bims-ectoca 2023-01-01 papers

bims-ectoca

Biomed News

on Epigenetic control of tolerance in cancer

Issue of 2023‒01‒01
ten papers selected by
Ankita Daiya, Birla Institute of Technology and Science

Autophagy induction sensitizes cancer cells to anti-cancer drugs.
Identification of potential extracellular vesicle protein markers altered in osteosarcoma from public databases.
An evolution-based machine learning to identify cancer type-specific driver mutations.
The landscape of therapeutic vulnerabilities in EGFR inhibitor osimertinib drug tolerant persister cells.
Cancer Plasticity: Investigating the causes for this agility.
Piezo protein determines stem cell fate by transmitting mechanical signals.
A Selective Nanoblocker of Cellular Stress Response for Improved Drug-Free Tumor Therapy.
Cell signaling activation and extracellular matrix remodeling underpin glioma tumor microenvironment heterogeneity and organization.
Biology-inspired data-driven quality control for scientific discovery in single-cell transcriptomics.
Noncanonical imprinting: intergenerational epigenetic inheritance mediated by Polycomb complexes.

Autophagy. 2022 Dec 29. 1-2

Autophagy induction sensitizes cancer cells to anti-cancer drugs.

Mei Luo, Leng Han.

  Resistance to anti-cancer therapy is a major challenge for cancer treatment. Many studies revealed that macroautophagy/autophagy inhibition can overcome autophagy-mediated therapy resistance, but these efforts have not yet led to the success of clinical applications. In a recent paper, we established a 37-gene autophagy signature to estimate the autophagy status of approximately 10,000 tumor samples across 33 cancer types from The Cancer Genome Atlas, and muti-omics characterization reveals that autophagy induction may also sensitize cancer cells to anti-cancer drugs. These findings provide a comprehensive resource of molecular alterations associated with autophagy and highlight the potential to utilize drug sensitivity induced by autophagy to overcome the resistance of cancer therapy.

Keywords:  Autophagy; drug sensitivity; gene signature; multi-omics; therapy

DOI:  https://doi.org/10.1080/15548627.2022.2162703
Proteomics Clin Appl. 2022 Dec 26. e2200084

Identification of potential extracellular vesicle protein markers altered in osteosarcoma from public databases.

Jinhe Zhang, Huiyan Li.

  1 PURPOSE: Extracellular vesicles (EVs) have become promising biomarkers for cancer management. Particularly, the molecular cargo such as proteins carried by EVs are similar to their cells of origin, providing important information that can be used for cancer diagnostics, prognosis, and treatment monitoring. However, to date, molecular analysis on EVs is still challenging, limited by the availability of efficient analytical technologies, largely due to the small size of EVs. In this work, we developed a computational workflow for in-silico identification of potential EV protein markers from genomics and proteomics databases, and applied it for the discovery of osteosarcoma (OS) EV protein markers. 2 EXPERIMENTAL DESIGN: Both mRNA and protein data were computed and compared from publicly accessible databases, and top markers with high differential expression levels were selected. 3 RESULTS: Thirty nine markers were identified overexpressed and seven found to be downregulated. These identified markers have been found to be associated with OS on different aspects in literature, demonstrating the usability of this workflow. 4 CONCLUSIONS AND CLINICAL RELEVANCE: This work provides a list of potential EV protein markers that are either overexpressed or downregulated in OS for further experimental validation for improved clinical management of OS. This article is protected by copyright. All rights reserved.

Keywords:  biomarkers; extracellular vesicles; osteosarcoma; proteins

DOI:  https://doi.org/10.1002/prca.202200084
Brief Bioinform. 2022 Dec 27. pii: bbac593. [Epub ahead of print]

An evolution-based machine learning to identify cancer type-specific driver mutations.

Donghyo Kim, Doyeon Ha, Kwanghwan Lee, Heetak Lee, Inhae Kim, Sanguk Kim.

  Identifying cancer type-specific driver mutations is crucial for illuminating distinct pathologic mechanisms across various tumors and providing opportunities of patient-specific treatment. However, although many computational methods were developed to predict driver mutations in a type-specific manner, the methods still have room to improve. Here, we devise a novel feature based on sequence co-evolution analysis to identify cancer type-specific driver mutations and construct a machine learning (ML) model with state-of-the-art performance. Specifically, relying on 28 000 tumor samples across 66 cancer types, our ML framework outperformed current leading methods of detecting cancer driver mutations. Interestingly, the cancer mutations identified by sequence co-evolution feature are frequently observed in interfaces mediating tissue-specific protein-protein interactions that are known to associate with shaping tissue-specific oncogenesis. Moreover, we provide pre-calculated potential oncogenicity on available human proteins with prediction scores of all possible residue alterations through user-friendly website (http://sbi.postech.ac.kr/w/cancerCE). This work will facilitate the identification of cancer type-specific driver mutations in newly sequenced tumor samples.

Keywords:  cancer type-specificity; driver mutations; machine learning; protein–protein interactions; sequence co-evolution

DOI:  https://doi.org/10.1093/bib/bbac593
NPJ Precis Oncol. 2022 Dec 27. 6(1): 95

The landscape of therapeutic vulnerabilities in EGFR inhibitor osimertinib drug tolerant persister cells.

Steven W Criscione, Matthew J Martin, Derek B Oien, Aparna Gorthi, Ricardo J Miragaia, Jingwen Zhang, Huawei Chen, Daniel L Karl, Kerrin Mendler, Aleksandra Markovets, Sladjana Gagrica, Oona Delpuech, Jonathan R Dry, Michael Grondine, Maureen M Hattersley, Jelena Urosevic, Nicolas Floc'h, Lisa Drew, Yi Yao, Paul D Smith.

Third-generation EGFR tyrosine kinase inhibitors (EGFR-TKIs), including osimertinib, an irreversible EGFR-TKI, are important treatments for non-small cell lung cancer with EGFR-TKI sensitizing or EGFR T790M resistance mutations. While patients treated with osimertinib show clinical benefit, disease progression and drug resistance are common. Emergence of de novo acquired resistance from a drug tolerant persister (DTP) cell population is one mechanism proposed to explain progression on osimertinib and other targeted cancer therapies. Here we profiled osimertinib DTPs using RNA-seq and ATAC-seq to characterize the features of these cells and performed drug screens to identify therapeutic vulnerabilities. We identified several vulnerabilities in osimertinib DTPs that were common across models, including sensitivity to MEK, AURKB, BRD4, and TEAD inhibition. We linked several of these vulnerabilities to gene regulatory changes, for example, TEAD vulnerability was consistent with evidence of Hippo pathway turning off in osimertinib DTPs. Last, we used genetic approaches using siRNA knockdown or CRISPR knockout to validate AURKB, BRD4, and TEAD as the direct targets responsible for the vulnerabilities observed in the drug screen.

DOI: https://doi.org/10.1038/s41698-022-00337-w
Semin Cancer Biol. 2022 Dec 27. pii: S1044-579X(22)00259-0. [Epub ahead of print]

Cancer Plasticity: Investigating the causes for this agility.

Shubhraneel Saha, Nikita Pradhan, B Neha, Ravikiran Mahadevappa, Shilpi Minocha, Saran Kumar.

  Cancer is not a hard-wired phenomenon but an evolutionary disease. From the onset of carcinogenesis, cancer cells continuously adapt and evolve to satiate their ever-growing proliferation demands. This results in the formation of multiple subtypes of cancer cells with different phenotypes, cellular compositions, and consequently displaying varying degrees of tumorigenic identity and function. This phenomenon is referred to as cancer plasticity, during which the cancer cells exist in a plethora of cellular states having distinct phenotypes. With the advent of modern technologies equipped with enhanced resolution and depth, for example, single-cell RNA-sequencing and advanced computational tools, unbiased cancer profiling at a single-cell resolution are leading the way in understanding cancer cell rewiring both spatially and temporally. In this review, the processes and mechanisms that give rise to cancer plasticity include both intrinsic genetic factors such as epigenetic changes, differential expression due to changes in DNA, RNA, or protein content within the cancer cell, as well as extrinsic environmental factors such as tissue perfusion, extracellular milieu are detailed and their influence on key cancer plasticity hallmarks such as epithelial-mesenchymal transition (EMT) and cancer cell stemness (CSCs) are discussed. Due to therapy evasion and drug resistance, tumor heterogeneity caused by cancer plasticity has major therapeutic ramifications. Hence, it is crucial to comprehend all the cellular and molecular mechanisms that control cellular plasticity. How this process evades therapy, and the therapeutic avenue of targeting cancer plasticity must be diligently investigated.

Keywords:  Cancer Stem Cells; Cancer heterogeneity; Cancer plasticity; Cancer therapy; Epithelial-Mesenchymal Transition; Therapy resistance; Tumor microenvironment

DOI:  https://doi.org/10.1016/j.semcancer.2022.12.005
Hum Cell. 2022 Dec 29.

Piezo protein determines stem cell fate by transmitting mechanical signals.

Xiaolei Qiu, Zhuoyue Deng, Meijing Wang, Yuqi Feng, Lintao Bi, Lisha Li.

  Piezo ion channel is a mechanosensitive protein on the cell membrane, which contains Piezo1 and Piezo2. Piezo channels are activated by mechanical forces, including stretch, matrix stiffness, static pressure, and shear stress. Piezo channels transmit mechanical signals that cause different downstream responses in the differentiation process, including integrin signaling pathway, ERK1/2 MAPK signaling pathway, Notch signaling, and WNT signaling pathway. In the fate of stem cell differentiation, scientists found differences in Piezo channel expression and found that Piezo channel expression is related to developmental diseases. Here, we briefly review the structure and function of Piezo channels and the relationship between Piezo and mechanical signals, discussing the current understanding of the role of Piezo channels in stem cell fate and associated molecules and developmental diseases. Ultimately, we believe this review will help identify the association between Piezo channels and stem cell fate.

Keywords:  Developmental disease; Downstream pathways; Mechanical signal; Piezo channels; Stem cell fate

DOI:  https://doi.org/10.1007/s13577-022-00853-8
Adv Healthc Mater. 2022 Dec 27. e2202893

A Selective Nanoblocker of Cellular Stress Response for Improved Drug-Free Tumor Therapy.

Cuimei Liu, Sihang Cheng, Xue Zhou, Jue Wang, Ping Mu, Zhongyao Wang, Lingyu Zhang, Lu Li, Chungang Wang.

  Nanotechnology-based drug-free therapeutic systems utilizing external stimuli can avoid the inherent side effects of drugs and become an attractive therapeutic strategy. However, the cellular stress responses (CSR) are activated encounter with external stimuli, which greatly weaken the efficacy of the drug-free antitumor. Thus, we proposed a CSR regulation strategy and synthesized the glucose oxidase (GOx)-modified Cu3 BiS3 nanosheets (CBSG NSs) encapsulated by calcium carbonate (CBSG@CaCO3 ) as the novel drug-free nanoagent. The CBSG@CaCO3 not only cause external stimuli such as energy consumption and oxidative stress damage, but also can destroy the CSR mechanism to guarantee optimal efficacy of starvation-chemodynamic therapy. In tumor cells, the CaCO3 shell layer of CBSG@CaCO3 is rapidly degraded, releasing the slowly degradable CBSG NSs with NIR-II photothermal propertie that accelerated the production of external stimuli under laser irradiation. Meanwhile, CaCO3 can block CSR to disrupt the adaptive viability of cancer cells by inhibiting expresstion of P27 and NRF2. Importantly, the CSR regulation achieves selective treatment on tumor cells based on the difference in physiological conditions between cancer cells and normal cells. This drug-free cancer therapy with selectivity improves the problem of poor efficacy under the action of CSR, which offers a new avenue in the cancer-related disease treatment. This article is protected by copyright. All rights reserved.

Keywords:  cellular stress responses; glucose depletion; oxidative stress; selective drug-free tumor therapy; stepwise degradable nanoblocker

DOI:  https://doi.org/10.1002/adhm.202202893
Cell Oncol (Dordr). 2022 Dec 26.

Cell signaling activation and extracellular matrix remodeling underpin glioma tumor microenvironment heterogeneity and organization.

Marija Dinevska, Samuel S Widodo, Liam Furst, Lucero Cuzcano, Yitong Fang, Stefano Mangiola, Paul J Neeson, Phillip K Darcy, Robert G Ramsay, Ryan Hutchinson, Fabienne MacKay, Michael Christie, Stanley S Stylli, Theo Mantamadiotis.

  PURPOSE: Tumor cells thrive by adapting to the signals in their microenvironment. To adapt, cancer cells activate signaling and transcriptional programs and migrate to establish micro-niches, in response to signals from neighboring cells and non-cellular stromal factors. Understanding how the tumor microenvironment evolves during disease progression is crucial to deciphering the mechanisms underlying the functional behavior of cancer cells.METHODS: Multiplex immunohistochemistry, spatial analysis and histological dyes were used to identify and measure immune cell infiltration, cell signal activation and extracellular matrix deposition in low-grade, high-grade astrocytoma and glioblastoma.
RESULTS: We show that lower grade astrocytoma tissue is largely devoid of infiltrating immune cells and extracellular matrix proteins, while high-grade astrocytoma exhibits abundant immune cell infiltration, activation, and extensive tissue remodeling. Spatial analysis shows that most T-cells are restricted to perivascular regions, but bone marrow-derived macrophages penetrate deep into neoplastic cell-rich regions. The tumor microenvironment is characterized by heterogeneous PI3K, MAPK and CREB signaling, with specific signaling profiles correlating with distinct pathological hallmarks, including angiogenesis, tumor cell density and regions where neoplastic cells border the extracellular matrix. Our results also show that tissue remodeling is important in regulating the architecture of the tumor microenvironment during tumor progression.
CONCLUSION: The tumor microenvironment in malignant astrocytoma, exhibits changes in cell composition, cell signaling activation and extracellular matrix deposition during disease development and that targeting the extracellular matrix, as well as cell signaling activation will be critical to designing personalized therapy.

Keywords:  Astrocytoma; Cell signaling; Extracellular matrix; Glioblastoma; Glioma; Macrophages; T-cells; Tissue remodeling; Tumor microenvironment

DOI:  https://doi.org/10.1007/s13402-022-00763-9
Genome Biol. 2022 Dec 27. 23(1): 267

Biology-inspired data-driven quality control for scientific discovery in single-cell transcriptomics.

Ayshwarya Subramanian, Mikhail Alperovich, Yiming Yang, Bo Li.

  BACKGROUND: Quality control (QC) of cells, a critical first step in single-cell RNA sequencing data analysis, has largely relied on arbitrarily fixed data-agnostic thresholds applied to QC metrics such as gene complexity and fraction of reads mapping to mitochondrial genes. The few existing data-driven approaches perform QC at the level of samples or studies without accounting for biological variation.RESULTS: We first demonstrate that QC metrics vary with both tissue and cell types across technologies, study conditions, and species. We then propose data-driven QC (ddqc), an unsupervised adaptive QC framework to perform flexible and data-driven QC at the level of cell types while retaining critical biological insights and improved power for downstream analysis. ddqc applies an adaptive threshold based on the median absolute deviation on four QC metrics (gene and UMI complexity, fraction of reads mapping to mitochondrial and ribosomal genes). ddqc retains over a third more cells when compared to conventional data-agnostic QC filters. Finally, we show that ddqc recovers biologically meaningful trends in gradation of gene complexity among cell types that can help answer questions of biological interest such as which cell types express the least and most number of transcripts overall, and ribosomal transcripts specifically.
CONCLUSIONS: ddqc retains cell types such as metabolically active parenchymal cells and specialized cells such as neutrophils which are often lost by conventional QC. Taken together, our work proposes a revised paradigm to quality filtering best practices-iterative QC, providing a data-driven QC framework compatible with observed biological diversity.

Keywords:  Adaptive QC; Biological variation; Data-driven; Exploratory data analysis (EDA); Quality control (QC); Single cell; scRNA-seq

DOI:  https://doi.org/10.1186/s13059-022-02820-w
Curr Opin Genet Dev. 2022 Dec 26. pii: S0959-437X(22)00130-7. [Epub ahead of print]78 102015

Noncanonical imprinting: intergenerational epigenetic inheritance mediated by Polycomb complexes.

Azusa Inoue.

Genomic imprinting is illustrative of intergenerational epigenetic inheritance. The passage of parental genomes into the embryo is accompanied by epigenetic modifications, resulting in imprinted monoallelic gene expression in mammals. Some imprinted genes are regulated by maternal inheritance of H3K27me3, which is termed noncanonical imprinting. Noncanonical imprinting is established by Polycomb repressive complexes during oogenesis and maintained in preimplantation embryos and extraembryonic tissues, including the placenta. Recent studies of noncanonical imprinting have contributed to our understanding of chromatin regulation in oocytes and early embryos, imprinted X-chromosome inactivation, secondary differentially DNA-methylated regions, and the anomalies of cloned mice. Here, I summarize the current knowledge of noncanonical imprinting and remark on analogous mechanisms in invertebrates and plants.

DOI: https://doi.org/10.1016/j.gde.2022.102015