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The purpose of this project is to develop a comprehensive database of genomic, transcriptomic, molecular, and clinical characteristics of oncology patients to discover, define, and develop genomic and transcriptomic markers to improve future clinical outcomes across cancer types
Immuno- and targeted therapies have shown promising results for many types of cancer (1). However, the effectiveness of these treatments is not optimal for many patients (2). Therefore, further research is needed to discover, define, and develop genomic, transcriptomic, and integrated molecular markers that can improve clinical outcomes across cancer types (3). Unfortunately, current research is restricted by the limited availability of genomic and transcriptomic results linked to clinical outcomes (3). This study will allow for the collection of key clinical data, including longitudinal follow-up, linked with individual genetic and molecular findings in a single comprehensive registry-based databank. Analysis of these data may lead to advances across cancer subtypes through the identification of transcriptomic and genomic associations with therapies.
Clinical and pathological information, including detailed genetic information from a participant's tumor biopsy, will be obtained by the research staff for each participant enrolled in the BIGR Study. Clinical information will include relevant details about the patient's diagnosis and treatment and will be stored in a secure electronic registry database. No extra scans or procedures for this study will be collected as part of this study. Information will be collected regarding a participant's initial diagnosis, treatment, and outcome. To obtain this information, study staff will contact participants or a participant's doctor at regular time intervals for up to 15 years.
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| Measure | Description | Time Frame |
|---|---|---|
| association between major finding and outcome, Descriptive | associations between genomic findings and outcomes of cancer patients who have undergone comprehensive sequencing. | 5 years |
| Measure | Description | Time Frame |
|---|---|---|
| Predictive probability | identify molecular findings associated with therapy. | 5 years |
| Clinical trials matching | identify and link registry subjects to future molecular-based clinical research |
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Inclusion Criteria:
Exclusion Criteria:
Life expectancy < 3 months
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Subjects will be identified for the BIGR study from a larger group of patients undergoing BostonGene clinical testing (e.g., BostonGene Tumor Portrait TestTM).
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Nathan Fowler | Contact | +1-617-658-4545 | nathan.fowler@bostongene.com |
| Name | Affiliation | Role |
|---|---|---|
| Nathan Fowler | BostonGene | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| BostonGene | Recruiting | Waltham | Massachusetts | 02453 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32467593 | Background | Murciano-Goroff YR, Warner AB, Wolchok JD. The future of cancer immunotherapy: microenvironment-targeting combinations. Cell Res. 2020 Jun;30(6):507-519. doi: 10.1038/s41422-020-0337-2. Epub 2020 May 28. | |
| 30941175 | Background | Sambi M, Bagheri L, Szewczuk MR. Current Challenges in Cancer Immunotherapy: Multimodal Approaches to Improve Efficacy and Patient Response Rates. J Oncol. 2019 Feb 28;2019:4508794. doi: 10.1155/2019/4508794. eCollection 2019. |
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| ID | Term |
|---|---|
| D009369 | Neoplasms |
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| 5 years |
| 31561483 | Background | Olivier M, Asmis R, Hawkins GA, Howard TD, Cox LA. The Need for Multi-Omics Biomarker Signatures in Precision Medicine. Int J Mol Sci. 2019 Sep 26;20(19):4781. doi: 10.3390/ijms20194781. |