Search

Additional file 2 : Table S2. MutSig 2CV v3.1 analysis of significantly mutated collagen genes in STAD TCGA cohort. Data downloaded from Firebrowse.

Additional file 6 : Figure S1. Alteration frequencies of collagens in ACRG and HK/Pfizer datasets. A. Alteration frequencies of sequenced collagens in other stomach cancer cohorts. B. Kaplan-Meier analysis of COl11A1, COL5, COL4, COL6 mutations in the ACRG targeted sequencing dataset compared to the same set of collagen genes in the TCGA cohort. Figure S2. Survival analysis of somatic mutations in each collagen gene. A. Kaplan Maier analysis of tumors with any type of mutation in each collagen gene across the whole STAD TCGA cohort. Tumors with the designated collagen mutation are in red. Wild-type tumors are in blue. P-values determined by log-rank test. B. Kaplan Maier analysis of tumors with truncation mutations in each collagen gene across the whole STAD TCGA cohort. C. Kaplan Maier analysis of tumors with any type of mutation in each collagen gene in MSIH cases. D. Kaplan Maier analysis of tumors with truncation mutation in each collagen gene in MSIH cases. Figure S3. Identification of combinations of collagens genes associated with overall survival relative to background. A. All mutations across the whole TCGA cohort. B. Representative examples of combinations of 2 collagens associated with overall survival. C. Combinations of all mutations in MSS tumors only. D. Combinations of all mutations in MSIH tumors only. E. Example of collagen genes with truncation mutations most frequently associated with overall survival when combined, classify MSIH tumors into high and low overall survival risk. Figure S4. Collagen mutations have MSIH and MSS context dependent differences in overall survival. Mutations in COL5A3 and COL14A1 have different associations in MSIH and MSS tumors even though the total number of mutations is similar. Figure S5. MSIH and MSS tumors have distinct microenvironments in TCGA. A. MSI status was associated with outcome in ACRG but not in TCGA. B. Comparison of MSIH and MSS stomach tumors by pre-ranked GSEA reveals differences in expression. Each heatmap plots the Normalized Enrichment Scores (NES) from the GSEA. NABA ECM gene sets were expressed higher in MSS tumors compared to MSIH tumors. Many immune cell expression signatures including cytotoxic cells were expressed higher in MSIH tumors compared to MSS tumors. B cells were expressed higher in MSS tumors. The majority of cancer hallmark expression signatures were expressed significantly higher in MSIH tumors compared to MSS tumors. Figure S6. Pre-ranked GSEA of collagen mutation combinations in Table S4 for the whole TCGA STAD cohort shows consistent impact for each mutation combination. A. Hallmarks for combinations with both missense and truncation mutations. B. The NABA and immune signature genes sets for combinations with both missense and truncation mutations. C. Hallmark, NABA, and immune signature gene sets for combinations with just truncation mutations. D. Clustering of hallmark gene sets for tumors with missense mutations only in the whole TCGA cohort showed significant difference for the EMT hallmark relative to overall survival. P-value calculated by Kolmogorov-Smirnov. Figure S7. In MSS cases, pre-ranked GSEA of tumors with either a missense or truncation mutation combination as listed in Table S4 show impact of collagen mutations on pathways some of which are correlated with overall survival. A. For all mutations in MSS cases, some hallmarks such as EMT were associated with overall survival as shown in the heat map and box plot. P-value calculated by Kolmogorov-Smirnov. B. NABA ECM and immune signature gene sets in MSS tumors. Basement membrane and macrophage signature gene sets were among the gene sets most associated with overall survival, showing consistent downregulation in tumors with mutant collagens and higher expression in wild-type tumors. P-value calculated by Kolmogorov-Smirnov. Figure S8. In MSIH cases, pre-ranked GSEA of tumors with either a missense or truncation mutation combination as listed in Table S4 show impact of collagen mutations on pathways some of which are correlated with overall survival. A. Clustering of hallmark gene sets partitions tumors with collagen combinations by overall survival. Box plot shows the significant difference in the EMT hallmark as defined by combinations associated with high or low risk of overall survival. B. NABA gene sets showing large differences in Basement Membrane and ECM Affiliated gene sets relative to overall survival. C. Immune cell signature gene sets showing large difference in Tregs and Macrophage expression signatures. P-value calculated by Kolmogorov-Smirnov. Figure S9. In MSIH cases, pre-ranked GSEA of tumors with only missense mutation combinations as listed in Table S4 show impact of collagen mutations on pathways some of which are correlated with overall survival. A. Hallmark gene sets. B. NABA ECM sets. C. Immune cell gene signatures. P-value calculated by Kolmogorov-Smirnov. Figure S10. In MSIH cases, pre-ranked GSEA of tumors with only truncation mutation combinations as listed in Table S4 show impact of collagen mutations on pathways some of which are correlated with overall survival. A. Hallmark gene sets. B. NABA ECM and immune cell signature gene sets. P-value calculated by Kolmogorov-Smirnov. Figure S11. COL7A1 is expressed in some tumor cells in STAD. Representative images of COL7A1 protein and RNA expression in stomach adenocarcinoma. A. Immunohistochemistry (A, C, E) and in situ hybridization (B, D, F) for COL7. Stromal localization in C, E, D, and F, and mixed stromal and carcinoma localization (at white arrows; A, B). B. Higher magnification of panels A and B from S7A showing expression by IHC in panel A and ISH in panel B of COL7A1 in epithelial regions. The arrow shows ISH signal in tumor cells. C. Representative images at higher power of COL7A1 protein expression by IHC in the epithelium and stroma. D. Representative image of COL7A1 protein expression in normal human skin. Note the line of expression in the ECM between the dermal and epidermal layers (red arrow). Cells expressing COL7A1 show cytoplasmic signal as they are overexpressing COL7A1 to be secreted to form the ���anchorage��� line. Figure S12. Comparison of pathological germline and somatic mutations in STAD in three collagens. Comparison of the distribution of mutations across each gene and a lollipop plot mapping the somatic mutations to the protein domains. A. COL1A1 and COL1A2. B. COL4A1 and COL4A2. C. COL5A1 and COL5A2.

Additional file 1 : Table S1. Collagen family for collagens of interest in stomach cancer.

Additional file 5 : Table S5. Summary of COL7A1 protein expression in stomach tumors from Rhode Island Hospital as assessed by immunohistochemical staining.

We consider the problem of constructing bounds on the average treatment effect (ATE) when unmeasured confounders exist but have bounded influence. Specifically, we assume that omitted confounders could not change the odds of treatment for any unit by more than a fixed factor. We derive the sharp partial identification bounds implied by this assumption by leveraging distributionally robust optimization, and we propose estimators of these bounds with several novel robustness properties. The first is double sharpness: our estimators consistently estimate the sharp ATE bounds when one of two nuisance parameters is misspecified and achieve semiparametric efficiency when all nuisance parameters are suitably consistent. The second is double validity: even when most nuisance parameters are misspecified, our estimators still provide valid but possibly conservative bounds for the ATE and our Wald confidence intervals remain valid even when our estimators are not asymptotically normal. As a result, our estimators provide a highly credible method for sensitivity analysis of causal inferences.

Additional file 1.

This thesis makes new observations of market phenomena for various commodities and trading strategies centered around these observations. In particular, our results imply that many aspects of the commodities markets, from delivery markets to producers and consumer derivative based ETFs can be modeled eectively using nancial engineering techniques. Chapter 2 examines what drives the returns of gold miner stocks and ETFs. Inspired by our real options model, we construct a method to dynamically replicate gold miner stocks using two factors: a spot gold ETF and a market equity portfolio. We find that our real options approach can explain a significant portion of the drivers of firm implied gold leverage. Chapter 3 studies commodity exchange-traded funds (ETFs). From empirical data, we find that many commodity leveraged ETFs underperform significantly against our constructed dynamic benchmark, and we quantify such a discrepancy via the novel idea of realized effective fee. Finally, we consider a number of trading strategies and examine their performance by backtesting with historical price data. Chapter 4 studies the phenomenon of non-convergence between futures and spot prices in the grains market. In our proposed approach, we incorporate stochastic spot price and storage cost, and solve an optimal double stopping problem to understand shipping certificate prices. Our new models for stochastic storage rates explain the spot-futures premium.

On orbit assembly of spacecraft has historically involved human intensive robotic operations. To facilitate this construction process the U.S. Naval Academy is augmenting its current robotic arm capabilities with the Intelligent Space Assembly Robot (ISAR) program. This research is aimed to identify key requirements and select a 3D camera for use in ISAR's robotic operations. The research has three stages: 1) requirements identification, 2) ground testing and 3) an on orbit demonstration. The camera requirements were identified based on the current robotic arm capacity of the previous version of the arms, and three cameras (Intel R200, DuoM, and Tara) were chosen for further testing. Terrestrial testing consisted of demonstrating capabilities of each camera by taking and processing photos of a test satellite that represented common spacecraft features. The second phase of testing was a comparison of real and measured depth data using CloudCompare software. This paper also details the design modifications required to incorporate the updated sensors as well as an outline for ground testing of the system. The on orbit demonstration of the system’s capabilities is planned to occur in 2019 with the launch of ISAR to the interior of the International Space Station as a payload science experiment.