bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-world outcomes of underrepresented patient populations treated with immune checkpoint inhibitors (ICIs): African American descent, poor ECOG performance status, and chronic viral infections.
Authors: Shah Neil J. , Blackburn Matthew , Cook Michael R , Belouali Anas , Serzan Michael , Kelly William , Bikas Athanasios , Kim Chul , Madhavan Subha , Liu Stephen V. , Atkins Michael B. 
Published: May 2019

2587 Background: ICIs have now become standard of care treatment for multiple malignancies. However, patients (pts) who are African American decent (AA), have a poor ECOG performance status (PS) or chronic viral infections [human immunodeficiency virus (HIV), hepatitis B (HBV) and hepatitis C (HCV)] were underrepresented in early clinical trials with ICIs and outcome data in these pt populations is not well reported. Methods: We performed a retrospective analysis of pts treated with ICIs (anti-PD(L)-1, anti-CTLA-4, or combination ICIs) across five MedStar Health hospitals from January 2011 to April 2018. Investigator-assessed best responses were noted. CTCAE v4.03 was used to capture immune-related adverse events (irAEs). Results: We identified 765 pts treated with 829 unique ICIs therapies across different malignancies. A total of 203 AA pts, 178 pts with a pre-treatment ECOG PS ≥2, 21pts with HIV, and 50 pts with HBV/HCV were noted. Any grade and grade ≥ 3 irAEs in the HIV cohort were 24% and 10% with an ORR of 29%. Any grade and grade ≥ 3 irAEs in HBV/HCV were 50% and 26% with an ORR of 21%. No viral reactivation or changes in pts anti-viral medications were noted during ICIs treatment. The ORR in AA pts was 35%. Any grade and grade ≥ 3 irAEs in the AA cohort were 27% and 8%, respectively. The ORR in pts with ECOG PS ≥2 was 14%. Any grade and grade ≥ 3 irAEs in this cohort were 20% and 4%. Similar trends were seen in the subset of patients with NSCLC treated with anti-PD(L)1 monotherapy (Table). Outcomes of NSCLC pts treated with anti-PD(L)-1 monotherapy. Conclusions: ICI therapy was not associated with any new safety signal in the above underrepresented populations. Prospective studies are needed to validate this data.[Table: see text]
Association of the imbalance between early and late differentiated intra-tumor CD4 T cells with mutational burden in non-small cell lung cancer.
Authors: Ghorani Ehsan , Reading James L. , Henry Jake Y. , Robert De Massy Marc , Rosenthal Rachel , Furness Andrew J.S. , Ben Aissa Assma , Jamal-Hanjani Mariam , Birkbak Nicolai , Wilson Gareth , Salgado Roberto , Lund Tom , Hiley Crispin T. , Loi Sherene , Hackshaw Allan , McGranahan Nicholas , Chain Benjamin M. , Peggs Karl S. , Swanton Charles , Quezada Sergio A. 
Published: May 2019

2590 Background: CD4 T helper cells are key orchestrators of immunity in states of persistent antigen exposure. In chronic viral infection, loss of immune control is associated with CD4 differentiation skewing (CD4ds) resulting from decline of early progenitors and gain in abundance of exhausted and terminally differentiated subsets. Here, we set out to identify whether a similar process occurs within the tumour microenvironment, contributing to immune dysfunction. Methods: Multiregional samples of tumour and non-tumour lung tissue from patients with untreated, surgically resected non-small cell lung cancer (NSCLC) within the first 100 recruited to the prospective lung TRACERx study were analysed by high dimensional flow cytometry of tumour infiltrating lymphocytes (TILs) and paired bulk tumour exome and RNA sequencing. We additionally reanalysed publically available single T cell and bulk tumour RNA sequencing from patients with NSCLC. Results: Unsupervised clustering and dimension reduction revealed a heterogenous landscape of CD4 TILs, with evidence of CD4ds in association with tumour mutational burden. Loss of PD1-CCR7+ T central memory enriched early differentiated cells was accompanied by gain in abundance of PD1+ populations with exhausted (CD57-ICOShiCTLA4hi) and terminally differentiated effector (CD57+Eomes+) phenotypes. Further characterisation of these populations by single cell RNA sequencing revealed differential expression of key genes involved in transcriptional regulation, co-inhibition and co-stimulatory pathways. A validated gene signature of CD4ds was associated with worse outcomes in TRACERx and TCGA cohorts. Conclusions: Our findings reveal remodelling of the CD4 differentiation landscape in association with tumour genomic characteristics, underscoring how mutational burden in the context of chronic stimulation may lead to loss of immune fitness and elucidating key regulatory pathways in potentially clinically relevant CD4 subsets.
Evidence for selective silencing of MHC-binding neoepitopes to avoid immune surveillance.
Authors: Parulkar Rahul , Nguyen Andrew , Sanborn J Zachary , Vaske Charles Joseph , Benz Stephen Charles , Reddy Sandeep K. , Kato Shumei , Kurzrock Razelle , Szeto Christopher 
Published: May 2019

2591 Background: Overall response rates to immune checkpoint inhibition (ICI) are < 50% even in TMB-high patients (e.g. Checkmate-227), suggesting other mechanisms of immune escape exist beyond expressing checkpoints. At least 18% of somatic-specific exonic DNA variants are not expressed into mRNA (Rabizadeh, 2018), yet the selection criteria for which variants to silence remains unclear. We sought to determine if immunogenicity of variants factors into their suppression. Methods: Somatic-specific single nucleotide variants (SNVs) were identified from paired tumor/normal whole-exome sequencing (WES), and annotated as expressed if observed in > = 2 RNAseq reads. MHC1 binding affinity for 9-mer neoepitope peptides resulting from said SNVs were predicted using NetMHC within presented HLA-types. Cases with > 200 non-synonymous exonic mutations were designated as TMB-high in accordance with Rizvi et al, 2015. Tumor immune activity was inferred by RNAseq expression of 6 checkpoint/TME markers, as well as by estimating immune infiltration using RNAseq deconvolution of immune genesets (Bindea et al 2013). Significant associations between TMB, neoantigen-load, expressed neoepitope binding affinities, and immune activity were analyzed. Results: Within a clinical database of 1,363 cases with T/N/R sequencing, a total of 147,015 potential neoepitopes were identified. A small but significant enrichment was observed for silencing neoepitopes that are predicted to bind MHC1 (OR = 1.22, p = 2.4e-78 one-sided Fishers test). The silencing rate was similar between the 17% of patients with high TMB vs others, but was increased in 35% of all patients with high inferred immune infiltration (N = 490, OR = 1.30, p = 1.8e-31). A further silencing enrichment was observed in 19% of all patients displaying high immune activity but low PDL1 expression (N = 263, OR = 1.44, p = 4.0e-45). Conclusions: We observe significant preferential silencing of MHC binding neoepitopes. Specifically, when tumor infiltrating immune cells are activated, silencing neoepitopes may be an alternative to checkpoint expression for avoiding an immune cascade. Patients with TILs and silenced neoepitopes may benefit from epigenetic priming therapy prior to ICI therapy.
Association of an inflammatory gene signature with CD8 expression by immunohistochemistry (IHC) in multiple tumor types.
Authors: Szabo Peter M , Qi Zhenhao , Zerba Kim , Ely Scott , Edwards Robin , Lu James , Cooley James , Navratil Marian , Dalgliesh Gillian L , Adya Neeraj 
Published: May 2019

2593 Background: A multiparameter tumor inflammation assay based on gene expression profiling (TIA-GEP) can extend the utility of IHC to interrogate the tumor microenvironment (TME). Using CD8 expression assessed by IHC (CD8-IHC) as a surrogate for inflammation, statistical modelling was used to develop a specific gene signature on the TIA-GEP panel to predict CD8-IHC. The correlation between TIA-GEP and CD8-IHC and the prevalence of inflammation were explored across multiple tumor types. Methods: Levels of inflammation were measured by CD8-IHC and TIA-GEP on 1778 procured samples across 12 tumor types. Quality control metrics involved sample input quality, technical errors, and inter-run variability. Generalized linear models were used to identify an inflammation score that predicts the CD8-IHC score in melanoma and SCCHN tissue. The predictive accuracy of this signature was also examined in 10 additional tumor types. Results: Assessment of TME inflammation by CD8-IHC was consistent with that observed by TIA-GEP in multiple tumor types. The range of inflammation varied across different tumor types, with relatively lower inflammation range and scores in SCLC, ovarian, and prostate cancers, and higher values in NSCLC, melanoma, SCCHN, and gastric cancers. R2 x 100 values reflecting percent variation in CD8-IHC associated with TIA-GEP ranged from 62.4% to 79.2% ( P < 0.0001) for all tumor types except prostate cancer (32.5%). Low correlation in prostate cancer may be a result of low prevalence of inflammation by CD8-IHC. Estimated linear regression slopes between CD8-IHC and TIA-GEP ranged from 0.74 in SCLC to 1.27 in gastric cancer. Conclusions: The results suggest that the inflammation signature is a robust potential diagnostic tool predicting inflammation in the TME. The inflammation signature not only correlates with CD8-IHC for multiple tumor types, but also leverages the alternative benefits associated with TIA-GEP, which include information related to tumor inflammation-associated biomarkers and flexibility in exploring the value of other genomic signatures.
Application of artificial intelligence to predict a new class of novel synthetic lethal targets.
Authors: Mousses Spyro , Schneider David , Kiefer Jeff , Derdeyn Pieter , Douglas Kendyl , Kothari Abhishek , Von Hoff Daniel D. , Yoo Chris 
Published: May 2019

2598 Background: Synthetic lethal targets are proteins that are contextually vulnerable. Inhibitors of PARP1, for example, selectively produce a lethal phenotype in the context of cancer cells which have lost BRCA1 or BRCA2 function. As a high mutation rate is a hallmark of many cancers, targeting synthetic lethal interactions to selectively inhibit cancer cells with altered genetic backgrounds may increase the specificity and efficacy of therapeutics. Recently, clinical trials have targeted synthetic lethal pairs such as EGFR and BRAF, TP53 and BCL2, and PTEN and CHD1. Previous attempts to identify synthetic lethal targets have relied on empirical results from published studies of biological pathways perturbed in cancer cells. Developing strategies to rapidly identify synthetic lethals by combining multiple experimental and computational approaches would result in a new class of potential cancer drug targets beyond the existing efforts that rely on single experimental or computational methods alone. Methods: Here we present Expansive AI, an artificial intelligence augmented knowledge network that enables rapid hypothesis generation for accelerated discovery research. Using a purpose-built, hypergraph database of massive, integrated genomic and biomedical data, we can query all synthetic lethals and their component genes, as well as a wealth of data related to these genes. The database of biological data includes 11,000+ cancer genomes from TCGA, prior knowledge resources such as gene ontology and pathway resources, and experimental data including chemical and protein interaction and patent data. The hypergraph’s architecture allows for linking and nesting data, enabling efficient extraction of biologically-relevant features. Results: Using these features, a neural network classified 540 new candidate pairs that have previously not been reported. The candidate pairs were filtered to include only known oncogenes and least-studied genes. This produced a list of gene pairs which may represent the most novel class of synthetic lethal target candidates identified to date. Conclusions: We highlight the results of this AI-based approach and discuss validation efforts of the predicted interactions in specific cancer contexts.
Immune profiling of tumor-infiltrating T cells using mass cytometry.
Authors: Roumanes David , Newell Evan , Fehlings Michael 
Published: May 2019

2607 Background: Immunotherapy recent successes have opened new avenues for the treatment of cancer and the presence of tumor-specific CD8+ T cells in tumor-bearing individuals offer a promising therapeutic target. However, the detection and profiling of such T cells are challenging due to the need to detect rare antigen-specific T cell subpopulations in patient samples that are limited in size thus making it difficult to exploit these parameters for predictive signatures of clinical response. Moreover, the identification and analysis of neoantigen-specific CD8+ T-cells in tumor-bearing individuals is challenging due to the small pool of such cells. Methods: In order to identify therapy-relevant tumor antigens and to facilitate a concurrent in-depth characterization of cells directed towards these targets, immunoSCAPE leverages the high-dimensional immune profiling capabilities of cytometry by time of flight (CyTOF) combined with a unique technology allowing the identification rare antigen-specific T-cell subsets. Results: We applied this technology to patient tumor-infiltrating lymphocytes from human cancer samples and tumor-derived neoantigens recognized by T-cells were identified and characterized. Interestingly, the majority of patient-derived tumor infiltrates consisted of tumor-unrelated T-cells characterized by a diverse phenotype. Strikingly, the expression of CD39 was absent from these bystander cells, suggesting that CD39 could be a useful biomarker for the identification of putative tumor-reactive T cells. Conclusions: Simultaneous immune profiling revealed that tumor-unrelated, bystander CD8+ T-cells are phenotypically different in human tumor infiltrates and identified CD39 as a putative marker of neoantigen-specific T-cells. By providing insights into the nature, frequency and phenotype of antigen-specific T-cells, immunoSCAPE’s unique target discovery and high-dimensional immune profiling platform is a valuable tool for the development of novel diagnostic and therapeutic strategies in immunotherapy.
Pan-tumor prognostic value of multiple immune protein expressions.
Authors: Lambert Tiphaine , Verlingue Loic , Colmet-Daage Léo , Rauby Brice , Sanchez-Escobar Aladro Nicolas , Kerisit Marie , Champiat Stephane , Wartelle Muriel , Lion Francois , Besse Benjamin , Angevin Eric , Hollebecque Antoine , Soria Jean-Charles , Scoazec Jean-Yves , Massard Christophe 
Published: May 2019

2618 Background: Using multiple immune-checkpoint proteins (ICP) screening in clinical routine could improve the evaluation of patients’ prognosis and ultimately tailor their treatment choice. We have evaluated this hypothesis in the context of early drug clinical trials. Methods: Patients included in MOSCATO-02 trial had refractory cancers and were candidate for phase 1 study. They were proposed to have a biopsy on an accessible tumor site for the analysis of four proteins by immunohistochemistry (IHC) and RNAseq: PD-L1, CD3, CD8 and FOXP3. Quantification of IHC staining was separated between intratumoral, intersitial and stromal by semi-quantitative method. Their relations to prognosis have been evaluated by survival Random Forest and compared to classical prognosis clinical variables, such as age and RMH score (calculated by the number of metastatic sites, lactate dehydrogenase (LDH) and serum albumin). Results: From April 2016 to September 2017, 228 patients included in MOSCATO-02 had a successful biopsy procedure with available IHC expression analysis. The main tumor subtypes were gastro-intestinal, urological, head and neck, breast and lung. RNAseq analyzes were performed for two thirds of the patients (N=170). Median overall survival was 8.1 months (CI95% 7.79 – 10, 65). We found that, in a cohort of phase I patients, RMH score was the most important variable used to estimate prognosis. Prognosis value of immune proteins were considerably inferior compared to clinical criteria. Among those proteins, the percentage of PD-L1 low score (1+) and average staining intensity of CD3 were the most valuables for prognosis evaluation. Variables with very few importance to prognosis estimation were CD8 and FOXP3 IHC scores, biopsy site and cancer types, subsequent treatments by immunotherapies or targeted therapies. Conclusions: In this cohort of patients with refractory cancers, the RMH score is confirmed as highly prognosis. Immune proteins could be used as a support to guide patient’s selection but does not constitute effective prognosis criteria.
Baseline tumor-immune signatures associated with response to bempegaldesleukin (NKTR-214) and nivolumab.
Authors: Hurwitz Michael E. , Cho Daniel C. , Balar Arjun Vasant , Curti Brendan D. , Siefker-Radtke Arlene O. , Sznol Mario , Kluger Harriet M. , Bernatchez Chantale , Fanton Christie , Iacucci Ernesto , Liu Yi , Nguyen Tuan , Overwijk Willem , Zalevsky Jonathan , Tagliaferri Mary Ann , Hoch Ute , Diab Adi 
Published: May 2019

2623 Background: PIVOT-02 is an ongoing phase 1/2 study of bempegaldesleukin (NKTR-214), a CD122-preferential IL-2 pathway agonist, plus nivolumab in patients with advanced solid tumors. Bempegaldesleukin (NKTR-214) increases proliferative tumor infiltrating lymphocytes (TIL) and cell surface PD-1 on immune cells and PD-L1 on tumor cells, demonstrating potential synergy with anti-PD-1 therapy. Pre-treatment tumor biopsies from metastatic 1L melanoma (MEL) and urothelial carcinoma (UC) patients were analyzed to correlate baseline immune phenotype to response. Methods: Pre-treatment TIL (CD8+ T cells/mm2 and %CD3+ by IHC; 29 MEL; 22 UC) were measured and divided into high and low groups based on median values. PD-L1 (% PD-L1 on tumor cells by IHC [28-8 PharmDx]; 33 MEL; 23 UC) was scored negative (<1%) or positive (≥1%). Interferon gamma gene score (IFNG; 11 MEL) was scored as high or low based on median p value of <0.1 for 15 genes (EdgeSeq). High and low groups were correlated with responses per RECIST 1.1. Results: Baseline demographics and prognostic factors were balanced in the biomarker subgroups. Response rates for response evaluable MEL and UC were 53% (SITC 2018) and 48% (ASCO-GU 2019), respectively. In MEL, median values of CD3-TIL and CD8-TIL were 19% and 203 cells/mm2, respectively. Response rate correlations were 67% and 20% with IFNG high and low, 79% and 29% with CD3-TIL high and low, 79% and 33% with CD8-TIL high and low, and 68% and 43% with PD-L1 positive and negative. Most importantly, responses were observed in patients with the least favorable tumor microenvironment, characterized as both PD-L1 negative and TIL low, with responses of 17% (1/6 CD8-TIL), and 25% (2/8 CD3-TIL), respectively. Similar correlative trends were observed in UC, with 50% (4/8 CD8-TIL) and 38% (3/8 CD3-TIL) responses in patients with least favorable microenvironment. Conclusions: The biomarker program included in PIVOT-02 identified baseline immune signatures correlated with response for MEL and UC. The response rates observed in both the favorable and unfavorable tumor microenvironments indicate the potential of this combination and support its broad development. Clinical trial information: NCT02983045.
Comparison between whole exome sequencing (WES) and single nucleotide polymorphism (SNP)-based tumor mutation burden analysis.
Authors: Timms Kirsten , Zharkikh Andrey , Perry Michael , Birkbak Nicolai , Szallasi Zoltan , Gutin Alexander , Richardson Andrea , Lanchbury Jerry 
Published: May 2019

2634 Background: Immune checkpoint inhibitors (ICI) block proteins which enable cancer cells to evade the immune system. Recent studies have shown that the higher the tumor mutation burden (TMB) the greater the likelihood of response to ICI therapy. Analysis of TMB has focused on WES of paired tumor and normal samples. This study tests the feasibility of measuring TMB from a SNP-based resequencing assay (myChoice HRD Plus). Methods: WES and myChoice HRD Plus were performed on matched tumor and normal DNA from 44 breast and 12 colon tumors. myChoice HRD Plus combines homologous recombination deficiency analysis with resequencing of 108 genes and microsatellite instability analysis. WES-based TMB was calculated by identifying all variants in paired samples, and subtracting germline variants. Two SNP-based TMB (SbTMB) methods were utilized to calculate TMB. The first used germline subtraction similar to the WES-based method. The second utilized an algorithm which removed background germline variants. Median sequence length to calculate TMB was 9.7 Mb for WES, 4.6 Mb for SbTMB (germline subtraction), and 1.9 Mb for SbTMB (algorithm). Results: Correlation coefficients for WES vs. SbTMB (germline subtraction) and SbTMB (algorithm) were 0.895 and 0.908, respectively. The two SbTMB methods had a correlation coefficient of 0.834. SbTMB measures of TMB were generally higher than WES-based TMB with a mean increase in score of 1.6 variants/Mb for SbTMB (germline subtraction; p = 4.6x10-6) and 1.5 variants/MB for SbTMB (algorithm; p = 1.2x10-5). No significant difference in magnitude of TMB score between the SbTMB measures was observed (0.04 variants/Mb; p = 0.88). Conclusions: SNP-based methods for calculating TMB produced highly concordant scores compared to WES-based methods. SbTMB assays produced elevated TMB scores, consistent with selective pressure against mutations in coding regions of genes, necessitating a higher score threshold for when using a SbTMB assay. This SbTMB analysis expands the utility of myChoice HRD Plus, and provides a method for calculation of TMB without sequencing a germline comparator.