The microbiome in pediatric oncology.
Ontology highlight
ABSTRACT:
SUBMITTER: Rotz SJ
PROVIDER: S-EPMC7678566 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
Publications
The human microbiome comprises a diverse set of microorganisms, which play a mostly cooperative role in processes such as metabolism and host defense. Next-generation genomic sequencing of bacterial nucleic acids now can contribute a much broader understanding of the diverse organisms composing the microbiome. Emerging evidence has suggested several roles of the microbiome in pediatric hematology/oncology, including susceptibility to infectious diseases, immune response to neoplasia, and contrib ...[more]
Similar Datasets
Project description:Cancer is a disease whose progression is driven by a series of accumulating genetic and epigenetic changes influenced by hereditary factors and the somatic environment. These changes result in individual cells acquiring a phenotype that provides those cells with a survival advantage over surrounding normal cells. Our understanding of the processes that occur in malignant transformation is increasing, with many discoveries in cancer cell biology having been made through the study of childhood tumors. The processes involved in oncogenesis and cancer progression will be discussed in this review.
| S-EPMC2914477 | biostudies-literature
Project description:Outcome in treatment of childhood cancers has improved dramatically since the 1970s. This success was largely achieved by the implementation of cooperative clinical research trial groups that standardized and developed treatment of childhood cancer. Nevertheless, outcome in certain types of malignancies is still unfavorable. Intensification of conventional chemotherapy and radiotherapy improved outcome only marginally at the cost of acute and long-term side effects. Hence, it is necessary to develop targeted therapy strategies.Here, we review the developments and perspectives in precision medicine in pediatric oncology with a special focus on targeted drug therapies like kinase inhibitors and inducers of apoptosis, the impact of cancer genome sequencing and immunotherapy.
| S-EPMC6119176 | biostudies-other
Project description:This study examined pediatric patients undergoing treatment for various cancers and examined the impact of antibiotic use and duration on antibiotic resistance genes
| PRJEB59728 | ENA
Project description:To assess their utility in routine neuropathology, we prospectively integrated DNA methylation-based CNS tumor classification and targeted gene panel sequencing of tumor and constitutional DNA with blinded neuropathological reference diagnostics for a population-based cohort of > 1,200 newly-diagnosed pediatric patients.
2023-01-30 | GSE215240 | GEO
Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration. Unsupervised clustering and supervised risk classification analyses of 207 diagnostic samples and associated clinical covariate data. See the Summary for greater details. The data were analyzed using Microarray Suite version 5.0 (MAS 5.0) in the Affymetrix Gene Chip Operating Software Version 1.4. Probe masking was used (see 9906_TT207_Affymetrix_probe_mask.msk, linked below as a supplementary file). Otherwise all Affymetrix default parameter settings were used. Global scaling as the normalization method, with the default target intensity of 500, was used.
2009-06-25 | E-GEOD-11877 | biostudies-arrayexpress
Project description:PURPOSE OF REVIEW:The current review describes recent advances and unique challenges in precision medicine for pediatric cancers and highlights clinical trials assessing the clinical impact of targeted therapy matched to molecular alterations identified by tumor profiling. RECENT FINDINGS:Multiple prospective clinical sequencing studies in pediatric oncology have been reported in the last 2 years. These studies demonstrated feasibility of sequencing in the clinic and revealed a rate of actionable variants that justifies the development of precision trials for childhood cancer. A number of precision medicine trials are recently completed, underway or in development and these will be reviewed herein, with a focus on highlighting aspects of precision medicine trial design relevant to pediatric oncology. SUMMARY:The primary results of the first round of pediatric precision oncology clinical trials will provide us with a greater understanding of the clinical impact of linking tumor profiling to selection of targeted therapies. The aggregation of sequencing and clinical data from these trials and the results of biologic investigations linked to these trials will drive further discoveries and broaden opportunities for precision medicine for children with cancer.
| S-EPMC5770114 | biostudies-literature
Project description:Improvements in outcome have been seen in children and adolescents with cancer. Nevertheless, challenges remain in trying to improve the outcomes for all children diagnosed with cancer, particularly in patients with metastatic disease or with cancers that are resistant or recur after standard treatment. Precision medicine trials using individualized tumor molecular profiling for selection of targeted therapies are ongoing in adult malignancies. Similar approaches are being applied to children and adolescents with cancer. This article describes how precision medicine is being applied to pediatric oncology and the unique challenges being faced with these efforts.
| S-EPMC7819485 | biostudies-literature
Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration.
2009-06-25 | GSE11877 | GEO
Project description:BackgroundIntegratedbehavioral health models have been proposed as care delivery approaches to mitigate mental health disparities in primary care settings. However, these models have not yet been widely adopted or evaluated in pediatric oncology medical homes.MethodsWe conducted a retrospective cohort study of 394 children with newly diagnosed cancer at Dana-Farber/Boston Children's Cancer and Blood Disorders Center (DF/BCH) from April 2013 to January 2017. Baseline sociodemographic characteristics and psychiatry utilization outcomes at 12 months following diagnosis were abstracted from the medical record. The severity of household material hardship (HMH), a concrete poverty exposure, at diagnosis and race/ethnicity were characterized by parent report using the Psychosocial Assessment Tool 2.0 (PAT). Associations between sociodemographic characteristics and receipt of psychiatry consultation were assessed with multivariable logistic regression models.ResultsAmong 394 children, 29% received a psychiatric consultation within 12 months postdiagnosis. Of these, 88% received a new psychiatric diagnosis, 76% received a psychopharmacologic recommendation, and 62% received a new behavioral intervention recommendation. In multivariable logistic regression adjusting for age, cancer diagnosis, and PAT total score, there was no statistically significant association between HMH severity or household income and psychiatry utilization. Children who identified as racial/ethnic minorities were significantly less likely to receive a psychiatry consultation (OR = 0.48, 95% CI = 0.27-0.84).ConclusionsIn a pediatric oncology medical home with an integrated behavioral health model, socioeconomic status was not associated with disparate psychiatry utilization. However, there remained a profound racial/ethnic disparity in psychiatry utilization, highlighting the need for additional research and care delivery intervention.
| S-EPMC8463506 | biostudies-literature
Project description:BackgroundDiversity is necessary for the survival and success of both biological and social systems including societies. There is a lack of diversity, particularly the proportion of women and minorities in leadership positions, within medicine [Leadley. AAMC 2009. Steinecke and Terrell. Acad Med 2010;85:236-245]. In 2009 a group of ASPHO members recognized the need to support the career advancement of women and minority members. This article reports the results of a survey designed to characterize the comparative career pathway experience of women and minority ASPHO members.ProcedureA group of ASPHO members modified a published Faculty Worklife survey [Pribbenow et al. High Educ Policy 2010;23:17-38] for use by Pediatric Hematologist-Oncologists (PHOs). A link to an online version of the survey was sent to all ASPHO members.ResultsOf 1,228 ASPHO members polled, 213 responded (17%). Women and minority PHOs reported less satisfaction than their counterparts on 70 of the 90 issues addressed in the survey including the hiring process, access to resources as well as integration and satisfaction with their organizations. Women also expressed greater dissatisfaction with issues of work-life balance, support for family obligations and personal health.ConclusionsThe current literature suggests that there are significant disparities in career opportunities, compensation and satisfaction for women compared to men and minority compared to majority faculty in academic medicine [Nivet. J Vasc Surg 2010;51:53S-58S; Peterson et al. J Gen Intern Med 2004;19:259-265; DesRoches et al. Acad Med 2010;85:631-639; Castillo-Page. AAMC 2008]. Our data, derived from a survey of ASPHO members, suggests that this holds true for PHOs as well.
| S-EPMC3092025 | biostudies-literature