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  • American Association for Cancer Research (AACR)  (16)
  • 1
    In: Cancer Discovery, American Association for Cancer Research (AACR), Vol. 11, No. 10 ( 2021-10-01), p. 2488-2505
    Abstract: We conducted next-generation DNA sequencing on 335 biliary tract cancers and characterized the genomic landscape by anatomic site within the biliary tree. In addition to frequent FGFR2 fusions among patients with intrahepatic cholangiocarcinoma (IHCC), we identified FGFR2 extracellular domain in-frame deletions (EID) in 5 of 178 (2.8%) patients with IHCC, including two patients with FGFR2 p.H167_N173del. Expression of this FGFR2 EID in NIH3T3 cells resulted in constitutive FGFR2 activation, oncogenic transformation, and sensitivity to FGFR inhibitors. Three patients with FGFR2 EIDs were treated with Debio 1347, an oral FGFR1/2/3 inhibitor, and all showed partial responses. One patient developed an acquired L618F FGFR2 kinase domain mutation at disease progression and experienced a further partial response for 17 months to an irreversible FGFR2 inhibitor, futibatinib. Together, these findings reveal FGFR2 EIDs as an alternative mechanism of FGFR2 activation in IHCC that predicts sensitivity to FGFR inhibitors in the clinic. Significance: FGFR2 EIDs are transforming genomic alterations that occur predominantly in patients with IHCC. These FGFR2 EIDs are sensitive to FGFR inhibition in vitro, and patients with these alterations benefited from treatment with FGFR inhibitors in the clinic. This article is highlighted in the In This Issue feature, p. 2355
    Type of Medium: Online Resource
    ISSN: 2159-8274 , 2159-8290
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 2
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 26, No. 23 ( 2020-12-01), p. 6158-6167
    Abstract: Dickkopf-1 (DKK1) modulates Wnt signaling, promoting tumor growth, metastasis, and immunosuppression. High DKK1 expression has been detected in various tumor types—including biliary tract cancer (BTC)—and is associated with poor prognosis. DKN-01—a humanized mAb targeting DKK1—was evaluated in a phase I multicenter study in combination with gemcitabine and cisplatin in patients with unresectable or metastatic BTC with no prior systemic therapy for advanced disease. Patients and Methods: This study included a dose-escalation phase assessing DKN-01 at two dose levels (150 mg and 300 mg) combined with gemcitabine (1,000 mg/m2) and cisplatin (25 mg/m2) followed by dose expansion. Primary endpoints evaluated safety and tolerability; secondary endpoints evaluated efficacy, pharmacokinetics, and circulating biomarkers. Results: Fifty-one patients with intrahepatic cholangiocarcinoma (63%), extrahepatic cholangiocarcinoma (8%), and gallbladder cancer (29%) were enrolled. No dose-limiting toxicities were seen, and the expansion phase proceeded with DKN-01 300 mg (N = 47). The most frequent grade 3/4 treatment-emergent adverse events included neutropenia (60%), thrombocytopenia (34%), and anemia (23%). The objective response rate was 21.3% and median progression-free survival was 8.7 months (95% confidence interval, 5.4–10.3 months). Better outcomes were associated with biomarkers of angiogenesis inhibition (increased sVEGFR1 and lower VEGF-C) and reduced inflammation (lower IL6 and decreased TNFα). Conclusions: DKN-01 300 mg was well tolerated in this combination but did not appear to have additional activity beyond historically reported efficacy with gemcitabine/cisplatin alone. Exploratory pharmacokinetic and biomarker data indicate potential antiangiogenic and immunomodulatory activity of DKN-01/chemotherapy and the need for increased dose/intensity. A study with DKN-01 600 mg in combination with a PD-1 inhibitor in BTC is ongoing.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), ( 2023-09-5)
    Abstract: International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international cancer registry collecting data from 19 cancer centers, makes data from & gt;130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional real-world longitudinal clinical data, including treatment and outcome data, are being collected by the AACR Project GENIE Biopharma Collaborative using the PRISSMM data curation model. Several thousand of these cases are now also available in cBioPortal. We have significantly enhanced the functionalities of cBioPortal to support the visualization and analysis of this rich clinico-genomic linked dataset, as well as datasets generated by other centers and consortia. Examples of these enhancements include 1) visualization of the longitudinal clinical and genomic data at the patient level, including timelines for diagnoses, treatments, and outcomes, 2) the ability to select samples based on treatment status, facilitating a comparison of molecular and clinical attributes between samples before and after a specific treatment, and 3) survival analysis estimates based on individual treatment regimens received. Together, these features provide cBioPortal users with a toolkit to interactively investigate complex clinico-genomic data in order to generate hypotheses and make discoveries about the impact of specific genomic variants on prognosis and therapeutic sensitivities in cancer.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 4
    In: Cancer Discovery, American Association for Cancer Research (AACR), Vol. 7, No. 8 ( 2017-08-01), p. 818-831
    Abstract: The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types ( & gt;30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to & gt;100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine. Significance: The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy. Cancer Discov; 7(8); 818–31. ©2017 AACR. See related commentary by Litchfield et al., p. 796. This article is highlighted in the In This Issue feature, p. 783
    Type of Medium: Online Resource
    ISSN: 2159-8274 , 2159-8290
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 5
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 26, No. 18_Supplement ( 2020-09-15), p. S10-02-S10-02
    Abstract: Introduction: Reports suggest worsened outcomes in patients with cancer (pts) and COVID-19 (Cov), varying by geography and local peak dynamics. We describe characteristics and clinical outcomes of pts with and without Cov. Methods: RWD at 2 Midwestern health systems from the Syapse Learning Health Network were used to identify adults with active cancer (AC) or past history of cancer (PHC). AC pts were identified by encounters with ICD-10 code for malignant neoplasm or receipt of an anticancer agent within 12 months prior to February 15, 2020; PHC pts were identified by encounters with an active cancer code from May 15, 2015 to February 15, 2019 and no receipt of anticancer therapy within the prior 12 months. Cov was defined by diagnostic codes and laboratory results from February 15 to May 13, 2020. Comorbidities were assessed prior to February 15, 2020; hospitalizations (hosp), invasive mechanical ventilation (IMV), and all-cause mortality (M) were assessed from February 15 to May 27, 2020. Results: We identified 800 pts with Cov (0.5%) out of a total of 154,585 pts with AC or PHC. Compared to AC pts without Cov (AC WO, 39,402), AC pts with Cov (AC Cov, 388) were more likely to be non-Hispanic Black (NHB, 39% vs. 9%), have renal failure (RF, 24% vs. 12%), cardiac arrhythmias (33% vs. 19%), congestive heart failure (CHF, 16% vs. 8%), obesity (19% vs. 14%), pulmonary circulation disorder (PCD, 9% vs. 4%), and a zip code with median annual household income (ZMI) & lt;$30k (18% vs. 5%). Comorbidity and income were similarly distributed for PHC pts with Cov (PHC Cov, 412). Compared to PHC pts without Cov (PHC WO, 114,383), coagulopathy (coag) was more common in PHC Cov pts (10% vs. 5%). Hosp for AC Cov pts was higher than for AC WO pts (81% vs. 15%). Hosp for PHC Cov pts was also higher than for PHC WO pts (68% vs. 6%). Hosp was highest for NHB pts in both AC Cov and PHC Cov groups (88% and 72%) and for AC Cov pts in low ZMI (94% in & lt;$30K). Pts & lt;50 years old had hosp rates of 79% (AC Cov) and 49% (PHC Cov). IMV rate for AC Cov pts was higher than for PHC Cov pts (21% vs. 14%). Rates of IMV for AC Cov pts were highest in low ZMI (27%) and in pts with coag (36%). M by group was: AC Cov 16%; AC WO 1%; PHC Cov 11%; PHC WO 1%. Among AC Cov pts, M was higher for men (19% vs. 13%) and pts with PCD (31%), RF (25%), or diabetes (DM, 24%); among PHC Cov pts, M was also higher for men (14% vs. 8%) and pts with coag (30%), valvular disease (27%), or PCD (24%). Increasing age, DM, RF, and PCD were associated with increased risk of M for AC Cov pts in age, race/ethnicity, and comorbidity-adjusted logistic regression; increasing age and coag were associated with M in PHC Cov pts. Conclusion: In this rapid characterization from RWD, pts with Cov have higher rates of pre-existing cardiopulmonary/vascular and renal conditions and increased risk of hospitalization, IMV, and mortality than pts without Cov. Higher Cov risk and worse outcomes in NHB and lower-income pts suggest health care disparities. Whether these outcomes are due to comorbidities or acute sequelae merits further study, as does investigation of alternative definitions for real-world populations and outcomes. Citation Format: Shirish M. Gadgeel, Michael A. Thompson, Monika A. Izano, Clara Hwang, Tom Mikkelsen, James L. Weese, Frank M. Wolf, Andrew Schrag, Sheetal Walters, Harpreet Singh, Jonathan Hirsch, Thomas D. Brown, Paul G. Kluetz. Using real-world data (RWD) from an integrated platform for rapid analysis of patients with cancer with and without COVID-19 across distinct health systems [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr S10-02.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 5721-5721
    Abstract: The digitization of health records and prompt availability of tumor DNA sequencing results offer a chance to study the determinants of cancer outcomes with unprecedented richness; however, abstraction of key attributes from free text presents a major limitation to large-scale analyses. Using natural language processing (NLP), we derived sites of metastasis, prior treatment at outside institutions, programmed death ligand 1 (PD-L1) levels, and smoking status from records of patients with tumor sequencing to create a richly annotated clinicogenomic cohort. We sought to define whether combining features would improve models of overall survival (OS) and treatment response as validated in a multi-institution, manually curated cohort. We leveraged the manually curated AACR GENIE Biopharma Collaborative (BPC) dataset to train NLP algorithms to abstract the aforementioned features from overlapping records available at Memorial Sloan Kettering (MSK). All models achieved precision and recall & gt; 0.85. We deployed these algorithms to records of all MSK patients with non-small cell lung cancer (NSCLC) and tumor profiling with our FDA-authorized institutional targeted sequencing platform (N=7,015). These labels were combined with genomic, demographic, histopathologic, internal treatment and staging data to train random survival forests (RSF) to predict OS and time-to-next-treatment (TTNT) for molecularly targeted and immunotherapies. RSFs trained on the MSK NSCLC cohort were validated with the curated, non-MSK BPC NSCLC cohort (N=977). The addition of NLP-derived variables to genomic features enhanced RSF predictive power for OS (c-index, 10x bootstrap 95%CI: 0.58, 0.57-0.59 vs 0.75, 0.74-0.76 combined) and targeted and immunotherapy TTNT. The size of the MSK NSCLC cohort enabled discovery of associations between metastatic sites, PD-L1 status, genomics, and TTNTs not apparent in the smaller BPC cohort. We measured the added predictive value of variables not available in BPC with MSK-only cross-validation analyses. White blood cell differential counts and additional tissue genomic features including tumor mutational burden and fraction genome altered added minimally, while circulating tumor DNA sequencing added prognostic power for OS over other factors including disease burden Using NLP we present a large NSCLC cohort with rich clinicoradiographic annotation, leading to superior models of patient outcomes. Our data uncovers associations not observed in smaller, manually curated cohorts and provides a foundation for further research in therapy choice and prognostication. Citation Format: Justin Jee, Chris Fong, Karl Pichotta, Thinh Tran, Anisha Luthra, Mirella Altoe, Steven Maron, Ronglai Shen, Si-Yang Liu, Michele Waters, Joseph Kholodenko, Brooke Mastrogiacomo, Susie Kim, A Rose Brannon, Michael F. Berger, Axel Martin, Jason Chang, Anton Safonov, Jorge S. Reis-Filho, Deborah Schrag, Sohrab P. Shah, Pedram Razavi, Bob T. Li, Gregory J. Riely, Nikolaus Schultz. Automated annotation for large-scale clinicogenomic models of lung cancer treatment response and overall survival. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5721.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 13_Supplement ( 2021-07-01), p. 2619-2619
    Abstract: Obtaining information regarding cancer recurrence from a retrospective, EHR-based dataset poses several challenges primarily due to the lack of structured data. Patients are at risk for cancer recurrence beginning at a time point at which they are characterized as having no evidence of disease. The absence of cancer may be indicated on a radiology report or a medical oncologist assessment, requiring manual review and interpretation of potentially ambiguous free text. Further, the recurrence event itself can be defined based on several distinct data sources including pathology, imaging, clinician assessments, or tumor markers. The likelihood of ascertaining recurrence is dependent on the frequency and type of surveillance performed and varies based on tumor type and based on clinicians' thresholds for pursuing workup of borderline or suspicious findings; if follow up assessments are infrequent, there are fewer opportunities to detect recurrence. Given these challenges, there is currently no standardized approach to evaluating cancer recurrence in EHR data, impeding analyses of rare molecular tumor subtypes in multi-institutional linked clinico-genomic databases. For this analysis, we leveraged the AACR Project GENIE Biopharma Collaborative data based on the PRISSMM curation model to develop an algorithm for identifying recurrence among patients diagnosed with stage I-III non-small cell lung cancer or with stage I-III colorectal cancer. This algorithm involves using curated pathology report data to identify a definitive surgery as the time at which patients have completed curative intent treatment. Subsequent imaging reports, pathology reports, medical oncologist assessments and tumor marker data are then evaluated in order to characterize the timing of specific recurrence events. We will present the real-world recurrence algorithm, its underlying rationale and discuss applications of recurrence endpoints. Beyond enabling estimates of recurrence-free survival, identifying cancer recurrence will allow for estimation of progression-free survival among stage I-III patients in addition to estimation of PFS among de novo stage IV patients. Estimating PFS in a large cohort of patients with linked phenomic and genomic data has historically been a limitation of these types of datasets. Overcoming this limitation will allow for precision medicine advances in oncology by facilitating data pooling across institutions and enabling examination of rare molecular subtypes in relation to clinically meaningful endpoints. Citation Format: Jessica A. Lavery, Samantha Brown, Eva Lepisto, Michele L. Lenoue-Newton, Caroline McCarthy, Hira Rizvi, Celeste Yu, Kenneth L. Kehl, Shawn M. Sweeney, Julia E. Rudolph, Nikolaus Schultz, Brooke Mastrogiacomo, Ritika Kundra, Jeremy Warner, Philippe Bedard, Gregory J. Riely, Katherine S. Panageas, Deborah Schrag, AACR Project GENIE Consortium. Defining real-world recurrence in the AACR Project GENIE Biopharma Collaborative Data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2619.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 8
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 4_Supplement ( 2022-02-15), p. P4-09-01-P4-09-01
    Abstract: Background: Clinician-rated adverse event data from pivotal trials of the CDK4/6 inhibitor palbociclib (palbo) in patients (pts) with HR+ HER2- metastatic breast cancer (MBC) describe fatigue as a common non-hematologic toxicity. While palbo and endocrine therapy (ET) significantly improve outcomes compared to ET alone, in a pooled analysis of the PALOMA trials, rates of incident Common Terminology Criteria for Adverse Events (CTCAE) all-grade fatigue over 4.2 years of treatment approached 39.2%, with grade 3/4 at 2.5%. As these studies included only provider-rated CTCAE toxicity, it is important to quantify pts’ ratings of fatigue severity, which may differ from clinician assessments. Methods: Eligible pts with HR+ HER2- MBC, initiating standard-dose palbo with ET (aromatase inhibitor or fulvestrant), and without clinically meaningful fatigue prior to initiation of palbo, were followed for the 6 initial treatment cycles. The absence of baseline fatigue was established using the patient-reported Functional Assessment of Chronic Illness Therapy Fatigue Scale (FACIT-F), a 13-item scale (range 0-52, lower score = more fatigue) validated against anemia to indicate clinically meaningful fatigue if FACIT-F score & lt;34. After screening and baseline assessments (several weeks apart), the FACIT-F was repeated during the 3rd week of 6 consecutive cycles. Pts also reported fatigue severity using the NCI Patient-Reported Outcomes for CTCAE (PRO-CTCAE; range 0-4; grade 3/4 = severe) when they completed the FACIT-F. The primary endpoint was new-onset fatigue (FACIT-F score & lt;34) after treatment initiation; the secondary endpoint was severe fatigue on the PRO-CTCAE fatigue severity item. Incident rate of fatigue was estimated based on frequencies (dichotomized FACIT-F scores & lt;34 vs. & gt;=34; PRO-CTCAE fatigue severity grade 3/4 vs. & lt;3). Rate of fatigue incidence on the FACIT-F in the presence of competing risks (e.g., disease progression or study burden) was estimated using the cumulative incidence function. Concurrently rated FACIT-F scores were compared between PRO-CTCAE severe and non-severe cases using linear mixed-models. Results: Of 115 pts enrolled (5/2018-1/2021), 88 were evaluable after excluding those not initiating palbo (n=3), without baseline data (n=13), or with clinically meaningful fatigue between screening and baseline (n=11). Mean (±SD) age was 59.4 ± 11.3, baseline FACIT-fatigue score was 44.4 ± 5.1, and follow-up duration was 5.8 ± 2.0 cycles. The majority (72%) were receiving palbo with letrozole. New-onset fatigue through the 6th treatment cycle was observed in 21 pts, translating to a fatigue incidence rate of 23.9% (95% CI 15.4% - 34.1%). The mean time to new-onset fatigue was 3.8 ± 1.7 treatment cycles. Those who withdrew early (n=26) completed data for 3.7 ± 2.1 treatment cycles; the cumulative incidence of fatigue at 4 treatment cycles was 18.2% (95% CI 10.9 - 26.9). Using the PRO-CTCAE, the incidence rate of severe fatigue was 14.8% (95% CI 8.1% - 23.9%). The mean FACIT-F score when PRO-CTCAE grade indicated severe fatigue was significantly lower (more fatigue) than when the PRO-CTCAE grade was non-severe (26.3 ± 5.1 vs. 44.8 ± 4.8, p & lt;0.0001). Conclusion: In pts with HR+ HER2- MBC initiating palbo and ET, approximately one-quarter develop fatigue within the first 6 cycles based on the FACIT-F, which associates significantly with a PRO-CTCAE severity grade 3/4. While direct comparison cannot be made between provider-rated CTCAE and patient-reported PRO-CTCAE, it is notable that the incidence of severe fatigue with PRO-CTCAE is higher than that observed with provider-rated CTCAE. Ongoing analyses will explore potential associations of factors (e.g., hematological, sleep, activity) with treatment-emergent fatigue developing on palbo and ET therapy. Citation Format: Shadab A Rahman, Erica L Mayer, Hanneke Poort, Deborah Schrag, Stephanie C Tung, Eric S Zhou, Aleta Wiley, Lauren Finkelstein, Elkhansaa Elguenaoui, Moira Nolan, Hadine Joffe. Incidence of patient-reported fatigue developing in patients receiving palbociclib and endocrine therapy for advanced HR+ HER2- breast cancer [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 P4-09-01.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. LB-103-LB-103
    Abstract: Background: AACR GENIE is an international data-sharing project that aggregates clinical-grade cancer genomic data. As a demonstration of utility, we evaluated the landscape of ERBB2 mutations in the first 18,486 patients included in this registry and compared it to the first 100 patients enrolled in an ongoing international Phase 2 SUMMIT ‘basket’ study of the pan-HER inhibitor neratinib in ERBB2 mutant solid tumors (NCT01953926). Results: ERBB2 mutations were identified in 2.8% (519/18,486) of patients in the GENIE cohort and observed at all participating centers. In total, there were 482 missense, 66 indels, 19 truncating mutations, and 14 structural variants. A total of 263 unique missense mutations were observed including 12 at previously identified hotspots which accounted for 69.2% of all missense mutations. 35 unique cancer types were represented. The tumor types with the highest proportion of ERBB2 mutations were bladder (12.8%, 82/641), breast (3.9%, 87/2230), colorectal (3.3%, 70/2102), and NSCLC (3%, 90/3006). Among patients with copy number data available (91%) 11% had concurrent ERBB2 amplification, most often in breast cancer. The most frequently observed alterations in ERBB2, adjusted for differing exon coverage between panels, was S310F/Y in 0.46% of the GENIE cohort (12.6% of samples with ERBB2 alterations), Y772_A775dup in 0.21% (6.9%), R678Q in 0.17% (4.5%), L755S in 0.16% (5.2%), V777L in 0.12% (3.8%), and V842I in 0.09% (3.1%). The distribution of specific ERBB2 variants differed significantly by tumor type with exon 20 insertions being most common in NSCLC (44.4%, 40/90), L755S (18.9%, 11/92) in breast, S310F/Y (26.9%, 28/104) in bladder, and V842I (13.9%, 10/72) in colorectal cancer. Structural variants included intragenic deletions (n=4) and fusions involving various partners including GRB7 (n=2), and one each of C1orf87, PPIL6, HEXIM2, THRA, ASIC2, BCA3, WIPF2. The frequencies of ERBB2 mutant cancer types observed in the GENIE cohort were generally comparable to those enrolled to the neratinib basket study including NSCLC (17 vs 22%, respectively), breast (16.4 vs 24%), bladder (15.5 vs 14%), colorectal (13.2 vs 17%), and endometrial (4.2 vs 6%). At the variant level, S310F/Y was less prevalent in GENIE compared to the neratinib study (12.6 vs 24%) while all other mutations were generally similar including L755S (5.2 vs 9%), R678Q (4.5 vs 2%), Y772_A775dup (6.9 vs 13%), V777L (3.8 vs 9%), and V842I (3.1 vs 6%). Conclusion: GENIE confirms that a diversity of ERBB2 mutations are prevalent across a variety of tumor types in patients with advanced cancer. The genomic landscape of ERBB2 mutations was largely similar in the population based GENIE cohort and the neratinib SUMMIT study, providing the first direct evidence that basket study enrollment accurately reflects the true landscape of the target alteration. Citation Format: Alison Schram, Helen H. Won, Fabrice Andre, Monica Arnedos, Funda Meric - Bernstam, Philippe L. Bedard, Kenna R. Shaw, Hugo Horlings, Christine Micheel, Ben Ho Park, Grace Mann, Alshad S. Lalani, Lillian Smyth, David B. Solit, Deborah Schrag, Mia A. Levy, Barrett J. Rollins, Mark Routbort, Charles L. Sawyers, Eva Lepisto, Michael F. Berger, David M. Hyman, on behalf of the AACR Project GENIE Consortium. Landscape of somatic ERBB2 Mutations: Findings from AACR GENIE and comparison to ongoing ERBB2 mutant basket study [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 LB-103. doi:10.1158/1538-7445.AM2017-LB-103
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 10
    In: Molecular Cancer Therapeutics, American Association for Cancer Research (AACR), Vol. 8, No. 12_Supplement ( 2009-12-10), p. B254-B254
    Abstract: Loss of coordination between cell cycle checkpoints and DNA damage repair is a fundamental feature tumor cells rely on for unregulated growth and developing chemotherapeutic resistance. The protein kinase Checkpoint kinase 1 (Chk1) is a sentinel molecule essential for cell cycle arrest at the S and G2M checkpoints, as well as regulating homologous recombination DNA repair. In tumor cells exposed to chemotherapy, Chk1 inhibition overrides cell cycle arrest and DNA repair functions, effectively driving tumor cells into a state of mitotic catastrophe and, ultimately, cell death. We have previously reported in schedule-dependence studies, using Chk1 inhibitors and irinotecan (CPT-11), that oral administration of Chk1 inhibitors allows for multi-day target-coverage, and thus continuous inhibition of Chk1 for a finite period of time, which maximizes anti-tumor efficacy. Here, we extend these studies and investigate the pharmacodynamic relationship to efficacy, as well as the specific biomarkers that are predictive of an anti-tumor effect, when Chk1 inhibitors are administered on a multi-day dosing schedule. Utilizing potent (IC50=24–27nM), selective, and orally bio-available small molecule Chk1 inhibitors of which Chk1-A and Chk1-C are representative, we find only modest inhibition of the functional biomarker phospho-cdc2, following a single dose of a Chk1 inhibitor. Alternatively, on multi-day Chk1 inhibitor dose schedules, we find dose-related pharmacodynamic inhibition of Chk1 signaling that is maximized at doses where we see significant tumor growth inhibition in efficacy experiments. Furthermore, multi-day dosing of Chk1 inhibitors induces marked inhibition of phospho-cdc2 and Rad51 protein levels, suggesting tumoricidal activity related to Chk1 inhibition is due to both checkpoint override and impairment of DNA damage repair. In human tumor xenografts administered combination therapy with gemcitabine, an orally-delivered Chk1 inhibitor dosed on a multi-day schedule shows superior efficacy over an IV administered compound. Taken together, our findings show a clear correlative relationship between pharmacodynamic target inhibition and anti-tumor activity that is exclusively achieved on multi-day dose schedules. These results demonstrate the need for prolonged Chk1 inhibition to provide robust pharmacodynamic inhibition and maximal anti-tumor efficacy. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):B254.
    Type of Medium: Online Resource
    ISSN: 1535-7163 , 1538-8514
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2009
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