLC line findings in xenografts is needed. The drug and compound response, gene expression, and microRNA expression data are publicly available at http://sclccelllines.cancer.gov.

RefCNV: Identification of Gene-Based Copy Number Variants Using Whole Exome Sequencing

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly (r = 0.96-0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman's coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.

New insights on PI3K/AKT pathway alterations and clinical outcomes in breast cancer

PI3K/AKT signaling pathway plays an important role in tumorigenesis and regulates critical cellular functions including survival, proliferation and metabolism. PIK3CA mutations and AKT activation by phosphorylation (pAKT) are often detected in many cancers and especially at high frequencies in breast cancer. Mounting data suggest that PIK3CA mutations or pAKT are mostly associated with better or insignificant outcomes in estrogen receptor-positive (ER+) early stage breast cancer and tend to be with worse prognosis in ER- disease. pAKT expression has been identified to predict paclitaxel chemotherapy benefit in node-positive breast cancer. Preclinical and neoadjuvant trial data suggest that PIK3CA alterations confer resistance to HER2-targeted therapy and are associated with lower pathological complete response (pCR) rate in HER2-positive breast cancer. However, recent results from randomized clinical trials of adjuvant and metastatic settings show that patients with mutant and wildtype PIK3CA tumors derived similar benefit from anti-HER2 therapy. This article, with our new insights, aims to decipher the mixed data and discusses the influence of the potential confounding factors in the assessments. We also share our views for validation of PI3K/AKT alterations in relation to clinical outcome in the context of specific breast cancer subtypes and treatment modalities towards further advance of the precision medicine for breast cancer treatment.

Bromodomain and hedgehog pathway targets in small cell lung cancer

Small cell lung cancer (SCLC) is an extremely aggressive cancer that frequently recurs. Twenty-three human SCLC lines were selected representing varied Myc status. Gene expression of lung cancer, stem-like, hedgehog pathway, and notch pathway genes were determined by RT(2)-PCR array and Exon 1.0 ST array. Etoposide and topotecan concentration response was examined. The IC50's for etoposide and topotecan ranged over nearly 3 logs upon 96 hrs exposure to the drugs. Myc status, TOP2A, TOP2B and TOP1 mRNA expression or topoisomerase 1 and topoisomerase 2 protein did not account for the range in the sensitivity to the drugs. γ-secretase inhibitors, RO429097 and PF-03084014, had little activity in the SCLC lines over ranges covering the clinical Cmax concentrations. MYC amplified lines tended to be more sensitive to the bromodomain inhibitor JQ1. The Smo antagonists, erismodegib and vismodegib and the Gli antagonists, HPI1 and SEN-450 had a trend toward greater sensitivity of the MYC amplified line. Recurrent SCLC is among the most recalcitrant cancers and drug development efforts in this cancer are a high priority.

Abstract B67: Sarcoma cell line screen of oncology drugs and investigational agents identifies patterns associated with gene and microRNA expression

The diversity in sarcoma phenotype and genotype make treatment of this family of diseases exceptionally challenging. Sixty-three human adult and pediatric sarcoma lines were screened with 100 FDA approved oncology agents and 345 investigational agents. The investigational agents library enabled comparison of several compounds targeting the same molecular entity allowing comparison of target specificity and heterogeneity of cell line response. Gene expression was derived from exon array data and microRNA expression was derived from direct digital detection assays. The compounds were screened against each cell line at 9 concentrations in triplicate with an exposure time of 96 hrs using Alamar blue as the endpoint. Results are presented for inhibitors of the following targets: aurora kinase, IGF-1R, MEK, BET bromodomain, and PARP1. Chemical structures, IC50 heat maps, concentration response curves, gene expression and miR expression heat maps are presented for selected examples. In addition, two cases of exceptional responders are presented. The drug and compound response, gene expression and microRNA expression data are publicly available at http://sarcoma.cancer.gov. These data provide a unique resource to the cancer research community.

Citation Format: Beverly A. Teicher, Eric Polley, Mark Kunkel, David Evans, Thomas Silvers, Rene Delosh, Julie Laudeman, Chad Ogle, Russell Reinhart, Michael Selby, John Connelly, Erik Harris, Anne Monks, Joel Morris. Sarcoma cell line screen of oncology drugs and investigational agents identifies patterns associated with gene and microRNA expression. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr B67.

Comprehensive characterization of the Published Kinase Inhibitor Set

Despite the success of protein kinase inhibitors as approved therapeutics, drug discovery has focused on a small subset of kinase targets. Here we provide a thorough characterization of the Published Kinase Inhibitor Set (PKIS), a set of 367 small-molecule ATP-competitive kinase inhibitors that was recently made freely available with the aim of expanding research in this field and as an experiment in open-source target validation. We screen the set in activity assays with 224 recombinant kinases and 24 G protein-coupled receptors and in cellular assays of cancer cell proliferation and angiogenesis. We identify chemical starting points for designing new chemical probes of orphan kinases and illustrate the utility of these leads by developing a selective inhibitor for the previously untargeted kinases LOK and SLK. Our cellular screens reveal compounds that modulate cancer cell growth and angiogenesis in vitro. These reagents and associated data illustrate an efficient way forward to increasing understanding of the historically untargeted kinome.

Sarcoma Cell Line Screen of Oncology Drugs and Investigational Agents Identifies Patterns Associated with Gene and microRNA Expression

The diversity in sarcoma phenotype and genotype make treatment of this family of diseases exceptionally challenging. Sixty-three human adult and pediatric sarcoma lines were screened with 100 FDA-approved oncology agents and 345 investigational agents. The investigational agents' library enabled comparison of several compounds targeting the same molecular entity allowing comparison of target specificity and heterogeneity of cell line response. Gene expression was derived from exon array data and microRNA expression was derived from direct digital detection assays. The compounds were screened against each cell line at nine concentrations in triplicate with an exposure time of 96 hours using Alamar blue as the endpoint. Results are presented for inhibitors of the following targets: aurora kinase, IGF-1R, MEK, BET bromodomain, and PARP1. Chemical structures, IC50 heat maps, concentration response curves, gene expression, and miR expression heat maps are presented for selected examples. In addition, two cases of exceptional responders are presented. The drug and compound response, gene expression, and microRNA expression data are publicly available at http://sarcoma.cancer.gov. These data provide a unique resource to the cancer research community.

Abstract 5475: Interrogation of NCI-60 patterns of growth inhibition in conjunction with investigational oncology agents kinase profiling for the elucidation of mechanistic targets

As oncology treatment moves toward personalized targeted therapeutic agents, the NCI-60 human tumor cell line panel is an ideal community-wide tool to further understanding of the disease and molecular targets of new agents. The panel includes cell lines from nine tumor types, and is extremely well characterized at the molecular level, enabling interrogation of patterns of growth inhibition by a set of targeted investigational oncology agents looking for characteristics of the cell lines that determine sensitivity. We have used a number of online tools to enable data analysis, including COMPARE (http://dtp.nci.nih.gov/compare/), which provided the identification of compounds and/or genes that have highly correlated response patterns for any selected ‘seed’ compound. These data enable comparisons between drug sensitivity profiles that lead to the elucidation of common mechanistic targets or pathways, associations with potential response biomarkers, the confirmation of mechanism of action or identification of novel mechanisms, and the uncovering of unexpected “off-target” activities. For example, using the allosteric Akt inhibitor MK-2206 as the seed compound, response patterns for the ATP-competitive Akt inhibitors PF-4173640 (0.84), GDC-0068 (0.80), AZD-5363 (0.83), GSK-690693 (0.67), and CCT-128930 (0.69) are highly correlated. In addition, examination of the response profile for vandetinib produced a set of highly correlative agents including the corresponding EGFR inhibitors sapatinib (0.81) and AEE-788 (0.83), as well as the recently FDA-approved BTK inhibitor, ibrutinib (0.72) and the SRC inhibitor, AZD-0530 (0.74). Not surprisingly, kinase profiling of these 5 agents (0.5 uM) showed &gt;90% inhibition of EGFR in all cases. In a third example, the BRAF V600E mutated cell lines were found to be sensitive to the bcr-abl inhibitors bafetinib and rebastinib, similarly to vemurafenib. This association suggested BRAF inhibitory activity for the former agents, which was confirmed through kinase profiling. Moreover, the NCI-60 response pattern for the androgen receptor modulator AZD-3514 has a high correlation with the BET bromodomain inhibitors JQ-1 (0.77), I-Bet-151 (0.80), and I-Bet-762 (0.78), suggesting a commonality of target/pathway for these compounds. Further correlations, associations and hypotheses generated from interrogating the compound response patterns, gene expression profiles, mutations and other characteristics will be presented. Funded by NCI Contract No. HHSN261200800001E.

Citation Format: Joel Morris, Mark Kunkel, Eric Polley, Susan Holbeck, Anne Monks, David Evans, Annamaria Rapisarda, Jerry Collins, Beverly Teicher. Interrogation of NCI-60 patterns of growth inhibition in conjunction with investigational oncology agents kinase profiling for the elucidation of mechanistic targets. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5475. doi:10.1158/1538-7445.AM2014-5475

Abstract 5450: Screening more than 60 human SCLC lines with approved and investigational agents indicates complex patterns of response: Identification of HSP90 and HDACs as potential targets

Small cell lung cancer (SCLC) is an aggressive cancer with a 5-year survival rate of &lt;5%. While initially responsive to treatments with platinum agents, topoisomerase inhibitors or methotrexate, the tumors frequently recur after chemotherapy. To identify whether approved small molecule drugs or investigational agents may have unexpected effects in SCLC lines, we undertook a systematic large-scale screen with &gt;500 compounds against &gt; 60 well characterized SCLC cell lines in culture. Cells were exposed to 101 Approved Oncology Drugs (AOD) and 433 Investigational Agents. By evaluating compounds at 9 concentrations (10uM to 1.5nM), using cell viability 96h post drug exposure as the endpoint (Cell Titer Glo), we were able to obtain concentration response curves and IC50 values for the compounds and rank activity of these agents. In parallel studies, using Affymetrix exon ST1 arrays and miRNA profiling, we examined these same cell lines for differences in gene expression patterns that may correlate with sensitivity or resistance to select agents in the screen. The Myc oncogene (cMyc, LMyc, or nMyc) is over-expressed in about 40% of SCLC lines. Surprisingly, early analyses of the SCLC screen data have been unable to correlate high Myc expression with response to drugs or investigational agents (there is a trend with bromodomain inhibitors). The large majority of SCLC lines were sensitive to compounds against select target classes (e.g. HSP90 inhibitors and HDAC inhibitors). Examining HSP70 and HSP90 levels by Western blot suggested a slight reduction in HSP90 levels in cells resistant to the HSP90 inhibitor Ganetespib with no change in HSP70 levels. Some inhibitors against these targets showed broader cell activity than others. We are currently determining whether such differential drug sensitivity is correlated with specific changes in gene expression patterns in these cells. Further data analyses from the screen combined with genomic profiling of the cells will be presented.

Funded by NCI Contract No. HHSN261200800001E.

Citation Format: David M. Evans, Rene Delosh, Julie Laudeman, Chad Ogle, Russell Reinhart, Michael Selby, Thomas Silvers, John Connelly, Anne Monks, Eric Polley, Gurmeet Kaur, Joel Morris, Beverly Teicher. Screening more than 60 human SCLC lines with approved and investigational agents indicates complex patterns of response: Identification of HSP90 and HDACs as potential targets. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5450. doi:10.1158/1538-7445.AM2014-5450

Abstract A102: NCI-60 response profiles of &gt;400 investigational oncology agents: A resource enabling drug and biomarker discovery

We have acquired &gt;400 investigational oncology agents, comprised primarily of targeted small molecules currently in clinical and/or preclinical anticancer studies. As oncology treatment moves toward personalized targeted therapeutic agents, the NCI-60 human tumor cell line panel is an ideal community-wide tool to further understanding of the disease targets of new agents. The panel includes cell lines from nine tumor types, and is extremely well characterized at the molecular level, with both in-house and crowd-sourced characterization, including exome sequence for mutations, SNPs, DNA methylation, metabolome, mRNA, microRNA, and protein expression. This molecular characterization dataset enables interrogation of patterns of growth inhibition by the investigational drug set looking for characteristics of the cell lines that determine sensitivity. More than 150,000 small molecules, including all (&gt; 100) FDA-approved anticancer drugs and now our acquired set of 400 investigational oncology agents have been screened against the panel for their effects on cell growth. We have used a number of online tools to enable data analysis for this set, including COMPARE (http://dtp.nci.nih.gov/compare/), which provided for the identification of compounds and/or genes that have highly correlated response patterns for any selected ‘seed’ compound. This presentation provides the first public disclosure of the NCI-60 data for this set of novel, targeted, investigational oncology agents. We anticipate that these data will enable comparison between drug sensitivity profiles that could lead to the elucidation of common mechanistic targets or pathways, associations with potential response biomarkers, the confirmation of mechanism of action or identification of novel mechanisms, and the uncovering of unexpected "off-target" activities. For example, Akt, pI3K, PDK, and mTOR inhibitors, multiple agents targeting one signaling pathway, display strong correlations with one another. Using the allosteric Akt inhibitor MK-2206 as the seed compound, response patterns for the ATP-competitive Akt inhibitors PF-4173640 (0.84), GDC-0068 (0.80), AZD-5363 (0.83), GSK-690693 (0.67), and CCT-128930 (0.69) are highly correlative. Moreover, the NCI-60 response pattern for the androgen receptor modulator AZD-3514 has a 0.77 correlation with the BET bromodomain inhibitor JQ-1, suggesting a commonality of target/pathway for these compounds. Further correlations, associations and hypotheses generated from interrogating the compound response patterns, gene expression profiles, mutations and other characteristics will be presented. Funded by NCI Contract No. HHSN261200800001E.

Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A102.

Citation Format: Joel Morris, Mark Kunkel, Eric Polley, Susan Holbeck, Kazimierz Wrzeszczynski, Anne Monks, David Evans, Annamaria Rapisarda, Jerry Collins, Beverly A. Teicher. NCI-60 response profiles of &gt;400 investigational oncology agents: A resource enabling drug and biomarker discovery. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A102.

Abstract C103: Sarcoma cell line sensitivity towards approved oncology drugs and investigational agents identifies distinct patterns of response which can be interrogated with associated gene expression

Sarcomas represent a heterogeneous group of cancers with significant unmet medical needs. We have examined the response of 64 sarcoma cell lines to treatment with 103 approved oncology drugs (available from The NCI/DTP Open Chemical Repository) and 420 agents in the investigational agents library, using inhibition of proliferation as an endpoint. Cells were exposed to compounds at varying concentrations (10μM to 1.5nM) for 96 h and the effect of compound on cell viability was monitored using Alamar Blue. From curve fitting algorithms we determined the IC50 values of each agent on the cell lines. Adult sarcomas comprise 23% of this sarcoma panel and have a different spectrum of sensitivities to selected agents. They were generally more chemoresistant than the pediatric lines, although they are marginally more sensitive to MEK inhibitors. Synovial tumor cell lines were an exception, being sensitive to several classes including dasatinib and Bcr-abl inhibitors. Ewings tumors tend to be the most sensitive pediatric group responding to Parp-1 and IGF-1R inhibitors. Overall, gene, and to a lesser extent, miRNA profiles from the adult sarcoma's were more similar to the profiles of normal, non-tumor cells, than the pediatric tumors, and this lack of genotypic divergence may underlie the insensitive phenotype observed in the sarcoma panel. From an analysis of sensitivity clustering, IGF-1R inhibitors (8), cluster with some of the AKT (8) and ALK (8) inhibitors. None of the cell lines have the EM4L-ALK translocation, thus we investigated the genes associated with sensitivity to these three mechanisms. Dendrograms identified a close relationship between the IGF-1R and AKT inhibitors, based on the gene expression patterns, while the ALK inhibitors were quite distinct, substantiating known pathways of IGFR-1R signaling through AKT, but unrelated to ALK. Genes associated with ALK sensitivity included several from gluconeogenesis, and potential activation of the MYC response. In contrast, genes associated with AKT and IGF1R sensitivity are focused around FOXO1 transcription factor. Interestingly, the PAX-FOXO1 gene fusion is a hallmark of the aggressive alveolar rhabdomyosarcoma which are more sensitive to these agents than embryonal rhabdomyosarcoma. Thus the combination of drug sensitivity data, together with the gene and miRNA profiles may allow correlations in treatment efficacy that may point to new avenues for clinical development in sarcoma. Funded by NCI Contract No. HHSN261200800001E.

Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C103.

Citation Format: Anne Monks, David Evans, Thomas Silvers, Rene Delosh, Julie Laudeman, Chad Ogle, Russell Reinhart, Michael Selby, John Connelly, Annamaria Rapisarda, Mark Kunkel, Joel Morris, Kazimierz Wrzeszczynski, Eric Polley, Beverley Teicher. Sarcoma cell line sensitivity towards approved oncology drugs and investigational agents identifies distinct patterns of response which can be interrogated with associated gene expression. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C103.

Clinical trials for precision oncology using next-generation sequencing

The demonstrated genomic heterogeneity of human cancers is having major impacts on the development and evaluation of cancer therapeutics and molecular diagnostics. Many new cancer drugs target somatic alterations in tumors and are being developed with companion diagnostics. Oncology drug development and practice are likely to become increasingly stratified and utilize the enrichment Phase III trial paradigm. Although this paradigm includes an increasing number of successes, single-agent molecularly targeted treatment of metastatic disease will generally provide limited patient benefit. More substantial gains will require better understanding of crosstalk among signaling pathways, ability to combine drugs and use of drugs at initial diagnosis. Early phase discovery clinical trials in which patients will have genome-wide tumor characterization at diagnosis and at critical retreatment points will provide data sets for learning how to effectively match therapeutics to genomic alterations. However, moving tumor genomics to clinical oncology entails many practical challenges. We review some of these challenges and the clinical studies that are being undertaken to translate genomics to clinical oncology.

Exploring large weight deletion and the ability to balance confounders when using inverse probability of treatment weighting in the presence of rare treatment decisions

PURPOSE

When medications are modified in response to changing clinical conditions, confounding by indication arises that cannot be controlled using traditional adjustment. Inverse probability of treatment weights (IPTWs) can address this confounding given assumptions of no unmeasured confounders and that all patients have a positive probability of receiving all levels of treatment (positivity). We sought to explore these assumptions empirically in the context of epoetin-alfa (EPO) dosing and mortality.

METHODS

We developed a single set of IPTWs for seven EPO dose categories and evaluated achieved covariate balance, mortality hazard ratios, and confidence intervals using two levels of treatment model parameterization and weight deletion.

RESULTS

We found that IPTWs improved covariate balance for most confounders, but was not optimal for prior hemoglobin. Including more predictors in the treatment model or retaining highly weighted individuals resulted in estimates closer to the null, although precision decreased.

CONCLUSION

We chose to evaluate weights and covariate balance at a single time-point to facilitate an empirical analysis of model assumptions. These same assumptions are applicable to a time-dependent analysis, although empirical examination is not straight forward in that case. We find that the inclusion of rare treatment decisions and the high weights that result is needed for covariate balance under the positivity assumption. Removal of these influential weights can result in bias in either direction relative to the original confounding. It is therefore important to determine the reason for these rare patterns and whether inference is possible for all treatment levels.