Breast cancer (BC) is a highly heterogeneous disease with diverse molecular subtypes, which complicates prognosis and treatment. In this study, we performed a multi-omics clustering analysis using the Cancer Integration via MultIkernel LeaRning (CIMLR) method on a large BC dataset from The Cancer Genome Atlas (TCGA) to identify key prognostic biomarkers. We identified three genes—LMO1, PRAME, and RSPO2—that were significantly associated with poor prognosis in both the TCGA dataset and an additional dataset comprising 146 metastatic BC patients. Patients’ stratification based on the expression of these three genes revealed distinct subtypes with markedly different overall survival (OS) outcomes. Further validation using almost 2000 BC patients’ data from the METABRIC dataset and RNA sequencing data from therapy-resistant cell lines confirmed the upregulation of LMO1 and PRAME, respectively, in patients with worse prognosis and in resistant cells, also suggesting their potential role in drug resistance. Our findings highlight LMO1 and PRAME as potential biomarkers for identifying high-risk BC patients and informing targeted treatment strategies. This study provides valuable insights into the multi-omics landscape of BC and underscores the importance of personalized therapeutic approaches based on molecular profiles.

Background: Colorectal cancer (CRC) is a leading cause of cancer-related mortality, largely driven by aberrant activation of the WNT/β-catenin and RAS pathways. Despite recent therapeutic advances, effective strategies to target these oncogenic signals remain limited. Methods: A multi-step chemical library screen was performed to identify compounds capable of suppressing β-catenin and RAS signaling. Drug mechanisms and combination effects were investigated through functional assays, in vitro and in vivo experiments, and transcriptomic profiling. Survival analysis of the Sidra-LUMC AC-ICAM CRC cohort ( n = 303) was conducted to evaluate the prognostic significance of candidate target genes. Results: We identified the CDK4/6 inhibitor palbociclib as an unexpected suppressor of β-catenin signaling. Uniquely, palbociclib promoted GSK3β-mediated β-catenin degradation by dampening AKT activity, revealing a previously unrecognized mechanism of action and broadening its role beyond canonical cell-cycle inhibition. Building on this mechanism, we found that combining palbociclib with the KRAS ^G12D -specific inhibitor MRTX1133 elicited potent and selective anti-tumor effects in vitro and in vivo. Parallel screening also revealed the ERK5 inhibitor ERK5-IN-1 as a promising combination partner: co-administration with palbociclib strongly suppressed proliferation across multiple CRC models, showed minimal toxicity in normal cells, and produced durable tumor control in vivo. Transcriptomic profiling indicated that both combinations converge on a common program of cancer cell-state reprogramming, characterized by suppression of proliferative drivers and remodeling of metabolic and mitochondrial pathways. Underscoring the clinical relevance of our findings, survival analysis of the Sidra-LUMC AC-ICAM CRC cohort ( n = 303) revealed that ERK5 target genes CREB5 and NUPR1 , identified in our dataset, were consistently linked to poor prognosis, thereby connecting this signaling axis to unfavorable patient outcomes. Conclusions: Together, these findings position palbociclib as a versatile therapeutic backbone in CRC. By simultaneously targeting cell cycle and oncogenic signaling networks, palbociclib-based combinations induce synergistic and durable responses, offering a compelling rationale for tailored therapeutic strategies in molecularly defined CRC.