CAPP-Seq Circulating Tumor DNA Analysis for Early Detection of Tumor Progression After Definitive Radiation Therapy for Lung Cancer

Volume 96  Number 2S  Supplement 2016 Purpose/Objective(s): Advances in imaging may improve disease characterization and outcomes in early stage classical Hodgkin lymphoma (HL). PET-CT scans are performed routinely after chemotherapy, and the Deauville scale is used to assess disease response. We hypothesized that novel post-chemotherapy PET-CT parameters, considered in combination with Deauville score, would improve risk stratification. Materials/Methods: All patients treated for stage I-II HL between 2002 and 2014, 18 years of age, with analyzable pre- and post-chemotherapy PET-CT scans were eligible. Soft tissue volume (STV, abnormality on CT), metabolic tumor volume (MTV, STV with SUV 2.5), and total lesion glycolysis (TLG, MTV x mean SUV) were recorded from pre- and postchemotherapy PET-CT scans. Ratios were defined as (final PET-CT value) / (corresponding initial PET-CT value). The primary endpoint was eventfree survival (EFS), with events defined as disease progression or death from HL. Results: The cohort consisted of 202 patients. Median age at diagnosis was 32 years (range 18-89), and 57% of patients were female. Disease was stage I in 14% and stage II in 86%. B symptoms were present in 27%, extranodal disease in 5%, and bulk (>10 cm in any dimension) in 30%. Treatment consisted of chemotherapy alone in 29% (n Z 59) and chemotherapy with consolidative radiation therapy (RT) in 71% (n Z 143). Median follow-up was 4.4 years from diagnosis (range 1 e 12). The 5-year EFS was 89% (95% CI Z 85-93%). All PET-CT parameters and corresponding ratios were strongly correlated with Deauville score (all P < 0.001). All parameters and ratios were significantly associated with EFS on univariate analysis (all P < 0.001). We aimed to identify PET-CT parameters that would improve risk stratification in the Deauville 1-4 subset (n Z 187), for which predictors of outcome would be particularly valuable. Parameters with the highest C-indices included Deauville score of 13 vs. 4 (C-index 0.67) and STV ratio (C-index 0.71). Recursive partitioning and regression tree analyses were used to select the optimal cut-off for the STV ratio: 0.355, representing a 64.5% reduction in STV. The risk of disease progression or death from HL was higher in patients with an STV ratio  0.355 (HR Z 19, P < 0.0001). The 5-year EFS was 50% for patients with an STV ratio  0.355 vs. 97% for patients with an STV ratio < 0.355 (P < 0.0001). After adjusting for Deauville score, the STV ratio maintained its association with EFS (HR Z 18, P < 0.0001). The STV ratio was highly predictive of outcome in patients treated with or without RT (both P < 0.001). The C-index for Deauville score + STV ratio was 0.83, so the combination of factors was more predictive of EFS than either measurement alone. STV ratio was not a surrogate for bulk (P Z 0.77). Conclusion: Multiple post-chemotherapy PET-CT parameters are associated with EFS in early stage HL. In the setting of a Deauville score of 1-4, the STV ratio, an indicator of disease response, may improve risk stratification and contribute to individualization of therapy. Author Disclosure: S.A. Milgrom: None. W. Dong: None. M. Akhtari: None. G.L. Smith: None. C.C. Pinnix: None. O.R. Mawlawi: None. E.M. Rohren: None. N. Garg: None. H.H. Chuang: None. Z. Abou Yehia: None. J. Reddy: None. J.R. Gunther: None. E.M. Osborne: None. Y. Oki: None. M. Fanale: None. B. Dabaja: None.

91 Circulating Cell-Free Human Papillomavirus DNA as a Marker of Treatment Outcome in Patients With HPV-Positive Squamous Cell Head and Neck Cancer After Radio(chemo) Therapy T. Rutkowski,1 A. Mazurek,2 M. Snietura,3 A. Wygoda,1 U. Bojko,2 P. Widlak,4 and K.A. Skladowski4; 1I Radiation and Clinical Oncology Department, MSC Memorial Cancer Center and Institute of Oncology, Gliwice, Poland, 2Center for Translational Research and Molecular Biology of Cancer, MSC Memorial Cancer Center and Institute of Oncology, Gliwice, Poland, 3Cancer Pathology Department, MSC Memorial Cancer Center and Institute of Oncology, Gliwice, Poland, 4 Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology Gliwice Branch, Gliwice, Poland Purpose/Objective(s): Recent studies confirmed that circulating cell-free HPV DNA (cfHPV DNA) could be found in blood of most patients with

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HPV-related HNSCC that its level changes as the treatment progresses and may be related to the treatment outcome. As the response to treatment is reflected in cfHPV DNA detection, it may become feasible tool in monitoring of treatment results. The study presents original results on cfHPV DNA estimation before, during radiotherapy (RT) or chemoradiotherapy (CHRT), and after their completion in patients with HNSCC. Materials/Methods: Between February 2012 and December 2015 collection of blood samples from 477 consecutive patients with HNSCC before definitive RT or CHRT was performed. If HPV-positive sample was identified, serial blood collections were taken during treatment, after its completion and during follow-up. The cfHPV DNA status was assessed in plasma blood samples by TaqMan/PCR and confirmed in formalin-fixed paraffin-embedded tumor samples. The results of cfHPV DNA assessment were correlated with the treatment outcome. The cfHPV DNA complete remission (cfHPVrem) was defined as a not detectable level of cfHPV DNA in blood serum. The cfHPV DNA recurrence (cfHPVrec) was defined as a detection of cfHPV DNA in serum of previously cfHPVrem patients during follow-up. Results: In 67 patients (14%), cfHPV DNA was found. Two patients were excluded due to palliative approach (1) or loss in follow-up. Thus, the cfHPV DNA was subsequently assessed in 65 (13.5%) patients after treatment. Three patients (0.5%) presented uncured disease after the treatment and their cfHPV DNA remained detectable over the observations. The rest of 62 patients had cfHPVrem after treatment completion and all of them were followed with cfHPV DNA estimation during followup. Subsequently cfHPVrec was found in 6 patients (9%) during follow-up. Despite of no evidence of locoregional recurrence of disease neither in physical examination nor on imaging diagnostic (TK or MRI) PET scanning was additionally performed in these patients and revealed locoregional recurrence and metastatic HNSCC in 3 (4.5%) and 3 (4.5%) patients, respectively. Conclusion: In patients with HPV-related HNSCC, the presence of cfHPV DNA in blood reflects active cancer progression. The estimation of cfHPV DNA in patients controlled by RT or CHRT suggests sub symptomatic HNSCC relapse and/or dissemination what opens a chance for successful salvage. Author Disclosure: T. Rutkowski: None. A. Mazurek: None. M. Snietura: None. A. Wygoda: None. U. Bojko: None. P. Widlak: None. K.A. Skladowski: None.

92 CAPP-Seq Circulating Tumor DNA Analysis for Early Detection of Tumor Progression After Definitive Radiation Therapy for Lung Cancer A.A. Chaudhuri,1 A.F. Lovejoy,1 J.J. Chabon,1 A. Newman,1 H. Stehr,1 C. Say,1 S. Aggarwal,2 J.N. Carter,1 R.B. West,1 J.W. Neal,1 H.A. Wakelee,1 B.W. Loo, Jr,1 A. Alizadeh,1 and M. Diehn1; 1Stanford University School of Medicine, Stanford, CA, 2Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA Purpose/Objective(s): Response Evaluation Criteria in Solid Tumors (RECIST) is the primary method used to evaluate response to cancer therapeutics in clinical trials but can be challenging to perform after radiotherapy. Cancer Personalized Profiling by deep Sequencing (CAPPSeq) is a novel blood-based assay that uses next-generating sequencing to quantitate circulating tumor DNA (ctDNA). We performed a prospective study to compare response evaluation by CAPP-Seq and RECIST after definitive radiotherapy for lung cancer. Materials/Methods: We prospectively enrolled 30 patients treated with definitive radiotherapy for non-metastatic primary lung cancer at our institution between June 2010 and December 2014. Our cohort included 21 (70%) patients with stage III, 5 (16.7%) patients with stage II, and 4 (13.3%) patients with stage IB disease. All patients received pre-treatment evaluation by thoracic CT and PET/CT scans and ctDNA quantitation by CAPP-Seq. Twenty-one (70%) patients were treated with chemo-radiation and 9 (30%) were treated with hypofractionated radiotherapy. Following treatment, patients underwent disease surveillance by CT scans and

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CAPP-Seq every 3-6 months. CT scans were evaluated using RECIST criteria by an experienced radiologist and radiation oncologist. CAPP-Seq was performed at each time point as previously described (Newman et al, Nature Medicine, 2014). Results: Median follow-up time was 20.8 months. Median overall survival was 23.1 months. Sixteen (53.3%) patients progressed based on RECIST criteria, while the remaining 14 (46.7%) patients demonstrated complete response, partial response, or stable disease. CAPP-Seq detected ctDNA at or before the time of RECIST progression in all patients who progressed with a lead-time of 113.6 +/- 27.8 days (mean +/- SEM) and did not detect ctDNA at last follow-up in non-progressing patients. In the majority of patients who progressed (11 of 16; 68.8%), ctDNA was detected prior to RECIST progression with a lead-time of 165.2 +/- 28.9 days (mean +/SEM). The ctDNA concentration at time of progression was 76.6 +/- 50.7 haploid genome equivalents/mL (mean +/- SEM). Two-year overall survival for patients with ctDNA progression was 21.1% versus 90.9% for non-progressors (P Z 0.0003, HR Z 6.7, 95% CI Z 2.4-18.7). Conclusion: Our data suggest that CAPP-Seq-based ctDNA assessment is an accurate and sensitive method for evaluating response to thoracic radiotherapy. On average, detection of ctDNA anticipated imaging-detected disease progression by over 3.5 months, potentially facilitating clinical studies of early therapeutic interventions when disease burden is minimal. Author Disclosure: A.A. Chaudhuri: None. A.F. Lovejoy: None. J.J. Chabon: Graduate student; Stanford University. A. Newman: Consultant; Roche Molecular Systems. H. Stehr: None. C. Say: None. S. Aggarwal: None. J.N. Carter: None. R.B. West: None. J.W. Neal: Research Grant; Genentech/Roche, Merck, ArQuie, Novartis, Exellxis, Boehringer Ingelheim, Nektar. Consultant; Clovis Oncology, CARET/Physicians Resource Management, Nektar, Boehringer Ingelheim. H.A. Wakelee: None. B.W. Loo: Research Grant; Varian Medical Systems, RaySearch Laboratories. Stock Options; TibaRay, Inc. Committee Chair, Practice Parameters for IGR; American College of Radiology. Committee Co-Chair, Small Cell Lung Cancer; National Comprehensive Cancer Network. A. Alizadeh: Consultant; Roche Molecular Systems. M. Diehn: Consultant; Roche Molecular Systems, Quanticel Pharmaceuticals.

(enrichment P value Z 5.0 E-22). Knockdown of genes associated with the radioresistance signature identifies previously unreported radiation resistance genes. Application of this RS signature to multiple independent breast cancer datasets with annotated local recurrence rates, some with median follow-up times of >13.5 years, accurately discriminates patients with increased and decreased rates of local recurrence (all datasets P value < 0.0001). Furthermore, extension of the signature now identifies intrinsic breast cancer subtype (based on PAM50) and is being incorporated into the signature. Conclusion: We previously derived a human BC-specific RT sensitivity signature with biologic relevance and extend our validation studies into datasets with longer median follow-up. The signature is not correlated to the intrinsic subtypes of human breast cancer. This signature is currently being validated in randomized, phase III clinical trials of early stage breast cancer patients treated with and without radiation treatment and is the first molecular signature of RT response to undergo validation in such randomized datasets. By identifying patients with tumors refractory to standard RT this signature has the potential for personalization of RT, particularly in patients for whom treatment intensification is needed and may further be refined to identify women for whom the omission of RT is appropriate. Author Disclosure: C. Speers: Research Grant; Medivation/Astellas. Stock; PFS Genomics. Patent/License Fees/Copyright; PFS Genomics. S.G. Zhao: None. L. Chang: None. H. Bartelink: None. L.J. Pierce: Research Grant; BCRF, Komen for the Cure. Stock; PFS Genomics. F. Feng: Advisory Board; Medivation/Astellas. Stock; PFS Genomics. Partnership; PFS Genomics. Patent/License Fees/Copyright; PFS Genomics.

93 Validation and Extension of a Radiation Sensitivity Signature in Human Breast Cancer: Toward Personalized Risk Stratification C. Speers,1 S.G. Zhao,1 L. Chang,1 H. Bartelink,2 L.J. Pierce,1 and F. Feng1; 1University of Michigan, Ann Arbor, MI, 2NKI-AvL, Amsterdam 1066 CX, Netherlands Purpose/Objective(s): An unmet clinical need in breast cancer (BC) management is the identification patients who will respond to radiation therapy (RT). We hypothesized that the integration of post-RT clonogenic survival data with gene expression data across a large spectrum of BC cell lines would generate a BC-specific RT sensitivity signature predictive for RT response in BC. Materials/Methods: Clonogenic survival assays were used to measure surviving fraction after 2 Gy of RT across 21 BC cell lines. SF2 Gy was used as a continuous variable and the RT sensitivity score (RSS) was correlated to gene expression using a Spearman correlation method on an individual gene basis. Genes were selected for the signature based on correlation with a P value < 0.05 and FDR of < 0.01. This signature was trained and validated in a separate human breast tumor datasets containing early stage patients treated with surgery and RT alone (no chemotherapy) to assess the predictive effect of RS signature on recurrence risk after RT. Intrinsic subtyping, scaling, cross-platforming, and validation was done to recapitulate PAM50 and MammaPrint using derived algorithms and source datasets. Results: We previously demonstrated that clonogenic survival identifies a range of radiation sensitivity in human BCC lines with no significant correlation to the intrinsic BC subtype. Refinement of our previous signature using Spearmans correlation method narrowed the signature to 51 genes associated with radiation sensitivity. This gene signature is enriched for genes involved in cell cycle arrest and DNA damage response

94 Pathology-Based Non-Small Cell Lung Cancer Radiomics Signature Describing the Local Tumor Immune Environment: Discovery and Validation C. Tang,1 A. Amer,2 B. Hobbs,3 X. Li,4 C. Behrens,3 E. Para Cuentas,3 J. Rodriguez Canales,3 J.Y. Chang,1 D. Hong,3 J.W. Welsh,1 I. Wistuba,5 and E.J. Koay1; 1Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 2Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 3MD Anderson Cancer Center, Houston, TX, 4UT Houston, Houston, TX, 5MD Anderson Cancer Center, Houston, TX Purpose/Objective(s): A biological basis for quantitative radiological features (Radiomics) would provide guidance for clinical applications. We developed a pathology-based radiomics signature using a validated immunologic classification for NSCLC. Materials/Methods: The training cohort consisted 114 patients treated with surgical resection and had pre-surgical contrast-enhanced CTs. We quantified IHC staining for PDL1, PD1, CD3, CD4, CD8, CD57, CD68, Granzyme B, and FOXP3. Patients were clustered based on PDL1 staining in tumor cells and characteristics of tumor infiltrating lymphocytes (TIL) into 4 previously established groups: PDL1hiTILhi (Gp1), PDL1loTILlo (Gp2), PDL1hiTILlo (Gp3), PDL1loTILhi (Gp4) (Teng et al. Cancer Res 2015). An initial 490 imaging features were extracted with custom software (IBEX). Radiomics signatures were identified using a 3-stage analysis pipeline: (1) L1 penalized regression to select radiomics features that best described the immune pathology marker scores and OS. Hierarchical clustering of selected features was used to create radiomics signatures associated with OS. (2) Model validation was conducted in an independent cohort (n Z 179). Consensus clustering was applied for each patient in the validation set to assess pairwise similarity with the training set and thus assign a radiomics signature class. (3) To assess inter-reader variability, 3 clinicians contoured tumors from 10 patients. Features exhibiting <2% variation were considered highly reproducible. Results: Patients in the training/validation datasets were predominately stage I (54%/64%) adenocarcinomas (55%/62%) with median OS of 74 and 96 mo, respectively. Regarding pathology groups, Gp 3 patients exhibited the worst median OS (34 mo), while patients in Gp 4 exhibited the best (100 mo). Significant differences in OS were noted among