Different Stages Of Tumor Development Research Articles

Differential cellular communication in tumor immune microenvironment during early and advanced stages of lung adenocarcinoma.

Heterogeneous behavior of each cell type and their cross-talks in tumor immune microenvironment (TIME) refers to tumor immunological heterogeneity that emerges during tumor progression and represents formidable challenges for effective anti-tumor immune response and promotes drug resistance. To comprehensively elucidate the heterogeneous behavior of individual cell types and their interactions across different stages of tumor development at system level, a computational framework was devised that integrates cell specific data from single-cell RNASeq into networks illustrating interactions among signaling and metabolic response genes within and between cells in TIME. This study identified stage specific novel markers which remodel the cross-talks, thereby facilitating immune stimulation. Particularly, multicellular knockout of metabolic gene APOE (Apolipoprotein E in mast cell, myeloid cell and fibroblast) combined with signaling gene CAV1 (Caveolin1 in endothelial and epithelial cells) resulted in the activation of T-cell mediated signaling pathways. Additionally, this knockout also initiated intervention of cytotoxic gene regulations during tumor immune cell interactions at the early stage of Lung Adenocarcinoma (LUAD). Furthermore, a unique interaction motif from multiple cells emerged significant in regulating the overall immune response at the advanced stage of LUAD. Most significantly, FCER1G (Fc Fragment of IgE Receptor Ig) was identified as the common regulator in activating the anti-tumor immune response at both stages. Predicted markers exhibited significant association with patient overall survival in patient specific dataset. This study uncovers the significance of signaling and metabolic interplay within TIME and discovers important targets to enhance anti-tumor immune response at each stage of tumor development.

Machine learning-based new classification for immune infiltration of gliomas.

Glioma is a highly heterogeneous and poorly immunogenic malignant tumor, with limited efficacy of immunotherapy. The characteristics of the immunosuppressive tumor microenvironment (TME) are one of the important factors hindering the effectiveness of immunotherapy. Therefore, this study aims to reveal the immune microenvironment (IME) characteristics of glioma and predict different immune subtypes using machine learning methods, providing guidance for immune therapy in glioma. We first performed unsupervised cluster analysis on the genes and arrays of 693 gliomas in CGGA database and 702 gliomas in TCGA database. Then establish and verify the classification model through Machine Learning (ML). Then, use DAVID to perform functional enrichment analysis for different immune subtypes. Next step, analyze the immune cell distribution, stemness maintenance, mesenchymal phenotype, neuronal phenotype, tumorigenic cytokines, molecular and clinical characteristics of different immune subtypes of gliomas. Firstly, we divide the IME of gliomas in the CGGA database into four different subtypes, namely IM1, IM2, IM3, and IM4; similarly, the IME of gliomas in the TCGA database can also be divided into four different subtypes (IMA, IMB, IMC, and IMD). Next, based on ML, we developed a highly reliable model for predicting different immune subtypes of glioma. Then, we found that Monocytic lineage, Myeloid dendritic cells, NK cells and CD8 T cells had the highest enrichment in the IM1/IMD subtypes. Cytotoxic lymphocytes were highest expressed in the IM4/IMA subtypes. Next step, Enrichment analysis revealed that the IM1-IMD subtypes were mainly closely related to the production and secretion of IL-8 and TNF signaling pathway. The IM2-IMB subtypes were strongly associated with leukocyte activation and NK cell mediated cytotoxicity. The IM3-IMC subtypes were closely related to mitotic nuclear division and mitotic cell cycle process. The IM4-IMA subtypes were strongly associated with Central Nervous System (CNS) development and striated muscle tissue development. Afterwards, Single sample gene set enrichment analysis (ssGSEA) showed that stemness maintenance phenotypes were mainly enriched in the IM4/IMA subtypes; Neuronal phenotypes were closely associated with the IM2/IMB subtypes; and mesenchymal phenotypes and tumorigenic cytokines were highly correlated with the IM2 /IMB subtypes. Finally, we found that compared with patients in the IM2/IMB and IM4/IMA subtypes, the IM1/IMD and IM3/IMC subtypes have the highest proportion of GBM patients, the shortest average overall survival of patients and the lowest proportion of patients with IDH mutation and 1p36/19q13 co-deletion. We developed a highly reliable model for predicting different immune subtypes of glioma by ML. Then, we comprehensively analyzed the immune infiltration, molecular and clinical features of different immune subtypes of gliomas and defined gliomas into four subtypes: immunogenic subtype, adaptive immune resistance subtype, mesenchymal subtype, and immune tolerance subtype, which represent different TMEs and different stages of tumor development.

The Pivotal Role of Preclinical Animal Models in Anti-Cancer Drug Discovery and Personalized Cancer Therapy Strategies.

The establishment and utilization of preclinical animal models constitute a pivotal aspect across all facets of cancer research, indispensably contributing to the comprehension of disease initiation and progression mechanisms, as well as facilitating the development of innovative anti-cancer therapeutic approaches. These models have emerged as crucial bridges between basic and clinical research, offering multifaceted support to clinical investigations. This study initially focuses on the importance and benefits of establishing preclinical animal models, discussing the different types of preclinical animal models and recent advancements in cancer research. It then delves into cancer treatment, studying the characteristics of different stages of tumor development and the development of anti-cancer drugs. By integrating tumor hallmarks and preclinical research, we elaborate on the path of anti-cancer drug development and provide guidance on personalized cancer therapy strategies, including synthetic lethality approaches and novel drugs widely adopted in the field. Ultimately, we summarize a strategic framework for selecting preclinical safety experiments, tailored to experimental modalities and preclinical animal species, and present an outlook on the prospects and challenges associated with preclinical animal models. These models undoubtedly offer new avenues for cancer research, encompassing drug development and personalized anti-cancer protocols. Nevertheless, the road ahead continues to be lengthy and fraught with obstacles. Hence, we encourage researchers to persist in harnessing advanced technologies to refine preclinical animal models, thereby empowering these emerging paradigms to positively impact cancer patient outcomes.

Clustering-Guided Twin Contrastive Learning for Endomicroscopy Image Classification.

Learning better representations is essential in medical image analysis for computer-aided diagnosis. However, learning discriminative semantic features is a major challenge due to the lack of large-scale well-annotated datasets. Thus, how can we learn a well-structured categorizable embedding space in limited-scale and unlabeled datasets? In this paper, we proposed a novel clustering-guided twin-contrastive learning framework (CTCL) that learns the discriminative representations of probe-based confocal laser endomicroscopy (pCLE) images for gastrointestinal (GI) tumor classification. Compared with traditional contrastive learning, in which only two randomly augmented views of the same instance are considered, the proposed CTCL aligns more semantically related and class-consistent samples by clustering, which improved intra-class tightness and inter-class variability to produce more informative representations. Furthermore, based on the inherent properties of CLE (geometric invariance and intrinsic noise), we proposed to regard CLE images with any angle rotation and CLE images with different noises as the same instance, respectively, for increased variability and diversity of samples. By optimizing CTCL in an end-to-end expectation-maximization framework, comprehensive experimental results demonstrated that CTCL-based visual representations achieved competitive performance on each downstream task as well as more robustness and transferability compared with existing state-of-the-art SSL and supervised methods. Notably, CTCL achieved 75.60%/78.45% and 64.12%/77.37% top-1 accuracy on the linear evaluation protocol and few-shot classification downstream tasks, respectively, which outperformed the previous best results by 1.27%/1.63% and 0.5%/3%, respectively. The proposed method holds great potential to assist pathologists in achieving an automated, fast, and high-precision diagnosis of GI tumors and accurately determining different stages of tumor development based on CLE images.

Revealing molecular and cellular heterogeneity in hypopharyngeal carcinogenesis through single-cell RNA and TCR/BCR sequencing.

Hypopharyngeal squamous cell carcinoma (HSCC) is one of the malignant tumors with the worst prognosis in head and neck cancers. The transformation from normal tissue through low-grade and high-grade intraepithelial neoplasia to cancerous tissue in HSCC is typically viewed as a progressive pathological sequence typical of tumorigenesis. Nonetheless, the alterations in diverse cell clusters within the tissue microenvironment (TME) throughout tumorigenesis and their impact on the development of HSCC are yet to be fully understood. We employed single-cell RNA sequencing and TCR/BCR sequencing to sequence 60,854 cells from nine tissue samples representing different stages during the progression of HSCC. This allowed us to construct dynamic transcriptomic maps of cells in diverse TME across various disease stages, and experimentally validated the key molecules within it. We delineated the heterogeneity among tumor cells, immune cells (including T cells, B cells, and myeloid cells), and stromal cells (such as fibroblasts and endothelial cells) during the tumorigenesis of HSCC. We uncovered the alterations in function and state of distinct cell clusters at different stages of tumor development and identified specific clusters closely associated with the tumorigenesis of HSCC. Consequently, we discovered molecules like MAGEA3 and MMP3, pivotal for the diagnosis and treatment of HSCC. Our research sheds light on the dynamic alterations within the TME during the tumorigenesis of HSCC, which will help to understand its mechanism of canceration, identify early diagnostic markers, and discover new therapeutic targets.

Matrix Metalloproteinase-7 Promoter Site Single Nucleotide Polymorphism (-181A>G) in Epithelial Ovarian Cancer in the Eastern Indian Population.

Matrix metalloproteinase-7 (MMP7) plays multiple roles in different stages of tumor development. Elevated MMP7 activity has been reported in ovarian cancer. Single nucleotide polymorphism (SNP) of promoter sites of the MMP7 gene has been shown to cause alteration in gene expression, hence resulting in changes in susceptibility to various diseases and tumor development. The current study evaluated the association of epithelial ovarian cancer risk with MMP7 promoter site -181A>G polymorphism in the population of eastern India. The present case-control study included 64 histopathologically confirmed cases of epithelial ovarian cancer and 100 control subjects. The MMP7 -181A/G polymorphism was identified using polymerase chain reaction-restriction fragment length polymorphism. The association between genotypes and epithelial ovarian cancer risk was analyzed by odds ratio (OR) with a 95% confidence interval. The frequencies of AA, AG, and GG genotypes in ovarian cancer cases were 37.5%, 46.9%, and 15.6%, respectively, while that of control subjects were 56%, 36%, and 8%, respectively, in the study population. By taking the wild-type AA genotype as a reference, it was found that genotypeGG was associated with a significant risk for epithelial ovarian cancer (OR: 2.92). Frequency distribution of genotypes did not show any significant association with tumor characteristics like the International Federation of Gynecology and Obstetrics (FIGO) stage, histology, lymph node status, and distant metastasis. The present study demonstrated the association of MMP7 promoter site -181 GG genotype and the G allele with increased risk for epithelial ovarian cancer in the eastern Indian population.

Implications of oral dysbiosis and HPV infection in head and neck cancer: from molecular and cellular mechanisms to early diagnosis and therapy.

Head and neck cancer (HNC) is the sixth most common type of cancer, with more than half a million new cases annually. This review focuses on the role of oral dysbiosis and HPV infection in HNCs, presenting the involved taxons, molecular effectors and pathways, as well as the HPV-associated particularities of genetic and epigenetic changes and of the tumor microenvironment occurred in different stages of tumor development. Oral dysbiosis is associated with the evolution of HNCs, through multiple mechanisms such as inflammation, genotoxins release, modulation of the innate and acquired immune response, carcinogens and anticarcinogens production, generation of oxidative stress, induction of mutations. Thus, novel microbiome-derived biomarkers and interventions could significantly contribute to achieving the desideratum of personalized management of oncologic patients, regarding both early diagnosis and treatment. The results reported by different studies are not always congruent regarding the variations in the abundance of different taxons in HNCs. However, there is a consistent reporting of a higher abundance of Gram-negative species such as Fusobacterium, Leptotrichia, Treponema, Porphyromonas gingivalis, Prevotella, Bacteroidetes, Haemophilus, Veillonella, Pseudomonas, Enterobacterales, which are probably responsible of chronic inflammation and modulation of tumor microenvironment. Candida albicans is the dominant fungi found in oral carcinoma being also associated with shorter survival rate. Specific microbial signatures (e.g., F. nucleatum, Bacteroidetes and Peptostreptococcus) have been associated with later stages and larger tumor, suggesting their potential to be used as biomarkers for tumor stratification and prognosis. On the other hand, increased abundance of Corynebacterium, Kingella, Abiotrophia is associated with a reduced risk of HNC. Microbiome could also provide biomarkers for differentiating between oropharyngeal and hypopharyngeal cancers as well as between HPV-positive and HPV-negative tumors. Ongoing clinical trials aim to validate non-invasive tests for microbiome-derived biomarkers detection in oral and throat cancers, especially within high-risk populations. Oro-pharyngeal dysbiosis could also impact the HNCs therapy and associated side-effects of radiotherapy, chemotherapy, and immunotherapy. HPV-positive tumors harbor fewer mutations, as well as different DNA methylation pattern and tumor microenvironment. Therefore, elucidation of the molecular mechanisms by which oral microbiota and HPV infection influence the HNC initiation and progression, screening for HPV infection and vaccination against HPV, adopting a good oral hygiene, and preventing oral dysbiosis are important tools for advancing in the battle with this public health global challenge.

Wide-Range SPRi Sensors Based on Aptamer/sPD-L1/anti–PD-L1 Sandwich and AuNPs Enhancement for Ultrasensitive Detection of sPD-L1

Soluble programmed death-ligand 1 (sPD-L1) levels vary widely among different stages of tumor development, so the direct quantification of sPD-L1 as a cancer biomarker is useful in cancer diagnosis, prognosis and therapeutic assessment. There is an urgent need for an sPD-L1 detection method with a broad detection range and high sensitivity for monitoring cancer progression and evaluating the effectiveness of immunotherapy in real time. Herein, we have reported an enzyme-free, label-free surface plasmon resonance imaging (SPRi) sensor based on an aptamer/sPD-L1/anti–PD-L1 sandwich structure with gold nanoparticle (AuNP) signal enhancement for the ultrasensitive quantitative measurement of sPD-L1 for the first time. The gold chip of the SPRi sensing platform was modified by DNA aptamers, sPD-L1 was specifically adsorbed on the surface of a DNA aptamer-modified gold chip and then coupled with anti–PD-L1. Thus, the detection of sPD-L1 at different concentrations was realized through the formation of an aptamer/sPD-L1/anti–PD-L1 sandwich structure. We also enhanced the SPR signal via AuNPs to further improve sensor sensitivity. The SPRi sensor is able to measure sPD-L1 within a linear range of 50 pM–10 nM and 100 fM–50 pM, and the minimum detection limit is 19 fM. The sensor is designed to be widely applicable, with better accuracy and reliability for more application scenarios. The prepared SPRi sensor shows great potential in improving the sensitivity of detecting sPD-L1. The proposed method demonstrates the excellent performance of the SPRi sensor and provides a possibility for the establishment of effective clinical assay methods in the future.

P21 Tyrosine and serine STAT3 phosphorylation drives cutaneous squamous cell carcinoma in recessive dystrophic epidermolysis bullosa as demonstrated using a 3D in vitro model

Abstract The early onset of aggressive cutaneous squamous cell carcinoma (cSCC) and its rapid progression in recessive dystrophic epidermolysis bullosa (RDEB) leads to nearly 100% mortality rates in these patients. Elevated levels of phospho-STAT3 on tyrosine residue (STAT3Tyr705) have been intensively demonstrated in RDEB-derived cSCC cells, demonstrating that the constitutive activation and dysregulation of the Janus kinase (JAK)/STAT pathway plays a role in RDEB cSCC pathogenesis. We efficiently applied ruxolitinib (JAK1/2 inhibitor that blocks phosphorylation on STAT3Tyr705) to a RDEB–cSCC xenograph mouse model, reducing the size of small tumours but found that it was insufficient to reduce bigger tumours completely. Recently, phosphorylation at serine-727 (STAT3Ser727) has been shown to be relevant in the evolution of some cancers, but it has not yet been studied in RDEB cSCC. We hypothesized that phosphorylation at serine-727 of the STAT3 pathway might play a role in RDEB cSCC tumour development and progression, and could not be inhibited by ruxolitinib. To validate our hypothesis, we studied two RDEB cSCC human patient samples with different degrees of dedifferentiation (normal RDEB skin, edge of the tumour and centre of the RDEB cSCC). We demonstrated that STAT3Tyr705 was preferentially upregulated in the normal RDEB skin followed by the tumour edge skin, presenting less phosphorylation on the tumour. When we analysed STAT3 phosphorylation on STAT3Ser727, we could see that it presented the opposite phosphorylation pattern, being more phosphorylated in the tumour and less in normal RDEB skin. Furthermore, we validated the STAT3Ser727residue pattern across other cSCC cell lines and found that serine phosphorylation is present in other SCCs, demonstrating its crucial role in tumour development. To further investigate and analyse cancer progression in more detail, an easy and robust RDEB cSCC model is instrumental. Therefore, we generated RDEB cSCC spheroids in vitro, which has four key advantages over the previous models developed: (i) it is easy to generate; (ii) small amounts of cells are required; (iii) it is suitable for drug testing; and (iv) it can be used to recapitulate different stages of tumour development. We have been able to control their size and use them for drug testing, observing a 20% size decrease after 6 days of ruxolitinib treatment. Taken together, this three-dimensional RDEB cSCC in vitro model, along with analysis of human samples, will allow us to better understand RDEB cSCC progression at different stages, allowing us to investigate new treatments for RDEB cSCC.

BACCHARIN FROM GREEN PROPOLIS: A REVIEW OF ITS ANTIPROLIFERATIVE EFFECTS

Baccharin (3-prenyl-4-dihydrocinnamoyloxy-cinnamic acid) is a prenylated phenolic compound found in the extract of the Baccharis dracunculifolia plant, as well as in green propolis. It is one of the main components of this resinous material, which results from the interaction between bees and plants. This substance has been extensively studied for its biological effects, mainly its anti-inflammatory and antitumor activities. In this literature review, we have compiled several articles available between 1999 and 2022 that discuss scientific research carried out on baccharin. The objective is to explore the already evaluated beneficial effects of this compound in different types of tumors. The cancer begins with a genetic mutation that transforms a normal cell into a mutated cell. Subsequently, important mechanisms for its development and progression occur, including increased proliferation, evasion of apoptosis, angiogenesis, invasion, and metastasis. In this regard, numerous studies are being conducted to identify natural compounds that can act on these stages of carcinogenesis, including the components of green propolis. It has already been demonstrated that baccharin can act at different stages of tumor development, exhibiting antimitotic, antiangiogenic, pro-apoptotic, and immunomodulatory activities. Additionally, baccharin has been found to interfere with carcinogenic metabolic pathways and exhibit genotoxic effects. Baccharin has demonstrated a significant antitumor activity when applied to melanoma cells, colon cancer, gastric cancer, hepatocarcinoma, sarcoma, prostate cancer, breast cancer, and leukemia tumor cells. Therefore, the studies cited in this review provide evidence of baccharin's ability to inhibit relevant steps in the carcinogenic process of different types of tumors.

Racial differences in prognostic role of white blood cell ratios in gastrointestinal stromal tumors.

e23507 Background: Gastrointestinal stromal tumors (GIST) are rare mesenchymal tumors with an estimated 3,300 to 6,000 new cases per year in the United States. Per SEER database, significant racial disparity exists with an incidence rate twice as high for African Americans as compared to Whites. Currently, parameters used in stratification of disease risk can only be determined by postoperative histopathological evaluation. Cancer-related inflammation is linked to different stages of tumor development so markers found in peripheral blood have been studied as surrogates. We present a study comparing the predictive prognostic ability of preoperative serum inflammatory markers in primary untreated GIST and highlight the differences between Black and White patients. Methods: This is a retrospective analysis of 149 patients who underwent operative resection of primary untreated GIST. Preoperative blood samples were used for the analysis. Patients were excluded if they showed clinical signs of infection during time of pre-operative blood sampling or had non-GIST synchronous malignancy. Clinicopathological data was obtained from patient chart review and logistic regression models were used to evaluate data. There is ongoing next-generation sequencing data analysis. Results: 149 patients were included: 80 (53.7%) Black, 43 (28.9%) White, 26 (17.5%) were other. The mean values for neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and monocyte to lymphocyte ratio (MLR) were 3.62 (SD 3.07), 191.55 (SD 119.15), and 0.47 (SD 0.49) respectively. On univariate analysis NLR and PLR were significant prognostic indicators of high and intermediate risk GISTs per the National Institute of Health (NIH) categories [NLR p = 0.008, PLR p = 0.007]. Upon subgroup analysis, NLR and PLR showed the highest statistical significance for predictors of high and intermediate risk GISTs among the Black patient population [NLR odds ratio (OR) 2.685; 95% confidence interval (CI) 0.976-7.381; p = 0.05 and PLR OR 1.792; 95% CI 1.054-3.049; p = 0.031]. The same was not shown to be true for the White patient population. 11 out 149 patients progressed since diagnosis of which 8 were Black and 3 White. 7 were in the high risk category, 3 in low risk and 1 in intermediate risk with an overall mean NLR and PLR 5.25 and 244 respectively. The average time to progression was noted to 28 months. Conclusions: The NLR and PLR are easily obtainable and cost-effective indexes which have the prognostic ability to serve as surrogates for high and intermediate risk GISTs. They appear to be more predictive in the Black patient population than in White. Further study is warranted for incorporation into risk stratification systems.

Plasma membrane Ca2+ pump isoform 4 function in cell migration and cancer metastasis.

The Ca2+ ion is a universal second messenger involved in many vital physiological functions including cell migration and development. To fulfil these tasks the cytosolic Ca2+ concentration is tightly controlled, and this involves an intricate functional balance between a variety of channels and pumps of the Ca2+ signalling machinery. Among these proteins, plasma membrane Ca2+ ATPases (PMCAs) represent the major high-affinity Ca2+ extrusion systems in the cell membrane that are effective in maintaining free Ca2+ concentration at exceedingly low cytosolic levels, which is essential for normal cell function. An imbalance in Ca2+ signalling can have pathogenic consequences including cancer and metastasis. Recent studies have highlighted the role of PMCAs in cancer progression and have shown that a particular variant, PMCA4b, is downregulated in certain cancer types, causing delayed attenuation of the Ca2+ signal. It has also been shown that loss of PMCA4b leads to increased migration and metastasis of melanoma and gastric cancer cells. In contrast, an increased PMCA4 expression has been reported in pancreatic ductal adenocarcinoma that coincided with increased cell migration and shorter patient survival, suggesting distinct roles of PMCA4b in various tumour types and/or different stages of tumour development. The recently discovered interaction of PMCAs with basigin, an extracellular matrix metalloproteinase inducer, may provide further insights into our understanding of the specific roles of PMCA4b in tumour progression and cancer metastasis.

Molecular regulation of prostate cancer by Galectin-3 and estrogen receptor.

Prostate cancer remains the most prevalent cancer among men worldwide. This cancer is hormone-dependent; therefore, androgen, estrogen, and their receptors play an important role in development and progression of this disease, and in emergence of the castration-resistant prostate cancer (CRPC). Galectins are a family of β-galactoside-binding proteins which are frequently altered (upregulated or downregulated) in a wide range of tumors, participating in different stages of tumor development and progression, but the molecular mechanisms which regulate its expression are still poorly understood. This review provides an overview of the current and emerging knowledge on Galectin-3 in cancer biology with focus on prostate cancer and the interplay with estrogen receptor (ER) signaling pathways, present in androgen-independent prostate cancer cells. We suggest a molecular mechanism where ER, Galectin-3 and β-catenin can modulate nuclear transcriptional events, such as, proliferation, migration, invasion, and anchorage-independent growth of androgen-independent prostate cancer cells. Despite a number of achievements in targeted therapy for prostate cancer, CRPC may eventually develop, therefore new effective drug targets need urgently to be found. Further understanding of the role of Galectin-3 and ER in prostate cancer will enhance our understanding of the molecular mechanisms of prostate cancer development and the future treatment of this disease.

Boosting few-shot confocal endomicroscopy image recognition with feature-level MixSiam.

As an emerging early diagnostic technology for gastrointestinal diseases, confocal laser endomicroscopy lacks large-scale perfect annotated data, leading to a major challenge in learning discriminative semantic features. So, how should we learn representations without labels or a few labels? In this paper, we proposed a feature-level MixSiam method based on the traditional Siamese network that learns the discriminative features of probe-based confocal laser endomicroscopy (pCLE) images for gastrointestinal (GI) tumor classification. The proposed method is divided into two stages: self-supervised learning (SSL) and few-shot learning (FS). First, in the self-supervised learning stage, the novel feature-level-based feature mixing approach introduced more task-relevant information via regularization, facilitating the traditional Siamese structure can adapt to the large intra-class variance of the pCLE dataset. Then, in the few-shot learning stage, we adopted the pre-trained model obtained through self-supervised learning as the base learner in the few-shot learning pipeline, enabling the feature extractor to learn richer and more transferable visual representations for rapid generalization to other pCLE classification tasks when labeled data are limited. On two disjoint pCLE gastrointestinal image datasets, the proposed method is evaluated. With the linear evaluation protocol, feature-level MixSiam outperforms the baseline by 6% (Top-1) and the supervised model by 2% (Top1), which demonstrates the effectiveness of the proposed feature-level-based feature mixing method. Furthermore, the proposed method outperforms the previous baseline method for the few-shot classification task, which can help improve the classification of pCLE images lacking large-scale annotated data for different stages of tumor development.

Characterization of the tumor-infiltrating immune repertoire in muscle invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease with several taxonomic molecular subtypes showing different genetic, clinical, and epidemiological profiles. It has been suggested that MIBC-subtypes follow different tumorigenesis pathways playing decisive roles at different stages of tumor development, resulting in distinct tumor microenvironment containing both innate and adaptive immune cells (T and B lymphocytes). We aim to characterize the MIBC tumor microenvironment by analyzing the tumor-infiltrating B and T cell repertoire according to the taxonomic molecular subtypes. RNAseq data from 396 MIBC samples included in TCGA were considered. The subtype information was collected from the international consensus taxonomic classification describing six subtypes: Basal/Squamous-like (Ba/Sq), Luminal papillary (LumP), Luminal non-Specify (LumNS), Luminal unstable (LumU), Stroma-rich, and Neuroendocrine-like (NE-like). Using MiXCR, we mapped the RNA read sequences to their respective B-cell receptor (BCR) and T-cell receptor (TCR) clonotypes. To evaluate the BCR and TCR differences among subtypes, we compared diversity measures (richness and diversity) using a Wilcoxon test and we performed a network analysis to characterize the clonal expansion. For the survival analysis stratified by subtypes, Cox regression models adjusted for age, region, and pathological stage were performed. Overall, we found different patterns of tumor-infiltrating immune repertoire among the different MIBC subtypes. Stroma-rich and Ba/Sq tumors showed the highest BCR and TCR infiltration while LumP showed the lowest. In addition, we observed that the Ba/Sq and Stroma-rich tumors were more clonally expanded than the Luminal subtypes. Moreover, higher TCR richness and diversity were significantly associated with better survival in the Stroma-rich and Ba/Sq subtypes. This study provides evidence that MIBC subtypes present differences in the tumor microenvironment, in particular, the Ba/Sq and the Stroma-rich are related with a higher tumoral-infiltrating immune repertoire, which seems to be translated into better survival. Determining the causes of the different tumoral-infiltrating immune repertoire according to the MIBC molecular subtypes will help to improve our understanding of the disease and the distinct responses to immunotherapy of MIBC.

Krüppel-like factors in tumors: Key regulators and therapeutic avenues.

Krüppel-like factors (KLFs) are a group of DNA-binding transcriptional regulators with multiple essential functions in various cellular processes, including proliferation, migration, inflammation, and angiogenesis. The aberrant expression of KLFs is often found in tumor tissues and is essential for tumor development. At the molecular level, KLFs regulate multiple signaling pathways and mediate crosstalk among them. Some KLFs may also be molecular switches for specific biological signals, driving their transition from tumor suppressors to promoters. At the histological level, the abnormal expression of KLFs is closely associated with tumor cell stemness, proliferation, apoptosis, and alterations in the tumor microenvironment. Notably, the role of each KLF in tumors varies according to tumor type and different stages of tumor development rather than being invariant. In this review, we focus on the advances in the molecular biology of KLFs, particularly the regulations of several classical signaling pathways by these factors, and the critical role of KLFs in tumor development. We also highlight their strong potential as molecular targets in tumor therapy and suggest potential directions for clinical translational research.

Glutathione and Its Metabolic Enzymes in Gliomal Tumor Tissue and the Peritumoral Zone at Different Degrees of Anaplasia.

This research was aimed at investigating the features of free radical activity and the parameters of glutathione metabolism in tumor tissues and the peritumoral zone at different degrees of glial tumor anaplasia. We analyzed postoperative material from 20 patients with gliomas of different degrees of anaplasia. The greatest differences compared to adjacent noncancerous tissues were found in the tumor tissue: an increased amount of glutathione and glutathione-related enzymes at Grades I and II, and a decrease of these parameters at Grades III and IV. For the peritumoral zone of Grades I and II, the indices changed in different directions, while for Grades III and IV, they occurred synchronously with the tumor tissue changes. For Low Grade and High Grade gliomas, opposite trends were revealed regarding changes in the level of glutathione and the enzymes involved in its metabolism and in the free radical activity in the peritumoral zone. The content of glutathione and the enzymes involved in its metabolism decreased with the increasing degree of glioma anaplasia. In contrast, free radical activity increased. The glutathione system is an active participant in the antioxidant defense of the body and can be used to characterize the cell condition of gliomas at different stages of tumor development.

Relationship between Glutathione-Dependent Enzymes and the Immunohistochemical Profile of Glial Neoplasms.

This research aimed to investigate the relationships between the parameters of glutathione metabolism and the immunohistochemical characteristics of glial tumors. Postoperative material from 20 patients with gliomas of different grades of anaplasia was analyzed. Bioinformatic analysis of the interactions between the gliomas’ immunohistochemical markers and their glutathione-dependent enzymes was carried out using the STRING, BioGrid, while Signor databases revealed interactions between such glioma markers as IDH and p53 and the glutathione exchange enzymes (glutathione peroxidase, glutathione reductase, glutathione S-transferase). The most pronounced relationship with glutathione metabolism was demonstrated by the level of the nuclear protein Ki67 as a marker of proliferative activity, and the presence of the IDH1 mutation as one of the key genetic events of gliomagenesis. The glutathione system is an active participant in the body’s antioxidant defense, involving the p53 markers and MGMT promoter methylation. It allows characterization of the gliomal cells’ status at different stages of tumor development.

Tumor accomplice: T cell exhaustion induced by chronic inflammation.

The development and response to treatment of tumor are modulated by inflammation, and chronic inflammation promotes tumor progression and therapy resistance. This article summarizes the dynamic evolution of inflammation from acute to chronic in the process of tumor development, and its effect on T cells from activation to the promotion of exhaustion. We review the mechanisms by which inflammatory cells and inflammatory cytokines regulate T cell exhaustion and methods for targeting chronic inflammation to improve the efficacy of immunotherapy. It is great significance to refer to the specific state of inflammation and T cells at different stages of tumor development for accurate clinical decision-making of immunotherapy and improving the efficiency of tumor immunotherapy.

Phytochemical analysis, cytostatic, cytotoxic, and anti-inflammatory effects of Arum palaestinum, Ocimum basilicum, and Trigonella foenum-graecum in human monocytic cell line (THP-1)-derived macrophages

The significance of the crosstalk between pro-inflammatory mediators and carcinogenesis is widely discussed. These mediators play decisive roles at different stages of tumor development, including initiation, promotion, and metastasis. Arum palaestinum Boiss., Ocimum basilicum L., and Trigonella foenum-graecum L. and their crude extracts are traditionally used in the Arab and Islamic herbal medicine to treat a variety of cancers and inflammatory illnesses. Human monocytic cell line (THP-1)-derived macrophages were used to evaluate anti-inflammatory, cytotoxic, and cytostatic effects of the ethanolic plant extracts. Cytotoxic and cytostatic effects were measured with the MTT assay. In addition, the production levels of pro-inflammatory mediators (TNF-α, IL-6, and nitric oxide) and anti-inflammatory cytokine (IL-10) were measured in lipopolysaccharide (LPS)-activated THP-1-derived macrophages in the absence and presence of increasing concentrations of the three plant extracts. The three plant extracts suppressed the production of NO and TNF-α and IL-6, and enhanced the production of IL-10 in LPS-activated THP-1-derived macrophages. In addition, these extracts inhibited the growth of THP-1-derived macrophages in a concentration-dependent manner at nontoxic concentrations. T. foenum-graecum exhibited the highest cytostatic effects with an IC50 of 512 µg/ mL compared to O. basilicum (no cytostatic effects) and A. palaestinum (IC50=1274 µg/mL). Even though more studies are needed to elucidate the mechanisms of observed cytostatic and anti-inflammatory effects, to some extent, these effects could be attributed to the flavonoids, phenolic compounds, and tannin content detected in the plants’ extracts.