Purpose: Despite generally favorable outcomes, 15-25% of patients with HPV-driven oropharyngeal squamous cell carcinoma (OPSCC) will recur. Current post-treatment surveillance practices rely on physical exams and imaging and are inconsistently applied. We assessed circulating tumor tissue modified viral (TTMV)-HPV DNA obtained during routine post-treatment surveillance among a large population of real-world patients. Experimental Design: This retrospective clinical case series included 1076 consecutive patients across 108 U.S. sites who were >=3 months post-treatment for HPV-driven OPSCC and who had 1 or more TTMV-HPV DNA tests (NavDx®, Naveris Laboratories, Natick, MA) obtained during surveillance. between 2/6/2020 and 6/29/2021. Test results were compared to subsequent clinical evaluations. Results: Circulating TTMV-HPV DNA was positive in 80/1076 (7.4%) patients, with follow-up available on all. At first positive surveillance testing, 21/80 (26%) patients had known recurrence while 59/80 (74%) patients were not known to have recurrent disease. Among these 59 patients, 55 (93%) subsequently had a confirmed recurrence, two patients have clinically suspicious lesions and two are clinically NED at last follow-up. To date, the overall positive predictive value of TTMV-HPV DNA testing for recurrent disease is 95% (N=76/80). Additionally, the point-in-time negative predictive value is 95% (N=1198/1256). Conclusions: These findings highlight the clinical potential for circulating TTMV-HPV DNA testing in routine practice. As a surveillance tool, TTMV-HPV DNA positivity was the first indication of recurrence in the majority of cases, pre-dating identification by routine clinical and imaging exams. These data may inform future clinical and guideline-endorsed strategies for HPV-driven malignancy surveillance.
Background: Human papillomavirus (HPV) is causally linked to oropharyngeal squamous cell carcinoma (OPSCC). Consensus guidelines recommend clinical exams and imaging in decreasing frequency as part of post-treatment surveillance for recurrence. Plasma tumor tissue modified viral (TTMV)-HPV DNA testing has emerged as a biomarker which can inform disease status during surveillance. Methods: This retrospective observational cohort study involved 543 patients who completed curative-intent therapy for HPV-associated OPSCC between February 2020 and January 2022 at 8 U.S. cancer care institutions. We determined the negative predictive value (NPV) of TTMV-HPV DNA for recurrence when matched to physician-reported clinical outcome data (median follow-up time: 27.9 months; range: 4.5-154). Results: The cohort included mostly men with a median age of 61 who had locoregionally advanced disease. HPV status was determined by p16 positivity in 87% of patients, with a positive HPV PCR/ISH among 55%; while pre-treatment TTMV-HPV DNA status was unknown for most (79%) patients. Patients had a mean of 2.6 tests and almost half had 3 or more TTMV-HPV DNA results during surveillance. The per-test and per-patient sensitivity of the assay was 92.5% (95%CI: 87.5-97.5) and 87.3% (95%CI: 79.1-95.5), respectively. The NPV for the assay was 99.4% (95%CI: 98.9-99.8) and 98.4% (95%CI: 97.3-99.5), respectively. Conclusions: TTMV-HPV DNA surveillance testing yields few false negative results and few missed recurrences. These data could inform decisions on when to pursue re-imaging following first disease restaging and could inform future surveillance practice. Additional study of how pre-treatment TTMV-HPV DNA status impacts sensitivity for recurrence is needed.
Background: Molecular profiling of cancers is now routine at many cancer centers, and the number of precision cancer medicine clinical trials, which are informed by profiling, is steadily rising. Additionally, these trials are becoming increasingly complex, often having multiple arms and many genomic eligibility criteria. Currently, it is a challenging for physicians to match patients to relevant clinical trials using the patient's genomic profile, which can lead to missed opportunities. Automated matching against uniformly structured and encoded genomic eligibility criteria is essential to keep pace with the complex landscape of precision medicine clinical trials.Results: To meet these needs, we built and deployed an automated clinical trial matching platform called MatchMiner at the Dana-Farber Cancer Institute (DFCI). The platform has been integrated with Profile, DFCI's enterprise genomic profiling project, which contains tumor profile data for >20,000 patients, and has been made available to physicians across the Institute. As no current standard exists for encoding clinical trial eligibility criteria, a new language called Clinical Trial Markup Language (CTML) was developed, and over 158 genomically-driven clinical trials were encoded using this language. The platform is open source and freely available for adoption by other institutions. Conclusion:MatchMiner is the first open platform developed to enable computational matching of patient-specific genomic profiles to precision cancer medicine clinical trials. Creating MatchMiner required developing clinical trial eligibility standards to support genome-driven matching and developing intuitive interfaces to support practical use-cases. Given the complexity of tumor profiling and the rapidly changing multi-site nature of genome-driven clinical trials, open source software is the most efficient, scalable, and economical option for matching cancer patients to clinical trials.
PURPOSE Evidence-based somatic and germline sequencing has transformed cancer care and improves patient outcomes. However, patients’ low genetic literacy and misunderstanding of their own genomic results poses a threat to the realization of precision oncology. To optimize patient genomic comprehension, we developed a Web-based, patient-directed, genomic sequencing education and return-of-results tool, HOPE-Genomics. METHODS The HOPE-Genomics prototype included somatic and germline sequencing results, embedded multimedia genomic education, and interactive features (eg, request for genetic counseling). Between January and April 2018, we elicited feedback on tool usability and comprehensiveness through participant surveys, 4 focus groups of patients with cancer and their family members, and 3 provider focus groups (comprising 8 patients, 5 family members, and 19 providers). RESULTS We identified themes in patient/family tool-related responses, including the desire to view a patient-friendly report, a desire to receive multiple types of genomic information (eg, prognostic and uncertain), high acceptability of report content, and interest in tool-enabled access to genetic counseling. Major themes from the clinician focus groups included believing the tool could help patients formulate questions and facilitate patients’ communication of results to family members. However, there were diverse responses from all participants in terms of tool implementation (ie, timing and nature of report release). Some participants preferred report release before meeting with the provider, and others preferred it during the appointment. Additionally, some clinicians were concerned about providing prognostic and treatment information through the tool. CONCLUSION There was high acceptability and interest from patients, family members, and providers in a patient-directed genomics report. Future work will determine whether direct-to-patient reporting of genomic results improves patient knowledge, care engagement, and compliance with genomically guided interventions.
Widespread, comprehensive sequencing of patient tumors has facilitated the usage of precision medicine (PM) drugs to target specific genomic alterations. Therapeutic clinical trials are necessary to test new PM drugs to advance precision medicine, however, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner, an open-source platform to computationally match genomically profiled cancer patients to PM trials. Here, we describe MatchMiner’s capabilities, outline its deployment at Dana-Farber Cancer Institute (DFCI), and characterize its impact on PM trial enrollment. MatchMiner’s primary goals are to facilitate PM trial options for all patients and accelerate trial enrollment onto PM trials. MatchMiner can help clinicians find trial options for an individual patient or provide trial teams with candidate patients matching their trial’s eligibility criteria. From March 2016 through March 2021, we curated 354 PM trials containing a broad range of genomic and clinical eligibility criteria and MatchMiner facilitated 166 trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiner’s impact on trial consent, we measured time from genomic sequencing report date to trial consent date for the 166 MMC compared to trial consents not facilitated by MatchMiner (non-MMC). We found MMC consented to trials 55 days (22%) earlier than non-MMC. MatchMiner has enabled our clinicians to match patients to PM trials and accelerated the trial enrollment process.
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