Effect of stereotactic radiation (SBRT) on survival in a preclinical model of spontaneous pancreatic cancer with induction gemcitabine/nab-paclitaxel.

273 Background: There are no useful preclinical models that resemble relevant fractionated radiation, such as SBRT, with relevant chemotherapy. Most preclinical studies use a single fraction of radiation to large fields, causing significant toxicity and/or insufficient dose which leads to accelerated repopulation and worsened outcomes. Here, we employ mice with spontaneous pancreatic tumors, and treat them in a preclinical trial utilizing gemcitabine/nab-paclitaxel +/-SBRT. Methods: Mice with an activated KRas (G12D) allele and heterozygous for p53 expression only in the pancreas (KPC) were created and spontaneous tumors were diagnosed via weekly palpation and ultrasound. Mice with single tumors that were between 3-7mm at diagnosis were sequentially randomized to received either no treatment, gemcitabine/nab-paclitaxel x 2 weeks, or gemcitabine/nab-paclitaxel x 2 weeks followed by 8Gy x 5 daily fractions of SBRT to the pancreatic tumor. SBRT was delivered using X-RAD 225Cx (Precision X-Ray, Inc) small animal irradiator under image guidance by cone beam micro CT using AP/PA technique with a 10mm collimator. Every mouse was subjected to necropsy and a cause of death assigned. Tumor growth was monitored by small animal ultrasound. Kaplan-Meier survival analysis was performed to assess efficacy of treatments. Results: A total of 40 mice were enrolled with 12 receiving chemotherapy alone, 13 receiving chemotherapy +SBRT and 15 mice had no further treatment. The addition of induction chemotherapy improves lifespan compared to untreated mice. The addition of SBRT further improved survival. Causes of death in untreated animals of the gemcitabine/nab-paclitaxel group were largely from local progression, whereas the addition of SBRT provided local control causing most of the mice in this cohort to die from metastatic progression. Conclusions: SBRT improves survival when added to gem/nab-paclitaxel in a preclinical model, which may reflect favorable biology for this approach. Our novel system employs similar SBRT fields and doses, and may thus be useful for the evaluation of other chemotherapeutic regimens with SBRT.

Accelerated hypofractionated radiotherapy for advanced lung cancer

Introduction – purposeThe aim of this study is to review the results of applying a hypofractionated radiotherapy schedule for locally advanced inoperable lung cancer in patients who have received chemotherapy. Lung cancer and especially non-small-cell lung cancer is prone to accelerated repopulation and shorter treatment schedules in the form of accelerated radiotherapy have been shown to improve treatment outcome.Patients – methodIn total, 29 patients with inoperable lung cancer (stage II, IIIa,b, IV) were treated with accelerated hypofractionated 3D conformal radiotherapy. All patients received a dose of 55 Gy in 20 fractions (daily dose of 2·75 Gy). The median age was 65·5 years, 87% of patients had stage III–IV disease, 93% of patients received sequential chemotherapy with their radiotherapy. Median follow-up of patients was 36 months.ResultsThe median overall survival from time of diagnosis was 16·5 months and the 1 year overall survival was 31%. Complications were present in 44·8% of the patients and the most common complication (20·7%) was pneumonitis alone. The complication rate was not significantly different according to histological type, stage, type of chemotherapy, presence of recurrence or death.ConclusionAlthough our study limitation is the small number of patients, these data suggest that the efficacy of this hypofractionated schedule could be considered as alternative option to the conventional regimen of 66 Gy given in 33 fractions.

Spatial concordance of tumor proliferation and accelerated repopulation from pathologic images to 18F-FLT PET images.

e23100 Background: PET imaging with 18F-fluorothymidine (18F-FLT) can potentially be used to identify tumor subvolumes for selecting dose escalation in radiation therapy. The aim of this study was to monitor tumor cell proliferation and repopulation during fractionated radiotherapy and investigated the spatial concordance of tumor cell proliferation and repopulation with 18F-FLT tracer uptake. Methods: Mice bearing A549 xenograft tumors were assigned to 5 different irradiated groups (3f/6d, 6f/12d, 9f/18d, 12f/24d and 18f/36d) with 2 Gy/fractions and non-irradiated group. Serial 18F-FLT micro PET scans were performed at different time points, the maximum of standard uptake value (SUVmax) were measured to detect the feasible time of tumor repopulation during irradiation. Ex vivo images of the spatial pattern of intratumor 18F-FLT uptake and Ki-67 labeling index (LI) were obtained from thin tumor tissue sections. A layer-by-layer comparison between SUVmax and Ki-67 LI results, including the thresholds at which maximum overlap occurred between FLT-segmented areas and areas of active cell proliferation, were conducted to evaluate the spatial imaging pathology correlation. Results: The SUVmax were observed decreases in the 3f/6d group (P = 0.000), compared to these for non-irradiated tumors. However, it was significantly increased in the 6f/12d later, and then gradually reduced with treatment time prolonged again after 6f/12d group. Proliferation changes on pathology imaging at 6f/12d were also confirmed. Significant correlations were found between the SUVmax and Ki-67 LI of all ROIs in each in vitro tumor of cell proliferation group (Ps < 0.001). Similar results were also found in each tumor of accelerated repopulation group (Ps < 0.001). Furthermore, both of the mean ORRs were more than 50% in all layer of the tumor cell proliferation and accelerated groups. Regions of high-intensity 18F-FLT uptake in the autoradiographs exhibited prominent staining for Ki-67. Conclusions: 18F-FLT PET may be a promising imaging surrogate of tumor proliferative response to fractionated radiotherapy and might help make adaptive radiation oncology treatment plan.

Emergent properties of a computational model of tumour growth

While there have been enormous advances in our understanding of the genetic drivers and molecular pathways involved in cancer in recent decades, there also remain key areas of dispute with respect to fundamental theories of cancer. The accumulation of vast new datasets from genomics and other fields, in addition to detailed descriptions of molecular pathways, cloud the issues and lead to ever greater complexity. One strategy in dealing with such complexity is to develop models to replicate salient features of the system and therefore to generate hypotheses which reflect on the real system. A simple tumour growth model is outlined which displays emergent behaviours that correspond to a number of clinically relevant phenomena including tumour growth, intra-tumour heterogeneity, growth arrest and accelerated repopulation following cytotoxic insult. Analysis of model data suggests that the processes of cell competition and apoptosis are key drivers of these emergent behaviours. Questions are raised as to the role of cell competition and cell death in physical cancer growth and the relevance that these have to cancer research in general is discussed.

Emergent properties of a computational model of tumour growth

While there have been enormous advances in our understanding of the genetic drivers and molecular pathways involved in cancer in recent decades, there also remain key areas of dispute with respect to fundamental theories of cancer. The accumulation of vast new datasets from genomics and other fields, in addition to detailed descriptions of molecular pathways, cloud the issues and lead to ever greater complexity. One strategy in dealing with such complexity is to develop models to replicate salient features of the system and therefore to generate hypotheses which reflect on the real system. A simple tumour growth model is outlined which displays emergent behaviours that correspond to a number of clinically relevant phenomena including tumour growth, intra-tumour heterogeneity, growth arrest and accelerated repopulation following cytotoxic insult. Analysis of model data suggests that the processes of cell competition and apoptosis are key drivers of these emergent behaviours. Questions are raised as to the role of cell competition and cell death in physical cancer growth and the relevance that these have to cancer research in general is discussed.

Emergent properties of a computational model of tumour growth

While there have been enormous advances in our understanding of the genetic drivers and molecular pathways involved in cancer in recent decades, there also remain key areas of dispute with respect to fundamental theories of cancer. The accumulation of vast new datasets from genomics and other fields, in addition to detailed descriptions of molecular pathways, cloud the issues and lead to ever greater complexity. One strategy in dealing with such complexity is to develop models to replicate salient features of the system and therefore to generate hypotheses which reflect on the real system. A simple tumour growth model is outlined which displays emergent behaviours that correspond to a number of clinically relevant phenomena including tumour growth, intra-tumour heterogeneity, growth arrest and accelerated repopulation following cytotoxic insult. Analysis of model data suggests that the processes of cell competition and apoptosis are key drivers of these emergent behaviours. Questions are raised as to the role of cell competition and cell death in physical cancer growth and the relevance that these have to cancer research in general is discussed.