scholarly journals Identification of three immune molecular subtypes associated with immune profiles, immune checkpoints, and clinical outcome in multiple myeloma

2021 ◽  
Author(s):  
Guangtao Gao ◽  
Mengkun Fang ◽  
Peipei Xu ◽  
Bing Chen
Keyword(s):  
Multiple Myeloma ◽  
Clinical Outcome ◽  
Molecular Subtypes ◽  
Immune Checkpoints

B171 Polymorphism of TNF-a Predicts Clinical Outcome in Multiple Myeloma Based on Thalidomide Regimens

2009 ◽  
Vol 9 ◽  
pp. S107
Author(s):  
J Du ◽  
C Zhang ◽  
H Jiang ◽  
Z Yuan ◽  
W Fu ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Clinical Outcome

scholarly journals The expression pattern of small nucleolar and small Cajal body-specific RNAs characterizes distinct molecular subtypes of multiple myeloma

2012 ◽  
Vol 2 (11) ◽  
pp. e96-e96 ◽  
Author(s):  
D Ronchetti ◽  
K Todoerti ◽  
G Tuana ◽  
L Agnelli ◽  
L Mosca ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Expression Pattern ◽  
Molecular Subtypes ◽  
Cajal Body

Response Assignment Using Hevylite Correlates With Clinical Outcome in Multiple Myeloma

2017 ◽  
Vol 17 (1) ◽  
pp. e44-e45
Author(s):  
Mauricette Michallet ◽  
Colette Chapuis-Cellier ◽  
Christine Lombard ◽  
Mohamad Sobh ◽  
Thomas Dejoie ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Clinical Outcome

scholarly journals The Prognostic Value of the m6A Score in Multiple Myeloma Based on Machine Learning

2021 ◽  
Vol 1 (3) ◽  
pp. 77-87
Author(s):  
Gong Xiao ◽  
Qiongjing Yuan ◽  
Wei Wang
Keyword(s):  
Multiple Myeloma ◽  
Cancer Progression ◽  
Risk Score ◽  
Prognostic Value ◽  
Risk Model ◽  
Cox Regression ◽  
Microarray Dataset ◽  
Immune Checkpoints ◽  
Bioinformatics Analyses ◽  
Cox Regression Analysis

Background: Multiple myeloma (MM) is one of the most common cancers of the blood system. N6-methyladenosine (m6A) plays an important role in cancer progression. We aimed to investigate the prognostic relevance of the m6A score in multiple myeloma through a series of bioinformatics analyses. Methods: The microarray dataset GSE4581 and GSE57317 used in this study were downloaded from the Gene Expression Omnibus (GEO) database. The m6A score was calculated using the GSVA package. The Random forests, univariate Cox regression analysis and Lasso analyses were performed for the differentially expressed genes (DEGs). Kaplan–Meier analysis and an ROC curve were used to diagnose the effectiveness of the model. Results: The GSVA R software package was used to predict the function. A total of 21 m6A genes were obtained, and 286 DEGs were identified between high and low m6A score groups. The risk model was constructed and composed of PRX, LBR, RB1, FBXL19-AS1, ARSK, MFAP3L, SLC44A3, UNC119 and SHCBP1. Functional analysis of risk score showed that with the increase in the risk score, Activated CD4 T cells, Memory B cells and Type 2 T helper cells were highly infiltrated. Conclusions: Immune checkpoints such as HMGB1, TGFB1, CXCL9 and HAVCR2 were significantly positively correlated with the risk score. We believe that the m6A score has a certain prognostic value in multiple myeloma.

scholarly journals The Complex Interaction between the Tumor Micro-Environment and Immune Checkpoints in Breast Cancer

Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1205 ◽  
Author(s):  
Vanessa Barriga ◽  
Nyanbol Kuol ◽  
Kulmira Nurgali ◽  
Vasso Apostolopoulos
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Cancer Progression ◽  
Molecular Subtypes ◽  
Breast Cancer Subtype ◽  
Complex Interaction ◽  
Immune Checkpoints ◽  
Expression Studies ◽  
Cancer Subtype ◽  
Insight Into

The progression of breast cancer and its association with clinical outcome and treatment remain largely unexplored. Accumulating data has highlighted the interaction between cells of the immune system and the tumor microenvironment in cancer progression, and although studies have identified multiple facets of cancer progression within the development of the tumor microenvironment (TME) and its constituents, there is lack of research into the associations between breast cancer subtype and staging. Current literature has provided insight into the cells and pathways associated with breast cancer progression through expression analysis. However, there is lack of co-expression studies between immune pathways and cells of the TME that form pro-tumorigenic relationships contributing to immune-evasion. We focus on the immune checkpoint and TME elements that influence cancer progression, particularly studies in molecular subtypes of breast cancer.

A new ten-gene risk fraction model serving as prognostic indicator for clinical outcome of multiple myeloma

Tumor Biology ◽  
2016 ◽  
Vol 37 (12) ◽  
pp. 15967-15975 ◽  
Author(s):  
Ai-Xin Hu ◽  
Zhi-Yong Huang ◽  
Ping Liu ◽  
Tian Xiang ◽  
Shi Yan ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Clinical Outcome ◽  
Prognostic Indicator

Abstract 4762: Deficient double strand breaks repair of bone marrow plasma cells correlates with better clinical outcome of multiple myeloma patients

2014 ◽  
Author(s):  
Maria Gkotzamanidou ◽  
Masood Shammas ◽  
Evangelos Terpos ◽  
Sathees C. Raghavan ◽  
Kenneth C. Anderson ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Bone Marrow ◽  
Clinical Outcome ◽  
Plasma Cells ◽  
Double Strand Breaks ◽  
Strand Breaks ◽  
Bone Marrow Plasma

scholarly journals Conversion of ATP to adenosine by CD39 and CD73 in multiple myeloma can be successfully targeted together with adenosine receptor A2A blockade

2020 ◽  
Vol 8 (1) ◽  
pp. e000610 ◽  
Author(s):  
Rui Yang ◽  
Samah Elsaadi ◽  
Kristine Misund ◽  
Pegah Abdollahi ◽  
Esten Nymoen Vandsemb ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
T Cell ◽  
Stromal Cells ◽  
Adenosine Receptor ◽  
Immune Checkpoints ◽  
Incurable Cancer ◽  
Myeloma Cells ◽  
Hematological Cancers ◽  
Adenosine Receptor A2a

BackgroundPD1/PDL1-directed therapies have been unsuccessful for multiple myeloma (MM), an incurable cancer of plasma cells in the bone marrow (BM). Therefore, other immune checkpoints such as extracellular adenosine and its immunosuppressive receptor should be considered. CD39 and CD73 convert extracellular ATP to adenosine, which inhibits T-cell effector functions via the adenosine receptor A2A (A2AR). We set out to investigate whether blocking the adenosine pathway could be a therapy for MM.MethodsExpression of CD39 and CD73 on BM cells from patients and T-cell proliferation were determined by flow cytometry and adenosine production by Liquid chromatograpy-mass spectrometry (HPCL/MS). ENTPD1 (CD39) mRNA expression was determined on myeloma cells from patients enrolled in the publicly available CoMMpass study. Transplantable 5T33MM myeloma cells were used to determine the effect of inhibiting CD39, CD73 and A2AR in mice in vivo.ResultsElevated level of adenosine was found in BM plasma of MM patients. Myeloma cells from patients expressed CD39, and high gene expression indicated reduced survival. CD73 was found on leukocytes and stromal cells in the BM. A CD39 inhibitor, POM-1, and an anti-CD73 antibody inhibited adenosine production and reduced T-cell suppression in vitro in coculture of myeloma and stromal cells. Blocking the adenosine pathway in vivo with a combination of Sodium polyoxotungstate (POM-1), anti-CD73, and the A2AR antagonist AZD4635 activated immune cells, increased interferon gamma production, and reduced the tumor load in a murine model of MM.ConclusionsOur data suggest that the adenosine pathway can be successfully targeted in MM and blocking this pathway could be an alternative to PD1/PDL1 inhibition for MM and other hematological cancers. Inhibitors of the adenosine pathway are available. Some are in clinical trials and they could thus reach MM patients fairly rapidly.

scholarly journals The impact of circulating suppressor cells in multiple myeloma patients on clinical outcome of DLIs

2015 ◽  
Vol 50 (6) ◽  
pp. 822-828 ◽  
Author(s):  
L E Franssen ◽  
N W C J van de Donk ◽  
M E Emmelot ◽  
M W H Roeven ◽  
N Schaap ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Clinical Outcome ◽  
Suppressor Cells ◽  
The Impact
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