Single-cell profiling in multiple myeloma: insights, problems, and promises

2.

Paiva

B

,

Gutiérrez

NC

,

Rosiñol

L

, et al.

High-risk cytogenetics and persistent minimal residual disease by multiparameter flow cytometry predict unsustained complete response after autologous stem cell transplantation in multiple myeloma

.

Blood

.

2012

;

119

(

3

):

687

-

691

.

3.

Guillaumet-Adkins

A

,

Rodriguez-Esteban

G

,

Mereu

E

, et al.

Single-cell transcriptome conservation in cryopreserved cells and tissues

.

Genome Biol

.

2017

;

18

(

1

):

45

.

4.

Wu

SZ

,

Roden

DL

,

Al-Eryani

G

, et al.

Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

.

Genome Med

.

2021

;

13

(

1

):

81

.

5.

Madissoon

E

,

Wilbrey-Clark

A

,

Miragaia

RJ

, et al.

scRNA-seq assessment of the human lung, spleen, and esophagus tissue stability after cold preservation

.

Genome Biol

.

2019

;

21

(

1

):

1

.

6.

Massoni-Badosa

R

,

Iacono

G

,

Moutinho

C

, et al.

Sampling time-dependent artifacts in single-cell genomics studies

.

Genome Biol

.

2020

;

21

(

1

):

112

.

7.

Lähnemann

D

,

Köster

J

,

Szczurek

E

, et al.

Eleven grand challenges in single-cell data science

.

Genome Biol

.

2020

;

21

(

1

):

31

.

8.

Argelaguet

R

,

Cuomo

ASE

,

Stegle

O

,

Marioni

JC

.

Computational principles and challenges in single-cell data integration

.

Nat Biotechnol

.

2021

;

39

(

10

):

1202

-

1215

.

9.

Slyper

M

,

Porter

CBM

,

Ashenberg

O

, et al.

A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors

.

Nat Med

.

2020

;

26

(

5

):

792

-

802

.

10.

Tran

HTN

,

Ang

KS

,

Chevrier

M

, et al.

A benchmark of batch-effect correction methods for single-cell RNA sequencing data

.

Genome Biol

.

2020

;

21

(

1

):

12

.

11.

Fei

T

,

Yu

T

.

scBatch: batch-effect correction of RNA-seq data through sample distance matrix adjustment

.

Bioinformatics

.

2020

;

36

(

10

):

3115

-

3123

.

12.

Dal Molin

A

,

Di Camillo

B

.

How to design a single-cell RNA-sequencing experiment: pitfalls, challenges and perspectives

.

Brief Bioinform

.

2019

;

20

(

4

):

1384

-

1394

.

13.

Haghverdi

L

,

Lun

ATL

,

Morgan

MD

,

Marioni

JC

.

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors

.

Nat Biotechnol

.

2018

;

36

(

5

):

421

-

427

.

14.

Tang

F

,

Barbacioru

C

,

Wang

Y

, et al.

mRNA-Seq whole-transcriptome analysis of a single cell

.

Nat Methods

.

2009

;

6

(

5

):

377

-

382

.

15.

Aldridge

S

,

Teichmann

SA

.

Single cell transcriptomics comes of age

.

Nat Commun

.

2020

;

11

(

1

):

4307

.

16.

Haque

A

,

Engel

J

,

Teichmann

SA

,

Lönnberg

T

.

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications

.

Genome Med

.

2017

;

9

(

1

):

75

.

17.

Anaparthy

N

,

Ho

Y-J

,

Martelotto

L

,

Hammell

M

,

Hicks

J

.

Single-cell applications of next-generation sequencing

.

Cold Spring Harb Perspect Med

.

2019

;

9

(

10

):

a026898

.

18.

Rashid

NU

,

Sperling

AS

,

Bolli

N

, et al.

Differential and limited expression of mutant alleles in multiple myeloma

.

Blood

.

2014

;

124

(

20

):

3110

-

3117

.

19.

DeKosky

BJ

,

Ippolito

GC

,

Deschner

RP

, et al.

High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire

.

Nat Biotechnol

.

2013

;

31

(

2

):

166

-

169

.

20.

Howie

B

,

Sherwood

AM

,

Berkebile

AD

, et al.

High-throughput pairing of T cell receptor α and β sequences

.

Sci Transl Med

.

2015

;

7

(

301

):

301ra131

.

21.

Redmond

D

,

Poran

A

,

Elemento

O

.

Single-cell TCRseq: paired recovery of entire T-cell alpha and beta chain transcripts in T-cell receptors from single-cell RNAseq

.

Genome Med

.

2016

;

8

(

1

):

80

.

22.

Stoeckius

M

,

Hafemeister

C

,

Stephenson

W

, et al.

Simultaneous epitope and transcriptome measurement in single cells

.

Nat Methods

.

2017

;

14

(

9

):

865

-

868

.

23.

Hao

Y

,

Hao

S

,

Andersen-Nissen

E

, et al.

Integrated analysis of multimodal single-cell data

.

Cell

.

2021

;

184

(

13

):

3573

-

3587.e29

.

24.

Cusanovich

DA

,

Daza

R

,

Adey

A

, et al.

Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing

.

Science

.

2015

;

348

(

6237

):

910

-

914

.

25.

Bartosovic

M

,

Kabbe

M

,

Castelo-Branco

G

.

Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues

.

Nat Biotechnol

.

2021

;

39

(

7

):

825

-

835

.

26.

Rotem

A

,

Ram

O

,

Shoresh

N

, et al.

Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state

.

Nat Biotechnol

.

2015

;

33

(

11

):

1165

-

1172

.

27.

Carter

B

,

Ku

WL

,

Kang

JY

, et al.

Mapping histone modifications in low cell number and single cells using antibody-guided chromatin tagmentation (ACT-seq)

.

Nat Commun

.

2019

;

10

(

1

):

3747

.

28.

Clark

SJ

,

Smallwood

SA

,

Lee

HJ

,

Krueger

F

,

Reik

W

,

Kelsey

G

.

Genome-wide base-resolution mapping of DNA methylation in single cells using single-cell bisulfite sequencing (scBS-seq)

.

Nat Protoc

.

2017

;

12

(

3

):

534

-

547

.

29.

Taavitsainen

S

,

Engedal

N

,

Cao

S

, et al.

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse

.

Nat Commun

.

2021

;

12

(

1

):

5307

.

30.

Grosselin

K

,

Durand

A

,

Marsolier

J

, et al.

High-throughput single-cell ChIP-seq identifies heterogeneity of chromatin states in breast cancer

.

Nat Genet

.

2019

;

51

(

6

):

1060

-

1066

.

31.

Casado-Pelaez

M

,

Bueno-Costa

A

,

Esteller

M

.

Single cell cancer epigenetics

.

Trends Cancer

.

2022

;

8

(

10

):

820

-

838

.

32.

Meir

Z

,

Mukamel

Z

,

Chomsky

E

,

Lifshitz

A

,

Tanay

A

.

Single-cell analysis of clonal maintenance of transcriptional and epigenetic states in cancer cells

.

Nat Genet

.

2020

;

52

(

7

):

709

-

718

.

33.

Bian

S

,

Hou

Y

,

Zhou

X

, et al.

Single-cell multiomics sequencing and analyses of human colorectal cancer

.

Science

.

2018

;

362

(

6418

):

1060

-

1063

.

34.

Luecken

MD

,

Buttner

M

,

Chaichoompu

K

, et al.

Benchmarking atlas-level data integration in single-cell genomics

.

Nat Methods

.

2022

;

19

(

1

):

41

-

50

.

35.

You

Y

,

Tian

L

,

Su

S

, et al.

Benchmarking UMI-based single-cell RNA-seq preprocessing workflows

.

Genome Biol

.

2021

;

22

(

1

):

339

.

36.

Mereu

E

,

Lafzi

A

,

Moutinho

C

, et al.

Benchmarking single-cell RNA-sequencing protocols for cell atlas projects

.

Nat Biotechnol

.

2020

;

38

(

6

):

747

-

755

.

37.

Saelens

W

,

Cannoodt

R

,

Todorov

H

,

Saeys

Y

.

A comparison of single-cell trajectory inference methods

.

Nat Biotechnol

.

2019

;

37

(

5

):

547

-

554

.

38.

Yu

L

,

Cao

Y

,

Yang

JYH

,

Yang

P

.

Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data

.

Genome Biol

.

2022

;

23

(

1

):

49

.

https://doi.org/10.1101/2022.05.26.493607

39.

Nolet

C

,

Lal

A

,

Ilango

R

, et al.

Accelerating single-cell genomic analysis with GPUs

.

bioRxiv

.

Preprint posted online 28 May 2022

.

40.

Li

H

,

Durbin

R

.

Fast and accurate short read alignment with Burrows-Wheeler transform

.

Bioinformatics

.

2009

;

25

(

14

):

1754

-

1760

.

41.

Patro

R

,

Duggal

G

,

Love

MI

,

Irizarry

RA

,

Kingsford

C

.

Salmon provides fast and bias-aware quantification of transcript expression

.

Nat Methods

.

2017

;

14

(

4

):

417

-

419

.

42.

Aktas Samur

A

,

Minvielle

S

,

Shammas

M

, et al.

Deciphering the chronology of copy number alterations in multiple Myeloma

.

Blood Cancer J

.

2019

;

9

(

4

):

39

.

43.

Samur

MK

,

Aktas Samur

A

,

Fulciniti

M

, et al.

Genome-wide somatic alterations in multiple myeloma reveal a superior outcome group

.

J Clin Oncol

.

2020

;

38

(

27

):

3107

-

3118

.

44.

Samur

MK

,

Minvielle

S

,

Gulla

A

, et al.

Long intergenic non-coding RNAs have an independent impact on survival in multiple myeloma

.

Leukemia

.

2018

;

32

(

12

):

2626

-

2635

.

45.

Ansari-Pour

N

,

Samur

MK

,

Flynt

E

, et al.

Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma

.

Blood

.

2023

;

141

(

6

):

620

-

633

.

46.

Walker

BA

,

Mavrommatis

K

,

Wardell

CP

, et al.

Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma

.

Blood

.

2018

;

132

(

6

):

587

-

597

.

47.

Maura

F

,

Bolli

N

,

Angelopoulos

N

, et al.

Genomic landscape and chronological reconstruction of driver events in multiple myeloma

.

Nat Commun

.

2019

;

10

(

1

):

3835

.

48.

Bolli

N

,

Maura

F

,

Minvielle

S

, et al.

Genomic patterns of progression in smoldering multiple myeloma

.

Nat Commun

.

2018

;

9

(

1

):

3363

.

49.

Corre

J

,

Munshi

NC

,

Avet-Loiseau

H

.

Risk factors in multiple myeloma: is it time for a revision?

.

Blood

.

2021

;

137

(

1

):

16

-

19

.

50.

Robiou du Pont

S

,

Cleynen

A

,

Fontan

C

, et al.

Genomics of multiple myeloma

.

J Clin Oncol

.

2017

;

35

(

9

):

963

-

967

.

51.

Corre

J

,

Munshi

N

,

Avet-Loiseau

H

.

Genetics of multiple myeloma: another heterogeneity level?

.

Blood

.

2015

;

125

(

12

):

1870

-

1876

.

52.

Tarabichi

M

,

Salcedo

A

,

Deshwar

AG

, et al.

A practical guide to cancer subclonal reconstruction from DNA sequencing

.

Nat Methods

.

2021

;

18

(

2

):

144

-

155

.

53.

Samur

MK

,

Shah

PK

,

Wang

X

, et al.

The shaping and functional consequences of the dosage effect landscape in multiple myeloma

.

BMC Genom

.

2013

;

14

:

672

.

54.

Jia

Q

,

Chu

H

,

Jin

Z

,

Long

H

,

Zhu

B

.

High-throughput single-сell sequencing in cancer research

.

Signal Transduct Target Ther

.

2022

;

7

(

1

):

145

.

55.

Almendro

V

,

Cheng

Y-K

,

Randles

A

, et al.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

.

Cell Rep

.

2014

;

6

(

3

):

514

-

527

.

56.

González-Silva

L

,

Quevedo

L

,

Varela

I

.

Tumor functional heterogeneity unraveled by scRNA-seq technologies

.

Trends Cancer

.

2020

;

6

(

1

):

13

-

19

.

57.

Liu

R

,

Gao

Q

,

Foltz

SM

, et al.

Co-evolution of tumor and immune cells during progression of multiple myeloma

.

Nat Commun

.

2021

;

12

(

1

):

2559

.

58.

Ledergor

G

,

Weiner

A

,

Zada

M

, et al.

Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma

.

Nat Med

.

2018

;

24

(

12

):

1867

-

1876

.

59.

Goicoechea

I

,

Puig

N

,

Cedena

MT

, et al.

Deep MRD profiling defines outcome and unveils different modes of treatment resistance in standard- and high-risk myeloma

.

Blood

.

2021

;

137

(

1

):

49

-

60

.

60.

Samur

MK

,

Fulciniti

M

,

Aktas Samur

A

, et al.

Biallelic loss of BCMA as a resistance mechanism to CAR T cell therapy in a patient with multiple myeloma

.

Nat Commun

.

2021

;

12

(

1

):

868

.

61.

Da Vià

MC

,

Dietrich

O

,

Truger

M

, et al.

Homozygous BCMA gene deletion in response to anti-BCMA CAR T cells in a patient with multiple myeloma

.

Nat Med

.

2021

;

27

(

4

):

616

-

619

.

62.

Lohr

JG

,

Kim

S

,

Gould

J

, et al.

Genetic interrogation of circulating multiple myeloma cells at single-cell resolution

.

Sci Transl Med

.

2016

;

8

(

363

):

363ra147

.

63.

Garces

JJ

,

Simicek

M

,

Vicari

M

, et al.

Transcriptional profiling of circulating tumor cells in multiple myeloma: a new model to understand disease dissemination

.

Leukemia

.

2020

;

34

(

2

):

589

-

603

.

64.

Maia

C

,

Puig

N

,

Cedena

M-T

, et al.

Biological and clinical significance of dysplastic hematopoiesis in patients with newly diagnosed multiple myeloma

.

Blood

.

2020

;

135

(

26

):

2375

-

2387

.

65.

Merz

M

,

Merz

AMA

,

Wang

J

, et al.

Deciphering spatial genomic heterogeneity at a single cell resolution in multiple myeloma

.

Nat Commun

.

2022

;

13

(

1

):

807

.

66.

Lannes

R

,

Samur

M

,

Perrot

A

, et al.

In multiple myeloma, high-risk secondary genetic events observed at relapse are present from diagnosis in tiny, undetectable subclonal populations

.

J Clin Oncol

.

2022

;

41

(

9

):

1695

-

1702

.

67.

Frede

J

,

Anand

P

,

Sotudeh

N

, et al.

Dynamic transcriptional reprogramming leads to immunotherapeutic vulnerabilities in myeloma

.

Nat Cell Biol

.

2021

;

23

(

11

):

1199

-

1211

.

68.

Alameda

D

,

Goicoechea

I

,

Vicari

M

, et al.

Tumor cells in light-chain amyloidosis and myeloma show distinct transcriptional rewiring of normal plasma cell development

.

Blood

.

2021

;

138

(

17

):

1583

-

1589

.

69.

Masuda

T

,

Haji

S

,

Nakashima

Y

, et al.

Identification of a drug-response gene in multiple myeloma through longitudinal single-cell transcriptome sequencing

.

iScience

.

2022

;

25

(

8

):

104781

.

70.

Kumar

H

,

Mazumder

S

,

Chakravarti

S

, et al.

secDrug: a pipeline to discover novel drug combinations to kill drug-resistant multiple myeloma cells using a greedy set cover algorithm and single-cell multi-omics

.

Blood Cancer J

.

2022

;

12

(

3

):

39

.

71.

Waldschmidt

JM

,

Kloeber

JA

,

Anand

P

, et al.

Single-cell profiling reveals metabolic reprogramming as a resistance mechanism in BRAF-mutated multiple myeloma

.

Clin Cancer Res

.

2021

;

27

(

23

):

6432

-

6444

.

72.

Cohen

YC

,

Zada

M

,

Wang

S-Y

, et al.

Identification of resistance pathways and therapeutic targets in relapsed multiple myeloma patients through single-cell sequencing

.

Nat Med

.

2021

;

27

(

3

):

491

-

503

.

73.

Fowler

NH

,

Cheah

CY

,

Gascoyne

RD

, et al.

Role of the tumor microenvironment in mature B-cell lymphoid malignancies

.

Haematologica

.

2016

;

101

(

5

):

531

-

540

.

74.

García-Ortiz

A

,

Rodríguez-García

Y

,

Encinas

J

, et al.

The Role of tumor microenvironment in multiple myeloma development and progression

.

Cancers

.

2021

;

13

(

2

):

217

.

75.

Kawano

Y

,

Moschetta

M

,

Manier

S

, et al.

Targeting the bone marrow microenvironment in multiple myeloma

.

Immunol Rev

.

2015

;

263

(

1

):

160

-

172

.

76.

Bianchi

G

,

Munshi

NC

.

Pathogenesis beyond the cancer clone(s) in multiple myeloma

.

Blood

.

2015

;

125

(

20

):

3049

-

3058

.

77.

Rodriguez-Otero

P

,

Paiva

B

,

San-Miguel

JF

.

Roadmap to cure multiple myeloma

.

Cancer Treat Rev

.

2021

;

100

:

102284

.

78.

Tirosh

I

,

Izar

B

,

Prakadan

SM

, et al.

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

.

Science

.

2016

;

352

(

6282

):

189

-

196

.

79.

Puram

SV

,

Tirosh

I

,

Parikh

AS

, et al.

Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer

.

Cell

.

2017

;

171

(

7

):

1611

-

1624.e24

.

80.

Hatlen

MA

,

Schmidt-Kittler

O

,

Sherwin

CA

, et al.

Acquired on-target clinical resistance validates FGFR4 as a driver of hepatocellular carcinoma

.

Cancer Discov

.

2019

;

9

(

12

):

1686

-

1695

.

81.

Zavidij

O

,

Haradhvala

NJ

,

Mouhieddine

TH

, et al.

Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

.

Nat Cancer

.

2020

;

1

(

5

):

493

-

506

.

82.

Bailur

JK

,

McCachren

SS

,

Doxie

DB

, et al.

Early alterations in stem-like/resident T cells, innate and myeloid cells in the bone marrow in preneoplastic gammopathy

.

JCI Insight

.

2019

;

5

(

11

):

e127807

.

83.

Schinke

C

,

Poos

AM

,

Bauer

MA

, et al.

Characterizing the role of the immune microenvironment in multiple myeloma progression at a single cell level

.

Blood Adv

.

2022

;

6

(

22

):

5873

-

5883

.

84.

Ogiya

D

,

Liu

J

,

Ohguchi

H

, et al.

The JAK-STAT pathway regulates CD38 on myeloma cells in the bone marrow microenvironment: therapeutic implications

.

Blood

.

2020

;

136

(

20

):

2334

-

2345

.

85.

Binder

M

,

Szalat

RE

,

Fulciniti

M

,

Parmigiani

G

,

Samur

MK

,

Munshi

NC

.

Chromatin remodeling and associated changes in gene expression induced by bone marrow stromal cells identify features of high-risk multiple myeloma [abstract]

.

Blood

.

2021

;

138

(

suppl 1

). Abstract 2672.

86.

de Jong

MME

,

Kellermayer

Z

,

Papazian

N

, et al.

The multiple myeloma microenvironment is defined by an inflammatory stromal cell landscape

.

Nat Immunol

.

2021

;

22

(

6

):

769

-

780

.

87.

Tirier

SM

,

Mallm

J-P

,

Steiger

S

, et al.

Subclone-specific microenvironmental impact and drug response in refractory multiple myeloma revealed by single-cell transcriptomics

.

Nat Commun

.

2021

;

12

(

1

):

6960

.

88.

Chauhan

D

,

Singh

AV

,

Brahmandam

M

, et al.

Functional Interaction of plasmacytoid dendritic cells with multiple myeloma cells: a therapeutic target

.

Cancer Cell

.

2009

;

16

(

4

):

309

-

323

.

89.

Robinson

H

,

Villa

N

,

Jaye

DL

, et al.

Tumor-immune architecture and the regulation of antigen-specific T-cell infiltration in multiple myeloma and premalignant plasma cell disorders [abstract]

.

Blood

.

2022

;

140

(

suppl 1

):

244

-

245

.

90.

Sklavenitis-Pistofidis

R

,

Aranha

MP

,

Redd

RA

, et al.

Immune biomarkers of response to immunotherapy in patients with high-risk smoldering myeloma

.

Cancer Cell

.

2022

;

40

(

11

):

1358

-

1373.e8

.

91.

Pilcher

W

,

Thomas

BE

,

Bhasin

SS

, et al.

Cross center single-cell RNA sequencing study of the immune microenvironment in rapid progressing multiple myeloma

.

NPJ Genom Med

.

2023

;

8

(

1

):

3

.

92.

Liang

Y

,

He

H

,

Wang

W

, et al.

Malignant clonal evolution drives multiple myeloma cellular ecological diversity and microenvironment reprogramming

.

Mol Cancer

.

2022

;

21

(

1

):

182

.

93.

Samur

MK

,

Roncador

M

,

Aktas Samur

A

, et al.

High-dose melphalan treatment significantly increases mutational burden at relapse in multiple myeloma

.

Blood

.

2023

;

141

(

14

):

1724

-

1736

.

94.

Ginhoux

F

,

Yalin

A

,

Dutertre

CA

,

Amit

I

.

Single-cell immunology: past, present, and future

.

Immunity

.

2022

;

55

(

3

):

393

-

404

.

95.

Yao

L

,

Jayasinghe

RG

,

Lee

BH

, et al.

Comprehensive characterization of the multiple myeloma immune microenvironment using integrated scRNA-seq, CyTOF, and CITE-seq analysis

.

Cancer Res Commun

.

2022

;

2

(

10

):

1255

-

1265

.

96.

Boiarsky

R

,

Haradhvala

NJ

,

Alberge

J-B

, et al.

Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis

.

Nat Commun

.

2022

;

13

(

1

):

7040

.

97.

Tsuji

J

,

Lightbody

ED

,

Sklavenitis-Pistofidis

R

, et al.

Single-cell RNA-sequencing of 245 tumor samples from patients with MGUS and smoldering multiple myeloma reveals novel insights into malignant plasma cell biology [abstract]

.

Blood

.

2022

;

140

(

suppl 1

):

254

-

255

.

98.

Boiarsky

R

,

Haradhvala

NJ

,

Alberge

JB

, et al.

Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis

.

Nat Commun

.

2022

;

13

(

1

):

7040

.

https://www.nature.com/articles/s41576-023-00580-2.

99.

Vandereyken

K

,

Sifrim

A

,

Thienpont

B

,

Voet

T

.

Methods and applications for single-cell and spatial multi-omics

.

Nat Rev Genet

.

Published online 2 March 2023

100.

Marx

V

.

How single-cell multi-omics builds relationships

.

Nat Methods

.

2022

;

19

(

2

):

142

-

146

.

101.

Rao

A

,

Barkley

D

,

França

GS

,

Yanai

I

.

Exploring tissue architecture using spatial transcriptomics

.

Nature

.

2021

;

596

(

7871

):

211

-

220

.

102.

Dhodapkar

KM

,

Cohen

AD

,

Kaushal

A

, et al.

Changes in bone marrow tumor and immune cells correlate with durability of remissions following BCMA CAR T therapy in myeloma

.

Blood Cancer Discov

.

2022

;

3

(

6

):

490

-

501

.

103.

Kehl

N

,

Kilian

M

,

Michel

J

, et al.

IgE type multiple myeloma exhibits hypermutated phenotype and tumor reactive T cells

.

J Immunother Cancer

.

2022

;

10

(

10

):

e005815

.

104.

Gao

T

,

Soldatov

R

,

Sarkar

H

, et al.

Haplotype-aware analysis of somatic copy number variations from single-cell transcriptomes

.

Nat Biotechnol

.

2023

;

41

(

3

):

417

-

426

.

105.

Welters

C

,

Lammoglia Cobo

MF

,

Stein

CA

, et al.

Immune phenotypes and target antigens of clonally expanded bone marrow T cells in treatment-naive multiple myeloma

.

Cancer Immunol Res

.

2022

;

10

(

11

):

1407

-

1419

.

106.

Yao

L

,

Jayasinghe

RG

,

Lee

BH

, et al.

Comprehensive characterization of the multiple myeloma immune microenvironment using integrated scRNA-seq, CyTOF, and CITE-seq Analysis

.

Cancer Res Commun

.

2022

;

2

(

10

):

1255

-

1265

.

107.

Kumar

H

,

Mazumder

S

,

Sharma

N

, et al.

Single-cell proteomics and tumor RNAseq identify novel pathways associated with clofazimine sensitivity in PI- and IMiD- resistant myeloma, and putative stem-like cells

.

Front Oncol

.

2022

;

12

:

842200

.

108.

Croucher

DC

,

Richards

LM

,

Tsofack

SP

, et al.

Longitudinal single-cell analysis of a myeloma mouse model identifies subclonal molecular programs associated with progression

.

Nat Commun

.

2021

;

12

(

1

):

6322

.

109.

Cho

H

,

Kim

KH

,

Lee

H

, et al.

Adaptive natural killer cells facilitate effector functions of daratumumab in multiple myeloma

.

Clin Cancer Res

.

2021

;

27

(

10

):

2947

-

2958

.

110.

Teh

CE

,

Gong

JN

,

Segal

D

, et al.

Deep profiling of apoptotic pathways with mass cytometry identifies a synergistic drug combination for killing myeloma cells

.

Cell Death Differ

.

2020

;

27

(

7

):

2217

-

2233

.

111.

Jang

JS

,

Li

Y

,

Mitra

AK

, et al.

Molecular signatures of multiple myeloma progression through single cell RNA-Seq

.

Blood Cancer J

.

2019

;

9

(

1

):

2

.

112.

Kourelis

TV

,

Villasboas

JC

,

Jessen

E

, et al.

Mass cytometry dissects T cell heterogeneity in the immune tumor microenvironment of common dysproteinemias at diagnosis and after first line therapies

.

Blood Cancer J

.

2019

;

9

(

9

):

72

.

113.

Hansmann

L

,

Blum

L

,

Ju

CH

,

Liedtke

M

,

Robinson

WH

,

Davis

MM

.

Mass cytometry analysis shows that a novel memory phenotype B cell is expanded in multiple myeloma

.

Cancer Immunol Res

.

2015

;

3

(

6

):

650

-

660

.