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Graphical abstract, Highlights • Candidate genomic biomarkers were revealed for PARPis from genetic interactions. • Gain-of-function mutation of EGFR induced resistance to PARP inhibitors. • Lung cancer may benefit from combination of PARP inhibitor and EGFR inhibitor. • Gene set of biomarkers for PARPis contributes to the prognosis of cancer patients., 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.

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.

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.

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., Graphical abstract, Gu et al. developed a qualitative transcriptional signature (24 gene pairs, 24-GPS) that could efficiently identify homologous recombination deficiency for pancreatic cancer at the individual level. 24-GPS has potential implications for selecting pancreatic cancer patients who may benefit from PARP inhibitors in the clinic.