Tumour immune characterisation of primary triple-negative breast cancer using automated image quantification of immunohistochemistry-stained immune cells.

The tumour immune microenvironment (TIME) in breast cancer is acknowledged with an increasing role in treatment response and prognosis. With a growing number of immune markers analysed, digital image analysis may facilitate broader TIME understanding, even in single-plex IHC data. To facilitate analyses of the latter an open-source image analysis pipeline, Tissue microarray MArker Quantification (TMArQ), was developed and applied to single-plex stainings for p53, CD3, CD4, CD8, CD20, CD68, FOXP3, and PD-L1 (SP142 antibody) in a 218-patient triple negative breast cancer (TNBC) cohort with complementary pathology scorings, clinicopathological, whole genome sequencing, and RNA-sequencing data. TMArQ's cell counts for analysed immune markers were on par with results from alternative methods and consistent with both estimates from human pathology review, different quantifications and classifications derived from RNA-sequencing as well as known prognostic patterns of immune response in TNBC. The digital cell counts demonstrated how immune markers are coexpressed in the TIME when considering TNBC molecular subtypes and DNA repair deficiency, and how combination of immune status with DNA repair deficiency status can improve the prognostic stratification in chemotherapy treated patients. These results underscore the value and potential of integrating TIME and specific tumour intrinsic alterations/phenotypes for the molecular understanding of TNBC.

Full-Automatic High-Efficiency Mueller Matrix Microscopy Imaging for Tissue Microarray Inspection.

This paper proposes a full-automatic high-efficiency Mueller matrix microscopic imaging (MMMI) system based on the tissue microarray (TMA) for cancer inspection for the first time. By performing a polar decomposition on the sample's Mueller matrix (MM) obtained by a transmissive MMMI system we established, the linear phase retardance equivalent waveplate fast-axis azimuth and the linear phase retardance are obtained for distinguishing the cancerous tissues from the normal ones based on the differences in their polarization characteristics, where three analyses methods including statistical analysis, the gray-level co-occurrence matrix analysis (GLCM) and the Tamura image processing method (TIPM) are used. Previous MMMI medical diagnostics typically utilized discrete slices for inspection under a high-magnification objective (20×-50×) with a small field of view, while we use the TMA under a low-magnification objective (5×) with a large field of view. Experimental results indicate that MMMI based on TMA can effectively analyze the pathological variations in biological tissues, inspect cancerous cervical tissues, and thus contribute to the diagnosis of postoperative cancer biopsies. Such an inspection method, using a large number of samples within a TMA, is beneficial for obtaining consistent findings and good reproducibility.

Detailed Profiling of the Tumor Microenvironment in Ethnic Breast Cancer, Using Tissue Microarrays and Multiplex Immunofluorescence.

Breast cancer poses a global health challenge, yet the influence of ethnicity on the tumor microenvironment (TME) remains understudied. In this investigation, we examined immune cell infiltration in 230 breast cancer samples, emphasizing diverse ethnic populations. Leveraging tissue microarrays (TMAs) and core samples, we applied multiplex immunofluorescence (mIF) to dissect immune cell subtypes across TME regions. Our analysis revealed distinct immune cell distribution patterns, particularly enriched in aggressive molecular subtypes triple-negative and HER2-positive tumors. We observed significant correlations between immune cell abundance and key clinicopathological parameters, including tumor size, lymph node involvement, and patient overall survival. Notably, immune cell location within different TME regions showed varying correlations with clinicopathologic parameters. Additionally, ethnicities exhibited diverse distributions of cells, with certain ethnicities showing higher abundance compared to others. In TMA samples, patients of Chinese and Caribbean origin displayed significantly lower numbers of B cells, TAMs, and FOXP3-positive cells. These findings highlight the intricate interplay between immune cells and breast cancer progression, with implications for personalized treatment strategies. Moving forward, integrating advanced imaging techniques, and exploring immune cell heterogeneity in diverse ethnic cohorts can uncover novel immune signatures and guide tailored immunotherapeutic interventions, ultimately improving breast cancer management.

Novel approach to HER2 quantification using phosphor-integrated dots in human breast invasive cancer microarray.

HER2 expression in breast cancer is evaluated to select patients for anti-HER2 therapy. With the advent of newly approved HER2-targeted drugs for low HER2 expression breast cancer, more solid evidence on the whole spectrum of HER2 expression is needed. In this study, we quantitatively assessed HER2 expression from the whole core by combining high-intensity phosphor-integrated dot (PID) immunostaining and whole slide imaging (WSI) analysis. Two types of staining were performed using a 170-core tissue microarray of invasive breast cancer. First, HER2 was stained by immunohistochemistry (IHC), and IHC scores were determined by two practicing pathologists according to the ASCO/CAP HER2 guideline. Second, HER2 was stained with PID, and tentative PID scores were determined by quantitative analysis. The results show that PID can numerically classify HER2 expression status into scores 3+, 2+, 1+, and 0. The HER2 value quantified by PID strongly correlated with the 3, 3'-diaminobenzidine (DAB) IHC score determined by pathologists (R2 = 0.93). PID IHC score 1+ cases included both DAB IHC score 1+ and 0 cases, and low HER2 expression cases appeared to be often evaluated as DAB IHC score 0. Therefore, digital image analysis by PID and WSI can help stratify HER2 IHC. It may also help classify low HER2 expression.

Fit-for-Purpose Ki-67 Immunohistochemistry Assays for Breast Cancer.

New therapies are being developed for breast cancer, and in this process, some "old" biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker's intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer. Canadian laboratories assessed the analytical performance and diagnostic accuracy of their Ki-67 IHC laboratory-developed tests (LDTs) of relevance for the LDTs' clinical utility. Canadian clinical IHC laboratories enrolled in the Canadian Biomarker Quality Assurance Pilot Run for Ki-67 in breast cancer by invitation. The Dako Ki-67 IHC pharmDx assay was employed as a study reference assay. The Dako central laboratory was the reference laboratory. Participants received unstained slides of breast cancer tissue microarrays with 32 cases and performed their in-house Ki-67 assays. The results were assessed using QuPath, an open-source software application for bioimage analysis. Positive percent agreement (PPA, sensitivity) and negative percent agreement (NPA, specificity) were calculated against the Dako Ki-67 IHC pharmDx assay for 5%, 10%, 20%, and 30% cutoffs. Overall, PPA and NPA varied depending on the selected cutoff; participants were more successful with 5% and 10%, than with 20% and 30% cutoffs. Only 4 of 16 laboratories had robust IHC protocols with acceptable PPA for all cutoffs. The lowest PPA for the 5% cutoff was 85%, for 10% was 63%, for 20% was 14%, and for 30% was 13%. The lowest NPA for the 5% cutoff was 50%, for 10% was 33%, for 20% was 50%, and for 30% was 57%. Despite many years of international efforts to standardize IHC testing for Ki-67 in breast cancer, our results indicate that Canadian clinical LDTs have a wide analytical sensitivity range and poor agreement for 20% and 30% cutoffs. The poor agreement was not due to the readout but rather due to IHC protocol conditions. International Ki-67 in Breast Cancer Working Group (IKWG) recommendations related to Ki-67 IHC standardization cannot take full effect without reliable fit-for-purpose reference materials that are required for the initial assay calibration, assay performance monitoring, and proficiency testing.

Clinicopathological role of Cyclin A2 in uterine corpus endometrial carcinoma: Integration of tissue microarrays and ScRNA-Seq.

BACKGROUND: The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered. METHODS: UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis. Single-cell RNA-sequencing (scRNA-seq) analysis was performed to explore cell types in UCEC, and the AUCell algorithm was used to investigate the activity of CCNA2 in different cell types. RESULTS: A total of 32 in-house UCEC and 30 normal endometrial tissues as well as 720 UCEC and 165 control samples from public databases were eligible and collected. Integrated calculation showed that the CCNA2 expression was up-regulated in the UCEC tissues (SMD = 2.43, 95% confidence interval 2.23∼2.64). E2F1 and FOXM1 were identified as transcription factors due to the presence of binding peaks on transcription site of CCNA2. CCNA2 predicted worse prognosis in UCEC. However, CCNA2 was not an independent prognostic factor in UCEC. The scRNA-seq analysis disclosed five cell types: B cells, T cells, monocytes, natural killer cells, and epithelial cells in UCEC. The expression of CCNA2 was mainly located in B cells and T cells. Moreover, CCNA2 was active in T cells and B cells using the AUCell algorithm. CONCLUSION: CCNA2 was up-regulated and mainly located in T cells and B cells in UCEC. Overexpression of CCNA2 predicted unfavorable prognosis of UCEC.

Tumor Heterogeneity Confounds Lymphocyte Metrics in Diagnostic Lung Cancer Biopsies.

CONTEXT.­: The immune microenvironment is involved in fundamental aspects of tumorigenesis, and immune scores are now being developed for clinical diagnostics. OBJECTIVE.­: To evaluate how well small diagnostic biopsies and tissue microarrays (TMAs) reflect immune cell infiltration compared to the whole tumor slide, in tissue from patients with non-small cell lung cancer. DESIGN.­: A TMA was constructed comprising tissue from surgical resection specimens of 58 patients with non-small cell lung cancer, with available preoperative biopsy material. Whole sections, biopsies, and TMA were stained for the pan-T lymphocyte marker CD3 to determine densities of tumor-infiltrating lymphocytes. Immune cell infiltration was assessed semiquantitatively as well as objectively with a microscopic grid count. For 19 of the cases, RNA sequencing data were available. RESULTS.­: The semiquantitative comparison of immune cell infiltration between the whole section and the biopsy displayed fair agreement (intraclass correlation coefficient [ICC], 0.29; P = .01; CI, 0.03-0.51). In contrast, the TMA showed substantial agreement compared with the whole slide (ICC, 0.64; P < .001; CI, 0.39-0.79). The grid-based method did not enhance the agreement between the different tissue materials. The comparison of CD3 RNA sequencing data with CD3 cell annotations confirmed the poor representativity of biopsies as well as the stronger correlation for the TMA cores. CONCLUSIONS.­: Although overall lymphocyte infiltration is relatively well represented on TMAs, the representativity in diagnostic lung cancer biopsies is poor. This finding challenges the concept of using biopsies to establish immune scores as prognostic or predictive biomarkers for diagnostic applications.

Combination of Tissue Microarray Profiling and Multiplexed IHC Approaches to Investigate Transport Mechanism of Nucleoside Analog Drug Resistance.

Nucleoside analogs (NAs) are an established class of anticancer agents being used clinically for the treatment of diverse cancers, either as monotherapy or in combination with other established anticancer or pharmacological agents. To date, nearly a dozen anticancer NAs are approved by the FDA, and several novel NAs are being tested in preclinical and clinical trials for future applications. However, improper delivery of NAs into tumor cells because of alterations in expression of one or more drug carrier proteins (e.g., solute carrier (SLC) transporters) within tumor cells or cells surrounding the tumor microenvironment stands as one of the primary reasons for therapeutic drug resistance. The combination of tissue microarray (TMA) and multiplexed immunohistochemistry (IHC) is an advanced, high-throughput approach over conventional IHC that enables researchers to effectively investigate alterations to numerous such chemosensitivity determinants simultaneously in hundreds of tumor tissues derived from patients. In this chapter, taking an example of a TMA from pancreatic cancer patients treated with gemcitabine (a NA chemotherapeutic agent), we describe the step-by-step procedure of performing multiplexed IHC, imaging of TMA slides, and quantification of expression of some relevant markers in these tissue sections as optimized in our laboratory and discuss considerations while designing and carrying out this experiment.

Constructing high-density tissue microarrays with a novel method and a self-made tissue-arraying instrument.

Tissue microarrays (TMAs), also called tissue chips, contain hundreds to thousands of tissue cores obtained from different tissue donor blocks. By using TMA technology, a molecular marker, such as protein, RNA or DNA, can be simultaneously examined in hundreds of different specimens under the same experimental conditions. A growing number of previous studies have introduced different methods for constructing TMAs. Many authors tried to use various methods to implant more tissue cores in a single recipient block, and most of these methods involved reducing the diameter of the tissue cores and/or the spacing between adjacent tissue cores. However, when creating TMAs, it is difficult to reduce the distance between tissue cores to zero except with extremely expensive automatic TMA arrayers. Here, we introduce a novel method to construct a high-density TMA that does not have spacing between the tissue cores. We also introduce a method for preparing a self-made tissue-arraying instrument. With this method and the tissue-arraying instrument, we successfully created a TMA containing 126 tissue cores that were 2 mm in diameter. H&E staining and immunohistochemical staining were performed on the sections cut from the TMA without any tissue spot loss. This method is easy to operate, and the materials for creating the tissue-arraying instrument are inexpensive and can be purchased anywhere. Therefore, this method can be applied in all laboratories.

Cellular microarrays for assessing single-cell phenotypic changes in vascular cell populations.

Microengineering technologies provide bespoke tools for single-cell studies, including microarray approaches. There are many challenges when culturing adherent single cells in confined geometries for extended periods, including the ability of migratory cells to overcome confining cell-repellent surfaces with time. Following studies suggesting clonal expansion of only a few vascular smooth muscle cells (vSMCs) contributes to plaque formation, the investigation of vSMCs at the single-cell level is central to furthering our understanding of atherosclerosis. Herein, we present a medium throughput cellular microarray, for the tracking of single, freshly-isolated vSMCs as they undergo phenotypic modulation in vitro. Our solution facilitates long-term cell confinement (> 3 weeks) utilising novel application of surface functionalisation methods to define individual culture microwells. We demonstrate successful tracking of hundreds of native vSMCs isolated from rat aortic and carotid artery tissue, monitoring their proliferative capacity and uptake of oxidised low-density lipoprotein (oxLDL) by live-cell microscopy. After 7 days in vitro, the majority of viable SMCs remained as single non-proliferating cells (51% aorta, 78% carotid). However, a sub-population of vSMCs demonstrated high proliferative capacity (≥ 10 progeny; 18% aorta, 5% carotid), in line with reports that a limited number of medial SMCs selectively expand to populate atherosclerotic lesions. Furthermore, we show that, when exposed to oxLDL, proliferative cells uptake higher levels of lipoproteins, whilst also expressing greater levels of galectin-3. Our microwell array approach enables long-term characterisation of multiple phenotypic characteristics and the identification of new cellular sub-populations in migratory, proliferative adherent cell types.

Slide-to-Slide Tissue Transfer and Array Assembly From Limited Samples for Comprehensive Molecular Profiling.

Tissue microarrays (TMA) have become an important tool in high-throughput molecular profiling of tissue samples in the translational research setting. Unfortunately, high-throughput profiling in small biopsy specimens or rare tumor samples (eg, orphan diseases or unusual tumors) is often precluded owing to limited amounts of tissue. To overcome these challenges, we devised a method that allows tissue transfer and construction of TMAs from individual 2- to 5-µm sections for subsequent molecular profiling. We named the technique slide-to-slide (STS) transfer, and it requires a series of chemical exposures (so-called xylene-methacrylate exchange) in combination with rehydrated lifting, microdissection of donor tissues into multiple small tissue fragments (methacrylate-tissue tiles), and subsequent remounting on separate recipient slides (STS array slide). We developed the STS technique by assessing the efficacy and analytical performance using the following key metrics: (a) dropout rate, (b) transfer efficacy, (c) success rates using different antigen-retrieval methods, (d) success rates of immunohistochemical stains, (e) fluorescent in situ hybridization success rates, and (f) DNA and (g) RNA extraction yields from single slides, which all functioned appropriately. The dropout rate ranged from 0.7% to 6.2%; however, we applied the same STS technique successfully to fill these dropouts ("rescue" transfer). Hematoxylin and eosin assessment of donor slides confirmed a transfer efficacy of >93%, depending on the size of the tissue (range, 76%-100%). Fluorescent in situ hybridization success rates and nucleic acid yields were comparable with those of traditional workflows. In this study, we present a quick, reliable, and cost-effective method that offers the key advantages of TMAs and other molecular techniques-even when tissue is sparse. The perspectives of this technology in biomedical sciences and clinical practice are promising, given that it allows laboratories to create more data with less tissue.

Detection of MDM2 gene amplification on tissue microarray-based Fluorescence In-Situ Hybridization (FISH) in well-differentiated and dedifferentiated liposarcomas, displaying a wide morphological spectrum: A validation study at a tertiary cancer referral centre.

BACKGROUND: Liposarcomas including atypical lipomatous tumors (ALT)/well-differentiated liposarcomas (WDLPS) and dedifferentiated liposarcomas (DDLPSs) display a histomorphological spectrum with their several diagnostic mimics. Murine double minute 2(MDM2) gene amplification characterizes ALT/WDLPS and DDLPS. Presently, there is no documented study from our subcontinent on the validation of MDM2 gene testing in these tumors. MATERIAL AND METHODS: Twenty-eight cases, diagnosed as ALT/WDLPS (n = 5) and DDLPSs (n = 23), along with 10 other tumors were tested for MDM2 gene amplification, using fluorescence in situ hybridization (FISH) on tissue microarrays (TMAs). Fourteen cases, diagnosed as ALT/WDLPS and DDLPS, along with 49 other tumors were tested for MDM2 immunostaining. Twenty tumors were tested for p16INK4a immunostaining. RESULTS: FISH was interpretable in 25 (89.2%) cases. Among the 20 cases diagnosed as DDLPSs, 19 displayed MDM2 gene amplification. Among the 5 cases diagnosed as ALT/WDLPS, four showed MDM2 gene amplification. Finally, 19 cases were confirmed as DDLPS and 4 as ALT/WDLPS. Furthermore, 7/19 cases confirmed as DDLPS and all 4 cases as ALT/WDLPS tested for MDM2 immunostaining, displayed its diffuse immunoexpression, while a single case of DDLPS showed its focal immunostaining. None of the 49 control cases displayed diffuse MDM2 immunoexpression. ALL 16 DDLPSs and 4 cases of ALT/WDLPS displayed p16INK4a immunostaining. The sensitivity for diffuse MDM2 immunostaining was 87.5% in cases of DDLPS, 100% in ALT/WDLPS, and specificity was 100%. The sensitivity for MDM2 gene amplification was 94.7% in cases of DDLPS and 100% in cases of ALT/WDLPS. The sensitivity for p16INK4a was 100%. CONCLUSION: This constitutes the first sizable study on MDM2 testing in ALT/WDLPS and DDLPS from our subcontinent using TMAs. MDM2 gene amplification testing continues as the diagnostic gold standard for ALTs/WDLPSs and DDLPSs and is useful in cases of diagnostic dilemmas. Diffuse MDM2 (IF2 clone) and p16INK4a immunostaining, together seem useful for triaging cases for FISH.

Advanced detection strategies for cardiotropic virus infection in a cohort study of heart failure patients.

The prevalence and contribution of cardiotropic viruses to various expressions of heart failure are increasing, yet primarily underappreciated and underreported due to variable clinical syndromes, a lack of consensus diagnostic standards and insufficient clinical laboratory tools. In this study, we developed an advanced methodology for identifying viruses across a spectrum of heart failure patients. We designed a custom tissue microarray from 78 patients with conditions commonly associated with virus-related heart failure, conditions where viral contribution is typically uncertain, or conditions for which the etiological agent remains suspect but elusive. Subsequently, we employed advanced, highly sensitive in situ hybridization to probe for common cardiotropic viruses: adenovirus 2, coxsackievirus B3, cytomegalovirus, Epstein-Barr virus, hepatitis C and E, influenza B and parvovirus B19. Viral RNA was detected in 46.4% (32/69) of heart failure patients, with 50% of virus-positive samples containing more than one virus. Adenovirus 2 was the most prevalent, detected in 27.5% (19/69) of heart failure patients, while in contrast to previous reports, parvovirus B19 was detected in only 4.3% (3/69). As anticipated, viruses were detected in 77.8% (7/9) of patients with viral myocarditis and 37.5% (6/16) with dilated cardiomyopathy. Additionally, viruses were detected in 50% of patients with coronary artery disease (3/6) and hypertrophic cardiomyopathy (2/4) and in 28.6% (2/7) of transplant rejection cases. We also report for the first time viral detection within a granulomatous lesion of cardiac sarcoidosis and in giant cell myocarditis, conditions for which etiological agents remain unknown. Our study has revealed a higher than anticipated prevalence of cardiotropic viruses within cardiac muscle tissue in a spectrum of heart failure conditions, including those not previously associated with a viral trigger or exacerbating role. Our work forges a path towards a deeper understanding of viruses in heart failure pathogenesis and opens possibilities for personalized patient therapeutic approaches.

Investigation of insulin resistance through a multiorgan microfluidic organ-on-chip.

The development of hepatic insulin resistance (IR) is a critical factor in developing type 2 diabetes (T2D), where insulin fails to inhibit hepatic glucose production but retains its capacity to promote hepatic de novo lipogenesis leading to hyperglycemia and hypertriglyceridemia. Improving insulin sensitivity can be effective in preventing and treating T2D. However, selective control of glucose and lipid synthesis has been difficult. It is known that excess white adipose tissue is detrimental to insulin sensitivity, whereas brown adipose tissue transplantation can restore it in diabetic mice. However, challenges remain in our understanding of liver-adipose communication because the confounding effects of hypothalamic regulation of metabolic function cannot be ruled out in previous studies. There is a lack ofin vitromodels that use primary cells to study cellular-crosstalk under insulin resistant conditions. Building upon our previous work on the microfluidic primary liver and adipose organ-on-chips, we report for the first time, the development of an integrated insulin resistant liver-adipose (white and brown) organ-on-chip. The design of the microfluidic device was carried out using computational fluid dynamics; the experimental studies were conducted by carrying out detailed biochemical analysis RNA-seq analysis on both cell types. Further, we tested the hypothesis that brown adipocytes (BAC) regulated both hepatic insulin sensitivity and de novo lipogenesis. Our results show that BAC effectively restored insulin sensitivity and supressed hepatic glucose production and de novo lipogenesis suggesting that the experimental platform could be useful for identifying potential therapeutics to treat IR and diabetes.

Combination therapy with novel androgen receptor antagonists and statin for castration-resistant prostate cancer.

BACKGROUND: One of the growth mechanisms of castration-resistant prostate cancer (CRPC) is de novo androgen synthesis from intracellular cholesterol, and statins may be able to inhibit this mechanism. In addition, statins have been reported to suppress the expression of androgen receptors (ARs) in prostate cancer cell lines. In this study, we investigated a combination therapy of novel AR antagonists and statin, simvastatin, for CRPC. METHODS: LNCaP, 22Rv1, and PC-3 human prostate cancer cell lines were used. We developed androgen-independent LNCaP cells (LNCaP-LA). Microarray analysis was performed, followed by pathway analysis, and mRNA and protein expression was evaluated by quantitative real-time polymerase chain reaction and Western blot analysis, respectively. Cell viability was determined by MTS assay and cell counts. All evaluations were performed on cells treated with simvastatin and with or without AR antagonists (enzalutamide, apalutamide, and darolutamide). RESULTS: The combination of darolutamide and simvastatin most significantly suppressed proliferation in LNCaP-LA and 22Rv1 cells. In a 22Rv1-derived mouse xenograft model, the combination of darolutamide and simvastatin enhanced the inhibition of cell proliferation. In LNCaP-LA cells, the combination of darolutamide and simvastatin led to reduction in the mRNA expression of the androgen-stimulated genes, KLK2 and PSA; however, this reduction in expression did not occur in 22Rv1 cells. The microarray data and pathway analyses showed that the number of differentially expressed genes in the darolutamide and simvastatin-treated 22Rv1 cells was the highest in the pathway termed "role of cell cycle." Consequently, we focused our efforts on the cell cycle regulator polo-like kinase 1 (PLK1), cyclin-dependent kinase 2 (CDK2), and cell cycle division 25C (CDC25C). In 22Rv1 cells, the combination of darolutamide and simvastatin suppressed the mRNA and protein expression of these three genes. In addition, in PC-3 cells (which lack AR expression), the combination of simvastatin and darolutamide enhanced the suppression of cell proliferation and expression of these genes. CONCLUSIONS: Simvastatin alters the expression of many genes involved in the cell cycle in CRPC cells. Thus, the combination of novel AR antagonists (darolutamide) and simvastatin can potentially affect CRPC growth through both androgen-dependent and androgen-independent mechanisms.

Impact of aerosols on liver xenobiotic metabolism: A comparison of two methods of exposure.

Assessment of aerosols effects on liver CYP function generally involves aqueous fractions (AF). Although easy and efficient, this method has not been optimized recently or comparatively assessed against other aerosol exposure methods. Here, we comparatively evaluated the effects of the AFs of cigarette smoke (CS) and Tobacco Heating System (THS) aerosols on CYP activity in liver spheroids. We then used these data to develop a physiological aerosol exposure system combining a multi-organs-on-a-chip, 3D lung tissues, liver spheroids, and a direct aerosol exposure system. Liver spheroids incubated with CS AF showed a dose-dependent increase in CYP1A1/1B1, CYP1A2, and CYP2B6 activity and a dose-dependent decrease in CYP2C9, CYP2D6, and CYP3A4 activity relative to untreated tissues. In our physiological exposure system, repeated CS exposure of the bronchial tissues also caused CYP1A1/1B1 and CYP1A2 induction in the bronchial tissues and liver spheroids; but the spheroids showed an increase in CYP3A4 activity and no effect on CYP2C9 or CYP2D6 activity relative to air-exposed tissues, which resembles the results reported in smokers. THS aerosol did not affect CYP activity in bronchial or liver tissues, even at 4 times higher concentrations than CS. In conclusion, our system allows us to physiologically test the effects of CS or other aerosols on lung and liver tissues cultured in the same chip circuit, thus delivering more in vivo like data.

Gene expression profile in functioning and non-functioning nodules of autonomous multinodular goiter from an area of iodine deficiency: unexpected common characteristics between the two entities.

PURPOSE: Toxic multinodular goiter is a heterogeneous disease associated with hyperthyroidism frequently detected in areas with deficient iodine intake, and functioning and non-functioning nodules, characterized by increased proliferation but opposite functional activity, may coexist in the same gland. To understand the distinct molecular pathology of each entity present in the same gland, the gene expression profile was evaluated by using the Affymetrix technology. METHODS: Total RNA was extracted from nodular and healthy tissues of two patients and double-strand cDNA was synthesized. Biotinylated cRNA was obtained and, after chemical fragmentation, was hybridized on U133A and B arrays. Each array was stained and the acquired images were analyzed to obtain the expression levels of the transcripts. Both functioning and non-functioning nodules were compared versus healthy tissue of the corresponding patient. RESULTS: About 16% of genes were modulated in functioning nodules, while in non-functioning nodules only 9% of genes were modulated with respect to the healthy tissue. In functioning nodules of both patients and up-regulation of cyclin D1 and cyclin-dependent kinase inhibitor 1 was observed, suggesting the presence of a possible feedback control of proliferation. Complement components C1s, C7 and C3 were down-regulated in both types of nodules, suggesting a silencing of the innate immune response. Cellular fibronectin precursor was up-regulated in both functioning nodules suggesting a possible increase of endothelial cells. Finally, Frizzled-1 was down-regulated only in functioning nodules, suggesting a role of Wnt signaling pathway in the proliferation and differentiation of these tumors. None of the thyroid-specific gene was deregulated in microarray analysis. CONCLUSION: In conclusion, the main finding from our data is a similar modulation for both kinds of nodules in genes possibly implicated in thyroid growth.

Multiplexed imaging and effluent analysis to monitor cancer cell intravasation using a colorectal cancer-on-chip.

Despite colorectal cancer's (CRC) prevalence, its progression is not well understood. The microfluidic organ-on-chip (OOC) model described herein recreates the epithelial-endothelial tissue-tissue interface, fluid flow, and mechanical forces that exist in vivo , making it an attractive model to understand and ultimately disrupt CRC intravasation. This protocol provides step-by-step details for tumor cell seeding to create a CRC-on-chip model, chip effluent collection and analysis, and on-chip imaging to monitor tumor cell invasion within a more physiologically relevant microenvironment. For complete details on the use and execution of this protocol, please refer to Strelez et al. (2021).

Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays.

Tissue microarrays (TMAs) have been used in thousands of cancer biomarker studies. To what extent batch effects, measurement error in biomarker levels between slides, affects TMA-based studies has not been assessed systematically. We evaluated 20 protein biomarkers on 14 TMAs with prospectively collected tumor tissue from 1448 primary prostate cancers. In half of the biomarkers, more than 10% of biomarker variance was attributable to between-TMA differences (range, 1-48%). We implemented different methods to mitigate batch effects (R package batchtma), tested in plasmode simulation. Biomarker levels were more similar between mitigation approaches compared to uncorrected values. For some biomarkers, associations with clinical features changed substantially after addressing batch effects. Batch effects and resulting bias are not an error of an individual study but an inherent feature of TMA-based protein biomarker studies. They always need to be considered during study design and addressed analytically in studies using more than one TMA.

To understand cancer, researchers need to know which molecules tumor cells use. These so-called 'biomarkers' tag cancer cells as being different from healthy cells, and can be used to predict how aggressive a tumor may be, or how well it might respond to treatment. A popular technique for assessing biomarkers across multiple tumors is to use tissue microarrays. This involves taking samples from different tumors and embedding them in a block of wax, which is then cut into micro-thin slices and stained with reagents that can detect specific biomarkers, such as proteins. Each block contains hundreds of samples, which all experience the same conditions. So, any patterns detected in the staining are likely to represent real variations in the biomarkers present. Many cancer studies, however, often compare samples from multiple tissue microarrays, which may increase the risk of technical artifacts: for example, staining may look stronger in one batch of tissue samples than another, even though the amount of biomarker present in these different arrays is roughly the same. These 'batch effects' could potentially bias the results of the experiment and lead to the identification of misleading patterns. To evaluate how batch effects impact tissue microarray studies, Stopsack et al. examined 14 wax blocks which contained tumor samples from 1,448 men with prostate cancer. This revealed that for some biomarkers, but not others, there were noticeable differences between tissue microarrays that were clearly the result of batch effects. Stopsack et al. then tested six different ways of fixing these discrepancies using statistical methods. All six approaches were successful, even if the arrays included tumors with different characteristics, such as tumors that had been diagnosed more or less recently. This work highlights the importance of considering batch effects when using tissue microarrays to study cancer. Stopsack et al. have used their statistical approaches to develop freely available software which can reduce the biases that sometimes arise from these technical artifacts. This could help researchers avoid misleading patterns in their data and make it easier to detect real variations in the biomarkers present between tumor samples.

Microarray analysis of hub genes and pathways in damaged cartilage tissues of knee.

ABSTRACT: The aim of this study was to identify genes and functional pathways associated with damaged cartilage tissues of knee using microarray analysis.The gene expression profile GSE129147 including including 10 knee cartilage tissues from damaged side and 10 knee nonweight-bearing healthy cartilage was downloaded and bioinformatics analysis was made.A total of 182 differentially-expressed genes including 123 up-regulated and 59 down-regulated genes were identified from the GSE129147 dataset. Gene ontology and pathway enrichment analysis confirmed that extracellular matrix organization, collagen catabolic process, antigen processing and presentation of peptide or polysaccharide antigen, and endocytic vesicle membrane were strongly associated with cartilage injury. Furthermore, 10 hub differentially-expressed genes with a higher connectivity degree in protein-protein interactions network were found such as POSTN, FBN1, LOX, insulin-like growth factor binding proteins3, C3AR1, MMP2, ITGAM, CDKN2A, COL1A1, COL5A1.These hub genes and pathways provide a new perspective for revealing the potential pathological mechanisms and therapy strategy of cartilage injury.