Integrative Analysis of the Doxorubicin-Associated LncRNA-mRNA Network Identifies Chemoresistance-Associated lnc-TRDMT1-5 as a Biomarker of Breast Cancer Progression

Emerging roles of non-coding RNAs in modulating the PI3K/Akt pathway in cancer

Cancer progression results from the dysregulation of molecular pathways, each with unique features that can either promote or inhibit tumor growth. The complexity of carcinogenesis makes it challenging for researchers to target all pathways in cancer therapy, emphasizing the importance of focusing on specific pathways for targeted treatment. One such pathway is the PI3K/Akt pathway, which is often overexpressed in cancer. As tumor cells progress, the expression of PI3K/Akt increases, further driving cancer advancement. This study aims to explore how ncRNAs regulate the expression of PI3K/Akt. NcRNAs are found in both the cytoplasm and nucleus, and their functions vary depending on their location. They can bind to the promoters of PI3K or Akt, either reducing or increasing their expression, thus influencing tumorigenesis. The ncRNA/PI3K/Akt axis plays a crucial role in determining cell proliferation, metastasis, epithelial-mesenchymal transition (EMT), and even chemoresistance and radioresistance in human cancers. Anti-tumor compounds can target ncRNAs to modulate the PI3K/Akt axis. Moreover, ncRNAs can regulate the PI3K/Akt pathway both directly and indirectly.

Quantitative estimates of the regulatory influence of long non-coding RNAs on global gene expression variation using TCGA breast cancer transcriptomic data

Long non-coding RNAs (lncRNAs) have received attention in recent years for their regulatory roles in diverse biological contexts including cancer, yet large gaps remain in our understanding of their mechanisms and global maps of their targets. In this work, we investigated a basic unanswered question of lncRNA systems biology: to what extent can gene expression variation across individuals be attributed to lncRNA-driven regulation? To answer this, we analyzed RNA-seq data from a cohort of breast cancer patients, explaining each gene's expression variation using a small set of automatically selected lncRNA regulators. A key aspect of this analysis is that it accounts for confounding effects of transcription factors (TFs) as common regulators of a lncRNA-mRNA pair, to enrich the explained gene expression for lncRNA-mediated regulation. We found that for 16% of analyzed genes, lncRNAs can explain more than 20% of expression variation. We observed 25-50% of the putative regulator lncRNAs to be in 'cis' to, i.e., overlapping or located proximally to the target gene. This led us to quantify the global regulatory impact of such cis-located lncRNAs, which was found to be substantially greater than that of trans-located lncRNAs. Additionally, by including statistical interaction terms involving lncRNA-protein pairs as predictors in our regression models, we identified cases where a lncRNA's regulatory effect depends on the presence of a TF or RNA-binding protein. Finally, we created a high-confidence lncRNA-gene regulatory network whose edges are supported by co-expression as well as a plausible mechanism such as cis-action, protein scaffolding or competing endogenous RNAs. Our work is a first attempt to quantify the extent of gene expression control exerted globally by lncRNAs, especially those located proximally to their regulatory targets, in a specific biological (breast cancer) context. It also marks a first step towards systematic reconstruction of lncRNA regulatory networks, going beyond the current paradigm of co-expression networks, and motivates future analyses assessing the generalizability of our findings to additional biological contexts.

Insights into molecular mechanisms of chemotherapy resistance in cancer

Cancer heterogeneity poses a significant hurdle to the successful treatment of the disease, and is being influenced by genetic inheritance, cellular and tissue biology, disease development, and response to therapy. While chemotherapeutic drugs have demonstrated effectiveness, their efficacy is impeded by challenges such as presence of resilient cancer stem cells, absence of specific biomarkers, and development of drug resistance. Often chemotherapy leads to a myriad of epigenetic, transcriptional and post-transcriptional alterations in gene expression as well as changes in protein expression, thereby leading to massive metabolic reprogramming. This review seeks to provide a detailed account of various transcriptional regulations, proteomic changes, and metabolic reprogramming in various cancer models in response to three primary chemotherapeutic interventions, docetaxel, carboplatin, and doxorubicin. Discussing the molecular targets of some of these regulatory events and highlighting their contribution in sensitivity to chemotherapy will provide insights into drug resistance mechanisms and uncover novel perspectives in cancer treatment.

Prediction Model for Therapeutic Responses in Ovarian Cancer Patients using Paclitaxel-resistant Immune-related lncRNAs

BACKGROUND

Ovarian cancer (OC) is the deadliest malignant tumor in women with a poor prognosis due to drug resistance and lack of prediction tools for therapeutic responses to anti- cancer drugs.

OBJECTIVE

The objective of this study was to launch a prediction model for therapeutic responses in OC patients.

METHODS

The RNA-seq technique was used to identify differentially expressed paclitaxel (PTX)- resistant lncRNAs (DE-lncRNAs). The Cancer Genome Atlas (TCGA)-OV and ImmPort database were used to obtain immune-related lncRNAs (ir-lncRNAs). Univariate, multivariate, and LASSO Cox regression analyses were performed to construct the prediction model. Kaplan- meier plotter, Principal Component Analysis (PCA), nomogram, immune function analysis, and therapeutic response were applied with Genomics of Drug Sensitivity in Cancer (GDSC), CIBERSORT, and TCGA databases. The biological functions were evaluated in the CCLE database and OC cells.

RESULTS

The RNA-seq defined 186 DE-lncRNAs between PTX-resistant A2780-PTX and PTXsensitive A2780 cells. Through the analysis of the TCGA-OV database, 225 ir-lncRNAs were identified. Analyzing 186 DE-lncRNAs and 225 ir-lncRNAs using univariate, multivariate, and LASSO Cox regression analyses, 9 PTX-resistant immune-related lncRNAs (DEir-lncRNAs) acted as biomarkers were discovered as potential biomarkers in the prediction model. Single-cell RNA sequencing (scRNA-seq) data of OC confirmed the relevance of DEir-lncRNAs in immune responsiveness. Patients with a low prediction score had a promising prognosis, whereas patients with a high prediction score were more prone to evade immunotherapy and chemotherapy and had poor prognosis.

CONCLUSION

The novel prediction model with 9 DEir-lncRNAs is a valuable tool for predicting immunotherapeutic and chemotherapeutic responses and prognosis of patients with OC.

Comprehensive Analysis of the Prognostic Value and Immune Infiltrates of the Three-m5C Signature in Colon Carcinoma

Background

The 5-methylcytosine (m5C) is one of the important forms of RNA post modification, and its regulatory mechanism in tumors has received increasing attention. However, its potential role in colorectal cancer remains unclear.

Materials and Methods

Here, we systematically investigated the genetic variation and prognostic value of the 14 m5c RNA methylation regulators in colon cancer. The prognostic risk score was constructed using three m5C regulators, which was verified in the GSE17536 (N=177), GSE41258 (N=248) and GSE38832 (N=122) datasets.

Results

The risk score developed from the three-m5C signature represents an independent prognostic factor, which can accurately predict the prognosis of patients with colon cancer in multiple datasets. The cytokine–cytokine receptor interaction and chemokine signaling pathway were significantly enriched in the low-risk score group. Further analysis showed that the three-m5C signature was related to tumor immune microenvironment (TIME), affecting the abundance of tumor-infiltrating immune cells. Especially, patients with low risk score had higher immune score than those with high risk score. In addition, gene set enrichment analysis (GSEA) confirmed that all three regulatory factors are associated with the MAPK/p38 signaling pathway.

Conclusion

In conclusion, our study illustrates that the three-m5C signature may be involved in the regulation of colon cancer immune microenvironment in synergy with the MAPK signaling pathway. Therefore, further studying the three-m5C signature regulatory mechanisms might provide promising targets for improving the responsiveness of colon cancer to immunotherapy.

Non-coding RNAs as Novel Biomarkers in Cancer Drug Resistance

Chemotherapy is often the primary and most effective anticancer treatment; however, drug resistance remains a major obstacle to it being curative. Recent studies have demonstrated that non-coding RNAs (ncRNAs), especially microRNAs and long non-coding RNAs, are involved in drug resistance of tumor cells in many ways, such as modulation of apoptosis, drug efflux and metabolism, epithelial-to-mesenchymal transition, DNA repair, and cell cycle progression. Exploring the relationships between ncRNAs and drug resistance will not only contribute to our understanding of the mechanisms of drug resistance and provide ncRNA biomarkers of chemoresistance, but will also help realize personalized anticancer treatment regimens. Due to the high cost and low efficiency of biological experimentation, many researchers have opted to use computational methods to identify ncRNA biomarkers associated with drug resistance. In this review, we summarize recent discoveries related to ncRNA-mediated drug resistance and highlight the computational methods and resources available for ncRNA biomarkers involved in chemoresistance.

Mechanisms of Resistance to Chemotherapy in Breast Cancer and Possible Targets in Drug Delivery Systems

Breast cancer (BC) is one of the most important cancers worldwide, and usually, chemotherapy can be used in an integrative approach. Usually, chemotherapy treatment is performed in association with surgery, radiation or hormone therapy, providing an increased outcome to patients. However, tumors can develop resistance to different drugs, progressing for a more aggressive phenotype. In this scenario, the use of nanocarriers could help to defeat tumor cell resistance, providing a new therapeutic perspective for patients. Thus, this systematic review aims to bring the molecular mechanisms involved in BC chemoresistance and extract from the previous literature information regarding the use of nanoparticles as potential treatment for chemoresistant breast cancer.