Loss of long-range co-expression is a common trait in cancer

García-Cortés, Diana; Hernández‐Lemus, Enrique; Espinal-Enríquez, Jesús

doi:10.1101/2022.10.27.513947

Cited by 8 publications

(16 citation statements)

References 97 publications

(130 reference statements)

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“…These genes are mainly over-expressed in every HCs. The large set of co-expressed ribonucleoprotein interchromosome genes, has been also reported in networks from other 15 cancer tissues (17). In the present work, the communities detected in this cluster were enriched for cytosplasmatic translation and other processes related with RNA processing.…”

Section: R a F Tsupporting

confidence: 76%

Section: Resultsmentioning

confidence: 87%

“…Several of these pseudogenes are also present in the intersection network, and are mainly overexpressed in all HCs. A large set of co-expressed riboprotein inter-chromosome genes has been also reported in networks from other 15 cancer tissues (16). We also found clusters of protein coding genes of ribonucleoproteins in our HCs.…”

Section: Resultsmentioning

confidence: 94%

“…From these analysis we have identified two main common phenomena between the different cancer GCNs: 1) an elevated proportion of strong interactions between genes from the same chromosomes (intra-chromosomal interactions) in comparison to the network of their respective normal tissue, and 2) the size of cancer-derived networks connected components is much smaller than those observed in a normal-derived GCN. We refer to this phenomenon as loss of inter-chromosomal co-expression and it has been observed in each cancer GCN that we have analyzed (16).…”

Section: Introductionmentioning

confidence: 99%

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The network structure of hematopoietic cancers

Nakamura-García

Espinal-Enríquez

2022

Preprint

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Hematopoietic cancers (HCs) are a heterogeneous group of malignancies that affect blood, bone marrow and lymphatic system. Despite arising from derivatives of hematopoietic stem cells, each disease has a unique set of characterizing genomic irregularities. Gene co-expression networks (GCNs) have been useful to analyze and integrate information of cancer transcriptomes. Here, we explored the co-expression landscape in HC, by inferring GCNs from four hematopoietic cancers (B and T-cell acute leukemia, -BALL, TALL-, acute myeloid leukemia -AML- and multiple myeloma -MM-) as well as non-cancer bone marrow. We characterized their structure (topological features) and function (enrichment analyses). We found that, as in other types of cancer, the highest co-expression interactions are intra-chromosomal, which is not the case for control GCNs. We also detected a highly co-expressed group of overexpressed pseudogenes in HC networks. The four GCNs present only a small fraction of common interactions, related to canonical functions, like immune response or erythrocyte differentiation. Those genes are differentially expressed in a unique fashion for each HC. For instance, cell cycle-associated genes are underexpressed in MM and AML, slightly overexpressed in BALL but highly overexpressed in TALL. With this approach, we are able to reveal cancer-specific features useful for detection of disease manifestations.

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Section: R a F Tsupporting

confidence: 76%

Section: Resultsmentioning

confidence: 87%

Section: Resultsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The network structure of hematopoietic cancers

Nakamura-García

Espinal-Enríquez

2022

Preprint

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“…The raw gene expression count values from human lung samples were preprocessed as follows: Initially, the mean of the counts for each gene across the samples was calculated. Genes with a mean below 10 were removed, and genes with zero count values in more than 50% of the samples were discarded (García-Cortés et al, 2022). Subsequently, the dataset was quantile normalized using the qnorm 0.8.1 library.…”

Section: Methodsmentioning

confidence: 99%

Transcriptomic signatures and network-based methods uncover new Senescent Cell Anti-Apoptotic Pathways and Senolytics

Olascoaga,

Konigsberg,

Espinal-Enríquez

et al. 2024

Preprint

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Cellular senescence is an irreversible cell cycle arrest caused by various stressors that damage cells. Over time, senescent cells accumulate and contribute to the progression of multiple age-related degenerative diseases. It is believed that these cells accumulate partly due to their ability to evade programmed cell death through the development and activation of survival and anti-apoptotic resistance mechanisms; however, many aspects of how these survival mechanisms develop and activate are still unknown. By analyzing transcriptomic signature profiles generated by the LINCS L1000 project and using network-based methods, we identified various genes that could represent new senescence-related survival mechanisms. Additionally, employing the same methodology, we identified over 600 molecules with potential senolytic activity. Experimental validation of our computational findings confirmed the senolytic activity of Fluorouracil, whose activity would be mediated by a multi-target mechanism, revealing that its targets AURKA, EGFR, IRS1, SMAD4, and KRAS are new senescence-associated survival and anti-apoptotic resistance pathways. The development of these pathways could depend on the stimulus that induces cellular senescence. The SCAPs development and activation mechanisms proposed in this work offer new insights into how senescent cells survive. Identifying new anti-apoptotic resistance targets and drugs with potential senolytic activity paves the way for developing new pharmacological therapies to eliminate senescent cells selectively.Graphical Abstract

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The network structure of hematopoietic cancers

Nakamura-García,

Espinal-Enríquez

2023

Sci Rep

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Hematopoietic cancers (HCs) are a heterogeneous group of malignancies that affect blood, bone marrow and lymphatic system. Here, by analyzing 1960 RNA-Seq samples from three independent datasets, we explored the co-expression landscape in HCs, by inferring gene co-expression networks (GCNs) with four cancer phenotypes (B and T-cell acute leukemia -BALL, TALL-, acute myeloid leukemia -AML-, and multiple myeloma -MM-) as well as non-cancer bone marrow. We characterized their structure (topological features) and function (enrichment analyses). We found that, as in other types of cancer, the highest co-expression interactions are intra-chromosomal, which is not the case for control GCNs. We also detected a highly co-expressed group of overexpressed pseudogenes in HC networks. The four GCNs present only a small fraction of common interactions, related to canonical functions, like immune response or erythrocyte differentiation. With this approach, we were able to reveal cancer-specific features useful for detection of disease manifestations.

show abstract

Loss of long-range co-expression is a common trait in cancer

Cited by 8 publications

References 97 publications

The network structure of hematopoietic cancers

The network structure of hematopoietic cancers

Transcriptomic signatures and network-based methods uncover new Senescent Cell Anti-Apoptotic Pathways and Senolytics

The network structure of hematopoietic cancers

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