bims-ectoca 2022-11-06 papers

bims-ectoca

Biomed News

on Epigenetic control of tolerance in cancer

Issue of 2022–11–06
nine papers selected by
Ankita Daiya, Birla Institute of Technology and Science

Selective advantage of epigenetically disrupted cancer cells via phenotypic inertia.
Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data.
Stress granules dynamics: benefits in cancer.
Superenhancers activate the autophagy-related genes Beclin1 and LC3B to drive metastasis and drug resistance in osteosarcoma.
Investigating Interactions Between Histone Modifying Enzymes and Transcription Factors in vivo by Fluorescence Resonance Energy Transfer.
Heterogeneity of the cancer cell line metabolic landscape.
Tumor glycolysis, an essential sweet tooth of tumor cells.
p62 bodies: phase separation, NRF2 activation, and selective autophagic degradation.
LncTarD 2.0: an updated comprehensive database for experimentally-supported functional lncRNA-target regulations in human diseases.

Cancer Cell. 2022 Oct 27. pii: S1535-6108(22)00493-7. [Epub ahead of print]

Selective advantage of epigenetically disrupted cancer cells via phenotypic inertia.

Ioannis Loukas, Fabrizio Simeoni, Marta Milan, Paolo Inglese, Harshil Patel, Robert Goldstone, Philip East, Stephanie Strohbuecker, Richard Mitter, Bhavik Talsania, Wenhao Tang, Colin D H Ratcliffe, Erik Sahai, Vahid Shahrezaei, Paola Scaffidi.

  The evolution of established cancers is driven by selection of cells with enhanced fitness. Subclonal mutations in numerous epigenetic regulator genes are common across cancer types, yet their functional impact has been unclear. Here, we show that disruption of the epigenetic regulatory network increases the tolerance of cancer cells to unfavorable environments experienced within growing tumors by promoting the emergence of stress-resistant subpopulations. Disruption of epigenetic control does not promote selection of genetically defined subclones or favor a phenotypic switch in response to environmental changes. Instead, it prevents cells from mounting an efficient stress response via modulation of global transcriptional activity. This "transcriptional numbness" lowers the probability of cell death at early stages, increasing the chance of long-term adaptation at the population level. Our findings provide a mechanistic explanation for the widespread selection of subclonal epigenetic-related mutations in cancer and uncover phenotypic inertia as a cellular trait that drives subclone expansion.

Keywords:  adaptation; cancer epigenetics; chromatin modifiers; environmental stress; mechanisms of cancer evolution; mutations; pan-cancer; plasticity; subclonal; tumor microenvironment

DOI:  https://doi.org/10.1016/j.ccell.2022.10.002
Nat Commun. 2022 Oct 30. 13(1): 6494

Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data.

Junyi Chen, Xiaoying Wang, Anjun Ma, Qi-En Wang, Bingqiang Liu, Lang Li, Dong Xu, Qin Ma.

Drug screening data from massive bulk gene expression databases can be analyzed to determine the optimal clinical application of cancer drugs. The growing amount of single-cell RNA sequencing (scRNA-seq) data also provides insights into improving therapeutic effectiveness by helping to study the heterogeneity of drug responses for cancer cell subpopulations. Developing computational approaches to predict and interpret cancer drug response in single-cell data collected from clinical samples can be very useful. We propose scDEAL, a deep transfer learning framework for cancer drug response prediction at the single-cell level by integrating large-scale bulk cell-line data. The highlight in scDEAL involves harmonizing drug-related bulk RNA-seq data with scRNA-seq data and transferring the model trained on bulk RNA-seq data to predict drug responses in scRNA-seq. Another feature of scDEAL is the integrated gradient feature interpretation to infer the signature genes of drug resistance mechanisms. We benchmark scDEAL on six scRNA-seq datasets and demonstrate its model interpretability via three case studies focusing on drug response label prediction, gene signature identification, and pseudotime analysis. We believe that scDEAL could help study cell reprogramming, drug selection, and repurposing for improving therapeutic efficacy.

DOI: https://doi.org/10.1038/s41467-022-34277-7
BMB Rep. 2022 Oct 31. pii: 5716. [Epub ahead of print]

Stress granules dynamics: benefits in cancer.

Jeong In Lee, Sim Namkoong.

Stress granules (SGs) are stress-induced subcellular compartments, which carry out a particular function to cope with stress. These granules protect cells from stress-related damage and cell death through dynamic sequestration of numerous ribonucleoproteins (RNPs) and signaling proteins, thereby promoting cell survival under both physiological and pathological condition. During tumorigenesis, cancer cells are repeatedly exposed to diverse stress stimuli from the tumor microenvironment, and the dynamics of SGs is often modulated due to the alteration of gene expression patterns in cancer cells, leading to tumor progression as well as resistance to anticancer treatment. In this mini review, we provide a brief discussion about our current understanding of the fundamental roles of SGs during physiological stress and the effect of dysregulated SGs on cancer cell fitness and cancer therapy.
Front Med. 2022 Nov 05.

Superenhancers activate the autophagy-related genes Beclin1 and LC3B to drive metastasis and drug resistance in osteosarcoma.

Hongyi Wang, Zhuochao Liu, Jun Wang, Fangqiong Hu, Qi Zhou, Li Wei, Qiyuan Bao, Jizhuang Wang, Jing Liang, Zhihong Liu, Weibin Zhang.

  Metastasis and drug resistance are the leading causes of poor prognosis in patients with osteosarcoma. Identifying the relevant factors that drive metastasis and drug resistance is the key to improving the therapeutic outcome of osteosarcoma. Here, we reported that autophagy was highly activated in metastatic osteosarcoma. We found increased autophagolysosomes in metastatic osteosarcoma cell lines by using electron microscopy, Western blot, and immunofluorescence experiments. We further examined the expression of the autophagy-related genes Beclin1 and LC3B in 82 patients through immunohistochemistry and found that Beclin1 and LC3B were highly related to unfavorable prognosis of osteosarcoma. Knockdown of Beclin1 and LC3B reduced invasion, metastasis, and proliferation in metastatic osteosarcoma cells. In vitro and in vivo studies also demonstrated that inhibiting by 3-MA inhibited cell growth and metastasis. Moreover, we demonstrated that autophagy-related genes were activated by SEs and that the inhibition of SEs by JQ-1 decreased the metastasis of osteosarcoma. Overall, our findings highlighted the association of autophagy with osteosarcoma progression and shed new light on autophagy-targeting therapy for osteosarcoma.

Keywords:  Beclin1; LC3B; autophagy; drug resistance; metastasis; osteosarcoma

DOI:  https://doi.org/10.1007/s11684-022-0919-0
J Vis Exp. 2022 Oct 14.

Investigating Interactions Between Histone Modifying Enzymes and Transcription Factors in vivo by Fluorescence Resonance Energy Transfer.

Mi Sa Vo Phan, Phu Tri Tran, Vitaly Citovsky.

Epigenetic regulation of gene expression is commonly affected by histone modifying enzymes (HMEs) that generate heterochromatic or euchromatic histone marks for transcriptional repression or activation, respectively. HMEs are recruited to their target chromatin by transcription factors (TFs). Thus, detecting and characterizing direct interactions between HMEs and TFs are critical for understanding their function and specificity better. These studies would be more biologically relevant if performed in vivo within living tissues. Here, a protocol is described for visualizing interactions in plant leaves between a plant histone deubiquitinase and a plant transcription factor using fluorescence resonance energy transfer (FRET), which allows the detection of complexes between protein molecules that are within <10 nm from each other. Two variations of the FRET technique are presented: SE-FRET (sensitized emission) and AB-FRET (acceptor bleaching), in which the energy is transferred non-radiatively from the donor to the acceptor or emitted radiatively by the donor upon photobleaching of the acceptor. Both SE-FRET and AB-FRET approaches can be adapted easily to discover other interactions between other proteins in planta.

DOI: https://doi.org/10.3791/64656
Mol Syst Biol. 2022 11;18(11): e11006

Heterogeneity of the cancer cell line metabolic landscape.

David Shorthouse, Jenna Bradley, Susan E Critchlow, Claus Bendtsen, Benjamin A Hall.

  The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 different species using mass spectrometry (MS). We correlate known cancer-associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.

Keywords:  cancer; heterogeneity; metabolomics; mutation

DOI:  https://doi.org/10.15252/msb.202211006
Semin Cancer Biol. 2022 Oct 28. pii: S1044-579X(22)00204-8. [Epub ahead of print]86(Pt 3): 1216-1230

Tumor glycolysis, an essential sweet tooth of tumor cells.

Sumana Paul, Saikat Ghosh, Sushil Kumar.

  Cancer cells undergo metabolic alterations to meet the immense demand for energy, building blocks, and redox potential. Tumors show glucose-avid and lactate-secreting behavior even in the presence of oxygen, a process known as aerobic glycolysis. Glycolysis is the backbone of cancer cell metabolism, and cancer cells have evolved various mechanisms to enhance it. Glucose metabolism is intertwined with other metabolic pathways, making cancer metabolism diverse and heterogeneous, where glycolysis plays a central role. Oncogenic signaling accelerates the metabolic activities of glycolytic enzymes, mainly by enhancing their expression or by post-translational modifications. Aerobic glycolysis ferments glucose into lactate which supports tumor growth and metastasis by various mechanisms. Herein, we focused on tumor glycolysis, especially its interactions with the pentose phosphate pathway, glutamine metabolism, one-carbon metabolism, and mitochondrial oxidation. Further, we describe the role and regulation of key glycolytic enzymes in cancer. We summarize the role of lactate, an end product of glycolysis, in tumor growth, and the metabolic adaptations during metastasis. Lastly, we briefly discuss limitations and future directions to improve our understanding of glucose metabolism in cancer.

Keywords:  Cancer metabolism; Lactate; Metastasis; Tumor glycolysis; metabolic adaptations

DOI:  https://doi.org/10.1016/j.semcancer.2022.09.007
IUBMB Life. 2022 Nov 04.

p62 bodies: phase separation, NRF2 activation, and selective autophagic degradation.

Masaaki Komatsu.

  When p62/Sequestosome-1 binds to a ubiquitinated protein, it undergoes liquid-liquid phase separation and forms a membraneless organelle, p62 body. There are two major physiological functions of the p62 body. One is effective autophagic degradation of ubiquitinated proteins and the other is antioxidant stress response, both of which contribute to cellular homeostasis. In this review, I review the history of p62 research in relation to autophagy and outline the formation, degradation, and physiological functions of the p62 body. This article is protected by copyright. All rights reserved.

Keywords:  KEAP1; NRF2; autophagy; p62; phase separation

DOI:  https://doi.org/10.1002/iub.2689
Nucleic Acids Res. 2022 Nov 02. pii: gkac984. [Epub ahead of print]

LncTarD 2.0: an updated comprehensive database for experimentally-supported functional lncRNA-target regulations in human diseases.

Hongying Zhao, Xiangzhe Yin, Haotian Xu, Kailai Liu, Wangyang Liu, Lixia Wang, Caiyu Zhang, Lin Bo, Xicheng Lan, Shihua Lin, Ke Feng, Shangwei Ning, Yunpeng Zhang, Li Wang.

An updated LncTarD 2.0 database provides a comprehensive resource on key lncRNA-target regulations, their influenced functions and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD 2.0 is freely available at (http://bio-bigdata.hrbmu.edu.cn/LncTarD or https://lnctard.bio-database.com/). LncTarD 2.0 was updated with several new features, including (i) an increased number of disease-associated lncRNA entries, where the current release provides 8360 key lncRNA-target regulations, with 419 disease subtypes and 1355 lncRNAs; (ii) predicted 3312 out of 8360 lncRNA-target regulations as potential diagnostic or therapeutic biomarkers in circulating tumor cells (CTCs); (iii) addition of 536 new, experimentally supported lncRNA-target regulations that modulate properties of cancer stem cells; (iv) addition of an experimentally supported clinical application section of 2894 lncRNA-target regulations for potential clinical application. Importantly, LncTarD 2.0 provides RNA-seq/microarray and single-cell web tools for customizable analysis and visualization of lncRNA-target regulations in diseases. RNA-seq/microarray web tool was used to mining lncRNA-target regulations in both disease tissue samples and CTCs blood samples. The single-cell web tools provide single-cell lncRNA-target annotation from the perspectives of pan-cancer analysis and cancer-specific analysis at the single-cell level. LncTarD 2.0 will be a useful resource and mining tool for the investigation of the functions and mechanisms of lncRNA deregulation in human disease.

DOI: https://doi.org/10.1093/nar/gkac984