The development of head and neck squamous cell carcinoma (HNSCC) is a multi-step process, and its survival depends on a complex tumor ecosystem, which not only promotes tumor growth but also helps to protect tumor cells from immune surveillance. With the advances of existing technologies and emerging models for ecosystem research, the evidence for cell-cell interplay is increasing. Herein, we discuss the recent advances in understanding the interaction between tumor cells, the major components of the HNSCC tumor ecosystem, and summarize the mechanisms of how biological and abiotic factors affect the tumor ecosystem. In addition, we review the emerging ecological treatment strategy for HNSCC based on existing studies.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest solid tumors. The rapid progression of PDAC results in an advanced stage of patients when diagnosed. However, the dynamic molecular mechanism underlying PDAC progression remains far from clear. Methods: The microarray GSE62165 containing PDAC staging samples was obtained from Gene Expression Omnibus and the differentially expressed genes (DEGs) between normal tissue and PDAC of different stages were profiled using R software, respectively. The software program Short Time-series Expression Miner was applied to cluster, compare, and visualize gene expression differences between PDAC stages. Then, function annotation and pathway enrichment of DEGs were conducted by Database for Annotation Visualization and Integrated Discovery. Further, the Cytoscape plugin DyNetViewer was applied to construct the dynamic protein–protein interaction networks and to analyze different topological variation of nodes and clusters over time. The phosphosite markers of stage-specific protein kinases were predicted by PhosphoSitePlus database. Moreover, survival analysis of candidate genes and pathways was performed by Kaplan–Meier plotter. Finally, candidate genes were validated by immunohistochemistry in PDAC tissues. Results: Compared with normal tissues, the total DEGs number for each PDAC stage were 994 (stage I), 967 (stage IIa), 965 (stage IIb), 1027 (stage III), 925 (stage IV), respectively. The stage-course gene expression analysis showed that 30 distinct expressional models were clustered. Kyoto Encyclopedia of Genes and Genomes analysis indicated that the up-regulated DEGs were commonly enriched in five fundamental pathways throughout five stages, including pathways in cancer, small cell lung cancer, ECM-receptor interaction, amoebiasis, focal adhesion. Except for amoebiasis, these pathways were associated with poor PDAC overall survival. Meanwhile, LAMA3, LAMB3, LAMC2, COL4A1 and FN1 were commonly shared by these five pathways and were unfavorable factors for prognosis. Furthermore, by constructing the stage-course dynamic protein interaction network, 45 functional molecular modules and 19 nodes were identified as featured regulators for all PDAC stages, among which the collagen family and integrins were considered as two main regulators for facilitating aggressive progression. Additionally, the clinical relevance analysis suggested that the stage IV featured nodes MLF1IP and ITGB4 were significantly correlated with shorter overall survival. Moreover, 15 stage-specific protein kinases were identified from the dynamic network and CHEK1 was particularly activated at stage IV. Experimental validation showed that MLF1IP, LAMA3 and LAMB3 were progressively increased from tumor initiation to progression. Conclusions: Our study provided a view for a better understanding of the dynamic landscape of molecular interaction networks during PDAC progression and offered potential targets for therapeutic intervention.

Anaplastic thyroid carcinoma (ATC) is one of the most aggressive and rapidly lethal tumors. However, limited advances have been made to prolong the survival and to reduce the mortality over the last decades. Therefore, identifying the master regulators underlying ATC progression is desperately needed. In our present study, three datasets including GSE33630, GSE29265, and GSE65144 were retrieved from Gene Expression Omnibus with a total of 32 ATC samples and 78 normal thyroid tissues. A total of 1804 consistently changed differentially expressed genes (DEGs) were identified from three datasets. KEGG pathways enrichment suggested that upregulated DEGs were mainly enriched in ECM-receptor interaction, cell cycle, PI3K-Akt signaling pathway, focal adhesion, and p53 signaling pathway. Furthermore, key gene modules in PPI network were identified by Cytoscape plugin MCODE and they were mainly associated with DNA replication, cell cycle process, collagen fibril organization, and regulation of leukocyte migration. Additionally, TOP2A, CDK1, CCNB1, VEGFA, BIRC5, MAPK1, CCNA2, MAD2L1, CDC20, and BUB1 were identified as hub genes of the PPI network. Interestingly, module analysis showed that 8 out of 10 hub genes participated in Module 1 network and more than 70% genes of Module 2 consisted of collagen family members. Notably, transcription factors (TFs) regulatory network analysis indicated that E2F7, FOXM1, and NFYB were master regulators of Module 1, while CREB3L1 was the master regulator of Module 2. Experimental validation showed that CREB3L1, E2F7, and FOXM1 were significantly upregulated in ATC tissue and cell line when compared with normal thyroid group. In conclusion, the TFs regulatory network provided a more detail molecular mechanism underlying ATC occurrence and progression. TFs including E2F7, FOXM1, CREB3L1, and NFYB were likely to be master regulators of ATC progression, suggesting their potential role as molecular therapeutic targets in ATC treatment.

Background: Anaplastic thyroid carcinoma (ATC) was a rare and extremely malignant endocrine cancer with the distinct hallmark of high proportion of cancer stem cell-like characteristics. Therapies aiming to cancer stem-like cells (CSCs) were emerging as a new direction in cancer treatment, but targeting ATC CSCs remained challenging, mainly due to incomplete insights of the regulatory mechanism of CSCs. Here, we unveiled a novel role of ISG15 in the modulation of ATC CSCs. Methods: The expression of ubiquitin-like proteins were detected by bioinformatics and immunohistochemistry. The correlation between ISG15 expression and tumor stem cells and malignant progression of ATC was analyzed by single-cell RNA sequence from the Gene Expression Omnibus. Flow cytometry combined with immunofluorescence were used to verify the enrichment of ISG15 and ISGyaltion in cancer stem cells. The effect and mechanism of ISG15 and KPNA2 on cancer stem cell-like characteristics of ATC cells were determined by molecular biology experiments. Mass spectrometry combined with immunoprecipitation to screen the substrates of ISG15 and validate its ISGylation modification. Nude mice and zebrafish xenograft models were utilized to demonstrate that ISG15 regulates stem cell characteristics and promotes malignant progression of ATC. Results: We found that among several ubiquitin proteins, only ISG15 was aberrantly expressed in ATC and enriched in CSCs. Single-cell sequencing analysis revealed that abnormal expression of ISG15 were intensely associated with stemness and malignant cells in ATC. Inhibition of ISG15 expression dramatically attenuated clone and sphere formation of ATC cells, and facilitated its sensitivity to doxorubicin. Notably, overexpression of ISGylation, but not the non-ISGylation mutant, effectively reinforced cancer stem cell-like characteristics. Mechanistically, ISG15 mediated the ISGylation of KPNA2 and impeded its ubiquitination to promote stability, further maintaining cancer stem cell-like characteristics. Finally, depletion of ISG15 inhibited ATC growth and metastasis in xenografted mouse and zebrafish models. Conclusion: Our studies not only provided new insights into potential intervention strategies targeting ATC CSCs, but also uncovered the novel biological functions and mechanisms of ISG15 and ISGylation for maintaining ATC cancer stem cell-like characteristics. Graphical