Splicing Factor Transcript Abundance in Saliva as a Diagnostic Tool for Breast Cancer
Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from sa...
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Published in | Genes Vol. 11; no. 8; p. 880 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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03.08.2020
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ISSN | 2073-4425 2073-4425 |
DOI | 10.3390/genes11080880 |
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Abstract | Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups (p value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients. |
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AbstractList | Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups (
p
value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients. Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups (p value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients. Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups (p value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients.Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups (p value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients. Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups ( value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients. |
Audience | Academic |
Author | Morgenstern, Guy Nevo, Yuval Monas, Liza Kay, Gillian Temper, Mark Basheer, Reham Maimon, Ofra Ben-Hur, Asa Salton, Maayan Peretz, Tamar Bentata, Mercedes Granit Mizrahi, Avital |
AuthorAffiliation | 3 Sharett Institute of Oncology, Hadassah-Hebrew University Medical Center, Hebrew University Medical School, Jerusalem 9112102, Israel; granit@hadassah.org.il (A.G.M.); markt@hadassah.org.il (M.T.); ofra406@hadassah.org.il (O.M.); lizam@hadassah.org.il (L.M.); basir@hadassah.org.il (R.B.); tamary@hadassah.org.il (T.P.) 2 Info-CORE, Bioinformatics Unit of the I-CORE at the Hebrew University of Jerusalem and Hadassah Medical Center, Jerusalem 9112102, Israel; yuval.nevo@mail.huji.ac.il 1 Department of Biochemistry and Molecular Biology, The Institute for Medical Research Israel–Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112102, Israel; mercedes.bentata@mail.huji.ac.il (M.B.); morgenstern.guy@gmail.com (G.M.); gilliank@ekmd.huji.ac.il (G.K.) 4 Department of Computer Science, Colorado State University, Fort Collins, CO 80523, USA; asa@cs.colostate.edu |
AuthorAffiliation_xml | – name: 1 Department of Biochemistry and Molecular Biology, The Institute for Medical Research Israel–Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112102, Israel; mercedes.bentata@mail.huji.ac.il (M.B.); morgenstern.guy@gmail.com (G.M.); gilliank@ekmd.huji.ac.il (G.K.) – name: 2 Info-CORE, Bioinformatics Unit of the I-CORE at the Hebrew University of Jerusalem and Hadassah Medical Center, Jerusalem 9112102, Israel; yuval.nevo@mail.huji.ac.il – name: 3 Sharett Institute of Oncology, Hadassah-Hebrew University Medical Center, Hebrew University Medical School, Jerusalem 9112102, Israel; granit@hadassah.org.il (A.G.M.); markt@hadassah.org.il (M.T.); ofra406@hadassah.org.il (O.M.); lizam@hadassah.org.il (L.M.); basir@hadassah.org.il (R.B.); tamary@hadassah.org.il (T.P.) – name: 4 Department of Computer Science, Colorado State University, Fort Collins, CO 80523, USA; asa@cs.colostate.edu |
Author_xml | – sequence: 1 givenname: Mercedes surname: Bentata fullname: Bentata, Mercedes – sequence: 2 givenname: Guy surname: Morgenstern fullname: Morgenstern, Guy – sequence: 3 givenname: Yuval surname: Nevo fullname: Nevo, Yuval – sequence: 4 givenname: Gillian orcidid: 0000-0003-0966-2388 surname: Kay fullname: Kay, Gillian – sequence: 5 givenname: Avital surname: Granit Mizrahi fullname: Granit Mizrahi, Avital – sequence: 6 givenname: Mark surname: Temper fullname: Temper, Mark – sequence: 7 givenname: Ofra surname: Maimon fullname: Maimon, Ofra – sequence: 8 givenname: Liza surname: Monas fullname: Monas, Liza – sequence: 9 givenname: Reham surname: Basheer fullname: Basheer, Reham – sequence: 10 givenname: Asa orcidid: 0000-0001-8269-6942 surname: Ben-Hur fullname: Ben-Hur, Asa – sequence: 11 givenname: Tamar surname: Peretz fullname: Peretz, Tamar – sequence: 12 givenname: Maayan orcidid: 0000-0001-8812-5577 surname: Salton fullname: Salton, Maayan |
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Keywords | saliva splicing factors breast cancer diagnosis |
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SubjectTerms | Adult Age Aged Alternative splicing Annotations Biomarkers Biomarkers, Tumor - genetics Biomarkers, Tumor - metabolism Breast cancer breast neoplasms Breast Neoplasms - diagnosis Breast Neoplasms - genetics Breast Neoplasms - metabolism Diagnosis diagnostic techniques Female Gene expression genes Genetic aspects Genetic transcription Genomes Health aspects Humans Isoforms Mammography messenger RNA Metabolites MicroRNAs Middle Aged neoplasm cells patients Proteins Quality RNA Splicing Factors - genetics RNA Splicing Factors - metabolism RNA, Messenger - genetics RNA, Messenger - metabolism Saliva Saliva - metabolism screening Splicing factors Transcription United States women Womens health |
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Title | Splicing Factor Transcript Abundance in Saliva as a Diagnostic Tool for Breast Cancer |
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