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With the escalating prevalence of obesity, the association between obesity and cancer is a growing public health concern. Obesity will soon surpass tobacco smoking as the most important preventable cause of cancer. Obesity-driven mechanisms can alter cell functions to induce metabolic changes, chronic inflammation, and insulin resistance that are believed to contribute to cancer risk and development; yet the specific underlying biological mechanisms of obesity-related cancer development are largely unknown. The Metabolic Dysregulation and Cancer Risk Program: a transdisciplinary approach to obesity-associated cancers (MeDOC) is a trans–National Cancer Institute research initiative supported by the Division of Cancer Control and Population Sciences, the Division of Cancer Biology, the Division of Cancer Prevention, and the Center to Reduce Cancer Health Disparities. The overall purpose of the MeDOC Program is to advance our understanding of the underlying mechanisms that connect obesity, metabolic dysregulation, and increased obesity cancer risk as well as identify markers that will enhance cancer risk prediction, improve screening for high-risk individuals, and identify targets for preventive and therapeutic interventions for cancer interception or treatment. This report describes the funded research projects, the Coordinating Center, and the goals of the MeDOC program. [ABSTRACT FROM AUTHOR]

In the recent decade, analysis of circulating tumor DNA (ctDNA) has improved cancer care by allowing for rapid detection of actionable molecular targets. A new generation of circulating DNA tests is now becoming available commercially. These tests are characterized by a superior limit of detection of 0.01% vaF or better, allowing for the detection of radiologically occult molecular residual disease (MRD). MRD tests have the potential to revolutionize neoadjuvant and adjuvant treatment. In addition, these tests can be used as tumor markers to assess disease response. We reviewed the current evidence for the use of high-sensitivity MRD assays with particular focus on the genitourinary tumors. Multiple studies have now been reported in urothelial, renal, and recently testicular carcinoma. We find that the sensitivity varies across tumor types in the adjuvant setting and may reach a high of 100% in urothelial cancer. Specificity in tumor-informed MRD appears to be preserved across tumor types (98%-100%). Several trials are now prospectively validating MRD testing in biomarker integral studies, mainly in urothelial carcinoma. [ABSTRACT FROM AUTHOR]

Despite advances in treatment strategies, breast cancer (BC) remains one of the most prevalent cancers worldwide. Recent studies implicate the gut microbiome as a potential risk factor for BC development. Alterations in gut microbial diversity resulting in dysbiosis have been linked to breast carcinogenesis by modulating host immune responses and inflammatory pathways, favoring tumorigenesis and progression. Moreover, gut microbiota populations are different between women with BC vs those that are cancer free, further implicating the role of the gut microbiome in cancer development. This alteration in gut microbiota is also associated with changes in estrogen metabolism, which strongly correlates with BC development. Gut microbiota that express the enzyme β-glucuronidase (GUS) may increase estrogen bioavailability by deconjugating estrogen-glucuronide moieties enabling reabsorption into circulation. Increased circulating estrogens may, in turn, drive estrogen receptor–positive BC. GUS-expressing microbiota also affect cancer therapy efficacy and toxicity by modifying glucuronide-conjugated drug metabolites. Therefore, GUS inhibitors have emerged as a potential antitumor treatment. However, the effectiveness of GUS inhibitors is still exploratory. Further studies are needed to determine how oral endocrine-targeting therapies may influence or be influenced by the microbiota and how that may affect carcinogenesis initiation and tumor recurrence. [ABSTRACT FROM AUTHOR]

Currently, cancer is the second leading cause of death worldwide, and potential targeted drugs and molecular pathways for cancer development and progression have been a hot research topic worldwide. In recent years, the importance of the kinase superfamily in diseases has been well demonstrated by studies on various molecular mechanisms of kinases and the successful application of their inhibitors in diseases. Pseudokinases are members of the kinase superfamily, which have been increasingly documented to play a crucial role in cancers year after year. As a member of pseudokinases, tribbles homolog 3 (TRIB3) also exerts diverse functions in different cancers through different interacting proteins and molecular pathways, especially in tumor immunity, stemness, drug resistance, metabolism, and autophagy. In addition, peptide drugs targeting TRIB3 have high specificity in preclinical studies, which shows great promise for TRIB3 application in diseases including cancers. In this review, we dissect diverse functions played by TRIB3 in different cancers, describing the underlying mechanisms in detail. Notably, inhibitors and agonists currently available for TRIB3 are discussed, indicating the potential for TRIB3 as a therapeutic target. [ABSTRACT FROM AUTHOR]

Lung cancer is a major contributor to cancer deaths worldwide and is on the rise. Although surgical resection has been widely used as a standard therapy for lung cancer patients, the relapse rate after surgery is high. It is still unclear whether there is a potential drug that can reduce the probability of postsurgical recurrence in lung cancer patients. We used 5 typical lung cancer cell lines as well as 41 lung cancer tissue samples and paracancer tissue samples to investigate the expression levels of interferon regulatory factor 6 (IRF6) and tumor suppressor candidate 2 (TUSC2, also known as FUS1). We also treated lung cancer cells (H322 and A549) with different concentrations of sevoflurane to study its influence on lung cancer cell tumorigenesis. Lentivirus-mediated gain-of-function studies of IRF6 and FUS1 were applied to validate the role of IRF6 and FUS1 in lung cancer. Next, we used short hairpin RNA-mediated loss of function of IRF6 and luciferase, chromatin immunoprecipitation assays to validate the regulatory role of IRF6 on FUS1. Our findings reported that IRF6 was upregulated in lung cancer tissues, while FUS1 was downregulated. Functional assays revealed that sevoflurane inhibits lung cancer development by downregulating IRF6 expression. Luciferase and chromatin immunoprecipitation-quantitative real-time PCR assays uncovered that IRF6 represses FUS1 transcriptional expression in lung cancer cells. We have shown that sevoflurane prevents lung cancer development by downregulating IRF6 to stimulate FUS1 transcription, indicating that sevoflurane can be used as the potential anesthetic drug in surgical resection to reduce postoperative tumor relapse in lung cancer patients. [ABSTRACT FROM AUTHOR]

Long intergenic noncoding RNAs (lincRNAs) do not overlap annotated coding genes and are located in intergenic regions, as opposed to antisense and sense-intronic lncRNAs, located in genic regions. LincRNAs influence gene expression profiles and are thereby key to disease pathogenesis. In this study, we assessed the association between lincRNAs and HPV16-positive cervical cancer (CaCx) pathogenesis using weighted gene co-expression network analysis (WGCNA) with coding genes, comparing differentially expressed lincRNA and coding genes (DElincGs and DEcGs, respectively) in HPV16-positive patients with CaCx (n  = 44) with those in HPV-negative healthy individuals (n  = 34). Our analysis revealed five DElincG modules, co-expressing and correlating with DEcGs. We validated a substantial number of such module-specific correlations in the HPV16-positive cancer TCGA-CESC dataset. Four such modules, displayed significant correlations with patient traits, such as HPV16 physical status, lymph node involvement and overall survival (OS), highlighting a collaborative effect of all genes within specific modules on traits. Using the DAVID bioinformatics knowledgebase, we identified the underlying biological processes associated with these modules as cancer development and progression-associated pathways. Next, we identified the top 10 DElincGs with the highest connectivity within each functional module. Focusing on the prognostic module hub genes, downregulated CTD-2619J13.13 expression was associated with poor patient OS. This lincRNA gene interacted with 25 coding genes of its module and was associated with such biological processes as keratinization loss and keratinocyte differentiation, reflecting severe disease phenotypes. This study has translational relevance in fighting various cancers with high mortality rates in underdeveloped countries. [ABSTRACT FROM AUTHOR]

Motivation Mutational signatures are a critical component in deciphering the genetic alterations that underlie cancer development and have become a valuable resource to understand the genomic changes during tumorigenesis. Therefore, it is essential to employ precise and accurate methods for their extraction to ensure that the underlying patterns are reliably identified and can be effectively utilized in new strategies for diagnosis, prognosis, and treatment of cancer patients. Results We present MUSE-XAE, a novel method for mutational signature extraction from cancer genomes using an explainable autoencoder. Our approach employs a hybrid architecture consisting of a nonlinear encoder that can capture nonlinear interactions among features, and a linear decoder which ensures the interpretability of the active signatures. We evaluated and compared MUSE-XAE with other available tools on both synthetic and real cancer datasets and demonstrated that it achieves superior performance in terms of precision and sensitivity in recovering mutational signature profiles. MUSE-XAE extracts highly discriminative mutational signature profiles by enhancing the classification of primary tumour types and subtypes in real world settings. This approach could facilitate further research in this area, with neural networks playing a critical role in advancing our understanding of cancer genomics. Availability and implementation MUSE-XAE software is freely available at https://github.com/compbiomed-unito/MUSE-XAE. [ABSTRACT FROM AUTHOR]

Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential correlations between samples and provide model interpretability. Herein, we propose a novel interpretable multi-omics data integration method (DeepKEGG) for cancer recurrence prediction and biomarker discovery. In DeepKEGG, a biological hierarchical module is designed for local connections of neuron nodes and model interpretability based on the biological relationship between genes/miRNAs and pathways. In addition, a pathway self-attention module is constructed to explore the correlation between different samples and generate the potential pathway feature representation for enhancing the prediction performance of the model. Lastly, an attribution-based feature importance calculation method is utilized to discover biomarkers related to cancer recurrence and provide a biological interpretation of the model. Experimental results demonstrate that DeepKEGG outperforms other state-of-the-art methods in 5-fold cross validation. Furthermore, case studies also indicate that DeepKEGG serves as an effective tool for biomarker discovery. The code is available at https://github.com/lanbiolab/DeepKEGG. [ABSTRACT FROM AUTHOR]

The article offers a perspective on lifileucel as a T-cell therapy approved by the U.S. Food and Drug Administration (FDA) for melanoma. It provides a history and evolution of tumor-infiltrating lymphocytes (TIL) for adoptive cell therapy and an overview of clinical trials supporting the use of TIL for metastatic melanoma. It considers data supporting the use of TIL prior to BRAF or MEK targeted small-molecule therapy inhibition for the treatment for metastatic melanoma.

Increasing environmental genotoxic chemicals have been shown to induce epigenetic alterations. However, the interaction between genetics and epigenetics in chemical carcinogenesis is still not fully understood. Here, we constructed an in vitro human lung carcinogenesis model (16HBE-T) by treating human bronchial epithelial cells with a typical significant carcinogen benzo(a)pyrene (BaP). We identified a novel circular RNA, circ0087385, which was overexpressed in 16HBE-T and human lung cancer cell lines, as well as in lung cancer tissues and serum exosomes from lung cancer patients. The upregulated circ0087385 after exposure to BaP promoted DNA damage in the early stage of chemical carcinogenesis and affected the cell cycle, proliferation, and apoptosis of the malignantly transformed cells. Overexpression of circ0087385 enhanced the expression of cytochrome P450 1A1 (CYP1A1), which is crucial for metabolically activating BaP. Interfering with circ0087385 or CYP1A1 reduced the levels of ultimate carcinogen benzo(a)pyrene diol epoxide (BPDE) and BPDE-DNA adducts. Interfering with CYP1A1 partially reversed the DNA damage induced by high expression of circ0087385, as well as decreased the level of BPDE and BPDE-DNA adducts. These findings provide novel insights into the interaction between epigenetics and genetics in chemical carcinogenesis which are crucial for understanding the epigenetic and genetic toxicity of chemicals. [ABSTRACT FROM AUTHOR]

Objectives: The aim is to evaluate the prevention and development of cervical cancer in systemic lupus erythematosus (SLE) patients in Japan and its background based on a questionnaire survey. Methods: The questionnaire was handed to 460 adult female SLE patients at 12 medical institutions. The participants were grouped by age, and data related to their human papillomavirus vaccination status, age at first coitus, cervical cancer screening, and diagnosis of cervical cancer were analysed. Results: A total of 320 responses were received. Patients aged 35–54 years included a higher proportion of patients whose age at first coitus was <20 years. This group also showed a higher rate of cervical cancer/dysplasia. Only nine patients had a human papillomavirus vaccination history. Adequate frequency of cervical cancer screening was slightly higher (52.1%) among SLE patients than in the Japanese general population. However, 23% of the patients had never undergone examination, primarily because of a feeling of troublesome. The incidence of cervical cancer was significantly higher among SLE patients. One reason for this may be associated with the use of immunosuppressants, although the difference was not significant. Conclusions: SLE patients are at a higher risk of cervical cancer and dysplasia. Rheumatologists should proactively recommend vaccination and screening examinations for SLE female patients. [ABSTRACT FROM AUTHOR]

Somatic copy number alterations (SCNAs) are a predominant type of oncogenomic alterations that affect a large proportion of the genome in the majority of cancer samples. Current technologies allow high-throughput measurement of such copy number aberrations, generating results consisting of frequently large sets of SCNA segments. However, the automated annotation and integration of such data are particularly challenging because the measured signals reflect biased, relative copy number ratios. In this study, we introduce labelSeg , an algorithm designed for rapid and accurate annotation of CNA segments, with the aim of enhancing the interpretation of tumor SCNA profiles. Leveraging density-based clustering and exploiting the length–amplitude relationships of SCNA, our algorithm proficiently identifies distinct relative copy number states from individual segment profiles. Its compatibility with most CNA measurement platforms makes it suitable for large-scale integrative data analysis. We confirmed its performance on both simulated and sample-derived data from The Cancer Genome Atlas reference dataset, and we demonstrated its utility in integrating heterogeneous segment profiles from different data sources and measurement platforms. Our comparative and integrative analysis revealed common SCNA patterns in cancer and protein-coding genes with a strong correlation between SCNA and messenger RNA expression, promoting the investigation into the role of SCNA in cancer development. [ABSTRACT FROM AUTHOR]

The 5th Kidney Cancer Research Summit was a hybrid event hosted in Boston, MA in July 2023. As in previous editions, the conference attracted a wide representation of global thought leaders in kidney cancer spanning all stages of clinical and laboratory research. Sessions covered tumor metabolism, novel immune pathways, advances in clinical trials and immunotherapy, and progress toward biomarkers. The abstract presentations were published as a supplement in The Oncologist (https://academic.oup.com/oncolo/issue/28/Supplement%5f1). Aiming to be more concise than comprehensive, this commentary summarizes the most important emerging areas of kidney cancer research discussed and debated among the stakeholders at the conference, with relevant updates that have occurred since. [ABSTRACT FROM AUTHOR]

Background FoundationOneCDx is approved in the US and Japan as a companion diagnostic test to identify patients with cancer who may benefit from treatment with 30 drug therapies in the US and 23 in Japan. Tumor profiling with FoundationOneCDx also detects genomic findings with evidence of clinical significance that may inform clinical care decisions beyond companion diagnostic claims. This observational study reports the breadth and impact of clinical decision insights from FoundationOneCDx solid tumor profiles. Materials and Methods Consecutive test result reports for patients with solid tumor diagnoses (n  = 109 695) were retrospectively analyzed for clinically significant predictive, prognostic, and diagnostic genomic alterations and signatures, determined in accordance with professional guidelines. Interventional clinical trials with targeted therapies or immune checkpoint inhibitors were matched to tumor profiles based on evidence that the genomic finding may be an actionable, investigational, or hypothetical target in the patient's tumor type. Results In 14 predefined cancer types (80.7% of analyzed solid tumors), predictive, prognostic, and diagnostic markers were reported in 47.6%, 13.2%, and 4.5% of samples, respectively, accounting for a total of 51.2% of tumor profiles. Pan-cancer predictive markers of tumor mutational burden (TMB) of 10 or more mutations per megabase, high microsatellite instability (MSI), or NTRK1/2/3 fusions were observed in 15.6%, 2.0%, and 0.1% of solid tumors, respectively. Most solid tumor profiles (89.2%) had genomic results that could theoretically inform decisions on the selection of immunotherapy and targeted therapy clinical trials. Conclusion For this real-world population of patients with FoundationOneCDx solid tumor profiles in the routine course of clinical care, clinically significant findings were reported for approximately half of patients with genomic results. [ABSTRACT FROM AUTHOR]

Disrupted protein phosphorylation due to genetic variation is a widespread phenomenon that triggers oncogenic transformation of healthy cells. However, few relevant phosphorylation disruption events have been verified due to limited biological experimental methods. Because of the lack of reliable benchmark datasets, current bioinformatics methods primarily use sequence-based traits to study variant impact on phosphorylation (VIP). Here, we increased the number of experimentally supported VIP events from less than 30 to 740 by manually curating and reanalyzing multi-omics data from 916 patients provided by the Clinical Proteomic Tumor Analysis Consortium. To predict VIP events in cancer cells, we developed VIPpred, a machine learning method characterized by multidimensional features that exhibits robust performance across different cancer types. Our method provided a pan-cancer landscape of VIP events, which are enriched in cancer-related pathways and cancer driver genes. We found that variant-induced increases in phosphorylation events tend to inhibit the protein degradation of oncogenes and promote tumor suppressor protein degradation. Our work provides new insights into phosphorylation-related cancer biology as well as novel avenues for precision therapy. [ABSTRACT FROM AUTHOR]

Accurate prediction of TCR-pMHC binding is important for the development of cancer immunotherapies, especially TCR-based agents. Existing algorithms often experience diminished performance when dealing with unseen epitopes, primarily due to the complexity in TCR-pMHC recognition patterns and the scarcity of available data for training. We have developed a novel deep learning model, 'TCR Antigen Binding Recognition' based on BERT, named as TABR-BERT. Leveraging BERT's potent representation learning capabilities, TABR-BERT effectively captures essential information regarding TCR-pMHC interactions from TCR sequences, antigen epitope sequences and epitope-MHC binding. By transferring this knowledge to predict TCR-pMHC recognition, TABR-BERT demonstrated better results in benchmark tests than existing methods, particularly for unseen epitopes. [ABSTRACT FROM AUTHOR]

Background: Substantial variation exists when performing a minimally invasive right hemicolectomy (MIRH) due to disparities in training, expertise and differences in implementation of innovations. This study aimed to achieve national consensus on an optimal and standardized MIRH technique for colon cancer and to develop and validate a video-based competency assessment tool (CAT) for MIRH. Method: Statements covering all elements of MIRH were formulated. Subsequently, the Delphi technique was used to reach consensus on a standardized MIRH among 76 colorectal surgeons from 43 different centres. A CAT was developed based on the Delphi results. Nine surgeons assessed the same 12 unedited full-length videos using the CAT, allowing evaluation of the intraclass correlation coefficient (ICC). Results: After three Delphi rounds, consensus (≥80% agreement) was achieved on 23 of the 24 statements. Consensus statements included the use of low intra-abdominal pressure, detailed anatomical outline how to perform complete mesocolic excision with central vascular ligation, the creation of an intracorporeal anastomosis, and specimen extraction through a Pfannenstiel incision using a wound protector. The CAT included seven consecutive steps to measure competency of the MIRH and showed high consistency among surgeons with an overall ICC of 0.923. Conclusion: Nationwide consensus on a standardized and optimized technique of MIRH was reached. The CAT developed showed excellent interrater reliability. These achievements are crucial steps to an ongoing nationwide quality improvement project (the Right study). The Delphi technique was employed to achieve a broad national consensus on 23 statements among 76 colorectal surgeons, defining a standardized MIRH. This standard includes complete mesocolic excision, intracorporeal anastomosis and Pfannenstiel incision using a wound protector. Building upon this consensus, a video-based competency assessment tool was developed, exhibiting excellent reliability. [ABSTRACT FROM AUTHOR]

The translocation of mitochondrial DNA (mtDNA) sequences into the nuclear genome, resulted in the occurrence of nuclear sequences of mitochondrial origin (NUMTs) which can be detected in nearly all sequenced eukaryotes. However, de novo mtDNA insertions can contribute to the development of pathological conditions including cancer. Recent data indicate that de novo mtDNA translocation into chromosomes can occur due to genotoxic influence of DNA double-strand break-inducing environmental mutagens. This confirms the hypothesis of the involvement of genome instability in the occurrence of mtDNA fragments in chromosomes. Mounting evidence indicates that mitochondria can be transferred from normal cells to cancer cells and recover cellular respiration. These exchanged mitochondria can facilitate cancer progression and metastasis. This review article provides a comprehensive overview of the potential carcinogenicity of mtDNA insertions, and the relevance of mtDNA escape in cancer progression, metastasis, and treatment resistance in humans. Potential molecular targets involved in mtDNA escape and exchange of mitochondria that can be of possible clinical benefits are presented and discussed. Understanding these processes could lead to improved diagnostic approaches, novel therapeutic strategies, and a deeper understanding of the intricate relationship between mitochondria, nuclear DNA, and cancer biology. [ABSTRACT FROM AUTHOR]

Background: Maackiain (Mac), a flavonoid analog isolated from Sophora flavescens, exhibits neuroprotective, anti-allergic, anti-inflammatory, and pro-apoptotic effects. It is not clear whether Mac has a therapeutic effect on cervical cancer. Method: In this work, we used RT-qPCR, western blot, immunofluorescence, and related methods to detect the therapeutic mechanism of Mac for cervical cancer. Results: We demonstrated that Mac significantly inhibited the proliferation, migration, and invasion of human cervical cancer cell lines HeLa and SiHa. And, Mac enhanced the pro-apoptotic effects of cisplatin in treating cervical cancer cells. Mac has shown good efficacy in treating cervical cancer. Furthermore, Mac inhibited the mammalian target of the rapamycin (mTOR) pathway, thereby inducing autophagy in cervical cancer cells. The regulation of mTOR/autophagy pathway by Mac relied on the activation of AMP-activated protein kinase (AMPK), and the inhibition of the AMPK reversed the Mac's anti-cervical cancer activity. In addition, experimental study of Mac in mouse xenograft tumor model further confirmed its good anti-cervical cancer activity. Conclusion: Mac inhibits human cervical cancer by activating the AMPK/mTOR/autophagy pathway, indicating that it is a potential natural compound for the treatment of cervical cancer. This study also provides a feasible molecular mechanism for the treatment of cervical cancer. [ABSTRACT FROM AUTHOR]

In this study, we explored the in vivo effects of Ocimum gratissimum aqueous extracts (OGE) on colorectal cancer (CRC) development provoked by azoxymethane/dextran sodium sulfate (AOM/DSS). The results showed a significant reduction in the tumor load and tumor number for the OGEH group that received continued administration of OGE compared to the AOM/DSS group, with P values of <0.01, but this was not observed in the OGEHs group that received separated administration of OGE. All groups except the control group exhibited aberrant crypt foci (ACF) and adenocarcinoma of lesion pathology in colon, and both conditions were significantly reduced in the OGEH group (P  < 0.01) as compared to the AOM/DSS group. Subsequent investigation into whether OGE exhibits eliminative effects on DSS-induced severe colitis (SC) in mice showed that the disease activity index score was significantly reduced in the OGE-treated groups (P  < 0.01), also colon colitis histological score was reversed. These data suggest that OGE may be potentially effective in preventing CRC when administered throughout the promotional stages of carcinogenesis by inhibiting inflammatory SC. [ABSTRACT FROM AUTHOR]

Cancer genomics is dedicated to elucidating the genes and pathways that contribute to cancer progression and development. Identifying cancer genes (CGs) associated with the initiation and progression of cancer is critical for characterization of molecular-level mechanism in cancer research. In recent years, the growing availability of high-throughput molecular data and advancements in deep learning technologies has enabled the modelling of complex interactions and topological information within genomic data. Nevertheless, because of the limited labelled data, pinpointing CGs from a multitude of potential mutations remains an exceptionally challenging task. To address this, we propose a novel deep learning framework, termed self-supervised masked graph learning (SMG), which comprises SMG reconstruction (pretext task) and task-specific fine-tuning (downstream task). In the pretext task, the nodes of multi-omic featured protein–protein interaction (PPI) networks are randomly substituted with a defined mask token. The PPI networks are then reconstructed using the graph neural network (GNN)-based autoencoder, which explores the node correlations in a self-prediction manner. In the downstream tasks, the pre-trained GNN encoder embeds the input networks into feature graphs, whereas a task-specific layer proceeds with the final prediction. To assess the performance of the proposed SMG method, benchmarking experiments are performed on three node-level tasks (identification of CGs, essential genes and healthy driver genes) and one graph-level task (identification of disease subnetwork) across eight PPI networks. Benchmarking experiments and performance comparison with existing state-of-the-art methods demonstrate the superiority of SMG on multi-omic feature engineering. [ABSTRACT FROM AUTHOR]

NcRNA-encoded small peptides (ncPEPs) have recently emerged as promising targets and biomarkers for cancer immunotherapy. Therefore, identifying cancer-associated ncPEPs is crucial for cancer research. In this work, we propose CoraL, a novel supervised contrastive meta-learning framework for predicting cancer-associated ncPEPs. Specifically, the proposed meta-learning strategy enables our model to learn meta-knowledge from different types of peptides and train a promising predictive model even with few labeled samples. The results show that our model is capable of making high-confidence predictions on unseen cancer biomarkers with only five samples, potentially accelerating the discovery of novel cancer biomarkers for immunotherapy. Moreover, our approach remarkably outperforms existing deep learning models on 15 cancer-associated ncPEPs datasets, demonstrating its effectiveness and robustness. Interestingly, our model exhibits outstanding performance when extended for the identification of short open reading frames derived from ncPEPs, demonstrating the strong prediction ability of CoraL at the transcriptome level. Importantly, our feature interpretation analysis discovers unique sequential patterns as the fingerprint for each cancer-associated ncPEPs, revealing the relationship among certain cancer biomarkers that are validated by relevant literature and motif comparison. Overall, we expect CoraL to be a useful tool to decipher the pathogenesis of cancer and provide valuable information for cancer research. The dataset and source code of our proposed method can be found at https://github.com/Johnsunnn/CoraL. [ABSTRACT FROM AUTHOR]

Cancer is a multi-factorial disease, and the etiology of breast cancer (BC) is due to a combination of both genetic and environmental factors. Breast tissue shows a unique microbiota, Proteobacteria and Firmicutes are the most abundant bacteria in breast tissue, and several studies have shown that the microbiota of healthy breast differs from that of BC. Breast microbiota appears to be correlated with different characteristics of the tumor, and prognostic clinicopathologic features. It also appears that there are subtle differences between the microbial profiles of the healthy control and high-risk patients. Genetic predisposition is an extremely important risk factor for BC. BRCA1/2 germline mutations and Li-Fraumeni syndrome are DNA repair deficiency syndromes inherited as autosomal dominant characters that substantially increase the risk of BC. These syndromes exhibit incomplete penetrance of BC expression in carrier subjects. The action of breast microbiota on carcinogenesis might explain why women with a mutation develop cancer and others do not. Among the potential biological pathways through which the breast microbiota may affect tumorigenesis, the most relevant appear to be DNA damage caused by colibactin and other bacterial-derived genotoxins, β-glucuronidase-mediated estrogen deconjugation and reactivation, and HPV-mediated cancer susceptibility. In conclusion, in patients with a genetic predisposition, an unfavorable breast microbiota may be co-responsible for the onset of BC. Prospectively, the ability to modulate the microbiota may have an impact on disease onset and progression in patients at high risk for BC. [ABSTRACT FROM AUTHOR]

Infection with chronic hepatitis C virus (HCV) is an important risk factor for hepatocellular carcinoma (HCC). Direct-acting antiviral therapy has transformed care for patients with HCV and reduces the risk of HCC. Despite HCV cure, a residual HCC risk remains in patients with advanced fibrosis and cirrhosis, with multiple mechanisms underlying subsequent hepatocarcinogenesis. Transcriptomic and proteomic signatures demonstrate the capacity for HCC risk stratification, and chemoprevention strategies are emerging. For now, pending more precise stratification, HCC surveillance of patients with cured HCV and advanced fibrosis or cirrhosis should continue. [ABSTRACT FROM AUTHOR]

Cancer driver genes are critical in driving tumor cell growth, and precisely identifying these genes is crucial in advancing our understanding of cancer pathogenesis and developing targeted cancer drugs. Despite the current methods for discovering cancer driver genes that mainly rely on integrating multi-omics data, many existing models are overly complex, and it is difficult to interpret the results accurately. This study aims to address this issue by introducing InDEP, an interpretable machine learning framework based on cascade forests. InDEP is designed with easy-to-interpret features, cascade forests based on decision trees and a KernelSHAP module that enables fine-grained post-hoc interpretation. Integrating multi-omics data, InDEP can identify essential features of classified driver genes at both the gene and cancer-type levels. The framework accurately identifies driver genes, discovers new patterns that make genes as driver genes and refines the cancer driver gene catalog. In comparison with state-of-the-art methods, InDEP proved to be more accurate on the test set and identified reliable candidate driver genes. Mutational features were the primary drivers for InDEP's identifying driver genes, with other omics features also contributing. At the gene level, the framework concluded that substitution-type mutations were the main reason most genes were identified as driver genes. InDEP's ability to identify reliable candidate driver genes opens up new avenues for precision oncology and discovering new biomedical knowledge. This framework can help advance cancer research by providing an interpretable method for identifying cancer driver genes and their contribution to cancer pathogenesis, facilitating the development of targeted cancer drugs. [ABSTRACT FROM AUTHOR]

Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases. [ABSTRACT FROM AUTHOR]

Introduction In epithelial cancers, truncated O -glycans, such as the Thomson-nouveau antigen (Tn) and its sialylated form (STn), are upregulated on the cell surface and associated with poor prognosis and immunological escape. Recent studies have shown that these carbohydrate epitopes facilitate cancer development and can be targeted therapeutically; however, the mechanism underpinning their expression remains unclear. Methods To identify genes directly influencing the expression of cancer-associated O -glycans, we conducted an unbiased, positive-selection, whole-genome CRISPR knockout-screen using monoclonal antibodies against Tn and STn. Results and Conclusions We show that knockout of the Zn2+-transporter SLC39A9 (ZIP9), alongside the well-described targets C1GALT1 (C1GalT1) and its molecular chaperone, C1GALT1C1 (COSMC), results in surface-expression of cancer-associated O -glycans. No other gene perturbations were found to reliably induce O -glycan truncation. We furthermore show that ZIP9 knockout affects N -linked glycosylation, resulting in upregulation of oligo-mannose, hybrid-type, and α2,6-sialylated structures as well as downregulation of tri- and tetra-antennary structures. Finally, we demonstrate that accumulation of Zn2+ in the secretory pathway coincides with cell-surface presentation of truncated O -glycans in cancer tissue, and that over-expression of COSMC mitigates such changes. Collectively, the findings show that dysregulation of ZIP9 and Zn2+ induces cancer-like glycosylation on the cell surface by affecting the glycosylation machinery. [ABSTRACT FROM AUTHOR]

An increasing number of studies have reported the role of gut microbes in colorectal cancer (CRC) development, as they can be influenced by dietary metabolism and mediate alterations in host epigenetics, ultimately affecting CRC. Intake of specific dietary components can affect gut microbial composition and function, and their metabolism regulates important epigenetic functions that may influence CRC risk. Gut microbes can regulate epigenetic modifications through nutrient metabolism, including histone modification, DNA methylation, and noncoding RNAs. Epigenetics, in turn, determines the gut microbial composition and thus influences the risk of developing CRC. This review discusses the complex crosstalk between metabolic reprogramming, gut microbiota, and epigenetics in CRC and highlights the potential applications of the gut microbiota as a biomarker for the prevention, diagnosis, and therapy of CRC. [ABSTRACT FROM AUTHOR]

The gut microbiota plays a crucial role in regulating various host metabolic, immune, and neuroendocrine functions, and has a significant impact on human health. Several lines of evidence suggest that gut dysbiosis is associated with a variety of diseases, including cancer. The gut microbiota can impact the development and progression of cancer through a range of mechanisms, such as regulating cell proliferation and death, modulating the host immune response, and altering the host metabolic state. Gene regulatory programs are considered critical mediators between the gut microbiota and host phenotype, of which RNA N6-methyladenosine (m6A) modifications have attracted much attention recently. Aberrant m6A modifications have been shown to play a crucial role in cancer development. This review aims to provide an overview of the diverse roles of gut microbiota and RNA m6A modifications in cancer and highlight their potential interactions in cancer development. [ABSTRACT FROM AUTHOR]

Aging is the largest risk factor for the development of cancer. A growing body of literature indicates that aging and cancer often play a somewhat reciprocal relationship at various times. On the one hand, aging is a "driver" of cancer, and on the other, cancer is a "disease driver" of aging. Here, we synthesize our reflections on the current literature linking cancer and aging, with an eye on fundamental aging processes, such as cellular senescence. Additionally, we consider how interventions that target fundamental aging processes can potentially transform cancer care, from preventing cancer development and progression to reducing the burden of accelerated aging in cancer survivors. Finally, we conclude with a reflection highlighting our vision for future directions to advance the science of cancer and aging and its applicability to improve the care of older adults with cancer. [ABSTRACT FROM AUTHOR]

Background We sought to determine the prevalence of germline pathogenic variants (gPVs) in unselected patients with endometrial cancer (EC), define biallelic gPVs within tumors, and describe their associations with clinicopathologic features. Methods Germline assessment of at least 76 cancer predisposition genes was performed in patients with EC undergoing clinical tumor-normal Memorial Sloan Kettering–Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) sequencing from January 1, 2015, to June 30, 2021. In patients with gPVs, biallelic alterations in ECs were identified through analysis of loss of heterozygosity and somatic PVs. Clinicopathologic variables were compared using nonparametric tests. Results Of 1625 patients with EC, 216 (13%) had gPVs, and 15 patients had 2 gPVs. There were 231 gPVs in 35 genes (75 [32%] high penetrance; 39 [17%] moderate penetrance; and 117 [51%] low, recessive, or uncertain penetrance). Compared with those without gPVs, patients with gPVs were younger (P  = .002), more often White (P  = .009), and less obese (P  = .025) and had differences in distribution of tumor histology (P  = .017) and molecular subtype (P  < .001). Among 231 gPVs, 74 (32%) exhibited biallelic inactivation within tumors. For high-penetrance gPVs, 63% (47 of 75) of ECs had biallelic alterations, primarily affecting mismatch repair (MMR) and homologous recombination related genes, including BRCA1, BRCA2 , RAD51D , and PALB2. Biallelic inactivation varied across molecular subtypes with highest rates in microsatellite instability-high (MSI-H) or copy-number (CN)–high subtypes (3 of 12 [25%] POLE, 30 of 77 [39%] MSI-H, 27 of 60 [45%] CN-high, 9 of 57 [16%] CN-low; P  < .001). Conclusions Of unselected patients with EC, 13% had gPVs, with 63% of gPVs in high-penetrance genes (MMR and homologous recombination) exhibiting biallelic inactivation, potentially driving cancer development. This supports germline assessment in EC given implications for treatment and cancer prevention. [ABSTRACT FROM AUTHOR]

Background Endometrial cancer risk stratification may help target interventions, screening, or prophylactic hysterectomy to mitigate the rising burden of this cancer. However, existing prediction models have been developed in select cohorts and have not considered genetic factors. Methods We developed endometrial cancer risk prediction models using data on postmenopausal White women aged 45-85 years from 19 case-control studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Relative risk estimates for predictors were combined with age-specific endometrial cancer incidence rates and estimates for the underlying risk factor distribution. We externally validated the models in 3 cohorts: Nurses' Health Study (NHS), NHS II, and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Results Area under the receiver operating characteristic curves for the epidemiologic model ranged from 0.64 (95% confidence interval [CI] = 0.62 to 0.67) to 0.69 (95% CI = 0.66 to 0.72). Improvements in discrimination from the addition of genetic factors were modest (no change in area under the receiver operating characteristic curves in NHS; PLCO = 0.64 to 0.66). The epidemiologic model was well calibrated in NHS II (overall expected-to-observed ratio [E/O]   =   1.09, 95% CI = 0.98 to 1.22) and PLCO (overall E/O   =   1.04, 95% CI = 0.95 to 1.13) but poorly calibrated in NHS (overall E/O   =   0.55, 95% CI = 0.51 to 0.59). Conclusions Using data from the largest, most heterogeneous study population to date (to our knowledge), prediction models based on epidemiologic factors alone successfully identified women at high risk of endometrial cancer. Genetic factors offered limited improvements in discrimination. Further work is needed to refine this tool for clinical or public health practice and expand these models to multiethnic populations. [ABSTRACT FROM AUTHOR]

Downregulation of ARHGAP25 was found in the tumor samples from breast cancer patients and five breast cancer cell lines. However, its precise role and molecular mechanisms in breast cancer remain completely unknown. Herein, we found that knockdown of ARHGAP25 in breast cancer cells promoted proliferation, migration and invasion of breast cancer cells. Mechanistically, ARHGAP25 silence facilitated the activation of the Wnt/β-catenin pathway and the upregulation of its downstream molecules (including c-Myc, Cyclin D1, PCNA, MMP2, MMP9, Snail and ASCL2) by directly regulating Rac1/PAK1 in breast cancer cells. In vivo xenograft experiments indicated ARHGAP25 silence promoted tumor growth and activated the Wnt/β-catenin pathway. In contrast, overexpression of ARHGAP25 in vitro and in vivo impeded all of the above cancer properties. Intriguingly, ASCL2, a downstream target of the Wnt/β-catenin pathway, transcriptionally repressed the expression of ARHGAP25 and therefore constituted a negative feedback loop. Moreover, bioinformatics analysis indicated that ARHGAP25 was significantly correlated with tumor immune cell infiltration and the survival of patients with different immune cell subgroups in breast cancer. Collectively, our work revealed that ARHGAP25 suppressed tumor progression of breast cancer. It provides a novel insight for the treatment of breast cancer. [ABSTRACT FROM AUTHOR]

Background and Aims Ulcerative colitis [UC] can lead to colitis-associated colorectal neoplasm [CAN]. Adenosine-to-inosine RNA editing, which is regulated by adenosine deaminase acting on RNA [ADAR], induces the post-transcriptional modification of critical oncogenes, including antizyme inhibitor 1 [AZIN1], leading to colorectal carcinogenesis. Therefore, we hypothesized that ADAR1 might be involved in the development of CAN in UC. Methods We systematically analysed a cohort of 139 UC cases [40 acute phase, 73 remission phase, 26 CAN]. The degree of inflammation was evaluated using the Mayo endoscopic score [MES]. Results The type 1 interferon [IFN]-related inflammation pathway was upregulated in the rectum of active UC, rectum of UC-CAN and tumour site of UC-CAN patients. ADAR1 expression was upregulated in the entire colon of CAN cases, while it was downregulated in non-CAN MES0 cases. ADAR1 expression in the rectum predicted the development of CAN better than p53 or β-catenin, with an area under the curve of 0.93. The high expression of ADAR1 and high AZIN1 RNA editing in UC was triggered by type 1 IFN stimulation from UC-specific microbiomes, such as seen in Fusobacterium in vitro analyses. The induction of AZIN1 RNA editing by ADAR1, whose expression is promoted by Fusobacterium , may induce carcinogenesis in UC. Conclusions The risk of CAN can be evaluated by assessing ADAR1 expression in the rectum of MES0 UC patients, freeing UC patients from unnecessary colonoscopy and reducing their physical burden. RNA editing may be involved in UC carcinogenesis, and may be used to facilitate the prevention and treatment of CAN in UC. [ABSTRACT FROM AUTHOR]

Chronic inflammation is widely recognized as a major risk factor for cancer formation, but the underlying mechanisms are poorly understood. Recently, it was shown that Gasdermin D (GSDMD) protein drives pyroptotic cell death in macrophages on cleavage by inflammatory caspases. Even though the Gsdmd gene is specifically expressed in the intestinal epithelium, the role of Gsdmd in the intestinal tissues remains poorly characterized. In this study, we examined the biological role of Gsdmd in colorectal cancer (CRC) development, employing an azoxymethane/dextran sulfate sodium carcinogenesis model. Results show that GSDMD deficiency enhances CRC development, probably due to decreased apoptosis caused by downregulation of interferon-gamma (IFNγ)—signal transducer and activator 1 (STAT1) signaling. Furthermore, we show that GSDMD protein is diminished in human colorectal cancer, indicating involvement of GSDMD in repression of CRC development in humans. Our findings provide a new insight into functions of Gsdmd/GSDMD in colonic inflammation and human CRC development. [ABSTRACT FROM AUTHOR]

AT-Rich Interaction Domain 1A (ARID1A) is an important SWItch/Sucrose Non-Fermentation (SWI/SNF) chromatin remodeling complex subunit, and its coding gene has a high mutation frequency in many cancers. Current studies have reported that ARID1A mutational status is correlated to cancer development, including cell proliferation, invasiveness, metastasis, and morphological alterations. ARID1A acts as a tumor suppressor, regulating gene transcription, participating in DNA damage response, and influencing tumor immune microenvironment and signaling pathways. The absence of ARID1A in cancer can lead to widespread dysregulation of gene expression in cancer initiation, promotion, and progression. For patients with ARID1A mutations, effective individualized treatment can improve the prognosis of patients. In this review, we aim to discuss the mechanism of ARID1A mutations in cancer development and explore the significance of discoveries for treatment. [ABSTRACT FROM AUTHOR]

Microsatellite instability (MSI) has emerged as an important predictor of sensitivity for immunotherapy-based strategies. β-2-Microglobulin (B2M) contains microsatellites within the coding regions and is prone to somatic changes in MSI/mismatch repair deficiency (MSI/dMMR) tumors. To delineate prevalence and associations of B2M mutations in MSI-H/dMMR cancers, we investigated the mutational profile of B2M and clinical and pathological features in gastric cancer (GC), colorectal cancer (CRC), and endometrial cancer (EC) with a high incidence of microsatellite instability-high (MSI-H)/dMMR. Formalin-fixed paraffin-embedded (FFPE) tumor tissues along with matched normal tissues were collected from 108 MSI/dMMR patients with GC, CRC, and EC. Genomic profiling of tissue and blood samples were assessed next-generation sequencing (NGS). Immunohistochemistry (IHC) was used to examine the presence or absence of B2M protein. Alternations in the exonic microsatellite regions of B2M were observed at various but high frequencies (57.5% in CRC, 23.9% in GC, and 13.6% in EC) and in different forms. NGS assay revealed that genes involved in chromatin regulation, the PI3K pathway, the WNT pathway, and mismatch repair were extensively altered in the MSI-H cohort. Signature 6 and 26, 2 of 4 mutational signatures associated with defective DNA mismatch repair, featured with high numbers of small insertion/deletions (INDEL) dominated in all 3 types of cancer. Alternations in the exonic microsatellite regions of B2M were observed at various but high frequencies (57.5% in CRC, 23.9% in GC, and 13.6% in EC) and in different forms. Tumor mutational burden (TMB) was significantly higher in the patients carrying MSI-H/dMMR tumors with B2M mutation than that in patients with wild-type B2M (P =.026).The frame shift alteration occurring at the exonic microsatellite sties caused loss of function of B2M gene. In addition, a case with CRC carrying indels in B2M gene resisted the ICI treatment was reported. In conclusion, patients carrying MSI-H/dMMR tumors with B2M mutation showed significantly higher TMB. Prescription of ICIs should be thoroughly evaluated for these patients. [ABSTRACT FROM AUTHOR]

Aberrant DNA methylation is the most common molecular lesion that is crucial for the occurrence and development of cancer, but has thus far been underappreciated as a clinical tool for cancer classification, diagnosis or as a guide for therapeutic decisions. Partly, this has been due to a lack of proven algorithms that can use methylation data to stratify patients into clinically relevant risk groups and subtypes that are of prognostic importance. Here, we proposed a novel Bayesian model to capture the methylation signatures of different subtypes from paired normal and tumor methylation array data. Application of our model to synthetic and empirical data showed high clustering accuracy, and was able to identify the possible epigenetic cause of a cancer subtype. [ABSTRACT FROM AUTHOR]

Objective Previous studies on the association between pks + Escherichia coli and colorectal cancer (CRC) demonstrated conflicting results. Hence, we performed a meta-analysis to obtain more precise estimates. Methods Related literature was obtained from PubMed, ScienceDirect, Google Scholar, and Cochrane Library. Data were then extracted, summarized, and subjected to analysis using Review Manager 5.4 by computing for the pooled odds ratios at the 95% confidence interval. Results Overall analysis showed that individuals carrying pks + E coli had a greater risk of developing CRC. Subgroup analysis further showed that individuals from Western countries carrying pks + E coli and individuals with pks + E coli in their tissue samples had increased risk of developing CRC. Conclusion Results of this meta-analysis suggest that individuals with pks + E coli have a greater risk of developing CRC. However, more studies are needed to confirm our claims. [ABSTRACT FROM AUTHOR]

A major near-term medical impact of the genomic technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Next-generation sequencing technologies have accelerated the characterization of a tumor, leading to the comprehensive discovery of all the major alterations in a given cancer genome, followed by the translation of this information using computational and immunoinformatics approaches to cancer diagnostics and therapeutic efforts. In the current article, we review various components of cancer immunoinformatics applied to a series of fields of cancer research, including computational tools for cancer mutation detection, cancer mutation and immunological databases, and computational vaccinology. [ABSTRACT FROM AUTHOR]

Non-lethal doses of ionizing radiation (IR) delivered to humans because of terrorist events, nuclear accidents or radiotherapy can result in carcinogenesis. Means of protecting against carcinogenesis are lacking. We questioned the role of the gut microbiome in IR-induced carcinogenesis. The gut microbiome was modulated by administering broad spectrum antibiotics (Ab) in the drinking water. Mice were given Ab 3 weeks before and 3 weeks after 3 Gy total body irradiation (TBI) or for 6 weeks one month after TBI. Three weeks of Ab treatment resulted in a 98% reduction in total 16S rRNA counts for 4 out of 6 of the phylum groups detected. However, 3 more weeks of Ab treatment (6 weeks total) saw an expansion in the phylum groups Proteobacteria and Actinobacteria. The Ab treatment altered the bacteria diversity in the gut, and shortened the lifespan when Ab were administered before and after TBI. Mortality studies indicated that the adverse Ab lifespan effects were due to a decrease in the time in which solid tumors started to appear and not to any changes in hematopoietic or benign tumors. In contrast, when Ab were administered one month after TBI, lifespan was unchanged compared to the control TBI group. Use of broad-spectrum antibiotics to simulate the germ-free condition did not afford an advantage on carcinogenesis or lifespan. [ABSTRACT FROM AUTHOR]

Pancreaticobiliary maljunction (PBM) is a congenital malformation. The reflux of pancreatic juice into the biliary tract caused by PBM plays a significant role in the development of biliary tract cancers (BTCs), such as gallbladder cancer and cholangiocarcinoma. Previous studies have demonstrated a high incidence of BTC in patients with PBM. However, there are only a few reports of patients who developed BTC after a diagnosis of PBM. We report the cases of two patients who developed gallbladder cancer after being diagnosed with PBM. They had refused treatment and were being managed with follow-up observation alone after the diagnosis of PBM and developed gallbladder cancer after several years of observation. Thus, surgical treatment should be recommended for all patients with PBM in order to prevent the development of BTC. Moreover, long-term, close, regular follow-up is necessary to facilitate the early diagnosis of subsequent BTC in patients with untreated PBM. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC) is the primary reason of tumor morbidity and mortality worldwide. We aimed to study the transfer process of S100A4 between cells and whether it affected NSCLC development by affecting STAT3 expression. First, S100A4 expression in NSCLC cells was measured. The exosomes in MRC-5, A549, and H1299 cells were isolated and identified. We constructed si-S100A4 and si-PD-L1 to transfect A549 cells and oe-S100A4 to transfect H1299 cells, and tested the transfection efficiency. Cell function experiments were performed to assess cell proliferation, clone number, apoptosis, cell cycle, migration, and invasion abilities. In addition, ChIP was applied to determine the targeting relationship between S100A4 and STAT3. Next, we explored NSCLC cell-derived exosomes role in NSCLC progress by transmitting S100A4. Finally, we verified the function of exosome-transmitted S100A4 in NSCLC in vivo. High expression of S100A4 was secreted by exosomes. After knocking down S100A4, cell proliferation ability was decreased, clones number was decreased, apoptosis was increased, G1 phase was increased, S phase was repressed, and migration and invasion abilities were also decreased. ChIP validated STAT3 and PD-L1 interaction. After knocking down S100A4, PD-L1 expression was decreased, while ov-STAT3 reversed the effect of S100A4 on PD-L1 expression. Meanwhile, S100A4 inhibited T-cell immune activity by activating STAT3. In addition, knockdown of PD-L1 inhibited cell proliferation, migration, and invasion. NSCLC cell-derived exosomes promoted cancer progression by transmitting S100A4 to activate STAT3 pathway. Finally, in vivo experiments further verified that exosome-transmitted S100A4 promoted NSCLC progression. Exosome-transmitted S100A4 induces immunosuppression and the development of NSCLC by activating STAT3. Non-small cell lung cancer (NSCLC) is the primary reason of tumor morbidity and mortality worldwide. We aimed to study the transfer process of S100A4 between cells and whether it affected NSCLC development by affecting STAT3 expression. [ABSTRACT FROM AUTHOR]

In this study, the natural radioactivity level and its effects on the environment of Lake Van, which is the largest lake in Turkey, were investigated extensively. Initially, 254 soil samples have been collected from the districts (Tusba, Edremit, Gevas, Tatvan, Ahlat, Adilcevaz, Ercis) located around the coastline of Lake Van in eastern Turkey. A Na(TI) detector was used to detect activity concentrations of radium (226Ra), thorium (232Th) and potassium (40K) in each collected soil sample. The obtained average results were compared with available data from Turkey and international data base. The average activity in soil samples was measured as 28.0 ± 3.7–43.6 ± 2.2 Bq/kg for 226Ra, 27.3 ± 4.1–55.4 ± 4.8 Bq/kg for 232Th and 377 ± 42– 706 ± 40 Bq/kg for 40K. It was observed that the average concentrations of 226Ra, 232Th, 40K (43.6 ± 2.2, 55.4 ± 4.8, 706 ± 40 Bq/kg, respectively) for Tatvan district and (37.0 ± 3.5, 51.4 ± 4.2, 479 ± 41 Bq/kg, respectively) for Ahlat district were higher than both national and international average value. In addition, radiological effect parameters originating from terrestrial natural radionuclides for the study area; gamma dose rate (D out), annual effective dose equivalent (AEDE), and lifetime cancer development probability (LCR) were calculated. The D out, AEDE, LCR (83.0 ± 3.9 nGy/h, 0.102 ± 0.005 mSv/y, 0.36 ± 0.02 x 10–3, respectively) parameters in Tatvan district were found to be above the international allowable value. [ABSTRACT FROM AUTHOR]

The traditional way for discovering genes which drive cancer (namely cancer drivers) neglects the dynamic information of cancer development, even though it is well known that cancer progresses dynamically. To enhance cancer driver discovery, we expand cancer driver concept to dynamic cancer driver as a gene driving one or more bio-pathological transitions during cancer progression. Our method refers to the fact that cancer should not be considered as a single process but a compendium of altered biological processes causing the disease to develop over time. Reciprocally, different drivers of cancer can potentially be discovered by analysing different bio-pathological pathways. We propose a novel approach for causal inference of genes driving one or more core processes during cancer development (i.e. dynamic cancer driver). We use the concept of pseudotime for inferring the latent progression of samples along a biological transition during cancer and identifying a critical event when such a process is significantly deviated from normal to carcinogenic. We infer driver genes by assessing the causal effect they have on the process after such a critical event. We have applied our method to single-cell and bulk sequencing datasets of breast cancer. The evaluation results show that our method outperforms well-recognized cancer driver inference methods. These results suggest that including information of the underlying dynamics of cancer improves the inference process (in comparison with using static data), and allows us to discover different sets of driver genes from different processes in cancer. R scripts and datasets can be found at https://github.com/AndresMCB/DynamicCancerDriver [ABSTRACT FROM AUTHOR]

Introduction Neuroendocrine neoplasms (NEN) are heterogeneous malignancies that can arise at almost any anatomical site and are classified as biologically distinct well-differentiated neuroendocrine tumors (NET) and poorly differentiated neuroendocrine carcinomas (NEC). Current systemic therapies for advanced disease, including targeted therapies, chemotherapy, and immunotherapy, are associated with limited duration of response. New therapeutic targets are needed. One promising target is delta-like ligand 3 (DLL3), an inhibitory ligand of the Notch receptor whose overexpression on the surface of NEN is associated with tumorigenesis. Methods This article is a narrative review that highlights the role of DLL3 in NEN progression and prognosis, the potential for therapeutic targeting of DLL3, and ongoing studies of DLL3-targeting therapies. Classification, incidence, pathogenesis, and current management of NEN are reviewed to provide biological context and illustrate the unmet clinical needs. Discussion DLL3 is overexpressed in many NENs, implicated in tumor progression, and is typically associated with poor clinical outcomes, particularly in patients with NEC. Targeted therapies using DLL3 as a homing beacon for cytotoxic activity mediated via several different mechanisms (eg, antibody-drug conjugates, T-cell engager molecules, CAR-Ts) have shown promising clinical activity in small-cell lung cancer (SCLC). DLL3 may be a clinically actionable target across NEN. Conclusions Current treatment options for NEN do not provide sustained responses. DLL3 is expressed on the cell surface of many NEN types and is associated with poor clinical outcomes. Initial clinical studies targeting DLL3 therapeutically in SCLC have been promising, and additional studies are expanding this approach to the broader group of NEN. [ABSTRACT FROM AUTHOR]

Ultraviolet radiation (UVR) exposure is the major risk factor for melanoma. However, epidemiologic studies on UVR and noncutaneous cancers have reported inconsistent results, with some suggesting an inverse relationship potentially mediated by vitamin D. To address this, we examined 3 US prospective cohorts, the Health Professionals Follow-up Study (HPFS) (1986) and Nurses' Health Study (NHS) I and II (1976 and 1989), for associations between cumulative erythemal UVR and incident cancer risk, excluding nonmelanoma skin cancer. We used a validated spatiotemporal model to calculate erythemal UVR. Participants (47,714 men; 212,449 women) were stratified into quintiles by cumulative average erythemal UVR, using the first quintile as referent, for Cox proportional hazards regression analysis. In the multivariable-adjusted meta-analysis of all cohorts, compared with the lowest quintile, risk of any cancer was slightly increased across all other quintiles (highest quintile hazard ratio (HR) = 1.04, 95% confidence interval (CI): 1.01, 1.07; P for heterogeneity = 0.41). All UVR quintiles were associated with similarly increased risk of any cancer excluding melanoma. As expected, erythemal UVR was positively associated with risk of melanoma (highest quintile HR = 1.17, 95% CI: 1.04, 1.31; P for heterogeneity = 0.83). These findings suggest that elevated UVR is associated with increased risk of both melanoma and noncutaneous cancers. [ABSTRACT FROM AUTHOR]

The transforming properties of the high-risk human papillomavirus (HPV) E7 oncoprotein are indispensable for driving the virus life cycle and pathogenesis. Besides inactivation of the retinoblastoma family of tumor suppressors as part of its oncogenic endeavors, E7-mediated perturbations of eminent cell cycle regulators, checkpoint proteins and proto-oncogenes are considered to be the tricks of its transformative traits. However, many such critical interactions are still unknown. In the present study, we have identified the anaphase-promoting complex/cyclosome (APC) co-activator, Cdh1, as a novel interacting partner and a degradation target of E7. We found that HPV16 E7-induced inactivation of Cdh1 promoted abnormal accumulation of multiple Cdh1 substrates. Such a mode of deregulation possibly contributes to HPV-mediated cervical oncogenesis. Our mapping studies recognized the C-terminal zinc-finger motif of E7 to associate with Cdh1 and interfere with the timely degradation of FoxM1, a bona fide Cdh1 substrate and a potent oncogene. Importantly, the E7 mutant with impaired interaction with Cdh1 exhibited defects in its ability for overriding typical cell cycle transition and oncogenic transformation, thereby validating the functional and pathological significance of the E7-Cdh1 axis during cervical carcinoma progression. Altogether, the findings from our study discover a unique nexus between E7 and APC/C-Cdh1, thereby adding to our understanding of the mechanism of E7-induced carcinogenesis and provide a promising target for the management of cervical carcinoma. [ABSTRACT FROM AUTHOR]

We investigated γ-H2AX formation, a biomarker of DNA damage, and expression of stem cell markers (SCMs), including cytokeratin 14, aldehyde dehydrogenase 1A1 (ALDH1A1), and CD44, in the development of rat bladder tumors induced by short-term administration of N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN). Histopathological examination showed that diffuse simple hyperplasia of the bladder urothelium induced by BBN recovered to the normal-appearing urothelium after withdrawal, whereas focal proliferative lesions were newly developed and subsequently progressed to benign papilloma and carcinoma. Immunohistochemical analysis revealed that BBN-induced γ-H2AX formation and ALDH1A1 and CD44 expression persisted at higher levels in the normal-appearing urothelium than those in the control group for long periods after withdrawal. Since persistent chronic inflammation was observed even after withdrawal, targeted gene expression analysis of inflammation-related factors revealed 101 genes, including Stat3 and Myc , that showed persistent high expression. Pathway analysis suggested that Stat3 and/or Myc activation may be associated with SCM expression. We focused on hepatocyte growth factor (Hgf), one of the genes predicted in relation to Stat3 / Myc , and confirmed that HGF-positive cells increased by BBN persisted in the normal-appearing urothelium after withdrawal and colocalized with γ-H2AX and SCMs. These results suggested that the long-term persistence of γ-H2AX formation and SCM expression, which occurred during the early stages of bladder tumorigenesis, is not a transient response to exposure and might contribute to bladder tumorigenesis. Although further studies are needed, BBN-induced rat bladder tumors may originate from focal hyperplasia arising from SCM-positive cells via activation of the STAT3/MYC pathway after DNA damage involving γ-H2AX formation. [ABSTRACT FROM AUTHOR]

Understanding the biological functions of molecules in specific human tissues or cell types is crucial for gaining insights into human physiology and disease. To address this issue, it is essential to systematically uncover associations among multilevel elements consisting of disease phenotypes, tissues, cell types and molecules, which could pose a challenge because of their heterogeneity and incompleteness. To address this challenge, we describe a new methodological framework, called Graph Local InfoMax (GLIM), based on a human multilevel network (HMLN) that we established by introducing multiple tissues and cell types on top of molecular networks. GLIM can systematically mine the potential relationships between multilevel elements by embedding the features of the HMLN through contrastive learning. Our simulation results demonstrated that GLIM consistently outperforms other state-of-the-art algorithms in disease gene prediction. Moreover, GLIM was also successfully used to infer cell markers and rewire intercellular and molecular interactions in the context of specific tissues or diseases. As a typical case, the tissue-cell-molecule network underlying gastritis and gastric cancer was first uncovered by GLIM, providing systematic insights into the mechanism underlying the occurrence and development of gastric cancer. Overall, our constructed methodological framework has the potential to systematically uncover complex disease mechanisms and mine high-quality relationships among phenotypical, tissue, cellular and molecular elements. [ABSTRACT FROM AUTHOR]