PARP4 interacts with hnRNPM to regulate splicing during lung cancer progression.

BACKGROUND: The identification of cancer driver genes from sequencing data has been crucial in deepening our understanding of tumor biology and expanding targeted therapy options. However, apart from the most commonly altered genes, the mechanisms underlying the contribution of other mutations to cancer acquisition remain understudied. Leveraging on our whole-exome sequencing of the largest Asian lung adenocarcinoma (LUAD) cohort (n = 302), we now functionally assess the mechanistic role of a novel driver, PARP4. METHODS: In vitro and in vivo tumorigenicity assays were used to study the functional effects of PARP4 loss and mutation in multiple lung cancer cell lines. Interactomics analysis by quantitative mass spectrometry was conducted to identify PARP4's interaction partners. Transcriptomic data from cell lines and patient tumors were used to investigate splicing alterations. RESULTS: PARP4 depletion or mutation (I1039T) promotes the tumorigenicity of KRAS- or EGFR-driven lung cancer cells. Disruption of the vault complex, with which PARP4 is commonly associated, did not alter tumorigenicity, indicating that PARP4's tumor suppressive activity is mediated independently. The splicing regulator hnRNPM is a potentially novel PARP4 interaction partner, the loss of which likewise promotes tumor formation. hnRNPM loss results in splicing perturbations, with a propensity for dysregulated intronic splicing that was similarly observed in PARP4 knockdown cells and in LUAD cohort patients with PARP4 copy number loss. CONCLUSIONS: PARP4 is a novel modulator of lung adenocarcinoma, where its tumor suppressive activity is mediated not through the vault complex-unlike conventionally thought, but in association with its novel interaction partner hnRNPM, thus suggesting a role for splicing dysregulation in LUAD tumorigenesis.

Single-cell and bulk transcriptome sequencing identifies two epithelial tumor cell states and refines the consensus molecular classification of colorectal cancer.

The consensus molecular subtype (CMS) classification of colorectal cancer is based on bulk transcriptomics. The underlying epithelial cell diversity remains unclear. We analyzed 373,058 single-cell transcriptomes from 63 patients, focusing on 49,155 epithelial cells. We identified a pervasive genetic and transcriptomic dichotomy of malignant cells, based on distinct gene expression, DNA copy number and gene regulatory network. We recapitulated these subtypes in bulk transcriptomes from 3,614 patients. The two intrinsic subtypes, iCMS2 and iCMS3, refine CMS. iCMS3 comprises microsatellite unstable (MSI-H) cancers and one-third of microsatellite-stable (MSS) tumors. iCMS3 MSS cancers are transcriptomically more similar to MSI-H cancers than to other MSS cancers. CMS4 cancers had either iCMS2 or iCMS3 epithelium; the latter had the worst prognosis. We defined the intrinsic epithelial axis of colorectal cancer and propose a refined 'IMF' classification with five subtypes, combining intrinsic epithelial subtype (I), microsatellite instability status (M) and fibrosis (F).

Cell interaction knowledgebase: an online database for innate immune cells, cytokines and chemokines.

The innate immune system is fundamental to the recognition of pathogens, triggering of immune-inflammatory response and host defense. Recent advance in this area has resulted in enormous amount of data, which are stored across different databases. Integrating relevant information from these different data sources is difficult because of their heterogeneous nature and dispersed physical location. We present here a single portal system, Cell Interaction Knowledgebase, with focus on the innate immunity. In particular, the knowledgebase houses comprehensive information on innate immune cells and cytokines/chemokines which are the principal mediators of communication among the immune cells. Currently the knowledgebase consists of extensive information on 2 major innate immune cell types (Macrophages and Dendritic cells) and 7 6 cytokines/chemokines for both human and mouse. In addition, intra-cellular molecular interactions and inter-cellular interactions involved in the innate immunity are curated and presented in an interactive and dynamic manner by animated pathways and query-driven cell-interaction map respectively. This is one of the first databases that houses extensive phenotypic, signaling, genomic, proteomic and knockout data on both the innate immune cells and their attendant cytokines/chemokines, and is aimed to evolve as a one-stop-shop for immunologists. The first version of database is available at http://cell-interaction.bii.a-star.edu.sg/.