Identifies microtubule-binding protein CSPP1 as a novel cancer biomarker associated with ferroptosis and tumor microenvironment

Centrosome and spindle pole-associated protein (CSPP1) is a centrosome and microtubule-binding protein that plays a role in cell cycle-dependent cytoskeleton organization and cilia formation. Previous studies have suggested that CSPP1 plays a role in tumorigenesis; however, no pan-cancer analysis has been performed. This study systematically investigates the expression of CSPP1 and its potential clinical outcomes associated with diagnosis, prognosis, and therapy. CSPP1 is widely present in tissues and cells and its aberrant expression serves as a diagnostic biomarker for cancer. CSPP1 dysregulation is driven by multi-dimensional mechanisms involving genetic alterations, DNA methylation, and miRNAs. Phosphorylation of CSPP1 at specific sites may play a role in tumorigenesis. In addition, CSPP1 correlates with clinical features and outcomes in multiple cancers. Take brain low-grade gliomas (LGG) with a poor prognosis as an example, functional enrichment analysis implies that CSPP1 may play a role in ferroptosis and tumor microenvironment (TME), including regulating epithelial-mesenchymal transition, stromal response, and immune response. Further analysis confirms that CSPP1 dysregulates ferroptosis in LGG and other cancers, making it possible for ferroptosis-based drugs to be used in the treatment of these cancers. Importantly, CSPP1-associated tumors are infiltrated in different TMEs, rendering immune checkpoint blockade therapy beneficial for these cancer patients. Our study is the first to demonstrate that CSPP1 is a potential diagnostic and prognostic biomarker associated with ferroptosis and TME, providing a new target for drug therapy and immunotherapy in specific cancers.

miR-7/TGF-β2 axis sustains acidic tumor microenvironment-induced lung cancer metastasis

Acidosis, regardless of hypoxia involvement, is recognized as a chronic and harsh tumor microenvironment (TME) that educates malignant cells to thrive and metastasize. Although overwhelming evidence supports an acidic environment as a driver or ubiquitous hallmark of cancer progression, the unrevealed core mechanisms underlying the direct effect of acidification on tumorigenesis have hindered the discovery of novel therapeutic targets and clinical therapy. Here, chemical-induced and transgenic mouse models for colon, liver and lung cancer were established, respectively. miR-7 and TGF-β2 expressions were examined in clinical tissues (n = 184). RNA-seq, miRNA-seq, proteomics, biosynthesis analyses and functional studies were performed to validate the mechanisms involved in the acidic TME-induced lung cancer metastasis. Our data show that lung cancer is sensitive to the increased acidification of TME, and acidic TME-induced lung cancer metastasis via inhibition of miR-7-5p. TGF-β2 is a direct target of miR-7-5p. The reduced expression of miR-7-5p subsequently increases the expression of TGF-β2 which enhances the metastatic potential of the lung cancer. Indeed, overexpression of miR-7-5p reduces the acidic pH-enhanced lung cancer metastasis. Furthermore, the human lung tumor samples also show a reduced miR-7-5p expression but an elevated level of activated TGF-β2; the expressions of both miR-7-5p and TGF-β2 are correlated with patients' survival. We are the first to identify the role of the miR-7/TGF-β2 axis in acidic pH-enhanced lung cancer metastasis. Our study not only delineates how acidification directly affects tumorigenesis, but also suggests miR-7 is a novel reliable biomarker for acidic TME and a novel therapeutic target for non-small cell lung cancer (NSCLC) treatment. Our study opens an avenue to explore the pH-sensitive subcellular components as novel therapeutic targets for cancer treatment.

Discovery of tumor immune infiltration-related snoRNAs for predicting tumor immune microenvironment status and prognosis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) has a high mortality rate and is difficult to diagnose and treat in its early stage. Previous studies have demonstrated that small nucleolar RNAs (snoRNAs) play a critical role in tumor immune infiltration and the development of a variety of solid tumors. However, there have been no studies on the correlation between tumor-infiltrating immune-related snoRNAs (TIISRs) and LUAD. In this study, we filtered six immune-related snoRNAs based on the tissue specificity index (TSI) and expression profile of all snoRNAs between all LUAD cell lines from the Cancer Cell Line Encyclopedia and 21 types of immune cells from the Gene Expression Omnibus database. Further, we performed real-time quantitative polymerase chain reaction (RT-qPCR) to validate the expression status of these snoRNAs on peripheral blood mononuclear cells (PBMCs) and lung cancer cell lines. Next, we developed a TIISR signature based on the expression profiles of snoRNAs from 479 LUAD patients filtered by the random survival forest algorithm. We then analyzed the value of this TIISR signature (TIISR risk score) for assessing tumor immune infiltration, immune checkpoint inhibitor (ICI) treatment response, and the prognosis of LUAD between groups with high and low TIISR risk score. Further, we found that the TIISR risk score groups showed significant differences in biological characteristics and that the risk score could be used to assess the level of tumor immune cell infiltration, thereby predicting prognosis and responsiveness to immunotherapy in LUAD patients.

Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods

Introduction

The risk of infection with COVID-19 is high in lung adenocarcinoma (LUAD) patients, and there is a dearth of studies on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape.

Objectives

To fill the research void on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape.

Methods

Herein, we identified genes, specifically the differentially expressed genes (DEGs), correlated with the susceptibility of LUAD patients to COVID-19. These were obtained by calculating standard mean deviation (SMD) values for 49 SARS-CoV-2-infected LUAD samples and 24 non-affected LUAD samples, as well as 3931 LUAD samples and 3027 non-cancer lung samples from 40 pooled RNA-seq and microarray datasets. Hub susceptibility genes significantly related to COVID-19 were further selected by weighted gene co-expression network analysis. Then, the hub genes were further analyzed via an examination of their clinical significance in multiple datasets, a correlation analysis of the immune cell infiltration level, and their interactions with the interactome sets of the A549 cell line.

Results

A total of 257 susceptibility genes were identified, and these genes were associated with RNA splicing, mitochondrial functions, and proteasomes. Ten genes, MEA1, MRPL24, PPIH, EBNA1BP2, MRTO4, RABEPK, TRMT112, PFDN2, PFDN6, and NDUFS3, were confirmed to be the hub susceptibility genes for COVID-19 in LUAD patients, and the hub susceptibility genes were significantly correlated with the infiltration of multiple immune cells.

Conclusion

In conclusion, the susceptibility genes for COVID-19 in LUAD patients discovered in this study may increase our understanding of the high risk of COVID-19 in LUAD patients.

Protein profiling reveals potential isomiR-associated cross-talks among RNAs in cholangiocarcinoma

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Protein profiling identified crucial genes that were used to screen related ncRNAs.

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Both miRNAs and isomiRs were involved in coding-non-coding RNA regulatory network.

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IsomiR-associated ceRNA networks implied the complex interactions among RNAs.

Cholangiocarcinomas (CCAs) are tumors that arise from the cholangiocytes. Although some genes have been shown with important roles in pathological process, interactions or cross-talks among different RNAs are important to understand the detailed molecular mechanisms in cancer development, especially discussing cross-talks among isomiRs and other RNAs. Herein, to characterize crucial genes in CCA, the protein expression profile was performed to survey potential crucial mRNAs and related non-coding RNAs (ncRNAs) in mRNA-ncRNA network, mainly including miRNAs/isomiRs and lncRNAs. Deregulated mRNAs were firstly obtained if consistent expression patterns were found at protein and mRNA levels, and related miRNAs/isomiRs were screened according to regulatory relationships. Diverse isomiRs from a given miRNA locus also contributed to interactions between the small RNAs and target mRNAs, and miRNAs were further used to survey related lncRNAs to expand the interactions. Thus, several groups of RNAs were constructed as candidate competitive endogenous RNA (ceRNA) networks. Finally, we found that RAB11FIP1:miR-101-3p:MIR3142HG may be a potential ceRNA network, and the interactions among them may be more complex due to variety of isomiRs. Simultaneously, RAB11FIP1 and miR-194-5p were also detected other related lncRNAs (FBXL19-AS1, SNHG1 and PVT1) that may be crucial in coding-non-coding RNA regulatory network. Our results show that diverse isomiRs with sequence and expression heterogeneities contribute to ceRNA regulatory network that may have crucial roles in CCA, which will expand our understanding of interactions among diverse RNAs and their contributions in cancer development.

Review on circular RNAs and new insights into their roles in cancer

Circular RNAs (circRNAs) are a very interesting class of conserved single-stranded RNA molecules derived from exonic or intronic sequences by precursor mRNA back-splicing. Unlike canonical linear RNAs, circRNAs form covalently closed, continuous stable loops without a 5'end cap and 3'end poly(A) tail, and therefore are resistant to exonuclease digestion. The majority of circRNAs are highly abundant, and conserved across different species with a tissue or developmental-stage-specific expression. circRNAs have been shown to play important roles as microRNA sponges, regulators of gene splicing and transcription, RNA-binding protein sponges and protein/peptide translators. Emerging evidence reveals that circRNAs function in various human diseases, particularly cancers, and may function as better predictive biomarkers and therapeutic targets for cancer treatment. In consideration of their potential clinical relevance, circRNAs have become a new research hotspot in the field of tumor pathology. In the present study, the current understanding of the biogenesis, characteristics, databases, research methods, biological functions subcellular distribution, epigenetic regulation, extracellular transport and degradation of circRNAs was discussed. In particular, the multiple databases and methods involved in circRNA research were first summarized, and the recent advances in determining the potential roles of circRNAs in tumor growth, migration and invasion, which render circRNAs better predictive biomarkers, were described. Furthermore, future perspectives for the clinical application of circRNAs in the management of patients with cancer were proposed, which could provide new insights into circRNAs in the future.

Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer analysis

Synthetic lethality is thought to play an important role in anticancer therapies. Herein, to understand the potential distributions and relationships between synthetic lethal interactions between genes, especially for pairs deriving from different sources, we performed an integrative analysis of genes at multiple molecular levels. Based on inter-species phylogenetic conservation of synthetic lethal interactions, gene pairs from yeast and humans were analyzed; a total of 37,588 candidate gene pairs containing 7,816 genes were collected. Of these, 49.74% of genes had 2–10 interactions, 22.93% were involved in hallmarks of cancer, and 21.61% were identified as core essential genes. Many genes were shown to have important biological roles via functional enrichment analysis, and 65 were identified as potentially crucial in the pathophysiology of cancer. Gene pairs with dysregulated expression patterns had higher prognostic values. Further screening based on mutation and expression levels showed that remaining gene pairs were mainly derived from human predicted or validated pairs, while most predicted pairs from yeast were filtered from analysis. Genes with synthetic lethality were further analyzed with their interactive microRNAs (miRNAs) at the isomiR level which have been widely studied as negatively regulatory molecules. The miRNA–mRNA interaction network revealed that many synthetic lethal genes contributed to the cell cycle (seven of 12 genes), cancer pathways (five of 12 genes), oocyte meiosis, the p53 signaling pathway, and hallmarks of cancer. Our study contributes to the understanding of synthetic lethal interactions and promotes the application of genetic interactions in further cancer precision medicine.

The SARS-CoV-2 host cell receptor ACE2 correlates positively with immunotherapy response and is a potential protective factor for cancer progression. Comput Struct Biotechnol J. 2020;18:2438-2444. [PMID: 32905022 PMCID: PMC7462778 DOI: 10.1016/j.csbj.2020.08.024]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 29 million people and has caused more than 900,000 deaths worldwide as of September 14, 2020. The SARS-CoV-2 human cell receptor ACE2 has recently received extensive attention for its role in SARS-CoV-2 infection. Many studies have also explored the association between ACE2 and cancer. However, a systemic investigation into associations between ACE2 and oncogenic pathways, tumor progression, and clinical outcomes in pan-cancer remains lacking. Using cancer genomics datasets from the Cancer Genome Atlas (TCGA) program, we performed computational analyses of associations between ACE2 expression and antitumor immunity, immunotherapy response, oncogenic pathways, tumor progression phenotypes, and clinical outcomes in 13 cancer cohorts. We found that ACE2 upregulation was associated with increased antitumor immune signatures and PD-L1 expression, and favorable anti-PD-1/PD-L1/CTLA-4 immunotherapy response. ACE2 expression levels inversely correlated with the activity of cell cycle, mismatch repair, TGF-β, Wnt, VEGF, and Notch signaling pathways. Moreover, ACE2 expression levels had significant inverse correlations with tumor proliferation, stemness, and epithelial-mesenchymal transition. ACE2 upregulation was associated with favorable survival in pan-cancer and in multiple individual cancer types. These results suggest that ACE2 is a potential protective factor for cancer progression. Our data may provide potential clinical implications for treating cancer patients infected with SARS-CoV-2.

Good or not good: Role of miR-18a in cancer biology

miR-18a is a member of primary transcript called miR-17-92a (C13orf25 or MIR17HG) which also contains five other miRNAs: miR-17, miR-19a, miR-20a, miR-19b and miR-92a. This cluster as a whole shows specific characteristics, where miR-18a seems to be unique. In contrast to the other members, the expression of miR-18a is additionally controlled and probably functions as its own internal controller of the cluster. miR-18a regulates many genes involved in proliferation, cell cycle, apoptosis, response to different kinds of stress, autophagy and differentiation. The disturbances of miR-18a expression are observed in cancer as well as in different diseases or pathological states. The miR-17-92a cluster is commonly described as oncogenic and it is known as 'oncomiR-1', but this statement is a simplification because miR-18a can act both as an oncogene and a suppressor. In this review we summarize the current knowledge about miR-18a focusing on its regulation, role in cancer biology and utility as a potential biomarker.

Rewired functional regulatory networks among miRNA isoforms (isomiRs) from let-7 and miR-10 gene families in cancer

Classical microRNA (miRNA) has been so far believed as a single sequence, but it indeed contains multiple miRNA isoforms (isomiR) with various sequences and expression patterns. It is not clear whether these diverse isomiRs have potential relationships and whether they contribute to miRNA:mRNA interactions. Here, we aimed to reveal the potential evolutionary and functional relationships of multiple isomiRs based on let-7 and miR-10 gene families that are prone to clustering together on chromosomes. Multiple isomiRs within gene families showed similar functions to their canonical miRNAs, indicating selection of the predominant sequence. IsomiRs containing novel seed regions showed increased/decreased biological function depending on whether they had more/less specific target mRNAs than their annotated seed. Few gene ontology(GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were shared among the target genes of the annotated seeds and the novel seeds. Various let-7 isomiRs with novel seed regions may cause opposing drug responses despite the fact that they are generated from the same miRNA locus and have highly similar sequences. IsomiRs, especially the dominant isomiRs with shifted seeds, may disturb the coding-non-coding RNA regulatory network. These findings provide insight into the multiple isomiRs and isomiR-mediated control of gene expression in the pathogenesis of cancer.

PreMSIm: An R package for predicting microsatellite instability from the expression profiling of a gene panel in cancer

Microsatellite instability (MSI) is a genomic property of the cancers with defective DNA mismatch repair and is a useful marker for cancer diagnosis and treatment in diverse cancer types. In particular, MSI has been associated with the active immune checkpoint blockade therapy response in cancer. Most of computational methods for predicting MSI are based on DNA sequencing data and a few are based on mRNA expression data. Using the RNA-Seq pan-cancer datasets for three cancer cohorts (colon, gastric, and endometrial cancers) from The Cancer Genome Atlas (TCGA) program, we developed an algorithm (PreMSIm) for predicting MSI from the expression profiling of a 15-gene panel in cancer. We demonstrated that PreMSIm had high prediction performance in predicting MSI in most cases using both RNA-Seq and microarray gene expression datasets. Moreover, PreMSIm displayed superior or comparable performance versus other DNA or mRNA-based methods. We conclude that PreMSIm has the potential to provide an alternative approach for identifying MSI in cancer.

The landscape of bacterial presence in tumor and adjacent normal tissue across 9 major cancer types using TCGA exome sequencing

Identification of microbial composition directly from tumor tissue permits studying the relationship between microbial changes and cancer pathogenesis. We interrogated bacterial presence in tumor and adjacent normal tissue strictly in pairs utilizing human whole exome sequencing to generate microbial profiles. Profiles were generated for 813 cases from stomach, liver, colon, rectal, lung, head & neck, cervical and bladder TCGA cohorts. Core microbiota examination revealed twelve taxa to be common across the nine cancer types at all classification levels. Paired analyses demonstrated significant differences in bacterial shifts between tumor and adjacent normal tissue across stomach, colon, lung squamous cell, and head & neck cohorts, whereas little or no differences were evident in liver, rectal, lung adenocarcinoma, cervical and bladder cancer cohorts in adjusted models. Helicobacter pylori in stomach and Bacteroides vulgatus in colon were found to be significantly higher in adjacent normal compared to tumor tissue after false discovery rate correction. Computational results were validated with tissue from an independent population by species-specific qPCR showing similar patterns of co-occurrence among Fusobacterium nucleatum and Selenomonas sputigena in gastric samples. This study demonstrates the ability to identify bacteria differential composition derived from human tissue whole exome sequences. Taken together our results suggest the microbial profiles shift with advanced disease and that the microbial composition of the adjacent tissue can be indicative of cancer stage disease progression.