A Retrospective Matched Cohort Study Evaluating the Effects of Percutaneous Endoscopic Gastrostomy Feeding Tubes on Nutritional Status and Survival in Patients With Advanced Gastroesophageal Malignancies Undergoing Systemic Anti-Cancer Therapy

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Description

Background: Many patients with cancer or other systemic illnesses can experience malnutrition. One way to mitigate malnutrition is by insertion of a percutaneous endoscopic gastrostomy feeding tube (PEG tube). The goal of this retrospective matched cohort study is to evaluate if

Background: Many patients with cancer or other systemic illnesses can experience malnutrition. One way to mitigate malnutrition is by insertion of a percutaneous endoscopic gastrostomy feeding tube (PEG tube). The goal of this retrospective matched cohort study is to evaluate if PEG tube placement improved nutritional status and overall survival (OS) in advanced gastroesophageal (GE) cancer patients who are undergoing anti-neoplastic therapy.

Methods: GE cancer patients who were treated and evaluated by a nutritionist and had at least 2 nutritionist follow-up visits were identified. Patients with PEG tube were matched to patients that did not undergo PEG placement (non-PEG). Clinical characteristics, GE symptoms reported at nutrition follow-up visits, and OS were recorded.

Results: 20 PEG and 18 non-PEG cases met criteria for further analyses. After correction for multiple testing, there were no OS differences between PEG and non-PEG, treatment naive and previously treated. However, PEG esophageal carcinoma has statistically significant inferior OS compared with non-PEG esophageal carcinoma. PEG placement did not significantly reduce the proportion of patients with weight loss between the initial nutrition assessment and 12-week follow-up.

Conclusions: In this small study, PEG placement had inferior OS outcome for GE esophageal carcinoma, no improvement in OS for other evaluated groups, and did not reduce weight loss between baseline and 12-week follow-up. Unless there is prospective randomized trial that can show superiority of PEG placement in this population, PEG placement in this group cannot be endorsed.

Date Created
2017-11-29
Agent

Genome-Wide Characterization of Pancreatic Adenocarcinoma Patients Using Next Generation Sequencing

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Description

Pancreatic adenocarcinoma (PAC) is among the most lethal malignancies. While research has implicated multiple genes in disease pathogenesis, identification of therapeutic leads has been difficult and the majority of currently available therapies provide only marginal benefit. To address this issue,

Pancreatic adenocarcinoma (PAC) is among the most lethal malignancies. While research has implicated multiple genes in disease pathogenesis, identification of therapeutic leads has been difficult and the majority of currently available therapies provide only marginal benefit. To address this issue, our goal was to genomically characterize individual PAC patients to understand the range of aberrations that are occurring in each tumor. Because our understanding of PAC tumorigenesis is limited, evaluation of separate cases may reveal aberrations, that are less common but may provide relevant information on the disease, or that may represent viable therapeutic targets for the patient. We used next generation sequencing to assess global somatic events across 3 PAC patients to characterize each patient and to identify potential targets. This study is the first to report whole genome sequencing (WGS) findings in paired tumor/normal samples collected from 3 separate PAC patients. We generated on average 132 billion mappable bases across all patients using WGS, and identified 142 somatic coding events including point mutations, insertion/deletions, and chromosomal copy number variants. We did not identify any significant somatic translocation events. We also performed RNA sequencing on 2 of these patients' tumors for which tumor RNA was available to evaluate expression changes that may be associated with somatic events, and generated over 100 million mapped reads for each patient. We further performed pathway analysis of all sequencing data to identify processes that may be the most heavily impacted from somatic and expression alterations. As expected, the KRAS signaling pathway was the most heavily impacted pathway (P<0.05), along with tumor-stroma interactions and tumor suppressive pathways. While sequencing of more patients is needed, the high resolution genomic and transcriptomic information we have acquired here provides valuable information on the molecular composition of PAC and helps to establish a foundation for improved therapeutic selection.

Date Created
2012-10-10
Agent

Identification of Somatic Mutations in Cancer Through Bayesian-Based Analysis of Sequenced Genome Pairs

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Description

Background: The field of cancer genomics has rapidly adopted next-generation sequencing (NGS) in order to study and characterize malignant tumors with unprecedented resolution. In particular for cancer, one is often trying to identify somatic mutations--changes specific to a tumor and

Background: The field of cancer genomics has rapidly adopted next-generation sequencing (NGS) in order to study and characterize malignant tumors with unprecedented resolution. In particular for cancer, one is often trying to identify somatic mutations--changes specific to a tumor and not within an individual's germline. However, false positive and false negative detections often result from lack of sufficient variant evidence, contamination of the biopsy by stromal tissue, sequencing errors, and the erroneous classification of germline variation as tumor-specific.

Results: We have developed a generalized Bayesian analysis framework for matched tumor/normal samples with the purpose of identifying tumor-specific alterations such as single nucleotide mutations, small insertions/deletions, and structural variation. We describe our methodology, and discuss its application to other types of paired-tissue analysis such as the detection of loss of heterozygosity as well as allelic imbalance. We also demonstrate the high level of sensitivity and specificity in discovering simulated somatic mutations, for various combinations of a) genomic coverage and b) emulated heterogeneity.

Conclusion: We present a Java-based implementation of our methods named Seurat, which is made available for free academic use. We have demonstrated and reported on the discovery of different types of somatic change by applying Seurat to an experimentally-derived cancer dataset using our methods; and have discussed considerations and practices regarding the accurate detection of somatic events in cancer genomes. Seurat is available at https://sites.google.com/site/seuratsomatic.

Date Created
2013-05-04
Agent