Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements.

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.

Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors.

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.

3-D chromatin conformation, accessibility, and gene expression profiling of triple-negative breast cancer.

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.

Epigenetic Profiles of Triple-Negative Breast Cancers of African American and White Females.

Importance: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and appears to have disproportionately higher incidence and worse outcomes among younger African American females. Objective: To investigate whether epigenetic differences exist in TNBCs of younger African American females that may explain clinical disparities seen in this patient group. Design, Setting, and Participants: This cross-sectional study used clinical, demographic, DNA methylation (HumanMethylation450; Illumina), and gene expression (RNA sequencing) data for US patient populations from publicly available data repositories (The Cancer Genome Atlas [TCGA], 2006-2012, and Gene Expression Omnibus [GEO], 2004-2013) accessed on April 13, 2021. White and African American females with TNBC identified in TCGA (69 patients) and a validation cohort of 210 African American patients from GEO (GSE142102) were included. Patients without available race or age data were excluded. Data were analyzed from September 2022 through April 2023. Main Outcomes and Measures: DNA methylation and gene expression profiles of TNBC tumors by race (self-reported) and age were assessed. Age was considered a dichotomous variable using age 50 years as the cutoff (younger [<50 years] vs older [≥50 years]). Results: A total of 69 female patients (34 African American [49.3%] and 35 White [50.7%]; mean [SD; range] age, 55.7 [11.6; 29-82] years) with TNBC were included in the DNA methylation analysis; these patients and 210 patients in the validation cohort were included in the gene expression analysis (279 patients). There were 1115 differentially methylated sites among younger African American females. The DNA methylation landscape on TNBC tumors in this population had increased odds of enrichment of hormone (odds ratio [OR], 1.82; 95% CI, 1.21 to 2.67; P = .003), muscle (OR, 1.85; 95% CI, 1.44 to 2.36; P < .001), and proliferation (OR, 3.14; 95% CI, 2.71 to 3.64; P < .001) pathways vs other groups (older African American females and all White females). Alterations in regulators of these molecular features in TNBCs of younger African American females were identified involving hormone modulation (downregulation of androgen receptor: fold change [FC] = -2.93; 95% CI, -4.76 to -2.11; P < .001) and upregulation of estrogen-related receptor α (FC = 0.86; 95% CI, 0.34 to 1.38; P = .002), muscle metabolism (upregulation of FOXC1: FC = 1.33; 95% CI, 0.62 to 2.03; P < .001), and proliferation mediators (upregulation of NOTCH1: FC = 0.71; 95% CI, 0.23 to 1.19; P = .004 and MYC (FC = 0.81; 95% CI, 0.18 to 1.45; P = .01). Conclusions and Relevance: These findings suggest that TNBC of younger African American females may represent a distinct epigenetic entity and offer novel insight into molecular alterations associated with TNBCs of this population. Understanding these epigenetic differences may lead to the development of more effective therapies for younger African American females, who have the highest incidence and worst outcomes from TNBC of any patient group.

Construction and validation of a gene expression classifier to predict immunotherapy response in primary triple-negative breast cancer.

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.

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.

Multiplatform Analysis of Intratumoral PTEN Heterogeneity in Melanoma.

Loss of protein expression of the tumor suppressor PTEN is associated with increased cancer aggressiveness, decreased tumor immune infiltration, and resistance to immune and targeted therapies in melanoma. We assessed a unique cohort of eight melanoma samples with focal loss of PTEN protein expression to understand the features and mechanisms of PTEN loss in this disease. We compared the PTEN-negative (PTEN[-]) areas to their adjacent PTEN-positive (PTEN[+]) areas using DNA sequencing, DNA methylation, RNA expression, digital spatial profiling, and immunohistochemical platforms. Variations or homozygous deletions of PTEN were identified in PTEN(-) areas that were not detected in the adjacent PTEN(+) areas in three cases (37.5%), but no clear genomic or DNA methylation basis for loss was identified in the remaining PTEN(-) samples. RNA expression data from two independent platforms identified a consistent increase in chromosome segregation gene expression in PTEN(-) versus adjacent PTEN(+) areas. Proteomic analysis showed a relative paucity of tumor-infiltrating lymphocytes in PTEN(-) versus adjacent PTEN(+) areas. The findings add to our understanding of potential molecular intratumoral heterogeneity in melanoma and the features associated with the loss of PTEN protein in this disease.

Epigenetically regulated PCDHB15 impairs aggressiveness of metastatic melanoma cells.

The protocadherin proteins are cell adhesion molecules at the crossroad of signaling pathways playing a major role in neuronal development. It is now understood that their role as signaling hubs is not only important for the normal physiology of cells but also for the regulation of hallmarks of cancerogenesis. Importantly, protocadherins form a cluster of genes that are regulated by DNA methylation. We have identified for the first time that PCDHB15 gene is DNA-hypermethylated on its unique exon in the metastatic melanoma-derived cell lines and patients' metastases compared to primary tumors. This DNA hypermethylation silences the gene, and treatment with the DNA demethylating agent 5-aza-2'-deoxycytidine reinduces its expression. We explored the role of PCDHB15 in melanoma aggressiveness and showed that overexpression impairs invasiveness and aggregation of metastatic melanoma cells in vitro and formation of lung metastasis in vivo. These findings highlight important modifications of the methylation of the PCDHß genes in melanoma and support a functional role of PCDHB15 silencing in melanoma aggressiveness.

Machine Learning-Based Epigenetic Classifiers for Axillary Staging of Patients with ER-Positive Early-Stage Breast Cancer.

BACKGROUND: In the era of molecular stratification and effective multimodality therapies, surgical staging of the axilla is becoming less relevant for patients with estrogen receptor (ER)-positive early-stage breast cancer (EBC). Therefore, a nonsurgical method for accurately predicting lymph node disease is the next step in the de-escalation of axillary surgery. This study sought to identify epigenetic signatures in the primary tumor that accurately predict lymph node status. PATIENTS AND METHODS: We selected a cohort of patients in The Cancer Genome Atlas (TCGA) with ER-positive, HER2-negative invasive ductal carcinomas, and clinically-negative axillae (n = 127). Clinicopathological nomograms from the Memorial Sloan Kettering Cancer Center (MSKCC) and the MD Anderson Cancer Center (MDACC) were calculated. DNA methylation (DNAm) patterns from primary tumor specimens were compared between patients with pN0 and those with > pN0. The cohort was divided into training (n = 85) and validation (n = 42) sets. Random forest was employed to obtain the combinations of DNAm features with the highest accuracy for stratifying patients with > pN0. The most efficient combinations were selected according to the area under the curve (AUC). RESULTS: Clinicopathological models displayed a modest predictive potential for identifying > pN0 disease (MSKCC AUC 0.76, MDACC AUC 0.69, p = 0.15). Differentially methylated sites (DMS) between patients with pN0 and those with > pN0 were identified (n = 1656). DMS showed a similar performance to the MSKCC model (AUC = 0.76, p = 0.83). Machine learning approaches generated five epigenetic classifiers, which showed higher discriminative potential than the clinicopathological variables tested (AUC > 0.88, p < 0.05). CONCLUSIONS: Epigenetic classifiers based on primary tumor characteristics can efficiently stratify patients with no lymph node involvement from those with axillary lymph node disease, thereby providing an accurate method of staging the axilla.

Glioblastoma Embryonic-like Stem Cells Exhibit Immune-Evasive Phenotype.

BACKGROUND: Glioma stem cells (GSCs) have self-renewal and tumor-initiating capacities involved in drug resistance and immune evasion mechanisms in glioblastoma (GBM). METHODS: Core-GSCs (c-GSCs) were identified by selecting cells co-expressing high levels of embryonic stem cell (ESC) markers from a single-cell RNA-seq patient-derived GBM dataset (n = 28). Induced c-GSCs (ic-GSCs) were generated by reprogramming GBM-derived cells (GBM-DCs) using induced pluripotent stem cell (iPSC) technology. The characterization of ic-GSCs and GBM-DCs was conducted by immunostaining, transcriptomic, and DNA methylation (DNAm) analysis. RESULTS: We identified a GSC population (4.22% ± 0.59) exhibiting concurrent high expression of ESC markers and downregulation of immune-associated pathways, named c-GSCs. In vitro ic-GSCs presented high expression of ESC markers and downregulation of antigen presentation HLA proteins. Transcriptomic analysis revealed a strong agreement of enriched biological pathways between tumor c-GSCs and in vitro ic-GSCs (κ = 0.71). Integration of our epigenomic profiling with 833 functional ENCODE epigenetic maps identifies increased DNA methylation on HLA genes' regulatory regions associated with polycomb repressive marks in a stem-like phenotype. CONCLUSIONS: This study unravels glioblastoma immune-evasive mechanisms involving a c-GSC population. In addition, it provides a cellular model with paired gene expression, and DNA methylation maps to explore potential therapeutic complements for GBM immunotherapy.

Epigenetic Signatures Predict Pathologic Nodal Stage in Breast Cancer Patients with Estrogen Receptor-Positive, Clinically Node-Positive Disease.

BACKGROUND: Breast cancer patients with clinically positive nodes who undergo upfront surgery are often recommended for axillary lymph node dissection (ALND), yet more than half are found to have limited nodal disease (≤ 3 positive nodes, pN1) at surgery. In this study, we examined the efficiency of molecular classifiers in stratifying patients with clinically positive nodes to pN1 versus > pN1 disease. METHODS: We evaluated the clinical and epigenetic data of patients in The Cancer Genome Atlas with estrogen receptor-positive, human epidermal growth factor receptor 2-negative invasive ductal carcinoma who underwent ALND for node-positive disease. Patients were divided into control (pN1, ≤ 3 positive nodes) and case (> pN1, > 3 positive nodes) groups. Machine learning algorithms were trained on 50% of the cohort and validated on the remaining 50% to identify DNA methylation signatures that predict > pN1 disease. Clinical variables and epigenetic signatures were compared. RESULTS: Controls (n = 34) and case (n = 24) cohorts showed similar mean age (56.4 ± 12.2 vs. 57.6 ± 16.7 years; p = 0.77), number of nodes removed (16.1 ± 7.3 vs. 17.5 ± 6.2; p = 0.45), tumor grade (p = 0.76), presence of lymphovascular invasion (p = 0.18), extranodal extension (p = 0.17), tumor laterality (p = 0.89), and tumor location (p = 0.42). The mean number of positive nodes was significantly different (1.76 ± 0.82, pN1; 8.83 ± 5.36, > pN1; p < 0.001). Three epigenetic signatures (EpiSig14, EpiSig13, EpiSig10) based on DNA methylation patterns of the primary tumors demonstrated high accuracy in predicting > pN1 disease (area under the curve 0.98). CONCLUSIONS: Epigenetic signatures have an excellent diagnostic accuracy for stratifying nodal disease in patients with clinically positive nodes. Validation of this tool is warranted and may provide an accurate and cost-effective method of identifying patients with predicted low nodal burden who could be spared the morbidity of ALND.

LCOR mediates interferon-independent tumor immunogenicity and responsiveness to immune-checkpoint blockade in triple-negative breast cancer.

Ligand-dependent corepressor (LCOR) mediates normal and malignant breast stem cell differentiation. Cancer stem cells (CSCs) generate phenotypic heterogeneity and drive therapy resistance, yet their role in immunotherapy is poorly understood. Here we show that immune-checkpoint blockade (ICB) therapy selects for LCORlow CSCs with reduced antigen processing/presentation machinery (APM) driving immune escape and ICB resistance in triple-negative breast cancer (TNBC). We unveil an unexpected function of LCOR as a master transcriptional activator of APM genes binding to IFN-stimulated response elements (ISREs) in an IFN signaling-independent manner. Through genetic modification of LCOR expression, we demonstrate its central role in modulation of tumor immunogenicity and ICB responsiveness. In TNBC, LCOR associates with ICB clinical response. Importantly, extracellular vesicle (EV) Lcor-messenger RNA therapy in combination with anti-PD-L1 overcame resistance and eradicated breast cancer metastasis in preclinical models. Collectively, these data support LCOR as a promising target for enhancement of ICB efficacy in TNBC, by boosting of tumor APM independently of IFN.

A Microcosm of Disparities in Breast Cancer: Comparison Between a Private Hospital and a Safety-Net County Hospital Within Los Angeles County.

BACKGROUND: Breast cancer survival is improving due to early detection and treatment advances. However, racial/ethnic differences in tumor biology, stage, and mortality remain. The objective of this study was to analyze presumed disparities at a local level. METHODS: Breast cancer patients at a county hospital and private hospital from 2010 to 2012 were retrospectively reviewed. Demographic, clinical, pathologic, and surgical data were collected. Comparisons were made between hospital cohorts and between racial/ethnic groups from both hospitals combined. RESULTS: 754 patients were included (322 from county hospital and 432 from private hospital). All patients were female. The median age was 54 years at county hospital and 60 years at private hospital (P < .0001). Racial/ethnic minorities comprised 85% of county hospital patients vs. 12% of private hospital patients (P < .0001). County hospital patients had a higher grade, clinical/pathologic stage, HER2-positive rate, and mastectomy rate. Compared to other racial/ethnic groups, non-Hispanic white women were more likely to have lower grade and ER-positive tumors. Hispanic/Latina women were younger and were more likely to have HER2-positive tumors. Both Hispanic/Latina and non-Hispanic black women presented at higher clinical stages and were more likely to undergo neoadjuvant chemotherapy and mastectomy. DISCUSSION: At county hospital compared to private hospital, the proportion of racial/ethnic minorities was higher, and patients presented at younger ages with more aggressive tumors and more advanced disease. The racial/ethnic disparities that were identified locally are largely consistent with those identified in national database studies. These marked differences at hospitals within a diverse city highlight the need for further research into the disparities.

Establishing Novel Molecular Subtypes of Appendiceal Cancer.

PURPOSE: Appendiceal cancer is a rare disease process with complex treatment strategies. The objective of this study was to identify mutation-based genetic subtypes that may differ from the current histological classification, compare the genetic make-up of primaries and metastases, and find novel targetable alterations. METHODS: The analyses involved the curation and normalization of gene mutation panels from appendiceal adenocarcinoma and mucinous adenocarcinoma (n = 196) stored in the AACR GENIE Database v6.0. Genes mutated in less than one patient and tumors profiled with incomplete mutation panels were excluded from the study. The optimal number of AC subtypes was established using the Nonnegative Matrix Factorization algorithm. Statistical comparisons of mutation frequencies were performed using Pearson's χ2 test. RESULTS: AC patients were stratified into five mutation subtypes, based on a final set of 41 cancer-related genes. AC0 had no mutations. The most frequently mutated genes varied between the subtypes were: AC1: KRAS (91.9%) and GNAS (77.4%); AC2: KRAS (52.5%), APC (32.5%), and GNAS (30%); AC3: KMT2D (38.7%), TP53 (38.7%), KRAS (35.5%), EP300 (22.6%); and AC4: TP53 (97.2%), KRAS (77.8%), and SMAD4 (36.1%). Additionally, AC3 was less likely to be mucinous (22.6% vs. 50.0-74.2%, p < 0.001) and had a higher mutation frequency (3.6 vs. 0-3.1, p < 0.001). There were no significant differences between primary tumors and metastases in the 41 assessed genes (p = 0.35). CONCLUSIONS: The characterization of these subtypes suggests a need for molecular approaches to complement anatomical and histopathological staging for AC. A prospective comparison of subtype prognosis and response to surgery and adjuvant treatment is needed to identify the clinical applications of the novel molecular subtypes.

iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes.

BACKGROUND: Glioblastoma (GBM) is the most aggressive and prevalent primary brain tumor, with a median survival of 15 months. Advancements in multi-omics profiling combined with computational algorithms have unraveled the existence of three GBM molecular subtypes (Classical, Mesenchymal, and Proneural) with clinical relevance. However, due to the costs of high-throughput profiling techniques, GBM molecular subtyping is not currently employed in clinical settings. METHODS: Using Random Forest and Nearest Shrunken Centroid algorithms, we constructed transcriptomic, epigenomic, and integrative GBM subtype-specific classifiers. We included gene expression and DNA methylation (DNAm) profiles from 304 GBM patients profiled in the Cancer Genome Atlas (TCGA), the Human Glioblastoma Cell Culture resource (HGCC), and other publicly available databases. RESULTS: The integrative Glioblastoma Subtype (iGlioSub) classifier shows better performance (mean AUC = 95.9%) stratifying patients than gene expression (mean AUC = 91.9%) and DNAm-based classifiers (AUC = 93.6%). Also, to expand the understanding of the molecular differences between the GBM subtypes, this study shows that each subtype presents unique DNAm patterns and gene pathway activation. CONCLUSIONS: The iGlioSub classifier provides the basis to design cost-effective strategies to stratify GBM patients in routine pathology laboratories for clinical trials, which will significantly accelerate the discovery of more efficient GBM subtype-specific treatment approaches.