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Plots showing percentage changes in total cfDNA concentration for each patient at weeks 4 and 8 of treatment, compared to same-patient baseline value. The left plot includes non-responding patients and the right plot includes patients who responded to olaparib in the clinical trial. Below, Mann-Whitney test comparing these changes at each time point for responders and non-responder patients.

Objectives In the Cancer Core Europe Consortium (CCE), standardized biomarkers are required for therapy monitoring oncologic multicenter clinical trials. Multiparametric functional MRI and particularly diffusion-weighted MRI offer evident advantages for noninvasive characterization of tumor viability compared to CT and RECIST. A quantification of the inter- and intraindividual variation occurring in this setting using different hardware is missing. In this study, the MRI protocol including DWI was standardized and the residual variability of measurement parameters quantified. Methods Phantom and volunteer measurements (single-shot T2w and DW-EPI) were performed at the seven CCE sites using the MR hardware produced by three different vendors. Repeated measurements were performed at the sites and across the sites including a traveling volunteer, comparing qualitative and quantitative ROI-based results including an explorative radiomics analysis. Results For DWI/ADC phantom measurements using a central post-processing algorithm, the maximum deviation could be decreased to 2%. However, there is no significant difference compared to a decentralized ADC value calculation at the respective MRI devices. In volunteers, the measurement variation in 2 repeated scans did not exceed 11% for ADC and is below 20% for single-shot T2w in systematic liver ROIs. The measurement variation between sites amounted to 20% for ADC and < 25% for single-shot T2w. Explorative radiomics classification experiments yield better results for ADC than for single-shot T2w. Conclusion Harmonization of MR acquisition and post-processing parameters results in acceptable standard deviations for MR/DW imaging. MRI could be the tool in oncologic multicenter trials to overcome the limitations of RECIST-based response evaluation. Key Points • Harmonizing acquisition parameters and post-processing homogenization, standardized protocols result in acceptable standard deviations for multicenter MR–DWI studies. • Total measurement variation does not to exceed 11% for ADC in repeated measurements in repeated MR acquisitions, and below 20% for an identical volunteer travelling between sites. • Radiomic classification experiments were able to identify stable features allowing for reliable discrimination of different physiological tissue samples, even when using heterogeneous imaging data.

Supplementary figure and table legends

Supplementary Data 6: Monitoring of somatic genomic alterations in plasma during targeted therapy. Allele frequencies (AF) of identified mutations are represented on the left Y-axis while the sum of the target lesions on the CT scan, are represented on the right Y-axis.

Additional Information on molecular analyses determining CHD1 and SPOP status

Supplementary Data 1: Primers and probes for ddPCR assay Supplementary Data 2: Consort Diagram Supplementary Data 3: List of drugs Supplementary Data 4: Cross validation of PGM sequencing assay with ddPCR Supplementary Data 5: To test intra-run assay performance, 3 different libraries were prepared using the same plasma cfDNA from a single patient Supplementary Data 6: See figure 6 below. Supplementary Data 7: Time to progression for patients having a 30% decrease in plasma mutation AF, following targeted drug administration, and association with time to progression by RECIST evaluation.

Sample overview

Figure S1. Flowchart of study selection process with ICIs treatment. Figure S2. Flowchart of study selection process with TAs treatment. Figure S3. Overall Survival comparing HPD with non-HPD in patients with progression disease as best response in the ICIs and TAs cohorts ( RECIST 1.1 progression disease Landmark Analysis). Figure S4. Overall Survival in second line (a) and third (b) setting HPD vs non-HPD progressors by RECIST criteria in ICIs cohort. Figure S5. Concordance between RECIST and TGR criteria in ICIs cohort. Table S1. Computed tomography (CT) acquisition protocol parameters. Table S2. Clinical variables in patients treated with TAs. Table S3. Multivariate model in patients with progression disease as best response in ICIs group (using TGR).

SPOP mutation identified in this cohort.

Purpose: CHD1 deletions and SPOP mutations frequently cooccur in prostate cancer with lower frequencies reported in castration-resistant prostate cancer (CRPC). We monitored CHD1 expression during disease progression and assessed the molecular and clinical characteristics of CHD1-deleted/SPOP-mutated metastatic CRPC (mCRPC).Experimental Design: We identified 89 patients with mCRPC who had hormone-naive and castration-resistant tumor samples available: These were analyzed for CHD1, PTEN, and ERG expression by IHC. SPOP status was determined by targeted next-generation sequencing (NGS). We studied the correlations between these biomarkers and (i) overall survival from diagnosis; (ii) overall survival from CRPC; (iii) duration of abiraterone treatment; and (iv) response to abiraterone. Relationship with outcome was analyzed using Cox regression and log-rank analyses.Results: CHD1 protein loss was detected in 11 (15%) and 13 (17%) of hormone-sensitive prostate cancer (HSPC) and CRPC biopsies, respectively. Comparison of CHD1 expression was feasible in 56 matched, same patient HSPC and CRPC biopsies. CHD1 protein status in HSPC and CRPC correlated in 55 of 56 cases (98%). We identified 22 patients with somatic SPOP mutations, with six of these mutations not reported previously in prostate cancer. SPOP mutations and/or CHD1 loss was associated with a higher response rate to abiraterone (SPOP: OR, 14.50 P = 0.001; CHD1: OR, 7.30, P = 0.08) and a longer time on abiraterone (SPOP: HR, 0.37, P = 0.002, CHD1: HR, 0.50, P = 0.06).Conclusions: SPOP-mutated mCRPCs are strongly enriched for CHD1 loss. These tumors appear highly sensitive to abiraterone treatment. Clin Cancer Res; 24(22); 5585–93. ©2018 AACR.

Purpose:Most hyperprogression disease (HPD) definitions are based on tumor growth rate (TGR). However, there is still no consensus on how to evaluate this phenomenon.Patients and Methods:We investigated two independent cohorts of patients with advanced solid tumors treated in phase I trials with (i) programmed cell death 1 (PD-1)/PD-L1 antibodies in monotherapy or combination and (ii) targeted agents (TA) in unapproved indications. A Response Evaluation Criteria in Solid Tumors (RECIST) 1.1–based definition of hyperprogression was developed. The primary endpoint was the assessment of the rate of HPD in patients treated with ICIs or TAs using both criteria (RECIST and TGR) and the impact on overall survival (OS) in patients who achieved PD as best response.Results:Among 270 evaluable patients treated with PD-1/PD-L1 inhibitors, 29 PD-1/PD-L1–treated patients (10.7%) had HPD by RECIST definition. This group had a significantly lower OS (median of 5.23 months; 95% CI, 3.97–6.45) when compared with the non-HPD progressor group (median, 7.33 months; 95% CI, 4.53–10.12; HR = 1.73, 95% CI, 1.05–2.85; P = 0.04). In a subset of 221 evaluable patients, 14 (6.3%) were categorized as HPD using TGR criteria, differences in median OS (mOS) between this group (mOS 4.2 months; 95% IC, 2.07–6.33) and non-HPD progressors (n = 44) by TGR criteria (mOS 6.27 months; 95% CI, 3.88–8.67) were not statistically significant (HR 1.4, 95% IC, 0.70–2.77; P = 0.346). Among 239 evaluable patients treated with TAs, 26 (10.9%) were classified as having HPD by RECIST and 14 using TGR criteria in a subset of patients. No differences in OS were observed between HPD and non-HPD progressors treated with TAs.Conclusions:HPD measured by TGR or by RECIST was observed in both cohorts of patients; however, in our series, there was an impact on survival only in the immune-checkpoint inhibitor cohort when evaluated by RECIST. We propose a new way to capture HPD using RECIST criteria that is intuitive and easy to use in daily clinical practice.

Combined SPOP/ CHD1 status and time/ response to abiraterone.

Background More accurate predictive biomarkers in patients with gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are needed. This study aims to investigate radiomics-based tumour phenotypes as a surrogate biomarker of the tumour vasculature and response prediction to antiangiogenic targeted agents in patients with GEP-NETs. Methods In this retrospective study, a radiomics signature was developed in patients with GEP-NETs and liver metastases receiving lenvatinib. Patients were selected from the multicentre phase II TALENT trial (NCT02678780) (development cohort). Radiomics variables were extracted from liver metastases in the pre-treatment CT-scans and selected using LASSO regression and minimum redundancy maximum relevance (mRMR). Logistic regression and Cox proportional-hazards models for radiomics and combined radiomics with clinical data were explored. The performance of the models was tested in an external cohort (test cohort). Associations between the radiomics score and vascularization factors in plasma were studied using hierarchical clustering and Mann-Whitney U test. Results A total of 89 patients were included in the study, 408 liver metastases where analysed. The CT-based radiomics signature was associated with clinical benefit in the development (training and validation sets) and test cohorts (AUC 0.75 [0.66-0.90], 0.67 [0.49-0.92] and 0.67 [0.43-0.91], respectively). The combined radiomics-clinical signature (including the radiomics score, Ki-67 index and primary tumour site) improved on radiomics-only signature performance (AUC 0.79 [95% CI 0.64-0.93]; PConclusions Radiomics-based phenotypes can provide valuable information about tumour characteristics, including vasculature, that are associated with response to antiangiogenics. Clinical Trial Registration This is a study of the Lenvatinib Efficacy in Metastatic Neuroendocrine Tumours (TALENT) phase II clinical trial (NCT02678780).

Standard DSC-PWI analyses are based on concrete parameters and values, but an approach that contemplates all points in the time-intensity curves and all voxels in the region-of-interest may provide improved information, and more generalizable models. Therefore, a method of DSC-PWI analysis by means of normalized time-intensity curves point-by-point and voxel-by-voxel is constructed, and its feasibility and performance are tested in presurgical discrimination of glioblastoma and metastasis.In this retrospective study, patients with histologically confirmed glioblastoma or solitary-brain-metastases and presurgical-MR with DSC-PWI (August 2007-March 2020) were retrieved. The enhancing tumor and immediate peritumoral region were segmented on CE-T1wi and coregistered to DSC-PWI. Time-intensity curves of the segmentations were normalized to normal-appearing white matter. For each participant, average and all-voxel-matrix of normalized-curves were obtained. The 10 best discriminatory time-points between each type of tumor were selected. Then, an intensity-histogram analysis on each of these 10 time-points allowed the selection of the best discriminatory voxel-percentile for each. Separate classifier models were trained for enhancing tumor and peritumoral region using binary logistic regressions.A total of 428 patients (321 glioblastomas, 107 metastases) fulfilled the inclusion criteria (256 men; mean age, 60 years; range, 20-86 years). Satisfactory results were obtained to segregate glioblastoma and metastases in training and test sets with AUCs 0.71-0.83, independent accuracies 65-79%, and combined accuracies up to 81-88%.This proof-of-concept study presents a different perspective on brain MR DSC-PWI evaluation by the inclusion of all time-points of the curves and all voxels of segmentations to generate robust diagnostic models of special interest in heterogeneous diseases and populations. The method allows satisfactory presurgical segregation of glioblastoma and metastases.• An original approach to brain MR DSC-PWI analysis, based on a point-by-point and voxel-by-voxel assessment of normalized time-intensity curves, is presented. • The method intends to extract optimized information from MR DSC-PWI sequences by impeding the potential loss of information that may represent the standard evaluation of single concrete perfusion parameters (cerebral blood volume, percentage of signal recovery, or peak height) and values (mean, maximum, or minimum). • The presented approach may be of special interest in technically heterogeneous samples, and intrinsically heterogeneous diseases. Its application enables satisfactory presurgical differentiation of GB and metastases, a usual but difficult diagnostic challenge for neuroradiologist with vital implications in patient management.

Enginyeria Biomèdica; Imatge del càncer Biomedical engineering; Cancer imaging Ingeniería Biomédica; Imágenes del cáncer Tumor heterogeneity has been postulated as a hallmark of treatment resistance and a cure constraint in cancer patients. Conventional quantitative medical imaging (radiomics) can be extended to computing voxel-wise features and aggregating tumor subregions with similar radiological phenotypes (imaging habitats) to elucidate the distribution of tumor heterogeneity within and among tumors. Despite the promising applications of imaging habitats, they may be affected by variability of radiomics features, preventing comparison and generalization of imaging habitats techniques. We performed a comprehensive repeatability and reproducibility analysis of voxel-wise radiomics features in more than 500 lung cancer patients with computed tomography (CT) images and demonstrated the effect of voxel-wise radiomics variability on imaging habitats computation in 30 lung cancer patients with test–retest images. Repeatable voxel-wise features characterized texture heterogeneity and were reproducible regardless of the applied feature extraction parameters. Imaging habitats computed using robust radiomics features were more stable than those computed using all features in test–retest CTs from the same patient. Nine voxel-wise radiomics features (joint energy, joint entropy, sum entropy, maximum probability, difference entropy, Imc1, Imc2, Idn and Idmn) were repeatable and reproducible. This supports their application for computing imaging habitats in lung tumors towards the discovery of previously unseen tumor heterogeneity and the development of novel non-invasive imaging biomarkers for precision medicine. This study was supported by the Banco Bilbao Vizcaya Argentaria and Fundacio La Caixa. R.P.L. is supported by the CRIS Foundation Talent Award (TALENT19-05), the Instituto de Salud Carlos III-Investigación en Salud (PI18/01395) and the Prostate Cancer Foundation Young Investigator Award. K.B. is supported by MSCA COFUND Beatriu de Pinós Grant (2019BP/00182). ML is supported by a PERIS Grant-PIS Program. We thank Sarah MacKenzie, PhD for editorial assistance.

Non-invasive differential diagnosis of brain tumours is currently based on the assessment of tumour vascularity through magnetic resonance imaging (MRI) coupled with dynamic susceptibility contrast (DSC). However, given its limited accuracy, reaching a definitive diagnosis often requires complex neurosurgical interventions that compromise the patients’ quality of life. We applied deep learning on DSC images from histology-confirmed patients with glioblastoma, metastasis or lymphoma, the three most common brain malignancies. The convolutional neural network trained on ~ 50,000 voxels from 40 patients provided intra-tumour probability maps that yielded clinical-grade diagnosis. Performance was tested in 400 additional cases and an external validation cohort (n = 128). The tool reached a three-way accuracy of 0.78, superior to standard diagnosis with cerebral blood volume (0.55) and percentage of signal recovery (0.59) perfusion metrics. Our open-access software, Brain Enhancing Region Radiological analysis (BERRY), demonstrates the potential of voxel-wise probability maps for differential diagnosis of brain tumours using standard-of-care MRI.

Colorectal cancer; Predictive markers; Tumour biomarkers Cáncer colorrectal; Marcadores predictivos; Biomarcadores tumorales Càncer colorrectal; Marcadors predictius; Biomarcadors tumorals Anti-BRAF/EGFR therapy was recently approved for the treatment of metastatic BRAFV600E colorectal cancer (mCRCBRAF-V600E). However, a large fraction of patients do not respond, underscoring the need to identify molecular determinants of treatment response. Using whole-exome sequencing in a discovery cohort of patients with mCRCBRAF-V600E treated with anti-BRAF/EGFR therapy, we found that inactivating mutations in RNF43, a negative regulator of WNT, predict improved response rates and survival outcomes in patients with microsatellite-stable (MSS) tumors. Analysis of an independent validation cohort confirmed the relevance of RNF43 mutations to predicting clinical benefit (72.7% versus 30.8%; P = 0.03), as well as longer progression-free survival (hazard ratio (HR), 0.30; 95% confidence interval (CI), 0.12–0.75; P = 0.01) and overall survival (HR, 0.26; 95% CI, 0.10–0.71; P = 0.008), in patients with MSS-RNF43mutated versus MSS-RNF43wild-type tumors. Microsatellite-instable tumors invariably carried a wild-type-like RNF43 genotype encoding p.G659fs and presented an intermediate response profile. We found no association of RNF43 mutations with patient outcomes in a control cohort of patients with MSS-mCRCBRAF-V600E tumors not exposed to anti-BRAF targeted therapies. Overall, our findings suggest a cross-talk between the MAPK and WNT pathways that may modulate the antitumor activity of anti-BRAF/EGFR therapy and uncover predictive biomarkers to optimize the clinical management of these patients. VHIO would like to acknowledge the Cellex Foundation for providing research facilities and equipment, the FERO Foundation for their funding support, the Consorcio Centro de Investigación Biomédica en Red de Cáncer (CIBERONC, CB16/12/00259) from the Institute of Health Carlos III (ISCIII), Ministry of Science and Innovation, and the Department of Health (Generalitat de Catalunya, SLT008/18/00198 and SLT008/18/00205) for their support on this research. Authors acknowledge financial support from the State Agency for Research (Agencia Estatal de Investigación) (CEX2020-001024-S / AEI / 10.13039 /501100011033). This research is funded by the SCITRON program; Novartis funded the genomics characterization by WES of samples from 28 patients from the discovery cohort and had no influence on data analysis/interpretation or writing of the paper (3003145512 to R.A.T.). S.Li. is financially supported by a Chinese Scholarship Council PhD fellowship (201909370083 to S. Li). R.P.-L. is supported by a CRIS Foundation Talent Award (TALENT19-05), the FERO Foundation, the Instituto de Salud Carlos III-Investigación en Salud (PI18/01395 and PI21/01019 to R.P.-L.) and the Prostate Cancer Foundation (Young Investigator Award). This work was supported by the Miguel Servet-I Research Award from ISCIII of the Ministry of Economy (CP17/00199 to R.A.T.), the Olga Torres Foundation Award to emerging researchers (2601 to R.A.T.), the ISCIII-FEDER (PI17/00947 and PI20/00968 to E.E.), and the Fundación AECC (CLSEN19001ELEZ to E.E.) and Ministry of Science and Innovation (Europa Redes y Gestores, ECT2020-000827 to E.E.).

Immunotherapy by immune checkpoint inhibitors has become a standard treatment strategy for many types of solid tumors. However, the majority of patients with cancer will not respond, and predicting response to this therapy is still a challenge. Artificial intelligence (AI) methods can extract meaningful information from complex data, such as image data. In clinical routine, radiology or histopathology images are ubiquitously available. AI has been used to predict the response to immunotherapy from radiology or histopathology images, either directly or indirectly via surrogate markers. While none of these methods are currently used in clinical routine, academic and commercial developments are pointing toward potential clinical adoption in the near future. Here, we summarize the state of the art in AI-based image biomarkers for immunotherapy response based on radiology and histopathology images. We point out limitations, caveats, and pitfalls, including biases, generalizability, and explainability, which are relevant for researchers and health care providers alike, and outline key clinical use cases of this new class of predictive biomarkers.

Histology; Liver; Microstructure Histología; Hígado; Microestructura Histologia; Fetge; Microestructura Purpose Relationships between diffusion-weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange? Methods Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity L / D0 , and clinical protocols (single diffusion encoding; maximum b-value: {1000, 1500, 2000} s/mm2; 5 unique gradient duration/separation pairs; SNR = { ∞ , 100, 80, 40, 20}), accounting for heterogeneity in (D0,L) and perfusion contamination. Diffusion ( D ) and kurtosis ( K ) coefficients were calculated, and relationships between (D0,L) and (D,K) were visualized. Functions mapping (D,K) to (D0,L) were computed to predict unseen (D0,L) values, tested for their ability to classify discrete cell-size contrasts, and deployed on 9.4T ex vivo MRI-histology data of fixed mouse livers Results Relationships between (D,K) and (D0,L) are complex and depend on the diffusion encoding. Functions mapping (D,K) to (D0,L) captures salient characteristics of D0(D,K) and L(D,K) dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three-class cell-size classification task (for SNR = 20, bmax = 1500 s/mm2, δ = 20 ms, and Δ = 75 ms). MRI detects cell-size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes. Conclusion Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible. This project was supported by Fundació La Caixa and by the investigator-initiated PREdICT study at the Vall d'Hebron Institute of Oncology (Barcelona), funded by AstraZeneca and supporting FG. FG has received funding from the postdoctoral fellowships programme Beatriu de Pinós (2020 BP 00117), funded by the Secretary of Universities and Research (Government of Catalonia). KB is funded by a Beatriu de Pinós post-doctoral grant (2019 BP 00182). RPL is supported by a CRIS Foundation Talent Award (TALENT19-05), the Instituto de Salud Carlos III-Investigación en Salud (PI18/01395), Spanish Ministry for Science, Innovation and Universities (RTI2018-095209-B-C21, FIS-G64384969), Prostate Cancer Foundation Young Investigator Award and Fero Foundation. ICS is supported by a fellowship from Fundació ”la Caixa” (ID 100010434) and the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 847648, fellowship code LCF/BQ/PI20/1176003

Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77

Anti-BRAF/EGFR therapy was recently approved for the treatment of metastatic BRAFsupV600E/supcolorectal cancer (mCRCsupBRAF-V600E/sup). However, a large fraction of patients do not respond, underscoring the need to identify molecular determinants of treatment response. Using whole-exome sequencing in a discovery cohort of patients with mCRCsupBRAF-V600E/suptreated with anti-BRAF/EGFR therapy, we found that inactivating mutations in RNF43, a negative regulator of WNT, predict improved response rates and survival outcomes in patients with microsatellite-stable (MSS) tumors. Analysis of an independent validation cohort confirmed the relevance of RNF43 mutations to predicting clinical benefit (72.7% versus 30.8%; P = 0.03), as well as longer progression-free survival (hazard ratio (HR), 0.30; 95% confidence interval (CI), 0.12-0.75; P = 0.01) and overall survival (HR, 0.26; 95% CI, 0.10-0.71; P = 0.008), in patients with MSS-RNF43supmutated/supversus MSS-RNF43supwild-type/suptumors. Microsatellite-instable tumors invariably carried a wild-type-like RNF43 genotype encoding p.G659fs and presented an intermediate response profile. We found no association of RNF43 mutations with patient outcomes in a control cohort of patients with MSS-mCRCsupBRAF-V600E/suptumors not exposed to anti-BRAF targeted therapies. Overall, our findings suggest a cross-talk between the MAPK and WNT pathways that may modulate the antitumor activity of anti-BRAF/EGFR therapy and uncover predictive biomarkers to optimize the clinical management of these patients.

PURPOSE Preclinical studies demonstrated that ATR inhibition can exploit synthetic lethality (eg, in cancer cells with impaired compensatory DNA damage responses through ATM loss) as monotherapy and combined with DNA-damaging drugs such as carboplatin. PATIENTS AND METHODS This phase I trial assessed the ATR inhibitor M6620 (VX-970) as monotherapy (once or twice weekly) and combined with carboplatin (carboplatin on day 1 and M6620 on days 2 and 9 in 21-day cycles). Primary objectives were safety, tolerability, and maximum tolerated dose; secondary objectives included pharmacokinetics and antitumor activity; exploratory objectives included pharmacodynamics in timed paired tumor biopsies. RESULTS Forty patients were enrolled; 17 received M6620 monotherapy, which was safe and well tolerated. The recommended phase II dose (RP2D) for once- or twice-weekly administration was 240 mg/m2. A patient with metastatic colorectal cancer harboring molecular aberrations, including ATM loss and an ARID1A mutation, achieved RECISTv1.1 complete response and maintained this response, with a progression-free survival of 29 months at last assessment. Twenty-three patients received M6620 with carboplatin, with mechanism-based hematologic toxicities at higher doses, requiring dose delays and reductions. The RP2D for combination therapy was M6620 90 mg/m2 with carboplatin AUC5. A patient with advanced germline BRCA1 ovarian cancer achieved RECISTv1.1 partial response and Gynecologic Cancer Intergroup CA125 response despite being platinum refractory and PARP inhibitor resistant. An additional 15 patients had RECISTv1.1 stable disease as best response. Pharmacokinetics were dose proportional and exceeded preclinical efficacious levels. Pharmacodynamic studies demonstrated substantial inhibition of phosphorylation of CHK1, the downstream ATR substrate. CONCLUSION To our knowledge, this report is the first of an ATR inhibitor as monotherapy and combined with carboplatin. M6620 was well tolerated, with target engagement and preliminary antitumor responses observed.

BACKGROUND AND PURPOSE: DSC-PWI has demonstrated promising results in the presurgical diagnosis of brain tumors. While most studies analyze specific parameters derived from time-intensity curves, very few have directly analyzed the whole curves. The aims of this study were the following: 1) to design a new method of postprocessing time-intensity curves, which renders normalized curves, and 2) to test its feasibility and performance on the diagnosis of primary central nervous system lymphoma. MATERIALS AND METHODS: Diagnostic MR imaging of patients with histologically confirmed primary central nervous system lymphoma were retrospectively reviewed. Correlative cases of glioblastoma, anaplastic astrocytoma, metastasis, and meningioma, matched by date and number, were retrieved for comparison. Time-intensity curves of enhancing tumor and normal-appearing white matter were obtained for each case. Enhancing tumor curves were normalized relative to normal-appearing white matter. We performed pair-wise comparisons for primary central nervous system lymphoma against the other tumor type. The best discriminatory time points of the curves were obtained through a stepwise selection. Logistic binary regression was applied to obtain prediction models. The generated algorithms were applied in a test subset. RESULTS: A total of 233 patients were included in the study: 47 primary central nervous system lymphomas, 48 glioblastomas, 39 anaplastic astrocytomas, 49 metastases, and 50 meningiomas. The classifiers satisfactorily performed all bilateral comparisons in the test subset (primary central nervous system lymphoma versus glioblastoma, area under the curve = 0.96 and accuracy = 93%; versus anaplastic astrocytoma, 0.83 and 71%; versus metastases, 0.95 and 93%; versus meningioma, 0.93 and 96%). CONCLUSIONS: The proposed method for DSC-PWI time-intensity curve normalization renders comparable curves beyond technical and patient variability. Normalized time-intensity curves performed satisfactorily for the presurgical identification of primary central nervous system lymphoma.

The genomics of primary prostate cancer differ from those of metastatic castration-resistant prostate cancer (mCRPC). We studied genomic aberrations in primary prostate cancer biopsies from patients who developed mCRPC, also studying matching, same-patient, diagnostic, and mCRPC biopsies following treatment. We profiled 470 treatment-naive prostate cancer diagnostic biopsies and, for 61 cases, mCRPC biopsies, using targeted and low-pass whole-genome sequencing (n = 52). Descriptive statistics were used to summarize mutation and copy number profile. Prevalence was compared using Fisher’s exact test. Survival correlations were studied using log-rank test. TP53 (27%) and PTEN (12%) and DDR gene defects (BRCA2 7%; CDK12 5%; ATM 4%) were commonly detected. TP53, BRCA2, and CDK12 mutations were markedly more common than described in the TCGA cohort. Patients with RB1 loss in the primary tumor had a worse prognosis. Among 61 men with matched hormone-naive and mCRPC biopsies, differences were identified in AR, TP53, RB1, and PI3K/AKT mutational status between same-patient samples. In conclusion, the genomics of diagnostic prostatic biopsies acquired from men who develop mCRPC differ from those of the nonlethal primary prostatic cancers. RB1/TP53/AR aberrations are enriched in later stages, but the prevalence of DDR defects in diagnostic samples is similar to mCRPC.

The management of advanced prostate cancer has changed substantially with the availability of multiple effective novel treatments, which has led to improved disease survival. In the era of personalized cancer treatments, more precise imaging may help physicians deliver better care. More accurate local staging and earlier detection of metastatic disease, accurate identification of oligometastatic disease, and optimal assessment of treatment response are areas where modern imaging is rapidly evolving and expanding. Next-generation imaging modalities, including whole-body MRI and molecular imaging with combined PET and CT and combined PET and MRI using novel radiopharmaceuticals, create new opportunities for imaging to support and refine management pathways in patients with advanced prostate cancer. This article demonstrates the potential and challenges of applying next-generation imaging to deliver the clinical promise of treatment breakthroughs.

CONTEXT: Patients with nonmetastatic castration-resistant prostate cancer (nmCRPC) have rising prostate-specific antigen (PSA) and castrate testosterone levels, with no radiological findings of metastatic disease on computed tomography and bone scan. Given recent drug approvals for nmCRPC, with many other therapeutics and imaging modalities being developed, management of nmCRPC is a rapidly evolving field that merits detailed investigation.OBJECTIVE: To review current nmCRPC management practices and identify opportunities for improving care of nmCRPC patients.EVIDENCE ACQUISITION: A literature search up to July 2018 was conducted, including clinical trials and clinical practice guidelines (National Comprehensive Cancer Network, European Society for Medical Oncology, European Association of Urology, Prostate Cancer Clinical Trials Working Group, Prostate Cancer Radiographic Assessments for Detection of Advanced Recurrence). Keywords included prostate cancer, nonmetastatic, castration resistance, rising PSA, and biochemical relapse.EVIDENCE SYNTHESIS: Recommendations regarding indications for, and frequency of, imaging and PSA testing, as well as for initiating systemic therapy in nmCRPC are based on PSA rise kinetics and symptoms. Both enzalutamide and apalutamide have been shown to significantly increase metastasis-free survival in phase III placebo-controlled randomised trials in nmCRPC patients with PSA doubling time (DT) ≤10 mo. The expected impact of new imaging techniques in the assessment of nmCRPC is also reviewed.CONCLUSIONS: nmCRPC is a heterogeneous disease; while observation may be an option for some patients, enzalutamide and apalutamide may be appropriate to treat nmCRPC patients with PSA-DT ≤10 mo. The emergence of more accurate imaging modalities as well as circulating tumour biomarker assays will likely redefine the assessment of nmCRPC in the near future.PATIENT SUMMARY: Herein, we review key literature and clinical practice guidelines to summarise the optimal management of patients with prostate cancer and rising prostate-specific antigen despite castrate testosterone levels, but with no evidence of distant metastasis on traditional imaging. New drugs are being developed for this disease setting; novel imaging and tumour biomarker blood tests are likely to define this disease state more accurately.

3560 Background: Currently, there are no well-established biomarkers available to select mCRC patients (pts) who will benefit most from antiangiogenic therapy. RAS mutant (mt) allele fraction in plasma (plMAF) is an independent prognostic factor in mCRC. Preliminary data from our group suggests the possible predictive role of plMAF in RAS mt pts treated with 1st line chemotherapy (ct) +/- bevacizumab (bev). Methods: Data prospectively/retrospectively collected from RASmt mCRC pts who received 1st line ct+/-bev treatment in our center, selecting the subset of pts with plMAF sample evaluable with digital PCR (BEAMing) at baseline. Pts were stratified as high (≥ 5.8%) or low ( < 5.8%) plMAF, based on a previously established prognostic cutoff (Elez et al, Mol Onc 2019). We investigated the associations between clinic-pathological variables, overall survival (OS), and progression-free survival (PFS) stratified by plMAF RAS levels using Cox regression models. OS and PFS were calculated by Kaplan-Meier method. Murine PDX were developed from mCRC pts including models from patients with KRASG12/G13 mutations to explore recapitulation of the clinical findings. Results: From October ‘17 to December ‘21, 102 basal plasma samples were analyzed by BEAMing. 47 pts (46%) were classified as high, 39 pts (38%) as low, and 16 (16%) as no-mt detected by BEAMing (non-shedding). OS was significant longer in low plMAF pts than in high plMAF pts (median OS 15.9 vs 37.1 months (mo); HR 0.43; p = 0.001). In high plMAF pts, a trend towards a better PFS was observed in those pts treated with ct+bev compared to ct alone (median 9.4 vs 6.1 mo; HR 0.6; p = 0.18). No differences were observed in low plMAF pts treated with ct +/- bev (median 14.5 vs 14.9 mo; HR 1.2; p = 0.58). Results were not modified when adjusted by the presence of liver metastases. The multivariate PFS model showed no association between RAS plMAF and clinicopathological variables, except for treatment benefit with ct+bev and better outcomes in pts with resectable liver metastases. Interestingly, human ctDNA in one murine PDX model from non-shedding pt was not detectable, whereas human ctDNA was present in another PDX model with a plMAF of 36.2%. Conclusions: This study suggests that plMAF could be a promising predictive biomarker of response to bev in 1st line RASmt mCRC, but more pts need to be analyzed to confirm this effect. Our results confirm the prognostic role of RASmt plMAF in mCRC. plMAF could partially depend on tumor cell shedding degree and characteristics on the tumor vasculature architecture, this is being investigated in ongoing imaging studies and PDX models. These models will also help to understand the biology behind tumor response to bev and its connection with ctDNA shedding.

1086 Background: Genomic alterations driving MBC progression may be better captured by ctDNA reflecting clonal evolution, but it is currently unknow whether ctDNA analysis can replace tumor sequencing for clinical decision purposes. Aim: to study the concordance between mut in synchronous plasma and tumor samples prospectively collected from patients (pts) with MBC progressing on their last systemic therapy. Methods: MiSeq Amplicon-based NGS (custom panel of 60 cancer-related genes; BRCA1/2 and PALB2 not included) was performed in both tumor biopsy and plasma. The concordance of ESCAT Tier I and II mut ( PIK3CA, AKT1, ERBB2, ESR1, PTEN) was determined and correlated with mutant allele fraction (MAF), TDV, and clinical features. Findings from liquid biopsies were classified as true positive (TP-ctDNA) if a given mut was detected in both tumor and plasma and false negative (FN-ctDNA) if only in the tumor. TDV: all metastasis volume assessed by CT scan (excluding sclerotic bone metastasis), and analyzed by an experienced radiologist using the 3DSlicer semiautomatic segmentation tool (TDV = pixel size x number of pixels). Non-shedding cases were those where any mut was detected in tumor but none in plasma. Results: 88 cases were collected (luminal 64, HER2+ 17, triple negative 7). Median age at diagnosis 49 years (range 28-80). Radiomics assessment could be performed in 78/88 cases. The plasma/tissue concordance at case level was 74%. Discordance came from 23 cases; in 15 cases mut was only found in tissue and in 8 cases it was only detected in plasma. At gene level, PIK3CA had the highest concordance (79%); in ESR1 it was 52%. Higher concordance associated with non-luminal subtype (OR 0.08, 95%CI 0.002 – 0.59) and shorter interval between primary diagnosis and metastatic relapse (20.3 vs 51 months; p =.02), but not with MAF. FN-ctDNA occurred in 15/49 cases (31%) and associated with luminal subtype (p =.02), but not with other clinical variables. Non-shedding cases associated with older age (p =.03), luminal subtype (p =.007), low TDV (p =.0006) and < 3 metastatic sites (p =.05). In patients with visceral metastasis (n = 45), higher TDV associated with lower probability of FN-ctDNA (p =.03). All non-luminal subtypes were shedders and all but one were TP-ctDNA. In multivariate analysis, higher probability of TP-ctDNA in luminal tumors associated with tumor sampling from a progressing lesion (OR 10.8; 95% 1.5 – 122; p =.03) and shorter interval between diagnosis of metastatic disease and biopsy (OR 0.96, 95% CI 0.92 – 0.99; p =.03). Conclusions: Our results suggest that ctDNA can detect a significant proportion of clinically relevant mut in MBC. Patients’ characteristics, tumor subtype, type of gene, and tumor volume should be integrated with ctDNA results to better inform clinical decisions.

Imatges per ressonància magnètica; Neoplàsies rectals; Microambient tumoral Imagen de resonancia magnética; Neoplasias rectales; Microambiente tumoral Magnetic Resonance Imaging; Rectal neoplasms; Tumor Microenvironment Objective This study evaluated the correlation between intratumoural stroma proportion, expressed as tumour-stroma ratio (TSR), and apparent diffusion coefficient (ADC) values in patients with rectal cancer. Methods This multicentre retrospective study included all consecutive patients with rectal cancer, diagnostically confirmed by biopsy and MRI. The training cohort (LUMC, Netherlands) included 33 patients and the validation cohort (VHIO, Spain) 69 patients. Two observers measured the mean and minimum ADCs based on single-slice and whole-volume segmentations. The TSR was determined on diagnostic haematoxylin & eosin stained slides of rectal tumour biopsies. The correlation between TSR and ADC was assessed by Spearman correlation ( r s ). Results The ADC values between stroma-low and stroma-high tumours were not significantly different. Intra-class correlation (ICC) demonstrated a good level of agreement for the ADC measurements, ranging from 0.84–0.86 for single slice and 0.86–0.90 for the whole-volume protocol. No correlation was observed between the TSR and ADC values, with ADC mean r s = -0.162 ( p= 0.38) and ADC min r s = 0.041 ( p= 0.82) for the single-slice and r s = -0.108 ( p= 0.55) and r s = 0.019 ( p= 0.92) for the whole-volume measurements in the training cohort, respectively. Results from the validation cohort were consistent; ADC mean r s = -0.022 ( p= 0.86) and ADC min r s = 0.049 ( p= 0.69) for the single-slice and r s = -0.064 ( p= 0.59) and r s = -0.063 ( p= 0.61) for the whole-volume measurements. Conclusions Reproducibility of ADC values is good. Despite positive reports on the correlation between TSR and ADC values in other tumours, this could not be confirmed for rectal cancer. This study received financial support from “ Genootschap Landgoed Keukenhof .” Author R.P.L.’s work is supported by a PCF-Young Investigator Award . The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

TPS209 Background: Multiple lines of evidence suggest a crosstalk between androgen receptor (AR) signaling and DNA damage repair (DDR) in prostate cancer. Co-targeting both pathways in mHNPC can result in a clinically relevant synergistic effect. ZZFIRST trial is evaluating the combination of TALA –a poly(ADP-ribose) polymerase inhibitor– and EZ –an AR signaling inhibitor– in mHNPC patients. Methods: This is a multicenter, open-label, randomized, investigator-initiated phase 2 clinical trial. Men aged ≥18 years with histologically confirmed mHNPC, an ECOG performance status of 0-1, and a prostate-specific antigen (PSA) ≥4 ng/mL at enrolment are eligible. Patients must have not received previous systemic treatment for locally advanced or mHNPC. A total of 54 patients will start treatment with EZ 160 mg/day for 2 28-day cycles in addition to standard androgen-deprivation therapy (ADT). Patients are then randomized and stratified based on homologous recombination gene alterations on a 1:2 ratio to either continue EZ 160 mg/day, or to receive EZ 160 mg/day plus TALA 0.5 mg/day. In both arms, patients will continue ADT throughout the trial. Treatment will continue until progressive disease (PD) or unacceptable toxicity. PSA will be determined every 4 weeks and radiological tumor extend will be assessed at screening and every 8 weeks for the 6 initial months of treatment and every 12 weeks thereafter until PD. Primary endpoint is PSA-complete response defined as the percentage of patients with PSA < 0.2 ng/mL at 12 months of therapy. Secondary endpoints include PSA-complete response at any time point and at month 7, PSA response ( < 4 ng/ml) at 7 and 12 months, PSA-progression-free survival (PSA-PFS), radiologic PFS, time to castration resistance based on PSA-PFS and rPFS, and overall survival. Safety will be assessed as per NCI-CTCAE 5.0. Exploratory endpoints include analysis of transcriptional changes in AR and DDR pathways and assessment of genomic signatures on tumor and liquid biopsies collected at baseline, 4 weeks, and PD. An imaging sub-study of whole-body diffusion weighted MRI will help to further study antitumor activity and drug resistance mechanisms. This trial was opened to accrual in July 2020. Currently 44 patients have been enrolled (with 37 randomized by cycle 3 day 1) out of 54 expected. Analysis will be assessed with the exact binomial test. At least 11 patients must maintain PSA < 0.2 ng/mL by 12 months of therapy among 32 evaluable patients in the combination arm to justify further investigation of this strategy. A drop-out rate of 10% has been considered. Clinical trial information: NCT04332744.

Objective To identify CT-acquisition parameters accounting for radiomics variability and to develop a post-acquisition CT-image correction method to reduce variability and improve radiomics classification in both phantom and clinical applications. Methods CT-acquisition protocols were prospectively tested in a phantom. The multi-centric retrospective clinical study included CT scans of patients with colorectal/renal cancer liver metastases. Ninety-three radiomics features of first order and texture were extracted. Intraclass correlation coefficients (ICCs) between CT-acquisition protocols were evaluated to define sources of variability. Voxel size, ComBat, and singular value decomposition (SVD) compensation methods were explored for reducing the radiomics variability. The number of robust features was compared before and after correction using two-proportion z test. The radiomics classification accuracy (K-means purity) was assessed before and after ComBat- and SVD-based correction. Results Fifty-three acquisition protocols in 13 tissue densities were analyzed. Ninety-seven liver metastases from 43 patients with CT from two vendors were included. Pixel size, reconstruction slice spacing, convolution kernel, and acquisition slice thickness are relevant sources of radiomics variability with a percentage of robust features lower than 80%. Resampling to isometric voxels increased the number of robust features when images were acquired with different pixel sizes (p < 0.05). SVD-based for thickness correction and ComBat correction for thickness and combined thickness–kernel increased the number of reproducible features (p < 0.05). ComBat showed the highest improvement of radiomics-based classification in both the phantom and clinical applications (K-means purity 65.98 vs 73.20). Conclusion CT-image post-acquisition processing and radiomics normalization by means of batch effect correction allow for standardization of large-scale data analysis and improve the classification accuracy. Key Points • The voxel size (accounting for the pixel size and slice spacing), slice thickness, and convolution kernel are relevant sources of CT-radiomics variability. • Voxel size resampling increased the mean percentage of robust CT-radiomics features from 59.50 to 89.25% when comparing CT scans acquired with different pixel sizes and from 71.62 to 82.58% when the scans were acquired with different slice spacings. • ComBat batch effect correction reduced the CT-radiomics variability secondary to the slice thickness and convolution kernel, improving the capacity of CT-radiomics to differentiate tissues (in the phantom application) and the primary tumor type from liver metastases (in the clinical application).

2042 Background: Malignant gliomas are heterogeneous diseases in genetic basis. The development of sequencing techniques, such as RNA-Sequencing, has identified many gene rearrangements encoding novel oncogenic fusions. Gene fusion discovery can potentially lead to the development of novel treatments, however studies of gene fusions in glioma remain limited. Methods: The GLIOCAT project studied 139 patient samples of newly diagnosed glioblastoma who had received the standard first-line treatment from 2004 to 2015, to identify gene fusion events from glioblastoma transcriptome data (RNA-Seq). The molecular subtype could be studied in 124 cases. RNA-Seq reads were mapped against the reference human genome with STAR-fusion version 0.7.0, specifically, with FusionInspector validate ( http://star-fusion.github.io ). Two other platforms, FusionHub ( https://fusionhub.persistent.co.in ) and Oncofuse ( www.unav.es/genetica/oncofuse.html ), were applied to eliminate false positives or previously described in healthy tissue and to predict of the oncogenic potential each fusion. Results: A total of61 patients showed 103 different fusions, a median of two fusions by sample. The majority of gene fusions were intrachromosomal and most frequently implied chromosome was 12 followed by 7. In addition, fusions were more common in patients with MGMT promoter methylation, TCGA classical subtype and 18 IGS subtype. There were no differences in age, sex, type of surgery or long survivors ( > 30 months). Ten fusions were already described in cancer, including three in gliomas (FRS2-KIF5A, EGFR-SEPT14 and FGFR3-TACC3). From the detected fusions, 22 of them included an oncogene or protooncogene. Conclusions: In our study, we report the landscape of gene fusions from a large data set of glioblastomas analyzed by RNA-seq. The majority of the fusions were private fusions. A minority of these recur in a low frequency but as many as a quarter of them included an oncogene or protooncogene. RNA-seq of GBM patient samples it is an important tool for the identification of patient-specific fusions that could drive personalized therapy. Furtherless, we will plan to validate this gene fusions.

Purpose To determine the usefulness of whole-body diffusion-weighted imaging (DWI) to assess the response of bone metastases to treatment in patients with metastatic castration-resistant prostate cancer (mCRPC). Materials and Methods A phase II prospective clinical trial of the poly-(adenosine diphosphate-ribose) polymerase inhibitor olaparib in mCRPC included a prospective magnetic resonance (MR) imaging substudy; the study was approved by the institutional research board, and written informed consent was obtained. Whole-body DWI was performed at baseline and after 12 weeks of olaparib administration by using 1.5-T MR imaging. Areas of abnormal signal intensity on DWI images in keeping with bone metastases were delineated to derive total diffusion volume (tDV); five target lesions were also evaluated. Associations of changes in volume of bone metastases and median apparent diffusion coefficient (ADC) with response to treatment were assessed by using the Mann-Whitney test and logistic regression; correlation with prostate-specific antigen level and circulating tumor cell count were assessed by using Spearman correlation (r). Results Twenty-one patients were included. All six responders to olaparib showed a decrease in tDV, while no decrease was observed in all nonresponders; this difference between responders and nonresponders was significant (P = .001). Increases in median ADC were associated with increased odds of response (odds ratio, 1.08; 95% confidence interval [CI]: 1.00, 1.15; P = .04). A positive association was detected between changes in tDV and best percentage change in prostate-specific antigen level and circulating tumor cell count (r = 0.63 [95% CI: 0.27, 0.83] and r = 0.77 [95% CI: 0.51, 0.90], respectively). When assessing five target lesions, decreases in volume were associated with response (odds ratio for volume increase, 0.89; 95% CI: 0.80, 0.99; P = .037). Conclusion This pilot study showed that decreases in volume and increases in median ADC of bone metastases assessed with whole-body DWI can potentially be used as indicators of response to olaparib in mCRPC. Online supplemental material is available for this article.

Background: Mucinous colorectal carcinoma (CRC) is found in 10-20% of patients and is associated with worse prognosis and treatment resistance. The early identification of mucinous tumor component at baseline and monitoring resistant clones at follow-up is challenging in clinical practice, which hinders appropriate and timely treatment selection. At CT, being routinely acquired in clinical practice, mucinous tumors can be characterized by semantic features, such as hypoattenuation and more heterogeneous enhancement than the non-mucinous tumors (Wnorowski et al 2019). However, the diagnostic accuracy of such CT findings reaches at most 62% (Young et al 2007). This can be substantially improved by utilizing robust feature quantification using state-of-art machine learning and neural network techniques. Materials and Methods: 7 mucinous and 7 non-mucinous CRC CTs were included in the model development (80% training and 20% validation) and 2 mucinous and 2 non-mucinous independent patients were used to test the model performance. Multiple lesions (primary and metastatic) were semi-automatically segmented in 3D Slicer (N=32 development and N=12 test). Three different classification models were generated using CT images: (1) a logistic regression model based on a newly developed hypodense tissue connectivity (HTC) metric, (2) a logistic regression model using a set of automatically selected radiomics (RAD) features (shape, 1st order and 2nd order) and (3) a convolutional neural network model (CNN) based on the ResNet architecture and automatically selected features. HTC was computed as a ratio between the volume of the connected hypodense tissue (0 Citation Format: Kinga Bernatowicz, Raquel Perez Lopez, Hector Garcia Palmer, Elena Elez Fernandez, Jose Fernandez Navarro, Marta Ligero Hernandez, Alonso Garcia Ruiz, Manuel Escobar Amores. Humans cannot accurately detect mucinous colorectal carcinoma from CT images, can AI help? [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-021.

Purpose To determine the correlation between the volume of bone metastasis as assessed with diffusion-weighted (DW) imaging and established prognostic factors in metastatic castration-resistant prostate cancer (mCRPC) and the association with overall survival (OS). Materials and Methods This retrospective study was approved by the institutional review board; informed consent was obtained from all patients. The authors analyzed whole-body DW images obtained between June 2010 and February 2013 in 53 patients with mCRPC at the time of starting a new line of anticancer therapy. Bone metastases were identified and delineated on whole-body DW images in 43 eligible patients. Total tumor diffusion volume (tDV) was correlated with the bone scan index (BSI) and other prognostic factors by using the Pearson correlation coefficient (r). Survival analysis was performed with Kaplan-Meier analysis and Cox regression. Results The median tDV was 503.1 mL (range, 5.6-2242 mL), and the median OS was 12.9 months (95% confidence interval [CI]: 8.7, 16.1 months). There was a significant correlation between tDV and established prognostic factors, including hemoglobin level (r = -0.521, P < .001), prostate-specific antigen level (r = 0.556, P < .001), lactate dehydrogenase level (r = 0.534, P < .001), alkaline phosphatase level (r = 0.572, P < .001), circulating tumor cell count (r = 0.613, P = .004), and BSI (r = 0.565, P = .001). A higher tDV also showed a significant association with poorer OS (hazard ratio, 1.74; 95% CI: 1.02, 2.96; P = .035). Conclusion Metastatic bone disease from mCRPC can be evaluated and quantified with whole-body DW imaging. Whole-body DW imaging-generated tDV showed correlation with established prognostic biomarkers and is associated with OS in mCRPC. (©) RSNA, 2016 Online supplemental material is available for this article.

Purpose: We evaluated whether next-generation sequencing (NGS) of circulating cell-free DNA (cfDNA) could be used for patient selection and as a tumor clone response biomarker in patients with advanced cancers participating in early-phase clinical trials of targeted drugs. Experimental Design: Plasma samples from patients with known tumor mutations who completed at least two courses of investigational targeted therapy were collected monthly, until disease progression. NGS was performed sequentially on the Ion Torrent PGM platform. Results: cfDNA was extracted from 39 patients with various tumor types. Treatments administered targeted mainly the PI3K–AKT–mTOR pathway (n = 28) or MEK (n = 7). Overall, 159 plasma samples were sequenced with a mean sequencing coverage achieved of 1,685X across experiments. At trial initiation (C1D1), 23 of 39 (59%) patients had at least one mutation identified in cfDNA (mean 2, range 1–5). Out of the 44 mutations identified at C1D1, TP53, PIK3CA and KRAS were the top 3 mutated genes identified, with 18 (41%), 9 (20%), 8 (18%) different mutations, respectively. Out of these 23 patients, 13 received a targeted drug matching their tumor profile. For the 23 patients with cfDNA mutation at C1D1, the monitoring of mutation allele frequency (AF) in consecutive plasma samples during treatment with targeted drugs demonstrated potential treatment associated clonal responses. Longitudinal monitoring of cfDNA samples with multiple mutations indicated the presence of separate clones behaving discordantly. Molecular changes at cfDNA mutation level were associated with time to disease progression by RECIST criteria. Conclusions: Targeted NGS of cfDNA has potential clinical utility to monitor the delivery of targeted therapies. Clin Cancer Res; 21(20); 4586–96. ©2015 AACR.

3541 Background: So far, no biomarkers of response to anti-angiogenic drugs are available in colorectal cancer (CRC) treatment. Liquid biopsy tracks dynamic mutational changes in CRC patients (pts). RAS mutant allele fraction in plasma (plMAF) is an independent prognostic marker in metastatic CRC (mCRC). We explored the predictive value of plMAF in RAS mutant pts treated in 1st line with chemotherapy +/- bevacizumab (bev). Methods: A multicentric prospective/retrospective analysis was conducted. We collected data from 226 mCRC pts and selected the subset not eligible for metastasis resection with basal plMAF sample evaluable for RAS mutant MAF quantification with digital PCR (BEAMing). Pts were stratified as high (≥ 5.8%) or low ( < 5.8%) plMAF. We investigated associations between clinicopathological variables and progression-free survival (PFS) stratified by plMAF RAS levels using Cox regression models and survival data were calculated by Kaplan-Meier method. Computational analysis of baseline CT scan data extracted 93 radiomics features of all the lesions per patient including 1) 1st class from density histogram distribution and texture analysis by 2) 2nd order and 3) higher order feature classes. The radiomic features distribution between pts with high and low pIMAF was assessed with Student’s t-test analysis. Results: From October 17 to May 19, 63 basal plasma samples were analysed with BEAMing. 42 pts (67.7%) were classified as high and 21 pts (32,3%) as low plMAF. In high plMAF subgroup, a statistically significant longer PFS favouring FOLFOX+bev was observed, compared to FOLFOX alone (10.7 vs 6.9 mts; HR: 0.30; p = 0.002). In low RAS plMAF subgroup, no differences in terms of PFS were observed in either arm (8.9 vs 8.7 mts; HR: 0.7; p = 0.6). Multivariate PFS model showed no association between RAS plMAF and clinicopathological variables, except for high RAS plMAF and treatment benefit with FOLFOX+bev. The CT-radiomics signature, that may translate tumor vascularization, differentiated patients with high vs low pIMAF (p = 0.002). 58 patients (92%) had similar radiomic score; 5 patients with high plMAF (8%) presented very heterogeneous radiomic score distribution. Conclusions: Tumor-borne RAS plMAFs may constitute a potential predictive biomarker of efficacy for anti-angiogenic drugs in mCRC. Next steps will include the identification of -histological, transcriptomic and radiomic- surrogate biomarkers of response that reflect tumor irrigational status.

BACKGROUND Germline DNA damage repair gene mutation (gDDRm) is found in >10% of metastatic prostate cancer (mPC). Their prognostic and predictive impact relating to standard therapies is unclear. OBJECTIVE To determine whether gDDRm status impacts benefit from established therapies in mPC. DESIGN, SETTING, AND PARTICIPANTS This is a retrospective, international, observational study. Medical records were reviewed for 390 mPC patients with known gDDRm status. All 372 patients from Royal Marsden (UK), Weill-Cornell (NY), and University of Washington (WA) were previously included in a prevalence study (Pritchard, NEJM 2016); the remaining 18 were gBRCA1/2m carriers, from the kConFab consortium, Australia. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Response rate (RR), progression-free survival (PFS), and overall survival (OS) data were collected. To account for potential differences between cohorts, a mixed-effect model (Weibull distribution) with random intercept per cohort was used. RESULTS AND LIMITATIONS The gDDRm status was known for all 390 patients (60 carriers of gDDRm [gDDRm+], including 37 gBRCA2m, and 330 cases not found to carry gDDRm [gDDRm-]); 74% and 69% were treated with docetaxel and abiraterone/enzalutamide, respectively, and 36% received PARP inhibitors (PARPi) and/or platinum. Median OS from castration resistance was similar among groups (3.2 vs 3.0 yr, p=0.73). Median docetaxel PFS for gDDRm+ (6.8 mo) was not significantly different from that for gDDRm- (5.1 mo), and RRs were similar (gDDRm+=61%; gDDRm-=54%). There were no significant differences in median PFS and RR on first-line abiraterone/enzalutamide (gDDRm+=8.3 mo, gDDRm-=8.3 mo; gDDRm+=46%, gDDRm-=56%). Interaction test for PARPi/platinum and gDDRm+ resulted in an OS adjusted hazard ratio of 0.59 (95% confidence interval 0.28-1.25; p=0.17). Results are limited by the retrospective nature of the analysis. CONCLUSIONS mPC patients with gDDRm appeared to benefit from standard therapies similarly to the overall population; prospective studies are ongoing to investigate the impact of PARPi/platinum. PATIENT SUMMARY Patients with inherited DNA repair mutations benefit from standard therapies similarly to other metastatic prostate cancer patients.

Purpose: CHD1 deletions and SPOP mutations frequently cooccur in prostate cancer with lower frequencies reported in castration-resistant prostate cancer (CRPC). We monitored CHD1 expression during disease progression and assessed the molecular and clinical characteristics of CHD1-deleted/SPOP-mutated metastatic CRPC (mCRPC). Experimental Design: We identified 89 patients with mCRPC who had hormone-naive and castration-resistant tumor samples available: These were analyzed for CHD1, PTEN, and ERG expression by IHC. SPOP status was determined by targeted next-generation sequencing (NGS). We studied the correlations between these biomarkers and (i) overall survival from diagnosis; (ii) overall survival from CRPC; (iii) duration of abiraterone treatment; and (iv) response to abiraterone. Relationship with outcome was analyzed using Cox regression and log-rank analyses. Results: CHD1 protein loss was detected in 11 (15%) and 13 (17%) of hormone-sensitive prostate cancer (HSPC) and CRPC biopsies, respectively. Comparison of CHD1 expression was feasible in 56 matched, same patient HSPC and CRPC biopsies. CHD1 protein status in HSPC and CRPC correlated in 55 of 56 cases (98%). We identified 22 patients with somatic SPOP mutations, with six of these mutations not reported previously in prostate cancer. SPOP mutations and/or CHD1 loss was associated with a higher response rate to abiraterone (SPOP: OR, 14.50 P = 0.001; CHD1: OR, 7.30, P = 0.08) and a longer time on abiraterone (SPOP: HR, 0.37, P = 0.002, CHD1: HR, 0.50, P = 0.06). Conclusions: SPOP-mutated mCRPCs are strongly enriched for CHD1 loss. These tumors appear highly sensitive to abiraterone treatment. Clin Cancer Res; 24(22); 5585–93. ©2018 AACR.

Background Loss of PTEN is a common genomic aberration in castration-resistant prostate cancer (CRPC) and is frequently concurrent with ERG rearrangements, causing resistance to next-generation hormonal treatment (NGHT) including abiraterone. The relationship between PTEN loss and docetaxel sensitivity remains uncertain. Objective To study the antitumor activity of docetaxel in metastatic CRPC in relation to PTEN and ERG aberrations. Design, setting, and participants Single-centre, retrospective analysis of PTEN loss and ERG expression using a previously described immunohistochemistry (IHC) binary classification system. Patients received docetaxel between January 1, 2006 and July 31, 2016. Outcome measurements and statistical analysis Response correlations were analyzed using Pearson's χ2 tests and independent-sample t tests. Overall (OS) and progression-free survival (PFS) were analyzed using univariate and multivariate (MVA) Cox regression and Kaplan-Meier methods. Results and limitations Overall, 215 patients were eligible. Established metastatic CRPC prognostic factors were well balanced between PTEN loss (39%) and normal patients (61%). PTEN loss was associated with shorter median OS (25.4 vs 34.7 mo; hazard ratio [HR] 1.66, 95% confidence interval [CI] 1.18–2.13; p = 0.001). There were no differences in median PFS (8.0 vs 9.1 mo; univariate HR 1.20, 95% CI 0.86–1.68; p = 0.28) and PSA response (53.4% vs 50.6%; p = 0.74). PTEN loss was an independent prognostics factor in MVA. ERG status was available for 100 patients. ERG positivity was not associated with OS or PFS. Limitations include the retrospective nature and the single-centre analysis. Conclusions Our findings suggest that metastatic CRPC with PTEN loss might benefit more from docetaxel than from NGHT. Patient summary In this study we found that metastatic prostate cancer with loss of the PTEN switch may benefit more from docetaxel than from abiraterone., Take Home Message PTEN loss in advanced prostate cancer may benefit more from taxanes than from abiraterone.