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MET is a receptor tyrosine kinase (RTK) responsible for initiating signaling pathways involved in development and wound repair. MET activation relies on ligand binding to the extracellular receptor, which prompts dimerization, intracellular phosphorylation, and recruitment of associated signaling proteins. Mutations, which are predominantly observed clinically in the intracellular juxtamembrane and kinase domains, can disrupt typical MET regulatory mechanisms. Understanding how juxtamembrane variants, such as exon 14 skipping (METΔEx14), and rare kinase domain mutations can increase signaling, often leading to cancer, remains a challenge. Here, we perform a parallel deep mutational scan (DMS) of the MET intracellular kinase domain in two fusion protein backgrounds: wild-type and METΔEx14. Our comparative approach has revealed a critical hydrophobic interaction between a juxtamembrane segment and the kinase ⍺C-helix, pointing to potential differences in regulatory mechanisms between MET and other RTKs. Additionally, we have uncovered a β5 motif that acts as a structural pivot for the kinase domain in MET and other TAM family of kinases. We also describe a number of previously unknown activating mutations, aiding the effort to annotate driver, passenger, and drug resistance mutations in the MET kinase domain.

The chromatin-associated protein WD Repeat Domain 5 (WDR5) is a promising target for cancer drug discovery, with most efforts blocking an arginine-binding cavity on the protein called the WIN site that tethers WDR5 to chromatin. WIN site inhibitors (WINi) are active against multiple cancer cell types in vitro, the most notable of which are those derived from MLL-rearranged (MLLr) leukemias. Peptidomimetic WINi were originally proposed to inhibit MLLr cells via dysregulation of genes connected to hematopoietic stem cell expansion. Our discovery and interrogation of small-molecule WINi, however, revealed that they act in MLLr cell lines to suppress ribosome protein gene (RPG) transcription, induce nucleolar stress, and activate p53. Because there is no precedent for an anticancer strategy that specifically targets RPG expression, we took an integrated multi-omics approach to further interrogate the mechanism of action of WINi in human MLLr cancer cells. We show that WINi induce depletion of the stock of ribosomes, accompanied by a broad yet modest translational choke and changes in alternative mRNA splicing that inactivate the p53 antagonist MDM4. We also show that WINi are synergistic with agents including venetoclax and BET-bromodomain inhibitors. Together, these studies reinforce the concept that WINi are a novel type of ribosome-directed anticancer therapy and provide a resource to support their clinical implementation in MLLr leukemias and other malignancies.

Mammalian ferredoxin 1 and 2 (FDX1/2) belong to an evolutionary conserved family of iron-sulfur cluster containing proteins and act as electron shutters between ferredoxin reductase (FDXR) and numerous proteins involved in critical biological pathways. FDX1 is involved in biogenesis of steroids and bile acids, Vitamin A/D metabolism, and lipoylation of tricarboxylic acid (TCA) cycle enzymes. FDX1 has been extensively characterized biochemically but its role in physiology and lipid metabolism has not been explored. In this study, we generated Fdx1-deficient mice and showed that knockout of both alleles of the Fdx1 gene led to embryonic lethality. We also showed that like Fdxr+/-+/-, Fdx1+/-+/- had a shorter life span and were prone to steatohepatitis. However, unlike Fdxr+/-+/-, Fdx1+/-+/- were not prone to spontaneous tumors. Additionally, we showed that FDX1 deficiency led to lipid droplet accumulation possibly via the ABCA1-SREBP1/2 pathway. Specifically, untargeted lipidomic analysis showed that FDX1 deficiency led to alterations in several classes of lipids, including cholesterol, triacylglycerides, acylcarnitines, ceramides, phospholipids and lysophospholipids. Taken together, our data indicate that FDX1 is essential for mammalian embryonic development and lipid homeostasis at both cellular and organismal levels.

STK11 (serine-threonine kinase 11), also known as LKB1 (liver kinase B1) is a highly conserved master kinase that regulates cellular metabolism and polarity through a complex signaling network involving AMPK and 12 other AMPK-related kinases. Germline mutations in LKB1 have been causatively linked to Peutz-Jeghers Syndrome (PJS), an autosomal dominant hereditary disease with high cancer susceptibility. The identification of inactivating somatic mutations in LKB1 in different types of cancer further supports its tumor suppressive role. Deleterious mutations in LKB1 are frequently observed in patients with epithelial ovarian cancer. However, its inconsistent effects on tumorigenesis and cancer progression suggest that its functional impact is genetic context-dependent, requiring cooperation with other oncogenic lesions. In this review, we summarize the pleiotropic functions of LKB1 and how its altered activity in cancer cells is linked to oncogenic proliferation and growth, metastasis, metabolic reprogramming, genomic instability, and immune modulation. We also review the current mechanistic understandings of this master kinase as well as therapeutic implications with particular focus on the effects of LKB1 deficiency in ovarian cancer pathogenesis. Lastly, we discuss whether LKB1 deficiency can be exploited as an Achilles heel in ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: The child cancer, neuroblastoma (NB), is characterised by a low incidence of mutations and strong oncogenic embryonal driver signals. Many new targeted epigenetic modifier drugs have failed in human trials as monotherapy. Methods: We performed a high‐throughput, combination chromatin‐modifier drug screen against NB cells. We screened 13 drug candidates in 78 unique combinations. Results: We found that the combination of two histone methyltransferase (HMT) inhibitors: GSK343, targeting EZH2, and SGC0946, targeting DOT1L, demonstrated the strongest synergy across 8 NB cell lines, with low normal fibroblast toxicity. High mRNA expression of both EZH2 and DOT1L in NB tumour samples correlated with the poorest patient survival. Combination HMT inhibitor treatment caused activation of ATF4‐mediated endoplasmic reticulum (ER) stress responses. In addition, glutathione and several amino acids were depleted by HMT inhibitor combination on mass spectrometry analysis. The combination of SGC0946 and GSK343 reduced tumour growth in comparison to single agents. Conclusion: Our results support further investigation of HMT inhibitor combinations as a therapeutic approach in NB. [ABSTRACT FROM AUTHOR]

Simple Summary: Small cell lung cancer (SCLC) is a deadly cancer that is treated by chemo- and radiotherapy, which work by damaging DNA. However, most SCLC patients will develop resistance to these treatments, resulting in a poor outlook with few effective treatment options available. This review summarizes our understanding of the causes of treatment resistance and the treatments which have been studied to overcome resistance. While there is still much to be understood, new methods being developed may improve our ability to study this disease and find effective treatments. Background: Small cell lung cancer (SCLC) is a lethal form of lung cancer with few treatment options and a high rate of relapse. While SCLC is initially sensitive to first-line DNA-damaging chemo- and radiotherapy, relapse disease is almost universally therapy-resistant. As a result, there has been interest in understanding the mechanisms of therapeutic resistance in this disease. Conclusions: Progress has been made in elucidating these mechanisms, particularly as they relate to the DNA damage response and SCLC differentiation and transformation, leading to many clinical trials investigating new therapies and combinations. Yet there remain many gaps in our understanding, such as the effect of epigenetics or the tumor microenvironment on treatment response, and no single mechanism has been found to be ubiquitous, suggesting a significant heterogeneity in the mechanisms of acquired resistance. Nevertheless, the advancement of techniques in the laboratory and the clinic will improve our ability to study this disease, especially in patient populations, and identify methods to surmount therapeutic resistance. [ABSTRACT FROM AUTHOR]

Simple Summary: Histopathological and molecular factors could play a role in determining LNM in colon cancer. Extended lymphadenectomies in right-sided patients have been associated with complications. We demonstrated that histopathological and molecular analysis can be useful in predicting LNM and therefore identify high risk patients which could potentially benefit from D3 lymphadenectomy/CME. Background: Lymphadenectomy plays a central role in the treatment of localized colon cancer. While in left colon cancer the D3 lymphadenectomy/CME is considered the standard of care, lymphatic stations to be removed in right colon cancer are still a matter of discussion. The individuation of LNM risk factors could help in choosing the lymphadenectomy in right-sided tumors. This study aims to analyze the correlation of histopathological and molecular characteristics with lymph node metastasis, both in right- and left-sided colon cancer, and their impact on survival; Methods: We conducted a single-center observational retrospective study. The following data were collected and analyzed for each patient: demographics, histopathological and molecular data, and intraoperative and perioperative data. Statistical analyses were performed, including descriptive statistics, multivariate logistic regression and survival analysis; Results: An association between tumor size (pT, p < 0.001), grading (p = 0.013), budding (p < 0.001), LVI (79,4% p < 0.001) and LNM was observed. A multivariate analysis identified pT4 (OR 5.45, p < 0.001) and LVI+ (OR 10.7, p < 0.001) as significant predictors of LNM. Right-sided patients presented a worse OS when associated with LNM, while no significant difference was observed in N0 patients; Conclusions: histological and molecular analysis can help identify high risk patients, which could benefit from extended lymphadenectomies. These patients could be ideal candidates for the D3 lymphadenectomy/CME. [ABSTRACT FROM AUTHOR]

Multi-omics data integration is a term that refers to the process of combining and analyzing data from different omic experimental sources, such as genomics, transcriptomics, methylation assays, and microRNA sequencing, among others. Such data integration approaches have the potential to provide a more comprehensive functional understanding of biological systems and has numerous applications in areas such as disease diagnosis, prognosis and therapy. However, quantitative integration of multi-omic data is a complex task that requires the use of highly specialized methods and approaches. Here, we discuss a number of data integration methods that have been developed with multi-omics data in view, including statistical methods, machine learning approaches, and network-based approaches. We also discuss the challenges and limitations of such methods and provide examples of their applications in the literature. Overall, this review aims to provide an overview of the current state of the field and highlight potential directions for future research. [ABSTRACT FROM AUTHOR]

Patient‐derived xenografts (PDX) involve transplanting patient cells or tissues into immunodeficient mice, offering superior disease models compared with cell line xenografts and genetically engineered mice. In contrast to traditional cell‐line xenografts and genetically engineered mice, PDX models harbor the molecular and biologic features from the original patient tumor and are generationally stable. This high fidelity makes PDX models particularly suitable for preclinical and coclinical drug testing, therefore better predicting therapeutic efficacy. Although PDX models are becoming more useful, the several factors influencing their reliability and predictive power are not well understood. Several existing studies have looked into the possibility that PDX models could be important in enhancing our knowledge with regard to tumor genetics, biomarker discovery, and personalized medicine; however, a number of problems still need to be addressed, such as the high cost and time‐consuming processes involved, together with the variability in tumor take rates. This review addresses these gaps by detailing the methodologies to generate PDX models, their application in cancer research, and their advantages over other models. Further, it elaborates on how artificial intelligence and machine learning were incorporated into PDX studies to fast‐track therapeutic evaluation. This review is an overview of the progress that has been done so far in using PDX models for cancer research and shows their potential to be further improved in improving our understanding of oncogenesis. [ABSTRACT FROM AUTHOR]

AbstractAs the integration of novel agents in the frontline therapy has primarily impacted upfront therapy of advanced stage classic Hodgkin lymphoma (cHL), this review will outline current management of advanced stage cHL at first line and at progression and relapse, focusing on the biology, clinical features, and therapeutic approaches. Due to S1826, HD21, and ECHELON-1, the first-line treatment of advanced cHL has dramatically changed, with novel agents part of standard frontline therapy. BV-AVD, BrECADD, and Nivo-AVD are now standard first-line regimens for patients with stage III-IV cHL, with improved outcomes compared to historical data in cHL. The addition of BV and PD-1 inhibitors to relapsed/refractory (r/r) cHL chemotherapy regimens improved outcomes in this population. Now, there is a paradigm shift with PD-1 moving into frontline therapy, so new studies to evaluate the role of these novel agents in salvage will be required to determine the optimal salvage approach in r/r cHL. [ABSTRACT FROM AUTHOR]

Bladder cancer (BCa) is the fourth most common cancer in men and one of the most common urinary tract cancers, especially in developed countries. The aim of this paper is to comprehensively analyze the biology of bladder cancer, including its epidemiology, etiology, histological types, risk factors, clinical symptoms, and diagnostic methods. The paper presents the dominant histological types of bladder cancer, such as transitional cell carcinoma (TCC), which accounts for 90–95% of cases, squamous cell carcinoma (SCC), and adenocarcinoma, which is much rarer. Risk factors, such as smoking, occupational exposure to chemicals, schistosomiasis, and genetic factors, which significantly affect the pathogenesis of bladder cancer, are also discussed. The paper focuses on modern diagnostic methods, including blue light cystoscopy (BLC) and computed tomography urography (CTU), which show increased sensitivity and specificity in detecting early neoplastic changes. The importance of TNM classification and the role of neoadjuvant chemotherapy in improving patient prognosis are also discussed. Based on a review of the scientific literature, the paper emphasizes the need for early diagnosis and an individualized therapeutic approach, which may contribute to improving the survival and quality of life of patients with bladder cancer. The potential for prevention, including quitting smoking and limiting exposure to harmful chemicals, has also been demonstrated to significantly reduce the risk of disease. Patient education and monitoring high-risk groups are key to reducing the incidence of bladder cancer. [ABSTRACT FROM AUTHOR]

This article describes how the transcriptional alterations of the innate immune system divide dysplasias into aggressive forms that, despite the treatment, relapse quickly and more easily, and others where the progression is slow and more treatable. It elaborates on how the immune system can change the extracellular matrix, favoring neoplastic progression, and how infections can enhance disease progression by increasing epithelial damage due to the loss of surface immunoglobulin and amplifying the inflammatory response. We investigated whether these dysregulated genes were linked to disease progression, delay, or recovery. These transcriptional alterations were observed using the RNA-based next-generation sequencing (NGS) panel Oncomine Immune Response Research Assay (OIRRA) to measure the expression of genes associated with lymphocyte regulation, cytokine signaling, lymphocyte markers, and checkpoint pathways. During the analysis, it became apparent that certain alterations divide dysplasia into two categories: progressive or not. In the future, these biological alterations are the first step to provide new treatment modalities with different classes of drugs currently in use in a systemic or local approach, including classical chemotherapy drugs such as cisplatin and fluorouracile, older drugs like fenretinide, and new checkpoint inhibitor drugs such as nivolumab and pembrolizumab, as well as newer options like T cell therapy (CAR-T). Following these observed alterations, it is possible to differentiate which dysplasias progress or not or relapse quickly. This information could, in the future, be the basis for determining a close follow-up, minimizing surgical interventions, planning a correct and personalized treatment protocol for each patient and, after specific clinical trials, tailoring new drug treatments. [ABSTRACT FROM AUTHOR]

5-fluorouracil (5-FU), a chemotherapeutic agent against oral squamous cell carcinoma (OSCC), is limited by poor pharmacokinetics and toxicity. The pH-sensitive zeolite imidazolate framework-8 (ZIF-8) may increase the selectivity and length of 5-FU released into the acidic tumor microenvironment. This study examined the in vitro 5-FU absorption and release profiles of ZIF-8, and then progressed to cytotoxicity assays using the OSCC primary cell line SCC7. The 5-FU loading capacity of ZIF-8 was calculated with UV-vis spectroscopy (λ = 260 nm). 5-FU release was quantified by submerging 5-FU@ZIF-8 in pH 7.4 and 5.5 acetate buffer over 48 h. For the cytotoxicity assays, 5-FU, ZIF-8, and 5-FU@ZIF-8 were added to SCC7 cultures at 25, 50, and 100 μg/mL. Cell viability was assessed through toluidine blue staining and further quantified through transcriptomic RNA sequencing. ZIF-8 stabilized at a maximum absorption of 2.71 ± 0.22 mg 5-FU, and released 0.66 mg more 5-FU at pH 5.5 than 7.4 for at least 72 h. The cytotoxicity assays showed that 5-FU@ZIF-8 had a synergistic inhibitory effect at 50 μg/mL. The RNA sequencing analysis further revealed the molecular targets of 5-FU@ZIF-8 in SCC7. 5-FU@ZIF-8 may release 5-FU based on the pH of the surrounding microenvironments and synergistically inhibit OSCC. [ABSTRACT FROM AUTHOR]

Simple Summary: Spatial transcriptomics is a technique of measuring gene expression with spatial resolution on a tissue slide, which is especially useful in cancer research. This scoping study reviews 41 articles published by the end of 2023 to examine current trends for employed methods, applications, and data analysis approaches for spatial transcriptomics, identifying challenges and practical uses of this technique in studying cancer. The research shows that cancer is a major focus in spatial transcriptomics studies, with certain tools and methods being particularly popular among scientists. However, many studies do not fully explain their data processing methods, making it hard to reproduce their results. Emphasis on transparent sharing of analysis scripts and tailored single-cell analysis methods for ST is recommended to enhance study reproducibility and reliability in the domain. This work may stand as a spatial transcriptomics developmental snapshot and reference to contemporary neoplasm biology research conducted through this technique. Spatial transcriptomics (ST) examines gene expression within its spatial context on tissue, linking morphology and function. Advances in ST resolution and throughput have led to an increase in scientific interest, notably in cancer research. This scoping study reviews the challenges and practical applications of ST, summarizing current methods, trends, and data analysis techniques for ST in neoplasm research. We analyzed 41 articles published by the end of 2023 alongside public data repositories. The findings indicate cancer biology is an important focus of ST research, with a rising number of studies each year. Visium (10x Genomics, Pleasanton, CA, USA) is the leading ST platform, and SCTransform from Seurat R library is the preferred method for data normalization and integration. Many studies incorporate additional data types like single-cell sequencing and immunohistochemistry. Common ST applications include discovering the composition and function of tumor tissues in the context of their heterogeneity, characterizing the tumor microenvironment, or identifying interactions between cells, including spatial patterns of expression and co-occurrence. However, nearly half of the studies lacked comprehensive data processing protocols, hindering their reproducibility. By recommending greater transparency in sharing analysis methods and adapting single-cell analysis techniques with caution, this review aims to improve the reproducibility and reliability of future studies in cancer research. [ABSTRACT FROM AUTHOR]

Cytosine methylation contributes to the regulation of gene expression and normal hematopoiesis in mammals. It is catalyzed by the family of DNA methyltransferases that include DNMT1, DNMT3A, and DNMT3B. Peripheral T–cell lymphomas (PTCLs) represent aggressive mature T–cell malignancies exhibiting a broad spectrum of clinical features with poor prognosis and inadequately understood molecular pathobiology. To better understand the molecular landscape and identify candidate genes involved in disease maintenance, we profiled DNA methylation and gene expression of PTCLs. We found that the methylation patterns in PTCLs are deregulated and heterogeneous but share 767 hypo- and 567 hypermethylated differentially methylated regions (DMRs) along with 231 genes up- and 91 genes downregulated in all samples, suggesting a potential association with tumor development. We further identified 39 hypomethylated promoters associated with increased gene expression in the majority of PTCLs. This putative oncogenic signature included the TRIP13 (thyroid hormone receptor interactor 13) gene whose genetic and pharmacologic inactivation inhibited the proliferation of T–cell lines by inducing G2-M arrest and apoptosis. Our data thus show that human PTCLs have a significant number of recurrent methylation alterations that may affect the expression of genes critical for proliferation whose targeting might be beneficial in anti-lymphoma treatments. [ABSTRACT FROM AUTHOR]

Bladder cancer (BCa) is the fourth most common cancer in men and one of the most common urinary tract cancers, especially in developed countries. The aim of this paper is to comprehensively analyze the biology of bladder cancer, including its epidemiology, etiology, histological types, risk factors, clinical symptoms, and diagnostic methods. The paper presents the dominant histological types of bladder cancer, such as transitional cell carcinoma (TCC), which accounts for 90–95% of cases, squamous cell carcinoma (SCC), and adenocarcinoma, which is much rarer. Risk factors, such as smoking, occupational exposure to chemicals, schistosomiasis, and genetic factors, which significantly affect the pathogenesis of bladder cancer, are also discussed. The paper focuses on modern diagnostic methods, including blue light cystoscopy (BLC) and computed tomography urography (CTU), which show increased sensitivity and specificity in detecting early neoplastic changes. The importance of TNM classification and the role of neoadjuvant chemotherapy in improving patient prognosis are also discussed. Based on a review of the scientific literature, the paper emphasizes the need for early diagnosis and an individualized therapeutic approach, which may contribute to improving the survival and quality of life of patients with bladder cancer. The potential for prevention, including quitting smoking and limiting exposure to harmful chemicals, has also been demonstrated to significantly reduce the risk of disease. Patient education and monitoring high-risk groups are key to reducing the incidence of bladder cancer.

This review article studies the complex field of noncoding RNAs (ncRNAs) in cancer biology, focusing on their potential use as biomarkers and therapeutic targets. NcRNAs include circular RNAs (circRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs). We discuss how ncRNAs affect gene expression in cancerous cells, the spread of cancer, and metastasis. The article illustrates the complex pathways through which ncRNAs can affect oncogenesis, tumor suppression, and therapeutic resistance. It also assesses the potential clinical uses of non-coding RNAs (ncRNAs), including their utility in cancer diagnosis, and prognosis. Besides, their potential for personalized cancer therapy is documented. Finally, it is concluded that understanding the role of ncRNA is of clinical importance regarding carcinogenesis, cancer diagnosis, and personalized therapy.

Ferroptosis is a newly identified iron‐dependent type of regulated cell death that can also be regarded as death caused by the specific collapse of the lipid antioxidant defence machinery. Ferroptosis has gained increasing attention as a potential therapeutic strategy for therapy‐resistant cancer types. However, many ferroptosis‐inducing small molecules do not reach the pharmacokinetic requirements for their effective clinical use yet. Nevertheless, their clinical optimization is under development. In this review, we summarize the current understanding of molecular pathways regulating ferroptosis, how cells protect themselves from the induction of ferroptotic cell death, and how a better understanding of cancer cell metabolism can represent vulnerabilities for ferroptosis‐based therapies. Lastly, we discuss the context‐dependent effect of ferroptosis on various cell types within the tumor microenvironment and address controversies on how tissue ferroptosis might impact systemic cancer immunity in a paracrine manner.

The intricate molecular landscape of cancer pathogenesis continues to captivate researchers worldwide, with Circular RNAs (circRNAs) emerging as pivotal players in the dynamic regulation of biological functions. The study investigates the elusive link between circRNAs and the Transforming Growth Factor-β (TGF-β) signalling pathway, exploring their collective influence on cancer progression and metastasis. Our comprehensive investigation begins by profiling circRNA expression patterns in diverse cancer types, revealing a repertoire of circRNAs intricately linked to the TGF-β pathway. Through integrated bioinformatics analyses and functional experiments, we elucidate the specific circRNA-mRNA interactions that modulate TGF-β signalling, unveiling the regulatory controls governing this crucial pathway. Furthermore, we provide compelling evidence of the impact of circRNA-mediated TGF-β modulation on key cellular processes, including epithelial-mesenchymal transition (EMT), migration, and cell proliferation. In addition to their mechanistic roles, circRNAs have shown promise as diagnostic and prognostic biomarkers, as well as potential molecular targets for cancer therapy. Their ability to modulate critical pathways, such as the TGF-β signalling axis, underscores their significance in cancer biology and clinical applications. The intricate interplay between circRNAs and TGF-β is dissected, uncovering novel regulatory circuits that contribute to the complexity of cancer biology. This review unravels a previously unexplored dimension of carcinogenesis, emphasizing the crucial role of circRNAs in shaping the TGF-β signalling landscape.

In cancer treatment, mild hyperthermia (HT) represents an old, but recently revived opportunity to increase the efficacy of radiotherapy (RT) without increasing side effects, thereby widening the therapeutic window. HT disrupts cellular homeostasis by acting on multiple targets, and its combination with RT produces synergistic antitumoral effects on specific pathophysiological mechanisms, associated to DNA damage and repair, hypoxia, stemness and immunostimulation. HT is furthermore associated to direct tumor cell kill, particularly in higher temperature levels. A phenomenon of temporary resistance to heat, known as thermotolerance, follows each HT session. Cancer treatment requires innovative concepts and combinations to be tested but, for a meaningful development of clinical trials, the understanding of the underlying mechanisms of the tested modalities is essential. In this mini-review, we aimed to describe the synergistic effects of the combination of HT with RT as well as the phenomena of thermal shock and thermotolerance, in order to stimulate clinicians in new, clinically relevant concepts and combinations, which become particularly relevant in the era of technological advents in both modalities but also cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Immune evasion is a key phenomenon in understanding tumor recurrence, metastasis, and other critical steps in tumor progression. The tumor microenvironment (TME) is in constant flux due to the tumor's ability to release signals that affect it, while immune cells within it can impact cancer cell behavior. Cancer cells undergo several changes, which can change the enrichment of different immune cells and modulate the activity of existing immune cells in the tumor microenvironment. Cancer cells can evade immune surveillance by downregulating antigen presentation or expressing immune checkpoint molecules. High levels of tumor-infiltrating lymphocytes (TILs) correlate with better outcomes, and robust immune responses can control tumor growth. On the contrary, increased enrichment of Tregs, myeloid-derived suppressor cells, and M2-like anti-inflammatory macrophages can hinder effective immune surveillance and predict poor prognosis. Overall, understanding these immune evasion mechanisms guides therapeutic strategies. Researchers aim to modulate the TME to enhance immune surveillance and improve patient outcomes. In this review article, we strive to summarize the composition of the tumor immune microenvironment, factors affecting the tumor immune microenvironment (TIME), and different therapeutic modalities targeting the immune cells. This review is a first-hand reference to understand the basics of immune surveillance and immune evasion. [ABSTRACT FROM AUTHOR]

A number of conditions and factors can cause the transformation of normal cells in the body into malignant tissue by changing the normal functions of a wide range of regulatory, apoptotic, and signal transduction pathways. Despite the current deficiency in fully understanding the mechanism of cancer action accurately and clearly, numerous genes and proteins that are causally involved in the initiation, progression, and metastasis of cancer have been identified. But due to the lack of space and the abundance of details on this complex topic, we have emphasized here more recent advances in our understanding of the principles implied tumor cell transformation, development, invasion, angiogenesis, and metastasis. Inhibition of angiogenesis is a significant strategy for the treatment of various solid tumors, that essentially depend on cutting or at least limiting the supply of blood to micro-regions of tumors, leading to pan-hypoxia and pan-necrosis inside solid tumor tissues. Researchers have continued to enhance the efficiency of anti-angiogenic drugs over the past two decades, to identify their potential in the drug interaction, and to discover reasonable interpretations for possible resistance to treatment. In this review, we have discussed an overview of cancer history and recent methods use in cancer therapy, focusing on anti-angiogenic inhibitors targeting angiogenesis formation. Further, this review has explained the molecular mechanism of action of these anti-angiogenic inhibitors in various tumor types and their limitations use. In addition, we described the synergistic mechanisms of immunotherapy and anti-angiogenic therapy and summarizes current clinical trials of these combinations. Many phase III trials found that combining immunotherapy and anti-angiogenic therapy improved survival. Therefore, targeting the source supply of cancer cells to grow and spread with new anti-angiogenic agents in combination with different conventional therapy is a novel method to reduce cancer progression. The aim of this paper is to overview the varying concepts of cancer focusing on mechanisms involved in tumor angiogenesis and provide an overview of the recent trends in anti-angiogenic strategies for cancer therapy. [ABSTRACT FROM AUTHOR]

Simple Summary: With advanced bioinformatic and sequencing technologies, many non-coding RNAs have been found to harbor non-canonical open reading frames (ncORFs). Some studies suggest that many ncORF-encoded microproteins or micropeptides possess important roles in cancer biology, yet the functional roles of these ncORF-encoded peptides are mostly unknown. The purpose of this review is to provide a comprehensive overview of existing knowledge on ncORF-encoded microproteins in cancer biology and highlight their roles as potential prognostic and therapeutic targets in cancer. Cancer develops from abnormal cell growth in the body, causing significant mortalities every year. To date, potent therapeutic approaches have been developed to eradicate tumor cells, but intolerable toxicity and drug resistance can occur in treated patients, limiting the efficiency of existing treatment strategies. Therefore, searching for novel genes critical for cancer progression and therapeutic response is urgently needed for successful cancer therapy. Recent advances in bioinformatics and proteomic techniques have allowed the identification of a novel category of peptides encoded by non-canonical open reading frames (ncORFs) from historically non-coding genomic regions. Surprisingly, many ncORFs express functional microproteins that play a vital role in human cancers. In this review, we provide a comprehensive description of different ncORF types with coding capacity and technological methods in discovering ncORFs among human genomes. We also summarize the carcinogenic role of ncORFs such as pTINCR and HOXB-AS3 in regulating hallmarks of cancer, as well as the roles of ncORFs such as HOXB-AS3 and CIP2A-BP in cancer diagnosis and prognosis. We also discuss how ncORFs such as AKT-174aa and DDUP are involved in anti-cancer drug response and the underestimated potential of ncORFs as therapeutic targets. [ABSTRACT FROM AUTHOR]

This study investigates differences in focal adhesion (FA) morphology and Talin cleavage levels between transformed and non-transformed cell lines. Utilizing fluorescently tagged wild-type Talin and Talin mutants with calpain cleavage site mutations, FA structures were visualized. Mutations in different Talin cleavage sites showed varying impacts on FA morphology and distribution across melanoma cell lines (Meljuso, A375P, A2058) and a non-transformed cell line (HFF). Western blot analysis, ratiometric fluorescence intensity-based measurements, and FRAP experiments revealed higher Talin cleavage levels within FAs of transformed cell lines compared to non-transformed cells. Additionally, growth assays indicated that reducing calpain cleavage levels attenuated transformed cell growth. These findings suggest that Talin cleavage level is crucial for FA morphology and assembly, with higher levels observed in transformed cells, influencing their growth dynamics. [ABSTRACT FROM AUTHOR]

There are over 100 types of human cancer, accounting for millions of deaths every year. Lung cancer alone claims over 1.8 million lives per year and is expected to surpass 3.2 million by 2050, which underscores the urgent need for rapid drug development and repurposing initiatives. The application of AI emerges as a pivotal solution to developing anti-cancer therapeutics. This state-of-the-art review aims to explore the various applications of AI in lung cancer therapeutics. Predictive models can analyse large datasets, including clinical data, genetic information, and treatment outcomes, for novel drug design and to generate personalised treatment recommendations, potentially optimising therapeutic strategies, enhancing treatment efficacy, and minimising adverse effects. A thorough literature review study was conducted based on articles indexed in PubMed and Scopus. We compiled the use of various machine learning approaches, including CNN, RNN, GAN, VAEs, and other AI techniques, enhancing efficiency with accuracy exceeding 95%, which is validated through a computer-aided drug design process. AI can revolutionise lung cancer therapeutics, streamlining processes and saving biological scientists' time and effort—however, further research is needed to overcome challenges and fully unlock AI's potential in Lung Cancer Therapeutics. [ABSTRACT FROM AUTHOR]

Background: Molecular changes in HCC development are largely unknown. As the liver plays a fundamental role in the body's metabolism, metabolic changes are to be expected. Aims: We aimed to identify metabolomic changes in HCC in comparison to liver cirrhosis (LC) patients, which could potentially serve as novel biomarkers for HCC diagnosis and prognosis. Methods: Metabolite expression from 38 HCC from the SORAMIC trial and 32 LC patients were analyzed by mass spectrometry. Metabolites with significant differences between LC and HCC at baseline were analyzed regarding expression over follow-up. In addition, association with overall survival was tested using univariate Cox proportional-hazard analysis. Results: 41 metabolites showed differential expression between LC and HCC patients. 14 metabolites demonstrated significant changes in HCC patients during follow-up. Campesterol, lysophosphatidylcholine, octadecenoic and octadecadienoic acid, and furoylglycine showed a differential expression in the local ablation vs. palliative care group. High expression of eight metabolites (octadecenoic acid, 2-hydroxybutyrate, myo-inositol, isocitrate, erythronic acid, creatinine, pseudouridine, and erythrol) were associated with poor overall survival. The association between poor OS and octadecenoic acid and creatinine remained statistically significant even after adjusting for tumor burden and LC severity. Conclusion: Our findings give promising insides into the metabolic changes during HCC carcinogenesis and provide candidate biomarkers for future studies. Campesterol and furoylglycine in particular were identified as possible biomarkers for HCC progression. Moreover, eight metabolites were detected as predictors for poor overall survival. [ABSTRACT FROM AUTHOR]

Simple Summary: Neoadjuvant chemotherapy (NACT) is a pivotal treatment for breast cancer (BC). However, the success of NACT is uncertain and dependent on BC subtype. A valuable tool to identify biomarkers of the response to chemotherapy is metabolomics. We used plasma from BC patients together with clinical data to verify whether certain metabolites present before NACT can predict the responsiveness of the patient. Liquid chromatography–mass spectrometry and untargeted metabolomic analysis were performed. A statistical model was used to predict the response to NACT for samples separated into two sets: training and validation. The results showed 95.4%/93.3% sensitivity, 94.6%/94.7% accuracy, and 91.6%/100.0% specificity for each set, respectively. The compounds correctly classified 94.9% of resistant and 93.7% of sensitive females. The identified metabolites can be considered together with clinical data, allowing for the development of precision medicine strategies that lead to better treatment choices. Background: Neoadjuvant chemotherapy (NACT) has arisen as a treatment option for breast cancer (BC). However, the response to NACT is still unpredictable and dependent on cancer subtype. Metabolomics is a tool for predicting biomarkers and chemotherapy response. We used plasma to verify metabolomic alterations in BC before NACT, relating to clinical data. Methods: Liquid chromatography coupled to mass spectrometry (LC-MS) was performed on pre-NACT plasma from patients with BC (n = 75). After data filtering, an SVM model for classification was built and validated with 75%/25% of the data, respectively. Results: The model composed of 19 identified metabolites effectively predicted NACT response for training/validation sets with high sensitivity (95.4%/93.3%), specificity (91.6%/100.0%), and accuracy (94.6%/94.7%). In both sets, the panel correctly classified 95% of resistant and 94% of sensitive females. Most compounds identified by the model were lipids and amino acids and revealed pathway alterations related to chemoresistance. Conclusion: We developed a model for predicting patient response to NACT. These metabolite panels allow clinical gain by building precision medicine strategies based on tumor stratification. [ABSTRACT FROM AUTHOR]

Cancer is increasingly acknowledged as a metabolic disease, characterized by metabolic reprogramming as its hallmark. However, the precise mechanisms behind this phenomenon and the factors contributing to tumorigenicity are still poorly understood. In a recent publication in Cell, Mossmann and colleague reported a study unveiling arginine as a molecule with second messenger‐like properties that reshapes metabolism to facilitate the tumor development in hepatocellular carcinoma (HCC). Their research revealed that the RNA‐binding motif protein 39 (RBM39)‐mediated increase in asparagine synthesis results in increased arginine uptake. This establishes a positive feedback loop that sustains elevated levels of arginine and facilitates oncogenic metabolic reprogramming. Additionally, Mossmann et al. demonstrated that depleting RBM39 with indisulam effectively disrupts the proto‐oncogenic metabolic reprogramming in HCC. This discovery presents a novel treatment strategy for arginine‐dependent liver cancers. [ABSTRACT FROM AUTHOR]

Biomarkers, including proteins, nucleic acids, antibodies, and peptides, are essential for identifying diseases such as cancer and differentiating between healthy and abnormal cells in patients. To date, studies have shown that cancer stem cells have DNA repair mechanisms that deter the effects of medicinal treatment. Experiments with cell cultures and chemotherapy treatments of these cultures have revealed the presence of small cells, with a small amount of cytoplasm that can be intensively stained with azure eosin, called microcells. Microcells develop during sporosis from a damaged tumor macrocell. After anticancer therapy in tumor cells, a defective macrocell may produce one or more microcells. This study aims to characterize microcell morphology in melanoma cell lines. In this investigation, we characterized the population of cancer cell microcells after applying paclitaxel treatment to a Sk-Mel-28 melanoma cell line using immunocytochemical cell marker detection and fluorescent microscopy. Paclitaxel-treated cancer cells show stronger expression of stem-associated ALDH2, SOX2, and Nanog markers than untreated cells. The proliferation of nuclear antigens in cells and the synthesis of RNA in microcells indicate cell self-defense, promoting resistance to applied therapy. These findings improve our understanding of microcell behavior in melanoma, potentially informing future strategies to counteract drug resistance in cancer treatment. [ABSTRACT FROM AUTHOR]

Metabolomics generates complex data necessitating advanced computational methods for generating biological insight. While machine learning (ML) is promising, the challenges of selecting the best algorithms and tuning hyperparameters, particularly for nonexperts, remain. Automated machine learning (AutoML) can streamline this process; however, the issue of interpretability could persist. This research introduces a unified pipeline that combines AutoML with explainable AI (XAI) techniques to optimize metabolomics analysis. We tested our approach on two data sets: renal cell carcinoma (RCC) urine metabolomics and ovarian cancer (OC) serum metabolomics. AutoML, using Auto-sklearn, surpassed standalone ML algorithms like SVM and k-Nearest Neighbors in differentiating between RCC and healthy controls, as well as OC patients and those with other gynecological cancers. The effectiveness of Auto-sklearn is highlighted by its AUC scores of 0.97 for RCC and 0.85 for OC, obtained from the unseen test sets. Importantly, on most of the metrics considered, Auto-sklearn demonstrated a better classification performance, leveraging a mix of algorithms and ensemble techniques. Shapley Additive Explanations (SHAP) provided a global ranking of feature importance, identifying dibutylamine and ganglioside GM-(d34:1) as the top discriminative metabolites for RCC and OC, respectively. Waterfall plots offered local explanations by illustrating the influence of each metabolite on individual predictions. Dependence plots spotlighted metabolite interactions, such as the connection between hippuric acid and one of its derivatives in RCC, and between GM3-(d34:1) and GM3(18:1_16:0) in OC, hinting at potential mechanistic relationships. Through decision plots, a detailed error analysis was conducted, contrasting feature importance for correctly versus incorrectly classified samples. In essence, our pipeline emphasizes the importance of harmonizing AutoML and XAI, facilitating both simplified ML application and improved interpretability in metabolomics data science. [ABSTRACT FROM AUTHOR]

Pain is one of the most common symptoms in patients with cancer. Pain not only negatively affects the quality of life of patients with cancer, but it has also been associated with reduced survival. Pain management is therefore a critical component of cancer care. Prescription opioids remain the first-line approach for the management of moderate-to-severe pain associated with cancer. However, there has been increasing interest in understanding whether these analgesics could impact cancer progression. Furthermore, epidemiological data link a possible association between prescription opioid usage and cancer development. Until more robust evidence is available, patients with cancer with moderate-to-severe pain may receive opioids to decrease suffering. However, future studies should be conducted to evaluate the role of opioids and opioid receptors in specific cancers. [ABSTRACT FROM AUTHOR]

Simple Summary: Brain cancers, which can start in the brain or spread there from other parts of the body, are difficult to treat and often lead to severe health issues and death. Radiotherapy (RT) is a main treatment that helps control symptoms and can sometimes cure the disease, but many brain cancers resist it, especially those that start in the brain. Combining immunotherapy with RT has shown promise for treating cancers that spread to the brain, but has limited success with gliomas, the most common primary brain cancer. This review looks at why brain tumors resist RT, new strategies to overcome this, and the role of the tumor's environment. We highlight key findings from recent research and identify new treatment opportunities to improve outcomes and survival rates for brain cancer patients. Malignant central nervous system (CNS) cancers include a group of heterogeneous dis-eases characterized by a relative resistance to treatments and distinguished as either primary tumors arising in the CNS or secondary tumors that spread from other organs into the brain. Despite therapeutic efforts, they often cause significant mortality and morbidity across all ages. Radiotherapy (RT) remains the main treatment for brain cancers, improving associated symptoms, improving tumor control, and inducing a cure in some. However, the ultimate goal of cancer treatment, to improve a patient's survival, remains elusive for many CNS cancers, especially primary tumors. Over the years, there have thus been many preclinical studies and clinical trials designed to identify and overcome mechanisms of resistance to improve outcomes after RT and other therapies. For example, immunotherapy delivered concurrent with RT, especially hypo-fractionated stereotactic RT, is synergistic and has revolutionized the clinical management and outcome of some brain tumors, in particular brain metastases (secondary brain tumors). However, its impact on gliomas, the most common primary malignant CNS tumors, remains limited. In this review, we provide an overview of radioresistance mechanisms, the emerging strategies to overcome radioresistance, the role of the tumor microenviroment (TME), and the selection of the most significant results of radiation–immuno–oncological investigations. We also identify novel therapeutic opportunities in primary and secondary brain tumors with the purpose of elucidating current knowledge and stimulating further research to improve tumor control and patients' survival. [ABSTRACT FROM AUTHOR]

Several chronic inflammatory diseases have been linked to high-salt (HS) diets. Chronic inflammation is an established causative hallmark of cancer. However, a direct role of HS diets in tumorigenesis is yet to be defined. Previous orthotopic murine breast tumor studies have shown that short-term HS diets caused inhibition of tumor growth through the activation of cytotoxic adaptive immune responses. However, there have been experimental challenges in developing a viable chronic HS-diet-based murine tumor model. To address this, we have developed a novel chronic HS diet tumor model through the sequential passaging of tumor cells in mice under HS dietary conditions. Two orthotopic murine triple-negative breast cancer models, 4T1 tumor cells injected into BALB/c mice and Py230 tumor cells injected into C57Bl/6 mice, were utilized in our study. For the HS diet cohort, prior to orthotopic injection with tumor cells, the mice were kept on a 4% NaCl diet for 2 weeks. For the regular salt (RS) diet cohort, the mice were kept on a 1% NaCl diet. Following syngeneic cancer cell injection, tumors were allowed to grow for 28 days, following which they were collected to isolate immune cell-depleted cancer cells (passage 1, P1). The tumor cells from P1 were reinjected into the next set of non-tumor-bearing mice. This procedure was repeated for three cycles (P2–P4). In P1, compared to the RS diet cohort, we observed reduced tumor kinetics in both murine tumor models on the HS diet. In contrast, by P4, there was significantly higher tumor progression in the HS diet cohort over the RS diet cohort. Flow cytometry analysis demonstrated an 8-fold increase in tumor-initiating stem cells (TISCs) from P1 to P4 of the HS diet cohort, while there were no significant change in TISC frequency with sequential passaging in the RS diet cohort. Molecular studies showed enhanced expression of TGFβR2 and CD80 on TISCs isolated from the P4 HS diet cohort. In vitro studies demonstrated that TGFβ stimulation of these TISCs increased the cellular expression of CD80 molecules. Further, the chronic HS diet selectively induced the glycolytic metabolic phenotype over the mitochondrial oxidative phosphorylation phenotype in TISCs, which is needed for the production of metabolites during tumor cell differentiation and proliferation. The infiltrating CD8 and CD4 T-lymphocytes in P4 tumors demonstrated increased expression of the immune checkpoint inhibitor (ICI) CTLA4, a known binding partner of CD80, to cause immune exhaustion and pro-tumorigenic effects. Interestingly, anti-TGFβ monoclonal antibodies (mAbs) played a synergistic role in further enhancing the anti-tumor effect of anti-CTLA4 mAb. In summary, our findings demonstrated that chronic HS diet increased the frequency of TISCs in tumors leading to blunting of cytotoxic adaptive immune responses causing tumor proliferation. Furthermore, a combination of anti-TGFβ with current ICI-based immunotherapies could exert more favorable anti-cancer clinical outcomes. [ABSTRACT FROM AUTHOR]

Ferroptosis is a newly identified iron‐dependent type of regulated cell death that can also be regarded as death caused by the specific collapse of the lipid antioxidant defence machinery. Ferroptosis has gained increasing attention as a potential therapeutic strategy for therapy‐resistant cancer types. However, many ferroptosis‐inducing small molecules do not reach the pharmacokinetic requirements for their effective clinical use yet. Nevertheless, their clinical optimization is under development. In this review, we summarize the current understanding of molecular pathways regulating ferroptosis, how cells protect themselves from the induction of ferroptotic cell death, and how a better understanding of cancer cell metabolism can represent vulnerabilities for ferroptosis‐based therapies. Lastly, we discuss the context‐dependent effect of ferroptosis on various cell types within the tumor microenvironment and address controversies on how tissue ferroptosis might impact systemic cancer immunity in a paracrine manner. [ABSTRACT FROM AUTHOR]

The prognosis and survival rate of head and neck squamous cell carcinoma (HNSCC) have remained unchanged for years, and the pathogenesis of HNSCC is still not fully understood, necessitating further research. An ideal animal model that accurately replicates the complex microenvironment of HNSCC is urgently needed. Among all the animal models for preclinical cancer research, tumor-bearing mouse models are the best known and widely used due to their high similarity to humans. Currently, mouse models for HNSCC can be broadly categorized into chemical-induced models, genetically engineered mouse models (GEMMs), and transplanted mouse models, each with its distinct advantages and limitations. In chemical-induced models, the carcinogen spontaneously initiates tumor formation through a multistep process. The resemblance of this model to human carcinogenesis renders it an ideal preclinical platform for studying HNSCC initiation and progression from precancerous lesions. The major drawback is that these models are time-consuming and, like human cancer, unpredictable in terms of timing, location, and number of lesions. GEMMs involve transgenic and knockout mice with gene modifications, leading to malignant transformation within a tumor microenvironment that recapitulates tumorigenesis in vivo, including their interaction with the immune system. However, most HNSCC GEMMs exhibit low tumor incidence and limited prognostic significance when translated to clinical studies. Transplanted mouse models are the most widely used in cancer research due to their consistency, availability, and efficiency. Based on the donor and recipient species matching, transplanted mouse models can be divided into xenografts and syngeneic models. In the latter, transplanted cells and host are from the same strain, making syngeneic models relevant to study functional immune system. In this review, we provide a comprehensive summary of the characteristics, establishment methods, and potential applications of these different HNSCC mouse models, aiming to assist researchers in choosing suitable animal models for their research. [ABSTRACT FROM AUTHOR]

A high level of homocysteine (Hcy) is associated with oxidative/ER stress, apoptosis, and impairment of angiogenesis, whereas hydrogen sulfide (H2S) has been found to reverse this condition. Recent studies have shown that cancer cells need to produce a high level of endogenous H2S to maintain cell proliferation, growth, viability, and migration. However, any novel mechanism that targets this balance of Hcy and H2S production has yet to be discovered or exploited. Cells require homocysteine metabolism via the methionine cycle for nucleotide synthesis, methylation, and reductive metabolism, and this pathway supports the high proliferative rate of cancer cells. Although the methionine cycle favors cancer cells for their survival and growth, this metabolism produces a massive amount of toxic Hcy that somehow cancer cells handle very well. Recently, research showed specific pathways important for balancing the antioxidative defense through H2S production in cancer cells. This review discusses the relationship between Hcy metabolism and the antiapoptotic, antioxidative, anti-inflammatory, and angiogenic effects of H2S in different cancer types. It also summarizes the historical understanding of targeting antioxidative defense systems, angiogenesis, and other protective mechanisms of cancer cells and the role of H2S production in the genesis, progression, and metastasis of cancer. This review defines a nexus of diet and precision medicine in targeting the delicate antioxidative system of cancer and explores possible future therapeutics that could exploit the Hcy and H2S balance.

Abstract Background The child cancer, neuroblastoma (NB), is characterised by a low incidence of mutations and strong oncogenic embryonal driver signals. Many new targeted epigenetic modifier drugs have failed in human trials as monotherapy. Methods We performed a high‐throughput, combination chromatin‐modifier drug screen against NB cells. We screened 13 drug candidates in 78 unique combinations. Results We found that the combination of two histone methyltransferase (HMT) inhibitors: GSK343, targeting EZH2, and SGC0946, targeting DOT1L, demonstrated the strongest synergy across 8 NB cell lines, with low normal fibroblast toxicity. High mRNA expression of both EZH2 and DOT1L in NB tumour samples correlated with the poorest patient survival. Combination HMT inhibitor treatment caused activation of ATF4‐mediated endoplasmic reticulum (ER) stress responses. In addition, glutathione and several amino acids were depleted by HMT inhibitor combination on mass spectrometry analysis. The combination of SGC0946 and GSK343 reduced tumour growth in comparison to single agents. Conclusion Our results support further investigation of HMT inhibitor combinations as a therapeutic approach in NB.

STK11 (serine-threonine kinase 11), also known as LKB1 (liver kinase B1) is a highly conserved master kinase that regulates cellular metabolism and polarity through a complex signaling network involving AMPK and 12 other AMPK-related kinases. Germline mutations in LKB1 have been causatively linked to Peutz-Jeghers Syndrome (PJS), an autosomal dominant hereditary disease with high cancer susceptibility. The identification of inactivating somatic mutations in LKB1 in different types of cancer further supports its tumor suppressive role. Deleterious mutations in LKB1 are frequently observed in patients with epithelial ovarian cancer. However, its inconsistent effects on tumorigenesis and cancer progression suggest that its functional impact is genetic context-dependent, requiring cooperation with other oncogenic lesions. In this review, we summarize the pleiotropic functions of LKB1 and how its altered activity in cancer cells is linked to oncogenic proliferation and growth, metastasis, metabolic reprogramming, genomic instability, and immune modulation. We also review the current mechanistic understandings of this master kinase as well as therapeutic implications with particular focus on the effects of LKB1 deficiency in ovarian cancer pathogenesis. Lastly, we discuss whether LKB1 deficiency can be exploited as an Achilles heel in ovarian cancer.

Abstract Patient‐derived xenografts (PDX) involve transplanting patient cells or tissues into immunodeficient mice, offering superior disease models compared with cell line xenografts and genetically engineered mice. In contrast to traditional cell‐line xenografts and genetically engineered mice, PDX models harbor the molecular and biologic features from the original patient tumor and are generationally stable. This high fidelity makes PDX models particularly suitable for preclinical and coclinical drug testing, therefore better predicting therapeutic efficacy. Although PDX models are becoming more useful, the several factors influencing their reliability and predictive power are not well understood. Several existing studies have looked into the possibility that PDX models could be important in enhancing our knowledge with regard to tumor genetics, biomarker discovery, and personalized medicine; however, a number of problems still need to be addressed, such as the high cost and time‐consuming processes involved, together with the variability in tumor take rates. This review addresses these gaps by detailing the methodologies to generate PDX models, their application in cancer research, and their advantages over other models. Further, it elaborates on how artificial intelligence and machine learning were incorporated into PDX studies to fast‐track therapeutic evaluation. This review is an overview of the progress that has been done so far in using PDX models for cancer research and shows their potential to be further improved in improving our understanding of oncogenesis.

Multi-omics data integration is a term that refers to the process of combining and analyzing data from different omic experimental sources, such as genomics, transcriptomics, methylation assays, and microRNA sequencing, among others. Such data integration approaches have the potential to provide a more comprehensive functional understanding of biological systems and has numerous applications in areas such as disease diagnosis, prognosis and therapy. However, quantitative integration of multi-omic data is a complex task that requires the use of highly specialized methods and approaches. Here, we discuss a number of data integration methods that have been developed with multi-omics data in view, including statistical methods, machine learning approaches, and network-based approaches. We also discuss the challenges and limitations of such methods and provide examples of their applications in the literature. Overall, this review aims to provide an overview of the current state of the field and highlight potential directions for future research.

The editorial discusses the importance of understanding the mesenchymal to epithelial transition (MET) in the context of epithelial-mesenchymal plasticity (EMP), particularly in cancer biology. Recent studies have highlighted the regulatory mechanisms of MET at the transcriptional level, emphasizing its significance in tumor biology and tissue homeostasis. The research explores various aspects of EMP, including the role of non-coding RNAs, gene expressions in lower-grade gliomas, interactions with the extracellular matrix, and cancer spreading patterns, to develop targeted interventions for cancer metastasis. The study underscores the complexity of EMP in tumor biology and the need for personalized treatment approaches, emphasizing the importance of understanding these transitions for innovative therapeutic strategies against cancer. [Extracted from the article]

Chronic myeloid leukemia (CML) is a blood cancer characterized by dysregulated production of maturing myeloid cells driven by the product of the Philadelphia chromosome, the BCR-ABL1 tyrosine kinase. Tyrosine kinase inhibitors (TKIs) have proved effective in treating CML, but there is still a cohort of patients who do not respond to TKI therapy even in the absence of mutations in the BCR-ABL1 kinase domain that mediate drug resistance. To discover novel strategies to improve TKI therapy in CML, we developed a nonlinear mathematical model of CML hematopoiesis that incorporates feedback control and lineage branching. Cell-cell interactions were constrained using an automated model selection method together with previous observations and new in vivo data from a chimeric BCR-ABL1 transgenic mouse model of CML. The resulting quantitative model captures the dynamics of normal and CML cells at various stages of the disease and exhibits variable responses to TKI treatment, consistent with those of CML patients. The model predicts that an increase in the proportion of CML stem cells in the bone marrow would decrease the tendency of the disease to respond to TKI therapy, in concordance with clinical data and confirmed experimentally in mice. The model further suggests that, under our assumed similarities between normal and leukemic cells, a key predictor of refractory response to TKI treatment is an increased maximum probability of self-renewal of normal hematopoietic stem cells. We use these insights to develop a clinical prognostic criterion to predict the efficacy of TKI treatment and design strategies to improve treatment response. The model predicts that stimulating the differentiation of leukemic stem cells while applying TKI therapy can significantly improve treatment outcomes.

A small percentage of bladder cancers in the general population have been found to harbor DNA viruses. In contrast, up to 25% of tumors of solid organ transplant recipients, who are at an increased risk of developing bladder cancer and have an overall poorer outcomes, harbor BK polyomavirus (BKPyV). To better understand the biology of the tumors and the mechanisms of carcinogenesis from potential oncoviruses, we performed whole genome and transcriptome sequencing on bladder cancer specimens from 43 transplant patients. Nearly half of the tumors from this patient population contained viral sequences. The most common were from BKPyV (N=9, 21%), JC polyomavirus (N=7, 16%), carcinogenic human papillomaviruses (N=3, 7%), and torque teno viruses (N=5, 12%). Immunohistochemistry revealed variable Large T antigen expression in BKPyV-positive tumors ranging from 100% positive staining of tumor tissue to less than 1%. In most cases of BKPyV-positive tumors, the viral genome appeared to be clonally integrated into the host chromosome consistent with microhomology-mediated end joining and coincided with focal amplifications of the tumor genome similar to other virus-mediated cancers. Significant changes in host gene expression consistent with the functions of BKPyV Large T antigen were also observed in these tumors. Lastly, we identified four mutation signatures in our cases, with those attributable to APOBEC3 and SBS5 being the most abundant. Mutation signatures associated with an antiviral drug, ganciclovir, and aristolochic acid, a nephrotoxic compound found in some herbal medicines, were also observed. The results suggest multiple pathways to carcinogenesis in solid organ transplant recipients with a large fraction being virus-associated.

Pain is one of the most common symptoms in patients with cancer. Pain not only negatively affects the quality of life of patients with cancer, but it has also been associated with reduced survival. Pain management is therefore a critical component of cancer care. Prescription opioids remain the first-line approach for the management of moderate-to-severe pain associated with cancer. However, there has been increasing interest in understanding whether these analgesics could impact cancer progression. Furthermore, epidemiological data link a possible association between prescription opioid usage and cancer development. Until more robust evidence is available, patients with cancer with moderate-to-severe pain may receive opioids to decrease suffering. However, future studies should be conducted to evaluate the role of opioids and opioid receptors in specific cancers.

The use of a novel and powerful technology that allows for the precise editing of the genetic material of various organisms is becoming widespread. This technology derives from bacterial and archaeal defense machinery and is called CRISPR Cas9. Unlike other gene editing tools that exclusively rely on proteins, CRISPR Cas9 utilizes interactions between the target DNA and an RNA sequence that guides the Cas9 enzyme to alter the structure of a target gene. Various genome locations can be edited thanks to the ease of programming different guide RNA sequences, facilitating its use and implementation. Furthermore, the non-active version of the Cas9 protein, guided by its corresponding RNA, can be utilized for visualization processes of genetic material or, more recently, for the regulation of the transcription process. Considering the recent advances and possibilities in biomedical and biotechnological research, we must understand that the exploration of this technology is just beginning, and its eventual applications will influence the world around us on multiple levels. In this review, we describe the biological foundations of the functioning of the Cas9 nuclease, together with selected applications of its use in editing and regulating specific sections of the genetic material of various organisms. We also discuss some bioethical issues surrounding this subject.

Genetic alterations that activate protein kinase A (PKA) are found in many tumor types. Yet, their downstream oncogenic signaling mechanisms are poorly understood. We used global phosphoproteomics and kinase activity profiling to map conserved signaling outputs driven by a range of genetic changes that activate PKA in human cancer. Two signaling networks were identified downstream of PKA: RAS/MAPK components and an Aurora Kinase A (AURKA)/glycogen synthase kinase (GSK3) sub-network with activity toward MYC oncoproteins. Findings were validated in two PKA-dependent cancer models: a novel, patient-derived fibrolamellar carcinoma (FLC) line that expresses a DNAJ-PKAc fusion and a PKA-addicted melanoma model with a mutant type I PKA regulatory subunit. We identify PKA signals that can influence both de novo translation and stability of the proto-oncogene c-MYC. However, the primary mechanism of PKA effects on MYC in our cell models was translation and could be blocked with the eIF4A inhibitor zotatifin. This compound dramatically reduced c-MYC expression and inhibited FLC cell line growth in vitro. Thus, targeting PKA effects on translation is a potential treatment strategy for FLC and other PKA-driven cancers.