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Transfer RNA (tRNA) activity is tightly regulated to provide a physiological protein translation, and tRNA chemical modifications control its function in a complex with ribosomes and messenger RNAs (mRNAs). In this regard, the correct hypermodification of position G37 of phenylalanine-tRNA, adjacent to the anticodon, is critical to prevent ribosome frameshifting events. Here we report that the tRNA-yW Synthesizing Protein 2 (TYW2) undergoes promoter hypermethylation-associated transcriptional silencing in human cancer, particularly in colorectal tumors. The epigenetic loss of TYW2 induces guanosine hypomodification in phenylalaninetRNA, an increase in −1 ribosome frameshift events, and downregulation of transcripts by mRNA decay, such as of the key cancer gene ROBO1. Importantly, TYW2 epigenetic inactivation is linked to poor overall survival in patients with early-stage colorectal cancer, a finding that could be related to the observed acquisition of enhanced migration properties and epithelial-to-mesenchymal features in the colon cancer cells that harbor TYW2 DNA methylationassociated loss. These findings provide an illustrative example of how epigenetic changes can modify the epitranscriptome and further support a role for tRNA modifications in cancer biology.

Background Triple-negative breast cancer (TNBC) is an aggressive subtype that exhibits a high incidence of distant metastases and lacks targeted therapeutic options. Here we explored how the epigenome contributes to matrix metalloprotease (MMP) dysregulation impacting tumor invasion, which is the first step of the metastatic process. Methods We combined RNA expression and chromatin interaction data to identify insulator elements potentially associated with MMP gene expression and invasion. We employed CRISPR/Cas9 to disrupt the CCCTC-Binding Factor (CTCF) binding site on an insulator element downstream of the MMP8 gene (IE8) in two TNBC cellular models. We characterized these models by combining Hi-C, ATAC-seq, and RNA-seq with functional experiments to determine invasive ability. The potential of our findings to predict the progression of ductal carcinoma in situ (DCIS), was tested in data from clinical specimens. Results We explored the clinical relevance of an insulator element located within the Chr11q22.2 locus, downstream of the MMP8 gene (IE8). This regulatory element resulted in a topologically associating domain (TAD) boundary that isolated nine MMP genes into two anti-correlated expression clusters. This expression pattern was associated with worse relapse-free (HR = 1.57 [1.06 − 2.33]; p = 0.023) and overall (HR = 2.65 [1.31 − 5.37], p = 0.005) survival of TNBC patients. After CRISPR/Cas9-mediated disruption of IE8, cancer cells showed a switch in the MMP expression signature, specifically downregulating the pro-invasive MMP1 gene and upregulating the antitumorigenic MMP8 gene, resulting in reduced invasive ability and collagen degradation. We observed that the MMP expression pattern predicts DCIS that eventually progresses into invasive ductal carcinomas (AUC = 0.77, p < 0.01). Conclusion Our study demonstrates how the activation of an IE near the MMP8 gene determines the regional transcriptional regulation of MMP genes with opposing functional activity, ultimately influencing the invasive properties of aggressive forms of breast cancer.

Identifying molecular drivers in triple-negative breast cancer (TNBC) is crucial. While HER2-low expression predicts response to novel antibody-drug conjugates, its biological influence on TNBC biology is unknown. We performed a comprehensive multi-omics analysis, integrating genomic, epigenomic, transcriptomic, and proteomic profiling to characterize HER2-low TNBC. We generated genome-wide DNA methylation profiles from a multi-institutional cohort and integrated our data with three independent cohorts (TCGA, SCAN-B, I-SPY2). TNBC cases were categorized as HER2-zero (IHC 0) or HER2-low TNBC (IHC 1+/2+, ISH non-amplified). Among 506 patients (HER2-low, n  = 288; HER2-zero, n  = 218), HER2-low TNBC exhibited significantly lower tumor mutational burden ( P  = 0.02). Epigenetic analysis identified 5287 differentially methylated sites, with consistent hypermethylation of HLA genes in HER2-low tumors. Transcriptomic analyses revealed significant downregulation of genes enriched in immune response pathways (e.g., leukocyte activation, T-cell signaling) in HER2-low TNBC (adjusted P  < 0.001). Immune cell deconvolution showed reduced immune cell infiltration in the HER2-low tumor microenvironment ( P  = 0.002). Higher expression of five immune-related genes, downregulated in HER2-low, correlated with improved relapse-free (HR = 0.52; P  < 0.001) and overall survival (HR = 0.36; P  < 0.001). HER2-low TNBC tumors display distinct molecular features compared to HER2-zero, imparting an immune-evasive phenotype. These findings provide critical insights into the unique biology of HER2-low TNBC, warranting further clinical investigation.

Background Immune checkpoint inhibitors (ICI) improve clinical outcomes in triple-negative breast cancer (TNBC) patients. However, a subset of patients does not respond to treatment. Biomarkers that show ICI predictive potential in other solid tumors, such as levels of PD-L1 and the tumor mutational burden, among others, show a modest predictive performance in patients with TNBC. Methods We built machine learning models based on pre-ICI treatment gene expression profiles to construct gene expression classifiers to identify primary TNBC ICI-responder patients. This study involved 188 ICI-naïve and 721 specimens treated with ICI plus chemotherapy, including TNBC tumors, HR+/HER2− breast tumors, and other solid non-breast tumors. Results The 37-gene TNBC ICI predictive (TNBC-ICI) classifier performs well in predicting pathological complete response (pCR) to ICI plus chemotherapy on an independent TNBC validation cohort (AUC = 0.86). The TNBC-ICI classifier shows better performance than other molecular signatures, including PD-1 ( PDCD1 ) and PD-L1 ( CD274 ) gene expression (AUC = 0.67). Integrating TNBC-ICI with molecular signatures does not improve the efficiency of the classifier (AUC = 0.75). TNBC-ICI displays a modest accuracy in predicting ICI response in two different cohorts of patients with HR + /HER2- breast cancer (AUC = 0.72 to pembrolizumab and AUC = 0.75 to durvalumab). Evaluation of six cohorts of patients with non-breast solid tumors treated with ICI plus chemotherapy shows overall poor performance (median AUC = 0.67). Conclusion TNBC-ICI predicts pCR to ICI plus chemotherapy in patients with primary TNBC. The study provides a guide to implementing the TNBC-ICI classifier in clinical studies. Further validations will consolidate a novel predictive panel to improve the treatment decision-making for patients with TNBC. Plain language summary Triple-Negative Breast Cancer (TNBC) is an aggressive type of breast cancer, responsible for a substantial burden of breast cancer-related deaths. In recent years, immunotherapy, a therapy that triggers the patient’s immune system to attack the tumor, has arisen as a promising treatment in various cancers, including TNBC. However, a subset of patients with TNBC does not respond to this treatment. Here, we employed advanced computational techniques to predict response to immunotherapy plus chemotherapy in patients with primary TNBC. Our method is more accurate than using other existing markers, such as PD-L1, but is not very accurate in patients with non-TNBC breast cancers or non-breast cancers. This method could potentially be used to better select patients for immunotherapy, upfront, avoiding the side effects and costs of treating patients in which immunotherapy might not work. Ensenyat–Mendez et al. construct a gene expression-based machine learning classifier to predict the response of triple-negative breast cancer to immune checkpoint inhibition combined with chemotherapy. Predictive performance of the 37-gene classifier is better than that of PD-1 or PD-L1.

Objectives Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype with limited treatment options. Unlike other breast cancer subtypes, the scarcity of specific therapies and greater frequencies of distant metastases contribute to its aggressiveness. We aimed to find epigenetic changes that aid in the understanding of the dissemination process of these cancers. Data description Using CRISPR/Cas9, our experimental approach led us to identify and disrupt an insulator element, IE8, whose activity seemed relevant for cell invasion. The experiments were performed in two well-established TNBC cellular models, the MDA-MB-231 and the MDA-MB-436. To gain insights into the underlying molecular mechanisms of TNBC invasion ability, we generated and characterized high-resolution chromatin interaction (Hi-C) and chromatin accessibility (ATAC-seq) maps in both cell models and complemented these datasets with gene expression profiling (RNA-seq) in MDA-MB-231, the cell line that showed more significant changes in chromatin accessibility. Altogether, our data provide a comprehensive resource for understanding the spatial organization of the genome in TNBC cells, which may contribute to accelerating the discovery of TNBC-specific alterations triggering advances for this devastating disease.

Human tumors show altered patterns of protein isoforms that can be related to the dysregulation of messenger RNA alternative splicing also observed in transformed cells. Although somatic mutations in core spliceosome components and their associated factors have been described in some cases, almost nothing is known about the contribution of distorted epigenetic patterns to aberrant splicing. Herein, we show that the splicing RNA-binding protein CELF2 is targeted by promoter hypermethylation-associated transcriptional silencing in human cancer. Focusing on the context of breast cancer, we also demonstrate that CELF2 restoration has growth-inhibitory effects and that its epigenetic loss induces an aberrant downstream pattern of alternative splicing, affecting key genes in breast cancer biology such as the autophagy factor ULK1 and the apoptotic protein CARD10. Furthermore, the presence of CELF2 hypermethylation in the clinical setting is associated with shorter overall survival of the breast cancer patients carrying this epigenetic lesion.

Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely \"junk DNA\", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.