bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using autoantibody signatures to predict immunotherapy discontinuation in melanoma patients.
Authors: Osman Iman , Giles Keith M. , Qian Yingzhi , Wind-Rotolo Megan , Loffredo John , Hulett Tyler , Weber Jeffrey S. , Zhong Hua 
Published: May 2020

3069 Background: Immune checkpoint inhibitors (ICIs), e.g., ipilimumab (IPI) and/or nivolumab (NIVO), produce durable survival benefit in a substantial proportion of melanoma patients but can also induce severe immune-related adverse events (irAEs) requiring treatment discontinuation. There is no biomarker to predict irAEs in ICI-treated melanoma patients. Given the similar clinical manifestation between irAEs and autoimmune disorders, we hypothesized that a subset of patients possess a subclinical baseline predisposition to developing irAEs that is characterized by specific autoantibodies (autoAbs). Methods: Pre-treatment melanoma patient sera from the CheckMate-238 Phase III trial of adjuvant IPI vs. NIVO were used for autoAb profiling with HuProt proteomic arrays (CDI Labs). The outcome of interest is to predict toxicity events that caused treatment discontinuation. For each treatment arm, we allocated patients to training and testing datasets in a 3:1 ratio. We calculated the area under the curve (AUC) of the receiver operating characteristic curve to select a probability threshold, which was applied to the testing dataset to assess accuracy, sensitivity, and specificity. Functional enrichment among autoAb protein targets was assessed using Metascape. Results: There were 707 irAEs among 597 patients (IPI = 423, NIVO = 174), of which 355 required treatment discontinuation (IPI = 287, NIVO = 68). In the training sets, we identified a 170 autoAbs signature consisting of 102 autoAbs for IPI treatment and 68 autoAbs for NIVO treatment. In the independent testing set, the signatures showed AUC of 0.85 (0.78, 0.92), 82% sensitivity, 78% specificity, and overall accuracy of 81% to predict IPI discontinuation, and AUC of 0.87 (0.74, 0.99), 75% sensitivity, 97% specificity, and overall accuracy of 88% to predict NIVO discontinuation. Enrichment of nuclear lumen-associated protein targets was identified among autoAb signatures that predict IPI or NIVO discontinuation. Conclusions: The identified signature within a large Phase III trial cohort highlights the potential utility of pre-treatment autoAbs for prediction of patients at high risk of developing irAEs in the adjuvant setting necessitating treatment termination. We are currently validating and refining toxicity-associated autoAb signatures with the goal of developing a Clinical Laboratory Improvement Amendments (CLIA)-certified assay to enable clinicians to optimize immunotherapy delivery and patient selection.
Influence of antibiotic therapy (ATB) on oncological outcomes of metastatic non-small cell lung cancer (mNSCLC) patients treated with chemo-immunotherapy (CIT).
Authors: Clark James , Ricciuti Biagio , Bolina Anita , Venkatraman Deepti , Newsom-Davis Thomas , Ottaviani Diego , Lee Karla , Awad Mark M. , Pinato David James 
Published: May 2020

3080 Background: ATB exposure is proven to worsen response and survival in immunotherapy recipients. However, its influence on outcomes from CIT is currently undefined. Methods: We conducted a retrospective, multi-centre observational study including 77 mNSCLC patients who received pembrolizumab, pemetrexed and carboplatin CIT as first-line therapy for mNSCLC, between December 1, 2018 and January 1, 2020 in 3 academic referral centres in Europe and in the United States. We documented ATB exposure in the 30 days prior to CIT commencement (pATB) or concurrently (cATB) until CIT cessation. Outcome measures included overall (OS) and progression-free survival (PFS) calculated from commencement of CIT, and overall response rates (ORR) defined by Response Evaluation Criteria in Solid Tumors (v1.1). Results: We enrolled 77 patients, 41 of whom were female (n = 53%) with adenocarcinoma (n = 73, 95%), performance status (PS) 0-1 (n = 69, 90%) PD-L1 Tumour Proportion Score < 50 (n = 57, 74%). Median OS was 16.4 months (95%CI 8.4-24.4), median PFS was 6.7 months (95%CI 5.7-7.6). ORR was 48% including 1 complete (1%) and 36 partial responses (47%). Eleven patients (14%) received pATB, with penicillin/cephalosporins (p/c, n = 7, 63%) for <7 days (n = 10, 90%). Thirty-five patients (45%) received cATB with p/c (n = 11, 40%) for <7 days (n = 28, 80%). Most common indication for ATB was peri-procedure prophylaxis in pATB (n = 7, 63%) and suspected febrile neutropenia in cATB (n = 14, 40%). pATB (p = 0.004) but not cATB (p = 0.85) predicted for worse OS (19.6 vs 6.5 months, Hazard Ratio [HR] 2.9 95%CI 1.3-6.3). Neither pATB nor cATB predicted for PFS or ORR (p > 0.05). Multivariable analyses confirmed pATB (HR 2.3 95%CI 1.1-5.5, p = 0.05) to predict for OS independent of PD-L1 status, PS and cATB. pATB+/- groups were balanced with regards to age, gender, PS nor PD-L1 status (p > 0.05). Conclusions: Whilst cATB does not compromise outcome from CIT, this study reproduces the detrimental effects observed for pATB exposure in immunotherapy recipients. Mechanistic verification of the immune-biologic foundations underlying this association is urgently warranted.
Targeting HER2 in combination with anti-PD-1 and chemotherapy confers a significant tumor shrinkage of gastric cancer: A multi-institutional phase Ib/II trial of first-line triplet regimen (pembrolizumab, trastuzumab, chemotherapy) for HER2-positive advanced gastric cancer (AGC).
Authors: Rha Sun Young , Lee Choong-Kun , Kim Hyo Song , Kang Beodeul , Jung Minkyu , Bae Woo Kyun , Koo Dong-Hoe , Shin Su-Jin , Jeung Hei-Cheul , Zang Dae Young , Chung Hyun Cheol 
Published: May 2020

3081 Background: Combining anti-PD-1 agent and trastuzumab has shown synergy in HER2 positive preclinical cancer models. We first report the result of a multi-institutional phase Ib/II trial of triple combination (pembrolizumab, trastuzumab, and chempotherapy) as first line therapy for HER2 positive AGC. (PANTHERA trial; NCT02901301). Methods: Pembrolizumab 200mg IV D1, Trastuzumab 6mg/kg (after 8mg/kg load) D1, Capecitabine 1000mg/m2 bid D1-14, and Cisplatin 80mg/m2 D1 every 3 weeks was selected as recommended phase II dose. The primary endpoint for phase II was ORR per RECIST v1.1. Secondary endpoints included PFS, OS, DoR, safety, and molecular analysis by targeted NGS. Results: Total of 43 patients were treated with median follow up of 16.1 months, and 11 pts remained on the treatment (treatment duration range: 1.4 to 24 months). There was significant tumor shrinkage of 95.3% with 54.6% median depth of response, with 76.7% ORR (CR 16.3%, PR 60.5%, conversion surgery 4.6%), and 97.7% DCR. Median PFS was 8.6 months (95% CI 7.2-22.0) and median OS was 18.4 months (95% CI 17.9-NA). Subsequent chemotherapy was given to 83.3% of 30 progressed pts. There were no MSI-H/dMMR or EBV-positive pts. PD-L1 status (57.1% of pts ≥ CPS 1 and 14.3% of pts ≥ CPS 10 among 35 pts), metastatic organ or baseline tumor burden was not related to the survival. Treatment-related AE (≥G3) occurred in 32 pts (74.4%) including 17 pts (39.5%) with neutropenia G3-4. Immune-related AEs (≥G3) occurred in 4 pts (10%). Ninety-six tumor tissues from 32 pts (paired tumor tissues from 25 pts) were analyzed with targeted NGS. TMB (median 12.7 mut/MB with range of 9.45-16.71) was not related to the PD-L1 expression or survival. Conclusions: First-line triplet regimen (Pembrolizumab, Trastuzumab, and Chemotherapy) confers a significant tumor shrinkage for HER2 positive AGC, regardless of PD-L1 status. Phase III Keynote-811 study (NCT03615326) is ongoing based on the protocol of this study. Clinical trial information: NCT02901301 . [Table: see text]
The spatial localization of CD163+ tumor-associated macrophages predicts prognosis and response to therapy in inflammatory breast cancer.
Authors: Van Berckelaer Christophe , Rypens Charlotte , Van Laere Steven , Marien Koen , Van Dam Pieter-Jan , Vermeulen Peter B. , Colpaert Cecile , Dirix Luc Yves , Kockx Mark , Van Dam Peter 
Published: May 2020

3086 Background: The mechanisms contributing to the aggressive biology of inflammatory breast cancer (IBC) are under investigation. A specific immune response seems to be an important driver, but the functional role of infiltrating immune cells in IBC remains unclear. Tumor-associated macrophages (TAMs) are associated with worse outcome, while CD8+ cytotoxic T cells demonstrate anti-tumor properties in breast cancer. In this study, we assessed spatial associations between CD163+ TAMs, CD8+ cells and cancer cells in IBC, using deep-learning and ecological statistics. Methods: We collected clinicopathological variables, evaluated PDL1-positivity (SP142, Ventana) and scored TILs according to the TIL working group guidelines on H&E slides for 144 IBC patients. Immunostainings for CD8 and CD163 (Hematoxylin-DAB) were done according to validated protocols. All slides were digitized, underwent virtual multiplexing and were evaluated in Visiopharm to quantify the number of DAB+ immune cells. Each immune cell was located using XY coordinates and spatial interactions were examined using a Morisita Horn Index (MHI). Tumor cell coordinates were collected using a deep-learning algorithm applied to the CD8-stained slide. This algorithm was trained in 18 images with more than 150.000 iterations (Deeplabv3+). Results: Complete pathological response (pCR) after neo-adjuvant chemotherapy was achieved by 30.6% (n= 30/98) of the patients with initially localized disease. Besides PDL1-postivity ( P= .03), infiltration with CD8+ T cells ( P= .02) and TAMs ( P= .01) also predicted pCR. However, a likelihood ratio test showed no difference between a model using CD8+ cells, TAMs or TILs. Interestingly, the colocalization of CD163+ and CD8+ cells (MHI >0.83) was associated with pCR (P= .01) and remained significant in a multivariate model (OR: 3.18; 95% CI: 1.04 – 10.6; P= .05) including TIL score, PDL1-positivity and hormone receptor (HR) status. Furthermore, a shorter disease-free survival (DFS) was associated with HR- status, no pCR and the colocalization of TAMs near tumor cells (HR: 3.3; 95% CI: 1.6 – 7.1; P= .002) in a multivariate model. The density of TAMs was not associated with outcome. Conclusions: The impact of TAMs on clinical outcome appears to depend on the spatial arrangement. The number of TAMs solely was not associated with outcome, but patients with more TAMs in proximity of the tumor cells had a worse DFS. Surprisingly, the clustering of TAMs near CD8+ cells was associated with pCR independent of the number of TAMs or TILs.
MR1 in combination with tumor mutational burden and PD-1/PD-L1 expression as a potentially novel clinical predictor for T cell exhaustion and immune checkpoint inhibitor response.
Authors: Farha Mark , Jairath Neil , El Naqa Issam , Spratt Daniel Eidelberg , Lawrence Theodore 
Published: May 2020

3109 Background: Immune checkpoint inhibitors (ICIs) restore T cell function by reversing T cell exhaustion. Variable response to ICIs warrants the development of precise predictive biomarkers, which is challenging due to difficulty in capturing the interplay of factors involved with tumor cell immune recognition. High intratumoral expression of MR1, the MHC-I related protein basally expressed on cancer cells, may drive T cell exhaustion through presentation of cancer-specific antigens. Here, we construct a database to study the relationship between MR1, tumor mutational burden (TMB), the PD-1/PD-L1 axis and T cell exhaustion across 8,975 sequenced tumors and 27 cancer types. Methods: RNA Seq by expectation maximization (RSEM) values from the TCGA were collected and normalized along with expression data for markers of interest (Table). TMB was defined as the number of non-synonymous somatic mutations per sample. For each cancer, 5 cohorts were created based on ascending mean expression levels of MR1, PD-1, PD-L1, and increasing TMB. For each cancer, an “immunogenicity score” for these factors was computed, and its relationship with T cell exhaustion signatures was assessed via linear regression. Data is presented as adjusted R2 and p-value. Results: While PD-1 and T cell exhaustion marker expression were correlated across cancers, the “immunogenicity score” (IS) correlated with exhaustion markers specifically in cancers with FDA-approved ICIs. Excluding MR1 from the score weakened the correlation with EOMES and TBET expression (Table). Each component of the score analyzed independently failed to show a statistically significant correlation for both EOMES and TBET expression. Conclusions: In this cross-cancer analysis, we support the hypothesis that presentation of metabolic intermediates in cancer cells via MR1 may drive T cell exhaustion. Also, the novel “immunogenicity score”, which incorporates MR1 into standard biomarkers for response to ICIs may convey the global picture of cancer cell recognition by the immune system and warrants further investigation as a tool for predicting clinical response. [Table: see text]
Association between immune and tumor gene signatures with response or resistance to tislelizumab monotherapy or in combination with chemotherapy in gastroesophageal adenocarcinoma.
Authors: Xu Jianming , Liu Tianshu , Lee Jong-Seok , Bai Yuxian , Chao Yee , Yang Silu , Zhang Yun , Ma Xiaopeng , Zhang Pei , Zheng Jianfei , Li Yanyan , Wang Jin , Shen Lin 
Published: May 2020

3115 Background: Tislelizumab, an anti-PD-1 monoclonal antibody, has demonstrated clinical benefit as a single agent and in combination with chemotherapy for patients (pts) with gastroesophageal adenocarcinoma (GEA), including gastric, gastroesophageal junction (G/GEJ), and esophageal adenocarcinoma (EAC). Immune- and tumor-transcriptomic features of response and resistance to tislelizumab were assessed from data collected in two monotherapy studies (NCT02407990, CTR20160872) and one tislelizumab plus chemotherapy study (NCT03469557). Methods: Gene expression profiling (GEP), using the 1392-gene HTG EdgeSeq panel, was performed on baseline tumor samples from 103 pts with GEA receiving monotherapy and 13 receiving combination therapy. Signature scores were calculated using the Gene Set Variation Analysis package with publicly available gene signatures (GS). Differential gene signature (DEG) analysis was performed between responders and nonresponders (NRs) using Wilcoxon rank-sum test; GS associated with survival were evaluated using Cox proportional hazards model. Results: Of the 76 pts with available GEP data, 64 (n=51 G/GEJ; n=13 EAC) had evaluable responses. Across these pts with GEA, tislelizumab demonstrated antitumor activity (Table). In pts treated with monotherapy, DEG showed IFNγ GS ( IFNG, CXCL9, CXCL10, HLA-DRA, IDO1, STAT1) scores were positively correlated with response ( P=0.03) as well as progression-free (HR=0.5, 95% CI: 0.27–0.93) and overall survival (HR=0.44, 95% CI: 0.21–0.89). Monotherapy NRs could be clustered into distinct GEP subgroups. Compared with responders, two NR subgroups had lower IFNγ GS ( P=0.002, 0.047) along with either higher epithelial-mesenchymal transition (EMT; P=0.027), and angiogenesis ( P=0.002) or cell cycle (CC; P=0.097) GS expression. A third NR subgroup showed higher CC GS scores compared with responders ( P=0.015), despite high IFNγ GS levels. Unlike tislelizumab monotherapy, responders to combination therapy showed higher CC GS expression versus NRs ( P=0.089). Conclusions: While higher IFNγ GS was associated with clinical benefit with monotherapy, elevated EMT/angiogenesis and CC GS levels may indicate resistance. The effects of these signatures in pts treated with combination therapy may vary. Both immune- and tumor-intrinsic factors may be considered for validation in a phase 3 study (NCT03777657). [Table: see text]
Validation of an immunomodulatory gene signature algorithm to predict response to neoadjuvant immunochemotherapy in patients with primary triple-negative breast cancer.
Authors: Iwase Toshiaki , Pusztai Lajos , Blenman Kim , Li Xiaotong , Seitz Robert , Nielsen Tyler J , Schweitzer Brock L , Hout David Richard , Bailey Dan B , Zhang Xiang , Shen Yichao , Ueno Naoto T. 
Published: May 2020

3117 Background: A 101-gene algorithm established as a molecular subtyping method for triple-negative breast cancer (TNBC) includes assignment of an immunomodulatory (IM) subtype based on genes active in immune cell processes. Recently, we isolated the IM concept to an independent 27-gene algorithm and its predictive ability for immunotherapy response was demonstrated in lung cancer. The objective of this study was to validate the predictive accuracy of the IM subtype as determined by the 27-gene algorithm for pathological complete response (pCR) compared with PD-L1 immunohistochemistry (IHC) staining in TNBC. Methods: We obtained RNA sequencing data from pretreatment core needle biopsies in 55 patients with stage I-III primary TNBC who received neoadjuvant immunotherapy (durvalumab with weekly nab-paclitaxel followed by ddAC) in phase I/II trial (NCT02489448). The 27-gene algorithm was used to determine IM positivity using a cutoff point previously validated from 71 lung cancer biopsy patients treated with immunotherapy. Results from the algorithm and PD-L1 IHC (antibody, SP263) were compared with pCR. Predictive accuracy of both methods was determined by diagnostic indicators. In cases positive for the IM subtype and pCR, we analyzed the immune microenvironment by deconvoluting the immune infiltration using a computational algorithm. Results: Of the 55 patients, 25 (45%) had pCR. Compared with previous subtyping methods, the 27-gene algorithm showed stronger predictive value (odds ratio, 4.125; 95% CI, 1.36-13.47; P < 0.015). For PD-L1 IHC, the odds ratio was 2.63 (95% CI, 0.82-9.21; P = 0.11). The positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio for PD-L1 IHC were 0.55, 0.68, 1.43, and 0.54, respectively. For the 27-gene algorithm, these metrics were 0.65, 0.69, 2.09, and 0.51, indicating its superior accuracy for predicting pCR. The computational algorithm showed that the IM subtype and pCR were negatively associated with a macrophage-enriched microenvironment. CD4+ T cells and dendritic cells were significantly increased among the baseline immune cell population in IM-positive patients. Conclusions: We conclude that 27-gene algorithm is a clinically applicable and a possible predictive marker for response to neoadjuvant immunochemotherapy for patients with primary TNBC. Our immune microenvironment results suggest that antigen-presenting immune cells have a crucial role in immunochemotherapy response.
Significance of meflin-positive cancer-associated fibroblasts in predicting response to immune checkpoint inhibitors in non-small cell lung cancer.
Authors: Miyai Yuki , Enomoto Atsushi , Ando Yuichi , Takahashi Masahide 
Published: May 2020

3118 Background: Tumor immunity is regulated by complex interactions between cancer and immune cells, which also involves other components of the tumor microenvironment (TME). Recently, cancer-associated fibroblasts (CAFs), a major constituent of the TME, have emerged as important regulators of tumor immunity. Specifically, for example, α-smooth muscle actin or leucine-rich repeat containing 15-positive CAFs have been shown to be crucial for the suppression of tumor immunity. However, a comprehensive picture of how other CAF subset(s) are involved in tumor immunity is still lacking. Here, we show the involvement of a CAF subset highly expressing Meflin, which was recently identified as a marker of cancer-restraining CAFs in pancreatic cancer (Mizutani et al., Cancer Res, 2019), in the response of non-small cell lung cancer (NSCLC) patients to immune checkpoint inhibitors (ICIs). Methods: A sample cohort of 122 subjects with NSCLC who had received ICI monotherapy with nivolumab, pembrolizumab, or atezolizumab was identified at the Department of Respiratory Medicine at Nagoya University Hospital. We selected 92 eligible patients, collected formalin-fixed paraffin-embedded tumor tissues, and prepared 4–µm-thick slides for the analysis of Meflin expression by RNA-in situ hybridization assay, followed by the evaluation of treatment response of 88 patients using the iRECIST criteria. We assessed the number of Meflin-positive CAFs and divided the patients into Meflin-High (20% and more CAFs express Meflin) and -Low groups. The cut-off value was obtained by the ROC analysis. Primarily, objective response rate (ORR) was compared between Meflin-High and –Low groups. Overall survival (OS), and progression free survival (PFS) were also assessed. Results: Patients who started to receive ICIs till the end of March 2019 were enrolled and followed-up until the end of 2019. Analysis of the tumor tissues revealed that 24 (40.7%) of 59 Meflin-High patients responded to the ICI monotherapy. In contrast, none (0%) of 29 Meflin-Low patients showed any significant response (p-value: 0.0000174). Meflin-High groups showed statistically significant prolongations in both OS and PFS with the hazard ratios of 0.3114 [0.1591-0.6094] and 0.3997 [0.2290-0.6976], respectively. Conclusions: This retrospective observation indicated that the high infiltration of Meflin-positive CAFs may shape tumor-suppressive immune response and increase the sensitivity to ICIs, which differs from those of other CAF subsets.