Cancers

Research

Jump to: Review

23 pages, 3154 KiB

Open AccessArticle

High-Throughput Profiling of Colorectal Cancer Liver Metastases Reveals Intra- and Inter-Patient Heterogeneity in the EGFR and WNT Pathways Associated with Clinical Outcome

by Kerstin Menck, Darius Wlochowitz, Astrid Wachter, Lena-Christin Conradi, Alexander Wolff, Andreas H. Scheel, Ulrike Korf, Stefan Wiemann, Hans-Ulrich Schildhaus, Hanibal Bohnenberger, Edgar Wingender, Tobias Pukrop, Kia Homayounfar, Tim Beißbarth and Annalen Bleckmann

Cancers 2022, 14(9), 2084; https://doi.org/10.3390/cancers14092084 - 21 Apr 2022

Cited by 4 | Viewed by 2984

Abstract

Seventy percent of patients with colorectal cancer develop liver metastases (CRLM), which are a decisive factor in cancer progression. Therapy outcome is largely influenced by tumor heterogeneity, but the intra- and inter-patient heterogeneity of CRLM has been poorly studied. In particular, the contribution [...] Read more.

Seventy percent of patients with colorectal cancer develop liver metastases (CRLM), which are a decisive factor in cancer progression. Therapy outcome is largely influenced by tumor heterogeneity, but the intra- and inter-patient heterogeneity of CRLM has been poorly studied. In particular, the contribution of the WNT and EGFR pathways, which are both frequently deregulated in colorectal cancer, has not yet been addressed in this context. To this end, we comprehensively characterized normal liver tissue and eight CRLM from two patients by standardized histopathological, molecular, and proteomic subtyping. Suitable fresh-frozen tissue samples were profiled by transcriptome sequencing (RNA-Seq) and proteomic profiling with reverse phase protein arrays (RPPA) combined with bioinformatic analyses to assess tumor heterogeneity and identify WNT- and EGFR-related master regulators and metastatic effectors. A standardized data analysis pipeline for integrating RNA-Seq with clinical, proteomic, and genetic data was established. Dimensionality reduction of the transcriptome data revealed a distinct signature for CRLM differing from normal liver tissue and indicated a high degree of tumor heterogeneity. WNT and EGFR signaling were highly active in CRLM and the genes of both pathways were heterogeneously expressed between the two patients as well as between the synchronous metastases of a single patient. An analysis of the master regulators and metastatic effectors implicated in the regulation of these genes revealed a set of four genes (SFN, IGF2BP1, STAT1, PIK3CG) that were differentially expressed in CRLM and were associated with clinical outcome in a large cohort of colorectal cancer patients as well as CRLM samples. In conclusion, high-throughput profiling enabled us to define a CRLM-specific signature and revealed the genes of the WNT and EGFR pathways associated with inter- and intra-patient heterogeneity, which were validated as prognostic biomarkers in CRC primary tumors as well as liver metastases. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

20 pages, 5613 KiB

Open AccessArticle

Implications of Intratumor Heterogeneity on Consensus Molecular Subtype (CMS) in Colorectal Cancer

by Saikat Chowdhury, Matan Hofree, Kangyu Lin, Dipen Maru, Scott Kopetz and John Paul Shen

Cancers 2021, 13(19), 4923; https://doi.org/10.3390/cancers13194923 - 30 Sep 2021

Cited by 16 | Viewed by 3234

Abstract

The implications of intratumor heterogeneity on the four consensus molecular subtypes (CMS) of colorectal cancer (CRC) are not well known. Here, we use single-cell RNA sequencing (scRNASeq) to build an algorithm to assign CMS classification to individual cells, which we use to explore [...] Read more.

The implications of intratumor heterogeneity on the four consensus molecular subtypes (CMS) of colorectal cancer (CRC) are not well known. Here, we use single-cell RNA sequencing (scRNASeq) to build an algorithm to assign CMS classification to individual cells, which we use to explore the distributions of CMSs in tumor and non-tumor cells. A dataset of colorectal tumors with bulk RNAseq (n = 3232) was used to identify CMS specific-marker gene sets. These gene sets were then applied to a discovery dataset of scRNASeq profiles (n = 10) to develop an algorithm for single-cell CMS (scCMS) assignment, which recapitulated the intrinsic biology of all four CMSs. The single-cell CMS assignment algorithm was used to explore the scRNASeq profiles of two prospective CRC tumors with mixed CMS via bulk sequencing. We find that every CRC tumor contains individual cells of each scCMS, as well as many individual cells that have enrichment for features of more than one scCMS (called mixed cells). scCMS4 and scCMS1 cells dominate stroma and immune cell clusters, respectively, but account for less than 3% epithelial cells. These data imply that CMS1 and CMS4 are driven by the transcriptomic contribution of immune and stromal cells, respectively, not tumor cells. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Graphical abstract

12 pages, 2373 KiB

Open AccessArticle

NPM1 Mutational Status Underlines Different Biological Features in Pediatric AML

by Claudia Tregnago, Maddalena Benetton, Davide Padrin, Katia Polato, Giulia Borella, Ambra Da Ros, Anna Marchetti, Elena Porcù, Francesca Del Bufalo, Cristina Mecucci, Franco Locatelli and Martina Pigazzi

Cancers 2021, 13(14), 3457; https://doi.org/10.3390/cancers13143457 - 10 Jul 2021

Cited by 1 | Viewed by 3181

Abstract

Nucleophosmin (NPM1) is a nucleocytoplasmic shuttling protein, predominantly located in the nucleolus, that regulates a multiplicity of different biological processes. NPM1 localization in the cell is finely tuned by specific signal motifs, with two tryptophan residues (Trp) being essential for the nucleolar localization. [...] Read more.

Nucleophosmin (NPM1) is a nucleocytoplasmic shuttling protein, predominantly located in the nucleolus, that regulates a multiplicity of different biological processes. NPM1 localization in the cell is finely tuned by specific signal motifs, with two tryptophan residues (Trp) being essential for the nucleolar localization. In acute myeloid leukemia (AML), several NPM1 mutations have been reported, all resulting in cytoplasmic delocalization, but the putative biological and clinical significance of different variants are still debated. We explored HOXA and HOXB gene expression profile in AML patients and found a differential expression between NPM1 mutations inducing the loss of two (A-like) Trp residues and those determining the loss of one Trp residue (non-A-like). We thus expressed NPM1 A-like- or non-A-like-mutated vectors in AML cell lines finding that NPM1 partially remained in the nucleolus in the non-A-like NPM1-mutated cells. As a result, only in A-like-mutated cells we detected HOXA5, HOXA10, and HOXB5 hyper-expression and p14ARF/p21/p53 pathway deregulation, leading to reduced sensitivity to the treatment with either chemotherapy or Venetoclax, as compared to non-A-like cells. Overall, we identified that the NPM1 mutational status mediates crucial biological characteristics of AML cells, providing the basis for further sub-classification and, potentially, management of this subgroup of patients. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Graphical abstract

14 pages, 10055 KiB

Open AccessArticle

AID Contributes to Accelerated Disease Progression in the TCL1 Mouse Transplant Model for CLL

by Maria Schubert, Franz Josef Gassner, Michael Huemer, Jan Philip Höpner, Ekaterina Akimova, Markus Steiner, Alexander Egle, Richard Greil, Nadja Zaborsky and Roland Geisberger

Cancers 2021, 13(11), 2619; https://doi.org/10.3390/cancers13112619 - 26 May 2021

Cited by 4 | Viewed by 2291

Abstract

Adaptive somatic mutations conferring treatment resistance and accelerated disease progression is still a major problem in cancer therapy. Additionally in CLL, patients receiving novel, efficient drugs frequently become treatment refractory and eventually relapse. Activation-induced deaminase (AID) is a cytosine deaminase that catalyzes somatic [...] Read more.

Adaptive somatic mutations conferring treatment resistance and accelerated disease progression is still a major problem in cancer therapy. Additionally in CLL, patients receiving novel, efficient drugs frequently become treatment refractory and eventually relapse. Activation-induced deaminase (AID) is a cytosine deaminase that catalyzes somatic hypermutation of genomic DNA at the immunoglobulin locus in activated B cells. As considerable off-target mutations by AID have been discerned in chronic lymphocytic leukemia, it is essential to investigate to which extent these mutations contribute to disease progression to estimate whether AID inhibition could counteract drug resistance mechanisms. In this study, we examined the TCL1 mouse model for CLL on an AID pro- and deficient background by comparing disease development and mutational landscapes. We provide evidence that AID contributes to the acquisition of somatic cancer-specific mutations also in the TCL1 model and accelerates CLL development particularly in the transplant setting. We conclude that AID is directly determining the fitness of the CLL clone, which prompts further studies to assess the effect of AID inhibition on the occurrence of drug resistance. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

21 pages, 17941 KiB

Open AccessArticle

Identification of CRYAB⁺ KCNN3⁺ SOX9⁺ Astrocyte-Like and EGFR⁺ PDGFRA⁺ OLIG1⁺ Oligodendrocyte-Like Tumoral Cells in Diffuse IDH1-Mutant Gliomas and Implication of NOTCH1 Signalling in Their Genesis

by Meera Augustus, Donovan Pineau, Franck Aimond, Safa Azar, Davide Lecca, Frédérique Scamps, Sophie Muxel, Amélie Darlix, William Ritchie, Catherine Gozé, Valérie Rigau, Hugues Duffau and Jean-Philippe Hugnot

Cancers 2021, 13(9), 2107; https://doi.org/10.3390/cancers13092107 - 27 Apr 2021

Cited by 8 | Viewed by 3867

Abstract

Diffuse grade II IDH-mutant gliomas are slow-growing brain tumors that progress into high-grade gliomas. They present intratumoral cell heterogeneity, and no reliable markers are available to distinguish the different cell subtypes. The molecular mechanisms underlying the formation of this cell diversity is also [...] Read more.

Diffuse grade II IDH-mutant gliomas are slow-growing brain tumors that progress into high-grade gliomas. They present intratumoral cell heterogeneity, and no reliable markers are available to distinguish the different cell subtypes. The molecular mechanisms underlying the formation of this cell diversity is also ill-defined. Here, we report that SOX9 and OLIG1 transcription factors, which specifically label astrocytes and oligodendrocytes in the normal brain, revealed the presence of two largely nonoverlapping tumoral populations in IDH1-mutant oligodendrogliomas and astrocytomas. Astrocyte-like SOX9⁺ cells additionally stained for APOE, CRYAB, ID4, KCNN3, while oligodendrocyte-like OLIG1⁺ cells stained for ASCL1, EGFR, IDH1, PDGFRA, PTPRZ1, SOX4, and SOX8. GPR17, an oligodendrocytic marker, was expressed by both cells. These two subpopulations appear to have distinct BMP, NOTCH1, and MAPK active pathways as stainings for BMP4, HEY1, HEY2, p-SMAD1/5 and p-ERK were higher in SOX9⁺ cells. We used primary cultures and a new cell line to explore the influence of NOTCH1 activation and BMP treatment on the IDH1-mutant glioma cell phenotype. This revealed that NOTCH1 globally reduced oligodendrocytic markers and IDH1 expression while upregulating APOE, CRYAB, HEY1/2, and an electrophysiologically-active Ca²⁺-activated apamin-sensitive K⁺ channel (KCNN3/SK3). This was accompanied by a reduction in proliferation. Similar effects of NOTCH1 activation were observed in nontumoral human oligodendrocytic cells, which additionally induced strong SOX9 expression. BMP treatment reduced OLIG1/2 expression and strongly upregulated CRYAB and NOGGIN, a negative regulator of BMP. The presence of astrocyte-like SOX9⁺ and oligodendrocyte-like OLIG1⁺ cells in grade II IDH1-mutant gliomas raises new questions about their role in the pathology. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Graphical abstract

20 pages, 3354 KiB

Open AccessArticle

Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma

by Zongtai Qi, Yating Liu, Michael Mints, Riley Mullins, Reilly Sample, Travis Law, Thomas Barrett, Angela L. Mazul, Ryan S. Jackson, Stephen Y. Kang, Patrik Pipkorn, Anuraag S. Parikh, Itay Tirosh, Joseph Dougherty and Sidharth V. Puram

Cancers 2021, 13(6), 1230; https://doi.org/10.3390/cancers13061230 - 11 Mar 2021

Cited by 21 | Viewed by 6692

Abstract

Complexities in cell-type composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate cell-type proportions from the gene expression data of bulk blood samples, but [...] Read more.

Complexities in cell-type composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate cell-type proportions from the gene expression data of bulk blood samples, but their performance when applied to tumor tissues, including those from head and neck, remains poorly characterized. Here, we use single-cell data (~6000 single cells) collected from 21 head and neck squamous cell carcinoma (HNSCC) samples to generate cell-type-specific gene expression signatures. We leverage bulk RNA-seq data from >500 HNSCC samples profiled by The Cancer Genome Atlas (TCGA), and using single-cell data as a reference, apply two newly developed deconvolution algorithms (CIBERSORTx and MuSiC) to the bulk transcriptome data to quantitatively estimate cell-type proportions for each tumor in TCGA. We show that these two algorithms produce similar estimates of constituent/major cell-type proportions and that a high T-cell fraction correlates with improved survival. By further characterizing T-cell subpopulations, we identify that regulatory T-cells (T_regs) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the T_reg population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core T_reg subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of T_reg in HNSCC outcomes. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

15 pages, 2842 KiB

Open AccessArticle

Adaptive Therapy for Metastatic Melanoma: Predictions from Patient Calibrated Mathematical Models

by Eunjung Kim, Joel S. Brown, Zeynep Eroglu and Alexander R.A. Anderson

Cancers 2021, 13(4), 823; https://doi.org/10.3390/cancers13040823 - 16 Feb 2021

Cited by 32 | Viewed by 4141

Abstract

Adaptive therapy is an evolution-based treatment approach that aims to maintain tumor volume by employing minimum effective drug doses or timed drug holidays. For successful adaptive therapy outcomes, it is critical to find the optimal timing of treatment switch points in a patient-specific [...] Read more.

Adaptive therapy is an evolution-based treatment approach that aims to maintain tumor volume by employing minimum effective drug doses or timed drug holidays. For successful adaptive therapy outcomes, it is critical to find the optimal timing of treatment switch points in a patient-specific manner. Here we develop a combination of mathematical models that examine interactions between drug-sensitive and resistant cells to facilitate melanoma adaptive therapy dosing and switch time points. The first model assumes genetically fixed drug-sensitive and -resistant popul tions that compete for limited resources. The second model considers phenotypic switching between drug-sensitive and -resistant cells. We calibrated each model to fit melanoma patient biomarker changes over time and predicted patient-specific adaptive therapy schedules. Overall, the models predict that adaptive therapy would have delayed time to progression by 6–25 months compared to continuous therapy with dose rates of 6–74% relative to continuous therapy. We identified predictive factors driving the clinical time gained by adaptive therapy, such as the number of initial sensitive cells, competitive effect, switching rate from resistant to sensitive cells, and sensitive cell growth rate. This study highlights that there is a range of potential patient-specific benefits of adaptive therapy and identifies parameters that modulate this benefit. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

18 pages, 2795 KiB

Open AccessArticle

A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases

by Daniel A. Anaya, Prashant Dogra, Zhihui Wang, Mintallah Haider, Jasmina Ehab, Daniel K. Jeong, Masoumeh Ghayouri, Gregory Y. Lauwers, Kerry Thomas, Richard Kim, Joseph D. Butner, Sara Nizzero, Javier Ruiz Ramírez, Marija Plodinec, Richard L. Sidman, Webster K. Cavenee, Renata Pasqualini, Wadih Arap, Jason B. Fleming and Vittorio Cristini

Cancers 2021, 13(3), 444; https://doi.org/10.3390/cancers13030444 - 25 Jan 2021

Cited by 14 | Viewed by 4371

Abstract

Chemotherapy remains a primary treatment for metastatic cancer, with tumor response being the benchmark outcome marker. However, therapeutic response in cancer is unpredictable due to heterogeneity in drug delivery from systemic circulation to solid tumors. In this proof-of-concept study, we evaluated chemotherapy concentration [...] Read more.

Chemotherapy remains a primary treatment for metastatic cancer, with tumor response being the benchmark outcome marker. However, therapeutic response in cancer is unpredictable due to heterogeneity in drug delivery from systemic circulation to solid tumors. In this proof-of-concept study, we evaluated chemotherapy concentration at the tumor-site and its association with therapy response by applying a mathematical model. By using pre-treatment imaging, clinical and biologic variables, and chemotherapy regimen to inform the model, we estimated tumor-site chemotherapy concentration in patients with colorectal cancer liver metastases, who received treatment prior to surgical hepatic resection with curative-intent. The differential response to therapy in resected specimens, measured with the gold-standard Tumor Regression Grade (TRG; from 1, complete response to 5, no response) was examined, relative to the model predicted systemic and tumor-site chemotherapy concentrations. We found that the average calculated plasma concentration of the cytotoxic drug was essentially equivalent across patients exhibiting different TRGs, while the estimated tumor-site chemotherapeutic concentration (eTSCC) showed a quadratic decline from TRG = 1 to TRG = 5 (p < 0.001). The eTSCC was significantly lower than the observed plasma concentration and dropped by a factor of ~5 between patients with complete response (TRG = 1) and those with no response (TRG = 5), while the plasma concentration remained stable across TRG groups. TRG variations were driven and predicted by differences in tumor perfusion and eTSCC. If confirmed in carefully planned prospective studies, these findings will form the basis of a paradigm shift in the care of patients with potentially curable colorectal cancer and liver metastases. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

Review

Jump to: Research

20 pages, 1151 KiB

Open AccessReview

An Epigenetic Perspective on Intra-Tumour Heterogeneity: Novel Insights and New Challenges from Multiple Fields

by Sven Beyes, Naiara Garcia Bediaga and Alessio Zippo

Cancers 2021, 13(19), 4969; https://doi.org/10.3390/cancers13194969 - 3 Oct 2021

Cited by 15 | Viewed by 3247

Abstract

Cancer is a group of heterogeneous diseases that results from the occurrence of genetic alterations combined with epigenetic changes and environmental stimuli that increase cancer cell plasticity. Indeed, multiple cancer cell populations coexist within the same tumour, favouring cancer progression and metastatic dissemination [...] Read more.

Cancer is a group of heterogeneous diseases that results from the occurrence of genetic alterations combined with epigenetic changes and environmental stimuli that increase cancer cell plasticity. Indeed, multiple cancer cell populations coexist within the same tumour, favouring cancer progression and metastatic dissemination as well as drug resistance, thereby representing a major obstacle for treatment. Epigenetic changes contribute to the onset of intra-tumour heterogeneity (ITH) as they facilitate cell adaptation to perturbation of the tumour microenvironment. Despite being its central role, the intrinsic multi-layered and reversible epigenetic pattern limits the possibility to uniquely determine its contribution to ITH. In this review, we first describe the major epigenetic mechanisms involved in tumourigenesis and then discuss how single-cell-based approaches contribute to dissecting the key role of epigenetic changes in tumour heterogeneity. Furthermore, we highlight the importance of dissecting the interplay between genetics, epigenetics, and tumour microenvironments to decipher the molecular mechanisms governing tumour progression and drug resistance. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

28 pages, 1783 KiB

Open AccessReview

A Systems Approach to Brain Tumor Treatment

by James H. Park, Adrian Lopez Garcia de Lomana, Diego M. Marzese, Tiffany Juarez, Abdullah Feroze, Parvinder Hothi, Charles Cobbs, Anoop P. Patel, Santosh Kesari, Sui Huang and Nitin S. Baliga

Cancers 2021, 13(13), 3152; https://doi.org/10.3390/cancers13133152 - 24 Jun 2021

Cited by 21 | Viewed by 5243

Abstract

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this [...] Read more.

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood–brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

17 pages, 858 KiB

Open AccessReview

Time to Move to the Single-Cell Level: Applications of Single-Cell Multi-Omics to Hematological Malignancies and Waldenström’s Macroglobulinemia—A Particularly Heterogeneous Lymphoma

by Ramón García-Sanz and Cristina Jiménez

Cancers 2021, 13(7), 1541; https://doi.org/10.3390/cancers13071541 - 26 Mar 2021

Cited by 8 | Viewed by 2616

Abstract

Single-cell sequencing techniques have become a powerful tool for characterizing intra-tumor heterogeneity, which has been reflected in the increasing number of studies carried out and reported. We have rigorously reviewed and compiled the information about these techniques inasmuch as they are relative to [...] Read more.

Single-cell sequencing techniques have become a powerful tool for characterizing intra-tumor heterogeneity, which has been reflected in the increasing number of studies carried out and reported. We have rigorously reviewed and compiled the information about these techniques inasmuch as they are relative to the area of hematology to provide a practical view of their potential applications. Studies show how single-cell multi-omics can overcome the limitations of bulk sequencing and be applied at all stages of tumor development, giving insights into the origin and pathogenesis of the tumors, the clonal architecture and evolution, or the mechanisms of therapy resistance. Information at the single-cell level may help resolve questions related to intra-tumor heterogeneity that have not been previously explained by other techniques. With that in mind, we review the existing knowledge about a heterogeneous lymphoma called Waldenström’s macroglobulinemia and discuss how single-cell studies may help elucidate the underlying causes of this heterogeneity. Full article

(This article belongs to the Special Issue Systems Biology and Intra-tumor Heterogeneity)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Systems Biology and Intra-tumor Heterogeneity

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (11 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI