Labeling Cancer Risk Factors as Lifestyle Limits Prevention Activities Across the Life Span

An Expanded Agenda for the Primary Prevention of Breast Cancer: Charting a Course for the Future

Advances in breast cancer science, early detection, and treatment have resulted in improvements in breast cancer survival but not in breast cancer incidence. After skin cancer, breast cancer is the most common cancer diagnosis in the United States. Each year, nearly a quarter million U.S. women receive a breast cancer diagnosis, and the number continues to rise each year with the growth in the population of older women. Although much remains to be understood about breast cancer origins and prevention, action can be taken on the existing scientific knowledge to address the systemic factors that drive breast cancer risk at the population level. The California Breast Cancer Research Program funded a team at Breast Cancer Prevention Partners (BCPP) to convene leaders in advocacy, policy, and research related to breast cancer prevention from across the state of California. The objective was the development of a strategic plan to direct collective efforts toward specific and measurable objectives to reduce the incidence of breast cancer. The structured, innovative approach used by BCPP to integrate scientific evidence with community perspectives provides a model for other states to consider, to potentially change the future trajectory of breast cancer incidence in the United States.

Advancing neuro-oncology of glial tumors from big data and multidisciplinary studies

INTRODUCTION

Multidisciplinary studies for glial tumors has produced an enormous amount of information including imaging, histology, and a large cohort of molecular data (i.e. genomics, epigenomics, metabolomics, proteomics, etc.). The big data resources are made possible through open access that offers great potential for new biomarker or therapeutic intervention via deep-learning and/or machine learning for integrated multi-omics analysis. An equally important effort to define the hallmarks of glial tumors will also advance precision neuro-oncology and inform patient-specific therapeutics. This review summarizes past studies regarding tumor classification, hallmarks of cancer, and hypothetical mechanisms. Leveraging on advanced big data approaches and ongoing cross-disciplinary endeavors, this review also discusses how to integrate multiple layers of big data toward the goal of precision medicine.

RESULTS

In addition to basic research of cancer biology, the results from integrated multi-omics analysis will highlight biological processes and potential candidates as biomarkers or therapeutic targets. Ultimately, these collective resources built upon an armamentarium of accessible data can re-form clinical and molecular data to stratify patient-tailored therapy.

CONCLUSION

We envision that a comprehensive understanding of the link between molecular signatures, tumor locations, and patients' history will identify a molecular taxonomy of glial tumors to advance the improvements in early diagnosis, prevention, and treatment.