Liquid Biopsy in Lung Cancer: Biomarkers for the Management of Recurrence and Metastasis.

Liquid biopsies have emerged as a promising tool for the detection of metastases as well as local and regional recurrence in lung cancer. Liquid biopsy tests involve analyzing a patient's blood, urine, or other body fluids for the detection of biomarkers, including circulating tumor cells or tumor-derived DNA/RNA that have been shed into the bloodstream. Studies have shown that liquid biopsies can detect lung cancer metastases with high accuracy and sensitivity, even before they are visible on imaging scans. Such tests are valuable for early intervention and personalized treatment, aiming to improve patient outcomes. Liquid biopsies are also minimally invasive compared to traditional tissue biopsies, which require the removal of a sample of the tumor for further analysis. This makes liquid biopsies a more convenient and less risky option for patients, particularly those who are not good candidates for invasive procedures due to other medical conditions. While liquid biopsies for lung cancer metastases and relapse are still being developed and validated, they hold great promise for improving the detection and treatment of this deadly disease. Herein, we summarize available and novel approaches to liquid biopsy tests for lung cancer metastases and recurrence detection and describe their applications in clinical practice.

Typical Lung Carcinoids with Metastasis: Potential Role of MicroRNAs in the Regulation of Adaptive Immunity Associated with Disease: a Case Study.

BACKGROUND/AIMS: Lung carcinoids are uncommon neuroendocrine tumours. Molecular features of lung carcinoids have been poorly defined. microRNAs (miRNAs) are potent gene expression regulators with important roles in cancer development and progression. However, little is known on the role of miRNAs in the pathogenesis of lung carcinoids. Our goals were to identify commonly deregulated miRNAs in a rare case of lung carcinoid of typical histology with metastasis, as well as map miRNA target genes in pathways potentially associated with disease development and progression. METHODS: miRNA expression profiles were assessed using the TaqMan Low Density Arrays, which is a platform including 384 miRNAs. miRNA profiles were generated in the tumor and its corresponding lymph node metastasis, compared to reference normal lung tissues. Furthermore, miRNA expression was validated in a separate, publicly available external dataset (n=19 typical lung carcinoids; 2/19 were metastatic tumors, compared to six normal lung tissues, GSE77380). Following this analysis, computational tools were applied for data interpretation. miRTarBase was used to determine miRNA-target genes, followed by ToppGene Suite analysis to identify pathways and biological functions. In addition, the expression of genes targeted by miRNAs was validated in a second, separate external dataset (n=13 tumour samples, GSE35679). GEO2R data analysis tool was used in both validation analyses (miRNAs and genes). RESULTS: We identified 15 commonly significantly downregulated miRNAs (fold change, FC≥2 and p<0.05) in the tumour and its paired metastasis, with further decreasing levels in the metastatic lesion. Downregulation of miR-126-3p and miR-146b-5p was validated in the external dataset GSE77380. In addition, SOX2 and TCF4 genes, targeted by miR-126-3p, were consistently overexpressed in a subset of six typical lung carcinoids from the external dataset GSE35679. Pathways analysis showed that miRNAs miR-126-3p and miR-146b-5p target genes with a role in the regulation of adaptive immune response. CONCLUSION: Our results contribute to the identification of miRNA expression changes in a typical lung carcinoid and its corresponding lymph node metastasis. Down-regulated levels of miR-126-3p and miR-146b-5p and target gene over-expression could play a role in the progression of this case of primary typical lung carcinoid to regional metastasis. Identified miRNAs and target genes are potential candidates for validation in a larger number of cases.

Antibiotic prophylaxis for surgical site infection in people undergoing liver transplantation.

BACKGROUND: Surgical site infection is more frequent in liver transplantation than in other types of solid organ transplantation with different antibiotics. Studies have shown that the rate of surgical site infection varies from 8.8% to 37.5% after liver transplantation. Therefore, antimicrobial prophylaxis is likely an essential tool for reducing these infections. However, the literature lacks evidence indicating the best prophylactic antibiotic regimen that can be used for liver transplantation. OBJECTIVES: To assess the benefits and harms of antibiotic prophylactic regimens for surgical site infection in people undergoing liver transplantation. SEARCH METHODS: We searched the Cochrane Hepato-Biliary Group Controlled Trials Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, Science Citation Index Expanded and Latin American Caribbean Health Sciences Literature (LILACS). The most recent search was performed on 11 September 2015. SELECTION CRITERIA: All eligible randomised clinical trials comparing any antibiotic regimen versus placebo, versus no intervention or versus another antibiotic regimen for surgical site infection in liver transplant recipients, regardless of age, sex and reason for transplantation. Quasi-randomised studies and other observational studies were considered for data on harm if retrieved with search results for randomised clinical trials. DATA COLLECTION AND ANALYSIS: Two review authors selected relevant trials, assessed risk of bias of studies and extracted data. MAIN RESULTS: The electronic search identified 786 publications after removal of duplicates. From this search, only one seemingly randomised clinical trial, published in abstract form, fulfilled the inclusion criteria of this review. This trial was conducted at Shiraz Transplant Centre, Shiraz, Iran, where investigators randomly assigned a total of 180 consecutive liver transplant recipients. We judged the overall risk of bias of the trial published in abstract form as high. Researchers reported no numerical data but mentioned that 163 participants met the inclusion criteria after randomisation, and hence were included in the analyses. Most probably, the 17 excluded participants were high-risk liver transplant recipients. Trial authors concluded that they could find no differences between the two antibiotic regimens - ceftriaxone plus metronidazole versus ampicillin-sulbactam plus ceftizoxime - when given to liver transplant recipients. Review authors could not reconfirm the analyses because, as it has been mentioned, trial authors provided no trial data for analyses. AUTHORS' CONCLUSIONS: Benefits and harms of antibiotic prophylactic regimens for surgical site infection in liver transplantation remain unclear. Additional well-conducted randomised clinical trials adhering to SPIRIT (Spirit Protocol Items: Recommendations for Interventional Trials) and CONSORT (Consolidated Standards of Reporting Trials) guidelines are needed to determine the exact role of antibiotic prophylactic regimens in patients undergoing liver transplantation.

Combining machine learning and texture analysis to differentiate mediastinal lymph nodes in lung cancer patients.

Evaluate whether texture analysis associated with machine learning approaches could differentiate between malignant and benign lymph nodes. A total 18 patients with lung cancer were selected, with 39 lymph nodes, being 15 malignant and 24 benign. Retrospective computed tomography scans were utilized both with and without contrast medium. The great differential of this work was the use of 15 textures from mediastinal lymph nodes, with five different physicians as operators. First and second order statistical textures such as gray level run length and co-occurrence matrix were extracted and applied to three different machine learning classifiers. The best machine learning classifier demonstrated a variability of less than 5% among operators. The support vector machine (SVM) classifier presented 95% of the area under the ROC curve (AUC) and 89% of sensitivity for sequences without contrast medium. SVM classifier presented 93% of AUC and 86% of sensitivity for sequences with contrast medium. Texture analysis and machine learning may be helpful in the differentiation between malign and benign lymph nodes. This study can aid the physician in diagnosis and staging of lymph nodes and potentially reduce the number of invasive analysis to histopathological confirmation.

Deregulated microRNAs Are Associated with Patient Survival and Predicted to Target Genes That Modulate Lung Cancer Signaling Pathways.

(1) Background: Although the advances in diagnostic and treatment strategies, lung cancer remains the leading cause of cancer-related deaths, worldwide, with survival rates as low as 16% in developed countries. Low survival rates are mainly due to late diagnosis and the lack of effective treatment. Therefore, the identification of novel, clinically useful biomarkers is still needed for patients with advanced disease stage and poor survival. Micro(mi)RNAs are non-coding RNAs and potent regulators of gene expression with a possible role as diagnostic, prognostic and predictive biomarkers in cancer. (2) Methods: We applied global miRNA expression profiling analysis using TaqMan® arrays in paired tumor and normal lung tissues (n = 38) from treatment-naïve patients with lung adenocarcinoma (AD; n = 23) and lung squamous cell carcinoma (SCC; n = 15). miRNA target genes were validated using The Cancer Genome Atlas (TCGA) lung AD (n = 561) and lung SCC (n = 523) RNA-Seq datasets. (3) Results: We identified 33 significantly deregulated miRNAs (fold change, FC ≥ 2.0 and p < 0.05) in tumors relative to normal lung tissues, regardless of tumor histology. Enrichment analysis confirmed that genes targeted by the 33 miRNAs are aberrantly expressed in lung AD and SCC, and modulate known pathways in lung cancer. Additionally, high expression of miR-25-3p was significantly associated (p < 0.05) with poor patient survival, when considering both tumor histologies. (4) Conclusions: miR-25-3p may be a potential prognostic biomarker in non-small cell lung cancer. Genes targeted by miRNAs regulate EGFR and TGFß signaling, among other known pathways relevant to lung tumorigenesis.

Defining Metabolic Rewiring in Lung Squamous Cell Carcinoma.

Metabolomics based on untargeted flow infusion electrospray ionization high-resolution mass spectrometry (FIE-HRMS) can provide a snap-shot of metabolism in living cells. Lung Squamous Cell Carcinoma (SCC) is one of the predominant subtypes of Non-Small Cell Lung Cancers (NSCLCs), which usually shows a poor prognosis. We analysed lung SCC samples and matched histologically normal lung tissues from eight patients. Metabolites were profiled by FIE-HRMS and assessed using t-test and principal component analysis (PCA). Differentially accumulating metabolites were mapped to pathways using the mummichog algorithm in R, and biologically meaningful patterns were indicated by Metabolite Set Enrichment Analysis (MSEA). We identified metabolic rewiring networks, including the suppression of the oxidative pentose pathway and found that the normal tricarboxylic acid (TCA) cycle were decoupled from increases in glycolysis and glutamine reductive carboxylation. Well-established associated effects on nucleotide, amino acid and thiol metabolism were also seen. Novel aspects in SCC tissue were increased in Vitamin B complex cofactors, serotonin and a reduction of γ-aminobutyric acid (GABA). Our results show the value of FIE-HRMS as a high throughput screening method that could be exploited in clinical contexts.

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.