Guidance for securing approvals for new biomarkers: from discovery to clinical implementation.

The journey of translating a molecular discovery into the clinic involves multiple steps and requires planning, time, effort, and money. In this review, we provide a quick guide on the technical and clinical validation parameters that are necessary for successful commercialization of molecular and other markers. We also briefly address the different options for regulatory approvals. Successful clinical implantation depends on rigorous technical and clinical validation, and the ability to develop clear guidelines for the indications for testing (i.e. which patients are eligible to have this test), the frequency of testing, and also a clear interpretation of test results. Successful implementation requires providing evidence that the results of this test can be used to improve patient care. There are currently multiple routes for implementation of clinical molecular tests, which include regulatory agency- approved companion diagnostics, laboratory developed tests, or direct-to-consumer testing. Regulatory approval is considered the gold-standard, but it requires time and resources. There is an ongoing debate about the need for regulatory approval of laboratory developed testing. Ongoing oversight is maintained through lab accreditation and proficiency testing programs, which provide a common approach to ensuring high standards and consistent performance in clinical molecular labs. Before moving into the clinic, confirmation of both the clinical and analytic validity of a new molecular test is essential.

Implementing Next-Generation Sequencing Process Changes to Increase Capacity and Improve Timeliness of Molecular Biomarker Profiling for Lung Cancer Patients.

BACKGROUND: Faced with expansion of molecular tumor biomarker profiling, the molecular genetics laboratory at Kingston Health Science Centre experienced significant pressures to maintain the provincially mandated 2-week turnaround time (TAT) for lung cancer (LC) patients. We used quality improvement methodology to identify opportunities for improved efficiencies and report the impact of the initiative. METHODS: We set a target of reducing average TAT from accessioning to clinical molecular lab report for LC patients. Process measures included percentage of cases reaching TAT within target and number of cases. We developed a value stream map and used lean methodology to identify baseline inefficiencies. Plan-Do-Study-Act cycles were implemented to streamline, standardize, and automate laboratory workflows. Statistical process control (SPC) charts assessed for significance by special cause variation. RESULTS: A total of 257 LC cases were included (39 baseline January-May 2021; 218 post-expansion of testing June 2021). The average time for baseline TAT was 12.8 days, peaking at 23.4 days after expansion of testing, and improved to 13.9 days following improvement interventions, demonstrating statistical significance by special cause variation (nonrandom variation) on SPC charts. CONCLUSIONS: The implementation of standardized manual and automated laboratory processes improved timeliness of biomarker reporting despite the increasing volume of testing at our center.

Plasma versus Tissue Tumor Mutational Burden as Biomarkers of Durvalumab plus Tremelimumab Response in Patients with Metastatic Colorectal Cancer in the CO.26 Trial.

PURPOSE: Tissue-derived tumor mutation burden (TMB) of ≥10 mutations/Mb is a histology-agnostic biomarker for the immune checkpoint inhibitor (ICI) pembrolizumab. However, the dataset in which this was validated lacked colorectal cancers (CRC), and there is limited evidence for immunotherapy benefits in CRC using this threshold. PATIENTS AND METHODS: CO.26 was a randomized phase II study of 180 patients, comparing durvalumab and tremelimumab (D + T, n = 119 patients) versus best supportive care (BSC; n = 61 patients). ctDNA sequencing was available for 168 patients (n = 118 D + T; n = 50), of whom 165 had evaluable plasma TMB (pTMB). Tissue sequencing was available for 108 patients. Optimal thresholds for stratifying patients based on OS were determined using a minimal P value approach. This report includes the final OS analysis. RESULTS: Tissue TMB ≥10 mutations/Mb was not predictive of benefit from D + T compared with BSC in microsatellite stable (MSS) metastatic CRC [HR, 0.71 (95% CI, 0.28-1.80); P = 0.47]. No tissue TMB threshold could identify a high TMB group that benefited from ICI. By contrast, plasma TMB (pTMB) ≥28 mutations/Mb was predictive of benefit from D + T [HR, 0.34 (95% CI, 0.13-0.85); P = 0.022], as was clonal pTMB ≥10.6 mutations/Mb [HR, 0.10 (95% CI, 0.014-0.79); P = 0.029] and subclonal pTMB ≥25.9/Mb [HR, 0.20 (95% CI, 0.061-0.69); P = 0.010]. Higher pTMB was associated with length of time on cytotoxic agents (P = 0.021) and prior anti-EGFR exposure (P = 2.44 × 10-06). CONCLUSIONS: pTMB derived from either clonal or subclonal mutations may identify a group likely to benefit from immunotherapy, although validation is required. Tissue TMB provided no predictive utility for immunotherapy in this trial.