Genetic variants in the mammalian target of rapamycin (mTOR) signaling pathway as predictors of survival and clinical response in women with ovarian cancer

Background. The mTOR pathway is commonly altered in human tumors and promotes cell survival and proliferation. Preliminary evidence suggests this pathway's involvement in chemoresistance to platinum and taxanes, first line therapy for epithelial ovarian cancer. A pathway-based approach was used to identify individual germline single nucleotide polymorphisms (SNPs) and cumulative effects of multiple genetic variants in mTOR pathway genes and their association with clinical outcome in women with ovarian cancer. ^ Methods. The case-series was restricted to 319 non-Hispanic white women with high grade ovarian cancer treated with surgery and platinum-based chemotherapy. 135 SNPs in 20 representative genes in the mTOR pathway were genotyped. Hazard ratios (HRs) for death and Odds ratios (ORs) for failure to respond to primary therapy were estimated for each SNP using the multivariate Cox proportional hazards model and multivariate logistic regression model, respectively, while adjusting for age, stage, histology and treatment sequence. A survival tree analysis of SNPs with a statistically significant association (p<0.05) was performed to identify higher order gene-gene interactions and their association with overall survival. ^ Results. There was no statistically significant difference in survival by tumor histology or treatment regimen. The median survival for the cohort was 48.3 months. Seven SNPs were significantly associated with decreased survival. Compared to those with no unfavorable genotypes, the HR for death increased significantly with the increasing number of unfavorable genotypes and women in the highest risk category had HR of 4.06 (95% CI 2.29–7.21). The survival tree analysis also identified patients with different survival patterns based on their genetic profiles. 13 SNPs on five different genes were found to be significantly associated with a treatment response, defined as no evidence of disease after completion of primary therapy. Rare homozygous genotype of SNP rs6973428 showed a 5.5-fold increased risk compared to the wild type carrying genotypes. In the cumulative effect analysis, the highest risk group (individuals with ≥8 unfavorable genotypes) was significantly less likely to respond to chemotherapy (OR=8.40, 95% CI 3.10–22.75) compared to the low risk group (≤4 unfavorable genotypes). ^ Conclusions. A pathway-based approach can demonstrate cumulative effects of multiple genetic variants on clinical response to chemotherapy and survival. Therapy targeting the mTOR pathway may modify outcome in select patients.^

Platelets and Anti-Angiogenic Resistance in Ovarian Carcinoma

Background: Resistance to targeted anti-angiogenic therapy is a growing clinical concern given the disappointing clinical impact of anti-angiogenic. Platelets represent a component of the tumor microenvironment that are implicated in metastasis and represent a significant reservoir of angiogenic regulators. Thrombocytosis has been shown to be caused by malignancy and associated with adverse clinical outcomes, however the causal connections between these associations remain to be identified. Materials and Methods: Following IRB approval, patient data were collected on patients from four U.S. centers and platelet levels through and after therapy were considered as indicators of recurrence of disease. In vitro effects of platelets on cancer cell proliferation, apoptosis, and migration were examined. RNA interference was used to query signaling pathways mediating these effects. The necessity of platelet activation for in vitro effect was analyzed. In vivo orthotopic models were used to query the impact of thrombocytosis and thrombocytopenia on the efficacy of cytotoxic chemotherapy, the effect of aspirin on thrombocytosis and cancer, and platelet effect on anti-angiogenic therapy. Results: Platelets were found to increase at the time of diagnosis of ovarian cancer recurrence in a pattern comparable to CA-125. Platelet co-culture increased proliferation, increased migration, and decreased apoptosis in all cell lines tested. RNA interference implicated platelet derived growth factor alpha (PDGFRA) and transforming growth factor beta-receptor 1 (TGFBR1) signaling. Biodistribution studies suggested minimal platelet sequestration of taxanes. Blockade of platelet activation blocked in vitro effects. In vivo, thrombocytosis blocked chemotherapeutic efficacy, thrombocytopenia increased chemotherapeutic efficacy, and aspirin therapy partially blocked the effects of thrombocytosis. In vivo, withdrawal of anti-angiogenic therapy caused loss of therapeutic benefit with evidence of accelerated disease growth. This effect was blocked by use of a small-molecule inhibitor of Focal Adhesion Kinase. Anti-angiogenic therapy was also associated with increased platelet infiltration into tumor that was not seen to the same degree in the control or FAK-inhibitor-treated mice. Conclusions: Platelets are active participants in the growth and metastasis of tumor, both directly and via facilitation of angiogenesis. Blocking platelets, blocking platelet activation, and blocking platelet trafficking into tumor are novel therapeutic avenues supported by this data. Copyright © 2012 Justin Neal Bottsford-Miller, all rights reserved.

A systematic review of personalized therapy in patients with advanced cancer

Background: An increased understanding of the pathogenesis of cancer at the molecular level has led to the development of personalized cancer therapy based on the mutation status of the tumor. Tailoring treatments to genetic signatures has improved treatment outcomes in patients with advanced cancer. We conducted a meta-analysis to provide a quantitative summary of the response to treatment on a phase I clinical trial matched to molecular aberration in patients with advanced solid tumors. ^ Methods: Original studies that reported the results of phase I clinical trials in patients with advanced cancer treated with matched anti-cancer therapies between January 2006 and November 2011 were identified through an extensive search of Medline, Embase, Web of Science and Cochrane Library databases. Odds Ratio (OR) with 95% confidence interval (CI) was estimated for each study to assess the strength of an association between objective response rate (ORR) and mutation status. Random effects model was used to estimate the pooled OR and their 95% CI was derived. Funnel plot was used to assess publication bias. ^ Results: Thirteen studies published between January 2006 and November 2011that reported on responses to matched phase I clinical trials in patients with advanced cancer were included in the meta-analysis. Nine studies reported on the responses seen in 538 of the 835 patients with driver mutations responsive to therapy and seven studies on the responses observed in 234 of the 306 patients with mutation predictive for negative response. Random effects model was used to estimate pooled OR, which was 7.767(95% CI = 4.199 − 14.366; p-value=0.000) in patients with activating mutations that were responsive to therapy and 0.287 (95% CI = 0.119 − 0.694; p-value=0.009) in patients with mutation predictive of negative response. ^ Conclusion: It is evident from the meta-analysis that somatic mutations present in tumor tissue of patients are predictive of responses to therapy in patients with advanced cancer in phase I setting. Plethora of research and growing evidence base indicate that selection of patients based on mutation analysis of the tumor and personalizing therapy is a step forward in the war against cancer.^

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

Comparison of Tumor Shrinkage and Cumulative Dose Distribution for Lung Cancers

Background: The physical characteristic of protons is that they deliver most of their radiation dose to the target volume and deliver no dose to the normal tissue distal to the tumor. Previously, numerous studies have shown unique advantages of proton therapy over intensity-modulated radiation therapy (IMRT) in conforming dose to the tumor and sparing dose to the surrounding normal tissues and the critical structures in many clinical sites. However, proton therapy is known to be more sensitive to treatment uncertainties such as inter- and intra-fractional variations in patient anatomy. To date, no study has clearly demonstrated the effectiveness of proton therapy compared with the conventional IMRT under the consideration of both respiratory motion and tumor shrinkage in non-small cell lung cancer (NSCLC) patients. Purpose: This thesis investigated two questions for establishing a clinically relevant comparison of the two different modalities (IMRT and proton therapy). The first question was whether or not there are any differences in tumor shrinkage between patients randomized to IMRT versus passively scattered proton therapy (PSPT). Tumor shrinkage is considered a standard measure of radiation therapy response that has been widely used to gauge a short-term progression of radiation therapy. The second question was whether or not there are any differences between the planned dose and 5D dose under the influence of inter- and intra-fractional variations in the patient anatomy for both modalities. Methods: A total of 45 patients (25 IMRT patients and 20 PSPT patients) were used to quantify the tumor shrinkage in terms of the change of the primary gross tumor volume (GTVp). All patients were randomized to receive either IMRT or PSPT for NSCLC. Treatment planning goals were identical for both groups. All patients received 5 to 8 weekly repeated 4-dimensional computed tomography (4DCT) scans during the course of radiation treatments. The original GTVp contours were propagated to T50 of weekly 4DCT images using deformable image registration and their absolute volumes were measured. Statistical analysis was performed to compare the distribution of tumor shrinkage between the two population groups. In order to investigate the difference between the planned dose and the 5D dose with consideration of both breathing motion and anatomical change, we re-calculated new dose distributions at every phase of the breathing cycle for all available weekly 4DCT data sets which resulted 50 to 80 individual dose calculations for each of the 7 patients presented in this thesis. The newly calculated dose distributions were then deformed and accumulated to T50 of the planning 4DCT for comparison with the planned dose distribution. Results: At the end of the treatment, both IMRT and PSPT groups showed mean tumor volume reductions of 23.6% ( 19.2%) and 20.9% ( 17.0 %) respectively. Moreover, the mean difference in tumor shrinkage between two groups is 3% along with the corresponding 95% confidence interval, [-8%, 14%]. The rate of tumor shrinkage was highly correlated with the initial tumor volume size. For the planning dose and 5D dose comparison study, all 7 patients showed a mean difference of 1 % in terms of target coverage for both IMRT and PSPT treatment plans. Conclusions: The results of the tumor shrinkage investigation showed no statistically significant difference in tumor shrinkage between the IMRT and PSPT patients, and the tumor shrinkage between the two modalities is similar based on the 95% confidence interval. From the pilot study of comparing the planned dose with the 5D dose, we found the difference to be only 1%. Overall impression of the two modalities in terms of treatment response as measured by the tumor shrinkage and 5D dose under the influence of anatomical change that were designed under the same protocol (i.e. randomized trial) showed similar result.

Comparison of clinical and economic outcomes between high-intensity care and hospice care for the end-of-life melanoma patients

The intensity of care for patients at the end-of-life is increasing in recent years. Publications have focused on intensity of care for many cancers, but none on melanoma patients. Substantial gaps exist in knowledge about intensive care and its alternative, hospice care, among the advanced melanoma patients at the end of life. End-of-life care may be used in quite different patterns and induce both intended and unintended clinical and economic consequences. We used the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked databases to identify patients aged 65 years or older with metastatic melanoma who died between 2000 and 2007. We evaluated trends and associations between sociodemographic and health services characteristics and the use of hospice care, chemotherapy, surgery, and radiation therapy and costs. Survival, end-of-life costs, and incremental cost-effectiveness ratio were evaluated using propensity score methods. Costs were analyzed from the perspective of Medicare in 2009 dollars. In the first journal Article we found increasing use of surgery for patients with metastatic melanoma from 13% in 2000 to 30% in 2007 (P=0.03 for trend), no significant fluctuation in use of chemotherapy (P=0.43) or radiation therapy (P=0.46). Older patients were less likely to receive radiation therapy or chemotherapy. The use of hospice care increased from 61% in 2000 to 79% in 2007 (P =0.07 for trend). Enrollment in short-term (1-3 days) hospice care use increased, while long-term hospice care (≥ 4 days) remained stable. Patients living in the SEER Northeast and South regions were less likely to undergo surgery. Patients enrolled in long-term hospice care used significantly less chemotherapy, surgery and radiation therapy. In the second journal article, of 611 patients identified for this study, 358 (59%) received no hospice care after their diagnosis, 168 (27%) received 1 to 3 days of hospice care, and 85 (14%) received 4 or more days of hospice care. The median survival time was 181 days for patients with no hospice care, 196 days for patients enrolled in hospice for 1 to 3 days, and 300 days for patients enrolled for 4 or more days (log-rank test, P < 0.001). The estimated hazard ratios (HR) between 4 or more days hospice use and survival were similar within the original cohort Cox proportional hazard model (HR, 0.62; 95% CI, 0.49-0.78, P < 0.0001) and the propensity score-matched model (HR, 0.61; 95% CI, 0.47-0.78, P = 0.0001). Patients with ≥ 4 days of hospice care incurred lower end-of-life costs than the other two groups ($14,298 versus $19,380 for the 1- to 3-days hospice care, and $24,351 for patients with no hospice care; p < 0.0001). In conclusion, Surgery and hospice care use increased over the years of this study while the use of chemotherapy and radiation therapy remained consistent for patients diagnosed with metastatic melanoma. Patients diagnosed with advanced melanoma who enrolled in ≥ 4 days of hospice care experienced longer survival than those who had 1-3 days of hospice or no hospice care, and this longer overall survival was accompanied by lower end-of-life costs.^