Metabolism pathway-based subtyping in endometrial cancer: An integrated study by multi-omics analysis and machine learning algorithms

Endometrial cancer (EC), the second most common malignancy in the female reproductive system, has garnered increasing attention for its genomic heterogeneity, but understanding of its metabolic characteristics is still poor. We explored metabolic dysfunctions in EC through a comprehensive multi-omics analysis (RNA-seq datasets from The Cancer Genome Atlas [TCGA], Cancer Cell Line Encyclopedia [CCLE], and GEO datasets; the Clinical Proteomic Tumor Analysis Consortium [CPTAC] proteomics; CCLE metabolomics) to develop useful molecular targets for precision therapy. Unsupervised consensus clustering was performed to categorize EC patients into three metabolism-pathway-based subgroups (MPSs). These MPS subgroups had distinct clinical prognoses, transcriptomic and genomic alterations, immune microenvironment landscape, and unique patterns of chemotherapy sensitivity. Moreover, the MPS2 subgroup had a better response to immunotherapy. Finally, three machine learning algorithms (LASSO, random forest, and stepwise multivariate Cox regression) were used for developing a prognostic metagene signature based on metabolic molecules. Thus, a 13-hub gene-based classifier was constructed to predict patients' MPS subtypes, offering a more accessible and practical approach. This metabolism-based classification system can enhance prognostic predictions and guide clinical strategies for immunotherapy and metabolism-targeted therapy in EC.

Successful Implementation of Image-Guided Pencil-Beam Scanning Proton Therapy in Medulloblastomas

Medulloblastoma is the most common malignant brain tumour in children, while much rarer in adults. Although the prognosis and outcomes have greatly improved in the era of modern multidisciplinary management, long-term treatment-induced toxicities are common. Craniospinal irradiation followed by a boost to the primary and metastatic tumour sites forms the backbone of treatment. Proton therapy has been endorsed over conventional photon-based radiotherapy due to its superior dosimetric advantages and subsequently lower incidence and severity of toxicities. We report here our experience from South-East Asia's first proton therapy centre of treating 40 patients with medulloblastoma (38 children and adolescents, 2 adults) who received image-guided, intensity-modulated proton therapy with pencil-beam scanning between 2019 and 2023, with a focus on dosimetry, acute toxicities, and early survival outcomes. All patients could complete the planned course of proton therapy, with mostly mild acute toxicities that were manageable on an outpatient basis. Haematological toxicity was not dose-limiting and did not prolong the overall treatment time. Preliminary data on early outcomes including overall survival and disease-free survival are encouraging, although a longer follow-up and data on long-term toxicities are needed.

Opportunities and Advances in Radiomics and Radiogenomics for Pediatric Medulloblastoma Tumors

Recent advances in artificial intelligence have greatly impacted the field of medical imaging and vastly improved the development of computational algorithms for data analysis. In the field of pediatric neuro-oncology, radiomics, the process of obtaining high-dimensional data from radiographic images, has been recently utilized in applications including survival prognostication, molecular classification, and tumor type classification. Similarly, radiogenomics, or the integration of radiomic and genomic data, has allowed for building comprehensive computational models to better understand disease etiology. While there exist excellent review articles on radiomics and radiogenomic pipelines and their applications in adult solid tumors, in this review article, we specifically review these computational approaches in the context of pediatric medulloblastoma tumors. Based on our systematic literature research via PubMed and Google Scholar, we provide a detailed summary of a total of 15 articles that have utilized radiomic and radiogenomic analysis for survival prognostication, tumor segmentation, and molecular subgroup classification in the context of pediatric medulloblastoma. Lastly, we shed light on the current challenges with the existing approaches as well as future directions and opportunities with using these computational radiomic and radiogenomic approaches for pediatric medulloblastoma tumors.

Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes

Background

DNA methylation can be used to predict clinical outcomes and improve the classification of tumors. The present study aimed to develop a new lung adenocarcinoma (LUAD) classification system according to the immune cell gene-related methylation sites and to reveal the survival outcomes, clinical characteristics, immune cell infiltration, stem cell characteristics, and genomic variations of each molecular subgroup.

Methods

The DNA methylation sites of LUAD samples collected from The Cancer Genome Atlas (TCGA) database were analyzed, and the prognosis-related differential methylation sites (DMS) were screened. Consistent clustering of the samples was conducted using ConsensusClusterPlus, and the classification results were verified by principal component analysis (PCA). The survival and clinical results, immune cell infiltration, stemness, DNA mutation, and copy number variation (CNV) of each molecular subgroup were analyzed.

Results

A total of 40 DMS were obtained by difference and univariate COX analyses, and the TCGA LUAD samples were divided into three subgroups: cluster 1 (C1), cluster 2 (C2), and cluster 3 (C3). Among these subgroups, the overall survival (OS) of C3 was significantly higher than that of C1 and C2. Compared with C1 and C3, C2 had the lowest innate immune cell and adaptive immune cell infiltration scores; the lowest stromal score, immune score, and iconic immune checkpoint expression; and the highest expression of messenger RNA (mRNA) expression-based stemness indices (mRNAsi), DNA methylation-based stemness index (mDNAsi), and tumor mutational burden (TMB).

Conclusions

In this study, we proposed a LUAD typing system based on DMS, which was closely related to the survival, clinical features, immune characteristics, and genomic variations of LUAD, and may contribute to the development of personalized therapy for new specific subtypes.

Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods

Aim: As the most common cardiomyopathy, dilated cardiomyopathy (DCM) often leads to progressive heart failure and sudden cardiac death. This study was designed to investigate the molecular subgroups of DCM. Methods: Three datasets of DCM were downloaded from GEO database (GSE17800, GSE79962 and GSE3585). After log2-transformation and background correction with "limma" package in R software, the three datasets were merged into a metadata cohort. The consensus clustering was conducted by the "Consensus Cluster Plus" package to uncover the molecular subgroups of DCM. Moreover, clinical characteristics of different molecular subgroups were compared in detail. We also adopted Weighted gene co-expression network analysis (WGCNA) analysis based on subgroup-specific signatures of gene expression profiles to further explore the specific gene modules of each molecular subgroup and its biological function. Two machine learning methods of LASSO regression algorithm and SVM-RFE algorithm was used to screen out the genetic biomarkers, of which the discriminative ability of molecular subgroups was evaluated by receiver operating characteristic (ROC) curve. Results: Based on the gene expression profiles, heart tissue samples from patients with DCM were clustered into three molecular subgroups. No statistical difference was found in age, body mass index (BMI) and left ventricular internal diameter at end-diastole (LVIDD) among three molecular subgroups. However, the results of left ventricular ejection fraction (LVEF) statistics showed that patients from subgroup 2 had a worse condition than the other group. We found that some of the gene modules (pink, black and grey) in WGCNA analysis were significantly related to cardiac function, and each molecular subgroup had its specific gene modules functions in modulating occurrence and progression of DCM. LASSO regression algorithm and SVM-RFE algorithm was used to further screen out genetic biomarkers of molecular subgroup 2, including TCEAL4, ISG15, RWDD1, ALG5, MRPL20, JTB and LITAF. The results of ROC curves showed that all of the genetic biomarkers had favorable discriminative effectiveness. Conclusion: Patients from different molecular subgroups have their unique gene expression patterns and different clinical characteristics. More personalized treatment under the guidance of gene expression patterns should be realized.

Erratum: Novel MRI deformation-heterogeneity radiomic features are associated with molecular subgroups and overall survival in pediatric medulloblastoma: Preliminary findings from a multi-institutional study

[This corrects the article DOI: 10.3389/fonc.2022.915143.].

ROS1 genomic rearrangements are rare actionable drivers in microsatellite stable colorectal cancer

c-Ros oncogene 1, receptor tyrosine kinase (ROS1) genomic rearrangements have been reported previously in rare cases of colorectal cancer (CRC), yet little is known about the frequency, molecular characteristics, and therapeutic vulnerabilities of ROS1-driven CRC. We analyzed a clinical dataset of 40 589 patients with CRC for ROS1 genomic rearrangements and their associated genomic characteristics (Foundation Medicine, Inc [FMI]). We moreover report the disease course and treatment response of an index patient with ROS1-rearranged metastatic CRC. ROS1 genomic rearrangements were identified in 34 (0.08%) CRC samples. GOPC-ROS1 was the most common ROS1 fusion identified (11 samples), followed by TTC28-ROS1 (3 samples). Four novel 5' gene partners of ROS1 were identified (MCM9, SRPK1, EPHA6, P4HA1). Contrary to previous reports on fusion-positive CRC, ROS1-rearrangements were found exclusively in microsatellite stable (MSS) CRCs. KRAS mutations were significantly less abundant in ROS1-rearranged vs ROS1 wild type cases. The index patient presented with chemotherapy-refractory metastatic right-sided colon cancer harboring GOPC-ROS1. Molecularly targeted treatment with crizotinib induced a rapid and sustained partial response. After 15 months on crizotinib disseminated tumor progression occurred and KRAS Q61H emerged in tissue and liquid biopsies. ROS1 rearrangements define a small, yet therapeutically actionable molecular subgroup of MSS CRC. In summary, the high prevalence of GOPC-ROS1 and noncanonical ROS1 fusions pose diagnostic challenges. We advocate NGS-based comprehensive molecular profiling of MSS CRCs that are wild type for RAS and BRAF and patient enrollment in precision trials.

Consensus clustering of gene expression profiles in peripheral blood of acute ischemic stroke patients

Acute ischemic stroke (AIS) is a primary cause of mortality and morbidity worldwide. Currently, no clinically approved immune intervention is available for AIS treatment, partly due to the lack of relevant patient classification based on the peripheral immunity status of patients with AIS. In this study, we adopted the consensus clustering approach to classify patients with AIS into molecular subgroups based on the transcriptomic profiles of peripheral blood, and we identified three distinct AIS molecular subgroups and 8 modules in each subgroup by the weighted gene co-expression network analysis. Remarkably, the pre-ranked gene set enrichment analysis revealed that the co-expression modules with subgroup I-specific signature genes significantly overlapped with the differentially expressed genes in AIS patients with hemorrhagic transformation (HT). With respect to subgroup II, exclusively male patients with decreased proteasome activity were identified. Intriguingly, the majority of subgroup III was composed of female patients who showed a comparatively lower level of AIS-induced immunosuppression (AIIS). In addition, we discovered a non-linear relationship between female age and subgroup-specific gene expression, suggesting a gender- and age-dependent alteration of peripheral immunity. Taken together, our novel AIS classification approach could facilitate immunomodulatory therapies, including the administration of gender-specific therapeutics, and attenuation of the risk of HT and AIIS after ischemic stroke.

News in the classification of WHO 2022 bladder tumors

The fifth-edition of World Health Organization (WHO) Classification of Tumors series for urinary and male genital tract tumors has been published, six years later the fourth-edition. In these years, new treatment approaches have been implemented and new molecular data on urological cancers are known.

Morphology remains the groundwork for taxonomy of the urinary tract tumors. However, a molecular approach to classification of urothelial carcinomas and the management of selected neoplasms with new therapeutic modalities such as immunotherapy are emerging. More data are needed for the application of these advances in routine pathology practice and patient management.

The 2022 World Health Organization (WHO) Classification of Tumors of the Urinary System and Male Genital Organs represents an update in classification on urinary tract tumors. It also offers new insights with regards to the grading of heterogeneous non-invasive urothelial neoplasms, the definition of inverted neoplasms, the grading of invasive urothelial carcinomas, the diversity of morphological appearance of urothelial carcinomas, the definition of precursor lesions and the lineage of differentiation of the tumors.

Proteogenomic characterization identifies clinically relevant subgroups of intrahepatic cholangiocarcinoma

We performed proteogenomic characterization of intrahepatic cholangiocarcinoma (iCCA) using paired tumor and adjacent liver tissues from 262 patients. Integrated proteogenomic analyses prioritized genetic aberrations and revealed hallmarks of iCCA pathogenesis. Aflatoxin signature was associated with tumor initiation, proliferation, and immune suppression. Mutation-associated signaling profiles revealed that TP53 and KRAS co-mutations may contribute to iCCA metastasis via the integrin-FAK-SRC pathway. FGFR2 fusions activated the Rho GTPase pathway and could be a potential source of neoantigens. Proteomic profiling identified four patient subgroups (S1-S4) with subgroup-specific biomarkers. These proteomic subgroups had distinct features in prognosis, genetic alterations, microenvironment dysregulation, tumor microbiota composition, and potential therapeutics. SLC16A3 and HKDC1 were further identified as potential prognostic biomarkers associated with metabolic reprogramming of iCCA cells. This study provides a valuable resource for researchers and clinicians to further identify molecular pathogenesis and therapeutic opportunities in iCCA.

Novel MRI deformation-heterogeneity radiomic features are associated with molecular subgroups and overall survival in pediatric medulloblastoma: Preliminary findings from a multi-institutional study

Introduction

Medulloblastoma (MB) is a malignant, heterogenous brain tumor. Advances in molecular profiling have led to identifying four molecular subgroups of MB (WNT, SHH, Group 3, Group 4), each with distinct clinical behaviors. We hypothesize that (1) aggressive MB tumors, growing heterogeneously, induce pronounced local structural deformations in the surrounding parenchyma, and (b) these local deformations as captured on Gadolinium (Gd)-enhanced-T1w MRI are independently associated with molecular subgroups, as well as overall survival in MB patients.

Methods

In this work, a total of 88 MB studies from 2 institutions were analyzed. Following tumor delineation, Gd-T_1w scan for every patient was registered to a normal age-specific T_1w-MRI template via deformable registration. Following patient-atlas registration, local structural deformations in the brain parenchyma were obtained for every patient by computing statistics from deformation magnitudes obtained from every 5mm annular region, 0 < d < 60 mm, where d is the distance from the tumor infiltrating edge.

Results

Multi-class comparison via ANOVA yielded significant differences between deformation magnitudes obtained for Group 3, Group 4, and SHH molecular subgroups, observed up to 60-mm outside the tumor edge. Additionally, Kaplan-Meier survival analysis showed that the local deformation statistics, combined with the current clinical risk-stratification approaches (molecular subgroup information and Chang's classification), could identify significant differences between high-risk and low-risk survival groups, achieving better performance results than using any of these approaches individually.

Discussion

These preliminary findings suggest there exists significant association of our tumor-induced deformation descriptor with overall survival in MB, and that there could be an added value in using the proposed radiomic descriptor along with the current risk classification approaches, towards more reliable risk assessment in pediatric MB.

Association of high-dose radiotherapy with improved survival in patients with newly diagnosed low-grade gliomas

BACKGROUND

The radiation dose for patients with low-grade gliomas (LGGs) is controversial. The objective of this study was to investigate the impact of the radiation dose on survival for patients with LGGs and especially for molecularly defined subgroups.

METHODS

Three hundred fifty-one patients with newly diagnosed LGGs from the multicenter Chinese Glioma Cooperative Group received postoperative radiotherapy (RT) in 2005-2018. The RT dose, as a continuous variable, was entered into a Cox regression model using penalized spline regression to allow for a nonlinear relationship between the RT dose and overall survival (OS) or progression-free survival (PFS). Inverse probability of treatment weighting (IPTW)-adjusted propensity scores were used to correct for potential confounders. Dose effects on survival within IDH mutation and 1p/19q codeletion defined subgroups were analyzed.

RESULTS

The risk of mortality and disease progression decreased sharply until 54 Gy. High-dose RT (≥54 Gy) was associated with significantly better 5-year OS (81.7% vs 64.0%; hazard ratio [HR], 0.33; P < .001) and PFS (77.4% vs 54.5%; HR, 0.46; P < .001) than low-dose RT (<54 Gy). IPTW correction confirmed the associations (HR for OS, 0.44; P = .001; HR for PFS, 0.48; P = .003). High-dose RT was associated with longer PFS (HR, 0.25; P = .002; HR, 0.21; P = .039) and OS (HR, 0.27; P = .006; HR, 0.07; P = .017) in IDH-mutant/1p/19q noncodeleted and IDH wild-type subgroups, respectively. No significant difference in survival was observed with high-dose RT in the IDH-mutant/1p/19q codeleted subgroup.

CONCLUSIONS

High-dose RT (≥54 Gy) was effective in LGGs. Patients with an IDH mutation/1p/19q noncodeletion or IDH wild-type may need to be considered for high-dose RT.

LAY SUMMARY

The radiotherapy dose-response was observed in patients with low-grade gliomas, and high-dose radiotherapy (≥54 Gy) was associated with improved survival. Patients with an IDH mutation/1p/19q noncodeletion or wild-type IDH may have improved survival with the administration of high-dose radiotherapy.

Characterization of Molecular Subtypes in Head and Neck Squamous Cell Carcinoma With Distinct Prognosis and Treatment Responsiveness

Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive malignancies with complex phenotypic, etiological, biological, and clinical heterogeneities. Previous studies have proposed different clinically relevant subtypes of HNSCC, but little is known about its corresponding prognosis or suitable treatment strategy. Here, we identified 101 core genes from three prognostic pathways, including mTORC1 signaling, unfold protein response, and UV response UP, in 124 pairs of tumor and matched normal tissues of HNSCC. Moreover, we identified three robust subtypes associated with distinct molecular characteristics and clinical outcomes using consensus clustering based on the gene expression profiles of 944 HNSCC patients from four independent datasets. We then integrated the genomic information of The Cancer Genome Atlas (TCGA) HNSCC cohort to comprehensively evaluate the molecular features of different subtypes and screen for potentially effective therapeutic agents. Cluster 1 had more arrested oncogenic signaling, the highest immune cell infiltration, the highest immunotherapy and chemotherapeutic responsiveness, and the best prognosis. By contrast, Cluster 3 showed more activated oncogenic signaling, the lowest immune cell infiltration, the lowest immunotherapy and chemotherapy responsiveness, and the worst prognosis. Our findings corroborate the molecular diversity of HNSCC tumors and provide a novel classification strategy that may guide for prognosis and treatment allocation.

Immune checkpoint inhibitors in oncogene-addicted non-small cell lung cancer: a systematic review and meta-analysis

Background

Treatment of oncogene-addicted non-small cell lung cancer (NSCLC) has been changed by the advent of tyrosine kinase inhibitors (TKIs). Albeit great benefits are achieved with target therapies, resistance invariably occurs and recourse to alternative treatments is unavoidable. Immune checkpoint inhibitors (ICIs) role and the best setting of immunotherapy administration in oncogene-driven NSCLC are matter of debate.

Methods

We performed a systematic literature review through PubMed, in order to gather all the available information regarding ICI activity and efficacy in oncogene-addicted NSCLC, from both prospective trials and retrospective series. A meta-analysis of objective response rate in different molecular subgroups was provided. Combinatorial strategies including ICIs and related toxicities were also recorded.

Results

Eighty-seven studies were included in the qualitative analysis. EGFR mutation may be a biomarker of poor response to single-agent ICIs (7% of EGFR-mutant NSCLC patients achieved disease response in prospective trials), while encouraging results have been shown with combination strategies. KRAS-mutated disease (response rate, RR, 22%) has different clinical and pathological characteristics, and the co-existence of additional mutations (e.g., STK11 or TP53) influence tumor microenvironment and response to immunotherapy. Other molecular alterations have been marginally considered prospectively, and data from clinical practice are variegated, given poor effectiveness of ICIs in ALK-rearranged disease (RR 9.5%, pooling the data of retrospective studies) or some encouraging results in BRAF-(RR 25%, retrospective data) or MET-driven one (with estimations conditioned by the presence of both exon 14 skipping mutations and gene amplification in reported series).

Conclusions

In oncogene-addicted NSCLC (with the exception of KRAS-mutated), ICIs are usually administered at the failure of other treatment options, but administering single-agent immunotherapy in later disease phases may limit its efficacy. With the progressive administration of TKIs and ICIs in early-stage disease, molecular characterization will become fundamental in this setting.

Associations of meningioma molecular subgroup and tumor recurrence

BACKGROUND

We and others have identified mutually exclusive molecular subgroups of meningiomas; however, the implications of this classification for clinical prognostication remain unclear. Integrated genomic and epigenomic analyses implicate unique oncogenic processes associated with each subgroup, suggesting the potential for divergent clinical courses. The aim of this study was to understand the associated clinical outcomes of each subgroup, as this could optimize treatment for patients.

METHODS

We analyzed outcome data for 469 meningiomas of known molecular subgroup, including extent of resection, postoperative radiation, surveillance imaging, and time to recurrence, when applicable. Statistical relationships between outcome variables and subgroup were assessed. Features previously associated with recurrence were further investigated after stratification by subgroup. We used Kaplan-Meier analyses to compare progression-free survival, and identified factors significantly associated with recurrence using Cox proportional hazards modeling.

RESULTS

Meningioma molecular subgroups exhibited divergent clinical courses at 2 years of follow-up, with several aggressive subgroups (NF2, PI3K, HH, tumor necrosis factor receptor-associated factor 7 [TRAF7]) recurring at an average rate of 22 times higher than others (KLF4, POLR2A, SMARCB1). PI3K-activated tumors recurred earlier than other subgroups but had intermediate long-term outcome. Among low-grade tumors, HH and TRAF7 meningiomas exhibited elevated recurrence compared with other subgroups. Recurrence of NF2 tumors was associated with male sex, high grade, and elevated Ki-67. Multivariate analysis identified molecular subgroup as an independent predictor of recurrence, along with grade and previous recurrence.

CONCLUSION

We describe distinct clinical outcomes and recurrence rates associated with meningioma molecular subgroups. Our findings emphasize the importance of genomic characterization to guide postoperative management decisions for meningiomas.

Molecular subgrouping of atypical teratoid/rhabdoid tumors-a reinvestigation and current consensus

Background

Atypical teratoid/rhabdoid tumors (ATRTs) are known to exhibit molecular and clinical heterogeneity even though SMARCB1 inactivation is the sole recurrent genetic event present in nearly all cases. Indeed, recent studies demonstrated 3 molecular subgroups of ATRTs that are genetically, epigenetically, and clinically distinct. As these studies included different numbers of tumors, various subgrouping techniques, and naming, an international working group sought to align previous findings and to reach a consensus on nomenclature and clinicopathological significance of ATRT subgroups.

Methods

We integrated various methods to perform a meta-analysis on published and unpublished DNA methylation and gene expression datasets of ATRTs and associated clinicopathological data.

Results

In concordance with previous studies, the analyses identified 3 main molecular subgroups of ATRTs, for which a consensus was reached to name them ATRT-TYR, ATRT-SHH, and ATRT-MYC. The ATRT-SHH subgroup exhibited further heterogeneity, segregating further into 2 subtypes associated with a predominant supratentorial (ATRT-SHH-1) or infratentorial (ATRT-SHH-2) location. For each ATRT subgroup we provide an overview of its main molecular and clinical characteristics, including SMARCB1 alterations and pathway activation.

Conclusions

The introduction of a common classification, characterization, and nomenclature of ATRT subgroups will facilitate future research and serve as a common ground for subgrouping patient samples and ATRT models, which will aid in refining subgroup-based therapies for ATRT patients.

Characterization of the Prognostic m6A-Related lncRNA Signature in Gastric Cancer

N6-methyladenosine (m⁶A) is a common form of mRNA modification regulated by m6A RNA methylation regulators and play an important role in the progression of gastric cancer (GC). However, the prognostic role of m⁶A-related lncRNA in gastric cancer has not been fully explored. This study aims at exploring the biological function and prognostic roles of the m⁶A-related lncRNA signature in gastric cancer. A total of 800 m6A-related lncRNAs were identified through Pearson correlation analysis between m6A regulators and all lncRNAs. Eleven m6A-related lncRNA signatures were identified through a survival analysis and the Kaplan-Meier (KM) curve analysis results suggest that patients in the low-risk group have a better overall survival (OS) and disease-free survival (DFS) outcome than the high-risk group. Also, the lncRNA signature can serve as an independent prognostic factor for OS and DFS. The gene set enrichment analysis (GSEA) result suggests that patients in the high-risk group were mainly enriched in the ECM receptor interaction, focal adhesion, and cytokine-cytokine receptor interaction pathway, while the low-risk group was characterized by the base excision repair pathway. We further constructed an individualized prognostic prediction model via the nomogram based on the independent prognostic factor for the OS and DFS, respectively. In addition, some candidate drugs aimed at GC risk group differentiation were identified using the Connective Map (CMAP) database. Lastly, four subgroups (C1, C2, C3, and C4) were identified based on the m6A-related lncRNA expression, through a consensus clustering algorithm. Among them, C1 and C2 have a greater likelihood to respond to immune checkpoint inhibitor immunotherapy, suggesting that the C1 and C2 subgroup might benefit from immunotherapy. In conclusion, the m6A-related lncRNA signature can independently predict the OS and DFS of GC and may aid in development of personalized immunotherapy strategies.

EGFR Amplification in Metastatic Colorectal Cancer

BACKGROUND

EGFR amplification occurs in about 1% of metastatic colorectal cancers (mCRCs) but is not routinely tested as a prognostic or predictive biomarker for patients treated with anti-EGFR monoclonal antibodies (mAbs). Herein, we aimed to characterize the clinical and molecular landscape of EGFR-amplified metastatic colorectal cancer (mCRC).

METHODS

In this multinational cohort study, we compared clinical data of 62 patients with EGFR-amplified vs. 1459 EGFR non-amplified mCRC, as well as comprehensive genomic data of 35 EGFR-amplified vs. 439 EGFR non-amplified RAS/BRAF wild-type and microsatellite stable (MSS) tumor samples.

RESULTS

EGFR amplification was statistically significantly associated with left primary tumor sidedness and RAS/BRAF wild-type status. All EGFR-amplified tumors were MSS and HER2 non-amplified. Overall, EGFR-amplified samples had higher median fraction of genome altered compared to EGFR non-amplified, RAS/BRAF wild-type MSS cohort. Patients with EGFR-amplified tumors reported longer overall survival (OS) (median OS = 71.3 months; 95% confidence interval [CI] = 50.7-NA) vs. EGFR non-amplified ones (24.0 months; 95% CI = 22.8-25.6; hazard ratio [HR] = 0.30, 95% CI = 0.20-0.44, P<.001; adjusted HR = 0.46, 95%CI = 0.30-0.69, P<.001). In the subgroup of patients with RAS/BRAF wild-type mCRC exposed to anti-EGFR-based therapy, EGFR amplification was again associated with better OS (median OS = 54.0 months [95% CI = 35.2-NA] vs. 29.1 months [95% CI = 27.0-31.9], respectively; HR = 0.46, 95%CI = 0.28-0.76, P=.002).

CONCLUSION

Patients with EGFR-amplified mCRC represent a biologically defined subgroup and merit dedicated clinical trials with novel and more potent EGFR targeting strategies beyond single-agent monoclonal antibodies.

Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies

Coeliac disease (CD) is a clinically heterogeneous autoimmune disease with variable presentation and progression triggered by gluten intake. Molecular or genetic factors contribute to disease heterogeneity, but the reasons for different outcomes are poorly understood. Transcriptome studies of tissue biopsies from CD patients are scarce. Here, we present a high-resolution analysis of the transcriptomes extracted from duodenal biopsies of 24 children and adolescents with active CD and 21 individuals without CD but with intestinal afflictions as controls. The transcriptomes of CD patients divide into three groups-a mixed group presenting the control cases, and CD-low and CD-high groups referring to lower and higher levels of CD severity. Persistence of symptoms was weakly associated with subgroup, but the highest marsh stages were present in subgroup CD-high, together with the highest cell cycle rates as an indicator of virtually complete villous atrophy. Considerable variation in inflammation-level between subgroups was further deciphered into immune cell types using cell type de-convolution. Self-organizing maps portrayal was applied to provide high-resolution landscapes of the CD-transcriptome. We find asymmetric patterns of miRNA and long non-coding RNA and discuss the effect of epigenetic regulation. Expression of genes involved in interferon gamma signaling represent suitable markers to distinguish CD from non-CD cases. Multiple pathways overlay in CD biopsies in different ways, giving rise to heterogeneous transcriptional patterns, which potentially provide information about etiology and the course of the disease.

Construction and Validation of a Cell Cycle-Related Robust Prognostic Signature in Colon Cancer

Colon cancer is one of the most common cancers, great progress was taken place in the treatment of colon cancer, however, the prognostic assessment system remains lagging. Cell cycle plays a vital role in the whole procedure of cancers. In this study, we firstly identified cell cycle-related genes specific in colon cancer. Functional enrichment analysis proved our analysis reliable. Furthermore, we constructed a robust signature based on the cell cycle-related genes. The AUC of the signature to predict the overall survival was 0.808, 0.807, and 0.831 of AUC at 1, 3, and 5 years, respectively. Internal and external validation proved the signature efficient. The 9 genes involved in the signature also showed a great job in molecular subgrouping which indicated the significant value of the 9 genes for further experimental research. In conclusion, the present research provided a novel robust signature predicting the prognosis of colon cancer.

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to develop machine learning models for predicting MB molecular subgroups based on multi-parameter magnetic resonance imaging (MRI) radiomics, tumor locations, and clinical factors. A total of 122 MB patients were enrolled retrospectively. After selecting robust, non-redundant, and relevant features from 5,529 extracted radiomics features, a random forest model was constructed based on a training cohort (n = 92) and evaluated on a testing cohort (n = 30). By combining radiographic features and clinical parameters, two combined prediction models were also built. The subgroup can be classified using an 11-feature radiomics model with a high area under the curve (AUC) of 0.8264 for WNT and modest AUCs of 0.6683, 0.6004, and 0.6979 for SHH, Group 3, and Group 4 in the testing cohort, respectively. Incorporating location and hydrocephalus into the radiomics model resulted in improved AUCs of 0.8403 and 0.8317 for WNT and SHH, respectively. After adding gender and age, the AUCs for WNT and SHH were further improved to 0.9097 and 0.8654, while the accuracies were 70 and 86.67% for Group 3 and Group 4, respectively. Prediction performance was excellent for WNT and SHH, while that for Group 3 and Group 4 needs further improvements. Machine learning algorithms offer potentials to non-invasively predict the molecular subgroups of MB.

Molecular Heterogeneity and Cellular Diversity: Implications for Precision Treatment in Medulloblastoma

Medulloblastoma, the most common pediatric malignant brain tumor, continues to have a high rate of morbidity and mortality in childhood. Recent advances in cancer genomics, single-cell sequencing, and sophisticated tumor models have revolutionized the characterization and stratification of medulloblastoma. In this review, we discuss heterogeneity associated with four major subgroups of medulloblastoma (WNT, SHH, Group 3, and Group 4) on the molecular and cellular levels, including histological features, genetic and epigenetic alterations, proteomic landscape, cell-of-origin, tumor microenvironment, and therapeutic approaches. The intratumoral molecular heterogeneity and intertumoral cellular diversity clearly underlie the divergent biology and clinical behavior of these lesions and highlight the future role of precision treatment in this devastating brain tumor in children.

The molecular biology of medulloblastoma metastasis

Medulloblastoma (MB) is the most common primary malignant brain tumor of childhood and a significant contributor to pediatric morbidity and death. While metastatic dissemination is the predominant cause of morbidity and mortality for patients with this disease, most research efforts and clinical trials to date have focused on the primary tumor; this is due mostly to the paucity of metastatic tumor samples and lack of robust mouse models of MB dissemination. Most current insights into the molecular drivers of metastasis have been derived from comparative molecular studies of metastatic and non-metastatic primary tumors. However, small studies on matched primary and metastatic tissues and recently developed mouse models of dissemination have begun to uncover the molecular biology of MB metastasis more directly. With respect to anatomical routes of dissemination, a hematogenous route for MB metastasis has recently been demonstrated, opening new avenues of investigation. The tumor micro-environment of the primary and metastatic niches has also been increasingly scrutinized in recent years, and further investigation of these tumor compartments is likely to result in a better understanding of the molecular mediators of MB colonization and growth in metastatic compartments.

Identification and Analyses of Extra-Cranial and Cranial Rhabdoid Tumor Molecular Subgroups Reveal Tumors with Cytotoxic T Cell Infiltration

Extra-cranial malignant rhabdoid tumors (MRTs) and cranial atypical teratoid RTs (ATRTs) are heterogeneous pediatric cancers driven primarily by SMARCB1 loss. To understand the genome-wide molecular relationships between MRTs and ATRTs, we analyze multi-omics data from 140 MRTs and 161 ATRTs. We detect similarities between the MYC subgroup of ATRTs (ATRT-MYC) and extra-cranial MRTs, including global DNA hypomethylation and overexpression of HOX genes and genes involved in mesenchymal development, distinguishing them from other ATRT subgroups that express neural-like features. We identify five DNA methylation subgroups associated with anatomical sites and SMARCB1 mutation patterns. Groups 1, 3, and 4 exhibit cytotoxic T cell infiltration and expression of immune checkpoint regulators, consistent with a potential role for immunotherapy in rhabdoid tumor patients.

Chun et al. report similarities between the MYC subgroup of cranial and extracranial rhabdoid tumors (RTs) at genetic, gene-expression, and epigenetic levels. They identify five DNA methylation subgroups of RTs across multiple organ sites, and some subgroups exhibit increased levels of immune cell infiltration and immune checkpoint expression.

Reproducibility of the NanoString 22-gene molecular subgroup assay for improved prognostic prediction of medulloblastoma

Medulloblastoma is the most frequent malignant brain tumor in children. Four medulloblastoma molecular subgroups, MB_SHH , MB_WNT , MB_GRP3 and MB_GRP4 , have been identified by integrated high-throughput platforms. Recently, a 22-gene panel NanoString-based assay was developed for medulloblastoma molecular subgrouping, but the robustness of this assay has not been widely evaluated. Mutations in the gene for human telomerase reverse transcriptase (hTERT) have been found in medulloblastomas and are associated with distinct molecular subtypes. This study aimed to implement the 22-gene panel in a Brazilian context, and to associate the molecular profile with patients' clinical-pathological features. Formalin-fixed, paraffin-embedded (FFPE) medulloblastoma samples (n = 104) from three Brazilian centers were evaluated. Expression profiling of the 22-gene panel was performed by NanoString and a Canadian series (n = 240) was applied for training phase. hTERT mutations were analyzed by PCR followed by direct Sanger sequencing and the molecular profile was associated with patients' clinicopathological features. Overall, 65% of the patients were male, average age at diagnosis was 18 years and 7% of the patients presented metastasis at diagnosis. The molecular classification was attained in 100% of the cases, with the following frequencies: MB_SHH (n = 51), MB_WNT (n = 19), MB_GRP4 (n = 19) and MB_GRP3 (n = 15). The MB_SHH and MB_GRP3 subgroups were associated with older and younger patients, respectively. The MB_GRP4 subgroup exhibited the lowest 5-year cancer-specific overall survival (OS), yet in the multivariate analysis, only metastasis at diagnosis and surgical resection were associated with OS. hTERT mutations were detected in 29% of the cases and were associated with older patients, increased hTERT expression and MB_SHH subgroup. The 22-gene panel provides a reproducible assay for molecular subgrouping of medulloblastoma FFPE samples in a routine setting and is well-suited for future clinical trials.

MRI features as a helpful tool to predict the molecular subgroups of medulloblastoma: state of the art

Medulloblastoma is the most common malignant pediatric brain tumor. Medulloblastoma should not be viewed as a single disease, but as a heterogeneous mixture of various subgroups with distinct characteristics. Based on genomic profiles, four distinct molecular subgroups are identified: Wingless (WNT), Sonic Hedgehog (SHH), Group 3 and Group 4. Each of these subgroups are associated with specific genetic aberrations, typical age of onset as well as survival prognosis. Magnetic resonance imaging (MRI) is performed for all patients with brain tumors, and has a key role in the diagnosis, surgical guidance and follow up of patients with medulloblastoma. Several studies indicate MRI as a promising tool for early detection of medulloblastoma subgroups. The early identification of the subgroup can influence the extent of surgical resection, radiotherapy and chemotherapy targeted treatments. In this article, we review the state of the art in MRI-facilitated medulloblastoma subgrouping, with a summary of the main MRI features in medulloblastoma and a brief discussion on molecular characterization of medulloblastoma subgroups. The main focus of the article is MRI features that correlate with medulloblastoma subtypes, as well as features suggestive of molecular subgroups. Finally, we briefly discuss the latest trends in MRI studies and latest developments in molecular characterization.

Perspectives on the evolving state of the art management of gastrointestinal stromal tumours

Gastrointestinal stromal tumours (GISTs) represent a very exciting tumour entity for the medical oncologist. There has been extensive clinical and preclinical research dissecting the natural behaviour, molecular landscape and therapeutic responsiveness of this rare mesenchymal tumour. Various molecular subtypes of GIST have a differing prognostic and predictive relevance in the state of the art management of the disease. Emerging mature clinical trial data gathered over the last one and half decade provided substantial molecular profiling information in understanding the success and eventual failure of treatment. In our review of the most relevant literature we aim to guide the clinician in tailoring neoadjuvant, adjuvant and palliative treatment of GIST alongside the different, now well established molecular subgroups of GISTs.

Medulloblastoma: From Molecular Subgroups to Molecular Targeted Therapies

Brain tumors are the leading cause of cancer-related death in children, and medulloblastoma (MB) is the most common malignant pediatric brain tumor. Advances in surgery, radiation, and chemotherapy have improved the survival of MB patients. But despite these advances, 25-30% of patients still die from the disease, and survivors suffer severe long-term side effects from the aggressive therapies they receive. Although MB is often considered a single disease, molecular profiling has revealed a significant degree of heterogeneity, and there is a growing consensus that MB consists of multiple subgroups with distinct driver mutations, cells of origin, and prognosis. Here, we review recent progress in MB research, with a focus on the genes and pathways that drive tumorigenesis, the animal models that have been developed to study tumor biology, and the advances in conventional and targeted therapy.

MicroRNA Expression in KRAS- and BRAF-mutated Colorectal Cancers

BACKGROUND/AIM

KRAS and BRAF are two genes commonly mutated in colorectal cancer (CRC). Even though BRAF is a downstream target of KRAS in the MAPK signalling pathway, KRAS- and BRAF-mutated CRCs are found to display several different clinical and histopathological features. We investigated whether a differential expression of microRNAs (miRNAs) could explain the clinicopathological differences seen between KRAS- and BRAF-mutated CRCs.

MATERIALS AND METHODS

Using a PCR array, we analyzed the expression of 84 different miRNAs in CRC cell lines wild-type in KRAS and BRAF, or mutated in KRAS or BRAF.

RESULTS

Ten miRNAs were selected for further analyses in tumor tissue specimens (let-7a, let-7i, miR-10a, miR-10b, miR-31, miR-100, miR-181a, miR-181b, miR-372, and miR-373). BRAF-mutated tumors were found to express significantly higher levels of miR-31 as well as significantly lower levels of miR-373, compared to wild-type tumors.

CONCLUSION

Our results suggest that KRAS- and BRAF-mutated CRCs may have different miRNA signatures compared to CRC tumors wild-type in KRAS and BRAF. However, no difference in expression levels between KRAS- and BRAF-mutated tumors was evident for the miRNAs analyzed in this study.

Differential patterns of metastatic dissemination across medulloblastoma subgroups

OBJECTIVE Metastatic dissemination is a major treatment challenge and cause of death in patients with medulloblastoma. However, the influence of molecular biology on the pattern of metastatic dissemination at diagnosis is not known. In this study, the authors sought to define the location, pattern, and imaging characteristics of medulloblastoma metastases across subgroups at diagnosis. METHODS A consecutive cohort of patients with metastatic medulloblastoma at The Hospital for Sick Children and the University Hospital Motol, who underwent up-front MRI of the craniospinal axis, was assembled and allocated to subgroups using NanoString limited gene-expression profiling. Radiological characteristics (including location, morphology, size, diffusion restriction, and contrast enhancement) were discerned through a retrospective review. RESULTS Forty metastatic medulloblastomas were identified with up-front neuroimaging of the craniospinal axis: 5 sonic hedgehog (SHH), 16 Group 3, and 19 Group 4 metastases. Significant subgroup-specific differences were observed, particularly with respect to tumor location, size, and morphology. Group 3 metastases were most frequently laminar compared with a more nodular pattern in Group 4 (14 of 16 in Group 3 vs 8 of 19 in Group 4; p = 0.0004). Laminar metastases were not observed in patients with SHH medulloblastoma. Suprasellar metastases are highly specific to Group 4 (p = 0.016). Two of the 5 SHH cases had multifocal lesions in the cerebellum, raising the possibility that these were in fact synchronous primary tumors and not true metastases. A minority of patients with Group 4 metastases harbored metastatic deposits that did not enhance on MRI after contrast administration, often in patients whose primary tumor did not enhance. CONCLUSIONS The location, morphology, and imaging characteristics of metastatic medulloblastoma differ across molecular subgroups, with implications for diagnosis and management. This suggests that the biology of leptomeningeal dissemination differs among medulloblastoma subgroups.

A Retrospective Study of Progression-Free and Overall Survival in Pediatric Medulloblastoma Based on Molecular Subgroup Classification: A Single-Institution Experience

Background

Medulloblastoma (MB) has been classified into four core subgroups according to the transcriptional profile in recent years. However, some disagreement among researchers remains regarding the prognoses and most effective treatments of the different subgroups with different age distributions.

Objective

The objective of this study was to analyze MB prognosis in children population based on the classification of four molecular subgroups.

Methods

From January 2011 to January 2013, 84 consecutive MB patients aged underwent tumor removal at Beijing Tiantan Hospital. A total of 55 patients who ranged in age from 4 to 18 years underwent detailed follow-up. Molecular subgrouping was performed using RT-PCR.

Results

The 2-year progression-free survival (PFS) and overall survival (OS) rates for the entire cohort were 76.2 ± 5.8 and 81.8 ± 5.2%, respectively. Univariate analysis revealed that the Group 4 patients had a better survival (2-year OS, 90.6 ± 5.2%) than the SHH subgroup (P = 0.002) and Group 3 patients (P = 0.008). Only two of the 23 non-metastasized Group 4 patients relapsed, and chemotherapy did significantly affect these patients (PFS, P = 0.685). One out of five WNT patients had tumor relapse and died at last. Large cell/anaplastic (LC/A) histology and chemotherapy were independent risk factors in multivariate analysis.

Conclusion

In our study, the non-metastasized Group 4 patients had an excellent prognosis. The SHH subgroup and Group 3 patients had worst prognoses. LC/A histology had a dismal prognosis in our cohorts, which warrants intensive treatment.

Molecular subtypes of gastrointestinal stromal tumors and their prognostic and therapeutic implications

Gastrointestinal stromal tumors (GISTs) are composed of various molecular subtypes, with differing prognostic and predictive relevance. Previously, tumors lacking mutations in the KIT and PDGFRA genes have been designated as 'wild-type' GISTs; however, they represent a heterogeneous group currently undergoing further subclassification. Primary and secondary resistance to imatinib poses a significant clinical challenge, therefore ongoing research is trying to evaluate mechanisms to overcome resistance. Thorough understanding of the prognostic and predictive relevance of different genetic subtypes of GIST can guide clinical decision-making both in the adjuvant and the metastatic setting. Further work is required to identify tailored therapies for specific subgroups of GISTs wild-type for KIT and PDGFRA mutations and to identify predictive factors of resistance to currently approved systemic therapies.

The infiltration, and prognostic importance, of Th1 lymphocytes vary in molecular subgroups of colorectal cancer

Giving strong prognostic information, T‐cell infiltration is on the verge of becoming an additional component in the routine clinical setting for classification of colorectal cancer (CRC). With a view to further improving the tools for prognostic evaluation, we have studied how Th1 lymphocyte infiltration correlates with prognosis not only by quantity, but also by subsite, within CRCs with different molecular characteristics (microsatellite instability, CpG island methylator phenotype status, and BRAF and KRAS mutational status). We evaluated the Th1 marker T‐bet by immunohistochemistry in 418 archival tumour tissue samples from patients who underwent surgical resection for CRC. We found that a high number of infiltrating Th1 lymphocytes is strongly associated with an improved prognosis in patients with CRC, irrespective of intratumoural subsite, and that both extent of infiltration and patient outcome differ according to molecular subgroup. In brief, microsatellite instability, CpG island methylator phenotype‐high and BRAF mutated tumours showed increased infiltration of Th1 lymphocytes, and the most pronounced prognostic effect of Th1 infiltration was found in these tumours. Interestingly, BRAF mutated tumours were found to be more highly infiltrated by Th1 lymphocytes than BRAF wild‐type tumours whereas the opposite was seen for KRAS mutated tumours. These differences could be explained at least partly by our finding that BRAF mutated, in contrast to KRAS mutated, CRC cell lines and tumour specimens expressed higher levels of the Th1‐attracting chemokine CXCL10, and reduced levels of CCL22 and TGFB1, stimulating Th2/Treg recruitment and polarisation. In conclusion, the strong prognostic importance of Th1 lymphocyte infiltration in CRC was found at all subsites evaluated, and it remained significant in multivariable analyses, indicating that T‐bet may be a valuable marker in the clinical setting. Our results also indicate that T‐bet is of value when analysed in molecular subgroups of CRC, allowing identification of patients with especially poor prognosis who are in need of extended treatment.

2013; 6(7): 1211-22

Medulloblastoma (MB) is the most common malignant brain tumor in children. Although multimodality treatment regimens including surgery, radiotherapy and chemotherapy have greatly improved disease outcome, about one-third of MB patient remains incurable, and many long-term survivors are suffered from deleterious effects due to aggressive treatment. Understanding the signaling pathways and the genetic mechanisms contributed to MB development would be the key to develop novel therapeutic treatment strategies for improving survival and outcome of MB. In this review, we discuss the biological signaling pathways involved in MB pathogenesis. We also go through the current international consensus of four core MB subgroups namely, SHH, WNT, Group 3 and Group 4. This is adopted based on the knowledge of genomic complexity of MB as analyzed by recent high-throughput genomic technology. We talk about immunohistochemistry assays established to determine molecular subgroup affiliation. In the last part of review, we discuss how identification of molecular subgroups is going to change our routine disease diagnosis and clinical management.

Tumor-associated macrophages in SHH subgroup of medulloblastomas

PURPOSE

Medulloblastoma in children can be categorized into at least four molecular subgroups, offering the potential for targeted therapeutic approaches to reduce treatment-related morbidities. Little is known about the role of tumor microenvironment in medulloblastoma or its contribution to these molecular subgroups. Tumor microenvironment has been shown to be an important source for therapeutic targets in both adult and pediatric neoplasms. In this study, we investigated the hypothesis that expression of genes related to tumor-associated macrophages (TAM) correlates with the medulloblastoma molecular subgroups and contributes to a diagnostic signature.

METHODS

Gene-expression profiling using human exon array (n = 168) was analyzed to identify medulloblastoma molecular subgroups and expression of inflammation-related genes. Expression of 45 tumor-related and inflammation-related genes was analyzed in 83 medulloblastoma samples to build a gene signature predictive of molecular subgroups. TAMs in medulloblastomas (n = 54) comprising the four molecular subgroups were assessed by immunohistochemistry (IHC).

RESULTS

A 31-gene medulloblastoma subgroup classification score inclusive of TAM-related genes (CD163 and CSF1R) was developed with a misclassification rate of 2%. Tumors in the Sonic Hedgehog (SHH) subgroup had increased expression of inflammation-related genes and significantly higher infiltration of TAMs than tumors in the Group 3 or Group 4 subgroups (P < 0.0001 and P < 0.0001, respectively). IHC data revealed a strong association between location of TAMs and proliferating tumor cells.

CONCLUSIONS

These data show that SHH tumors have a unique tumor microenvironment among medulloblastoma subgroups. The interactions of TAMs and SHH medulloblastoma cells may contribute to tumor growth revealing TAMs as a potential therapeutic target.

Clinical implications of medulloblastoma subgroups: incidence of CSF diversion surgery

OBJECT

While medulloblastoma was initially thought to comprise a single homogeneous entity, it is now accepted that it in fact comprises 4 discrete subgroups, each with its own distinct demographics, clinical presentation, transcriptomics, genetics, and outcome. Hydrocephalus is a common complication of medulloblastoma and not infrequently requires CSF diversion. The authors report the incidence of CSF diversion surgery in each of the subgroups of medulloblastoma (Wnt, Shh, Group 3, and Group 4).

METHODS

The medical and imaging records for patients who underwent surgery for medulloblastoma at The Hospital for Sick Children were retrospectively reviewed. The primary outcome was the requirement for CSF diversion surgery either before or within 60 days of tumor resection. The modified Canadian Preoperative Prediction Rule for Hydrocephalus (mCPPRH) was compared among subgroups.

RESULTS

Of 143 medulloblastoma patients, treated from 1991 to 2013, sufficient data were available for 130 patients (15 with Wnt, 30 with Shh, 30 with Group 3, and 55 with Group 4 medulloblastomas). Of these, 28 patients (22%) ultimately underwent CSF diversion surgery: 0% with Wnt, 29% with Shh, 29% with Group 3, and 43% with Group 4 tumors. Patients in the Wnt subgroup had a lower incidence of CSF diversion than all other patients combined (p = 0.04). Wnt patients had a lower mCPPRH score (lower risk of CSF diversion, p = 0.045), were older, had smaller ventricles at diagnosis, and had no leptomeningeal metastases.

CONCLUSIONS

The overall rate of CSF diversion surgery for Shh, Group 3, and Group 4 medulloblastomas is around 30%, but no patients in the present series with a Wnt medulloblastoma required shunting. The low incidence of hydrocephalus in patients with Wnt medulloblastoma likely reflects both host factors (age) and disease factors (lack of metastases). The absence of hydrocephalus in patients with Wnt medulloblastomas likely contributes to their excellent rate of survival and may also contribute to a higher quality of life than for patients in other subgroups.

Molecular variants and mutations in medulloblastoma

Medulloblastoma is the commonest malignant brain tumor in children. Treatment with surgery, irradiation, and chemotherapy has improved outcomes in recent years, but patients are frequently left with devastating neurocognitive and other sequelae following such therapy. While the prognosis has traditionally been based on conventional histopathology and clinical staging (based on age, extent of resection, and presence or absence of metastasis), it has become apparent in recent years that the inherent biology of the tumor plays a significant part in predicting survival and sometimes supersedes clinical or pathologic risk factors. The advent of deep sequencing gene technology has provided invaluable clues to the molecular makeup of this tumor and allowed neuro-oncologists to understand that medulloblastoma is an amalgamation of several distinct disease entities with unique clinical associations and behavior. This review is a concise summary of the pathology, genetic syndromes, recent advances in molecular subgrouping, and the associated gene mutations and copy number variations in medulloblastoma. The association of molecular alterations with patient prognosis is also discussed, but it should be remembered that further validation is required in prospective clinical trials utilizing uniform treatment approaches.

Signaling pathway and molecular subgroups of medulloblastoma

Medulloblastoma (MB) is the most common malignant brain tumor in children. Although multimodality treatment regimens including surgery, radiotherapy and chemotherapy have greatly improved disease outcome, about one-third of MB patient remains incurable, and many long-term survivors are suffered from deleterious effects due to aggressive treatment. Understanding the signaling pathways and the genetic mechanisms contributed to MB development would be the key to develop novel therapeutic treatment strategies for improving survival and outcome of MB. In this review, we discuss the biological signaling pathways involved in MB pathogenesis. We also go through the current international consensus of four core MB subgroups namely, SHH, WNT, Group 3, and Group 4. This is adopted based on the knowledge of genomic complexity of MB as analyzed by recent high-throughput genomic technology. We talk about immunohistochemistry assays established to determine molecular subgroup affiliation. In the last part of review, we discuss how identification of molecular subgroups is going to change our routine disease diagnosis and clinical management.

Matching mice to malignancy: molecular subgroups and models of medulloblastoma

INTRODUCTION

Medulloblastoma, the largest group of embryonal brain tumors, has historically been classified into five variants based on histopathology. More recently, epigenetic and transcriptional analyses of primary tumors have subclassified medulloblastoma into four to six subgroups, most of which are incongruous with histopathological classification.

DISCUSSION

Improved stratification is required for prognosis and development of targeted treatment strategies, to maximize cure and minimize adverse effects. Several mouse models of medulloblastoma have contributed both to an improved understanding of progression and to developmental therapeutics. In this review, we summarize the classification of human medulloblastoma subtypes based on histopathology and molecular features. We describe existing genetically engineered mouse models, compare these to human disease, and discuss the utility of mouse models for developmental therapeutics. Just as accurate knowledge of the correct molecular subtype of medulloblastoma is critical to the development of targeted therapy in patients, we propose that accurate modeling of each subtype of medulloblastoma in mice will be necessary for preclinical evaluation and optimization of those targeted therapies.