Comprehensive Analysis of Lung Adenocarcinoma and Brain Metastasis through Integrated Single-Cell Transcriptomics.

Lung adenocarcinoma (LUAD) is a highly prevalent and lethal form of lung cancer, comprising approximately half of all cases. It is often diagnosed at advanced stages with brain metastasis (BM), resulting in high mortality rates. Current BM management involves complex interventions and conventional therapies that offer limited survival benefits with neurotoxic side effects. The tumor microenvironment (TME) is a complex system where cancer cells interact with various elements, significantly influencing tumor behavior. Immunotherapies, particularly immune checkpoint inhibitors, target the TME for cancer treatment. Despite their effectiveness, it is crucial to understand metastatic lung cancer and the specific characteristics of the TME, including cell-cell communication mechanisms, to refine treatments. Herein, we investigated the tumor microenvironment of brain metastasis from lung adenocarcinoma (LUAD-BM) and primary tumors across various stages (I, II, III, and IV) using single-cell RNA sequencing (scRNA-seq) from publicly available datasets. Our analysis included exploring the immune and non-immune cell composition and the expression profiles and functions of cell type-specific genes, and investigating the interactions between different cells within the TME. Our results showed that T cells constitute the majority of immune cells present in primary tumors, whereas microglia represent the most dominant immune cell type in BM. Interestingly, microglia exhibit a significant increase in the COX pathway. Moreover, we have shown that microglia primarily interact with oligodendrocytes and endothelial cells. One significant interaction was identified between DLL4 and NOTCH4, which demonstrated a relevant association between endothelial cells and microglia and between microglia and oligodendrocytes. Finally, we observed that several genes within the HLA complex are suppressed in BM tissue. Our study reveals the complex molecular and cellular dynamics of BM-LUAD, providing a path for improved patient outcomes with personalized treatments and immunotherapies.

Discovery of Novel miRNAs in Colorectal Cancer: Potential Biological Roles and Clinical Utility.

Deregulated miRNAs are associated with colorectal cancer (CRC), with alterations depending on the tumor location. Novel tissue-specific miRNAs have been identified in different tumors and are associated with cancer. We used miRMaster to identify novel miRNAs in CRC from the TCGA and GEO data (discovery and validation groups). We used TCGA data from five tissues to analyze miRNA tissue specificity. miRDB was used to predict miRNA targets, and the UCSC Xena Browser was used to evaluate target expression. After successive analyses, we identified 15 novel miRNAs with the same expression patterns in CRC in both the discovery and validation groups. Four molecules (nov-miR-13844-5p, nov-miR-7154-5p, nov-miR-5035-3p, and nov-miR-590-5p) were differentially expressed in proximal and distal CRC. The nov-miR-3345-5p and nov-miR-13172-3p, which are upregulated in tumors, are only expressed in colorectal tissues. These molecules have been linked to a worse prognosis in right-sided colon and rectal carcinomas. An analysis revealed an association between eight novel miRNAs and 81 targets, mostly cancer-related genes, with varying expression based on tumor location. These findings provide new miRNAs with potential biological relevance, molecular biomarkers, and therapeutic targets for CRC treatment.

Identifying New Contributors to Brain Metastasis in Lung Adenocarcinoma: A Transcriptomic Meta-Analysis.

Lung tumors frequently metastasize to the brain. Brain metastasis (BM) is common in advanced cases, and a major cause of patient morbidity and mortality. The precise molecular mechanisms governing BM are still unclear, in part attributed to the rarity of BM specimens. In this work, we compile a unique transcriptomic dataset encompassing RNA-seq, microarray, and single-cell analyses from BM samples obtained from patients with lung adenocarcinoma (LUAD). By integrating this comprehensive dataset, we aimed to enhance understanding of the molecular landscape of BM, thereby facilitating the identification of novel and efficient treatment strategies. We identified 102 genes with significantly deregulated expression levels in BM tissues, and discovered transcriptional alterations affecting the key driver 'hub' genes CD69 (a type II C-lectin receptor) and GZMA (Granzyme A), indicating an important role of the immune system in the development of BM from primary LUAD. Our study demonstrated a BM-specific gene expression pattern and revealed the presence of dendritic cells and neutrophils in BM, suggesting an immunosuppressive tumor microenvironment. These findings highlight key drivers of LUAD-BM that may yield therapeutic targets to improve patient outcomes.

Advances in the Molecular Landscape of Lung Cancer Brain Metastasis.

Lung cancer is one of the most frequent tumors that metastasize to the brain. Brain metastasis (BM) is common in advanced cases, being the major cause of patient morbidity and mortality. BMs are thought to arise via the seeding of circulating tumor cells into the brain microvasculature. In brain tissue, the interaction with immune cells promotes a microenvironment favorable to the growth of cancer cells. Despite multimodal treatments and advances in systemic therapies, lung cancer patients still have poor prognoses. Therefore, there is an urgent need to identify the molecular drivers of BM and clinically applicable biomarkers in order to improve disease outcomes and patient survival. The goal of this review is to summarize the current state of knowledge on the mechanisms of the metastatic spread of lung cancer to the brain and how the metastatic spread is influenced by the brain microenvironment, and to elucidate the molecular determinants of brain metastasis regarding the role of genomic and transcriptomic changes, including coding and non-coding RNAs. We also present an overview of the current therapeutics and novel treatment strategies for patients diagnosed with BM from NSCLC.

MicroRNA modulated networks of adaptive and innate immune response in pancreatic ductal adenocarcinoma.

Despite progress in treatment strategies, only ~24% of pancreatic ductal adenocarcinoma (PDAC) patients survive >1 year. Our goal was to elucidate deregulated pathways modulated by microRNAs (miRNAs) in PDAC and Vater ampulla (AMP) cancers. Global miRNA expression was identified in 19 PDAC, 6 AMP and 25 paired, histologically normal pancreatic tissues using the GeneChip 4.0 miRNA arrays. Computational approaches were used for miRNA target prediction/identification of miRNA-regulated pathways. Target gene expression was validated in 178 pancreatic cancer and 4 pancreatic normal tissues from The Cancer Genome Atlas (TCGA). 20 miRNAs were significantly deregulated (FC≥2 and p<0.05) (15 down- and 5 up-regulated) in PDAC. miR-216 family (miR-216a-3p, miR-216a-5p, miR-216b-3p and miR-216b-5p) was consistently down-regulated in PDAC. miRNA-modulated pathways are associated with innate and adaptive immune system responses in PDAC. AMP cancers showed 8 down- and 1 up-regulated miRNAs (FDR p<0.05). Most enriched pathways (p<0.01) were RAS and Nerve Growth Factor signaling. PDAC and AMP display different global miRNA expression profiles and miRNA regulated networks/tumorigenesis pathways. The immune response was enriched in PDAC, suggesting the existence of immune checkpoint pathways more relevant to PDAC than AMP.

Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma.

Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma.

Whole-genome sequencing analysis identifies a distinctive mutational spectrum in an arsenic-related lung tumor.

INTRODUCTION: Arsenic exposure is a significant cause of lung cancer in North America and worldwide. Arsenic-related tumors are structurally indistinguishable from those induced by other carcinogens. Because carcinogens, like tobacco, induce distinctive mutational signatures, we sought to characterize the mutational signature of an arsenic-related lung tumor from a never smoker with the use of whole-genome sequencing. METHODS: Tumor and lung tissues were obtained from a never smoker with lung squamous cell carcinoma (LUSC), without familiar history of lung cancer and chronically exposed to high levels of arsenic-contaminated drinking water. The Illumina HiSeq-2000 platform was used to sequence each genome at approximately 30-fold haploid coverage. The mutational signature was compared with those observed in previously characterized lung tumors. RESULTS: The arsenic-related tumor exhibited alterations common in LUSC, such as the increased number of copies at 3q26 (SOX2 locus). However, the arsenic-related genome not only harbored a lower number of point mutations, but also had a remarkably high fraction of T>G/A>C mutations and low fraction of C>A/G>T transversions, which is uncharacteristic of LUSCs. Furthermore, at the gene level, we identified a rare G>C mutation in TP53, which is uncommon in lung tumors in general (<0.2%) but has been observed in other arsenic-related malignancies. CONCLUSIONS: We generated the first whole-genome sequence of an LUSC from a never-smoker patient chronically exposed to arsenic, and identified a distinct mutational spectrum associated with arsenic exposure, providing novel evidence supporting the hypothesis that arsenic-induced lung tumors arise through molecular mechanisms that differ from those of the common lung cancer.