Poly (adenosine diphosphate-ribose) polymerase inhibitors (PARPis) belong to a class of targeted drugs developed for the treatment of homologous recombination repair (HRR)-defective tumors. Preclinical and limited clinical data suggest that PARP inhibition is effective against prostate cancer (PC) in patients with HRR-deficient tumors and that PARPis can improve the mortality rate of PC in patients with BRCA1/2 mutations through a synthetic lethality. Olaparib has been approved by the FDA for advanced ovarian and breast cancer with BRCA mutations, and as a maintenance therapy for ovarian cancer after platinum chemotherapy. PARPis are also a new and emerging clinical treatment for metastatic castration-resistant prostate cancer (mCRPC). Although PARPis have shown great efficacy, their widespread use is restricted by various factors, including drug resistance and the limited population who benefit from treatment. It is necessary to study the combination of PARPis and other therapeutic agents such as anti-hormone drugs, USP7 inhibitors, BET inhibitors, and immunotherapy. This article reviews the mechanism of PARP inhibition in the treatment of PC, the progress of clinical research, the mechanisms of drug resistance, and the strategies of combination treatments.

METTL3 and N6-methyladenosine (m6A) are involved in many types of biological and pathological processes, including DNA repair. However, the function and mechanism of METTL3 in DNA repair and chemotherapeutic response remain largely unknown. In present study, we identified that METTL3 participates in the regulation of homologous recombination repair (HR), which further influences chemotherapeutic response in both MCF-7 and MDA-MB-231 breast cancer (BC) cells. Knockdown of METTL3 sensitized these BC cells to Adriamycin (ADR; also named as doxorubicin) treatment and increased accumulation of DNA damage. Mechanically, we demonstrated that inhibition of METTL3 impaired HR efficiency and increased ADR-induced DNA damage by regulating m6A modification of EGF/RAD51 axis. METTL3 promoted EGF expression through m6A modification, which further upregulated RAD51 expression, resulting in enhanced HR activity. We further demonstrated that the m6A 'reader', YTHDC1, bound to the m6A modified EGF transcript and promoted EGF synthesis, which enhanced HR and cell survival during ADR treatment in breast cancer cells. Our findings reveal a pivotal mechanism of METTL3-mediated HR and chemotherapeutic drug response, which may contribute to cancer therapy.

Chimeric antigen receptor T-cell (CAR-T) therapy has shown tremendous success in eradicating hematologic malignancies. However, this success has not yet been extrapolated to solid tumors due to the limited infiltration and persistence of CAR-T cells in the tumor microenvironment (TME). In this study, we screened a novel anti-CD70 scFv and generated CD70 CAR-T cells that showed effective antitumor functions against CD70+ renal carcinoma cells (RCCs) both in vitro and in vivo. We further evaluated the effect and explored the molecular mechanism of a PARP inhibitor (PARPi) in CAR-T cell immunotherapy by administering the PARPi to mouse xenografts model derived from human RCC cells. Treatment with the PARPi promoted CAR-T cell infiltration by stimulating a chemokine milieu that promoted CAR-T cell recruitment and the modulation of immunosuppression in the TME. Moreover, our data demonstrate that PARPi modulates the TME by activating the cGAS-STING pathway, thereby altering the balance of immunostimulatory signaling and enabling low-dose CAR-T cell treatment to induce effective tumor regression. These data demonstrate the application of CD70 CAR-T cell therapeutic strategies for RCC and the cross-talk between targeting DNA damage responses and antitumor CAR-T cell therapy. These findings provide insight into the mechanisms of PARPis in CAR-T cell therapy for RCC and suggest a promising adjuvant therapeutic strategy for CAR-T cell therapy in solid tumors.

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Dilated cardiomyopathy (DCM) is a condition of impaired ventricular remodeling and systolic diastole that is often complicated by arrhythmias and heart failure with a poor prognosis. This study attempted to identify autophagy-related genes (ARGs) with diagnostic biomarkers of DCM using machine learning and bioinformatics approaches. Differential analysis of whole gene microarray data of DCM from the Gene Expression Omnibus (GEO) database was performed using the NetworkAnalyst 3.0 platform. Differentially expressed genes (DEGs) matching (|log2FoldChange ≥ 0.8, p value < 0.05|) were obtained in the GSE4172 dataset by merging ARGs from the autophagy gene libraries, HADb and HAMdb, to obtain autophagy-related differentially expressed genes (AR-DEGs) in DCM. The correlation analysis of AR-DEGs and their visualization were performed using R language. Gene Ontology (GO) enrichment analysis and combined multi-database pathway analysis were served by the Enrichr online enrichment analysis platform. We used machine learning to screen the diagnostic biomarkers of DCM. The transcription factors gene regulatory network was constructed by the JASPAR database of the NetworkAnalyst 3.0 platform. We also used the drug Signatures database (DSigDB) drug database of the Enrichr platform to screen the gene target drugs for DCM. Finally, we used the DisGeNET database to analyze the comorbidities associated with DCM. In the present study, we identified 23 AR-DEGs of DCM. Eight (PLEKHF1, HSPG2, HSF1, TRIM65, DICER1, VDAC1, BAD, TFEB) molecular markers of DCM were obtained by two machine learning algorithms. Transcription factors gene regulatory network was established. Finally, 10 gene-targeted drugs and complications for DCM were identified.