TP53 is a critical tumor-suppressor gene that is mutated in more than half of all human cancers. Mutations in TP53 not only impair its antitumor activity, but also confer mutant p53 protein oncogenic properties. The p53-targeted therapy approach began with the identification of compounds capable of restoring/reactivating wild-type p53 functions or eliminating mutant p53. Treatments that directly target mutant p53 are extremely structure and drug-species-dependent. Due to the mutation of wild-type p53, multiple survival pathways that are normally maintained by wild-type p53 are disrupted, necessitating the activation of compensatory genes or pathways to promote cancer cell survival. Additionally, because the oncogenic functions of mutant p53 contribute to cancer proliferation and metastasis, targeting the signaling pathways altered by p53 mutation appears to be an attractive strategy. Synthetic lethality implies that while disruption of either gene alone is permissible among two genes with synthetic lethal interactions, complete disruption of both genes results in cell death. Thus, rather than directly targeting p53, exploiting mutant p53 synthetic lethal genes may provide additional therapeutic benefits. Additionally, research progress on the functions of noncoding RNAs has made it clear that disrupting noncoding RNA networks has a favorable antitumor effect, supporting the hypothesis that targeting noncoding RNAs may have potential synthetic lethal effects in cancers with p53 mutations. The purpose of this review is to discuss treatments for cancers with mutant p53 that focus on directly targeting mutant p53, restoring wild-type functions, and exploiting synthetic lethal interactions with mutant p53. Additionally, the possibility of noncoding RNAs acting as synthetic lethal targets for mutant p53 will be discussed.

Synthetic lethality is a lethal phenomenon in which the occurrence of a single genetic event is tolerable for cell survival, whereas the co-occurrence of multiple genetic events results in cell death. The main obstacle for synthetic lethality lies in the tumor biology heterogeneity and complexity, the inadequate understanding of synthetic lethal interactions, drug resistance, and the challenges regarding screening and clinical translation. Recently, DNA damage response inhibitors are being tested in various trials with promising results. This review will describe the current challenges, development, and opportunities for synthetic lethality in cancer therapy. The characterization of potential synthetic lethal interactions and novel technologies to develop a more effective targeted drug for cancer patients will be explored. Furthermore, this review will discuss the clinical development and drug resistance mechanisms of synthetic lethality in cancer therapy. The ultimate goal of this review is to guide clinicians at selecting patients that will receive the maximum benefits of DNA damage response inhibitors for cancer therapy.

Objective: Most cases of coronavirus disease 2019 (COVID-19) are identified as moderate, which is defined as having a fever or dry cough and lung imaging with ground-glass opacities. The risk factors and predictors of prognosis in such cohorts remain uncertain. Methods: All adults with COVID-19 of moderate severity diagnosed using quantitative RT-PCR and hospitalized at the Central Hospital of Wuhan, China, from 1 January to 20 March 2020 were enrolled in this retrospective study. The main outcomes were progression from moderate to severe or critical condition or death. Results: Among the 456 enrolled patients with moderate COVID-19, 251/456 (55.0%) had poor prognosis. Multivariate logistic regression analysis identified higher neutrophil count: lymphocyte count ratio (NLR) on admission (OR 1.032, 95% CI 1.042e1.230, p 0.004) and higher C-reactive protein (CRP) on admission (OR 3.017, 95% CI 1.941e4.690, p < 0.001) were associated with increased OR of poor prognosis. The area under the receiver operating characteristic curve (AUC) for NLR and CRP in predicting progression to critical condition was 0.77 (95% CI 0.694e0.846, p < 0.001) and 0.84 (95% CI 0.780e0.905, p < 0.001), with a cutoff value of 2.79 and 25.95 mg/L, respectively. The AUC of NLR and CRP in predicting death was 0.81 (95% CI 0.732e0.878, p < 0.001) and 0.89 (95% CI 0.825e0.946, p < 0.001), with a cutoff value of 3.19 and 33.4 mg/L, respectively. Conclusions: Higher levels of NLR and CRP at admission were associated with poor prognosis of individuals with moderate COVID-19. NLR and CRP were good predictors of progression to critical condition and death.