Simulation-Assisted Localized DNA Logical Circuits for Cancer Biomarkers Detection and Imaging.

DNA-based nanodevices equipped with localized modules have been promising probes for biomarker detection. Such devices heavily rely on the intramolecular hybridization reaction. However, there is a lack of mechanistic insights into this reaction that limits the sensing speed and sensitivity. A coarse-grained model is utilized to simulate the intramolecular hybridization of localized DNA circuits (LDCs) not only optimizing the performance, but also providing mechanistic insights into the hybridization reaction. The simulation guided-LDCs enable the detection of multiple biomarkers with high sensitivity and rapid speed showing good consistency with the simulation. Fluorescence assays demonstrate that the simulation-guided LDC shows an enhanced sensitivity up to 9.3 times higher than that of the same probes without localization. The detection limits of ATP, miRNA, and APE1 reach 0.14 mM, 0.68 pM, and 0.0074 U mL-1 , respectively. The selected LDC is operated in live cells with good success in simultaneously detecting the biomarkers and discriminating between cancer cells and normal cells. LDC is successfully applied to detect the biomarkers in cancer tissues from patients, allowing the discrimination of cancer/adjacent/normal tissues. This work herein presents a design workflow for DNA nanodevices holding great potential for expanding the applications of DNA nanotechnology in diagnostics and therapeutics.

Microbiome composition indicate dysbiosis and lower richness in tumor breast tissues compared to healthy adjacent paired tissue, within the same women.

BACKGROUND: Breast cancer (BC) is the most common malignancy in women, in whom it reaches 20% of the total neoplasia incidence. Most BCs are considered sporadic and a number of factors, including familiarity, age, hormonal cycles and diet, have been reported to be BC risk factors. Also the gut microbiota plays a role in breast cancer development. In fact, its imbalance has been associated to various human diseases including cancer although a consequential cause-effect phenomenon has never been proven. METHODS: The aim of this work was to characterize the breast tissue microbiome in 34 women affected by BC using an NGS-based method, and analyzing the tumoral and the adjacent non-tumoral tissue of each patient. RESULTS: The healthy and tumor tissues differed in bacterial composition and richness: the number of Amplicon Sequence Variants (ASVs) was higher in healthy tissues than in tumor tissues (p = 0.001). Moreover, our analyses, able to investigate from phylum down to species taxa for each sample, revealed major differences in the two richest phyla, namely, Proteobacteria and Actinobacteria. Notably, the levels of Actinobacteria and Proteobacteria were, respectively, higher and lower in healthy with respect to tumor tissues. CONCLUSIONS: Our study provides information about the breast tissue microbial composition, as compared with very closely adjacent healthy tissue (paired samples within the same woman); the differences found are such to have possible diagnostic and therapeutic implications; further studies are necessary to clarify if the differences found in the breast tissue microbiome are simply an association or a concausative pathogenetic effect in BC. A comparison of different results on similar studies seems not to assess a universal microbiome signature, but single ones depending on the environmental cohorts' locations.

Deep Learning for Chondrogenic Tumor Classification through Wavelet Transform of Raman Spectra.

The grading of cancer tissues is still one of the main challenges for pathologists. The development of enhanced analysis strategies hence becomes crucial to accurately identify and further deal with each individual case. Raman spectroscopy (RS) is a promising tool for the classification of tumor tissues as it allows us to obtain the biochemical maps of the tissues under analysis and to observe their evolution in terms of biomolecules, proteins, lipid structures, DNA, vitamins, and so on. However, its potential could be further improved by providing a classification system which would be able to recognize the sample tumor category by taking as input the raw Raman spectroscopy signal; this could provide more reliable responses in shorter time scales and could reduce or eliminate false-positive or -negative diagnoses. Deep Learning techniques have become ubiquitous in recent years, with models able to perform classification with high accuracy in most diverse fields of research, e.g., natural language processing, computer vision, medical imaging. However, deep models often rely on huge labeled datasets to produce reasonable accuracy, otherwise occurring in overfitting issues when the training data is insufficient. In this paper, we propose a chondrogenic tumor CLAssification through wavelet transform of RAman spectra (CLARA), which is able to classify with high accuracy Raman spectra obtained from bone tissues. CLARA recognizes and grades the tumors in the evaluated dataset with 97% accuracy by exploiting a classification pipeline consisting of the division of the original task in two binary classification steps, where the first is performed on the original RS signals while the latter is accomplished through the use of a hybrid temporal-frequency 2D transform.

Photodynamic therapy in breast cancer treatment.

Breast cancer is a serious public problem in modern society. Photodynamic therapy (PDT) is increasingly used in modern medicine. Currently, PDT is an innovative method of treating breast cancer. Irreversible damage to neoplastic tissues is associated with the use of physicochemical processes. Generating cytotoxic reactive oxygen species [singlet oxygen (1O2)] is leading to tumor cell death. At the same time, valuable information can be extracted from breast cancer cells. Photogenerated 1O2 is the major factor responsible for cell necrosis during PDT. 1O2 can react rapidly intracellularly with all organic substances. The use of photodynamic therapy on tissues in vitro creates conditions for testing various types of solutions and implementing them in in vivo treatment. This article is a review of recent advances in PDT for treatment of breast cancer. PDT is a novel cancer diagnostic and cancer treatment therapy. Therefore, an understanding of the possibility to generate a toxic form of 1O2 is necessary. The knowledge gained from the basics of PDT in vitro can be useful in biomedical applications in vivo. The current literature mentions PDT in the treatment of cancers located very deep within the human body. Therefore, the development of agents used to deliver 1O2 to the deep cancerous tissue is a new challenge which can have an efficient impact on this discipline. This review covers the literature between 2000-2022.

Benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers: a case study of pancreatic cancer.

Pancreatic cancer is a highly malignant tumor of the digestive tract that is difficult to diagnose and treat. It is more common in developed countries and has become one of the main causes of death in some countries and regions. Currently, pancreatic cancer generally has a poor prognosis, partly due to the lack of symptoms in the early stages of pancreatic cancer. Therefore, most cases are diagnosed at advanced stage. With the continuous in-depth research of glycoproteomics in precision medical diagnosis, there have been some reports on quantitative analysis of cancer-related cells, plasma or tissues to find specific biomarkers for targeted therapy. This research is based on the developed complete N-linked glycopeptide database search engine GPSeeker, combined with liquid-mass spectrometry and stable diethyl isotope labeling, providing a benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers. With spectrum-level FDR ≤1%, 20,038 intact N-Glycopeptides corresponding to 4518 peptide backbones, 228 N-glycan monosaccharide compositions 1026 N-glycan putative structures, 4460 N-glycosites and 3437 intact N-glycoproteins were identified. With the criteria of ≥1.5-fold change and p value<0.05, 52 differentially expressed intact N-glycopeptides (DEGPs) were found in pancreatic cancer tussues relative to control, where 38 up-regulated and 14 down-regulated, respectively.

PAX8, an Emerging Player in Ovarian Cancer.

Ovarian Cancer is one of the most lethal and widespread gynecological malignancies. It is the seventh leading cause of all cancer deaths worldwide. High-Grade Serous Cancer (HGSC), the most commonly occurring subtype, alone contributes to 70% of all ovarian cancer deaths. This is mainly attributed to the complete lack of symptoms during the early stages of the disease and absence of an early diagnostic marker.PAX8 is emerging as an important histological marker for most of the epithelial ovarian cancers, as it is expressed in about 90% of malignant ovarian cancers, specifically in HGSC. PAX8 is a member of the Paired-Box gene family (PAX1-9) of transcription factors whose expression is tightly controlled temporally and spatially. The PAX genes are well known for their role in embryonic development and their expression continues to persist in some adult tissues. PAX8 is required for the normal development of Müllerian duct that includes Fallopian tube, uterus, cervix, and upper part of vagina. In adults, it is expressed in the Fallopian tube and uterine epithelium and not in the ovarian epithelium. Considering the recent studies that predict the events preceding the tumorigenesis of HGSC from the Fallopian tube, PAX8 appears to have an important role in the development of ovarian cancer.In this chapter, we review some of the published findings to highlight the significance of PAX8 as an important marker and an emerging player in the pathogenesis of ovarian cancer. We also discuss regarding the future perspectives of PAX8 wherein it could contribute to the betterment of ovarian cancer diagnosis and treatment.

The Spectroscopic Similarity between Breast Cancer Tissues and Lymph Nodes Obtained from Patients with and without Recurrence: A Preliminary Study.

Lymph nodes (LNs) play a very important role in the spread of cancer cells. Moreover, it was noticed that the morphology and chemical composition of the LNs change in the course of cancer development. Therefore, finding and monitoring similarities between these characteristics of the LNs and tumor tissues are essential to improve diagnostics and therapy of this dreadful disease. In the present study, we used Raman and Fourier transform infrared (FTIR) spectroscopies to compare the chemical composition of the breast cancer tissues and LNs collected from women without (I group-4 patients) and with (II group-4 patients) recurrence. It was shown that the similarity of the chemical composition of the breast tissues and LNs is typical for the II group of the patients. The average Raman spectrum of the breast cancer tissues from the I group was not characterized by vibrations in the 800-1000 cm-1 region originating from collagen and carbohydrates, which are typical for tumor-affected breast tissues. At the same time, this spectrum contains peaks at 1029 cm-1, corresponding to PO2- from DNA, RNA and phospholipids, and 1520 cm-1, which have been observed in normal breast tissues before. It was shown that Raman bands of the average LN spectrum of the II group associated with proteins and carbohydrates are more intensive than those of the breast tissues spectrum. The intensity of the Raman spectra collected from the samples of the II group is almost three times higher compared to the I group. The vibrations of carbohydrates and amide III are much more intensive in the II group's case. The Raman spectra of the breast cancer tissues and LNs of the II group's samples do not contain bands (e.g., 1520 cm-1) found in the Raman spectra of the normal breast tissues elsewhere. FTIR spectra of the LNs of the I group's women showed a lower level of vibrations corresponding to functional group building nucleic acid, collagen, carbohydrates, and proteins in comparison with the breast cancer tissues. Pearson's correlation test showed positive and more significant interplay between the nature of the breast tissues and LN spectra obtained for the II group of patients than that in the I group's spectra. Moreover, principal component analysis (PCA) showed that it is possible to distinguish Raman and FTIR spectra of the breast cancer tissues and LNs collected from women without recurrence of the disease.

Characterization of human frataxin missense variants in cancer tissues.

Human frataxin is an iron-binding protein involved in the mitochondrial iron-sulfur (Fe-S) clusters assembly, a process fundamental for the functional activity of mitochondrial proteins. Decreased level of frataxin expression is associated with the neurodegenerative disease Friedreich ataxia. Defective function of frataxin may cause defects in mitochondria, leading to increased tumorigenesis. Tumor-initiating cells show higher iron uptake, a decrease in iron storage and a reduced Fe-S clusters synthesis and utilization. In this study, we selected, from COSMIC database, the somatic human frataxin missense variants found in cancer tissues p.D104G, p.A107V, p.F109L, p.Y123S, p.S161I, p.W173C, p.S181F, and p.S202F to analyze the effect of the single amino acid substitutions on frataxin structure, function, and stability. The spectral properties, the thermodynamic and the kinetic stability, as well as the molecular dynamics of the frataxin missense variants found in cancer tissues point to local changes confined to the environment of the mutated residues. The global fold of the variants is not altered by the amino acid substitutions; however, some of the variants show a decreased stability and a decreased functional activity in comparison with that of the wild-type protein.

The Hedgehog signalling pathway mediates drug response of MCF-7 mammosphere cells in breast cancer patients.

BCSCs (breast cancer stem cells) have been shown to be resistant to chemotherapy. However, the mechanisms underlying BCSC-mediated chemoresistance remain poorly understood. The Hh (Hedgehog) pathway is important in the stemness maintenance of CSCs. Nonetheless, it is unknown whether the Hh pathway is involved in BCSC-mediated chemoresistance. In the present study, we cultured breast cancer MCF-7 cells in suspension in serum-free medium to obtain BCSC-enriched MCF-7 MS (MCF-7 mammosphere) cells. We showed that MCF-7 MS cells are sensitive to salinomycin, but not paclitaxel, distinct from parent MCF-7 cells. The expression of the critical components of Hh pathway, i.e., PTCH (Patched), SMO (Smoothened), Gli1 and Gli2, was significantly up-regulated in MCF-7 MS cells; salinomycin, but not paclitaxel, treatment caused a remarkable decrease in expression of those genes in MCF-7 MS cells, but not in MCF-7 cells. Salinomycin, but not paclitaxel, increased apoptosis, decreased the migration capacity of MCF-7 MS cells, accompanied by a decreased expression of c-Myc, Bcl-2 and Snail, the target genes of the Hh pathway. The salinomycin-induced cytotoxic effect could be blocked by Shh (Sonic Hedgehog)-mediated Hh signalling activation. Inhibition of the Hh pathway by cyclopamine could sensitize MCF-7 MS cells to paclitaxel. In addition, salinomycin, but not paclitaxel, significantly reduced the tumour growth, accompanied by decreased expression of PTCH, SMO, Gli1 and Gli2 in xenograft tumours. Furthermore, the expression of SMO and Gli1 was positively correlated with the expression of CD44+ / CD24-, and the expression of SMO and Gli1 in CD44+ / CD24- tissues was associated with a significantly shorter OS (overall survival) and DFS (disease-free survival) in breast cancer patients receiving chemotherapy.

Profiling of metabolic dysregulation in ovarian cancer tissues and biofluids.

Ovarian cancer (OC) is the most lethal gynecologic cancer, mainly due to late diagnosis with widespread peritoneal spread at first presentation. We performed metabolomic analyses of ovarian and paired control tissues using capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry to understand its metabolomic dysregulation. Of the 130 quantified metabolites, 96 metabolites of glycometabolism, including glycolysis, tricarboxylic acid cycles, urea cycles, and one-carbon metabolites, showed significant differences between the samples. To evaluate the local and systemic metabolomic differences in OC, we also analyzed low or non-invasively available biofluids, including plasma, urine, and saliva collected from patients with OC and benign gynecological diseases. All biofluids and tissue samples showed consistently elevated concentrations of N1,N12-diacetylspermine compared to controls. Four metabolites, polyamines, and betaine, were significantly and consistently elevated in both plasma and tissue samples. These data indicate that plasma metabolic dysregulation, which the most reflected by those of OC tissues. Our metabolomic profiles contribute to our understanding of metabolomic abnormalities in OC and their effects on biofluids.

The mRNA of solute carrier family 22, member 17 (SLC22A17) plays the potential diagnostic and prognostic role in advantage non-small cell lung cancer patients.

This study aims to evaluate the mRNA levels of solute carrier family 22, member 17 (SLC22A17) and its potential clinical value as a diagnostic and prognostic biomarker in non-small cell lung cancer. This prospective study measured SLC22A17 mRNA levels in lung cancer and paracancer tissues using quantitative reverse transcription-polymerase chain reaction (PCR). The levels of SLC22A17 mRNA in plasma samples from healthy control subjects and patients with lung cancer were also measured. The association between SLC22A17 mRNA levels in plasma and clinicopathological characteristics was determined. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic value of SLC22A17 in plasma. Survival curve analysis was performed using the Kaplan-Meier method. SLC22A17 mRNA levels were significantly higher in lung cancer samples than in the paired paracancerous tissues. Plasma SLC22A17 mRNA levels were also significantly higher in patients with lung cancer than in healthy controls. The COX analysis indicated that there was a significant correlation between elevated plasma SLC22A17 mRNA levels and lymph node metastasis, distant metastasis, and TNM stage. Furthermore, the ROC curve analysis demonstrated that plasma SLC22A17 had high diagnostic value. High plasma SLC22A17 mRNA levels are associated with a significantly shorter survival time. SLC22A17 is upregulated in lung cancer and may serve as a novel diagnostic and prognostic biomarker.

Machine learning- a new paradigm in nanoparticle-mediated drug delivery to cancerous tissues through the human cardiovascular system enhanced by magnetic field.

Nanoparticle-mediated drug delivery offers a promising approach to targeted cancer therapy, leveraging the ability of nanoparticles to deliver therapeutic agents directly to cancerous tissues with minimal impact on surrounding healthy cells. The presence of these nanoparticles is governed by a concentration equation, which accounts for the diffusion, convection, and reaction of the nanoparticles with the blood components. It is well-known that whenever a disease or infection occurs in a human, in 80% of cases a rise in the concentration of hydrogen peroxide in the blood occurs. This is the reason why blood is assumed to contain hydrogen peroxide (in the present study), which is a biomarker of oxidative stress and inflammation. This study explores the integration of machine learning (ML) techniques into the optimization of drug delivery processes within the human cardiovascular system, focusing on the enhancement of these processes through the application of magnetic fields. By employing ML algorithms, we analyze and predict the behavior of nanoparticles as they navigate the complex fluid dynamics of the cardiovascular system, particularly under the influence of an external magnetic field. The predictive power of ML models enables the precise control of nanoparticle trajectories, optimizing their accumulation in cancerous tissues and improving the efficacy of the drug delivery system. The findings of this study demonstrate that ML-enhanced magnetic targeting can significantly enhance the precision and effectiveness of nanoparticle-mediated drug delivery, offering a new paradigm in cancer treatment strategies. This approach has the potential to revolutionize the field by providing personalized and highly efficient therapeutic solutions for cancer patients.

Systematic pan-cancer analyses of the potential function of the Golgi scaffold protein PAQR3.

Progesterone and AdipoQ Receptor 3 (PAQR3) is a member of the AdipoQ receptor. Our previous studies have found that PAQR3 plays a role as a candidate inhibitor in cardiac adenocarcinoma, breast cancer, gastric cancer and colorectal cancer, but the systematic analysis of PAQR3 in tumors is currently lacking. The objective of this study was to investigate the prognostic and therapeutic value of PAQR3 in 31 tumors. Through the analysis of TCGA, UALCAN, GEO, GEPIA2, TIMER, Kaplan-Meier plotter, TISIDB and other databases, it was found that the expression level of PAQR3 changed significantly in different tumor types, and the expression level of Neuroblastoma was very high. And the level of Prostate adenocarcinoma is low. In addition, the expression level of PAQR3 in Cholangiocarcinoma, Esophageal carcinoma, Head and neck squamous carcinoma, Liver Hepatocellular Carcinoma, Lung Adenocarcinoma and Lung squamous cell carcinoma was significantly higher than that in normal tissues. However, the expression level of PAQR3 in Breast Cancer, Kidney Renal Clear Cell Carcinoma, Kidney renal papillary cell carcinoma, Prostate Adenocarcinoma, Rectum Adenocarcinoma, Thyroid Cancer and Uterine Corpus Endometrial Carcinoma was lower than that in normal tissues. Subsequently, we explored the value of PAQR3 as a prognostic indicator of cancer. In Acute Myeloid Leukemia, Lower-grade Glioma and Glioblastoma, Pediatric Low-grade Gliomas, Kidney Chromophobe, and Thyroid Cancer, PAQR3 expression was positively correlated with OS and DSS, while in Rectum Adenocarcinoma, PAQR3 expression was negatively correlated with OS. PAQR3 high expression group Lower-grade Glioma and Glioblastoma, Pediatric Low-grade Gliomas, Uveal Melanoma, Kidney Chromophobe and DFI were positively correlated. PAQR3 can be used as a risk factor for the prognosis of multiple tumors. Then, we discussed the correlation between PAQR3 and immunology, and found that PAQR3 has a wide range of mutations in various tumor types, the most common mutation type is missense mutation, and common mutation types also include amplification, depth deletion, splicing, truncation and structural variation. Among the tumor samples with PAQR3 alterations, mutation occurred in all tumor samples except prostate adenocarcinoma and adrenal cortical carcinoma, head and neck squamous cell carcinoma, brain low-grade glioma, and kidney clear cell carcinoma, while esophageal adenocarcinoma had the highest total alteration frequency. PAQR3 was strongly associated with CNV in 18 tumors, particularly in Ovarian cancer, Lung squamous cell carcinoma, and Adenoid cystic carcinoma. On the other hand, PAQR3 has a higher SNV frequency in Uterine Corpus Endometrial Carcinoma, Skin Cutaneous Melanoma and Lung Adenocarcinoma, among which Uterine Corpus Endometrial Carcinoma has the highest SNV frequency. These results showed that PAQR3 expression levels were significantly correlated with tumor mutation load, microsatellite instability, neoantigens, and purity. In summary, PAQR3 can affect the tumor microenvironment and has potential for chemotherapy. Finally, we investigated the role of PAQR3 in tumor resistance and found that the expression of PAQR3 affects the efficacy of multiple chemotherapy drugs. Based on these studies, we found that PAQR3 plays an important role in cancer and has potential in tumor diagnosis and prognosis.

Translational Research for Identifying Potential Early-stage Prostate Cancer Biomarkers.

BACKGROUND/AIM: Prostate cancer (PCa) is one of the most common types of cancer in men. Prostate-specific antigen (PSA) is currently the only biomarker used to screen for the risk of developing PCa. Because PSA tests may show false positives, identifying novel PCa-specific biomarkers would improve prediction and diagnosis at an early stage. Previously, we identified a number of genes/microRNAs (miRNAs) in prostate tissue as potential biomarkers of chronic prostatitis in a rat model of chemical-induced prostatitis. The current study aimed to evaluate their potential for use as translational, diagnostic markers in humans. MATERIALS AND METHODS: We performed quantitative polymerase chain reaction analysis using pathologically clear (normal) or confirmed PCa tissue samples from the same patients (N=18 per group). RESULTS: Levels (relative fold changes) of bone morphogenetic protein 7 (BMP7) transcripts were significantly lower in PCa tissues, compared with clear tissues, in a paired t-test (p=0.0075). Although neural cell adhesion molecule 1 (NCAM1) transcripts tended to be altered in PCa tissues, statistically insignificant differences were observed (p=0.0521). No statistically significant differences were observed for the other genes/miRNAs analyzed in PCa tissues due to a high degree of individual variance in expression. CONCLUSION: Similar to the results previously observed in rats, changes in the levels of BMP7 and NCAM1 transcripts were evident in human PCa tissues, suggesting that these genes may serve as potential diagnostic biomarkers during the early stages of PCa. Further studies are needed to determine the potential use of these molecules as biomarkers.

Impact of Sample Processing and Storage Conditions on RNA Quality of Fresh-Frozen Cancer Tissues.

Background: A biobank is a central resource that supports basic and clinical research. RNA quality of fresh-frozen tissue specimens in the biobank is highly associated with the success of downstream applications. Therefore, it is very important to evaluate the impact of tissue processing and storage conditions on RNA quality. Methods: A total of 238 surgically removed tissue specimens, including esophagus, lung, liver, stomach, colon, and rectal cancer, were used to evaluate RNA quality. Two tissue homogenization methods, manual and TissueLyser, were compared and the impacts of temperature fluctuation, tissue types, storage period, and clinicopathological parameters on RNA quality were analyzed. Results: RNA integrity was not influenced by tissue homogenization methods and tissue types. However, RNA integrity number (RIN) values were significantly correlated with temperature fluctuation. When the power of a -80°C freezer was cut off, RNA integrity of frozen tissues was not significantly affected until the temperature increased to 0°C. When the temperature rose to room temperature and remained for 4 hours, RNA integrity was almost completely destroyed. In addition, various cancer tissues with short-term storage at -80°C (<5 years) or high tumor differentiation had higher RINs. Conclusions: Tissue processing and storage conditions affected RNA quality of fresh-frozen cancer tissues. It is necessary to keep storage temperature stable and keep specimens at ultralow temperatures during homogenization. Also, for a biobank containing multiple types of cancer tissue samples, it is better to store them in liquid nitrogen if the storage duration is more than 5 years.

Integrated transcriptomics, proteomics, and functional analysis to characterize the tissue-specific small extracellular vesicle network of breast cancer.

Small extracellular vesicles (sEVs) are essential mediators of intercellular communication within the tumor microenvironment (TME). Although the biological features of sEVs have been characterized based on in vitro culture models, recent evidence indicates significant differences between sEVs derived from tissue and those derived from in vitro models in terms of both content and biological function. However, comprehensive comparisons and functional analyses are still limited. Here, we collected sEVs from breast cancer tissues (T-sEVs), paired normal tissues (N-sEVs), corresponding plasma (B-sEVs), and tumor organoids (O-sEVs) to characterize their transcriptomic and proteomic profiles. We identified the actual cancer-specific sEV signatures characterized by enriched cell adhesion and immunomodulatory molecules. Furthermore, we revealed the significant contribution of cancer-associated fibroblasts in the sEV network within the TME. In vitro model-derived sEVs did not entirely inherit the extracellular matrix- and immunity regulation-related features of T-sEVs. Also, we demonstrated the greater immunostimulatory ability of T-sEVs on macrophages and CD8+ T cells compared to O-sEVs. Moreover, certain sEV biomarkers derived from noncancer cells in the circulation exhibited promising diagnostic potential. This study provides valuable insights into the functional characteristics of tumor tissue-derived sEVs, highlighting their potential as diagnostic markers and therapeutic agents for breast cancer.

Searching for SARS-CoV-2 in Cancer Tissues: Results of an Extensive Methodologic Approach based on ACE2 and Furin Expression.

SARS-CoV-2 pandemics have been massively characterized on a global scale by the rapid generation of in-depth genomic information. The main entry gate of SARS-CoV-2 in human cells is the angiotensin-converting enzyme 2 (ACE2) receptor. The expression of this protein has been reported in several human tissues, suggesting a correlation between SARS-CoV-2 organotropism and ACE2 distribution. In this study, we selected (a series of) 90 patients who were submitted to surgery for tumor removal between the beginning of the SARS-CoV-2 pandemic and the closure of operating rooms (by the end of March 2020) in two different countries-Portugal and Brazil. We evaluated the expressions of ACE2 and furin (another important factor for virus internalization) in colon (n = 60), gastric (n = 19), and thyroid (n = 11) carcinomas. In a subseries of cases with PCR results for SARS-CoV-2 detection in the peri-operatory window (n = 18), we performed different methodological approaches for viral detections in patient tumor samples. Our results show that colon and gastric carcinomas display favorable microenvironments to SARS-CoV-2 tropism, presenting high expression levels of ACE2 and furin. From the subseries of 18 cases, 11 tested positive via PCR detection performed in tumor blocks; however, a direct association between the ACE2 expression and SARS-CoV-2 infection was not demonstrated in cancer cells using histology-based techniques, such as immunohistochemistry or in situ hybridization. This study raises the possibility of ACE2-mediated viral tropism in cancer tissues to be clarified in future studies.

Roles of Wnt/ß-catenin signaling pathway related microRNAs in esophageal cancer.

MicroRNAs (miRNAs) are endogenous, noncoding, single-stranded small RNAs that regulate expression of tumor suppressor genes and oncogenes and are involved in almost all tumor-related processes. MiRNA dysregulation plays an important role in the occurrence and development of esophageal cancer through specific signal pathways, including the Wnt/ß-catenin signaling pathway, and is closely related to the malignant characteristics of esophageal cancer. The interaction between miRNAs and the Wnt/ß-catenin signaling pathway, which is specifically expressed in esophageal cancer tissues, shows potential as a new biomarker and therapeutic target. This article reviews the role of miRNAs related to the Wnt pathway in the carcinogenesis of esophageal carcinoma and its role in Wnt signal transduction. The content of this review can be used as the basis for formulating or improving the treatment strategy of esophageal cancer.

Expression of miR-92a in colon cancer tissues and its correlation with clinicopathologic features and prognosis.

OBJECTIVE: This study analyzed the expression of miR-92a in colon tumor tissues and its correlation with disease clinicopathologic features and prognosis. METHODS: 83 cases of colorectal cancer tissues and paracancerous normal tissues acquired from colon cancer resection surgery during January 2015-January 2017 were collected. We detected the expression of miR-92a in cancer tissues and paracancerous tissues by qRT-PCR, and analyzed the correlation between the relative expression of miR-92 in colon cancer tissues and clinicopathologic characteristics, progression-free survival (PFS), and overall survival (OS) of the patients accordingly. RESULTS: The relative expression level of miR-92a in colon cancer tissues was higher than of paracancerous tissues (P<0.05). Relative expression of miR-92a in cancer was correlated with the degree of differentiation, TNM stage, and lymph node metastasis (P<0.05), while uncorrelated with gender, age, tumor diameter, or invasion depth (P>0.05). Patients with low expression of miR-92a had superior PFS to the control group (P>0.05) and better OS (P<0.05). CONCLUSION: Abnormally high expression of miR-92a occurs in colon tumor tissues. Its expression is related to the occurrence, progression, and prognosis of patients with colon cancer. It may be a marker for diagnosis, treatment, and prognosis of disease.

Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues.

Failure to adequately characterize cell lines, and understand the differences between in vitro and in vivo biology, can have serious consequences on the translatability of in vitro scientific studies to human clinical trials. This project focuses on the Michigan Cancer Foundation-7 (MCF-7) cells, a human breast adenocarcinoma cell line that is commonly used for in vitro cancer research, with over 42,000 publications in PubMed. In this study, we explore the key similarities and differences in gene expression networks of MCF-7 cell lines compared to human breast cancer tissues. We used two MCF-7 data sets, one data set collected by ARCHS4 including 1032 samples and one data set from Gene Expression Omnibus GSE50705 with 88 estradiol-treated MCF-7 samples. The human breast invasive ductal carcinoma (BRCA) data set came from The Cancer Genome Atlas, including 1212 breast tissue samples. Weighted Gene Correlation Network Analysis (WGCNA) and functional annotations of the data showed that MCF-7 cells and human breast tissues have only minimal similarity in biological processes, although some fundamental functions, such as cell cycle, are conserved. Scaled connectivity-a network topology metric-also showed drastic differences in the behavior of genes between MCF-7 and BRCA data sets. Finally, we used canSAR to compute ligand-based druggability scores of genes in the data sets, and our results suggested that using MCF-7 to study breast cancer may lead to missing important gene targets. Our comparison of the networks of MCF-7 and human breast cancer highlights the nuances of using MCF-7 to study human breast cancer and can contribute to better experimental design and result interpretation of study involving this cell line.