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      Aminopeptidase Expression in Multiple Myeloma Associates with Disease Progression and Sensitivity to Melflufen

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          Abstract

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          The aims of this study were to investigate aminopeptidase expression in multiple myeloma and to identify the aminopeptidases responsible for the activation of the peptide–drug conjugate melflufen in multiple myeloma. We observed a differential expression of aminopeptidases between relapsed/refractory and newly diagnosed multiple myeloma patients. A higher expression of the aminopeptidase genes XPNPEP1, RNPEP, DPP3, and BLMH in multiple myeloma plasma cells was associated with shorter patient overall survival. The peptide–drug conjugate melflufen was particularly active towards plasma cells from relapsed/refractory multiple myeloma patients. Melflufen could be hydrolyzed to its active form by the aminopeptidases LAP3, LTA4H, RNPEP, and ANPEP, all of which are expressed in multiple myeloma. These results indicate critical roles for aminopeptidases in disease progression and the activity of melflufen in multiple myeloma.

          Abstract

          Multiple myeloma (MM) is characterized by extensive immunoglobulin production leading to an excessive load on protein homeostasis in tumor cells. Aminopeptidases contribute to proteolysis by catalyzing the hydrolysis of amino acids from proteins or peptides and function downstream of the ubiquitin–proteasome pathway. Notably, aminopeptidases can be utilized in the delivery of antibody and peptide-conjugated drugs, such as melflufen, currently in clinical trials. We analyzed the expression of 39 aminopeptidase genes in MM samples from 122 patients treated at Finnish cancer centers and 892 patients from the CoMMpass database. Based on ranked abundance, LAP3, ERAP2, METAP2, TTP2, and DPP7 were highly expressed in MM. ERAP2, XPNPEP1, DPP3, RNPEP, and CTSV were differentially expressed between relapsed/refractory and newly diagnosed MM samples ( p < 0.05). Sensitivity to melflufen was detected ex vivo in 11/15 MM patient samples, and high sensitivity was observed, especially in relapsed/refractory samples. Survival analysis revealed that high expression of XPNPEP1, RNPEP, DPP3, and BLMH ( p < 0.05) was associated with shorter overall survival. Hydrolysis analysis demonstrated that melflufen is a substrate for aminopeptidases LAP3, LTA4H, RNPEP, and ANPEP. The sensitivity of MM cell lines to melflufen was reduced by aminopeptidase inhibitors. These results indicate critical roles of aminopeptidases in disease progression and the activity of melflufen in MM.

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          Most cited references53

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body. Copyright © 2015, American Association for the Advancement of Science.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                26 March 2021
                April 2021
                : 13
                : 7
                : 1527
                Affiliations
                [1 ]Institute for Molecular Medicine Finland-FIMM, HiLIFE–Helsinki Institute of Life Science, iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, 00290 Helsinki, Finland; juho.miettinen@ 123456helsinki.fi (J.J.M.); romika.kumari@ 123456helsinki.fi (R.K.); maiju-emilia.huppunen@ 123456helsinki.fi (M.-E.H.); philipp.sergeev@ 123456helsinki.fi (P.S.); muntasir.mamun@ 123456helsinki.fi (M.M.M.)
                [2 ]Stem Cell Research Unit, Biomedical Center, University of Iceland, 101 Reykjavik, Iceland; gutra@ 123456hi.is (G.A.T.); schepsky@ 123456hi.is (A.S.); tgudjons@ 123456hi.is (T.G.)
                [3 ]Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, 00290 Helsinki, Finland; juha.lievonen@ 123456hus.fi (J.L.); pekka.anttila@ 123456hus.fi (P.A.); raija.silvennoinen@ 123456helsinki.fi (R.S.)
                [4 ]Department of Hematology, Mater Misericordiae University Hospital, D07 Dublin, Ireland; despina.bazou@ 123456ucd.ie (D.B.); pogorman@ 123456mirtireland.com (P.O.)
                [5 ]Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland; paul.dowling@ 123456mu.ie
                [6 ]Oncopeptides AB, 111 53 Stockholm, Sweden; ana.slipicevic@ 123456oncopeptides.com (A.S.); nina.nupponen@ 123456oncopeptides.com (N.N.N.); fredrik.lehmann@ 123456oncopeptides.com (F.L.)
                Author notes
                [* ]Correspondence: caroline.heckman@ 123456helsinki.fi ; Tel.: +358-50-415-6769
                [†]

                These authors equally contributed to this work.

                Author information
                https://orcid.org/0000-0002-3987-1693
                https://orcid.org/0000-0001-6044-0989
                https://orcid.org/0000-0003-3671-477X
                https://orcid.org/0000-0001-9645-9665
                https://orcid.org/0000-0001-8939-1586
                https://orcid.org/0000-0002-4324-8706
                Article
                cancers-13-01527
                10.3390/cancers13071527
                8036322
                33810334
                c81b2c57-29ee-48ba-8697-4ea18008ee20
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 08 January 2021
                : 20 March 2021
                Categories
                Article

                multiple myeloma,aminopeptidase,gene expression,melflufen

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