Abstract 166: Real world genomic data supports combined use of SHP-2 and PD-1/PD-L1 inhibitors in solid tumors

Recent discoveries of genomic alterations that underlie and promote the malignant phenotype, together with an expanded repertoire of targeted agents, have provided many opportunities to conduct hypothesis-driven clinical trials. The ability to profile each unique cancer for actionable aberrations by using high-throughput technologies in a cost-effective way provides unprecedented opportunities for using matched therapies in a selected patient population. The major challenges are to integrate and make biologic sense of the substantial genomic data derived from multiple platforms. We define two different approaches for the analysis, interpretation, and clinical applicability of genomic data: (1) the genomically stratified model originates from the “one test-one drug” paradigm and is currently being expanded with an upfront multicategorical approach following recent advances in multiplexed genotyping platforms; and (2) the comprehensive assessment model is based on whole-genome, -exome, and -transcriptome data and allows identification of novel drivers and subsequent therapies in the experimental setting. Tumor heterogeneity and evolution of the diverse populations of cancer cells during cancer progression, influenced by the effects of systemic treatments, will need to be addressed in the new scenario of early drug development. Logistical issues related to prescreening strategies and trial allocation, in addition to concerns in the economic and ethical domains, must be taken into consideration. Here we present a historical view of how increased understanding of cancer genomics has been translated to the clinic and discuss the prospects and challenges for further implementation of a personalized treatment strategy for human solid tumors.

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Leveraging Real World Genomic Data to Advance Prostate Cancer Precision Oncology

European Urology ◽

10.1016/j.eururo.2021.10.029 ◽

2021 ◽

Author(s):

Himisha Beltran ◽

Alicia K. Morgans

Keyword(s):

Prostate Cancer ◽

Real World ◽

Genomic Data ◽

Precision Oncology

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Fleet optimization considering overcapacity and load sharing restrictions using genetic algorithms and ant colony optimization

Artificial intelligence for engineering design analysis and manufacturing ◽

10.1017/s0890060419000428 ◽

2020 ◽

Vol 34 (1) ◽

pp. 104-113

Author(s):

Fredy Kristjanpoller ◽

Kevin Michell ◽

Werner Kristjanpoller ◽

Adolfo Crespo

Keyword(s):

Ant Colony Optimization ◽

Real World ◽

Life Cycle Cost ◽

Optimal Solution ◽

Load Sharing ◽

Ant Colony ◽

Added Value ◽

Fleet Size ◽

Combined Use ◽

Computing Performance

AbstractThis paper presents a fleet model explained through a complex configuration of load sharing that considers overcapacity and is based on a life cycle cost (LCC) approach for cost-related decision-making. By analyzing the variables needed to optimize the fleet size, which must be evaluated in combination with the event space method (ESM), the solution to this problem would normally require high computing performance and long computing times. Considering this, the combined use of an integer genetic algorithm (GA) and the ant colony optimization (ACO) method was proposed in order to determine the optimal solution. In order to analyze and highlight the added value of this proposal, several empirical simulations were performed. The results showed the potential strengths of the proposal related to its flexibility and capacity in solving large problems with a near optimal solution for large fleet size and potential real-world applications. Even larger problems can be solved this way than by using the complete enumeration approach and a non-family fleet approach. Thus, this allows for a more real solution to fleet design that also considers overcapacity, availability, and an LCC approach. The simulations showed that the model can be solved in much less time compared with the base model and allows for the resolution of a fleet of at least 64 trucks using GA and 130 using ACO, respectively. Thus, the proposed framework can solve real-world problems, such as the fleet design of mining companies, by offering a more realistic approach.

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Development and validation of a real-world clinicogenomic database.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.2514 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 2514-2514 ◽

Cited By ~ 4

Author(s):

Gaurav Singal ◽

Peter Grant Miller ◽

Vineeta Agarwala ◽

Jie He ◽

Anala Gossai ◽

...

Keyword(s):

Real World ◽

Cancer Genomics ◽

False Negative ◽

Genomic Data ◽

Female Gender ◽

Driver Mutations ◽

New Paradigm ◽

Process Data ◽

Genomic Databases ◽

Negative Results

2514 Background: Genomic findings have diagnostic, prognostic, and predictive utility in clinical oncology. Population studies have been limited by reliance on trials, registries, or institutional chart review, which are costly and represent narrow populations. Integrating electronic health record (EHR) and genomic data collected as part of routine clinical practice may overcome these hurdles. Methods: Patients in the Flatiron Health Database with non-small cell lung cancer (NSCLC) who underwent comprehensive genomic profiling (CGP) by Foundation Medicine were included. EHR processing included structured data harmonization and abstraction of variables from unstructured documents. EHR and CGP data were de-identified and linked in a HIPAA-compliant process. Data included clinical characteristics, alterations across > 300 genes, tumor mutation burden (TMB), therapies and associated real-world responses, progression, and overall survival (OS). Results: The cohort (n = 1619) had expected clinical (mean age 66; 75% with smoking hx; 80% non-squamous) and genomic (18% EGFR; 4% ALK; 1% ROS1) properties of NSCLC. Presence of a driver mutation (EGFR, ALK, ROS1, MET, BRAF, RET, or ERBB2; n = 576) was associated with younger age, female gender, non-smoking, improved OS (35 vs 19 mo, LR p < 0.0001), and prolonged survival when treated with NCCN-recommended therapy (42 vs 28 mo, LR p = 0.001). CGP identified false negative results in up to 30% of single-biomarker tests for EGFR, ALK, and ROS1. CGP accuracy was supported by clinical outcomes. For example, 5 patients with prior negative ALK-fusion testing began ALK-directed therapy after positive CGP results. All 5 exhibited at least a partial response as recorded in the EHR by treating clinicians. Immunotherapy was used in 22% of patients (n = 353). TMB predicted response to nivolumab, including in PD-L1 negative populations. We recapitulated known associations with smoking, histology, and driver mutations. Conclusions: We present and validate a new paradigm for rapidly generating large, research-grade, longitudinal clinico-genomic databases by linking genomic data with EHR clinical annotation. This method offers a powerful tool for understanding cancer genomics and advancing precision medicine.

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Real world results of liquid biopsy in stage 3/4 solid tumors and potential ''clinical actionability."

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.15_suppl.2555 ◽

2018 ◽

Vol 36 (15_suppl) ◽

pp. 2555-2555

Author(s):

Rebecca Christian Arend ◽

Angelina Londono ◽

Alba Martínez ◽

Andrew Ford ◽

Charmaine Brown ◽

...

Keyword(s):

Solid Tumors ◽

Real World ◽

Liquid Biopsy

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An evaluation of administrative data linkage for measurement of real-world outcomes of large clinical panel sequencing for advanced solid tumors.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.29_suppl.283 ◽

2020 ◽

Vol 38 (29_suppl) ◽

pp. 283-283

Author(s):

Ramy Saleh ◽

Philippe L. Bedard ◽

Paul Nguyen ◽

Eoghan Ruadh Malone ◽

Celeste Yu ◽

...

Keyword(s):

Solid Tumors ◽

Administrative Data ◽

Real World ◽

Short Interval ◽

Common Disease ◽

Advanced Solid Tumors ◽

Vital Status ◽

Treatment Matching ◽

The Impact ◽

Panel Sequencing

283 Background: There is limited real-world evidence of impact of large clinical panel sequencing on treatment-matching for patients with advanced solid tumors. The province of Ontario has a single payer, publicly funded health care system. We linked genomic testing results from a prospective province-wide trial, OCTANE (Ontario-Wide Cancer TArgeted Nucleic Acid Evaluation), to administrative data to determine the feasibility of this approach for evaluating survival and the impact of sequencing on treatment matching. Methods: We linked all Ontario patients from Princess Margaret (PM) with panel testing results (tumor-only 555-gene panel) to province-wide administrative data on treatments and outcomes. Patients were recruited from August 2016 to August 2018. Only clinically actionable variants based upon OncoKB annotation (Level 1 and 2) were assessed for genotype-informed treatment matching. Results: All 888 eligible patients were successfully linked to administrative data. Mean age was 58 (±13) years, 635 (71.5%) were female. Most common disease sites were ovary (26.4%), uterus (14.0%), colorectal (11.8%) and breast (9.5%). Administrative data vital status was more complete than trial collected data with 262 of 476 deaths only recorded in administrative data. Median survival was 1.70 years (95% confidence interval 1.50-1.91). 247 (27.8%) had actionable mutations, most commonly PIK3CA (54.7%), BRCA1 (15.8%), BRCA2 (15.0%) and BRAF (8.9%). 37 (15.0%) and 42 (17.0%) patients with actionable mutations received targeted therapy within 6 and 12 months of test report date, respectively. Conclusions: This is the first known feasibility study of linked administrative data to measure outcomes of large clinical panel sequencing for patients with advanced solid tumors. Vital status was more complete with administrative data compared to trial-collected data, and treatment data was successfully linked. About one in twenty-one enrolled patients received genome-informed treatments within 12 months, or about one in six of all patients with actionable mutations. This may be due to short interval follow up, trial and drug access, successful standard of care treatments, early patient deterioration or limited alterations covered by the panel, among other causes.

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Real-world integration of genomic data into the electronic health record: the PennChart Genomics Initiative

Genetics in Medicine ◽

10.1038/s41436-020-01056-y ◽

2020 ◽

Author(s):

Kelsey S. Lau-Min ◽

Stephanie Byers Asher ◽

Jessica Chen ◽

Susan M. Domchek ◽

Michael Feldman ◽

...

Keyword(s):

Electronic Health Record ◽

Real World ◽

Genomic Data ◽

Health Record ◽

Electronic Health

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Real-world effectiveness of approved anticancer agents among Medicare beneficiaries.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.6589 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. 6589-6589

Author(s):

Angela Green ◽

Michael A. Curry ◽

Peter Bach ◽

Sham Mailankody

Keyword(s):

Clinical Trial ◽

Solid Tumors ◽

Anticancer Agents ◽

Real World ◽

Drug Approval ◽

Cancer Drugs ◽

Oral Drugs ◽

Eligibility Criteria ◽

Cancer Specific Survival ◽

Median Difference

6589 Background: The overall survival (OS) among elderly patients (pts) treated with novel anticancer agents in the real world may be inferior to the OS reported in pivotal trials for drug approval. Pts ≥ 65 yrs old constitute 60% of cancer pts, yet only 40% of cancer clinical trial participants. Elderly pts have greater comorbidities and experience a higher risk of toxicity from cancer drugs. Using the Surveillance Epidemiology and End Results-Medicare database (SEER-Medicare), we compared the OS among elderly pts treated with FDA-approved cancer drugs for advanced solid tumors to the OS reported in the clinical trial. Methods: We identified cancer drugs FDA-approved for metastatic solid tumors between 1/1/08-12/31/12. In a retrospective analysis, for each indication we identified pts in SEER-Medicare meeting disease eligibility criteria (stage, histology, prior therapies) in the trial associated with approval. Pts were diagnosed with cancer from 2010-2013 with follow-up through 2014. Treatment (tx) was determined from national drug codes in Medicare Part B for intravenous (IV) drugs and Part D for oral drugs. Indications were included if ≥ 30 pts receiving tx met eligibility. Kaplan-Meier methods were used to calculate median OS and cancer-specific survival (CSS) in Medicare pts. Median duration of therapy (DOT) was estimated from date of the first through completion of the last prescription claim for oral drugs and number of cycles for IV drugs. Results: OS data were available and sample size parameters met for 14 drug indications. The median OS among SEER-Medicare pts was shorter than the reported trial OS of tx arms for 13 of 14 drug indications (median difference -7.6 mos, range +3.4 to -28.7 mos). CSS was similar to OS among Medicare pts. Median DOT among SEER-Medicare pts was shorter than the reported trial DOT of tx arms for 13 of 14 indications (median difference -2.9 mos, range 0 to -8.9 mos). Conclusions: The OS and DOT among SEER-Medicare pts treated with FDA-approved cancer drugs was inferior to the reported OS in pivotal clinical trials for nearly all indications analyzed. The shorter DOT among Medicare pts may explain survival differences. Trials leading to regulatory approval may not be generalizable to cancer pts ≥ 65 yrs.

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