Up-regulated SPP1 increases the risk from IPF to lung cancer via activating the pro-tumor macrophages.

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.

Mutant RB1 enhances therapeutic efficacy of PARPis in lung adenocarcinoma by triggering the cGAS/STING pathway.

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.

Synthetic viability induces resistance to immune checkpoint inhibitors in cancer cells.

BACKGROUND: Immune checkpoint inhibitors (ICI) have revolutionized the treatment for multiple cancers. However, most of patients encounter resistance. Synthetic viability (SV) between genes could induce resistance. In this study, we established SV signature to predict the efficacy of ICI treatment for melanoma. METHODS: We collected features and predicted SV gene pairs by random forest classifier. This work prioritized SV gene pairs based on CRISPR/Cas9 screens. SV gene pairs signature were constructed to predict the response to ICI for melanoma patients. RESULTS: This study predicted robust SV gene pairs based on 14 features. Filtered by CRISPR/Cas9 screens, we identified 1,861 SV gene pairs, which were also related with prognosis across multiple cancer types. Next, we constructed the six SV pairs signature to predict resistance to ICI for melanoma patients. This study applied the six SV pairs signature to divide melanoma patients into high-risk and low-risk. High-risk melanoma patients were associated with worse response after ICI treatment. Immune landscape analysis revealed that high-risk melanoma patients had lower natural killer cells and CD8+ T cells infiltration. CONCLUSIONS: In summary, the 14 features classifier accurately predicted robust SV gene pairs for cancer. The six SV pairs signature could predict resistance to ICI.

A genetic map of the chromatin regulators to drug response in cancer cells.

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.

Upregulation of CXCL1 and LY9 contributes to BRCAness in ovarian cancer and mediates response to PARPi and immune checkpoint blockade.

BACKGROUND: Mutations in BRCA1 or BRCA2 (BRCA1/2) cause homologous recombination deficiency (HRD). Ovarian cancer (OvCa) patients harbouring HRD beyond BRCA1/2 mutation result in a state referred to as "BRCAness". OvCa with BRCAness could benefit from PARP inhibitors. This study aims to identify a signature to detect the BRCAness population at the transcriptome level. METHODS: We used a rank-based algorithm to develop a qualitative BRCAness signature for OvCa. Upregulation of CXCL1 with downregulation of SV2A and upregulation of LY9 with downregulation of CHRNB3 were constructed as the BRCAness signature (2 gene pairs, 2-GPS) for OvCa. RESULTS: OvCa samples that were classified as BRCAness by 2-GPS showed improved overall survival, progression-free survival and exhibited increased multi-omics alterations in homologous recombination genes and enhanced sensitivity to immune checkpoint blockade. BRCAness cells were sensitive to PARP inhibitors. By biological experiments, we validated SKOV3 cells and patients with HRD exhibited higher expression of CXCL1 than SV2A and higher expression of LY9 than CHRNB3 at mRNA level. Both SKOV3 and A2780 with HRD were sensitive to mitomycin C, cisplatin and olaparib. CONCLUSIONS: In conclusion, 2-GPS could robustly predict BRCAness OvCa at the individual level and extend the population who may benefit from PARP inhibitors.

Pan-cancer multi-omics analyses reveal crosstalk between the Hippo and immune signaling pathways in the tumor microenvironment.

The Hippo signaling pathway is critical for carcinogenesis. However, the roles of the Hippo signaling pathway in the tumor immune microenvironment have been rarely investigated. This study systematically analyzed the relationship between the Hippo signaling pathway and immune cell infiltration across 32 cancer types. Both bioinformatics analyses and biological experiments revealed that the downstream effector of Hippo signaling YAP1 might inhibit CD8+ T cell infiltration by upregulating the expression of the transcription factor CREB1 in uterine corpus endometrial carcinoma. In addition, esophageal carcinoma (ESCA) patients were classified into three subtypes based on the Hippo-immune gene panel. The subtypes of ESCA had distinct characteristics in immune cell infiltration, immune pathways, and prognosis. Thus, this study also reveals a new classification of the immune subtypes with prognostic characteristics in ESCA.

A transcriptional signature detects homologous recombination deficiency in pancreatic cancer at the individual level.

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.

Discovering a qualitative transcriptional signature of homologous recombination defectiveness for prostate cancer.

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.

Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome.

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.