bims-ectoca 2024-12-29 papers

Issue of 2024–12–29
four papers selected by
Ankita Daiya, OneCell Diagnostics Inc.

Biochim Biophys Acta Rev Cancer. 2024 Dec 23. pii: S0304-419X(24)00184-7. [Epub ahead of print] 189253

Emerging role of EZH2 in solid tumor metastasis.

Ayushi Verma, Muqtada Ali Khan, Saumya Ranjan Satrusal, Dipak Datta.

Cancer cells experience multiple reversible changes during their metastatic spread. Epigenetic reprogramming, being reversible, has emerged as a critical driver of cancer metastasis. Epigenetic modulator Enhancer of Zeste homolog 2 (EZH2) is an important candidate for such reprogramming events. Both EZH2 protein and its catalytic function (H3K27me3) have been shown to promote solid tumor metastasis, although EZH2 functional inhibition has limited impact on primary tumor growth in some cancers. The dichotomous gene regulatory roles of EZH2 and H3K27me3 are currently being investigated to understand how they collectively contribute to promote metastasis. Here, we examine the multifaceted role of EZH2 in modulating solid tumor metastasis and its therapeutic potential.

Keywords: Cancer therapy; EZH2; H3K27me3; Metastasis

DOI: https://doi.org/10.1016/j.bbcan.2024.189253

PLoS One. 2024 ;19(12): e0311976

Sub-toxic cisplatin concentrations induce extensive chromosomal, nuclear and nucleolar abnormalities associated with high malignancy before acquired resistance develops: Implications for clinical caution.

John G Delinassios, Robert M Hoffman, George Koumakis, Dimitrios Palitskaris, Kyriaki-Nefelli Poulatsidou, George J Delinasios.

AIM: This study investigates the impact of sub-toxic cisplatin levels on nuclear and nucleolar abnormalities and chromosome instability in HeLa cells since our current knowledge of cisplatin effects on these parameters is based on studies with high concentrations of cisplatin.
MATERIALS AND METHODS: HeLa cells were exposed to gradually increasing sub-toxic doses of cisplatin (0.01 to 0.2 μg/ml). Cells treated with 0.1 and 0.2 μg/ml, termed HeLaC0.1 and HeLaC0.2, were not cisplatin-resistant, only exhibiting a slightly reduced viability, and were termed "cisplatin-sensitized cells." Giemsa and silver staining were used to detect nuclear and nucleolar abnormalities and chromosomal alterations.
RESULTS: Notable abnormalities were observed in HeLaC0.1 and HeLaC0.2 cells after treatment with sub-toxic concentrations of cisplatin: nuclei showed abnormal shapes, blebs, micronuclei, fragmentation, pulverization, and multinucleation; nucleoli exhibited irregular shapes and increased numbers; anaphase cells showed more nucleolar organizing regions. Abnormal chromosome segregation, heightened aneuploidy (81-140 chromosomes), polyploidy, double minutes, dicentrics, chromatid exchanges, chromatid separations, pulverization, and chromosome markers were prominently noted. These abnormalities were intensified in cells pre-sensitized to 0.02 or 0.08 μg/ml cisplatin for seven days, then exposed to 0.03 or 0.1 μg/ml cisplatin for 24 hours, and finally cultured in cisplatin-free medium for 24 hours before chromosome analysis.
CONCLUSION: HeLa cells subjected to increasing concentrations of sub-toxic cisplatin exhibited large-scale, multiple-type abnormalities in nuclei, nucleoli, chromosomes, and chromosomal numbers, indicating genetic/chromosomal instability associated with high malignancy, before the development of cisplatin resistance. These results suggest that low doses of cisplatin administration in the clinical setting may promote malignancy and caution should be used with this type of treatment.

DOI: https://doi.org/10.1371/journal.pone.0311976

Front Immunol. 2024 ;15 1507476

Exploring the heterogeneity of osteosarcoma cell characteristics and metabolic states and their association with clinical prognosis.

Sen Qin, YaoFeng Hu, RuCui Deng, Zhe Wang.

Background: Osteosarcoma is a malignant tumor originating from mesenchymal bone tissue, characterized by high malignancy and poor prognosis. Despite progress in comprehensive treatment approaches, the five-year survival rate remains largely unchanged, highlighting the need to clarify its underlying mechanisms and discover new therapeutic targets.
Methods: This study utilized RNA sequencing data from multiple public databases, encompassing osteosarcoma samples and healthy controls, along with single-cell RNA sequencing data. Various methods were utilized, such as differential expression analysis of genes, analysis of metabolic pathways, and weighted gene co-expression network analysis (WGCNA), to pinpoint crucial genes. Using this list of genes, we developed and validated a prognostic model that incorporated risk signatures, and we evaluated the effectiveness of the model through survival analysis, immune cell infiltration examination, and drug sensitivity evaluation.
Results: We analyzed gene expression and metabolic pathways in nine samples using single-cell sequencing data. Initially, we performed quality control and clustering, identifying 21 statistically significant cell subpopulations. Metabolic analyses of these subpopulations revealed heterogeneous activation of metabolic pathways. Focusing on the osteoblastic cell subpopulation, we further subdivided it into six groups and examined their gene expression and differentiation capabilities. Differential expression and enrichment analyses indicated that tumor tissues were enriched in cytoskeletal and structural pathways. Through WGCNA, we identified core genes negatively correlated with four highly activated metabolic pathways. Using osteosarcoma patient data, we developed a risk signature model that demonstrated robust prognostic predictions across three independent cohorts. Ultimately, we performed a thorough examination of the model, which encompassed clinical and pathological characteristics, enrichment analysis, pathways associated with cancer markers, and scores of immune infiltration, highlighting notable and complex disparities between high-risk and low-risk populations.
Conclusion: This research clarifies the molecular mechanisms and metabolic features associated with osteosarcoma and how they relate to patient outcomes, offering novel perspectives and approaches for targeted therapy and prognostic assessment in osteosarcoma.

Keywords: comprehensive analysis; immune infiltration; metabolic pathways; osteosarcoma; prognostic analysis

DOI: https://doi.org/10.3389/fimmu.2024.1507476

Cancer Sci. 2024 Dec 27.

Mechanisms of Resistance to KRAS Inhibitors: Cancer Cells' Strategic Use of Normal Cellular Mechanisms to Adapt.

Noritaka Tanaka, Hiromichi Ebi.

KRAS was long deemed undruggable until the discovery of the switch-II pocket facilitated the development of specific KRAS inhibitors. Despite their introduction into clinical practice, resistance mechanisms can limit their effectiveness. Initially, tumors rely on mutant KRAS, but as they progress, they may shift to alternative pathways, resulting in intrinsic resistance. This resistance can stem from mechanisms like epithelial-to-mesenchymal transition (EMT), YAP activation, or KEAP1 mutations. KRAS inhibition often triggers cellular rewiring to counteract therapeutic pressure. For instance, feedback reactivation of signaling pathways such as MAPK, mediated by receptor tyrosine kinases, supports tumor cell survival. Inhibiting KRAS disrupts protein homeostasis, but reactivation of MAPK or AKT can restore it, aiding tumor cell survival. KRAS inhibition also causes metabolic reprogramming and protein re-localization. The re-localization of E-cadherin and Scribble from the membrane to the cytosol causes YAP to translocate to the nucleus, where it drives MRAS transcription, leading to MAPK reactivation. Emerging evidence indicates that changes in cell identity, such as mucinous differentiation, shifts from alveolar type 2 to type 1 cells, or lineage switching from adenocarcinoma to squamous cell carcinoma, also contribute to resistance. In addition to these nongenetic mechanisms, secondary mutations in KRAS or alterations in upstream/downstream signaling proteins can cause acquired resistance. Secondary mutations in the switch-II pocket disrupt drug binding, and known oncogenic mutations affect drug efficacy. Overcoming these resistance mechanisms involves enhancing the efficacy of drugs targeting mutant KRAS, developing broad-spectrum inhibitors, combining therapies targeting multiple pathways, and integrating immune checkpoint inhibitors.

Keywords: KRAS; lineage plasticity; nongenetic mechanism; resistance; secondary mutation

DOI: https://doi.org/10.1111/cas.16441