bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 2091: DeepBTS: Prediction of recurrence-free survival of non-small cell lung cancer using time-binned deep neural network
Authors: An Ho Jung , Lee Bora , Chun Sang Hoon , Hong Ji Hyung , Woo In Sook , Kim Seoree , Jeong Joon Won , Kim Jae Jun , Lee Hyun Woo , Park Sungsoo , Jo Heejoon , Ko Yoon Ho
Published: September 2020

Introduction: Accurate prediction of non-small cell lung cancer (NSCLC) prognosis after surgery is still challenging. Cox proportional hazard model is widely used, but there are some limitations like proportional hazard assumption, computational complexity, and unspecified time component. In this study, we developed the novel neural network models using 30 clinicopathological features of surgically resected NSCLC patients.

Materials and Methods: We analyzed a dataset of training cohorts of 1,034 patients and external validation cohort of 303 patients, and compared the novel neural network model and Cox PH model to predict 3-year recurrence of the patient.

Results: We developed deep neural network for binned time survival analysis (DeepBTS) algorithm, which use root-mean-squared error (supervised learning model, s- DeepBTS) or negative log-likelihood (semi-unsupervised learning model, su- DeepBTS) as loss function. The su-DeepBTS algorithm showed the improved performance (C-index, 0.7166; AUC, 0.7606) compared to other models (Cox PH: 0.6861 and 0.7185; s-DeepBTS: 0.6926 and 0.7250, respectively). Top 10 features was selected from su-DeepBTS model and su-DeepBTS selector pair: the number of lymph node metastasis, tumor size, histologic subtype, vascular invasion, R0 resection, neoadjuvant /adjuvant treatment, and performance status of patients. These features distinguished low and high-risk group in the training cohort (p = 4.25×10-5) and the validation cohort (p = 1.07×10-11).

Conclusions: The su-DeepBTS model using 10 selected features can predict the prognosis of resected NSCLC patients. We plan to diversify the input features by radiologic, pathological imaging and genomic data to integrate multimodal medical information and enhance the performance of this model using deep neural network.

Citation Format: Ho Jung An, Bora Lee, Sang Hoon Chun, Ji Hyung Hong, In Sook Woo, Seoree Kim, Joon Won Jeong, Jae Jun Kim, Hyun Woo Lee, Sungsoo Park, Heejoon Jo, Yoon Ho Ko. DeepBTS: Prediction of recurrence-free survival of non-small cell lung cancer using time-binned deep neural network [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2091.
Abstract 2102: Interpretable machine learning for perturbation biology
Authors: Shen Judy , Yuan Bo , Luna Augustin , Korkut Anil , Marks Debora , Ingraham John , Sander Chris
Published: September 2020

Systematic perturbation of cells followed by comprehensive measurements of molecular and phenotypic responses provides an informative data resource for constructing computational models of cell biology. Models that generalize well beyond training data can be used to identify combinatorial perturbations of potential therapeutic interest. Major challenges for machine learning on large biological datasets are to find global optima in an enormously complex multi-dimensional solution space and to mechanistically interpret the solutions. To address these challenges, we introduce a hybrid approach that combines explicit mathematical models of dynamic cell biological processes with a machine learning framework, implemented in Tensorflow. We tested the modeling framework on a perturbation-response dataset for a melanoma cell line after drug treatments. The models can be efficiently trained to accurately describe cellular behavior, as tested by cross-validation. Even though completely data-driven and independent of prior knowledge, the resulting de novo network models recapitulate known interactions. The main predictive application of our work is the identification of combinatorial candidates for cancer therapy. This approach is readily applicable to a wide range of kinetic models of cell biology.

Citation Format: Judy Shen, Bo Yuan, Augustin Luna, Anil Korkut, Debora Marks, John Ingraham, Chris Sander. Interpretable machine learning for perturbation biology [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2102.
Abstract 2107: Seeing glycolysis on PDAC: Applying deep learning convolutional neural network model
Authors: Tsou Peiling , Wu Chang-Jiun
Published: September 2020

The reprogramming of cellular metabolism to support continuous proliferation is a hallmark of cancer. Accumulating evidence indicates that the reprogramming of tumor metabolism is under the control of various oncogenic signals. The Kras oncogene is known to induce aerobic glycolysis, and pancreatic adenocarcinoma (PDAC) cells have been shown previously to have metabolism consistent with elevated aerobic glycolysis. Several glycolytic inhibitors are currently in preclinical and clinical development. It had been reported that cancer metabolic status could play a role in the interaction with tumor microenvironment. We hypothesized that cancer glycolysis activity could affect tumor-stromal interaction in PDAC. As a proof-of-concept study, we trained a deep learning convolutional neural network (CNN) model (Google Inception v3) on histopathologic images obtained from The Cancer Genome Atlas (TCGA) PDAC cohort to classify tumors with high and low glycolysis pathway activity. We aimed to answer whether CNNs can predict PDAC glycolysis status using images as the only input. The accuracy on independent validation set is 77.4% with area under ROC curve as 0.698 (Pearson correlation=0.418, p=0.026). Survival analysis showed that higher glycolysis activity was associated with worse clinical outcome in TCGA PDAC. The current study demonstrates the potential of deep learning approaches for histopathologically classifying cancer based on metabolic status. This information could be of value in assisting clinical decisions on targeting cancer metabolism.

Citation Format: Peiling Tsou, Chang-Jiun Wu. Seeing glycolysis on PDAC: Applying deep learning convolutional neural network model [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2107.
Abstract 2108: Application of random forest machine learning techniques on mixed data from breast cancer studies
Authors: Quist Jelmar , Taylor Lawson , Staaf Johan , Grigoriadis Anita
Published: September 2020

Integrative analysis of diverse high-dimensional molecular, histopathological and clinical data provides an effective way to identify biologically and clinically relevant subclasses across multi-level data. However, unbiased integrative methods to identify distinctive features and group structure in such data remains problematic. We propose a machine learning clustering technique based on random forest methods that enables unbiased integration. Using a permutation-based framework for the tree construction procedure and measuring of feature importance, robust and pure clusters can be produced. The performance of standard, regularised, and conditional inference random forest methods was evaluated using the adjusted Rand index, the Calinski-Harabasz index, and cluster and feature purity. In simulations studies, random forest clustering techniques were able to identify clusters of high purity. Using datasets from the UCI Machine Learning Repository as a proof of concept, all three techniques were able to identify clusters in mixed data, whereby the conditional inference method produced clusters with the highest feature purity. Next, we applied our clustering techniques to high-dimensional data obtained from two independent breast cancer studies: (i) International Cancer Genome Consortium (ICGC), consisting of 560 cases and 147 features, and (ii) Sweden Cancerome Analysis Network - Breast (SCAN-B), incorporating 241 cases and 53 features. Features included rearrangement and mutational signatures, somatic mutation in cancer drivers, germline mutations in BRCA1/2, genomic instability measures, intrinsic molecular breast cancer subtypes, and clinico-pathological characteristics. Despite dissimilarities in the breast cancer subtype composition between these two datasets, the conditional inference random forest method was able to identify concordant subgroups between the studies supported by molecular and histopathological characteristics. Moreover, novel relationships amongst molecular features with potential clinical relevance were revealed. For example, one cluster was enriched for BRCA2-deficient breast cancer cases with MYC amplifications, while another predominantly consisted of non-basal-like triple-negative breast cancers with PIK3CA mutations. Together, these results support the use of our machine learning clustering technique based on random forest methods to identify robust and biologically relevant group structures using complex high-dimensional mixed data.

Citation Format: Jelmar Quist, Lawson Taylor, Johan Staaf, Anita Grigoriadis. Application of random forest machine learning techniques on mixed data from breast cancer studies [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2108.
Abstract 2129: Proteogenomic analysis points to relationship between LINE-1 retrotransposon expression and copy number variation
Authors: McKerrow Wilson H. , Wang Xuya , Grivainis Mark , Fenyö David
Published: September 2020

Changes in the DNA copy number of genes (copy number variation/CNV) are widespread in many cancers and affect the expression of tumor suppressors and oncogenes. Many of these CNVs arise from chromosomal aberrations that are the result of improperly repaired DNA damage. LINE-1 retrotransposons - genomic elements that cut DNA and then reverse transcribe themselves into the gap - are expressed in many cancers and likely contribute to DNA damage and CNV in cancer cells. Using multi-omic data from CPTAC, we developed cloud-based tools on the NCI funded Cancer Genomics Cloud to measure LINE-1 RNA, protein, phosphoprotein and insertion in five cancer types - breast, ovarian, endometrial, kidney and colon - and identified mutation, expression and phosphorylation correlates of LINE-1 expression. We found significant LINE-1 expression in all, but kidney cancer. LINE-1 expression was significantly correlated with global copy number variation in breast, endometrial and ovarian cancer, a trend that was reflected in the fact that we observed the highest LINE-1 expression in ovarian cancer, which is characterized by very high CNV, and the lowest LINE-1 expression in kidney cancer, which has less overall CNV. This correlation is mirrored in our finding that, in breast, ovarian and endometrial cancer, p53 mutants express more LINE-1, indicating that high LINE-1 expression occurs in a background that is tolerant of DNA damage and CNV. We also observed an association between LINE-1 expression and phosphorylation of 53BP1 in breast, colon and endometrial cancers. ATM phosphorylated 53BP1 localizes to double strand breaks and promotes repair by non-homologous end-joining (NHEJ). Taken together, this analysis supports the hypothesis that in many cancers LINE-1 contributes to DNA damage and copy number variation, perhaps involving mismatched repair by NHEJ.

Funded by NCI Contract No. HHSN261200800001E

Citation Format: Wilson H. McKerrow, Xuya Wang, Mark Grivainis, David Fenyö. Proteogenomic analysis points to relationship between LINE-1 retrotransposon expression and copy number variation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2129.
Abstract 2130: Human papillomavirus and hepatitis B virus in situ tumor oncoviral genotype and coinfection drive oncogenesis and patient clinical response in cross cancer analysis
Authors: Bubie Adrian P. , Testoni Barbara , Zoulim Fabien , Miles Brett , Posner Marshall , Villanueva Augusto , Losic Bojan
Published: September 2020

Genotype of hepatitis B virus (HBV) and human papillomavirus (HPV) infection is well known as a significant risk factor in developing liver (HCC), cervical, and head and neck cancers. However, the effect of tumor viral genotype and single-virus coinfection in driving oncogenesis and striating patient survival is generally unclear, as previous studies have not exhaustively genotyped viral-cofactors or profiled viral gene expression in tumors. In this work, we develop and deploy a new scalable, high throughput dynamic sequence alignment tool that facilitates extremely sensitive and precise oncoviral genotype deconvolution using tumor RNA sequencing data from 536 virally infected liver, cervical, and head and neck tumors across several cohorts. Pairing these results with tumor gene expression and survival analyses, we find HBV genotype C (HBV-C) associated HCC patients (n=79) are significantly upregulated in cancer proliferation and decreased cancer survival (FDR<0.01) compared to HBV genotype B associated tumors (n=23). Across 3 liver cancer cohorts, oncogenes TERT, MLL4, and FN1 are found recurrently integrated in HBV-C but not HBV-B. HPV clade a9 infected cervical cancers (n=173) are associated with more aggressive tumor growth and worse survival than HPV clade a7 (n=39) infected tumors (FDR<0.01), and are enriched in COSMIC mutational signatures linked with defective DNA repair and hypermutation. Furthermore, we demonstrate that HPV coinfection may drive patient response as neoantigens from cervical tumors with multiple HPV infections (n=18) are more immunogenic on average than single-infection tumors (n=23), controlling for HPV genotype (p<0.001). Finally, we compare HPV gene expression in cervical and head and neck patients, demonstrating that HPV genotype drives viral gene expression over cancer type (p<0.0001), and indicating viral protein expression may be similar across episomal and integration-based infections. Our results illustrate that HBV and HPV genotype, and coinfection of tumor with multiple genotypes, serve as significant predictors of patient survival and tumor immune responsiveness, and should be considered alongside clinical covariates to improve survival and treatment models.

Citation Format: Adrian P. Bubie, Barbara Testoni, Fabien Zoulim, Brett Miles, Marshall Posner, Augusto Villanueva, Bojan Losic. Human papillomavirus and hepatitis B virus in situ tumor oncoviral genotype and coinfection drive oncogenesis and patient clinical response in cross cancer analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2130.
Abstract 2136: RegTools: Integrative analysis of genomic and transcriptomic data to identify splice altering mutations across 35 cancer types
Authors: Cotto Kelsy C. , Feng Yang-Yang , Skidmore Zachary L. , Ramu Avinash , Kunisaki Jason , Conrad Donald F. , Lin Yiing , Chapman William , Uppaluri Ravindra , Govindan Ramaswamy , Griffith Obi L. , Griffith Malachi
Published: September 2020

The interpretation of variants in cancer is often focused on genomic alterations that have a known coding consequence. This analysis strategy excludes somatic mutations in non-coding regions of the genome and even exonic mutations may have unidentified non-coding consequences. To address this issue, we created RegTools, a free, open-source software package that integrates analysis of variant calls from genomic data with evidence of expressed splice junctions from transcriptomic data to efficiently identify variants that may cause aberrant splicing in tumors. To date, we have applied RegTools to over 9,000 samples from TCGA and the McDonnell Genome Institute in an effort to identify somatic variants that are associated with alternative splicing patterns within these tumors. For each mutation, we defined a set of control samples in the same cancer cohort that lacked the particular mutation. We then determined putative splicing-relevant mutations by identifying novel splice isoforms whose expression was significantly elevated in the presence of the associated mutation. To further characterize these somatic variants and their associated splice isoforms, we annotated them with the Variant Effect Predictor (VEP), SpliceAI, and Genotype-Tissue Expression (GTEx) junction counts. While some of these mutations would have been predicted by VEP or SpliceAI to be splicing relevant, our analysis provides additional detail by specifically associating a mutation with an altered junction or junctions, including ones not predicted by VEP/SpliceAI or observed within GTEx normal tissue data. RegTools is freely available and open source (www.regtools.org) and all analysis scripts are provided within the project's GitHub repo (https://github.com/griffithlab/regtools).

Citation Format: Kelsy C. Cotto, Yang-Yang Feng, Zachary L. Skidmore, Avinash Ramu, Jason Kunisaki, Donald F. Conrad, Yiing Lin, William Chapman, Ravindra Uppaluri, Ramaswamy Govindan, Obi L. Griffith, Malachi Griffith. RegTools: Integrative analysis of genomic and transcriptomic data to identify splice altering mutations across 35 cancer types [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2136.
Abstract 2152: Characterisation of co-expression of CD39 with other IO-relevant markers on major T/NK cell TIL subsets
Authors: Hair Jim , Luheshi Nadia , Dovedi Simon J. , Wilkinson Robert W.
Published: September 2020

CD39 has recently been identified as critically differentiating tumour-reactive from bystander tumour-infiltrating leukocyte (TIL) CD8+ T cells. CD39 is an ectonucleotidase that degrades immunostimulatory ATP to ADP and AMP. CD73 then further metabolises AMP to generate immunosuppressive adenosine in the tumor microenvironment. To facilitate our understanding of CD39 as a therapeutic target we established a detailed receptor co-expression profile for CD39 with other immuno-oncology (IO)-relevant targets on TIL T/NK cells. TIL samples from three diseases (NSCLC, Renal cancer [RC] and Melanoma) were profiled, via the creation and use of a single large flow cytometry panel, combined with computational analysis.

Unbiased clustering identified the expected major T and NK cell populations, however one of the most striking findings was that CD39 was highly differentially expressed across the different cell subsets. Almost all TREG cells were CD39 positive, whereas CD8+ T cells and NK cells were highly variable in their degree of expression of CD39. CD4+CD8+ T cells predominantly did not express cell surface CD39 and only very few CD4+ TCONV cells expressed CD39.

The co-expression profile for TREG, TCONV and NK cells is presented, but we have also defined a detailed phenotype of the critical tumour-specific CD39+CD8+ T cell population. Our analyses show that CD39+CD8+ T cells express more markers associated with antigen-experienced T cells versus CD39-CD8+ T cells; a significantly greater proportion of CD39+CD8+ T cells expressed TIM3, CTLA-4, PD-1, TIGIT, CD137 and GITR versus CD39-CD8+ T cells. Significantly fewer CD39+CD8+ T cells than CD39-CD8+ T cells expressed CD28, a receptor known to be downregulated on antigen-experienced cytotoxic CD8+ T cells.

These data reveal the detailed co-expression patterns of key IO-relevant receptors across TIL T and NK cell subsets and are consistent with recent reports identifying CD39 as a key marker differentiating the critical tumor-specific, antigen-experienced tumor infiltrating CD8+ T cells.

Citation Format: Jim Hair, Nadia Luheshi, Simon J. Dovedi, Robert W. Wilkinson. Characterisation of co-expression of CD39 with other IO-relevant markers on major T/NK cell TIL subsets [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2152.
Abstract 2168: A growth rate corrected metric for cytotoxic co-culture systems
Authors: Melms Johannes Christian , Yapp Clarence , Mills Caitlin Elizabeth , Sorger Peter , Izar Benjamin
Published: September 2020

Tumor/T-cell co-cultures in combination with large-scale genome-editing tools emerged as powerful tools for discovery of drivers of resistance to immunotherapies. Traditionally, chromium or lactate-dehydrogenase release and/or target cell viability counts before and after co-culture treatment are used as surrogate endpoint assays to estimate the selection pressure applied. These assays cannot dissect growth arrest, cell death, cell viability and target cell outgrowth, all of which occur as a consequence of released cytokines and direct tumor/T-cell interactions, hence, significantly impact the interpretation of small- and large-scale screens in co-culture models. These biases are particularly relevant when comparing cell lines or genotypes with different growth kinetics. Here, we use a dual reporter system and adopt pharmaco-mathematical principles to dissect these biases to create a growth-rate corrected co-culture metric (GRC), which normalizes T-cell mediated antiproliferative and cytotoxic effects in tumor target cells. We illustrate the value of this metric by comparing fast and slow-growing tumor cells in autologous patient-derived melanoma/T-cell co-culture pairs. At tumor-T-cell ratios resulting in a half maximal relative reduction of target cell counts compared to controls, the fast-proliferating cell line had not changed in absolute cell counts since baseline while the slow-growing cell line showed a 50% reduction. This indicates that in one instance (fast growing cell line) growth-retardation occurred due to a balance of immune editing and target cell proliferation, while in the other (slow-growing cell line) T-cell mediated killing resulted in net loss of tumor cells. Using GRC, these differences can be readily distinguished, and comparable selection conditions can be selected. This has important implications for large-scale screens with perturbations within cancer cells: drop-outs from a screen in the fast-growing cell line would not only contain perturbations that increase specific sensitivity to T-cell mediated cytotoxicity, but also perturbations causing a general loss in proliferation/survival fitness. In addition, some of the discrepancy in recently published screens may be explained by differences in models with varying proliferation rates and therefore selection conditions. In summary, the GRC metric enhances the interpretation of co-culture experiments and could contribute to improved selection of targets from large-scale screens investigating resistance to T-cell mediated toxicity for drug development.

Citation Format: Johannes Christian Melms, Clarence Yapp, Caitlin Elizabeth Mills, Peter Sorger, Benjamin Izar. A growth rate corrected metric for cytotoxic co-culture systems [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2168.
Abstract 2189: Generating Merkel cell polyomavirus-specific T cells from healthy donors for adoptive immunotherapy
Authors: Davies Sarah , Barrett John , Muranski Pawel J. , Brownell Isaac
Published: September 2020

Merkel Cell Carcinoma (MCC) is an aggressive neuroendocrine skin cancer that is highly immunogenic. Approximately 80% of MCC tumors are virus positive (VP-MCC) and express Merkel cell polyomavirus (MCPyV) T antigens that drive oncogenesis. As VP-MCC have a low mutation burden with few predicted neoantigens, viral oncogenes are thought to be primary targets for anti-cancer immunity. Immune checkpoint inhibitors improve MCC survival, yet not all patients have durable responses. VP-MCC patients who fail checkpoint inhibition or who have immune dysfunction may benefit from adoptive cellular therapy using virus-specific T cells from HLA-matched donors. As the risk of graft versus host disease is low with virus-specific T cells, this approach is being investigated for other viral diseases. We set out to generate MCPyV-specific T cells from healthy donors for potential adoptive immunotherapy. Naïve and memory T cells from donors were magnetically isolated prior to stimulation with autologous monocyte-derived dendritic cells pulsed with 15-mer overlapping peptide libraries of MCPyV T antigens. T cells were serially re-stimulated with peptide-pulsed irradiated, autologous PHA-blasts up to five times. Cultures were maintained in either standard growth cytokines (IL-2, IL-7, and IL-15) or a pro-inflammatory cytokine cocktail. T cell phenotype and reactivity were evaluated by flow cytometry. We found that standard cytokine conditions were unable to promote growth of MCPyV-specific mature T cells. Altering growth conditions to include a cocktail of pro-inflammatory cytokines promoted expansion of polyfunctional Th1 CD4+ T cells specific for MCPyV T antigen peptides. These cells produced TNFα and upregulated the activation markers CD154 and CD137 upon cognate antigen exposure. Cells were generated without bias for particular HLAs. These results suggest that peptide-based expansions may be a suitable platform to generate allogeneic adoptive T cell immunotherapies for patients with VP-MCC.

Citation Format: Sarah Davies, John Barrett, Pawel J. Muranski, Isaac Brownell. Generating Merkel cell polyomavirus-specific T cells from healthy donors for adoptive immunotherapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2189.
Abstract 2219: OnxoVEXmGM-CSF promotes systemic response to PD-L1 /PD-1 blockade in multiple mouse syngeneic tumor models
Authors: Cooke Keegan , Estrada Juan , Mitchell Petia , Zhan Jinghiu , Beltran Pedro J. , Qing Jing , Canon Jude
Published: September 2020

Inhibition of the immune-checkpoint axis that involves PD-L1/PD-1 has improved responses and outcomes for certain cancer patients, but there remains unmet need as only a fraction of patients respond to these therapies. Talimogene laherparepvec (T-VEC) is an FDA-approved, first-in-class oncolytic immunotherapy based on a modified herpes simplex virus type 1 (HSV-1) designed to selectively replicate in tumors and produce granulocyte-macrophage stimulating factor (GM-CSF) to enhance a tumor-antigen specific adaptive immune response. Intratumoral treatment with T-VEC has been shown to promote an inflammatory tumor microenvironment both preclinically and clinically. Combining T-VEC with immune checkpoint inhibitors is of high interest to potentially broaden and deepen the clinical responses in checkpoint-resistant tumors. In the current study, we evaluated the efficacy of OncoVEXmGM-CSF (an HSV modified like T-VEC, except that it produces murine GM-CSF) in combination with anti-PD-1/PD-L1 treatment in multiple syngeneic mouse tumor models. Bilateral tumor models were used, where only one tumor was treated with OncoVEXmGM-CSF (representing the local oncolytic effect), allowing the evaluation of systemic abscopal effect in the uninjected contralateral tumors. OncoVEXmGM-CSF in combination with anti-PD-L1/PD-1 enhanced tumor growth inhibition in both treated and contralateral tumors in the A20 and MC38 syngeneic models and overcame anti-PD-L1 resistance in the CT26 model. The combination treatment also led to a significant increase in median overall survival compared to either agent as a monotherapy. In addition, tumor antigen epitopes were identified by combining exome sequencing and MHC/HLA-binding prediction algorithms. Antigen-specific T cell response was measured in an IFN-γ ELISPOT assay using splenocytes from treated mice. OncoVEXmGM-CSF induced and /or enhanced systemic T cell responses directed against both tumor neoantigens and tumor-associated antigens. Together, these data reveal that OncoVEXmGM-CSF treatment can cause direct tumor lysis along with the potentiation of an adaptive, systemic T cell-mediated anti-tumor immune response that can be enhanced by the addition of PD-L1/PD-1. Our study provides a strong rationale for the ongoing clinical evaluation of the combination of T-VEC and PD1-/PD-L1-targeted therapy in cancer patients.

Citation Format: Keegan Cooke, Juan Estrada, Petia Mitchell, Jinghiu Zhan, Pedro J. Beltran, Jing Qing, Jude Canon. OnxoVEXmGM-CSF promotes systemic response to PD-L1 /PD-1 blockade in multiple mouse syngeneic tumor models [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2219.
Abstract 2230: MG1131, a novel TIGIT-targeting monoclonal antibody, enhances anti-tumor immune responses by modulating NK and T cell activity
Authors: Lee Jeewon , Kim Munkyung , Nam Hye-mi , Sheen Joong Hyuk , Song Eun Jung , Yum Hye In , Lim So Jung , Park Hye-Young
Published: September 2020

As the recent rise of immune checkpoint inhibitors has resulted in durable clinical outcomes in cancer patients, the need for a newer and more widely effective target for immunotherapy has been vigorously sought in the field; T cell immunoreceptor with Ig and ITIM domain (TIGIT) is an immune checkpoint molecule expressed on CD8+ T cells, CD4+ T cells, NK cells, and regulatory T cells (Treg). TIGIT induces exhaustion of effector T cells (Teff) and NK cells in the tumor microenvironment via engagement with its ligand PVR (CD155) which is dominantly expressed on malignant tumor cells. After initial screening processes from a synthetic library, MG1131 clone was chosen based on the strongest binding affinity to human TIGIT and the superior PVR-blocking activity. MG1131 was cross-reactive with the cynomolgus monkey TIGIT, but not with the mouse TIGIT. Our in vitro efficacy data demonstrated that MG1131 activated NF-κB signaling in T cells, and enhanced NK-mediated tumor killing activities in a PVR-dependent manner. In vitro Treg suppression assays showed that MG1131 inhibited immunosuppressive functionality of Treg, leading to restoration of proliferation and IFN-γ secretion capacities of Teff even in the presence of Treg. In addition, expression levels of TIGIT on CD8+ T cells from PBMCs of cancer patient samples were higher compared with other immune inhibitory molecules such as PD-1, Tim-3, CTLA-4, or LAG-3, and the blockade of TIGIT by MG1131 resulted in increased IFN-γ secretion. Thus, our data indicate that MG1131 is a promising candidate for cancer immunotherapy by modulating NK and T cell functions.

Citation Format: Jeewon Lee, Munkyung Kim, Hye-mi Nam, Joong Hyuk Sheen, Eun Jung Song, Hye In Yum, So Jung Lim, Hye-Young Park. MG1131, a novel TIGIT-targeting monoclonal antibody, enhances anti-tumor immune responses by modulating NK and T cell activity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2230.
Abstract 2234: Development of caninized monoclonal antibodies against PD1
Authors: Kocikowski Mikolaj , Dziubek Katarzyna , Vojtesek Borek , Argyle David , Hupp Ted , Parys Maciej
Published: September 2020

Immune blockade of inhibitory immune checkpoint (IC) mediated by Programmed cell death protein 1 (PD1) significantly increases survival of patients with advanced melanoma and other cancers. Dogs constitute a unique model for studying cancer types relevant to humans. Canine malignancies occur spontaneously and share many pathogenic pathways as well as therapy responses with their human counterparts. Dogs have a fully functional immune system, share the owners' lifestyle, environmental exposures, and their genome is more similar to the human one than the murine one is. Canine cancer research may be a superior alternative to mouse studies in the context of immunotherapy development. Unfortunately, IC-blocking antibodies are not available for companion animals. Monoclonal antibody against canine ICs has been previously developed by our group using mouse hybridoma technology. While functional, it couldn't be used clinically due to immunogenicity. To create a viable therapeutic, the antibody sequence was caninized. The murine constant regions of heavy and light chains were substituted with corresponding canine sequences. Following that, the variable regions' structural frameworks were replaced with canine sequences generated based on a canine library of antibody sequences.Additionally, we developed an antibody against the PDL1 protein using a previously established canine antibody phage library. The PD1 and PDL1 antibodies are being characterized by ELISA and cell-based blocking assays, T-cell activation assays and growth assessment of the impact on spheroid growth in patient-derived cultures.The characterized antibodies will widen the availability of canine IC blockers and pave the path for further research in comparative oncology.

Citation Format: Mikolaj Kocikowski, Katarzyna Dziubek, Borek Vojtesek, David Argyle, Ted Hupp, Maciej Parys. Development of caninized monoclonal antibodies against PD1 [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2234.
Abstract 2251: Analysis of cancer survival using peripheral blood immunological parameters
Authors: Williams R. Michael , Zuniga Joaquin , Granados Julio , Feris Edmond Tato , Yunis Edmond J.
Published: September 2020

The purpose of this study is to use Immunological Evaluation of Peripheral Blood NK cell number to predict survival in the War of the Immune System against cancer. Comparison of the two survival curves starts with the null hypothesis: there is no difference between the top 50% NK vs bottom 50% NK survival curves. P value is derived from Test Statistic found using log rank test. Breast cancer patients and colon cancer patients were evaluated. Both showed statistically significant differences in survival based on NK Cell number. Eight breast cancer patients had local radiation which showed in every one that the peripheral blood NK cell number decreased during radiation and returned to baseline values after radiation ended. In colon cancer patients the level of quantitative IgM and IgA defined a difference in overall survival. This was not the case for breast cancer patients. Survival was evaluated over a 9+ year period in a single California practice.

Citation Format: R. Michael Williams, Joaquin Zuniga, Julio Granados, Edmond Tato Feris, Edmond J. Yunis. Analysis of cancer survival using peripheral blood immunological parameters [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2251.
Abstract 226: Pathways of nucleotide synthesis in NSCLC
Authors: Fan Teresa W-M , Sun Qiushi , Higashi Richard M. , Lane Andrew N.
Published: September 2020

Tracer-based mapping of metabolic networks is a powerful approach for revealing metabolic reprogramming in human cancer. Nucleotide synthesis and turnover is critical for cell proliferation and is tightly regulated [1,2]. We have developed NMR and tandem MS methods for determining the active pathways of the synthesis of free nucleotides and nucleotide sugars including UDP-Glucose and UDPGlcNAc using multiplexed stable isotope resolved metabolomics (mSIRM)[3] in a variety of models including freshly resected lung tumor tissue, mouse PDX and organoids. Using multiple isotopic labels (13C, 2H and 15N) we determined the relative contributions to purine and pyrimidine nucleotide synthesis of both exogenous glucose, glutamine, serine and glycine and metabolically-derived intracellular precursors. We have used these approaches to compare the relative importance of different metabolic pathways in NSCLC under various conditions to assess the role of the tumor microenvironment, and how these pathways are impacted by arsenite and selenite. Our findings indicate that the substrates for de novo nucleotide synthesis may differ profoundly between cancer cell lines and fresh human lung cancer tissues; for purines, the latter preferred glucose to exogenous serine or glycine but not the former. Pyrimidine nucleotides also utilize glucose for ribose synthesis via the pentose phosphate pathway, but both glucose and glutamine for the pyrimidine rings depending on the conditions and cell type. This distinction in substrate utilization in nucleotide synthesis in human cancer tissues should be considered when targeting one-carbon metabolism for cancer therapy.

Acknowledgements: This work was supported in part by grants: 1R01ES022191-01 (to TWMF and RMH), 1P01CA163223-01A1 (to ANL and TWMF), and 1U24DK097215-01A1 (to RMH, TWMF, and ANL).

References

1. Lane, A.N. & Fan,T. W-M. (2015) Regulation of nucleic acid metabolism in mammalian cells. Nucl.Acids Res. 43, 2466-85

2. Fan, T. W-M. et al. (2019) De novo synthesis of serine and glycine fuels purine nucleotide biosynthesis in human lung cancer tissues. J. Biol. Chem. 294, 13464-13477

3. Yang, Y., Fan, W. W-M., Lane, A.N. & Higashi, R.M. (2017) Chloroformate Derivatization for Tracing the Fate of Amino Acids in Cells by Multiple Stable Isotope Resolved Metabolomics (mSIRM). Anal. Chim. Acta 976, 63-73

Citation Format: Teresa W-M Fan, Qiushi Sun, Richard M. Higashi, Andrew N. Lane. Pathways of nucleotide synthesis in NSCLC [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 226.
Abstract 2283: A novel GUCY2C - CD3 bispecific engages T cells to induce cytotoxicity in gastrointestinal tumors
Authors: Mathur Divya , Root Adam , Bugaj-Gaweda Bozena , Tan Xingzhi , Fang Wei , Bisulco Stephanie , Golas Jonathan , Fernandez Diane , Kearney Jessica , Upeslacis Eric , Yao Johnny , Rosfjord Edward , Stevens Chad , Kobylarz Keith , King Lindsay , Narula Jatin , Kelleher Kerry , Schaer David , Kamperschroer Cris , Buetow Bernard , Rohde Cynthia , Moreau Allison , Wong Gilbert , Sapra Puja
Published: September 2020

Gastrointestinal malignancies, including colorectal cancer (CRC) remain an area of high unmet need. Here we demonstrate tumor selective and potent in vitro and in vivo efficacy with PF-07062119, a novel T cell engaging CD3 bispecific against tumors expressing the Guanylyl Cyclase C (GUCY2C) receptor, a target expressed in more than 90% of CRC, and in other gastrointestinal cancers. Additionally, to address immune evasion mechanisms, combinations of the GUCY2C-CD3 bispecific are explored with immune checkpoint blockade therapy, as well as with chemotherapeutic and anti-angiogenic agents that could enhance immune infiltration into tumors. Our preclinical in vivo data demonstrate that GUCY2C-positive tumors can be targeted with an anti-GUCY2C/anti-CD3ϵ bispecific, with selective drug biodistribution to tumors. PF-07062119 showed potent T cell mediated anti-tumor activity in several human xenograft models of CRC, using adoptive transfer of human T cells, including those with KRAS and BRAF mutations, as well as in models with syngeneic tumors in immunocompetent human CD3 transgenic mice. PF-07062119 activity was further enhanced when combined with anti PD-1/PD-L1 treatment or in combination with chemotherapy or anti-angiogenic therapy. A combination of immunohistochemistry, flow cytometry and CyTOF analyses was used to demonstrate the mechanism of action of PF-07062119 in single agent and combination studies in vivo. Toxicity and pharmacokinetic studies were done in cynomolgus macaques and indicated a monitorable and manageable toxicity profile. These data highlight the potential for PF-07062119 to demonstrate efficacy and improve patient outcomes in CRC and other gastrointestinal malignancies. A clinical Phase I study has been initiated in patients with CRC, gastric and esophageal adenocarcinomas (NCT04171141).

Citation Format: Divya Mathur, Adam Root, Bozena Bugaj-Gaweda, Xingzhi Tan, Wei Fang, Stephanie Bisulco, Jonathan Golas, Diane Fernandez, Jessica Kearney, Eric Upeslacis, Johnny Yao, Edward Rosfjord, Chad Stevens, Keith Kobylarz, Lindsay King, Jatin Narula, Kerry Kelleher, David Schaer, Cris Kamperschroer, Bernard Buetow, Cynthia Rohde, Allison Moreau, Gilbert Wong, Puja Sapra. A novel GUCY2C - CD3 bispecific engages T cells to induce cytotoxicity in gastrointestinal tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2283.
Abstract 2300: Deleterious germline mutations in the BRCA1 gene are associated with increased risk for cancers of the female reproductive system other than breast and ovarian as well as other cancers
Authors: Middlebrooks Candace , Pantin Kenzhane , Stacey Mark , Snyder Carrie , Casey Murray J. , Shaw Trudy , Bailey-Wilson Joan E. , Lynch Henry T.
Published: September 2020

Introduction: Mutations within the BRCA1 gene have been linked to up to an 80% lifetime risk of breast cancer as well as increased risk for ovarian, pancreatic and melanoma cancers. In this study we examined families with known germline mutations in BRCA1 after long-term follow-up to determine whether carriers experience higher rates of other cancers that have not yet been associated with germline mutations in the BRCA1 gene.

Methods: We studied 127 Hereditary Breast and Ovarian Cancer (HBOC) syndrome families (N = 23,078 individuals who have been followed at Creighton University) in which a causal mutation in the BRCA1 gene was identified. We performed survival analysis and a mixed effects cox regression with age at follow-up or cancer event as our time variable and presence or absence of BRCA1-related or other cancers (separate analyses) as our indicator variable.

Results: The survival curves showed a significant age effect with carriers having a younger age at cancer onset for BRCA1-related (as expected) as well as other cancers than that of non-carriers. The cox regression models were also highly significant (P = 1.77E-37 and P = 1.04E-07 for the BRCA1-related and other cancers, respectively). Of the cancers with enough samples to do stratified analyses, uterine, skin, lymphoma and colon cancers occurred at higher rates and at earlier ages in mutation carriers.

Conclusions: These analyses support the hypothesis that the BRCA1 mutations carriers of HBOC syndrome have increased risk for early onset of several additional cancer types, especially cancers that arise in estrogen-influenced tissues.

Citation Format: Candace Middlebrooks, Kenzhane Pantin, Mark Stacey, Carrie Snyder, Murray J. Casey, Trudy Shaw, Joan E. Bailey-Wilson, Henry T. Lynch. Deleterious germline mutations in the BRCA1 gene are associated with increased risk for cancers of the female reproductive system other than breast and ovarian as well as other cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2300.
Abstract 2301: Indications for systematic prostate biopsy in men with negative multi-parametric magnetic resonance imaging
Authors: Molokwu Chidi N. , Gkikas Christos , Bardgett Harry , Lee Nicola , Ali Faisal , Chahal Rohit , Singh Rajindra
Published: September 2020

Introduction: Multiparametric Magnetic Resonance Imaging (mpMRI) is a valuable tool in the prostate cancer diagnostic pathway, and MRI-influenced biopsy has been shown to be superior to systematic biopsy alone for detecting clinically significant prostate cancer (csPCa), defined as the presence of any Gleason ≥ 4. Negative predictive value of mpMRI for csPCa varies widely in published reports, with a median of approximately 88%. Counselling patients with negative mpMRI (PIRADS score <3)to decide whether or not to proceed with systematic biopsy or PSA monitoring could be challenging. Several studies have shown that a PSA density (PSAD) ≥ 0.15 is an indication for systematic biopsy. We analysed the clinical, radiological and pathological features of patients with negative mpMRI but csPca on systematic biopsy to identify other criteria that may inform the need for systematic biopsy when mpMRI is negative.

Methods: For 18 months between Nov 2017 and May 2019, all men on our prostate diagnostic pathway with negative mpMRI were offered systematic biopsy. The criteria for pre-biopsy mpMRI was any man suitable for radical surgery or radiotherapy, plus one or more of PSA ≥ 3, palpable lesion on digital rectal examination, or family history of PCa in a first degree relative (father or brother). mpMRI was performed with a 1.5-Tesla magnet and included T2, DWI and DCE sequences. Systematic biopsy was TRUS-guided, with 8-16 biopsy cores.

Results: Of 589 mpMRI scans in 573 men, 216 (37%) had negative mpMRI. Of these, 141 (65%) proceeded with systematic biopsy. Among the men that had biopsy, Gleason 3+3 was detected in 12 men (9%) and Gleason ≥ 4 in six (4%). Important pre-biopsy features in men with Gleason ≥ 4 were PSAD ≥ 0.15 (n=3), artefact on MRI from hip joint prosthesis (n=1), and family history (n=2). There were no unusual histological variants seen on the positive biopsy cores.

Conclusion: Most men with negative mpMRI can avoid prostate biopsy and be managed with PSA monitoring. Based on our experience, we recommend systematic biopsy in men with negative mpMRI who have PSAD ≥ 1.5, family history or any imaging artifact that may alter image interpretation.

Citation Format: Chidi N. Molokwu, Christos Gkikas, Harry Bardgett, Nicola Lee, Faisal Ali, Rohit Chahal, Rajindra Singh. Indications for systematic prostate biopsy in men with negative multi-parametric magnetic resonance imaging [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2301.