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The survival prediction for patients with resected pancreatic adenocarcinoma by using the Tumor-Node-Metastasis (TNM) staging system remains limited. A nomogram is a efficient tool that can be used to predict the outcome of patients with various types of malignancy. The present study aimed to develop and validate a nomogram for patients with resected pancreatic adenocarcinoma. A total of 368 patients (258 in the training set and 110 in the validation set) who underwent pancreatic adenocarcinoma resection at the China National Cancer Center between January 2008 and October 2018 were included in the present study. The nomogram was established according to the results from Cox multivariate analysis, which was validated by discrimination and calibration. The area under the receiver operating characteristic curve (AUC) was determined to assess the accuracy of survival predictions. The results from multivariate analysis in the training set demonstrated that blood transfusion, T-stage, N-stage, tumor grade, capsule invasion, carbohydrate antigen 199, neutrophil percentage and adjuvant therapy were independent prognostic factors for overall survival (OS; all P<0.05). Subsequently, a nomogram predicting the 1-year, 3-year and 5-year OS rates, with favorable calibration, was established based on the independent prognostic factors. The concordance indices of the nomogram were higher compared with the TNM staging system in both training and validation sets. Furthermore, a clear risk stratification system based on the nomogram was used to classify patients into the three following groups: Low-risk group (≤168), moderate-risk group (168-255) and high-risk group (>255). The risk stratification system demonstrated an improved ability in predicting the 1-year, 3-year and 5-year OS rates compared with the TNM system (AUC, 0.758, 0.709 and 0.672 vs. AUC, 0.614, 0.604 and 0.568; all P<0.05). The present study developed and validated a nomogram for patients with resected pancreatic adenocarcinoma by including additional independent prognostic factors, including tumor marker, immune index, surgical information, pathological data and adjuvant therapy. Taken together, the results from the present study indicated an improved performance of the nomogram in predicting the prognosis of patients with resected pancreatic adenocarcinoma compared with the TNM staging system.

Background. The 8th American Joint Committee on Cancer (AJCC) staging system for pancreatic ductal adenocarcinoma (PDAC) outperforms its previous version in reproducibility but not in survival discrimination. Tumor grade, an indicator of the aggressive biology of PDAC, has been suggested as a reliable prognostic factor. This study aimed to construct a novel staging system with greater prognostication for resectable PDAC by incorporating tumor grade into the 8th AJCC system. Methods. A total of 9966 patients with resectable PDAC from the Surveillance Epidemiology and End Results (SEER) database were randomly separated into training and interval validation sets. Another 324 patients from our center were included as an external validation set. We proposed a novel staging system by sorting the substages yielded by a combination of T, N, and tumor grade based on their overall survival (OS) and grouping them into several stages. Prognostic homogeneity and discrimination were determined using the likelihood ratio χ2 and the linear trend χ2 test, respectively. Prognostic accuracies were evaluated by the area under the receiver operating characteristics curve (AUC). Results. Using the 8th AJCC system, the prognosis of patients within the same stage was quite heterogeneous among different substages. The multivariate Cox model identified the tumor grade (hazard ratio 1.333, 95% confidence interval 1.250–1.423, p<0.001) was an independent prognostic factor of the OS. In the training set, the AUC, homogeneity, and discriminatory ability were superior for the novel staging system than for the 8th AJCC system (0.642 vs. 0.615, 403.4 vs. 248.6, and 335.1 vs. 218.0, respectively). Similar results were observed in the internal and external validation sets. Conclusions. The novel staging system incorporating tumor grade into the 8th AJCC system was associated with better prognostic accuracy, homogeneity, and discriminatory ability among resectable PDAC patients. Moreover, the novel staging system also allowed possibly adjuvant chemotherapy decisions.

Metabolic reprogramming has been proposed to be a hallmark of cancer. Aside from the glycolytic pathway, the metabolic changes of cancer cells primarily involve amino acid metabolism. However, in glioma, the characteristics of the amino acid metabolism‐related gene set have not been systematically profiled. In the present study, RNA sequencing expression data from 309 patients in the Chinese Glioma Genome Atlas database were included as a training set, while another 550 patients within The Cancer Genome Atlas database were used to validate. Consensus clustering of the 309 samples yielded two robust groups. Compared with Cluster1, Cluster2 correlated with a better clinical outcome. We then developed an amino acid metabolism‐related risk signature for glioma. Our results showed that patients in the high‐risk group had dramatically shorter overall survival than low‐risk counterparts in any subgroup, stratified by isocitrate dehydrogenase and 1p/19q status based on the 2016 World Health Organization classification guidelines. The 30‐gene signature showed better prognostic value than the traditional factors “age” and “grade” by analyzing the receiver operating characteristic curve with areas under curve of 0.966, 0.692, 0.898 and 0.975, 0.677, 0.885 for 3‐ and 5‐year survival, respectively. Moreover, univariate and multivariate analysis showed that the 30‐gene signature was an independent prognostic factor for glioma. Furthermore, Gene Ontology analysis and Gene Set Enrichment Analysis showed that tumors with a high risk score correlated with various aspects of the malignancy of glioma. In summary, we demonstrated a novel amino acid metabolism‐related risk signature for predicting prognosis for glioma. In the present study, for the first time, we identified an amino acid metabolism‐related risk signature analyzed by bioinformatics for glioma patients. Further, the 30‐gene signature could not only strikingly stratify the clinical and molecular characteristics of glioma, but showed superior evaluation of prognosis than did the traditional factors. Of note, we identified that the amino acid metabolism‐related risk signature remained an independent prognostic factor after adjustment for clinical and molecular features.

Lipid metabolism reprogramming plays important role in cell growth, proliferation, angiogenesis and invasion in cancers. However, the diverse lipid metabolism programmes and prognostic value during glioma progression remain unclear. Here, the lipid metabolism‐related genes were profiled using RNA sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database. Gene ontology (GO) and gene set enrichment analysis (GSEA) found that glioblastoma (GBM) mainly exhibited enrichment of glycosphingolipid metabolic progress, whereas lower grade gliomas (LGGs) showed enrichment of phosphatidylinositol metabolic progress. According to the differential genes of lipid metabolism between LGG and GBM, we developed a nine‐gene set using Cox proportional hazards model with elastic net penalty, and the CGGA cohort was used for validation data set. Survival analysis revealed that the obtained gene set could differentiate the outcome of low‐ and high‐risk patients in both cohorts. Meanwhile, multivariate Cox regression analysis indicated that this signature was a significantly independent prognostic factor in diffuse gliomas. Gene ontology and GSEA showed that high‐risk cases were associated with phenotypes of cell division and immune response. Collectively, our findings provided a new sight on lipid metabolism in diffuse gliomas.

Due to the rare incidence of spinal cord astrocytomas, their molecular features remain unclear. Here, we characterized the landscapes of mutations in H3 K27M, isocitrate dehydrogenase 1 ( IDH1 ) R132H, BRAF V600E, and the TERT promoter in 83 diffuse spinal cord astrocytic tumors. Among these samples, thirty-five patients had the H3 K27M mutation; this mutant could be observed in histological grade II (40%), III (40%), and IV (20%) astrocytomas. IDH1 mutations were absent in 58 of 58 cases tested. The BRAF V600E mutation (7/57) was only observed in H3-wildtype astrocytomas, and was associated with a better prognosis in all histological grade II/III astrocytomas. TERT promoter mutations were observed in both H3 K27M-mutant (4/25) and -wildtype (9/33) astrocytomas, and were associated with a poor prognosis in H3-wildtype histological grade II/III astrocytomas. In the 2016 WHO classification of CNS tumors, H3 K27M-mutant diffuse midline gliomas, including spinal cord astrocytomas, are categorized as WHO grade IV. Here, we noticed that the median overall survival of histological grade II/III H3 K27M-mutant cases ( n  = 28) was significantly longer than that of either the total histological grade IV cases ( n  = 12) or the H3 K27M-mutant histological grade IV cases ( n  = 7). We also directly compared H3 K27M-mutant astrocytomas to H3-wildtype astrocytomas of the same histological grade. In histological grade II astrocytomas, compared to H3-wildtype cases ( n  = 37), H3 K27M-mutant patients ( n  = 14) had showed a significantly higher Ki-67-positive rate and poorer survival rate. However, no significant differences in these parameters were observed in histological grade III and IV astrocytoma patients. In conclusion, these findings indicate that spinal cord astrocytomas are considerably different from hemispheric and brainstem astrocytomas in terms of their molecular profiles, and that the histological grade cannot be ignored when assessing the prognosis of H3 K27M-mutant spinal cord astrocytomas.

H3 K27‐altered diffuse midline glioma is a highly lethal pediatric‐type tumor without efficacious treatments. Recent findings have highlighted the heterogeneity among diffuse midline gliomas with different locations and ages. Compared to tumors located in the brain stem and thalamus, the molecular and clinicopathological features of H3 K27‐altered spinal cord glioma are still largely elusive, thus hindering the accurate management of patients. Here we aimed to characterize the clinicopathological and molecular features of H3 K27M‐mutant spinal cord glioma in 77 consecutive cases. We found that the H3 K27M‐mutant spinal cord glioma, with a median age of 35 years old, had a significantly better prognosis than H3 K27M‐mutant brain tumors. We noticed a molecular heterogeneity of H3 K27M‐mutant spinal cord astrocytoma via targeted sequencing with 34 cases. TP53 mutation which occurred in 58.8% of cases is mutually exclusive with PPM1D (26%) and NF1 (44%) mutations. The TP53‐mutant cases had a significantly higher number of copy number variants (CNV) and a marginally higher proportion of pediatric patients (age at diagnosis <18 years old, p = 0.056). Cox regression and Kaplan–Meier curve analysis showed that the higher number of CNV events (≥3), chromosome (Chr) 9p deletion, Chr 10p deletion, ATRX mutation, CDK6 amplification, and retinoblastoma protein (RB) pathway alteration are associated with worse survival. Cox regression analysis with clinicopathological features showed that glioblastoma histological type and a high Ki‐67 index (>10%) are associated with a worse prognosis. Interestingly, the histological type, an independent prognostic factor in multivariate Cox regression, can also stratify molecular features of H3 K27M‐mutant spinal cord glioma, including the RB pathway, KRAS/PI3K pathway, and chromosome arms CNV. In conclusion, although all H3 K27M‐mutant spinal cord diffuse glioma were diagnosed as WHO Grade 4, the histological type, molecular features representing chromatin instability, and molecular alterations associated with accelerated cell proliferative activity should not be ignored in clinical management. In a large cohort (n=77), we characterized the molecular, clinicopathological, and prognostic characteristics of H3 K27M‐mutant spinal cord diffuse glioma. ATRX mutation, CDK6 amplification, RB pathway alteration, a higher number of Copy number variant (CNV) events, chromosome (Chr) 9p deletion, and Chr 10p deletion is associated with worse survival. Glioblastoma histological type and a high Ki‐67 index (>10%) are associated with a worse prognosis. Interestingly, the histological type, an independent prognostic factor in multivariate Cox regression, can stratify molecular features of H3 K27M‐mutant spinal cord glioma, including the RB pathway and PI3K pathway.

Transcriptomic data derived from bulk sequencing have been applied to delineate the tumor microenvironment (TME) and define immune subtypes in various cancers, which may facilitate the design of immunotherapy treatment strategies. We herein gathered published gene expression data from diffuse lower‐grade glioma (LGG) patients to identify immune subtypes. Based on the immune gene profiles of 402 LGG patients from The Cancer Genome Atlas, we performed consensus clustering to determine robust clusters of patients, and evaluated their reproducibility in three Chinese Glioma Genome Atlas cohorts. We further integrated immunogenomics methods to characterize the immune environment of each subtype. Our analysis identified and validated three immune subtypes—Im1, Im2, and Im3—characterized by differences in lymphocyte signatures, somatic DNA alterations, and clinical outcomes. Im1 had a higher infiltration of CD8+ T cells, Th17, and mast cells. Im2 was defined by elevated cytolytic activity, exhausted CD8+ T cells, macrophages, higher levels of aneuploidy, and tumor mutation burden, and these patients had worst outcome. Im3 displayed more prominent T helper cell and APC coinhibition signatures, with elevated pDCs and macrophages. Each subtype was associated with distinct somatic alterations. Moreover, we applied graph structure learning‐based dimensionality reduction to the immune landscape and revealed significant intracluster heterogeneity with Im2 subtype. Finally, we developed and validated an immune signature with better performance of prognosis prediction. Our results demonstrated the immunological heterogeneity within diffuse LGG and provided valuable stratification for the design of future immunotherapy. We classified diffuse lower‐grade gliomas (LGGs) into three distinct subtypes based on consensus clustering of immune‐related gene expression profiles. Each of the three immune subtypes was associated with distinct molecular and cellular features, and clinical outcomes. The identification of immune‐related subtypes may facilitate the optimal selection of LGG patients responsive to immunotherapy.

PurposeDue to the rarity of diffuse spinal cord astrocytoma, an effective model is still lacking to stratify their prognosis. Here, we aimed to establish a prognostic model through comprehensively evaluating clinicopathological features and preoperative peripheral blood inflammatory markers in 89 cases.MethodsWe performed univariate and multivariate Cox regression to identify prognosis factors. The Kaplan–Meier curves and ROC curves were employed to compare the prognostic value of selected factors.ResultsIn addition to clinicopathological factors, we revealed the preoperative peripheral blood leukocyte count, neutrophils-to-lymphocytes ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were also significantly correlated with overall survival of spinal cord astrocytoma in univariate Cox regression, and NLR was still significant in multivariate Cox analysis. Further, we demonstrated that NLR ≤ 3.65 and preoperative McCormick score (MMS) ≤ 3 were independently correlated with better survival of WHO grade IV tumors. Meanwhile, Ki-67 < 10% and resection extent ≥ 90% were independent prognostic factors in WHO grade II/III tumors. Finally, we developed a prognostic model that had better predictive efficiencies than WHO grade and histological grade for 1-year (AUC = 76.6), 2- year (AUC = 80.9), and 3-year (AUC = 80.3) survival. This model could classify tumors into 4 classifications with increasingly poor prognosis: 1, WHO grade II/III, with Ki-67 < 10% and resection extent ≥ 90%; 2, WHO grade II/III, Ki-67 ≥ 10% or resection < 90%; 3, WHO grade IV, NLR ≤ 3.65 and MMS ≤ 3; 4, WHO grade IV, with NRL > 3.65 or MMS = 4.ConclusionWe successfully constructed a comprehensive prognostic model including preoperative peripheral blood inflammatory markers, which can stratify diffuse spinal cord astrocytoma into 4 subgroups.

Abstract BACKGROUND “Diffuse midline glioma, H3 K27M-mutant” (DMG) mainly arises within the pontine, thalamic, and spinal cord regions. Because of the rarity of spinal cord gliomas, the general knowledge surrounding DMGs is mainly based on pontine and thalamic gliomas, whereas tumor location tends to influence the clinicopathological features and prognosis. OBJECTIVE To determine the clinicopathological characteristics and molecular profiles of DMGs located in the spinal cord. METHODS The clinical and molecular pathologic features and prognosis were comprehensively analyzed in a series of 44 patients with spinal cord DMGs. RESULTS The median age was 36 yr, and 88.7% of patients (39/44) were adults (≥18 yr). Histopathologically, malignant grades included grade II (16 cases), grade III (20 cases), and grade IV (8 cases). Compared with patients with histological grade IV, patients with lower histological grade (grade II/III) were older (37 vs 24 yr, P = .020) and were associated with longer overall survival (24.1 vs 8.6 mo, P = .007). All 30 tested tumors were isocitrate dehydrogenase (IDH) wild type, and 96% of cases (22/23) presented with unmethylated O6-methylguanine-DNA methyltransferase. Univariate and multivariate analyses showed that histological grade and presurgery McCormick Scale scores were independent prognostic factors for overall survival, whereas extensive surgical resection and chemoradiotherapy were not significantly associated with improved survival. The most frequent anatomic locations were the cervical enlargement (C4-T1, n = 16) and conus medullaris (T12-L1, n = 13), which exhibited distinctive clinical characteristics and molecular features. CONCLUSION The findings provide guidelines for the evidence-based practice of the specialized management of spinal cord DMGs.

The methylation status of the promoter of MGMT gene is a crucial factor influencing clinical decision-making in patients with gliomas. MGMT pyrosequencing results are often dichotomized by a cut-off value based on an average of several tested CpGs. However, this method frequently results in a “gray zone”, representing a dilemma for physicians. We therefore propose a novel analytical model for MGMT methylation pyrosequencing. MGMT CpG heterogeneity was investigated in 213 glioma patients in two tested cohorts: cohort A in which CpGs 75–82 were tested and cohort B in which CpGs 72–78 were tested. The predictive performances of the novel and traditional averaging models were compared in 135 patients who received temozolomide using receiver operating characteristic curves and Kaplan–Meier curves, and in patients stratified according to isocitrate dehydrogenase gene mutation status. The results were validated in an independent cohort of 65 consecutive patients with high-grade gliomas from the Chinese Glioma Genome Atlas database. Heterogeneity of MGMT promoter CpG methylation level was observed in most gliomas. The optimal cut-off value for each individual CpG varied from 4–16%. The current analysis defined MGMT promoter methylation as occurring when at least three CpGs exceeded their respective cut-off values. This novel analysis could accurately predict the prognosis of patients in the methylation “gray zone” according to the standard averaging method, and improved the area under the curves from 0.67, 0.76, and 0.67 to 0.70, 0.84, and 0.72 in cohorts A, B, and the validation cohort, respectively, demonstrating superiority of this analytical method in all three cohorts. Furthermore, the advantages of the novel analysis were retained regardless of WHO grade and isocitrate dehydrogenase gene mutation status. In conclusion, this novel analytical model offers an improved clinical predictive performance for MGMT pyrosequencing results and is suitable for clinical use in patients with gliomas.