No abstract

The dysregulation of post-translational modifications (PTM) transversally impacts cancer hallmarks and constitutes an appealing vulnerability for drug development. In breast cancer there is growing preclinical evidence of the role of ubiquitin and ubiquitin-like SUMO and Nedd8 peptide conjugation to the proteome in tumorigenesis and drug resistance, particularly through their interplay with estrogen receptor signaling and DNA repair. Herein we explored genomic alterations in these processes using RNA-seq and mutation data from TCGA and METABRIC datasets, and analyzed them using a bioinformatic pipeline in search of those with prognostic and predictive capability which could qualify as subjects of drug research. Amplification of UBE2T, UBE2C, and BIRC5 conferred a worse prognosis in luminal A/B and basal-like tumors, luminal A/B tumors, and luminal A tumors, respectively. Higher UBE2T expression levels were predictive of a lower rate of pathological complete response in triple negative breast cancer patients following neoadjuvant chemotherapy, whereas UBE2C and BIRC5 expression was higher in luminal A patients with tumor relapse within 5 years of endocrine therapy or chemotherapy. The transcriptomic signatures of USP9X and USP7 gene mutations also conferred worse prognosis in luminal A, HER2-enriched, and basal-like tumors, and in luminal A tumors, respectively. In conclusion, we identified and characterized the clinical value of a group of genomic alterations in ubiquitination, SUMOylation, and neddylation enzymes, with potential for drug development in breast cancer.

Alternative splicing is an essential biological process, which increases the diversity and complexity of the human transcriptome. In our study, 304 splicing pathway-related genes were evaluated in tumors from breast cancer patients (TCGA dataset). A high number of alterations were detected, including mutations and copy number alterations (CNAs), although mutations were less frequently present compared with CNAs. In the four molecular subtypes, 14 common splice genes showed high level amplification in >5% of patients. Certain genes were only amplified in specific breast cancer subtypes. Most altered genes in each molecular subtype clustered to a few chromosomal regions. In the Luminal subtype, amplifications of LSM1, CLNS1A, and ILF2 showed a strong significant association with prognosis. An even more robust association with OS and RFS was observed when expression of these three genes was combined. Inhibition of LSM1, CLNS1A, and ILF2, using siRNA in MCF7 and T47D cells, showed a decrease in cell proliferation. The mRNA expression of these genes was reduced by treatment with BET inhibitors, a family of epigenetic modulators. We map the presence of splicing-related genes in breast cancer, describing three novel genes, LSM1, CLNS1A, and ILF2, that have an oncogenic role and can be modulated with BET inhibitors.

Identification of genomic alterations that influence the immune response within the tumor microenvironment is mandatory in order to identify druggable vulnerabilities. In this article, by interrogating public genomic datasets we describe copy number variations (CNV) present in breast cancer (BC) tumors and corresponding subtypes, associated with different immune populations. We identified regulatory T-cells associated with the Basal-like subtype, and type 2 T-helper cells with HER2 positive and the luminal subtype. Using gene set enrichment analysis (GSEA) for the Type 2 T-helper cells, the most relevant processes included the ERBB2 signaling pathway and the Fibroblast Growth Factor Receptor (FGFR) signaling pathway, and for CD8+ T-cells, cellular response to growth hormone stimulus or the JAK-STAT signaling pathway. Amplification of ERBB2, GRB2, GRB7, and FGF receptor genes strongly correlated with the presence of type 2 T helper cells. Finally, only 8 genes were highly upregulated and present in the cellular membrane: MILR1, ACE, DCSTAMP, SLAMF8, CD160, IL2RA, ICAM2, and SLAMF6. In summary, we described immune populations associated with genomic alterations with different BC subtypes. We observed a clear presence of inhibitory cells, like Tregs or Th2 when specific chromosomic regions were amplified in basal-like or HER2 and luminal groups. Our data support further evaluation of specific therapeutic strategies in specific BC subtypes, like those targeting Tregs in the basal-like subtype.

e13045 Background: Combination therapeutic strategies including CDK4/6 inhibitors and an endocrine backbone are the standard of care of treatment for patients with estrogen receptor positive (ER+)/HER2- advanced breast cancer (ABC). Endocrine agents mainly include aromatase inhibitors, which target ER-driven transcription, and fulvestrant, which functions as ER antagonist. PI3K-AKT-mTOR is a key point of resistance to endocrine therapy, activated in 40% of these patients by mutations concentrated in critical regions of PIK3CA, coding for the p110 catalytic subunit α of PI3K. Additionally, 30% of patients previously exposed to non-steroidal aromatase inhibitors develop mutations in the ligand binding domain of ESR1, causing endocrine resistance by constitutive activation of the ER. Furthermore, metastasis and primary tumors may show a highly heterogenous mutational landscape. Monitoring the dynamic changes of these mutations in ctDNA may provide a non-invasive, real-time and accessible tool to convey predictive/prognostic information and guide decisions on sequential endocrine therapies. Methods: Pre-planned interim analysis results of an observational, prospective cohort pilot study to assess the predictive and prognostic value of monitoring PIK3CA and ESR1 mutations in ctDNA of patients with endocrine-resistant ER+/HER2- ABC. We have studied longitudinal liquid biopsies from 30 patients using digital PCR to interrogate PIK3CA mutations (H1047R / E545K) and ESR1 mutations (D538G / Y537S). Blood samples were drawn at the time of progression to endocrine therapy, at 8 weeks of subsequent endocrine line and at new progression. This exploratory analysis will provide preliminary data on clinical homogeneity, treatment regimens, median follow-up and progression-free survival, mutation incidence and intraindividual variation of mutant allele frequency and copy number. The percentage of progressors at 24 weeks of follow-up according to the mutational status will be evaluated by using the Fisher’s exact test. The predictive potential of ctDNA biomarkers will be characterized by ROC curve analysis. Tracking ctDNA mutations to predict endocrine resistance in a real-world setting represents a critical step towards precision medicine in oncology.