bluuebunny/crossref_metadata_2025_split huggingface dataset:
US oncologists' perception of the efficacy, safety, and willingness to prescribe biosimilar cancer therapies.
Authors: Galan Cesar , Johnson Kjel Andrew , Avalos-Reyes Elisea 
Published: May 2020

e15213 Background: Biosimilars are the fastest-growing class of therapeutic products in the United States and can offer treatment options that can potentially lower healthcare-related costs in cancer care. It is essential to know if an oncologist will use such products. Therefore, we assessed the expected biosimilar prescribing behaviors of practicing oncologists for the originator products Avastin, Herceptin, Rituxan and Neulasta. Methods: We conducted an online cross-sectional survey of 75 hospital affiliated (46.7%) and community-based (53.3%) oncologists in July 2019 and used a Likert scale rating of “Never,” “Seldom,” “Sometimes,” “Often” and Always.” Descriptive statistics and percentages are reported; the Chi-square test was used for between-group comparisons. Results: The majority of oncologists (62.7%) worked in a for-profit practice, with 38.7% of primary practices offering exclusive in-office dispensing. Physicians currently reported prescribing branded drugs often or always 76% of the time. When asked to rate biosimilars by quality, safety and effectiveness, over 70% of providers perceived these four biosimilars to be the same or near equivalent to the branded drug. When asked to report their expected likelihood of prescribing a biosimilar in the future, 60% of providers believed they would often or always prescribe a biosimilar. There was no difference in the providers’ current biosimilar prescription pattern by type of insurance plan. Provided financial equivalence, oncologists reported being more likely to prescribe a biosimilar to new patients (85.3%) compared to existing patients (69.3%) (p = 0.019). The top 3 drivers of using biosimilar cancer therapies are the patient’s out of pocket cost, value of reimbursement and cost to the practice; 61%, 51% and 52%, respectively for fee-for-service reimbursement and 69%, 44% and 61%, respectively for value-based reimbursement. When asked why providers would not switch from buy-and bill to white-bagging, control of the drug (41.3%) and financial benefit to the providers’ practice (40%) were the top 2 reasons. Conclusions: Biosimilars are expected to reduce drug expenditures in cancer care. While providers in this study found biosimilars to be safe and effective, they reported being less likely to prescribe these drugs when there is a potential for their practice to lose money and control of the drug. Payment models for biosimilars in cancer care must support practice economics.
Immunomagnetic separation in LAK generation in patients with breast cancer.
Authors: Shamova Tatiana V. , Kit Oleg I. , Sitkovskaya Anastasia O. , Zlatnik Elena Yu. , Bondarenko Elena S. , Novikova Inna A. , Vashchenko Larisa N. , Kechedzhieva Emma E. , Dashkova Irina R. , Ausheva Tatiana V. , Andreiko Elena , Saforyan Natalya S. , Vladimirova Liubov Yu , Lisutin Aleksandr E. 
Published: May 2020

e15220 Background: The purpose of the study was to evaluate the effect of IL-2 and INF-γ on the proliferation and phenotype of lymphocytes in patients with breast cancer (BC) after T-regs removal from the pool in vitro. Methods: Lymphocytes were isolated from the blood of 11 patients with stage II BC, T-regs were removed by immunomagnetic separation, and samples were cultured for 6 days with cytokines: IL-2 - 0.1/1 μg, INF-γ - 10 IU and their combinations. Results: The level of NK cells in the samples with IL-2 was maintained throughout the experiment, with IFN-γ - gradually decreased, and in the control (samples without stimulation) it decreased sharply. In experimental samples (IL-2, IL-2+IFN-γ), the amount of NKT remained at the initial level by day 6, and in the control it decreased by 2 times (p < 0.05). The number of CD335+ NK cells with high cytotoxicity against target cells increased after 3 days in the test samples with IL-2 by 5.2 times, and after 6 days - by 11.6 times in comparison with the control (p < 0.05). On day 6, the level of double-positive T cells increased by 1.8 times in co-culturing with IL-2+INF-γ (1 μg/10 IU), (p < 0.05). The percentage of double-negative T cells increased in the dynamics of cultivation from days 1 to 6, in some cases statistically significantly (IL-2 - 1 μg: by 2 times; IL-2+INF-γ - 0.1 μg/10 IU: by 1.8 times; p < 0.05). The percentage of CD4+CD38+ cells on day 6 of incubation with IL-2 at both doses increased by 1.8-2 times compared with the control, and CD8+CD38+ by 4-6 times. The percentage of CD4+HLA-DR+ cells after 6 days of cultivation with IL-2 increased by 6 times, and CD8+HLA-DR+ by 8-9 times. Cultivation with INF-γ reduced the stimulating effect, and in some cases it did not appear. The combined effect of IL-2 and INF-γ on day 6 led to an increase in the proportion of CD4+CD25+CD127dim cells by 1.8 times in comparison with the control (p < 0.05), and when exposed to INF-γ only, the number of these cells remained at the control levels. Conclusions: INF-γ is not an effective inducer of activation of immune effector cells, while the effect of IL-2, both alone and in combination with INF-γ, leads to a significant increase in the proportion of cytotoxic cells, as well as to activation of the T cell unit, including CD4 + CD25 + CD127dim.
Comparative assessment of different radiological criteria to identify paradoxical hyperprogression (HPD) to IO drugs.
Authors: Gomes de Morais Ana Luiza , Cardenas Jose M , de Miguel Luken Maria Jose , Boni Valentina , Moreno Irene , Ao Gerileto , Liu Run Han , de Hoyos Fernando Bergaz , Cubillo Antonio , Calvo Emiliano 
Published: May 2020

e15229 Background: HPD is a new pattern of response consisting of accelerated tumor growth due to immunotherapy (5%-20% of pts on IO drugs). The tumor growth rate (TGR, Champiat et al.) estimates the differential increase in tumor volume over time, pre- and on IO drugs, to assess for HPD, but it is not easily calculated in practice. A comparison of the different methods to identify HPD is missing. Methods: Retrospective study of 182 consecutive pts treated in Phase 1 studies of IO drugs at START Madrid-CIOCC in 2017-8, comparing 3 HPD measurement criteria (Champiat, Matos -which does not use pre-baseline CT scans-, and Saâda-Bouzid). Cohen’s Kappa index was calculated as a measure of the agreement between the 3 methods, being those values closer to 1 the more concordant ones. Overall survival (OS) rates were calculated by Kaplan-Meier (p < 0.05 to be significant). Results: 99 (54%) of 182 pts had progressive disease at cycle 1 of treatment and in 62 (34%) pre-baseline CT scans were available to calculate TGR. The Champiat method identified 18 (9.9%) pts with HPD. Of 61 cases validated to comparison, the Matos criteria labeled 27 pts (14.8% of 182) with HPD, of whom only 10 pts coincided with those identified by Champiat with a low agreement (Kappa: 0.140, p:0.251). No significant differences in OS between pts with non-HPD vs HPD by Matos criteria were seen (p = 0.16). With Saâda-Bouzid method, of 59 cases validated to comparison, 17 pts (9.3% of 182) were labeled with HPD and 13 of them coincided with those identified by Champiat method with a high agreement (Kappa:0.706, p:0.000). Differences in OS between non-HPD vs HPD pts were statistically significant (p = 0.038). Conclusions: HPD might have a detrimental effect to 10% of pts on IO drugs, also in our series. Every effort should be done to obtain pre-baseline CT scans to identify HPD response to IO drugs, based on differential TGR. The use of Saâda-Bouzid method is preferred due to its practical application and its correlation with survival. [Table: see text]
High correlation between TMB, expressed TMB, and neoantigen load using tumor: Normal whole exome DNA and matched whole transcriptome RNA sequencing.
Authors: Szeto Christopher , Gounder Mrinal M. , Parulkar Rahul , Nguyen Andrew , Rabizadeh Shahrooz , Reddy Sandeep K. 
Published: May 2020

e15238 Background: Tumor Mutation Burden (TMB) has emerged as a biomarker of response to immune checkpoint inhibitor therapy, independent of PDL1 expression. The optimal cutoff for high versus low TMB is unknown and neoantigen load has been proposed as an alternative biomarker. We have previously described neoantigen silencing at the RNA level as potential means of immune escape. We hypothesized that expressed TMB (eTMB) and neoantigen load would differ from TMB. Methods: Using data from matched tumor:normal DNA, whole exome sequencing at 150x average depth, and whole RNA transcriptome at ~200x106 reads per tumor from a commercial database of 1395 heterogeneous cancer patient samples, we measured TMB and eTMB ( > 2 alternate RNA reads supporting). Neoantigen load was measured as the count of unique 9mer peptides resulting from expressed somatic-specific variants with predicted binding affinity < 500nM by NetMHC. Results: High correlation between TMB and eTMB was seen (R2 = 0.94). No significant differences were seen between TMB, eTMB, and predicted neoantigen load. Using a cutoff of 200 non-synonymous variants (Rizvi 2015) to define TMB high versus highest quintile (TMB-20) (Samstein 2019) we saw high agreement of the 2 methods to assign TMB status as high v low. In the TMB-20 group with low TMB ( < 200), most often reclassified were soft tissue sarcoma (18%) and pancreatic cancers (17%). Conclusions: Surprisingly, eTMB, TMB-20, and neoantigen load showed no significant difference from TMB using 200 variants as a cutoff for high. Tissue-specific TMB may be useful in patient with Sarcoma and Pancreatic cancers. Additional data inputs such as microbiome, chemokine expression, and TME cell phenotyping may be required to improve upon TMB as a biomarker of immunotherapy response.
Cross-site concordance evaluation for the CIMAC-CIDC network to establish QC metrics enabling reliable generation of WES and RNA-seq data.
Authors: Wistuba Ignacio Ivan ,   CIMAC-CIDC Network
Published: May 2020

e15240 Background: Whole-exome sequencing (WES) and RNA-sequencing (RNA-seq) have become key components of cancer genomics, and analysis to provide comprehensive evaluation of spectrum somatic alterations and changes in gene expression present in cancer samples. To test the ability to generate comparable data for these genomic assays across CIMAC-affiliated sequencing centers, the CIDC performed a cross-site harmonization effort at two CIMAC sites (MD Anderson [MDACC] and DFCI/Broad Institute) and the MoCha Lab (MoCha) at the National Cancer Institute. Fresh frozen (FF) and FFPE samples from 8 non-small cell lung carcinoma (NSCLC) tumors were provided by MDACC, and processed for DNA and RNA extraction, aliquoted, and sent by MDACC to MoCha, MDACC and DFCI/Broad to be processed as replicates. Two reference samples,pools of 10 HapMap cell lines were sent for WES processing. Methods: WES analysis was carried out using center-specific pipelines as and central workflows that included: coverage metrics (target-based and genome-wide), variant calls (somatic and germline), variant annotations, tumor purity and clonality. Only minimal differences in somatic mutation calls were found between different replicates and centers for the HapMap samples, and technical differences were much smaller than biological differences between the patient tumors. For both sets of data, when focusing on reads at > 50X common coverage and events with variant allele frequency (VAF) > 5%, the different centers achieved high precision ( > 98%) and recall ( > 87%).Further, ISA for patient samples ranged from 0.667-0.875, while that for HapMap samples ranged from 0.817-0.827. Results: The RNA-seq analysis pipeline used the tools STAR for read mapping, RSEQC for quality control, SALMON for transcript quantification and LIMMA for batch removal on log transformed TPM values. Our analysis revealed that a DV200 of 24- 30% was a reasonable cutoff to achieve consistent quality in RNA-seq data generation. In addition, a medTIN cutoff value of 50% was found to be effective in determining the quality of the samples. Using these criteria, the Spearman correlation of log(TPM) among all the FF samples from the same tumor were higher than 0.976, and among all FFPE samples from the same tumor were higher than 0.942. Conclusions: In summary,cross-center concordance evaluation has identified the factors that introduce variability in the analyses, while also demonstrating the ability to provide comparable results across CIMAC sites by using a centralized analysis pipeline.
Analytical validation of iSort digital cytometry for leukocyte enumeration in clinical tumor specimens.
Authors: Newman Aaron M. , Nakao Aki , Li Kathy , Wilson Douglas Collins , Liu Chih-Long , Diehn Maximilian , Alizadeh Ash A. 
Published: May 2020

e15243 Background: Tumor infiltrating leukocytes (TILs) are major determinants of anti-tumor immune responses and mediate effector functions for diverse immunotherapies. Techniques relying on intact cells such as flow cytometry (FACS), immunohistochemistry (IHC), and scRNA-Seq can be powerful for measuring TIL heterogeneity. However, such methods are often impractical on large patient cohorts, can be poorly quantitative, and some cannot be applied to formalin-fixed paraffin embedded (FFPE) specimens. We developed iSort, a transcriptome deconvolution method based on CIBERSORTx for TIL enumeration. We evaluated iSort by comparing its performance in FFPE and fresh frozen (FF) human tumor tissues to established methods. Methods: We profiled human tumors for diverse TIL subsets, as quantified by iSort, FACS, and IHC. iSort was performed on RNA-Seq libraries derived from bulk human tumors, including FF tumor tissue samples, tumor cell suspensions obtained after dissociation, and FFPE specimens. We assessed the influence of tissue fixation on common TIL subsets enumerated by iSort, by comparing matched pairs of FF and FFPE lung tumor specimens (NSCLC). Finally, we compared iSort with automated microscopic enumeration of CD8 TILs by IHC on primary human lung tumors (FFPE/NSCLC). Results: iSort TIL enumeration was highly correlated with FACS across primary human tumors (CRC = 3, HNSCC = 1) for common TIL subsets (B cells, CD8 T, CD4 T, monocytes/macrophages, dendritic cells, PMNs/MDSCs) and total immune content (median r = 0.91 [0.71 - 0.99]). Tissue dissociation caused significant depletion of monocytes/macrophages (p < 0.01), when comparing bulk tumor specimens with cell suspensions after sample digestion. iSort showed high correlation across 12 TIL subsets when comparing 9 pairs of FF and FFPE specimens (r = 0.90). Finally, we observed high linearity between iSort and microscopic enumeration of CD8 TILs from IHC (r = 0.87, n = 5). Conclusions: iSort digital cytometry achieves accurate and robust TIL enumeration as compared with FACS and IHC, showing comparable performance in fixed and frozen primary human tumors. Importantly, iSort is directly applicable to bulk tumors and is unaffected by tissue dissociation artifacts, unlike methods requiring cell suspensions for TIL enumeration (FACS, scRNA-seq). Therefore, iSort is a promising approach for development and measurement of immunotherapy biomarkers.
A survey of cancer testis antigen (CTA) expression across T-cell lymphoma subtypes.
Authors: Ma Helen , Soderquist Craig R. , Marchi Enrica , Scotto Luigi , Bhagat Govind , O'Connor Owen A. 
Published: May 2020

e15246 Background: T-cell lymphomas (TCL) are a rare and heterogeneous group of non-Hodgkin lymphomas (NHL) that originate from T- and NK-cells and portends a poor prognosis. One promising therapeutic strategy involves generation of tumor associated antigen directed T-cells (TAA-T) against specific CTA. RNAseq have established that combinations of histone deacetylase inhibitors and hypomethylating agents uniquely induce genes characterized as cancer testes antigens (CTA), which may increase immunogenicity. There is a lack of data on the baseline expression of CTA across the TCL, limiting application of TAA-T. We sought to establish the baseline expression of CTA in PTCL using immunohistochemistry to better understand treatment effects. Methods: A tissue microarray was created using formalin-fixed paraffin embedded tissue from 40 patients with diverse T-cell neoplasms. Expression of WT1, SCP1, survivin, PLAC1, SSX2, and PRAME was evaluated by immunohistochemistry. The percentage of positive tumor cells (divided into quartiles), staining intensity (weak, moderate, strong), and subcellular localization (nuclear, cytoplasmic) was assessed. Results: Forty patients with T-cell lymphomas were included in the analysis. The median age of diagnosis and median number of treatments was 60.2 years and 2 (0-9), respectively. Thirty-nine (98%) patients expressed at least one CTA. A high frequency of survivin, which is associated with cell proliferation and is expressed on normal lymphoid tissue, was expressed in 98% of TCL, 5% expressed WT1, and 12.5% expressed SCP1, and expression of other CTA was not observed. Of five patients with anaplastic large cell lymphoma, 3 samples were positive for SCP1 and one was also positive for WT1. One of 9 angioimmunoblastic T-cell lymphoma samples was positive for SCP1. Of 4 T-lymphoblastic lymphoma patients, 1 was positive for WT1, and of 3 transformed mycosis fungoides specimens, 1 demonstrated SCP1 expression. In this sample set, we did not find a correlation with expression and response to chemotherapy. There were no patients with CTA expression who were treated with epigenetic treatments. Conclusions: We described low expression of CTA on T-cell lymphomas, which is consistent with the literature on expression by RT-PCR. By establishing this baseline expression of CTA, we have the foundation on which to measure changes in CTA expression pre- and post-treatment by immunohistochemistry.
Developing and validating an approach for diagnosing and prognosticating cancer from biochemical motifs in T-cell receptors.
Authors: Ostmeyer Jared L , Cowell Lindsay G , Christley Scott 
Published: May 2020

e15260 Background: Immune repertoire deep sequencing allows profiling T-cell populations and enables novel approaches to diagnose and prognosticate cancer by identifying T-cell receptor sequence patterns associated with clinical phenotypes and outcomes. Methods: Our goal is to develop a method to diagnose and prognosticate cancer using sequenced T-cell receptors. To determine how to profile the specificity of a T-cell receptor, we analyze 3D X-ray crystallographic structures of T-cell receptors bound to antigen. We observe a contiguous strip typically 4 amino acid residues in length from the complimentary determining region 3 (CDR3) lying in direct contact with the antigen. Based on this observation, we extract 4 residue long snippets from every receptor’s CDR3 and represent each snippet using biochemical features encoded by its amino acid sequence. The biochemical features are combined with information about the abundance of the snippet or the receptor and scored using a machine learning based approach. Each predictive model is fitted and validated under the requirement that at least one positively labelled snippet appears per tumor and no positively labelled snippets appear in healthy tissue. Results: Using a patient-holdout cross-validation, we fit predictive models to distinguish: 1. colorectal tumors from healthy tissue matched controls with 93% accuracy, 2. breast tumors from healthy tissue matched controls with 94% accuracy, 3. ovarian tumors from non-cancer patient ovarian tissue with 95% accuracy (80% accuracy on a blinded follow-up cohort) 4. and regression of preneoplastic cervical lesions over 1 year in advance with 96% accuracy. Conclusions: Immune repertoires can be used to diagnose and prognosticate cancer.
A comparative study of PD-L1 IHC assays using immune cell scoring and CPS in breast cancer.
Authors: Li Bin , Dillon Lloye M. , Jones Jennifer , Desai Keyur , Gold David , Pandya Dimple , Roberts Mustimbo 
Published: May 2020

e15262 Background: The clinical benefit of immune checkpoint inhibitors (ICIs) targeting the programmed death-1/programmed death ligand 1 (PD-L1) pathway has previously been demonstrated across a range of tumor types, including in PD-L1+ patients with metastatic triple-negative breast cancer (TNBC). Various PD-L1 immunohistochemistry (IHC) assays and scoring algorithms are being investigated to select patients with breast cancer (BC) most likely to respond to ICIs. Scoring algorithms include PD-L1 expression on tumor cells, immune cells (ICs), or both. We compared the analytical concordance of 3 PD-L1 IHC assays and evaluated PD-L1+ prevalence, using combined positive score (CPS) and % IC scoring algorithms in commercially procured TNBC and hormone receptor–positive, HER2-negative (HR+/HER2−) BC samples. Methods: PD-L1 expression was assessed by HistoGeneX (Naperville, IL) in 163 commercially procured, surgically resected, formalin-fixed, paraffin-embedded BC samples (mostly stage I–III) using the Ventana PD-L1 (SP142) and Dako PD-L1 IHC 28-8 and 22C3 pharmDx assays in conjunction with the CPS (28-8 and 22C3 assays) and % IC algorithms (SP142 and 28-8 assays). PD-L1+ prevalence with each assay and concordance between assays were calculated using CPS ≥ 1 and IC ≥ 1% cutoffs, with a single pathologist assigned to each scoring algorithm. Results: 93 HR+/HER2− BC and 70 TNBC samples were evaluable for PD-L1 expression across all assays and algorithms. Overall concordance was higher between the 28-8 and 22C3 assays (CPS cutoff of 1) than between the 28-8 and SP142 assays (IC cutoff of 1%). PD-L1+ prevalence was similar with the 28-8 and 22C3 assays (CPS ≥ 1) and higher with the 28-8 assay (IC ≥ 1%) than with the SP142 assay (IC ≥ 1%). PD-L1+ samples identified by the SP142 assay (IC ≥ 1%) were mostly included within PD-L1+ sample sets defined by the 28-8 assay (IC ≥ 1% and CPS ≥ 1). PD-L1+ prevalence was higher in TNBC vs HR+/HER2− BC for all assays (Table). No clear trend in PD-L1+ prevalence was observed across tumor grade and stage. Conclusions: High analytical concordance was observed between the 28-8 and 22C3 assays (CPS cutoff of 1) in both HR+/HER2− BC and TNBC samples. PD-L1+ prevalence varied according to IHC assay, scoring algorithm, and cutoff used. Further studies are needed to select the most appropriate PD-L1 assay and scoring algorithm for BC clinical trials. [Table: see text]