Oncoscience最新文献

Breast cancer (BC) metastasis can occur decades before clinical diagnosis. During this time, the cancer cells (BCCs) can remain dormant for decades. This type of dormancy also occurs during remission where the dormant BCCs adapt cycling quiescence within the tissue microenvironment. BC shows preference for the bone marrow (BM), resulting in poor prognosis. The BM provides a challenge due to the complex niche between the peripheral interface and endosteum. The process of dormancy begins upon entry into the marrow with the changes facilitated through crosstalk between the cancer cells and tissue niche. More importantly, dormancy can occur at any time during the disease process, including the time during treatment. This perspective discusses the challenges posed by the marrow microenvironment to develop treatment. The article discusses the complex mechanisms at each compartment within the marrow niche and the added negative issue of toxicity to the endogenous stem cells.

Long non-coding RNAs (lncRNAs) exert central pathophysiological roles through the regulation of gene expression both at transcriptional and post-transcriptional levels. The characterization of lncRNAs' interactome is disclosing several new mechanisms that control disease onset and progression thus opening the way to the development of new pioneering therapeutic approaches. Regarding the lncRNA HOTAIR, found upregulated in several cancers and in liver fibrosis, it has been proved as a potential therapeutic target. HOTAIR acts as a ceRNA for several miRNAs and it directly interacts with chromatin remodelling complexes (e.g. PRC2 and LSD1/NuRD complexes). In this regard, we recently reported the transcription factor SNAIL-mediated recruitment of HOTAIR/PRC2 complex on specific chromatin sites causing epithelial genes' repression through epigenetic chromatin modifications. Conversely, HOTAIR is repressed by the liver-enriched transcriptional factor HNF4a that binds to both HOTAIR promoter and distant enhancer and impairs the formation of a chromatin loop between these genomic regions. In a therapeutic perspective, we design and validated the first example of a dominant negative lncRNA molecule (HOTAIR-sbid) that covers the HOTAIR portion involved in the interaction with SNAIL while is devoid of the domain of interaction with EZH2. Functionally, HOTAIR-sbid expression impairs SNAIL/EZH2/endogenous HOTAIR interaction; thus, PRC2 complex is not recruited on SNAIL-target chromatin sites (i.e. epithelial genes' promoters). Accordingly, the cells rescue an epithelial phenotype, reduce EMT and, in turn, migratory, invasive and anchorage independent growth abilities. This approach promises high level of specificity and limited off-target effects. Future investigations should enhance RNAs' stability and should design strategies for the delivery of these molecules to specific target cells.

Large language models utilizing transformer neural networks and other deep learning architectures demonstrated unprecedented results in many tasks previously accessible only to human intelligence. In this article, we collaborate with ChatGPT, an AI model developed by OpenAI to speculate on the applications of Rapamycin, in the context of Pascal's Wager philosophical argument commonly utilized to justify the belief in god. In response to the query "Write an exhaustive research perspective on why taking Rapamycin may be more beneficial than not taking Rapamycin from the perspective of Pascal's wager" ChatGPT provided the pros and cons for the use of Rapamycin considering the preclinical evidence of potential life extension in animals. This article demonstrates the potential of ChatGPT to produce complex philosophical arguments and should not be used for any off-label use of Rapamycin.

Background: Meningiomas are common intracranial tumors with variable prognoses not entirely captured by commonly used classification schemes. We sought to determine the relationship between meningioma mutations and oncologic outcomes using a targeted next-generation sequencing panel.

Materials and methods: We identified 184 grade I and II meningiomas with both >90 days of post-surgical follow-up and linked targeted next-generation sequencing. For mutated genes in greater than 5% of the sample, we computed progression-free survival Cox-regression models stratified by gene. We then built a multi-gene model by including all gene predictors with a p-value of less than 0.20. Starting with that model, we performed backward selection to identify the most predictive factors.

Results: ATM (HR = 4.448; 95% CI: 1.517-13.046), CREBBP (HR = 2.727; 95% CI = 1.163-6.396), and POLE (HR = 0.544; HR = 0.311-0.952) were significantly associated with alterations in disease progression after adjusting for clinical and pathologic factors. In the multi-gene model, only POLE remained a significant predictor of recurrence after adjusting for the same clinical covariates. Backwards selection identified recurrence status, resection extent, and mutations in ATM (HR = 7.333; 95% CI = 2.318-23.195) and POLE (HR = 0.413; 95% CI = 0.229-0.743) as predictive of recurrence.

Conclusions: Mutations in ATM and CREBBP were associated with accelerated meningioma recurrence, and mutations in POLE were protective of recurrence. Each mutation has potential implications for treatment. The effect of these mutations on oncologic outcomes and as potential targets for intervention warrants future study.