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Genomics and Proteomics of Cancer

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Oncology".

Deadline for manuscript submissions: 20 April 2025 | Viewed by 2148

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Occupational Medicine, Department of Clinical and Molecular Sciences, Polytechnic University of Marche, 60126 Ancona, Italy
Interests: cancer cell proteomic profile; new anticancer therapy; cancer related signaling pathways
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Carcinogenesis, tumor growth, and cancer progression are classified as complex multifactorial tissue-dependent processes. Furthermore, tumor growth and progression are primarily stimulated by genetic predispositions or environmental causes, or a combination of the two. Genetic and epigenetic modifications are important in many diseases, especially in cancer development where cells are able to proliferate and escape the mechanisms that normally control their survival and migration. Cancer cells show extensive alterations in protein expression levels and in protein phosphorylation. A complete characterization of the altered proteins in cancer versus normal cells can also help explain multidrug resistance, therapy-related side effects, and disease recurrence after therapy. Proteomic profile data can be used to elucidate cancer biology and metastasis processes in detail and drive the development of novel drug targets.

This Special Issue of IJMS focuses on the proteins involved in the signaling pathways implicated in cancer biogenesis and progress.

Dr. Raffaella Lazzarini
Guest Editor

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Keywords

  • cancer
  • carcinogenesis
  • genetic
  • epigenetic modification
  • protein expression
  • protein phosphorylation
  • proteomic

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Published Papers (1 paper)

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Research

39 pages, 21725 KiB  
Article
Unveiling the Dynamics behind Glioblastoma Multiforme Single-Cell Data Heterogeneity
by Marcos Guilherme Vieira Junior , Adriano Maurício de Almeida Côrtes, Flávia Raquel Gonçalves Carneiro, Nicolas Carels and Fabrício Alves Barbosa da Silva
Int. J. Mol. Sci. 2024, 25(9), 4894; https://doi.org/10.3390/ijms25094894 - 30 Apr 2024
Cited by 1 | Viewed by 1526
Abstract
Glioblastoma Multiforme is a brain tumor distinguished by its aggressiveness. We suggested that this aggressiveness leads single-cell RNA-sequence data (scRNA-seq) to span a representative portion of the cancer attractors domain. This conjecture allowed us to interpret the scRNA-seq heterogeneity as reflecting a representative [...] Read more.
Glioblastoma Multiforme is a brain tumor distinguished by its aggressiveness. We suggested that this aggressiveness leads single-cell RNA-sequence data (scRNA-seq) to span a representative portion of the cancer attractors domain. This conjecture allowed us to interpret the scRNA-seq heterogeneity as reflecting a representative trajectory within the attractor’s domain. We considered factors such as genomic instability to characterize the cancer dynamics through stochastic fixed points. The fixed points were derived from centroids obtained through various clustering methods to verify our method sensitivity. This methodological foundation is based upon sample and time average equivalence, assigning an interpretative value to the data cluster centroids and supporting parameters estimation. We used stochastic simulations to reproduce the dynamics, and our results showed an alignment between experimental and simulated dataset centroids. We also computed the Waddington landscape, which provided a visual framework for validating the centroids and standard deviations as characterizations of cancer attractors. Additionally, we examined the stability and transitions between attractors and revealed a potential interplay between subtypes. These transitions might be related to cancer recurrence and progression, connecting the molecular mechanisms of cancer heterogeneity with statistical properties of gene expression dynamics. Our work advances the modeling of gene expression dynamics and paves the way for personalized therapeutic interventions. Full article
(This article belongs to the Special Issue Genomics and Proteomics of Cancer)
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