Unraveling the potential clinical utility of circulating tumor DNA detection in colorectal cancer-evaluation in a nationwide Danish cohort.

BACKGROUND: Increasingly, circulating tumor DNA (ctDNA) is proposed as a tool for minimal residual disease (MRD) assessment. Digital PCR (dPCR) offers low analysis costs and turnaround times of less than a day, making it ripe for clinical implementation. Here, we used tumor-informed dPCR for ctDNA detection in a large colorectal cancer (CRC) cohort to evaluate the potential for post-operative risk assessment and serial monitoring, and how the metastatic site may impact ctDNA detection. Additionally, we assessed how altering the ctDNA-calling algorithm could customize performance for different clinical settings. PATIENTS AND METHODS: Stage II-III CRC patients (N = 851) treated with a curative intent were recruited. Based on whole-exome sequencing on matched tumor and germline DNA, a mutational target was selected for dPCR analysis. Plasma samples (8 ml) were collected within 60 days after operation and-for a patient subset (n = 246)-every 3-4 months for up to 36 months. Single-target dPCR was used for ctDNA detection. RESULTS: Both post-operative and serial ctDNA detection were prognostic of recurrence [hazard ratio (HR) = 11.3, 95% confidence interval (CI) 7.8-16.4, P < 0.001; HR = 30.7, 95% CI 20.2-46.7, P < 0.001], with a cumulative ctDNA detection rate of 87% at the end of sample collection in recurrence patients. The ctDNA growth rate was prognostic of survival (HR = 2.6, 95% CI 1.5-4.4, P = 0.001). In recurrence patients, post-operative ctDNA detection was challenging for lung metastases (4/21 detected) and peritoneal metastases (2/10 detected). By modifying the cut-off for calling a sample ctDNA positive, we were able to adjust the sensitivity and specificity of our test for different clinical contexts. CONCLUSIONS: The presented results from 851 stage II-III CRC patients demonstrate that our personalized dPCR approach effectively detects MRD after operation and shows promise for serial ctDNA detection for recurrence surveillance. The ability to adjust sensitivity and specificity shows exciting potential to customize the ctDNA caller for specific clinical settings.

Neoadjuvant calcium electroporation for potentially curable colorectal cancer.

BACKGROUND: The development of new perioperative treatment modalities to activate the immune system in colorectal cancer might have a beneficial effect on reducing the risk of recurrence after surgery. Calcium electroporation is a promising treatment modality that potentially modulates the tumor microenvironment. The aim of this study was to evaluate the safety of the procedure in the neoadjuvant setting in localized left-sided colorectal cancer (CRC). METHODS: The study included patients with potentially curable sigmoid or rectal cancer with no indication for other neoadjuvant treatment. Patients were offered calcium electroporation as a neoadjuvant treatment before elective surgery. Follow-up visits were conducted on the preoperative day before elective surgery, POD2, POD14, and POD30, with an evaluation of adverse events, impact on elective surgery, clinical examination, and quality of recovery. RESULTS: Endoscopic calcium electroporation was performed as an outpatient procedure in all 21 cases, with no procedure-related complications reported. At follow-up, five adverse events were registered, two of which were classified as serious adverse events. Surgery was performed as planned in 19 patients (median time to surgery, 8 days), and the final two patients underwent surgery with a delay due to adverse events (14 and 33 days). No significant impact on the quality of recovery scores nor inflammatory markers were seen before and after calcium electroporation, nor baseline and POD30. CONCLUSIONS: Endoscopic calcium electroporation is a safe and feasible procedure in patients with potentially curable CRC. The study showed limited side effects and limited impact on the following elective surgical resection.

Training prediction models for individual risk assessment of postoperative complications after surgery for colorectal cancer.

BACKGROUND: The occurrence of postoperative complications and anastomotic leakage are major drivers of mortality in the immediate phase after colorectal cancer surgery. We trained prediction models for calculating patients' individual risk of complications based only on preoperatively available data in a multidisciplinary team setting. Knowing prior to surgery the probability of developing a complication could aid in improving informed decision-making by surgeon and patient and individualize surgical treatment trajectories. METHODS: All patients over 18 years of age undergoing any resection for colorectal cancer between January 1, 2014 and December 31, 2019 from the nationwide Danish Colorectal Cancer Group database were included. Data from the database were converted into Observational Medical Outcomes Partnership Common Data Model maintained by the Observation Health Data Science and Informatics initiative. Multiple machine learning models were trained to predict postoperative complications of Clavien-Dindo grade ≥ 3B and anastomotic leakage within 30 days after surgery. RESULTS: Between 2014 and 2019, 23,907 patients underwent resection for colorectal cancer in Denmark. A Clavien-Dindo complication grade ≥ 3B occurred in 2,958 patients (12.4%). Of 17,190 patients that received an anastomosis, 929 experienced anastomotic leakage (5.4%). Among the compared machine learning models, Lasso Logistic Regression performed best. The predictive model for complications had an area under the receiver operating characteristic curve (AUROC) of 0.704 (95%CI 0.683-0.724) and an AUROC of 0.690 (95%CI 0.655-0.724) for anastomotic leakage. CONCLUSIONS: The prediction of postoperative complications based only on preoperative variables using a national quality assurance colorectal cancer database shows promise for calculating patient's individual risk. Future work will focus on assessing the value of adding laboratory parameters and drug exposure as candidate predictors. Furthermore, we plan to assess the external validity of our proposed model.

The effect of time from diagnosis to surgery on oncological outcomes in patients undergoing surgery for colon cancer: A systematic review.

Many countries have implemented cancer pathways with strict time limits dictating the pace of diagnostic testing and treatment. There are concerns that prehabilitation may worsen long-term oncological outcomes if surgery is delayed. We aimed to systematically review the literature investigating the association between increased time between diagnosis of colon cancer and surgical treatment, with special focus on survival outcomes. METHODS: Through a systematic search and analysis of the databases PubMed (1966-2017), EMBASE (1974-2017), CINHAL (1981-2017), and The Cochrane Library performed on June 7th, 2017, the effect of treatment delays on overall survival in colon cancer patients was reviewed. Treatment delay was defined as time from diagnosis to initiation of surgical treatment. All patients included were diagnosed with colon cancer and treated with elective curative surgery without neoadjuvant chemotherapy. This review was prospectively registered on the PROSPERO database of systematic review protocols with registration number CRD42017059774. RESULTS: Five observational studies including 13,514 patients were included. The treatment delay intervals ranged from 1 to ≥56 days. Four of the five studies found no association between time elapsed from diagnosis to surgery and reduced overall survival. One study found a clinically insignificant association between longer treatment delays and overall survival. Three studies investigated the effect on disease specific survival and found no negative associations. CONCLUSION: The available data showed no association between treatment delay and reduced overall survival in colon cancer patients.