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Poly (ADP-ribose) polymerase inhibitors (PARPis) are approved for cancer therapy according to their synthetic lethal interactions, and clinical trials have been applied in non–small cell lung cancer. However, the therapeutic efficacy of PARPis in lung adenocarcinoma (LUAD) is still unknown. We explored the effect of a mutated retinoblastoma gene (RB1) on PARPi sensitivity in LUAD. Bioinformatic screening was performed to identify PARPi-sensitive biomarkers. Here, we showed that viability of LUAD cell lines with mutated RB1 was significantly decreased by PARPis (niraparib, rucaparib, and olaparib). RB1 deficiency induced genomic instability, prompted cytosolic double-stranded DNA (dsDNA) formation, activated the cGAS/STING pathway, and upregulated downstream chemokines CCL5 and CXCL10, triggering immune cell infiltration. Xenograft experiments indicated that PARPi treatment reduced tumorigenesis in RB1-KO mice. Additionally, single-cell RNA sequencing analysis showed that malignant cells with downregulated expression of RB1 had more communications with other cell types, exhibiting activation of specific signaling such as GAS, IFN response, and antigen-presenting and cytokine activities. Our findings suggest that RB1 mutation mediates the sensitivity to PARPis through a synthetic lethal effect by triggering the cGAS/STING pathway and upregulation of immune infiltration in LUAD, which may be a potential therapeutic strategy.

The incidence of lung cancer (LC) in Idiopathic Pulmonary Fibrosis (IPF) patients is more than twice that in non-IPF. This study aims to investigate IPF-to-LC pathogenesis and to develop a predictor for detecting IPF predisposing patients to LC. We conducted unsupervised clustering to detect high-risk subtypes from IPF to LC. Subsequently, we performed single-cell RNA-seq analysis to characterize high-risk IPF by examining the immune microenvironment. We identified 42 common immune function-related pathogenic genes between IPF and LC. We developed an LC risk classifier for IPF patients, comprising five genes: SPP1, MMP9, MMP12, FABP4, and IL1B. The five-gene classifier can successfully distinguish the high-risk population from IPF patients. High-risk IPF patients exhibited an immunosuppressive microenvironment with higher oncogene expression than low-risk patients. Single-cell analysis revealed that SPP1+ macrophages at the terminal of macrophages' developmental trajectory may promote the progression from IPF to LC. The strong crosstalk between SPP1+ macrophages and inflammation-related cancer-associated fibroblasts promoted the tumorigenic process in IPF. In vitro, assays showed that co-culturing macrophages overexpressing SPP1 with MRC-5 cells induced the transition of fibroblasts into cancer-associated fibroblasts. SPP1 produced by macrophages promoted epithelial-mesenchymal transition in alveolar epithelial cells via stimulating the upregulation of N-cadherin and Vimentin in MLE-12 cells. This study provided a novel method to identify the LC risk population from IPF, revealing the cellular interactions involved in the transition from IPF to LC. Our findings highlighted SPP1 as a critical driver in IPF progression, offering a potential target for therapy in fibrosis.

Abstract Background Diverse drug vulnerabilities owing to the Chromatin regulators (CRs) genetic interaction across various cancers, but the identification of CRs genetic interaction remains challenging. Methods In order to provide a global view of the CRs genetic interaction in cancer cells, we developed a method to identify potential drug response-related CRs genetic interactions for specific cancer types by integrating the screen of CRISPR-Cas9 and pharmacogenomic response datasets. Results Totally, 625 drug response-related CRs synthetic lethality (CSL) interactions and 288 CRs synthetic viability (CSV) interactions were detected. Systematically network analysis presented CRs genetic interactions have biological function relationship. Furthermore, we validated CRs genetic interactions induce multiple omics deregulation in The Cancer Genome Atlas. We revealed the colon adenocarcinoma patients (COAD) with mutations of a CRs set (EP300, MSH6, NSD2 and TRRAP) mediate a better survival with low expression of MAP2 and could benefit from taxnes. While the COAD patients carrying at least one of the CSV interactions in Vorinostat CSV module confer a poor prognosis and may be resistant to Vorinostat treatment. Conclusions The CRs genetic interaction map provides a rich resource to investigate cancer-associated CRs genetic interaction and proposes a powerful strategy of biomarker discovery to guide the rational use of agents in cancer therapy.

Pancreatic cancer (PC) with homologous recombination deficiency (HRD) has been reported to benefit from poly ADP-ribose polymerase (PARP) inhibitors. However, accurate identification of HRD status for PC patients from the transcriptional level is still a great challenge. Here, based on a relative expression ordering (REO)-based algorithm, we developed an HRD signature including 24 gene pairs (24-GPS) using PC transcriptional profiles from The Cancer Genome Atlas (TCGA). HRD samples classified by 24-GPS showed worse overall survival (p = 4.4E-3 for TCGA; p = 1.2E-3 for International Cancer Genome Consortium-Australia cohort; p = 6.4E-2 for GSE17891; p = 7.5E-2 for GSE57495) and higher HRD scores than non-HRD samples (p = 1.4E-4). HRD samples showed highly unstable genomic characteristics and also displayed HRD-related alterations at the epigenomic and proteomic levels. Moreover, HRD cell lines identified by 24-GPS tended to be sensitive to PARP inhibitors (p = 6.6E-2 for olaparib; p = 2.6E-3 for niraparib). Compared with the non-HRD group, the HRD group presented lower immune scores and CD4/CD8 T cell infiltration proportion. Interestingly, PC tumor cells with co-inhibition of PARP-related genes and ATR showed reduced survival ability. In conclusion, 24-GPS can robustly identify PC patients with HRD status at the individualized level.

Poly (ADPribose) polymerase inhibitors (PARPis) are clinically approved drugs designed according to the concept of synthetic lethality (SL) interaction. It is crucial to expand the scale of patients who can benefit from PARPis, and overcome drug resistance associated with it. Genetic interactions (GIs) include SL and synthetic viability (SV) that participate in drug response in cancer cells. Based on the hypothesis that mutated genes with SL or SV interactions with PARP1/2/3 are potential sensitive or resistant PARPis biomarkers, respectively, we developed a novel computational method to identify them. We analyzed fitness variation of cell lines to identify PARP1/2/3-related GIs according to CRISPR/Cas9 and RNA interference functional screens. Potential resistant/sensitive mutated genes were identified using pharmacogenomic datasets. We identified 41 candidate resistant and 130 candidate sensitive PARPi-response related genes, and observed that EGFR with gain-of-function mutation induced PARPi resistance, and predicted a combination therapy with PARP inhibitor (veliparib) and EGFR inhibitor (erlotinib) for lung cancer. We also revealed that a resistant gene set (TNN, PLEC, and TRIP12) in lower grade glioma and a sensitive gene set (BRCA2, TOP3A, and ASCC3) in ovarian cancer, which were associated with prognosis. Thus, cancer genome-derived GIs provide new insights for identifying PARPi biomarkers and a new avenue for precision therapeutics.

Summary: The discovery of homologous recombination deficiency (HRD) biomarkers in prostate cancer is important for patients who will benefit from poly ADP-ribose polymerase inhibitor (PARPi). Here, we developed a transcriptional homologous recombination defectiveness (HRDness) signature, comprising 16 gene pairs (16-GPS), for prostate cancer by a relative expression ordering (REO)-based discovery procedure. Subsequently, two newly subtypes classified by 16-GPS showed a higher significance level in various clinicopathological and HRD features than subtypes obtained by other methods, such as HRDetect. HRDness subtype also displayed more aggressive features and higher genomics scores than non-HRDness in three independent datasets. HRDness prostate cancer cells were more sensitive to PARPi than non-HRDness. Moreover, the HRDness samples showed distinct multi-omics characteristics related to homologous recombination repair function loss. Overall, the newly proposed qualitative signature can robustly determine the HRD status for prostate cancer at the personalized level, and especially be an auxiliary tool for PARPi treatment strategy.