Alpha-Emitter Radiopharmaceuticals and External Beam Radiotherapy: A Radiobiological Model for the Combined Treatment

Previously published studies combined external beam radiotherapy (EBRT) treatments with different activities of 223Ra. The data of two-year overall survival (2y-OS) and neutropenia (TOX) incidence when combining EBRT and 223Ra are not homogeneous in literature. We adapted the linear–quadratic model (LQ) to 223Ra therapy using brachytherapy formalism for a mixture of radionuclides, considering the contribution of all daughter isotopes in the decay chain. A virtual cohort of patients undergoing 223Ra therapy was derived using data from the literature. The doses delivered using 223Ra and EBRT were converted into biologically equivalent doses. Fixed-effect logistic regression models were derived for both the 2y-OS and TOX and compared with available literature. Based on the literature search, four studies were identified to have reported the 223Ra injection activity levels varying from the placebo (0) to 80 kBq/kg, associated or not with EBRT. Logistic regression models revealed a dose-dependent increase in both the 2y-OS (intercept = −1.364; slope = 0.006; p-value ≤ 0.05) and TOX (−5.035; 0.018; ≤0.05) using the EBRT schedule of 8 Gy in 1 fr. Similar results were obtained for other schedules. Discrepancies between our TOX model and those derived for EBRT combined with chemotherapy are discussed. Radiobiological models allow us to estimate dose-dependent relationships, to predict the OS and TOX following combined 223Ra + EBRT treatment, which will guide future treatment optimization

A Novel Benchmarking Approach to Assess the Agreement among Radiomic Tools

Background: The translation of radiomic models into clinical practice is hindered by the limited reproducibility of features across software and studies. Standardization is needed to accelerate this process and to bring radiomics closer to clinical deployment.Purpose: To assess the standardization level of seven radiomic software programs and investigate software agreement as a function of built-in image preprocessing (eg, interpolation and discretization), feature aggregation methods, and the morphological characteristics (ie, volume and shape) of the region of interest (ROI).Materials and Methods: The study was organized into two phases: In phase I, the two Image Biomarker Standardization Initiative (IBSI) phantoms were used to evaluate the IBSI compliance of seven software programs. In phase II, the reproducibility of all IBSI-standardized radiomic features across tools was assessed with two custom Italian multicenter Shared Understanding of Radiomic Extractors (ImSURE) digital phantoms that allowed, in conjunction with a systematic feature extraction, observations on whether and how feature matches between program pairs varied depending on the preprocessing steps, aggregation methods, and ROI characteristics.Results: In phase I, the software programs showed different levels of completeness (ie, the number of computable IBSI benchmark values). However, the IBSI-compliance assessment revealed that they were all standardized in terms of feature implementation. When considering additional preprocessing steps, for each individual program, match percentages fell by up to 30%. In phase II, the ImSURE phantoms showed that software agreement was dependent on discretization and aggregation as well as on ROI shape and volume factors.Conclusion: The agreement of radiomic software varied in relation to factors that had already been standardized (eg, interpolation and discretization methods) and factors that need standardization. Both dependences must be resolved to ensure the reproducibility of radiomic features and to pave the way toward the clinical adoption of radiomic models. Published under a CC BY 4.0 license

Limited impact of discretization/interpolation parameters on the predictive power of CT radiomic features in a surgical cohort of pancreatic cancer patients

Purpose To explore the variation of the discriminative power of CT (Computed Tomography) radiomic features (RF) against image discretization/interpolation in predicting early distant relapses (EDR) after upfront surgery. Materials and methods Data of 144 patients with pre-surgical high contrast CT were processed consistently with IBSI (Image Biomarker Standardization Initiative) guidelines. Image interpolation/discretization parameters were intentionally changed, including cubic voxel size (0.21–27 mm3) and binning (32–128 grey levels) in a 15 parameter’s sets. After excluding RF with poor inter-observer delineation agreement (ICC < 0.80) and not negligible inter-scanner variability, the variation of 80 RF against discretization/interpolation was first quantified. Then, their ability in classifying patients with early distant relapses (EDR, < 10 months, previously assessed at the first quartile value of time-to-relapse) was investigated in terms of AUC (Area Under Curve) variation for those RF significantly associated to EDR. Results Despite RF variability against discretization/interpolation parameters was large and only 30/80 RF showed %COV < 20 (%COV = 100*STDEV/MEAN), AUC changes were relatively limited: for 30 RF significantly associated with EDR (AUC values around 0.60–0.70), the mean values of SD of AUC variability and AUC range were 0.02 and 0.05 respectively. AUC ranges were between 0.00 and 0.11, with values ≤ 0.05 in 16/30 RF. These variations were further reduced when excluding the extreme values of 32 and 128 for grey levels (Average AUC range 0.04, with values between 0.00 and 0.08). Conclusions The discriminative power of CT RF in the prediction of EDR after upfront surgery for pancreatic cancer is relatively invariant against image interpolation/discretization within a large range of voxel sizes and binning

The potential role of MR based radiomic biomarkers in the characterization of focal testicular lesions

How to differentiate with MRI-based techniques testicular germ (TGCTs) and testicular non-germ cell tumors (TNGCTs) is still under debate and Radiomics may be the turning key. Our purpose is to investigate the performance of MRI-based Radiomics signatures for the preoperative prediction of testicular neoplasm histology. The aim is twofold: (i), differentiating TGCTs and TNGCTs status and (ii) differentiating seminomas (SGCTs) from non-seminomatous (NSGCTs). Forty-two patients with pathology-proven testicular neoplasms and referred for pre-treatment MRI, were retrospectively enrolled. Thirty-two out of 44 lesions were TGCTs. Twelve out of 44 were TNGCTs or other histologies. Two radiologists segmented the volume of interest on T2-weighted images. Approximately 500 imaging features were extracted. Least Absolute Shrinkage and Selection Operator (LASSO) was applied as method for variable selection. A linear model and a linear support vector machine (SVM) were trained with selected features to assess discrimination scores for the two endpoints. LASSO identified 3 features that were employed to build fivefold validated linear discriminant and linear SVM classifiers for the TGCT-TNGCT endpoint giving an overall accuracy of 89%. Four features were employed to build another SVM for the SGCT-SNGCT endpoint with an overall accuracy of 86%. The data obtained proved that T2-weighted-based Radiomics is a promising tool in the diagnostic workup of testicular neoplasms by discriminating germ cell from non-gem cell tumors, and seminomas from non-seminomas

Abstract B169: Neratinib has clinical activity in HER2-amplified breast cancer patients with tumors that have acquired activating mutations in HER2

Abstract Overexpression/amplification of HER2/ERBB2 occurs in 20% of breast cancers. Thanks to specific anti-HER2 agents, the prognosis of HER2-positive breast cancer has improved considerably. However, acquired resistance inevitably emerges over time and tumors escape pharmacologic pressure. In this work, we propose that acquisition of activating somatic mutations in HER2 upon anti-HER2 therapy may be more frequent than commonly reported and can reduce sensitivity to these agents. Moreover, we tested whether neratinib, an irreversible pan-HER inhibitor, is effective in tumors bearing both amplification and mutations of ERBB2. By targeted exome sequencing, we found that samples from metastatic breast cancer (MBC) patients relapsing to multiple lines of anti-HER2 therapy presented the acquisition of HER2 mutations. These mutations spanned from the extracellular domain (L313I, R456C) to the kinase domain (L755S, D769Y) of the receptor. To investigate the role of these mutations in drug resistance, we conducted functional studies by stably transducing the L755S HER2 mutation (the most frequent HER2 mutation in breast cancer) in two ERBB2-amplified breast cancer cell lines intrinsically sensitive to HER2 inhibition. In both models, we found that expression of L755S mutant-HER2 was sufficient to limit sensitivity to trastuzumab, lapatinib, or the combination of both agents. Consistently, neither trastuzumab nor lapatinib was effective in inhibiting tumor growth of patient-derived xenografts established from a patient with ERBB2-amplified/mutant (D769Y) breast cancer. However, neratinib treatment demonstrated marked sensitivity in this tumor model, resulting in significant tumor growth inhibition. The antitumor activity of neratinib was also explored in breast cancer patients with coexisting ERBB2 amplification and mutation, either by compassionate use after failure of standard-of-care therapy or as part of a “basket” trial (NCT01953926) enrolling ERBB2-mutant patients. In both settings, we observed durable clinical response to neratinib. MBC case #HER2 co-mutationResponse to neratinibDurability of response (mo)1D769YSD62L313ISD93Y772_A775dupSD44L755SSD55V777LPR6 Our findings indicate that acquired HER2 mutations may reduce the effectiveness of therapeutic agents commonly used for the management of ERBB2-amplified MBC. Moreover, we propose neratinib as an effective treatment option for patients whose tumors harbor both ERBB2 amplifications and mutations. Citation Format: Emiliano Cocco, F. Javier Carmona, Helen H. Won, Michael F. Berger, David M. Hyman, Valentina Rossi, Carmen Chan, Alyssa Moriarty, Kyriakos P. Papadopoulos, Michael J. Wick, James Cownie, Ivana Sarotto, Richard E. Cutler, Francesca Avogadri-Connors, Peter Savas, Alshad S. Lalani, Valentina Boni, Sherene Loi, Jose Baselga, Filippo Montemurro, Maurizio Scaltriti. Neratinib has clinical activity in HER2-amplified breast cancer patients with tumors that have acquired activating mutations in HER2 [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B169

Italian Goat Consortium: a collaborative project to study the Italian caprine biodiversity

The Italian Goat Consortium (IGC), joined the effort of many Universities and Research Institutes, in a comprehensive study of the Italian goat population genetic makeup using a medium density (54K) SNPs chip. Currently IGC has genotyped more than 1,000 animals from more than 30 goat breeds and populations from all Italian geographical and agroecological areas of goat rearing. The aim of this work is to obtain a clear picture of the Italian caprine biodiversity, to reconstruct the ancestry, to disentangle the genetic background and to assess the relationships among and within the investigated breeds. To date, the IGC dataset includes about 50 million genotypes. The data were quality checked by excluding markers and individuals on the basis of missing genotypes, minor allele frequency and close individual relatedness. Genetic relationships among and within breeds was investigated by Multi-Dimensional Scaling and Principal Component Analysis. Population structure, ancestry models and admixture were estimated by ADMIXTURE and fastSTRUCTURE software. Finally, phylogenic trees were reconstructed with PHYLIP software suite starting from shared-allele identity by state, and Reynolds distance matrices, while past migration events were modeled with TreeMix software. The results confirmed high levels of genetic polymorphism and confirmed the North-South geographical pattern of diversity, previously reported on a smaller sample of Italian goat breeds. The analysis also revealed a pivotal role of Central Italy in connecting the genetic resources of the northern and southern areas of the country, and confirms the genetic isolation of insular breeds. Moreover, some breeds show clearly distinctive and homogeneous gene pools, whereas other breeds present complex and, in some cases, dishomogeneous genetic background. Even if “A breed is a group of domestic animals, termed such by common consent of the breeders” (Lush J.L., 1994), genomic tools are useful in understanding the genetic background of populations and in defining their relationships or uniqueness. These tools can complement the traditional ones in providing farmers and their associations a powerful aid for a more conscious management of goat populations and their biodiversity

Neratinib is effective in breast tumors bearing both amplification and mutation of ERBB2 (HER2)

Mutations in , the gene encoding epidermal growth factor receptor (EGFR) family member HER2, are common in and drive the growth of "HER2-negative" (not amplified) tumors but are rare in "HER2-positive" ( amplified) breast cancer. We analyzed DNA-sequencing data from HER2-positive patients and used cell lines and a patient-derived xenograft model to test the consequence of HER2 mutations on the efficacy of anti-HER2 agents such as trastuzumab, lapatinib, and neratinib, an irreversible pan-EGFR inhibitor. HER2 mutations were present in ~7% of HER2-positive tumors, all of which were metastatic but not all were previously treated. Compared to HER2 amplification alone, in both patients and cultured cell lines, the co-occurrence of HER2 mutation and amplification was associated with poor response to trastuzumab and lapatinib, the standard-of-care anti-HER2 agents. In mice, xenografts established from a patient whose HER2-positive tumor acquired a D769Y mutation in HER2 after progression on trastuzumab-based therapy were resistant to trastuzumab or lapatinib but were sensitive to neratinib. Clinical data revealed that six heavily pretreated patients with tumors bearing coincident HER2 amplification and mutation subsequently exhibited a statistically significant response to neratinib monotherapy. Thus, these findings indicate that coincident HER2 mutation reduces the efficacy of therapies commonly used to treat HER2-positive breast cancer, particularly in metastatic and previously HER2 inhibitor-treated patients, as well as potentially in patients scheduled for first-line treatment. Therefore, we propose that clinical studies testing the efficacy of neratinib are warranted selectively in breast cancer patients whose tumors carry both amplification and mutation of /HER2

HER kinase inhibition in patients with HER2- and HER3-mutant cancers

Somatic mutations of ERBB2 and ERBB3 (which encode HER2 and HER3, respectively) are found in a wide range of cancers. Preclinical modelling suggests that a subset of these mutations lead to constitutive HER2 activation, but most remain biologically uncharacterized. Here we define the biological and therapeutic importance of known oncogenic HER2 and HER3 mutations and variants of unknown biological importance by conducting a multi-histology, genomically selected, 'basket' trial using the pan-HER kinase inhibitor neratinib (SUMMIT; clinicaltrials.gov identifier NCT01953926). Efficacy in HER2-mutant cancers varied as a function of both tumour type and mutant allele to a degree not predicted by preclinical models, with the greatest activity seen in breast, cervical and biliary cancers and with tumours that contain kinase domain missense mutations. This study demonstrates how a molecularly driven clinical trial can be used to refine our biological understanding of both characterized and new genomic alterations with potential broad applicability for advancing the paradigm of genome-driven oncology