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BackgroundAlthough neoadjuvant therapy has brought numerous benefits to patients, not all patients can benefit from it. Chemokines play a crucial role in the tumor microenvironment and are closely associated with the prognosis and treatment of colorectal cancer. Therefore, constructing a prognostic model based on chemokines will help risk stratification and providing a reference for the personalized treatment.MethodsEmploying LASSO-Cox predictive modeling, a chemokine-based prognostic model was formulated, harnessing the data from TCGA and GEO databases. Then, our exploration focused on the correlation between the chemokine signature and elements such as the immune landscape, somatic mutations, copy number variations, and drug sensitivity. CXCL10+M1 macrophages identified via scRNA-seq. Monocle2 showed cell pseudotime trajectories, CellChat characterized intercellular communication. CytoTRACE analyzed neoadjuvant therapy stemness, SCENIC detected cell type-specific regulation. Lastly, validation was performed through multiplex immunofluorescence experiments.ResultsA model based on 15 chemokines was constructed and validated. High-risk scores correlated with poorer prognosis and advanced TNM and clinical stages. Individuals presenting elevated risk scores demonstrated an increased propensity towards the development of chemotherapy resistance. Subsequent scRNA-seq data analysis indicated that patients with higher presence of CXCL10+ M1 macrophages in tumor tissues are more likely to benefit from neoadjuvant therapy.ConclusionWe developed a chemokine-based prognostic model by integrating both single-cell and bulk RNA-seq data. Furthermore, we revealed epithelial cell heterogeneity in neoadjuvant outcomes and identified CXCL10+ M1 macrophages as potential therapy response predictors. These findings could significantly contribute to risk stratification and serve as a key guide for the advancement of personalized therapeutic approaches.

Abstract Empowered by recent advances of sequencing techniques, transcriptome-wide studies have characterized over 150 different types of post-transcriptional chemical modifications of RNA, ranging from methylations of single base to complex installing reactions catalyzed by coordinated actions of multiple modification enzymes. These modifications have been shown to regulate the function and fate of RNAs and further affecting various cellular events. However, the current understanding of their biological functions in human diseases, especially in cancers, is still limited. Once regarded as “junk” or “noise” of the transcriptome, noncoding RNA (ncRNA) has been proved to be involved in a plethora of cellular signaling pathways especially those regulating cancer initiation and progression. Accumulating evidence has demonstrated that ncRNAs manipulate multiple phenotypes of cancer cells including proliferation, metastasis and chemoresistance and may become promising biomarkers and targets for diagnosis and treatment of cancer. Importantly, recent studies have mapped plenty of modified residues in ncRNA transcripts, indicating the existence of epigenetic modulation of ncRNAs and the potential effects of RNA modulation on cancer progression. In this review, we briefly introduced the characteristics of several main epigenetic marks on ncRNAs and summarized their consecutive effects on cancer cells. We found that ncRNAs could act both as regulators and targets of epigenetic enzymes, which indicated a cross-regulating network in cancer cells and unveil a novel dimension of cancer biology. Moreover, by epitomizing the knowledge of RNA epigenetics, our work may pave the way for the design of patient-tailored therapeutics of cancers.

Metastasis remains to be one of the most prevalent causes leading to poor long-term survival of colorectal cancer (CRC) patients. The clinical significances of tumor metastatic suppressor, N-myc downregulated gene 1 (NDRG1), have been inconsistently reported in a variety of cancerous diseases. In this study with 240 CRC clinical specimens, we showed that NDRG1 expression was significantly decreased in most of CRC tissues compared to the paired non-tumor counterparts. Statistical analysis revealed a significant inverse correlation of NDRG1 expression with tumor stage, differentiation status and metastasis. Compared with NDRG1-negative group, NDRG1-positve group had better disease-free/overall survival (p = 0.000) over 5 years' follow-up. Furthermore, NDRG1 was considered to be an independent prognostic factor for overall survival (p = 0.001) and recurrence (p = 0.003). Our study concludes that NDRG1 is a novel favorable predictor for the prognosis in CRC patients.

Background: Although neoadjuvant therapy has brought numerous benefits to patients, not all patients can benefit from it. Chemokines play a crucial role in the tumor microenvironment and are closely associated with the prognosis and treatment of colorectal cancer. Therefore, constructing a prognostic model based on chemokines will help risk stratification and providing a reference for the personalized treatment. Methods: Employing LASSO-Cox predictive modeling, a chemokine-based prognostic model was formulated, harnessing the data from TCGA and GEO databases. Then, our exploration focused on the correlation between the chemokine signature and elements such as the immune landscape, somatic mutations, copy number variations, and drug sensitivity. CXCL10+M1 macrophages identified via scRNA-seq. Monocle2 showed cell pseudotime trajectories, CellChat characterized intercellular communication. CytoTRACE analyzed neoadjuvant therapy stemness, SCENIC detected cell type-specific regulation. Lastly, validation was performed through multiplex immunofluorescence experiments. Results: A model based on 15 chemokines was constructed and validated. High-risk scores correlated with poorer prognosis and advanced TNM and clinical stages. Individuals presenting elevated risk scores demonstrated an increased propensity towards the development of chemotherapy resistance. Subsequent scRNA-seq data analysis indicated that patients with higher presence of CXCL10+ M1 macrophages in tumor tissues are more likely to benefit from neoadjuvant therapy. Conclusion: We developed a chemokine-based prognostic model by integrating both single-cell and bulk RNA-seq data. Furthermore, we revealed epithelial cell heterogeneity in neoadjuvant outcomes and identified CXCL10+ M1 macrophages as potential therapy response predictors. These findings could significantly contribute to risk stratification and serve as a key guide for the advancement of personalized therapeutic approaches. [ABSTRACT FROM AUTHOR]

Background: E2A gene, which encodes two basic helix-loop-helix (bHLH) transcription factors E12 and E47, has been identified as regulator of B lymphoid hematopoiesis and suppressor of lymphoma. E47 protein was found to decrease E-cadherin expression and induce epithelial-mesenchymal transition (EMT). However, the role of E2A in colorectal cancer (CRC) metastasis is still elusive.Methods: qRT-PCR and semi-qRT-PCR were performed to determine mRNA level of E2A in CRC specimens and colorectal cancer cells. RNAi was employed to downregulate E2A expression and subsequent protein level change was evaluated by immunoblot. Cell invasion and migration capacity were detected by transwell assay using cell culture inserts with or without basement membrane matrix, respectively.Results: E2A expression was decreased in metastatic CRC tissues. Invasion and migration assays showed downregulation of E2A increased metastatic capacity of CRC cells while forced expression of E12 or E47 could offset this effect. Both E12 and E47 suppressed EMT induced by E2A downregulation. Moreover, Yes-Associated Protein (YAP) was a downstream target of E2A and suppression of YAP inhibited the pro-migration/invasion of E2A deficiency.Conclusion: Our results suggest that E2A suppresses CRC cell metastasis, at least partially if not all, by inhibiting YAP expression. [ABSTRACT FROM AUTHOR]