BIOM-35. CLINICALLY TRACTABLE OUTCOME PREDICTION OF GROUP 3/4 MEDULLOBLASTOMA BASED ON TPD52 IMMUNOHISTOCHEMISTRY: A MULTICOHORT STUDY

Abstract BACKGROUND International consensus and the 2021 WHO classification recognize eight molecular subgroups among Group 3/4 medulloblastoma (representing ~60% of tumors). However, very few clinical centers worldwide possess the technical capabilities to determine DNA-methylation patterns or other molecular parameters of high-risk for Group 3/4 tumors. As a result, biomarker-driven risk stratification and therapy assignment constitutes a major challenge in medulloblastoma research. Here, we identify an immunohistochemistry (IHC) marker as a clinically tractable method for improved medulloblastoma risk-stratification. PATIENTS AND METHODS We bioinformatically analyzed published medulloblastoma transcriptomes and proteomes identifying as a potential biomarker TPD52, whose IHC prognostic value was validated across three Group 3/4 medulloblastoma clinical cohorts (n = 387) treated with conventional therapies. Risk stratification and prediction capability were computed utilizing uni- and multivariate survival analysis. Newly developed risk classifiers including TPD52 IHC were compared to state-of-the-art risk stratification schemes in terms of prediction error, area under the time-dependent receiver operating characteristic (ROC) curves and C-statistic. Biomarker-driven prognostic stratification models identified were cross validated in different cohorts. RESULTS TPD52 IHC positivity represents a significant independent predictor of early relapse and death for Group 3/4 medulloblastoma (HRs between 3.67-26.7 [95% CIs between 1.00-706.23], p = 0.05, 0.017 and 0.0058). Cross-validated survival models incorporating TPD52 IHC with clinical features outperformed existing disease risk-stratification schemes, and reclassified ~50% of patients into more appropriate risk categories. Finally, TPD52 immunopositivity is a predictive indicator of poor response to chemotherapy (HR 12.66 [95% CI 3.53-45.40], p < 0.0001), suggesting important implication for therapeutic choices. CONCLUSION The current study redefines the approach to risk-stratification in Group 3/4 medulloblastoma. Integration of TPD52 IHC in classification algorithms significantly improves outcome prediction and can be rapidly adopted for risk stratification on a global scale, independently of advanced but technically challenging molecular profiling techniques.

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EMBR-21. CLINICALLY TRACTABLE OUTCOME PREDICTION OF GROUP 3/4 MEDULLOBLASTOMA BASED ON TPD52 IMMUNOHISTOCHEMISTRY: A MULTICOHORT STUDY

Neuro-Oncology ◽

10.1093/neuonc/noab090.039 ◽

2021 ◽

Vol 23 (Supplement_1) ◽

pp. i10-i10

Author(s):

Alberto Delaidelli ◽

Christopher Dunham ◽

Maria Rita Santi ◽

Gian Luca Negri ◽

Joanna Triscott ◽

...

Keyword(s):

Risk Stratification ◽

Outcome Prediction ◽

Disease Risk ◽

Poor Response ◽

Survival Models ◽

International Consensus ◽

Significant Independent Predictor ◽

Potential Biomarker ◽

Response To Chemotherapy ◽

Group 3

Abstract Background International consensus and the 2021 WHO classification recognize eight molecular subtypes among Group 3/4 medulloblastoma (representing ~60% of tumors). However, very few clinical centers worldwide possess the technical capabilities to determine DNA-methylation patterns or other molecular parameters of high-risk for Group 3/4 tumors. As a result, biomarker-driven risk stratification and therapy assignment constitutes a major challenge in medulloblastoma research. Here, we identify an immunohistochemistry (IHC) marker as a clinically tractable method for improved medulloblastoma risk-stratification. Patients and Methods We bioinformatically analyzed published medulloblastoma transcriptomes and proteomes identifying as a potential biomarker TPD52, whose IHC prognostic value was validated across three Group 3/4 medulloblastoma clinical cohorts (n = 387) treated with conventional therapies. Risk stratification and prediction capability were computed utilizing uni- and multivariate survival analysis. Newly developed risk classifiers including TPD52 IHC were compared to state-of-the-art risk stratification schemes in terms of prediction error, area under the time-dependent receiver operating characteristic (ROC) curves and C-statistic. Biomarker-driven prognostic stratification models identified were cross validated in different cohorts. Results TPD52 IHC positivity represents a significant independent predictor of early relapse and death for Group 3/4 medulloblastoma (HRs between 3.67–26.7 [95% CIs between 1.00–706.23], p = 0.05, 0.017 and 0.0058). Cross-validated survival models incorporating TPD52 IHC with clinical features outperformed existing disease risk-stratification schemes, and reclassified ~50% of patients into more appropriate risk categories. Finally, TPD52 immunopositivity is a predictive indicator of poor response to chemotherapy (HR 12.66 [95% CI 3.53–45.40], p < 0.0001), suggesting important implication for therapeutic choices. Conclusion The current study redefines the approach to risk-stratification in Group 3/4 medulloblastoma. Integration of TPD52 IHC in classification algorithms significantly improves outcome prediction and can be rapidly adopted for risk stratification on a global scale, independently of advanced but technically challenging molecular profiling techniques.

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Prognostic Significance of NOTCH1 and FBXW7 Mutations in Childhood T-Cell Acute Lymphoblastic Leukemia (T-ALL): Results From the EORTC Children Leukemia Group.

Blood ◽

10.1182/blood.v114.22.909.909 ◽

2009 ◽

Vol 114 (22) ◽

pp. 909-909 ◽

Cited By ~ 1

Author(s):

Emmanuelle Clappier ◽

Sandra Collette ◽

Nathalie Grardel ◽

Sandrine Girard ◽

Lydia Suarez ◽

...

Keyword(s):

Risk Stratification ◽

Prognostic Significance ◽

Poor Response ◽

Early Response ◽

Favourable Outcome ◽

High Dose ◽

Prognostic Impact ◽

Childhood All ◽

Response To Chemotherapy ◽

Notch1 Mutations

Abstract Abstract 909 T-ALL accounts for approximately 15% of childhood ALL. Despite major improvement of treatments, relapses still occur with dramatic prognosis. Efforts made in the past decade to understand T-ALL oncogenesis led to the identification of a number of oncogenes deregulated by genomic abnormalities, including TAL1, HOX11/TLX1, HOX11L2/TLX3, CALM-AF10, NUP214-ABL1, and MYB, some of them determining subtypes with distinct biological profiles. However, in EORTC trials, using BFM-derived protocols, these various genetic lesions have no prognostic impact, with the exception of a trend toward a favourable outcome for SIL-TAL1 fusion or HOX11 over expression (Cavé et al. 2004). Thus, risk-stratification remained based on early response to chemotherapy, as assessed by poor response to the (corticosteroid) prephase (PPR) and, in addition (58951 trial), on a high level (>10-2) of minimal residual disease (MRD) at completion of induction therapy. Hyperactivation of the NOTCH pathway by mutations of NOTCH1 or FBXW7 has been recently demonstrated in T-ALL. We investigated whether NOTCH1 and/or FBXW7 status could help to improve risk-stratification in T-ALL. We screened NOTCH1 and FBXW7 mutations by direct sequencing in 133 children with T-ALL enrolled in EORTC-CLG trials 58881 and 58951. Activating NOTCH1 mutations were found in 75 (56%) patients. Inactivating FBXW7 mutations were found in 20 (14%) patients, mostly in association with NOTCH1 mutations. Overall, 78 (59%) patients were considered NOTCH+ (NOTCH1 and/or FBXW7 mutated) whereas 55 (41%) were NOTCH- (NOTCH1 and FBXW7 wild type). NOTCH+ patients were distributed through all genetic subgroups. No significant relationships between NOTCH status and sex, age, WBC count, CNS or mediastinal involvement were observed. However, NOTCH+ had more often a cortical immunophenotype (53% vs 28%; p=0.02). NOTCH+ patients had a better early response to chemotherapy vs NOTCH- patients: lower PPR rate (20% vs 42%; p=0.02), and a lower incidence of high MRD level (13% (6/45) versus 30% (9/30); p=0.14). This led to less frequent switch to a very high risk (VHR) protocol for NOTCH+ versus NOTCH- patients (29% vs 49%, p=0.05). After a median follow-up of 4.6 years, 3 patients did not reach CR, 25 relapsed, 1 died in CR and 84 remained alive in CR; a total of 18 patients died. The outcome of NOTCH+ patients was similar to that of NOTCH- patients. The 5-yr EFS were 74% and 69% (p=0.8), respectively, and the 5-yr overall survival were 82% and 80% (p=0.7), respectively. However, prognostic importance of NOTCH status differed according to early response to treatment. In patients with a PPR, the NOTCH+ patients had a worse outcome than NOTCH- patients (5-yr EFS was 44% vs 58%; HR=1.54, p=0.43), whereas in non-PPR subgroup a reverse trend was observed (5-yr EFS was 83% vs 76%; HR=0.94, p=0.91). Similarly, in patients with high MRD levels the outcome was worse in NOTCH+ vs NOTCH- patients (5-yr EFS was 0% vs 47%, HR=11.7, p=0.03) whereas in MRD- patients the trend was reversed (5-yr EFS was 79% vs 71%, HR=0.88, p=0.83). Thus, although NOTCH1+ patients responded earlier and better to chemotherapy as compared to NOTCH1- patients, they did not show, overall, a better EFS. This was due to the poor outcome of NOTCH+ patients who had VHR features. In the German BFM trials, NOTCH1 mutations were also associated with lower rate of “poor response” to chemotherapy but this translated into a favourable outcome (see the ASH 2009 abstract of Kox et al.) NOTCH1- patients had a similar outcome in EORTC and BFM studies (5-yr EFS: 69% vs 74%) whereas NOTCH1+ patients had a lower 5-yr EFS in EORTC than in BFM studies (74% vs 87%). Noteworthy, in the EORTC trials the rate of isolated CNS relapses was quite high in NOTCH1+ patients (7.8%=6/77) as compared to NOTCH- patients (1.9%=1/53). Recently it was shown that NOTCH1 positively controls the expression of the chemokine receptor CCR7, an adhesion signal required for targeting T-ALL cells into the CNS (Buonamici et al. 2009). This may explain the higher propensity of NOTCH+ ALL to relapse in CNS. Although this is not the only difference in treatment between EORTC and BFM, the use of high dose methotrexate and intrathecal chemotherapy only, with omission of cranial irradiation prophylaxis in EORTC protocols, might have led to a suboptimal prevention of CNS relapses in NOTCH+ T-ALL, resulting in a lower EFS in EORTC trials as compared with German BFM in this group of patients. Disclosures: No relevant conflicts of interest to declare.

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Rapamycin Antagonizes BCRP-Mediated Drug Resistance Through the PI3K/Akt/mTOR Signaling Pathway in mPRα-Positive Breast Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.608570 ◽

2021 ◽

Vol 11 ◽

Author(s):

Jing Zhang ◽

Jing Hu ◽

Weiwei Li ◽

Chunyan Zhang ◽

Peng Su ◽

...

Keyword(s):

Breast Cancer ◽

Signaling Pathway ◽

Therapeutic Option ◽

Poor Response ◽

Mtor Signaling ◽

Cell Counting ◽

Mtor Signaling Pathway ◽

Potential Biomarker ◽

Response To Chemotherapy

PurposeOverexpression of breast cancer (BCa) resistance protein (BCRP) is detected in approximately 30% of BCa cases. BCRP indicates a poor response to chemotherapy, and it has become a classic target to overcome drug-resistant tumor cells. In this study, we aimed to explore the mechanism of BCRP overexpression and a strategy to reverse this overexpression in invasive BCa.MethodsBCRP expression in BCa tissues was determined by immunohistochemistry. GSE25066 was downloaded from the NCBI GEO database. Western blot was used to determine the expression of key molecules in vitro. Cell counting kit-8 assays were used to assess the drug response of BCa cells.ResultsOur results suggested that BCRP is an independent risk factor for BCa. We further established that upon 17α-PG binding, membrane progesterone receptor α (mPRα) promoted BCRP expression via the PI3K/Akt/mTOR signaling pathway. mPRα physically interacted with p-Akt1 S473. Moreover, rapamycin, an inhibitor of mTOR complex 1 (mTORC1), downregulated BCRP expression and enhanced the effects of particular drugs, including doxorubicin and paclitaxel.ConclusionBCRP is a potential biomarker of poor prognosis in BCa. BCRP expression is regulated by 17α-PG in mPRα-positive BCa cells through the PI3K/Akt/mTOR signaling pathway. Rapamycin might enhance the therapeutic effect of chemotherapy agents in mPRα-positive MDA-MB-453/BCRP cells and might be a therapeutic option for mPRα-positive invasive BCa with BCRP overexpression.

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Quantitative disease risk scores from EHR with applications to clinical risk stratification and genetic studies

npj Digital Medicine ◽

10.1038/s41746-021-00488-3 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Danqing Xu ◽

Chen Wang ◽

Atlas Khan ◽

Ning Shang ◽

Zihuai He ◽

...

Keyword(s):

Risk Stratification ◽

Disease Risk ◽

Association Studies ◽

Large Datasets ◽

Risk Scores ◽

Sequencing Data ◽

Case Definitions ◽

Phenotypic Data ◽

Clinical Risk ◽

Phenotypic Features

AbstractLabeling clinical data from electronic health records (EHR) in health systems requires extensive knowledge of human expert, and painstaking review by clinicians. Furthermore, existing phenotyping algorithms are not uniformly applied across large datasets and can suffer from inconsistencies in case definitions across different algorithms. We describe here quantitative disease risk scores based on almost unsupervised methods that require minimal input from clinicians, can be applied to large datasets, and alleviate some of the main weaknesses of existing phenotyping algorithms. We show applications to phenotypic data on approximately 100,000 individuals in eMERGE, and focus on several complex diseases, including Chronic Kidney Disease, Coronary Artery Disease, Type 2 Diabetes, Heart Failure, and a few others. We demonstrate that relative to existing approaches, the proposed methods have higher prediction accuracy, can better identify phenotypic features relevant to the disease under consideration, can perform better at clinical risk stratification, and can identify undiagnosed cases based on phenotypic features available in the EHR. Using genetic data from the eMERGE-seq panel that includes sequencing data for 109 genes on 21,363 individuals from multiple ethnicities, we also show how the new quantitative disease risk scores help improve the power of genetic association studies relative to the standard use of disease phenotypes. The results demonstrate the effectiveness of quantitative disease risk scores derived from rich phenotypic EHR databases to provide a more meaningful characterization of clinical risk for diseases of interest beyond the prevalent binary (case-control) classification.

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The number of osteoclasts in a biopsy specimen can predict the efficacy of neoadjuvant chemotherapy for primary osteosarcoma

Scientific Reports ◽

10.1038/s41598-020-80504-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Y. Araki ◽

N. Yamamoto ◽

K. Hayashi ◽

A. Takeuchi ◽

S. Miwa ◽

...

Keyword(s):

Neoadjuvant Chemotherapy ◽

Biopsy Specimen ◽

Osteoclast Differentiation ◽

Poor Response ◽

Underlying Mechanism ◽

Biopsy Specimens ◽

Response To Chemotherapy ◽

Simple Factor ◽

Chemotherapy Agents ◽

Chemotherapy Efficacy

AbstractOsteosarcoma is the most common primary malignant bone tumor, and its standard treatment is a combination of surgery and chemotherapy. A poor response to chemotherapy causes unfavorable oncological outcomes. We investigated the correlation between osteoclast differentiation in biopsy specimens and the efficacy of neoadjuvant chemotherapy in resected specimens. Forty-nine patients who underwent neoadjuvant chemotherapy and subsequent surgical treatment at our institution between 1999 and 2018 were enrolled. Using medical records, we investigated the age, sex, tumor size, location, subtype, staging, chemotherapy agents (doxorubicin, cisplatin, ifosfamide, and methotrexate), number of neoadjuvant chemotherapy courses, number of osteoclasts in biopsy specimens, and efficacy of neoadjuvant chemotherapy according to the Rosen and Huvos classification (Grade I-IV) in resected specimens. Univariate and multivariate analyses were performed to identify factors predictive of a good response in resected specimens after neoadjuvant chemotherapy. A good response (Grade III/IV) was detected in 25, while a poor response (Grade I/II) was detected in 24. According to the multivariate analysis, ≥ 46 years old (odds ratio [OR], 0.05; 95% confidence interval [CI], 0.01–0.45; p < 0.01) and ≥ 5 mature osteoclasts in a biopsy specimen (OR, 36.9; 95% CI, 6.03–225; p < 0.01) were significantly associated with the neoadjuvant chemotherapy efficacy. The accuracy for predicting a good response to chemotherapy based on ≥ 5 osteoclasts in a biopsy specimen in patients < 46 years old was 85%. The number of mature osteoclasts in biopsy specimens is a simple factor for predicting the efficacy of chemotherapy before treatment, although further studies will be required to determine the underlying mechanism.

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Sudden Cardiac Death in Hereditary Dilated Cardiomyopathy

Sudden Cardiac Death ◽

10.5772/intechopen.91702 ◽

2020 ◽

Author(s):

Marianna Leopoulou ◽

Jo Ann LeQuang ◽

Joseph V. Pergolizzi ◽

Peter Magnusson

Keyword(s):

Sudden Cardiac Death ◽

Left Ventricle ◽

Sudden Death ◽

Risk Stratification ◽

Dilated Cardiomyopathy ◽

Cardiac Death ◽

Disease Risk ◽

Systolic Dysfunction ◽

Preventive Strategies ◽

Genetic Origin

Dilated cardiomyopathy (DCM) is characterized by the phenotype of a dilated left ventricle with systolic dysfunction. It is classified as hereditary when it is deemed of genetic origin; more than 50 genes are reported to be related to the condition. Symptoms include, among others, dyspnea, fatigue, arrhythmias, and syncope. Unfortunately, sudden cardiac death may be the first manifestation of the disease. Risk stratification regarding sudden death in hereditary DCM as well as preventive management poses a challenge due to the heterogeneity of the disease. The purpose of this chapter is to present the epidemiology, risk stratification, and preventive strategies of sudden cardiac death in hereditary DCM.

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