bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 5086: Effects of immune negative genes on immunotherapy combined anti-vascular for liver cancer
Authors: Zhu Xinhua , Chen Yanan , Zhang Junling , Huang Mengli , Xia Xihua 
Published: June 2022

Abstract
Background: In recent years, the application of immune checkpoint inhibitors (ICIs) therapies targeting the programmed cell death-1 (PD-1)/programmed cell death ligand 1 (PD-L1) or cytotoxic T lymphocyte (CTLA-4) pathway represents a major breakthrough in many types of cancer. However, low response rates has limited the clinical application of ICIs monotherapy for liver cancer.Anti-vascular combined ICIs are the preferred regiments in first-line systemic treatment of hepatocellular carcinoma (HCC) by NCCN. Therefore, strategies to improve efficacy through patient stratification, biomarker-directed therapies or combinations remain urgently needed. The purpose of this study was to explore potential genomic markers associated with “low response rates” in liver cancer with ICIs combination therapy.
Methods: Between July 2019 and April 2021, a total of 47 patients with advanced liver cancer treated with ICIs combined anti-vascular or anti-vascular alone therapy were admitted to Drum Tower Hospital. We retrospectively identified genomic markers, abstracted clinicopathologic features and treatment outcomes.
Results: 47 patients with advanced liver cancer treated with immunotherapy combined anti-vascular or anti-vascular were included in this analysis. 40 of 47patients (85.1%) were male and the median age was 58 years (range, 32 to 80 years). Most patients (85.1%) were HCC and 12 patients had at least one immune negative gene mutation (including CCND1, FGF19, FGF3, FGF4, KEAP1, JAK1, MDM4, DNMT3A, EGFR and STK11). Median follow-up was 206 days in immunotherapy combined anti-vascular group and 215 days in anti-vascular group. In the immunotherapy combined anti-vascular group, compared with wild-type, patients with immune negative gene mutations were significantly associated with poorer overall survival (P=0.021). In anti-vascular alone group, there was no significant difference in median OS for patients with/without immune negative gene (P=0.94). In addition, patients with immune negative gene mutations, OS of anti-vascular alone was better than immunotherapy combined anti-vascular (P=0.085).
Conclusion: Our study revealed that liver cancer with immune negative gene mutations have a worse prognosis than wild-type patients on immunotherapy combined anti-vascular. In addition, in patients with immune negative gene mutations, immunotherapy combined anti-vascular did not significantly improve prognosis compared to anti-vascular alone.
Citation Format: Xinhua Zhu, Yanan Chen, Junling Zhang, Mengli Huang, Xihua Xia. Effects of immune negative genes on immunotherapy combined anti-vascular for liver cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5086.
Abstract 5087: KDR mutation as novel biomarker for immune checkpoint inhibitors in pan-cancer
Authors: Guo Renhua , Cui Yanan , Zhang Pengpeng , Liang Xiao , Xu Jiali , Liu Xinyin , Wu Yuemin , Wang Wei , Zhang Fang , Zhang Junling , Huang Mengli 
Published: June 2022

Abstract
Purpose: Immune Checkpoint Inhibitors (ICIs) have marked important milestones in cancer treatment, while few patients experience clinical benefits from them. Therefore, reliable predictive markers for ICIs are urgently needed. Nowadays, the combination of antiangiogenic therapy and ICIs exhibits encouraging efficacy. As a key protein of VEGFR signaling, KDR may also function to regulate immune responses beyond its role in angiogenesis.
Experimental Design: Pan-cancer immunotherapeutic patients from public cohorts including genomic data and clinical data were analyzed. Further analysis was performed on an internal validation data set including 67 non-small cell lung cancer (NSCLC). Investigation on underlying mechanism was performed in The Cancer Genome Atlas (TCGA) data via bioinformatics analysis.
Results: We found better responses to ICIs in patients who harbored KDR mutation from pan-cancer public datasets (discovery cohort: n=662; validation cohort: n=1333). Our NSCLC cohort verified the value of KDR mutation in predicting better ICI outcomes, including objective response rate (70.0% vs 22.81%, P=0.0057) and progression-free survival (HR=0.158, 95% CI, 0.045-0.773; P=0.007). KDR mutation was associated with increased TMB level, neoantigen burden, immune cellular activities, and decreased VEGFR signaling. Meanwhile, KDR mutation was indicative of an immune-hot status, characterized by higher expression of PD-L1 and abundance of cytotoxic lymphocytes.
Conclusions: Our work demonstrates that KDR mutation has the potential to become a predictive biomarker for ICIs.
Citation Format: Renhua Guo, Yanan Cui, Pengpeng Zhang, Xiao Liang, Jiali Xu, Xinyin Liu, Yuemin Wu, Wei Wang, Fang Zhang, Junling Zhang, Mengli Huang. KDR mutation as novel biomarker for immune checkpoint inhibitors in pan-cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5087.
Abstract 5096: Characteristics of tumor immune microenvironment in patients carrying comutations of DNA damage response pathways in esophageal cancer
Authors: Chen Hao , Xia Xihua , Zhang Junling , Chen Yanan , Huang Mengli 
Published: June 2022

Abstract
Background: Immunotherapy exhibits promising clinical efficacy in treating unresectable esophageal cancer, and several studies have demonstrated that both comutations in DNA damage response (DDR) pathways and tumor immune microenvironment(TIME) could serve as potential biomarkers for immune checkpoint blockade (ICB) treatment. However, the associtation between DDR comutations and TIME remains unclear.
Methods: Between April 2020 and September 2020, NGS and TIME analysis of tumor tissue from 22 patients with esophageal cancer were performed by 3D Medicines, Inc., a College of American Pathologists (CAP)-accredited and Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. We retrospectively investigated the association between genomic alterations and immune microenvironment features. Among eight DDR pathways, comutations of check point factors(CPF) plus base excision repair(BER), homologous recombination repair(HRR), mismatch repair(MMR) or Fanconi anemia(FA) were defined as "DDR co-mut+", while mutation of CPF or comutations of CPF plus nucleotide excision repair (NER) were defined as “DDR co-mut-”. In addition, the relationship between comutations of DDR pathways and tumor mutational burden (TMB) was also analyzed.
Results: 22 patients with esophageal cancer were included for analysis. 16 of 22 patients (72.7%) were male and the median age was 62 years old(range, 52 to 73 years). Based on the definition of DDR co-mut+ and DDR co-mut-, 13 patients were devided into DDR co-mut+ group, and 9 patients belonged to DDR co-mut- group. Gene alterations and TIME analysis revealed that patients with DDR co-mut+ showed a higher abundance of CD56dim natural killer cells in both tumor(p=0.0161) and stroma(p=0.028) compared with DDR co-mut- patients. No differences were observed in the densities of CD8+ T cells, M1-TAMs, and M2-TAMs between DDR co-mut+ and DDR co-mut- patients. TMB analysis displayed slightly higher in DDR co-mut+ group with no significant difference.
Conclusions: Patients with DDR co-mut+ showed better infiltration of CD56dim NK cells in tumor and stroma in esophageal cancer. Combination of DDR comutations with TIME features may be a more promising biomarker to guide immunotherapy.
Keywords: esophageal cancer; DNA damage response pathway; tumor immune microenvironment; tumor mutational burden
Citation Format: Hao Chen, Xihua Xia, Junling Zhang, Yanan Chen, Mengli Huang. Characteristics of tumor immune microenvironment in patients carrying comutations of DNA damage response pathways in esophageal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5096.
Abstract 5115: Combine high risk factors with circulating tumor DNA (ctDNA) to assist adjuvant chemotherapy (ACT) decision in Stage II colorectal cancer (CRC)
Authors: Yuan Xie Gui , Miao Liu , Li Huang Meng 
Published: June 2022

Abstract
Background: Approximately 10% to 15% have residual disease after surgery in patients with stage II CRC. Identification of this high-risk population and treatment with ACT could potentially reduce their risk of recurrence. However, the relative contribution of the factors used to define high risk stage II disease needs better understanding, although post-surgical ctDNA has been studied as a marker for an elevated risk of recurrence in stage I-III colorectal cancer.
Methods: Individual data from 3 early colorectal cancer clinical studies(Tie, 2016;Reinert, 2019; Chen, 2021) that included information on high-risk factors and post-surgical ctDNA status were collected and reanalysed for 595 patients with or without ACT.
Results: In stage II CRC patients with ctDNA-negative not treated with ACT form the Tie cohort, with high-risk status (n=42) showed a significantly reduced recurrence-free survival (RFS) compared to those with low-risk status(n=122) [HR, 3.283; 95%CI, 1.398 to 14.18; P = 0.0116], but in the ctDNA-negative patients with high-risk status, ACT (n=32) or not did not affect the RFS(P=0.1758). It meant false negatives of ctDNA made for bias of survival analysis results. Interestingly, in other two cohorts of stage II CRC patients with ctDNA-negative not treated with ACT, high-risk status showed no difference in RFS compared to low-risk status (p=0.3429 and 0.3173, respectively). In addition to the low sample size, the contribution of defined high-risk factors in prognosis was worth exploring which meant pseudo high-risk status also affect survival analysis results. And there were big differences in the high-risk factors included in the three cohorts especially in ctDNA-negative patients, such as the proportion of lymph nodes (LN) yield &lt;12 seemed higher in Tie cohort.
Conclutions: It was not enough to predict recurrence depend on ctDNA status alone for stage II CRC. Different risk factors might have different prognostic weights so that different combinations of post-surgical ctDNA status and risk factors might be used to make more accurate ACT decision.
Citation Format: Xie Gui Yuan, Liu Miao, Huang Meng Li. Combine high risk factors with circulating tumor DNA (ctDNA) to assist adjuvant chemotherapy (ACT) decision in Stage II colorectal cancer (CRC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5115.
Abstract 5119: Genomic landscape analysis in tumor tissue and circulating tumor DNA of Chinese patients with hepatocellular carcinoma
Authors: Yang Dinghua , Yu Sheng , Guo Baitang , Chen Tingting 
Published: June 2022

Abstract
Background: Hepatocellular carcinoma (HCC) is a leading cause of tumor-associated death worldwide, owing to its high 5-year postoperative recurrence rate and heterogeneity. Although Molecular profiling has been used to predict prognosis and guide targeted therapy, obtaining liver tissue biopsies was still a clinical challenge of advanced HCC patients. Circulating tumor DNA (ctDNA) testing as a novel and convenient detecting techniques, which can revealed comprehensive information regarding to tumor genome profiles. The purpose of the study was to analyze and compare the genomic landscape characteristics of tumor tissue and ctDNA in Chinese HCC.
Methods: 187 tumor tissue samples and 293 plasma samples from patients with HCC were collected from Nanfang hospital and 3DMed cohort, respectively. Next generation sequencing (NGS) assay (381/733 genes panel) was performed on tumor and plasma samples to capture tumor somatic single-nucleotide variants (SNVs). The gene variants information was summarized, analyzed and visualize using the maftools R package (Mayakonda et al. 2018.).
Results: In total, DNA alterations were detected in 93.86% (275/293) plasma samples and 90.91% (170/187) in tumor samples, which variant levels included pathogenic, likely pathogenic and variant of uncertain significance. The most commonly altered genes in ctDNA results were TP53 (52%), TERT (24%), LRP1B (22%), FAT1 (15%), CTNNB1 (14%). While in HCC tumor testing results were TP53 (55%), TERT (27%), CTNNB1 (17%), SPTA1 (14%) and ARID1A (12%). Both the most variant classification was missense, next were frameshift indel. Both the top five affected pathways were TP53, RTK-RAS, NOTCH, WNT and Cell Cycle. In WNT pathway related genes, the highest alteration frequency tumor oncogene was CTNNB1, and suppressor gene was APC. We analyzed mutually exclusive and co-occurring event on top 25 mutated genes. In ctDNA analysis results, the probability of co-mutation between LRP1B and KMT2A gene was the highest (p &lt; 0.001), while mutual exclusion between ARID1A and EGFR gene was the highest.
Conclusion: Circulating tumor DNA mutation detection in HCC is feasible in the absence of HCC tissue DNA. The analysis results revealed the genomic landscape characteristics of blood-derived ctDNA in HCC were consistent with tumor tissues, which can provided HCC potential prognosis and treatment related genes information to further study.
Citation Format: Dinghua Yang, Sheng Yu, Baitang Guo, Tingting Chen. Genomic landscape analysis in tumor tissue and circulating tumor DNA of Chinese patients with hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5119.
Abstract 5120: Deciphering melanoma CTC signatures leading to immune escape and brain metastasis: The first MRI CTC xenograft model
Authors: Bowley Tetiana , Marchetti Dario 
Published: June 2022

Abstract
Melanoma brain metastasis (MBM) is a devastating disease which is diagnosed in up to 60% of melanoma patients and 80% of patients at autopsy. While microarray studies identified many genes differentially expressed between MBM and extracranial metastasis, magnetic resonance imaging (MRI) is the established technology to evaluate clinical MBM. Circulating Tumor Cells (CTCs) are “seeds” of fatal metastasis and smallest functional units of cancer. Defining mechanisms which regulate the spatial and temporal competence of patient-isolated CTCs driving MBM thus presents the opportunity to suppress its occurrence. Hypothesis is that MRI has fundamental translational relevance to validate preclinical CTC models and that MBM onset depends upon the absence or presence of human immune system cells (Hu-mice), and mice gender and age. We isolated CTCs from blood of primary/metastatic melanoma patients, and confirmed CTC detection by CellSearch࣪, Parsortix࣪, high-definition microscopy and RNA-Seq profiling. Second, we injected melanoma CTCs in immunodeficient but also immunocompetent xenografts (NBSGW female/male mice generated by multiple donors CD34+ cells), and assessed tumor progression by IVIS and MRI with parallel monitoring of CTC gene-specific transcriptional activation. Third, we discovered specific differences in number of CTCs/CTC clustering patterns and CTC signatures which were dependent upon MBM status. Quantitation of melanoma CTC-derived signatures enabled serial noninvasive monitoring of tumor burden. Lastly, we found that these differences and the occurrence, severity and spatial distribution of MBM highly depended from gender, age, and immunocompetency status of injected animals. Thus, by reporting the first MRI CTC xenograft model, its use for melanoma CTC interrogation can provide a platform for early monitoring of response to immunotherapeutic and/or targeted interventions in melanoma, and contribute to rational therapy applications, notably for MBM prediction or prevention.
Citation Format: Tetiana Bowley, Dario Marchetti. Deciphering melanoma CTC signatures leading to immune escape and brain metastasis: The first MRI CTC xenograft model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5120.
Abstract 513: Radiomic profiles revealing targets for therapy in cervical cancer
Authors: Halle Mari Kyllesø , Hodneland Erlend , Hoivik Erling , Wagner-Larsen Kari , Lura Njål G. , Dybvik Julie , Forsse David , Bertelsen Bjørn I. , Krakstad Camilla , Haldorsen Ingfrid S. , Bozickovic Olivera , Woie Kathrine 
Published: June 2022

Abstract
Magnetic resonance imaging (MRI) has emerged as an important part of the diagnostic work-up in cervical cancer, with tumor volume and extent as important prognosticators. MRI radiomic tumor features may aid in prognostication and tailoring of treatment in cervical cancer. We extracted whole-volume radiomic texture features from 124 manually segmented tumors and performed unsupervised clustering yielding two distinct clusters. Overlapping clinicopathologic, genomic (whole exome sequencing, n=61), transcriptomic (L1000 arrays, n= 65) and molecular biomarker (n=82) data were applied to characterize the clusters. Independent of tumor size parameters, patients in cluster II had significantly reduced disease-specific survival as compared to those in cluster I (p&gt;0.001), also within squamous cell carcinomas (n=96, p&lt;0.001). Cluster II associated with high age (p=0.02), high FIGO-2009 stage (p&lt;0.001), high BMI (p=0.03) and PR negative tumors (p=0.004). Distinct mutational and copy-number profiles were detected for the two clusters. By gene set enrichment analyses, gene sets associated to immune activation were enriched in cluster I tumors, whilst gene sets associated with oxidative phosphorylation and epithelial to mesenchymal transition associated to cluster II tumors. This study links radiomic signatures to distinct genomic profiles that may potentially aid in prognostication and tailoring of treatments in cervical cancer patients.
Citation Format: Mari Kyllesø Halle, Erlend Hodneland, Erling Hoivik, Kari Wagner-Larsen, Njål G. Lura, Julie Dybvik, David Forsse, Bjørn I. Bertelsen, Camilla Krakstad, Ingfrid S. Haldorsen, Olivera Bozickovic, Kathrine Woie. Radiomic profiles revealing targets for therapy in cervical cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 513.
Abstract 5131: Deep learning-based tumor microenvironment cell types mapping from H&E images of lung adenocarcinoma using spatial transcriptomic data
Authors: Choi Hongyoon , Na Kwon Joong , Koh Jaemoon , Kim Young Tae 
Published: June 2022

Abstract
Purpose Spatial characterization of cell types of the tumor microenvironment (TME) is a key to finding new targets as well as developing biomarkers for immuno-oncology treatment. Here, we develop and validate a deep learning model trained by integrating H&E images of lung adenocarcinoma and spatial transcriptomic data to decipher spatial mapping of multiple cell types in TME only using H&E images.
Methods A total of 21 H&E images combined with spatial transcriptomic data of lung adenocarcinoma were used to develop a model. As each spot of spatial transcriptomic data consisted of a few cells, the cell types were inferred by CellDART, a domain adaptation-based method to estimating five cell types defined by single cell RNA-seq (scRNA-seq) data - B, T/NK, myeloid cells, fibroblasts, and epithelial cells. A convolutional neural network using H&E image patches as inputs was developed to predict the cell type scores for each corresponding spot. For the external validation, the model estimated the cell type scores from H&E-stained tissue image patches of lung adenocarcinoma of the Cancer Genome Atlas (TCGA-LUAD). Furthermore, the model inferred cell types from H&E images of lung adenocarcinoma tissues acquired by different patients and the results were compared with immunohistochemistry.
Results The cell types inferred by the model using H&E image patches were significantly correlated with those derived by spatial transcriptomic data as an internal validation. The mean value of the deep learning-based cell types scores estimated by the TCGA-LUAD tissue images was significantly correlated with the cell type scores estimated by bulk RNA-seq data of corresponding TCGA data. When cell type inference maps of independent lung adenocarcinoma H&E images were spatially co-registered with immunohistochemistry slides, including CD3, CD20, and CD68, pixel-wise correlation analysis revealed positive significant correlations.
Conclusions A deep learning model to infer spatial cell types of tumor microenvironment using H&E images was developed. The results of cell type scores were positively correlated with bulk RNA-seq-based immune cell enrichment scores and pixelwise analyses on immunohistochemistry images using typical cell type markers. This approach can provide objective and flexible deep learning-based models for characterizing tumor microenvironment.
Citation Format: Hongyoon Choi, Kwon Joong Na, Jaemoon Koh, Young Tae Kim. Deep learning-based tumor microenvironment cell types mapping from H&E images of lung adenocarcinoma using spatial transcriptomic data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5131.