Real-World Clinical Performance of a DNA-Based Comprehensive Genomic Profiling Assay for Detecting Targetable Fusions in Nonsquamous NSCLC.

BACKGROUND: Genomic fusions are potent oncogenic drivers across cancer types and many are targetable. We demonstrate the clinical performance of DNA-based comprehensive genomic profiling (CGP) for detecting targetable fusions. MATERIALS AND METHODS: We analyzed targetable fusion genes in >450 000 tissue specimens profiled using DNA CGP (FoundationOne CDx, FoundationOne). Using a de-identified nationwide (US-based) non-small cell lung cancer (NSCLC) clinico-genomic database, we assessed outcomes in patients with nonsquamous NSCLC (NonSqNSCLC) who received matched therapy based on a fusion identified using DNA CGP. Lastly, we modeled the added value of RNA CGP for fusion detection in NonSqNSCLC. RESULTS: We observed a broad diversity of fusion partners detected with DNA CGP in conjunction with targetable fusion genes (ALK, BRAF, FGFR2, FGFR3, NTRK1/2/3, RET, and ROS1). In NonSqNSCLC with oncogenic ALK, NTRK, RET, and ROS1 fusions detected by DNA CGP, patients treated with a matched tyrosine kinase inhibitor had better real-world progression-free survival than those receiving alternative treatment regimens and benefit was observed regardless of the results of orthogonal fusion testing. An estimated 1.3% of patients with NonSqNSCLC were predicted to have an oncogenic driver fusion identified by RNA, but not DNA CGP, according to a model that accounts for multiple real-world factors. CONCLUSION: A well-designed DNA CGP assay is capable of robust fusion detection and these fusion calls are reliable for informing clinical decision-making. While DNA CGP detects most driver fusions, the clinical impact of fusion detection is substantial for individual patients and exhaustive efforts, inclusive of additional RNA-based testing, should be considered when an oncogenic driver is not clearly identified.

Comprehensive genomic profiling of ESR1, PIK3CA, AKT1, and PTEN in HR(+)HER2(-) metastatic breast cancer: prevalence along treatment course and predictive value for endocrine therapy resistance in real-world practice.

BACKGROUND: The treatment landscape for HR(+)HER2(-) metastatic breast cancer (MBC) is evolving for patients with ESR1 mutations (mut) and PI3K/AKT pathway genomic alterations (GA). We sought to inform clinical utility for comprehensive genomic profiling (CGP) using tissue (TBx) and liquid biopsies (LBx) in HR(+)HER2(-) MBC. METHODS: Records from a de-identified breast cancer clinicogenomic database for patients who underwent TBx/LBx testing at Foundation Medicine during routine clinical care at ~ 280 US cancer clinics between 01/2011 and 09/2023 were assessed. GA prevalence [ESR1mut, PIK3CAmut, AKT1mut, PTENmut, and PTEN homozygous copy loss (PTENloss)] were calculated in TBx and LBx [stratified by ctDNA tumor fraction (TF)] during the first three lines of therapy. Real-world progression-free survival (rwPFS) and overall survival (rwOS) were compared between groups by Cox models adjusted for prognostic factors. RESULTS: ~ 60% of cases harbored 1 + GA in 1st-line TBx (1266/2154) or LBx TF ≥ 1% (80/126) and 26.5% (43/162) in LBx TF < 1%. ESR1mut was found in 8.1% TBx, 17.5% LBx TF ≥ 1%, and 4.9% LBx TF < 1% in 1st line, increasing to 59% in 3rd line (LBx TF ≥ 1%). PTENloss was detected at higher rates in TBx (4.3%) than LBx (1% in TF ≥ 1%). Patients receiving 1st-line aromatase inhibitor + CDK4/6 inhibitor (n = 573) with ESR1mut had less favorable rwPFS and rwOS versus ESR1 wild-type; no differences were observed for fulvestrant + CDK4/6 inhibitor (n = 348). CONCLUSION: Our study suggests obtaining TBx for CGP at time of de novo/recurrent diagnosis, followed by LBx for detecting acquired GA in 2nd + lines. Reflex TBx should be considered when ctDNA TF < 1%.

Mismatch repair deficiency, next-generation sequencing-based microsatellite instability, and tumor mutational burden as predictive biomarkers for immune checkpoint inhibitor effectiveness in frontline treatment of advanced stage endometrial cancer.

OBJECTIVE: Molecular profiling is developing to inform treatment in endometrial cancer. Using real world evidence, we sought to evaluate frontline immune checkpoint inhibitor vs chemotherapy effectiveness in advanced endometrial cancer, stratified by Tumor Mutational Burden (TMB) ≥10 mut/MB and microsatellite instability (MSI). METHODS: Patients with advanced endometrial cancer in the US-based de-identified Flatiron Health-Foundation Medicine Clinico-Genomic Database were included. Data originated from patients treated between January 2011- March 2022 at 280 US clinics. Next-generation sequencing assays were performed via FoundationOne or FoundationOneCDx. Longitudinal clinical data were derived from electronic health records. Immune checkpoint inhibitor treatment included pembrolizumab, dostarlimab, and nivolumab monotherapies. Time to next treatment, time to treatment discontinuation, and overall survival were assessed with the log-rank test and Cox proportional hazard models with adjusted hazard ratios (aHR) for known prognostic factors. We used the Likelihood ratio test to compare biomarker performance. RESULTS: A total of 343 patients received chemotherapy and 28 received immune checkpoint inhibitor monotherapy as frontline treatment. Patients who received monotherapy were more likely to be stage III at diagnosis (immune checkpoint inhibitor: 54.6% vs chemotherapy: 15.0%; p<0.001) and more likely to test MSI-high via next-generation sequencing (immune checkpoint inhibitor: 53.6% vs chemotherapy: 19.2%; p<0.001). In MSI-high cancers, single-agent immune checkpoint inhibitor had a more favorable time to next treatment (aHR: 0.18, p=0.001) and overall survival (aHR 0.29, p=0.045). Additional analyses on 70 unique tumor specimens revealed mismatch repair deficiency (dMMR) via immunohistochemistry and MSI-high via next-generation sequencing concordance (91%), with nominal improvement of MSI over dMMR to predict time to treatment discontinuation (p=0.030), time to next treatment (p=0.032), and overall survival (p=0.22). MSI status was concordant with tumor mutational burden ≥10 in 94.3% of cases. CONCLUSION: Immune checkpoint inhibitors may have improved efficacy over chemotherapy in frontline treatment for advanced endometrial cancer defined by MSI-high using next-generation sequencing as a nominally better predictor of outcomes than dMMR with immunohistochemistry. This provides the biologic rationale of active phase III trials.

Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned.

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.

Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database.

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 in EGFR, ALK, or ROS1 (701 [17.2%] with EGFR, 128 [3.1%] with ALK, and 42 [1.0%] with ROS1 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 < .001). TMB (in mutations/Mb) was significantly higher among smokers vs nonsmokers (8.7 [IQR, 4.4-14.8] vs 2.6 [IQR, 1.7-5.2]; P < .001) and significantly lower among patients with vs without an alteration in EGFR (3.5 [IQR, 1.76-6.1] vs 7.8 [IQR, 3.5-13.9]; P < .001), ALK (2.1 [IQR, 0.9-4.0] vs 7.0 [IQR, 3.5-13.0]; P < .001), RET (4.6 [IQR, 1.7-8.7] vs 7.0 [IQR, 2.6-13.0]; P = .004), or ROS1 (4.0 [IQR, 1.2-9.6] vs 7.0 [IQR, 2.6-13.0]; P = .03). In patients treated with anti-PD-1/PD-L1 therapies (n = 1290, 31.7%), TMB of 20 or more was significantly associated with improved OS from therapy initiation (16.8 months [95% CI, 11.6-24.9] vs 8.5 months [95% CI, 7.6-9.7]; P < .001), longer time receiving therapy (7.8 months [95% CI, 5.5-11.1] vs 3.3 months [95% CI, 2.8-3.7]; P < .001), and increased clinical benefit rate (80.7% vs 56.7%; P < .001) vs TMB less than 20. 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.

Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer.

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<0.01, log-rank test). Furthermore, the image analysis scores were shown to consistently lead to statistical significance across a wide range of potential cutoff thresholds, indicating the robustness of the method, and identify sub-populations of cases exhibiting different expression patterns within the p53 and Ki67 data sets that warrant further investigation. These findings have demonstrated QuPath's suitability for fast, reproducible, high-throughput TMA analysis across a range of important biomarkers. This was achieved using our tumor recognition algorithms for IHC-stained sections, trained interactively without the need for any additional tumor recognition markers, for example, cytokeratin, to obtain greater insight into the relationship between biomarker expression and clinical outcome applicable to a range of cancer types.

Molecular fixative enables expression microarray analysis of microdissected clinical cervical specimens.

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 50ng 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.

Predictive Impact of Tumor Mutational Burden on Real-World Outcomes of First-Line Immune Checkpoint Inhibition in Metastatic Melanoma.

PURPOSE: The choice of threshold and reliability of high tumor mutational burden (TMB) to predict outcomes and guide treatment choice for patients with metastatic melanoma receiving first-line immune checkpoint inhibitor (ICI) therapy in the real world is not well known. METHODS: Using a deidentified nationwide (US-based) melanoma clinicogenomic database, we identified a real-world cohort of patients with metastatic melanoma (N = 497) who received first-line monotherapy anti-PD-1 (n = 240) or dual anti-PD-1 and anti-CTLA-4 ICI (n = 257) and had a tissue-based comprehensive genomic profiling test TMB score. RESULTS: TMB-high (TMB-H; ≥10 mutations per megabase [muts/Mb], n = 352, 71%) was independently predictive of superior real-world progression-free survival and overall survival versus TMB-low (<10 mut/Mb, n = 145, 29%) in both mono ICI (hazard ratio [HR], 0.45 [95% CI, 0.32 to 0.63]; P < .001; HR, 0.61 [95% CI, 0.41 to 0.90]; P = .01, respectively) and dual ICI (HR, 0.67 [95% CI, 0.49 to 0.90]; P = .009; HR, 0.61 [95% CI, 0.42 to 0.88]; P = .007, respectively) patients. Dual ICI offered no significant advantage in BRAFwt patients and unexpectedly demonstrated greatest benefit in the TMB 10-19 mut/Mb group, identifying a TMB-very high (≥20 mut/Mb, n = 247, 50%) BRAFmut patient subgroup for whom mono ICI may be preferable. CONCLUSION: TMB-H predicts superior outcomes on ICI while coassessment of BRAF status and TMB may inform first-line regimen choice.

Clinical and Genomic Factors Associated with Greater Tumor Mutational Burden in Prostate Cancer.

Tumor mutational burden (TMB) is a biomarker that predicts response to immune checkpoint inhibitor therapy. We currently lack a comprehensive understanding of how genomic and clinical factors correlate with TMB. We used a clinicogenomic database to assess independent predictors of TMB levels. The study included 2740 prostate cancer specimens from prostate gland (51.6%), lymph nodes (14.6%), and bone (10.4%). Androgen deprivation therapy use beyond 24 mo was weakly associated with high TMB (fold-change estimate [FCE] 1.14, 95% confidence interval [CI] 1.03-1.26; p = 0.009). In comparison to the prostate gland, metastases in the bladder (FCE 1.20, 95% CI 1.02-1.42; p = 0.029), liver (FCE 1.26, 95% CI 1.10-1.43; p < 0.001), and other locations (FCE 1.26, 95% CI 1.11-1.43; p < 0.001) were associated with high TMB. Microsatellite instability high (FCE 8.46, 95% CI 6.42-11.15; p < 0.001) and intermediate (FCE 1.77, 95% CI 1.46-2.14; p < 0.001) status were associated with greater TMB. Altered genes associated with greater TMB included MLH1 (FCE 1.81; p = 0.004), MSH2 (FCE 1.87; p < 0.001), MSH6 (FCE 1.92; p < 0.001), BRCA2 (FCE 1.69; p < 0.001), CDK12 (FCE 1.40; p < 0.001), MRE11 (FCE 2.28; p = 0.016), and PALB2 (FCE 2.08; p < 0.001). Our study demonstrates that TMB is relatively stable over lines of therapies and can be used to guide treatment at diagnosis or in later lines for patients with metastatic prostate cancer. Patient summary: The number of genetic mutations in a tumor (tumor mutational burden, TMB) may help in predicting a patient's response to immunotherapy in advanced prostate cancer. We evaluated clinical and genetic factors that may affect TMB. We found that metastases in the bladder and liver are more likely to have high TMB than the primary tumor. Some individual genes are associated with high TMB. No prior treatment type was strongly associated with TMB, suggesting that TMB can be used to guide treatment at any time point.These data were presented at the American Society of Clinical Oncology 2023 Genitourinary Cancers Symposium.

Tumor Mutational Burden in Real-World Patients With Pancreatic Cancer: Genomic Alterations and Predictive Value for Immune Checkpoint Inhibitor Effectiveness.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) is largely considered a nonimmunogenic malignancy; however, approximately 1%, of patients may have tumors with deficient mismatch repair, high microsatellite instability, or high tumor mutational burden (TMB ≥10 mutations/Mb), which may be predictive of response to immune checkpoint inhibitor (ICI) therapy. We sought to analyze outcomes of patients with high-TMB and pathogenic genomic alterations observed in this population. METHODS: This study included patients with PDAC who underwent comprehensive genomic profiling (CGP) at Foundation Medicine (Cambridge, MA). Clinical data were obtained from a US-wide real-world clinicogenomic pancreatic database. We report genomic alterations in those with high and low TMB, and compare outcomes on the basis of receipt of single-agent ICI or therapy regimens not containing ICI. RESULTS: We evaluated 21,932 patients with PDAC who had tissue CGP data available, including 21,639 (98.7%) with low-TMB and 293 (1.3%) with high-TMB. Among patients with high-TMB, a greater number of alterations were observed in BRCA2, BRAF, PALB2, and genes of the mismatch repair pathway, whereas fewer alterations were observed in KRAS. Among patients who received an ICI (n = 51), those with high-TMB had more favorable median overall survival when compared with the low-TMB subset (25.7 v 5.2 months; hazard ratio, 0.32; 95% CI, 0.11 to 0.91; P = .034). CONCLUSION: Longer survival was observed in patients with high-TMB receiving ICI compared with those with low-TMB. This supports the role of high-TMB as a predictive biomarker for efficacy of ICI therapy in PDAC. Additionally, we report higher rates of BRAF and BRCA2 mutations and lower rates of KRAS mutation among patients with PDAC and high-TMB, which to our knowledge, is a novel finding.

Quantifying the Value of Multigene Testing in Resected Early Stage Lung Adenocarcinoma.

INTRODUCTION: Tyrosine kinase inhibitors and immune checkpoint inhibitors (ICIs), each requiring testing for precision biomarkers, have recently been approved in the adjuvant setting. We assessed the potential value of multigene testing in early lung adenocarcinoma (LUAD). METHODS: Using a real-world clinicogenomic 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 programmed death-ligand 1-positive (PD-L1+) LUAD and an ALK, ROS1 or RET driver. RESULTS: The CGP was performed on a specimen collected before advanced disease in 20% (1320 of 6697) of cases and ordered before advanced diagnosis for 12.6% (847 of 6697) 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 before versus after recurrence had less time between recurrence and the start of any first-line treatment (median 3.6 versus 6 wk, p < 0.001). Through avoidance of ICI in programmed death-ligand 1-positive early LUAD with an ALK, ROS1 or RET driver, we estimated that the universal CGP could reduce expected costs by $1597.23 per patient relative to EGFR single-gene testing. CONCLUSIONS: The 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.

Durable responders in advanced NSCLC with elevated TMB and treated with 1L immune checkpoint inhibitor: a real-world outcomes analysis.

BACKGROUND: For 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 METHODS: The 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). RESULTS: Of 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 (<10 muts/Mb), high TMB (10-19 muts/Mb), and very high TMB (≥20 muts/Mb) receiving ICPI alone, we observed a stepwise increase in median rwPFS (real world-progression free survival) (6.5, 7.5, 17.2 months) and rwOS (real world-overall survival) (10.1, 11.8, 26.9 months) as TMB increased. In the low PD-L1 (TS <50%) cohort, TMB <20 muts/Mb showed a more favorable rwPFS (HR: 0.56 (95% CI: 0.40 to 0.79)) and rwOS (HR 0.74 (95% CI: 0.58 to 0.96)) on chemoICPI when compared with ICPI alone while the point estimate in rwPFS favored monoICPI in the TMB ≥20 muts/Mb cohort, the CI is wide and does not reach statistical significance (HR: 1.68 (95% CI: 0.52 to 5.48)). CONCLUSION: This 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.

Comparative Effectiveness of Immune Checkpoint Inhibitors vs Chemotherapy in Patients With Metastatic Colorectal Cancer With Measures of Microsatellite Instability, Mismatch Repair, or Tumor Mutational Burden.

Importance: The 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. Objective: To 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 Participants: This 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. Exposures: ICI therapy or chemotherapy assigned at physician discretion without randomization. Main Outcomes and Measures: The 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. Results: A 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 < .001), PFS (median, 24.87 months [IQR, 19.10 months to NR] vs 5.65 months [IQR, 4.70-8.34 months]; AHR, 0.31; 95% CI, 0.18-0.52; P < .001), and OS (median, NR vs 24.1 months [IQR, 13.90 months to NR]; HR, 0.45; 95% CI, 0.23-0.88; 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 Relevance: In 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.

Genomic Profiles and Clinical Outcomes of Penile Squamous Cell Carcinoma With Elevated Tumor Mutational Burden.

Importance: Tumor mutational burden (TMB) is a putative biomarker of efficacy for immune checkpoint inhibitor (ICI) therapies of solid tumors, but not specifically for penile squamous cell carcinoma (PSCC). Objective: To characterize biomarker features and ICI therapy outcomes associated with high TMB in PSCC in the routine clinical practice setting. Design, Setting, and Participants: In this cohort study, 397 PSCC cases were analyzed to identify genomic alterations in more than 300 cancer-associated genes and genomic signatures, including TMB, using a hybrid capture-based comprehensive genomic profiling assay. Tumor mutational burden was categorized as low (<10 mutations per megabase [mut/Mb]), high (10-19 mut/Mb), or very high (≥20 mut/Mb). Germline status of genetic alterations was predicted using a validated somatic-germline computational method. Clinical outcomes of patients with metastatic PSCC receiving first-line ICI were abstracted using the deidentified nationwide Clinico-Genomic Database (CGDB) from January 1, 2011, through December 31, 2022. Exposure: Comprehensive genomic profiling was performed using FoundationOne and FoundationOne CDx assays from Foundation Medicine Inc. Main outcomes and measures: The spectrum of genetic alterations by TMB level in PSCC, the percentage of germline genetic alterations, and the outcome (overall survival with routine clinical treatment) by TMB of chemotherapy-naive patients with PSCC who received ICI treatment up front were assessed in this descriptive study. Results: Among 397 patients (median [IQR] age, 65 [54-73] years; 266 [67.0%] of European, 83 [20.9%] of admixed American, and 34 [8.5%] of African or other genomic ancestry), the median (IQR) age (eg, 65 [53-73] years for low TMB vs 68 [61-78] years for TMB ≥10 mut/Mb) and genomic ancestry distribution (eg, European 228 of 339 [67.3%] for low TMB vs 38 of 58 [65.5%] for TMB ≥10 mut/Mb) were similar between TMB subgroups. There were 339 PSCC cases (85.4%) with low TMB, 40 cases (10.1%) with high TMB, and 18 cases (4.5%) with very high TMB. Comparisons of TMB of 10 mut/Mb or higher vs low TMB showed an enrichment of genetic alterations in PIK3CA (48.3% vs 18.3%; P < .001) and KMT2D (29.3% vs 7.7%; P < .001) and less frequent genetic alterations in CDKN2A (25.9% vs 45.7%; P = .05). Most genetic alterations did not co-occur. Human papillomavirus identification was more frequent as TMB increased: 28.3% for low TMB, 50.0% for high, and 72.2% for very high. In total, 95 of 1377 genetic alterations (6.9%) were germline. Of 10 patients identified from the CGDB receiving frontline ICIs, median (IQR) follow-up was 9.9 months. Four patients had overall survival with clinical treatment of more than 12 months, including 2 of 3 patients with TMB of 10 mut/Mb or higher. Conclusions and Relevance: In this cohort study of advanced metastatic PSCC based on TMB levels, significant differences were observed for biomarkers in nearly 15% of patients with a TMB of 10 mut/Mb or higher. Germline testing and ICI-based therapy should be integrated into the management of selected PSCC cases.

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

PURPOSE: Intensification of androgen deprivation therapy (ADT) with either docetaxel or androgen receptor axis-targeted therapies (ARAT) are the current standard of care for patients with metastatic castration-sensitive prostate cancer (mCSPC). However, biomarkers guiding treatment selection are lacking. We hypothesized that ADT intensification with ARAT, but not with docetaxel, would be associated with improved outcomes in patients with de novo (dn)-mCSPC harboring SPOP mutations. EXPERIMENTAL DESIGN: Patient-level data from a deidentified nationwide (U.S.-based) prostate cancer clinico-genomic database between January 2011 and December 2021 were extracted. Eligibility criteria: diagnosis of metastatic disease within 30 days of original prostate cancer diagnosis, genomic profiling of a tissue biopsy collected within 90 days of original diagnosis, and initiation of ARAT or docetaxel within 120 days of initial diagnosis. The log-rank test and Cox proportional hazards models were used to compare time to castration-resistant prostate cancer (TTCRPC) and overall survival (OS) for patients with and without SPOP mutations undergoing ADT intensification with ARAT or docetaxel. RESULTS: In the ARAT cohort, presence of SPOP mutation compared with wild-type was associated with more favorable TTCRPC [not reached (NR) vs. 16.7 months; adjusted HR (aHR), 0.20; 95% confidence interval (CI), 0.06-0.63; P = 0.006] and OS (NR vs. 27.2 months; aHR, 0.19; 95% CI, 0.05-0.79; P = 0.022). In contrast, SPOP mutation status was not associated with TTCRPC or OS in docetaxel-treated cohort. CONCLUSIONS: In real-world settings, SPOP mutations were associated with improved outcomes to ADT plus ARAT (but not ADT plus docetaxel) in patients with dn-mCSPC. This may serve as a predictive biomarker to guide treatment selection for patients with mCSPC.

Complementary Roles for Tissue- and Blood-Based Comprehensive Genomic Profiling for Detection of Actionable Driver Alterations in Advanced NSCLC.

Introduction: Whereas tumor biopsy is the reference standard for genomic profiling of advanced NSCLC, there are now multiple assays approved by the Food and Drug Administration for liquid biopsy testing of circulating tumor DNA. Here, we study the incremental value that liquid biopsy comprehensive genomic profiling (CGP) adds to tissue molecular testing. Methods: Patients with metastatic NSCLC were enrolled in a prospective diagnostic study to receive circulating tumor DNA CGP; tissue CGP was optional in addition to their standard tissue testing. Focusing on nine genes listed per the National Comprehensive Cancer Network (NCCN) guidelines, liquid CGP was compared with available tissue testing results across three subcohorts: tissue CGP, standard-of-care testing of up to five biomarkers, or no tissue testing. Results: A total of 515 patients with advanced nonsquamous NSCLC received liquid CGP. Among 131 with tissue CGP results, NCCN biomarkers were detected in 86 (66%) with tissue CGP and 56 (43%) with liquid CGP (p < 0.001). Adding liquid CGP to tissue CGP detected no additional patients with NCCN biomarkers, whereas tissue CGP detected NCCN biomarkers in 30 patients (23%) missed by liquid CGP. Studying 264 patients receiving tissue testing of up to five genes, 102 (39%) had NCCN biomarkers detected in tissue, with an additional 48 (18%) detected using liquid CGP, including 18 with RET, MET, or ERBB2 drivers not studied in tissue. Conclusions: For the detection of patients with advanced nonsquamous NSCLC harboring 9 NCCN biomarkers, liquid CGP increases detection in patients with limited tissue results, but does not increase detection in patients with tissue CGP results available. In contrast, tissue CGP can add meaningfully to liquid CGP for detection of NCCN biomarkers and should be considered as a follow-up when an oncogenic driver is not identified by liquid biopsy.

Genomic Biomarkers and Genome-Wide Loss-of-Heterozygosity Scores in Metastatic Prostate Cancer Following Progression on Androgen-Targeting Therapies.

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.

Pan-cancer analysis of CD274 (PD-L1) mutations in 314,631 patient samples and subset correlation with PD-L1 protein expression.

BACKGROUND: The effects of non-amplification short variant (SV) mutations in CD274 (programmed death-ligand 1 (PD-L1)) on PD-L1 protein expression and immune checkpoint inhibitors (ICPIs) therapy are unknown. Here, we present a retrospective analysis of CD274 mutations detected by comprehensive genomic profiling (CGP) and correlate these results with tumor-cell PD-L1 immunohistochemistry (IHC)-based expression assessment to better understand the relationship between mutations and protein expression of PD-L1. METHODS: CGP was performed on hybridization-captured, adaptor ligation-based libraries using DNA and/or RNA extracted from 314,631 tumor samples that were sequenced for up to 406 cancer-related genes and select gene rearrangements. PD-L1 IHC was performed on a subset of cases (n=58,341) using the DAKO 22C3 PD-L1 IHC assay and scored with the tumor proportion score (TPS). RESULTS: Overall, the prevalence of CD274 SV mutations was low (0.3%, 1081/314,631) with 577 unique variants. The most common CD274 SV mutations were R260H (n=51), R260C (n=18), R125Q (n=12), C272fs*13 (n=11), R86W (n=10), and R113H (n=10). The prevalence of CD274 mutations varied depending on tumor type with diffuse large B-cell lymphoma (1.9%, 19/997), cutaneous squamous cell carcinoma (1.6%, 14/868), endometrial adenocarcinoma (1.0%, 36/3740), unknown primary melanoma (0.9%, 33/3679), and cutaneous melanoma (0.8%, 32/3874) having the highest frequency of mutations. Of the R260H cases concurrently tested with PD-L1 IHC, most (81.8%, 9/11) had no PD-L1 expression, which contrasts to the five E237K cases where most (80%, 4/5) had PD-L1 expression. In addition, we saw a significantly lower level of PD-L1 expression in samples with a clonal truncating variant (nonsense or frameshift indel) when compared with samples with a subclonal truncating variants (mean: TPS=1 vs TPS=38; p<0.001), and also in clonal versus subclonal missense mutations (mean: TPS=11 vs TPS=22, respectively; p=0.049) CONCLUSIONS: We defined the landscape of CD274 mutations in a large cohort of tumor types that can be used as a reference for examining CD274 mutations as potential resistance biomarkers for ICPI. Furthermore, we presented novel data on the correlation of CD274 mutations and PD-L1 protein expression, providing important new information on the potential functionality of these mutations and can serve as a basis for future research.

Somatic HLA Class I Loss Is a Widespread Mechanism of Immune Evasion Which Refines the Use of Tumor Mutational Burden as a Biomarker of Checkpoint Inhibitor Response.

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.