Treatment barriers and clinical outcome of children with medulloblastoma in China: a report from the Chinese Children’s Cancer Group (CCCG)

Background Medulloblastoma (MB) is the most common malignant central nervous system tumor of childhood. Management requires interdisciplinary care and is associated with unique challenges in developing regions. Here, we report the characteristics, clinical outcome and treatment barriers for Chinese children with MB based on a multi-institutional cohort from the Chinese Children’s Cancer Group (CCCG). Methods Retrospective cohort study among 12 Chinese pediatric oncology units from the CCCG Brain Tumor Workgroup on patients aged < 18 years diagnosed with MB from 2016-2019. Results 221 patients (male:female = 138:83) were included, 175 (79%) were ≥ 3 years of age, and 46 (21%) < 3 years. 177 patients (80%) were completely staged, among which 50 (28%) had metastasis and 70 (40%) were considered to have high-risk (HR) disease. Gross/near-total resection was achieved in 203 patients (92%). In patients where molecular grouping could be assigned, 19 (16%), 35 (29%), and 65 (54%) respectively had WNT-activated, SHH-activated, and Group 3/4 MB. The median duration between resection and initiation of adjuvant therapy was 36 days. Respective 2-year PFS and OS rates were 76.0%±3.0% and 88.0%±2.3%. PFS was significantly associated with age, metastatic status and clinical risk grouping. Chemotherapy use during CSI or alkylator choice were not significant predictors for patient outcome. Conclusions We reported the clinical profiles and outcome from the largest cohort of Chinese children with MB after multi-modal therapy. Strengths and limitations on the local provision of neuro-oncology service are identified.

Prognostic Immunity and Therapeutic Sensitivity Analyses Based on Differential Genomic Instability-Associated LncRNAs in Left- and Right-Sided Colon Adenocarcinoma

Background: The purpose of our study was to develop a prognostic risk model based on differential genomic instability-associated (DGIA) long non-coding RNAs (lncRNAs) of left-sided and right-sided colon cancers (LCCs and RCCs); therefore, the prognostic key lncRNAs could be identified.Methods: We adopted two independent gene datasets, corresponding somatic mutation and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Identification of differential DGIA lncRNAs from LCCs and RCCs was conducted with the appliance of “Limma” analysis. Then, we screened out key lncRNAs based on univariate and multivariate Cox proportional hazard regression analysis. Meanwhile, DGIA lncRNAs related prognostic model (DRPM) was established. We employed the DRPM in the model group and internal verification group from TCGA for the purpose of risk grouping and accuracy verification of DRPM. We also verified the accuracy of key lncRNAs with GEO data. Finally, the differences of immune infiltration, functional pathways, and therapeutic sensitivities were analyzed within different risk groups.Results: A total of 123 DGIA lncRNAs were screened out by differential expression analysis. We obtained six DGIA lncRNAs by the construction of DRPM, including AC004009.1, AP003555.2, BOLA3-AS1, NKILA, LINC00543, and UCA1. After the risk grouping by these DGIA lncRNAs, we found the prognosis of the high-risk group (HRG) was significantly worse than that in the low-risk group (LRG) (all p < 0.05). In all TCGA samples and model group, the expression of CD8+ T cells in HRG was lower than that in LRG (all p < 0.05). The functional analysis indicated that there was significant upregulation with regard to pathways related to both genetic instability and immunity in LRG, including cytosolic DNA sensing pathway, response to double-strand RNA, RIG-Ⅰ like receptor signaling pathway, and Toll-like receptor signaling pathway. Finally, we analyzed the difference and significance of key DGIA lncRNAs and risk groups in multiple therapeutic sensitivities.Conclusion: Through the analysis of the DGIA lncRNAs between LCCs and RCCs, we identified six key DGIA lncRNAs. They can not only predict the prognostic risk of patients but also serve as biomarkers for evaluating the differences of genetic instability, immune infiltration, and therapeutic sensitivity.

Implementation of the 2021 molecular ESGO/ESTRO/ESP risk groups in endometrial cancer

ABSTRACT Introduction In 2021, a joint ESGO/ESTRO/ESP committee updated their evidence-based guidelines for endometrial cancer, recommending a new risk grouping incorporating both clinicopathologic and molecular parameters. We applied the new risk grouping and compared the results to those of the prior 2016 clinicopathologic system. Materials and methods We classified molecularly a cohort of 604 women diagnosed with endometrial cancer using immunohistochemistry for TP53 and MMR proteins on a tissue microarray, as well as Sanger sequencing for POLE mutations. These results, combined with clinicopathologic data, allowed the patients to be risk grouped using both the new 2021 molecular/clinicopathologic parameters and the prior 2016 clinicopathologic system. In addition, clinical treatment and outcome data were collected from medical records. Results The application of the 2021 molecular markers shows Kaplan-Meier curves with a significant difference between the groups for all survival. Molecular classification under the 2021 guidelines revealed a total of 39 patients (39/594, 7%) with a change in risk group in relation to the 2016 classification system: the shift was alone due to either P53abn or POLEmut molecular marker. In order to ensure correct 2021 molecular risk classification, not all patients with endometrial cancer need a molecular diagnostic: 386 (65.0%) cases would need to be analyzed by TP53 IHC, only 44 (7.4%) by MMR IHC and 109 (18.4%) POLE sequencing reactions. Conclusion Application of the 2021 molecular risk groups is feasible and shows significant differences in survival. IHC for TP53 and MMR and applying POLE sequencing is only needed in selected

Differential Genomic Instability-Associated LncRNAs Predict Differences of Clinical Outcome and Immunity in Left- And Right- Sided Colon Adenocarcinoma

Background: The left-sided and right-sided colon adenocarcinoma (LCCs and RCCs, respectively) have unique characteristics in various aspects, particularly molecular features and clinical heterogeneity. The purpose of our study was to develop a prognostic risk model based on differential genomic instability-associated (DGIA) Long non-coding RNAs (lncRNAs) of LCCs and RCCs, therefore the prognostic key lncRNAs could be identified.Methods: We adopted two independent gene data-sets, corresponding somatic mutation and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Identification of differential DGIA lncRNAs from LCCs and RCCs were conducted with appliance of "Limma" analysis. Then, we screened out key lncRNAs based on univariate and multivariate Cox proportional hazard regression analysis. Meanwhile, DGIA lncRNAs related prognostic model (DRPM) was established. We employed the DRPM in the model group and internal verification group from TCGA for the purpose of risk grouping and accuracy verification of PRSM. We also verified the accuracy of key lncRNAs with GEO data. Finally, the differences of immune infiltration and functional pathways were analyzed within different risk groups. Results: A total of 123 DGIA lncRNAs were screened out by differential expression analysis. We obtained 6 DGIA lncRNAs by the construction of DRPM, including AC004009.1, AP003555.2, BOLA3-AS1, NKILA, LINC00543 and UCA1. After the risk grouping by these DGIA lncRNAs, we found the prognosis of high-risk group (HRG) was significantly worse than that in low-risk group (LRG) (all p＜0.05). In all TCGA samples and model group, the expression of CD8+ T cells in HRG was lower than that in LRG (all p＜0.05). The functional analysis indicated that there was significant up-regulation with regard of pathways related to both genetic instability and immunity in LRG, including cytosolic DNA sensing pathway, response to dsRNA, RIG-Ⅰ like receptor signaling pathway and Toll-like receptor signaling pathway.Conclusion: Through the analysis of the DGIA lncRNAs between LCCs and RCCs, we established a DRPM which could predicate prognosis of LCCs and RCCs, and 6 key DGIA lncRNAs were identified as well. They can not only predict the prognostic risk of patients, but also serve as biomarkers for evaluating the differences of genetic instability and immune infiltration.

External Validation of a Nomogram and Risk Grouping System for Predicting Individual Prognosis of Patients With Medulloblastoma

Background: Medulloblastoma (MB) is one of the most malignant neuroepithelial tumors in the central nervous system. This study aimed to establish an effective prognostic nomogram and risk grouping system for predicting overall survival (OS) of patients with MB.Materials and Methods: The nomogram was constructed based on data from the database of Surveillance, Epidemiology, and End Results (SEER). This database consisted of 2,824 patients with medulloblastoma and was used as the training cohort. The data of another additional 161 patients treated at the Sun Yat-sen University Cancer Center (SYSUCC) were used as the external validation cohort. Cox regression analysis was used to select independent prognostic factors. Concordance index (C-index) and calibration curve were used to predict the prognostic effect of the nomogram for overall survival.Results: In the training cohort, Cox regression analyses showed that the prognostic factors included histopathology, surgery, radiotherapy, chemotherapy, tumor size, dissemination, and age at diagnosis. The internal and external validated C-indexes were 0.681 and 0.644, respectively. Calibration curves showed that the nomogram was able to predict 1-, 3-, and 5-year OS for patients with MB precisely. Using the training cohort, a risk grouping system was built, which could perfectly classify patients into four risk nomogroups with a 5-year survival rate of 83.9%, 76.5%, 64.5%, and 46.8%, respectively.Conclusion: We built and validated a nomogram and risk grouping system that can provide individual prediction of OS and distinguish MB patients from different risk groups. This nomogram and risk grouping system could help clinicians making better treatment plan and prognostic assessment.

Early oncological outcomes and accuracy of risk stratification and tailoring surgical staging based on preoperative histology, Ca125 and MRI in endometrial cancer: a prospective cohort study

Background: momentum to select patients who will benefit from the extensive procedures. However, the parameters used for risk stratification have variable accuracy outside of tertiary cancer centres. This study looks into the accuracy of risk stratification using preoperative histology, MRI and Ca 125 levels and the oncological outcomes after tailoring surgical staging based on the risk stratification by combining the three variables in a suburban centre with a growing cancer population.Methods: This prospective observational cohort study was undertaken in a suburban cancer center in Pushpagiri Medical College, Tiruvalla, Kerala between June 2014 and December 2018. All patients underwent surgical staging with hysterectomy and salpingo oophorectomy as the least procedure. Lymphadenectomy was tailored according to the preoperative risk grouping and changed only in the presence of gross findings at surgery. Adjuvant treatment and follow up data obtained and collected in Microsoft Excel and analysed using statistical software SPSS version 22.Results: Of 47 patients recruited for the study, 35 patients were available for final analysis. Preoperative histology was accurate in 73%. There was 20 % overestimation and 8% underestimation. Ca 125 levels were elevated in 15%. MRI had an overall sensitivity of 74% and specificity of 60%. When MRI, Ca125 and histology were combined together, there was patients were deemed to be high risk. On final risk grouping, 9 patients were down staged and none were upstaged.Conclusions: Preoperative histology, MRI and ca 125 levels have moderate accuracy individually as preoperative risk determinates. The three parameters combined together show high specificity and PPV for preoperative risk stratification and the risk stratification has not been detrimental with respect to oncological outcomes of recurrence.