Epithelioid Sarcoma Machine Learning Engine: $150,000 annually

EPS does not yet have a long history of international clinical data collection, with centralized imaging, histology slides or specimen collection (e.g., for future DNA and RNA studies). The purpose of this proposal is to empower a centralized resource of all available EPS data and resources so that Big Data (machine learning) can answer key questions around EPS care. Goals include Patient-oriented Registry & Biobank, Proteomics, Cutting-edge Database & Sequence Analysis Pipelines, Synchronization and Sharing, Outreach and Portability and Publication.

Clear Cell Sarcoma BigData – Drug Discovery: $470,154 annually for 2 years

Clear Cell Sarcoma (CCS) is a very rare soft tissue of children and adults. The underlying clinical problem is that only surgery is curative: chemotherapy and radiation are ineffective. Relapse with metastases results in a significant unmet clinical need because surgery is not possible and effective targeted therapies have not yet been developed. To meet this clinical need by developing new therapies, the biology of CCS needs to be taken into consideration: not only is the EWSR1-ATF1 chimeric transcription factor/fusion gene present, but cooperating mutations may also be present.

Expanding Chemical Space

Expanding the Chemical Space for Osteosarcoma: $782,377 over 2 years

An outstanding field of basic scientists and clinical investigators have explored the chemical space (druggable space) for osteosarcoma and have pioneered an efficient system of rapidly-completed phase II studies in the Children’s Oncology Group. Drugs have included RANKL inhibitors, anti-disialoganglioside antibodies, irreversible tubulin inhibitors, and anti-glycoprotein NMB conjugates – among others.

Engineering Forward Initiative for Childhood Cancer Therapies: $1,500,000

This multi-disciplinary approach to accelerating discovery of therapies for childhood cancer is made possible by a joint effort of our scientific director Dr. Keller and our Board member, Sunit Rikhi, former VP of the Intel custom foundry. Together, our teams of biologists and engineers will maximize automation and the design of new devices and biomaterials that address challenges in the treatment of cancer as well as prevention of recurrence, ultimately improving outcomes for children with cancer.

Building Blocks to a Cure: $1500 adds a child

Generating data as efficiently and accurately as possible, we plan to have drug – genetic matches for each type of embryonal rhabdomyosarcoma … and to publish this data, but also to share it in real time with pediatric oncologists of eRMS patients who may have scientific interest.

GEAR up! Genomics Endotypes in Alveolar Rhabdomyosarcoma: $1500 adds a child

Can we define a new standard of care for every subgroup of children battling aRMS? This project is important because many children, teens and young adults with alveolar rhabdomyosarcoma need new treatment options. When metastatic, the five-year survival rate is only 8%. We want aRMS to be universally survivable

Patient-specific CSF testing system for medulloblastoma metastasis: $97,000 one year

We propose a pilot study to (1) design a computational model of patient-specific flow conditions in the vicinity of a brain tumor leptomeningeal metastasis, and (2) to experimentally test whether drug exposures under those flow conditions would be effective against medulloblastoma tumor cells that represent the biology of the patient’s tumor.

Osteosarcoma BigData Target Discovery: $160,000 over one year

Osteosarcoma is a difficult cancer to have, a difficult cancer to treat, and a difficult cancer to understand. Osteosarcoma afflicts children, adults, pet dogs and even mice – a perfect storm to understand what drives this disease by looking at what is in common in all of these patients. Despite the need for better treatments and the despite efforts of the brightest and most innovative clinical trialists over the last 25 years, we remain unable to understand the key therapeutic targets of this disease

We need to move from a fragmented collection of osteosarcoma knowledge to a centralized one that is shared freely – and co-developed by patients and families.

Synthetic Human 2.1 — Empowering the Surgeon: $160,000 over one year

Alveolar rhabdomyosarcoma is a cancer of the soft tissues. Local control for rhabdomyosarcoma is an important clinical challenge, and recurrence at the tumor resection bed can be a gateway to progression and metastasis. Our project seeks to put the types of cutting edge, non-chemotherapy medicines used by internists into the hands of the surgeon for the purpose of preventing local recurrence at the earliest possible moment.

PLK1 in hepatoblastoma: $160,000 over one year

Approximately 100 patients are diagnosed with hepatoblastoma each year in the United States, and for the 20% of patients with unresectable or metastatic hepatoblastoma exist limited options. We propose preclinical validation studies of the drug volasertib, which targets the Polo-like kinase 1 (PLK1) oncogene in hepatoblastoma.

Epithelioid Sarcoma Machine Learning Engine: $150,000 annually

EPS does not yet have a long history of international clinical data collection, with centralized imaging, histology slides or specimen collection (e.g., for future DNA and RNA studies). The purpose of this proposal is to empower a centralized resource of all available EPS data and resources so that Big Data (machine learning) can answer key questions around EPS care. Goals include Patient-oriented Registry & Biobank, Proteomics, Cutting-edge Database & Sequence Analysis Pipelines, Synchronization and Sharing, Outreach and Portability and Publication.

Clear Cell Sarcoma BigData – Drug Discovery: $470,154 annually for 2 years

Clear Cell Sarcoma (CCS) is a very rare soft tissue of children and adults. The underlying clinical problem is that only surgery is curative: chemotherapy and radiation are ineffective. Relapse with metastases results in a significant unmet clinical need because surgery is not possible and effective targeted therapies have not yet been developed. To meet this clinical need by developing new therapies, the biology of CCS needs to be taken into consideration: not only is the EWSR1-ATF1 chimeric transcription factor/fusion gene present, but cooperating mutations may also be present.

Expanding Chemical Space

Expanding the Chemical Space for Osteosarcoma: $782,377 over 2 years

An outstanding field of basic scientists and clinical investigators have explored the chemical space (druggable space) for osteosarcoma and have pioneered an efficient system of rapidly-completed phase II studies in the Children’s Oncology Group. Drugs have included RANKL inhibitors, anti-disialoganglioside antibodies, irreversible tubulin inhibitors, and anti-glycoprotein NMB conjugates – among others.

Engineering Forward Initiative for Childhood Cancer Therapies: $1,500,000

This multi-disciplinary approach to accelerating discovery of therapies for childhood cancer is made possible by a joint effort of our scientific director Dr. Keller and our Board member, Sunit Rikhi, former VP of the Intel custom foundry. Together, our teams of biologists and engineers will maximize automation and the design of new devices and biomaterials that address challenges in the treatment of cancer as well as prevention of recurrence, ultimately improving outcomes for children with cancer.

Building Blocks to a Cure: $1500 adds a child

Generating data as efficiently and accurately as possible, we plan to have drug – genetic matches for each type of embryonal rhabdomyosarcoma … and to publish this data, but also to share it in real time with pediatric oncologists of eRMS patients who may have scientific interest.

GEAR up! Genomics Endotypes in Alveolar Rhabdomyosarcoma: $1500 adds a child

Can we define a new standard of care for every subgroup of children battling aRMS? This project is important because many children, teens and young adults with alveolar rhabdomyosarcoma need new treatment options. When metastatic, the five-year survival rate is only 8%. We want aRMS to be universally survivable

Patient-specific CSF testing system for medulloblastoma metastasis: $97,000 one year

We propose a pilot study to (1) design a computational model of patient-specific flow conditions in the vicinity of a brain tumor leptomeningeal metastasis, and (2) to experimentally test whether drug exposures under those flow conditions would be effective against medulloblastoma tumor cells that represent the biology of the patient’s tumor.

Osteosarcoma BigData Target Discovery: $160,000 over one year

Osteosarcoma is a difficult cancer to have, a difficult cancer to treat, and a difficult cancer to understand. Osteosarcoma afflicts children, adults, pet dogs and even mice – a perfect storm to understand what drives this disease by looking at what is in common in all of these patients. Despite the need for better treatments and the despite efforts of the brightest and most innovative clinical trialists over the last 25 years, we remain unable to understand the key therapeutic targets of this disease

We need to move from a fragmented collection of osteosarcoma knowledge to a centralized one that is shared freely – and co-developed by patients and families.

Synthetic Human 2.1 — Empowering the Surgeon: $160,000 over one year

Alveolar rhabdomyosarcoma is a cancer of the soft tissues. Local control for rhabdomyosarcoma is an important clinical challenge, and recurrence at the tumor resection bed can be a gateway to progression and metastasis. Our project seeks to put the types of cutting edge, non-chemotherapy medicines used by internists into the hands of the surgeon for the purpose of preventing local recurrence at the earliest possible moment.

PLK1 in hepatoblastoma: $160,000 over one year

Approximately 100 patients are diagnosed with hepatoblastoma each year in the United States, and for the 20% of patients with unresectable or metastatic hepatoblastoma exist limited options. We propose preclinical validation studies of the drug volasertib, which targets the Polo-like kinase 1 (PLK1) oncogene in hepatoblastoma.

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