E6-Encoded by Cancer-Causing Human Papillomavirus Interacts with Aurora Kinase A To Promote HPV-Mediated Carcinogenesis.

The expression of human papillomavirus (HPV) oncoproteins perturbed multiple cellular events of the host cells, leading to the formation of cancer phenotypes. Our current and previous studies indicated that Aurora kinase A (AurA), a mitotic regulator that is often aberrantly expressed in human cancers, is preferentially bound to E6-encoded by cancer-causing HPV. AurA is believed to be important for the proliferation and survival of HPV-positive cells. Nonetheless, the interaction between AurA and E6, and the mechanism of how this association is involved in carcinogenesis, have not been elucidated clearly. Hence, we performed a series of biochemical assays to characterize the AurA-E6 association and complex formation. We found the C-terminus of E6, upstream of the PDZ binding motif of E6, is important to forming the AurA-E6 complex in the nucleus. We also showed that the expression level of E6 corresponded positively with AurA expression. Meanwhile, the functional consequences of the AurA-E6 association to AurA kinase function and host cellular events were also delineated. Intriguingly, we revealed that AurA-E6 association regulated the expression of cyclin E and phosphor-Histone H3, which are involved in G1/S and mitotic phases of the cell cycle, respectively. Depletion of AurA also reduced the invasive ability of HPV-positive cells. AurA inhibition may not be sufficient to reduce the oncogenic potential exerted by E6. Altogether, our study unleashed the mechanism of how HPVE6 deploy AurA to promote cancer phenotypes, particularly through dysregulation of cell cycle checkpoints and suggests that the AurA-E6 complex possesses a therapeutic value. IMPORTANCE We unveiled the mechanism of how HPV employs Aurora kinase A (AurA) of host cells to exert its oncogenic capability synergistically. We systematically characterized the mode of interaction between E6-encoded by cancer-causing HPV and AurA. Then, we delineated the consequences of AurA-E6 complex formation on AurA kinase function and changes to cellular events at molecular levels. Using a cell-based approach, we unleashed that disruption of AurA-E6 association can halt cancer phenotype exhibited by HPV-positive cancer cells. Our findings are vital for the designing of state-of-the-art therapies for HPV-associated cancers.

SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.

The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predicting drug synergy, but high computational cost for training models as well as great diversity and limited size in screening data escalate the difficulty of prediction. To address this challenge, we propose a simple machine learning framework, namely Similarity Network-based Synergy prediction (SNSynergy), for predicting synergistic effects towards new cell lines and new drug combinations by two locally weighted models CLSN and DCSN. This framework only requires a small amount of auxiliary data, like genomics information of cell lines and the molecular fingerprints or targets of drugs. Based on the assumption that similar cell lines and similar drug combinations have similar synergistic effects, CLSN and DCSN predict synergy scores through capturing individual synergy contributions of nearest cell line and drug combination neighbors, respectively. High correlations between predicted and measured synergy scores on two leading cancer cell line pharmacogenomic screening datasets (the O'Neil dataset and the NCI-ALMANAC dataset) demonstrate the effectiveness and robustness of SNSynergy. Many of the identified drug combinations are consistent with previous studies, or have been explored in clinical settings against the specific cancer type, showing that SNSynergy has the potential to supply cost-saving and effective high-throughput screening for prioritizing the most applicable cell lines and the most promising drug combinations.

Oesophageal carcinoma: The prevalence of DNA tumour viruses and therapy.

Oesophageal carcinoma ranks the sixth leading cause of cancer death and affected 544,000 - 604,000 people in 2020. Patients often presented with a poor cancer prognosis with a low survival rate of 15-25%. Depending upon the cell type, oesophageal carcinoma is categorised into oesophageal squamous cell carcinoma (ESCC) and oesophageal adenocarcinoma (EAC). ESCC is predominantly reported in developing countries, while EAC is more common in developed countries. Aside from the presence of exogenous co-factors, such as cigarette smoking, alcohol consumption, obesity, gastroesophageal reflux disease (GERD); infection with oncogenic viruses is suspected to be one of the major factors contributing to EC development. Oncogenic viruses, including human papillomavirus (HPV), Epstein Barr virus (EBV), Cytomegalovirus (CMV) and Herpes Simplex Virus (HSV) have been detected in various proportions of EC samples. Nonetheless, their aetiological roles in EC remain debatable. In this review, we garnered previous studies that focus on the association between oncogenic viruses and EC. Among these oncogenic viruses, HPV appears to have a stronger association with EC than the others. In addition, we also discuss the pros and cons of the treatment regimens to treat EC patients, including immunotherapy, chemo- and chemoradiotherapy, and their efficacy.

Current Updates on Cancer-Causing Types of Human Papillomaviruses (HPVs) in East, Southeast, and South Asia.

Human papillomavirus (HPV) infection remains one of the most prominent cancer-causing DNA viruses, contributing to approximately 5% of human cancers. While association between HPV and cervical cancers has been well-established, evidence on the attribution of head and neck cancers (HNC) to HPV have been increasing in recent years. Among the cancer-causing HPV genotypes, HPV16 and 18 remain the major contributors to cancers across the globe. Nonetheless, the distribution of HPV genotypes in ethnically, geographically, and socio-economically diverse East, Southeast, and South Asia may differ from other parts of the world. In this review, we garner and provide updated insight into various aspects of HPV reported in recent years (2015-2021) in these regions. We included: (i) the HPV genotypes detected in normal cancers of the uterine cervix and head and neck, as well as the distribution of the HPV genotypes by geography and age groups; (ii) the laboratory diagnostic methods and treatment regimens used within these regions; and (iii) the oncogenic properties of HPV prototypes and their variants contributing to carcinogenesis. More importantly, we also unveil the similarities and discrepancies between these aspects, the areas lacking study, and the challenges faced in HPV studies.

Temporal-Geographical Dispersion of SARS-CoV-2 Spike Glycoprotein Variant Lineages and Their Functional Prediction Using in Silico Approach.

SARS-CoV-2 is a positive-sense single-stranded RNA virus with emerging mutations, especially on the Spike glycoprotein (S protein). To delineate the genomic diversity in association with geographic dispersion of SARS-CoV-2 variant lineages, we collected 939,591 complete S protein sequences deposited in the Global Initiative on Sharing All Influenza Data (GISAID) from December 2019 to April 2021. An exponential emergence of S protein variants was observed since October 2020 when the four major variants of concern (VOCs), namely, alpha (α) (B.1.1.7), beta (ß) (B.1.351), gamma (γ) (P.1), and delta (δ) (B.1.617), started to circulate in various communities. We found that residues 452, 477, 484, and 501, the 4 key amino acids located in the hACE2 binding domain of S protein, were under positive selection. Through in silico protein structure prediction and immunoinformatics tools, we discovered D614G is the key determinant to S protein conformational change, while variations of N439K, T478I, E484K, and N501Y in S1-RBD also had an impact on S protein binding affinity to hACE2 and antigenicity. Finally, we predicted that the yet-to-be-identified hypothetical N439S, T478S, and N501K mutations could confer an even greater binding affinity to hACE2 and evade host immune surveillance more efficiently than the respective native variants. This study documented the evolution of SARS-CoV-2 S protein over the first 16 months of the pandemic and identified several key amino acid changes that are predicted to confer a substantial impact on transmission and immunological recognition. These findings convey crucial information to sequence-based surveillance programs and the design of next-generation vaccines. IMPORTANCE Our study showed the global distribution of SARS-CoV-2 S protein variants from January 2020 to the end of April 2021. We highlighted the key amino acids of S protein subjected to positive selection. Using computer-aided approaches, we predicted the impact of the amino acid variations in S protein on viral infectivity and antigenicity. We also predicted the potential amino acid mutations that could arise in favor of SARS-CoV-2 virulence. These findings are vital for vaccine designing and anti-SARS-CoV-2 drug discovery in an effort to combat COVID-19.

Genetic Characteristics of Three Unique Recombinant Forms of HIV-1 in Yunnan, China.

To explore the molecular epidemiological status of human immunodeficiency virus type 1 (HIV-1) in Yunnan, China, three HIV-1 near full-length genomes were amplified and sequenced from plasma samples that were collected from Burmese patients newly diagnosed with HIV-1 in Dehong Prefecture in Yunnan Province in 2017. Phylogenetic and bootscanning analyses revealed that all the sequences might be HIV-1 second-generation recombinant forms of circulating recombinant forms (CRF07_BC and CRF83_cpx) and unique recombinant forms. One of the sequences contained six CRF01_AE fragments, five subtype C fragments, and two subtype B fragments, which were separated by 12 breakpoints. These results revealed that the second-generation recombination of HIV-1 within different strains is still ongoing in Dehong, China. Systematic surveys and immediate interventions are urgently needed to prevent the formation of increasingly complex HIV-1 recombinant forms.