Comparative evaluation of three proliferation markers, Ki-67, TOP2A, and RacGAP1, in bronchopulmonary neuroendocrine neoplasms: Issues and prospects

Disruption of Circadian Clock Induces Abnormal Mammary Morphology and Aggressive Basal Tumorigenesis by Enhancing LILRB4 Signaling

Epidemiological studies have shown that circadian rhythm disruption (CRD) is associated with the risk of breast cancer. However, the role of CRD in mammary gland morphology and aggressive basal mammary tumorigenesis and the molecular mechanisms underlying CRD and cancer risk remain unknown. To investigate the effect of CRD on aggressive tumorigenesis, a genetically engineered mouse model that recapitulates the human basal type of breast cancer was used for this study. The effect of CRD on mammary gland morphology was investigated using wild-type mice model. The impact of CRD on the tumor microenvironment was investigated using the tumors from LD12:12 and CRD mice via scRNA seq. ScRNA seq was substantiated by multiplexing immunostaining, flow cytometry, and realtime PCR. The effect of LILRB4 immunotherapy on CRD-induced tumorigenesis was also investigated. Here we identified the impact of CRD on basal tumorigenesis and mammary gland morphology and identified the role of LILRB4 on CRD-induced lung metastasis. We found that chronic CRD disrupted mouse mammary gland morphology and increased tumor burden, and lung metastasis and induced an immunosuppressive tumor microenvironment by enhancing LILRB4a expression. Moreover, CRD increased the M2-macrophage and regulatory T-cell populations but decreased the M1-macrophage populations. Furthermore, targeted immunotherapy against LILRB4 reduced CRD-induced immunosuppressive microenvironment and lung metastasis. These findings identify and implicate LILRB4a as a link between CRD and aggressive mammary tumorigenesis. This study also establishes the potential role of the targeted LILRB4a immunotherapy as an inhibitor of CRD-induced lung metastasis.

Revealing the role of SPP1+ macrophages in glioma prognosis and therapeutic targeting by investigating tumor-associated macrophage landscape in grade 2 and 3 gliomas

BACKGROUND

Glioma is a highly heterogeneous brain tumor categorized into World Health Organization (WHO) grades 1-4 based on its malignancy. The suppressive immune microenvironment of glioma contributes significantly to unfavourable patient outcomes. However, the cellular composition and their complex interplays within the glioma environment remain poorly understood, and reliable prognostic markers remain elusive. Therefore, in-depth exploration of the tumor microenvironment (TME) and identification of predictive markers are crucial for improving the clinical management of glioma patients.

RESULTS

Our analysis of single-cell RNA-sequencing data from glioma samples unveiled the immunosuppressive role of tumor-associated macrophages (TAMs), mediated through intricate interactions with tumor cells and lymphocytes. We also discovered the heterogeneity within TAMs, among which a group of suppressive TAMs named TAM-SPP1 demonstrated a significant association with Epidermal Growth Factor Receptor (EGFR) amplification, impaired T cell response and unfavourable patient survival outcomes. Furthermore, by leveraging genomic and transcriptomic data from The Cancer Genome Atlas (TCGA) dataset, two distinct molecular subtypes with a different constitution of TAMs, EGFR status and clinical outcomes were identified. Exploiting the molecular differences between these two subtypes, we developed a four-gene-based prognostic model. This model displayed strong associations with an elevated level of suppressive TAMs and could be used to predict anti-tumor immune response and prognosis in glioma patients.

CONCLUSION

Our findings illuminated the molecular and cellular mechanisms that shape the immunosuppressive microenvironment in gliomas, providing novel insights into potential therapeutic targets. Furthermore, the developed prognostic model holds promise for predicting immunotherapy response and assisting in more precise risk stratification for glioma patients.

Uncovering Minimal Pathways in Melanoma Initiation

Cutaneous melanomas are clinically and histologically heterogeneous. Most display activating mutations in Braf or Nras and complete loss of function of one or more tumor suppressor genes. Mouse models that replicate such mutations produce fast-growing, pigmented tumors. However, mice that combine Braf activation with only heterozygous loss of Pten also produce tumors and, as we show here, in an Albino background this occurs even with Braf activation alone. Such tumors arise rarely, grow slowly, and express low levels of pigmentation genes. The timing of their appearance was consistent with a single step stochastic event, but no evidence could be found that it required de novo mutation, suggesting instead the involvement of an epigenetic transition. Single-cell transcriptomic analysis revealed such tumors to be heterogeneous, including a minor cell type we term LNM ( L ow-pigment, N eural- and extracellular M atrix-signature) that displays gene expression resembling "neural crest"-like cell subsets detected in the fast-growing tumors of more heavily-mutated mice, as well as in human biopsy and xenograft samples. We provide evidence that LNM cells pre-exist in normal skin, are expanded by Braf activation, can transition into malignant cells, and persist with malignant cells through multiple rounds of transplantation. We discuss the possibility that LNM cells not only serve as a pre-malignant state in the production of some melanomas, but also as an important intermediate in the development of drug resistance.

Crucial Roles of the Mesenchymal Androgen Receptor in Wolffian Duct Development

Wolffian duct (WD) maintenance and differentiation is predominantly driven by the androgen action, which is mediated by the androgen receptor (AR). It is well established that the mesenchyme indicates the fate and differentiation of epithelial cells. However, in vivo developmental requirement of mesenchymal AR in WD development is still undefined. By designing a mesenchyme-specific Ar knockout (ARcKO), we discovered that the loss of mesenchymal Ar led to the bilateral or unilateral degeneration of caudal WDs and cystic formation at the cranial WDs. Ex vivo culture of ARcKO WDs invariably resulted in bilateral defects, suggesting that some factor(s) originating from surrounding tissues in vivo might promote WD survival and growth even in the absence of mesenchymal Ar. Mechanistically, we found cell proliferation was significantly reduced in both epithelial and mesenchymal compartments; but cell apoptosis was not affected. Transcriptomic analysis by RNA sequencing of E14.5 mesonephroi revealed 131 differentially expressed genes. Multiple downregulated genes (Top2a, Wnt9b, Lama2, and Lamc2) were associated with morphological and cellular changes in ARcKO male embryos (ie, reduced cell proliferation and decreased number of epithelial cells). Mesenchymal differentiation into smooth muscle cells that are critical for morphogenesis was also impaired in ARcKO male embryos. Taken together, our results demonstrate the crucial roles of the mesenchymal AR in WD maintenance and morphogenesis in mice.

Overexpression of RACGAP1 by E2F1 Promotes Neuroendocrine Differentiation of Prostate Cancer by Stabilizing EZH2 Expression

Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer. It is characterized by the loss of androgen receptor (AR) signaling in neuroendocrine transdifferentiation, and finally, resistance to AR-targeted therapy. With the application of a new generation of potent AR inhibitors, the incidence of NEPC is gradually increasing. The molecular mechanism of neuroendocrine differentiation (NED) after androgen deprivation therapy (ADT) remains largely unclear. In this study, using NEPC-related genome sequencing database analyses, we screened RACGAP1, a common differentially expressed gene. We investigated RACGAP1 expression in clinical prostate cancer specimens by IHC. Regulated pathways were examined by Western blotting, qRT-PCR, luciferase reporter, chromatin immunoprecipitation, and immunoprecipitation assays. The corresponding function of RACGAP1 in prostate cancer was analyzed by CCK-8 and Transwell assays. The changes of neuroendocrine markers and AR expression in C4-2-R and C4-2B-R cells were detected in vitro. We confirmed that RACGAP1 contributed to NE transdifferentiation of prostate cancer. Patients with high tumor RACGAP1 expression had shorter relapse-free survival time. The expression of RACGAP1 was induced by E2F1. RACGAP1 promoted neuroendocrine transdifferentiation of prostate cancer by stabilizing EZH2 expression in the ubiquitin-proteasome pathway. Moreover, overexpression of RACGAP1 promoted enzalutamide resistance of castration-resistant prostate cancer (CRPC) cells. Our results showed that the upregulation of RACGAP1 by E2F1 increased EZH2 expression, which drove NEPC progression. This study explored the molecular mechanism of NED and may provide novel methods and ideas for targeted therapy of NEPC.

Prevalence of Thyroid Transcription Factor-1 (TTF-1)-Negative Small Cell Carcinoma and Napsin A Positivity in Small Cell Carcinoma in a Cross-Sectional Study of Lung Core Biopsies

Background The prevalence of thyroid transcription factor-1 (TTF-1) and napsin A expression are poorly characterized in lung core biopsies of small cell carcinoma. Locally, the TTF-1 clone is 8G7G3/1 (Agilent/Dako), and the napsin A clone is IP64 (Leica Biosystems). Methods All in-house lung core biopsy reports for cases accessioned at a regional laboratory from January 2011 to December 2020 were retrieved and analyzed using a validated hierarchical free-text string matching algorithm (HFTSMA) to establish the diagnosis. TTF-1 and napsin A were manually coded with the assistance of a logical text parsing tool. All TTF-1-negative small cell lung carcinoma (SCLC) cases had a full report review by pathologists. Results The cohort had 5,867 lung core biopsies, and 232 cases were confirmed as small cell carcinoma on pathologist review. TTF-1 immunostain results were available in 173 SCLC cases, and 16 cases of TTF-1-negative SCLC were confirmed on full report review. These 16 cases had at least one positive neuroendocrine (NE) marker and positive keratin staining; cases with mixed histology or positive CK5/6 staining were excluded. Ki-67 was done in 10/16 cases; the average Ki-67 was 75%. Napsin A was negative in 50/51 small cell carcinomas, and 0/3 TTF-1-negative SCLC had napsin A positivity. Conclusions Standardized immunostain reporting would simplify such analyses. Based on the cohort, approximately 9% (16/173) of SCLC is TTF-1 negative. Napsin A positivity in suspected small cell carcinoma should prompt consideration of an alternate diagnosis or explanation.

High-Throughput Cellular Heterogeneity Analysis in Cell Migration at the Single-Cell Level

Cancer cell migration represents an essential step toward metastasis and cancer deaths. However, conventional drug discovery focuses on cytotoxic and growth-inhibiting compounds rather than inhibitors of migration. Drug screening assays generally measure the average response of many cells, masking distinct cell populations that drive metastasis and resist treatments. Here, this work presents a high-throughput microfluidic cell migration platform that coordinates robotic liquid handling and computer vision for rapidly quantifying individual cellular motility. Using this innovative technology, 172 compounds were tested and a surprisingly low correlation between migration and growth inhibition was found. Notably, many compounds were found to inhibit migration of most cells while leaving fast-moving subpopulations unaffected. This work further pinpoints synergistic drug combinations, including Bortezomib and Danirixin, to stop fast-moving cells. To explain the observed cell behaviors, single-cell morphological and molecular analysis were performed. These studies establish a novel technology to identify promising migration inhibitors for cancer treatment and relevant applications.

Granulocytic myeloid-derived suppressor cells to prevent and treat murine immune-mediated bone marrow failure

Myeloid-derived suppressor cells (MDSCs) are immature myeloid cells that originate in the bone marrow (BM) and have immunoregulatory functions. MDSCs have been implicated in the pathogenesis of several autoimmune diseases but have not been investigated in immune aplastic anemia (AA). We examined the roles of granulocytic-MDSCs (G-MDSCs) in murine models of human AA and BM failure (BMF). As both prophylaxis and therapy, BM-derived G-MDSCs improved pancytopenia and BM cellularity and suppressed BM T-cell infiltration in major histocompatibility complex (MHC)-matched C.B10 BMF mice. These effects were not obtained in the MHC-mismatched CByB6F1 AA model, likely because of MHC disparity between G-MDSCs and donor T cells. Single-cell RNA sequencing demonstrated that G-MDSCs downregulated cell cycle-related genes in BM-infiltrated T cells, consistent with suppression of T-cell proliferation by G-MDSCs through reactive oxygen species pathways. Clearance of G-MDSCs in the MHC-mismatched CByB6F1 model using anti-Ly6G antibody facilitated T cell-mediated BM destruction, suggesting an intrinsic immunosuppressive property of G-MDSCs. However, the same anti-Ly6G antibody in the MHC-matched C.B10 AA model mildly mitigated BMF, associated with expansion of an intermediate Ly6G population. Our results demonstrate that G-MDSC eradication and therapeutic efficacy are immune context-dependent.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Comparative single-cell RNA-sequencing profiling of BMP4-treated primary glioma cultures reveals therapeutic markers

BACKGROUND

Glioblastoma (GBM) is the most aggressive primary brain tumor. Its cellular composition is very heterogeneous, with cells exhibiting stem-cell characteristics (GSCs) that co-determine therapy resistance and tumor recurrence. Bone Morphogenetic Protein (BMP)-4 promotes astroglial and suppresses oligodendrocyte differentiation in GSCs, processes associated with superior patient prognosis. We characterized variability in cell viability of patient-derived GBM cultures in response to BMP4 and, based on single-cell transcriptome profiling, propose predictive positive and early-response markers for sensitivity to BMP4.

METHODS

Cell viability was assessed in 17 BMP4-treated patient-derived GBM cultures. In two cultures, one highly-sensitive to BMP4 (high therapeutic efficacy) and one with low-sensitivity, response to treatment with BMP4 was characterized. We applied single-cell RNA-sequencing, analyzed the relative abundance of cell clusters, searched for and identified the aforementioned two marker types, and validated these results in all 17 cultures.

RESULTS

High variation in cell viability was observed after treatment with BMP4. In three cultures with highest sensitivity for BMP4, a substantial new cell subpopulation formed. These cells displayed decreased cell proliferation and increased apoptosis. Neuronal differentiation was reduced most in cultures with little sensitivity for BMP4. OLIG1/2 levels were found predictive for high sensitivity to BMP4. Activation of ribosomal translation (RPL27A, RPS27) was up-regulated within one day in cultures that were very sensitive to BMP4.

CONCLUSION

The changes in composition of patient-derived GBM cultures obtained after treatment with BMP4 correlate with treatment efficacy. OLIG1/2 expression can predict this efficacy, and upregulation of RPL27A and RPS27 are useful early-response markers.

Overexpressed or hyperactivated Rac1 as a target to treat hepatocellular carcinoma

Despite novel targeted and immunotherapies, the prognosis remains bleak for patients with hepatocellular carcinoma (HCC), especially for advanced and/or metastatic forms. The rapid emergence of drug resistance is a major obstacle in the success of chemo-, targeted-, immuno-therapies of HCC. Novel targets are needed. The prominent roles of the small GTPase Rac1 in the development and progression of HCC are discussed here, together with its multiple protein partners, and the targeting of Rac1 with RNA-based regulators and small molecules. We discuss the oncogenic functions of Rac1 in HCC, including the contribution of Rac1 mutants and isoform Rac1b. Rac1 is a ubiquitous target, but the protein is frequently overexpressed and hyperactivated in HCC. It contributes to the aggressivity of the disease, with key roles in cancer cell proliferation, tumor metastasis and resistance to treatment. Small molecule targeting Rac1, indirectly or directly, have shown anticancer effects in HCC experimental models. Rac1-binding agents such as EHT 1864 and analogues offer novel opportunities to combat HCC. We discuss the different modalities to repress Rac1 overactivation in HCC with small molecules and the combination with reference drugs to promote cancer cell death and to repress cell invasion. We highlight the necessity to combine Rac1-targeted approach with appropriate biomarkers to select Rac1 activated tumors. Our analysis underlines the prominent oncogenic functions of Rac1 in HCC and discuss the modalities to target this small GTPase. Rac1 shall be considered as a valid target to limit the acquired and intrinsic resistance of HCC tumors and their metastatic potential.

Automated Analysis of Proliferating Cells Spatial Organisation Predicts Prognosis in Lung Neuroendocrine Neoplasms

Simple Summary

Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome, particularly for the intermediate domains of adenocarcinomas and large-cell neuroendocrine carcinomas. Moreover, subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. The aim of this study was to design and evaluate an objective and reproducible approach to the grading of lung NENs, potentially extendable to other NENs, by exploring a completely new perspective of interpreting the well-recognised proliferation marker Ki-67. We designed an automated pipeline to harvest quantitative information from the spatial distribution of Ki-67-positive cells, analysing its heterogeneity in the entire extent of tumour tissue—which currently represents the main weakness of Ki-67—and employed machine learning techniques to predict prognosis based on this information. Demonstrating the efficacy of the proposed framework would hint at a possible path for the future of grading and classification of NENs.

Abstract

Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome. Subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. Here, we propose a machine learning framework for tumour prognosis assessment based on a quantitative, automated and repeatable evaluation of the spatial distribution of cells immunohistochemically positive for the proliferation marker Ki-67, performed on the entire extent of high-resolution whole slide images. Combining features from the fields of graph theory, fractality analysis, stochastic geometry and information theory, we describe the topology of replicating cells and predict prognosis in a histology-independent way. We demonstrate how our approach outperforms the well-recognised prognostic role of Ki-67 Labelling Index on a multi-centre dataset comprising the most controversial lung NENs. Moreover, we show that our system identifies arrangement patterns in the cells positive for Ki-67 that appear independently of tumour subtyping. Strikingly, the subset of these features whose presence is also independent of the value of the Labelling Index and the density of Ki-67-positive cells prove to be especially relevant in discerning prognostic classes. These findings disclose a possible path for the future of grading and classification of NENs.

Characterization of In Vitro 3D Cell Model Developed from Human Hepatocellular Carcinoma (HepG2) Cell Line

In genetic toxicology, there is a trend against the increased use of in vivo models as highlighted by the 3R strategy, thus encouraging the development and implementation of alternative models. Two-dimensional (2D) hepatic cell models, which are generally used for studying the adverse effects of chemicals and consumer products, are prone to giving misleading results. On the other hand, newly developed hepatic three-dimensional (3D) cell models provide an attractive alternative, which, due to improved cell interactions and a higher level of liver-specific functions, including metabolic enzymes, reflect in vivo conditions more accurately. We developed an in vitro 3D cell model from the human hepatocellular carcinoma (HepG2) cell line. The spheroids were cultured under static conditions and characterised by monitoring their growth, morphology, and cell viability during the time of cultivation. A time-dependent suppression of cell division was observed. Cell cycle analysis showed time-dependent accumulation of cells in the G0/G1 phase. Moreover, time-dependent downregulation of proliferation markers was shown at the mRNA level. Genes encoding hepatic markers, metabolic phase I/II enzymes, were time-dependently deregulated compared to monolayers. New knowledge on the characteristics of the 3D cell model is of great importance for its further development and application in the safety assessment of chemicals, food products, and complex mixtures.

TOP2A expression predicts responsiveness to carfilzomib in myeloma and informs novel combinatorial strategies for enhanced proteasome inhibitor cell killing

Microarray was utilized to determine if a genetic signature associated with resistance to carfilzomib (CFZ) could be identified. Twelve human myeloma (MM) cell lines (HMCLs) were treated with CFZ and a cell-viability profile was assessed categorizing HMCLs as sensitive or resistant to CFZ. The gene expression profiles (GEP) of untreated resistant versus sensitive HMCLs revealed 29 differentially expressed genes. TOP2A, an enzyme involved in cell cycle and proliferation, was overexpressed in carfilzomib-resistant HMCLs. TOP2A protein expression levels, evaluated utilizing trephine biopsy specimens acquired prior to treatment with proteasome inhibitors, were higher in patients failing to achieve a response when compared to responding patients. Logistic-regression analysis confirmed that TOP2A protein expression was a highly significant predictor of response to PIs (AUC 0.738). Further, the combination of CFZ with TOP2A inhibitors, demonstrated synergistic cytotoxic effects in vitro, providing a rationale for combining topoisomerase inhibitors with CFZ to overcome resistance in MM.

Application of advanced HepG2 3D cell model for studying genotoxic activity of cyanobacterial toxin cylindrospermopsin

Cylindrospermopsin (CYN) is an emerging cyanotoxin increasingly being found in freshwater cyanobacterial blooms worldwide. Humans and animals are exposed to CYN through the consumption of contaminated water and food as well as occupational and recreational water activities; therefore, it represents a potential health threat. It exhibits genotoxic effects in metabolically active test systems, thus it is considered as pro-genotoxic. In the present study, the advanced 3D cell model developed from human hepatocellular carcinoma (HepG2) cells was used for the evaluation of CYN cyto-/genotoxic activity. Spheroids were formed by forced floating method and were cultured for three days under static conditions prior to exposure to CYN (0.125, 0.25 and 0.5 μg/mL) for 72 h. CYN influence on spheroid growth was measured daily and cell survival was determined by MTS assay and live/dead staining. The influence on cell proliferation, cell cycle alterations and induction of DNA damage (γH2AX) was determined using flow cytometry. Further, the expression of selected genes (qPCR) involved in the metabolism of xenobiotics, proliferation, DNA damage response, apoptosis and oxidative stress was studied. Results revealed that CYN dose-dependently reduced the size of spheroids and affected cell division by arresting HepG2 cells in G1 phase of the cell cycle. No induction of DNA double strand breaks compared to control was determined at applied conditions. The analysis of gene expression revealed that CYN significantly deregulated genes encoding phase I (CYP1A1, CYP1A2, CYP3A4, ALDH3A) and II (NAT1, NAT2, SULT1B1, SULT1C2, UGT1A1, UGT2B7) enzymes as well as genes involved in cell proliferation (PCNA, TOP2α), apoptosis (BBC3) and DNA damage response (GADD45a, CDKN1A, ERCC4). The advanced 3D HepG2 cell model due to its more complex structure and improved cellular interactions provides more physiologically relevant information and more predictive data for human exposure, and can thus contribute to more reliable genotoxicity assessment of chemicals including cyanotoxins.

Prediction of Poor Outcomes in Patients with Colorectal Cancer: Elevated Preoperative Prothrombin Time (PT) and Activated Partial Thromboplastin Time (APTT)

Background and Objective

Tools for the non-invasive assessment of colorectal cancer (CRC) prognosis have profound significance. Although plasma coagulation tests have been investigated in a variety of tumours, the prognostic value of the prothrombin time (PT) and activated partial thromboplastin time (APTT) in CRC has not been discussed. Our study objective was to explore the prognostic significance of preoperative PT and APTT in CRC patients.

Patients and Methods

A retrospective analysis of preoperative coagulation indexes including PT, PTA, INR, APTT, FIB, TT, PLT, NLR and PLR in 250 patients with CRC was performed. Kaplan–Meier and multivariate Cox regression analysis were used to demonstrate the prognostic value of these preoperative coagulation indexes.

Results

The overall survival (OS, p<0.05) and disease-free survival (DFS, p<0.05) of CRC patients with lower PT and APTT levels were significantly prolonged. Based on univariate analysis, PT levels (p<0.001, p<0.001), PTA levels (p=0.001, p=0.001), APTT levels (p=0.001, p<0.001), INR levels (p<0.001, p<0.001), fibrinogen levels (p=0.032, p=0.036), tumour status (p=0.005, p=0.003), nodal status (p<0.001, p<0.001), metastasis status (p<0.001, p<0.001) and TNM stages (p<0.001, p<0.001) were remarkably associated with DFS and OS. Multivariate Cox regression analysis suggested that the levels of PT (HR: 2.699, p=0.006) and APTT (HR: 1.942, p=0.015), metastasis status (HR: 2.091, p= 0.015) and TNM stage (HR: 7.086, p=0.006) were independent predictors of survival in CRC. In the whole cohort, the enrolled patients were then divided into three groups according to their PT and APTT levels. The OS and DFS differed notably among the low-risk (PT<11.85 sec and APTT<25.85 sec), medium-risk (PT≥11.85 sec or APTT≥25.85 sec), and high-risk (PT≥11.85 sec and APTT≥25.85 sec) groups.

Conclusion

Elevated levels of preoperative PT and APTT were predictors of poor outcomes in CRC patients. Moreover, the combination of preoperative PT and APTT can be a new prognostic stratification approach for more precise clinical staging of CRC.

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

BACKGROUND

Large-cell neuroendocrine carcinoma of the lung (LCNEC) and small-cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC.

METHODS

GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein-protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re-analyzed, and potential interactions between these genes and miRNAs were explored via FunRich.

RESULTS

A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug-resistance, radio-sensitivity, or autophagy in lung cancer.

CONCLUSION

This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.

Ki-67 Labeling Index in Pulmonary Carcinoid Tumors: Comparison Between Small Biopsy and Resection Using Tumor Tracing and Hot Spot Methods

CONTEXT.—

Pulmonary carcinoids are classified as typical or atypical by assessing necrosis and mitoses, which usually cannot be adequately assessed on small biopsies. Ki-67 is not currently used to grade pulmonary carcinoids, but it may be helpful to determine preliminary grade in biopsies. However, the rate at which Ki-67 could underestimate or overestimate grade on small biopsies has not been well studied.

OBJECTIVE.—

To compare Ki-67 labeling obtained on small biopsies to subsequent resection.

DESIGN.—

Ki-67 was performed on paired biopsy and resection specimens from 55 patients. Slides were scanned using Aperio ScanScope. Labeling index was determined using automated hot spot and tumor tracing methods.

RESULTS.—

The study included 41 typical and 14 atypical carcinoids. Atypical carcinoids were larger and had more distant metastases. Death from disease occurred in 3 patients (all had atypical carcinoids). Median hot spot Ki-67 labeling index was greater in resection compared with biopsy by 0.7% (P = .02). Median tumor tracing Ki-67 was lower in resection compared with biopsy by 0.5% (P < .001). Receiver-operating characteristic analysis showed similar hot spot Ki-67 cutoffs to predict atypical histology (3.5% for biopsy, 3.6% for resection; area under the curve [AUC], 0.75 and 0.74, respectively). Different optimal cutoffs were needed for tracing method based on biopsy (2.1%; AUC, 0.75) compared with resection (1.0%; AUC, 0.67).

CONCLUSIONS.—

Hot spot Ki-67 tends to underestimate grade on small biopsies, whereas grade is overestimated by tumor tracing. Hot spot Ki-67 cutoff of 3.5% predicted atypical histology for both biopsy and resection. Different biopsy and resection cutoffs were necessary for tumor tracing, which would make clinical implementation more difficult.

Joint Transcriptomic Analysis of Lung Cancer and Other Lung Diseases

Background: Epidemiological and clinical evidence points cancer comorbidity with pulmonary chronic disease. The acquisition of some hallmarks of cancer by cells affected with lung pathologies as a cell adaptive mechanism to a shear stress, suggests that could be associated with the establishment of tumoral processes. Objective: To propose a bioinformatic pipeline for the identification of all deregulated genes and the transcriptional regulators (TFs) that are coexpressed during lung cancer establishment, and therefore could be important for the acquisition of the hallmarks of cancer. Methods: Ten microarray datasets (six of lung cancer, four of lung diseases) comparing normal and diseases-related lung tissue were selected to identify hub differentiated expressed genes (DEGs) in common between lung pathologies and lung cancer, along with transcriptional regulators through the utilization of specialized libraries from R language. DAVID bioinformatics tool for gene enrichment analyses was used to identify genes with experimental evidence associated to tumoral processes and signaling pathways. Coexpression networks of DEGs and TFs in lung cancer establishment were created with Coexnet library, and a survival analysis of the main hub genes was made. Results: Two hundred ten DEGs were identified in common between lung cancer and other lung diseases related to the acquisition of tumoral characteristics, which are coexpressed in a lung cancer network with TFs, suggesting that could be related to the establishment of the tumoral pathology in lung. The comparison of the coexpression networks of lung cancer and other lung diseases allowed the identification of common connectivity patterns (CCPs) with DEGs and TFs correlated to important tumoral processes and signaling pathways, that haven´t been studied to experimentally validate their role in the early stages of lung cancer. Some of the TFs identified showed a correlation between its expression levels and the survival of lung cancer patients. Conclusion: Our findings indicate that lung diseases share genes with lung cancer which are coexpressed in lung cancer, and might be able to explain the epidemiological observations that point to direct and inverse comorbid associations between some chronic lung diseases and lung cancer and represent a complex transcriptomic scenario.

Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA‑gene pairs in small‑cell lung cancer

Small-cell lung cancer (SCLC) is a type of lung cancer with early metastasis, and high recurrence and mortality rates. The molecular mechanism is still unclear and further research is required. The aim of the present study was to examine the pathogenesis and potential molecular markers of SCLC by comparing the differential expression of mRNA and microRNA (miRNA) between SCLC tissue and normal lung tissue. A transcriptome sequencing dataset (GSE6044) and a non-coding RNA sequence dataset (GSE19945) were downloaded from the Gene Expression Omnibus (GEO) database. In total, 451 differentially expressed genes (DEGs) and 134 differentially expressed miRNAs (DEMs) were identified using the R limma software package and the GEO2R tool of the GEO, respectively. The Gene Ontology function was significantly enriched for 28 terms, and the Kyoto Encyclopedia of Genes and Genomes database had 19 enrichment pathways, mainly related to ‘cell cycle’, ‘DNA replication’ and ‘oocyte meiosis mismatch repair’. The protein-protein interaction network was constructed using Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities in SCLC. The 1,402 miRNA-gene pairs encompassed 602 target genes of the DEMs using miRNAWalk, which is a bioinformatics platform that predicts DEM target genes and miRNA-gene pairs. There were 19 overlapping genes regulated by 32 miRNAs between target genes of the DEMs and DEGs. Bioinformatics analysis may help to better understand the role of DEGs, DEMs and miRNA-gene pairs in cell proliferation and signal transduction. The related hub genes may be used as biomarkers for the diagnosis and prognosis of SCLC, and as potential drug targets.

Histological type distribution and expression of nm23, VEGF, TOP2A and MUM-1 in peripheral T-cell and NK-cell lymphomas in Chinese: analysis of 313 cases

Peripheral T cell and natural killer cell lymphomas (PT/NKCLs) are rare malignant tumors of lymphoid tissue. The incidence varies by geographical region and race. We reclassified 313 cases of PT/NKCLs based on the 4th edition of the World Health Organization (WHO) classification to demonstrate the distribution of each histologic type of PT/NKCLs in Chinese populations. In our series, extranodal NK/T-cell lymphoma (ENKT) was the most common (37.1%) type, followed by peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) (31.3%) and angioimmunoblastic T-cell lymphoma (AITL) (12.8%). Also, we investigated the expression level of nm23, VEGF, TOP2A, and MUM-1 in all 313 cases. The positive rate of nm23, VEGF, TOP2A, and MUM-1 expression was more than 50% in most histologic types. Among the five common types, the expression rate of nm23 (34.5%) and TOP2A (27.6%) in ENKT were the lowest (P<0.05). VEGF expression was also lowest in ENKT (26.7%), but it was much higher in PTCL-NOS (54.1%), AITL (70.0%), and ALCL-ALK- (56.5%) and ALCL-ALK+ (42.9%). The difference of VEGF expression between ENKT and PTCL-NOS and AITL was significant (P<0.05). Fourteen of 23 (60.9%) cases of ALCL-ALK- and 9 of 14 (64.3%) cases of ALCL-ALK+ were positive for MUM-1, which was much higher than in ENKT (19.8%), PTCL-NOS (26.5%) and AITL (35.0%) (P<0.05). Although the significance of their expression in PT/NKCLs is not clear, we suggested that they may be novel tumor markers for developing targeted therapy in the future.

Immunohistochemical Biomarkers of Gastrointestinal, Pancreatic, Pulmonary, and Thymic Neuroendocrine Neoplasms

Neuroendocrine neoplasms (NENs) are a heterogeneous group of epithelial neoplastic proliferations that irrespective of their primary site share features of neural and endocrine differentiation including the presence of secretory granules, synaptic-like vesicles, and the ability to produce amine and/or peptide hormones. NENs encompass a wide spectrum of neoplasms ranging from well-differentiated indolent tumors to highly aggressive poorly differentiated neuroendocrine carcinomas. Most cases arise in the digestive system and in thoracic organs, i.e., the lung and thymus. A correct diagnostic approach is crucial for the management of patients with both digestive and thoracic NENs, because their high clinical and biological heterogeneity is related to their prognosis and response to therapy. In this context, immunohistochemistry represents an indispensable diagnostic tool that pathologists need to use for the correct diagnosis and classification of such neoplasms. In addition, immunohistochemistry is also useful in identifying prognostic and theranostic markers. In the present article, the authors will review the role of immunohistochemistry in the routine workup of digestive and thoracic NENs.

Qualitative and Quantitative Analysis of Cardiac Progenitor Cells in Cases of Myocarditis and Cardiomyopathy

We aimed to identify and quantify CD117⁺ and CD90⁺ endogenous cardiac progenitor cells (CPC) in human healthy and diseased hearts. We hypothesize that these cells perform a locally acting, contributing function in overcoming medical conditions of the heart by endogenous means. Human myocardium biopsies were obtained from 23 patients with the following diagnoses: Dilatative cardiomyopathy (DCM), ischemic cardiomyopathy (ICM), myocarditis, and controls from healthy cardiac patients. High-resolution scanning microscopy of the whole slide enabled a computer-based immunohistochemical quantification of CD117 and CD90. Those signals were evaluated by Definiens Tissue Phenomics® Technology. Co-localization of CD117 and CD90 was determined by analyzing comparable serial sections. CD117⁺/CD90⁺ cardiac cells were detected in all biopsies. The highest expression of CD90 was revealed in the myocarditis group. CD117 was significantly higher in all patient groups, compared to healthy specimens (^*p < 0.05). The highest co-expression was found in the myocarditis group (6.75 ± 3.25 CD90⁺CD117⁺ cells/mm²) followed by ICM (4 ± 1.89 cells/mm²), DCM (1.67 ± 0.58 cells/mm²), and healthy specimens (1 ± 0.43 cells/mm²). We conclude that the human heart comprises a fraction of local CD117⁺ and CD90⁺ cells. We hypothesize that these cells are part of local endogenous progenitor cells due to the co-expression of CD90 and CD117. With novel digital image analysis technologies, a quantification of the CD117 and CD90 signals is available. Our experiments reveal an increase of CD117 and CD90 in patients with myocarditis.

Proliferation markers RacGAP1 and Ki-67 in gastrointestinal stromal tumors by immunohistochemistry with respect to clinicopathological features and different risk stratification systems

RacGAP1 is a protein associated with cell proliferation, cell growth regulation, cell transformation and metastasis. The present study was designed to evaluate RacGAP1 expression in gastrointestinal stromal tumors (GISTs) for the first time in the literature and to determine its association with some predictive clinicopathological features, Ki-67 proliferation index, and risk stratification systems of Armed Forces Institute of Pathology (AFIP) and modified National Institutes of Health (NIH). Paraffin-embedded tissues of 100 GISTs were investigated, retrospectively. High (≥10%) Ki-67 proliferation index, higher mitotic count, high cellularity, small intestinal location, and high-risk groups according to both AFIP and modified NIH criteria were found to be correlated with RacGAP1 positivity in the univariate analysis (all P values <0.05). The association between RacGAP1 expression and higher cellularity was supported by the multivariate analysis (P=0.023). High (≥10%) Ki-67 proliferation index was correlated with higher nuclear pleomorphism, necrosis, ulceration, small intestinal location, greater tumor size, higher mitotic count, and high risk group according to AFIP and NIH criteria in the univariate analysis (all P values <0.05). The correlation of Ki-67 proliferation index and mitotic count and high risk group according to AFIP criteria was confirmed by the multivariate analysis (all P values <0.05). In conclusion, higher RacGAP1 expression and Ki-67 index might be considered as effective complementation of risk stratification systems and unfavorable clinicopathological features in predicting poor outcome of GISTs. However, the utility of RacGAP1 expression in GISTs should be further validated in larger cohorts of patients with long-term follow-up data.

An Improved Isoform-Selective Assay for Sphingosine Kinase 1 Activity

Sphingosine kinases (SK) are the sole enzymes responsible for the production of sphingosine 1-phosphate (S1P). S1P is a signaling molecule with a plethora of targets, acting as both a second messenger intracellularly and extracellularly via a family of cell surface G-protein-coupled S1P receptors. The two sphingosine kinases, SK1 and SK2, arise from different genes and have some distinct and overlapping cellular functions that are regulated in part by differential cellular localization, developmental expression, and catalytic properties. Here, we describe an improved method for selectively detecting SK1 activity in vitro and cell lysates via the use of the zwitterionic detergent CHAPS, which effectively inhibits SK2 activity and thus allows selective analysis of SK1 activity in a range of cell samples. The assay measures the production of ³²P-labeled S1P following the addition of exogenous sphingosine and [γ³²P]ATP. The S1P product can be purified by Bligh-Dyer solvent extraction, separated by thin layer chromatography (TLC), and the radiolabeled S1P quantified by exposing the TLC plate to a storage phosphor screen. This sensitive, reproducible assay can be used to selectively detect SK1 activity in tissue, cell, and recombinant protein samples.

Recent updates on grading and classification of neuroendocrine tumors

Neuroendocrine tumors (NETs) are originating from neuroendocrine cells in diffuse endocrine systems. NETs are diagnosed by characteristic histologic features and immunoprofiles. Recent 2010 WHO classification for gastroenteropancreatic NETs introduced grading system based on mitotic count and Ki-67 proliferation index. Gastroenteropancreatic NETs are classified as NET grade 1, NET grade 2, and neuroendocrine carcinoma (NET grade 3). However, the carcinoid is still used in classification of NETs of the lung and uterine cervix. Some issues with grading system such as methodologies for evaluation of Ki-67 index and subclassification of neuroendocrine carcinoma (NET grade 3) are arising. The importance of Ki-67 labeling index is emerging in differential diagnosis of lung carcinoids. In this review, we focus on recent grading and classification of NETs and related issues in various organs, including gastrointestinal tract, pancreas, lung, and female reproductive organs.