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Cancers
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Multi-Omics Approaches in Oncology
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Multi-Omics Approaches in Oncology

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Molecular Cancer Biology".

Deadline for manuscript submissions: closed (10 April 2022) | Viewed by 39808

Special Issue Editor

Prof. Dr. Jerome Solassol

E-Mail Website
Guest Editor
1. Faculty of Medicine, University of Montpellier, 34090 Montpellier, France
2. Montpellier Research Cancer Institute (IRCM), Institut National de la Santé et de la Recherche Médicale (INSERM) U1194, University of Montpellier, 34298 Montpellier, France
3. Department of Pathology and Onco-Biology, Centre Hospitalier Universitaire (CHU) Montpellier, 34295 Montpellier, France
Interests: genomics; proteomics; biomarkers; system biology; precision therapy

Special Issue Information

Dear Colleagues,

With the development of personalized medicine, antitumor therapy, including tyrosine kinase and immune checkpoint inhibitors, is now based on individual patient profiles. While a single type of omics study can provide a significant amount of information at a specific level (e.g., genomics for the mutational landscapes of cancer patients), the complexity of cancer–host interactions can only be addressed by combining complementary approaches (such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics) to provide a complete picture of tumor abnormalities. Therefore, multi-omics-based subtype analysis encompassing proteome and phosphoproteome profiling of cancerous tissues, in conjunction with genomic analysis, offers the promise of better elucidating the intertwining of cancer signaling and key metabolic pathways. This combinatorial approach leads to the possible discovery of more effective diagnostic tools and new therapeutic opportunities for patients. 

The purpose of this Special Issue is to explore the expanding diversity of mechanisms that regulate oncodriver activation and signaling in human cancer that may provide new opportunities for personalized anti-cancer therapies. This Special Issue welcomes both reviews as well as original research articles by 30 June 2021. 

Prof. Dr. Jérôme Solassol
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • genomics
  • proteomics
  • biomarkers
  • system biology
  • precision therapy
  • kinase inhibitors

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Published Papers (9 papers)

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Research

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30 pages, 7362 KiB  
Article
Integrated Multi-Omics Maps of Lower-Grade Gliomas
by Hans Binder, Maria Schmidt, Lydia Hopp, Suren Davitavyan, Arsen Arakelyan and Henry Loeffler-Wirth
Cancers 2022, 14(11), 2797; https://doi.org/10.3390/cancers14112797 - 4 Jun 2022
Cited by 8 | Viewed by 3608
Abstract
Multi-omics high-throughput technologies produce data sets which are not restricted to only one but consist of multiple omics modalities, often as patient-matched tumour specimens. The integrative analysis of these omics modalities is essential to obtain a holistic view on the otherwise fragmented information [...] Read more.
Multi-omics high-throughput technologies produce data sets which are not restricted to only one but consist of multiple omics modalities, often as patient-matched tumour specimens. The integrative analysis of these omics modalities is essential to obtain a holistic view on the otherwise fragmented information hidden in this data. We present an intuitive method enabling the combined analysis of multi-omics data based on self-organizing maps machine learning. It “portrays” the expression, methylation and copy number variations (CNV) landscapes of each tumour using the same gene-centred coordinate system. It enables the visual evaluation and direct comparison of the different omics layers on a personalized basis. We applied this combined molecular portrayal to lower grade gliomas, a heterogeneous brain tumour entity. It classifies into a series of molecular subtypes defined by genetic key lesions, which associate with large-scale effects on DNA methylation and gene expression, and in final consequence, drive with cell fate decisions towards oligodendroglioma-, astrocytoma- and glioblastoma-like cancer cell lineages with different prognoses. Consensus modes of concerted changes of expression, methylation and CNV are governed by the degree of co-regulation within and between the omics layers. The method is not restricted to the triple-omics data used here. The similarity landscapes reflect partly independent effects of genetic lesions and DNA methylation with consequences for cancer hallmark characteristics such as proliferation, inflammation and blocked differentiation in a subtype specific fashion. It can be extended to integrate other omics features such as genetic mutation, protein expression data as well as extracting prognostic markers. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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22 pages, 7735 KiB  
Article
Transcriptomics and Metabolomics Integration Reveals Redox-Dependent Metabolic Rewiring in Breast Cancer Cells
by Marcella Bonanomi, Noemi Salmistraro, Giulia Fiscon, Federica Conte, Paola Paci, Valentina Bravatà, Giusi Irma Forte, Tatiana Volpari, Manuela Scorza, Fabrizia Mastroianni, Stefano D’Errico, Elenio Avolio, Gennaro Piccialli, Anna Maria Colangelo, Marco Vanoni, Daniela Gaglio and Lilia Alberghina
Cancers 2021, 13(20), 5058; https://doi.org/10.3390/cancers13205058 - 9 Oct 2021
Cited by 11 | Viewed by 3670
Abstract
Rewiring glucose metabolism toward aerobic glycolysis provides cancer cells with a rapid generation of pyruvate, ATP, and NADH, while pyruvate oxidation to lactate guarantees refueling of oxidized NAD+ to sustain glycolysis. CtPB2, an NADH-dependent transcriptional co-regulator, has been proposed to work as [...] Read more.
Rewiring glucose metabolism toward aerobic glycolysis provides cancer cells with a rapid generation of pyruvate, ATP, and NADH, while pyruvate oxidation to lactate guarantees refueling of oxidized NAD+ to sustain glycolysis. CtPB2, an NADH-dependent transcriptional co-regulator, has been proposed to work as an NADH sensor, linking metabolism to epigenetic transcriptional reprogramming. By integrating metabolomics and transcriptomics in a triple-negative human breast cancer cell line, we show that genetic and pharmacological down-regulation of CtBP2 strongly reduces cell proliferation by modulating the redox balance, nucleotide synthesis, ROS generation, and scavenging. Our data highlight the critical role of NADH in controlling the oncogene-dependent crosstalk between metabolism and the epigenetically mediated transcriptional program that sustains energetic and anabolic demands in cancer cells. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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18 pages, 1576 KiB  
Article
Integrative cBioPortal Analysis Revealed Molecular Mechanisms That Regulate EGFR-PI3K-AKT-mTOR Pathway in Diffuse Gliomas of the Brain
by Petar Brlek, Anja Kafka, Anja Bukovac and Nives Pećina-Šlaus
Cancers 2021, 13(13), 3247; https://doi.org/10.3390/cancers13133247 - 29 Jun 2021
Cited by 19 | Viewed by 6212
Abstract
Diffuse gliomas are a heterogeneous group of tumors with aggressive biological behavior and a lack of effective treatment methods. Despite new molecular findings, the differences between pathohistological types still require better understanding. In this in silico analysis, we investigated AKT1, AKT2, [...] Read more.
Diffuse gliomas are a heterogeneous group of tumors with aggressive biological behavior and a lack of effective treatment methods. Despite new molecular findings, the differences between pathohistological types still require better understanding. In this in silico analysis, we investigated AKT1, AKT2, AKT3, CHUK, GSK3β, EGFR, PTEN, and PIK3AP1 as participants of EGFR-PI3K-AKT-mTOR signaling using data from the publicly available cBioPortal platform. Integrative large-scale analyses investigated changes in copy number aberrations (CNA), methylation, mRNA transcription and protein expression within 751 samples of diffuse astrocytomas, anaplastic astrocytomas and glioblastomas. The study showed a significant percentage of CNA in PTEN (76%), PIK3AP1 and CHUK (75% each), EGFR (74%), AKT2 (39%), AKT1 (32%), AKT3 (19%) and GSK3β (18%) in the total sample. Comprehensive statistical analyses show how genomics and epigenomics affect the expression of examined genes differently across various pathohistological types and grades, suggesting that genes AKT3, CHUK and PTEN behave like tumor suppressors, while AKT1, AKT2, EGFR, and PIK3AP1 show oncogenic behavior and are involved in enhanced activity of the EGFR-PI3K-AKT-mTOR signaling pathway. Our findings contribute to the knowledge of the molecular differences between pathohistological types and ultimately offer the possibility of new treatment targets and personalized therapies in patients with diffuse gliomas. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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17 pages, 3324 KiB  
Article
Pan-Cancer Analysis of Human Kinome Gene Expression and Promoter DNA Methylation Identifies Dark Kinase Biomarkers in Multiple Cancers
by Siddesh Southekal, Nitish Kumar Mishra and Chittibabu Guda
Cancers 2021, 13(6), 1189; https://doi.org/10.3390/cancers13061189 - 10 Mar 2021
Cited by 13 | Viewed by 4242
Abstract
Kinases are a group of intracellular signaling molecules that play critical roles in various biological processes. Even though kinases comprise one of the most well-known therapeutic targets, many have been understudied and therefore warrant further investigation. DNA methylation is one of the key [...] Read more.
Kinases are a group of intracellular signaling molecules that play critical roles in various biological processes. Even though kinases comprise one of the most well-known therapeutic targets, many have been understudied and therefore warrant further investigation. DNA methylation is one of the key epigenetic regulators that modulate gene expression. In this study, the human kinome’s DNA methylation and gene expression patterns were analyzed using the level-3 TCGA data for 32 cancers. Unsupervised clustering based on kinome data revealed the grouping of cancers based on their organ level and tissue type. We further observed significant differences in overall kinase methylation levels (hyper- and hypomethylation) between the tumor and adjacent normal samples from the same tissue. Methylation expression quantitative trait loci (meQTL) analysis using kinase gene expression with the corresponding methylated probes revealed a highly significant and mostly negative association (~92%) within 1.5 kb from the transcription start site (TSS). Several understudied (dark) kinases (PKMYT1, PNCK, BRSK2, ERN2, STK31, STK32A, and MAPK4) were also identified with a significant role in patient survival. This study leverages results from multi-omics data to identify potential kinase markers of prognostic and diagnostic importance and further our understanding of kinases in cancer. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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19 pages, 2138 KiB  
Article
Widespread Aberrant Alternative Splicing despite Molecular Remission in Chronic Myeloid Leukaemia Patients
by Ulf Schmitz, Jaynish S. Shah, Bijay P. Dhungel, Geoffray Monteuuis, Phuc-Loi Luu, Veronika Petrova, Cynthia Metierre, Shalima S. Nair, Charles G. Bailey, Verity A. Saunders, Ali G. Turhan, Deborah L. White, Susan Branford, Susan J. Clark, Timothy P. Hughes, Justin J.-L. Wong and John E.J. Rasko
Cancers 2020, 12(12), 3738; https://doi.org/10.3390/cancers12123738 - 11 Dec 2020
Cited by 9 | Viewed by 4376
Abstract
Vast transcriptomics and epigenomics changes are characteristic of human cancers, including leukaemia. At remission, we assume that these changes normalise so that omics-profiles resemble those of healthy individuals. However, an in-depth transcriptomic and epigenomic analysis of cancer remission has not been undertaken. A [...] Read more.
Vast transcriptomics and epigenomics changes are characteristic of human cancers, including leukaemia. At remission, we assume that these changes normalise so that omics-profiles resemble those of healthy individuals. However, an in-depth transcriptomic and epigenomic analysis of cancer remission has not been undertaken. A striking exemplar of targeted remission induction occurs in chronic myeloid leukaemia (CML) following tyrosine kinase inhibitor (TKI) therapy. Using RNA sequencing and whole-genome bisulfite sequencing, we profiled samples from chronic-phase CML patients at diagnosis and remission and compared these to healthy donors. Remarkably, our analyses revealed that abnormal splicing distinguishes remission samples from normal controls. This phenomenon is independent of the TKI drug used and in striking contrast to the normalisation of gene expression and DNA methylation patterns. Most remarkable are the high intron retention (IR) levels that even exceed those observed in the diagnosis samples. Increased IR affects cell cycle regulators at diagnosis and splicing regulators at remission. We show that aberrant splicing in CML is associated with reduced expression of specific splicing factors, histone modifications and reduced DNA methylation. Our results provide novel insights into the changing transcriptomic and epigenomic landscapes of CML patients during remission. The conceptually unanticipated observation of widespread aberrant alternative splicing after remission induction warrants further exploration. These results have broad implications for studying CML relapse and treating minimal residual disease. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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21 pages, 3651 KiB  
Article
Proximal Protein Interaction Landscape of RAS Paralogs
by Benoît Béganton, Etienne Coyaud, Estelle M. N. Laurent, Alain Mangé, Julien Jacquemetton, Muriel Le Romancer, Brian Raught and Jérôme Solassol
Cancers 2020, 12(11), 3326; https://doi.org/10.3390/cancers12113326 - 11 Nov 2020
Cited by 7 | Viewed by 3922
Abstract
RAS proteins (KRAS, NRAS and HRAS) are frequently activated in different cancer types (e.g., non-small cell lung cancer, colorectal cancer, melanoma and bladder cancer). For many years, their activities were considered redundant due to their high degree of sequence homology (80% identity) and [...] Read more.
RAS proteins (KRAS, NRAS and HRAS) are frequently activated in different cancer types (e.g., non-small cell lung cancer, colorectal cancer, melanoma and bladder cancer). For many years, their activities were considered redundant due to their high degree of sequence homology (80% identity) and their shared upstream and downstream protein partners. However, the high conservation of the Hyper-Variable-Region across mammalian species, the preferential activation of different RAS proteins in specific tumor types and the specific post-translational modifications and plasma membrane-localization of each paralog suggest they could ensure discrete functions. To gain insights into RAS proteins specificities, we explored their proximal protein–protein interaction landscapes using the proximity-dependent biotin identification technology (BioID) in Flp-In T-REx 293 cell lines stably transfected and inducibly expressing wild type KRAS4B, NRAS or HRAS. We identified more than 800 high-confidence proximal interactors, allowing us to propose an unprecedented comparative analysis of wild type RAS paralogs protein networks. These data bring novel information on poorly characterized RAS functions, e.g., its putative involvement in metabolic pathways, and on shared as well as paralog-specific protein networks that could partially explain the complexity of RAS functions. These networks of protein interactions open numerous avenues to better understand RAS paralogs biological activities. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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Review

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24 pages, 772 KiB  
Review
Toward More Comprehensive Homologous Recombination Deficiency Assays in Ovarian Cancer, Part 1: Technical Considerations
by Stanislas Quesada, Michel Fabbro and Jérôme Solassol
Cancers 2022, 14(5), 1132; https://doi.org/10.3390/cancers14051132 - 23 Feb 2022
Cited by 10 | Viewed by 3186
Abstract
High-grade serous ovarian cancer (HGSOC), the most frequent and lethal form of ovarian cancer, exhibits homologous recombination deficiency (HRD) in 50% of cases. In addition to mutations in BRCA1 and BRCA2, which are the best known thus far, defects can also be [...] Read more.
High-grade serous ovarian cancer (HGSOC), the most frequent and lethal form of ovarian cancer, exhibits homologous recombination deficiency (HRD) in 50% of cases. In addition to mutations in BRCA1 and BRCA2, which are the best known thus far, defects can also be caused by diverse alterations to homologous recombination-related genes or epigenetic patterns. HRD leads to genomic instability (genomic scars) and is associated with PARP inhibitor (PARPi) sensitivity. HRD is currently assessed through BRCA1/2 analysis, which produces a genomic instability score (GIS). However, despite substantial clinical achievements, FDA-approved companion diagnostics (CDx) based on GISs have important limitations. Indeed, despite the use of GIS in clinical practice, the relevance of such assays remains controversial. Although international guidelines include companion diagnostics as part of HGSOC frontline management, they also underscore the need for more powerful and alternative approaches for assessing patient eligibility to PARP inhibitors. In these companion reviews, we review and present evidence to date regarding HRD definitions, achievements and limitations in HGSOC. Part 1 is dedicated to technical considerations and proposed perspectives that could lead to a more comprehensive and dynamic assessment of HR, while Part 2 provides a more integrated approach for clinicians. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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21 pages, 373 KiB  
Review
Toward More Comprehensive Homologous Recombination Deficiency Assays in Ovarian Cancer Part 2: Medical Perspectives
by Stanislas Quesada, Michel Fabbro and Jérôme Solassol
Cancers 2022, 14(4), 1098; https://doi.org/10.3390/cancers14041098 - 21 Feb 2022
Cited by 11 | Viewed by 3081
Abstract
High-grade serous ovarian cancer (HGSOC) is the most frequent and aggressive form of ovarian cancer, representing an important challenge for clinicians. Half of HGSOC cases have homologous recombination deficiency (HRD), which has specific causes (mainly alterations in BRCA1/2, but also other alterations [...] Read more.
High-grade serous ovarian cancer (HGSOC) is the most frequent and aggressive form of ovarian cancer, representing an important challenge for clinicians. Half of HGSOC cases have homologous recombination deficiency (HRD), which has specific causes (mainly alterations in BRCA1/2, but also other alterations encompassed by the BRCAness concept) and consequences, both at molecular (e.g., genomic instability) and clinical (e.g., sensitivity to PARP inhibitor) levels. Based on its prevalence and clinical impact, HRD status merits investigation. To date, three PARP inhibitors have received FDA/EMA approval. For some approvals, the presence of specific molecular alterations is required. Three companion diagnostic (CDx) assays based on distinct technical and medical considerations have received FDA approval to date. However, their use remains controversial due to their technical and medical limitations. In this companion and integrated review, we take a “bench-to-bedside” perspective on HRD definition and evaluation in the context of HGSOC. Part 1 of the review adopts a molecular perspective regarding technical considerations and the development of CDx. Part 2 focuses on the clinical impact of HRD evaluation, primarily through currently validated CDx and prescription of PARP inhibitors, outlining achievements, limitations and medical perspectives. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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20 pages, 1117 KiB  
Review
Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches
by Nuria Gómez-Cebrián, José Luis Poveda, Antonio Pineda-Lucena and Leonor Puchades-Carrasco
Cancers 2022, 14(3), 596; https://doi.org/10.3390/cancers14030596 - 25 Jan 2022
Cited by 11 | Viewed by 4801
Abstract
Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In [...] Read more.
Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors. Full article
(This article belongs to the Special Issue Multi-Omics Approaches in Oncology)
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