With the development and improvement of new sequencing technology, next-generation sequencing (NGS) has been applied increasingly in cancer genomics research over the past decade. More recently, NGS has been adopted in clinical oncology to advance personalized treatment of cancer. NGS is used to identify novel and rare cancer mutations, detect familial cancer mutation carriers, and provide molecular rationale for appropriate targeted therapy. Compared to traditional sequencing, NGS holds many advantages, such as the ability to fully sequence all types of mutations for a large number of genes (hundreds to thousands) in a single test at a relatively low cost. However, significant challenges, particularly with respect to the requirement for simpler assays, more flexible throughput, shorter turnaround time, and most importantly, easier data analysis and interpretation, will have to be overcome to translate NGS to the bedside of cancer patients. Overall, continuous dedication to apply NGS in clinical oncology practice will enable us to be one step closer to personalized medicine.

Background Colorectal cancer (CRC) is the leading cause of cancer death worldwide. Screening is a confirmed way to reduce the incidence and mortality rates of CRC. This study aimed to identify a fecal-based, noninvasive, and accurate method for detection of colorectal cancer (CRC) and advanced adenoma (AA). Methods Through detection in tissue (n = 96) and fecal samples (n = 88) and tested in an independent group of fecal samples (n = 294), the methylated DNA marker ITGA4 and bacterial markers Fusobacterium nucleatum (Fn) and Pepetostreptococcusanaerobius (Pa) were identified from the candidate biomarkers for CRC and AA detection. A prediction score (pd-score) was constructed using the selected markers and fecal immunochemical test (FIT) for distinguishing AA and CRC from healthy subjects by logistic regression method. The diagnostic performance of the pd-score was compared with FIT and validated in the external validation cohort (n = 117) and in a large CRC screening cohort. Results The pd-score accurately identified AA and CRC from healthy subjects with an area under the curve (AUC) of 0.958, at a specificity of 91.37%; the pd-score showed sensitivities of 95.38% for CRC and 70.83% for AA, respectively. In the external validation cohort, the sensitivities of the pd-score for CRC and AA detection were 94.03% and 80.00%, respectively. When applied in screening, the pd-score identified 100% (11/11) of CRC and 70.83% (17/24) of AA in participants with both colonoscopy results and qualified fecal samples, showing an improvement by 41.19% compared to FIT. Conclusions The current study developed a noninvasive and well-validated approach for AA and CRC detection, which could be applied widely as a diagnostic and screening test.