Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials
The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM ti...
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creator | Danziger, Samuel A McConnell, Mark Gockley, Jake Young, Mary H Rosenthal, Adam Schmitz, Frank Reiss, David J Farmer, Phil Alapat, Daisy V Singh, Amrit Ashby, Cody Bauer, Michael Ren, Yan Smith, Kelsie Couto, Suzana S van Rhee, Frits Davies, Faith Zangari, Maurizio Petty, Nathan Orlowski, Robert Z Dhodapkar, Madhav V Copeland, Wilbert B Fox, Brian Hoering, Antje Fitch, Alison Newhall, Katie Barlogie, Bart Trotter, Matthew W B Hershberg, Robert M Walker, Brian A Dervan, Andrew P Ratushny, Alexander V Morgan, Gareth J |
description | The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases.
Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5-29, 49-69 versus 70-82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI -1 to 31, 92-120 versus 113-129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6-36, 49-73 versus 74-90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies.
In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in p |
doi_str_mv | 10.1371/journal.pmed.1003323 |
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Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5-29, 49-69 versus 70-82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI -1 to 31, 92-120 versus 113-129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6-36, 49-73 versus 74-90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies.
In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies.</description><identifier>ISSN: 1549-1676</identifier><identifier>ISSN: 1549-1277</identifier><identifier>EISSN: 1549-1676</identifier><identifier>DOI: 10.1371/journal.pmed.1003323</identifier><identifier>PMID: 33147277</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Algorithms ; Asymptomatic ; Biology and Life Sciences ; Biopsy ; Bone marrow ; Bone Marrow - pathology ; Cancer ; CD8 antigen ; Clinical outcomes ; Clinical trials ; Cohort analysis ; Cohort Studies ; Computer applications ; Development and progression ; Estimates ; Female ; Gene expression ; Genomes ; Granulocytes ; Health aspects ; Humans ; Immunohistochemistry ; Informed consent ; Leukocytes (granulocytic) ; Lymphocytes T ; Machine learning ; Male ; Medicine and Health Sciences ; Middle Aged ; Monocytes ; Multiple myeloma ; Multiple Myeloma - diagnosis ; Multiple Myeloma - drug therapy ; Multiple Myeloma - pathology ; Mutation ; Neutrophils ; Patients ; Physiological aspects ; Plasma ; Prognosis ; Review boards ; Thalidomide ; Transplants & implants ; Tumor Burden ; Tumor Microenvironment ; Tumors</subject><ispartof>PLoS medicine, 2020-11, Vol.17 (11), p.e1003323-e1003323</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Danziger et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Danziger et al 2020 Danziger et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c764t-15a8aba763005aadb5d3318b3546c854e2b50da1aec5a423859b9a3f55315a8f3</citedby><cites>FETCH-LOGICAL-c764t-15a8aba763005aadb5d3318b3546c854e2b50da1aec5a423859b9a3f55315a8f3</cites><orcidid>0000-0002-8615-6254 ; 0000-0002-5669-414X ; 0000-0003-0566-3607 ; 0000-0001-9959-1282 ; 0000-0003-1448-1346 ; 0000-0001-6116-1017 ; 0000-0002-1701-4084 ; 0000-0002-9616-6341 ; 0000-0003-4843-8645 ; 0000-0002-4709-3027 ; 0000-0003-0978-2291 ; 0000-0002-9361-0283 ; 0000-0002-4271-6360 ; 0000-0003-2921-6107 ; 0000-0001-7993-5308 ; 0000-0002-6482-8654 ; 0000-0002-9090-0277 ; 0000-0003-2498-7295</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641353/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641353/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33147277$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Kawano, Yawara</contributor><creatorcontrib>Danziger, Samuel A</creatorcontrib><creatorcontrib>McConnell, Mark</creatorcontrib><creatorcontrib>Gockley, Jake</creatorcontrib><creatorcontrib>Young, Mary H</creatorcontrib><creatorcontrib>Rosenthal, Adam</creatorcontrib><creatorcontrib>Schmitz, Frank</creatorcontrib><creatorcontrib>Reiss, David J</creatorcontrib><creatorcontrib>Farmer, Phil</creatorcontrib><creatorcontrib>Alapat, Daisy V</creatorcontrib><creatorcontrib>Singh, Amrit</creatorcontrib><creatorcontrib>Ashby, Cody</creatorcontrib><creatorcontrib>Bauer, Michael</creatorcontrib><creatorcontrib>Ren, Yan</creatorcontrib><creatorcontrib>Smith, Kelsie</creatorcontrib><creatorcontrib>Couto, Suzana S</creatorcontrib><creatorcontrib>van Rhee, Frits</creatorcontrib><creatorcontrib>Davies, Faith</creatorcontrib><creatorcontrib>Zangari, Maurizio</creatorcontrib><creatorcontrib>Petty, Nathan</creatorcontrib><creatorcontrib>Orlowski, Robert Z</creatorcontrib><creatorcontrib>Dhodapkar, Madhav V</creatorcontrib><creatorcontrib>Copeland, Wilbert B</creatorcontrib><creatorcontrib>Fox, Brian</creatorcontrib><creatorcontrib>Hoering, Antje</creatorcontrib><creatorcontrib>Fitch, Alison</creatorcontrib><creatorcontrib>Newhall, Katie</creatorcontrib><creatorcontrib>Barlogie, Bart</creatorcontrib><creatorcontrib>Trotter, Matthew W B</creatorcontrib><creatorcontrib>Hershberg, Robert M</creatorcontrib><creatorcontrib>Walker, Brian A</creatorcontrib><creatorcontrib>Dervan, Andrew P</creatorcontrib><creatorcontrib>Ratushny, Alexander V</creatorcontrib><creatorcontrib>Morgan, Gareth J</creatorcontrib><title>Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials</title><title>PLoS medicine</title><addtitle>PLoS Med</addtitle><description>The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases.
Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5-29, 49-69 versus 70-82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI -1 to 31, 92-120 versus 113-129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6-36, 49-73 versus 74-90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies.
In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies.</description><subject>Adult</subject><subject>Algorithms</subject><subject>Asymptomatic</subject><subject>Biology and Life Sciences</subject><subject>Biopsy</subject><subject>Bone marrow</subject><subject>Bone Marrow - pathology</subject><subject>Cancer</subject><subject>CD8 antigen</subject><subject>Clinical outcomes</subject><subject>Clinical trials</subject><subject>Cohort analysis</subject><subject>Cohort Studies</subject><subject>Computer applications</subject><subject>Development and progression</subject><subject>Estimates</subject><subject>Female</subject><subject>Gene expression</subject><subject>Genomes</subject><subject>Granulocytes</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Immunohistochemistry</subject><subject>Informed consent</subject><subject>Leukocytes (granulocytic)</subject><subject>Lymphocytes T</subject><subject>Machine learning</subject><subject>Male</subject><subject>Medicine and Health Sciences</subject><subject>Middle Aged</subject><subject>Monocytes</subject><subject>Multiple myeloma</subject><subject>Multiple Myeloma - diagnosis</subject><subject>Multiple Myeloma - drug therapy</subject><subject>Multiple Myeloma - pathology</subject><subject>Mutation</subject><subject>Neutrophils</subject><subject>Patients</subject><subject>Physiological aspects</subject><subject>Plasma</subject><subject>Prognosis</subject><subject>Review boards</subject><subject>Thalidomide</subject><subject>Transplants & implants</subject><subject>Tumor Burden</subject><subject>Tumor 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marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials</title><author>Danziger, Samuel A ; McConnell, Mark ; Gockley, Jake ; Young, Mary H ; Rosenthal, Adam ; Schmitz, Frank ; Reiss, David J ; Farmer, Phil ; Alapat, Daisy V ; Singh, Amrit ; Ashby, Cody ; Bauer, Michael ; Ren, Yan ; Smith, Kelsie ; Couto, Suzana S ; van Rhee, Frits ; Davies, Faith ; Zangari, Maurizio ; Petty, Nathan ; Orlowski, Robert Z ; Dhodapkar, Madhav V ; Copeland, Wilbert B ; Fox, Brian ; Hoering, Antje ; Fitch, Alison ; Newhall, Katie ; Barlogie, Bart ; Trotter, Matthew W B ; Hershberg, Robert M ; Walker, Brian A ; Dervan, Andrew P ; Ratushny, Alexander V ; Morgan, Gareth J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c764t-15a8aba763005aadb5d3318b3546c854e2b50da1aec5a423859b9a3f55315a8f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adult</topic><topic>Algorithms</topic><topic>Asymptomatic</topic><topic>Biology and Life Sciences</topic><topic>Biopsy</topic><topic>Bone marrow</topic><topic>Bone Marrow - pathology</topic><topic>Cancer</topic><topic>CD8 antigen</topic><topic>Clinical outcomes</topic><topic>Clinical trials</topic><topic>Cohort analysis</topic><topic>Cohort Studies</topic><topic>Computer applications</topic><topic>Development and progression</topic><topic>Estimates</topic><topic>Female</topic><topic>Gene expression</topic><topic>Genomes</topic><topic>Granulocytes</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Immunohistochemistry</topic><topic>Informed consent</topic><topic>Leukocytes (granulocytic)</topic><topic>Lymphocytes T</topic><topic>Machine learning</topic><topic>Male</topic><topic>Medicine and Health Sciences</topic><topic>Middle Aged</topic><topic>Monocytes</topic><topic>Multiple myeloma</topic><topic>Multiple Myeloma - diagnosis</topic><topic>Multiple Myeloma - drug therapy</topic><topic>Multiple Myeloma - pathology</topic><topic>Mutation</topic><topic>Neutrophils</topic><topic>Patients</topic><topic>Physiological aspects</topic><topic>Plasma</topic><topic>Prognosis</topic><topic>Review boards</topic><topic>Thalidomide</topic><topic>Transplants & implants</topic><topic>Tumor Burden</topic><topic>Tumor Microenvironment</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Danziger, Samuel A</creatorcontrib><creatorcontrib>McConnell, Mark</creatorcontrib><creatorcontrib>Gockley, Jake</creatorcontrib><creatorcontrib>Young, Mary H</creatorcontrib><creatorcontrib>Rosenthal, Adam</creatorcontrib><creatorcontrib>Schmitz, Frank</creatorcontrib><creatorcontrib>Reiss, David J</creatorcontrib><creatorcontrib>Farmer, Phil</creatorcontrib><creatorcontrib>Alapat, Daisy V</creatorcontrib><creatorcontrib>Singh, Amrit</creatorcontrib><creatorcontrib>Ashby, Cody</creatorcontrib><creatorcontrib>Bauer, Michael</creatorcontrib><creatorcontrib>Ren, Yan</creatorcontrib><creatorcontrib>Smith, Kelsie</creatorcontrib><creatorcontrib>Couto, Suzana S</creatorcontrib><creatorcontrib>van Rhee, Frits</creatorcontrib><creatorcontrib>Davies, Faith</creatorcontrib><creatorcontrib>Zangari, Maurizio</creatorcontrib><creatorcontrib>Petty, Nathan</creatorcontrib><creatorcontrib>Orlowski, Robert Z</creatorcontrib><creatorcontrib>Dhodapkar, Madhav V</creatorcontrib><creatorcontrib>Copeland, Wilbert B</creatorcontrib><creatorcontrib>Fox, Brian</creatorcontrib><creatorcontrib>Hoering, Antje</creatorcontrib><creatorcontrib>Fitch, Alison</creatorcontrib><creatorcontrib>Newhall, Katie</creatorcontrib><creatorcontrib>Barlogie, Bart</creatorcontrib><creatorcontrib>Trotter, Matthew W B</creatorcontrib><creatorcontrib>Hershberg, Robert M</creatorcontrib><creatorcontrib>Walker, Brian A</creatorcontrib><creatorcontrib>Dervan, Andrew P</creatorcontrib><creatorcontrib>Ratushny, Alexander V</creatorcontrib><creatorcontrib>Morgan, Gareth J</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><collection>PLoS Medicine</collection><jtitle>PLoS medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Danziger, Samuel A</au><au>McConnell, Mark</au><au>Gockley, Jake</au><au>Young, Mary H</au><au>Rosenthal, Adam</au><au>Schmitz, Frank</au><au>Reiss, David J</au><au>Farmer, Phil</au><au>Alapat, Daisy V</au><au>Singh, Amrit</au><au>Ashby, Cody</au><au>Bauer, Michael</au><au>Ren, Yan</au><au>Smith, Kelsie</au><au>Couto, Suzana S</au><au>van Rhee, Frits</au><au>Davies, Faith</au><au>Zangari, Maurizio</au><au>Petty, Nathan</au><au>Orlowski, Robert Z</au><au>Dhodapkar, Madhav V</au><au>Copeland, Wilbert B</au><au>Fox, Brian</au><au>Hoering, Antje</au><au>Fitch, Alison</au><au>Newhall, Katie</au><au>Barlogie, Bart</au><au>Trotter, Matthew W B</au><au>Hershberg, Robert M</au><au>Walker, Brian A</au><au>Dervan, Andrew P</au><au>Ratushny, Alexander V</au><au>Morgan, Gareth J</au><au>Kawano, Yawara</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials</atitle><jtitle>PLoS medicine</jtitle><addtitle>PLoS Med</addtitle><date>2020-11-04</date><risdate>2020</risdate><volume>17</volume><issue>11</issue><spage>e1003323</spage><epage>e1003323</epage><pages>e1003323-e1003323</pages><issn>1549-1676</issn><issn>1549-1277</issn><eissn>1549-1676</eissn><abstract>The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases.
Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5-29, 49-69 versus 70-82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI -1 to 31, 92-120 versus 113-129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6-36, 49-73 versus 74-90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies.
In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33147277</pmid><doi>10.1371/journal.pmed.1003323</doi><orcidid>https://orcid.org/0000-0002-8615-6254</orcidid><orcidid>https://orcid.org/0000-0002-5669-414X</orcidid><orcidid>https://orcid.org/0000-0003-0566-3607</orcidid><orcidid>https://orcid.org/0000-0001-9959-1282</orcidid><orcidid>https://orcid.org/0000-0003-1448-1346</orcidid><orcidid>https://orcid.org/0000-0001-6116-1017</orcidid><orcidid>https://orcid.org/0000-0002-1701-4084</orcidid><orcidid>https://orcid.org/0000-0002-9616-6341</orcidid><orcidid>https://orcid.org/0000-0003-4843-8645</orcidid><orcidid>https://orcid.org/0000-0002-4709-3027</orcidid><orcidid>https://orcid.org/0000-0003-0978-2291</orcidid><orcidid>https://orcid.org/0000-0002-9361-0283</orcidid><orcidid>https://orcid.org/0000-0002-4271-6360</orcidid><orcidid>https://orcid.org/0000-0003-2921-6107</orcidid><orcidid>https://orcid.org/0000-0001-7993-5308</orcidid><orcidid>https://orcid.org/0000-0002-6482-8654</orcidid><orcidid>https://orcid.org/0000-0002-9090-0277</orcidid><orcidid>https://orcid.org/0000-0003-2498-7295</orcidid><oa>free_for_read</oa></addata></record> |
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identifier | ISSN: 1549-1676 |
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language | eng |
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source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Public Library of Science (PLoS) |
subjects | Adult Algorithms Asymptomatic Biology and Life Sciences Biopsy Bone marrow Bone Marrow - pathology Cancer CD8 antigen Clinical outcomes Clinical trials Cohort analysis Cohort Studies Computer applications Development and progression Estimates Female Gene expression Genomes Granulocytes Health aspects Humans Immunohistochemistry Informed consent Leukocytes (granulocytic) Lymphocytes T Machine learning Male Medicine and Health Sciences Middle Aged Monocytes Multiple myeloma Multiple Myeloma - diagnosis Multiple Myeloma - drug therapy Multiple Myeloma - pathology Mutation Neutrophils Patients Physiological aspects Plasma Prognosis Review boards Thalidomide Transplants & implants Tumor Burden Tumor Microenvironment Tumors |
title | Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials |
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