Intrinsically disordered proteins have dramatically changed the structure-function paradigm of proteins in the 21
century. Resilin is a native elastic insect protein, which features intrinsically ...disordered structure, unusual multi-stimuli responsiveness and outstanding resilience. Advances in computational techniques, polypeptide synthesis methods and modular protein engineering routines have led to the development of novel resilin-like polypeptides (RLPs) including modular RLPs, expanding their applications in tissue engineering, drug delivery, bioimaging, biosensors, catalysis and bioelectronics. However, how the responsive behaviour of RLPs is encoded in the amino acid sequence level remains elusive. This review summarises the milestones of RLPs, and discusses the development of modular RLP-based biomaterials, their current applications, challenges and future perspectives. A perspective of future research is that sequence and responsiveness profiling of RLPs can provide a new platform for the design and development of new modular RLP-based biomaterials with programmable structure, properties and functions.
Multiple myeloma (MM) is a haematological malignancy of plasma cells characterized by substantial intraclonal genetic heterogeneity. Although therapeutic advances made in the past few years have led ...to improved outcomes and longer survival, MM remains largely incurable. Over the past decade, genomic analyses of patient samples have demonstrated that MM is not a single disease but rather a spectrum of haematological entities that all share similar clinical symptoms. Moreover, analyses of samples from monoclonal gammopathy of undetermined significance and smouldering MM have also shown the existence of genetic heterogeneity in precursor stages, in some cases remarkably similar to that of MM. This heterogeneity highlights the need for a greater dissection of underlying disease biology, especially the clonal diversity and molecular events underpinning MM at each stage to enable the stratification of individuals with a high risk of progression. Emerging single-cell sequencing technologies present a superlative solution to delineate the complexity of monoclonal gammopathy of undetermined significance, smouldering MM and MM. In this Review, we discuss how genomics has revealed novel insights into clonal evolution patterns of MM and provide examples from single-cell studies that are beginning to unravel the mutational and phenotypic characteristics of individual cells within the bone marrow tumour, immune microenvironment and peripheral blood. We also address future perspectives on clinical application, proposing that multi-omics single-cell profiling can guide early patient diagnosis, risk stratification and treatment strategies.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Multiple myeloma (MM) is a largely incurable haematological malignancy defined by the clonal proliferation of malignant plasma cells (PCs) within the bone marrow. Clonal heterogeneity has recently ...been established as a feature in MM, however, the subclonal evolution associated with disease progression has not been described. Here, we performed whole-exome sequencing of serial samples from 10 patients, providing new insights into the progression from monoclonal gammopathy of undetermined significance (MGUS) and smouldering MM (SMM), to symptomatic MM. We confirm that intraclonal genetic heterogeneity is a common feature at diagnosis and that the driving events involved in disease progression are more subtle than previously reported. We reveal that MM evolution is mainly characterised by the phenomenon of clonal stability, where the transformed subclonal PC populations identified at MM are already present in the asymptomatic MGUS/SMM stages. Our findings highlight the possibility that PC extrinsic factors may play a role in subclonal evolution and MGUS/SMM to MM progression.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Adipocytes (AdCs) and osteoblasts (OBs) are derived from mesenchymal stem cells (MSCs) and differentiation toward either lineage is both mutually exclusive and transcriptionally controlled. Recent ...studies implicate the mammalian target of rapamycin (mTOR) pathway as important in determining MSC fate, with inhibition of mTOR promoting OB differentiation and suppressing AdC differentiation. mTOR functions within two distinct multiprotein complexes, mTORC1 and mTORC2, each of which contains the unique adaptor protein, raptor or rictor, respectively. While compounds used to study mTOR signaling, such as rapamycin and related analogs, primarily inhibit mTORC1, prolonged exposure can also disrupt mTORC2 function, confounding interpretation of inhibitor studies. As a result, the relative contribution of mTORC1 and mTORC2 to MSC fate determination remains unclear. In this study, we generated primary mouse MSCs deficient in either Rptor (RapKO) or Rictor (RicKO) using the Cre/loxP system. Cre‐mediated deletion of Rptor or Rictor resulted in impaired mTORC1 and mTORC2 signaling, respectively. Under lineage‐inductive culture conditions, RapKO MSCs displayed a reduced capacity to form lipid‐laden AdCs and an increased capacity to form a mineralized matrix. In contrast, RicKO MSCs displayed reduced osteogenic differentiation capacity and enhanced adipogenic differentiation potential. Taken together, our findings reveal distinct roles for mTORC1 and mTORC2 in MSC lineage commitment. Stem Cells 2015;33:1359–1365
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Patients with smoldering multiple myeloma (SMM) are observed until progression, but early treatment may improve outcomes. We conducted a phase II trial of elotuzumab, lenalidomide, and dexamethasone ...(EloLenDex) in patients with high-risk SMM and performed single-cell RNA and T cell receptor (TCR) sequencing on 149 bone marrow (BM) and peripheral blood (PB) samples from patients and healthy donors (HDs). We find that early treatment with EloLenDex is safe and effective and provide a comprehensive characterization of alterations in immune cell composition and TCR repertoire diversity in patients. We show that the similarity of a patient’s immune cell composition to that of HDs may have prognostic relevance at diagnosis and after treatment and that the abundance of granzyme K (GZMK)+ CD8+ effector memory T (TEM) cells may be associated with treatment response. Last, we uncover similarities between immune alterations observed in the BM and PB, suggesting that PB-based immune profiling may have diagnostic and prognostic utility.
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•EloLenDex is associated with 4-year PFS of 89% in patients with high-risk SMM•Immune reactivity, post-therapy immune normalization are associated with longer PFS•Higher abundance of GZMK+ cytotoxic T cells is associated with longer PFS•Blood-based immune profiling detects immune dysregulation associated with disease
Sklavenitis-Pistofidis et al. report results of a phase II trial of EloLenDex in patients with high-risk smoldering multiple myeloma and use single-cell RNA sequencing to identify biomarkers of outcomes. They show that immune cell composition affects progression-free survival and that blood-based immune profiling can detect immune alterations observed in the bone marrow.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Multiple myeloma (MM) develops from well-defined precursor stages; however, invasive bone marrow (BM) biopsy limits screening and monitoring strategies for patients. We enumerated circulating tumor ...cells (CTC) from 261 patients (84 monoclonal gammopathy of undetermined significance, 155 smoldering multiple myeloma, and 22 MM), with neoplastic cells detected in 84%. We developed a novel approach, MinimuMM-seq, which enables the detection of translocations and copy-number abnormalities through whole-genome sequencing of highly pure CTCs. Application to CTCs in a cohort of 51 patients, 24 with paired BM, was able to detect 100% of clinically reported BM biopsy events and could replace molecular cytogenetics for diagnostic yield and risk classification. Longitudinal sampling of CTCs in 8 patients revealed major clones could be tracked in the blood, with clonal evolution and shifting dynamics of subclones over time. Our findings provide proof of concept that CTC detection and genomic profiling could be used clinically for monitoring and managing disease in MM.
In this study, we established an approach enabling the enumeration and sequencing of CTCs to replace standard molecular cytogenetics. CTCs harbored the same pathognomonic MM abnormalities as BM plasma cells. Longitudinal sampling of serial CTCs was able to track clonal dynamics over time and detect the emergence of high-risk genetic subclones. This article is highlighted in the In This Issue feature, p. 247.
Summary
Multiple Myeloma (MM) is a haematological malignancy characterised by the clonal expansion of plasma cells (PCs) within the bone marrow. Despite advances in therapy, MM remains a largely ...incurable disease with a median survival of 6 years. In almost all cases, the development of MM is preceded by the benign PC condition Monoclonal Gammopathy of Undetermined Significance (MGUS). Recent studies show that the transformation of MGUS to MM is associated with complex genetic changes. Understanding how these changes contribute to evolution will present targets for clinical intervention. We discuss three models of MM evolution; the linear, the expansionist and the intraclonal heterogeneity models. Of particular interest is the intraclonal heterogeneity model. Here, distinct populations of MM PCs carry differing combinations of genetic mutations. Acquisition of additional mutations can contribute to subclonal lineages where “driver” mutations may influence selective pressure and dominance, and “passenger” mutations are neutral in their effects. Furthermore, studies show that clinical intervention introduces additional selective pressure on tumour cells and can influence subclone survival, leading to therapy resistance. This review discusses how Next Generation Sequencing approaches are revealing critical insights into the genetics of MM development, disease progression and treatment. MM disease progression will illuminate possible mechanisms underlying the tumour.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
•Genomic analysis of MF identifies alterations associated with high risk of progression and shorter overall survival.•Clonal evolution of MF shows acquisition of JUNB, gain of 10p15.1 (IL2RA/IL15RA), ...or del12p13.1 (CDKN1B) at progression.
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Mycosis fungoides (MF) is the most prevalent primary cutaneous T-cell lymphoma, with an indolent or aggressive course and poor survival. The pathogenesis of MF remains unclear, and prognostic factors in the early stages are not well established. Here, we characterized the most recurrent genomic alterations using whole-exome sequencing of 67 samples from 48 patients from Lille University Hospital (France), including 18 sequential samples drawn across stages of the malignancy. Genomic data were analyzed on the Broad Institute’s Terra bioinformatics platform. We found that gain7q, gain10p15.1 (IL2RA and IL15RA), del10p11.22 (ZEB1), or mutations in JUNB and TET2 are associated with high-risk disease stages. Furthermore, gain7q, gain10p15.1 (IL2RA and IL15RA), del10p11.22 (ZEB1), and del6q16.3 (TNFAIP3) are coupled with shorter survival. Del6q16.3 (TNFAIP3) was a risk factor for progression in patients at low risk. By analyzing the clonal heterogeneity and the clonal evolution of the cohort, we defined different phylogenetic pathways of the disease with acquisition of JUNB, gain10p15.1 (IL2RA and IL15RA), or del12p13.1 (CDKN1B) at progression. These results establish the genomics and clonality of MF and identify potential patients at risk of progression, independent of their clinical stage.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Introduction
Multiple Myeloma (MM) develops from well-defined precursors Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM), where patients remain stable ...or may unknowingly rapidly progress. Bone marrow (BM) biopsies are not routine for precursor disease management, and precursor patients are limited to monitoring few proteins within peripheral blood (PB) for signs of progressive disease. Deep proteome profiling of PB circulating proteins may help track disease; however, the dynamic range of the plasma proteome has limited the depth of detection for MS-based proteomics without first depleting abundant proteins and fractionating the samples after digestion to peptides. Technological advancements in multiplex immunoassays with low cross-reactivity and off-target events have enabled plasma profiling for disease stage classification, defining high-risk disease features, and novel therapeutic target discovery. Here, we perform the first comprehensive plasma proteomic profiling study on patients across the MM disease continuum and longitudinal sequential samples from progressive and stable disease.
Methods
We carried out high-throughput plasma proteomic profiling for approximately 3000 proteins simultaneously using the Olink® Explore 3072 library and Proximity Extension Assay (PEA) technology. Targeted proteins are recognized by multiplexed, matched pairs of antibodies labelled with unique DNA oligonucleotides that upon binding come into proximity, hybridize, and are extended to generate a unique sequence for protein identification with NextGen DNA sequencing.
We profiled 423 PB plasma samples from 348 individuals, including MGUS (n=67), SMM (n=179), MM (n=44), and healthy controls (n=58). Sequential samples from patients with progressive disease (n=27) and patients with stable disease with matched clinical follow-up time were also profiled. Precursor defined samples from progressors ranged 1.03-5.88 yrs prior to diagnosis and were untreated in the precursor setting, while MM disease samples were also collected prior to any active disease therapy. Patients had a median clinical follow-up time of 7.05 years. T-tests, ANOVAs, and a linear mixed effect (LME) model were used to identify proteins that change across disease stages, progression status, and time. Results were adjusted for multiple testing using the Benjamini-Hochberg Method.
Results
We identified 751 significantly dysregulated proteins with the majority upregulated in progressive disease. We captured circulating levels of proteins highly expressed on the surface of plasma cells, including CD38, SDC1, BCMA and SLAMF7, highlighting the utility of PEA technology to monitor clinically-relevant targets for which monoclonal antibodies, antibody-drug conjugates, CAR-T and BiTE therapies are being developed. We identified proteins that significantly distinguished MGUS, SMM, and NDMM from healthy donors (n=222, 423 and 494), where increasing B-cell maturation antigen (BCMA) was a significant classifier and positive control. Consistent with previous findings, baseline BCMA levels were also significantly elevated in SMM-MM progressors vs. SMM non-progressors, further supporting the potential utility of BCMA measurements during routine blood tests of precursor MM patients. Proinflammatory cytokines were also identified, including IL1, IL5, IL6, IL16, and IL18, known to create a BM environment that promotes malignant cell development by suppressing the microenvironment, promoting cellular adhesion, or increasing angiogenesis. Four novel proteins that are vital for calcium homeostasis and integrin-mediated cell adhesion significantly increased from healthy to MM and were also significantly elevated in SMM progressors vs. SMM non-progressors, nominating these proteins as candidate biomarkers of high-risk disease.
Conclusion
We performed the most comprehensive plasma proteomics study to date, which characterized disease stage proteomes and identified candidate high-risk disease biomarkers in longitudinal progressor samples. Further advancements are underway to validate the accuracy levels of the novel candidates, test the performance of a classification model that recognizes disease stage-specific proteins, and determine how best to integrate proteins into current MM risk stratification models.
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IJS, IMTLJ, NUK, PNG, SAZU, UL, UM, UPUK, ZRSKP
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