bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing PD-L1 without a biopsy and through PD-L1 PET imaging with 18F-BMS-986229.
Authors: Postow Michael A. , Mauguen Audrey , Frosina Denise , Jungbluth Achim A. , Busam Klaus J. , Pandit-Taskar Neeta 
Published: June 2022

2578 Background: Programmed death ligand-1 (PD-L1) is usually determined by immunohistochemistry (IHC). Determining PD-L1 status by whole body, non-invasive PD-L1 PET imaging with 18F-BMS-986229 tracer infusion may be a way to circumvent limitations to PD-L1 IHC such as poor tissue availability; discrepant PD-L1 IHC results among different tumors within the same patient; and inability to measure PD-L1 longitudinally given challenges with repeated biopsies. Methods: Within the prospective ADAPT-IT trial (NCT03122522) testing an abbreviated course of nivolumab (nivo) + ipilimumab (ipi) in patients with unresectable stage III or IV melanoma, we investigated PD-L1 PET imaging in a 10-patient expansion cohort at baseline and after 6 weeks of treatment. Maximum standard uptake value (SUV max) and mean of all SUV max for lesions for PD-L1 PET were calculated on a whole patient level for each target/ non target lesion. Standard treatment response was determined by RECIST v1.1 at weeks 6 and 12. PD-L1 IHC was scored using the E1L3N antibody by tumor proportion score (TPS), Immune Cell Score (ICS), and a Combined Positive Score (CPS). Comparisons between PD-L1 PET parameters and response were determined by complete or partial response (CR/PR); stable disease (SD), and progressive disease (PD) at respective imaging timepoints. Absolute changes in PD-L1 SUV mean and max were calculated between scans. The correlation between PD-L1 PET and IHC was estimated using Spearman’s coefficient correlation. Results: Five patients (50%) had a PR to treatment at week 6; one of these PR became a CR at week 12 and one PR was not assessable at week 12. All RECIST responders at week 6 (n = 5) had baseline PD-L1 SUV mean ≥3.00, and all progressors at week 6 (n = 3) had baseline PD-L1 SUV mean ≤2.60 (Table). A similar trend was observed when assessing response at week 12 and when considering baseline PD-L1 SUV max. Patients had changes in their PD-L1 SUV levels between baseline and week 6. Baseline PD-L1 SUV mean (inclusive of all lesions within a patient) correlated with PD-L1 IHC by TPS, ICS, and CPS (r = 0.64, 0.5, 0.47, respectively). No patients had side effects from 18F-BMS-986229 tracer infusion. Conclusions: The signal of PD-L1 positivity by PET imaging with 18F-BMS-986229 at baseline appears associated with early efficacy from nivo + ipi in this small cohort and may offer additional information than PD-L1 IHC. The ability to assess PD-L1 on a whole patient level at multiple timepoints on treatment may have future implications in how best to sequence and combine immunotherapies but further study in larger patient cohorts is needed. Clinical trial information: NCT03122522. [Table: see text]
A phase 1 first-in-human dose finding/randomized phase 2 study of IMM60 and pembrolizumab (PEM) in advanced melanoma and non–small cell lung cancer (NSCLC; IMP-MEL).
Authors: Coupe Nicholas , Walters Ian B. , Kramer Robert A. , Gileadi Uzi , Middleton Mark R. 
Published: June 2022

2582 Background: Invariant natural killer T-cells (iNKTs) share features of innate cells (NK-like) and T-cells (can prime and boost an adaptive immune response). The importance of this relatively rare lymphocyte subset has generated increased interest due to its dual ability to have a direct cytotoxic effect on CD1d expressing tumors and also its ability to induce long-lasting antitumor CD8 T cell responses mediated by cross priming and licensing of dendritic cells. Various clinical approaches involving the use of allogenic iNKT cells (both untransduced and CARs) are in development and here we describe initial clinical studies with IMM60, a synthetically derived agonist of iNKT cells which is formulated in a liposome( PORT-2). In preclinical studies, IMM-60 treatment results in maturation of DCs and B cells and a potent stimulation of iNKT cell-derived IFN-g. In efficacy studies, IMM60 demonstrated monotherapy activity in PD-1 resistant models, (eg., B16-F10), up-regulation of PD-L1 expression on cancer cells as a consequence of its priming effect, and was able to overcome resistance to PD-1 antibody therapy. Methods: IMP-MEL is an open-label first-in-man phase 1/2 study, currently enrolling adult subjects with advanced NSCLC and melanoma. IMM60 containing liposomes were administered IV Q3W at 3 escalating dose levels for 6 doses alone or with PEM 200mg Q3W. The study seeks to assess the safety and efficacy of IMM-60 alone and in combination with PEM. Results: 5 subjects have been enrolled in the monotherapy cohort having a median of 3 prior therapies (min 2, max 5). Median age was 64.5 years. No treatment related adverse events have been reported nor any objective disease responses in the evaluable monotherapy subjects (n=3) to date. Conclusions: IMM-60 is well tolerated when administered IV as monotherapy at the doses tested. The liposomal formulation leads to a favorable preliminary safety profile. Full results of the phase 1 will be reported at the meeting with analysis of circulating cytokines and flow cytometric analysis. The trial plans to transition to phase 2 testing IMM60-alone vs PEM monotherapy vs the combination of IMM60 with PEM. Clinical trial information: 80472712.
Outcomes of responders to PD-1/PD-L1 inhibitors who discontinue therapy after sustained disease control.
Authors: Sharma Harsh , Moturi Krishna Rekha , Yilmaz Emrullah , Gbolahan Olumide B. , Kumar Atul , Hashemi-Sadraei Neda 
Published: June 2022

2586 Background: PD-1/PD-L1 immune checkpoint inhibitors (ICIs) are widely used in the treatment of metastatic malignancies. Judiciously balancing disease control (DC) against development of immune-related adverse events (irAE) remains a crucial aspect of treatment. The effect of treatment discontinuation after sustained disease control (SDC) is unknown. The purpose of this analysis was to evaluate outcomes of responders to ICI who discontinue treatment after a minimum of 12 months (SDC). Methods: We retrospectively reviewed the database of the University of New Mexico Comprehensive Cancer Center between 2014 and 2021 and identified patients who had received ICI. Patients with metastatic solid tumors who had stopped ICI therapy after achieving SDC [stable disease, partial response, complete response (SD,PR,CR)] were selected and outcomes reviewed from their electronic health records. Results: We identified 204 patients who were treated with ICI for various solid cancers. Forty-four patients (21.6%) met the criteria, of whom 35 with follow-up data were included in the final analysis; including 11 melanoma, 5 non-small cell lung, 4 head & neck, 8 renal, 4 urothelial, 1 anal, 1 Merkel cell carcinoma, and 1 liposarcoma. Patients were divided into two groups: those who stopped ICI due to an irAE [irAE group, n=14, median treatment time (MTT), 16.6 mo] and those who stopped due to other reasons (eg completion of 2 years of therapy, n=20, non-cancer related surgery, n=1) (non-irAE group, n=21, MTT, 23.7 mo). Among the irAE group, the most common irAE included pneumonitis, rash, transaminitis, and fatigue. As of data cutoff date, 10 of 14 (71%) patients continued to show SDC. Only 4 of 14 (28.6%) patients in this group experienced progression of disease (PD), one of whom was re-challenged with nivolumab and achieved DC (median follow-up of 19.2 mo after last dose of treatment, range 3-50.2 mo). Among the non-irAE group, 13 of 21 (62%) continued to have SDC. Eight of 21 (38%) experienced PD after stopping treatment, 7 of whom received ICI rechallenge, with 2 of 7 achieving DC (median follow-up of 22.2 mo, range 3.6-54.8 mo). At a median follow-up of 21.3 mo from stopping ICI therapy (range, 3-54.8 mo), 10 patients (71%) from the irAE group and 13 (61.9%) from the non-irAE group are in DC and have not experienced PD. Conclusions: We demonstrate that 23 (66%) patients experienced SDC, regardless of cancer type or development of irAE. After including patients who were re-challenged with ICI due to PD, 26 (74%) remain in DC. Future prospective malignancy-specific trials such as NCT04637594 are warranted to evaluate optimal treatment duration. [Table: see text]
Actual immune checkpoint inhibitor drug use in U.S. patients with cancer.
Authors: Rawji Alia , Henk Henry J. , DaCosta Byfield Stacey , Malin Jennifer 
Published: June 2022

2608 Background: By 2018, seven Immune Checkpoint Inhibitor (ICI) drugs had gained FDA approval in nine cancers and the number of indications has continued to increase. Haslam et al. estimated that between 36.1 and 38.5% of US patients with cancer were eligible for ICI therapy in 2019. We report the use of ICI dugs in the first-line of therapy (LOT1) and second-line (LOT2) among enrollees treated for 9 cancers with an FDA indication approval in or before 2017. Methods: A cohort of patients treated for one of the nine most common cancers with an FDA indication for ICI drugs in 2017 was identified using de-identified data from the OptumLabs Data Warehouse, and clinical information from the Optum Cancer Guidance Program’s electronic prior authorization (ePA) platform. De-identified administrative claims data were then linked to ePA information (cancer type & diagnosis date) at the patient level to identify details of treatment received. Eligible patients were enrolled in a commercial or Medicare Advantage (MA) plan and initiated treatment within six months of diagnosis, enrolled at least six months prior to diagnosis date (ensuring this was the LOT1) and at least thirty days after start of first identified treatment regimen (to identify the full treatment regimen). LOT1 treatment initiation ranged from 1/1/2017 to 12/31/2020 for those who were diagnosed before 6/30/2020. ICI regimens are defined as those with an ICI drug received within first thirty days of the LOT start date. Results: In this population, we identified 17,283 eligible patients treated for non-small cell lung cancer (4654), melanoma (705), renal cell carcinoma (554), bladder cancer (1974), colorectal (4502), hepatocellular carcinoma (673), gastric cancer (1786), head and neck cancer (1923), or Hodgkin lymphoma (512) in 2018, 2019, and 2020. Overall, 3,291 (19%) of these patients received an ICI in LOT1 with rates increasing over time. The highest rates of ICI use in LOT1 are for the treatment of melanoma, remaining consistent over time, while ICI use in LOT2 is highest for the treatment of non-small cell lung cancer although evidence from 2020 suggests this may be waning. Among patients being treated for renal cell carcinoma, ICI use in LOT2 decreased from 43% (2018) to 15% (2020) while LOT1 ICI use increased to 81% in 2020. Conclusions: Overall, ICI use has changed over time in both the first- and second-line setting. In particular, we observe a shift in ICI use from LOT2 to LOT1, consistent with the more recent FDA approvals in earlier lines of therapy.[Table: see text]
Density patterns of tumor-infiltrating lymphocytes and association with objective response to nivolumab in patients with lung adenocarcinoma from CheckMate 057.
Authors: Corredor Germán , Ding Ruiwen , Prasanna Prateek , Barrera Cristian , Toro Paula , Viswanathan Vidya Sankar , Zens Philipp , Berezowska Sabina , Baxi Vipul , Balli David , Belete Merzu , Velcheti Vamsidhar , Schalper Kurt A. , Madabhushi Anant 
Published: June 2022

2662 Background: Immune checkpoint inhibitors (ICIs) are currently approved for use as therapy in advanced stage lung adenocarcinoma (LUAD). ICIs can decrease risk of progression by up to 60% when compared to chemotherapy, but only about 20% of patients (pts) show response. Given that high levels of tumor-infiltrating lymphocytes (TILs) have been shown to be associated with better prognosis, here, we assess whether computationally derived TIL density measures on digitized H&E images can predict RECIST derived response to nivolumab in LUAD in Checkmate 057 (CM057). CM057 is a clinical trial designed to compare the overall survival of metastatic non-squamous non-small cell lung cancer subjects treated with either nivolumab or docetaxel after failing platinum-based chemotherapy. Methods: H&E-stained samples of 683 LUAD pts were collected from TCGA (n = 421), University of Bern (UBern) (n = 100), and CM057 (n = 162). Tumor response was assessed using RECIST v1.1. Samples were digitized as whole slide images. 294 pts randomly selected from TCGA formed the training set. The remaining 389 pts were used for validation in response to nivolumab in CM057 and prognosticating overall survival (OS) in UBern and TCGA. Computerized algorithms automatically identified TILs and extracted features related to quantity and compactness of TILs with respect to other surrounding nuclei. The top 6 features, determined by least absolute shrinkage and selection operator, were used to train Cox regression models that assign a death risk score to each patient. Pts with risk scores higher than the training median score were considered “high risk” or “non-responders” while pts with lower scores were considered “low risk” or “responders”. Results: The classifier predicted objective response in CM057 with an AUC = 0.61. Additionally, survival analysis showed that the model was prognostic for OS with hazard ratios of 2.38 (confidence interval (CI): 1.32-4.29, p = 0.01, n = 127) in TCGA and 2.37 (CI: 1.32-4.25, p < 0.01, n = 100) in UBern. Conclusions: A computerized image analysis model based on measurements of TIL density showed association with response to treatment in LUAD pts who received nivolumab and was prognostic of OS. Although the AUC was not high, the results suggest analysis of TILs has potential to identify pts who will respond to treatment. Future work will include training a classifier using response to treatment as endpoint and combining the TIL measures with other biomarkers like TMB or PD-L1.
Tumor-infiltrating lymphocyte enrichment predicted by CT radiomic analysis is associated with clinical outcomes of immune checkpoint inhibitor in non–small cell lung cancer.
Authors: Park Changhee , Jeong Dong Young , Choi Yeonu , Oh You Jin , Kim Jonghoon , Pereira Sergio , Paeng Kyunghyun , Ock Chan-Young , Lee Se-Hoon , Lee Ho Yun 
Published: June 2022

2663 Background: Enrichment of tumor-infiltrating lymphocytes (TIL) in the tumor microenvironment (TME) is a reliable biomarker of immune checkpoint inhibitors (ICI) in non-small cell lung cancer (NSCLC). Phenotyping through CT radiomics has the overcome the limitations of tissue-based assessment, including for TIL analysis. Here, we objectively assess TIL enrichment using an artificial intelligence-powered H&E analyzer, Lunit SCOPE IO, and analyze its association with advanced quantitative imaging features extracted via radiomic analysis. Clinical significance of the selected radiomic features (RFs) is then validated in independent NSCLC patients who received ICI. Methods: In the training cohort, which included 235 NSCLC patients with both tumor tissue and corresponding CT images obtained within 1 month, we extracted 86 RFs from the CT images. From tissue, a patient’s TIL enrichment score (TILes) was defined as the fraction of tissue area with high intra-tumoral or stromal TIL density, divided by the whole TME area, as measured on an H&E slide. From the corresponding CT images, the least absolute shrinkage and selection operator model was then developed using features that were significantly associated with TIL enrichment. The CT model was then applied to CT images from the validation cohort, which included 242 NSCLC patients who received ICI as ≥ second line. Results: Among the extracted RFs, 22 features were significantly associated with TILes (p < 0.005). After excluding features of multicollinearity and/or zero-coefficient, two features, gray level variance (coefficient 1.71 x 10-3) and low gray level emphasis (coefficient -2.48 x 10-5), were finally included in the model. The two features were both computed from the size-zone matrix (SZM), the idea of which is to break down a given tumor volume into smaller spatially contiguous compartments of different sizes. In the validation cohort, the patients with high predicted TILes (≥ median) had significantly prolonged progression-free survival compared with those with low predicted TILes (median 3.81 months [95% CI 2.14 – 5.69] versus 1.94 months [95% CI 1.58 – 2.93], hazard ratio 0.69 [95% CI 0.53 – 0.90], p = 0.007). Conclusions: This CT radiomics model is able to assess TIL enrichment in TME, which is significantly associated with favorable ICI outcomes in NSCLC. Analyzing the TME through radiomics may overcome limitations of tissue-based analysis and inform clinical decisions, particularly related to use of ICI.
Differential diagnosis of hematologic and solid tumors using targeted transcriptome and artificial intelligence.
Authors: Zhang Hong , Albitar Maher , Qureshi Muhammad Asif , Wahid Mohsin , Charifa Ahmad , Ehsan Aamir , Ip Andrew , De Dios Ivan , Ma Wanlong , McCloskey James , Donato Michele , Siegel David Samuel DiCapua , Gutierrez Martin , Pecora Andrew L , Goy Andre 
Published: June 2022

3018 Background: Diagnosis and classification of tumors is becoming increasingly dependent on biological and molecular biomarkers. RNA expression profiling using next generation sequencing (NGS) provides information on various biological and molecular changes in the cancer and in the microenvironment. We explored the potential of using targeted transcriptome and artificial intelligence (AI) in the differential diagnosis and classification of various hematologic and solid tumors. Methods: RNA from hematologic neoplasms (N = 2606) and solid tumors (N = 2038) as well as normal bone marrow and lymph node control (N = 806) were sequenced by NGS using a targeted 1408-gene panel. The hematologic neoplasms included 20 different subtypes. Solid tumors included 24 different subtypes. Machine learning is used for comparing two classes at a time. Geometric Mean Naïve Bayesian (GMNB) classifier is used to provide differential diagnosis across 45 diagnostic entities with assigned ranking. Results: Machine learning showed high accuracy in distinguishing between two diagnoses with AUC varied between 1 (Sarcoma vs GIST) and 0.841 (MDS vs normal control) (examples in Table). For differential diagnosis between all 45 different diagnoses, we used 3045 samples for training the GMNB algorithm and 1415 samples for testing. Correct first choice diagnosis was obtained in 100% of ALL, 88% of AML, 85% of DLBCL, 82% of colorectal cancer, 88% of lung cancer, 72% of CLL, and 72% of follicular lymphoma. The algorithm had difficulty in typically overlapping diagnoses and diagnosed as first choice 19% of MDS, 46% of normal, and 12% of MPN. Diagnosis improved significantly when second choice was considered. Conclusions: Targeted RNA profiling with proper AI can provide highly useful tools for the pathologic diagnosis and classification of various cancers. Additional information such as mutation profile and clinical information can improve these algorithms, reduce subjectivity, and minimize errors in pathologic diagnoses. [Table: see text]
Monitoring engorgement of phagocytic circulating stromal cells during chemo-radiotherapy induction predicts survival in unresectable stage 2/3 NSCLC.
Authors: Gardner Kirby P , Adams Daniel L , Lopez Bravo Pablo , He Jianzhong , Qiao Yawei , Xu Ting , Liao Zhongxing X. , Tang Cha-Mei , Lin Steven H. 
Published: June 2022

3054 Background: Circulating stromal cells, ie Cancer Associated Macrophage-Like cells (CAMLs), are prevalent in the circulation of non-small cell lung carcinoma (NSCLC) patients (pts), appearing as giant phagocytic macrophages that represent an inflammatory pro-tumorigenic microenvironment. Previously it was shown that pts with engorged CAMLs of ≥50µm after treatment are prognostic for poor clinical outcomes. However, analyzing the dynamic changes in CAMLs over time or in response to treatment, ie chemoradiation (CRT) and immunotherapy (IMT) has not been evaluated. We monitored n = 182 unresectable NSCLC stage II/III pts treated with CRT alone (n = 91) or with concurrent IMT (n = 91) to evaluate changes in CAMLs before and after CRT induction at it relates to progression free survival (PFS) or overall survival (OS). Methods: We prospectively procured pts from 3 different regimes, treated with CRT alone (n = 91), treated concurrently with CRT & Atezolizumab (n = 40, clinical trial NCT02525757), or treated concurrently with Durvalumab (n = 51). We recruited 182 pts with pathologically confirmed stage II/III unresectable NSCLC. A total of 15 mL blood samples were drawn prior to start of therapy at baseline (BL) and ̃5 weeks (T1) after CRT induction. Blood filtration was done using CellSieve filters, then CAMLs were identified and measured to evaluate PFS & OS hazard ratios (HRs) by censored univariate and multivariate analyses at 2 years. Results: CAMLs were found in 89% of all samples tested. Increases in CAML size between BL & T1 were significantly correlated with worse clinical outcomes, with higher CAML increases correlated with increasingly worse outcomes, including CAML increases >10μm resulting in PFS HR=1.7 p = 0.027 & OS HR=1.9 p = 0.045, through increases >40μm resulting in PFS HR=2.1 p = 0.013 & OS HR=2.5 p = 0.020. Increases of CAMLs >35μm was optimal at stratifying pts PFS HR=2.2 p = 0.005 & OS HR=2.8 p = 0.005. Specifically, pts treated with only CRT and increasing CAMLs >35μmhad significantly worse PFS HR=2.7 p = 0.029 & OS HR=4.1 p = 0.013. In parallel, pts treated with CRT+IMT and increasing CAMLs >35μm had near significance for worse PFS (HR=2.1 p = 0.073) & OS (HR=2.3, p = 0.147), though follow up clinical data is ongoing. Conclusions: Our data suggest that in unresectable stage II/III NSCLC, tracking the increase of pro inflammatory immune cells (CAMLs) in circulation during therapy induction can identify pts less responsive to CRT or PD-L1/PD-1 IMTs.