Faculty Bibliography

4-1BB has been considered a promising target in cancer immunotherapy for decades. Nevertheless, early 4-1BB-targeted agent demonstrated significant liver immuno-toxicity. A new wave of 4-1BB-based therapy is being developed to circumvent hepatotoxicity with bispecific molecule that directs 4-1BB agonism to the tumor microenvironment by targeting tumor-associated immune checkpoint molecule, PD-L1.

BACKGROUND:Tumor infiltrating lymphocytes (TILs) reflect adaptive antitumor immune responses in cancer and are generally associated with favorable prognosis. However, the relationships between TILs subsets and their spatial arrangement with clinical benefit from immune checkpoint inhibitors (ICI) in non-small cell lung cancer (NSCLC) remains less explored. METHODS:B cells, and T cell exhaustion markers, programmed cell death protein-1 (PD-1),lymphocyte-activation gene 3 (LAG-3) and T cell immunoglobulin mucin-3 (TIM-3) with outcomes in a multi-institutional cohort of baseline tumor samples from 179 patients with NSCLC treated with ICI. The analysis of full-face tumor biopsies including numerous fields of view allowed a detailed spatial analysis and assessment of tumor immune heterogeneity using a multiparametric quadratic entropy metric (Rao's Q Index (RQI)). RESULTS:cytotoxic T cells was significantly associated with longer survival, and this effect was more prominent in programmed death ligand-1 (PD-L1) positive cases. The role of baseline T cell infiltration to stratify PD-L1 expressing cases was confirmed measuring the T cell receptor-burden in an independent NSCLC cohort studied with whole-exome DNA sequencing. High levels of LAG-3 on T cells or elevated RQI heterogeneity index were associated with worse survival in the cohort. CONCLUSION/CONCLUSIONS:Baseline T cell density and T cell exhaustion marker expression can stratify outcomes in PD-L1 positive patients with NSCLC treated with ICI. Spatial immune heterogeneity can be measured using the RQI and is associated with survival in NSCLC.

Objectives/UNASSIGNED:Immune checkpoint inhibitors (ICIs) of programmed cell death 1/programmed cell death ligand 1 (PD-1/PD-L1) have been rapidly adopted in US clinical practice for first-line therapy of metastatic non-small cell lung cancer (NSCLC) since regulatory approval in October 2016, and a better understanding is needed of long-term outcomes of ICI therapy administered in real-world settings outside of clinical trials. Our aim was to describe long-term outcomes of first-line pembrolizumab monotherapy at US oncology practices for patients with metastatic NSCLC, PD-L1 expression ≥50%, and good performance status. Methods/UNASSIGNED:genomic aberration, and ECOG performance status 0-1 who initiated first-line pembrolizumab monotherapy from 1-November-2016 to 31-March-2020 (EHR cohort, with data cutoff 31-March-2021) or from 1-December-2016 to 30-November-2017 (spotlight cohort, with data cutoff 31-August-2020). Kaplan-Meier analysis was used to determine overall survival (OS; both cohorts) and, for the spotlight cohort, real-world progression-free survival (rwPFS) and real-world tumor response (rwTR). Results/UNASSIGNED:The EHR cohort included 566 patients (298 [53%] men); the spotlight cohort included 228 (105 [46%] men); median age in both cohorts was 71. Median follow-up from pembrolizumab initiation to data cutoff was 35.1 months (range, 12.0-52.7) and 38.4 months (range, 33.1-44.9) in EHR and spotlight cohorts, respectively. Median OS was 19.6 months (95% CI, 16.6-24.3) and 21.1 months (95% CI, 16.2-28.9), respectively; 3-year OS rates were 36.2% and 38.2% in EHR and spotlight cohorts, respectively. In the spotlight cohort, median rwPFS was 7.3 months (95% CI, 5.7-9.2); 88 patients (38.6%; 95% CI, 32.2-45.2) experienced rwTR of complete or partial response. For 151/228 patients (66%) who discontinued pembrolizumab, the most common reasons were disease progression (70 [46%]) and therapy-related adverse effects (35 [23%]). Conclusions/UNASSIGNED:Real-world outcomes remain consistent with outcomes observed in clinical trials, supporting long-term benefits of first-line pembrolizumab monotherapy for patients with metastatic NSCLC, PD-L1 expression ≥50%, and good performance status.

PURPOSE/OBJECTIVE:Patients with KRAS-mutant non-small cell lung cancer (NSCLC) with brain metastases (BM) have a poor prognosis. Adagrasib (MRTX849), a potent oral small molecule KRASG12C inhibitor, irreversibly and selectively binds KRASG12C, locking it in its inactive state. Adagrasib has been optimized for favorable pharmacokinetic (PK) properties, including long half-life (~24 hours), extensive tissue distribution, dose-dependent PK, and central nervous system penetration, however BM-specific anti-tumor activity of KRASG12C inhibitors remains to be fully characterized. EXPERIMENTAL DESIGN/METHODS:A retrospective database query identified patients with KRAS-mutant NSCLC to understand their propensity to develop BM. Preclinical studies assessed physiochemical and PK properties of adagrasib. Mice bearing intracranial KRASG12C-mutant NSCLC xenografts (LU99-Luc/H23-Luc/LU65-Luc) were treated with clinically relevant adagrasib doses and levels of adagrasib in plasma, cerebrospinal fluid (CSF), and brain were determined along with anti-tumor activity. Preliminary clinical data were collected from 2 patients with NSCLC with untreated BM who had received adagrasib 600 mg BID in the Phase 1b cohort of the KRYSTAL-1 trial; CSF was collected, adagrasib concentrations measured, and anti-tumor activity in BM evaluated. RESULTS:Patients with KRAS-mutant NSCLC demonstrated high propensity to develop BM ({greater than or equal to}40%). Adagrasib penetrated into CSF and demonstrated tumor regression and extended survival in multiple preclinical BM models. In 2 patients with NSCLC and untreated BM, CSF concentrations of adagrasib measured above the target cellular IC50. Both patients demonstrated corresponding BM regression, supporting potential clinical activity of adagrasib in the brain. CONCLUSIONS:These data support further development of adagrasib in patients with KRASG12C-mutant NSCLC with untreated BM.

Tumor mutational burden (TMB) in circulating tumor DNA (ctDNA) has shown promise in predicting benefit from PD-L1/PD-1 inhibitors in retrospective studies. Aiming to assess blood TMB (bTMB) prospectively, we conducted B-F1RST ( NCT02848651 ), an open-label, phase 2 trial that evaluated bTMB as a predictive biomarker for first-line atezolizumab monotherapy in locally advanced or metastatic stage IIIB-IVB non-small cell lung cancer (n = 152). The co-primary endpoints were investigator-assessed objective response rate (ORR) per RECIST version 1.1 and investigator-assessed progression-free survival (PFS) between high and low bTMB subgroups at the pre-defined bTMB ≥ 16 (14.5 mutations per megabase) cutoff. Secondary endpoints included investigator-assessed PFS, overall survival (OS) and duration of response at various bTMB cutoffs, as well as safety. Investigator-assessed PFS in the bTMB ≥ 16 versus bTMB < 16 groups was not statistically significant. However, bTMB ≥ 16 was associated with higher ORR, and ORR improved as bTMB cutoffs increased. No new safety signals were seen. In exploratory analyses, patients with maximum somatic allele frequency (MSAF) < 1% had higher ORR than patients with MSAF ≥ 1%. However, further analysis showed that this effect was driven by better baseline prognostics rather than by MSAF itself. At 36.5-month follow-up, an exploratory analysis of OS found that bTMB ≥ 16 was associated with longer OS than bTMB < 16. Further study and assay optimization will be required to develop bTMB as a predictive, standalone biomarker of immunotherapy or for use in conjunction with other biomarkers.

Our aim was to evaluate real-world time on treatment (rwToT), overall and by KRAS mutation status, with first-line pembrolizumab monotherapy for advanced non-small cell lung cancer (NSCLC) in real-world oncology practice in the US. rwToT is a readily available, intermediate-range endpoint that is moderately to highly correlated with overall survival in clinical trials and real-world data. Using deidentified electronic medical record data, we studied patients with ECOG performance status (PS) of 0-2 who initiated pembrolizumab (1 November 2016 to 31 March 2020) for advanced NSCLC with programmed death-ligand 1 (PD-L1) expression ≥ 50% and without EGFR/ALK/ROS1 genomic alterations. The data cutoff was 31 March 2021, and the median study follow-up was 34 months. The Kaplan-Meier median rwToT with first-line pembrolizumab monotherapy was 7.4 months (95% CI, 6.3-8.1) for 807 patients with PS 0-1, which was consistent with the median treatment duration in the KEYNOTE-024 trial (7.9 months). The median rwToT for 237 patients with PS 2 was 2.1 months (95% CI, 1.4-2.8). For those with KRAS-mutated and KRAS wild-type nonsquamous NSCLC and PS 0-1, the median rwToT was 7.6 months and 7.0 months, respectively. Our findings suggest long-term benefit of first-line pembrolizumab monotherapy for advanced NSCLC with PD-L1 expression ≥ 50% in real-world settings in the US, particularly for patients with good performance status at the start of therapy, irrespective of KRAS status.

Objectives: Despite availability of new treatments, the prognosis of lung cancer remains poor. This study aims to provide recent estimates of survival in patients with advanced non-small cell lung cancer (NSCLC) in the US.
Method(s): The survival of patients with advanced NSCLC was estimated using two US databases together covering 2010-2020. The study included patients with stage III or IV NSCLC diagnosed between 2010-2016 in the Surveillance, Epidemiology, and End Results Program (SEER) database, and patients with stage IIIB, IIIC or IV NSCLC, diagnosed between 2017-2020, without known oncogenic driver mutations who had completed >=4 cycles of 1L treatment (restricted to platinum-based combinations, immuno-oncology monotherapy, or ipilimumab/nivolumab) in the Flatiron Health database, a US Oncology Electronic Medical Record database. Overall survival (OS) was defined as time from diagnosis of stage III or IV NSCLC to death or to date of last confirmed activity.
Result(s): A total of 49,298 and 133,395 patients with stage III and IV diagnosis respectively were identified in SEER. The 1-, 3- and 5-year OS for patients with Stage III disease were 55.1%, 26.3% and 17.5%, and for stage IV disease were 25.8%, 7.4% and 4.0%, respectively. The Flatiron database had 1,045 patients with stage IIIB, 130 patients with stage IIIC and 3,210 patients with stage IV disease at diagnosis. The 1- and 3-year OS for stage IIIB/IIIC disease were 72.5% and 36.4%, and for patients with stage IV disease were 65.9% and 24.6%, respectively.
Conclusion(s): Despite differences in study population characteristics between the two databases, the study shows that mortality in patients with advanced NSCLC remains high, underscoring the need for continued efforts to identify novel treatments and synergetic treatment combinations to improve patient outcomes.
Copyright

Declaration de liens d'interets: B. Besse : Research Funding-4D Pharma (Inst); Abbvie (Inst); Amgen (Inst); Aptitude Health (Inst); AstraZeneca (Inst); BeiGene (Inst); Blueprint Medicines (Inst); Boehringer Ingelheim (Inst); Bristol-Myers Squibb (Inst); Celgene (Inst); Cergentis (Inst); Cristal Therapeutics (Inst); Daiichi Sankyo (Inst); GlaxoSmithKline (Inst); Inivata (Inst); Janssen Oncology (Inst); Lilly (Inst); Onxeo (Inst); OSE Immunotherapeutics (Inst); Pfizer (Inst); Roche/Genentech (Inst); Sanofi (Inst); Takeda (Inst); Tolero Ph. F. Skoulidis : Honoraria-Bristol-Myers Squibb Research Funding-AIMM Therapeutics (I); Amgen (Inst) Travel, Accommodations, Expenses-Tango Therapeutics. B.T. Li : Amgen (Inst); AstraZeneca (Inst); Bolt Biotherapeutics (Inst); Daiichi Sankyo (Inst); GRAIL (Inst); Guardant Health (Inst); Hengrui Therapeutics (Inst); Lilly (Inst); MORE Health (Inst); Roche/Genentech (Inst)Karger Publishers-Book royalty; Shanghai Jiao Tong University Press-Book royalty; US62/514,661 (Inst); US62/685,057 (Inst)Jiangsu Hengrui Medicine; MORE Health; Boehringer Ingelheim; Genentech; Lilly. G. Ramaswamy : Honoraria-Abbvie; Genentech/Abbvie; Geneplus Consulting or Advisory Role-Abbvie; Achilles Therapeutics; Amgen; AstraZeneca/MedImmune; Bristol-Myers Squibb; Celgene; EMD Serono; Genentech/Roche; GlaxoSmithKline; Ignyta; Janssen; Jounce Therapeutics; Lilly; Merck Serono; Nektar; Pfizer; Phillips Gilmore Oncology; Roche. G.K. Dy : Honoraria-AstraZeneca/MedImmune; GlaxoSmithKline Consulting or Advisory Role-AstraZeneca; GlaxoSmithKline; Takeda Research Funding-AMGEN (Inst); AstraZeneca (Inst); Bristol-Myers Squibb (Inst); Tesaro (Inst). G. Shapiro : Almac Dc; Angiex; Artios; Astex Ph; Atrin Ph; Bayer; Bicycle Th; Boehringer Ingelheim; Concarlo; Cybrexa Th; CytomX Th; Daiichi; Sankyo; Fusion Ph; G1 Th; Ipsen; Lilly; Merck Serono; Pfizer; Roche; Seattle Gen; Sierra Oncology; Syros Ph; Zentalis; Aileron Th; Amgen; Array BioPharma; AstraZeneca; BMS; CanBas; Cellceutix; Clovis Oncology; Covidien; Curis; Cyclacel; Esperas Ph; Exelixis; Genentech; GSK; Immune Design; Millennium; Mirati Th; Novartis; PharmaMar; PTC Th; PumaBiotechnology; Sanofi; Tensha Th; Tesaro; Vertex. J. Bauml : Consulting or Advisory Role-AstraZeneca; Ayala Pharmaceuticals; Boehringer Ingelheim; Bristol-Myers Squibb; Celgene; Foundation Medicine; Genentech; Guardant Health; Inivata; Janssen; Merck; Novartis; Novartis; Regeneron; Takeda Research Funding-Amgen (Inst); AstraZeneca (Inst); Bayer (Inst); Carevive Systems (Inst); Incyte (Inst); Janssen (Inst); Merck (Inst); Mirati Therapeutics (Inst); Novartis (Inst); Pfizer (Inst); Takeda (Inst). M.H. Schuler : Honoraria-Amgen; Boehringer Ingelheim; Bristol-Myers Squibb; Janssen-Cilag; Novartis; Roche Pharma AG Consulting or Advisory Role-Amgen; AstraZeneca; Boehringer Ingelheim; Bristol-Myers Squibb; GlaxoSmithKline; MorphoSys; Novartis; Roche; Takeda Research Funding-AstraZeneca (Inst); Boehringer Ingelheim (Inst); Bristol-Myers Squibb (Inst); Novartis (Inst) Patents, Royalties, Other Intellectual Property-Highly sensitive method for mutation detection by PCR (Inst). A. Addeo : Consulting or Advisory Role-Amgen; Astellas Pharma; AstraZeneca; Bristol-Myers Squibb; Lilly; MSD; Novartis; Pfizer; Roche. T. Kato : AZ; Boehringer Ingelheim; BMS; Chugai Pharma; Daiichi Sankyo; Lilly; Merck Serono; Merck Sharp & Dohme; Nippon Kayaku; Novartis; Ono Ph; Pfizer; Taiho Ph; Takeda; Lilly; Abbvie; Amgen; BMS; Regeneron; Taiho Pharmaceutical. A. Anderson : Employment-Amgen Stock and Other Ownership Interests-Amgen Patents, Royalties, Other Intellectual Property-I am listed as an inventor on several Amgen patents. I do not receive royalties on these patents. Travel, Accommodations, Expenses-Amgen. A. Ang : Employment-Amgen Stock and Other Ownership Interests-Amgen. G. Ngarmchamnanrith : Employment-Amgen Stock and Other Ownership Interests-Amgen. Q. Tran : Employment-Amgen Stock and Other Ownership Interests-Amgen. V. Velcheti : Consulting or Advisory Role-AstraZeneca/MedImmune; Boston Scientific; Bristol-Myers Squibb; EMD Serono; Foundation Medicine; GlaxoSmithKline; Lilly; Merck; Novartis; Novocure Research Funding-Alkermes (Inst); Altor BioScience (Inst); Atreca (Inst); Bristol-Myers Squibb (Inst); Eisai (Inst); Genentech (Inst); Genoptix (Inst); GlaxoSmithKline (Inst); Heat Biologics (Inst); Leap Therapeutics (Inst); Merck (Inst); NantWorks (Inst); OncoPlex Diagnostics (Inst); RSIP Vision (Inst); Trovagene.
Copyright

OBJECTIVES/OBJECTIVE:Effective therapy for non-small-cell lung cancer (NSCLC) depends on morphological and genomic classification, with comprehensive screening for guideline-recommended biomarkers critical to guide treatment. Companion diagnostics, which provide robust genotyping results, represent an important component of personalized oncology. We evaluated the clinical validity of Guardant360 CDx as a companion diagnostic for sotorasib for detection of KRAS p.G12C, an important oncogenic NSCLC driver mutation. MATERIALS AND METHODS/METHODS:KRAS p.G12C was tested in NSCLC patients from CodeBreaK100 (NCT03600833) in pretreatment plasma samples using Guardant360 CDx liquid biopsy and archival tissue samples using therascreen® KRAS RGQ polymerase chain reaction (PCR) kit tissue testing. Matched tissue and plasma samples were procured from other clinical trials or commercial vendors, and results were compared. Demographics and clinical characteristics and objective response rate (ORR) were evaluated. RESULTS:Of 126 CodeBreaK patients, 112 (88.9%) were tested for KRASp.G12C mutations with Guardant360 CDx. Among 189 patients in the extended analysis cohort, the positive and negative percent agreement (95% CI) for Guardant360 CDx plasma testing relative to therascreen® KRAS RGQ PCR kit tissue testing were 0.71 (0.62, 0.79) and 1.00 (0.95, 1.00), respectively; overall percent agreement (95% CI) was 0.82 (0.76, 0.87). TP53 co-mutations were the most common regardless of KRAS p.G12C status (KRAS p.G12C-positive, 53.4%; KRAS p.G12C-negative, 45.5%). STK11 was co-mutated in 26.1% of KRAS p.G12C-positive samples. The ORR was similar among patients selected by plasma and tissue testing. CONCLUSION/CONCLUSIONS:Comprehensive genotyping for all therapeutic targets including KRAS p.G12C is critical for management of NSCLC. Liquid biopsy using Guardant360 CDx has clinical validity for identification of patients with KRASp.G12C-mutant NSCLC and, augmented by tissue testing methodologies as outlined on the approved product label, will identify patients for treatment with sotorasib.

The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the application of AI-based cancer imaging analysis to address other, more complex, clinical needs. In this Perspective, we discuss the next generation of challenges in clinical decision-making that AI tools can solve using radiology images, such as prognostication of outcome across multiple cancers, prediction of response to various treatment modalities, discrimination of benign treatment confounders from true progression, identification of unusual response patterns and prediction of the mutational and molecular profile of tumours. We describe the evolution of and opportunities for AI in oncology imaging, focusing on hand-crafted radiomic approaches and deep learning-derived representations, with examples of their application for decision support. We also address the challenges faced on the path to clinical adoption, including data curation and annotation, interpretability, and regulatory and reimbursement issues. We hope to demystify AI in radiology for clinicians by helping them to understand its limitations and challenges, as well as the opportunities it provides as a decision-support tool in cancer management.