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Somatic HLA-I LOH is associated with decreased durable clinical benefit and progression free survival in ICI-treated NSCLC

Neoantigen presentation arises as a result of tumor-specific mutations and is a critical component of immune surveillance that can be abrogated by somatic LOH of the human leukocyte antigen class I (HLA-I) locus. To understand the role of HLA-I LOH in oncogenesis and treatment, we utilized a pan-cancer genomic dataset of 83,644 patient samples, a small subset of which had treatment outcomes with immune checkpoint inhibitors (ICI). HLA-I LOH was common (17%) and unexpectedly had a nonlinear relationship with tumor mutational burden (TMB). HLA-I LOH was frequent at intermediate TMB, yet prevalence decreased above 30 mutations/megabase, suggesting highly mutated tumors require alternate immune evasion mechanisms. In ICI-treated patients with nonsquamous non–small cell lung cancer, HLA-I LOH was a significant negative predictor of overall survival. Survival prediction improved when combined with TMB, suggesting TMB with HLA-I LOH may better identify patients likely to benefit from ICIs.Significance:This work shows the pan-cancer landscape of HLA-I LOH, revealing an unexpected “Goldilocks” relationship between HLA-I LOH and TMB, and demonstrates HLA-I LOH as a significant negative predictor of outcomes after ICI treatment. These data informed a combined predictor of outcomes after ICI and have implications for tumor vaccine development.This article is highlighted in the In This Issue feature, p. 211

Characteristics of patients in the real-world clinico-genomic cohort

Supplementary Data from SPOP Mutations as a Predictive Biomarker for Androgen Receptor Axis–Targeted Therapy in De Novo Metastatic Castration-Sensitive Prostate Cancer

Supplementary Figure from SPOP Mutations as a Predictive Biomarker for Androgen Receptor Axis–Targeted Therapy in De Novo Metastatic Castration-Sensitive Prostate Cancer

Tyrosine kinase inhibitors and immune checkpoint inhibitors (ICI), each requiring testing for precision biomarkers, have recently been approved in the adjuvant setting. We assessed the potential value of multi-gene testing in early lung adenocarcinoma (LUAD).Using a real-world clinico-genomic database linking deidentified electronic health record-derived clinical data to genomic data, we selected patients with LUAD who underwent tissue comprehensive genomic profiling (CGP). Using a probabilistic decision tree, we estimated the cost implications of the avoidance of adjuvant ICI in patients with PD-L1+ LUAD and an ALK/ROS1/RET driver.CGP was performed on a specimen collected prior to advanced disease in 20% (1,320/6,697) of cases and ordered prior to advanced diagnosis for 12.6% (847/6,697) of patients. The prevalence of driver alterations in early and advanced stage specimens was similar, though KRAS mutations were enriched in early disease and drivers including ALK rearrangements in advanced disease. Patients who had CGP results obtained prior to vs after recurrence had less time between recurrence and the start of any first-line treatment (median 3.6 vs 6 weeks, p0.001). Through avoidance of ICI in PD-L1+ early LUAD with an ALK/ROS1/RET driver, we estimated the universal CGP could reduce expected costs by $1,597.23 per patient relative to EGFR single-gene testing.CGP can identify driver alterations and accelerate the start of first-line therapy at recurrence. It may also represent a cost-effective approach for avoiding futile adjuvant ICI in patients with drivers that have historically lacked activity with ICI in metastatic disease.

PURPOSE To study the impact of standard-of-care hormonal therapies on metastatic prostate cancer (mPC) clinical genomic profiles in real-world practice, with a focus on homologous recombination-repair (HRR) genes. PATIENTS AND METHODS Targeted next-generation sequencing of 1,302 patients with mPC was pursued using the FoundationOne or FoundationOne CDx assays. Longitudinal clinical data for correlative analysis were curated via technology-enabled abstraction of electronic health records. Genomic biomarkers, including individual gene aberrations and genome-wide loss-of-heterozygosity (gLOH) scores, were compared according to biopsy location and time of sample acquisition (androgen deprivation therapy [ADT]-naïve, ADT-progression and post-ADT, and novel hormonal therapies [NHT]-progression), using chi-square and Wilcoxon rank-sum tests. Multivariable analysis used linear regression. False-discovery rate of 0.05 was applied to account for multiple comparisons. RESULTS Eight hundred forty (65%), 132 (10%), and 330 (25%) biopsies were ADT-naïve, ADT-progression, and NHT-progression, respectively. Later-stage samples were enriched for AR, MYC, TP53, PTEN, and RB1 aberrations (all adjusted P values < .05), but prevalence of HRR-related BRCA2, ATM, and CDK12 aberrations remained stable. Primary and metastatic ADT-naïve biopsies presented similar prevalence of TP53 (36% v 31%) and BRCA2 (8% v 7%) aberrations; 81% of ADT-naïve BRCA2-mutated samples presented BRCA2 biallelic loss. Higher gLOH scores were independently associated with HRR genes ( BRCA2, PALB2, and FANCA), TP53, and RB1 aberrations, and with prior exposure to hormonal therapies in multivariable analysis. CONCLUSION Prevalence of HRR-gene aberrations remains stable along mPC progression, supporting the use of diagnostic biopsies to guide poly (ADP-ribose) polymerase inhibitor treatment in metastatic castration-resistant prostate cancer. gLOH scores increase with emerging resistance to hormonal therapies, independently of individual HRR gene mutations.

Neoantigen presentation arises as a result of tumor-specific mutations and is a critical component of immune surveillance that can be abrogated by somatic LOH of the human leukocyte antigen class I (HLA-I) locus. To understand the role of HLA-I LOH in oncogenesis and treatment, we utilized a pan-cancer genomic dataset of 83,644 patient samples, a small subset of which had treatment outcomes with immune checkpoint inhibitors (ICI). HLA-I LOH was common (17%) and unexpectedly had a nonlinear relationship with tumor mutational burden (TMB). HLA-I LOH was frequent at intermediate TMB, yet prevalence decreased above 30 mutations/megabase, suggesting highly mutated tumors require alternate immune evasion mechanisms. In ICI-treated patients with nonsquamous non–small cell lung cancer, HLA-I LOH was a significant negative predictor of overall survival. Survival prediction improved when combined with TMB, suggesting TMB with HLA-I LOH may better identify patients likely to benefit from ICIs. Significance: This work shows the pan-cancer landscape of HLA-I LOH, revealing an unexpected “Goldilocks” relationship between HLA-I LOH and TMB, and demonstrates HLA-I LOH as a significant negative predictor of outcomes after ICI treatment. These data informed a combined predictor of outcomes after ICI and have implications for tumor vaccine development. This article is highlighted in the In This Issue feature, p. 211

Background Small cell lung cancer (SCLC) has the strongest association with smoking among lung cancers. The characteristics of never smokers with SCLC is not known. Research Question Are the clinical characteristics, prognostic factors, survival, genomic alterations, and tumor mutational burdens of SCLC in patients who have never smoked different from those who have smoked? Study Design and Methods A retrospective multicenter cohort study of patients with clinician-confirmed SCLC was performed with the use of a longitudinal and nationally representative electronic medical records database. Smoking history was assessed through technology-enabled abstraction and confirmed for never smokers via chart review. Genomic characteristics of never smoker patients with SCLC were examined with the use of a next-generation sequencing-based gene panel and whole exome sequencing. Results One hundred of 5,632 patients (1.8%) with SCLC were never smokers. Relative to smokers, never smokers were more likely to be female (66.0% vs 52.4%; P = .009) and present with extensive stage (70.0% vs 62.2%; P = .028). Never smokers had a higher proportion of patients in age groups 35 to 49 years (7.0% vs 3.0%; P = .006) and ≥80 years (17.0% vs 8.2%; P = .006). Known risk factors for lung cancer were found in Interpretation The sex- and age-specific distribution of SCLC among never smokers, along with differences that were identified by genomic analyses, suggests a distinct biology of SCLC in never smokers compared with smokers.

240 Background: TMB is an emerging biomarker to predict clinical benefit from immune checkpoint inhibitors (ICI). Although high TMB in prostate cancer is rare, and we sought to evaluate independent associations of TMB by clinical factors, prior treatment, and genomics. Methods: This study used the US-based nationwide de-identified Flatiron Health-Foundation Medicine prostate cancer clinico-genomic database. The de-identified data originated from approximately 280 US cancer clinics (~800 sites) between January 2011-March 2022. Multivariable linear regression model was used to assess independent prediction of TMB levels, which were log2+1 transformed to better normalize distribution. Data are expressed as (estimate, [95% CI], p-value). Results: The study included 2,748 tissue specimens: 51.7% were from the prostate, 10.3% from bone, and 14.6% from lymph nodes. Specimens from white patients comprised 61.2% of samples, with another 7.5% from Black, 1.1% from Asian, and 30% from other or unknown race patients. Of our cohort, 58.5%, 15.5%, and 26.0% were from patients who received 0, 1-24 months, and >24 months of androgen deprivation therapy (ADT), respectively. Also 19.7%, 1.8%, 11.4%, and 0.4% had any exposure to novel hormonal therapies (NHT), Radium-223, taxanes, and ICI, respectively. Higher TMB was independently associated with ADT use >24 months (0.16, [0.05-0.27], p=0.005) and Asian race (0.36, [0.03-0.69], p=0.034). Prior treatment with NHT, taxanes, or radium was not associated with higher TMB. Compared to prostate, bladder (0.22, [0.03-0.41], p=0.023), liver (0.27, [0.13-0.42], p

46 Background: The KEYNOTE-177 randomized controlled trial demonstrated that mCRC patients with MSI high (MSI-H) and/or deficient MMR (dMMR) have better outcomes on first-line ICI than chemotherapy. This study aimed to evaluate MSI by next-generation sequencing (NGS) as a predictive biomarker of ICI effectiveness in real-world settings, and compare MSI (NGS), dMMR (immunohistochemistry, IHC), and TMB (10 mut/Mb cutoff) in predicting ICI outcomes. Methods: A prospectively declared statistical analysis plan compared the effectiveness of first-line treatment ICI versus chemotherapy in patients with MSI-H mCRC, and compared the predictive power of ICI outcomes associated with biomarkers in any line of therapy (LOT). Patient data was obtained by the US-based de-identified Flatiron Health-Foundation Medicine real-world mCRC clinico-genomic database (FH-FMI CGDB), originating from ~280 US cancer clinics between Jan/2011 and Dec/2021. Differences in progression-free survival (PFS) and overall survival (OS) were evaluated by Cox proportional hazard models, adjusted for a risk score generated from prognostic clinical features. The likelihood ratio test evaluated the superiority of a biomarker in anticipating outcomes. Results: Patients with MSI-H mCRC had more favorable outcomes receiving first-line ICI (n=49) than chemotherapy (n=89) for PFS (median 24.87 vs. 5.65 months, hazard ratio (HR): 0.31, 95% confidence interval (CI) 0.18-0.52, p 10, three with mutations in MMR genes, and 5 with BRAF mutation, consistent with MSI biology). When MSI (NGS) is added to dMMR (IHC) evaluation, there is an improvement in the prediction of TTNT (p = 0.0013), PFS (p = 0.0202), and OS (p = 0.0717), but adding MMR status to MSI did not improve explanatory power. Conclusions: MSI (NGS) robustly identifies mCRC patients with favorable outcomes on first-line ICI vs. chemotherapy, and is a nominally better predictor of ICI outcomes when compared with dMMR (IHC) alone. dMMR (IHC), MSI (NGS), and TMB have similar predictive power for ICI benefit. [Table: see text]

ImportanceThe KEYNOTE-177 trial demonstrated that patients with metastatic colorectal cancer (MCRC) with high microsatellite instability (MSI-H) and/or mismatch repair deficiency (DMMR) have better outcomes when receiving first-line immune checkpoint inhibitors (ICIs) compared with chemotherapy. Data on performance of ICIs in patients with MCRC in standard practice settings remain limited, and direct MMR vs MSI outcome association comparisons are lacking.ObjectiveTo validate MSI (determined by next-generation sequencing [NGS]) as a biomarker of ICI effectiveness among patients with MCRC in standard practice settings and examine the association of MSI assessed by NGS, DMMR by immunohistochemistry, and tumor mutational burden (cutoff, 10 mutations/megabase) with ICI outcomes.Design, Setting, and ParticipantsThis comparative effectiveness research study of outcomes in prospectively defined biomarker subgroups used data from a deidentified clinicogenomic database and included patients who received Foundation Medicine testing (FoundationOne or FoundationOne CDx) during routine clinical care at approximately 280 US academic or community-based cancer clinics between March 2014 and December 2021. The population included 1 cohort of patients with MSI-H MCRC who received first-line ICIs or chemotherapy and a second cohort who received ICIs in any line of therapy (LOT) for biomarker examination.ExposuresICI therapy or chemotherapy assigned at physician discretion without randomization.Main Outcomes and MeasuresThe main outcomes were time to next treatment (TTNT), progression-free survival (PFS), and overall survival (OS). Hazard ratios were adjusted for known prognostic imbalances. Comparisons of explanatory power used the likelihood ratio test.ResultsA total of 138 patients (median age, 67.0 years [IQR, 56.2-74.0 years]; 73 [52.9%] female) with MSI-H MCRC received first-line ICIs or chemotherapy. A total of 182 patients (median age, 64.5 years [IQR, 55.2-72.0]; 98 [53.8%] female) received ICIs in any LOT. Patients receiving first-line ICIs vs chemotherapy had longer TTNT (median, not reached [NR] vs 7.23 months [IQR, 6.21-9.72 months]; adjusted hazard ratio [AHR], 0.17; 95% CI, 0.08-0.35; P P P = .02). MSI added to DMMR better anticipated TTNT and PFS in patients receiving ICIs than DMMR alone. The same was not observed when DMMR evaluation was added to MSI.Conclusions and RelevanceIn this comparative effectiveness research study, MSI assessed by NGS robustly identified patients with favorable outcomes on first-line ICIs vs chemotherapy and appeared to better anticipate ICI outcomes compared with DMMR.

BackgroundFor patients with advanced non-small cell lung carcinoma (NSCLC), immune checkpoint inhibitor (ICPI) and chemotherapy (chemo) ICPI represent two distinct first-line standard-of-care regimens without clear and established biomarkers to inform the optimal choice for individual patients. Here, we examined the complementary roles of tumor mutational burden (TMB) and programmed death ligand-1 (PD-L1) immunohistochemistry (IHC) to inform first-line therapy using a large real-world (rw) data set.Materials and methodsThe study included patients with NSCLC from an rw de-identified clinico-genomic database. All patients underwent genomic testing using Foundation Medicine’s tissue comprehensive genomic profiling assay and PD-L1 IHC assay scored for tumor cell staining (TS).ResultsOf 2165 patients included in the analysis, 150 exhibited durable benefit from first-line ICPI regimens (these patients were enriched for PD-L1 TS ≥50, non-squamous histology, and TMB ≥20 mutations/megabase (muts/Mb)). Comparing low TMB (ConclusionThis study provides evidence that higher TMB cut-offs, such as 20 muts/Mb, can identify patients with prolonged benefit from ICPI. TMB ≥20 muts/Mb is a potential biomarker that may identify patients in whom an ICPI without chemo could be considered, even in the setting of lower PD-L1 levels. Prospective validation of these findings could increase access to chemo-sparing regimens for the first-line treatment of advanced NSCLC.

BACKGROUND: Small cell lung cancer (SCLC) has the strongest association with smoking among lung cancers. The characteristics of never smokers with SCLC is not known. RESEARCH QUESTION: Are the clinical characteristics, prognostic factors, survival, genomic alterations, and tumor mutational burdens of SCLC in patients who have never smoked different from those who have smoked? STUDY DESIGN AND METHODS: A retrospective multicenter cohort study of patients with clinician-confirmed SCLC was performed with the use of a longitudinal and nationally representative electronic medical records database. Smoking history was assessed through technology-enabled abstraction and confirmed for never smokers via chart review. Genomic characteristics of never smoker patients with SCLC were examined with the use of a next-generation sequencing-based gene panel and whole exome sequencing. RESULTS: One hundred of 5,632 patients (1.8%) with SCLC were never smokers. Relative to smokers, never smokers were more likely to be female (66.0% vs 52.4%; P = .009) and present with extensive stage (70.0% vs 62.2%; P = .028). Never smokers had a higher proportion of patients in age groups 35 to 49 years (7.0% vs 3.0%; P = .006) and ≥80 years (17.0% vs 8.2%; P = .006). Known risk factors for lung cancer were found in

Digital image analysis (DIA) is becoming central to the quantitative evaluation of tissue biomarkers for discovery, diagnosis and therapeutic selection for the delivery of precision medicine. In this study, automated DIA using a new purpose-built software platform (QuPath) is applied to a cohort of 293 breast cancer patients to score five biomarkers in tissue microarrays (TMAs): ER, PR, HER2, Ki67 and p53. This software is able to measure IHC expression following fully automated tumor recognition in the same immunohistochemical (IHC)-stained tissue section, as part of a rapid workflow to ensure objectivity and accelerate biomarker analysis. The digital scores produced by QuPath were compared with manual scores by a pathologist and shown to have a good level of concordance in all cases (Cohen's κ>0.6), and almost perfect agreement for the clinically relevant biomarkers ER, PR and HER2 (κ>0.86). To assess prognostic value, cutoff thresholds could be applied to both manual and automated scores using the QuPath software, and survival analysis performed for 5-year overall survival. DIA was shown to be capable of replicating the statistically significant stratification of patients achieved using manual scoring across all biomarkers (P

Background: Liquid biopsy offers the ability to non-invasively analyze the genome of a tumor through circulating tumor DNA (ctDNA) to identify targetable and prognostic genomic alterations. Few studies have rigorously analyzed ctDNA results and determined the fidelity with which they recapitulate the genomics of a sequenced tissue sample obtained from the same tumor. The clinical utility study (CUS) for the FoundationACT™ ctDNA assay (Foundation Medicine, Cambridge, MA, USA; NCT02620527) is a multi-center prospective clinical study for multiple solid tumor types to compare genomic profiling of paired tissue and blood samples from the same patient. In this subset of the study, paired specimens from 96 patients with colorectal cancer (CRC) were analyzed with comprehensive genomic profiling (CGP) of the tumor tissue sample (FoundationOne ® ) and blood sample (FoundationACT™). Methods: Both samples underwent CGP using the hybrid capture-based Illumina Hi-Seq technology. Maximum somatic allele frequency (MSAF) was used to estimate the fraction of ctDNA in the sample. The set of genes and targeted regions common to both tumor and liquid were compared for each subject. Results: Among these patients, 61% were male; 74% had clinical stage IV disease, 19% had clinical stage III disease, and 7% had clinical stage II disease. Time between the tissue biopsy and liquid biopsy (range, 0 – 709 days) had a significant impact on the positive percent agreement (PPA) between the two assays. Eighty percent of cases had evidence of ctDNA in the blood (MSAF >0). For all cases with MSAF >0, 171 base substitutions and insertions/deletions (indels) were identified in the tumor, and 79% (PPA) of these identical alterations were also identified in matched ctDNA samples; PPA increased to 87% for cases

e18688 Background: Comprehensive genomic profiling (CGP) is an established diagnostic approach to select patients for TT. As CGP gains wide adoption, an increasing number of patients are found to harbor driver mutations for which no approved TT is available. This is often addressed through use of matched TKI and mAb approved for other mutations or anatomic sites. In this work, we examined the clinical efficacy of off-label TT in R/M NSCLC. Methods: Using a de-identified NSCLC clinico-genomic database (CGDB), we identified 6590 NSCLC patients who underwent Foundation Medicine CGP, of whom 17.8% harbored an actionable genomic alteration (GA) for which an FDA-approved TT was available and 2% (133) whose GA (MET ex-14, uncommon EGFRm, EGFR ex20ins, HER2 amp/mut, RET fusion, BRAF class 2/3) lacked an FDA-approved TT (62 in 1L and 71 in ≥2L ) who received matched off-label TT. ESMO Scale for Clinical Actionability (ESCAT) was used to grade levels of evidence. For patients who progressed on initial chemotherapy (range 2 – 9 lines, median 3), we calculated clinical efficacy using the ratio of real world PFS on targeted therapy (rw-PFS2) to rw-PFS on the last prior line of therapy (rw-PFS1) and used a cut-off of PFS2/PFS1 > 1.3 to determine off-label drug efficacy. Results: Of the 133 patients reviewed, 72 were classified as ESCAT level IB (uncommon EGFRm, MET-ex14), 45 IIB (HER2m/amp, EGFR ex-20ins), 7 IC (RET fusions). PFS varied significantly by mutation and line of therapy (table 1) with uncommon EGFRm+ and MET-ex14 exhibiting best response while EGFR ex20 ins, BRAF class 2/3 and HER2 amp fared significantly worse. 55.8% of the patients (39 of 71) reached a PFS2/PFS1 ratio > 1.3 (two-sided 95% CI, 45.3 % – 68.7 %), ranging from 93% in uncommon EGFRm+ down to 20% in HER2 amp and 44% in ex20ins. Conclusions: We provide real-world evidence to assess off-label TT in NSCLC. Clinical benefit derived from off-label TT is unevenly distributed across various mutations with most survival advantage accruing to specific mutations (MET-ex14 and uncommon EGFRm) at the expense of others (HER2 amp). Survival advantage was highly influenced by two factors: A) the timing of CGP with the earlier recipients of genomic profiling achieving better outcome, B) the identity of the driver mutation, highlighting the role of clinical actionability tier system to define level of evidence supporting such intervention.[Table: see text]

4045 Background: HER2 ( ERBB2) overexpression or amplification (amp) are biomarkers for approved anti-HER2 therapies. ERBB2amp may be a superior predictor of anti-HER2 therapy outcome compared to IHC/ISH, and degree of CN gain may further stratify patients (pts). We investigated the distribution of ERBB2amp in adv GEA and hypothesized that increased CN was associated with better outcome to trastuzumab (T). Methods: Genomic analysis was performed using the Foundation Medicine (FM) tissue database (DB) of 313,896 pts with solid tumors including 12,749 pts with GEA and 34,629 pts with breast cancer (BC) used for comparison. ERBB2amp was defined as predicted CN ≥5 with > 80% of exons amplified. Using the nationwide US-based Flatiron Health-FM clinico-genomic DB linking de-identified EHR-derived clinical data to FM genomic data, pts with ERBB2amp adv GEA (01/2011 - 12/2020) were selected. RW progression (rwP) was obtained via technology-enabled abstraction of EHR. Multivariable Cox proportional hazard models were used for outcome comparisons. Results: ERBB2amp was detected in 15% (1,920/12,749) of GEA samples; median CN 22 (IQR 9-73), and 97% of cases had full gene amp. Median ERBB2 amplicon size was 0.27Mbp (IQR 0.13-0.95). In comparison, ERBB2amp was detected in 9.2% (3,193/34,629) of BC samples; median CN 20 (IQR 9-40), median amplicon size 0.32Mbp (IQR 0.13-1.37). In both cancers, smaller amplicons were associated with higher CN (P < 0.001), excluding amplicons < 0.1Mbp where less than 100% target amp was common. ERBB2amp was additionally seen in 2.7% of other solid tumors, and specifically in 2.3% of NSCLC and 3.1% of CRC. In the RW DB of 183 pts with ERBB2amp adv GEA, chemo + T (45%) and chemo alone (17%) were the most common first therapies after genomic report. In 101 evaluable first-line T treated pts ERBB2 CN was a significant predictor of rwP free survival (rwPFS) as a continuous variable (aHR = 0.74 [95% CI: 0.61 - 0.89], P = 0.002) and a range of cutoffs were similarly predictive. For control, in ERBB2amp pts treated with chemo ERBB2 CN was not predictive of rwPFS (aHR = 0.93, [95% CI: 0.72 – 1.20], P = 0.060). Among T treated pts, co- PIK3CA mutation was more common with lower CN (p = 0.03 by Wilcox test); no significant differences were observed for primary tumor location, age, stage at adv diagnosis, co- KRASmut, EGFRamp or F GF R1/2amp. Conclusions: ERBB2amp was detected in 15% of GEA tissue samples, with significant diversity in ERBB2 CN and amplicon focality, but with a similar CN distribution and amplicon focality seen in ERBB2amp BC. ERBB2 CN was predictive of rwPFS as a continuous variable for pts with GEA treated with T in the RW setting. Further studies exploring the clinical utility of quantitative ERBB2 CN, and extending to ctDNA, particularly in the setting of the evolving anti-HER2 landscape and combination therapies, are warranted.

e17035 Background: Assessment of disease burden and severity influences numerous decisions in cancer care yet is not always straightforward. In mCRPC, most patients (pts) have bone-only metastases, for which disease burden quantification by imaging is challenging. Using commercially available assays for comprehensive genomic profiling (CGP), we hypothesized higher levels of ctDNA would associate with worse rwOS in mCRPC. Methods: Pts with mCRPC who received care within Flatiron Health (FH) network between 1/1/2011-6/30/2020 were assessed. Pts had to have FoundationOne Liquid performed ≤60 days prior to initiation of at least one line of therapy (LOT). Clinical characteristics and treatment history were obtained from deidentified, EHR data and linked to genomic data in the FH-Foundation Medicine Clinico-Genomic Database. Univariable and multivariable Cox proportional hazard models were utilized for rwOS comparisons indexed to LOT start, adjusted for LOT, age, and PSA, hemoglobin, alkaline phosphatase, albumin, and recent ECOG status when available. For one pt with two samples, the earlier one was used. Plasma ctDNA levels were quantified using a composite tumor fraction (cTF) measure based on aneuploidy and variant allele fraction (VAF), dichotomized at a previously reported threshold of 10% (Stover et al, JCO, 2018). Association of cTF with rwOS across common solid tumors was then explored in the FH-FMI CGDB for advanced breast cancer (BC), metastatic colorectal cancer (mCRC) and advanced non-small cell lung cancer (aNSCLC). Results: 78 mCRPC pts met criteria with 36 deaths to date. 15 (19%), 19 (24%), 17 (22%) and 27 (35%) samples were respectively obtained prior to first, second, third, or fourth mCRPC LOT, and median PSA was 85.1 ng/mL (IQR: 23.2 – 177). 69/78 (88%) were from community sites. cTF was ≥ 10% in 46/78 samples (60%) and was significantly associated with median PSA (115 vs. 27 ng/mL, p = 0.006) and elevated alk phos (52.2% vs. 12.5%, p < 0.001). Pts with ≥ 10% cTF had significantly worse rwOS (median 6.2 mo vs. not reached, HR: 9.9, 95% CI: 3.0 – 32.4, p < 0.001), which persisted in the multivariable Cox regression (HR: 9.4, 95% CI: 2.4 – 36.4, p = 0.001, n = 65, 13 missing clinical data). Preliminary results in other cancers, adjusted for LOT number only, were consistent with mCRPC; cTF ≥ 10% was associated with a worse rwOS in mBC (n=245, HR: 1.8 CI: 1.1 – 3.0), mCRC (n=107, HR: 2.1 CI: 1.1 – 4.3) and aNSCLC (n=432, HR: 1.8 CI: 1.3 – 2.5). Conclusions: Pretreatment ctDNA level is a prognostic factor in mCRPC in a real-world setting. With prospective validation, cTF may permit identification of high risk pts requiring more aggressive or investigational therapies. This phenomenon may not be unique to mCRPC and could offer similar insights in other cancer types.

142 Background: Robust biomarkers for personalization of NHT treatment decisions remains an unmet need. Most assessments of candidate biomarkers to predict NHT resistance have been conducted in clinical trials or academic centers, meriting additional validation in diverse community settings. We sought to correlate real-world outcomes on NHT with comprehensive genomic profiling (CGP)-reported alterations, hypothesizing that AR amplification ( ARamp) and deleterious genomic alterations (GAs) in BRCA2, PTEN, RB1, TP53 would correlate with worse outcomes on NHT. Methods: Following a prespecified analysis plan, pts were selected from Flatiron Health (FH)-Foundation Medicine (FMI) clinico-genomic database (CGDB), a nationwide deidentified electronic health record database linked to FMI CGP. Inclusion criteria: mCRPC diagnosis, treatment in FH network and CGP result between 1/1/11-3/30/20 where tissue collected prior to initiation of first line (1L) or second (2L) NHT (within 180 days for ARamp +/- comparison). A priori power analyses were conducted. Adjusted hazard ratios (aHR) from multivariable Cox proportional hazard models were utilized for TTD and OS comparisons from start of NHT including: GA groups, adjusted for age, line number, practice type, and left truncation. Results: Among 1626 evaluable pts, 397 received 1L (n = 287; 72%) or 2L (n = 110; 28%) NHT with majority treated in community setting (n = 297; 75%). Abiraterone (n = 242; 61%) and enzalutamide (n = 145; 39%) were most common NHTs. Incidence: ARamp (15%) and deleterious GA in TP53 (45%), PTEN (28%), RB1 (3%), and BRCA2 (8%). Cohort was strongly powered to assess TP53 & PTEN, moderately for ARamp & BRCA2, weakly for RB1. As hypothesized, ARamp correlated with worse TTD (aHR: 3.37 [1.26-9.0]) and OS (aHR: 4.92 [1.47-16.5]). BRCA2 GA correlated with improved OS (aHR: 0.41 [0.21-0.81]), but no differences in TTD (aHR: 1.25 [0.82-1.9]). RB1 GA had trends for worse OS (aHR: 2.0 [0.93-4.28]) and worse TTD (aHR – 1.41 [0.72-2.8]). TP53 GA had worse OS (aHR: 1.47 [1.1-2.0]), but no difference in TTD (aHR: 1.08 [0.85-1.4]), and PTEN GA did not correlate with TTD (aHR: 0.94 [0.72-1.2]) or OS (aHR: 1.01 [0.74-1.38]). Conclusions: ARamp is associated with worse TTD and OS in mCRPC pts treated with NHT in real-world, mostly community practice, consistent with prior academic center studies and trials data. Surprisingly, BRCA2 GA correlated with improved OS but not TTD. RB1 GA were directionally consistent with prior studies but underpowered. This study supports using CGP to inform decisions for escalation of non-NHT treatment use in conjunction with patient goals and predictive CGP biomarkers for other drugs. Additional biomarkers, multivariable models and, NHT vs taxane chemo predictive assessments will be reported at symposium.

Importance Tumor mutational burden (TMB) is a potential biomarker associated with response to immune checkpoint inhibitor therapies. The prognostic value associated with TMB in the absence of immunotherapy is uncertain. Objective To assess the prevalence of high TMB (TMB-H) and its association with overall survival (OS) among patients not treated with immunotherapy with the same 10 tumor types from the KEYNOTE-158 study. Design, setting, and participants This retrospective cohort study evaluated the prognostic value of TMB-H, assessed by Foundation Medicine (FMI) and defined as at least 10 mutations/megabase (mut/Mb) in the absence of immunotherapy. Data were sourced from the deidentified Flatiron Health-FMI clinicogenomic database collected up to July 31, 2018. Eligible patients were aged 18 years or older with any of the following solid cancer types: anal, biliary, endometrial, cervical, vulvar, small cell lung, thyroid, salivary gland, mesothelioma, or neuroendocrine tumor. Patients with microsatellite instability-high tumors were excluded from primary analysis. For OS analysis, patients were excluded if immunotherapy started on the FMI report date or earlier or if patients died before January 1, 2012, and patients were censored if immunotherapy was started later than the FMI report date. Data were analyzed from November 2018 to February 2019. Main outcomes and measures Overall survival was analyzed using the Kaplan-Meier method and Cox proportional hazards model, adjusting for age, sex, cancer types, practice type, and albumin level. Results Of 2589 eligible patients, 1671 (64.5%) were women, and the mean (SD) age was 63.7 (11.7) years. Median (interquartile range) TMB was 2.6 (1.7-6.1) mut/Mb, and 332 patients (12.8%) had TMB-H (≥10 mut/Mb). Prevalence of TMB-H was highest among patients with small cell lung cancer (40.0%; 95% CI, 34.7%-45.6%) and neuroendocrine tumor (29.3%; 95% CI, 22.8%-36.6%) and lowest was among patients with mesothelioma (1.2%; 95% CI, 0.3%-4.4%) and thyroid cancer (2.7%; 95% CI, 1.2%-5.7%). Adjusted hazard ratio for OS of patients not treated with immunotherapy with TMB-H vs those without TMB-H was 0.94 (95% CI, 0.77-1.13). Comparable results were observed when including patients with high microsatellite instability tumors and calculating OS from first observed antineoplastic treatment date. Conclusions and relevance These findings suggest that prevalence of TMB-H varies widely depending on tumor type and TMB-H does not appear to be a factor associated with OS among patients across these cancer types treated in the absence of immunotherapy.

3060 Background: The first tumor-agnostic, biomarker-based FDA approval in oncology was P in May 2017 for pts with MSI-H or mismatch repair (MMR) deficient tumors. 1 yr overall survival (OS) was >70% for colorectal cancer (CRC) and >60% for non-CRC in P-treated MSI-H clinical trial pts (Le 2019; Marabelle 2019). As tumor-agnostic therapies are a new paradigm, it is important to assess their use and effectiveness in routine clinical practice. We examined characteristics and outcomes of RW pts with MSI-H solid tumors who received P after May 2017. Methods: Pts with MSI-H solid tumors who received P after May 2017 were selected from the Flatiron Health-Foundation Medicine (FH-FMI) clinico-genomic database, a nationwide de-identified EHR-derived database linked to comprehensive genomic profiling (CGP) data. Pts with 2+ visits in the FH network from 01/2011-09/2019 with CGP prior to P use were included. Clinical characteristics were assessed at first P use. Time to treatment discontinuation (TTD) and OS from first P use were estimated with Kaplan-Meier analyses of all pts and the largest tumor types. Results: 33,395 pts had a solid tumor tested for MSI by CGP, of which 557 (1.7%) were MSI-H (median age 68 yrs; 34% male). 129 MSI-H pts across 33 tumor types received first P after May 2017. CRC (N=36) and Endometrial cancer (N=39) were most common. 52 pts (40%) had a concurrent MMR alteration (MLH1, MSH2, MSH6 or PMS2); median TMB was 32.2 mut/mb (IQR 20.9-47.5). Median number of therapies prior to P was 1; median time from CGP to first P use was 3 mos. Table shows OS and TTD. Conclusions: In this RW study, P use was observed across 33 MSI-H tumor types. Median OS exceeded 1 yr across all pts and in CRC, Endometrial, and Other cohorts. 1 yr OS rate was consistent with P trial outcomes. Further study should evaluate whether effectiveness differs across diseases, MSI testing method, or other genomic attributes to improve treatment selection. [Table: see text]

The majority of US adult cancer patients today are diagnosed and treated outside the context of any clinical trial (that is, in the real world). Although these patients are not part of a research study, their clinical data are still recorded. Indeed, data captured in electronic health records form an ever-growing, rich digital repository of longitudinal patient experiences, treatments, and outcomes. Likewise, genomic data from tumor molecular profiling are increasingly guiding oncology care. Linking real-world clinical and genomic data, as well as information from other co-occurring data sets, could create study populations that provide generalizable evidence for precision medicine interventions. However, the infrastructure required to link, ensure quality, and rapidly learn from such composite data is complex. We outline the challenges and describe a novel approach to building a real-world clinico-genomic database of patients with cancer. This work represents a case study in how data collected during routine patient care can inform precision medicine efforts for the population at large. We suggest that health policies can promote innovation by defining appropriate uses of real-world evidence, establishing data standards, and incentivizing data sharing.

Background Little is known about the prognostic effect of TMB-H among patients with less common cancers who did not receive an immunotherapy (IO). Methods The de-identified Flatiron Health-Foundation Medicine (FMI) Clinico-Genomic Database was used to select patients (pts) with any of 10 solid cancers (Table). 109 Pts with confirmed microsatellite instability-high (MSIH) cancers were excluded, of which 101 pts were endometrial cancer. TMB-H was defined as ≥ 10 mutations per megabase (Mut/Mb) with an additional analysis using a cutoff of 13 Mut/Mb. For overall survival (OS) analysis, Pts with IO were excluded if start of IO earlier than or equal to FMI report date (69 pts), or censored if start of IO later than FMI report date (243 pts). OS was analyzed using Kaplan-Meier method and Cox proportional hazard model, adjusting for age, gender, cancer types, practice type and albumin. A non-inferiority test of TMB-H having longer OS than TMB-low (-L) was carried out with a prespecified hazard ratio (HR) of 0.75. Results Of the 2,589 pts (table), average age at diagnosis was 64 years and 65% were female. Median TMB was 2.6 Mut/Mb overall, ranged from 1.7 (Meso, salivary, thyroid) to 8.7 (SCLC) Mut/Mb. Overall 12.8% were TMB-H with the highest in SCLC (40.0%) and lowest in meso (1.2%). The adjusted HR (AHR) of TMB-H vs. -L was 0.94 (95% CI: 0.77-1.13) for OS from FMI report date, which met the prespecified threshold for non-inferiority by rejecting the null hypothesis. The AHR was 0.84 (0.67-1.05) using alternative cutoff of 13 Mut/Mb. Comparable results were observed when including MSI-H pts and calculating OS from 1st observed antineoplastic treatment date. Table: 1877PD . N TMB-H OS (month, 95%CI) HRadjust Padjust n % TMB-H TMB-L Total 2,589 332 12.8 8.4 (7.4; 11.4) 10.5 (9.5; 11.5) 0.94 (0.77; 1.13) 0.491 SCLC 305 122 40.0 6.4 (5.4; 7.5) 7.4 (5.5; 10.5) 1.03 (0.74; 1.44) 0.863 Neuroendocrine 164 48 29.3 10.4 (6.4; NA) 6.4 (4.5; 10.5) 0.83 (0.48; 1.44) 0.506 Cervical 114 17 14.9 NA (6.4; NA) 7.4 (4.4; 11.5) 0.32 (0.08; 1.31) 0.113 Anal 125 17 13.6 7.4 (2.5; NA) 7.5 (5.5; 15.4) 0.84 (0.40; 1.79) 0.659 Vulvar 30 4 13.3 8.5 (0.5; NA) 6.5 (2.5; NA) 1.18 (0.22; 6.29) 0.848 Salivary 169 22 13.0 4.5 (3.5; NA) 15.5 (10.5; 21.5) 1.20 (0.48; 2.99) 0.691 Endometrial 590 66 11.2 11.4 (8.5; 26.5) 13.5 (11.5; 15.4) 1.15 (0.75; 1.75) 0.522 Biliary 706 28 4.0 11.5 (7.4; NA) 8.4 (7.4; 10.4) 0.65 (0.35; 1.19) 0.162 Thyroid 223 6 2.7 10.2 (1.5; NA) 27.5 (21.5; NA) 1.64 (0.39; 6.96) 0.502 Meso 163 2 1.2 NA 12.5 (8.5; 15.5) - 0.997 Conclusions There is a wide range of TMB among these cancers. Non-inferiority testing and HR estimates comparing OS for TMB-H (≥10 Mut/Mb) vs. -L did not support an effect of TMB on OS in the absence of IO for these cancers. Further research is needed to explore whether the prognostic effect of TMB varies by tumor type or threshold. Legal entity responsible for the study Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Funding Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Disclosure D. Backenroth: Shareholder / Stockholder / Stock options, Full / Part-time employment: Flatiron Health Inc. C. Shao: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co. G. Li: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. L. Huang: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co.. S.K. Pruitt: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. E. Castellanos: Full / Part-time employment: Flatiron Health Inc.. G.M. Frampton: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. K.R. Carson: Full / Part-time employment: Flatiron Health Inc.. T. Snow: Full / Part-time employment: Flatiron Health Inc.. G. Singal: Full / Part-time employment: Foundation Medicine. D. Fabrizio: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. B.M. Alexander: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. F.J. Jin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. W. Zhou: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc..

// Qing Wen 1 , Philip D. Dunne 1 , Paul G. O’Reilly 1 , Gerald Li 1 , Anthony J. Bjourson 2 , Darragh G. McArt 1 , Peter W. Hamilton 1, * , Shu-Dong Zhang 1, 2, * 1 Centre for Cancer Research and Cell Biology, Queen’s University Belfast, UK 2 Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, C-TRIC, Londonderry, UK * Joint Senior Author Correspondence to: Qing Wen, email: qwen02@qub.ac.uk Peter W. Hamilton, email: P.Hamilton@qub.ac.uk Keywords: connectivity mapping, differentially expressed genes, colorectal cancer, KRAS mutation, FDA approved drugs Received: May 15, 2016 Accepted: November 30, 2016 Published: December 10, 2016 ABSTRACT Colorectal cancer (CRC) is a life-threatening disease with high prevalence and mortality worldwide. The KRAS oncogene is mutated in approximately 40% of CRCs. While antibody based EGFR inhibitors (cetuximab and panitumumab) represent a major treatment strategy for advanced KRAS wild type (KRAS-WT) CRCs, there still remains no effective therapeutic course for advanced KRAS mutant (KRAS-MT) CRC patients. In this study, we employed a novel and comprehensive approach of gene expression connectivity mapping (GECM) to identify candidate compounds to target KRAS-MT tumors. We first created a combined KRAS-MT gene signature with 248 ranked significant genes using 677 CRC clinical samples. A series of 248 sub-signatures was then created containing an increasing number of the top ranked genes. As an input to GECM analysis, each sub-signature was translated into a statistically significant therapeutic drugs list, which was finally combined to obtain a single list of significant drugs. We identify four antihypertensive angiotensin II receptor blockers (ARBs) within the top 30 significant drugs indicating that these drugs have a mechanism of action that can alter the KRAS-MT CRC oncogenic signaling. A hypergeometric test ( p-value = 6.57 × 10 −6 ) confirmed that ARBs are significantly enriched in our results. These findings support the hypothesis that ARB antihypertensive drugs may directly block KRAS signaling resulting in improvement in patient outcome or, through a reversion to a KRAS wild-type phenotype, improve the response to anti-EGFR treatment. Antihypertensive angiotensin II receptor blockers are therefore worth further investigation as potential therapeutic candidates in this difficult category of advanced colorectal cancers.

Formalin-fixed tissue has been a mainstay of clinical pathology laboratories, but formalin alters many biomolecules, including nucleic acids and proteins. Meanwhile, frozen tissues contain better-preserved biomolecules, but tissue morphology is affected, limiting their diagnostic utility. Molecular fixatives promise to bridge this gap by simultaneously preserving morphology and biomolecules, enabling clinical diagnosis and molecular analyses on the same specimen. While previous reports have broadly evaluated the use of molecular fixative in various human tissues, we present here the first detailed assessment of the applicability of molecular fixative to both routine histopathological diagnosis and molecular analysis of cervical tissues. Ten specimens excised via the Loop Electrosurgical Excision Procedure, which removes conical tissue samples from the cervix, were cut into alternating pieces preserved in either formalin or molecular fixative. Cervical specimens preserved in molecular fixative were easily interpretable, despite featuring more eosinophilic cytoplasm and more recognizable chromatin texture than formalin-fixed specimens. Immunohistochemical staining patterns of p16 and Ki-67 were similar between fixatives, although Ki-67 staining was stronger in the molecular fixative specimens. The RNA of molecular fixative specimens from seven cases representing various dysplasia grades was assessed for utility in expression microarray analysis. Cluster analysis and scatter plots of duplicate samples suggest that data of sufficient quality can be obtained from as little as 50 ng of RNA from molecular fixative samples. Taken together, our results show that molecular fixative may be a more versatile substitute for formalin, simultaneously preserving tissue morphology for clinical diagnosis and biomolecules for immunohistochemistry and gene expression analysis.

2630 Background: PD-L1 expression and TMB, as a proxy for neoantigen burden, have been correlated with response to IO in advanced NSCLC (aNSCLC) clinical trials, but their combined utility is unclear. We assessed TMB and PD-L1 as predictors of response in aNSCLC patients (pts) after IO monotherapy in a real-world setting. Methods: Pts had a diagnosis of aNSCLC, comprehensive genomic profiling of 186-315 genes/1.1 megabase (Mb), PD-L1 testing of pre-IO specimens, and were treated in the Flatiron Health network (1/2011 - 6/2018). Clinical characteristics and real-world tumor response (rwTR) were obtained via technology-enabled abstraction of clinician notes and radiology/pathology reports, and linked to genomic data in the Flatiron Health-Foundation Medicine Clinico-Genomic Database. A general additive model examined the predictive value of TMB (as continuous measure) and PD-L1 level on rwTR. A reduced PD-L1-only model was compared to the full model using Akaike Information Criterion (AIC). rwTR predictions at representative TMB and PD-L1 levels were calculated. Results: Of 426 pts, PD-L1 expression was high (≥50%) in 140, low (1-49%) in 123, and negative (

Importance Data sets linking comprehensive genomic profiling (CGP) to clinical outcomes may accelerate precision medicine. Objective To assess whether a database that combines EHR-derived clinical data with CGP can identify and extend associations in non–small cell lung cancer (NSCLC). Design, Setting, and Participants Clinical data from EHRs were linked with CGP results for 28 998 patients from 275 US oncology practices. Among 4064 patients with NSCLC, exploratory associations between tumor genomics and patient characteristics with clinical outcomes were conducted, with data obtained between January 1, 2011, and January 1, 2018. Exposures Tumor CGP, including presence of a driver alteration (a pathogenic or likely pathogenic alteration in a gene shown to drive tumor growth); tumor mutation burden (TMB), defined as the number of mutations per megabase; and clinical characteristics gathered from EHRs. Main Outcomes and Measures Overall survival (OS), time receiving therapy, maximal therapy response (as documented by the treating physician in the EHR), and clinical benefit rate (fraction of patients with stable disease, partial response, or complete response) to therapy. Results Among 4064 patients with NSCLC (median age, 66.0 years; 51.9% female), 3183 (78.3%) had a history of smoking, 3153 (77.6%) had nonsquamous cancer, and 871 (21.4%) had an alteration inEGFR,ALK, orROS1(701 [17.2%] withEGFR, 128 [3.1%] withALK, and 42 [1.0%] withROS1 alterations). There were 1946 deaths in 7 years. For patients with a driver alteration, improved OS was observed among those treated with (n = 575) vs not treated with (n = 560) targeted therapies (median, 18.6 months [95% CI, 15.2-21.7] vs 11.4 months [95% CI, 9.7-12.5] from advanced diagnosis;P Conclusions and Relevance Among patients with NSCLC included in a longitudinal database of clinical data linked to CGP results from routine care, exploratory analyses replicated previously described associations between clinical and genomic characteristics, between driver mutations and response to targeted therapy, and between TMB and response to immunotherapy. These findings demonstrate the feasibility of creating a clinicogenomic database derived from routine clinical experience and provide support for further research and discovery evaluating this approach in oncology.

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.