Stratify Patient Survival Research Articles

Development and Validation of a Prognostic Model for Postoperative Anastomotic Recurrence in Siewert II or III Adenocarcinomas Without Neoadjuvant Therapy in an East Asian Population.

Anastomotic recurrence leads to poor prognosis in patients with Siewert II or III adenocarcinoma who undergo radical gastrectomy and do not receive neoadjuvant therapy. We aimed to establish a prognostic model to evaluate the risk of postoperative anastomotic recurrence in patients with Siewert II or III adenocarcinoma who did not receive neoadjuvant therapy. We included 366 patients with Siewert II or III adenocarcinoma who were treated with radical gastrectomy without neoadjuvant therapy at Fujian Provincial Hospital (FPH) between 2012 and 2018 as the development cohort. Cox regression was used to verify prognostic factors for anastomotic recurrence, and a nomogram was established. The nomogram was externally validated using a combined cohort of two external centers. Patients were classified into high- or low-risk groups according to the diagnostic threshold and nomogram scores, and recurrence-related survival analysis was analyzed. The average age was 64.6 years, and 285 patients were male. All surgeries were successfully performed (185 open vs 181 laparoscopic). The 3-year anastomotic recurrence rate was significantly lower in the low-risk group (3.5% vs 18.8%, P < 0.001). The predictive performance was verified in the external validation cohort. This model better stratified patient survival than the American Joint Committee on Cancer (AJCC) TNM staging system. This novel nomogram with surgical margin, postoperative tumor node metastasis (pTNM) stage, and neural invasion as prognostic factors has a significant predictive performance for the risk of anastomotic recurrence after radical gastrectomy in patients with Siewert II or III adenocarcinoma.

Radiogenomic landscape: Assessment of specific phagocytosis regulators in lower-grade gliomas.

Genome-wide CRISPR-Cas9 knockout screens have emerged as a powerful method for identifying key genes driving tumor growth. The aim of this study was to explore the phagocytosis regulators (PRs) specifically associated with lower-grade glioma (LGG) using the CRISPR-Cas9 screening database. Identifying these core PRs could lead to novel therapeutic targets and pave the way for a non-invasive radiogenomics approach to assess LGG patients' prognosis and treatment response. We selected 24 PRs that were overexpressed and lethal in LGG for analysis. The identified PR subtypes (PRsClusters, geneClusters, and PRs-score models) effectively predicted clinical outcomes in LGG patients. Immune response markers, such as CTLA4, were found to be significantly associated with PR-score. Nine radiogenomics models using various machine learning classifiers were constructed to uncover survival risk. The area under the curve (AUC) values for these models in the test and training datasets were 0.686 and 0.868, respectively. The CRISPR-Cas9 screen identified novel prognostic radiogenomics biomarkers that correlated well with the expression status of specific PR-related genes in LGG patients. These biomarkers successfully stratified patient survival outcomes and treatment response using The Cancer Genome Atlas (TCGA) database. This study has important implications for the development of precise clinical treatment strategies and holds promise for more accurate therapeutic approaches for LGG patients in the future.

CTIM-33. SEXUAL DIMORPHISM OF HUMAN IMMUNE SYSTEM PREDICTS CLINICAL OUTCOMES IN GLIOBLASTOMA IMMUNOTHERAPY: A SYSTEMATIC REVIEW AND META-ANALYSIS

Abstract Biological differences based on sex have been documented throughout scientific literature. Glioblastoma, the most common primary malignant brain tumor in adults, has a male sex incidence bias, however, no clinical trial data examining differential effects of treatment between sexes currently exist. We analyzed genomic data, as well as clinical trials, to delineate the effect of sex on the immune system and glioblastoma outcome following immunotherapy. We found that, in general females possess enriched immunological signatures on gene set enrichment analysis, that also stratified patient survival when delineated by sex. Female glioblastoma patients treated with immunotherapy had a statistically significant survival advantage at the 1-year compared to males (RR = 1.15; p = 0.0241). This effect was even more pronounced in vaccine-based immunotherapy, (RR = 1.29; p = 0.0158). Our study shows a meaningful difference in the immunobiology between males and females that also influences overall response to immunotherapy in the setting of glioblastoma. Our study adds to a growing body of literature examining sex differences in male and female immunology. We demonstrate both using large scale omic data sets, as well as clinical trials, that female sexually dimorphic genes are tied to immunological responses, and that females have better outcomes during GBM immunotherapy treatments. This data is critical to better inform treatment practices and further crystalizes the need for balanced trial design and prospective reporting of sex as a variable across all GBM clinical trials.

Early Post-treatment Pseudo-continuous Arterial Spin Labelling Stratifies 12 Month Survival in Gliomas

Abstract AIMS Arterial spin labelling (ASL) is a non-invasive perfusion technique that uses endogenous contrast and is proving to be of value in paediatric neuro-oncology. ASL derived rCBV has been shown to correlate with Dynamic Susceptibility Contrast (DSC) -derived CBV and could be an alternative perfusion technique when DSC is not possible. The aim of the study was to investigate whether early post-treatment tumour ASL can stratify patient survival at 12 months. METHOD 180 consecutive patients diagnosed with glioblastoma and undergoing treatment between 2017-2021 were imaged with an extended MRI protocol that included pseudo-continuous ASL (pCASL). Patients that were imaged with pCASL within 1-3 months of completing radiotherapy were identified retrospectively. Scanner generated Perfusion weighted images were inspected and regions of interest encompassing the tumour were generated and compared with a control region in the contra-lateral grey matter. Overall survival data was collated and a comparison of tumour ASL was assessed with t-test statistics between patients surviving &amp;lt; and &amp;gt;12 months. RESULTS 43 patients were identified (23 male, median age 58 years, diagnoses: IDHwt-GBM 17, IDHmut-Astrocytoma 13, IDHmut 1p19q co-deleted Oligodendroglioma 13). Tumour ASL was 3.22 (± 2.1) in patients that survived less than 12 months compared to 1.64 (± 1.9) in patients that survived greater than 12 months, p=0.02). CONCLUSION Early post-treatment ASL can stratify patient survival at 12 months and show promise as an alternative to DSC perfusion in the prognostication of patients being treated for glioma.

A Novel Predictive Model for Adrenocortical Carcinoma Based on Hypoxia- and Ferroptosis-Related Gene Expression

BackgroundThe impact of hypoxia on ferroptosis is important in cancer proliferation, but no predictive model combining hypoxia and ferroptosis for adrenocortical carcinoma (ACC) has been reported. The purpose of this study was to construct a predictive model based on hypoxia- and ferroptosis-related gene expression in ACC.MethodsWe assessed hypoxia- and ferroptosis-related gene expression using data from 79 patients with ACC in The Cancer Genome Atlas (TCGA). Then, a predictive model was constructed to stratify patient survival using least absolute contraction and selection operation regression. Gene expression profiles of patients with ACC in the Gene Expression Omnibus (GEO) database were used to verify the predictive model.ResultsBased on hypoxia-related gene expression, 79 patients with ACC in the TCGA database were divided into three molecular subtypes (C1, C2, and C3) with different clinical outcomes. Patients with the C3 subtype had the shortest survival. Ferroptosis-related genes exhibited distinct expression patterns in the three subtypes. A predictive model combining hypoxia- and ferroptosis-related gene expression was constructed. A nomogram was constructed using age, sex, tumor stage, and the predictive gene model. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the gene signature was mainly related to the cell cycle and organelle fission.ConclusionThis hypoxia-and ferroptosis-related gene signature displayed excellent predictive performance for ACC and could serve as an emerging source of novel therapeutic targets in ACC.

Pan-Cancer HLA Gene-Mediated Tumor Immunogenicity and Immune Evasion.

Taken together, we highlight the prognostic potential of HLA genes in immunotherapies and suggest that higher tumor immunogenicity mediated by HLA expression may sometimes lead to tumor escape under strong selective pressure.

Sexual dimorphism of the immune system predicts clinical outcomes in glioblastoma immunotherapy: A systematic review and meta-analysis.

BackgroundBiological differences based on sex have been documented throughout the scientific literature. Glioblastoma (GBM), the most common primary malignant brain tumor in adults, has a male sex incidence bias, however, no clinical trial data examining differential effects of treatment between sexes currently exists.MethodWe analyzed genomic data, as well as clinical trials, to delineate the effect of sex on the immune system and GBM outcome following immunotherapy.ResultsWe found that in general females possess enriched immunological signatures on gene set enrichment analysis, which also stratified patient survival when delineated by sex. Female GBM patients treated with immunotherapy had a statistically significant survival advantage at the 1-year compared to males (relative risk [RR] = 1.15; P = .0241). This effect was even more pronounced in vaccine-based immunotherapy (RR = 1.29; P = .0158).ConclusionsOur study shows a meaningful difference in the immunobiology between males and females that also influences the overall response to immunotherapy in the setting of GBM.

Abstract 94: Multi-compartment reprogramming and spatially-resolved interactions in frozen pancreatic cancer with and without neoadjuvant chemotherapy and radiotherapy at single-cell resolution

Abstract A molecular classification of pancreatic ductal adenocarcinoma (PDAC) that informs clinical management remains elusive. Previously identified bulk expression subtypes in the untreated setting were influenced by contaminating stroma whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Two consensus subtypes have arisen from these prior efforts: (1) classical-like, and (2) basal-like. Basal-like tumors were associated with worse survival in the metastatic setting but attempts to refine this binary classification have failed to further stratify patient survival. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for banked frozen PDAC specimens and studied a cohort of untreated resected primary tumors (n ~ 20). Gene expression programs learned across malignant cell and cancer-associated fibroblast (CAF) profiles uncovered a clinically-relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Digital spatial profiling revealed an association between malignant cells expressing basal-like programs and greater immune infiltration with relatively fewer macrophages, whereas those exhibiting classical-like programs were linked to inflammatory CAFs and macrophage-predominant microniches. Recent clinical trials have supported the increasing adoption of neoadjuvant therapy to aggressively address the risk of micro-metastatic spread and to circumvent concerns of treatment tolerance in the postoperative setting. There is an urgent need to understand how preoperative treatment impacts residual tumor cells and their interactions with other cell types in the tumor microenvironment to identify additional therapeutic vulnerabilities that can be exploited. Towards this end, we performed snRNA-seq on an unmatched cohort of neoadjuvant-treated resected primary tumors (n ~ 25) with most cases involving FOLFIRINOX chemotherapy followed by chemoradiation. Remarkably, the quality of single-nucleus mRNA profiles was comparable between heavily pre-treated and untreated specimens. We identified differentially expressed genes between treated and untreated samples to infer cell-type specific reprogramming in the residual tumor. This analysis revealed that in the neoadjuvant treatment context, there was lower expression of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states. Our refined molecular taxonomy and spatial resolution may help advance precision oncology in PDAC through informative stratification in clinical trials and insights into compartment-specific therapies. Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Payman Yadollahpour, Jason Reeves, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Samouil Farhi, Denis Schapiro, George Eng, Jason M. Schenkel, William A. Freed-Pastor, Orr Ashenberg, Clifton Rodrigues, Domenic Abbondanza, Toni Delorey, Devan Phillips, Jorge Roldan, Debora Ciprani, Marina Kern, Jaimie L. Barth, Daniel R. Zollinger, Kit Fuhrman, Robin Fropf, Joseph Beechem, Colin Weekes, Cristina R. Ferrone, Jennifer Y. Wo, Theodore S. Hong, Orit Rozenblatt-Rosen, Andrew J. Aguirre, Mari Mino-Kenudson, Carlos Fernandez-del- Castillo, Andrew S. Liss, David T. Ting, Tyler Jacks, Aviv Regev. Multi-compartment reprogramming and spatially-resolved interactions in frozen pancreatic cancer with and without neoadjuvant chemotherapy and radiotherapy at single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 94.

Apolipoprotein E Promotes Immune Suppression in Pancreatic Cancer through NF-κB-Mediated Production of CXCL1.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with few effective therapeutic options. PDAC is characterized by an extensive fibroinflammatory stroma that includes abundant infiltrating immune cells. Tumor-associated macrophages (TAM) are prevalent within the stroma and are key drivers of immunosuppression. TAMs in human and murine PDAC are characterized by elevated expression of apolipoprotein E (ApoE), an apolipoprotein that mediates cholesterol metabolism and has known roles in cardiovascular and Alzheimer's disease but no known role in PDAC. We report here that ApoE is also elevated in peripheral blood monocytes in PDAC patients, and plasma ApoE protein levels stratify patient survival. Orthotopic implantation of mouse PDAC cells into syngeneic wild-type or in ApoE-/- mice showed reduced tumor growth in ApoE-/- mice. Histologic and mass cytometric (CyTOF) analysis of these tumors showed an increase in CD8+ T cells in tumors in ApoE-/- mice. Mechanistically, ApoE induced pancreatic tumor cell expression of Cxcl1 and Cxcl5, known immunosuppressive factors, through LDL receptor and NF-κB signaling. Taken together, this study reveals a novel immunosuppressive role of ApoE in the PDAC microenvironment. SIGNIFICANCE: This study shows that elevated apolipoprotein E in PDAC mediates immune suppression and high serum apolipoprotein E levels correlate with poor patient survival.See related commentary by Sherman, p. 4186.

Post-transplant Lymphoproliferative Disorders After Liver Transplantation: A Retrospective Cohort Study Including 1954 Transplants.

Post‐transplant lymphoproliferative disorders (PTLDs) are life‐threatening neoplasms after organ transplantation. Because of their rarity and multiple grades of malignancy, the incidence, outcomes, and clinicopathological features affecting patient survival after liver transplantation (LT) remain unclear. We reviewed 1954 LTs in 1849 recipients (1990‐2020), including 886 pediatric (<18 years of age) and 963 adult recipients. The following clinicopathological factors were studied: age, sex, liver etiologies, malignancy grades, Epstein‐Barr virus status, performance status (PS), Ann Arbor stage, international prognostic index, and histopathological diagnosis. Of 1849 recipients, 79 PTLD lesions (4.3%) were identified in 70 patients (3.8%). After excluding 3 autopsy cases incidentally found, 67 (45 pediatric [5.1%] and 22 adult [2.3%]) patients were finally enrolled. Comorbid PTLDs significantly worsened recipient survival compared with non‐complicated cases (P < 0.001). The 3‐year, 5‐year, and 10‐year overall survival rates after PTLD diagnosis were 74%, 66%, and 58%, respectively. The incidence of PTLDs after LT (LT‐PTLDs) was significantly higher (P < 0.001) with earlier onset (P = 0.002) in children, whereas patient survival was significantly worse in adults (P = 0.002). Univariate and multivariate analyses identified the following 3 prognostic factors: age at PTLD diagnosis ≥18 years (hazard ratio [HR], 11.2; 95% confidence interval [CI], 2.63‐47.4; P = 0.001), PS ≥2 at diagnosis (HR, 6.77; 95% CI, 1.56‐29.3; P = 0.01), and monomorphic type (HR, 6.78; 95% CI, 1.40‐32.9; P = 0.02). A prognostic index, the “LT‐PTLD score,” that consists of these 3 factors effectively stratified patient survival and progression‐free survival (P = 0.003 and <0.001, respectively). In conclusion, comorbid PTLDs significantly worsened patient survival after LT. Age ≥18 years and PS ≥2 at PTLD diagnosis, and monomorphic type are independent prognostic factors, and the LT‐PTLD score that consists of these 3 factors may distinguish high‐risk cases and guide adequate interventions.

Abstract PO-001: Deep learning-based image analysis of the histological Glasgow Microenvironment Score in patients with colorectal cancer

Abstract Background: Efforts to prognostically stratify colorectal cancer (CRC) patients using histological samples has led to the development of the Glasgow Microenvironment Score (GMS). However, the subjective nature of the GMS assessment criteria makes reproducing the score challenging. Therefore, the aim of the current study was to assess the clinical utility of an image analysis-based approach. Methods: In two cohorts of patients (a test cohort of 297 Stage II/III CRC patients from Norway and a validation cohort of 233 Stage II/III CRC patients from Scotland), one H&amp;E section representing the deepest point of tumour invasion was assessed for Tumour Stroma Percentage (TSP) and the Klintrup-Makinen (KM) local immune grade to produce the GMS. A decision forest-based classifier was built to segment the tumour and stroma compartments, having been trained on a hand annotated subset of the test cohort. A UNET convolutional neural network was trained on the same training set as the decision forest algorithm to segment and quantify the tumour and stroma components. Each section was also annotated for the invasive margin and a manually built, threshold-based lymphocyte detection algorithm applied to quantify the local immune grade. Results: The decision forest classifier was able to stratify the test cohort patients for cancer specific survival (P = 0.009) based on the patients TSP, however failed to stratify patients from the validation cohort (P = 0.055) for TSP without retraining, therefore the deep learning approach was used for this cohort. Individually, the TSP (P = 0.001) generated from the UNET based classifier and the quantification of the local immune grade (P = 0.005), both significantly stratified validation cohort patients for survival. When the individual scores were combined into a digital version of the GMS, not only did the image analysis approach significantly stratify patient survival (P &amp;lt; 0.0001), it also significantly correlated with the manual scores both statistically (Chi Square = 32, P = 1.5 × 10−8) and in terms of survival estimates per patient group (GMS 0 - manual = 159 months vs digital = 159 months; GMS 1 – manual = 136 months vs digital = 139 months ; GMS2 – manual 101 months vs 97 months). To negate the need for any annotation prior to analysis, the lymphocyte detection algorithm was applied to the stroma areas determined by the UNET algorithm. This fully automated digital version of the GMS was able to stratify validation cohort patients into the 3 prognostic groups based on CSS (P &amp;lt; 0.001), however, GMS 0 had a lower survival estimate (automated = 148 vs annotated = 159 months). Conclusion: An H&amp;E based image analysis approach to the GMS, on a single H&amp;E slide, holds prognostic significance for CRC patients and correlates significantly with manual pathological assessment, making the assessment of the GMS more time efficient, reproducible, and clinically relevant. Citation Format: Christopher J. Bigley, John Waller, Alison Bigley, Karin Oien, Joanne Edwards, Antonia Roseweir. Deep learning-based image analysis of the histological Glasgow Microenvironment Score in patients with colorectal cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-001.

Tumor Microenvironmental Prognostic Risk in Primary Operable Small Intestinal Adenocarcinoma.

The tumor microenvironment (TME) has become an important area of investigation with respect to improving prognosis in malignancies. Here we evaluated TME prognostic risk in small intestinal adenocarcinomas based on histologic assessment of tumor budding at the peritumoral-invasive front (pTB) and stromal tumor-infiltrating lymphocytes (sTILs). pTB and sTILs were analyzed in 230 surgically resected small intestinal adenocarcinomas, as recommended by the International Tumor Budding Consensus Conference (ITBCC) and the International TILs Working Group (ITWG). On the basis of high levels of pTB count (≥10) and sTIL density (≥20%), we combined pTB and sTIL to produce a collective TME-based prognostic risk index: low-risk (pTBLow/sTILHigh; n=39, 17.0%), intermediate-risk (pTBLow/sTILLow or pTBHigh/sTILHigh; n=99, 43.0%), and high-risk groups (pTBHigh/sTILLow; n=92, 40.0%). TME risk index provided better prognostic stratification than the individual pTB and sTIL (14.9 vs. 6.7 vs. 10.3). Tumors with higher TME prognostic risk were associated with an infiltrative growth pattern and nonintestinal immunophenotype (both P=0.001), pancreatic invasion (P=0.010), lymphovascular (P<0.001) or perineural invasion (P=0.006), higher T-category (P<0.001), N-category (P=0.004), and stage grouping (P=0.002), and KRAS mutation (P=0.008). In multivariate analysis, higher TME prognostic risk index (P<0.001), distal tumor location and nonintestinal immunophenotype (both P=0.001), higher N-category (P<0.001), and microsatellite stable (P=0.015) were worse-independent prognosticators. TME prognostic risk index consistently stratified patient survival regardless of tumor location (P<0.001 in proximal; P=0.002 in distal), stages (P<0.001 in lower stages I to II; P=0.028 in stage III), and DNA mismatch repair gene status (P<0.001 in microsatellite stable; P=0.001 in microsatellite instability). TME risk index is a powerful prognostic predictor for risk stratification of patients with small intestinal adenocarcinoma.

Importance of Examined Lymph Node Number in Accurate Staging and Enhanced Survival in Resected Gastric Adenocarcinoma-The More, the Better? A Cohort Study of 8,696 Cases From the US and China, 2010-2016.

BackgroundWhile most guidelines advocate D2 lymphadenectomy for non-metastatic gastric adenocarcinoma (nmGaC), it is not always performed as standard of care outside East Asia. The recommended minimal examined lymph node (ELN) count in nmGaC to stage cancer accurately varies largely across guidelines, and the optimal count to satisfactorily stratify patient survival has yet to be determined. This large cohort study aimed at robustly defining the minimal and optimal thresholds of examined lymph node (ELN) number in non-metastatic gastric adenocarcinoma (nmGaC).MethodsData on nmGaC patients operated in 2010–2016 and surviving ≥3 months were retrieved from the US SEER-18 Program and a Chinese multi-institutional gastric cancer database (MIGC). The correlation of ELN count with stage migration and patient survival were quantified with the use of the multivariable-adjusted logistic and proportional hazards Cox models, respectively. The sequences of odds ratios (ORs) and hazard ratios (HRs) for each additional ELN were smoothed, and the structural breakpoints were determined.ResultsTogether 7,228 patients from the US and 1,468 from China were analyzed, encompassing 23,114 person-years of follow-up. The mean ELN count was 20 in the US and 30 in China. With more ELNs, both cohorts significantly showed proportional increases from lower to higher nodal stage (ORSEER = 1.03, 95%-CI = 1.03–1.04; ORMIGC = 1.02, 95%-CI = 1.02–1.03) and sequential enhancements in postoperative survival (HRSEER = 0.97, 95%-CI = 0.97–0.97; HRMIGC = 0.98, 95%-CI = 0.97–0.99). Correlations for both stage migration and survival were still significant in most subgroups by patient, cancer, and management factors. Breakpoint analyses revealed a minimum threshold ELN count of 17 and an optimum count of 33, which were validated in both cohorts with good efficacy to differentiate probabilities of both stage migration and survival.ConclusionIn resected nmGaC patients with anticipated survival ≥3 months, more ELNs are correlated with more accurate staging, which may partly explain the survival correlation. This observational investigation does not indicate causality. Our findings robustly conclude 17 ELNs as the minimum and propose 33 ELNs as the optimum thresholds, to assess the quality of lymph node examination and to stratify postsurgical survival.

The molecular feature of macrophages in tumor immune microenvironment of glioma patients

BackgroundGliomas are one of the most common types of primary tumors in central nervous system. Previous studies have found that macrophages actively participate in tumor growth. MethodsWeighted gene co-expression network analysis was used to identify meaningful macrophage-related gene genes for clustering. Pamr, SVM, and neural network were applied for validating clustering results. Somatic mutation and methylation were used for defining the features of identified clusters. Differentially expressed genes (DEGs) between the stratified groups after performing elastic regression and principal component analyses were used for the construction of MScores. The expression of macrophage-specific genes were evaluated in tumor microenvironment based on single cell sequencing analysis. A total of 2365 samples from 15 glioma datasets and 5842 pan-cancer samples were used for external validation of MScore. ResultsMacrophages were identified to be negatively associated with the survival of glioma patients. Twenty-six macrophage-specific DEGs obtained by elastic regression and PCA were highly expressed in macrophages at single-cell level. The prognostic value of MScores in glioma was validated by the active proinflammatory and metabolic profile of infiltrating microenvironment and response to immunotherapies of samples with this signature. MScores managed to stratify patient survival probabilities in 15 external glioma datasets and pan-cancer datasets, which predicted worse survival outcome. Sequencing data and immunohistochemistry of Xiangya glioma cohort confirmed the prognostic value of MScores. A prognostic model based on MScores demonstrated high accuracy rate. ConclusionOur findings strongly support a modulatory role of macrophages, especially M2 macrophages in glioma progression and warrants further experimental studies.

The evaluation of the 8th and 7th edition of the American joint committee on cancer tumor classification for distal cholangiocarcinoma: the proposal of a modified new tumor classification

BackgroundThe 7th and 8th editions of the American Joint Committee on Cancer (AJCC) tumor (T) classification of distal cholangiocarcinoma (DCC), which are based on either layer or depth, may not accurately stratify patient survival. MethodsA total of 121 patients who underwent resection for DCC between 2002 and 2016 were analyzed. The impact of the AJCC staging system on survival was examined and a new T classification was established based on independent prognostic factors. ResultsRegarding overall survival, the optimal depth of invasion (DOI) cut-off value (8 mm) was the only independent prognostic factor. Regarding the relapse-free survival (RFS), a DOI >8 mm, portal vein (PV) invasion, and duodenal or pancreatic invasion were independent prognostic factors. A new T classification was developed as follows: T1, no invasion of adjacent organs; T2, invasion of the duodenum or pancreas; T3, invasion >8 mm into the bile duct wall; and T4, invasion of the PV or arteries. There were no significant differences in RFS according to the 8th edition of the AJCC. However, significant differences were observed in the RFS between T1 and T2 and between T2 and T3. ConclusionA new T classification based on the layer and depth may be more feasible.

EPEN-21. IMPAIRED NEURONAL-GLIAL FATE SPECIFICATION IN PEDIATRIC EPENDYMOMA REVEALED BY SINGLE-CELL RNA-SEQ

Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets including IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.

Abstract PR-007: Single-nucleus and spatial transcriptomics of archival pancreatic ductal adenocarcinoma reveals multi-compartment reprogramming after neoadjuvant treatment

Abstract Molecular subtyping of pancreatic ductal adenocarcinoma (PDAC) remains in its nascent stages and does not currently inform clinical management or therapeutic development. Previously identified bulk expression subtypes in the untreated setting were influenced by contaminating stroma whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Two consensus subtypes have arisen from these prior efforts: (1) classical-pancreatic, encompassing a spectrum of pancreatic lineage precursors, and (2) basal-like/squamous/quasi-mesenchymal, characterized by loss of endodermal identity and aberrations in chromatin modifiers. Basal-like tumors were associated with poorer responses to chemotherapy and worse survival in the metastatic setting but attempts to refine this binary classification have failed to further stratify patient survival. Recent clinical trials have supported the increasing adoption of neoadjuvant therapy to aggressively address the risk of micro-metastatic spread and to circumvent concerns of treatment tolerance in the postoperative setting. There is an urgent need to understand how preoperative treatment reprograms residual tumor cells to identify additional therapeutic vulnerabilities that can be exploited in combination with neoadjuvant CRT. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors (n = 15) and those that received neoadjuvant CRT (n = 11). Gene expression programs learned across malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification (median survival: 11.2 months in highest risk group to 44.7 months in lowest risk group) compared to prior classifications. Moreover, in the neoadjuvant treatment context, there was lower expression of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. These results suggest that differentiated endodermal phenotypes are only prevalent enough to be detected under treatment selection pressure and when observed in treatment-naïve bulk studies, may reflect normal cell contamination. Spatially-resolved transcriptomics revealed an association between malignant cells expressing basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to distinct therapeutic susceptibilities. Our refined molecular taxonomy and spatial resolution may help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system. Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Samouil Farhi, Denis Schapiro, Jason Reeves, Daniel R. Zollinger, George Eng, Jason M. Schenkel, William A. Freed-Pastor, Clifton Rodrigues, Domenic Abbondanza, Debora Ciprani, Jennifer Y. Wo, Theodore S. Hong, Andrew J. Aguirre, Orit Rozenblatt-Rosen, Mari Mino-Kenudson, Carlos Fernandez-del Castillo, Andrew S. Liss, Tyler E. Jacks, Aviv Regev. Single-nucleus and spatial transcriptomics of archival pancreatic ductal adenocarcinoma reveals multi-compartment reprogramming after neoadjuvant treatment [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-007.

EPCO-35. SINGLE-CELL RNA-SEQ OF PEDIATRIC EPENDYMOMA REVEALS PROGNOSTIC IMPACT OF IMPAIRED NEURONAL-GLIAL FATE SPECIFICATION

Abstract Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/single nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets such as IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.

Drug Response Associated With and Prognostic lncRNAs Mediated by DNA Methylation and Transcription Factors in Colon Cancer.

Colon cancer is the most commonly diagnosed malignancy and the leading cause of cancer deaths worldwide. As well as lifestyle, genetic and epigenetic changes are key factors that influence the risk of colon cancer. However, the impact of epigenetic alterations in non-coding RNAs and their consequences in colon cancer have not been fully characterized. We detected differential methylation sites (DMSs) in long non-coding RNA (lncRNA) promoters and identified lncRNA expression quantitative trait methylations (lncQTMs) by association tests. To investigate how transcription factor (TF) binding was affected by DNA methylation, we characterized the occurrence of known TFs among DMSs collected from the MEME suite. We further combined methylome and transcriptome data to construct TF–methylation–lncRNA relationships. To study the role of lncRNAs in drug response, we used pharmacological and lncRNA profiles from the Cancer Cell Line Encyclopedia (CCLE) and investigated the association between lncRNAs and drug activity. We also used combinations of TF–methylation–lncRNA relationships to stratify patient survival using a risk model. DNA methylation sites displayed global hyper-methylation in lncRNA promoters and tended to have negative relationships with the corresponding lncRNAs. Negative lncQTMs located near transcription start sites (TSSs) had more significant correlations with the corresponding lncRNAs. Some lncRNAs found to be mediated by the interplay between DNA methylation and TFs were previously identified as markers for colon cancer. We also found that the ELF1-cg05372727- LINC00460 relationship were prognostic signatures for colon cancer. These findings suggest that lncRNAs mediated by the interplay between DNA methylation and TFs are promising predictors of drug response, and that combined TF–methylation–lncRNA can serve as a prognostic signature for colon cancer.

Multi-Institutional Prospective Validation of Prognostic mRNA Signatures in Early Stage Squamous Lung Cancer (Alliance).

Surgical resection is curative for some patients with early lung squamous cell carcinoma. Staging and clinical factors do not adequately predict recurrence risk. We sought to validate the discriminative performance of proposed prognostic gene expression signatures at a level of rigor sufficient to support clinical use. The two-stage validation used independent core laboratories, objective quality control standards, locked test parameters, and large multi-institutional specimen and data sets. The first stage validation confirmed a signature's ability to stratify patient survival. The second-stage validation determined which signature(s) optimally improved risk discrimination when added to baseline clinical predictors. Participants were prospectively enrolled in institutional (cohort I) or cooperative group (cohort II) biospecimen and data collection protocols. All cases underwent a central review of clinical, pathologic, and biospecimen parameters using objective criteria to determine final inclusion (cohort I: n= 249; cohort II: n= 234). Primary selection required that a signature significantly predict a 3-year survival after surgical resection in cohort I. Signatures meeting this criterion were further tested in cohort II, comparing risk prediction using baseline risk factors alone versus in combination with the signature. Male sex, advanced age, and higher stage were associated with shorter survival in cohort I and established a baseline clinical model. Of the three signatures validated in cohort I, one signature was validated in cohort II and statistically significantly enhanced the prognosis relative to the baseline model (C-index difference 0.122; p < 0.05). These results represent the first rigorous validation of a test appropriate to direct adjuvant treatment or clinical trials for patients with lung squamous cell carcinoma.