The outbreak of coronavirus disease 2019 (COVID‐19) has rapidly spread globally since being identified as a public health emergency of major international concern and has now been declared a pandemic by the World Health Organization (WHO). In December 2019, an outbreak of atypical pneumonia, known as COVID‐19, was identified in Wuhan, China. The newly identified zoonotic coronavirus, severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2), is characterized by rapid human‐to‐human transmission. Many cancer patients frequently visit the hospital for treatment and disease surveillance. They may be immunocompromised due to the underlying malignancy or anticancer therapy and are at higher risk of developing infections. Several factors increase the risk of infection, and cancer patients commonly have multiple risk factors. Cancer patients appear to have an estimated twofold increased risk of contracting SARS‐CoV‐2 than the general population. With the WHO declaring the novel coronavirus outbreak a pandemic, there is an urgent need to address the impact of such a pandemic on cancer patients. This include changes to resource allocation, clinical care, and the consent process during a pandemic. Currently and due to limited data, there are no international guidelines to address the management of cancer patients in any infectious pandemic. In this review, the potential challenges associated with managing cancer patients during the COVID‐19 infection pandemic will be addressed, with suggestions of some practical approaches. Implications for Practice The main management strategies for treating cancer patients during the COVID‐19 epidemic include clear communication and education about hand hygiene, infection control measures, high‐risk exposure, and the signs and symptoms of COVID‐19. Consideration of risk and benefit for active intervention in the cancer population must be individualized. Postponing elective surgery or adjuvant chemotherapy for cancer patients with low risk of progression should be considered on a case‐by‐case basis. Minimizing outpatient visits can help to mitigate exposure and possible further transmission. Telemedicine may be used to support patients to minimize number of visits and risk of exposure. More research is needed to better understand SARS‐CoV‐2 virology and epidemiology.

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Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In current study, the microarray data GSE66272 containing ccRCC and adjacent normal tissues was analyzed to identify 4042 differentially expressed genes, on which weighted gene co-expression network analysis was performed. Then 12 co-expressed gene modules were identified. The highest association was found between blue module and pathological stage (r = -0.77) by Pearson's correlation analysis. Functional enrichment analysis revealed that biological processes of blue module focused on inflammatory response, immune response, chemotaxis (all p < 1e-10). In the significant module, a total of 38 network hub genes were identified, FCER1G exhibited the highest correlation (r = 0.95) with ccRCC progression. In addition, FCER1G was hub node in the protein-protein interaction network of the genes in blue module as well. Thus, FCER1G was subsequently selected for validation. In the test set GSE53757 and RNA-sequencing data, FCER1G expression was also positively correlated with four stages of ccRCC progression (p < 0.001). Receiver operating characteristic (ROC) curve indicated that FCER1G could distinguish localized (pathological stage I, II) from non-localized (pathological stage III, IV) ccRCC (AUC=0.74, p < 0.001). Besides, FCER1G could be a prognostic gene in clinical practice as well, revealed by survival analysis based on RNA-sequencing data (p < 0.05). In conclusion, using weighted gene co-expression analysis, FCER1G was identified and validated in association with ccRCC progression and prognosis, which might improve the prognosis by influencing immune-related pathways.

These authors contributed equally to this work. SUMMARYLow temperature severely influences potato production as the cultivated potato (Solanum tuberosum) is frost sensitive, however the mechanism underlying the freezing tolerance of the potato is largely unknown. In the present research, we studied the transcriptome and metabolome of the freezing-tolerant wild species Solanum acaule (Aca) and freezing-sensitive cultivated S. tuberosum (Tub) to identify the main pathways and important factors related to freezing tolerance. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation indicated that polyamine and amino acid metabolic pathways were specifically upregulated in Aca under cold treatment. The transcriptome changes detected in Aca were accompanied by the specific accumulation of putrescine, saccharides, amino acids and other metabolites. The combination of transcriptome and metabolome analyses revealed that putrescine exhibited an accumulative pattern in accordance with the expression of the arginine decarboxylase gene ADC1. The primary role of putrescine was further confirmed by analyzing all three polyamines (putrescine, spermidine, and spermine) and the genes encoding the corresponding enzymes in two sets of potato genotypes with distinct freezing tolerance, implying that only putrescine and ADC1 were uniquely enhanced by cold in the freezingtolerant genotypes. The function of putrescine was further analyzed by its exogenous application and the overexpression of SaADC1 in S. tuberosum cv. E3, indicating its important role(s) in cold-acclimated freezing tolerance, which was accompanied with the activation of C-repeat binding factor genes (CBFs). The present research has identified that the ADC1-associated putrescine pathway plays an important role in coldacclimated freezing tolerance of potato, probably by enhancing the expression of CBF genes.