Biology subjects

Gazzo, A.

Publications and source records attributed to Gazzo, A..

5 recordsLinked to original sources

bioRxiv2025

RRAS and RRAS2 mutations are oncogenic drivers in lung cancer and are sensitive to the pan-RAS inhibitor RMC-6236

IntroductionRRAS and RRAS2 encode a subfamily of RAS-like small GTPases that share considerable structural and functional similarities with KRAS, HRAS, and NRAS. Whether homologous RRAS/RRAS2 mutations are oncogenic and actionable drivers in lung cancer remains underexplored. MethodsAn institutional cohort of 8,488 non-small cell lung carcinomas (NSCLC) sequenced by comprehensive targeted DNA sequencing (MSK-IMPACT) between 2016-2024 was evaluated for RRAS/RRAS2 mutations. RRASQ87L or RRAS2Q72L were modeled in murine IL3-dependent Ba/F3 cells and immortalized human bronchiolar epithelial cells (HBECs). The oncogenic potential, signaling characteristics, and sensitivity to PI3K and MAPK pathway inhibitors, including the novel pan-RAS inhibitor RMC-6236, were evaluated in vitro and in vivo. ResultsRRASQ87L or RRAS2Q72L, homologous to KRAS-codon Q61 substitutions, were found in [~]0.45% of NSCLCs (38/8,488), with all but two lacking other MAPK pathway oncogenic drivers. RRASQ87L and RRAS2Q72L mutations transformed Ba/F3 and HBEC cells and robustly activated MAPK and PI3K-mTOR pathway signaling. RMC-6236 suppressed proliferation of RRASQ87L and RRAS2Q72L mutant cell lines, reduced ERK phosphorylation, induced apoptosis, and impeded cell-cycle progression. In vivo, RMC-6236 significantly inhibited growth of RRASQ87L/RRAS2Q72L-mutant HBEC-derived xenografts. ConclusionsRRASQ87L and RRAS2Q72L are recurrent, oncogenic, and potentially actionable drivers in NSCLC. Our study supports the inclusion of RRAS/RRAS2 into routine molecular diagnostic panels for precision oncology and provides preclinical rationale for investigating the potential therapeutic utility of pan-RAS inhibitors for patients with RRASQ87L/RRAS2Q72L-mutant lung cancers. Statement of translational relevanceTargeted therapies have transformed standard of care for oncogene-driven non-small cell lung carcinomas (NSCLC), yet a significant subset lacks actionable drivers. We identified recurrent RRASQ87L and RRAS2Q72L mutations which are mutually exclusive with other MAPK pathway drivers and found in [~]0.45% of NSCLC, comparable in prevalence to NTRK and NRG1 fusions. In preclinical models, these mutations activate canonical growth signaling, drive tumorigenic phenotypes, and confer sensitivity to RAS/MAPK-directed agents, including the novel pan-RAS inhibitor RMC-6236, currently in trials for patients with solid tumors harboring KRAS mutations. These data support RRASQ87L and RRAS2Q72L as bona fide lung cancer drivers and nominate RRAS/RRAS2-mutant tumors as candidates for pan-RAS-targeted therapeutics. Our findings provide a biologic rationale and preclinical evidence to inform molecular testing paradigms and to prioritize enrollment of patients with RRAS/RRAS2-mutant NSCLC into future clinical trials of pan-RAS inhibitors.

cancer biology↗

bioRxiv2025

RNA Transcripts Serve as a Template for Double-Strand Break Repair in Human Cells

Double-strand breaks (DSBs) are toxic lesions that lead to genome instability. While canonical DSB repair pathways typically operate independently of RNA, emerging evidence suggests that RNA:DNA hybrids and transcripts near damaged sites can influence repair outcomes. However, a direct role for transcript RNA as a template during DSB repair in human cells is yet to be established. In this study, we designed fluorescent- and sequencing-based assays, which demonstrated that RNA-containing oligonucleotides and messenger RNA serve as templates to promote DSB repair. We conducted a CRISPR/Cas9-based genetic screen to identify factors that promote RNA-templated DSB repair (RT-DSBR), and of the candidate polymerases, we identified DNA polymerase-zeta (Pol{zeta}) as the potential reverse transcriptase that facilitates RT-DSBR. Furthermore, by analyzing sequencing data from cancer genomes, we identified the presence of whole intron deletions, a unique genomic scar reflective of RT-DSBR activity generated when spliced mRNA serves as the repair template. These findings highlight RT-DSBR as an alternative pathway for repairing DSBs in transcribed genes, with potential mutagenic consequences.

molecular biology↗

bioRxiv2024

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer1-7, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naive hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

cancer biology↗

bioRxiv2023

Interferon response and epigenetic modulation by SMARCA4 mutations drive ovarian tumor immunogenicity

Cell-intrinsic mechanisms of immunogenicity in ovarian cancer (OC) are not well understood. The presence of damaging mutations in the SWI/SNF chromatin remodeling complex, such as the SMARCA4 (BRG1) catalytic subunit, has been associated with improved response to ICB, however the mechanism by which this occurs is unclear. The aim of this current study was to examine the alterations in tumor cell-intrinsic and extrinsic immune signaling caused by SMARCA4 loss. Using OC models with loss-of-function mutations in SMARCA4, we found that SMARCA4 loss resulted in increased cancer cell-intrinsic immunogenicity, characterized by upregulation of long-terminal RNA repeats such as endogenous retroviruses, increased expression of interferon-stimulated genes, and upregulation of antigen presentation machinery. Notably, this response was dependent on IRF3 signaling, but was independent of the type I interferon receptor. Mice inoculated with cancer cells bearing SMARCA4 loss demonstrated increased activation of cytotoxic T cells and NK cells in the tumor microenvironment as well as increased infiltration with activated dendritic cells. These results were recapitulated when animals bearing SMARCA4-proficient tumors were treated with a BRG1 inhibitor, suggesting that modulation of chromatin remodeling through targeting SMARCA4 may serve as a strategy to reverse immune evasion in OC.

cancer biology↗

bioRxiv2019

Predicting disease-causing variant combinations

Notwithstanding important advances in the context of single-variant pathogenicity identification, novel breakthroughs in discerning the origins of many rare diseases require methods able to identify more complex genetic models. We present here the Variant Combinations Pathogenicity Predictor (VarCoPP), a machine-learning approach that identifies pathogenic variant combinations in gene pairs (bi-locus variant combinations). We show that the results produced by this method are highly accurate and precise, an efficacy that is endorsed when validating the method on recently published independent disease-causing data. Confidence labels of 95% and 99% are identified, representing the probability of a bi-locus combination being a true pathogenic result, providing geneticists with rational markers to evaluate the most relevant pathogenic combinations and limit the search space and time. Finally, VarCoPP has been designed to act as an interpretable method that can provide explanations on why a bi-locus combination is predicted as pathogenic and which biological information is important for that prediction. This work provides an important new step towards the genetic understanding of rare diseases, paving the way to new clinical knowledge and improved patient care.

bioinformatics↗