why Early detection of cancer

When cancer is detected at the earliest stages, treatment is more effective and survival drastically improves. Yet ~50% of cancers are still only detected at an advanced stage. Improved earlier detection of cancer could substantially increase survival rates. Although recent advances in early detection have saved lives, further innovations and development of early cancer detection approaches are needed. The field is evolving rapidly, owing to advances in biological understanding and an increasing pace of technological progress.

We highlight five challenges facing the field, current work in those areas, and where more research is needed to make early detection a reality. The first challenge is to build a greater understanding of the biology and behavior of early disease. This will help identify ways to distinguish between consequential, aggressive lesions and inconsequential lesions that will not cause harm. Such insight will be crucial to realizing the potential for early detection to inform treatment decisions and improve survival, while minimizing the risk of overtreatment. Alongside studies in human samples, better models of disease are enabling identification of early signals of tumorigenesis and clarifying the contributions of the immune system and microenvironment to tumor development.Survival improves when cancer is detected early. However, ~50% of cancers are at an advanced stage when diagnosed. Early detection of cancer or precancerous change allows early intervention to try to slow or prevent cancer development and lethality. 

The second challenge is determining the risk of developing cancer. How can we use germline genomic susceptibility, family history, exposures, demographic, and behavioral data to build nuanced risk models to identify who should be tested for cancer and how test results should be interpreted and followed up? Progress is being made to address this challenge through improved understanding of the genomics of cancer risk, integration of that insight with other risk factors, and the development of large-scale population cohorts where risk models can be developed and validated.

The third challenge is finding and validating biomarkers of early cancer. There is considerable difficulty in finding accurate signals of early cancer (which usually exist in very small amounts) amid the noise of normal human physiology. Although progress has historically been slow, many promising early detection markers are emerging, including circulating tumor DNA, circulating tumor cells, proteins, exosomes, and cancer metabolites. Advances in data analysis methodologies (such as machine learning) and integration across marker types in multimodal tests are also accelerating progress.