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HPV circulating tumor DNA (ctDNA) is a liquid biopsy biomarker that could evaluate treatment response and risk stratify patients after (chemo)radiotherapy ([C]RT). However, HPV ctDNA is undetectable at baseline in up to 15% of pts and needs prospective validation. HPV next-generation sequencing (HPV-seq) offers both genotyping and ultrasensitive quantification of HPV ctDNA. We validated HPV-seq, testing pre-specified hypotheses: (1) pre-RT HPV ctDNA correlates with gross tumor volume (GTV); (2) undetectable post-RT HPV ctDNA predicts favorable 2-year locoregional control (LRC) and progression-free survival (PFS). We analyzed pre- and post-RT HPV ctDNA in 2 cohorts of non-metastatic p16+ OPC. Cohort 1 (n = 237): single-institution prospective study, standard RT/CRT; HPV ctDNA at pre-RT and ~3 mo post-RT. Cohort 2 (n = 126): secondary endpoint of NRG-HN002, a phase II trial of low-risk p16+ OPC (AJCC 7e T1-T2 N1-N2b or T3 N0-N2b, ≤10 pack-year) randomized to de-escalated RT vs. CRT to 60 Gy; HPV ctDNA at pre-RT and ~4 wk post-RT. HPV ctDNA was measured by HPV-seq, targeting 38 HPV types. Correlations were assessed by Spearman coefficient (r). Associations with LRC/PFS were assessed by Fisher exact test (2-sided α = 0.05). Pre-RT HPV ctDNA was detected in 228/237 (96.2%) of Cohort 1 and 126/126 (100%) of Cohort 2 (range = 0.2 to 408147 copies/mL). Across both cohorts, dominant HPV types were HPV-16 (87.1%), 33 (5.0%), 35 (4.8%), 18 (2.0%), 26 (0.6%), 38 (0.3%), and 59 (0.3%). Pre-RT HPV ctDNA was correlated with GTV in both Cohort 1 (r = 0.46 [0.34, 0.56]) and Cohort 2 (r = 0.25 [0.08, 0.41]). In a multivariable model, baseline HPV ctDNA was associated with N category in both Cohort 1 (p<0.001) and Cohort 2 (P = 0.0125) and not with T category or site (tonsil vs. other). At post-RT, HPV ctDNA clearance occurred in 189/237 (79.7% [74.2-84.4]) in Cohort 1 and 88/126 (69.8% [61.3, 77.2]) in Cohort 2. Pts who demonstrated post-RT HPV ctDNA clearance had better 2-yr LRC and PFS (Table) with negative predictive value (NPV) > 96% for LRC and > 94% for PFS. This study provides prospective clinical validation of the prognostic value of HPV-seq in two high quality independent cohorts. Pre-RT HPV ctDNA was detected in >96% of pts with p16+ OPC and correlated with GTV and N-category. Post-RT HPV ctDNA clearance was associated with favorable outcomes. Cohort 1 showed more clearance and stronger association with LRC and PFS, possibly due to test timing (3 vs. 1 month post-RT) and sample size. [ABSTRACT FROM AUTHOR]

Circulating tumor DNA (ctDNA) can be utilized to identify the presence of cancer as well as minimal residual disease (MRD). Quantification of ctDNA can be a useful cancer management tool to assess prognosis. Here we evaluate the feasibility of using a tumor-naïve genome-wide methylome enrichment platform to quantify ctDNA in plasma and predict recurrence in early-stage non-small cell lung cancer (NSCLC). In a retrospective evaluation of banked, pre-treatment samples from newly diagnosed Stage I and II NSCLC patients (collected from 2009 to 2013, Princess Margaret Cancer Centre), samples were analyzed with a bisulfite-free, non-degradative genome-wide DNA methylation enrichment platform using 5-10 ng of cell-free DNA isolated from plasma. ctDNA was quantified from average normalized counts across informative regions. Events were defined as cancer recurrence or death due to any cause, whichever occurred earlier. A ctDNA quantity threshold was set where all samples from patients without an event fell below the threshold (i.e., 100% specificity). Time to recurrence or death was compared for samples with ctDNA quantities above the threshold to those below the threshold. Recurrence-free survival was estimated using Kaplan-Meier method, and the difference was assessed by the log-rank test. Multivariable Cox regression analysis was used to adjust for known prognostic covariates. Samples from 41 patients were included. The table describes clinico-demographic information. With a median follow-up time of 56.4 months, there were 27 events. Samples with ctDNA above the threshold showed significantly worse recurrence-free survival [hazard ratio (HR) 2.70 (95% CI 1.26, 5.78), log-rank P=0.008], even after accounting for histology (selected using univariate analysis) [HR 2.79 (95% CI 1.30, 6.02), P=0.009]. Our data shows that this blood-based genome-wide methylome enrichment platform can be used for ctDNA quantification and prognostication in early-stage NSCLC. Initial feasibility was evaluated here using treatment-naïve plasma samples. Applications for cancer management will be further evaluated in future studies utilizing post-treatment and longitudinal samples. [ABSTRACT FROM AUTHOR]

Evidence of prognostic importance of pre-radiotherapy (RT) total lymphocyte counts (TLC) and interaction with addition of cisplatin (CRT) in HPV-positive oropharyngeal carcinoma (HPV+OPC) is conflicting. Recent data suggest patients with high TLC may not benefit from the addition of chemotherapy (Price et al, JCO 2022). We assess the prognostic and predictive value of TLC in a large single center HPV+OCP cohort. All HPV+OPC patients treated at a single academic center with definitive RT/CRT between 2005-2018 were included. Pre-treatment TLC up to 6 weeks prior to RT start were considered. Multivariable analysis (MVA) was applied to assess the prognostic importance of TLC (continuous variable), adjusted for age, gender, performance status, TNM-8 stage, and smoking status in the CRT and RT subgroups. The actuarial rates of locoregional control (LRC), distant control (DC), and overall survival (OS) were calculated using Kaplan-Meier and competing risk methods, stratified by low vs high TLC (determined using Contal and O'Quigley method for optimal cutoff). Among 1153 eligible patients, 707 (61%) were treated with CRT. Median age was 59.7 (range 22.7-92.2) years. 526 patients were (46%) TNM-8 stage I, 366 (32%) stage II and 261 (23%) stage III. Median TLC was 1.6 x 109/L (range 0.1-8.5). Median follow-up was 5.5 years. On MVA, TLC was prognostic for patients receiving CRT (OS [adjusted hazard ration (aHR) 0.55 (0.38-0.79), p = 0.002], DC [aHR 0.57 (0.37-0.88), p = 0.011], LRC [aHR 0.57 (0.36-0.89), p = 0.014]) but not RT (OS [aHR 1.04 (0.82-1.31), p = 0.74], LRC [aHR 1.26 (0.86-1.85), p = 0.23], DC [aHR 0.87 (0.64-1.19), p = 0.4)]. The optimal TLC cut-off for OS with CRT was 1.9 x 109/L. Low vs high TLC patients receiving CRT had significantly inferior 5-year DC (87% vs 93%, p = 0.017) and OS (84% vs 90%, p = 0.026). The benefit of higher TLC was most evident in stage II disease (table 1). CRT vs RT improved OS for stage II/III disease at high and low TLC. Pre-treatment TLC is prognostic in a large cohort of HPV+OPC patients receiving CRT but not RT alone. Further investigation of the interaction of cisplatin and immune response during RT is warranted. The omission of chemotherapy based on TLC is not supported. [ABSTRACT FROM AUTHOR]

The use of stereotactic body radiation (SBRT) for tumors in close proximity to the central mediastinal structures has been associated with a high risk of toxicity. This prospective study (NCT03306680) aimed to determine the maximally tolerated dose (MTD) of SBRT for ultra-central (UC) non-small cell lung carcinoma (NSCLC), using a time-to-event continual reassessment methodology (TITE-CRM). Eligibility criteria included age ≥ 18 years, ECOG performance status 0-2, with stage T1-3N0M0(≤ 6 cm), NSCLC, and UC tumor location, defined as planning target volume (PTV) touching or overlapping the proximal bronchial tree (PBT), esophagus, pulmonary vein (PV), or pulmonary artery (PA). The MTD was defined as the dose of radiotherapy associated with a ≤ 30% rate of grade (G) 3-5 pre-specified treatment-related toxicity occurring within 2 years of treatment. The starting dose level was 60 Gy in 8 fractions (7.5 Gy/fraction) delivered daily, with de-escalation to 60 Gy in 10 or 15 fractions if toxicity rates exceeded 30% using TITE-CRM. Estimated sample size was 30 patients. The hotspot was limited to 120% within the PTV; tumors with endobronchial invasion were excluded. Adverse event rates were assessed using CTCAE version 4.0. Secondary endpoints included overall survival (OS), progression-free survival (PFS), local control (LC), regional control (RC), and distant control (DC), calculated using Kaplan-Meier estimates, and quality of life (QOL), assessed using the Functional Assessment of Cancer Therapy (FACT) Lung questionnaire. This primary analysis occurred two years after completion of accrual. Between March 2018 and April 2021, enrollment completed with 30 patients at five Canadian academic institutions. The median follow-up was 36.5 months (range: 8.9-50.8). The median age was 73 years (interquartile range [IQR]: 69-78), 17 (56.7%) were female, 23 (76.7%) were T1, 6 (20.0%) T2 and 1 (3.3%) T3. Tumor was located near PBT in 18 (60.0%), esophagus 5 (16.7%), PV 1 (3.3%) and PA 14 (46.7%). All patients were assigned a dose of 60 Gy in 8 fractions. Two patients (6.7%) experienced G3-5 adverse events related to treatment: one patient with G3 dyspnea and 1 G5 pneumonia (related to interstitial lung disease [ILD]); the latter had CT findings consistent with a background of ILD identified after SBRT. Three-year actuarial outcomes were as follows: OS was 72.5% (95% confidence interval [CI]: 52.3-85.3%), PFS 66.1% (95% CI: 46.1-80.2%), LC 89.6% (95% CI: 71.2-96.5%), RC 96.4% (95% CI: 77.2-99.5%) and DC 85.9% (95% CI: 66.7-94.5%). QOL scores declined numerically over time, but the decrease were not clinically or statistically significant. 60 Gy in 8 fractions, planned and delivered with only a moderate hotspot, has a favorable adverse event rate, within the pre-specified acceptability criteria, and results in excellent tumor control. [ABSTRACT FROM AUTHOR]

Poster: Physics track: Radiobiological and predictive modelling, and radiomics PO-1583: Non-invasive radiomic imaging prediction of tumour hypoxia: biomarker for FLASH irradiation? S. Sanduleanu, T. Tamanupadhaya@gmail.com, R. Klaassen, H. Woodruff, M. Hatt, J. Kaanders, O. Vrieze, H. Laarhoven, R. Subramiam, S.H. Huang, S. Bratman, L. Dubois, R. Miclea, D. Di Perri, X. Geets, M. Crispin-Ortuzar, A. Aptea, J. Hun Oh, N. Lee, J. Humm, H. Schoder, D. Ruysscher, F. Hoebers, P. Lambin. [Extracted from the article]

Poster: Physics track: Radiobiological and predictive modelling, and radiomics PO-1549: Non-invasive prediction of lymph node risk in oral cavity cancer patients A. Traverso, A. Hosni Abdalaty, M. Hasan, T. Tadic, T. Patel, M. Giuliani, J. Kim, J. Ringash, J. Cho, S. Bratman, A. Bayley, J. Waldron, B. O'Sullivan, J. Irish, D. Chepeha, J. De Almeida, D. Goldstein, D. Jaffray, L. Wee, A. Dekker, A. Hope. [Extracted from the article]

Poster: Clinical track: Head and Neck PO-0805: Dental insurance status influences prophylactic dental care prior to head and neck radiation E. Watson, W. Xu, M. Giuliani, J. Huang, S. Huang, B. O'Sullivan, J. Ringash, A. Hosni, J. Kim, J. Waldron, A. Bayley, J. Cho, S. Bratman, D. Goldstein, W. Maxymiw, M. Glogauer, A. Hope. [Extracted from the article]

Limited data exist in the clonal dynamics of serial ctDNA as a predictive biomarker in advanced solid tumor pts receiving immune checkpoint blockade. Pts with mixed solid tumors received single agent P (anti-PD-1) 200 mg IV Q3wks in the investigator-initiated phase II INSPIRE trial (NCT02644369). ctDNA was assayed at baseline (B) and start of cycle 3 (C3) using a pt-specific amplicon-based NGS assay (Signatera™). Samples were considered ctDNA positive if ≥ 2 of 16 pt-specific targets met the qualifying confidence score threshold. Table: 113P Table: 113P Endpoint ORR N = 72 * CBR N = 72 * Endpoint PFS N = 73 * OS N = 73 * Subgroup CR/PR N = 15 SD/PD N = 57 CR/PR/SD≥6 cycles N = 22 CR/PR/SD<6 cycles N = 50 Subgroup ↑ from baseline N = 33 ↓ from baseline N = 40 ↑ from baseline N = 33 ↓ from baseline N = 40 ΔctDNA (% change) Median = -91.5% Range = -100% to 60% Median = 40% Range = -98.4% to 2458% Median = -75% Range = -100% to 96% Median = 52% Range = -94.6% to 2458% Results based on ΔctDNA Median = 7.9m6m = 51.5% Median = 2.8m6m = 10.0% Median = not reached 6m = 91% 12m = 82% Median = 9.1m6m = 73% 12m = 45% P-value P < 0.001 P < 0.001 Adjusted HR (95% CI)^ 0.43 (0.25-0.75) P = 0.003 0.35 (0.18–0.67) P = 0.002 ^Adjustment on cohorts; * 2 pts were excluded from ORR/CBR analyses as baseline ctDNA = 0; 1 of these 2 pts (with PR) excluded from PFS/OS analyses as C3 ctDNA = 0 Of 94 pts are presented. Demographics: male 38%; median age=55 yrs (range 21–81); triple negative breast (19%), ovarian (19%) and head and neck (17%) cancers comprised the major malignancies. Median no. of P cycles=3 (range 1–35); follow up was 14m (range 0.6-35.4); RECIST responses: CR 3.2% (n = 3), PR 14% (n = 13), CBR (CR+PR+SD>6 cycles) 28% (n = 26), RECIST/clinical PD (n = 61/18; 65%/19%). Median PFS=2.5m and median OS = 14m. In all 94 pts, ctDNA B correlated with PFS (adjusted HR 0.53, 95% CI 0.34-0.84, p = 0.01) and OS (adjusted HR 0.47, 95% CI 0.28-0.8, p = 0.01). Among 74 pts with both ctDNA B and ctDNA C3 , the change (ΔctDNA) correlated with clinical efficacy parameters (Table). Strong correlations exist between both ctDNA B and ΔctDNA with clinical outcome, suggesting both prognostic and predictive values in pts with mixed solid tumors. NCT02644369, December 31, 2015. University Health Network, Toronto. Merck, Netera, Terry Fox Research Institute, Princess Margaret Cancer Foundation. S. Dashner: Shareholder / Stockholder / Stock options, Full / Part-time employment: Netera. A.R. Hansen: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Merck; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): GlaxoSmithKline; Research grant / Funding (institution): Genentech/Roche; Research grant / Funding (institution): Bristol-Myers Squibb; Research grant / Funding (institution): Novartis; Research grant / Funding (institution): Boston Biomedical; Research grant / Funding (institution): Boehringer-Ingelheim; Research grant / Funding (institution): AstraZeneca/Medimmune; Research grant / Funding (institution): Janssen; Research grant / Funding (institution): Karyopharm. P. Bedard: Honoraria (institution), Advisory / Consultancy: Sanofi; Advisory / Consultancy, Research grant / Funding (institution): Roche/Genentech; Advisory / Consultancy, Research grant / Funding (institution): Bristol-Myers Squibb; Advisory / Consultancy, Research grant / Funding (institution): Pfizer; Research grant / Funding (institution): Novartis; Research grant / Funding (institution): GlaxoSmithKline; Research grant / Funding (institution): AstraZeneca/Medimmune; Research grant / Funding (institution): Merck; Research grant / Funding (institution): Nektar Therapeutics; Research grant / Funding (institution): Servier; Research grant / Funding (institution): Seattle Genetics; Research grant / Funding (institution): PTC Therapeutics; Research grant / Funding (institution): Oncothyreon. S. Lheureux: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Merck; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): AstraZeneca/Medimmune; Research grant / Funding (institution): Roche/Genentech; Research grant / Funding (institution): Tesaro. A. Spreafico: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Merck; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Bristol-Myers Squibb; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Novartis; Honoraria (self), Advisory / Consultancy: Oncorus; Research grant / Funding (institution): Symphogen; Research grant / Funding (institution): AstraZeneca/Medimmune; Research grant / Funding (institution): Bayer; Research grant / Funding (institution): Surface Oncology; Research grant / Funding (institution): Northern Biologics; Research grant / Funding (institution): Janssen; Research grant / Funding (institution): Oncology/Johnson & Johnson; Research grant / Funding (institution): Array Biopharma. A.A. Razak: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Boehringer Ingelheim; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Eli Lilly; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Merck; Research grant / Funding (institution): CASI Pharmaceuticals; Research grant / Funding (institution): Novartis; Research grant / Funding (institution): Deciphera; Research grant / Funding (institution): Karyopharm Therapeutics; Research grant / Funding (institution): Pfizer; Research grant / Funding (institution): Roche/Genentech; Research grant / Funding (institution): Boston Biomedical; Research grant / Funding (institution): Bristol-Myers Squibb; Research grant / Funding (institution): AstraZeneca/Medimmune; Research grant / Funding (institution): Amgen; Research grant / Funding (institution): GlaxoSmithKline; Research grant / Funding (institution): Blueprint Medicines; Research grant / Funding (institution): Merck; Research grant / Funding (institution): Abbvie; Research grant / Funding (institution): Adaptimmune. H. Wu: Shareholder / Stockholder / Stock options, Full / Part-time employment: Netera. S. Shchegrova: Shareholder / Stockholder / Stock options, Full / Part-time employment: Netera. P.S. Ohashi: Honoraria (self), Advisory / Consultancy: Symphogen Inc; Honoraria (self), Advisory / Consultancy: Providence Therapeutics. M. Louie: Shareholder / Stockholder / Stock options, Full / Part-time employment: Netera. H. Sethi: Shareholder / Stockholder / Stock options, Full / Part-time employment: Netera. A. Aleshin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Netera. L.L. Siu: Honoraria (self), Advisory / Consultancy: Merck; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Pfiser; Honoraria (self), Advisory / Consultancy: Celgene; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): AstraZeneca/Medimmune; Honoraria (self), Advisory / Consultancy: Morphosys; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Roche/Genentech; Honoraria (self), Advisory / Consultancy: GeneSeeq; Honoraria (self), Advisory / Consultancy: Loxo; Honoraria (self), Advisory / Consultancy: Oncorus; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Symphogen; Honoraria (self), Advisory / Consultancy: Seattle Genetics; Research grant / Funding (institution): Novartis; Research grant / Funding (institution): Bristol-Myers Squibb; Research grant / Funding (institution): Boerhinger-Ingelheim; Research grant / Funding (institution): GlaxoSmithKline; Research grant / Funding (institution): Karyopharm; Research grant / Funding (institution): Astellas; Research grant / Funding (institution): Bayer; Research grant / Funding (institution): Abbvie; Research grant / Funding (institution): Amgen; Research grant / Funding (institution): Intensity Therapeutics; Research grant / Funding (institution): Mirati; Research grant / Funding (institution): Shattucks; Spouse / Financial dependant: Agios. S. Bratman: Research grant / Funding (self): Nektar Therapeutics; Licensing / Royalties, Co-inventor of a patent relating to circulating tumor DNA detection technology: Roche Molecular Diagnostics. T.J. Pugh: Honoraria (self): Merck; Honoraria (self): Prosigna; Honoraria (self): Chrysalis Medical Advisors; Advisory / Consultancy: DynaCare; Research grant / Funding (self): Boehringer Ingelheim. All other authors have declared no conflicts of interest. [ABSTRACT FROM AUTHOR]