Damon Hostin

The fly Drosophila melanogaster is one of the most intensively studied organisms in biology and serves as a model system for the investigation of many developmental and cellular processes common to higher eukaryotes, including humans. We have determined the nucleotide sequence of nearly all of the approximately 120-megabase euchromatic portion of the Drosophila genome using a whole-genome shotgun sequencing strategy supported by extensive clone-based sequence and a high-quality bacterial artificial chromosome physical map. Efforts are under way to close the remaining gaps; however, the sequence is of sufficient accuracy and contiguity to be declared substantially complete and to support an initial analysis of genome structure and preliminary gene annotation and interpretation. The genome encodes approximately 13,600 genes, somewhat fewer than the smaller Caenorhabditis elegans genome, but with comparable functional diversity.

Importance: Clinical guidelines recommend biomarker testing to identify patients eligible for targeted therapy. However, evidence suggests that biomarker testing rates are below guideline recommendations, which has been associated with worsened clinical outcomes, including overall survival. Objectives: To identify patients with newly diagnosed advanced cancer receiving comprehensive genomic profiling (CGP), non-CGP, or no biomarker testing and to explore the change in rates of testing over time and compare targeted therapy rates and health care costs during first-line therapy. Design, Setting, and Participants: This retrospective cohort study used the deidentified Optum Labs Data Warehouse, a claims database of longitudinal health information on commercial health plan and Medicare Advantage enrollees, to identify patients diagnosed with advanced cancer between January 1, 2018, and January 1, 2022. The study included 26 311 adults with newly diagnosed advanced cancer (breast, colorectal, gastric, non-small cell lung, ovarian, and pancreatic) and continuous enrollment in a commercial or Medicare Advantage health plan for 12 months before and 6 months after their first advanced cancer diagnosis. Data were analyzed between February 1, 2023, and March 31, 2024. Exposure: Biomarker testing. Main Outcomes and Measures: Evidence of biomarker testing, the receipt of targeted therapy during first-line therapy, and per-patient, per-month (PPPM) costs during first-line therapy. Results: Among 26 311 patients (mean [SD] age, 68 [11] years; 62% female; 70% Medicare Advantage enrollees), molecular testing rates were suboptimal (35% had evidence of molecular testing), but testing rates increased across time for most cancer types (from 32% in 2018 to 39% in 2021-2022). Patients with non-small cell lung cancer and colorectal cancer with CGP testing were more likely to receive targeted therapy (odds ratio [OR], 1.57; 95% CI, 1.31-1.90; P < .001) compared with patients who received non-CGP testing (OR, 2.34; 95% CI, 1.58-3.47; P < .001). Costs among patients with CGP testing were not statistically different from those with non-CGP testing (cost ratios of 1.03; 95% CI, 0.91-1.17 [P = .63] for breast cancer, 0.98; 95% CI, 0.89-1.09 [P = .71] for colorectal cancer, 1.10; 95% CI, 0.87-1.40 [P = .42] for gastric cancer, 1.06; 95% CI, 1.00-1.13 [P = .054] for non-small cell lung, 0.94; 95% CI, 0.76-1.15 [P = .55] for ovarian cancer, and 1.00; 95% CI, 0.83-1.21 [P = .98] for pancreatic cancer). Conclusions and Relevance: In this cohort study, although increasing over time, biomarker testing rates were suboptimal despite guideline recommendations and increasing insurance coverage for testing. Given the potential benefits of CGP testing, such as increasing rates of targeted therapy without increased treatment-related costs, increasing CGP testing may improve outcomes.

PURPOSE Therapeutic decision making for patients with advanced non–small cell lung cancer (aNSCLC) includes a growing number of options for genomic, biomarker-guided, targeted therapies. We compared actionable biomarker detection, targeted therapy receipt, and real-world overall survival (rwOS) in patients with aNSCLC tested with comprehensive genomic profiling (CGP) versus small panel testing (SP) in real-world community health systems. METHODS Patients older than 18 years diagnosed with aNSCLC between January 1, 2015, and December 31, 2020, who received biomarker testing were followed until death or study end (September 30, 2021), and categorized by most comprehensive testing during follow-up: SP (≤52 genes) or CGP (&gt;52 genes). RESULTS Among 3,884 patients (median age, 68 years; 50% female; 73% non-Hispanic White), 20% received CGP and 80% SP. The proportion of patients with ≥one actionable biomarker (actionability) was significantly higher in CGP than in SP (32% v 14%; P &lt; .001). Of patients with actionability, 43% (CGP) and 38% (SP) received matched therapies ( P = .20). Among treated patients, CGP before first-line treatment was associated with higher likelihood of matched therapy in any line (odds ratio, 3.2 [95% CI, 1.84 to 5.53]). CGP testing (hazard ratio [HR], 0.80 [95% CI, 0.72 to 0.89]) and actionability (HR, 0.84 [95% CI, 0.77 to 0.91]) were associated with reduced risk of mortality. Among treated patients with actionability, matched therapy receipt showed improved median rwOS in months in CGP (34 [95% CI, 21 to 49] matched v 14 [95% CI, 10 to 18] unmatched) and SP (27 [95% CI, 21 to 43] matched v 10 [95% CI, 8 to 14] unmatched). CONCLUSION Patients who received CGP had improved detection of actionable biomarkers and greater use of matched therapies, both of which were associated with significant increases in survival.

6633 Background: Guideline-recommended molecular testing has become essential for biomarker-guided clinical decision making, particularly for patients with advanced (adv) disease. Several biomarkers have indications that are tumor type-agnostic (starting with MSI in 2017, NTRK in 2018, TMB in 2020, and RET and BRAF in 2022). Biomarker testing is covered by insurers, both Medicare (covers comprehensive genomic profiling [CGP] and non-CGP panels) and commercial (at least non-CGP). This study aimed to understand utilization of biomarker testing across tumor types. Methods: This retrospective analysis used de-identified administrative claims from Optum Labs Data Warehouse. Adult Commercial (COM) and Medicare Advantage (MA) enrollees diagnosed with any 1 of 6 adv cancer types from 1/2018 to 8/2021 were identified; the date of the first claim indicating adv cancer was the index date. Continuous enrollment for 12 months prior to (baseline), and ≥6 months post-index date, unless they died (follow-up) was required. Biomarker testing was captured using Current Procedural Terminology (CPT) codes indicating CGP (&gt; 50 gene panels), non-CGP (at most 5-50 gene panels), or CPT code 81479 (unlisted molecular pathology procedure) during the study period. The primary analysis evaluates testing in the follow-up only, with secondary analyses evaluating testing including the baseline (to account for testing prior to the index date). Results: We identified 16,931 breast (BC), 16,838 non-small cell lung (NSCLC), 8,755 colorectal (CRC), 4,244 pancreatic (PC), 2,610 ovarian (OC), and 1,231 gastric (GC) adv cancer patients meeting study criteria. Overall biomarker testing rates in the follow-up period were: 37% NSCLC, 19% BC, 41% CRC, 35% PC, 51% OC, 35% GC. The Table shows testing rates by cancer, insurance type, and panel size during follow-up. Testing rates were lower among MA patients compared to COM patients. Even considering baseline and follow-up periods, overall biomarker testing rates were low, and lower among MA compared to COM : 48% NSCLC (53% COM, 47% MA), 27% BC (34% COM, 22% BC), 56% OC (61% COM, 53% MA),42% PC (53% COM, 38% MA), 47% CRC (56% COM, 42% MA), 41% GC (54% COM, 35% MA). Conclusions: Considering guideline recommendations, rates of biomarker testing across tumor types are far from optimal despite insurance coverage for testing. Identification of barriers to biomarker testing and interventions to overcome these are needed to improve adherence to biomarker testing guidelines. [Table: see text]

Introduction: Cardiovascular disease (CVD) continues to be the leading cause of death in the US and globally. Clinical practice guidelines recommend genetic testing for the diagnosis of select CVDs to improve disease management, reduce incidence of cardiac events, and positively impact major cardiac adverse events. Professional guidelines also recommend pharmacogenomic (PGx) testing for patients being prescribed certain medications. Research Question: What is the utilization of genetic diagnosis and PGx testing in patients with CVD in the US? Methods: This study used data from the Optum Labs Data Warehouse, composed of de-identified administrative claims data for both commercially insured and Medicare Advantage enrollees to assess rates of genetic testing among adult patients diagnosed with 4 major types of CVD conditions (arrhythmias (N=518,316), familial hypercholesterolemia (FH) (N=38,068), cardiomyopathies (CM) (N=74,597), and aortopathies (N=58,316)) and PGx testing rates in patients prescribed CVD medications with PGx test recommendations (per CPIC guidelines) between January 1, 2017 to December 31, 2021. Patients were required to have ≥12 months of continuous enrollment prior (baseline) to diagnosis (index date) and ≥12 months post-index period unless they died (follow-up). Genetic and PGx testing was captured using Current Procedural Terminology (CPT®) codes in both baseline and follow-up periods. Results: Low genetic testing utilization was found across the 4 major types of CVD conditions. Genetic testing rates were 1.3% in the arrythmia cohort, 1.9% in the CM cohort, 2.0% in the aortopathy cohort and 1.9% in the FH cohort. PGx testing rates in patients prescribed with CVD relevant medications were 0.6% (N=2,094/377,111) in the arrhythmia cohort, 0.8% (N=501/60,632) in the CM cohort, 0.7% (N=247/37,344) in the aortopathy cohort, and 1.3% (N=329/25,835) in FH cohort. Conclusions: Despite clinical practice guidelines, genetic and PGx testing in patients with CVD conditions remains underutilized. Future work will help us understand the barriers to guideline adherence both for genetic diagnosis and PGx testing that could impact clinical management and patient outcomes.