KRCC1: A potential therapeutic target in ovarian cancer

KRCC1, a modulator of the DNA damage response

The lysine-rich coiled-coil 1 (KRCC1) protein is overexpressed in multiple malignancies, including ovarian cancer, and overexpression correlates with poor overall survival. Despite a potential role in cancer progression, the biology of KRCC1 remains elusive. Here, we characterize the biology of KRCC1 and define its role in the DNA damage response and in cell cycle progression. We demonstrate that KRCC1 associates with the checkpoint kinase 1 (CHK1) upon DNA damage and regulates the CHK1-mediated checkpoint. KRCC1 facilitates RAD51 recombinase foci formation and augments homologous recombination repair. Furthermore, KRCC1 is required for proper S-phase progression and subsequent mitotic entry. Our findings uncover a novel component of the DNA damage response and a potential link between cell cycle, associated damage response and DNA repair.

Characterizing kinase intergenic-breakpoint rearrangements in a large-scale lung cancer population and real-world clinical outcomes

BACKGROUND

Kinase gene fusions are strong driver mutations in neoplasia; however, kinase intergenic-breakpoint rearrangements (IGRs) confound the detection of such fusions and of targeted treatments. We aim to provide an overview of kinase IGRs in a large lung cancer cohort and examine real-world survival outcomes of patients with such fusions.

METHODS

Mutational profiles analyzed using targeted next-generation sequencing of 425 cancer-related genes between June 2016 and July 2019 were retrospectively reviewed. Patients' demographic data, clinical characteristics, and survivals were analyzed. RNA sequencing or immunohistochemical assays were carried out to verify chimeric fusion products.

RESULTS

We identified 3411 patients with kinase fusions from a cohort of 30 450 patients with lung cancer, and 624 kinase IGR events were identified in 538 of the 3411 patients. The most frequently identified kinase genes included anaplastic lymphoma kinase (ALK), RET proto-oncogene (RET), ROS proto-oncogene 1 (ROS1), Erb-B2 receptor tyrosine kinase 2/3 (ERBB2/3), and epidermal growth factor receptor (EGFR). Our data showed that most (67%) kinase IGRs occurred on the same chromosome and kinase domains remained intact at the 3'-end. Approximately 3% (19/624) of the kinase IGRs had one genomic breakpoint located in gene promoter regions, including nine fusion events involving ALK, RET, ROS1, EGFR, ERBB2, or fibroblast growth factor receptor 3 (FGFR3). Among the 538 patients with kinase IGRs, 167 (31%) lacked oncogenic driver mutations, among which 28 received targeted therapies in real-world practice. Notably, three ALK IGR patients who harbored no canonical oncogenic aberrations were confirmed with an EML4-ALK chimeric fusion product by RNA sequencing and/or ALK immunohistochemical assays. One patient demonstrated a favorable clinical outcome after 14 months on crizotinib. An additional two patients who had ROS1 IGRs demonstrated a clinical benefit after 13 and 19 months on crizotinib, respectively.

CONCLUSION

A large real-world lung cancer cohort with kinase IGRs was comprehensively analyzed for their molecular characteristics. The data indicated the potential oncogenic function of kinase IGRs and their outcomes following the administration of targeted therapies.

scTenifoldKnk: An efficient virtual knockout tool for gene function predictions via single-cell gene regulatory network perturbation

Gene knockout (KO) experiments are a proven, powerful approach for studying gene function. However, systematic KO experiments targeting a large number of genes are usually prohibitive due to the limit of experimental and animal resources. Here, we present scTenifoldKnk, an efficient virtual KO tool that enables systematic KO investigation of gene function using data from single-cell RNA sequencing (scRNA-seq). In scTenifoldKnk analysis, a gene regulatory network (GRN) is first constructed from scRNA-seq data of wild-type samples, and a target gene is then virtually deleted from the constructed GRN. Manifold alignment is used to align the resulting reduced GRN to the original GRN to identify differentially regulated genes, which are used to infer target gene functions in analyzed cells. We demonstrate that the scTenifoldKnk-based virtual KO analysis recapitulates the main findings of real-animal KO experiments and recovers the expected functions of genes in relevant cell types.