Background COVID-19 has spread globally. Epidemiological susceptibility to COVID-19 has been reported in patients with cancer. We aimed to systematically characterise clinical features and determine risk factors of COVID-19 disease severity for patients with cancer and COVID-19. MethodsIn this multicentre, retrospective, cohort study, we included all adult patients (aged ≥18 years) with any type of malignant solid tumours and haematological malignancy who were admitted to nine hospitals in Wuhan, China, with laboratory-confirmed COVID-19 between Jan 13 and March 18, 2020. Enrolled patients were statistically matched (2:1) with patients admitted with COVID-19 who did not have cancer with propensity score on the basis of age, sex, and comorbidities. Demographic characteristics, laboratory examinations, illness severity, and clinical interventions were compared between patients with COVID-19 with or without cancer as well as between patients with cancer with non-severe or severe COVID-19. COVID-19 disease severity was defined on admission on the basis of the WHO guidelines. Univariable and multivariable logistic regression, adjusted for age, sex, comorbidities, cancer type, tumour stage, and antitumour treatments, were used to explore risk factors associated with COVID-19 disease severity. This study was registered in the Chinese Clinical Trial Register, ChiCTR2000030807. Findings Between Jan 13 and March 18, 2020, 13 077 patients with COVID-19 were admitted to the nine hospitals in Wuhan and 232 patients with cancer and 519 statistically matched patients without cancer were enrolled. Median follow-up was 29 days (IQR 22-38) in patients with cancer and 27 days (20-35) in patients without cancer. Patients with cancer were more likely to have severe COVID-19 than patients without cancer (148 [64%] of 232 vs 166 [32%] of 519; odds ratio [OR] 3•61 [95% CI 2•59-5•04]; p<0•0001). Risk factors previously reported in patients without cancer, such as older age; elevated interleukin 6, procalcitonin, and D-dimer; and reduced lymphocytes were validated in patients with cancer. We also identified advanced tumour stage (OR 2•60, 95% CI 1•05-6•43; p=0•039), elevated tumour necrosis factor α (1•22, 1•01-1•47; p=0•037), elevated N-terminal pro-B-type natriuretic peptide (1•65, 1•03-2•78; p=0•032), reduced CD4+ T cells (0•84, 0•71-0•98; p=0•031), and reduced albumin-globulin ratio (0•12, 0•02-0•77; p=0•024) as risk factors of COVID-19 severity in patients with cancer. Interpretation Patients with cancer and COVID-19 were more likely to deteriorate into severe illness than those without cancer. The risk factors identified here could be helpful for early clinical surveillance of disease progression in patients with cancer who present with COVID-19.

Numerous studies have shown that transcription factors are important in regulating plant responses to environmental stress. However, specific functions for most of the genes encoding transcription factors are unclear. In this study, we used mRNA profiles generated from microarray experiments to deduce the functions of genes encoding known and putative Arabidopsis transcription factors. The mRNA levels of 402 distinct transcription factor genes were examined at different developmental stages and under various stress conditions. Transcription factors potentially controlling downstream gene expression in stress signal transduction pathways were identified by observed activation and repression of the genes after certain stress treatments. The mRNA levels of a number of previously characterized transcription factor genes were changed significantly in connection with other regulatory pathways, suggesting their multifunctional nature. The expression of 74 transcription factor genes responsive to bacterial pathogen infection was reduced or abolished in mutants that have defects in salicylic acid, jasmonic acid, or ethylene signaling. This observation indicates that the regulation of these genes is mediated at least partly by these plant hormones and suggests that the transcription factor genes are involved in the regulation of additional downstream responses mediated by these hormones. Among the 43 transcription factor genes that are induced during senescence, 28 of them also are induced by stress treatment, suggesting extensive overlap responses to these stresses. Statistical analysis of the promoter regions of the genes responsive to cold stress indicated unambiguous enrichment of known conserved transcription factor binding sites for the responses. A highly conserved novel promoter motif was identified in genes responding to a broad set of pathogen infection treatments. This observation strongly suggests that the corresponding transcription factors play general and crucial roles in the coordinated regulation of these specific regulons. Although further validation is needed, these correlative results provide a vast amount of information that can guide hypothesis-driven research to elucidate the molecular mechanisms involved in transcriptional regulation and signaling networks in plants.

We performed large-scale mRNA expression profiling using an Affymetrix GeneChip to study Arabidopsis responses to the bacterial pathogen Pseudomonas syringae . The interactions were compatible (virulent bacteria) or incompatible (avirulent bacteria), including a nonhost interaction and interactions mediated by two different avirulence gene-resistance ( R ) gene combinations. Approximately 2000 of the ‫ف‬ 8000 genes monitored showed reproducible significant expression level changes in at least one of the interactions. Analysis of biological variation suggested that the system behavior of the plant response in an incompatible interaction was robust but that of a compatible interaction was not. A large part of the difference between incompatible and compatible interactions can be explained quantitatively. Despite high similarity between responses mediated by the R genes RPS2 and RPM1 in wild-type plants, RPS2 -mediated responses were strongly suppressed by the ndr1 mutation and the NahG transgene, whereas RPM1 -mediated responses were not. This finding is consistent with the resistance phenotypes of these plants. We propose a simple quantitative model with a saturating response curve that approximates the overall behavior of this plant-pathogen system.

SummaryThe signal transduction network controlling plant responses to pathogens includes pathways requiring the signal molecules salicylic acid (SA), jasmonic acid (JA), and ethylene (ET). The network topology was explored using global expression phenotyping of wild-type and signaling-defective mutant plants, including eds3, eds4, eds5, eds8, pad1, pad2, pad4, NahG, npr1, sid2, ein2, and coi1. Hierarchical clustering was used to de®ne groups of mutations with similar effects on gene expression and groups of similarly regulated genes. Mutations affecting SA signaling formed two groups: one comprised of eds4, eds5, sid2, and npr1-3 affecting only SA signaling; and the other comprised of pad2, eds3, npr1-1, pad4, and NahG affecting SA signaling as well as another unknown process. Major differences between the expression patterns in NahG and the SA biosynthetic mutant sid2 suggest that NahG has pleiotropic effects beyond elimination of SA. A third group of mutants comprised of eds8, pad1, ein2, and coi1 affected ethylene and jasmonate signaling. Expression patterns of some genes revealed mutual inhibition between SA-and JA-dependent signaling, while other genes required JA and ET signaling as well as the unknown signaling process for full expression. Global expression phenotype similarities among mutants suggested, and experiments con®rmed, that EDS3 affects SA signaling while EDS8 and PAD1 affect JA signaling. This work allowed modeling of network topology, de®nition of co-regulated genes, and placement of previously uncharacterized regulatory genes in the network.