Whether diagnosed as a child (< age 15), adolescent, or young adult (AYA, age 15-39), young survivors of cancer face many challenges regarding their long-term outcomes. This presents a timely opportunity for the CCDI to clarify what this growing population will need in the future, but we must first clearly understand the target population for this initiative. Clarity is needed whether the intention of the CCDI is to provide... more »
The initiative will prioritize scientific and clinical research data needs for addressing the burden of cancer in children, adolescents, and young adults. We must determine which research questions should be answered.
Answer one or more of the following questions in your response:
- What research questions can be addressed through improved childhood cancer data sharing?
- What common data would be needed to answer those questions?
Lynch syndrome (LS) population are at increased risk for cancers, such as colorectal, endometrium, ovaries, stomach, small bowel, pancreas, kidneys, brain, ureters and bile duct. LS is caused by genetic defects in one or more DNA MMR genes, including MLH1, MSH2, MSH6, and PMS2. Cancer progression is rapid in LS patients compared to general population. Clinicians now have a simple and easily employed means of determining... more »
One of the most aggressive forms of childhood cancer predisposition syndromes is constitutional mismatch repair deficiency syndrome (CMMRD). CMMRD results from biallelic deleterious germline mutations in one of the mismatch repair (MMR) genes, MLH1, MSH2, MSH6, or PMS2. Children with CMMRD develop hematological malignancies, brain tumors, gastrointestinal cancers, and other cancers. Compared to cancers associated with... more »
Familial adenomatous polyposis (FAP) is an autosomal dominant cancer predisposition syndrome. It is caused by germline mutations in the APC gene. Individuals affected with FAP are at increased risk of developing not only colorectal cancer but also other cancers, such as thyroid cancer, pancreatic cancer, hepatoblastoma, medulloblastoma, and desmoid tumors. Children, adolescents, and young adults with a family history... more »
Incidence of several cancers continues to increase in children and adolescents. Individual studies and international collaborations have made progresses in understanding risk factors of certain childhood cancers, yet gaps remain. The CCDI should also invest in supporting data sharing for etiologic research (population-based and mechanistic studies).
Predictive disease models of pediatric hematologic cancers can inform efficient testing of possible novel therapeutic agents in the clinical setting. However, to ensure that these models are useful in prioritizing novel therapeutic targets, pre-clinical assessments must be conducted. Conducting such analysis efficiently and consistently will require investigators to share pre-clinical data generated from models (e.g.,... more »
Refining risk stratification protocols and enhancing risk prediction in the pediatric population to identify children at risk of developing hematologic cancers: While the treatment outcome of children with acute leukemias (e.g., acute myeloid leukemia and ALL) has improved over the years, there remains a population of these patients who are unable to respond favorably to available therapies. Predicting poor response remains... more »
Understanding the biology of pediatric hematologic cancer development through: • Insights from epigenetics: In all hematologic malignancies, including acute and chronic leukemias, and lymphomas, there are both inherited and somatic genetic alterations that contribute to predisposition, transformation, and disease progression. While genomics plays a significant role in the onset and progression of such malignancies,... more »
Dear Committee; - i would like to introduce you to my idea " relapse prediction using machine learning algorithms " - my topic is about turning the initial data collected from the patients when introduced for first time before starting the treatment into insights using data science. it depends on each disease type and according to the treatment protocol. - by using an Electronic Data Capture (EDC) system , we can turn... more »
Dear committee, I would like to write a new plan for two date sets for cancer therapy of youth. One set of data is based on the pharmacological data set coming from the patient's cells embedded embryo of Zebrafish. Such PDX (Patient-Derived Xenograft Model; PDX) is now getting realistic and offer more precise medicine of cancer therapy. Because of the mechanism of Zebrafish based PDX, each embryo of Zebrafish needs... more »
Cancer treatment outcomes depend on the hospital environment. Research should evaluate the effects of ambient lighting (color, intensity, timing), and the best time of day for chemotherapy and feeding and other interventions which can disrupt a patient's normal circadian rhythm. This initiative was chosen as representative of the recommendations from members of the Society for Research on Biological Rhythms (SRBR).
primary prevention of childhood cancers
Parents of children who receive radiation for cancer treatment want to know about the long term effects of radiation on growth and development; robust data to answer these important questions are lacking. To address these questions, serial standard of care imaging could be collected from children undergoing radiation therapy at baseline and in followup. Using RTSTRUCT data in DICOM format, radiation dose to tumor volumes... more »
Emerging evidence suggests that childhood and AYA cancer survivors experience age-related conditions decades earlier in life due to cancer and its treatments. Having markers of biological age over time would allow researchers to assess aging trajectories in cancer survivors and determine whether cancer and its treatments cause an acceleration or accentuation of the aging process. Risk factor data would allow researchers... more »
There are number of hereditary cancer syndromes which may result in neoplasms in children and/or adolescents, for example: Li-Fraumeni syndrome, PTEN hamartoma tumor syndrome, Fanconi anemia, etc. Number of cancer screening/surveillance protocols have been established in order to decrease morbidity and mortality for individuals with pathogenic germline alterations known to cause hereditary cancer syndromes. For example,... more »