Tumor Genotype Research Articles

Tumor genotype, location, and malignant potential shape the immunogenicity of primary untreated gastrointestinal stromal tumors.

Intratumoral immune infiltrate was recently reported in gastrointestinal stromal tumors (GISTs). However, the tumor-intrinsic factors that dictate GIST immunogenicity are still largely undefined. To shed light on this issue, a large cohort (82 samples) of primary untreated GISTs, representative of major clinicopathological variables, was investigated by an integrated immunohistochemical, transcriptomic, and computational approach. Our results indicate that tumor genotype, location, and malignant potential concur to shape the immunogenicity of primary naive GISTs. Immune infiltration was greater in overt GISTs compared with that in lesions with limited malignant potential (miniGISTs), in KIT/PDGFRA-mutated tumors compared with that in KIT/PDGFRA WT tumors, and in PDGFRA-mutated compared with KIT-mutated GISTs. Within the KIT-mutated subset, a higher degree of immune colonization was detected in the intestine. Immune hot tumors showed expression patterns compatible with a potentially proficient but curbed antigen-specific immunity, hinting at sensitivity to immunomodulatory treatments. Poorly infiltrated GISTs, primarily KIT/PDGFRA WT intestinal tumors, showed activation of Hedgehog and WNT/β-catenin immune excluding pathways. This finding discloses a potential therapeutic vulnerability, as the targeting of these pathways might prove effective by both inhibiting pro-oncogenic signals and fostering antitumor immune responses. Finally, an intriguing anticorrelation between immune infiltration and ANO1/DOG1 expression was observed, suggesting an immunomodulatory activity for anoctamin-1.

Abstract PR-005: Tumor intrinsic p53 mutation drives accumulation of neutrophils in the pancreatic tumor microenvironment promoting resistance to immunotherapy

Abstract Intratumoral genetic alterations can cause remodeling of local immune cell populations through distinct cellular mechanisms. After oncogenic KRAS, TP53 is the gene most frequently mutated in pancreatic ductal adenocarcinoma (PDAC). These mutations in TP53 are neomorphic and confer phenotypes distinct from those due to homozygous TP53 deletion. We sought to evaluate the non-cell-autonomous role of mutant p53 protein in the immune microenvironment by studying KrasG12D-mutated mouse pancreatic ductal epithelial cells (PDEC) engineered using CRISPR/Cas gene editing to express the Trp53R172H gain-of-function mutation. We found distinct immune profiles associated with orthotopically implanted tumors derived from KrasG12D;Trp53R172H PDEC, characterized by an influx of intratumoral CD11b+Ly6G+ neutrophils and concomitant decreases in CD3+ T cells, CD8+ T cells, and CD4+ T helper 1 (Th1) cells. Analysis of publicly available human PDAC cohorts revealed enrichment of genes in neutrophil-related pathways in TP53-mutated tumors. Knockdown of CXCL2, a neutrophil chemoattractant, in the tumor epithelial compartment of KrasG12D;Trp53R172H PDEC tumors reversed the neutrophil phenotype. Depleting neutrophils in mice bearing KrasG12D;Trp53R172H PDEC tumors augmented sensitivity to combined CD40 immunotherapy and chemotherapy. Collectively, these data link mutant p53 to the presence of intratumoral neutrophils in pancreatic cancer and suggests that tumor genotypes could inform patient selection for immunotherapy. Citation Format: Despina Siolas, Emily Vucic, Emma Kurz, Cristina Hajdu, Dafna Bar-Sagi. Tumor intrinsic p53 mutation drives accumulation of neutrophils in the pancreatic tumor microenvironment promoting resistance to immunotherapy [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PR-005.

DDRE-05. DECREASED EXPRESSION OF DNA DAMAGE RESPONSE PATHWAYS CORRELATES WITH SYNERGISTIC ACTIVITY OF TEMOZOLOMIDE WITH ATR INHIBITORS IN GLIOBLASTOMA

Abstract The lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most important gaps in enabling the development of effective targeted cancer therapies. Increasing evidence supports the notion that DNA damage response (DDR) signaling plays an important role in inducing radiation and temozolomide (TMZ) resistance in glioblastoma (GBM) and hence, it has emerged as a molecular target for therapeutic development. The cellular response to TMZ therapy is critically mediated by MGMT and DDR signaling networks that are regulated by Ataxia Telangiectasia Mutated (ATM) and Ataxia Telangiectasia and Rad3-related protein (ATR). ATR is a primary sensor of DNA damage initiating subsequent repair leading to cell survival. Here, we show that three clinical grade ATR inhibitors (Bay1895344, AZD6738 and VE-822) had similar selective sensitivity pattern across eight glioma-like stem cells (GSC) lines tested with three (GSC28, GSC11, GSC274) being the most sensitive, and three (GSC300, GSC272, and GSC20) being the most resistant cell lines. Interestingly, all three ATR inhibitors showed a significant synergism with TMZ (Combination index and Bliss model) in GSC300, GSC272, and GSC20, and antagonism in GSC28, GSC11, and GSC274. Further analysis showed that the synergistic group was resistant to single agent ATR inhibitor, whereas antagonistic group was inherently sensitive to ATR inhibitor. The synergistic response was not associated with any major genetic alterations such as MGMT status, EGFR amplification, PTEN deletion/mutation, or p53 deletion/mutation. However, GSEA analysis of baseline RNA-seq data of the 6 cell lines showed an enhanced expression of six DNA damage/repair/response pathways in the antagonistic group. It suggests that a low level of DNA damage/repair/response pathways could be a marker of synergy for TMZ with ATR inhibitors in GBM. Further studies are underway to validate this observation in more GSC lines in vitro and in vivo.

TAMI-45. PHENOGENOMIC CHARACTERIZATION OF IMMUNOMODULATORY PURINERGIC SIGNALING IN GLIOBLASTOMA

Abstract INTRODUCTION Purinergic signaling plays critical roles in the regulation of tumor growth and anti-tumor immunity via autocrine/paracrine binding of metabolites to receptors on neoplastic and non-neoplastic populations. Extracellular purine concentrations are mediated by the ectonucleotidase enzymes CD39 and CD73, which catabolize ATP to adenosine. Within tumors such as glioblastoma, neoplastic, immune, and stromal cells expressing these enzymes may co-localize to generate immunosuppressive adenosine-rich environments. However, the composition, architecture, and phenotypic properties of these tumor ecosystems and their relationship to tumor genotype are poorly characterized. METHODS We quantified CD73 expression by immunohistochemistry in a cohort of CNS tumors [meningiomas(n=222), gliomas(n=244), ependymomas(n=44), medulloblastomas(n=24), and craniopharyngiomas(n=38)]. We used publicly-available single-cell RNA-seq data and 36-marker multiplexed tissue imaging (t-CyCIF) of 139 clinically and genomically annotated glioblastoma resections to characterize CD39 and CD73-expressing populations, define the immune architecture and tumor cell-states at single cell resolution, and identify markers of clinical outcome. We used mass spectrometry imaging (MALDI-MSI) to generate spatially-resolved quantification of purine metabolite levels in glioblastoma resections (n=10). RESULTS CD73 exhibited strong expression in a subset of gliomas and meningiomas but was typically not expressed in ependymomas or medulloblastomas. CD73 expression correlated with poor progression-free-survival in IDH-wildtype glioblastoma (p=0.04). scRNA-seq and t-CyCIF in glioblastoma showed CD73 expression in tumor cells, and CD39 expression in macrophages and endothelial cells. MALDI-MSI showed significantly greater adenosine concentrations (3.5-fold;p=0.04) in glioblastomas with high CD73 expression. scRNA-seq showed direct correlations between stem-like mRNA expression, proliferation, and CD73 expression in DIPG. CD73 expression significantly correlated with EGFR amplification, interferon signaling, and PD-L1 expression in glioblastoma. CONCLUSIONS Phenogenomic analysis of purinergic immunomodulatory signaling revealed significant interplay between CD73 activity and genotype, adenosine concentration, differentiation-state, clinical outcome, and possible interaction between CD39-positive macrophages and CD73-positive neoplastic cells. Anti-CD73 therapy may provide therapeutic benefits in glioblastoma by blunting immunosuppressive and oncogenic adenosine signaling.

Analysis of reliability of different risk classifications for assessment of relapses of gastrointestinal stromal tumors (GIST) — the impact of primary tumor genotyping

Background. Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract. Radical surgery is the primary treatment for GIST. Unfortunately, 40–50% of patients relapse, mainly due to hepatic and peritoneal metastases. Currently, the treatment of choice for locally advanced, inoperable or metastatic GIST is the use of tyrosine kinase inhibitors, including imatinib. GISTs are a group of tumors with various morphological, pathological and molecular features as well as different clinical courses, therefore their biological course is difficult to determine. Nevertheless, we currently have 5 classifications that assess the risk of relapse after surgery. The aim of this study was to analyze prognostic factors with regard to the risk of recurrence and overall survival, and to compare the clinical reliability of the recurrence risk classifications developed so far with an attempt to present a new classification including the genotype of primary GIST. Patients and methods. The material consisted of a group of 697 patients with primary GIST treated with the intention to cure, collected prospectively as part of the GIST clinical registry, Department of Melanoma and Soft Tissue and Bone Sarcomas, Maria Sklodowska-Curie National Research Institute of Oncology in Warsaw. All patients were classified based on 5 existing recurrence risk classifications. Univariate and multivariate analysis were performed for disease-free survival (DFS) and overall survival (OS). The relationships of the following factors with DFS and OS were assessed: sex, age, primary tumor mutational status, primary tumor location, primary tumor size, number of mitoses/50 HPF, surgical margins and the presence of tumor rupture. The next analysis concerned the comparison of the accuracy of existing recurrence risk classifications. The analysis was performed using ROC curves and a new classification model was proposed including mutation analysis as well as factors such as gender and age for selected existing recurrence risk assessment models. Results. Univariate and multivariate analyses showed statistical significance of variables such as male sex (P = 0.02), mitotic index 5–10/50 HPF and > 10/50 HPF (P < 0.001), primary tumor size 5–10 cm and > 10 cm (P < 0.001), primary tumor location outside of the stomach (P < 0.001), R1 surgery (P < 0.001), tumor rupture (P < 0.001), and the presence of mutations in the KIT gene exon 11 including deletion 557–558 and the KIT gene exon 9 (P = 0.009) as negative prognostic factors affecting disease recurrence. Five-year disease-free survival rate was 57.3%. Median DFS was 76 months. Negative prognostic factors for OS are: age < 40 (P = 0.045), mitotic index 5–10/50 and > 10/50 HPF (P < 0.001), primary tumor size 5–10 cm and > 10 cm (P < 0.001), R1 surgery and tumor rupture (P < 0.001). All existing recurrence risk classifications showed prognostic value for assessing differences in DFS and OS, no significant differences were found between individual recurrence risk classifications. In addition, the reliability of all these classifications was improved by adding gender, age and mutation status. The value added of mutation status for better risk assessment was most significant when used in intermediate risk groups according to different classifications (P < 0.01). Conclusion. All current GIST recurrence risk classifications allow for reliable assessment of recurrence risk. Mutations involving deletions (557–558) in the KIT gene exon 11 are most often present in the group at high risk of recurrence. Patients with confirmed mutations in the PDGFRA gene exon 18 and wild-type genotype have a favorable prognostic effect. The reliability of existing classifications for assessing the risk of relapse after GIST resection can be improved by adding mutation status, especially in groups at intermediate risk of relapse, which should facilitate therapeutic decisions in the context of adjuvant therapy.

Implementing ctDNA Analysis in the Clinic: Challenges and Opportunities in Non-Small Cell Lung Cancer.

Simple SummaryThe clinical relevance of tumor genotyping through analysis of ctDNA is now widely recognized at all steps of the clinical evaluation process in metastatic non-small cell lung cancer (NSCLC) patients. ctDNA analysis through liquid biopsy has recently gained increasing attention as well in the management of early and locally advanced, not oncogene-addicted, NSCLC. The aim of this review is to summarize the landscape of liquid biopsies in clinical practice and also to provide an overview of the potential perspectives of development focusing on early detection and screening, the assessment of minimal residual disease, and its potential role in predicting response to immunotherapy.Tumor genomic profiling has a dramatic impact on the selection of targeted treatment and for the identification of resistance mechanisms at the time of progression. Solid tissue biopsies are sometimes challenging, and liquid biopsies are used as a non-invasive alternative when tissue is limiting. The clinical relevance of tumor genotyping through analysis of ctDNA is now widely recognized at all steps of the clinical evaluation process in metastatic non-small cell lung cancer (NSCLC) patients. ctDNA analysis through liquid biopsy has recently gained increasing attention as well in the management of early and locally advanced, not oncogene-addicted, NSCLC. Its potential applications in early disease detection and the response evaluation to radical treatments are promising. The aim of this review is to summarize the landscape of liquid biopsies in clinical practice and also to provide an overview of the potential perspectives of development focusing on early detection and screening, the assessment of minimal residual disease, and its potential role in predicting response to immunotherapy. In addition to available studies demonstrating the clinical relevance of liquid biopsies, there is a need for standardization and well-designed clinical trials to demonstrate its clinical utility.

Real-World Analysis of Clinical Characters, Prognosis, And Recurrence Pattern: A Retrospective Multicenter Study of 429 Patients with Epidermal Growth Factor Receptor (EGFR) Mutant Locally Advanced Non-Small Cell Lung Cancer (LA-NSCLC)

Advanced NSCLC with EGFR mutations is a distinct subgroup which has unique biology and a high response rate towards target therapy of EGFR-tyrosine kinase inhibitors (TKIs). However, for EGFR-mutant unresectable LA-NSCLC who treated with conventional chemoradiotherapy (CRT), limited data are available about the relationship between clinical characteristics, prognosis, and subsequent failure patterns. Here we summarized these clinical data using a joint academic center database. We retrospectively collected data for patients with unresectable stage III NSCLC harboring EGFR mutations from nine major academic cancer institutions in China from Jan 2012 to December 2018. Patients with concurrent ALK rearrangements were excluded. Tumor or ctDNA genotyping was performed using polymerase chain reaction amplification or next-generation sequencing method. OS, PFS, local-regional failure free survival (LRFS), and distant metastasis-free survival (DMFS) were calculated from the date of diagnosis. A total of 429 patients met selection criteria were included in the study, among whom 209 (48.7%) patients had exon 19 deletion, 165 (38.5%) had L858R exon, 26 (6.1%) had uncommon mutations, and 29 (6.8%) had multiple mutations. 298 patients (69.5%) were smoker, and 227 (61.9%) were female. The median age was 58 (30-89) years and 230 (53.6%) was younger than 60 years. 296 (69.0%) patients had stage IIIB disease and 285patients (66.4%) with smaller primary lesions (T1/2). Of the 367 patients with survival information, the median follow-up time was 40.8 months. the median OS were 55.5 month (95%CI 43.4-67.5). The 1-, 2-, 3-, and 5-years OS rates are 94%, 79%, 63%, and 47%, respectively. The median PFS was 16.6 months (95%CI 14.9-18.2). The 1-, 2-, 3-, and 5-years PFS rates are 64%, 34%, 22%, and 14%, respectively. There was no difference in OS or PFS by different genotypes. In multivariable analysis, use of EGFR-TKIs (yes v not: HR = 0.56, 95%CI 0.43-0.74, P<0.001) and stage (IIIA v IIIB: HR = 0.67, 95% CI 0.51-0.87, P = 0.003) were independently associated with PFS; and age was independently associated with OS (≥60 v <60 years: HR = 1.45, 95% CI 1.03-2.03, P = 0.035). As for relapse pattern after initial treatment of thoracic radiotherapy (RT) and chemotherapy, 46.5% of patients developed DM, 31.0% developed LRR, and 22.5% developed simultaneous DM and LRR. The incidence of brain metastasis was 24.8% (91 patients). By multivariable analysis, EGFR-TKIs independently increased the DMFS (yes v not: HR 0.51,95%CI 0.37-0.70, P<0.001). To our knowledge this is the largest retrospective analysis of EGFR-mutant LA-NSCLC, aiming to provide a reliable baseline and prognosis estimate. Multivariable analysis demonstrated EGFR-TKIs might independently prolong DMFS. The combined treatment modality of RT and EGFR-TKIs may be promising.

Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells

Most drugs entering clinical trials fail, often related to an incomplete understanding of the mechanisms governing drug response. Machine learning techniques hold immense promise for better drug response predictions, but most have not reached clinical practice due to their lack of interpretability and their focus on monotherapies. We address these challenges by developing DrugCell, an interpretable deep learning model of human cancer cells trained on the responses of 1,235 tumor cell lines to 684 drugs. Tumor genotypes induce states in cellular subsystems that are integrated with drug structure to predict response to therapy and, simultaneously, learn biological mechanisms underlying the drug response. DrugCell predictions are accurate in cell lines and also stratify clinical outcomes. Analysis of DrugCell mechanisms leads directly to the design of synergistic drug combinations, which we validate systematically by combinatorial CRISPR, drug-drug screening invitro, and patient-derived xenografts. DrugCell provides a blueprint for constructing interpretable models for predictive medicine.

Newly established gastrointestinal cancer cell lines retain the genomic and immunophenotypic landscape of their parental cancers

Human cancer cell lines are frequently used as model systems to study molecular mechanisms and genetic changes in cancer. However, the model is repeatedly criticized for its lack of proximity to original patient tumors. Therefore, understanding to what extent cell lines cultured under artificial conditions reflect the phenotypic and genomic profiles of their corresponding parental tumors is crucial when analyzing their biological properties. To directly compare molecular alterations between patient tumors and derived cell lines, we have established new cancer cell lines from four patients with gastrointestinal tumors. Tumor entities comprised esophageal cancer, colon cancer, rectal cancer and pancreatic cancer. Phenotype and genotype of both patient tumors and derived low-passage cell lines were characterized by immunohistochemistry (22 different antibodies), array-based comparative genomic hybridization and targeted next generation sequencing (48-gene panel). The immunophenotype was highly consistent between patient tumors and derived cell lines; the expression of most markers in cell lines was concordant with the respective parental tumor and characteristic for the respective tumor entities in general. The chromosomal aberration patterns of the parental tumors were largely maintained in the cell lines and the distribution of gains and losses was typical for the respective cancer entity, despite a few distinct differences. Cancer gene mutations (e.g., KRAS, TP53) and microsatellite status were also preserved in the respective cell line derivates. In conclusion, the four examined newly established cell lines exhibited a phenotype and genotype closely recapitulating their parental tumor. Hence, newly established cancer cell lines may be useful models for further pharmacogenomic studies.

Identifying Drug Sensitivity Subnetworks with NETPHIX

SummaryPhenotypic heterogeneity in cancer is often caused by different patterns of genetic alterations. Understanding such phenotype-genotype relationships is fundamental for the advance of personalized medicine. We develop a computational method, named NETPHIX (NETwork-to-PHenotype association with eXclusivity) to identify subnetworks of genes whose genetic alterations are associated with drug response or other continuous cancer phenotypes. Leveraging interaction information among genes and properties of cancer mutations such as mutual exclusivity, we formulate the problem as an integer linear program and solve it optimally to obtain a subnetwork of associated genes. Applied to a large-scale drug screening dataset, NETPHIX uncovered gene modules significantly associated with drug responses. Utilizing interaction information, NETPHIX modules are functionally coherent and can thus provide important insights into drug action. In addition, we show that modules identified by NETPHIX together with their association patterns can be leveraged to suggest drug combinations.

Revisiting MET: Clinical Characteristics and Treatment Outcomes of Patients with Locally Advanced or Metastatic, MET-Amplified Esophagogastric Cancers.

Metastatic esophagogastric cancers (EGCs) have a poor prognosis with an approximately 5% 5-year survival. Additional treatment approaches are needed. c-MET gene-amplified tumors are an uncommon but potentially targetable subset of EGC. Clinical characteristics and outcomes were evaluated in patients with MET-amplified EGC and compared with those without MET amplification to facilitate identification of these patients and possible treatment approaches. Patients with locally advanced or metastatic MET-amplified EGC at Massachusetts General Hospital (MGH) were identified using fluorescent in situ hybridization analysis, with a gene-to-control ratio of ≥2.2 defined as positive. Non-MET-amplified patients identified during the same time period who had undergone tumor genotyping and treatment at MGH were evaluated as a comparison group. We identified 233 patients evaluated for MET amplification from 2002 to 2019. MET amplification was seen in 28 (12%) patients versus 205 (88%) patients without amplification. Most MET-amplified tumors occurred in either the distal esophagus (n = 9; 32%) or gastroesophageal junction (n = 10; 36%). Of MET-amplified patients, 16 (57%) had a TP53 mutation, 5(18%) had HER2 co-amplification, 2 (7.0%) had EGFR co-amplification, and 1 (3.5%) had FGFR2 co-amplification. MET-amplified tumors more frequently had poorly differentiated histology (19/28, 68.0% vs. 66/205, 32%; p = .02). Progression-free survival to initial treatment was substantially shorter for all MET-amplified patients (5.6 vs. 8.8 months, p = .026) and for those with metastatic disease at presentation (4.0 vs. 7.6 months, p = .01). Overall, patients with MET amplification had shorter overall survival (19.3 vs. 24.6 months, p = .049). No difference in survival was seen between low MET-amplified tumors (≥2.2 and <25 MET copy number) compared with highly amplified tumors (≥25 MET copy number). MET-amplified EGC represents a distinct clinical entity characterized by rapid progression and short survival. Ideally, the identification of these patients will provide opportunities to participate in clinical trials in an attempt to improve outcomes. This article describes 233 patients who received MET amplification testing and reports (a) a positivity rate of 12%, similar to the rate of HER2 positivity in this data set; (b) the clinical characteristics of poorly differentiated tumors and nodal metastases; and (c) markedly shorter progression-free survival and overall survival in MET-amplified tumors. Favorable outcomes are reported for patients treated with MET inhibitors. Given the lack of published data in MET-amplified esophagogastric cancers and the urgent clinical importance of identifying patients with MET amplification for MET-directed therapy, this large series is a valuable addition to the literature and will have an impact on future practice.

Strategies for the successful implementation of plasma-based NSCLC genotyping in clinical practice.

Upfront tumour genotyping is now considered an essential step in guiding treatment decision-making in the management of patients with advanced-stage non-small-cell lung cancer (NSCLC) in light of the ever-expanding toolbox of targeted therapies and immune-checkpoint inhibitors. However, genotyping of tumour biopsy samples is not feasible for all patients and, therefore, genomic analysis of circulating tumour DNA (ctDNA) has emerged as a compelling non-invasive option. Current guidelines universally recommend genotyping and support the use of ctDNA testing in certain settings, although they often omit the detail necessary for integrating these tests into clinical care on an individual basis. In this Perspective, we describe the rationale, promise and challenges associated with ctDNA-based NSCLC genotyping and suggest a framework for the implementation of these assays into routine clinical practice. We also offer considerations for the interpretation of ctDNA genotyping results, which, particularly when using next-generation sequencing panels, can be nuanced. Through the addition of this new approach to clinical practice, we propose that oncologists might finally be able to utilize effective genotyping in nearly all patients with advanced-stage NSCLC.

Visual histological assessment of morphological features reflects the underlying molecular profile in invasive breast cancer: a morphomolecular study.

Tumour genotype and phenotype are related and can predict outcome. In this study, we hypothesised that the visual assessment of breast cancer (BC) morphological features can provide valuable insight into underlying molecular profiles. The Cancer Genome Atlas (TCGA) BC cohort was used (n=743) and morphological features, including Nottingham grade and its components and nucleolar prominence, were assessed utilising whole-slide images (WSIs). Two independent scores were assigned, and discordant cases were utilised to represent cases with intermediate morphological features. Differentially expressed genes (DEGs) were identified for each feature, compared among concordant/discordant cases and tested for specific pathways. Concordant grading was observed in 467 of 743 (63%) of cases. Among concordant case groups, eight common DEGs (UGT8, DDC, RGR, RLBP1, SPRR1B, CXorf49B, PSAPL1 and SPRR2G) were associated with overall tumour grade and its components. These genes are related mainly to cellular proliferation, differentiation and metabolism. The number of DEGs in cases with discordant grading was larger than those identified in concordant cases. The largest number of DEGs was observed in discordant grade 1:3 cases (n=1185). DEGs were identified for each discordant component. Some DEGs were uniquely associated with well-defined specific morphological features, whereas expression/co-expression of other genes was identified across multiple features and underlined intermediate morphological features. Morphological features are probably related to distinct underlying molecular profiles that drive both morphology and behaviour. This study provides further evidence to support the use of image-based analysis of WSIs, including artificial intelligence algorithms, to predict tumour molecular profiles and outcome.

Nanomicellar Lenalidomide-Fenretinide Combination Suppresses Tumor Growth in an MYCN Amplified Neuroblastoma Tumor.

PurposeIn a previous study, we demonstrated that the combination of fenretinide with lenalidomide, administered by a novel nanomicellar formulation (FLM), provided a strong antitumor effect in a neuroblastoma TrkB-expressing tumor. In this study, we tested the nanomicellar combination in an MYCN amplified neuroblastoma xenograft to assess its efficacy in different tumor genotypes and evaluate the interactions of the nanomicelles with the tumor cells.Experimental DesignFLM was administered to mice bearing human NLF xenografts to evaluate its efficacy in comparison with the nanomicelles containing fenretinide alone (FM). Confocal laser-scanning fluorescence microscopy images of the NLF cells treated with FLM and FM allowed us to estimate the nanomicelle ability to transport the encapsulated drugs inside the tumor cells. Flow cytometric analysis of the cells from treated tumors was performed to assess the effect of treatment on GD2 expression and NK cell infiltration.ResultsFLM and FM decreased the growth of NLF xenografts at comparable extents during the treatment period. Afterwards, FLM induced a progressive tumor regression without regrowth, while FM treatment was followed by regrowth within 15–20 days after the end of treatment. Both FLM and FM were able to penetrate the tumor cells transporting the encapsulated drugs. FLM transported higher amount of fenretinide inside the cells. Also, FLM treatment strongly increased GD2 expression in treated tumors and slightly decreased the NK infiltration compared to FM.ConclusionFLM treatment induced a superior antitumor response than FM in NLF xenografts, presumably due to the combined effects of fenretinide cytotoxicity and lenalidomide antiangiogenic activity. The ability of FLM to penetrate tumor cells, transporting the encapsulated drugs, substantially improved the therapeutic efficiency of this system. Moreover, the enhancement of GD2 expression in FLM treated tumors offers the possibility to further increase the antitumor effect by the use of anti-GD2 CAR-T cells and anti-GD2 antibodies in combination with FLM in multimodal therapies.

Phenotypes from cell-free DNA.

Cell-free DNA (cfDNA) has the potential to enable non-invasive detection of disease states and progression. Beyond its sequence, cfDNA also represents the nucleosomal landscape of cell(s)-of-origin and captures the dynamics of the epigenome. In this review, we highlight the emergence of cfDNA epigenomic methods that assess disease beyond the scope of mutant tumour genotyping. Detection of tumour mutations is the gold standard for sequencing methods in clinical oncology. However, limitations inherent to mutation targeting in cfDNA, and the possibilities of uncovering molecular mechanisms underlying disease, have made epigenomics of cfDNA an exciting alternative. We discuss the epigenomic information revealed by cfDNA, and how epigenomic methods exploit cfDNA to detect and characterize cancer. Future applications of cfDNA epigenomic methods to act complementarily and orthogonally to current clinical practices has the potential to transform cancer management and improve cancer patient outcomes.

Radiogenomics of lung cancer.

Machine learning (ML) and artificial intelligence (AI) are aiding in improving sensitivity and specificity of diagnostic imaging. The rapid adoption of these advanced ML algorithms is transforming imaging analysis; taking us from noninvasive detection of pathology to noninvasive precise diagnosis of the pathology by identifying whether detected abnormality is a secondary to infection, inflammation and/or neoplasm. This is led to the emergence of “Radiobiogenomics”; referring to the concept of identifying biologic (genomic, proteomic) alterations in the detected lesion. Radiobiogenomic involves image segmentation, feature extraction, and ML model to predict underlying tumor genotype and clinical outcomes. Lung cancer is the most common cause of cancer related death worldwide. There are several histologic subtypes of lung cancer, e.g., small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC) (adenocarcinoma, squamous cell carcinoma). These variable histologic subtypes not only appear different at microscopic level, but these also differ at genetic and transcription level. This intrinsic heterogeneity reveals itself as different morphologic appearances on diagnostic imaging, such as CT, PET/CT and MRI. Traditional evaluation of imaging findings of lung cancer is limited to morphologic characteristics, such as lesion size, margins, density. Radiomics takes image analysis a step further by looking at imaging phenotype with higher order statistics in efforts to quantify intralesional heterogeneity. This heterogeneity, in turn, can be potentially used to extract intralesional genomic and proteomic data. This review aims to highlight novel concepts in ML and AI and their potential applications in identifying radiobiogenomics of lung cancer.

Integrated dia-gnostics of diffuse gliomas.

Recently, the World Health Organization (WHO) classification of tumours of the central nervous system (CNS) has brought essential changes. The currently valid revised WHO 2016 classification of CNS tumours introduced the concept of integrated dia-gnostics, which incorporated not only histopathological morphological finding and immunophenotype but also molecular-genetic characteristics of the tumour. Thus, the final integrated dia-gnosis comprises the traditional morphological and growth pattern characteristics of a tumour including histopathological grade and also specific molecular bio-markers. The classification of tumour based on a combination of both tumour phenotype and genotype enables more precise prognostic stratification, increases the objectivity of dia-gnostics and prediction of response to treatment. In 2017, an international platform, The Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy - not official WHO (cIMPACT-NOW), was established to create and formulate practical recommendations for integrated dia-gnostics of CNS tumours and upcoming WHO classification. The incorporation of molecular bio-markers into the integrated dia-gnostics radically changed the classification of diffuse gliomas, which include entities with different morphological characteristics, genetic alterations and bio-logical behaviour. This review article summarizes essential morphological, immunophenotypical and molecular genetic characteristics of diffuse gliomas within the scope of integrated dia-gnostics according to the valid WHO classification of tumours of the CNS and subsequent recommendations of dia-gnostic approaches. This work was supported by grant of the Ministry of Health of the Czech Republic - Conceptual Development of a Research Organization (MMCI 00209805) and Grant Agency of Masaryk University (MUNI/A/1562/2018). The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.

CD8+ T-cell-Mediated Immunoediting Influences Genomic Evolution and Immune Evasion in Murine Gliomas.

Cancer immunoediting shapes tumor progression by the selection of tumor cell variants that can evade immune recognition. Given the immune evasion and intratumor heterogeneity characteristic of gliomas, we hypothesized that CD8+ T cells mediate immunoediting in these tumors. We developed retrovirus-induced PDGF+ Pten -/- murine gliomas and evaluated glioma progression and tumor immunogenicity in the absence of CD8+ T cells by depleting this immune cell population. Furthermore, we characterized the genomic alterations present in gliomas that developed in the presence and absence of CD8+ T cells. Upon transplantation, gliomas that developed in the absence of CD8+ T cells engrafted poorly in recipients with intact immunity but engrafted well in those with CD8+ T-cell depletion. In contrast, gliomas that developed under pressure from CD8+ T cells were able to fully engraft in both CD8+ T-cell-depleted mice and immunocompetent mice. Remarkably, gliomas developed in the absence of CD8+ T cells exhibited increased aneuploidy, MAPK pathway signaling, gene fusions, and macrophage/microglial infiltration, and showed a proinflammatory phenotype. MAPK activation correlated with macrophage/microglia recruitment in this model and in the human disease. Our studies indicate that, in these tumor models, CD8+ T cells influence glioma oncogenic pathways, tumor genotype, and immunogenicity. This suggests immunoediting of immunogenic tumor clones through their negative selection by CD8+ T cells during glioma formation.

Abstract 1557: Landscape of tumor cell states and cellular ecosystems in diffuse large B cell lymphoma

Abstract The tumor microenvironment (TME) plays critical roles in cancer development, tumor progression, and susceptibility to therapy. However, the phenotypic states and interaction patterns of its underlying cell types remain poorly understood. To address this challenge, we developed a new computational framework, EcoTyper, for large-scale dissection of cell states and cellular communities (i.e., ecosystems) from tumor genomic profiles. EcoTyper integrates single-cell RNA sequencing (scRNA-seq) with CIBERSORTx, an algorithm for bulk RNA-seq deconvolution (Newman et al., Nat Biotechnol, 2019), to identify and validate cellular states and ecosystems that reflect fundamental distinctions in TME biology. Here we applied EcoTyper to diffuse large B cell lymphoma (DLBCL), an aggressive B cell malignancy with clinically distinct molecular subtypes and several immunologically-active therapies. We sought to determine whether EcoTyper could reveal novel biological variation in the DLBCL TME linked to tumor subtypes and genotypes, therapeutic responses, and clinical outcomes. We applied our approach to define transcriptional states from 13 cell types, including malignant, immune, and stromal cells, in over 1,500 DLBCL tumors. Remarkably, nearly all cell states identified by EcoTyper were validated in independent scRNA-seq and bulk RNA-seq datasets. Moreover, many cells states reflected novel phenotypic groupings, and the majority showed strong associations with overall survival, specific mutational profiles, and tumor molecular subtypes. Additionally, by identifying DLBCL tumors with similar communities of cellular states, we defined novel cellular ecosystems, or “ecotypes”, with distinct biological characteristics and clinical outcomes. Several ecotypes showed significant enrichments in canonical or novel tumor genotypes, suggesting an evolutionary interplay between the tumor and host TME. In summary, we developed a novel computational framework to dissect the TME at scale and present the most comprehensive atlas to date of cell states and cellular communities in DLBCL. Our approach is extensible to nearly any cancer type and may lead to the development of novel diagnostics and individualized immunotherapies. Citation Format: Chloe B. Steen, Bogdan Luca, Mohammad S. Esfahani, Barzin Y. Nabet, Brian Sworder, Farshad Farshidfar, David Kurtz, Chih Long Liu, Ranjana H. Advani, Yasodha Natkunam, June H. Myklebust, Maximilian Diehn, Andrew Gentles, Ash Alizadeh, Aaron M. Newman. Landscape of tumor cell states and cellular ecosystems in diffuse large B cell lymphoma [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 1557.

Abstract 2981: Biased activation of PP2A through selective heterotrimer binding and stabilization

Abstract Development of molecularly targeted therapies have shifted our clinical approach to cancer allowing for an integrated treatment approach where tumor genotype and molecular profiles are paired in a clinically actionable manner with specific targeted therapies. This approach maximizes efficacy and minimizes toxicity for each patient. While the vast majority of molecularly targeted therapies have focused on the development of kinase inhibition, an equally effective yet underexplored strategy exists in the activation or regulation of phosphatases. The tumor suppressor Protein Phosphatase 2A (PP2A) negatively regulates multiple oncogenic drivers common to a broad range of human malignancies including MYC, AKT, and ERK; and has been demonstrated as a critical tumor suppressor. In cancer, PP2A is inactivated through several mechanisms including increased expression of endogenous inhibitors, post-translational modifications of the catalytic subunit, and somatic mutation in its catalytic, regulatory or scaffold subunits. The vast mechanisms employed to dysregulate and inhibit PP2A in cancer, highlights it's potential as an endogenous molecular target to combat malignant growth. Our laboratory has been involved in the development of a novel series of small molecule activators of PP2A (SMAPs). Using structural, biochemical, cellular, and in vivo model systems we reveal how the lead SMAP, DT-061, specifically stabilizes a B56 containing PP2A holoenzyme, in its fully assembled, active state, to direct enzymatic activity towards specific oncogenic targets, including its well-known substrate c-MYC. Our structure identifies a unique interfacial small molecule binding pocket that involves all three PP2A subunits to prevent dissociation of select B56 subunit containing holoenzymes. Elucidating the mechanism of SMAPs allowed us to explore appropriate clinical placement for this targeting strategy and investigate potential mechanisms of resistance. For example, in vivo xenograft studies of cancer-associated Aα mutants, most notably R183W, demonstrates that these mutations render malignant cells resistant to these SMAPs and further support the mechanism of SMAPs described. Thus, our findings provide fundamental insights into PP2A complex assembly and regulation, identify a unique interfacial stabilizing mode of action for therapeutic targeting, and aid in the development of phosphatase-based therapeutics tailored against disease specific phospho-protein targets. Citation Format: Daniel Leonard, Wei Huang, Sudeh Izadmehr, Caitlin M. O'Connor, Danica D. Wiredja, Zhizhi Wang, Nilesh Zaware, Daniela M. Schlatzer, Stefan Schuchner, Janna Kiselar, Yinghua Chen, Nikhil Vasireddi, Abbey L. Perl, Matthew D. Glasky, Wenqing Xu, David L. Brautigan, Egon Ogris, Derek J. Taylor, Goutham Narla. Biased activation of PP2A through selective heterotrimer binding and stabilization [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 2981.