Cancer is a disease which frequently has a poor prognosis. Although multiple therapeutic strategies have been developed for various cancers, including chemotherapy, radiotherapy, and immunotherapy, resistance to these treatments frequently impedes the clinical outcomes. Besides the active resistance driven by genetic and epigenetic alterations in tumor cells, the tumor microenvironment (TME) has also been reported to be a crucial regulator in tumorigenesis, progression, and resistance. Here, we propose that the adaptive mechanisms of tumor resistance are closely connected with the TME rather than depending on non-cell-autonomous changes in response to clinical treatment. Although the comprehensive understanding of adaptive mechanisms driven by the TME need further investigation to fully elucidate the mechanisms of tumor therapeutic resistance, many clinical treatments targeting the TME have been successful. In this review, we report on recent advances concerning the molecular events and important factors involved in the TME, particularly focusing on the contributions of the TME to adaptive resistance, and provide insights into potential therapeutic methods or translational medicine targeting the TME to overcome resistance to therapy in clinical treatment.

Magnetic nanoparticles double coated with β-cyclodextrin and chitosan were prepared for hydrophobic drug delivery, and its related mechanism was discussed.

As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.

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BackgroundCardiovascular death (CVD) in breast cancer patients without chemotherapy (CT) or (and) radiotherapy (RT) has not been studied yet. This study evaluates the correlation between breast cancer and CVD risk independent of chemotherapy or (and) radiotherapy.MethodsData of female breast cancer patients without receiving CT or RT were retrieved from the Surveillance, Epidemiology, and End Result (SEER) database (2004–2015). Data were divided into two cohorts: tumor resection cohort and no resection cohort. The CVD risk in patients was expressed as standardized mortality ratios (SMRs). A 1:1 propensity score matching (PSM) was applied to balance inter-group bias, and competing risk regressions were utilized to evaluate the impact of tumor resection on CVD.ResultsThe CVD risk was significantly higher (SMR = 2.196, 95% CI: 2.148–2.245, P<0.001) in breast cancer patients who did not receive CT or RT compared to the general population. Breast cancer patients without tumor resection showed higher CVD risk than patients who underwent tumour resection (tumor resection SMR = 2.031, 95% CI: 1.983–2.079, P<0.001; no resection SMR = 5.425, 95% CI: 5.087–5.781, P<0.001). After PSM, the CVD risk among patients without tumor resection indicated an increase of 1.165-fold compared to patients with tumor resection (HR=1.165, 95% CI: 1.039–1.306, P=0.009).ConclusionsFemale breast cancer patients are at higher risk of CVD despite unexposure to cardio-toxic CT or RT. However, female breast cancer patients subjected to tumor resection have decreased CVD risk. These results indicated that monitoring female breast cancer patients not receiving RT or CT might serve as a preventative measure against CVD.

Analysis of single-cell RNA sequencing (scRNA-seq) data of immune cells from the tumor microenvironment (TME) may identify tumor progression biomarkers. This study was designed to investigate the prognostic value of differentially expressed genes (DEGs) in intrahepatic cholangiocarcinoma (ICC) using scRNA-seq. We downloaded the scRNA-seq data of 33,991 cell samples, including 17,090 ICC cell samples and 16,901 ICC adjacent tissue cell samples regarded as normal cells. scRNA-seq data were processed and classified into 20 clusters. The immune cell clusters were extracted and processed again in the same way, and each type of immune cells was divided into several subclusters. In total, 337 marker genes of macrophages and 427 marker genes of B cells were identified by comparing ICC subclusters with normal subclusters. Finally, 659 DEGs were obtained by merging B cell and macrophage marker genes. ICC sample clinical information and gene expression data were downloaded. A nine-prognosis-related-gene (PRG) signature was established by analyzing the correlation between DEGs and overall survival in ICC. The robustness and validity of the signature were verified. Functional enrichment analysis revealed that the nine PRGs were mainly involved in tumor immune mechanisms. In conclusion, we established a PRG signature based on scRNA-seq data from immune cells of patients with ICC. This PRG signature not only reflects the TME immune status but also provides new biomarkers for ICC prognosis.

PurposeTo study the cardiovascular death (CVD) risk in primary central nervous system lymphoma (PCNSL) patients with chemotherapy.MethodsWe obtained 2,020 PCNSL participants and 88,613 non-central nervous system lymphoma (NCNSL) participants with chemotherapy from Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015. A 1:3 propensity score matching (PSM) was used to reduce the imbalance between PCNSL participants with and without chemotherapy, as well as the imbalance between PCNSL and NCNSL participants with chemotherapy. Competing risks regressions were conducted to evaluate the independent influence of chemotherapy on CVD.ResultsAfter 1:3 PSM, the CVD risk in PCNSL patients with chemotherapy was lower than those without chemotherapy [decreased 53%, adjusted HR, 0.469 (95% CI, 0.255–0.862; P = 0.015)] as well as NCNSL patients with chemotherapy [decreased 36%, adjusted HR in model 1, 0.636 (95% CI, 0.439–0.923; P = 0.017)]. The CVD risk of chemotherapy decreased in PCNSL patients with age at diagnosis >60 years old [adjusted HR, 0.390 (95% CI, 0.200–0.760; P = 0.006)], and those patients diagnosed at 2010 to 2015 [adjusted HR, 0.339 (95% CI, 0.118–0.970; P = 0.044)].ConclusionPCNSL patients with chemotherapy are associated with lower CVD risk. Our findings may provide new foundations for that chemotherapy is the first-line treatment for PCNSL patients, according to a cardiovascular risk perspective.

Long non-coding RNAs (lncRNAs) and their N6-methyladenosine (m6A) modifications play an essential role in tumorigenesis and cancer progression. This study was designed to explore the value of m6A-related lncRNAs in prognosis and therapeutic applications of immune infiltration of colon adenocarcinoma (COAD). We downloaded the COAD gene expression and clinical data from The Cancer Genome Atlas project. By co-expression analysis, Lasso Cox regression analysis, and univariate and multivariate Cox regression, we constructed an independent prognostic signature of seven m6A-related lncRNAs. The prognostic lncRNAs were divided into two clusters by consistent clustering analysis, as well as into two groups of low–high risk based on the signature. Then we identified the relationship between the different groups with clinical features and immune cell infiltration. Cluster 2 had a higher risk score with a lower survival rate. The risk score was higher in groups with advanced clinical features, such as stage III–IV, N1-3, and M1. The expression of AC156455.1 was increased in tumor tissues and cluster 2, and the lncRNA ZEB1−AS1 was notably higher in the high-risk group. Five types of immune cells showed differences in two clusters, and most were upregulated in type 2. The expression of memory B cells was positively correlated with the risk score. The prognostic model was verified by the Gene Expression Omnibus (GEO) dataset. Besides, we found that the expression of these seven lncRNAs in tumor tissues was significantly higher than that in normal tissues, which verified the feasibility of the model. Thus, the signature of seven m6A-related lncRNAs can independently predict the prognosis of COAD. This signature is also closely associated with immune cell infiltration, and new therapeutic targets can be explored from this field.