Metabolic Reprogramming of Phospholipid Fatty Acids as a Signature of Lung Cancer Type.

Background: Lung cancer is one of the leading causes of cancer-related mortality. Non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) differ in aggressiveness, proliferation speed, metastasis propensity, and prognosis. Since tumor cells notably change lipid metabolism, especially phospholipids and fatty acids (FA), this study aimed to identify FA alterations in lung cancer tissues. Methods: Our study included patients with newly diagnosed, histologically confirmed SCLC (n = 27) and NSCLC (n = 37). Samples were collected from both malignant and healthy tissues from each patient, providing they were within subject design. Results: In both NSCLC and SCLC tumor tissues, FA contents were shifted toward pro-inflammatory profiles, with increased levels of some individual n-6 polyunsaturated FA (PUFA), particularly arachidonic acid, and elevated activity of Δ6 desaturase. Compared to healthy counterparts, lower levels of alpha-linolenic acid (18:3n-3) and total saturated FA (SFA) were found in NSCLC, while decreased levels of linoleic acid (18:2n-6) and all individual n-3 FA were found in SCLC tissue in comparison to the healthy tissue control. When mutually compared, SCLC tissue had higher levels of total SFA, especially stearic acid, while higher levels of linoleic acid, total PUFA, and n-3 and n-6 PUFA were detected in NSCLC. Estimated activities of Δ6 desaturase and elongase were higher in SCLC than in NSCLC. Conclusions: Our findings indicate a notable impairment of lipid metabolism in two types of lung cancer tissues. These type-specific alterations may be associated with differences in their progression and also point out different therapeutic targets.

Proteogenomic analysis of air-pollution-associated lung cancer reveals prevention and therapeutic opportunities.

Air pollution significantly impacts lung cancer progression, but there is a lack of a comprehensive molecular characterization of clinical samples associated with air pollution. Here, we performed a proteogenomic analysis of lung adenocarcinoma (LUAD) in 169 female never-smokers from the Xuanwei area (XWLC cohort), where coal smoke is the primary contributor to the high lung cancer incidence. Genomic mutation analysis revealed XWLC as a distinct subtype of LUAD separate from cases associated with smoking or endogenous factors. Mutational signature analysis suggested that Benzo[a]pyrene (BaP) is the major risk factor in XWLC. The BaP-induced mutation hotspot, EGFR-G719X, was present in 20% of XWLC which endowed XWLC with elevated MAPK pathway activations and worse outcomes compared to common EGFR mutations. Multi-omics clustering of XWLC identified four clinically relevant subtypes. These subgroups exhibited distinct features in biological processes, genetic alterations, metabolism demands, immune landscape, and radiomic features. Finally, MAD1 and TPRN were identified as novel potential therapeutic targets in XWLC. Our study provides a valuable resource for researchers and clinicians to explore prevention and treatment strategies for air-pollution-associated lung cancers.

White Light Diffraction Phase Microscopy in Imaging of Breast and Colon Tissues.

This paper reports results obtained using white light diffraction phase microscopy (wDPM) on captured images of breast and colon tissue samples, marking a contribution to the advancement in biomedical imaging. Unlike conventional brightfield microscopy, wDPM offers the capability to capture intricate details of biological specimens with enhanced clarity and precision. It combines high resolution, enhanced contrast, and quantitative capabilities with non-invasive, label-free imaging. These features make it a useful tool for tissue imaging, providing detailed and accurate insights into tissue structure and dynamics without compromising the integrity of the samples. Our findings underscore the potential of quantitative phase imaging in histopathology, in the context of automating the process of tissue analysis and diagnosis. Of particular note are the insights gained from the reconstructed phase images, which provide physical data regarding peripheral glandular cell membranes. These observations serve to focus attention on pathologies involving the basal membrane, such as early invasive carcinoma. Through our analysis, we aim to contribute to catalyzing further advancements in tissue (breast and colon) imaging.

[Hyaluronan receptors: role in aging and age-associated processes.]

The review describes the involvement of various hyaluronic acid receptors, including CD44, RHAMM, HARE, TLR, LYVE-1, in maintaining normal homeostasis and aging, as well as in the development of age-associated inflammatory processes (inflamaging) and malignant tumors. The association of CD44 receptor activation with immune cells and the development of coronary heart disease has been shown. In addition, a link between the CD44 receptor and osteoarthritis has been shown, via TLR2 and TLR4. The oncogenic potential of RHAMM in relation to breast, prostate, leukemia, pancreas, lung and glioblastoma cancers has been described, with the strongest expression observed in metastatic tumors. In vivo and in vitro experiments, it was found that fragments of hyaluronic acid with a length of 4 to 25 disaccharides can contribute to the proliferation of lymphatic endothelial cells and lymphangiogenesis. Thus, hyaluronic acid receptors play an important role in the aging process through the regulation of inflamaging and in the development of malignant neoplasms.

Exploring the impact of GSTM1 as a novel molecular determinant of survival in head and neck cancer patients of African descent.

BACKGROUND: Blacks/African American (BAA) patients diagnosed with head and neck squamous cell carcinoma (HNSCC) have worse survival outcomes than White patients. However, the mechanisms underlying racial disparities in HNSCC have not been thoroughly characterized. METHODS: Data on gene expression, copy number variants (CNVs), gene mutations, and methylation were obtained from 6 head and neck cancer datasets. Comparative bioinformatics analysis of the above genomic features was performed between BAAs and Whites. The expression pattern of GSTM1 was validated by immunohistochemistry using tumor tissue microarray (TMA). Effect of GSTM1 knockdown were assessed by cell proliferation, colony formation, and tumor development in an orthotopic mouse model. The changes in protein kinases were determined using the Proteome Profiler Human Phospho-Kinase Array Kit in HNSCC cells with or without GSTM1 knockdown. RESULTS: We identified ancestry-related differential genomic profiles in HNSCC. Specifically, in BAA HNSCC, FAT1 mutations were associated with its gene expression, SALL3 gene expression correlated with its gene CNVs, and RTP4 gene expression showed an inverse correlation with its methylation. Notably, GSTM1 emerged as a prognostic risk factor for BAA HNSCC, with high gene CNVs and expression levels correlating with poor overall survival in BAA patients. Immunohistochemistry results from newly developed in-house TMA validated the expression pattern of GSTM1 between BAA HNSCC and White HNSCC. In an orthotopic mouse model, GSTM1 knockdown significantly inhibited malignant progression in tumors derived from BAAs. In contrast, loss of GSTM1 did not affect the development of HNSCC originating in Whites. Mechanistically, GSTM1 knockdown suppressed HSP27 phosphorylation and ß-catenin in BAA HNSCC cells, but not in White HNSCC cells. This differential effect at least partially contributes to tumor development in BAA patients. CONCLUSION: This study identifies GSTM1 as a novel molecular determinant of survival in HNSCC patients of African descent. It also provides a molecular basis for future research focused on identifying molecular determinants and developing therapeutic interventions to improve outcomes for BAA patients with HNSCC.

Close relationship between mediators of inflammation and pancreatic cancer: Our experience.

In this editorial, we focus specifically on the mechanisms by which pancreatic inflammation affects pancreatic cancer. Cancer of the pancreas remains one of the deadliest cancer types. The highest incidence and mortality rates of pancreatic cancer are found in developed countries. Trends of pancreatic cancer incidence and mortality vary considerably worldwide. A better understanding of the etiology and identification of the risk factors is essential for the primary prevention of this disease. Pancreatic tumors are characterized by a complex microenvironment that orchestrates metabolic alterations and supports a milieu of interactions among various cell types within this niche. In this editorial, we highlight the foundational studies that have driven our understanding of these processes. In our experimental center, we have carefully studied the mechanisms of that link pancreatic inflammation and pancreatic cancer. We focused on the role of mast cells (MCs). MCs contain pro-angiogenic factors, including tryptase, that are associated with increased angiogenesis in various tumors. In this editorial, we address the role of MCs in angiogenesis in both pancreatic ductal adenocarcinoma tissue and adjacent normal tissue. The assessment includes the density of c-Kit receptor-positive MCs, the density of tryptase-positive MCs, the area of tryptase-positive MCs, and angiogenesis in terms of microvascularization density.

High Expression of miR-218-5p in the Peripheral Blood Stream and Tumor Tissues of Pediatric Patients with Sarcomas.

Sarcomas are malignant tumors that may metastasize and the course of the disease is highly aggressive in children and young adults. Because of the rare incidence of sarcomas and the heterogeneity of tumors, there is a need for non-invasive diagnostic and prognostic biomarkers in sarcomas. The aim of the study was to investigate the level of miR-218-5p in peripheral blood and tumor tissue samples of Ewing's sarcoma, osteosarcoma, spindle cell sarcoma patients, and healthy controls, and assessed whether the corresponding molecule was a diagnostic and prognostic biomarker. The study was performed patients (n = 22) diagnosed and treated with Ewing's sarcoma and osteosarcoma and in a control group of 22 healthy children who were matched for age, gender, and ethnicity with the patient group. The expression level of miR-218-5p in RNA samples from peripheral blood and tissue samples were analyzed using the RT-PCR and the expression level of miR-218-5p was evaluated by comparison with the levels in patients and healthy controls. The expression level of miR-218-5p was found to be statistically higher (3.33-fold, p = 0.006) in pediatric patients with sarcomas and when the target genes of miR-218-5p were investigated using the bioinformatics tools, the miR-218-5p was found as an important miRNA in cancer. In this study, the miR-218-5p was shown for the first time to have been highly expressed in the peripheral blood and tumor tissue of sarcoma patients. The results suggest that miR-218-5p can be used as a diagnostic and prognostic biomarker in sarcomas and will be evaluated as an important therapeutic target.

Biphasic co-detection of melanoma aneuploid tumor cells and tumor endothelial cells in guidance of specifying the field cancerized surgical excision margin and administering immunotherapy.

An optimum safety excision margin (EM) delineated by precise demarcation of field cancerization along with reliable biomarkers that enable predicting and timely evaluating patients' response to immunotherapy significantly impact effective management of melanoma. In this study, optimized biphasic "immunofluorescence staining integrated with fluorescence insitu hybridization" (iFISH) was conducted along the diagnosis-metastasis-treatment-cellular MRD axis to longitudinally co-detect a full spectrum of intact CD31- aneuploid tumor cells (TCs), CD31+ aneuploid tumor endothelial cells (TECs), viable and necrotic circulating TCs (CTCs) and circulating TECs (CTECs) expressing PD-L1, Ki67, p16 and Vimentin in unsliced specimens of the resected primary tumor, EM, dissected sentinel lymph nodes (SLNs) and peripheral blood in an early-stage melanoma patient. Numerous PD-L1+ aneuploid TCs and TECs were detected at the conventional safety EM (2 cm), quantitatively indicating the existence of a field cancerized EM for the first time. Contrary to highly heterogeneous PD-L1 expression and degrees of Chr8 aneuploidy in TCs and TECs in the primary lesions as well as CTCs and CTECs in peripheral blood, almost all TCs and TECs in SLNs and EM were homogeneously PD-L1+ haploid cells. Dynamic monitoring and cellular MRD assessment revealed that, in contrast to PD-L1+ CTCs being responsive to the immune checkpoint inhibitor (ICI-anti-PD-1), multiploid (≥pentasomy 8) PD-L1+ and Ki67+ CTECs were respectively resistant to ICI-sensitized T cells. In therapeutically stressed lymphatic and hematogenous metastatic cascades, stratified phenotypic and karyotypic profiling of iFISH tissue and liquid biopsied TCs, TECs, CTCs and CTECs in future large-cohort studies will enable appropriate re-specification of the optimal safety EM and distribution mapping of in-depth characterized, subcategorized target cells to help illustrate their metastatic relevance, ultimately improving risk stratification and clinical intervention of tumor progression, metastases, therapy resistance and cancer relapse.

Utility of TTMV-HPV DNA in resolving indeterminate findings during oropharyngeal cancer surveillance.

OBJECTIVES: Clinical and imaging examinations frequently have indeterminate results during cancer surveillance, which can lead to overtreatment and cause psychological and financial harm to the patient. This study addresses the critical need to enhance diagnostic precision and decision-making in the management of HPV-associated oropharyngeal cancer. This study evaluated the utility of tumor tissue-modified viral (TTMV)-HPV DNA to resolve indeterminate disease status following definitive treatment for HPV-associated oropharyngeal cancer. MATERIALS AND METHODS: In this retrospective cohort, patients treated for HPV-associated oropharyngeal cancer at eight U.S. institutions and who received one or more TTMV-HPV DNA tests during post-treatment surveillance between February 2020 and January 2022 were included. RESULTS: Among 543 patients, 210 patients (38.7%; 210/543) experienced one or more clinically indeterminate findings (CIFs) during surveillance, with 503 CIFs recorded. Of those patients with an "indeterminate" disease status at a point during surveillance, 79 were associated with contemporaneous TTMV-HPV DNA testing. TTMV-HPV DNA testing demonstrated high accuracy (97.5%; 77/79) in correctly determining recurrence status. Patients whose disease status was "indeterminate" at the time of a positive TTMV-HPV DNA test were clinically confirmed to recur faster than those whose disease status was "no evidence of disease." Only 3% of patients (17/543) experienced indeterminate TTMV-HPV DNA tests during surveillance. Discordance between TTMV-HPV DNA tests and clinical results was minimal, with only 0.6% (3/543) of patients showing positive tests without recurrence. CONCLUSION: Our findings support the utility of circulating TTMV-HPV DNA in resolving indeterminate disease status and informing the subsequent clinical course.

Comparison of the classifiers based on mRNA, microRNA and lncRNA expression and DNA methylation profiles for the tumor origin detection.

Background: Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA methylation profiles have been confirmed to be feasible and reliable to predict the tumor primary. However, few works have been performed to compare the performance of these classifiers based on different profiles. Methods: Using gene expression and DNA methylation profiles from The Cancer Genome Atlas (TCGA) project, eight machine learning methods were employed for the tumor tissue origin detection. We then evaluated the predictive performance using DNA methylation, mRNA, microRNA (miRNA) and long non-coding RNA (lncRNA) expression profiles in a comparative manner. A statistical method was introduced to select the most informative CpG sites. Results: We found that LASSO is the most predictive models based on various profiles. Further analyses indicated that the results derived from DNA methylation (overall accuracy: 97.77%) are better than those derived from mRNA expression (overall accuracy: 88.01%), microRNA expression (overall accuracy: 91.03%) and lncRNA expression (overall accuracy: 95.7%). It has been suggested that we can achieve an overall accuracy >90% using only 1,000 methylated CpG sites for prediction. Conclusion: In this work, we comprehensively evaluated the performance of classifiers based on different profiles for the tumor origin detection. Our findings demonstrated the effectiveness of DNA methylation as biomarker for tracing tumor tissue origin using LASSO and neural network.

Signal enhancement ratio of multi-phase contrast-enhanced MRI: an imaging biomarker for survival in pancreatic adenocarcinoma.

OBJECTIVES: To evaluate signal enhancement ratio (SER) for tissue characterization and prognosis stratification in pancreatic adenocarcinoma (PDAC), with quantitative histopathological analysis (QHA) as the reference standard. METHODS: This retrospective study included 277 PDAC patients who underwent multi-phase contrast-enhanced (CE) MRI and whole-slide imaging (WSI) from three centers (2015-2021). SER is defined as (SIlt - SIpre)/(SIea - SIpre), where SIpre, SIea, and SIlt represent the signal intensity of the tumor in pre-contrast, early-, and late post-contrast images, respectively. Deep-learning algorithms were implemented to quantify the stroma, epithelium, and lumen of PDAC on WSIs. Correlation, regression, and Bland-Altman analyses were utilized to investigate the associations between SER and QHA. The prognostic significance of SER on overall survival (OS) was evaluated using Cox regression analysis and Kaplan-Meier curves. RESULTS: The internal dataset comprised 159 patients, which was further divided into training, validation, and internal test datasets (n = 60, 41, and 58, respectively). Sixty-five and 53 patients were included in two external test datasets. Excluding lumen, SER demonstrated significant correlations with stroma (r = 0.29-0.74, all p < 0.001) and epithelium (r = -0.23 to -0.71, all p < 0.001) across a wide post-injection time window (range, 25-300 s). Bland-Altman analysis revealed a small bias between SER and QHA for quantifying stroma/epithelium in individual training, validation (all within ± 2%), and three test datasets (all within ± 4%). Moreover, SER-predicted low stromal proportion was independently associated with worse OS (HR = 1.84 (1.17-2.91), p = 0.009) in training and validation datasets, which remained significant across three combined test datasets (HR = 1.73 (1.25-2.41), p = 0.001). CONCLUSION: SER of multi-phase CE-MRI allows for tissue characterization and prognosis stratification in PDAC. CLINICAL RELEVANCE STATEMENT: The signal enhancement ratio of multi-phase CE-MRI can serve as a novel imaging biomarker for characterizing tissue composition and holds the potential for improving patient stratification and therapy in PDAC. KEY POINTS: Imaging biomarkers are needed to better characterize tumor tissue in pancreatic adenocarcinoma. Signal enhancement ratio (SER)-predicted stromal/epithelial proportion showed good agreement with histopathology measurements across three distinct centers. Signal enhancement ratio (SER)-predicted stromal proportion was demonstrated to be an independent prognostic factor for OS in PDAC.

Near-infrared fluorescent probe for sensitive detection and imaging of DNA G4s in living cells.

G-quadruplexs (G4s), four-stranded nucleic acid secondary structures, which formed by guanine-rich sequences play a vital role in human biological systems. Studies have shown that the formation of G4s is closely related to tumor development and apoptosis, which is considered as a new target for the development of anti-tumor drugs. Therefore, it is important to develop novel probes for G4s imaging. In this article, we engineered a near-infrared fluorescent probe (TOH) which can be activated by DNA G4s in living cells and tumor. TOH exhibits high selectivity to the structure of DNA G4s with the limit of detection for DNA G4s (Mito-0.5-2) is calculated to be 0.43 nM. Imaging studies of different cell lines revealed that the brighter fluorescence in cancer cell lines than in normal, indicating that DNA G4s maybe highly express in tumor cell lines. Simultaneously, TOH is also introduced into live tumor tissue imaging and found that the fluorescence intensity of tumor is the brightest relative to normal tissue, further validating the high expression of DNA G4s structures in tumor tissue. These features demonstrate TOH not only have the ability to image DNA G4 structures in real time, but also may have tumor diagnostic capabilities.

Morphological and Molecular Biological Characteristics of Experimental Rat Glioblastoma Tissue Strains Induced by Different Carcinogenic Chemicals.

Glioblastoma (GBM) is a highly aggressive human neoplasm with poor prognosis due to its malignancy and therapy resistance. To evaluate the efficacy of antitumor therapy, cell models are used most widely, but they are not as relevant to human GBMs as tissue models of gliomas, closely corresponding to human GBMs in cell heterogeneity. In this work, we compared three different tissue strains of rat GBM 101.8 (induced by DMBA), GBM 11-9-2, and GBM 14-4-5 (induced by ENU). MATERIALS AND METHODS: We estimated different gene expressions by qPCR-RT and conducted Western blotting and histological and morphometric analysis of three different tissue strains of rat GBM. RESULTS: GBM 101.8 was characterized by the shortest period of tumor growth and the greatest number of necroses and mitoses; overexpression of Abcb1, Sox2, Cdkn2a, Cyclin D, and Trp53; and downregulated expression of Vegfa, Pdgfra, and Pten; as well as a high level of HIF-1α protein content. GBM 11-9-2 and GBM 14-4-5 were relevant to low-grade gliomas and characterized by downregulated Mgmt expression; furthermore, a low content of CD133 protein was found in GBM 11-9-2. CONCLUSIONS: GBM 101.8 is a reliable model for further investigation due to its similarity to high-grade human GBMs, while GBM 11-9-2 and GBM 14-4-5 correspond to Grade 2-3 gliomas.

Unmasking the Metabolite Signature of Bladder Cancer: A Systematic Review.

Bladder cancer (BCa) research relying on Omics approaches has increased over the last few decades, improving the understanding of BCa pathology and contributing to a better molecular classification of BCa subtypes. To gain further insight into the molecular profile underlying the development of BCa, a systematic literature search was performed in PubMed until November 2023, following the PRISMA guidelines. This search enabled the identification of 25 experimental studies using mass spectrometry or nuclear magnetic resonance-based approaches to characterize the metabolite signature associated with BCa. A total of 1562 metabolites were identified to be altered by BCa in different types of samples. Urine samples displayed a higher likelihood of containing metabolites that are also present in bladder tumor tissue and cell line cultures. The data from these comparisons suggest that increased concentrations of L-isoleucine, L-carnitine, oleamide, palmitamide, arachidonic acid and glycoursodeoxycholic acid and decreased content of deoxycytidine, 5-aminolevulinic acid and pantothenic acid should be considered components of a BCa metabolome signature. Overall, molecular profiling of biological samples by metabolomics is a promising approach to identifying potential biomarkers for early diagnosis of different BCa subtypes. However, future studies are needed to understand its biological significance in the context of BCa and to validate its clinical application.

Expression of cyclin-dependent kinase 9 is positively correlated with the autophagy level in colon cancer.

BACKGROUND: Cyclin-dependent kinase 9 (CDK9) expression and autophagy in colorectal cancer (CRC) tissues has not been widely studied. CDK9, a key regulator of transcription, may influence the occurrence and progression of CRC. The expression of autophagy-related genes BECN1 and drug resistance factor ABCG2 may also play a role in CRC. Under normal physiological conditions, autophagy can inhibit tumorigenesis, but once a tumor forms, autophagy may promote tumor growth. Therefore, understanding the relationship between autophagy and cancer, particularly how autophagy promotes tumor growth after its formation, is a key motivation for this research. AIM: To investigate the relationship between CDK9 expression and autophagy in CRC, assess differences in autophagy between left and right colon cancer, and analyze the associations of autophagy-related genes with clinical features and prognosis. METHODS: We collected tumor tissues and paracarcinoma tissues from colon cancer patients with liver metastasis to observe the level of autophagy in tissues with high levels of CDK9 and low levels of CDK9. We also collected primary tissue from left and right colon cancer patients with liver metastasis to compare the autophagy levels and the expression of BECN1 and ABCG2 in the tumor and paracarcinoma tissues. RESULTS: The incidence of autophagy and the expression of BECN1 and ABCG2 were different in left and right colon cancer, and autophagy might be involved in the occurrence of chemotherapy resistance. Further analysis of the relationship between the expression of autophagy-related genes CDK9, ABCG2, and BECN1 and the clinical features and prognosis of colorectal cancer showed that the high expression of CDK9 indicated a poor prognosis in colorectal cancer. CONCLUSION: This study laid the foundation for further research on the combination of CDK9 inhibitors and autophagy inhibitors in the treatment of patients with CRC.

Addressing the Mechanical Interaction Between Cancer-Associated Fibroblasts and Cancer Cells by Laser Ablation.

Cells within a tumor interact by generating, transmitting, and sensing mechanical forces. Among all the cells of the tumor microenvironment, cancer-associated fibroblasts (CAFs) are a paradigmatic example of mechanical communication. In different steps of tumor progression, CAFs pull and push on cancer cells, regulating cancer cell migration, invasion, compartmentalization, and signaling. There is thus an increasing need to experimentally address mechanical interactions within a tumor. A common technique to measure these interactions is laser ablation. Cutting a tissue region with a high-power laser triggers a sudden tissue displacement whose direction and magnitude reveal the local mechanical stresses. In this chapter, we provide a detailed protocol to perform laser ablations in vitro and ex vivo. First, we describe how to prepare cocultures of primary CAFs and cancer cells and tumor explants. Then, we explain how to perform laser ablations in these two systems and how to analyze the induced tissue displacements using particle image velocimetry (PIV). Overall, we provide a workflow to perform, analyze, and interpret laser ablations to explore tumor mechanical interactions.

Optical Emission Spectroscopy for the Real-Time Identification of Malignant Breast Tissue.

Breast conserving resection with free margins is the gold standard treatment for early breast cancer recommended by guidelines worldwide. Therefore, reliable discrimination between normal and malignant tissue at the resection margins is essential. In this study, normal and abnormal tissue samples from breast cancer patients were characterized ex vivo by optical emission spectroscopy (OES) based on ionized atoms and molecules generated during electrosurgical treatment. The aim of the study was to determine spectroscopic features which are typical for healthy and neoplastic breast tissue allowing for future real-time tissue differentiation and margin assessment during breast cancer surgery. A total of 972 spectra generated by electrosurgical sparking on normal and abnormal tissue were used for support vector classifier (SVC) training. Specific spectroscopic features were selected for the classification of tissues in the included breast cancer patients. The average classification accuracy for all patients was 96.9%. Normal and abnormal breast tissue could be differentiated with a mean sensitivity of 94.8%, a specificity of 99.0%, a positive predictive value (PPV) of 99.1% and a negative predictive value (NPV) of 96.1%. For 66.6% patients all classifications reached 100%. Based on this convincing data, a future clinical application of OES-based tissue differentiation in breast cancer surgery seems to be feasible.

Liver Regeneration-Related Genes of Nontumor Liver Tissues Predict the Prognosis of Patients with Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most serious malignant tumors threatening human life with a high mortality rate. The liver regenerative capacity after hepatectomy in early-stage HCC patients is influenced by various factors, including surgical methods and energy metabolism. This study aims to provide a prognostic model based on genes related to liver regeneration that can predict the prognosis of non-tumor tissues in HCC patients. Patients and Methods: A total of 584 non-tumor tissues from HCC patients were collected from three independent databases. Kaplan-Meier survival curves were used to identify prognostic liver-regeneration genes. Subsequently, a prognostic indicator, designated as the Liver Regeneration score (LR score), was determined using single-sample gene set enrichment analysis (ssGSEA). Independent cohorts were used to verify the relationship between LR score and prognosis in non-tumor tissues of HCC patients. Furthermore, a liver regeneration-related model was established to validate key genes identified through LASSO Cox regression analysis. Results: We constructed a gene set comprising 24 liver regeneration-related genes, and the LR score was utilized to predict the prognosis of HCC patients based on its levels in non-tumor tissues. In non-tumor tissues of HCC patients, higher LR scores were associated with improved prognosis. Higher LR scores in non-tumor tissues indicate improved liver metabolism in HCC patients, revealed by Enrichment analysis. LASSO Cox regression analysis identified two key genes, DHTKD1 (dehydrogenase E1 and transketolase domain containing 1) and PHYH (phytanoyl-CoA 2-hydroxylase), and higher expression levels of these genes in non-tumor tissues were correlated with better prognosis. The expression levels of these two genes also changed corresponding to the progression of liver regeneration. Conclusion: In summary, our study has introduced a novel LR gene signature for HCC patients, providing a predictive model for estimating clinical prognosis from non-tumor tissues. The LR score demonstrates promise as a reliable indicator for predicting overall survival in HCC.

Expression study of microRNA cluster on chromosome 19 (C19MC) in tumor tissue and serum of breast cancer patient.

BACKGROUND: Breast cancer (BC) is the most prevalent cancer among females worldwide. Numerous studies suggest that specific RNAs play a crucial role in carcinogenesis. The primate-specific microRNA gene cluster located on the 19q27.3 region of chromosome 19 (C19MC) could potentially regulate tumor cell proliferation, migration, and invasion. OBJECTIVE: The objective of this study was to compare the expression of miRNAs from the C19MC cluster in breast cancer tumor and non-tumor samples, as well as in the serum of individuals affected by BC and healthy individuals. METHODS: Peripheral blood was collected from 100 BC patients and 100 healthy individuals, and breast cancer samples including tumor and margin tissues were obtained. After RNA extraction, Real-time PCR was employed to investigate the expression of C19MC, specifically mir-515-1, mir-515-2, mir-516-A1, mir-516-A2, mir-516-B1, mir-516-B2, mir-517-A, mir-517-B, mir-517-C, and mir-518-A1, in the serum and tissue of BC patients and tumor margins. Statistical analyses and ROC curves were generated using GraphPad Prism software (v8.04), with a significance level set at p < 0.05. RESULTS: Our findings demonstrate a strong correlation between high expression of all C19MC miRNAs mentioned, except for mir-517-B, mir-517-C and mir- 518 in BC. These miRNAs show potential as notable non-invasive tumor markers. CONCLUSION: The data obtained from our study support the overall impact of C19MC miRNAs in BC detection and emphasize the potential role of several C19MC members in this process.