microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers

microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-s...
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Autor*in:	Carmelo Tibaldi [verfasserIn] Stefania Carasi Gabriele Minuti Federico Cappuzzo Greta Alì Lorenza Landi Carlo M. Croce Pierluigi Gasparini Francesca Lovat Gabriella Fontanini Luciano Cascione Antonio Chella Armida D’Incecco Matteo Fassan

Format:	Artikel
Sprache:	Englisch

Erschienen:	2015

Rechteinformationen:	Nutzungsrecht: © COPYRIGHT 2015 National Academy of Sciences

Schlagwörter:	Care and treatment Patient outcomes Complications and side effects Research Development and progression Lung cancer Tissue Ribonucleic acid--RNA Lymphomas Mutation Rodents

Übergeordnetes Werk:	Enthalten in: Proceedings of the National Academy of Sciences of the United States of America - Washington, DC : NAS, 1877, 112(2015), 48, Seite 14924
Übergeordnetes Werk:	volume:112 ; year:2015 ; number:48 ; pages:14924

Links:	Volltext Link aufrufen Link aufrufen Link aufrufen

DOI / URN:	10.1073/pnas.1520329112

Katalog-ID:	OLC1970292822

Internformat


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650		4	\|a Care and treatment
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700	0		\|a Luciano Cascione \|4 oth
700	0		\|a Antonio Chella \|4 oth
700	0		\|a Armida D’Incecco \|4 oth
700	0		\|a Matteo Fassan \|4 oth
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allfields	10.1073/pnas.1520329112 doi PQ20160211 (DE-627)OLC1970292822 (DE-599)GBVOLC1970292822 (PRQ)g1827-ff2356c65df92c88e5bdfb52afd310aa157ef273a919b904871f92530036cd810 (KEY)0583363920150000112004814924micrornaclassifiersarepowerfuldiagnosticprognostic DE-627 ger DE-627 rakwb eng 500 DNB 570 AVZ LING fid BIODIV fid Carmelo Tibaldi verfasserin aut microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens. Nutzungsrecht: © COPYRIGHT 2015 National Academy of Sciences Care and treatment Patient outcomes Complications and side effects Research Development and progression Lung cancer Tissue Ribonucleic acid--RNA Lymphomas Mutation Rodents Stefania Carasi oth Gabriele Minuti oth Federico Cappuzzo oth Greta Alì oth Lorenza Landi oth Carlo M. Croce oth Pierluigi Gasparini oth Francesca Lovat oth Gabriella Fontanini oth Luciano Cascione oth Antonio Chella oth Armida D’Incecco oth Matteo Fassan oth Enthalten in Proceedings of the National Academy of Sciences of the United States of America Washington, DC : NAS, 1877 112(2015), 48, Seite 14924 (DE-627)129505269 (DE-600)209104-5 (DE-576)014909189 0027-8424 nnns volume:112 year:2015 number:48 pages:14924 http://dx.doi.org/10.1073/pnas.1520329112 Volltext http://www.pnas.org/content/112/48/14924.abstract http://www.ncbi.nlm.nih.gov/pubmed/26627242 http://search.proquest.com/docview/1748595728 GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-LING FID-BIODIV SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-FOR SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-MAT SSG-OPC-FOR GBV_ILN_40 GBV_ILN_59 AR 112 2015 48 14924
spelling	10.1073/pnas.1520329112 doi PQ20160211 (DE-627)OLC1970292822 (DE-599)GBVOLC1970292822 (PRQ)g1827-ff2356c65df92c88e5bdfb52afd310aa157ef273a919b904871f92530036cd810 (KEY)0583363920150000112004814924micrornaclassifiersarepowerfuldiagnosticprognostic DE-627 ger DE-627 rakwb eng 500 DNB 570 AVZ LING fid BIODIV fid Carmelo Tibaldi verfasserin aut microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens. Nutzungsrecht: © COPYRIGHT 2015 National Academy of Sciences Care and treatment Patient outcomes Complications and side effects Research Development and progression Lung cancer Tissue Ribonucleic acid--RNA Lymphomas Mutation Rodents Stefania Carasi oth Gabriele Minuti oth Federico Cappuzzo oth Greta Alì oth Lorenza Landi oth Carlo M. Croce oth Pierluigi Gasparini oth Francesca Lovat oth Gabriella Fontanini oth Luciano Cascione oth Antonio Chella oth Armida D’Incecco oth Matteo Fassan oth Enthalten in Proceedings of the National Academy of Sciences of the United States of America Washington, DC : NAS, 1877 112(2015), 48, Seite 14924 (DE-627)129505269 (DE-600)209104-5 (DE-576)014909189 0027-8424 nnns volume:112 year:2015 number:48 pages:14924 http://dx.doi.org/10.1073/pnas.1520329112 Volltext http://www.pnas.org/content/112/48/14924.abstract http://www.ncbi.nlm.nih.gov/pubmed/26627242 http://search.proquest.com/docview/1748595728 GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-LING FID-BIODIV SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-FOR SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-MAT SSG-OPC-FOR GBV_ILN_40 GBV_ILN_59 AR 112 2015 48 14924
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allfieldsGer	10.1073/pnas.1520329112 doi PQ20160211 (DE-627)OLC1970292822 (DE-599)GBVOLC1970292822 (PRQ)g1827-ff2356c65df92c88e5bdfb52afd310aa157ef273a919b904871f92530036cd810 (KEY)0583363920150000112004814924micrornaclassifiersarepowerfuldiagnosticprognostic DE-627 ger DE-627 rakwb eng 500 DNB 570 AVZ LING fid BIODIV fid Carmelo Tibaldi verfasserin aut microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens. Nutzungsrecht: © COPYRIGHT 2015 National Academy of Sciences Care and treatment Patient outcomes Complications and side effects Research Development and progression Lung cancer Tissue Ribonucleic acid--RNA Lymphomas Mutation Rodents Stefania Carasi oth Gabriele Minuti oth Federico Cappuzzo oth Greta Alì oth Lorenza Landi oth Carlo M. Croce oth Pierluigi Gasparini oth Francesca Lovat oth Gabriella Fontanini oth Luciano Cascione oth Antonio Chella oth Armida D’Incecco oth Matteo Fassan oth Enthalten in Proceedings of the National Academy of Sciences of the United States of America Washington, DC : NAS, 1877 112(2015), 48, Seite 14924 (DE-627)129505269 (DE-600)209104-5 (DE-576)014909189 0027-8424 nnns volume:112 year:2015 number:48 pages:14924 http://dx.doi.org/10.1073/pnas.1520329112 Volltext http://www.pnas.org/content/112/48/14924.abstract http://www.ncbi.nlm.nih.gov/pubmed/26627242 http://search.proquest.com/docview/1748595728 GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-LING FID-BIODIV SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-FOR SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-MAT SSG-OPC-FOR GBV_ILN_40 GBV_ILN_59 AR 112 2015 48 14924
allfieldsSound	10.1073/pnas.1520329112 doi PQ20160211 (DE-627)OLC1970292822 (DE-599)GBVOLC1970292822 (PRQ)g1827-ff2356c65df92c88e5bdfb52afd310aa157ef273a919b904871f92530036cd810 (KEY)0583363920150000112004814924micrornaclassifiersarepowerfuldiagnosticprognostic DE-627 ger DE-627 rakwb eng 500 DNB 570 AVZ LING fid BIODIV fid Carmelo Tibaldi verfasserin aut microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens. Nutzungsrecht: © COPYRIGHT 2015 National Academy of Sciences Care and treatment Patient outcomes Complications and side effects Research Development and progression Lung cancer Tissue Ribonucleic acid--RNA Lymphomas Mutation Rodents Stefania Carasi oth Gabriele Minuti oth Federico Cappuzzo oth Greta Alì oth Lorenza Landi oth Carlo M. Croce oth Pierluigi Gasparini oth Francesca Lovat oth Gabriella Fontanini oth Luciano Cascione oth Antonio Chella oth Armida D’Incecco oth Matteo Fassan oth Enthalten in Proceedings of the National Academy of Sciences of the United States of America Washington, DC : NAS, 1877 112(2015), 48, Seite 14924 (DE-627)129505269 (DE-600)209104-5 (DE-576)014909189 0027-8424 nnns volume:112 year:2015 number:48 pages:14924 http://dx.doi.org/10.1073/pnas.1520329112 Volltext http://www.pnas.org/content/112/48/14924.abstract http://www.ncbi.nlm.nih.gov/pubmed/26627242 http://search.proquest.com/docview/1748595728 GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-LING FID-BIODIV SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-FOR SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-MAT SSG-OPC-FOR GBV_ILN_40 GBV_ILN_59 AR 112 2015 48 14924
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source	Enthalten in Proceedings of the National Academy of Sciences of the United States of America 112(2015), 48, Seite 14924 volume:112 year:2015 number:48 pages:14924
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author	Carmelo Tibaldi
spellingShingle	Carmelo Tibaldi ddc 500 ddc 570 fid LING fid BIODIV misc Care and treatment misc Patient outcomes misc Complications and side effects misc Research misc Development and progression misc Lung cancer misc Tissue misc Ribonucleic acid--RNA misc Lymphomas misc Mutation misc Rodents microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers
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title	microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers
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title_full	microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers
author_sort	Carmelo Tibaldi
journal	Proceedings of the National Academy of Sciences of the United States of America
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title_sort	microrna classifiers are powerful diagnostic/prognostic tools in alk-, egfr-, and kras-driven lung cancers
title_auth	microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers
abstract	microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens.
abstractGer	microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens.
abstract_unstemmed	microRNAs (miRNAs) can act as oncosuppressors or oncogenes, induce chemoresistance or chemosensitivity, and are major posttranscriptional gene regulators. Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens.
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title_short	microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers
url	http://dx.doi.org/10.1073/pnas.1520329112 http://www.pnas.org/content/112/48/14924.abstract http://www.ncbi.nlm.nih.gov/pubmed/26627242 http://search.proquest.com/docview/1748595728
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author2	Stefania Carasi Gabriele Minuti Federico Cappuzzo Greta Alì Lorenza Landi Carlo M. Croce Pierluigi Gasparini Francesca Lovat Gabriella Fontanini Luciano Cascione Antonio Chella Armida D’Incecco Matteo Fassan
author2Str	Stefania Carasi Gabriele Minuti Federico Cappuzzo Greta Alì Lorenza Landi Carlo M. Croce Pierluigi Gasparini Francesca Lovat Gabriella Fontanini Luciano Cascione Antonio Chella Armida D’Incecco Matteo Fassan
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up_date	2024-07-03T14:41:46.177Z
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Anaplastic lymphoma kinase (ALK), EGF receptor (EGFR), and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) are major drivers of non-small cell lung cancer (NSCLC). The aim of this study was to assess the miRNA profiles of NSCLCs driven by translocated ALK, mutant EGFR, or mutant KRAS to find driver-specific diagnostic and prognostic miRNA signatures. A total of 85 formalin-fixed, paraffin-embedded samples were considered: 67 primary NSCLCs and 18 matched normal lung tissues. Of the 67 primary NSCLCs, 17 were echinoderm microtubule-associated protein-like 4-ALK translocated (ALK(+)) lung cancers; the remaining 50 were not (ALK(-)). Of the 50 ALK(-) primary NSCLCs, 24 were EGFR and KRAS mutation-negative (i.e., WT; triple negative); 11 were mutant EGFR (EGFR(+)), and 15 were mutant KRAS (KRAS(+)). We developed a diagnostic classifier that shows how miR-1253, miR-504, and miR-26a-5p expression levels can classify NSCLCs as ALK-translocated, mutant EGFR, or mutant KRAS versus mutation-free. We also generated a prognostic classifier based on miR-769-5p and Let-7d-5p expression levels that can predict overall survival. This classifier showed better performance than the commonly used classifiers based on mutational status. Although it has several limitations, this study shows that miRNA signatures and classifiers have great potential as powerful, cost-effective next-generation tools to improve and complement current genetic tests. Further studies of these miRNAs can help define their roles in NSCLC biology and in identifying best-performing chemotherapy regimens.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: © COPYRIGHT 2015 National Academy of Sciences</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Care and treatment</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Patient outcomes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Complications and side effects</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Research</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Development and progression</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Lung cancer</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Tissue</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ribonucleic acid--RNA</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Lymphomas</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mutation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Rodents</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Stefania Carasi</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Gabriele Minuti</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Federico Cappuzzo</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Greta Alì</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lorenza Landi</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Carlo M. 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microRNA classifiers are powerful diagnostic/prognostic tools in ALK-, EGFR-, and KRAS-driven lung cancers

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