Tumors are not only aggregates of malignant cells but also well-organized complex ecosystems. The immunological components within tumors, termed the tumor immune microenvironment (TIME), have long been shown to be strongly related to tumor development, recurrence and metastasis. However, conventional studies that underestimate the potential value of the spatial architecture of the TIME are unable to completely elucidate its complexity. As innovative high-flux and high-dimensional technologies emerge, researchers can more feasibly and accurately detect and depict the spatial architecture of the TIME. These findings have improved our understanding of the complexity and role of the TIME in tumor biology. In this review, we first epitomized some representative emerging technologies in the study of the spatial architecture of the TIME and categorized the description methods used to characterize these structures. Then, we determined the functions of the spatial architecture of the TIME in tumor biology and the effects of the gradient of extracellular nonspecific chemicals (ENSCs) on the TIME. We also discussed the potential clinical value of our understanding of the spatial architectures of the TIME, as well as current limitations and future prospects in this novel field. This review will bring spatial architectures of the TIME, an emerging dimension of tumor ecosystem research, to the attention of more researchers and promote its application in tumor research and clinical practice.
The pandemic of the coronavirus disease 2019 (COVID-19) has posed huge threats to healthcare systems and the global economy. However, the host response towards COVID-19 on the molecular and cellular levels still lacks full understanding and effective therapies are in urgent need. Here, we integrate three datasets, GSE152641, GSE161777, and GSE157103. Compared to healthy people, 314 differentially expressed genes were identified, which were mostly involved in neutrophil degranulation and cell division. The protein-protein network was established and two significant subsets were filtered by MCODE: ssGSEA and CIBERSORT, which comprehensively revealed the alternation of immune cell abundance. Weighted gene coexpression network analysis (WGCNA) as well as GO and KEGG analyses unveiled the role of neutrophils and T cells during the progress of the disease. Based on the hospital-free days after 45 days of follow-up and statistical methods such as nonnegative matrix factorization (NMF), submap, and linear correlation analysis, 31 genes were regarded as the signature of the peripheral blood of COVID-19. Various immune cells were identified to be related to the prognosis of the patients. Drugs were predicted for the genes in the signature by DGIdb. Overall, our study comprehensively revealed the relationship between the inflammatory response and the disease course, which provided strategies for the treatment of COVID-19.
Background: The emergence of anti-HER2 antibody–drug conjugates (ADCs) gave rise to the concept of HER2-low breast cancer (BC). HER2-low BC, which refers to a subgroup of HER2-negative BC with relatively higher HER2 expression (defined as 1+ or 2+ by immunohistochemistry (IHC) staining, without ERBB2 amplification), represents a rather large part of all BCs. However, the molecular nature and internal heterogeneity of HER2-low breast cancer remain obscure, and little is known about the ethnic differences of HER2-low BC. These limitations prevent us from a more precise patient selection and better drug combination strategies in the era of ADCs. To provide a comprehensive and intensive landscape of HER2-low BCs, we characterized HER2-low BCs both clinically and molecularly, which may help clinicians to achieve a more precise clinical management of these patients. Patients and methods: We established a HER2-low BC cohort (N=441) in early-stage Chinese patients and included HER2-0 (N=114) and HER2-positive (N=181) tumors as auxiliary cohorts to characterize HER2-low breast cancers both clinically and molecularly. Whole-exome sequencing, copy number variation assays, RNA sequencing and isobaric quantitative proteomics were conducted to obtain multiomics data. We compared the clinicopathological and molecular features between HER2-low tumors and other HER2 status subgroups stratified and not stratified hormone receptor (HR) status to clarify the distinctness of HER2-low BCs. And we analyzed the internal heterogeneity and ethnic difference of HER2-low BCs by characterizing a distinct subgroup of patients with unique driving mechanisms. Results: HER2-low BCs showed different molecular manifestations from HER2-0 BCs in different HR subgroups. In the HR-negative subgroup, HER2-low BCs consisted of more non-basal-like subtypes than HER2-0 tumors (40.0% vs. 9.1%, P = 0.002), which was an East Asian-specific phenomenon absent in Western cohorts. Also, HR-negative HER2-low BCs showed significant internal molecular heterogeneity, of which basal-like tumors closely mimicked HER2-0 BCs, whereas non-basal-like tumors were similar to HER2-positive BCs. These non-basal-like tumors were mostly categorized as HER2-enriched and luminal androgen receptor (LAR) subtypes. These molecularly distinct tumors might be driven by frequent mutation in PIK3CA and overexpression of FGFR4 and PTK6, which may also serve as therapeutic targets. These results have also been proved in a triple negative breast cancer cohort we reported previously. In contrast, in the HR-positive subgroup, HER2-low BCs showed no large-scale molecular difference from HER2-0 BCs or internal heterogeneity. However, HER2-low patients showed significantly better distant metastasis-free survival than HER2-0 patients (P = 0.029), which might be attributed to the lower loss/deletion levels of 17q11.12 and 17q21.31 in HER2-low breast cancers, in which genes including NF1 and BRCA1 are located. Conclusions: We reported the largest single-center multiomics HER2-low BC cohort in East Asian hitherto, and revealed its molecular nature, internal heterogeneity and ethnic difference. Compared with HR-positive diseases, HER2-low BCs in the HR-negative subgroup were more likely to be a molecularly distinct entity from HER2-0 tumors. Furthermore, HR-negative HER2-low BC also accommodates higher internal heterogeneity, which was ethnicity-specific in our East Asian cohort and may infer a different treatment response. Our work emphasized the need of a more precise stratification within HER2-low BCs and across ethnic groups, which has also been inferred by the results in the subgroup analysis of DESTINY-Breast04 trial. Citation Format: Lei-Jie Dai, Ding Ma, Yi Xiao, Xi Jin, Song-Yang Wu, Ya-Xin Zhao, Han Wang, Wen-Tao Yang, Yi-Zhou Jiang, Zhi-Ming Shao. HER2-09 Multiomics Profiling Characterizes Distinct HER2-low Breast Cancer Subgroups in the East Asian Population [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr HER2-09.
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