BACKGROUND:Next-generation sequencing (NGS) testing in patients with metastatic non-small cell lung cancer (mNSCLC) identifies actionable driver oncogenes (ADO) and targeted treatment (TT). Potential inequities were evaluated in NGS testing and TT in patients with mNSCLC. PATIENTS AND METHODS:This retrospective study used a nationwide electronic health record-derived deidentified database for patients ≥18 years diagnosed with mNSCLC between 4/2018 and 4/2024, ≥2 recorded visits, and follow-up ≥90 days post diagnosis. For TT, patients must have received NGS testing before first-line (1L) treatment and harbored ≥1 1L ADO. RESULTS:A total of 15 392 patients with mNSCLC were included: 66% with commercial insurance, 16% with Medicare, 12% with other, 4% with Medicaid, and 3% with other government insurance. Patients with commercial insurance had significantly higher odds of receiving NGS testing vs Medicare, Medicaid, or other insurance. While patient characteristics varied across insurances, the effect of insurance type on NGS testing did not differ by race/ethnicity, age, or socioeconomic status (SES). Site of care was a significant effect modifier, with increased odds of NGS testing for community vs academic settings for commercial, Medicare, and other insurance and decreased odds for Medicaid. When all patients received NGS testing, significantly lower odds of receiving TT occurred for patients with SES 2 vs SES 1 (lowest); higher odds occurred for Asian vs white patients. CONCLUSION:Insurance is a key contributor to inequity in NGS testing. When all patients received NGS testing, equity was achieved in patients receiving TT, except those with lower SES, who potentially did not qualify for Medicaid.

280 Background: Comprehensive biomarker testing allows for selection of molecularly targeted therapies that improve patient outcomes and is considered a best practice. Despite its importance, access to biomarker testing is often hindered by gaps in insurance coverage, limiting the potential for personalized medicine. As of 2023, fifteen states and the District of Columbia have enacted legislation mandating insurance coverage for biomarker testing, acknowledging its clinical significance. However, Tennessee remains without such legal protections, creating barriers for patients in accessing this vital diagnostic tool. In this study, we obtain and assess instances of initial insurer denial for biomarker testing at a large community oncology practice. Methods: We conducted a retrospective analysis of electronic health record (EHR) data from Tennessee Oncology for patients whose insurance companies denied coverage for biomarker testing from one lab vendor. This limited cohort consisted of 45 patients with denials for comprehensive solid tumor tissue testing documented between June 2023 and December 2024. Data extracted included cancer type, reason for biomarker testing, and if there were actionable mutations based on clinical notes and testing results. Additionally, we analyzed whether testing was guideline concordant based on National Comprehensive Cancer Network (NCCN) guidelines for specific cancer type and stage. Results: The most common diagnoses prompting biomarker testing were stage IV non-small cell lung cancer (NSCLC) (n = 9), stage IV breast cancer (n = 7), stage III NSCLC (n = 5), and stage IV colorectal cancer (CRC) (n = 4). A majority of tests (73%) were performed in accordance with National Comprehensive Cancer Network (NCCN) guidelines. Among those tested, 45% revealed actionable mutations with the potential to influence therapeutic decision. Finally, 16% (7/45) of tests were conducted for recurrent disease. Conclusions: Our analysis highlights significant barriers to biomarker testing for patients with advanced solid tumors. Despite a high rate of guideline-concordant testing and identification of actionable mutations in nearly half of the cases, insurance denials remain a barrier to accessing precision medicine, and thereby, appropriate targeted therapies. These findings underscore the need for policy reform in states that do not already have mandated insurance coverage for biomarker testing.

424 Background: With the ever-expanding landscape of precision medicine, there is an enormous amount of biomarker information that oncologists are expected to meaningfully process and utilize for patient care. The relevance of this information can change over time as new FDA approvals come in or there is a change in prognostic or treatment guidelines. Unfortunately, PDF reports that are in the patient’s chart do not change with time and so there is a risk of this actionable information going unnoticed. Leveraging raw data from sequencing companies, we were able to identify patients who were eligible for a new indication based on biomarker findings on historic NGS tests. Methods: New FDA approval was reviewed carefully to extract disease and biomarker criteria. This was used to identify relevant patient cohort from our genomic data warehouse with an additional filter to remove deceased patients and ones who were not actively being treated/followed. Personalized emails were sent to the physicians alerting them about the new approval and calling out the specific patients who were impacted. Results: 555 patients who were eligible for a new targeted therapy were identified via genomic lookback. None of these patients had this drug mentioned as an eligible therapy option on their NGS reports. 194 physicians who were thought to be the primary medical oncologists for these patients were notified via email. As of late April, 87 (15%) patients had already started on the targeted therapy with an average monthly addition of 13 patients. Conclusions: Precision oncology continues to rapidly grow in complexity as diverse testing modalities, targets, and drug indications all proliferate. Expert level help can be necessary for interpretation of rare variants, discordant results, or other confusing situations. Providing access to such expertise on-demand and at scale across a large community oncology network has led to increasing usage of the service, and high rates of reported satisfaction.

e13673 Background: Targeted treatments (TT) have been approved for pts with mNSCLC harboring ADO in the 1L setting in recent years. This study aimed to understand if subpopulations of mNSCLC pts harboring ADO do not receive equitable access to guideline recommended 1L TT in US clinical settings. Methods: This retrospective study used the Flatiron Health electronic health record-derived, US nationwide, de-identified database. Pts with de novo mNSCLC (stage IVA or IVB) diagnosed between 4/1/2018-6/30/2023 were included if they were ≥18 y, had ≥2 visits after advanced diagnosis (aDx) and ≥90 days follow-up, received any biomarker testing prior to 1L Tx initiation, and harbored ADO (ALK, BRAF, EGFR, MET, NTRK, RET and/or ROS1). Results: Overall 2165 pts met study criteria: mean age was 67 y, 65% female, 11% Medicare insured, 58% commercial insured, 76% treated in the community setting with 11% Medicare and 64% commercial insured (vs 12% and 41% treated in the academic setting with Medicare and commercial insurance), and 45% had smoking history; of non-missing data, 12% had lowest socioeconomic status (SES), 26% with highest SES, 95% had non-squamous NSCLC, and 83% had ECOG performance status ≤1. The median time from aDx to testing result among the 53% non-Latinx (nL) white, 8% nL Black, 7% Latinx, 13% nL Asian, 7% nL other and 13% missing race/ethnicity was 21, 23, 24, 21, 23 and 20 days, respectively; median time from aDx to TT initiation was 38, 38, 43, 36, 47 and 37 days, respectively. Pts significantly more likely to receive 1L TT were (Table): pts of color vs white pts; Medicare vs commercial insurance at community sites; without vs with smoking history. Pts less likely to receive 1L TT were (Table): community vs academic sites; Medicare vs commercial insurance at academic sites. Consistent findings were seen in the 1817 pts with established 1L ADO (ie. ALK, EGFR or ROS1) (Table). Conclusions: When pts with mNSCLC harboring ADO had biomarker testing before Tx initiation, contrary to prior observed racial inequity in NGS testing, there was no racial inequity in receiving 1L TT. However, inequity in receiving 1L TT was observed by insurance type, smoking history and site of care. Interventions are warranted to address these contributors to 1L TT inequities. [Table: see text]

6507 Background: Recent real-world studies observed that some aNSCLC pts with ADO initiated non-targeted therapy (non-TT) before biomarker test results became available. This study assesses the clinical impact of the timing of first line (1L) TT in aNSCLC pts with ADO. Methods: In a retrospective analysis of the nationwide Flatiron Health electronic health record-derived de-identified database, pts aged ≥18 years, diagnosed (Dx) with aNSCLC between 1/1/2015-10/18/2022, had ADO (ALK, BRAF, EGFR, RET, MET, ROS-1, or NTRK) based on biomarker testing ≤ 90 days of advanced Dx, and received 1L treatment (tx) were included. Cohorts were defined by tx patterns after test result: Cohort 1 received 1L TT ≤ 42 days; Cohort 2 initiated 1L non-TT before or after testing but switched to TT ≤ 42 days; Cohort 3 initiated non-TT before or after testing and did not switch to TT ≤ 42 days. Pts were followed from test results + 42 days until 11/30/2022 or death, whichever earliest. Multivariate Cox regression evaluated real-world progression-free survival (rwPFS) and overall survival (OS) between cohorts. Results: A total of 5156 aNSCLC pts with ADO were included: 79% were treated in the community setting and 56% received NGS testing. Most common ADO were EGFR and ALK for both Cohort 1 (78% and 13%) and Cohort 2 (67% and 24%); EGFR (39%) and BRAF (35%) for Cohort 3. Cohort 3 included more rare mutations (MET, NTRK, RET). Statistically significant differences were observed in gender, race/ethnicity, practice type, and area-level socioeconomic status across all cohorts. There was no significant difference in outcomes observed between Cohort 2 and 1, but significantly inferior outcomes in Cohort 3 vs 1. Conclusions: Our findings demonstrated better outcomes with upfront 1L TT vs non-TT in aNSCLC pts with ADO. The comparable outcomes between pts who received 1L TT after test result and pts who switched to TT ≤ 42 days of test result available underscore the importance of timely tx decisions based on ADO detection in lieu of tx-switch at progression. Opportunities remain to improve utilization of NGS to identify all ADO upfront to inform the appropriate 1L TT when indicated. [Table: see text]

Supplementary Figure S3. Overall survival (OS) and progression free survival (PFS) in different subgroups. (A) Subgroup analysis by HPV status and oropharyngeal primary site, (B) subgroup analysis by PIK3CA mutational status and oropharyngeal primary site, and (C) Subgroup analysis by TP53 mutational status and oropharyngeal primary site.

Supplemental Methods. Supplemental Table 1: ââ,¬â€¹Genomic Data Characterization by Center. Supplemental Table 2: ââ,¬â€¹Gene Panels Submitted by Each Center. Figure S1: Number of putative germline SNPs per sample, before and after uniform germline filtering. Figure S2ââ,¬â€¹. Distribution of total somatic mutation burden per sample stratified by sequencing panel. Figure S3: ââ,¬â€¹Log-scale comparison of mutation frequencies at hotspot sites between GENIE (data aggregated from all sequencing panels) and cancerhotspots.org (CHS) using a binomial test. Figure S4:ââ,¬â€¹ Comparison of mutation frequencies at hotspot sites in each GENIE sequencing panel with cancerhotspots.org (CHS) using a binomial test.

Supplementary Figure S5. Immunohistochemistry shows the difference among subtypes (A) Protein levels as determined by immunohistochemistry (IHC) (N=47) for the differentiation of the three super-groups and five subtypes (B) Representative examples of IHC staining of HNC samples for key genes, such as SOX2, CDKN2A, CCDN1 and TP63.

Background:Third generation EGFR TKIs have emerged as a first line treatment of choice for aNSCLC patients with qualifying EGFR mutations due to high and durable response rates; however most patients will progress on therapy and may receive further treatment. Second line (2L) options include other EGFR TKIs, chemotherapy (C) and chemoimmunotherapy (C-IO). An optimal treatment strategy and utility of biomarkers in this 2L setting remain uncharacterized. In this study, we aim to describe the real-world treatment patterns and outcomes of patients with aNSCLC after treatment with first line (1L) EGFR TKIs to elucidate the potential for biomarker-guided approaches. Methods:We selected patients with non-squamous aNSCLC treated with 1L EGFR TKIs on or after April 1, 2018 (based on 1L approval of osimertinib) within the US-based de-identified Flatiron Health-Foundation Medicine (FMI) real world clinico-genomic database. Real world overall survival (rwOS) and progression free survival (rwPFS) curves and estimates of median survival time were generated using the Kaplan-Meier method. PD-L1 and tumor mutational burden (TMB) were summarized overall and by 2L treatment regimen. Results:Among 428 patients who received 1L EGFR TKI treatment, 386 (90%) received osimertinib, 30 (7%) received afatinib and 11 (3%) received erlotinib. For patients with known 2L treatment information (n=139, 32%) most received EGFR TKI alone (n=43, 31%), followed by C-IO (n=38, 27%), and C alone (n=14, 10%). Median rwOS following 2L treatment with EGFR TKI, C-IO, and C was 21.0 (95% CI 17.4-28.7) months, 9.9 (95% CI 7.7-19.8) months, and 17.4 (95% CI 4.3-NA) months respectively. Median rwPFS for the EGFR-TKI, C-IO, and C cohorts was 5.1 (95% CI 3.4-12.5) months, 5.5 (95% CI 3.3-7.0) months, and 3.5 (95% CI 1.9-NA) months. 416 (97%) of 428 patients harbored an EGFR mutation detected by FoundationOne®CDx, including 361 (84%) patients with at least one EGFR mutation in NCCN Guidelines. Among patients with available PD-L1 status (n=254, 59%), PD-L1 positivity (≥1% tumor proportion score) was more common among patients who received 2L C-IO (88%) compared to patients overall (59%). 30 (7%) of 428 patients had high TMB (≥10 mut/Mb); prevalence of high TMB was similar regardless of 2L therapy choice. Conclusions:This real-world data analysis confirmed that among patients with aNSCLC treated with EGFR TKIs, the vast majority received 1L osimertinib. Among 2L treatment options, additional EGFR TKI use was the most common and patients in this cohort had robust outcomes, with a median rwOS of 21 mos. Further analyses will describe the clinical characteristics of patients receiving different 2L treatment strategies and evaluate the association of PD-L1 status and select EGFR mutations with outcomes across therapeutic classes. Citation Format: Ericka Ebot, Jie He, David Fabrizio, Ivy Altomare, Neha Jain, Davey Daniel, Thomas Stricker, Edward Arrowsmith. Real world treatment patterns and outcomes in patients with advanced non-small cell lung cancer (aNSCLC) post-EGFR tyrosine kinase inhibitor (TKI) therapy [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 933.

Supplementary Figure S4. Disruption of various key cellular processes by genomic alterations. Genomic alterations that affect: (A) apoptosis, (B) Differentiation, (C) Oxidative stress and (D) Nucleic acid processing/modification.

S3. Representative images of cells grown in 3D Matrigel for 14D and treated with ABT-263 (1.0 uM). S4. Whole cell lysates from cells treated with ABT-263 (1.0uM) for 0=24 hours.

Supplementary Figure S3. Pathway annotation for HNSCC super-groups. Each horizontal bar graph represents enriched pathways in different subtypes. The number at the end of bar is the total number of genes in a pathway. Percentage of genes in the dataset that overlap with the pathway are shown in grey colour of the bar. The trend line represents the -log(p-value).

Supplementary Table from Natural History and Characteristics of ERBB2-mutated Hormone Receptor–positive Metastatic Breast Cancer: A Multi-institutional Retrospective Case–control Study from AACR Project GENIE

Treatment decisions in primary myelofibrosis (PMF) are guided by numerous prognostic systems. Patient-specific comorbidities have influence on treatment-related survival and are considered in clinical contexts but have not been routinely incorporated into current prognostic models. We hypothesized that patient-specific comorbidities would inform prognosis and could be incorporated into a quantitative score. All patients with PMF or secondary myelofibrosis with available DNA and comprehensive electronic health record (EHR) data treated at Vanderbilt University Medical Center between 1995 and 2016 were identified within Vanderbilt's Synthetic Derivative and BioVU Biobank. We recapitulated established PMF risk scores (eg, Dynamic International Prognostic Scoring System [DIPSS], DIPSS plus, Genetics-Based Prognostic Scoring System, Mutation-Enhanced International Prognostic Scoring System 70+) and comorbidities through EHR chart extraction and next -generation sequencing on biobanked peripheral blood DNA. The impact of comorbidities was assessed via DIPSS-adjusted overall survival using Bonferroni correction. Comorbidities associated with inferior survival include renal failure/dysfunction (hazard ratio [HR], 4.3; 95% confidence interval [95% CI], 2.1-8.9; P = .0001), intracranial hemorrhage (HR, 28.7; 95% CI, 7.0-116.8; P = 2.83e-06), invasive fungal infection (HR, 41.2; 95% CI, 7.2-235.2; P = 2.90e-05), and chronic encephalopathy (HR, 15.1; 95% CI, 3.8-59.4; P = .0001). The extended DIPSS model including all 4 significant comorbidities showed a significantly higher discriminating power (C-index 0.81; 95% CI, 0.78-0.84) than the original DIPSS model (C-index 0.73; 95% CI, 0.70-0.77). In summary, we repurposed an institutional biobank to identify and risk-classify an uncommon hematologic malignancy by established (eg, DIPSS) and other clinical and pathologic factors (eg, comorbidities) in an unbiased fashion. The inclusion of comorbidities into risk evaluation may augment prognostic capability of future genetics-based scoring systems.

Supplementary Table 1. List of antibodies used for immunoblotting. Supplementary Table 2. Patient biopsies used for IHC analysis. Supplementary Table 3. List of genes that are significantly upregulated in TPB-resistant tumors relative to untreated parental tumors. Supplementary Table 4. Expression of ECM/cell adhesion genes in pre-treatment tumor biopsies from patients in the NeoSphere trial.

Distribution of clinically actionable mutations according to PEPI score, PCNA proliferation signature and breast cancer subtypes

Supplementary Figure S2. Workflow of training HNSCC subtypes and consensus clustering of three training datasets. (A) Workflow of the procedure to identify and validate HNSCC subtypes (B) Consensus clustering in three training datasets identifies five HNC subtypes that differ across platforms. Consensus index matrix for k=5, cumulative distribution function (CDF) for k=2 to k=10 and relative change in area under the CDF curve for k=2 to k=10 are shown. From top to bottom are Agilent (n=134), Illumina (n=131), and Affymetrix (n=106) cohorts.

Supplementary Figure S1. Workflow showing the processing and usage of HNSCC samples. Samples with more that 60% tumor content were included for HPV consensus testing and next generation sequencing and other analyses.

448 Background: As an increasing number of biomarker-driven therapies get approved, the burden on the oncology provider to keep track of approved therapies has increased. Further, most of the genomic findings are trapped in unstructured documents and are not easily searchable within the electronic medical record (EMR). We circumvented these issues in a pilot study by creating physician alerts that highlight actionable biomarker-driven therapies and institutional trials, making them easily accessible to oncology providers. Methods: Provider Messaging for Precision Treatments (ProMPT) service is being piloted at a large community oncology practice site with 29 oncology providers. Leveraging the raw genomic data feed from NGS vendors, we perform a weekly query for all the patients with a molecular test signed in the past week. We then examine the diagnoses and the identified mutations for the patients to match FDA approved precision therapies and institutional trials (genomic and diagnosis-based). The findings are recorded in a tabular format and sent weekly to providers via email to assist them in choosing the best therapy for their patients. Results: In the 12 weeks since launch, we have reviewed 1274 mutations from 114 unique patients. In addition, we also highlighted findings that warranted germline counseling/testing (based on the variant allele frequency), additional testing (lack of a clear driver mutation), and biomarkers that may confer resistance to treatment via targeted therapy or immunotherapy. Conclusions: Creating automated services that alleviate provider burden to recall and recommend appropriate therapies by surfacing actionable genomic findings when the NGS results first become available can ensure that all patients receive the best care. Services such as ProMPT are needed to effectively deliver on the promise of personalized medicine.[Table: see text]