Alternative protein-coding transcripts of the RASSF1 gene have been associated with dual functions in human cancer: while RASSF1C isoform has oncogenic properties, RASSF1A is a tumour suppressor frequently silenced by hypermethylation. Recently, the antisense long non-coding RNA RASSF1 (ANRASSF1) was implicated in a locus-specific mechanism for the RASSF1A epigenetic repression mediated by PRC2 (Polycomb Repressive Complex 2). Here, we evaluated the methylation patterns of the promoter regions of RASSF1A and RASSF1C and the expression levels of these RASSF1 transcripts in breast cancer and breast cancer cell lines. As expected, RASSF1C remained unmethylated and RASSF1A was hypermethylated at high frequencies in 75 primary breast cancers, and also in a panel of three mammary epithelial cells (MEC) and 10 breast cancer cell lines (BCC). Although RASSF1C was expressed in all cell lines, only two of them expressed the transcript RASSF1A. ANRASSF1 expression levels were increased in six BCCs. In vitro induced demethylation with 5-Aza-2ʹ-deoxicytydine (5-Aza-dC) resulted in up-regulation of RASSF1A and an inverse correlation with ANRASSF1 relative abundance in BCCs. However, increased levels of both transcripts were observed in two MECs (184A1 and MCF10A) after treatment with 5-Aza-dC. Overall, these findings indicate that ANRASSF1 is differentially expressed in MECs and BCCs. The lncRNA ANRASSF1 provides new perspectives as a therapeutic target for locus-specific regulation of RASSF1A.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly heterogeneous malignancy, characterized by low tumor cellularity, a dense stromal response, and intricate cellular and molecular interactions within the tumor microenvironment (TME). Although bulk omics technologies have enhanced our understanding of the molecular landscape of PDAC, the specific contributions of non-malignant immune and stromal components to tumor progression and therapeutic response remain poorly understood. Methods: We explored genome-wide DNA methylation and transcriptomic data from the Cancer Genome Atlas Pancreatic Adenocarcinoma cohort (TCGA-PAAD) to profile the immune composition of the TME and uncover gene co-expression networks. Bioinformatic analyses included DNA methylation profiling followed by hierarchical deconvolution, epigenetic age estimation, and a weighted gene co-expression network analysis (WGCNA). Results: The unsupervised clustering of methylation profiles identified two major tumor groups, with Group 2 (n = 98) exhibiting higher tumor purity and a greater frequency of KRAS mutations compared to Group 1 (n = 87) (p < 0.0001). The hierarchical deconvolution of DNA methylation data revealed three distinct TME subtypes, termed hypo-inflamed (immune-deserted), myeloid-enriched, and lymphoid-enriched (notably T-cell predominant). These immune clusters were further supported by co-expression modules identified via WGCNA, which were enriched in immune regulatory and signaling pathways. Conclusions: This integrative epigenomic–transcriptomic analysis offers a robust framework for stratifying PDAC patients based on the tumor immune microenvironment (TIME), providing valuable insights for biomarker discovery and the development of precision immunotherapies.

Pancreatic cancer is one of the most lethal malignancies worldwide, it often results in therapeutic failure and unfavorable outcome because of the absence of screening strategies, difficulties in tumor early detection due to the lack of specific signs/symptoms and aggressive behavior of the disease. Early detection of this cancer is a challenge with the technology we have, its late detection results in a poor outcome and reduced quality of life for the patient. The treatment success depends on surgical intervention, which is not always possible. Thus, trying to find alterations that occur in the early stages of pancreatic cancer is needed. Taking into consideration that the accumulation of genetic and epigenetic alterations results in a complex and heterogeneous disease, each patient has a unique tumor. The heterogeneity of cancer is not restricted to inter-patient differences but, intra-tumoral heterogeneity contributes to functional properties of tumor cell subclones, including proliferative capacity and progression to aggressive phenotypes such as drug tolerance and metastatic potential. Driver mutations are responsible for malignant transformation and tumor progression across different cancer types. One of the most common driver mutations are those leading to the constitutive activation of KRAS oncogene, a GTPase enzyme responsible for cell proliferation and survival that is frequently mutated in pancreatic cancer. Gain-of-function mutation of KRAS gene leads to a protein constitutively activated, which stimulates the proliferation of tumor cells. The c.34G>T missense mutation (rs121913530) causes the substitution of glycine for cysteine in the encoded protein KRASG12C; this mutation has been related to poorer prognosis and therapy resistance in lung cancer. As KRAS occurs before the progression of pancreatic cancer to invasive carcinoma, it is a promising target for new biomarker development. We design three near-infrared probe-drug conjugate directed to the KRASG12C and to predict in silico the best orientation and conformation of the test compounds bound to the KRAS G12C (PDB code: 6OIM), the PyRx program was used, which uses AutoDock Vina as docking software. Based on these profiles and structures of the compounds, AutoDock Vina infers the possible pharmacological interactions and allows the most promising compounds to be classified according to the studied biological activity, using the empirical score function for this classification. The AMG 510 (established inhibitor) and GDP (endogenous activator) were used as a reference to establish the docking box coordinates. The binding energy of the three compounds predicted by docking was analyzed and classified according to the binding affinity described in Kcal/mol. The tested compounds show an excellent affinity for this protein based on the binding energy results obtained by docking using the crystallized KRAS G12C protein. Therefore, they could be great candidates for further chemical synthesis studies aiming to improve diagnosis, treatment, and patient survival in pancreatic cancer. Citation Format: Barbara M. Barbosa, Allana C. F. Martins, Roberto S. Gomes, Claudia A. Rainho. In silico drug design using KRASG12C as a theranostic target for pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B040.