Comparison Log
2024-12-01 01:52:38.455742
mwtab Python Library Version: 1.2.5
Source:      https://www.metabolomicsworkbench.org/rest/study/analysis_id/AN000627/mwtab/...
Study ID:    ST000391
Analysis ID: AN000627
Status:      Inconsistent

Sections "STUDY" contain missmatched items: {('STUDY_SUMMARY', 'Lung cancer has been the leading cause of cancer death in the United States and worldwide for many decades. Low dose spiral computerized tomography (LDCT) is likely to become the first approved screening and early detection test in the upcoming year, but it is plagued by a high false-positive rate. There is a need to develop complementary screening and early detection tools. A blood-based lung cancer signature is an attractive solution. Given that our knowledge of the molecular biology of smoking-induced lung cancer has dramatically increased over the past few years, this approach is plausible. To date, this effort has been focused on the identification of genomic and proteomic signatures with limited success. A broader strategy that incorporates additional cancer traits is needed. It is well recognized that wide coverage of cellular metabolism in cancer could help provide valuable diagnostic biomarkers and potentially identify molecular drivers of tumorigenesis. Recent advances in mass spectrometry have enabled comprehensive metabolomic analyses of lipids, carbohydrates, amino acids, and nucleotides within a variety of biologic matrices. Early evidence from metabolomic investigation of cancer has identified many altered biochemical profiles. However, to date, there have been few investigations of lung cancer, and most studies have looked at blood plasma or were limited by small sample sizes with mixed histologies. In the current investigation, gas chromatography time-offlight mass spectrometry (GC-TOF) was used to measure 462 lipid, carbohydrate, amino acid, organic acid, and nucleotide metabolites in 39 malignant and nonmalignant lung tissue pairs from current or former smokers with early stage adenocarcinoma. This study cohort represents patient characteristics and tumor histology most likely to be detected with LDCT screening. We hypothesize that identification of cancer-induced cellular and tissue level biochemical changes can offer a robust method for identification of candidate circulating biomarkers and improve our understanding of biochemical changes involved in adenocarcinoma tumorigenesis.'), ('STUDY_SUMMARY', 'Lung cancer has been the leading cause of cancer death in the United States and worldwide for many decades. Low dose spiral computerized tomography (LDCT) is likely to become the first approved screening and early detection test in the upcoming year, but it is plagued by a high false-positive rate. There is a need to develop complementary screening and early detection tools. A blood-based "lung cancer" signature is an attractive solution. Given that our knowledge of the molecular biology of smoking-induced lung cancer has dramatically increased over the past few years, this approach is plausible. To date, this effort has been focused on the identification of genomic and proteomic signatures with limited success. A broader strategy that incorporates additional cancer traits is needed. It is well recognized that wide coverage of cellular metabolism in cancer could help provide valuable diagnostic biomarkers and potentially identify molecular drivers of tumorigenesis. Recent advances in mass spectrometry have enabled comprehensive metabolomic analyses of lipids, carbohydrates, amino acids, and nucleotides within a variety of biologic matrices. Early evidence from metabolomic investigation of cancer has identified many altered biochemical profiles. However, to date, there have been few investigations of lung cancer, and most studies have looked at blood plasma or were limited by small sample sizes with mixed histologies. In the current investigation, gas chromatography time-offlight mass spectrometry (GC-TOF) was used to measure 462 lipid, carbohydrate, amino acid, organic acid, and nucleotide metabolites in 39 malignant and nonmalignant lung tissue pairs from current or former smokers with early stage adenocarcinoma. This study cohort represents patient characteristics and tumor histology most likely to be detected with LDCT screening. We hypothesize that identification of cancer-induced cellular and tissue level biochemical changes can offer a robust method for identification of candidate circulating biomarkers and improve our understanding of biochemical changes involved in adenocarcinoma tumorigenesis.')}
Sections "PROJECT" contain missmatched items: {('PROJECT_SUMMARY', 'Lung cancer has been the leading cause of cancer death in the United States and worldwide for many decades. Low dose spiral computerized tomography (LDCT) is likely to become the first approved screening and early detection test in the upcoming year, but it is plagued by a high false-positive rate. There is a need to develop complementary screening and early detection tools. A blood-based lung cancer signature is an attractive solution. Given that our knowledge of the molecular biology of smoking-induced lung cancer has dramatically increased over the past few years, this approach is plausible. To date, this effort has been focused on the identification of genomic and proteomic signatures with limited success. A broader strategy that incorporates additional cancer traits is needed. It is well recognized that wide coverage of cellular metabolism in cancer could help provide valuable diagnostic biomarkers and potentially identify molecular drivers of tumorigenesis. Recent advances in mass spectrometry have enabled comprehensive metabolomic analyses of lipids, carbohydrates, amino acids, and nucleotides within a variety of biologic matrices. Early evidence from metabolomic investigation of cancer has identified many altered biochemical profiles. However, to date, there have been few investigations of lung cancer, and most studies have looked at blood plasma or were limited by small sample sizes with mixed histologies. In the current investigation, gas chromatography time-offlight mass spectrometry (GC-TOF) was used to measure 462 lipid, carbohydrate, amino acid, organic acid, and nucleotide metabolites in 39 malignant and nonmalignant lung tissue pairs from current or former smokers with early stage adenocarcinoma. This study cohort represents patient characteristics and tumor histology most likely to be detected with LDCT screening. We hypothesize that identification of cancer-induced cellular and tissue level biochemical changes can offer a robust method for identification of candidate circulating biomarkers and improve our understanding of biochemical changes involved in adenocarcinoma tumorigenesis.'), ('PROJECT_SUMMARY', 'Lung cancer has been the leading cause of cancer death in the United States and worldwide for many decades. Low dose spiral computerized tomography (LDCT) is likely to become the first approved screening and early detection test in the upcoming year, but it is plagued by a high false-positive rate. There is a need to develop complementary screening and early detection tools. A blood-based "lung cancer" signature is an attractive solution. Given that our knowledge of the molecular biology of smoking-induced lung cancer has dramatically increased over the past few years, this approach is plausible. To date, this effort has been focused on the identification of genomic and proteomic signatures with limited success. A broader strategy that incorporates additional cancer traits is needed. It is well recognized that wide coverage of cellular metabolism in cancer could help provide valuable diagnostic biomarkers and potentially identify molecular drivers of tumorigenesis. Recent advances in mass spectrometry have enabled comprehensive metabolomic analyses of lipids, carbohydrates, amino acids, and nucleotides within a variety of biologic matrices. Early evidence from metabolomic investigation of cancer has identified many altered biochemical profiles. However, to date, there have been few investigations of lung cancer, and most studies have looked at blood plasma or were limited by small sample sizes with mixed histologies. In the current investigation, gas chromatography time-offlight mass spectrometry (GC-TOF) was used to measure 462 lipid, carbohydrate, amino acid, organic acid, and nucleotide metabolites in 39 malignant and nonmalignant lung tissue pairs from current or former smokers with early stage adenocarcinoma. This study cohort represents patient characteristics and tumor histology most likely to be detected with LDCT screening. We hypothesize that identification of cancer-induced cellular and tissue level biochemical changes can offer a robust method for identification of candidate circulating biomarkers and improve our understanding of biochemical changes involved in adenocarcinoma tumorigenesis.')}
'Metabolites' section of 'MS_METABOLITE_DATA' block do not match.